The Study of Hong Kong Secondary School Students’

Attitude towards Performing

‘Physical Activity for 3 times per week, at least 20 minutes for

each time’

An Application of

Theory of Planned Behaviour

Research Report

By

To Chun Yin, Toby

Liu Kar Hang, Jackie

Liao Wai Kee, Marco

Mok Cheuk Yiu, Yo

2015

Final year project submitted to the Chinese University of Hong Kong, School of

Continuing and Professional Studies in partial fulfilment of the requirement for

the Higher Diploma in Business Studies (Marketing)

Acknowledgement

This research is supported by the teachers of the CUSCS. Their assistance helps us to finish

this research and help us to learn more knowledge other than this curriculum of the BS

programme.

Our thanks to the CUSCS supports of the material and campus, it provided us with material

supports like computers, statistic programs, and text books.

We are grateful to give our thanks to friends, classmate, and parents. For their supports, they

gave us supports at the time of difficult and desperate. They helped to motivate us to continue

to finish this research at our best.

Lastly, I wish to deliver my thanks to Michael’s FYP team. They actively provide us opinions

on our research in an objective perspective. They help us to see our research more than a fixed

model perspective and see more insights and idea from this research.

Thank You,

i

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Table of ContentsList of Figures..........................................................................................................................ivAbstract......................................................................................................................................vCHAPTER 1 INTRODUCTION.............................................................................................11.1 Background.........................................................................................................................1

1.1.1 Global situation of physical inactivity........................................................................11.1.2 The situation of physical inactivity in Hong Kong....................................................11.1.3 Public health impact of physical inactivity................................................................21.2 Research Objectives..........................................................................................................6

Reference.................................................................................................................................82

iii

List of Figures

Figure 5.2 TPB model to predict intention...........................................................................lxxivFigure 5.3 TPB model to predict intention (female)..............................................................lxxvFigure 5.4 TPB model to predict intention (male).................................................................lxxv

iv

Abstract

Situation of physical inactivity is serious in Hong Kong and it will cause a big problem.

Physical Activity Baseline Indicator set by Hong Kong which recommends people to do

physical activity more than 30 minutes in at least 3 days a week. To analyze the exercise habit

of secondary school students (Form one to Form six), TPB model was conducted in the

research to recognize what are the reasons lead to lack of physical activities . Base on the

research result, we recommend solutions to improve the problems. In the research pilot study

and questionnaire were designed by TPB model. Questionnaire was conducted base on result

of pilot study. 4 secondary schools were selected using cluster sampling with sample size of

100 respondents. All of the respondents are secondary school students from form one to form

six. Problems will be found by analysis the attitude, subjective norms, perceived behavioral

control, intention and behavior of respondents. TPB model help to find out the self and social

factor that influence the behavior of respondents in doing physical activities.

Data of the research run by SPSS and we can observe the correlation of factors. Male does

physical activities more than female. In the self-factors, attitude and perceived behavioral

control of TPB model are two major factors that influence the intention for physical activity

of the secondary school students. Overall, they have positive attitude towards the perceived

health benefits to do physical activities. Three major groups of secondary school students was

found that they have different approach in being physical active. Research shows genders

have different correlation in attitude which male has correlation of attitude towards enlarge

social cycle and set goals while female wants to reduce pressure and improve perseverance.

For the social factors, male likes to do physical activities with friends or alone while female

do it with family or alone. Students who are physical inactivity are driven by school at first to

do exercise. Whereas, students with exercise habit are driven by friends or classmates at first.

v

CHAPTER 1 INTRODUCTION

The following chapter will discuss the background information of the physical inactivity

problem and the research objective of this research.

1.1.1 Global situation of physical inactivity

Physical inactivity is one of the most common issues around the world. 1 Every year, more

than three million of deaths in the world as a result of physical inactivity.2 Compared to

people that have proper exercises regularly, people who are insufficiently active have a higher

risk of dying early by 20% to 30% (The World Bank, 2014). According to WHO (World

Health Organization), this issue is the fourth leading cause of global mortality. It is also the

key factor to cause non-communicable diseases (NCDs) such as heart related disease and

cancers. Moreover, NCDs cause nearly half of the overall global burden of disease.3 The top

ten leading causes are mainly heart disease and lung disease related. These kinds of diseases

are mainly caused by unhealthy life style and lack of physical activities (Department of

Health, 2010; Johns & Lindner, 2006). There are more than 80% of adolescent in the world

that are physically inactive and are living mainly in the most developed countries (WHO,

2015). WHO recommends adolescents to perform at least 60 minutes of moderate to

vigorous-intensity physical activities every day, since the health condition is strongly

correlated with an inactive lifestyle.

1.1.2 The situation of physical inactivity in Hong Kong

In Hong Kong, the situation of physical inactivity is rather serious. Around 50% of the

population is physically inactive according to “Physical Activity Baseline Indicator”, which

means participating in moderate to vigorous physical activity for at least an accumulation of

30 minutes every day and at least three days a week. This is leaded by the sedentary lifestyle

of Hong Kong (Centre for Health Protection, 2012).4 Hong Kong has rather a low fitness and

physical activities level (Fu, 1994) as well as the most inactive primary level students in the 1 World Health Organization. (2015) Media centre: Physical activity, 2015 [Online] Available from:http://www.who.int/mediacentre/factsheets/fs385/en/ [Accessed: 30th January 2015].2 Healthy Hong Kong, Department of Health. (2002) "World Health Day" reminds public to "Move for Health’’[Online] Available from: http://www.dh.gov.hk/english/press/2002/02_04_06.html[Accessed: 28th January 2015].3 World Health Organization. (2004) Burden of disease: DALYs [Online] Available from:http://www.who.int/healthinfo/global_burden_disease/GBD_report_2004update_part4.pdf [Accessed: 30th January 2015].4 Centre for Health Protection. (2012) Physical Activity: Situation in Hong Kong [Online] Available from:http://www.chp.gov.hk/en/content/9/25/8804.html [Accessed: 20th April 2015].

