THE AUTOMATIC ACTIVATION AND

IMPLICIT MEASUREMENT OF

SELF-DETERMINED MOTIVATION

FOR EXERCISE.

LAUREN K BANTING

B.SC (HONS). THE UNIVERSITY OF WESTERN AUSTRALIA

This thesis is presented for the degree of

Doctor of Philosophy at

The University of Western Australia

School of Sport Science, Exercise and Health

2012

i

ACKNOWLEDGEMENTS

I would like to thank my supervisor Dr James Dimmock for taking such an

interest in my research and my progress as a research student. I find his

enthusiasm for his work in exercise science an inspiration and his work ethic never

ceases to amaze me. Despite me moving across the country and taking longer than

expected to complete, he was helpful and supportive the whole time. My most

sincere thanks. I could not have done this without you.

I would also like to thank Professor Bob Grove for his insightful comments

and support throughout my candidature, I really appreciate the time spent

reviewing chapters and discussing the project. Also, I would also like to thank Dr

Ben Jackson for his support. Whilst not an official supervisor, Ben provided infinite

amounts of moral support and understanding.

I share this thesis with a great group of PhD students, Julie Hardt, Marcus

Lee, Emilie Thienot, James Dunne and Jay-Lee Longbottom. I loved our productive

(and not-so productive) chats in the office and wish you all every success. And to

Jon Donnelly, thank you to a true friend and support to me over my candidature.

Finally to my friends and family. Thank you for understanding when I

decided to go back to university, and then supporting me as I remained a student.

Karlee, Alisha, Bek and Carla, I truly value your friendship and look forward to

being a ‘real adult’ now with you all. Mum, Dad and Chris, your support to me

during my PhD has been unrelenting and you all continually inspire me to keep

learning and do my best. And as a late mention, to Matthew. Your patience and love

has been so special to me and I look forward to one Varley & Banting paper (one

will do) and many more memories together.

ii

ABSTRACT

The first study in this thesis examined the extent to which exercise

outcomes are influenced by automatic activation of controlled and autonomous

motivational orientations. Results indicated that motivational orientations can be

activated without consciousness and that such activation can have implications for

their exercise. More specifically, priming for autonomous motivation, as opposed

to controlled motivation, increased the amount of time individuals chose to

exercise, increased participants’ physiological exertion, decreased their amount of

perceived exertion, and improved their affective responses to exercise. In Study 2,

two implicit measurement tools were developed to assess implicit exercise

motivation as described in self-determination theory. The Go/ No-Go Association

Task and the Lexical Decision Task were used to evaluate participants’ automatic

tendency to associate stimuli that represent the behavioural regulation styles with

exercise. The scores derived from each test were compared to traditional self-

reported motivation scores. Implicit motivation scores were also examined for

their relationship with duration of exercise and perceptions of exercise. Results

from this investigation indicated that the lexical decision task was a better

predictor of the dependent variables than the Go/No-Go task, with lexical decision

scores correlating with time exercised, self-reported exercise enjoyment, and

intention to exercise. Another benefit of the lexical decision task was that it

produced scores relating to individual types of motivation on the self-

determination continuum.

After refining the implicit measurement tool we assessed the role of the

strength of autonomous motivation and controlled motivation when engaging

participants in a priming experiment. Participants we required to cycle at a self-

iii selected intensity and given a choice to stop midway through the protocol. Priming

group predicted heart rate, exercise duration and rating of perceived exertion.

Implicit motivation predicted intention to exercise, exercise duration and average

heart rate. No significant interactions were observed between priming group and

implicit motivation.

iv

PRESENTATIONS AND PUBLICATIONS BASED ON THIS RESEARCH

Banting, L.K., Dimmock, J.A., & Grove, J.R. (2011). The impact of automatically

activated motivation on exercise-based outcomes. Journal of Sport and Exercise

Psychology, 33, 569-585.

Banting, L.K., Dimmock, J.A., & Grove, J.R. (June, 2011). Predicting intentions and

behaviours from an implicit measure of motivation. Poster session presented at

the 2011 Annual Meeting of the International Society for Behavioral Nutrition and

Physical Activity, Melbourne, Australia.

Banting, L.K., Dimmock, J.A., & Grove, J.R. (May, 2010). Development of an implicit

exercise motivation measure. Poster session presented at the Fourth International

Conference on Self-determination Theory, Ghent, Belgium.

Dimmock, J.A., & Banting, L.K. (May, 2010). The impact of non-consciously

activated motivation on exercise. Paper session presented at the Fourth

International Conference on Self-determination Theory, Ghent, Belgium.

Dimmock, J.A., & Banting, L.K. (2009). The influence of implicit cognitive processes

on physical activity: how the theory of planned behaviour and self-determination

theory can provide a platform for our understanding. International Review of Sport

and Exercise Psychology, 2(1), 3 – 22.

v

PRESENTATIONS AND PUBLICATIONS GENERATED DURING TIME OF

CANDIDATURE

Banting, L.K., Dimmock, J.A., & Lay, B.S. (2009). The role of implicit and explicit

components of exerciser self-schema in the prediction of exercise behaviour.

Psychology of Sport and Exercise, 10(1), 80-86.

Banting, L.K., & Jackson, B.S. (October, 2009). Predicting effort, enjoyment and

performance in a tertiary practical class using aspects of self-determination theory.

Paper session presented at the 2010 Teaching and Learning Forum Perth,

Australia.

Banting, L.K., Dimmock J.A., Lay, B.S., & Braham, R. (June, 2009). Considering the

role of implicit and explicit self-schema in the theory of planned behaviour. Paper

session presented at the 12th World Congress of Sport Psychology, Marrakech,

Morocco.

Banting, L.K., Dimmock, J.A. (June, 2009). Ways to promote exercise adherence

amongst fitness centre patrons using adaptations of motivational interviewing:

Suggestions for future research. Poster session presented at the 12th World

Congress of Sport Psychology, Marrakech, Morocco.

6

CONTENTS

Acknowledgements .............................................................................................................................. i

Abstract .................................................................................................................................................... ii

Presentations and Publications Based on this Research ..................................................... iv

Presentations and Publications Generated During Time of Candidature ...................... v

List of Figures ..................................................................................................................................... 12

List of Tables ....................................................................................................................................... 13

Chapter 1: Thesis Overview .......................................................................................................... 15

Chapter summary .......................................................................................................................... 15

Introduction .................................................................................................................................... 16

Self-determination theory ..................................................................................................... 16

Statement of the Problem .......................................................................................................... 20

Purpose and Overview of Research ....................................................................................... 21

Significance of Research ............................................................................................................. 21

Definition of Terms ....................................................................................................................... 22

Chapter References ...................................................................................................................... 25

Chapter 2: Literature Review ....................................................................................................... 28

Chapter Summary ......................................................................................................................... 28

Introduction .................................................................................................................................... 29

Barriers to Physical Activity ..................................................................................................... 30

7

Exercise Adherence ...................................................................................................................... 32

Theories of Health Behaviour ................................................................................................... 32

Self-Determination Theory ........................................................................................................ 36

Motivation research .................................................................................................................. 36

Cognitive evaluation theory .................................................................................................. 38

Basic needs theory .................................................................................................................... 39

Organismic integration theory ............................................................................................. 41

Causality orientations theory ............................................................................................... 44

Goal contents theory ................................................................................................................ 46

Self-determination theory and physical activity ........................................................... 47

Cognition ........................................................................................................................................... 49

Implicit constructs and automaticity ................................................................................. 52

Implicit processes and behaviour ....................................................................................... 54

Priming social constructs ....................................................................................................... 55

Implicit motivation ................................................................................................................... 58

Implicit measures of motivation .......................................................................................... 63

Implicit motivation and physical activity ............................................................................. 67

Questions arising from the literature .................................................................................... 69

Chapter References ....................................................................................................................... 71

Chapter 3: The Impact of Automatically Activated Motivation on Exercise-Related

Outcomes. ............................................................................................................................................. 85

Chapter Summary .......................................................................................................................... 85

8

Introduction .................................................................................................................................... 86

Methods ............................................................................................................................................ 92

Participants ................................................................................................................................. 92

Overview of procedures ......................................................................................................... 92

Materials and measures .......................................................................................................... 93

Word Scramble Sentence Task. ........................................................................................... 93

Questionnaire measures. ........................................................................................................ 93

Heart Rate .................................................................................................................................... 95

Test of Awareness ..................................................................................................................... 96

Procedures ................................................................................................................................... 96

Results ............................................................................................................................................... 98

Test of awareness...................................................................................................................... 98

Priming effects on primary dependent variables ......................................................... 99

Heart rate analysis .................................................................................................................. 101

Discussion ...................................................................................................................................... 104

Chapter References .................................................................................................................... 110

Chapter 4: The measurement and outcomes of implicit self-determination in

exercise. .............................................................................................................................................. 115

Chapter Summary ....................................................................................................................... 115

Introduction .................................................................................................................................. 116

Implicit measures .................................................................................................................... 119

Research Aims .......................................................................................................................... 120

9

Methods .......................................................................................................................................... 121

Participants ............................................................................................................................... 121

Materials and Measures ....................................................................................................... 121

Procedures ................................................................................................................................ 127

Data analysis ............................................................................................................................. 128

Results ............................................................................................................................................. 129

Preliminary analyses ............................................................................................................. 129

Explicit behavioural regulation ......................................................................................... 130

Comparing implicit measures ............................................................................................ 132

Predictive capability of GNAT ............................................................................................ 133

Predictive capacity of LDT .................................................................................................. 136

Discussion ...................................................................................................................................... 140

Conclusions ............................................................................................................................... 145

Chapter References .................................................................................................................... 146

Chapter 5: Do Motivation Priming Effects Vary as a Function of Implicit

Motivational Orientation? ........................................................................................................... 150

Chapter Summary ....................................................................................................................... 150

Introduction .................................................................................................................................. 151

Chronic accessibility and Implicit Motivation: Similarities and Methodologies

........................................................................................................................................................ 154

Method ............................................................................................................................................ 157

Participants ............................................................................................................................... 157

10

Materials and Measures ........................................................................................................ 157

Procedures ................................................................................................................................. 162

Data Analysis ............................................................................................................................. 164

Results ............................................................................................................................................. 166

Test of awareness.................................................................................................................... 166

Effects of primed motivation .............................................................................................. 166

Effects of Implicit motivation ............................................................................................. 168

Priming and Implicit Motivation Interaction ............................................................... 169

Discussion ...................................................................................................................................... 170

Chapter references ..................................................................................................................... 176

Chapter 6: General Discussion and Summary ...................................................................... 181

Chapter Summary ....................................................................................................................... 181

Introduction .................................................................................................................................. 182

Summary of priming .................................................................................................................. 185

Summary of Implicit Motivation ........................................................................................... 185

Dual process models .................................................................................................................. 186

Conclusion ...................................................................................................................................... 188

Chapter References .................................................................................................................... 190

Appendices ........................................................................................................................................ 193

Appendix A: Chapter 3 Publication ...................................................................................... 193

Appendix B: Word Scrambled Sentence Tasks ................................................................ 211

Neutral Priming Task ............................................................................................................. 212

11

Autonomous Priming Task ................................................................................................. 213

Controlled Priming Task ...................................................................................................... 214

Appendix C: Questionnaire Measures ................................................................................. 215

Behavioural Regulation in Exercise Questionnaire: Revised Version ................ 216

Intrinsic motivation Inventory Items ............................................................................. 217

Profile of Mood States (POMS) .......................................................................................... 218

Intention Questions ............................................................................................................... 219

Test of Awareness .................................................................................................................. 220

12

LIST OF FIGURES

Figure 1.1 Self-determination theory ........................................................21

Figure 2.1 Main barriers to physical activity in

Australia

........................................................33

Figure 2.2 Theory of Planned Behaviour ........................................................37

Figure 3.1 .Average Percentage of Maximum Heart

Rate Over Time

......................................................102

13

LIST OF TABLES

Table 3.1 Characteristics of Priming Group

Participants

......................................................101

Table 3.2 Mean Scores and Standard Deviations for

Dependent Variables in Priming Group

Participants

......................................................103

Table 3.3 ANCOVA Results for Dependent

Variables Using Sex, Age and RAI Scores

as Covariates with Prime Group as the

Fixed Factor

......................................................104

Table 4.1 Stimuli used for the GNAT categories ......................................................125

Table 4.2 Stimuli used for the LDT categories ......................................................126

Table 4.3 Descriptive statistics and Pearson’s

correlation values for dependent

variables

......................................................131

Table 4.4 Correlation values of regulation types

as measured in the BREQ-2 with

implicit measures and outcome

variables

......................................................132

Table 4.5 Pearson’s correlation values for Lexical

Decision Task regulation types

......................................................133

Table 4.6 Hierarchical Regression Analyses for

Dependent Variables when GNAT Score

and Explicit RAI are used as the

Predictor Variables

......................................................135

Table 4.7 Hierarchical Regression Analyses for

Dependent Variables when LDT score

and Explicit RAI are used as the

Predictor Variables

......................................................139

Table 5.1 Participant characteristics according to

priming group

......................................................157

14 Table 5.2 Lexical decision task stimuli ......................................................161

Table 5.3 Implicit RAI scores of the implicit

motivation groups

......................................................165

Table 5.4 Descriptive statistics according to priming

group

......................................................167

Table 5.5 Descriptive statistics according to

motivational orientation

......................................................168

15

CHAPTER 1: THESIS OVERVIEW

CHAPTER SUMMARY

This chapter presents a brief summary of the research to be presented as a

part of this thesis. The rationale for the research conducted in each chapter is

provided based on current psychology and exercise science research. Key terms

are also defined in order to clarify language that will be used throughout the thesis.

The foundational theory of the research conducted in this thesis, self-

determination theory, is also described.

16

INTRODUCTION

Goal-directed behaviour is often considered to be driven by conscious

processes, decided upon and regulated thoughtfully. Even in situations where such

behaviour is repetitive, many individuals would assume that they have consciously

made a decision to act in a certain manner. In recent years, however, evidence has

mounted to indicate that much of our goal-directed behaviour is a function of

automatic cognitive processes. John Bargh, a prominent scholar in this field, argues

that goal selection and pursuit can operate entirely without consciousness (Bargh,

2005). He also suggests that the outcomes of such behaviour can be identical to

goal-directed behaviour that has been consciously regulated (Bargh, 2005;

Chartrand & Bargh, 1996). Most research on Bargh’s auto-motive model (Bargh,

1990) has focused on the activation and pursuit of concrete goals, such as to make

money. Only recent work has investigated whether the abstract motivational

orientations in self-determination theory can be activated without consciousness

and become consequential. Radel, Sarrazin and Pelletier (2009) and Hodgins,

Yacko and Gottlieb (2006), for example, have activated the motivational

orientations detailed in self-determination theory through priming. Both studies

found greater levels of effort expended and improved performance as a result of

autonomous (versus controlled) motivation priming in a physical activity setting.

Self-determination theory is also the key theory used in the research presented in

this thesis. Self-determination theory provides a basis for understanding the

importance of automatic processes in exercise.

SELF-DETERMINATION THEORY

The self-determination theory (Deci & Ryan, 1985a, 1985b) is comprised of

several sub-theories which address aspects of motivation, personality, and

17 psychological need satisfaction. The theory differs from other motivation theories

in the way that it distinguishes between forms of extrinsic motivation. In

particular, the organismic integration sub-theory of self-determination theory

(Deci & Ryan, 1985b; Ryan & Connell, 1989) identifies four types of behavioural

regulation: External, introjected, identified, and integrated. Identified and

integrated regulations are considered to be autonomous (self-endorsed) and tend

to produce positive outcomes, whereas introjected and external regulation are

considered to be more controlled forms of regulation and are associated with

negative outcomes (Deci & Ryan, 1985b; Ryan & Connell, 1989).

Just as individual behaviours can be driven by autonomous or controlled

motivation, an individual can also display a general tendency to perceive situations

as more autonomous or controlled. The causality orientations theory (Deci & Ryan,

1985a) addresses individual differences in terms of motivation. This sub-theory

suggests that individuals possess certain motivational orientations, with some

individuals more readily feeling autonomously motivated in general, whilst others

are more inclined to perceive circumstances as being controlling.

Self-determination theory also addresses psychological need satisfaction

and how the various forms of motivation can enhance or inhibit the satisfaction of

these needs. The basic needs theory (Ryan & Deci, 2000) stipulates that autonomy,

competence and relatedness are three innate psychological needs necessary for

personal growth and well-being. Figure 1.1 outlines the major components of the

self-determination theory.

Much of the research on exercise that has been based on self-determination

theory has yielded positive results from promoting need satisfaction and more

autonomous forms of behavioural regulation. For example, exercise programs have

18 resulted in greater persistence in tasks, increased feelings of enjoyment, greater

performance, and increased frequency of exercise behaviour as a result of their

focus on basic need satisfaction (Edmunds, Ntoumanis & Duda, 2006, 2008). Most

of these interventions have only assessed behavioural regulation, motivational

orientation, and need satisfaction with measures that require conscious

introspection. In light of research highlighting the importance of implicit measures

for behaviour prediction (e.g., Banting, Dimmock & Lay, 2009; Conroy, Hyde,

Doerksen & Ribeiro, 2010; Dotsch & Wigboldus, 2008), we hypothesise that

measures of implicit motivation may improve our ability to predict and modify

exercise behaviour.

19

Figure 1. Self determination theory. Adapted from Hagger & Chatzisarantis, 2007.

Intrinsic Motivation

Integrated High

Internalisation

Low

Internalisation

Autonomous

Motives

Controlled

Motives

Behaviours that are

incorporated into a

set of behaviours

that satisfy

psychological

needs.

For personally held

values such as

learning skills;

internally

referenced

contingency.

For avoiding

external sources of

disapproval or

gaining externally

referenced

approval.

For external

reinforcement such

as gaining rewards

or avoiding

punishment.

Lack of

intentionality and

personal causation.

Integrated

Regulation

Identified

Regulation

Introjected

Regulation

Exernal Regulation Amotivation

Intrinsic

Motivation Extrinsic

Motivation Amotivation

Basic Psychological Need Satisfaction

Need for Autonomy Need for Competence Need for Relatedness

Degree of

Internalisation

Position on Relative

Autonomy

Continuum

Defining features

& Reward

Contingencies

Perceived Locus

of Causality

Types of

Motivation

For enjoyment,

pleasure & fun. No

discernable

reinforcement or

reward.

20

STATEMENT OF THE PROBLEM

Physical inactivity is undeniably one of the most modifiable risk factors for

a vast array of modern diseases and ailments that plague western society. Whilst

local, national and international health agencies recommend specific amounts of

physical activity, these same health agencies report that actual levels of physical

activity remain low and insufficient for health benefits and maintenance of good

health (Australian Bureau of Statistics [ABS], 2009; World Health Organization

[WHO], 2003). Health promotion campaign evaluations suggest that the message is

getting through and that individuals are aware of the benefits of physical activity

(Huy, Steindorf, Litaker, Thiel & Diehm, 2011; Lee, 1993), but people still seem to

be failing in their efforts to maintain physically active lifestyles. Clearly, further

support is needed to encourage physical activity adoption and adherence.

In Australia, the 2007-2008 National Health Survey by the ABS found that

72% of individuals over 15 years of age were classified as sedentary or engaging in

inadequate amounts of physical activity (ABS; 2009). Moreover, 62% of Australian

adults were determined to be obese or overweight according to the body mass

index (ABS, 2009). These findings are not unique to Australia. The World Health

Organisation (WHO) estimates that over 60% of the global population are not

achieving the recommended targets of daily physical activity (WHO, 2003). These

statistics, and the knowledge that inactivity and obesity can lead to serious and

long-term health problems, provide compelling evidence that physical activity

interventions need to be appropriately designed to improve the health status of

the community.

21

Research is beginning to show that despite good intentions and well made

plans, conscious will may not be sufficient (or even necessary) to engage in some

goal directed behaviours (Dijksterhuis, Chartrand & Aarts, 2007). A thorough

examination of both deliberate and automatic cognitive processes may therefore

prove useful when planning exercise interventions.

PURPOSE AND OVERVIEW OF RESEARCH

This thesis will examine the effect of automatic cognitive processes in

physical activity. The first study will involve a procedure in which the motivational

orientations outlined in causality orientations theory will be primed (Deci & Ryan,

1985a). The effect of these primes on exercise-related behaviour, perceptions, and

affect will be assessed. Based on research highlighting the importance of implicit

cognition for behaviour, the aim of Study 2 will be to develop a measure of implicit

motivation for exercise, once again focusing on motivation outlined in self-

determination theory. Finally, an investigation examining the interaction between

implicit motivational orientations and autonomy/control priming will be

conducted.

SIGNIFICANCE OF RESEARCH

This research will contribute to the literature in several unique ways. Study

1 and 3 build on previous priming literature by administering supraliminal

priming activities designed to activate general motivational orientations. The

behavioural and psychological effects of these primes will be observed as the

prime is being administered (as well as after the administration of the prime),

making Study 1 unique from any other priming study performed. More specifically,

Study 1 will investigate the effect of motivation primes on intensity of exercise

22 (during and after the priming procedure), duration of exercise, and intentions to

exercise in the future. Studies 2 and 3 will involve the development of an

instrument to measure implicit motivation to exercise. By assessing two commonly

employed implicit measurement methodologies, the current research will suggest

and refine an instrument appropriate for use in the measurement of implicit

exercise motivation. A similar tool for exercise motivation, or motivation in

general, has not been designed before. Study 3 will also assess interaction effects

between priming procedures and implicit motivation. The interaction between an

individual’s motivation and the priming technique they are exposed to can

potentially explain discrepancies in priming results and improve the ways in which

we approach priming in the future.

DEFINITION OF TERMS

Autonomous motivation: Motivation derived from intrinsic motivation and

highly internalized extrinsic motivation. Autonomous

motivation indicates volitional, self-endorsed

behaviour (Deci & Ryan, 2000).

Behavioural regulation: The drive or motive for behaviour to occur. According

to the organismic integration sub-theory in self-

determination theory, behavioural regulation is on a

continuum of internalisation or self-determination

(Deci & Ryan, 1985b).

Causality Orientation: An individual’s general tendency towards an

autonomous or controlled motivation; or a general

state of amotivation (Deci & Ryan, 1985a).

23 Controlled motivation: Motivation derived from external and introjected

regulation, where the self is controlled by pressures

and contingencies (Ryan & Deci, 2007).

Exercise: Exercise is a type of physical activity that is planned,

structured, repetitive and initiated with the purpose of

maintaining or improving at least one aspect of fitness

(Caspersen, Powell & Christenson, 1985).

Implicit Cognition: Information processing outside of conscious

awareness’ (Kihlstrom, Barnhardt & Tataryn, 1992)

Implicit Measures: An instrument used to measure the strength and

valence of a nonconscious process or construct existing

for an individual (Nosek, 2007; Nosek & Banaji, 2001).

Internalisation: Incorporating a value or motive into one’s identity.

Although the motive may be essentially externally

referenced, the value has been personally accepted and

integrated into the self (Deci & Ryan, 1985a).

Motivation The drive to act which may be internally or externally

derived (Deci & Ryan, 1985a). Motivation in this thesis

will be examined at a contextual level, specific to a

certain context or “a distinct sphere of human activity”

(i.e., exercise) (Emmons, 1995; Vallerand, 2007).

Physical activity: Any form of movement produced by the skeletal

muscles that requires energy expenditure (Caspersen

et al., 1985).

24 Priming: The automatic activation a psychological construct by

exposing an individual to the prime (stimulus item, such

as a word or picture) that is symbolic of the construct

being primed (Bargh, 1984).

Supraliminal priming: A priming method that presents the primes for a period

of time that can be consciously detected by the

participants. Although the individual may be consciously

aware of the prime, they do not understand the effect

that the primes have on their behaviour (Radel, Sarrazin,

Legrain & Gobancé, 2009).

25

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World Health Organization. (2003). Global Strategy for Diet, Physical Activity and Health. Retrieved from http://www.who.int/dietphysicalactivity/media/en/gsfs_pa.pdf.

28

CHAPTER 2: LITERATURE REVIEW

CHAPTER SUMMARY

This chapter will present the literature that underpins the research

presented in this thesis. Local and global physical inactivity trends will be

discussed first, and the health and economic concerns associated with these trends

will also be highlighted. Then, motivation, which is the cornerstone for

engagement in physical activity, will be extensively reviewed from the perspective

of the self-determination theory. Concepts of implicit and explicit motivation will

be discussed at the end of this section. Finally, literature on the automatic

activation of motivation and the measurement of implicit motivation will be

presented.

29

INTRODUCTION

With a proliferation in devices and conveniences that make our lives

increasingly sedentary, exercise and deliberate physical activity is becoming more

important for our physical and mental health. Although the advantages of an active

lifestyle are widespread, The Australian Bureau of Statistics (ABS, 2006) report

that the prevalence of obese and overweight Australian adults is increasing. In the

last ten years, the proportion of overweight or obese adults has increased from

52% to 62% for men and from 37% to 45% for women (ABS, 2006). These

concerning trends are aligned with statistics indicating that Australians are

reducing their volume of physical activity (ABS, 2006). A recent report produced

by the Australian Sports Commission (Australian Sports Commission, 2011)

indicates that only 47.7% of the Australian public exercise at least three times per

week. Moreover, approximately 31% of the population exercise less than once per

week on average according to the same report. Alarming rates of physical

inactivity are mirrored at a global level, with the World Health Organisation (WHO,

2003) declaring that only 40% of the world’s population are active enough to

attain health benefits.

The health benefits of physical activity have been substantially documented

in a variety of research. Manson et al. (2002), for example, found that physical

activity, both moderate and vigorous, was beneficial to cardiovascular health.

Exercise has also been shown to aid in the prevention of several types for cancer

(for a review see Friedenreich & Orenstein, 2002) and other chronic physiological

conditions, such as type 2 diabetes (Barr et al., 2006) and cardiovascular disease

(Sassen, Cornelissen, Kiers, Wittink, Kok & Vanhees, 2009). Furthermore, physical

activity has been associated with reduced severity of depression, anxiety and other

30 mental health problems (see Asztalos, De Bourdeaudhuij & Cardon, 2010; Landers

& Arent, 2007) and improvements in quality of life (e.g., Acree et al., 2006). The

health care costs per annum associated with physical inactivity are estimated at

$719 million (Medibank Private, 2008), with the figure certain to increase as the

incidence of obesity continues to rise. The United States, which is regarded as the

‘heaviest nation’ in the world, spent more than $75(US) billion per year on

expenses directly attributable to obesity alone (Finkelstein, Fiebelkorn & Wang,

2003, 2004). In Australia, a leading health insurance company quantified the total

cost of physical inactivity (including health care, economic and mortality costs) as

being AU$1.5 billion annually (Medibank Private, 2007). Perhaps as a consequence

of the personal and economic costs of physical inactivity, an abundance of research

has been undertaken to explore the psychology of exercise participation.

BARRIERS TO PHYSICAL ACTIVITY

Many barriers to physical activity have been identified in a report

commissioned by the government of Western Australia (McCormack et al., 2003).

In this survey, lack of time was reported by 49% of respondents as a factor limiting

their involvement in exercise. Lack of motivation, poor health, child care, and age

(being too old) were other commonly cited reasons for limited activity levels

(Figure 2.1). Statistics reveal that, on average, Australians spend approximately

50% (2hour, 11minutes) of their spare time engaging with audio and visual media

per day (ABS, 2006). Although the public perception of exercise and general

attitudes towards physical activity may be favourable (Bylina et al., 2006), it

appears that many individuals do not choose to participate despite perhaps having

the opportunity to do so. The main barrier to physical activity is, therefore, a

perceived lack of time rather than an actual lack of time.

31 Figure 2.1. Main barriers to physical activity in Australia. Adapted from

McCormack et al. 2003.