1

world (Adab et al, 1998). The overall physical fitness and ability are also weaker than average

adolescents in Europe, America and some other Asian countries (Ip, 2013). Take Singapore as

an example, Singapore has a very similar cultural background and values to Hong Kong

which Singapore has about 48% of the population which is physically inactive according to

the Singapore National Health Survey. 5 This statistic is based on the WHO advised physical

activity baseline indicator. Which Hong Kong used their own indicator of doing physical

activity more than 30 minutes in at least 3 days a week of doing moderate to vigorous

physical activities. Many researches show that Chinese culture is one of the key factor which

is leading this problem. Since Asian parents are more focused on academic results than other

activities (Fu, 1993) (Ip, 2013) (Ng, 2005).

Hong Kong environment is also one of the factors causing the problem of physical inactivity

from adolescents. In a study environment, Hong Kong is an examination oriented society

which students’ later achievements and careers are mainly based on the marks of the

examination and how well they perform in all their subjects. This discourage students to

participate in more sport activities but to spend more effort in studying during school time as

well as leisure time (Ng, 2005). Furthermore, crowded environment is another factor that

causes adolescents to participate less in physical activities. The lack of recreation environment

and area to perform sport will influence adolescents to spend more effort in sedentary

activities instead (Ng, 1996a). According to the reports done by Chinese University and

Physical Fitness Association, it shows that Hong Kong adolescents spend most of their leisure

time with friends on gatherings, movies, and other audio entertainments. This shows that

adolescents’ friends play a very important role in influencing adolescents in leisure activities.

One of the factor Ng had stated in 2005 is different than other research, Ng states that the lack

of skills in perform certain sports is one of the reason that causes adolescent to not participate

in physical activities. It is one of the barriers that stop people from doing sports (Speak,

Linder, & Li, 1993). It is crucial for schools to provide sport education to teach students the

correct way in performing different sports so that it may increase students’ confidence when

participating sport activities with others.

1.1.3 Public health impact of physical inactivity

5 Ministry of Health. (2010) National Health Survey 2010 [Online] Available from: https://www.moh.gov.sg/content/dam/moh_web/Publications/Reports/2011/NHS2010%20-%20low%20res.pdf [Accessed: 20th April 2015].

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There are serval health risks that may result from physical inactivity which include both

physical and mental diseases. People who are less active and do not exercise regularly are

more likely to develop high blood pressure, coronary heart disease, certain type of cancers

and other diseases that may harm the human body physically (The American Heart

Association, 2014). Estimated by The Disability - Adjusted Life Year (DALY), Physical

inactivity can cause 21 - 25% of breast and colon cancer burden, 27% of diabetes and 30% of

Ischemic heart disease burden. According to the Student Health Service, the obesity rate of

secondary school students was increased from 13.6% in 1997 and 1998 to 17.7% in 2010 and

2011. Table 1 illustrates the weight status by gender and age in Hong Kong. It was clear that

the proportion of overweight and obesity increased as age grew. A study by The Chinese

University of Hong Kong and Physical Fitness Association of Hong Kong in 2012 revealed

that a current trend of people suffering from high blood pressure at a younger age is occurring

in Hong Kong. There are 4.1% of primary school students that have the risk of having high

blood pressure. Although the ratio of children suffered from high blood pressure is low, but it

was worth a thought. Moreover, physical inactivity may also harm the human body mentally

which creates a feeling of anxiety and depression. (V. Nedeltcheva, A., Kessler, L., Imperial,

J., & D. Penev, P., 2009). This shows that the common sedentary lifestyle of Hong Kong

people will directly influence their health status and the continue of this lifestyle practice may

lead to long term health issues mentally and physically.

Table 1 Weight status by gender and age group in Hong Kong3

Age Underweight Normal Overweight Obese

Boys

(%)

Girls

(%)

Boys

(%)

Girls

(%)

Boys

(%)

Girls

(%)

Boys

(%)

Girls

(%)

3 - 6 19.3 19.5 67.8 66.4 7.5 11.2 5.5 2.9

7 - 12 7.8 9.9 61.5 67.2 20.5 18.3 10.1 4.5

13 - 19 15.5 21.0 66.1 69.6 13.2 7.4 5.3 2.1

20 - 39 6.8 14.0 39.1 60.1 19.3 13.3 34.8 12.6

40 - 59 2.1 3.5 31.4 48.1 26.2 21.7 40.3 26.7

60 - 69 5.4 3.0 31.7 37.1 28.7 19.1 34.2 40.8

Note: Figures may not add up to 100% due to rounding

Source: Census and Statistics Department, 2013

Physical inactivity does not only cause health problems to individuals, as well as increasing

the government financial burden from healthcare. It is predicted that NCDs will account for

80 percent of the global burden of disease in 2020 (Boutayeb, A., & Boutayeb, S., 2005).

When more people have health problem, the more medical resources will be in demand such

as labor, medicines, medical technology, which directly influence the healthcare system of

Hong Kong negatively. The health expenditure is predicted to be increased to solve the needs

and demand of health care (Fredrik Erixon & Erik van der Marel, 2011) and the increase of

health expenditure will increase the financial burden for the whole city which affect the social

welfare of Hong Kong due to a decrease in budget. Moreover, the health problem will affect

the productivity of Hong Kong because a patient will need to spend time and money in

medicate treatment instead of going to work. Since the competitive advantage will decrease,

the health problem will damage the economy of Hong Kong because of the financial burden

and the low productivity.

Physical activities are important to be studied in adolescent because it is the developing stage

of a person. The adolescence is the crucial stage of human being where a person develops

4

physically and psychologically, from a child to an adult. This will root their behaviour

throughout their lifetime. Research shows that building a habit of doing physical activity

regularly at adolescence will increase the attitude to maintain this behaviour after 10 years

(Graham, Sirard, & Neumark-Sztainer, 2011). According to the Senior Secondary Curriculum

Guide (CDC, 2007), physical education is an elective subject in Hong Kong secondary

school, it can be part of the school curriculum, aims to help students to develop an active

lifestyle and good health, physical fitness and bodily coordination. Also, there is “School

Sports Programme” which targets at all primary, secondary and special school students, it is

an education and training, to teach them the importance and raise the awareness of doing

exercises. Exclude lessons and programmes in schools, Hong Kong government also have

other polices to promote physical activities, such as introducing “Sport for All Day” in 2009,

invite the public to join this event every year, with different themes and topics.

It is familiar that doing exercise can actually help to develop a better physical health and

mental health (American College of Sports Medicine, 2006). For instance, increase bone

density6, reduce anxiety and tension, and against develop NCDS. 7In addition, it can help to

ease the financial burdens. It is important to build habits to adolescent to do enough exercise,

because this kind of habits will developed into their mind are last for 5 to 10 years (Graham,

Sirard, & Neumark-Sztainer, 2011). The earlier to develop a physical activity habits to

children, they are more likely to extend their habits to their adulthood. So, we should have an

appropriate strategy to encourage people to do exercise, since there are numerous benefits for

individuals and community.

1.2 Research ObjectivesPhysical inactivity is a global problem, the problem is also significant in Hong Kong.

Compare to Taiwan, Singapore and China, Hong Kong situation is more serious in terms of

younger generations and adolescent. The research objective will be finding the effective

variables to predict do physical activity. It can help the society or the government to develop a

future plan of physical activity based on the important variables.

1.3 Research Framework

Theory of Planned Behaviour is used as the theoretical framework of this research. Ajzen

(1991, 2007, and 2011) have indicated that TPB is a model that suitable in predicting the

6 King, A. C., & King, D. K. (2010). Physical activity for an aging population. Public Health Rev, 32(2), 401-426.7 Centers for Diseases Control and Prevention, US Department of Health and Human Services, Physical Activityand Health: A Report of the Surgeon General. Atlanta, 1996

5

physical activity behaviour. As well as numbers of research related to physical activity and

health psychologies are using TPB as their theoretical framework. The framework, by using

attitude, subjective norm and PBC, can used to predict the intention of the physical activity

behaviour in a cognitive approach.

CHAPTER 2 LITERATURE REVIEW

This chapter begins by describing the historical aspects of theory of reasoned action (TRA)

and its newer, the Theory of Planned Behavior (TPB). Next it describes the various constructs 6

that make up this model. It then discusses the application of TPB in behavior research.

Finally, it notes the limitation of the model and the reason we used TPB.

2.1 Theory of Reasoned Action and Theory of Planned Behavior

Both TRA (Ajzen & Fishbein, 1969, 1980) and TPB (Ajzen, 1985; Ajzen & Madden, 1986)

have been used widely in health education and health promotion which can predict human

behavior and behavioral dispositions (Chiou, 1999). The two prominent are clams that

behavior intention is the important determinant of behavior (Manoj & John, 2008; Debra,

Suha & Barbara, 2011). Those theories have considered the implication of one’s action before

deciding to engage or disengage in a specific behavior.

The TRA posits that human’s intention is determined by two factors. One is the personal

factor refers to the degree of a person have a favorable or unfavorable in evaluation toward a

behavior. The second factor is related to social, as known as subjective norm, about the

perceived social pressure to perform the behavior or not (Ajzen & Madden, 1985). However,

TRA focus on volitional behavior, serval researchers noted TRA did not consider people have

control over a behavior (Ajzen, 1991; Randolf & Wolff, 1994; Taylor & Todd, 1995; Godin

& Kok 1996; Sherran & Oberall, 1999). To remedy these limitations, Ajzen added third

element, perceived behavior control (PBC) which can influence ones’ intention or one’s

behavior directly (Ajzen, 1985).

2.2 Historical Perspectives

The TRA originated from Martin Fishbein (1965, 1967), a social psychologist at the

University of Illinois at Urbana, when he examines the relationship between attitudes and

beliefs in 1960s. He founded that attitudes are response to an object in a favorable or

unfavorable way and belief is a hypotheses to concern the nature of object. In 1970s, Fishbein

teamed up with Icek Ajzen of the University of Massachusetts at Amherst formed the basic

TRA, when write the book Belief, Attitude, Intention and Behavior: An Introduction to Theory

and Research (Fishbein & Ajzen, 1975). These theories linked belief to attitude, intention,

and perform behavior. Additionally, they published second book which called Understanding

Attitudes and Predicting Social Behavior to simplify TRA and made it more practical.

In early 1980s, the theory was popular after publication among researchers to explain one’s

behavior in various domains. However, Liska (1984) and other researchers (Sheppard et al.,

1988) conducted a meta - analysis on the TRA and discovered it cannot deal with behaviors

that require resources, cooperation, and skills. Therefore, Ajzen added another construct, PBC 7

to the TRA. The concept of PBC was came from Bandura’s (1986) social cognitive theory,

Atkinson’s (1964) theory of achievement motivation, and Rotter’s (1996) locus of control

theory. As a result, TRA revised and renamed to TPB. At present, both TRA and TPB are

popular theories in health promotion (Ajzen, 2014), although it has limitation as we will

discuss it in 2.1.5.

2.3 Construct of Theory of Planned Behavior

The following three predictors serve as the main constructs of the model: attitude toward

behavior, subjective norm, and perceived behavioral control. Theses model also include

behavior, behavioral intention, behavioral beliefs, normative beliefs, motivation to comply,

control beliefs, and perceived power. Each of these factors, individually or in combination,

can be used to explain health behavior.

Figure 1. The theory of reasoned action and theory of planned behavior

Note. The upper shaded section shows the theory of reasoned action; the entire figure shows

the theory of planned behavior

Sources: Montano, D. e., & Kaspryzk, D. (2002).

The first construct of TPB is behavior refers a single action that performed by someone that is

observable. The behavior is in term of its target, action, context, and time (TACT). For

instance, the behavior of help a sedentary kid to practices two hours of badminton at school.

This is the target for the kid, the action is practice badminton, the context is the sedentary

nature of the kid, and the time is two hours.

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The second construct is behavioral intention. Also, it will be perform the behavior. The

intention is based on subjective norm, attitude toward the behavior, and perceived behavioral

control. It can measure by a 7 point bipolar scale, extremely probable (+3), quite probable

(+2), slightly probable (+1), neither probable nor improbable (0), slightly improbable (-1),

quite improbable (-2), and extremely improbable (-3). The intentions also include TACT.