A lack of motivation to exercise was cited by 11% of people surveyed

(McCormack et al., 2003) as a barrier to physical activity. However, as indicated in

the previous paragraph, lack of motivation may be a reflection of the most

commonly cited barrier, a perceived lack of time. Low motivation to exercise is

likely to be a function of a number of factors. First, although the effects of being

inactive are potentially severe (Jakicic & Otto, 2006), these negative effects are

only realised in the long-term and the positive outcomes of physical activity take

time to attain. Furthermore, for many individuals, exercise is neither enjoyable nor

fun. Exercise professionals must therefore explore strategies to improve adherence

(Martin, Tipler, Marsh, Richards & Williams, 2006) and provide tangible evidence

of fitness and health improvements to inspire even the most unenthusiastic

exerciser. The extensive challenge for individuals, government agencies and health

related businesses is to increase motivation levels and make exercise accessible

and feasible.

32

EXERCISE ADHERENCE

Exercise adherence is best defined as maintaining an exercise regime for a

long period of time (Lox, Martin & Petruzzello, 2003) . Whilst adoption of an active

lifestyle is important, sustaining that lifestyle is vital for long-term health benefits.

Exercise adherence (or lack thereof) is a major problem for individuals, businesses

and governments alike. For a government, the costs associated with inactivity

(both direct and indirect) amount to billions of dollars. From a business

perspective, exercise adherence is often a key concern, as individuals who perceive

themselves as adherent to their exercise intentions are more likely to renew gym

memberships and make long term commitments to exercise services (Ekstrom,

2006). Member attrition is a prominent and financially draining problem for the

fitness industry, and improving exercisers’ adherence plays a vital role in

improving member retention (Ekstrom, 2006). From an individual viewpoint,

exercise adherence is important in terms of helping one to feel competent about

one’s exercise pursuits (Hagger, Chatzisarantis & Harris, 2006). Improving exercise

adherence is therefore a priority research objective for many health researchers

around the globe.

THEORIES OF HEALTH BEHAVIOUR

Multiple theoretical frameworks have been created to understand and aid

in the prediction of behaviour in health and exercise settings. A great deal of

observational and experimental research has tested the tenets of these theories

and examined the predictive capacity of each model in an exercise setting.

Theoretical models of exercise adoption and adherence can be useful to plan and

evaluate exercise interventions in both research and applied health settings.

Importantly, these models propose factors that have a causal relationship with

33 behaviour and have been tested and validated using experimental and longitudinal

research designs (Courneya, Friedenreich, Arthur & Bobick, 1999; Quine, Rutter &

Arnold, 2000). Most of these models presume that health behaviours are the result

of rational and deliberate mental processes, largely under the conscious control of

the individual performing the behaviour.

One of the first cognitive models used to guide exercise behaviour change

was the Health Belief Model (Becker, 1974; Rosenstock, 1966, 1974). This model

suggests that individuals will engage in healthy behaviours on the basis of two

appraisals. The individual will first assess the severity of the potential illness and

how likely they are to be affected by the illness should they not engage in the

healthy behaviour (exercise). The second assessment is a decisional balance

between the benefits of engaging in the behaviour and the negative consequences.

Research has shown that the health belief model is useful in understanding

exercise behavior (Kiviniemi, Voss-Humke & Seifert, 2007; Quine et al., 2000).

Exercise practitioners and researchers using this model often use education to

ensure that the decisions an individual is making about the exercise are well-

informed. This is coupled with an active endeavour to diminish the negative

aspects of exercise, whilst making the positive consequences more salient and

tangible where possible.

The Social Cognitive Theory (Bandura, 1977) suggests that personal

(cognitions, emotions, and physiology), behavioural (frequency, duration, and

intensity) and environmental (culture, facilities, life settings) factors interact to

determine future behaviour and perceptions of behaviour. Bandura’s theory also

proposes that an individual’s self-efficacy (perception that they are able to

successfully perform the task) and expectations of the outcomes significantly

predict future instances of behaviour. Bandura’s theory and his concept of self-

34 efficacy have guided many exercise interventions and continue to inform practise

and evaluation of applied exercise programs.

One widely accepted model of behaviour prediction is the Theory of

Planned Behaviour, which was proposed by Icek Ajzen in 1985 (Figure 2.2). The

Theory of Planned Behaviour proposes that planned behaviour is the product of

behavioural intentions and that intentions are the product of attitudes, subjective

norms and perceived behavioural control (Ajzen, 1985). Attitudes indicate an

individual’s personal evaluation of the behaviour, and subjective norms reflect an

individual’s perception of the social desirability of performing the behaviour

(Ajzen, 1985). Perceived behavioural control relates to the amount of influence an

individual feels that they have over being able to execute the behaviour (Ajzen,

1985). External factors, such as weather, faulty equipment and reliance on other

people may reduce perceived behavioural control and therefore either obstruct

exercise intentions or hinder the behaviour directly. Perceived behavioural control

is the only antecedent to intention which can also directly impact upon behaviour

as proposed by the Theory of Planned Behaviour (Ajzen, 1985), which is illustrated

in Figure 2.2. This theory was developed following Ajzen and Fishbein’s theory of

reasoned action (1975), which simply states that behaviour is purely the product

of intentions which are formed by attitudes and subjective norms. The theory of

reasoned action made no mention of behavioural control, and was proposed to be

appropriate when an individual’s behaviour was completely within their control.

The Theory of Planned Behaviour accounts for instances when an individual fully

intends to engage in a certain behaviour, but situations arise which may prevent

them from ultimately performing that behaviour. Although originally designed for

the prediction of social behaviours (Ajzen, 1985), the TPB has been found to be an

35 acceptable predictive model for health behaviours (Conner & Sparks, 1996), and in

particular, exercise behaviours (French et al., 2005; Rhodes & Blanchard, 2006).

Figure 2.2. Theory of Planned Behaviour (Ajzen, 1985)

When reviewing many models of behaviour prediction that are used in the

health and exercise settings, there are several common features about them.

Perceptions of one’s ability to engage in a certain behaviour is common to the

theory of planned behaviour (Ajzen, 1985) and social learning theory (Bandura,

1977). Similarly, perceptions of the value of the activity in terms of risk reduction

and benefits associated with participating are common to the health belief model

(Becker, 1974; Rosenstock, 1966, 1974) and the theory of planned behaviour

(Ajzen, 1985). The social cognitive theory and the health belief model are

composed of many similar components, and involve cognitive appraisals of

individual and environmental factors which affect the behavioural outcomes

(Rosenstock, Strecher & Becker, 1988). On closer inspection, many of the

theoretical models are composed of similar features which has inspired many

researchers to inspect health behaviours in light of multiple models (e.g., Hagger,

Chatzisarantis & Biddle, 2002; Rosenstock et al., 1988)

Attitudes

Intentions Subjective Norms

Behaviour

Perceived Behavioural

Control

36

SELF-DETERMINATION THEORY

MOTIVATION RESEARCH

Self-determination theory is a complex, macro-theory of human motivation

and well-being. Self-determination theory takes a positive approach to human

psychology and behaviour by defining sub-theories which describe the drives of

human behaviour and well-being. Developed by Deci and Ryan (1985b), the theory

addresses locus of causality for motivation, types of motivation, basic

psychological needs, and the effects these elements have on well-being. The theory

is comprised of several sub theories: cognitive evaluation theory (Deci, 1975; Deci

& Ryan, 1980), organismic integration theory (Deci & Ryan, 1985b; Ryan &

Connell, 1989), causality orientations theory (Deci & Ryan, 1985a), basic needs

theory (Ryan & Deci, 2000) and goal contents theory (Ryan & Deci, 2010). The

tenets of self-determination theory are based on the assumption that humans have

an innate tendency to seek challenges, learn information about the environment in

which they exist, and engage in purposeful conduct (Deci & Ryan, 1985a, 1985b).

In doing so, humans instinctively aspire towards psychological growth and a

unified sense of self. These assumptions are by no means new or unique to self-

determination theory. The idea that humans are constantly and actively striving

towards a coherent self was examined in the works of Aristotle and has been the

basis of many psychological investigations. Ego psychology in psychoanalysis

identified the personality organising and unifying function of the ego, ego

synthesis, to be a central role of the ego (Freud, 1927; White, 1963). Likewise, the

foundations of client-centred therapy rely on the assumption that individuals

constantly move in the direction of enhancing themselves (Rogers, 1959, 1963).

Carl Rogers defined an actualising tendency as the universal drive in every living

37 organism to grow, develop, and realise its full potential (Rogers, 1959, 1963). It

was at a similar time that Robert White (1959) proposed that humans were

inherently motivated to master their environments and engage in new challenges.

White suggested that in the pursuit for mastery, the satisfaction and reward for

engaging in this behaviour was the task itself. This was the first concrete

conception of intrinsic motivation. Following White’s 1959 paper, other prominent

figures in psychology also claimed that humans have an innate drive to learn and

grow within their environments. Jean Piaget, a cognitive psychologist, claimed that

humans were positively inclined to progress in terms of learning, intellect, and

emotional development (Piaget, 1971, 1977). Furthermore, humanistic

psychologist Carl Rogers proposed that humans were by nature inclined to grow

and prosper within their environments (Rogers, 1963). In addition to the evidence

suggesting that humans had a need to be competent in their environment, there

was burgeoning research interest in the origin of behaviour. Heider (1958)and

deCharms (1968), for example, proposed that behaviour may emanate from

internal or external origins. Heider (1958) had proposed an impersonal causation,

where behaviour occurred due to the environment alone without the individual’s

intention, and an interpersonal causation, where behaviour occurred due to the

individual’s intention to act. deCharms (1968) expanded on this by broadening the

interpersonal causation to include two aspects. He defined an external locus of

causality, where the individual decided to act in a certain manner mainly due to

impersonal reasons and circumstances, and an internal locus of causality, where

behaviour occurred due to the individual’s personal values and interests.

deCharms argued that individuals who saw themselves as the drivers of their own

behaviour would have more intrinsic motivation (deCharms, 1968), and he

proposed that autonomy was a basic psychological need for growth and well-being.

38 These researchers and the advances their work made in the study of motivation

laid the foundation for motivation to be explored in greater depth.

COGNITIVE EVALUATION THEORY

It was in the context of early motivation research that Edward Deci began to

investigate effects of external rewards on intrinsic motivation. He conducted a

series of studies examining persistence in a simple task, and he found that

participants who were originally rewarded for completing the task showed less

persistence once the reward was removed compared to participants who never

received a reward (Deci, 1971). Similar findings were observed in the work of

Lepper, Greene and Nisbitt (1973) which found that children showed greater

persistence when no reward was presented following a task. The cognitive

evaluation theory (Deci, 1975) was developed to account for these findings. The

theory suggests that external, task-contingent rewards can detract from intrinsic

motivation. The mechanism for this is proposed to be based on the reduction in

autonomy perceived by the individual (Deci, 1971, 1975; Deci, Koestner & Ryan,

1999). Based on deCharm’s suggestion that autonomy is a fundamental

psychological need and critical for intrinsic motivation (deCharms, 1968), lowering

autonomy was suggested to decrease intrinsic motivation. Rather than engaging in

the task for self-determined reasons, the individual may come to associate the task

with the external reward, shifting an internal locus of control to an external one

(Deci, 1975).

The types of rewards and scheduling of rewards effects how much intrinsic

motivation is undermined (for a review see Deci et al., 1999). Irregular (or

unexpected) rewards offered for positive performance have a lower ability to

undermine intrinsic motivation than scheduled rewards offered based on

39 participation or task completion (Deci et al., 1999; Ryan, Mims & Koestner, 1983).

Unexpected or highly irregular rewards may not detract from autonomy as the

individual is not reliant on the reward, and behaviour may not be motivated by

that reward (Deci, 1975). For performance related rewards, the reduction in

autonomy may be counteracted by an increase in competence, as the reward is

indicative of the individual’s ability to perform the task effectively (Deci, 1975). As

White (1959) defined, a perception of mastery in one’s environment is extremely

important for intrinsically motivated behaviour and supports the use of

performance-related rewards.

BASIC NEEDS THEORY

Self-determination theory proposes that all humans have three innate

psychological needs for optimal health, growth and development (Deci & Ryan,

1985a). The cognitive evaluation theory is based on these needs, as are the other

sub-theories of self-determination theory. However, this particular sub-theory was

not formalised as part of self-determination theory until quite recently. This sub-

theory formally included the psychological needs that self-determination theory

had been guided by since its inception. self-determination theory suggests that

individuals possess a need for autonomy (to be the director of one’s own actions

and behaviour), relatedness (a sense of belonging and association with others) and

competence (the innate desire to behave and perform effectively and to

successfully interact within the environment) (Deci & Ryan, 1985a; Deci, Ryan,

Gagné, Leone, Usunov & Kornaazheva, 2001).

Deci (Deci, 1971, 1975) recognised the importance of autonomy, as defined

by deCharms (1968), for intrinsic motivation and well-being. Additionally, White’s

conceptualisation of intrinsic motivation was based on individuals’ need for

40 competence (White, 1959), another important component of cognitive evaluation

theory. These two needs were integrated into cognitive evaluation theory and the

other tenets of self-determination theory. However, the third need, relatedness,

was recognised as an important and unique need by Baumeister and Leary (1995)

following a review of the motivation literature. Maslow (1968) had identified

belonging as a middle-order need in his hierarchy of motivation, with self-

actualisation need satisfaction being achievable only after satisfying the need to

belong. The attachment theory (Bowlby, 1969, 1973, 1988) also informed the

Baumeister and Leary review providing more empirical evidence that individuals

are inherently motivated to form bonds with significant others in their lives.

Ryan and Deci’s basic needs sub-theory combined the works of these

researchers, and others, to guide future motivation research grounded in self-

determination theory. They identified satisfaction of the three psychological needs

is as important for psychological growth as the satisfaction of basic physiological

needs is for sustaining life(Ryan & Deci, 2000, 2002). Self-determination theory

suggests that all humans possess similar amounts of each need. However, every

individual differs in terms of how easily satisfied these needs are (Deci & Ryan,

2000; Deci et al., 2001). For example, some individuals inherently feel more

relatedness in general whilst others do not necessarily. Satisfaction of the basic

psychological needs has been shown to improve psychological wellness and

produce positive social behaviours, and several research groups have shown that

satisfaction of the needs contributes to general well-being in various age-groups

(Grolnick, Bridges & Frodi, 1984; Vansteenkiste, Neyrinck, Niemiec, Soenens, De

Witte & Van den Broek, 2007) and in different cultures (Deci et al., 2001; Jang,

Reeve, Ryan & Kim, 2009; Reis, Sheldon, Gable, Roscoe & Ryan, 2000).

41

Basic psychological needs sub-theory acknowledges the importance of the

environment in which motivated behaviour occurs. The social environment can be

manipulated to increase need satisfaction or create a need thwarting environment.

Autonomy supportive, well-structured, inclusive and responsive environments

support the satisfaction of autonomy, competence, and relatedness respectively

(see Vansteenkiste, Niemiec & Soenens, 2010). Satisfaction of these needs will, in

turn, facilitate the adoption of self-determined forms of motivational regulation

and enhanced well-being (Deci, Eghrari, Patrick & Leone, 1994; Edmunds,

Ntoumanis & Duda, 2006; Wilson, & Rodgers, 2004). Moreover, perceptions of

autonomy support increase as individuals feel they are provided with choice in a

non-coercive and unconstrained environment (Deci et al., 1994). It is also vital for

perceived autonomy support that individuals feel their perspective is being

acknowledged by those around them and are provided with a meaningful rationale

for any behaviour suggestions by those surrounding them (Deci et al., 1994). Need

satisfaction in one specific environment has been shown to influence general well-

being, not just context-specific well-being. For example, Sheldon and Elliot (1999)

found that many positive experiences in an academic context produced increases

in general well-being of the students. This has since been replicated in other

settings, including sport, where gymnasts displayed greater vitality and self-

esteem when autonomy, competence, and relatedness needs were satisfied by

parents and coaches (Gagné, Ryan & Bargmann, 2003).

ORGANISMIC INTEGRATION THEORY

Self-determination theory distinguishes between three types of motivation;

amotivation, extrinsic motivation and intrinsic motivation. Amotivation refers to a

state of lacking any intention to engage in the behaviour being investigated

42 (Markland & Tobin, 2004). Broadly, extrinsic motivation reflects action in pursuit

of a goal independent of the activity itself (Calder & Staw, 1975), whilst intrinsic

motivation stems from an inherent satisfaction from merely engaging in the

behaviour (Young, 1961). The way that self-determination theory differs from

previous theories of motivation is the way in which it distinguishes between

various forms of extrinsic motivation. The organismic integration theory (Deci &

Ryan, 1985b) describes the differentiation of various types of extrinsic motivation

based on the degree of autonomy and internalisation of the motives. Deci and Ryan

have identified that although extrinsic motivation is similar in the way that

external reasons and rewards drive the behaviour, the degree of internalisation of

the motive can differ quite substantially. The quality, not just the quantity, of

motivation is emphasised in the theory, with Deci and Ryan suggesting that the

degree of internalisation and amount of need satisfaction is important for long-

term motivation, well-being, and personal growth (Deci & Ryan, 1985a, 1985b,

2000; Ryan & Deci, 2000).

Self-determination theory suggests that extrinsic motivation is comprised

of four types of regulation: external, introjected, identified, and integrated, each

with increasing levels of internalisation (Deci & Ryan, 1985b). External regulation

is characterised by individuals acting in a certain manner solely to avoid

punishment or receive external rewards (Ryan & Deci, 2000). This form of

extrinsic motivation is regulated with extremely low degrees of internalisation and

there is limited personal value given to engaging in the behaviour. Individuals who

experience introjected regulation are motivated into action due to internal

pressures, such as guilt, embarrassment, or ego enhancement (Ryan & Deci, 2000).

The two other forms of extrinsic motivation are more self-determined. Identified

regulation occurs when an individual participates due to personally held beliefs

43 that the outcomes will be satisfying (Ryan & Connell, 1989). Integrated regulation

is the most internalised form of extrinsic motivation and arises when identified

regulations are fully assimilated into the self and also correspond to other

personally held beliefs and values (Deci & Ryan, 2000). The difference between

integrated regulation and the final form of motivation, intrinsic motivation, lies in

the satisfaction derived from the outcomes of the activity, rather than the activity

itself. Intrinsic motivation reflects a desire to participate in an activity because it is

inherently enjoyable or interesting (Deci & Ryan, 2000). Identified regulation,

integrated regulation, and intrinsic motivation are often referred to as autonomous

motivation, whilst introjected and external regulatory styles are considered to be

controlled motivation.

Deci and Ryan (2000) conjectured that the type of motivation regulation

that drives behaviour is largely dependent on the satisfaction of the three basic

psychological needs discussed in the theory. More self-determined forms of

regulation will be engaged when some or all of the needs are being satisfied. In

situations when the three needs are not being satisfied, or are in conflict with one

another, less self-determined forms of self-regulation will guide behaviour, or

amotivation may occur (Deci & Ryan, 1985a, 2000). Optimal behavioural,

cognitive, and affective outcomes arise in situations where needs are being

satisfied and more autonomous forms of regulation are in effect (Deci & Ryan,

1985a; Edmunds, Ntoumanis & Duda, 2007a, 2007b). Hagger and colleagues

(2006), for example, found that in an exercise and dieting context, psychological

need satisfaction influenced autonomous motives. These autonomous motives

subsequently predicted behavioural intentions by increasing perceived

behavioural control and facilitating the creation of more positive contextually

specific attitudes (Hagger et al., 2006).

44 CAUSALITY ORIENTATIONS THEORY

The sub-theories of the self-determination theory presented so far have

addressed the environment in which the behaviour is performed, the reward

contingencies that may be presented to the individual, and how these factors affect

need satisfaction. The causality orientations sub-theory (Deci & Ryan, 1985a)

considers the individual differences of motivational or causality orientations.

Causality orientations reflect the dominant way in which an individual perceives

stimuli within their environment and the locus of control from which they operate.

Deci and Ryan proposed three types of orientations: autonomy, control, and

impersonal (Deci & Ryan, 1985a). Individuals with a dominant autonomy

orientation perceive that their behaviour is driven by their own self-endorsed

values and inherent interest, whether this is in the activity itself, or the outcomes

of that activity. On the other hand, those with high control orientation perceive

their behaviour to be dictated and directed by external (instructions and protocols

received from others) and internal (such as guilt or ego-enhancement) pressures.

Finally, impersonal orientation is dominant when an individual believes that their

behaviour is a product of a completely external locus of control. To reflect this

orientation to a regulatory style, an individual high in impersonal orientation

would often be amotivated, simply reacting to their environment, rather than

engaging in motivated behaviour. The causality orientations sub-theory is

complemented well by Vallerand’s Hierarchical Model of Intrinsic and Extrinsic

Motivation, in which the global level of motivation is specified as an individual’s

tendency to be either intrinsically or extrinsically motivated in general (Vallerand,

1997).

45 The orientations are somewhat trait-like, and in most situations an

individual can be relied upon to act in accordance with their dominant causality

orientation (Deci & Ryan, 1985a). However, they are not as stable as personality

constructs, such as the Big Five traits (Asendorf & van Aken, 2003). Like

personality traits, orientations are a product of genetic and biological factors

considered with environmental factors. Causality orientations are in many way an

evolving construct as repeated experiences of autonomy and/ or controlled

motivation in social settings can alter an individual’s dominant orientation (Deci &

Ryan, 1985a). Despite having a dominant orientation, the context and immediate

social setting can also influence the orientation adopted by the individual in that

particular situation (Deci & Ryan, 1985a). Thus, an individual does not always act

in accordance with their dominant causality orientation. In fact individuals have

representations of all three types of orientation (Deci & Ryan, 1985a; Radel,

Sarrazin & Pelletier, 2009; Williams, Grow, Freedman, Ryan & Deci, 1996) and in

situations that prompt an underlying orientation, an individual may act

uncharacteristically in accordance with another orientation type. Several

investigations which aim to alter the salience of the various representations of

causality orientations via priming protocols have been published recently in the

literature (e.g., Radel, Sarrazin, LeGrain, et al, 2009; Radel, Sarrazin & Pelletier,

2009). These research groups have used nonconscious priming techniques

traditionally used to prime specific goals or attitudes to prime a general

orientation and have observed changes in affective, behavioural and physiological

responses.

46 GOAL CONTENTS THEORY

The most recent formal theoretical addition to self-determination theory is

the goals contents theory (Vansteenkiste et al., 2010). Investigation into goals from

a self-determination theory perspective began when Kasser and Ryan (1996)

proposed that goals can be either intrinsic or extrinsic. Intrinsic goals (such as

physical health, meaningful relationships and personal growth) are more likely to

directly satisfy the basic psychological needs (autonomy, competence and

relatedness). On the other hand, extrinsic goals (such as money and fame) are less

likely to satisfy those basic needs. This proposition is interesting as an underlying

premise of self-determination theory is that individuals are driven by an innate

desire to grow and prosper. Extrinsic goals which do not satisfy any of the basic

psychological needs would theoretically be irrelevant, particularly if the individual

was also pursuing these goals for controlled reasons. La Guardia (2009) proposed

that extrinsic goals are pursued in the hope that goal achievement will lead to

improved self-perception, an ideal perpetuated by media and greater society

(Dittmar, 2007; Soenens & Vansteenkiste, 2011). Ultimately achievement of these

goals does not satisfy basic psychological needs, reducing the benefits to

psychological well-being and growth (Vansteenkiste et al., 2010).

These findings were incorporated into the self-concordance model which

proposed that increasingly self-concordant goals will improve the likelihood of

goal attainment via sustained effort. This goal attainment will then elicit greater

improvements in well-being (Sheldon & Elliot, 1999). Self-concordant goals are

defined as those goals pursued for intrinsic, integrated, or identified reasons as

defined by self-determination theory (Deci & Ryan, 1985a), and are inspired by an

individual’s deeply held core values (Little, 1993). Originally referred to as self-

47 determined goals, these goals are derived from personal choices. They have an

internal locus of causality, which, in reference to self-determination theory,

explains how attainment of the goals increases basic psychological need

satisfaction and well-being. However, the sense of disappointment felt by not

attaining self-concordant goals can be great and cause decreases in well-being due

to the greater value being placed on goal attainment (Sheldon, 2002; Sheldon,

Kasser, Smith & Share, 2002). The goal contents theory notably acknowledges that

intrinsic goals can be pursued for both autonomous and controlled reasons, as can

extrinsic goals (Vansteenkiste et al., 2010). It has also been shown that extrinsic

goals and controlled regulation are commonly associated, as are intrinsic goals and

autonomous regulation, but that this is not always the case (Sheldon, Ryan, Deci &

Kasser, 2004). Goals contents theory also purports that goals should also be self-

developed (Vansteenkiste et al., 2010). The detriments caused by the removal of

choice in the selection of goals pursued will potentially counteract the benefits of

intrinsic goals in terms of goal attainment, need satisfaction and well-being.

SELF-DETERMINATION THEORY AND PHYSICAL ACTIVITY

Self-determination theory has been widely applied to physical activity

settings, including physical education in different child age groups, coaching and

sports settings, exercise and active living. The theory has been applied to explain

observed phenomena and experimentally manipulate behavioural and affective

outcomes. Many coaching, physical education and exercise interventions have been

framed in self-determination theory, and the health and fitness benefits of

encouraging active pursuits in this manner have been empirically tested. The

exercise environment can influence an individual’s behavioural regulation

(Pelletier, Fortier, Vallerand & Briére, 2001) which is associated with greater

48 psychological need satisfaction (Edmunds et al., 2006). Need satisfaction and

autonomous motivation have numerous benefits for exercise behaviour (e.g.,

Fortier, Sweet, O'Sullivan & Williams, 2007). Autonomy supportive environments

have been shown to be superior in encouraging exercise behaviour, increasing

attendance at fitness classes, and promoting sustained commitment to exercise

programs (Edmunds et al., 2006; Edmunds, Ntoumanis & Duda, 2008).

Although goal contents theory is only a recent formal addition to the

literature, physical activity researchers have acknowledged and explored the idea

that exercise or fitness goals can differ in nature. The Motives for Physical Activity

Measures (Ryan, Frederick, Lepes, Rubio & Sheldon, 1997) distinguish between

motives concerning appearance, enjoyment, competence, social and fitness. These

motives are related to the extrinsic and intrinsic goals that have come to be

acknowledged and defined in the goal contents theory (Vansteenkiste et al, 2010).

Positive exercise behaviours (e.g. time spent exercising and attendance at exercise

classes) have been associated with the more intrinsic motives in several studies

(Frederick & Ryan, 1993; Ryan et al., 1997).

Self-determination theory based exercise programs seem to elicit greater

adherence to active lifestyles than the provision of exercise interventions alone.

The promotion of competence and relatedness need satisfaction is also usually

woven into these interventions, further increasing program success and long-term

behaviour change (Edmunds et al., 2007a, 2008; Fortier et al., 2007). However,

despite the success of these programs, overall there is still a reasonably high

degree of attrition following the exercise interventions and, as always, some

aspects of exercise behaviour remain unexplained by the theory as it stands.

49

One field of research that has emerged in psychosocial research of late is

the consideration of implicit cognitive processes. In general, all theories of

behaviour change and motivation have been based on the notion that behaviour

emanates from, and is controlled by, fully conscious processes. The health

behaviour models discussed previously and the self-determination theory itself are

all proposed as theories incorporating conscious awareness and control. There is

no doubt that behaviour, particularly exercise behaviour, is controlled in some

instances by conscious processes. However, the decision to plan an occasion of

physical activity or even the initiation of behaviour may be heavily guided by

implicit cognitive processes (see Dimmock & Banting, 2009). The following section

of the literature review highlights theory and empirical work on nonconscious

processes, with an emphasis on nonconscious representations of motivation and

how motivation may be automatically activated.

COGNITION

Research exploring cognition and human behaviour has always been of

interest to psychologists. Cognition describes “the acquisition, storage,

transformation and use of knowledge” (Matlin, 2005, p. 2). Traditionally, cognitive

constructs have been thought to operate within an individual’s awareness. There

has been a widespread assumption that human beings are ‘rational animals’ who

make behavioural choices via a belief of what is best for them. For higher order

mental processes, such as goal-directed behaviour, self-identity and self-esteem, it

has been assumed that individuals operate on and behave according to consciously

appraised processes. Thus, many theories of behaviour and models of behavioural

prediction assume that behaviour and perceptions of that behaviour are

50 determined by conscious thought and introspection (Ajzen, 1985; Ajzen &

Fishbein, 1980; Rosenstock et al., 1988).