The third constructs in the model is attitude toward the behavior. This is an evaluation by an

individual on whether the perceived value from performing a particular behavior is positive or

negative. The evaluation is based on the correlation between the total set of accessible beliefs

in the particular behavior and the behavior to different outcomes and attributes. The (b) being

the strength of each individual’s belief and it weights with the evaluation (e) of the outcome

or attribute of the behavior. (Ajzen, I 2006) The equation is being shown below:

The fourth construct of the model is behavioral beliefs which can perform a behavior and lead

to certain outcomes. Moreover, the fifth constructs is the evaluation of outcome. To assess

attitude toward a behavior, we should multiply the score of behavioral beliefs and outcome

evaluation.

The six construct is subjective norm refer an individual have social pressure to perform or not

to perform in a behavior (Ajzen, 1991).There are two motives motivate people take part in

physical activities which are intrinsic and extrinsic motive (Ryan & Frederick, 1997). For

example people seek for enjoyment is intrinsic motive while concern about appearance is

extrinsic (Ryan & Frederick, 1997). The equation is being shown below:

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The seventh construct is normative beliefs. It concerned with the probability that important

referent people approve or disapprove of performing a given behavior (Ajzen 1991, p.195). It

regarding different social referents combine to produce a totally perceives social pressure and

their subjective norm (P.A.M. Lange 2012, p. 443).

The eighth constructs is motivation to comply that about the degree for a person wants to act

in accordance with the perceived wishes. It can also measure on a 7 - point bipolar scale.

The ninth constructs in the model is perceived behavioural control. Tis the belief that create

an intention to do the behaviour. It is being affected by the control beliefs of the behaviour. It

can be past experience, information and different factors that make a person to feel easy or

difficult to do the behaviour (Ajzen, 1991). It is a belief about resources and opportunity to do

the behaviour. The belief is calculated by the sum of each control beliefs (c i) multiply by the

perceived power (pi). The equation is being shown below:

The tenth constructs is control beliefs. It refers to a internal and external factors that may

inhibit or facilitate the performance of the behavior.

2.4 The mechanism of Theory of Planned Behaviour

2.4.1 Attitude toward the Behaviour

Each individual adolescent has different beliefs in physical activity and expect different kinds

of outcomes and attributes from being physical active. The kind of goals an adolescent wish

to peruse from being physical active is an important factor since it may identify the expected

value to be positive or negative. There are two types of goals in exercise setting, intrinsic and

extrinsic goals. Intrinsic goals include the goals of health, fitness, social relationships and

enjoyment which are inseparable from the activity. (F. B. Gillison, M. Standage and S.M.

Skevington 2006) It is being seen as a type of reward which self-determined behaviors are

being encouraged by adolescents. Extrinsic goals include goals that are separable from the

activity such as wealth and status which are based on aiming to achieve outcomes to reduce

the given social pressure throughout the process. Adolescents know that through physical

activity, it may improve their physical appearance like weight losing which is a type of

characteristic of extrinsic goals. Male adolescent and female adolescent are motivated

differently towards physical activity. (Moira D. Luke and Gary D. Sinclai) It has been

reported that most boys exercise for leisure time and the purpose of enjoyment while girls

10

exercise due to perceived pressure to lose weight. In a sample of 580 adolescents with 300

males and 280 females, 43% of female adolescents see themselves as overweight while 26%

for male adolescents. Having a perspective of being overweighed may receive added pressure

from parents, friends, and the media to be thinner, and to lose weight. (James F. Sallis. Judith

J. Prochaska, and Wendell C. Taylor) According to the prediction of hypothesized model,

individuals that perceived pressure to lose weight are more likely to experience social

physique anxiety and lead to extrinsic goals which perusing a better physical appearance

becomes the way to a better quality of life. It has been reported that out of 100%, 36% of boys

aim fitness as a goal from being physical active, 33% for health which are mainly intrinsic

goals. There are 27% of girls aim for a better body tone from being physical active, 26% for

health, and 26% for attractiveness. In comparison, there is a difference in belief between the

two genders where girls exercising for extrinsic goals more frequently than boys, and intrinsic

goals. (F. B. Gillison, M. Standage and S.M. Skevington 2006)

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2.4.2 Subjective norms

Teenagers participate in physical activity may influenced by the other individuals and the

social standard. Researches show that both of parents and peers plays an important role to

motivate teenagers do exercise. Parents support can appeared by rewards and participation

and education, build up their knowledge and attitude towards sports while they are young

(Robert J, 2010), they should be their role-model as kids always learn from them, like having

the health diets and habits.(Payne, 2003) Parents who are active in sport can encourage their

kid to be physically active in doing exercise (Fredricks, 2004). They are responsibility in

establishing a family climate surrounding physical activity (Robert J, 2010). Family-based

approaches for the promotion of physical activity are having great potential in making logical

sense and giving knowledge that help children to develop physical activity-related their

habits, values, and beliefs within the family environment. Through education and role

modeling practices, children can own some knowledge, create high involvement and habits in

doing exercise with positive attitude. (Robert J. 2010). Parents reinforce the child activity

directly or indirectly (Cheatom, 2014). They encourage their child to do physical activity and

influence the child’s attitude (Cheatom, 2014). Moreover, children’s perceptions of parents’

beliefs and behaviors are more strongly related to their self-evaluations and physical activity

behaviors than parent-told beliefs and behaviors (Fredricks, 2004). So, if the parents who

create supportive, enjoyment and encouragement, children can develop a competence and

attraction to physical activity. (Weiss, 2000). A good and long life habit is important to child

since it drives them keep doing exercise when they are teenagers or older which reduce the

bad result occur in the future. Promotion of physical activity in the period of transition from

childhood into early adolescence is important for maintain and establish a health habit

(Murtagh, 2012).