The assumption that consciousness is the driver of cognitive functioning

and behaviour has been challenged by several prominent psychologists (Wilson,

Dijksterhuis & Bargh, 2001; Frith, Blakemore & Wolpert, 2000; Prinz, 1997; 2002).

These studies have built on the work of early psychologists, for example Jung

(1964; 1968) who formally proposed that there are two basic ways of interpreting

information: thinking and intuitive interpretation. This concept was not

completely novel, Freud (1927; 1965) proposed that aspects of the self may not be

totally accessible for conscious examination, yet were still important parts of the

individual’s cognitive functioning. Many other psychologists have also

acknowledged that not all cognitive processes can be accessed introspectively

(Nisbett & Wilson, 1977; Wegner, 2002). Nisbett and Wilson (1977) suggested

that individuals may have conscious access to the product of cognitive processes,

but not to the processes enabled to create the product (for example a memory,

attitude, or belief). Wegner (2002) has also shown that feelings of control and the

formation of intentions are products of nonconscious processes and initiated

without the awareness of the individual. Thus, theory and empirical studies have

indicated that cognition exists on both explicit and implicit levels (e.g., Fazio, 1990;

Strack & Deutsch, 2004; Wilson, Lindsey & Schooler, 2000). Explicit cognitive

constructs are available for conscious introspection (Greenwald & Banaji, 1995),

meaning that an individual is able to access and report the state of the construct in

question. Implicit cognition, on the other hand, has been described as information

processing outside of conscious awareness (Kihlstrom, Barnhardt & Tataryn,

1992).

51

Many models of dual-processing have been developed, each sharing

common characteristics (For a review see Smith & DeCoster, 2000), and generally

advocating two processing systems. The first of these systems draws on

associations in memory and develops via conditioning or repeated experiences.

This system operates automatically and without consciousness (Smith & DeCoster,

2000). The second processing system is structured by logic, language, and social

rules perceived by the individual. This processing system is consciously activated

when the individual has the time and sufficient cognitive resources available

(Smith & DeCoster, 2000). One dual process model, Strack and Deutsch’s reflective-

impulsive model (RIM; 2004) assumes that all information will be processed by the

impulsive system (conceptually similar to an automatic processing system), but

depending on the intensity of the information and the attention received, the

stimuli may also be processed by the reflective system (similar to a conscious

processing system). The ultimate perception and possible resultant behaviour is

caused by an interaction of the two systems. Depending on the arousal level of the

individual, the implicit process may largely drive behaviour, yet in highly mindful

situations, the individual may disengage from their implicit processes completely if

their reasoning and current goals are at odds with these processes (Strack &

Deutsch, 2004). The PAST model (Petty, Tormala, Briñol & Jarvis, 2006), which

indicates that when explicit attitudes change, the old attitude can remain in

memory and influence behaviour is a similar model. This model builds upon a

wealth of research indicating that prior attitudes can exert an impact on current

responses above and beyond current attitudes (e.g., Petty, Baker, & Gleicher, 1991;

Petter, Gleicher, & Jarvis, 1993; Wilson et al., 2000). Petty et al. (2006) have

provided support for their PAST model over four studies, in which it was

demonstrated that when people undergo attitude change, their old and new

52 attitudes interact to produce a state of implicit ambivalence. Much of this work has

indicated that implicit and explicit attitudes are empirically distinct and that

people’s automatic, evaluative reactions to stimuli in their environment are

important determinants of their behaviour, particularly when the behaviour in

question is being performed under stressful, impulsive or hurried circumstances

(Damasio, 2001; Strack & Deutsch, 2004). There is speculation (e.g., Smith &

DeCoster, 2000; Strack & Deutsch, 2004) that this explicit and implicit trend found

in attitudes would apply to many different aspects of the personality.

IMPLICIT CONSTRUCTS AND AUTOMATICITY

In addition to automatic or implicit processes, constructs have been

acknowledged to exist implicitly and explicitly. Greenwald and Banaji (1995)

defined an implicit construct as “the introspectively unidentified (or inaccurately

identified) trace of past experience that mediates R”, where R refers to the

category of responses that are assumed to be influenced by that construct (p. 5).

They noted that implicit cognition could reveal traces of past experience that

people would consciously reject or might avoid revealing. Moreover, implicit

cognition could also reveal information that was not available to introspective

access even if individuals were motivated to acquire it (Greenwald & Banaji, 1995).

Explicit cognitive constructs are available for conscious introspection (Greenwald

& Banaji, 1995), meaning an individual is able to access and report the state of the

construct in question. Implicit cognition, on the other hand, has been described as

‘information processing outside of conscious awareness’ (Kihlstrom, Bernhardt &

Tataryn, 1992). Wilson et al. (2000) supported this notion in regards to attitudes

and proposed that attitudes exist on two levels, implicit and explicit. Similar to the

suggestion of Smith and DeCoster (2000) the authors suggested that individuals

53 will engage their implicit attitudes if they do not have the cognitive capacity or the

motivation to activate their explicit attitudes. Implicit attitudes may be engaged in

situations of high stress, time constraints, and extreme emotions (Wilson et al.,

2000). They also speculated that the explicit/implicit dichotomy in attitude

constructs would apply to many different aspects of personality. John Bargh

(1994) describes four elements which typify an automatic process- unintentional,

outside of awareness, uncontrollable and efficient (Bargh, 1984, 1994). Given the

resistance towards automatic or implicit processes from researchers firmly

positioned in the view that behaviour is driven by conscious processes, there

seemed to be a strong drive from researchers to define and describe implicit or

automatic constructs and processes.

Originally, researchers were fairly rigid in their requirement for all four

elements to be present for a process to be called automatic. However, Bargh

(Bargh, 1994; Bargh, Gollwitzer, Lee-Chai, Barndollar & Trotschel, 2001; Bargh,

Lombardi & Higgins, 1988) and other researchers (for a review see Moors & de

Houwer, 2007) have since strongly advocated that there is some degree of

automaticity and the ‘automatic or not’ dichotomy presented in some research

(Bruner, 1957; Shiffrin & Schneider, 1977; Wilson et al., 2000) may not be

appropriate for most constructs. Important work by Ferguson and Bargh (2004)

and Ferguson (2007), however, has indicated that automatic evaluations of

intangible objects may also exert a strong influence over behaviour. Ferguson and

Bargh (2004) found that spontaneously activated evaluative information in

relation to a goal increased the likelihood of motivation and intention to pursue

that goal. Support for these findings was offered by Ferguson (2007), in which it

was demonstrated over four studies that participants’ automatic attitudes toward

54 goals (e.g., egalitarianism) significantly predicted their goal pursuit. Bargh (1992)

argued that any combination of his four features of automaticity may be present in

a process that is largely automatic. He also described three types of automatic

processes (preconscious, post-conscious and goal-dependent) and suggested that

automaticity is a gradual process (Bargh, 1989, 1992, 1997) . Bargh (1992) then

proposed a ‘minimal feature of automaticity’- that the process is autonomous. He

defined an autonomous process as one that can run to completion without

conscious monitoring, irrespective of whether it started intentionally or

unintentionally. Moors and DeHouwer (2007), based on Bargh’s work and that of

others (e.g., Logan, 1985), summarised that there may indeed by a continuum of

automaticity but that there is no objective way of distinguishing a point to

determine whether a process an implicit or explicit process.

Most research on implicit cognitive processes has focused on automatic

associations toward objects with a physical presence, such as group (e.g., Dasgupta

& Rivera, 2008; McConnell, Rydell, Strain & Mackie, 2008; Son Hing, Chung-Yan,

Hamilton & Zanna, 2008). Despite some difficulty in defining automaticity and

specifying when a process is implicit, there is ample evidence to indicate that

implicit and explicit processes are present and can interact to some extent. Implicit

attitudes may be engaged in situations of high stress, time constraints and extreme

emotions (Wilson et al., 2000).

IMPLICIT PROCESSES AND BEHAVIOUR

As Strack and Deutsch (2004) described, both impulsive and reflective

(implicit and explicit) processes can activate overt behaviour. Both the RIM (Strack

& Deutsch, 2004) and work by Kehr (2004) found that implicit and explicit

processes (motives in the case of Kehr, 2004) may correspond and lead to a

55 smaller draw on cognitive resources for behavioural control. Evidence is mounting

that behaviours which are spontaneous and difficult to control are often uniquely

predicted by implicit attitudes (e.g., Dovidio, Kawakami, Johnson, Johnson &

Howard, 1997; Egloff & Schmukle, 2002; Wilson et al., 2000). Perugini (2005) for

example, found that implicit attitudes toward fruit and snacks were found to be

more predictive of participants’ spontaneous choices for these foods than explicit

attitudes. Furthermore, Ferguson (2007) found that implicit evaluations of goals

only predicted behaviour that was difficult to monitor and control (e.g., subtle

prejudice) rather than behaviour that was easy to monitor and control (blatant

prejudice). Such findings are consistent with tenets in the MODE model of attitude-

behaviour relations (Fazio, 1990; Fazio & Towles-Schwenn, 1999), in which it is

postulated that implicit attitudes predict spontaneous or highly automatic

behaviour better than controlled behaviour, whereas explicit attitudes predict

controlled behaviour better than spontaneous or highly automatic behaviour.

PRIMING SOCIAL CONSTRUCTS

Based on the notion that social constructs are represented implicitly and

social processes can occur automatically without conscious awareness, many

researchers have begun to investigate the role of priming in social and goal

directed behaviour. Posner and Snyder (1975) drew on the semantic priming

paradigm and Stroop task research to suggest that stimuli representing a certain

construct can be used to automatically activate a neural pathway to engage a

certain construct or initiate a certain process. More recent priming research has

built on this premise with experimental priming tasks designed to artificially

activate a certain process via the supra- or subliminal presentation of stimuli.

Typically priming consists of two stages: the afferent stage, where stimuli is

56 presented in order to activate associations in the memory; and the efferent stage,

where experimenters observe the responses to the stimuli (Fiedler, 2003). Bargh,

again, performed much of the research examining how priming can influence

behaviour and perceptions of behaviour. Building on these findings, Dijkersterhuis,

Chartrand and Aarts (2007) defined three routes to behaviour: the mimicry route,

the trait route and the goal route.

The mimicry route is best described by Bargh and Chartrand’s experiment

in which individuals mimicked the behaviour of experimenter without any

awareness that they were doing so (1999). The trait route described the activation

of a certain personality trait such as helpfulness (Nelson & Norton, 2005) or

elderly (Bargh et al., 1996). In this route, suites of behaviours are activated that

align with the trait being primed. For example in the Nelson and Norton study,

participants primed with super-heroes were more helpful than those not primed.

The final route is the goal route which assumes that goals, in a similar ways

to attitudes and memories, have mental representations of behaviours and other

outcomes (Bargh & Gollwitzer, 1994). Described in Bargh’s Auto-Motive Model,

this route suggests that motives and goals can be activated automatically and

without conscious involvement from the individual. Surrounding these mentally

represented goals is knowledge of behaviours, settings and actions which are likely

to increase the likelihood of goal attainment (Aarts & Dijksterhuis, 2000). This

conceptualisation of goals suggests that goal representations have cognitive

(knowledge of the goal and means to achieve it) and affective-motivational

(achievement of a desired, incentivised state) informational features (Aarts,

Custers & Holland, 2007). Presentation of goal related stimuli is then likely to

57 activate cognitive and motivational processes that are mentally connected to the

goal (Aarts et al., 2007; Custers & Aarts, 2007a, 2007b).

Goals setting and goal pursuit are traditionally thought of as explicit

activities, however, recently researchers have investigated the influence of priming

on both goal formation and goal pursuit. Stimuli can be presented which are

designed to activate the setting of a certain goal, without the individual having

previously set that goal (Aarts, Dijksterhuis & De Vries, 2001). Likewise, goal

adoption itself can be primed (Dijksterhuis et al., 2007), with stimuli activating a

goal and causing behavioural outcomes related to goal attainment (Chartrand &

Bargh, 1996). The cognitive processes that lead to goal directed behaviours occur

automatically and without the awareness of the individual (Aarts, Custers &

Wegner, 2005; Chartrand & Bargh, 1996; Dijksterhuis et al., 2007). Finally goal

pursuit of a personally held goal can be primed by presenting stimuli related to the

goal itself and activating the cognitive and motivational processes that are likely to

enable goal directed behaviour (Dijksterhuis et al., 2007). For the priming of goals

to be successful, the individual must have some mental representation of the goal

being primed. A central tenet of the priming paradigm described by Bargh is that

the construct being automatically activated by external stimuli must be

represented in memory to some degree for that individual (Bargh, 1990). Repeated

experiences of goal pursuit lead to the formation of a mental representation of the

goal which can then be activated by stimuli in the environment, much like attitudes

or stereotypes which have shown to be successfully primed. Quite specific goals

and motives have been successfully primed (Aarts et al., 2001) and there have

recently been research priming more general goals and motivational states

(Levesque & Pelletier, 2003).

58 IMPLICIT MOTIVATION

This thesis largely focuses on motivation and how motivation, as described

in the self-determination theory (Deci & Ryan, 1985b) can influence exercise

behaviour. Murray (1938) was one of the first to specify implicit and explicit

representations of the need for achievement, the motivation behind pursuits of

excellence, mastery and efficiency (see Elliot, Conroy, Barron & Murayama, 2010).

Other investigations into implicit motivation were instigated by the suggestion in

Social-Cognitive theory (Bandura, 1977) that conscious, explicit motives can come

to operate in an implicit and automatic manner over time (Bargh & Chartrand,

2000). Kehr (2004) also provided evidence to suggest that motives exist implicitly

and explicitly, although he did not investigate this proposition from the

perspective of self-determination theory.

There have been a handful of investigations into the implicit nature of

motivation from a self-determination theory perspective. Levesque and Pelletier

(Levesque & Pelletier, 2003) were perhaps the first to examine this issue. In four

studies, the authors assessed the extent to which chronically accessible motivation

predicted academic-related outcomes among students. Chronically accessible

motivation was assessed by examining the first motives provided by participants

in a task that required speed and limited self-reflection from the participants,

which is similar in nature to implicit measurement tools. They found that

chronically accessible motivations were positively associated with self-report

academic motivation. Furthermore, they showed that chronically accessible

motivations were the strongest predictor of some academic outcomes (Levesque &

Pelletier, 2003). These findings were supported in a subsequent study by

Levesque and Brown (2007), who used an implicit association test to measure

59 implicit motivation. In this study, implicit motivation and day-to-day self-report

motivation were found to be associated, but the relationship was moderated by

dispositional mindfulness. This finding is conceptually appealing, as an individual

who is highly aware of their behaviour and the environment is more likely to

attend to incoming information and moderate the influence of implicit motivation.

An increased level of attention is proposed to transfer the processing of the

information from implicit (or impulsive) processes to explicit processes (Strack &

Deutsch, 2004). Finally, research by Burton, Lydon, D’Alessandro and Koestner

(2006) assessed differences in outcomes between intrinsic and identified

motivations in an education context. Although explicit measures of the constructs

were used for their first two studies, the researchers utilised an implicit measure

(a lexical decision making task) of intrinsic and identified regulation in their final

investigation. Consistent with their hypothesis, Burton et al. found that implicit

identified regulation predicted academic performance and that this effect was

independent of implicit intrinsic motivation. Moreover, the authors revealed an

interaction effect between implicit identified regulation and explicit identified

regulation in the prediction of academic performance. Students that were low on

both types of identification had significantly lower exam grades than students in

the other three groups (low implicit/high explicit; high implicit/ low explicit; high

implicit/high explicit). The academic performance of these other three groups did

not differ significantly. In discussing their findings, Burton et al. suggested that

autonomous self-regulations guide behaviour in an automatic as well as a

conscious manner, and they recommended further work on the topic of implicit

motivation.

60 PRIMING MOTIVATION

Whilst the aforementioned studies indicate that motivation exists implicitly,

there has been significant research focused on the automatic activation of

motivation. Similar to the priming research discussed earlier, various motivations

are activated through the use of stimuli presentation or language tasks. In possibly

the first example of motivational priming, Levesque and Pelletier (2003) assessed

the ability of motivational orientations to be primed. A scrambled sentence task

was developed to supraliminally prime autonomous or controlled motivation. It

was found that motivations activated without the individuals’ conscious awareness

predicted intrinsic motivation, interest/ enjoyment, and perceptions of choice in a

generic cross-word task. Participants in the autonomous priming condition also

performed better in the cross-word task compared to those in the controlled

priming condition. The results supported the tenets of the self-determination

theory insofar as more self-determined motivation was associated with positive

affective and behavioural outcomes. The findings also concurred with previous

priming research by indicating that automatically activated higher order mental

processes could elicit changes in affective and behavioural outcomes. Similarly,

Ratelle, Baldwin and Vallerand (2005) primed feelings of control or autonomy and

found that self-determined motivation was undermined, and self-initiated

participation in a task was diminished, following presentation of controlling

stimuli. These authors also assessed mood and were able to discount mood

changes as an explanation for differences found between groups (Ratelle et al.,

2005). Hodgins and colleagues also assessed the influence of primed autonomous

motivation on outcome variables conceptually associated to self-determined

motivational states (Hodgins, Yacko & Gottlieb, 2006). They found a lower desire

61 to escape and less self-serving bias amongst autonomously primed participants

compared to participants primed with controlled or impersonal orientations. In

Study 3 of the same paper, Hodgins and colleagues found that priming autonomous

motivation could elicit changes in physical performance and reduce anticipatory

self-handicapping (Hodgins et al., 2006). Hodgins continued this line of work with

other researchers (Hodgins, Brown & Carver, 2007), investigating the influence of

primed autonomous or controlled motivation for self-esteem, a construct

associated with greater need satisfaction and autonomous motivation (Deci &

Ryan, 1995; Reis et al., 2000; Ryan & Deci, 2004). Using scrambled sentence tasks

to prime the motivations, Hodgins et al. found that self-esteem (particularly

defensive self-esteem) was lower following a controlling prime compared to an

autonomous prime (Study 1; Hodgins et al., 2007) or a neutral condition (Study 2;

Hodgins et al., 2007).

Recently, Radel and colleagues (Radel, Sarrazin, Legrain & Gobancé, 2009;

Radel, Sarrazin & Pelletier, 2009) have investigated motivational priming and its

direct behavioural and affective influences. Rather than using a scrambled

sentence task to prime participants, in both studies the authors used subliminal

priming techniques, presenting autonomous or controlled word stimuli in a

memorisation task (Radel, Sarrazin & Pelletier, 2009) or between lecture slides

(Radel, Sarrazin, Legrain, et al., 2009). In both cases, findings were consistent with

those of other researchers in the field (Hodgins et al., 2007; Hodgins et al., 2006;

Levesque & Brown, 2007; Levesque & Pelletier, 2003; Ratelle et al., 2005).

Autonomous primes were associated with greater performance on a motor task,

increased enjoyment of that task (Radel, Sarrazin & Pelletier, 2009), and better

information retention following a university lecture amongst students (Radel,

62 Sarrazin, Legrain, et al., 2009), whilst controlled primes were associated with

negative outcomes. Interestingly, Radel and colleagues combined the afferent and

efferent stages of priming in an academic setting, leading to the notion that

individuals are constantly susceptible to priming stimuli, even whilst performing

the priming activity itself (Radel, Sarrazin, Legrain, et al., 2009). In all cases, these

motivational manipulations were conducted without the participants’ awareness,

supporting the notion that the causality orientations and regulatory styles in self-

determination theory can influence behaviour without conscious processing

interference.

THE IMPORTANCE OF IMPLICIT MOTIVATION ON THE EFFECTS OF PRIMING

In all the papers relating to priming discussed, there is some variability in

terms of the magnitude of the priming effect. This may be due to the strength of the

prime, the priming procedures, and the relationship of the primed construct with

the dependent variables (Bargh, 1990). Researchers have proposed several

mediators and moderators which may influence the priming effect such as

mindfulness (Levesque & Brown, 2007; Radel, Sarrazin, Legrain, et al., 2009) and

gender (Hodgins et al., 2007). There is also a possibility that the strength of

implicit motivation influences the extent to which a motivation priming technique

alters affective and behavioural responses. The research conducted by Levesque

and Pelletier (Study 4; 2003) examined this issue; their findings suggest that

autonomous/control primes are more likely to be consequential when primed

individuals have no chronically accessible motivation. Priming a motivation that is

represented mentally, but not necessarily dominant (chronically accessible) on all

occasions, appears to raise the accessibility of the motivation in subsequent

activities. Likewise, priming a motivation that is already dominant is likely to have

63 little effect as the individual is already naturally inclined to behave in a manner

consistent with the motivation being primed. On the other hand, priming a concept

that is in opposition to the dominant motivation is likely to be ineffective as the

dominant motivation masks the effect of any prime. Levesque and Pelletier (2003)

found that priming effects were more pronounced for individuals with no

dominant motivational orientation. Thus, chronically accessible motivation is

another possible moderator to priming effects. Exciting opportunities are open to

investigate the interaction between implicit motivation and priming, but

individuals who are interesting in pursuing this line of research should be aware of

measurement problems that may hinder their progress.

IMPLICIT MEASURES OF MOTIVATION

Explicit processes have been extensively investigated using self-report

methods such as questionnaires, surveys, and individual or group interviews.

However, investigations into implicit processes have been somewhat limited by

the lack of comprehensive measurement instruments. Introspection as a way of

examining the strength and valence of an implicit process or construct is largely

invalid as individuals are proposed to have no (or limited ability) to access these

constructs in this manner (Nosek, 2007; Nosek, Greenwald & Banaji, 2007). Nosek

(2007) defines an implicit measure as one that reduces response controllability,

has a lack of intention, reduces awareness of the origin or meaning of the response,

and requires a high efficiency of processing. Steffans and Jonas (2010) supported

this definition but added that implicit measures are ‘indirect measures which rely

on response latencies or other indices of spontaneous trait association, the

activation of action semantics, or even real behaviour’ (pp. 1; Steffens & Jonas,

2010).

64

One method which meets some of the criteria for implicit measurement is

that of free style writing exercises. This method reduces impression management

and assesses constructs in a less contrived manner than traditional self-report.

McClelland and colleagues used a series of pictures to serve as the basis for

imaginative stories which are then coded for motivational content (McClelland,

Atkinson, Clark & Lowell, 1953). This technique has also been used by other

research groups, particularly to measure the implicit need for achievement (e.g.,

Schultheiss, 2001). Pennebaker (1997) discussed a technique whereby

participants were asked to write about themselves for a given amount of time

without editing their work. It was proposed that this process reduced inhibitory

processes associated with self-report and face-to-face interviews (Pennebaker,

1997). This method of construct assessment is perhaps somewhat more able to

assess implicit constructs, but there is still a wide scope for impression

management, and there exists a possibility that individuals cannot consciously

access implicit constructs with this technique (Greenwald & Farnham, 2000). This

method is also difficult to evaluate objectively and requires substantial training for

assessors.

Levesque and Pelletier (2003) and McLachlan and Hagger (2010) measured

chronically accessible motivation with a free-response task developed by Higgins,

King and Mavin (1982). To assess motivation, this task requires participants to list

up to ten reasons they have for engaging in a certain behaviour under a time

constraint, without editing the list. According to Higgins et al. (1982), the first two

or three responses are most indicative of the individual’s chronically accessible

constructs. Chronically accessible motives in an education setting (Levesque &

Pelletier, 2003) and an exercise setting (McLachlan & Hagger, 2010) were assessed

65 using this method. Both studies assessed chronically accessible motives rather

than motivational orientations, but coded these as being autonomous or controlled

according to self-determination theory. In both cases the motivation assessed

using this technique was associated with outcome variables commonly associated

with explicitly measured motivation (Levesque & Pelletier, 2003; McLachlan &

Hagger, 2010). Although this measure does not present as an implicit measure, it

inherently consists of elements which suggest its suitability for measuring implicit

constructs. There is a pressure to respond quickly and efficiently, and individuals

do not have an awareness of the importance of order as they list their ten motives.

This type of measure aligns strongly with the definition of an implicit measure

proved by Steffans and Jonas (2010).

A series of measures have been developed on the assumption that implicit

constructs can be inferred from behaviour (Greenwald, Banaji, Rudman, Farnham,

Nosek & Mellot, 2002). These measures use response time to stimuli presentation

tasks as a measure of the implicit construct in question (Craeynest, Crombez,

Deforche, Tanghe & De Bourdeaudhuij, 2008). One of the most extensively

researched and validated measures of this kind is the Implicit Association Test

(IAT; Greenwald, McGhee & Schwartz, 1998). The test measures response latency,

and compares the differences between two experimental, combination blocks of

the concept and attribute dimension. The test requires responses to two sets of

target stimuli and two sets of attribute stimuli, and scores are derived from

comparing response latencies of the two combinations of target and attribute

categories. Stimulus items are presented in the middle of the screen and the

participants must assign them to the correct category as quickly as possible by

selecting a key on the keyboard. The IAT has consistently been shown to have

66 greater reliability and validity than other implicit measures (Bosson, Swann &

Pennebaker, 2000; Cunningham, Preacher & Banaji, 2001; Teige, Schnabel, Banse &

Asendorpf, 2004). It has been used to assess attitudes (Greenwald & Banaji, 1995),

self-esteem (Greenwald & Farnham, 2000), and self-concept and identity (Banting,

Dimmock & Lay, 2009; Greenwald & Farnham, 2000).

A similar test to the IAT is the Go/ No-Go Association Task (Nosek & Banaji,

2001). This test also requires participants to assign stimuli to attribute and target

categories, but does not require a complementary or contrasting target category

(Nosek & Banaji, 2001). The test has been used to assess attitudes to objects (fruit

and bugs) and attitudes to in-group vs. out-group persons (Nosek & Banaji, 2001).

This task has been shown to effectively measure automatic preferences in these

situations, and is particularly useful to assess social cognitions towards targets

with no natural opposite category (as required by the IAT). The Extrinsic Affective

Simon Task (EAST; De Houwer, 2003) is also quite similar to the IAT, but for this

procedure colour is used to assess implicit attitudes. Participants must categorise

words written in white according to their valence and coloured words according to

their colour (Craeynest, Crombez, De Houwer, Deforche, Tanghe & De

Bourdeaudhuij, 2005; De Houwer, 2003). This task has successfully measured

attitudes towards food and physical activity (Craeynest et al., 2005; Craeynest et

al., 2008), and alcohol (De Houwer, Crombez, Kostner & N, 2004).

Two tasks less reliant of stimuli categorisation are the lexical decision task

(LDT; Meyer & Schvaneveldt, 1971; Wittenbrink, Judd & Park, 1997) and the

evaluative priming procedure (Fazio, Jackson, Dunton & Williams, 1995). The

evaluative priming task is based on the affective priming procedure developed by

Fazio and colleagues in 1986 (Fazio, Sanbonmatsu, Powell & Kardes, 1986). These

tasks rely on response time, but participants must identify the stimuli as a word or

67 non-word on the LDT, or evaluate the word for Fazio et al.’s task. Although both

tasks are designed to assess implicit social cognitions, a study by Wittenbrink, Judd

and Park (2001) found that the two tests varied in their ability to predict

stereotyping and prejudice, leading the authors to speculate that the design of an

implicit measure may assess implicit constructs in different ways. The LDT has

since been used to assess motivation, particularly intrinsic and identified

regulatory style as described in self-determination theory (Deci & Ryan, 1985a) by

Burton and colleagues (Burton, Lydon, D'Alessandro & Koestner, 2006). This study

and dual process models suggesting motives exist implicitly (e.g., Kehr, 2004) lend

support to the notion that other response time based implicit measures may be

appropriate for measuring implicit motivation.

IMPLICIT MOTIVATION AND PHYSICAL ACTIVITY

Physical activity is often performed without significant deliberation,

and implicit processes might be particularly predictive of such behaviour.

Moreover, many behaviours and judgments within an exercise session could be

influenced by implicit motivation. For example, the decision to renege on a

previously made exercise plan, the amount of effort invested in an activity, and the

time spent persisting in the activity may all be made without a large degree of

conscious awareness and influenced by motivation assessed with implicit

measures. There are also instances of unplanned incidental physical activity that

an individual may not dedicate sufficient cognitive resources to consciously

process their behaviour. Activities such as taking the stairs in favour of the lift and

self-selecting a faster walking pace during ‘non-exercise’ periods may also be

governed by implicit processes. In several recent investigations, stair use has been

increased by the use of simple posters (Kwak, Kremers, van Baak & Brug; Lewis &

68 Eves, 2011; van den Auweele, Boen, Schapendonk & Dornez, 2005). These studies

did not actively assess the public’s conscious processing of the information

presented on the posters but Lewis and Eves speculated that implicit processes

may have been activated based on the presence of the posters (Lewis & Eves, ,

2012).

Research relating to implicit constructs in health settings is increasing

rapidly in volume and diversity. Several investigations have been into measuring

social cognitions that are related to exercise. Physical activity attitudes have been

measured implicitly by several research teams and have been shown to predict

behaviour (e.g., Conroy, Hyde, Doerksen & Ribeiro, 2010; Craeynest et al., 2005;

Craeynest et al., 2008; Hyde, Doerksen, Ribeiro & Conroy, 2010). It has also been

shown that implicit attitudes are related to motivation, and measuring implicit

motivation effectively may strengthen professionals’ ability to predict physical

activity behaviour (Conroy et al., 2010).

The research focused on actually measuring implicit motivation is limited

however. To the researchers knowledge only one study has been published which

measures implicit motivation for physical activity (McLachlan & Hagger, 2010).

Whilst measurement of implicit motivation is somewhat constrained by the

measurement instruments, the success of measuring cognitions conceptually

related to physical activity is promising. To build on the findings of McLachlan and

Hagger (2010), the most promising method of measurement to assess implicit

motivation is probably the LDT used by Burton et al. (2006). However, given the

success of other implicit measures, investigation of other single-category

measurement tools (such as the GNAT) is worthy as exercise does not have a

natural ‘opposite’ category.

69

Priming research in the physical activity setting has also been limited.

Hodgins et al. (2006) found that in rowers, autonomous priming could improve

rowing time in a 500m split of a 2000m distance (a typical training exercise). This

was supported by Radel, Sarrazin and Pelletier (2009) who showed that following

autonomous priming, participants spent longer practising a motor task (a

physically demanding power ball exercise) when compared to a controlled priming

condition and a neutrally primed condition. Furthermore, this trend was replicated

when percentage of maximum heart rate was assessed, those primed

autonomously had a higher heart rate during the exercise. These two studies

reveal that priming in an effort to elicit behavioural effects in an exercise or sport

setting may be appropriate. Both studies assessed the effect of immediate

behaviour following the priming procedure, however, there is scope to examine

the behaviour of individuals throughout the priming process and in the short- and

longer-term following the priming task.

QUESTIONS ARISING FROM THE LITERATURE

Following the mainstream psychology research on implicit processes and

priming, some researchers have begun investigating exercise motivation from an

implicit perspective. There is sufficient evidence to indicate that motivation in an

exercise setting can be represented implicitly and may well be activated

automatically. However, the type of exercise behaviour that may be influenced by

priming and the way that behavioural and affective responses alter according to

the priming style is still largely unknown. Moreover, the role that strength of

implicit motivation has in exercise behaviour has not been extensively researched

and there are no reaction time based instruments developed to measure implicit

exercise motivation. It would be interesting to follow the lead of researchers such

70 as Levesque and Pelletier (Levesque & Pelletier, 2003) to not only measure implicit

motivation in an exercise setting, but investigate the interactive effects of

motivational priming and implicit exercise motivation in that setting. Priming

methods shown to alter behaviour and perceptions of behaviour exist, and the

procedures for developing implicit measures of social cognitions are well-

documented. The goal of this thesis is to investigate priming and implicit

motivation in an exercise setting from the perspective of self-determination

theory.

71

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85

CHAPTER 3: THE IMPACT OF AUTOMATICALLY ACTIVATED

MOTIVATION ON EXERCISE-RELATED OUTCOMES.

CHAPTER SUMMARY

This study examined the effect of motivational primes on participants

(N=171) during a cycling exercise task. Relative to participants primed with a

controlled motivational orientation, it was hypothesized that participants primed

for autonomous motivation would report greater feelings of enjoyment, effort, and

choice in relation to the cycling activity. Members of the autonomous group were

also expected to exercise for longer, exercise at a greater percentage of their heart

rate maximum, and report lower levels of perceived exertion in relation to the task.

Finally, participants primed with an autonomous orientation were hypothesized to

report greater intentions to exercise in the future. It was found that enjoyment was

higher for participants in the autonomy prime group relative to the controlled

prime group, as was percentage of heart rate maximum, intention to exercise, and

time cycled. Ratings of perceived exertion were higher for participants in the

controlled prime condition. Results highlight the importance of automatic

processes in activating motivation for exercise.

*This chapter is previously published in the Journal of Sport and Exercise Psychology

(Appendix A).

86

INTRODUCTION

Physical inactivity is undeniably one of the most modifiable risk factors for

a range of diseases and ailments that plague modern society. Local, national, and

international health agencies recommend specific amounts of physical activity, yet

these same health agencies report that actual levels of physical activity remain low

and insufficient for health benefits and maintenance of good health (ABS, 2009;

WHO, 2003) . Whilst adoption of physical activity is important, preventing drop-

out is another issue to address, with some reports indicating that approximately

50% of exercisers withdraw from exercise programs within six months (Dishman

& Buckworth, 1996). Many theories have been developed and examined in an

attempt to better predict and increase goal-directed exercise behavior and

adherence (thus preventing drop-out). These theories have examined intentions,

self-reported attitudes and perceptions of social norms (Ajzen, 1985; Ajzen &

Fishbein, 1980; Fishbein & Ajzen, 1975) , perceptions of self-efficacy (Bandura,

1977) and behavioral control (Ajzen, 1985), and motivation (e.g., Deci, 1975; Deci

& Ryan, 1985a, 1985b) as antecedents to goal directed behavior.

Self-determination theory (Deci & Ryan, 1985b) has been widely applied to

physical activity (see, e.g., Ryan & Deci, 2007) and used to increase exercise

frequency and adherence (e.g., Edmunds, Ntoumanis & Duda, 2008; Puente &

Anshel, 2010). The theory addresses locus of causality for motivation, types of

motivation, basic psychological needs, and the effects these constructs have on

well-being. Self-determination theory is comprised of several sub theories: the

cognitive evaluation theory (Deci, 1975; Deci & Ryan, 1980), organismic

integration theory (Deci & Ryan, 1985b; Ryan & Connell, 1989), causality

orientations theory (Deci & Ryan, 1985a), basic needs theory (Ryan & Deci, 2000)

87 and goal contents theory (Ryan & Deci, 2010). Many researchers have suggested

that motivation exists in intrinsic and extrinsic forms (e.g., deCharms, 1968), with

intrinsic motivation originating from the self, and extrinsic motivation being

derived from external factors. However, Deci and Ryan formalized the notion that

extrinsic motivation varied in terms of how internalized the external motives were.

The organismic integration theory (OIT; Deci & Ryan, 1985b; Ryan & Connell,

1989) of self-determination theory differentiates between four types of extrinsic

motivation: external, introjected, identified, and integrated regulation styles.

External regulation is the least internalized, whilst integrated regulation is almost

completely internalized and the motive is integrated into the individual’s values

and personality (Deci & Ryan, 1985b; Ryan & Connell, 1989). External and

introjected regulation are often grouped and referred to as controlled forms of

motivation, while identified regulation, integrated regulation, and intrinsic

motivation are often referred to as autonomous motivation. The relative autonomy

index (RAI; Markland & Ingledew, 2007) is a composite index used to incorporate

the strength of an individual’s autonomous motivation and controlled motivation

according to the results of the Behavioral Regulation in Exercise Questionnaire

(Markland & Tobin, 2004). Autonomous forms of motivation have been shown to

produce more adaptive behavioral responses, such as greater task persistence

(Pelletier, Fortier, Vallerand & Briére, 2001), increased levels of enjoyment and

positive affect (Edmunds et al., 2008), and improved performance (Gillet,

Vallerand, Amoura & Baldes, 2010). Controlled motivation tends to elicit drop-out,

negative affect, and maladaptive psychological responses (Edmunds, Ntoumanis &

Duda, 2007; Pelletier et al., 2001). Although these studies have been valuable in

guiding practice for increasing exercise behavior, discrepancies still exist between

the motivation people report and the behavior that is actually displayed.

88

Until recently, most researchers have operated under the assumption that

human behavior can be explained by conscious deliberation and reasoned

intention to engage in goal-directed action (e.g., Ajzen, 1985; Bandura, 1977; Deci

& Ryan, 1985b). Undoubtedly, deliberate, conscious processes can play an

important role in guiding behavior, but evidence is now mounting to indicate that

goal-directed behavior is often regulated by automatic processes (e.g., Bargh, 1990,

2005; Burton, Lydon, D'Alessandro & Koestner, 2006). Automatic processes occur

when there is a lack of awareness, control and/ or intention from the perceiver,

and a minimal draw on cognitive resources for the individual (Bargh, 1994). Bargh

(1990) was the first to comment on the automaticity of goal activation and pursuit

in his auto-motive model. Although evidence already existed to demonstrate that

goals could be pursued without awareness, Bargh’s argument was unique in that

he suggested that the entire goal process, from activation to pursuit, could unfold

without conscious intervention (Bargh, 1990). He argued that repeated

associations between a situation and a goal could eventually lead to automatic

activation of that goal in the situation. This automatic activation could then

produce the same effects as if the goal had been consciously chosen, and the

individual would have no awareness of having pursued it (Bargh & Chartrand,

1999).

Numerous studies have confirmed Bargh’s auto-motive model using the

priming paradigm. In these experiments, goal-related stimuli are presented to

participants either below the level of conscious perception (subliminal priming) or

above the level of conscious perception (supraliminal priming). In both cases, the

participants are unaware of the influence of the presented stimuli on their

subsequent behaviour and judgment. Support for the auto-motive model has been

provided by Chartrand and Bargh (1996), for example, who found that participants

89 who had been primed with an impression formation goal were subsequently able

to recall more information about an individual’s behaviour. In another study, Aarts,

Gollwitzer, and Hassin (2004) found that male participants were more willing to

help a female experimenter after they had read a short story in which the goal of

casual sex was salient. The existing body of empirical literature indicates that

automatically activated processes can effectively regulate goal directed behaviour

and trigger motivational qualities.

Most research supporting the auto-motive model has focused on the

automatic activation and pursuit of concrete goals, such as to evaluate, perform

well, or cooperate. In contrast to this, Levesque and Pelletier (2003) examined

whether more abstract and complex constructs could also be activated

automatically. In accordance with the causality orientations theory (Deci & Ryan,

1985a), Levesque and Pelletier (2003) investigated whether an individual’s

motivational orientation (an inherent tendency to be autonomous or controlled in

general), could be automatically activated and subsequently influence behaviour.

In their first study, Levesque and Pelletier found that people who had been primed

with an autonomy orientation performed better at a puzzle task than those primed

with a controlled orientation (referred to in their study as a heteronomous

orientation). Hodgins, Yacko, and Gottlieb (2006, Study 3) conducted a similar

study in a sporting context, and found that autonomy-primed rowers engaged in

less self-handicapping than rowers primed for controlled or impersonal

motivations. Additionally, the autonomy-primed participants subsequently rowed

faster than participants in the other two priming groups (Hodgins et al., 2006).

Most recently, Radel, Sarrazin and Pelletier (2009) provided support for the notion

that autonomous and controlled orientations could be automatically activated and

provide consequential effects in the context of exercise. They observed that the

90 subliminal priming of autonomous motivation led participants to perform better,

invest more effort, persist longer, and enjoy a novel and simple physical activity

task more than participants who had been subliminally primed with controlled

motivation.

A consistent feature of the aforementioned studies is that the researchers

have examined the effects of a priming task on a subsequent activity. Priming

usually consists of two distinct stages. The first stage, called the afferent stage, is

characterized by the presentation of stimuli to activate the associated memory

structures (when the act of priming actually occurs). The second stage, termed the

efferent stage, is where experimenters observe the responses to the stimuli

(Fiedler, 2003). The idea behind this strategy is that the afferent stage temporarily

increases the accessibility of the construct being primed, making it more likely to

be used in subsequent situations (Forster & Liberman, 2007). In the context of

exercise, however, many people consciously attend to a variety of stimuli in the

environment (e.g., magazines, television programs) while they are exercising, and

the extent to which such stimuli can influence exercise behavior via motivational

priming is yet to be investigated. Nevertheless, recent research by Radel, Sarrazin,

Legrain, and Gobancé (2009) indicates that priming effects might be expected even

when combining the afferent and efferent stages of priming. In this study, Radel

and colleagues subliminally primed students with autonomous or controlled

motivation by displaying words related to these motivations for 32 milliseconds on

lecture slides. Results of a class test after the lecture indicated that participants

who were low in mindfulness performed better after being primed with the

concept of autonomous motivation. Although the performance measure (test) was

administered after the priming procedure, the most likely explanation for these

results is that the students were influenced by the priming procedure during the

91 lecture. A similar strategy of combining the afferent and efferent stages of priming

(i.e., observing the effects of the prime whilst still priming) was adopted in the

current investigation to examine the effects of priming motivational orientations

on exercise. In the case of the present study, however, the priming was

supraliminal (i.e., participants were aware of the stimuli being presented but

unaware of its influence on behavior).

Only investigations by Radel, Sarrazin, and Pelletier (2009) and Hodgins et

al. (2006) have examined the effect of primed motivational orientations on

exercise behavior. Based on the notion that automatic activation of motivation can

elicit similar outcomes to when motivation is consciously activated (Pelletier et al.,

2001), we expected to witness increased adaptive responses amongst those

primed with autonomous motivation. More specifically, we expected to find that

autonomy primed participants would report lower ratings of perceived exertion

(RPE), cycle for longer, and report a greater intention to exercise in the future than

participants primed with controlled motivation. We also expected the autonomy

primed participants to work harder at the cycling task than those in the controlled

condition, as measured by heart rate. Differences in heart rate were expected

between the groups during a period in which the participants attended to the

scrambled sentence task while cycling, as well as during a period of cycling after

the completion of this task. Finally, similar to the study by Radel and colleagues

(Radel, Sarrazin & Pelletier, 2009), differences were expected between groups on

perceived choice, enjoyment, and effort for the task. We expected all these

differences to occur while controlling for the effect of self-reported behavioral

regulation (i.e., participants would be influenced by the prime irrespective of their

self-reported motivation).

92

METHODS

PARTICIPANTS

One hundred and seventy-one undergraduate sport science students (100

females, 71 males, Mage= 19.86 years, SD= 2.48) were recruited from an Australian

university in exchange for course credit. All participants were advised of the

voluntary nature of the research and gave written informed consent. Before

commencing, all participants completed a Physical Activity Readiness

Questionnaire (PAR-Q) to ensure that they were physically able to undertake a 30

minute cycling activity. One individual was unable to participate because of an

injury that prevented his/her engagement in cycling.

OVERVIEW OF PROCEDURES

The protocols observed in the study were approved by the School of Sport

Science, Exercise and Health Ethics Committee prior to the commencement of the

testing procedures. Students were first asked for their voluntary involvement in a

study of the effect of exercise on mood. Participants then completed a mood

questionnaire, were fitted with a heart rate monitor, and were advised that they

would cycle on stationary bikes for 30 minutes. In the first 10 minutes of cycling,

all participants completed a word scrambled sentence task which primed an

autonomous motivational orientation, a controlled motivational orientation, or no

motivational orientation. After completing this task, participants continued to

cycle until 20 minutes was reached. At this point, they were given a choice about

whether they wanted to continue cycling, and were told that despite the original

30 minute target, changes in mood would be detectable at 20 minutes. Participants

were reminded about the option of stopping at 25 minutes (if they had continued

93 to cycle), and those who continued to cycle were stopped after 30 minutes, allowed

to rest for a few minutes, and then completed a follow-up questionnaire.

MATERIALS AND MEASURES

WORD SCRAMBLE SENTENCE TASK.

The chosen supraliminal priming procedure consisted of 25-item scrambled

sentence tasks that were intended to prime an autonomous orientation, a

controlled orientation, or no motivational orientation (Appendix B). These tasks

were based on the priming procedure developed by Srull and Wyer (1979), in

which participants formed sentences using four out of five words presented in a

scrambled order. Similar procedures have been used recently by Levesque and

Pelletier (2003) and Hodgins, Brown, and Carver (2007). In order to avoid

suspicion about the purpose of the tasks, some neutral sentences were included in

the autonomous and controlled priming tasks. Similar to the work of Levesque and

Pelletier, these tasks involved a ratio of 4 priming sentences to 1 neutral sentence.

In all conditions, only one grammatically correct sentence could be formed from

the five words presented. Examples of the scrambled sentences include: book we

the read top (neutral), feel are interested I usually (autonomous), and feel are

pressured I usually (controlled).

QUESTIONNAIRE MEASURES.

All questionnaire measures are presented in Appendix C of this thesis.

MOOD. The abbreviated 24 item version of the Profile of Mood States

questionnaire (POMS-A) assessed participants’ mood both before and after cycling.

The measure included 4 items for each of the six subscales (anger, confusion,

depression, fatigue, tension and vitality) identified in the original POMS (McNair,

94 Lorr & Droppleman, 1971). This particular abbreviation has been extensively

validated for use with adult populations (Terry, Lane & Fogarty, 2003; Terry, Lane,

Lane & Keohane, 1999) and is used commonly in exercise settings (see Berger &

Motl, 2000).

PERCEIVED EXERTION. Immediately after exercise, Borg’s rating of perceived

exertion scale (RPE; Borg, 1982) was used to obtain a rating of perceived exertion

for each person. Borg’s scale is commonly used to assess the intensity of exercise

for young- middle aged, moderately fit individuals. It has shown to correlate highly

with heart rate (r = .80- .90). The scale begins at 6 (no exertion at all) and ends at

20 (maximal exertion). Participants were asked to indicate their general level of

exertion for the cycling period.

BEHAVIORAL REGULATION. The BREQ-2 (Markland & Tobin, 2004) was used to

assess participants’ behavioral regulation according the self-determination

theory’s organismic integration theory. The reliabilities for each of the subscales

for this measure have been shown to be strong (e.g., introjected regulation, α= .80).

This scale includes 19 items on a 5 point Likert scale ranging from 1 (not at all

true) to 5 (very true). The scores can be used to form a composite relative

autonomy index (RAI) to indicate the extent of autonomous (or controlled)

regulation for exercise behavior (Markland & Ingledew, 2007). The RAI is obtained

by applying a weighting to each behavioral regulation subscale and then summing

these weighted scores. As the BREQ-2 includes amotivation items, we used

Markland and Ingledew’s RAI calculation formula: -3*amotivation + -2*external

regulation + -1* introjected regulation + 2*identified regulation + 3*intrinsic

motivation.

INTRINSIC MOTIVATION. Items from the Intrinsic Motivation Inventory (IMI;

Ryan, 1982) were chosen to measure enjoyment (7 items), effort (5 items) and

95 choice (7 items). These items were rated by participants on a 7 point Likert scale

(1= not true at all, 7= very true).

INTENTION. In a similar way to previous physical activity studies (e.g.

Caperchione, Duncan, Mummery, Steele & Schofield, 2008; Everson, Daley &

Ussher, 2007), intention was measured using an average of 2 scales developed

following theory of planned behavior guidelines (TpB; Ajzen, 1985). The items

asked participants to rate their agreement to the following statements: I will try to

exercise regularly over the next two weeks; I intend to exercise regularly over the

next two weeks. These items were measured on a 7 point Likert scale (1= strongly

disagree, 7= strongly agree). The two items showed a high internal consistency (α=

.92).

HEART RATE

Heart rate was measured using Polar Heart Rate Monitors, and information

was downloaded using the Polar Team System and analyzed using Polar Precision

SW 3.0 software. The monitor was strapped to the chest to allow for continuous

recording of heart rate. One hundred thirty three participants were included for

analysis (excluding 30 participants due to missing or incomplete heart rate data,

and 6 with incomplete RAI scores). The researchers were able to intermittently

check to ensure the monitor was still recording heart rate, but some participants

experienced extended periods of signal drop-out and were excluded from further

analysis. Other participants recorded several peaks of impossibly high magnitudes,

indicating problems with the heart rate monitor contact point with the body. These

participants were also excluded from the analyses. The size of each group

remained similar, with 45 participants in the controlled group and 44 in each of

the autonomous and neutral priming groups. Average heart rates were calculated

96 for the total exercise time, and separate averages were calculated for the first 10

minutes of exercise (the afferent stage when participants were completing the

priming task) and the second 10 minutes of exercise (the efferent stage after the

completion of the priming task). These average heart rates were calculated as a

percentage of maximum heart according to Londeree and Moeschberger’s (1982)

formula of 220- age (% maximum heart rate= Average heart rate/ (220-age)* 100).

This formula is commonly used to predict maximal heart rate among moderately

trained adult individuals.

TEST OF AWARENESS

A test of awareness was used to ascertain whether the participants were

able to correctly suspect the relevance of the priming activity to the exercise task,

and whether this suspicion caused any behavior change. The questions were based

on the funneled debriefing procedure used by Chartrand and Bargh (1996). Five

items (including 2 yes/no responses and 3 open questions) were used to survey

the participants in regards to what they thought the purpose of the study was,

whether they saw a connection between the exercise and the cycling, and whether

their cycling was affected by the scrambled sentence task.

PROCEDURES

Participants arrived at the exercise venue and, after giving informed

consent, were fitted with Polar heart rate monitors. They completed the PAR-Q and

the POMS-A mood questionnaire at this point. In order to control for procedural

effects on the outcome measures, the order of experimental stages was counter-

balanced at this point. Half of the participants started with the written measures

for behavioral regulation and causality orientations before starting the cycling. The

other half started with the cycling task and completed these same written

97 measures after the cycling. In either case, a distraction period of 15 minutes was

given between the two tasks. No differences were observed between participants

based on the order of administration of the tasks, so the procedures starting with

the cycling will be described from this point on.

Participants were asked to adjust their Lemond RevMaster Pro stationary

bikes to a comfortable configuration, and were then advised to cycle at their own

pace for 30 minutes. They were asked to refrain from interacting with the

researcher under the pretence that talking would unnecessarily increase their

heart rate, and they were told the primary objective of the research was to

examine the effect of exercise on mood.

At the commencement of the cycling, participants were asked to pedal as

fast as they could for 15 seconds before settling into a self-selected pace. Once

participants had settled into this pace, the researcher asked them to complete the

word scrambled sentence task which had been attached to the handlebars of their

bicycle. The number of participants completing each version of the scrambled

sentence task was relatively equal (nneutral= 56, nautonomous= 57, ncontrolled= 57). The

instructor explained that the scrambled sentence task was part of an investigation

being conducted by the English Department at the University. Participants were

asked to indicate by raising their hand when they had completed the task. The

average time for completing the scrambled sentence task was 9.66mins (SD= 0.66),

and there were no differences between groups for completion of the task (F= 1.80,

p= .12). After completing the word scrambled sentence task, the cycling activity

continued without any further distraction.

After cycling for 20 minutes, the researcher informed participants that

expected mood changes would be observed after 20 minutes, that they could stop

cycling if they wished, and any remaining time could be used to shower or relax.

98 Participants who chose to continue riding were reminded about the option of

stopping again at 25 minutes. At both the 20 minute and 25 minute time points, the

researcher used a scripted dialogue to ensure a lack of bias in the options being

relayed to the participants. The time was recorded for any participant indicating

that they wished to stop. Any participants still cycling at 30 minutes were told to

stop. Irrespective of their stopping time, participants were immediately asked to

rate their level of exertion on the RPE scale. Following this, they removed their

heart rate monitor and were able to take a few minutes to relax. Finally,

participants completed the BREQ-2 and GCOS, the second POMS-A mood

questionnaire (in keeping with the cover story of the research), the IMI items, the

intention items, and completed the funneled debrief.

RESULTS

TEST OF AWARENESS

Each participant was screened to ensure that no relationship was perceived

between the priming procedure and the other components of the experimental

protocol. Importantly, participants did not report altering their exercise behavior

or their evaluations of the exercise based on the content of the scrambled

sentences. The large majority of participants reported that the purpose of the

research was to detect the effect of exercise on mood, which was the cover story of

the research. No participant indicated any awareness of the true purpose of the

study. Twelve students suggested a connection between the priming activity and

mood, but this suggested link was not substantiated by empirical data. More

specifically, one-way ANOVAs were conducted between priming groups for each

post-exercise mood state and no differences between groups were detected (all F

values < 2.00, all ps> .10).

99 PRIMING EFFECTS ON PRIMARY DEPENDENT VARIABLES

To examine any differences between the priming groups, between groups

ANCOVAs were conducted which allowed for age, gender, and explicit behavioral

regulation score to be statistically controlled for. Following correct ANCOVA

protocol (Field, 2009; Miller & Chapman, 2001), one-way between groups ANOVAs

and chi-square analyses were conducted to ensure that there were no differences

across groups for each of the covariates (age, gender, and behavioral regulation

RAI score). These preliminary analyses revealed no differences between priming

groups for age (F(2, 167)= 1.27, p= .283), RAI (F(2,165)=1.44; p= .239), or gender

(controlled χ2(1)= 0.42, p= .061; autonomous χ2(1)= 2.20, p= .138; neutral χ2(1)= 3.50,

p= .515), with the means presented in Table 3.1. All means and standard deviations

for the dependent variables are shown in Table 3.2, and a summary of the ANCOVA

results is presented in Table 3.3.

Separate 3x1 between-groups ANCOVAs were conducted to examine

potential differences between priming groups in time cycled and rating of

perceived exertion, using age, gender, and RAI as the covariates. Different priming

methods elicited differences in both outcome measures. Results revealed that RAI

scores were significantly related the amount of time cycled by participants. After

controlling for the RAI scores, there were significant differences between priming

groups. Bonferroni post hoc analyses revealed that the controlled group cycled for

less time than both the autonomous group (p<.001) and the neutral group

(p=.010). RPE was significantly different across groups with the specific

differences between the autonomous and controlled prime groups (p= .050).

In relation to the self-report measures, ANCOVA and post-hoc analyses

revealed several significant differences between the groups. There was a

100 significant effect of priming group on self-report ratings of enjoyment, with the

significant difference lying between the controlled and autonomous priming group

(p= .029). Effort significantly differed across groups, and Bonferroni post hoc

analyses revealed a significant difference between the autonomous and neutral

group (p= .027). For the self-report choice measure, there was no significant effect

of priming group after controlling for the covariates. Gender and RAI scores both

had a significant effect of the level of choice reported, however group means were

consistently high.

Table 3.1. Characteristics of Priming Group Participants.

Note. No statistical significant differences were observed between groups for each variable.

Participants’ intention to exercise also differed between priming groups.

The RAI scores had a significant influence on intention to exercise, and after

controlling for the RAI scores, the priming conditions had a significant effect of

intention to exercise. Bonferroni post hoc analyses revealed that the participants

in the controlled prime group reported significantly lower intentions to exercise

than both the neutral (p=.005) and autonomous (p= .002) groups.

Variable Controlled Neutral Autonomous Total N= 59 N=56 N= 55 N= 170

Gender: Number of males (%)

27 (45.8%) 21 (37.5%) 22 (40.0%) 70 (41.2%)

Age in years (SD) 20.03 (2.50) 19.42 (1.45) 20.11 (3.18) 19.85 (2.48)

Relative Autonomy Index (SD)

11.02 (3.79) 11.21 (4.17) 12.17 (3.44) 11.46 (3.82)

101 HEART RATE ANALYSIS

We had hypothesized that any differences between groups in terms of heart

rate would exist in both the afferent and efferent stages of priming. A mixed model

ANOVA, using time as the within groups variable and priming group as the

between groups variable, revealed significant main effects for time F(1,132)=

79.85, p<.001, and priming group F(2,132)= 8.21, p<.001. Bonferroni post hoc

analyses revealed that the participants primed with autonomous motivation

experienced higher percentages of heart rate maximum than the participants

primed with controlled motivation (p<.001) and the neutral group participants (p=

.032). Figure 3.1 illustrates the differences observed over time between groups.