However, peers’ motivation are more powerful than family, it is common that the adolescents

spend more time with peers (Klarin, 2012) so they also play an important role to influence the

behavior of teenagers (Patrick & Ryan, 1999). Adolescents who do physical exercise are want

to develop and show off their physical ability, like sport skills, physical fitness, and physical

appearance. Meanwhile, they like to gain social acceptance and support in their social circle

(Robert J. Brustad, 2010), including friends, peers, brothers or sisters, parents, teachers or

coaches, those people are their significant people who can gain the acceptance, approval and

encouragement (Robert J. Brustad, 2010), it is a key to make them to start and continue the

participation in sports, they like to have a group. In their social circle, friends are the most

powerful motivators than their family (Kenneth J. Gruber, 2008). Also, during adolescents, 12

they spend a lot of time with their friends and peers, their interaction that positive promote

health behavior, such as weight control, health diet and physical exercise (Kenneth J. 2008)

are important in prevent some problems caused by less exercise. Teenagers like to do sports

as a group because they can talk and exchange ideas during exercise, they also think that

friends can encourage them to stick in the activity program (Ya-Wen Hsu 2011, p.213), so

peers are the catalyst for teenagers to take part in physical activity (John M. 2002), During

physical activity, there will have good interaction with peers that can give opportunity for

them to expose different points of view.

Instead of their parents and friends, teacher and coaches are also important to influence their

participation in physical exercise. As like as parents, they can influence them by rewards or

punishments to teenagers’ performance outcome. (Keegan, 2009) Teacher and coaches who

around them can give informational feedback, adolescents can evaluate themselves with right

direction but not rely on normative standard or peers perception. (Weiss, 2000). Their clear

visions of physical education are more supportive to develop lifelong habits, because other

influencer like friends and parents may give some unsuitable provision to harm their health

practices (Keegan, 2009). With the professional knowledge and skill, adolescents’ motor

skills can have great development, also the attitude and awareness can be created positively

(Song & Chen, 2012).

The behavior of participating in physical activity also affected by the social norms and

environment. Social factors including efficacy expectations and perceptual affective

experiences in physical activity affect the psychological of the person and they drive

teenagers to do exercise (Lewthwaite, 1990). Compare with female and male, their lifestyle of

diet and physical activity are different by what they think are important to them. Female are

willing to do exercise because they concern about their appearance and fitness and it is more

than male (Ryan & Frederick, 1997). Also, female usually response to contemporary the

social standard of body shape (Kilpatrick, 2005), they may tend to be more involve in

healthful eating and self-body care (Robert M, 1987). Male usually motivated by social

recognition (Kilpatrick, 2005). According to the research of Ryan & Frederick (1997), both of

female and male rated extrinsic motive be the major reason that drive them to take part in

physical activities.

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2.4.3 Perceived behavioral control

The PBC plays an important role in the TPB model. It is the parts that make TPB are different

from TRA. As many scholars argued that TRA predicts the behaviour without factors that the

person can have control over the behaviour. PBC is a perception of the people ability to

perform the physical activity. Ajzen indicated that PBC have a strong role in predicting the

behaviour. As PBC can affect a person to have change of intention in doing a behavior, or it

can affect a person to do or not to do a behavior. When there is little information about the

behaviour, unfamiliar elements are added into PBC, it will affect the realistic of the PBC.

Researches have shown that PBC having a significant effect in the variables of doing physical

activity (Godin and Shephard, 1986; Atsalakis and Sleap, 1996)

In perceived behavioral control, it may include two components, the first one is the

availability of resources that used to deal with the behavior, like money, time or skills, and the

second one is the self-confidence from the person in capability to do the behavior. (Jyh-Shen

Chiou, 1998). Lack of skills is one of the PBC that ease adolescent from doing physical

activity (Ng, 2005), it is one the exercise barrier which cause by low in confidence in their

skills in doing exercise better, since Gentle (1994) found that if young people has low activity

levels, they may have less positive beliefs about the social value of doing exercises, it increase

the difficulty in perform physical activity. That mean the physical self-concept, ability and

confidence are critical determinants in joining the physical exercise (Daley, 2002). So, if

teenagers do not have well development in the skills required to take part in the exercise,

when there has opportunities to do sports, they will not try to participate and because of lack

of exposure make them incompetence to follow (Daley, 2002). Smith A. (1998) also indicated

that nervous and low of confidence increase the difficulty to perform physical activity,

participants will tends to do more physical activity after participate with exercise leaders,

which provide them with more confidence in exercise. Similar results are found by de Bruijn

& Rhodes (2009) that low in confidence is the reason of not doing physical activity too.

Bad weathers and having other hobbies to do are being discovered as the main PBC for the

young people in UK (Hagger et al., 2001). Chinese culture is also one of the reasons of

increasing the difficulty in doing physical activity (Rhodes et al., 2006; Ng, 2005). Also,

teenagers easily affected by technology which making them more willing to spent time

sedentary behavior, there are less than 1% of children and youth can fulfill the health

recommendation of having less than 120 minutes of sedentary screen time during daylight

hours (Woods, 2010). Technology based sedentary behaviors like watching TV or playing 14

video games, one research from Robert Wood Johnson Foundation showed that the most

average hours children and adolescents spent daily is watching TV, which has 4.5 hours and

others are the computers games (1.5hours) and video games (1.25hours). The intention to do

exercise can effect by the technology.

Same research also pointed out that children and adolescents spend an average of 6 to 8 hours

per day in sedentary behaviors, both during and outside of school. Chinese culture affected

the subjective norms which are the parents as well as the adolescents. Adolescent will devoted

more time in academic, homework than doing physical activity (Rhodes et al., 2006). As well

as a competitive education system which examination is more focused by the adolescent

themselves (Ng, 2005). In Hong Kong, parents and society are attached great importance to

students’ academic achievement, different academic standards produces different

interpretations of success, it may influence teenager’s evaluation of their self-efficacy. (Chan,

2008). Great importance to academic performance to children may restrict the opportunities

and time for them to have physical activities as they are required to have more academic or

tutorial schedules after school (Yu, 2006). However, research also shown that adolescent with

better academic results are more willing to put time to do physical activity (Chow, 2002).

2.5 The reason of using Theory of Planned Behavior

Much recent research about the relation between attitude and behavior are conducted with the

framework of TPB (Hagger et al., 2001) and the model is suitable to do prediction. As

Fishbein and Cappella (2006) have stated that health care communication is better to

explained by behavioural model. TPB model have been widely used to predict the physical

activity and solutions of physical inactivity in different researches (Hagger, 2002; Brickell,

2006). Hagger (2002) through tests have indicate that Perceived behavioural control a key

influence to do physical activity which make this model suitable to be used. At the same time,

the author had indicate that using TPB to predict physical activity can do as well as using the

past behavioral in predicting physical activity.