Figure 3.1. Average Percentage of Maximum Heart Rate Over Time.

To account for any possible influence of covariates, an ANCOVA was

conducted to control for age, gender, and RAI scores. The average percentage of

maximum heart rate for the total exercise time was used. As expected, gender had

a significant influence on percentage of age-predicted heart rate max, with females

exhibiting higher heart rates. After controlling for the covariates, priming group

102 had a significant effect on the average percentage of maximum heart rate

experienced by the participants. Post hoc Bonferroni analyses showed that the

autonomously primed group exhibited higher average percentages of maximum

heart rate than both the neutral (p= .017) and controlled (p< .001) priming groups.

Table 3.2. Mean Scores and Standard Deviations for Dependent Variables in

Priming Group Participants.

Variable Controlled Neutral Autonomous

Time Cycled (mins)

N 59 56 55

Mean (SD) 27.35 (3.68) 28.92 (2.39) 29.80 (0.70)

RPE

N 59 56 55

Mean (SD) 12.83 (2.14) 12.29 (2.00) 12.04 (1.32)

Enjoyment

N 59 56 55

Mean (SD) 3.47 (1.25) 3.81 (0.99) 4.11 (1.26)

Effort

N 59 56 55

Mean (SD) 4.08 (1.43) 3.70 (1.39) 4.35 (1.07)

Choice

N 59 56 55

Mean (SD) 5.73 (1.37) 5.64 (1.26) 6.19 (0.80)

Max HR for total time (%)

N 46 45 44

Mean (SD) 60.36 (10.19) 63.50 (12.26) 69.57 (9.22)

Intention

N 59 56 55

Mean 6.24 (0.85) 6.62 (0.53) 6.68 (0.54)

103 Table 3.3. ANCOVA Results for Dependent Variables Using Sex, Age and RAI Scores as Covariates with Prime Group as the Fixed

Factor.

Variable

Sex Age RAI Priming Group

F(df) p Partial

η2 F(df) p Partia

l η2 F(df) p Partia

l η2 F(df) p Partia

l η2

Time Cycled (mins) 2.85 (1,162) .093 .02 3.55 (1,162) .061 .02 4.28 (1,162) .040 .03

11.85 (2,162)

<.001 .13

RPE 0.15 (1,162) .704 .00 0.09 (1,162) .762 .00 0.03 (1,162) .859 .00 3.24 (2,162) .042 .04

Enjoyment 0.41 (1,162) .525 .00 0.94 (1,162) .333 .01 0.33 (1,162) .567 .00 3.45 (2,162) .034 .04

Effort 0.06 (1,162) .816 .00 0.01 (1,162) .916 .00 0.62 (1,162) .431 .00 3.75 (2,162) .026 .04

Choice 4.14 (1,162) .043 .03 0.01 (1,162) .917 .00 19.09 (1,162) <.001 .11 2.28 (2,162) .105 .03

Max HR for tot. time (%) 9.07 (1,127) .003 .07 1.84 (1,127) .178 .01 0.13 (1,127) .721 .00 8.80 (2,127) <.001 .12

Intention 3.57 (1.162) .061 .02 3.51 (1,162) .063 .02 22.48 (1,167) <.001 0.12 7.52 (2,162) .001 .09

104

DISCUSSION

Several key findings emerged that have meaningful implications for self-

determination theory and the current knowledge on priming. Similar to past

research (Hodgins et al., 2006; Levesque & Pelletier, 2003; Radel, Sarrazin, Legrain,

et al., 2009; Radel, Sarrazin & Pelletier, 2009), the current findings suggest that

motivational orientations can be activated outside consciousness. Our test of

awareness showed that participants were unaware of the link between the prime

and the activity, indicating that the observed effects occurred below the threshold

of consciousness. The differences between the priming groups were consistent

with differences observed in other self-determination theory studies where

motivation has been consciously activated (see, e.g., Ryan & Deci, 2007). In

general, the autonomously primed group reported more adaptive responses and

displayed positive behavioral tendencies when compared to the controlled and

neutral priming groups. For example, as expected, participants in the autonomy

prime condition displayed higher levels of task enjoyment. Researchers conducting

previous investigations have found that individuals experiencing autonomous

motivation tend to report higher levels of task enjoyment whether that motivation

be activated consciously (e.g., Puente & Anshel, 2010) or nonconsciously (e.g.,

Radel, Sarrazin & Pelletier, 2009). In terms of effort expended in the task, a

significant difference was observed between the autonomous and neutral priming

groups, leading the researchers to conclude that autonomous priming may be the

most beneficial in terms of encouraging increased effort. This is in line with the

findings of Radel and colleagues (Radel, Sarrazin & Pelletier, 2009), who found

greater amounts of effort being expended in a task when participants had been

primed with autonomous motivation.

105

Differences in immediate performance outcomes were also observed, with

those primed with controlled motivation cycling for a significantly shorter period

of time than those primed with autonomous motivation. In many situations

involving exercise, there will be opportunities for individuals to choose the length

of their workout or their involvement in exercise in addition to what is asked of

them by trainers. Findings such as these suggest that individuals primed with

autonomous motivation will choose to continue to engage in exercise longer than

individuals primed with controlled motivation. This increased level of persistence

when experiencing autonomous motivation has been observed when the

motivation has been consciously activated (e.g., Deci & Ryan, 2000) or

automatically activated (Levesque & Pelletier, 2003; Radel, Sarrazin & Pelletier,

2009)

The controlled priming group in this study reported a lower intention to

exercise in the immediate future compared with the autonomous and the neutral

priming groups. The finding that priming can guide conscious decision processes

relating to exercise (in this case forming an intention to exercise) is supported by

Dimmock and Banting (2009). These authors agreed with Jaccard and Blanton’s

(2007) argument that implicit processes can act as distal variables in the theory of

planned behavior. The positive influence of autonomous primes of explicit

intention to exercise in a self-determination theory framework is somewhat

unique to this study. Dijksterhuis, Chartrand, and Aarts (2007) have provided a

convincing argument that automatic cognitive processes can influence conscious

deliberation associated with goal setting. A variety of strategies could be

recommended as a result of the finding in the present study that exercise

intentions differed between priming groups. For example, Petty, Barden, and

Wheeler (Petty, Barden & Wheeler, 2009) advocate the use of central route

106 processing immediately after peripheral route processing to obtain long-term

changes in unmotivated audiences. Petty et al. (2009) indicate that central route

processing describes the processing of information in a very conscious and

introspective manner, whereas peripheral route processing involves the

processing of information without the commitment of many cognitive resources. In

relation to exercise, trainers might wish to be strategic in the timing of goal setting

activities with clientele, such that goals relating to future exercise might be set

after exercise in which autonomous, rather than controlled, motivation has been

primed.

The current research examined the influence of primed motivational

orientations on physiological responses during exercise. It was found that

autonomously primed individuals exerted themselves more than participants in

the neutral or controlled prime group. An interesting finding was that the priming

effect was observed at both the afferent and efferent stages of priming. Analyses

revealed that the autonomous priming group worked at a higher percentage of

maximal heart than the controlled and neutral priming group. This trend existed

during the first 10 minutes of exercise (the afferent stage of priming) and the

second 10 minutes (the efferent stage of priming). This evidence that priming may

be effective during both the afferent and efferent stages is quite unique. Perhaps

most interesting, however, was that the group primed with an autonomy

orientation worked harder at the cycling task despite reporting lower perceptions

of exertion than the other groups. To our knowledge, this is the first time that

physical measures of exertion and perceptions of exertion have been compared

following a priming procedure. From a practical perspective, this has important

ramifications for behavioral adherence. Relative to exercisers who experience low

levels of exertion, individuals who feel over-exerted may decrease their frequency

107 or duration of exercise or drop-out altogether. Indeed, Ekkekakis and colleagues

found that perceptions of increased levels of exertion can produce negative

affective consequences (Ekkekakis, Hall & Petruzzello, 2004), and potentially

reduce future exercise behavior. Our finding indicates that autonomy primes may

reduce these potentially detrimental effects of increased RPE.

Another implication of the present study relates to association and

dissociation attentional strategies during exercise. Association refers to the

direction of attention toward task oriented cues, whereas dissociation refers to an

attentional focus that is unrelated to the experience of the exercise being

performed (Stevinson & Biddle, 1999). By asking participants to complete the

priming procedure whilst exercising, we essentially encouraged dissociation in this

present investigation. Research on association and dissociation strategies has

typically compared the effects of the two strategies. Association is often related to

faster pace, for example, whereas dissociation is typically related to greater

endurance and lower perceptions of exertion (Hutchinson & Tenenbaum, 2007;

Masters & Ogles, 1998). Broad conclusions relating to association and dissociation

strategies are somewhat inconclusive in terms of which strategy is best for

exercising, but results from the present investigation indicate that significant

differences in outcomes might be evident within each of these broad strategies.

More specifically, asking participants to dissociate to scrambled sentence tasks had

varied effects on exercise intensity, so the content of the dissociative thoughts may

influence whether dissociation is productive or not. Priming autonomous

motivation during a period of dissociation may not only be positive whilst the

exerciser is dissociating, but the priming effects might remain consequential

during a subsequent phase of association. A recent review by Salmon, Hanneman,

and Harwood (2010) provides support for the notion that individuals can associate

108 and dissociate in a single session of exercise. In a similar way to Radel, Sarrazin,

LeGrain, et al. (2009), the current results seem to suggest that the priming effects

can be detected during both the afferent and efferent stages of priming. For

exercise, this is important as supraliminal priming during exercise would require

the individual to dissociate at least during the afferent stage of priming, even if

only briefly. Despite these encouraging findings, more research is encouraged to

further investigate the effect of primes during an exercise task. Employing a

procedure to ensure absolute absorption in a priming task would be a useful

addition to the literature in this regard. Although the participants in the present

study were absorbed in a scrambled sentence task for the first ten minutes of

exercise, the extent to which their attention was broken at different stages of this

period was not measured.

Past theorizing and research has indicated that the effect of primes might be

moderated by such factors as mindfulness (Radel, Sarrazin & Pelletier, 2009),

chronic motivational orientation (e.g. Levesque & Pelletier, 2003), and mood (e.g.

Schwarz & Clore, 1996). Our investigation indicated that there were no differences

between priming groups in mood after the exercise, with all participants reporting

small improvements in mood compared to before the exercise. It is possible,

however, that positive moods not captured by the POMS-A might have been

influenced by the primes. Only one of the six mood states examined in the POMS-A

is positive (vitality). Other investigations in this area might wish to include other

measures of mood, in addition to measures for other proposed moderators, such as

mindfulness. Another fruitful avenue of future research relates to the influence of

autonomous and controlled motivation primes on social mimicry. Controlled

motivation reflects an orientation to be governed by external directives and

internal pressures, whereas autonomous motivation reflects regulation on the

109 basis of personal goals and interests. Consequently, the intensity of exercise

adopted by an individual primed for controlled motivation might be more

influenced by the exercise intensity adopted by others in the environment. This

effect might occur without the individual being aware that their behavior was

influenced by others around them. The current study presented a priming

technique which was very laboratory oriented. More ecologically valid priming

techniques would be of interest to trainers working with individuals aiming to

increase their exercise levels. Priming using verbal interaction, signage or reading

material may be possible; however, these techniques need to be investigated

further.

Thus, the present study adds to a small body of research on the effects of

motivational priming on exercise, but abundant research opportunities are

available for those interested in this area. As it stands, priming autonomous

motivation has positive, adaptive responses for an individual’s immediate exercise

intensity, perceptions of exercise, and intention to exercise in the future as

opposed to priming controlled motivation.

110

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115

CHAPTER 4: THE MEASUREMENT AND OUTCOMES OF IMPLICIT SELF-

DETERMINATION IN EXERCISE.

CHAPTER SUMMARY

The role of implicit exercise motivation on physical activity and judgments

of this activity were assessed. Participants (N=101) completed two implicit

measures – a Go/ No-Go Association Task and a Lexical Decision Task – to assess

implicit exercise motivation. It was found that the Lexical Decision Task predicted

important exercise-related outcomes independent of scores on relevant traditional

self-report measures. More specifically, an implicit autonomy index derived from

the Lexical Decision Task predicted the amount of time cycled by participants, the

intensity at which they cycled, and their future exercise behaviour. The Go/ No-Go

Association Task did not predict any of the outcome variables tested, but

correlated with the explicit measure of exercise motivation. The results indicate

that after considering self-report questionnaires, implicit measures, particularly

the Lexical Decision Task, can explain exercise behaviour.

116

INTRODUCTION

Widespread communication of the benefits of physical activity has enabled

many people to appreciate the virtues of an active lifestyle (Bylina et al., 2006), but

a significant proportion of the population remain insufficiently active. This

apparent incongruence between attitudes and behaviour is not unique to exercise.

Ajzen (2005) , for example, has commented on the lack of symmetry between self-

reported attitudes and behaviour for a multitude of behaviours, including studying,

racially prejudiced behaviour, and medical adherence. One explanation for this

divergence between attitudes and behaviour relates to methodologies used in

previous studies. Traditionally, attitudes and other cognitive constructs have been

measured using self-report instruments in which conscious introspection guides

responses. A problem with these measures is that self-presentation strategies may

distort the results, particularly when the focus activity is seen as a socially

desirable behaviour (Craeynest, Crombez, Deforche, Tanghe & De Bourdeaudhuij,

2008; Schwarz, 1999). The self-reporting of attitudes might also be influenced by

factors that are less associated with conscious manipulation, such as item wording

and order (e.g., Ajzen, 2002, 2005; Sudman, Bradburn & Schwarz, 1996). A

compelling argument has recently been forwarded to indicate that many cognitive

constructs either cannot be accessed via conscious introspection, or that conscious

access to them is limited (Greenwald, McGhee & Schwartz, 1998; Wittenbrink, Judd

& Park, 2001). Finally, evidence is accumulating to suggest that these implicit

cognitive constructs have behavioural consequences (e.g., Banting, Dimmock, &

Lay, 2009; Greenwald & Banaji, 1995; McLachlan & Hagger, 2010). For example,

Petty and colleagues (e.g., Petty, Barden, & Wheeler, 2009; Petty & Wegener, 1999)

have indicated that when an old attitude is rejected and superseded by a new

117 attitude, the old attitude may still exist in a dormant state and influence ongoing

experiences. In addition to attitudes, stereotypes; self-esteem; motivations and

prejudices may be assessed as implicit cognitive constructs (e.g., Levesque &

Pelletier, 2003; Greenwald, Banaji, Rudman, Farnham, Nosek, & Mellot, 2002;

Greenwald, McGhee, & Schwartz, 1998), and one of the lenses through which

implicit motivation can be measured and assessed is offered by self-determination

theory (see Dimmock & Banting, 2009).

Self-determination theory (SDT; Deci & Ryan, 1985) suggests that

individuals require satisfaction of three basic psychological needs (autonomy,

competence and relatedness) for growth (Deci & Ryan, 2000). The theory also

advocates two types of motivation, extrinsic and intrinsic, although this theory

differs from other motivational theories in that it distinguishes between types of

extrinsic motivation. Extrinsic motivation is categorized into four types of

behavioural regulations: integrated, identified, introjected and external (Deci &

Ryan, 1985). Integrated and identified regulatory styles are associated with higher

amounts of self-determination and the regulation of behaviour is highly

internalized despite being dependent on the outcomes of the activity (Deci & Ryan,

1985). Both integrated and identified regulation are often grouped with intrinsic

motivation and called autonomous motivation, a highly internalized and personally

endorsed behavioural driver which promotes psychological need satisfaction (Deci

& Ryan, 1985). Introjected and external regulatory styles involve lower degrees of

self-determination, have a low degree of internalization, and are often categorized

together as controlled motivation (Deci, Eghrari, Patrick & Leone, 1994; Deci &

Ryan, 1985; Markland & Tobin, 2004). Controlled motivation is often associated

with lower psychological need satisfaction and lower well-being (Deci & Ryan,

1985). Self-report measurement scales, such as the Behavioural Regulation in

118 Exercise Questionnaires (BREQ and BREQ-2 (Markland & Ingledew, 2007;

Markland & Tobin, 2004), can be used to create a relative autonomy index by

comparing the self-reported strength of autonomous motivation to controlled

motivation.

An abundance of theoretical and empirical work has highlighted the

importance of measuring implicit, as well as explicit, attitudes and motivation (see

Dimmock & Banting, 2009). It is commonly found that implicit and explicit

motivational constructs do not necessarily align (Thrash, Elliot & Schultheiss,

2007; Pang & Schultheiss, 2005), and this lack of congruence can have

consequences in terms of well-being and behaviour (Baumann, Kaschel & Kuhl,

2005; Kehr, 2004). Kehr (2004) for example, found that discrepancies between

implicit and explicit motives were negatively associated with subjective well-being,

and that such discrepancies were related to declines in volitional strength.

Furthermore, Kehr indicated that individuals who possessed large discrepancies

between implicit and explicit motives required higher degrees of self-regulation

for a certain action or decision. Kehr alluded to the presence of a dual systems

approach on motivation, an idea that has been forwarded by others. For instance,

Strack and Deutsch (2004) indicated that impulsive and reflective systems impact

behaviour differently and that behaviour is often governed by the compatibility

between these two systems. More specifically, they suggested that there are

significant behavioural and motivational implications stemming from antagonistic

and collaborative relationships between reflective and impulsive processes.

The need to assess implicit as well as explicit motivation has also been

supported by Burton, Lydon, D’Alessandro, and Koestner (2006) , who assessed

differences in outcomes between intrinsic and identified motivations in an

119 education context. Although explicit measures of the constructs were used for their

first two studies, the researchers utilised an implicit measure (a lexical decision

making task) of intrinsic and identified regulation in their final investigation. The

authors revealed an interaction effect between implicit identified regulation and

explicit identified regulation in the prediction of academic performance. More

specifically, students that were low on both types of identification had significantly

lower exam grades than students in the other three groups (low implicit/high

explicit; high implicit/ low explicit; high implicit/high explicit). The academic

performance of these other three groups did not differ significantly. In discussing

their findings, Burton et al. (2006) suggested that autonomous regulations guide

behaviour in an automatic as well as a self-conscious manner, and they

recommended further work on the topic of implicit motivation.

IMPLICIT MEASURES

A variety of implicit measurement techniques have been devised and

include the coding of imaginative writing concerning the self (Pennebaker, 1997)

and others (e.g., Murray, 1938; McClelland, Atkinson, Clark & Lowell, 1953;

Schultheiss, 2001). A second suite of implicit measures has been developed which

primarily rely on reaction times and differences in latencies when comparing

responses to various categories of stimuli (Craeynest et al., 2008; Greenwald,

Banaji, Rudman, Farnham, Nosek & Mellot, 2002). Such methods lower participant

controllability, reduce participants’ awareness of the origin of their response,

and/or require high processing efficiency and speed (Nosek, 2007). These qualities

align closely with the criteria for automaticity (unintentional, unconscious,

uncontrollable, efficient and fast), as defined by Bargh (1994). Insofar as

motivation can function effortlessly and without conscious awareness (Bandura,

120 1977), implicit measures of motivation, such as that used by Burton et al. (2006),

are important to determine the contribution of all forms of motivation to

behaviour and affect. Implicit measures have been used to assess attitudes

(Greenwald et al., 1998), self-esteem (Greenwald et al., 2002), stereotypes (Banaji

& Greenwald, 1995; Rudman, Greenwald & McGhee, 2001), self-concept (Banting,

Dimmock & Lay, 2009; Greenwald et al., 2002), and motivation in an education

setting (Burton et al., 2006) , but an implicit measure of exercise motivation is yet

to be developed.

Several methodologies have been developed to examine implicit cognitive

processes. The most popular and widely used measures include the Implicit

Association Task (IAT), the related Go/ No-Go Association Task (GNAT), and the

Lexical Decision Task (LDT). In the current study, the GNAT and LDT are explored

as potential measurement tools for implicit exercise motivation. Unlike the GNAT

and LDT, the IAT would rely on participants making comparisons between exercise

and an ‘opposite’ concept category, rendering this procedure as problematic (see

Dimmock & Banting, 2009).

RESEARCH AIMS

The purpose of this research was to modify two implicit measurement tools

to assess self-determined exercise motivation, and to examine the predictive utility

of these measures for exercise behaviour and judgments. It was hypothesized that

implicit autonomy scores derived from the GNAT would correlate positively with

the LDT relative autonomy scores. Also, based on the models of Strack and Deutsch

(2004) and Kehr (2004), as well as on empirical work in academic settings (Burton

et al., 2006; Levesque & Pelletier, 2003), we expected that high implicit

autonomous motivation on both measures would predict more positive

121 behavioural and affective responses regarding exercise, and that this influence

would be observed while controlling for self-reported explicit motivation.

Specifically, it was expected that the implicit motivation measures would provide

unique prediction of exercise enjoyment and effort, as well as behavioural

outcomes including the intention to exercise, exercise duration and intensity, and

actual instances of behaviour in the future.

METHODS

PARTICIPANTS

One hundred and one undergraduate sport science students (59 females, 42

males, Mage= 20.05 years, SD= 1.12) were recruited from an Australian university

in exchange for course credit. All participants were advised of the voluntary nature

of the research and gave written informed consent. In order to participate,

individuals needed to be able to cycle for an extended period of time and be

sufficiently fit to exercise at a moderate intensity as indicated on a physical activity

readiness questionnaire (PAR-Q; Canadian Society for Exercise Physiology, 2002).

MATERIALS AND MEASURES

QUESTIONNAIRE MEASURES

BEHAVIOURAL REGULATION. The BREQ-2 (Markland & Tobin, 2004), which is

based on self-determination theory’s organismic integration theory, was used to

assess participants’ behavioural regulation. This scale includes 19 items on a 5

point Likert scale ranging from 1 (not at all true) to 5 (very true). The BREQ-2

measures intrinsic motivation (4 items; α = 0.86), identified regulation (4 items; α

= 0.73), introjected regulation (3 items; α = 0.80), external regulation (4 items; α =

122 0.79) and amotivation (4 items, α = 0.83) (Markland & Tobin, 2004). The scores

can be used to calculate a composite relative autonomy index (RAI) to indicate the

extent of autonomous (or controlled) regulation for exercise behaviour (Markland

& Ingledew, 2007). The RAI is obtained by weighting each of the subscale totals

and summing these values. We followed the formula used by Markland and

Ingledew in their RAI calculation: (-3 * amotivation) + (-2 * external regulation)

+ (-1 * introjected regulation) + (2 * identified regulation) + (3 * intrinsic

motivation).

INTRINSIC MOTIVATION. Items from the Intrinsic Motivation Inventory (IMI;

Ryan, 1982) were chosen to measure enjoyment (7 items; α = 0.78) and effort (5

items; α = 0.84) (Tsigilis & Theodosiou, 2003). These items were rated by

participants on a 7 point Likert scale (1= not true at all, 7= very true). The

participants were instructed to rate each of the statements based on the cycling

activity that they had just completed.

INTENTION. Similar to previous physical activity studies (e.g. Caperchione,

Duncan, Mummery, Steele & Schofield, 2008; Everson, Daley & Ussher, 2007),

intention was measured using an average of two scales developed following theory

of planned behaviour guidelines. The items asked participants to rate their

agreement for the statements I will try to exercise regularly over the next week and I

intend to exercise regularly over the next week. These items were measured on a 7

point Likert scale (1= strongly disagree, 7= strongly agree), and showed high

internal consistency (α = .92).

123 BEHAVIOURAL MEASURES

EXERCISE INTENSITY. Participants were able to select a level of intensity on a

stationary exercise bicycle. All participants initially started on level 5 but were told

to adjust the bike to their preferred intensity. The researcher noted the level that

the participant adjusted the bike to and recorded if any changes were made after

the first minute of cycling. The level selected at the one minute time point was used

for analyses as no participant adjusted the cycling intensity after the first minute.

Higher levels reflected a greater degree of resistance and more effort required

from the participant.

EXERCISE BEHAVIOUR. Participants were contacted via e-mail one week after

the testing session. They were asked to recall the number of times they had

engaged in exercise in the previous 7 days. Participants were asked to list the day,

the type of activity, and the amount of time that they had exercised. Exercise

sessions of less than 15 minutes were excluded from analyses. Response rates

were good, with 99 participants responding to the e-mail within two days. The

number of exercise sessions greater than 15 minutes was used for analyses.

IMPLICIT MEASURES

GO/NO-GO ASSOCIATION TASK (GNAT). The GNAT was designed based on the

attribute only GNAT developed by Nosek and Banaji (Study 3; 2001). The GNAT

quantifies an implicit construct by comparing the sensitivity (or accuracy) between

one target category and two opposite poles of an attribute dimension (e.g., good/

bad, me/ not me). The attribute only GNAT removes the need for a comparison

target category. In this case, the target category was ‘exercise’ and the two

attribute categories were ‘autonomous’ and ‘controlled’ motivation. The GNAT is a

computer-based reaction time task which requires participants to hit the space bar

124 (“Go” response) if a stimulus item belongs to either the target category or the

presented attribute category within a predetermined period of time. Other

stimulus items belonging to the other attribute category required the participant

to do nothing (“No-Go” response) until the deadline time was reached. The

underlying assumption of the GNAT for the measurement of implicit constructs is

that individuals will be more accurate when responding to a stimulus that they

naturally associate with both the target and selected attribute. For example, if the

target is ‘exercise’ and the attribute category is ‘autonomous’, individuals who are

autonomously motivated for exercise will respond more accurately when the

stimulus presented relates to either autonomous motivation or exercise, rather

than controlled motivation.

The stimuli chosen to represent each category were chosen by 5 psychology

postgraduate students from a short list of 15 words as the most representative of

their respective categories. The words in the short list were taken from scales

commonly used to measure autonomous and controlled motivation in self-

determination theory research (e.g., Enjoyable, Pressured, Guilty, and Valuable). In

each category, five stimuli items were selected (see Table 4.1 for details).

Table 4.1. Stimuli used for the GNAT categories.

Target Category (Exercise)

Attribute Category 1 (Autonomous Motivation)

Attribute Category 2 (Controlled Motivation)

Stimuli

Athletic Interesting Pressured

Keep Fit Enjoyable Forced

Exercise Satisfying Mandatory

Fitness Worthwhile Compelled

Training Important Obligated

125

Three response deadline times (833ms, 750ms and 666ms) were used for

each pair of blocks. These deadlines were based on the recommendations of Nosek

and Banaji in the GNAT development guidelines (Nosek & Banaji, 2001). Scores

were calculated based on differences in sensitivity in the autonomous-exercise and

the controlled-exercise pairings. Individuals who more automatically associate

autonomous motivation with exercise should achieve a greater sensitivity score for

the blocks that require ‘Go’ responses for the autonomous motivation and exercise

stimuli. The GNAT consisted of three practice blocks to familiarize participants

with the words being used, and 6 experimental blocks. The experimental blocks

included an autonomous motivation-exercise and controlled motivation-exercise

pairing for each of the three deadline times. The first 16 trials of each block were

for practice and the final 60 trials were used for analyses.

LEXICAL DECISION TASK. The LDT was based on the task developed by

Wittenbrink, Judd, and Park (2001). The task involves multiple word pairs being

presented on the computer screen, the first being a priming stimulus followed by a

target letter strings. The current investigation followed a supraliminal priming

LDT protocol, which presents the priming stimulus item long enough for the

participant to consciously process it. In this task, the priming stimulus items

represented the concept of ‘exercise’ (exercise and fitness) and the target letter

strings represented the four types of behavioural regulation as defined by the

BREQ-2 (intrinsic motivation, identified regulation, introjected regulation and

external regulation). The task works on the assumption that certain word

combinations will be easier for different participants depending on their implicit

motivation. For example, participants with a high level of intrinsic motivation for

exercise will be able to respond faster to exercise priming stimuli and intrinsic

motivation target letter strings as that individual naturally and automatically

126 associates exercise with the target letter strings (e.g., fun and challenge). Likewise

those who experience controlled motivation in relation to exercise would respond

faster to exercise primes and external regulation target stimuli (such as forced and

pressured).