2.6 Limitation of the Theory of Planned Behavior

TPB are widely used by many healthcare researches, still there are limitation of the TPB

model. One of the factors that TPB have not taken in the prediction is the implicit attitude

(Devos, 2008). Although this model have put volitional control as one of the predictive factor,

Godin (1993) had suggested that it is difficult to say which physical activity are volitionally

control and which are not. Also, studies have shown that the TPB is not a stable model (Kiene 15

et al., 2008. Hobbs et al., 2012), which there is a daily fluctuation on the volitional control at

different time point.

2.7 Development of the hypothesis

In this research, five major hypotheses will be tested. It is summarized as follows:

1. The intention towards the behaviour is indirectly affected by other variables other than

PBC, attitude and subjective norm.

2. Subjective norm have a higher predicting power than PBC. As parental influence are

mainly studies in Chinese culture environment, it is related to the subjective norm.

Parental influence had been seen as an important factor to influence students to physical

activity.

3. Female have a higher control power than male. As the society usually say ‘female is more

self-control than male’. This hypothesis wish to test whether female have a higher self-

control ability than male, and do the behaviour based on self-factor more than outsider

factor.

4. As Hong Kong government majorly use healthy life as the influencing factor to promote

teenagers to do physical activity. This hypothesis is used to prove health related beliefs are

not important beliefs of attitudes towards the behaviour.

5. Self-efficacy is a variable that indirectly affect subjective norm, respondent will based on

their self-efficacy, choose to comply their most important advice or not.

16

Table 1 Relevant journal

Journal Author Year Results Data

Parental Influence

on Children’s

Physical Activity

Motivation

Octavia

Cheatom

Jun

2014

Subjective Norms

Parents (not limited to

biological parents) are

playing important role to

influence their attitudes

and encourage their

physical activity. They

also reinforce the child

activity directly or

indirectly.

COLLEGE

STUDENTS’

MOTIVATION

FOR PHYSICAL

ACTIVITY

Lori Lynn

DeLong

Dec

2006

Subjective Norms

People do exercise

because of the

appearance. They want to

lose weight and maintain

fitness.

People are motivated to

perform exercise because

of the self-esteem

especially female.

Adolescents'

Commitment to

Developing Talent:

The Role of Peers in

Continuing

Motivation

for Sports and the

Arts

Helen Patrick,

Allison M.

Ryan,

Corinne Alfeld-

Liro,

Jennifer A.

Fredricks,

Ludmila Z.

Hruda,

Aug

1999

Subjective Norms

Peers play an important

role to affect their friends

to participate in the

physical activities when

they are children or

adolescents because they

usually spend more time

with peers in this period.

17

and

Jacquelynne S.

Eccles

Motivational

Considerations in

Physical

Activity Involvement

Rebecca

Lewthwaite

Dec

1990

Subjective Norms

Social environmental

influences on motivation

to take part in do exercise.

Social factors such as

efficacy expectations and

perceptual affective

experiences in physical

activity affect the

psychological of the

person.

College Students’s

Motivation for

Physical Activity:

Differentiating

Men’s and Women’s

Motives for Sport

Participation and

Exercise

Marcus

Kilpatrick

2005 Subjective Norms

There is exercise behavior

because people concern

the health and appearance.

Female response to

contemporary the social

standard of body shape

while males are motivated

by the factors related to

ego such as social

recognition.

Intrinsic Motivation

and Exercise

Adherence

Richard M.

Ryan

Christina M,

Frederick

Deborah Lepes

Noel Rubio

Kennon M.

Sheldon

1997 Subjective Norms

Intrinsic and extrinsic

motives motivate people

do physical activities. For

example, seek for

enjoyment is intrinsic

while concern about the

fitness and appearance is

18

extrinsic.

Female willing to do

exercise because of

extrinsic motive is more

than male. But both of

female and male rated

extrinsic motive is the

main reason drive them to

take part in physical

activities.

University Students’

Leisure Exercise

Behaviours

Judy, K., Ng. 2005 Subjective Norms

Chinese culture and

competitive education

system focus on academic

rather than physical

activity.

The living environment

was crowed and lack of

facilities.

The people are lack of

skill and it leads low

participation.

The influence of self

– efficacy and past

behavior on the

physical activity

intentions young

people

Martin S.

Hagger , Nikos

Chatzisarantis

& Stuart J.H.

Biddle

09

Dec

2010

Behavioural beliefs &

attitudes

The teenagers’ attitudes

toward physical activity

are providing enjoyment.

Subjective norm

Parents have greater

influence than friend to

younger people

-37.2 %

respondents

though having

exercise are

fun.

- The beliefs

of parents

(2.25%) and

friends

(1.44%)

Perceived self, Chow, Chi- kin 2002 Behavioural beliefs & The kids try

19

parental and

situational factors in

physical activity

participatory

behavior of Hong

Kong children and

youth: a test of

Ajzen’s theory of

planned behavior

attitudes

The teenager notice the

importance between

physical exercise and

fitness.

hard to have a

good shape

(0.838) and

think it is

important to

always in

good shape

(0.818).

Social Environment

and Physical

activity:

A review of concepts

and evidence

Lorna

Haughton

McNeilla,

Matthew W.

Kreuterb ,S.V.

Subramaniana

2

May

2006

Subjective norm

Social interactions and

interpersonal relationships

are an important in social

environment, people who

having a supportive

partners, family and

friends are positively

associated with physical

activity increasing.

Social Support For

Exercise and Dietary

Habits Among

College Students

Kenneth J.

Gruber

2008 As social support is a

powerful motivator for

young adolescents to do

healthful behaviors, such

as exercise, weigh control

and healthy diet. Close

friends and peers are more

powerful than family

because they want to

build up friendship with

each other.

Teens talkin' health:

A qualitative study of

family, peer and

Sara Mijares St.

George

2007 Parental social support

can provide a positive

environment via

20

intrapersonal factors

related to physical

activity and healthy

eating in underserved

African American

adolescents

providing resources,

encouragement, and role-

modeling of health

behaviors, which lead

adolescents to increases in

exercise and health diet in

youth, meanwhile to have

parent-child relationship .

Peer relationships in

physical activity

contexts: a road less

traveled in youth

sport and exercise

psychology research

Alan L. Smith 2003 High quality peer

relationships may

translate to positive

health-related outcomes in

12-15 year old

adolescents, with the

development of effective

and efficient ways to do

physical activity. They

can expanded to explore

the interactive

contributions of their

significant others (friends

and peers) in the social

groups.

The Role of Family in

Promoting Physical

Activity

Robert J.

Brustad,

2010 Family-based approaches

for the promotion of

physical activity are

having great potential in

making logical sense and

giving knowledge that

help children to develop

physical activity-related

their habits, values, and

beliefs within the family

environment. Through 21

education and role

modeling practices,

children can build up their

knowledge, high

involvement and behavior

in doing exercise with

positive attitude.

Influences of Social

Support, Perceived

Barriers,

and Negative

Meanings of Physical

Activity

on Physical Activity

in Middle School

Students

Ya-Wen Hsu,

Chih-Ping

Chou, Selena T.

Nguyen-

Rodriguez

2011 In friend social support,

teenagers like play sports

with their peers because

they can discuss physical

activity with each other,

giving encouragement to

make them stick with

activity program, and also

can change schedule to

play together. In family

social support, they think

family will give reward

for their good

performance, also

included encouragement

elements here.

Motivating Kids in

Physical Activity

(

Maureen R.

Weiss, Ph.D.

2000 Friends, peers, parents,

teachers and coaches are

the significant people with

the teenagers, those

people should develop

close friendships with

them, add encouragement

and education in the

physical activity

environment, to mass the

benefits of people 22

interactions, relationships

and skills develop..

Chapter 3 Methodology

This chapter will explain the methodology of this research. The research is based on the

Ajzen’s Theory of Planned Behaviour as the theoretical framework, which include the use of

secondary data, pilot study and the final questionnaire.

3.1 Secondary Data

In this research, different secondary data are used to define the criteria of the adolescent to

perform physical activity as a behaviour. Referenced researches are mainly from America,

United Kingdom, China and Hong Kong. As former research have shown that the TPB model

do not fit into Chinese culture8. Hong Kong and China research can be used as a support to fit

into Hong Kong environment. Research referenced are mainly using TPB model as well, or

can display factors that can related to the Behavioural belief, Normative Belief and Perceived

behavioural control. It can help us to get insight in developing our researches in the stage of

pilot study and questionnaire. Researches population are mainly adolescents, some research

have population of different age groups below 50. These researches are useful to us as it fit

into our research population and can provide us useful insights.

3.2 Pilot Study

Five pilot studies are distributed (3 boys, 2 girls) to understand the elements of the TPB

model, which are the behavioural beliefs, normative beliefs and control beliefs. Respondents

are selected by judgement of secondary school uniform on the street.

Measure of Belief

The pilot studies use questions like ‘What is the advantages/disadvantages you see of doing

exercise for 3 times per week, at least 20 minutes each time, and their degree of strength

motivate you to do exercise.’ It used to measure the behavioural beliefs and the outcome

expectation. Result of healthier body are the only answer from the pilot studies, which it have

8 Rodham K, (2010), Health Psychology. London: Palgrave Macmillan23

a medium degree of strength. And the major belief of disadvantage are waste time and feel

tired. And they see these disadvantages as a high degree of not doing exercise.

Measure of Normative Belief

A second question to measure the normative belief asked respondent to list the person who

approve/disapprove them to do exercise for 3 times per week, at least 20 minutes each time.

Respondents give the person as ‘mother ‘and ‘friends’ as approval people, and ‘school’ and

‘parents’ as disapproval people. Further asking on why they will have such belief on them.

Respondent tells that they say them doing, so they follow it. While, respondent think that

school too many homework and test which make them have no time to do exercise.

Measure of Control Belief

Third question are asked ‘What are the factors that make you feel easy/difficult to do exercise

for 3 times per week, at least 20 minutes each time.’ Respondents give beliefs of ‘no school

day’ and ‘friends invited them’ as the factor which will make it easier to do exercise. ‘Lazy’,

‘many homework’ and ‘have other things to do’ are the beliefs for difficulties to do exercise.

These wording can help to formulate the final questionnaires as the control beliefs, as these

response are frequently appeared in other studies of physical activity behaviour.

3.3 The Final Questionnaire

3.3.1 Sampling Method

The sampling method used in this research is the stratified sampling. Cluster sampling method

is suitable in this research, as school list provided by Education Bureau and class name sheet

can help to be our sampling frame in the procedure of final questionnaire.

A sample of 102 respondent (44 male, 58 female) of secondary school students participated in

the questionnaire. Respondents are approached based on four selected school according to

each districts. A quota is sampled based on half with physical activity habits and half with

not.

According to Hong Kong Educational Bureau, schools district are separate into Hong Kong

Island, Kowloon, New Territories West and East. One region is randomly selected for

representing each district in Hong Kong. The following district are selected: Eastern District

(HKI), Wong Tai Sin (KWL), Yuen Long (NTW), Shatin (NTE). One secondary school is

randomly selected from the Hong Kong secondary school list provided by the Education

Bureau.

Eastern District: Shau Kei Wan Government Secondary School

Wong Tai Sin: Po Leung Kuk Celine Ho Yam Tong College

Shatin: S.K.H. Lam Kau Mow Secondary School24

Yuen Long: Chinese YMCA Secondary School

By using the proportion of the secondary students based on each district, there are 17% in

HKI, 31% in KWL, 24% in NTE, 28% in NTW, which 18,32, 24, 28 questionnaire are

proportionally distributed to these secondary schools based on each districted accordingly.

Table 3.1: Number of Students in Each District

中學生 中學生 中學生 中學生

中西區 11346 油尖旺 15511

西貢 21797 34326

灣仔 12461 深水埗 24051

沙田 38588 28496

東區 26727 九龍城 32576

大埔 15395 11876

南區 16666 黃大仙 20729

北區 17974 26719

觀塘 30480 393286

Table 3.2: Number of Questionnaire Distributed According to

District

中學生 %

問卷數目

問卷數目 2

有做運動

沒有做運動

港島區 67200 17% 17 18 9 9

九龍區 123347 31% 31 32 16 16

新界東 93754 24% 24 24 12 12

新界西 108985 28% 28 28 14 14

393286 100% 100 102 51 51

25

3.3.2 Questionnaire Design

The procedures of designing the Theory of Planned Behaviour Questionnaire is mainly guided

by the journal from Ajzen (2006) and Francis et.al (2004).