The stimulus items were also chosen by exercise psychology postgraduate

students and appear in Table 4.2. Neutral primes were used for comparison

purposes (garden and basket). According to protocol, positive and negative letter

strings were also used, as were non-word letter strings. These additional strings

also appear in Table 4.2. The amount of non-word letter strings was three times

the amount of other category letter strings in an effort to prevent anticipation of

word string trials.

Table 4.2. Target letter strings used for the LDT

Intrinsic Motivation

Identified Regulation

Introjected Regulation

External Regulation

Positive/ Negative

Nonwords (examples)

Sti

mu

li

Fun Important Guilt Pressured Flower Mather

Interesting Valuable Ashamed Forced Kitten Scire

Challenge Beneficial Pride Coerced Music Pajer

Enjoyable Worthwhile Embarrassed Controlled Angry Kniges

Exciting Useful Approval Prescribed Spider Podding

Following a similar protocol to Wittenbrink et al. (1997), a fixation point (*)

appeared on the screen for 600ms, followed by the priming stimulus for 300ms

and then the target letter string. The target letter string remained on the screen

until the participant responded. Participants were instructed to classify the word

pairs as either both words or one non-word by pressing the appropriate key (A or

127 L on a United Kingdom configured keyboard). Participants were instructed to place

their fingers over these keys at the start of the procedure. The LDT consisted of

one practice block with ten trials and three experimental blocks, each with 64

trials.

PROCEDURES

Participants completed a questionnaire one week before the main study

protocol. The questionnaire included the BREQ-2 (Markland & Tobin, 2004) and

several demographic items. Administering this questionnaire before participants

were required to complete the main study protocol reduced the likelihood that the

explicit exercise motivation questions would alter the participants’ responses in

the implicit measures. On the day of the testing, participants arrived at the exercise

laboratory and completed the PAR-Q to ensure they were able to safely complete

the protocol. All participants were tested individually in the laboratory.

The researcher informed the participants that the purpose of the research

was to assess the effect of mental fatigue on exercise perceptions, and that the

computer-task was designed to require large amounts of concentration on a

generic task. The participants then began the computer-based GNAT and the LDT,

which took approximately 20 minutes to complete. They were invited to take

regular breaks in between trials within the tasks, and were also encouraged to take

an extended break between the LDT and the GNAT (which were presented in a

counter-balanced order).

A break was given at the conclusion of the computer tasks, after which

participants were given information about the cycling exercise. Participants were

verbally instructed to cycle for “ABOUT 15 minutes or 2 kilometres” at a speed

they felt comfortable with. Thus, instructions were vague as to the time or distance

128 that would be spent cycling. Pilot testing had shown that participants would easily

cycle 2 kilometres within the 15 minute time frame. The researcher did not

interact with them once the participant had started to cycle. When the participant

indicated that they had finished, the researcher recorded the time cycled and the

level of intensity the participant had exercised at. Participants were then

encouraged to take a drink break, after which they completed items from the IMI

(Ryan, 1982) measuring enjoyment and effort.

DATA ANALYSIS

GO/ NO-GO ASSOCIATION TASK

A sensitivity score was calculated for autonomous motivation and

controlled motivation. This was calculated by assessing the difference between the

proportion of hits to false alarms, and was the scoring method used by the authors

of the seminal GNAT paper (Nosek & Banaji, 2001). A response is termed a “hit” if

the participant correctly responded to signal stimuli (correct Go response),

whereas a false alarm occurred when a noise item was categorized as signal

(incorrect Go response). Three participants were excluded from analyses as they

scored less than zero for either autonomous or controlled motivation. Scoring zero

(or less) indicates that the individual was unable to distinguish between signal and

noise, or was not completing the task as instructed. To gauge whether participants

were more autonomous or controlled in their motivation for exercise, the

difference between the autonomous and controlled sensitivity scores were

calculated so that higher scores indicated higher autonomous motivation, and

negative scores indicated more controlled motivation.

129 LEXICAL DECISION TASK

Wittenbrink and colleagues (Wittenbrink, Judd & Park, 1997) assessed

implicit scores based on differences in reaction time. The difference between the

response time for the neutral prime with a target word string for a certain

motivation type and the exercise prime with the same motivation type word string

was calculated. Trials where the response time was less than 150ms were

excluded from analyses as these scores indicated anticipation from the participant

(occurred in 0.13% of all trials). Trials where the response time was greater than

1500ms were also excluded from analyses as these scores indicated that the

participant was distracted temporarily from the task (occurred in 0.80% of all

trials). In our analyses, only correct responses were included. Higher scores

indicated that the exercise prime, relative to the neutral prime, facilitated

responses to the motivation stimuli. This method provided scores for intrinsic

motivation and identified, introjected and external regulations. Following the

formula used by Mullan, Markland, and Ingledew (1997) for the BREQ, these

scores were used to calculate an implicit RAI score. This formula does not consider

amotivation ([-2 * external regulation] + [-1 * introjected regulation] + [identified

regulation] + [2 * intrinsic motivation]).

RESULTS

PRELIMINARY ANALYSES

Descriptive statistics and Pearson’s correlations were obtained to examine

the dependent variables and three types of exercise motivation (the implicit RAI,

the GNAT score and the explicit RAI as measured by the BREQ-2). Each measure of

motivation was assessed for normality via inspection of histograms. All measures

130 were determined to be normally distributed. All statistics are presented in Table

4.3.

EXPLICIT BEHAVIOURAL REGULATION

Independent sub-scale scores of the BREQ-2 were correlated to assess the

suitability of creating the RAI score. Table 4.4 shows the specific values of the

subscale correlations and the expected matrix pattern observed (see Markland &

Tobin, 2004). To assess the typical relationships of self-reported behavioural

regulation, Pearson’s bivariate correlations were conducted between the

dependent variables (time cycled, level of intensity, enjoyment, effort, intention to

exercise and future exercise frequency) and the five subscales of the BREQ-2

(amotivation, external, introjected, and identified regulation, and intrinsic

motivation). These analyses revealed few significant correlations between the

variables (see Table 4.4 for specific values).

131 Table 4.3. Descriptive statistics and Pearson’s correlation values for dependent

variables.

Intercorrelations

Variable Mean SD 1 2 3 4 5 6 7 8

1 Explicit RAI

10.98 4.07 1

2 Implicit RAI

35.09 234.01 -.03 1

3 GNAT Score

.17 .17 .28* -.08 1

4 Time Cycled

14.13 2.00 .15 .39** .10 1

5 Level of Intensity

5.38 1.37 .06 .35** .10 .09 1

6 Enjoyment

4.21 1.21 .03 .23* -.11 -.03 -.05 1

7 Effort

4.48 1.10 .08 .16 .11 .17 -.01 .26* 1

8 Intention to Exercise

6.05 1.26 .21* -.05 .24* .23* -.13 .16 .07 1

9 Exercise Frequency

4.22 1.92 .12 .33* .10 .26* .21* .05 .08 -.01

Note. *p < .05; **p < .001

132 Table 4.4. Correlation values of regulation types as measured in the BREQ-2 with

implicit measures and outcome variables.

Note. * p < 0.05; **p < .001

COMPARING IMPLICIT MEASURES

Given that the implicit measures were designed to measure the same

implicit process, we expected to see some degree of correlation between the

scores. A Pearson’s bivariate correlation analysis revealed no significant

Variable 1 2 3 4 5 6 7

1 Intrinsic motivation

1

2 Identified regulation

.55** 1

3 Introjected regulation

.01 .14 1

4 External regulation

-.27** -.14 .34** 1

5 Amotivation .16 -.18 .01 .16 1

6 GNAT score .26* .25* .07 -.16 -.15 1

7 Implicit RAI .12 .04 .01 .16 .20* -.08 1

8 Time cycled .15 .15 -.11 -.02 .03 .10 .39**

9 Level of intensity .12 .11 -.02 -.05 .22* .10 .35**

10 Enjoyment .14 .03 .06 .19 -.15 -.11 -.05

11 Effort .08 .11 .07 -.07 -.02 .11 .17

12 Intention to exercise

.09 .23* -.09 -.01 -.25* .24* -.05

13 Exercise frequency

.19 .09 -.05 .02 .05 .10 .33**

133 correlation between the GNAT sensitivity score and the implicit RAI score

(calculated from the LDT scores, see Table 4.5 for regulation type correlation

values). We also compared the implicit scores to the explicit measures of

motivation. Correlations were conducted between the GNAT score, the LDT

implicit RAI index, the separate behavioural regulation scores from the LDT, and

RAI scores from the BREQ-2. Only the GNAT correlated significantly (albeit

weakly) with the explicit RAI, r = .28, p =.006.

Table 4.5. Pearson’s correlation values for Lexical Decision Task regulation types.

Intercorrelations

Variable Mean (ms)

SD 1 2 3 4

1 Intrinsic Motivation

7.08 65.93 1

2 Identified Regulation

3.99 56.92 .35** 1

3 Introjected Regulation

-1.17 67.78 -.21* -.11 1

4 External Regulation

-18.21 78.13 -.29** -.27** .10 1

Note. * p < 0.05; **p < .001

PREDICTIVE CAPABILITY OF GNAT

A similar procedure to that used by Burton and colleagues (2006) was

undertaken to assess whether the GNAT scores, in conjunction with the explicit

RAI results, were predictive of any of the dependent variables. A series of

hierarchical regression analyses were then conducted, with age and gender being

entered into Step 1 to control for any influence from inherent differences in the

134 sample. Although the age range was relatively small, the majority of participants

were in a transition from a structured high school physical activity environment to

the unstructured physical activity environment of adulthood which is a time of

considerable change in terms of physical activity and sport participation (Eime,

Harvey, Brown & Payne, 2010). As such, age was controlled for in all regression

analyses. The GNAT score, explicit RAI and interaction between the two measures

were entered into Step 2 for each dependent variable (time cycled, intensity of

cycling, enjoyment, effort, intention to exercise and future exercise frequency).

Only intention to exercise was significantly predicted by the explicit and implicit

measures after controlling for age and gender (∆ R2 = .13, ∆ F = 4.27, p = .007).

Partial correlations were then conducted to ascertain the individual

contributions of the implicit GNAT and explicit measures. No partial correlations

were detected except for the intention to exercise with the GNAT score (pr = .24, p

= .03) and intention to exercise with the explicit RAI (pr = .31, p = .004). Another

series of hierarchical regressions analyses were then conducted with age and

gender entered into Step 1, individual GNAT scores and explicit RAIs entered into

Step 2 and the GNAT score * explicit RAI interaction term entered into Step 3. The

motivation measures only predicted intention to exercise, with a significant

increase in predictive ability between Step 1 and Step 2 of the model (∆ R2 = .12, ∆

F = 5.67, p = .005). The significant predictive variable was the GNAT score (β = .23,

t = 2.16, p = .033), although this prediction is not statistically significant if a

Bonferroni adjustment is performed. All results for the final series of regression

equations are included in Table 4.6.

135 Table 4.6. Hierarchical Regression Analyses for Dependent Variables when GNAT Score and Explicit RAI are used as the Predictor Variables.

Variable Adj R2 ∆R2 F (p) St. β t p

Time Cycled

1: Age

Gender

.04 .06 2.73 (.071) -.24

-.08

-2.26

-.72

.026

.472

2: GNAT score

Explicit RAI

.04 .03 1.95 (.110) .09

.11

.80

.98

.424

.331

3: GNAT*Explicit RAI .03 .00 1.57 (.177) .04 .39 .697

Level of Intensity

1: Age

Gender

.14

.16 8.45 (<.001) -.01

-.40

-.11

-4.11

.913

<.001

2: GNAT score

Explicit RAI

.13 .00 4.24 (.004) -.01

.06

-.07

.60

.948

.550

3: GNAT*Explicit RAI .12 .00 3.42 (.007) .05 .51 .614

Enjoyment

1: Age

Gender

-.00 .02 .81 (.448) .07

.12

.68

1.12

.499

.267

2: GNAT score

Explicit RAI

-.01 .01 .70 (.593) -.12

.04

-1.10

.37

.277

.713

3: GNAT*Explicit RAI -.03 .00 .56 (.734) -.00 -.03 .977

Effort

1: Age

Gender

-.02 .01 .25 (.782) .08

.01

.70

.12

.488

.904

2: GNAT score

Explicit RAI

-.01 .03 .69 (.602) .08

.12

.67

1.07

.506

.286

3: GNAT*Explicit RAI -.03 .00 .55 (.737) .02 .19 .850

136

Table 4.6 (cont’d). Hierarchical Regression Analyses for Dependent Variables when GNAT Score and Explicit RAI are used as the Predictor Variables.

Variable Adj R2 ∆R2 F (p) St. β t p

Intention to Exercise

1: Age

Gender

-.02 .01 .24 (.791) -.05

-.06

-.49

-.51

.626

.612

2: GNAT score

Explicit RAI

.08 .12 2.97 (.024) .23

.19

2.16

1.78

.033

.078

3: GNAT*Explicit RAI .09 .02 2.67 (.028) -.13 -1.19 .238

Exercise Frequency

1: Age

Gender

-.00 .02 .89 (.416) -.12

-.08

-1.15

-.77

.254

.446

2: GNAT score

Explicit RAI

-.00 .02 .93 (.454) .13

.05

1.13

.45

.262

.652

3: GNAT*Explicit RAI -.01 .00 .77 (.574) .05 .43 .669

PREDICTIVE CAPACITY OF LDT

An implicit RAI score was calculated from the LDT response latencies for

intrinsic motivation and identified, introjected and external regulations. To

examine how much the dependent variables could be predicted by the implicit RAI,

another series of hierarchical regression analyses were conducted. Again, age and

gender were entered into the first step of the analyses to control for any potential

influence on the dependent variables. Explicit RAI, implicit RAI and the explicit RAI

* implicit RAI interaction were entered in Step 2. The regression analysis was

conducted for the all dependent variables (time cycled, level of intensity,

137 enjoyment, effort, intention to exercise and future exercise frequency). By

assessing the R2 change values from Step 1 to Step 2 we were able to assess

whether the explicit and implicit RAI values contributed to the prediction of the

outcome variables. The three behavioural measures (time cycled, intensity and

future exercise frequency) were all significantly predicted by the implicit and

explicit RAIs.

To examine the unique role of implicit and explicit relative autonomy (RAI),

partial correlations were conducted for each dependent variable, controlling for

age and gender. The partial correlation for explicit RAI and intention to exercise

was significant (r= .27, p =.012). Controlling for age and gender, implicit RAI

correlated significantly with time cycled (r = .40, p<.001), intensity (r = .36, p

<.001), enjoyment (r = .24, p =.022) and future exercise frequency (r = .31, p

=.003).

Then, in hierarchical regression analyses for each of the dependent

variables, age and gender were entered into Step 1 to control for any inherent

differences according to these variables. In Step 2 the implicit RAI and explicit RAI

scores were entered, and in Step 3 the interaction term of implicit RAI and explicit

RAI was entered. For time cycled, Step 2 significantly improved the model (∆ F =

10.06; p < .001). The significant predictive variable was implicit RAI (β = .40, t =

4.22, p < .001). There was no significant interaction effect. Similar findings were

observed for level of intensity (∆ F = 7.63; p = .001), with implicit RAI being the

significant predictor (β = .34, t = 3.76, p < .001), and future frequency (∆ F = 5.175;

p = .008) with implicit RAI again being the significant predictor (β = .31, t = 3.08, p

= .003). Neither intensity nor future frequency was predicted by the interaction

term. For intention to exercise, the model was significantly improved by the

138 addition of Step 2 (∆ F = 3.60; p = .031), with explicit RAI being the sole significant

contributor (β = .27, t = 2.64, p = .010), although significance in this instance

should be interpreted with caution (see Abdi, 2007). No dependent variables were

significantly predicted by the interaction of implicit RAI and explicit RAI. See Table

4.7 for the final series of regression results.

139 Table 4.7. Hierarchical Regression Analyses for Dependent Variables when LDT

score and Explicit RAI are used as the Predictor Variables.

Variable Adj R2 ∆R2 F (p) St. β t p

Time Cycled

1: Age

Gender

.04 .06 2.68 (.074) -.23

-.08

-2.23

-.76

.028

.451

2: LDT score

Explicit RAI

.20 .18 6.64 (<.001) .40

.15

4.22

2.15

<.001

.111

3: LDT* Explicit RAI .19 .00 5.35 (<.001) -.16 -.63 .531

Level of Intensity

1: Age

Gender

.13 .15 7.80 (.001) .00

-.38

.02

-3.94

.982

<.001

2: LDT score

Explicit RAI

.24 .13 8.29 (<.001) .34

.10

3.76

1.16

<.001

.248

3: LDT* Explicit RAI .23 .00 6.59 (<.001) .09 .36 .721

Enjoyment

1: Age

Gender

.00 .02 1.07 (.348) .07

.14

.64

1.36

.525

.178

2: LDT score

Explicit RAI

.04 .06 1.86 (.124) .24

.02

2.28

.20

.025

.842

3: LDT* Explicit RAI .03 .00 1.50 (.197) .11 .39 .701

Effort

1: Age

Gender

-.02 .01 .21 (.809) .07

.01

.65

.07

.517

.944

2: LDT score

Explicit RAI

.00 .04 .94 (.445) .16

.11

1.52

1.04

.132

.300

3: LDT* Explicit RAI -.01 .00 .74 (.593) .01 .03 .975

140 Table 4.7 (cont’d). Hierarchical Regression Analyses for Dependent Variables when

LDT score and Explicit RAI are used as the Predictor Variables.

Variable Adj R2 ∆R2 F (p) St. β t p

Intention to Exercise

1: Age

Gender

-.02 .00 .20 (.821) -.05

-.05

-.49

-.43

.625

.670

2: LDT score

Explicit RAI

.04 .08 1.90 (.117) -.05

.27

-.44

2.63

.662

.010

3: LDT* Explicit RAI .03 .00 1.53 (.190) .09 .31 .756

Exercise Frequency

1: Age

Gender

.00 .02 1.02 (.366) -.12

-.10

-1.13

-.95

.258

.341

2: LDT score

Explicit RAI

.09 .11 3.14 (.018) .31

.10

3.08

.97

.003

.336

3: LDT* Explicit RAI .08 .00 2.56 (.033) .15 .55 .582

DISCUSSION

The main purpose of this study was to examine the value of assessing

implicit exercise motivation to predict exercise-related cognition, affect, and

behaviour. Results indicated that the LDT produced scores that were predictive of

immediate and future exercise behaviour. This prediction was significant after

considering the effects of the explicit measures of motivation. The LDT produced

implicit RAI scores that predicted immediate exercise behaviour (duration and

intensity) and future exercise frequency. These findings were all observed after

controlling for the RAI calculated from the BREQ-2. Interestingly, the GNAT did not

predict any of the exercise related outcome variables, but did correlate with the

141 explicit measure of exercise motivation. The LDT did not produce scores which

were correlated with the explicit measure of motivation, which has been the case

in other research concerning implicit and explicit constructs (e.g., Banting et al.,

2009; Thrash, Elliot & Schultheiss, 2007).

It was hypothesized that the GNAT and the LDT would produce scores

which were correlated. This was based on the assumption that both methods of

implicit measurement assessed the same automatic processes. However, the low

correlation between these measures indicated that they may not actually assess

the same construct in the same way. Wittenbrink et al. (2001) found that their two

implicit measures of attitudes correlated in different patterns with the explicit

measures of the same attitudes. The authors suggested that these differences may

be due to the measures assessing different aspects of an individual’s racial attitude,

a possibility that has been supported by others (e.g., Eagly & Chaiken, 2007;

Rhodes & Courneya, 2003). In a similar vein, the two implicit measures of

motivation used in the present study might assess different components of

motivation. Given that the LDT predicted many of the variables commonly

associated with higher levels of autonomous motivation in exercise, the LDT may

measure an aspect of motivation that the GNAT was unable to detect. The implicit

assessment of cognitive constructs warrants further investigation to understand

the mechanisms by which these constructs operate. Likewise the calculation of

indices or scores based on these implicit measures should be the subject of further

investigation. After finding discrepancies in the results of two implicit judgment

tasks, Wittenbrink and colleagues suggested that the type of prejudice being

assessed by the two implicit measures was different. The discrepancy between the

two measures used the in current study emphasizes the importance of

142 understanding the ways in which each type of implicit measurement assesses the

construct being investigated.

In the present study, the data for the implicit measures was analysed

according to recommendations by the authors who developed each technique.

There is some scope for a different type of analysis of the data, however.

Incorporating error penalties [as seen in the Implicit Association Test, (Greenwald,

Nosek & Banaji, 2003)], for instance, may be an appropriate way of accounting for

the accuracy and speed of an individual completing the implicit task. In the current

investigation, a sensitivity score (assessing accuracy) in the GNAT was compared

to average response latencies (assessing speed) in the LDT. This discrepancy may

be a reason behind the low correlation between the two implicit measures. Also,

the standard IAT protocol requires participants to be eliminated if more than 10%

of the trials are less than 300ms, as this would indicate they are anticipating more

than 10% of the trials. These steps could potentially be included in future

calculations of both GNAT and LDT scores.

The prediction of all behavioural choices was improved by considering the

implicit RAI score produced from the LDT. These findings support many dual

process theories which suggest that implicit processes may facilitate behaviour

with or without subsequent conscious awareness. The results of the current study

indicate that traditional theories based on self-report measures alone may be

improved by considering implicit aspects of psychological constructs, in particular

implicit motivation. However, these computer based tasks are limited by the

requirement that single words are used as the stimulus items, an issue that creates

difficulties when designing these procedures to measure complex motivations. In

the current study, word choice was guided by a scrutiny of the literature in self-

143 determination theory and by selection methods with sport psychology graduate

students. Other implicit testing techniques have used picture stimulus items with

positive results (e.g., Dimmock, Hallett & Grove, 2009; Sriram & Greenwald, 2009),

and some studies have used free-response measures based on Higgins, King, and

Mavin’s (1982) measure of accessible constructs (Levesque & Pelletier, 2003;

McLachlan & Hagger, 2010). If words are to be used in an implicit test for

motivation, our recommendation is that careful attention is given to word choice

for the regulatory styles. No other text is available to contextualise or explain the

word, and so it must stand alone as a representative stimulus for the category

being assessed. The complexity of regulation styles makes word selection a

difficult but important process. Word choice is likely to be different according to

cultural group, age and even education level. Researchers are recommended to

engage in pilot testing and to carefully consider the target participant population’s

characteristics when selecting the stimulus items.

Including implicit measures to comprehensively assess psychological

constructs such as motivation appears to have some value, especially in terms of

behavioural outcomes. However, more work should be done to evaluate the

psychometric properties of the implicit measures. Test-retest reliabilities, internal

consistency and predictive validity could all be assessed to improve confidence

when reporting the findings of implicit measures. In this study a RAI score was

calculated to give a single indicator of implicit motivation (as measured by the

LDT). This calculation process warrants further investigation of the weightings

applied to individual regulation scores in order to develop an index that is relevant

to the construct being measured. In the BREQ (Markland & Tobin, 2004) the

weightings were applied on the assumption that intrinsic explicit motivation was

144 twice as autonomous as identified regulation, and that external regulation was

twice as controlling as introjected regulation. Investigation into the individual

contributions of the implicit facets of motivation/ behavioural regulation is

worthwhile to construct an index specific to implicit measurement. It would also

be a fruitful avenue of research to investigate how environmental stimuli may

affect an individual’s response on an implicit measure. Research has already

established that primes presented above or below the threshold of consciousness

can influence motivation and behaviour (Hodgins, Yacko & Gottlieb, 2006;

Levesque & Pelletier, 2003; Radel, Sarrazin, Legrain & Gobancé, 2009; Radel,

Sarrazin & Pelletier, 2009). The extent to which the implicit measures of exercise

motivation used in the present study produce consistent scores across time and

across settings is therefore worthy of future research.

The BREQ-2 did not significantly predict any outcome variables concerning

behaviour in this experiment. The poor predictive power of the explicit measure of

exercise motivation was unexpected. This may have been due to the consistently

high responses from the participants, resulting in a ceiling effect. There may be

considerable impression management on the BREQ-2 from the participants, who

were sports science students, and considerably high explicit motivation to exercise

as this is a concept repeatedly mentioned throughout their course. This makes the

implicit RAI very interesting as in this population it did predict the behavioural

outcome variables. Future research may include a wider selection of the

community to assess the generalisability of these results. These findings are not

intended to question the value of explicitly measuring behavioural regulation in

exercise setting as it has consistently been shown to predict behavioural outcomes

(Conroy, Hyde, Doerksen & Ribeiro, 2010; Markland & Ingledew, 2007; Markland &

Tobin, 2004). In this particular sample of very active individuals, for the fairly

145 generic exercise task, explicit motivation may not be as useful as other measures.

Additionally, the BREQ-2 measures motivation to exercise, not motivation to cycle

on a stationary bicycle. The regulation strategies the participants may have

employed to engage in the laboratory based cycle task are likely to be very

different from the regulation processes used to initiate and maintain self-selected

exercise behaviour. This proposition further indicates the need to conduct studies

of implicit motivation in more applied, real-world settings with a more diverse

sample.

CONCLUSIONS

This research aimed to use the LDT and the GNAT to assess implicit

motivation in exercise. Findings indicated that the LDT can predict several

immediate and future behavioural outcomes in the exercise domain. The GNAT did

not predict any behavioural or affective variables, yet it was the only measure that

correlated with the explicit measure of motivation. Future research is required to

examine the psychometric properties of implicit measures and the validity of their

use in other exercise settings with a more general population.

146

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150

CHAPTER 5: DO MOTIVATION PRIMING EFFECTS VARY AS A

FUNCTION OF IMPLICIT MOTIVATIONAL ORIENTATION?

CHAPTER SUMMARY

This chapter uses the implicit measure of motivation developed in Chapter

4 to investigate the interaction between motivational primes and implicit

motivational orientation. Numerous experiments on priming as well as the results

from Chapter 3 indicate that motivation primes can influence behaviour without

conscious awareness of the individual. However, more research is needed to

investigate the extent to which such primes are effective for people with different

motivational orientations. Participants (N= 59) completed an implicit measure of

motivation and either an autonomous, controlled or neutral priming task before

completing a cycling task. Priming group predicted heart rate, exercise duration

and rating of perceived exertion. Implicit motivation predicted intention to

exercise, exercise duration and average heart rate. No significant interactions were

observed between priming group and implicit motivation.

151

INTRODUCTION

External stimuli when exercising, or engaging in any type behaviour, can

influence an individual’s behavioural performance and perception of that

performance in a variety of ways. According to multiple dual-process models, some

information will guide behaviour and decisions via conscious deliberation; other

information, on the other hand, will be processed through a fast implicit

processing system which closes its doors to conscious introspection (e.g., Petty &

Cacioppo, 1984, 1986; Smith & DeCoster, 2000; Strack & Deutsch, 2004; Wilson,

Lindsey & Schooler, 2000). The activity of this implicit system can then guide

spontaneous and unmediated behavior (i.e., mimicry) or behavior via the

activation of stereotypes or traits (see Dijksterhuis, Chartrand, & Aarts, 2007). The

system can also activate and regulate motivations or goals (e.g., Bargh, 1990, 1994;

Dijksterhuis, Aarts, Bargh & van Knippenberg, 2000). Typically, information will be

processed implicitly when there is a lack of time, motivation or cognitive capacity

to engage consciously with the information (e.g., Bargh, 1994; Strack & Deutsch,

2004; Wilson et al., 2000).

Bargh’s auto-motive model (1990) is the first model to discuss the

automatic activation and pursuit of goals. In this model, it is suggested that a goal

can be activated without conscious input from the individual, and that this

automatic activation can then produce the same effects as if the goal had been

consciously chosen (Bargh & Chartrand, 1999). Numerous studies have confirmed

Bargh’s auto-motive model using the priming paradigm, in which goal-related

stimuli are presented to participants either below the level of conscious perception

(subliminal priming) or above the level of conscious perception (supraliminal

priming). In both cases, the participants are unaware of the influence of the

152 presented stimuli on their subsequent behaviour and judgment. Studies have

confirmed the auto-motive model by finding that perception of stimuli associated

with a specific goal (e.g., the smell of cleaning detergent) can successfully activate

goal pursuit (cleaning) without conscious awareness of the individual (Aarts,

Chartrand, Custers, Danner, Dik & Jefferis, 2005; Shah & Kruglanski, 2003).

Recently, the priming paradigm has been used to automatically activate

motivational orientations as described by the self-determination theory (SDT; Deci

& Ryan, 1985a, 1985b, 2000). Motivational orientations are general tendencies for

individuals to perceive information in an autonomous, controlled or impersonal

manner, and to respond based on this general tendency (Deci & Ryan, 1985a).

Individuals are assumed to have some representation of each orientation, although

one is likely to be dominant in most situations (Deci & Ryan, 1985a, 2002).

Individuals with a dominant autonomy orientation are likely to be driven by

intrinsic and/or by well-integrated extrinsic motivation, and they engage in

behaviour because of personal values and interests (Deci & Ryan, 1985a). Those

with controlled orientations are likely to be driven by introjected and external

regulations, guided by pressures and obligation (Deci & Ryan, 1985a). Impersonal

orientations (which will not be addressed the study presented in this chapter)

indicate a general tendency towards amotivation and a low desire to form

intentions (Deci & Ryan, 1985a).

Goals and motivational orientations are represented in memory in a similar

way (for a review see Bargh, 1997b), and the success observed in goal priming has

been replicated in motivational priming on several occasions. In Chapter 3, a

scrambled sentence task was used to prime autonomous and controlled motivation

in an exercise setting (Banting, Dimmock & Grove, 2011). Both behavioural and

affective responses to exercise were altered based on the priming task, and these

153 effects occurred without participants’ awareness. These results supported the

findings of Radel and colleagues, who observed improvements in heart rate and

performance of a motor task after autonomous priming procedures (Radel,

Sarrazin & Pelletier, 2009). Hodgins et al. (2006) also primed motivational

orientations and found improvements in rowing performance following an

autonomous prime. However, the first researchers to assess the priming of

autonomous or controlled motivations were Levesque and Pelletier (2003), who

found that automatically activated motivation was consequential in an academic

setting. Moreover, the affective responses and behaviour associated with the

automatically activated motivation were very similar to those typically observed in

situations of explicitly activated autonomous motivation (Levesque & Pelletier,

2003).

A central tenet of the auto-motive model described by Bargh is that

automatic goal activation relies on an associative link between the prime and the

goal in the individual’s semantic network (Bargh, 1990). These links are built via a

conditioning process whereby the stimulus is repeatedly paired with the goal.

Thus, no stimuli can be associated with a goal in memory if individuals rarely or

never pursue that goal. Understanding this tenet, Levesque and Pelletier (2003)

proposed that an individual’s chronically accessible motivation will influence the

effectiveness of a motivation prime for that individual. The authors used a free-

response measure of accessible constructs to measure individuals’ highly

accessible motives for engaging in academic pursuits. The authors found that

individuals with no chronically accessible motivation (dominant motivation), but

who nevertheless possessed some mental representation of the primed

motivation, were affected by the prime more than other participants (Levesque &

Pelletier, 2003). Individuals with a chronically accessible motivation were not

154 affected by the prime. It was suggested that for individuals with no chronically

accessible motivation, priming could raise the salience of a particular motivation

(so long as it existed in the first place) relative to other motivations. Conversely,

individuals with a chronically accessible motivation behaved in accordance with

their normal orientation, irrespective of any priming procedure (see Levesque &

Pelletier, 2003). Weinstein and Hodgins (2009) found a similar interaction trend

for participants who were dispositionally controlled in motivation (chronically

accessible controlled motivation). These controlled disposition individuals

responded positively to autonomous priming methods in terms of energy and well-

being (Weinstein & Hodgins, 2009).

CHRONIC ACCESSIBILITY AND IMPLICIT MOTIVATION: SIMILARITIES AND METHODOLOGIES

In his review, Bargh (1997a) suggested that after repeated events evoking a

certain goal and regulatory style, these motivations can become automatically

associated in memory with the event, becoming chronically accessible. In the past,

measures of chronically accessible motivation, which bear a resemblance to

implicit measures, have been used to predict behavior (e.g., Levesque & Pelletier,

2003). Measures of chronic accessibility are similar to implicit measures in that

they examine automatically activated constructs that are associated with

frequency of use (Higgins, King & Mavin, 1982). Unfortunately, methodological

problems are often associated with measures of chronic accessibility. For example,

Levesque and Pelletier (2003), who used a free-response measure to quantify an

individual’s chronically accessible motivational orientation, used a subjective

coding process to generate results. McLachlan and Hagger (2010) coded the

responses from a free-response measure for a similar purpose in a health setting.

Whilst both studies found that the free response measures were associated with

155 self-report measures, and in the case of Levesque and Pelletier, improved

behaviour prediction, implicit measures may be able to do so in a more objective

manner.

Dual process theories have been proposed to suggest that attitudes

and motivations can be represented consciously or unconsciously. The reflective-

impulsive model (RIM; Strack & Deutsch, 2004) and the dual process model

(Wilson et al., 2000), for example, both suggest that attitudes and motivations can

be reflective and/ or impulsive, and subsequent work has led to the development

of several procedures to measure implicit motivation. Implicit measures quantify

cognitive processes by assessing automatic associations which guide behaviour

(Greenwald, Banaji, Rudman, Farnham, Nosek & Mellot, 2002). They primarily rely

on reaction times and differences in response latencies when comparing responses

to various categories of stimuli (Craeynest, Crombez, Deforche, Tanghe & De

Bourdeaudhuij, 2008; Greenwald et al., 2002) . These methods lower participant

controllability, reduce participants’ awareness of the origin of their response,

and/or require high processing efficiency and speed (Nosek, 2007). These qualities

align closely with the criteria for automaticity (unintentional, unconscious,

uncontrollable, efficient and fast) as defined by Bargh (1994). Implicit measures

have been used to assess attitudes (Greenwald, McGhee & Schwartz, 1998), self-

esteem (Greenwald et al., 2002), stereotypes (Banaji & Greenwald, 1995; Rudman,

Greenwald & McGhee, 2001), and self-concept (Banting, Dimmock & Lay, 2009;

Greenwald et al., 2002). Although measures of implicit motivation have also been

developed, implicit measurement of exercise motivation has not been explored

substantially. In Chapter 4, an implicit measure of motivation was developed using

a reaction time software packages and supraliminal stimuli presentation. The

156 findings indicated that it is possible to use implicit measures of exercise motivation

to provide a quantifiable index of an individual’s chronic exercise motivation.

Given the importance of exercise to health outcomes, it is important to

understand how to prime the motivation to exercise and to investigate the factors

that determine priming effectiveness. The research by Levesque and Pelletier

forms the foundation of the research presented in this chapter. Similar findings are

expected to Levesque and Pelletier (2003); however, this chapter employs a more

sophisticated measure of implicit motivation. Whilst the aforementioned authors

used an open-ended written measure of chronically accessible motivations, this

study will use a more objective computer-based measure. Using the lexical

decision task (LDT) developed in Chapter 4 and the priming procedures used in

Chapter 3, this study aims to assess how implicit exercise motivation alters an

individual’s response to a motivational prime. The LDT measure reduces (if not

removes entirely) the amount of cognitive control required by participants when

responding to the stimuli.

The primary goal of this study is to assess exercise-related outcomes

as a function of the interaction between motivation priming and an individual’s

implicit motivation for exercise. In accordance with the findings of Levesque and

Pelletier (2003), it is hypothesized that individuals whose implicit motivation is

highly autonomous or controlled will be less affected by the priming task after

controlling for explicit motivation. These individuals are likely to have a dominant

motivation that will be resilient against priming techniques. For individuals with

no dominant implicit motivation, however, it is hypothesized that the priming task

will have a greater influence on their subsequent behaviour and perceptions of this

behaviour. Priming for these individuals will increase the relative salience of one

157 motivation over the other. Dependent variables in this study include enjoyment,

effort, and choice perceived in the task, heart rate, rating of perceived exertion,

intention for future exercise, and duration.

METHOD

PARTICIPANTS

Sixty-three undergraduate exercise science students were recruited to

participate in the study for bonus credit. Four participants were unable to start the

experimental protocol due to injuries preventing them from cycling. The final

sample of 59 (25 male, 34 female) ranged in age from 18 to 40 years (M= 20.4

years). The participants were divided into the three priming groups randomly with

approximately equal numbers in each group (18 autonomous, 20 controlled, 21

neutral). Participant characteristics according to priming group are described in

Table 5.1.

Table 5.1. Participant characteristics according to priming group.

Priming Group Mean age (SD) % Male

Neutral 19.48 (1.10) 42.8

Autonomous 21.06 (5.38) 50.0

Controlled 20.75 (4.14) 42.1

MATERIALS AND MEASURES

WORD SCRAMBLE SENTENCE TASK

Participants completed a 25 item scrambled sentence task, based on

the priming procedure developed by Srull & Wyer (1979). The task was the same

158 as the used in the study presented in Chapter 3. Participants were required to form

sentences using four out of five words presented in a scrambled order. For each

item, only one sentence could be correctly formed. Similar to Levesque and

Pelletier (2003), the priming to neutral sentence ratio was 4:1 for motivation

priming conditions. Participants in the neutral group were asked to complete 25

sentences in which no motivation words or ideas were included. See Appendix A

for the priming tasks used.

QUESTIONNAIRE MEASURES

PERCEIVED EXERTION. Immediately after exercising, participants completed

Borg’s rating of perceived exertion scale (RPE; Borg, 1982). Participants were

encouraged to rate their general level of exertion for the entire cycling task when

completing this scale. Borg’s measure has been shown to correlate highly with

heart rate (r = .80- .90), and is often used to assess the intensity of exercise for

young- middle aged, moderately fit individuals. The scale ranges from 6 (no

exertion at all) to 20 (maximal exertion).

BEHAVIOURAL REGULATION. To measure the participants’ self-reported

regulatory style from a self-determination theory perspective, the Behavioural

Regulation in Exercise Questionnaire (BREQ-2; Markland & Tobin, 2004) was used.

This scale includes 19 items on a 5 point Likert scale ranging from 1 (not at all

true) to 5 (very true). The BREQ-2 measures intrinsic motivation (4 items; e.g. I

enjoy my exercise sessions), identified regulation (4 items; e.g. I value the benefits of

exercise), introjected regulation (3 items; e.g. I feel guilty when I don’t exercise),

external regulation (4 items; e.g. I exercise because other people say I should) and

amotivation (4 items, e.g. I don’t see the point in exercising). The scale has been

reported to be reliable and internally consistent with Cronbach’s alphas all

159 exceeding 0.73 (Markland & Tobin, 2004). If responses to each of the subscales

correlate in the expected matrix pattern, a relative autonomy index (RAI) can be

calculated to quantify the degree of autonomous (or controlled) regulation for

exercise behaviour (Markland & Ingledew, 2007). The RAI is obtained by weighting

each of the subscale totals and summing these values. Given the use of the revised

version of this questionnaire, we calculated an index according to the formula

which includes an amotivation subscale (Markland & Tobin, 2004); (-3 *

amotivation) + (-2 * external regulation) + (-1 * introjected regulation) + (2 *

identified regulation) + (3 * intrinsic motivation).

INTRINSIC MOTIVATION. Items from the Intrinsic Motivation Inventory

(IMI; Ryan, 1982) were chosen to measure enjoyment/ interest (7 items; e.g. This

activity was fun to do), effort (5 items; e.g. I put a lot of effort into this) and choice (7

items; e.g. I did this activity because I wanted to) in relation to the cycling activity.

These subscales are internally consistent with Cronbach’s Alphas exceeding 0.78

for all subscales (Tsigilis & Theodosiou, 2003) These items were rated by

participants on a 7 point Likert scale (1= not true at all, 7= very true).

INTENTION. The average response to the items ‘I will try to exercise

regularly over the next two weeks’ and ‘I intend to exercise regularly over the next

two weeks’ was used to indicate the strength of intention for future exercise. These

items, which have been recommended by Ajzen (1985), were measured on a 7

point Likert scale (1= strongly disagree, 7= strongly agree). The two items showed

a high internal consistency (α= .92).

160 HEART RATE

Heart rate was measured using Polar Heart Rate Monitors, and

information was downloaded using the Polar Team System and analyzed using

Polar Precision SW 3.0 software. The heart rate monitors were strapped to the

chests of participants to allow for continuous recording of heart rate. The

researchers were able to intermittently check to ensure the monitor was still

recording heart rate with a watch.

LEXICAL DECISION TASK

The exercise motivation LDT was developed using the guidelines suggested

by Wittenbrink, Judd and Park (2001). The LDT used in the research presented in

this chapter was based on the instrument used in Chapter 4. In response to some of

the findings from Chapter 4, several small changes were made to the instructions

presented on the screen as participants completed the task. Additionally, one word

originally used as a stimuli item in the intrinsic category (motivated) was replaced

with ‘satisfying’ to increase the similarity between words used in explicit measures

of motivation and this particular implicit measure. Like the LDT described in

Chapter 4, the priming stimuli in the LDT were presented long enough for the

participant to consciously process them (300ms). These primes represented the

concept of exercise (‘exercise’ and ‘fitness’), and the target letter strings

represented the four types of behavioural regulation as defined by the BREQ:

intrinsic motivation, identified regulation, introjected regulation and external

regulation. The stimulus items were also chosen by exercise psychology

postgraduate students and appear in Table 5.2. Neutral primes were used for

comparison purposes (garden and basket). According to protocol, positive and

negative letter strings were also used, as were non-word letter strings. These

161 additional strings also appear in Table 2. The amount of non-word letter strings

was three times the amount of other category letter strings in an effort to prevent

anticipation of word string trials.

Table 5.2. Lexical decision task stimuli.

Intrinsic Motivation

Identified Regulation

Introjected Regulation

External Regulation

Positive/ Negative

Non-words (examples)

Sti

mu

li

Fun Important Guilt Pressured Flower Mather

Interesting Valuable Ashamed Forced Kitten Scire

Challenge Beneficial Pride Coerced Music Pajer

Enjoyable Worthwhile Superiority Controlled Angry Kniges

Exciting Rewarding Approval Obligated Spider Podding

Satisfying Useful Embarrassed Prescribed Shooting Swetch

Following a similar protocol to Wittenbrink et al. (1997), a fixation point (*)

appeared on the screen for 600ms, followed by the priming stimulus for 300ms

and then the target letter string. The target letter string remained on the screen

until the participant responded. Participants were instructed to classify the word

pairs as either both words or one non-word by pressing the appropriate key.

Participants were instructed to place their fingers over these keys at the start of

the procedure. The LDT consisted of one practice block with 10 trials, and three

experimental blocks, each with 64 trials.

TEST OF AWARENESS

In a similar way to the study presented in Chapter 3, and following the

standard protocol used in priming experiments, a test of awareness was used to

162 ascertain whether the participants realized the true rationale for using the

scrambled sentence task. The questions were based on the funneled debriefing

procedure used by Chartrand and Bargh (1996). Five items (including 2 yes/no

responses and 3 open questions) were used to survey the participants in regard to

what they thought the purpose of the study was, whether they saw a connection

between the scrambled sentence task and the cycling, and whether their cycling

was affected by the scrambled sentence task.

PROCEDURES

The procedures followed in the study were approved by the Ethics

Committee at the School of Sport Science, Exercise and Health. One week before

each participant’s scheduled testing session, they completed a series of

questionnaires, including the BREQ-2 (Markland & Tobin, 2004) and several

demographic questions. These were completed in a small research room at the

university. The next week, participants returned to complete the LDT measure and

exercise task. Participants completed these procedures in a laboratory at the

university campus. Upon entering the laboratory, the researcher reminded the

participants of the protocols, and then each participant completed a physical

activity readiness questionnaire (Canadian Society for Exercise Physiology, 2002)

to ensure they were able to participate in the cycling task. Following this,

participants immediately completed the LDT measure on a computer positioned in

a small room adjacent to the exercise laboratory. This room was free of

distractions and the researcher was positioned at the back of the room to provide

assistance in the task if the participant required clarification on the computer task.

The LDT took most participants 15 minutes to complete after which they could

take a break to rest and prepare for the cycling.

163

The participants were then fitted with a Polar heart rate monitor and the

researcher helped the participant configure the stationary bike to a comfortable

height. All heart rate monitors were checked and adjusted if necessary to ensure

the heart rate data could be accurately downloaded following the exercise session.

Participants were told that they were to cycle for 30 minutes, at a pace they felt

comfortable with. The researcher also explained the scrambled sentence task,

telling participants that the study was looking at the effect of mental distraction on

heart rate during exercise. Participants were asked to complete the scrambled

sentence task to the best of their ability whilst cycling and to inform the researcher

when they had completed it. The scrambled sentence task took participants

between 6 and 14 minutes to complete (M= 8.27 minutes). There were no

differences observed in the amount of time taken on average to complete each type

of priming task (F(2,56)= 1.438, p= .246).

Throughout the cycling time, the researcher did not interact with the

participant other than to let them know the 15 minute (“halfway”) time point. After

20 minutes, participants were tested for the fragility of their desire to cycle. They

were informed that although their presence in the laboratory was needed for the

entire 30 minutes, they could choose to stop or continue cycling. The participants

who continued to cycle were reminded of this again at the 25 minute time point.

Any participants who were still cycling after 30 minutes were asked to stop.

Irrespective of their stopping time, participants immediately indicated their rating

of perceived exertion on Borg’s Scale and then were told to take as much time as

they needed to recover.

Participants completed another series of questionnaires measuring

enjoyment of the cycling, effort invested into the cycling and degree of choice they

164 felt during the cycling. Items measuring exercise intentions were also included.

Finally, participants completed a test of awareness based on funnelled debriefing

procedures commonly used in priming research.

DATA ANALYSIS

IMPLICIT SCORING PROCEDURES

Wittenbrink and colleagues (1997) assessed implicit scores based on

differences in reaction time. The difference between the response time for the

neutral prime with a target word string for a certain motivation type and the

exercise prime with the same motivation type word string was calculated. Trials

where the response time was less than 150ms were excluded from analyses as

these scores indicated anticipation from the participant (occurred in 0.13% of all

trials). Trials where the response time was greater than 1500ms were also

excluded from analyses as these scores indicated that the participant was

distracted temporarily from the task (occurred in 0.95% of all trials). In our

analyses, only correct responses were included. Higher scores indicated that there

was a greater degree of facilitation in responding to that particular motivation

following the exercise prime, compared to the neutral prime. This method

provided scores for intrinsic motivation and identified, introjected and external

regulation. After establishing that a matrix pattern existed in implicit regulation

scores, an implicit RAI score was developed using the formula created by Mullan,

Markland and Ingledew (1997). This formula does not consider amotivation (-

2*external regulation + -1* introjected regulation+ identified regulation +

2*intrinsic motivation). Low absolute scores on this measure indicate that neither

autonomous or controlled motivation are chronically accessible for the individual,

i.e., they have equal representations and access to both. Low absolute scores do not

165 necessarily mean low levels of motivation; rather, there are equal relative amounts

of both autonomous and controlled motivations. High absolute values indicate that

either autonomous (higher positive scores) or controlled (lower negative scores)

motivation is more chronically accessible for that person. The scoring system

allowed the testing of the hypothesis that individuals with no chronically

accessible motivation would be most affected by the priming procedure.

To allow for comparisons to Levesque and Pelletier’s work (study 4; 2003),

participants were divided into three groups. After calculating the participants’

implicit RAI scores, the controlled chronic group was formed using the lowest

scoring third of participants, the autonomous chronics were the highest scoring

third, and the non-chronic group consisted of participants scoring between these

two ranges. Formation of groups based on implicit motivation was also used by

Burton and colleagues who formed groups based on the scores of an LDT (Burton,

Lydon, D'Alessandro & Koestner, 2006). Scores were assessed to ensure that

controlled chronics did indeed score a negative RAI and that autonomous chronics

all scored positive scores. Descriptive statistics on the implicit RAI scores for each

group are presented in Table 5.3 below

Table 5.3. Implicit RAI scores of the implicit motivation groups.

Implicit RAI

Minimum Maximum Mean

Controlled chronic (n= 20) -1093.57 -82.00 -285.99

Non-chronic (n= 19) -65.94 111.13 24.21

Autonomous chronic (n= 20) 139.77 1054.04 407.86

166 GROUPS DIFFERENCE ANALYSIS

To reduce the risk of making a type I error due to conducting multiple

ANOVAs, a MANOVA was conducted to assess group differences, and post-hoc

Bonferroni tests were used to examine particular differences across the priming

groups. This technique allowed all dependent variables (enjoyment, effort and

choice, average heart rate, RPE, exercise intentions and exercise duration) to be

assessed. Positive perceptions of the exercise and increased effort exerted during

the exercise were expected to lead to high scores on all of the variables, whereas

negative perceptions and lower effort was expected to lead to consistent lower

scores and so one MANOVA was used in this case.

RESULTS

TEST OF AWARENESS

To ensure that participants remained unaware of the effect of the priming

task and did not alter their behaviour subsequently, each participant was screened

using a test of awareness. No participant indicated that they had altered their

behaviour based on the scrambled sentence task. Seven participants indicated that

they observed a connection between the priming task and the exercise task. Upon

examination of these results, no participant indicated any awareness of the true

purpose of the study and all participants were retained for analyses as further

questioning revealed they did not alter their cycling behaviour as a result of the

priming task. In cases where participants provided a response, they cited the

connection as being related to a distraction technique (the research cover story),

or that they didn’t know.

EFFECTS OF PRIMED MOTIVATION

167

A MANOVA was used to examine the priming effects of each of the

dependent variables. Using Pillai’s trace there was a significant effect of the prime

on all dependent variables measured (F(14, 82)= 2.30, p= 0.01). This effect was

observed after controlling for age, gender and explicit RAI (explicit motivation).

Further separate univariate analyses revealed that priming group had a significant

effect on the average heart rate of participants (F(2, 46)= 4.56, p= .016), the rating

of perceived exertion (F(2, 46)= 4.45, p= .017), and the total time cycled by the

participants (F(2, 46)= 17.84, p< 0.001). Further examination of the main effect of

priming group on the dependent variables revealed specific differences between

the three priming groups. As illustrated in Table 4, results indicated that the

autonomous group cycled at a higher heart rate than the controlled group (p=

.012), the controlled group rated their exertion levels significantly higher than the

autonomous group (p= .015), and the autonomous group cycled longer than both

the neutral group (p= 0.05) and the controlled group (p< .001). The neutral group

also cycled for longer than the controlled group (p= .003). All differences were

observed after controlling for age, gender and explicit motivation. Means for all

variables are displayed in Table 5.4.

Table 5.4. Descriptive statistics according to priming group.

Mean (SD)

Controlled Prime

Neutral Prime

Autonomous Prime

Time Cycled 24.83 (3.83)*+ 28.67 (2.11)*+ 29.61 (0.78)

Average HR 132.69 (17.25)+ 141.18 (18.37) 146.74 (18.57)

Intention 6.17 (0.95) 6.57 (0.53) 6.28 (1.36)

RPE 13.50 (1.34)+ 13.1 (1.64) 12.17 (0.99)

Enjoyment 4.32 (0.82) 4.39 (0.56) 4.34 (1.02)

Effort 4.56 (1.07) 4.72 (0.93) 4.77 (.88)

Choice 6.35 (0.90) 6.33 (0.91) 6.75 (0.49)

Note: * indicates significant difference to neutral priming group; + indicates significant difference to autonomous priming group.

168 EFFECTS OF IMPLICIT MOTIVATION

The MANOVA analysis was also used to examine the differences between

the implicit motivation groups which were formed on the basis of the implicit RAI

scores. After controlling for age, gender and explicit motivation, Pillai’s trace

indicated a significant effect of implicit motivation on the dependent variables (F

(14, 82)= 2.81, p= .002). The implicit motivation score had a significant effect on

the participants’ intention to exercise in the next two weeks (F(2, 46)= 4.45, p=

.017), the average heart rate of the participants (F(2, 46)= 5.03, p= .011) and the

total time cycled by participants (F(2, 46)= 10.01, p< .001). Bonferroni post-hoc

analyses were used to assess the nature of the differences between the groups. For

intention to exercise, the controlled chronics reported a significantly lower

intention to exercise than the non-chronics (p= .017). For average heart rate across

the cycling time, the autonomous chronics recorded a significantly higher heart

rate than the controlled chronics (p= 0.019) and the non-chronics (p= 0.041). In

terms of total cycling time, the controlled chronics cycled for significantly less time

than both the non-chronics (p= .001) and the autonomous chronics (p= .002). All

means for all variables are displayed in Table 5.5.

Table 5.5. Descriptive statistics according to motivational orientation.

Mean (SD)

Controlled Chronics Non-chronics Autonomous Chronics

Time Cycled 25.79 (3.60)*+ 29.05 (2.17) 28.42 (2.95)

Average HR 134.44 (16.70)+ 137.22 (20.23)+ 149.10 (16.31)

Intention 5.82 (1.39)* 6.75(0.29) 6.53 (0.59)

RPE 12.79 (1.27) 13.11 (1.82) 12.89 (1.24)

Enjoyment 4.49 (0.96) 4.41 (0.79) 4.15 (0.59)

Effort 4.73 (1.06) 4.61(1.04) 4.72 (0.76)

Choice 6.38 (0.86) 6.38 (0.98) 6.65 (0.52)

Note: * indicates significant difference to non-chronic group; + indicates significant difference to autonomous chronics group.

169 PRIMING AND IMPLICIT MOTIVATION INTERACTION

Using the multivariate tests produced from the MANOVA analysis, only the

Roy’s Largest Root statistic indicated a significant effect of the implicit motivation

and priming group interaction effect. This lack of support for a significant

interaction effect was maintained when examining the separate univariate tests.

There were no significant interactions between the priming group and the implicit

motivation groups. However, interactions approached significance (p< .1) for both

average heart rate (F (4, 46)= 2.13, p= .093) and total time cycled (F (4, 46)= 2.39,

p= .064).

To further investigate the interaction between priming and implicit

motivation we divided the participants into groups according to a median-split of

the absolute value of the participant’s implicit RAI. The median-split technique was

used by Burton et al. (2006) to create high and low motivation groups according to

the LDT. Following the formation of groups, separate MANOVAs were conducted

for the chronic and non-chronic groups, controlling for age, gender and explicit

RAI. Assessing the data for these groups separately showed no effect of prime after

controlling for age, gender and explicit RAI. Inspection of the univariate analyses

suggests that cycling time for the low motivation group may have been influenced

by the prime (F= 4.622, p= .020), but this was also the case for the high motivation

group (F= 4.596, p= .022). In this case, contrary to the hypothesis, there appears to

be little significant interaction between the priming condition and the individual’s

implicit motivation for exercise.

170

DISCUSSION

The study presented in this chapter partially supports the findings of the

previous two chapters which examined the independent effects of automatically

activating motivational orientations and implicit motivation on exercise behaviour

and perceptions of that behaviour. Priming of autonomous motivation was found

have a significant effect on participants’ heart rate compared to priming controlled

motivation. This pattern was repeated for cycling time, although the autonomous

group also cycled for longer than the neutrally primed group, and the neutral

group longer than the controlled. The detrimental effect of priming controlled

motivation was confirmed, as ratings of perceived exertion for the controlled

group was significantly higher than those reported by participants in the

autonomous and neutral condition. This effect occurred despite the controlled

group exhibiting lower heart rates than the autonomously primed group and

similar heart rates to the neutrally primed group during the cycling. In terms of

priming, the results of the current study support those found in Chapter 3 and

indicate that autonomous priming is consequential and beneficial, whereas the

priming of controlled motivation can have negative behavioural and affective

consequences.

Implicit motivation, as measured by the LDT, predicted intention to

exercise, average heart rate and cycling time. The significant influence of implicit

motivation on the behavioural measures (heart rate and cycling time) supports the

findings of Chapter 4, where the implicit measure of motivation successfully

predicted cycling time, cycling intensity, and future exercise behaviour. Implicit

motivation influenced the outcome measures in ways consistent with the tenets of

SDT, with individuals with higher RAI scores recording more positive outcomes,

171 and individuals with lower negative RAI scores recording more negative outcomes.

Specifically, a higher positive RAI scores were associated with higher heart rates

than those with a lower RAI score and those with lower negative RAI scores. Those

with high levels of controlled motivation (controlled chronics) cycled for

significantly less time than other participants and reported lower intentions to

engage in future exercise compared to those who had no dominant motivation.

It appears that implicit motivation, as measured by the LDT, may be most

predictive of behavioural measures, although in this instance, self-reported

intention was also predicted. This finding, also observed in Chapter 4, supports the

proposition of several researchers in the field of implicit cognition. Strack and

Deutsch (2004) suggested that the impulsive (implicit) processing system may

dictate behaviour in situations where the cognitive demands for reflection cannot

or will not be satisfied due motivational or situational circumstances. In an

exercise setting, Banting and colleagues found that implicit exercise self-schema

had a direct affect on exercise behaviour, suggesting that behaviour without

conscious intent may be most influenced by implicit constructs (Banting et al.,

2009).

An influence of implicit exercise motivation on behavioural intention was

not expected based on the findings of Chapter 4. However, Jaccard and Blanton

(2007) suggested that implicit constructs can influence the antecedents to

behavioural intention and the intention-behaviour relationship in the theory of

planned behaviour (Ajzen, 1985). Additionally, a meta-analytical review has

suggested that implicit attitudes may affect behavioural beliefs, influencing an

individual’s ultimate intention regarding the behaviour (Greenwald, Poehlman,

Uhlmann & Banaji, 2009). In this case, it is conceptually viable that an implicit

172 orientation toward controlled exercise motivation can guide conscious thought

processes relating to exercise, including the formation of intentions to engage in

future exercise.

The main objective of the current study was to assess whether there was

any interactive effects of the priming protocol and the individuals’ implicit

motivation. It was hypothesized that individuals with no dominant implicit

motivation (non-chronics) would be more susceptible to the priming procedures.

The data was assessed using two different grouping strategies- autonomous

chronic, controlled chronic and non-chronic groups; and chronically motivated

compared to non-chronically motivated only. The results indicate no interaction

effects in either analysis although the results approach significance for two

outcome variables when assessing the three group split (cycling time and heart

rate). Upon inspection of the data, an unfortunate division of participants occurred

in relation to the priming task and implicit exercise motivation. As it transpired, no

non-chronics individuals were assigned to the neutral priming condition, leaving

approximately equal numbers of participants in the autonomous and controlled

priming conditions. This in turn led to disproportionally large numbers of

controlled chronics and autonomous chronics in the neutral priming condition. As

such, it is inappropriate to interpret and make strong comments on the findings of

the interaction analyses. The trends observed in relation to the prediction of

behavioural measures by the interaction are promising; however, more

investigations will need to be undertaken in this area. Future research designs may

involve pre-experimental testing of implicit exercise motivation and assignment to

priming groups as a function of this motivation. A greater sample size would also

reduce the likelihood of such a division of participants according to their implicit

173 motivation, and increase the statistical power of the research itself. The interaction

between priming and implicit motivation is likely to be of a small magnitude,

therefore requiring a larger sample size to be able to detect any significant

differences. Caution must be applied when categorising so broadly, as median-split

groups and arbitrary cut-off points for autonomous chronics, controlled chronics,

and non-chronics limits information available for analysis. Self-determination

theory highlights the importance of all types of behavioural regulation and

motivation, which is not possible when calculating overall indices and grouping

participants into high and low motivation categories. In this research, the

technique allowed for comparison to the only other priming and implicit

measurement research conducted to date (e.g., Burton et al, 2006). However,

future research may benefit from considering individual regulatory styles.

Despite the lack of support for the interaction hypothesis, the study has

indicated that exercise-related outcomes can be influenced by motivation priming

as well as implicit motivation. The measure of implicit motivation successfully

predicted two behavioural measures - heart rate and time cycled - and also

influenced intention to engage in future exercise. These findings were obtained

while controlling for the effects of self-reported motivation for exercise. Insofar as

implicit motivation predicted behavioural measures, findings were largely

consistent with those obtained in the study presented in Chapter 4. Also similar to

the previous study was the finding that implicit motivation was less successful at

predicting affective and perceptual outcomes than behavioural ones.

In this instance, the results provided in Chapters 4 and 5 indicate that the

LDT measures an implicit construct that is highly related to motivation as it is

conceptualised in self-determination theory. The LDT successfully predicted

174 several variables (including exercise duration and heart rate) which demonstrate a

greater amount of self-determined regulation for the exercise task (Hagger &

Chatzisarantis, 2007).The confirmed main effects for implicit motivation indicate

that the LDT can successfully predict motivated behaviour in an exercise setting.

The LDT used as an implicit measure in this chapter and Chapter 4 only assesses

intrinsic motivation and identified, introjected and external behavioural

regulation. Future implicit measures could incorporate a measure of amotivation

to allow for direct comparisons to be made to the BREQ-2 (Markland & Tobin,

2004).

The current study strengthens the growing argument that our immediate

motivational orientation to a task (implicit motivation) and motivation priming

stimuli are influential factors when considering behaviour. There is now a large

number of researchers advocating that the automatic activation of goals and

motives (Bargh, Gollwitzer, Lee-Chai, Barndollar & Trotschel, 2001; Chartrand &

Bargh, 1996), and higher order mental processes in general (Bargh & Ferguson,

2000), can produce behavioural and affective outcomes similar to when the

construct is consciously activated. In this study, priming was successfully used to

automatically activate autonomous and controlled motivation, giving direct

support to the work of Levesque and Pelletier (2003), Hodgins et al. (2006) and

Radel and colleagues (2009). Also, the strength of implicit motivation (for

exercise) was predictive of behavioural outcomes and the intention to exercise,

which supports the findings of Levesque and Pelletier (2003). Similar to this study,

Burton and colleagues (2006) also assessed motivation using an LDT; however,

their measure was designed to just quantify an individual’s intrinsic motivation

and identified motivation. The more comprehensive measure used in the study

175 presented in this chapter allowed us to replicate the study of Levesque and

Pelletier in an exercise context and observe main effects for implicit motivation.

Although no interaction effects were observed when accounting for priming

condition, the ways that individual differences influence the effectiveness of a

priming task is certainly worthy of further investigation. Based on the non-

significant trends observed in the current study and the findings of other

researchers such as Levesque and Pelletier (2003), implicit motivation may play an

important role in priming from a research and applied perspective. Weinstein and

Hodgins (2009) also found positive well-being outcomes and significant

interactions when priming situational autonomous motivation amongst

dispositionally controlled individuals. However, priming situational controlled

motivation further reduced perceptions of well-being and energy amongst

dispositionally controlled participants. The work of both Levesque and Pelletier

(2003), and Weinstein and Hodgins (2009) suggests that primed motivation does

interact with chronically accessible (or dispositional) motivation. However, the

exact nature of the interaction and the role of moderating situational and

individual characteristics is still worthy of future research. Whilst the role of

implicit motivation and automatically activated motivation appears to be

important in an exercise setting, this is not to dispute the important role explicit

motivation and consciously regulated motivation. Individuals concerned with

promoting and prescribing behaviour may be well advised to consider both the

implicit and explicit motivation in order to facilitate long-term exercise behaviour.

176

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181

CHAPTER 6: GENERAL DISCUSSION AND SUMMARY

CHAPTER SUMMARY

This chapter summarises the findings of Chapters 3, 4 and 5 and places

them in context of current research. Based on the findings and protocols followed

as part of this thesis, suggestions are made for future research in terms of

procedures and directions for new discoveries. The value of priming motivation

and considering implicit exercise motivation is discussed in terms of practical

applications and behavioural change.

182

INTRODUCTION

The aim of this thesis was to investigate implicit motivation in an exercise

setting and assess whether motivation could be manipulated outside of conscious

awareness. All research undertaken in this thesis was conducted using the self-

determination theory (Deci & Ryan, 1985a, 1985b) as a foundation for describing

motivation. A comprehensive review of the literature in Chapter 2 revealed that

priming higher order constructs, such as motivation, has been achieved in health

and exercise settings (Hodgins, Yacko & Gottlieb, 2006; Radel, Sarrazin & Pelletier,

2009). Likewise, a significant amount of research has investigated the presence of

implicit, or automatic psychological constructs, including attitudes, stereotypes

and motivations. The works of Greenwald (Greenwald & Farnham, 2000;

Greenwald, McGhee & Schwartz, 1998; Greenwald, Poehlman, Uhlmann & Banaji,

2009), Nosek (Nosek & Banaji, 2001), Wittenbrink (Wittenbrink, Judd & Park,

1997, 2001) and their respective colleagues have shown that implicit constructs

can be successfully measured using reaction time tasks based on word

categorization and association. Technology has also advanced to a point where

very accurate reaction times can be recorded and used to assess implicit

constructs. Whilst these implicit measures have been used to assess implicit

attitudes (Greenwald et al., 1998) and stereotypes (Nosek & Banaji, 2001), no

implicit measure has been developed for exercise motivation. Free response

measures have been used to assess motivational chronicity, with individuals who

have chronically accessible appearance-related motives for exercise reporting

higher levels of external regulation (McLachlan & Hagger, 2010); however, there is

scope to expand on these findings by implementing more sophisticated measures

of implicit motivation. The review of the literature suggested that both priming in

183 an exercise setting and measurement of implicit motivation warrants further

research.

Three studies were designed to first investigate the effect of priming in an

exercise setting, and test for the presence and influence of implicit exercise

motivation. The first study, presented in Chapter 3, examined the effect of

motivational primes on participants during an exercise task. Using a scrambled

sentence task, participants were primed with either autonomous motivation,

controlled motivation, or assigned to a control (neutral) condition. It was found

that enjoyment was higher for participants in the autonomy prime group relative

to the controlled prime group, as was percentage of heart rate maximum, intention

to exercise, and time cycled. Ratings of perceived exertion were higher for

participants in the controlled prime condition relative to the other two groups.

These findings indicate that controlled priming conditions can have a detrimental

effect on the exercise of an individual, with participants feeling like they had

expended more effort following an exercise session, despite engaging in a lower

intensity exercise (as indicated by heart rate). In this study, priming for

autonomous motivation can be helpful in achieving longer exercise efforts of a

higher intensity and increased intention to repeat exercise in the future.

In Chapter 4, a study is presented in which the notion that implicit

measures could measure implicit exercise motivation and predict exercise-related

outcomes is explored. To assess implicit exercise motivation, participants

completed a Go/ No-Go Association Task and a Lexical Decision Task. After

considering explicitly reported exercise motivation, it was found that the Lexical

Decision Task predicted important exercise-related outcomes. The implicit

motivation score obtained from the Lexical Decision Task predicted the amount of

184 time cycled by participants, the intensity at which they cycled, and their future

exercise behaviour. Scores on this task did not correlate with the explicit exercise

motivation scores, although scores from the Go/ No-Go Association Task did. The

Go/ No-Go Association Task did not significantly predict any outcome variables

after controlling for explicit exercise motivation. The results indicate that after

considering self-report questionnaires, implicit measures, particularly the Lexical

Decision Task, can explain unique variance in exercise behaviour.

Chapters 3 and 4 provided a foundation for Chapter 5 to explore possible

interactions between implicit motivation and supraliminal motivation primes.

Numerous experiments on priming as well as the results from Chapter 3 indicate

that motivation primes can influence behaviour without conscious awareness of

the individual. However, research published by Levesque and Pelletier (2003)

indicated that an individual’s chronic motivational orientation may influence the

effectiveness of a prime in an academic setting. In the study presented in Chapter

5, participants completed an implicit measure of motivation and either an

autonomous, controlled, or neutral priming task, and then undertook a basic

exercise task. The findings confirmed the results of Chapter 3 as priming group

predicted heart rate, exercise duration and rating of perceived exertion. Likewise,

similar results to Chapter 4 occurred in respect to implicit motivation. Intention to

exercise, exercise duration and average heart rate were all associated with implicit

motivation. No significant interactions were observed between priming group and

implicit motivation, which can perhaps be attributed to an uneven distribution of

participants across cells in the study design. Trends in the data suggest that

interactions may well exist, which would have supported the findings of Levesque

and Pelletier (2003).

185

SUMMARY OF PRIMING

The main effects of priming observed in Chapter 3 and 5 indicate that

autonomous priming has a largely positive effect when compared to a neutral

priming condition and a controlled priming condition. As primes may occur

naturally in the exercise environment (for example, in the forms of signage,

dialogue with trainers and other exercisers and promotional material), it is

important to understand the effects of both autonomous and controlled primes.

Investigating how common exercise-related material is perceived by exercisers is

an important future research direction. Whilst priming controlled motivation may

not be a likely applied outcome of this line of research, understanding the nature of

controlled primes is critical to ensure naturally occurring controlled primes are

limited. The effects of the priming were largely behavioural in nature, with

increases in exercise duration and intensity observed in both Chapter 3 and 5. The

findings in this thesis support other priming research in the exercise and health

setting, indicating that constructs such as schema (Banting, Dimmock & Lay, 2009;

Wryobeck & Chen, 2003), attitudes (Conroy, Hyde, Doerksen & Ribeiro, 2010) and

motivation (Hodgins et al., 2006; Hyde, Doerksen, Ribeiro & Conroy, 2010) can be

automatically activated.

SUMMARY OF IMPLICIT MOTIVATION

In the exercise experiences designed as a part of the research conducted in

this thesis, implicit motivation had clear associations with exercise behaviour.

However, only the Lexical Decision Task predicted exercise outcome variables. The

success of the Lexical Decision Task, as opposed to the lack of associations

between the Go/ No-Go Association Task and exercise outcomes, demonstrates the

sensitivity of implicit measures to procedural modifications. There is a need to

186 further investigate exactly how implicit measures operate and the most suitable

protocols for various constructs. Implicit measurement in an exercise setting has

been used to successfully predict exercise outcomes; however, this is the first

reaction time based measure of implicit exercise motivation. Berry has

investigated attentional bias amongst exercise schematics and non- schematics

and found differences in response latencies when presented with exercise related

stimuli (Berry, 2006). Berry also expanded on these findings by showing that

implicit constructs can influence the cognitive processing of exercise-relevant

information (Berry, Jones, McLeod & Spence, 2011). Implicit attitudes have been

shown to be associated with physical activity (Eves, Scott, Hoppé & French, 2007),

predict exercise behaviour (Conroy et al., 2010) and be associated with higher

explicit exercise motivation (Conroy et al., 2010). Also, implicit exercise self-

schema has been associated with more frequent exercise behaviour, after

controlling for intentions and explicit self-schema (Banting et al., 2009). These

investigations in the exercise setting indicate that whilst explicit measurement of

psychological constructs remains important and valid, measuring constructs

implicitly can explain additional variance in exercise-related variables.

DUAL PROCESS MODELS

A central tenet underpinning the research in this thesis is the notion that

cognitive processes can occur both implicitly and explicitly. Traditionally in

psychological research, constructs have been conceptualized as explicit, conscious

processes and measurement of these processes has largely been through self-

reporting, introspective techniques. However, there is some agreement now that

constructs can exist and be activated automatically (Dijksterhuis & Aarts, 2010;

Dijksterhuis & Bargh, 2001). Several researchers have proposed dual process

187 models, suggesting that higher order mental processes such as attitudes can have

conscious and unconscious representations in memory which can then be

activated and implemented with or without conscious awareness (Petty, Tormala,

Briñol & Jarvis, 2006; Petty & Wegener, 1999; Strack & Deutsch, 2004; Wilson,

Lindsey & Schooler, 2000). The terminology varies amongst models but each

suggests one pathway that is a considered and conscious pathway to behaviour,

and another that is automatic and spontaneous. In this research, participants were

given an unexpected choice in an effort to activate implicit motivation. The

significant findings of this research indicate that the presence of implicit higher

order mental processes is likely, and furthermore these implicit constructs can

have an effect on the behaviour of the individual in an exercise setting. The

research presented in this thesis supports dual process models in general,

particularly those which suggest implicit constructs are more likely to influence

behaviour in spontaneous situations (Strack & Deutsch, 2004). The findings of the

studies presented in this thesis are amongst the first to examine implicit

motivational pathways in a self-determination theory framework, particularly in

an exercise setting. The results of this thesis support other work (e.g., Levesque &

Pelletier, 2003) conducted in self-determination theory research by suggesting

that implicit and explicit regulatory styles are worthwhile considering in the sub-

theory of organismic integration theory. The implicit measure of motivation was

somewhat context specific (exercise); however, future research would no doubt

profit from also considering more global implicit motivational orientations. This

research did not assess motives or goal contents, yet the work of McClelland

(1953) and others (e.g., Baumann, Kaschel & Kuhl, 2005; Schultheiss 2001)

suggests that motives can exist in both implicit and explicit forms. As such,

considering implicit goal contents may strengthen our understanding of self-

188 determined goal pursuit as discussed in the goals contents sub-theory of SDT.

Furthermore, well-being is said to improve when both implicit and explicit

constructs are congruent (Kehr, 2004). In a model that specifies autonomous

regulatory styles and psychological need satisfaction for increased well-being and

internalization of behaviour, considering both implicit and explicit processes may

strengthen the theory and improve its utilization in real-world settings.

CONCLUSION

Overall, this thesis demonstrated the complex nature of implicit constructs

and automatically activated motivation. In an exercise setting, there is great value

in considering implicit motivation to better predict exercise behaviour. Likewise,

automatically activating motivation in an exercise setting can be used to improve

the immediate exercise behaviour of an individual, increasing the intensity of their

exercise and the duration of the exercise session. More research is required to

better understand how the effectiveness of a prime is influenced by the individuals

implicit exercise motivation. Future research may focus on developing more

ecologically valid primes which have the potential to be used as health

promotional material, or advertising in an exercise setting. The current research

indicates that words used in an exercise setting can have a measurable impact on

the exercise behavior of the individual. Based on this research, individuals working

in an exercise setting should adopt autonomy inducing language and resist words

associated with external and introjected regulation. Likewise, understanding the

behavioural indicators of controlled implicit exercise motivation may be useful for

assisting those who do not have high levels of implicit and/ or explicit exercise

motivation.

189

The research presented in this thesis suggests that priming autonomous

motivation can have a positive effect on exercise behaviour compared to a control

condition and priming controlled motivation. Likewise, this research supports the

existence of dual processes, in this case motivational, and suggests that behaviour

can be better predicted by considering by implicit and explicit motivation in an

exercise setting.

190

CHAPTER REFERENCES

Banting, L. K., Dimmock, J. A., & Lay, B. S. (2009). The role of implicit and explicit components of exerciser self-schema in the prediction of exercise behaviour. Psychology of Sport and Exercise, 10, 80-86.

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APPENDICES

APPENDIX A: CHAPTER 3 PUBLICATION

Banting, L.K., Dimmock, J.A., & Grove, J.R. (2011). The impact of automatically

activated motivation on exercise-based outcomes. Journal of Sport and Exercise

Psychology, 33, 569-585.

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APPENDIX B: WORD SCRAMBLED SENTENCE TASKS

212 NEUTRAL PRIMING TASK

Below are items for a language proficiency test that has not been used in university students. Therefore, we need to obtain norms for university students. Please use the five words on each line to construct a grammatically correct four-word sentence to the right. 1. book we the read top ________________________________________ 2. by people walk some now _______________________________________ 3. sale for by shirts are ______________________________________ 4. books they be often read ________________________________________ 5. dollars salad costs two for ________________________________________ 6. the shall brown was dog ________________________________________ 7. often juice but drink I ________________________________________ 8. fence they but saw the _____________________________________________ 9. in bookmark used the she _______________________________________ 10. two was had he hats ________________________________________ 11. pencil and blue the is ________________________________________ 12. plant I like obvious that ________________________________________ 13. bright is the yes lamp _______________________________________ 14. was sign a there too ________________________________________ 15. is to here served lunch ________________________________________ 16. he now are wears glasses ________________________________________ 17. apple was to the delicious ________________________________________ 18. you coffee the is hot _______________________________________ 19. in bookmark used the she ________________________________________ 20. tablecloth and patterned the is _______________________________________ 21. dark is the yes room ________________________________________ 22. the tree tall is and ________________________________________ 23. is the now desk wooden _______________________________________ 24. the her to fits shoe _______________________________________ 25 . you vegetables the are fresh ___ ____________________________________

213 AUTONOMOUS PRIMING TASK

Below are items for a language proficiency test that has not been used in university students. Therefore, we need to obtain norms for university students. Please use the five words on each line to construct a grammatically correct four-word sentence to the right. 1. options have I two and ________________________________________ 2. you coffee the is hot ______________________________________ 3. feel are interested I usually _______________________________________ 4. my many have opportunities I ________________________________________ 5. challenge I like a he ________________________________________ 6. mouse interesting I this find ________________________________________ 7. enjoy I freedom my he ________________________________________ 8. the her to fits shoe _______________________________________ 9. this task is feet worthwhile _______________________________________ 10. we activities enjoy exciting she ________________________________________ 11. choices dizzy rewarding my are ________________________________________ 12. important are it my decisions _______________________________________ 13. is the now desk wooden _______________________________________ 14. we exciting day my is ________________________________________ 15. I he strive to achieve _______________________________________ 16. strong I very mother feel _______________________________________ 17. we are highly she motivated ________________________________________ 18. is to here served lunch _______________________________________ 19. activities most enjoy walk I _______________________________________ 20. my behavior he is important _______________________________________ 21. I dog am completely engaged _______________________________________ 22. involved being her has benefits ________________________________________ 23. have we choices him challenging ________________________________________ 24. bright is the yes lamp ________________________________________ 25.my castle diverse are alternatives ________________________________________

214 CONTROLLED PRIMING TASK

Below are items for a language proficiency test that has not been used in university students. Therefore, we need to obtain norms for university students. Please use the five words on each line to construct a grammatically correct four-word sentence to the right. 1. options have I no and _______________________________________ 2. bright is the yes lamp ________________________________________ 3. feel are pressured I usually _______________________________________ 4. I have many restrictions my ________________________________________ 5. I made was to building _______________________________________ 6. mouse controlling I this find ________________________________________ 7. comply he demands I with ____________________________________________ 8. is to here served lunch ________________________________________ 9. obey I’m required feet to _______________________________________ 10. I’m participate to forced him _______________________________________ 11. involvement my was expected sky_______________________________________ 12. I and feel usually pressured ________________________________________ 13. is the now desk wooden ________________________________________ 14. required dog contribute am I _______________________________________ 15. coerced my he behaviour is ________________________________________ 16. limited my are him choices ________________________________________ 17. is life building controlled my ________________________________________ 18. the her to fits shoe _______________________________________ 19. forced to I’m path conform _______________________________________ 20. choices dizzy limited my are ________________________________________ 21. proving I’m always dog something_______________________________________ 22. involved be should I cats ________________________________________ 23. decisions my are is imposed ________________________________________ 24 . you coffee the is hot _______________________________________ 25. alternative no him there is ________________________________________

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APPENDIX C: QUESTIONNAIRE MEASURES

216 BEHAVIOURAL REGULATION IN EXERCISE QUESTIONNAIRE: REVISED VERSION

Read the following statements and use the scale to indicate the extent each of the items is true for you. 1= Not at all true 3= Somewhat true 5= Very True

No

t a

t a

ll t

rue

So

me

wh

at

T

rue

V

ery

Tru

e

1 I exercise because other people say I should. 1 2 3 4 5 2 I feel guilty when I don’t exercise. 1 2 3 4 5 3 I value the benefits of exercise. 1 2 3 4 5 4 I exercise because it’s fun, 1 2 3 4 5 5 I don’t see why I should have to exercise. 1 2 3 4 5 6 I take part in exercise because my friends/family/ partner say I

should. 1 2 3 4 5

7 I feel ashamed when I miss an exercise session. 1 2 3 4 5 8 It’s important to me to exercise regularly. 1 2 3 4 5 9 I can’t see why I should bother exercising. 1 2 3 4 5 10 I enjoy my exercise sessions. 1 2 3 4 5 11 I exercise because others will not be pleased with me if I don’t. 1 2 3 4 5 12 I don’t see the point in exercising. 1 2 3 4 5 13 I feel like a failure when I haven’t exercised in a while. 1 2 3 4 5 14 I think it is important to make the effort to exercise regularly. 1 2 3 4 5 15 I find exercise a pleasurable activity. 1 2 3 4 5 16 I feel under pressure from my friends/ family to exercise. 1 2 3 4 5 17 I get restless if I don’t exercise regularly. 1 2 3 4 5 18 I get pleasure and satisfaction from participating in exercise. 1 2 3 4 5 19 I think exercising is a waste of time. 1 2 3 4 5

217 INTRINSIC MOTIVATION INVENTORY ITEMS

Please rate the extent to which you agree with the following statements. The activity refers to the cycling exercise you have just performed. 1= Not at all true 4= Somewhat true 7= Very true

No

t at

all

tru

e

Som

ewh

at T

rue

Ver

y T

rue

I enjoyed doing this activity very much. 1 2 3 4 5 6 7 This activity was fun to do. 1 2 3 4 5 6 7 I thought this was a boring activity. 1 2 3 4 5 6 7 This activity did not hold my attention at all. 1 2 3 4 5 6 7 I would describe this activity as very interesting. 1 2 3 4 5 6 7 I thought this activity was quite enjoyable. 1 2 3 4 5 6 7 While I was doing this activity, I was thinking about how much I enjoyed it.

1 2 3 4 5 6 7

I put a lot of effort into this. 1 2 3 4 5 6 7 I didn't try very hard to do well at this activity. 1 2 3 4 5 6 7 I tried very hard on this activity. 1 2 3 4 5 6 7 It was important to me to do well at this task. 1 2 3 4 5 6 7 I didn't put much energy into this. 1 2 3 4 5 6 7

I believe I had some choice about doing this activity. 1 2 3 4 5 6 7 I didn't really have a choice about doing this task 1 2 3 4 5 6 7 I didn't really have a choice about doing this task. 1 2 3 4 5 6 7 I felt like I had to do this. 1 2 3 4 5 6 7 I did this activity because I had no choice. 1 2 3 4 5 6 7 I did this activity because I wanted to. 1 2 3 4 5 6 7 I did this activity because I had to. 1 2 3 4 5 6 7

218 PROFILE OF MOOD STATES (POMS)

Below is a list of words that describe feelings that people have. Please read each one carefully. Then circle the answer which best describes HOW YOU FEEL RIGHT NOW. Make sure you answer every question.

Not at all A little Moderately Quite a bit Extremely Panicky 0 1 2 3 4 Lively 0 1 2 3 4 Confused 0 1 2 3 4 Worn Out 0 1 2 3 4 Depressed 0 1 2 3 4 Downhearted 0 1 2 3 4 Annoyed 0 1 2 3 4 Exhausted 0 1 2 3 4 Mixed-up 0 1 2 3 4 Sleepy 0 1 2 3 4 Bitter 0 1 2 3 4 Unhappy 0 1 2 3 4 Anxious 0 1 2 3 4 Worried 0 1 2 3 4 Energetic 0 1 2 3 4 Miserable 0 1 2 3 4 Muddled 0 1 2 3 4 Nervous 0 1 2 3 4 Angry 0 1 2 3 4 Active 0 1 2 3 4 Tired 0 1 2 3 4 Bad Tempered 0 1 2 3 4 Alert 0 1 2 3 4 Uncertain 0 1 2 3 4

219 INTENTION QUESTIONS

The last page of questions are related to how you feel about exercise and your plans to exercise in the future. They should be quite easy for you to answer. Please indicate on the scales provided your response to the following questions I intend to exercise regularly over the next few weeks.

I will try to exercise regularly over the next few weeks.

How many times do you see yourself exercising in the next week? _________times.

Strongly

Disagree

Agree Strongly Agree Neither Agree

or Disagree

Disagree Slightly

Agree

Slightly

Disagree

Strongly

Disagree

Agree Strongly Agree Neither Agree

or Disagree

Disagree Slightly

Agree

Slightly

Disagree

220 TEST OF AWARENESS

This is the final page of questions which relate to the tasks you have just

completed in this research study.

What did you think the purpose of this research was?

Did you see any connection between the sentence formation task and the exercise

you were asked to perform? YES NO

What was this connection? (briefly describe)

Do you think your cycling after finishing the sentence formation task was affected

by the sentence formation task? YES NO

Could you describe briefly how you think your cycling was affected?

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