The first two questionnaire are used as the filter question to identify whether the respondents

is a secondary students and whether they have participate physical activity behaviour.

Measure of Attitude

In the first part of the questionnaire, we have questions like ‘In the coming 3 months for doing

exercise 3 times per week for at least 20 minutes, I believe:’ It was using 7-points semantic

differential scales of -3/3 with six-scales of : beneficial-harmful, joyful-unpleasant, pressure-

relaxing, waste-save time, satisfaction-exhausting, spiritual-tired. These scales are used as a

direct measure of the attitude. And directly measure how is the attitude of the respondent feel

about the behaviour.

Behavioural Belief are measured by using ‘in the coming 3 months, I believe doing physical

activity for 3 times per week for at least 20 minutes, I will:’ The questions had list total nine

beliefs for the respondent, It intend to measure the likelihood that the outcome of the

behaviour will appear and the belief on whether doing physical activity will cause them to

happen. The nine items are healthy body, enlarge social network, ideal body, waste time,

relaxing, reduce pressure, perseverance, attract opposite gender and set goal. This nine items

are set based on the benefits of physical activity provided by WHO and researches. It can be

separated into physical health and mental health, goal directed and other purpose.

Outcome Evaluation are further asked to measure the behavioural belief by directly

multiplying the according beliefs. By measure the beliefs have a positive or negative outcome,

it is asked ‘ in the coming 3 months, I believe doing physical activity for 3 times per week at

least 20 minutes, and their outcome is:’ it is measure by using 7-points Likert scales of

absolutely negative-absolutely positive.

Measure of Subjective Norm

Starting from question 6, it used to define the most important person to respondent. According

to researches and pilot studies, four major people and one other options is provided which

they are classmates/friends, parents, teachers, partners. ‘the most important to me approve me

for doing physical activity 3 times per week, at least 20 minutes. With 7-points Likert scales

of approve-disapprove, and ‘the most important people to me think that I should do physical

activity 3 times per week, at least 20 minutes’ are used to measure the normative belief of the

respondents. To measure the motivation to comply with the normative belief. Question is 26

asked ‘in the matters of health, I will do what the most important person think I should do’.

The score is used to multiply with the normative belief score, the answer will generate the

subjective norm.

Measure of Perceived Behavioural Control

In the part 3 of the questionnaire, we have list out four major control beliefs which are parents

focus on academic, adequate time, accompany from others and facilities in the society. We

decided to put ‘parents focus on academic’ as a factor in this questionnaire, as we have found

that Chinese culture society are more academic results in other researches. To test the control

belief strength, we ask ‘I expect that I will have (control factor) in the coming 3 months.’

With a 7-points Likert scale of agree-disagree. ‘ Having (control factor) would enable me to

exercise for 3 times per week, at least 20 minutes each time for the coming 3 months’ is asked

to measure the power of control factor with 7-points Likert scale of agree-disagree. By

displaying the existence of the control factor, answer the possibility to do the behavioural can

help us to know the power of each control factor. ‘I am confident that I can exercise for 3

times per week, at least 20 minutes each time for the coming 3 months’ and ‘Exercise for 3

times per week, at least 20 minutes each time for the coming 3 months is entirely up to me’

are the questions are to measure whether the respondent have the autonomy to do exercise by

themselves. These questions are used to measure the self-efficacy of the respondents. It is

based on the respondent internal measure of their own self, whether then a situational

questions to measure the control factors in the above mentioned.

Measure of Intention

In part four, questions are used to measure the intention to have a behaviour of ‘exercising for

3 times per week, at least 20 minutes each time for the coming 3 months’. This part consist of

three questions which are ‘I plan to exercise for 3 times per week, at least 20 minutes each

time for the coming 3 months’ and ‘ I intend to exercise for 3 times per week, at least 20

minutes each time for the coming 3 months’. The questions are set to use generalise intention

measure, as it is the most commonly used method in questionnaire (Francis et.al, 2004). By

using the more ‘real’ situation, it can help us to predict the actual intention towards the

behaviour. Finally, to measure the behaviour of the respondent whether they will do it or not,

it ask ‘under any barriers, I will do physical activity 3 times per week, at least 20 minutes’.

Other Measure

Other questions which concern the demographics of the respondents like age, gender, form is

asked to find out the difference of the respondent. Other questions like ‘Whether my

parents/friends have exercise habits’ are asked. These questions can help to find out

correlations to the three elements of the TPB model. A question which let the student to write 27

down their preferred exercise indicator can help this research to show the difference their

preferred one and the government advised one. It is one way to measure the strength of the

barrier to stop them from exercising to the standard.

3.3.3 Fieldwork

The fieldwork were conducted outside the secondary school. The fieldwork time is at 7:30 to

8:30, 12:00-1:30, after 3:30. As these time are more easily to approach the secondary school

students when they have lunch time, and leave the schools. Fieldworkers are grouped by 2 to

prevent interviewer cheating and improve the response rate of the respondents. As two

interviewers are more easily to approach to the respondent. Interviewers will ask the questions

to the respondent according to the words of the questionnaire and answer were recorded by

the interviewers. Interviewers were allowed to provide further instructions and explanation to

the respondent of they have any difficulties in understanding the questions and wordings. The

explanation of the questionnaires are only explaining the words with more details meanings or

sampler words, instead of providing examples to the respondents, it can help respondents to

understand what they need to answer without leading them with answers.

3.3.4 Data Screening

The data screening process is to identify the respondent that give meaningless response or

with extreme response. Questionnaire that have 1 sided response are screened out.

Questionnaire that is visible to be answered with random selection by the respondents are

selected out. Extra questionnaire are conducted to match the sampling size of 102.

3.4 Factor Analysis

Factor analysis will be run for all the data collected. Data of the behavioural belief, normative

belief, and control belief will be used to test in factor analysis. There will be an elimination of

cross-loading items and items which have a factor score lower than 0.50. Also items with

reliability of a Cronbach’s alpha (α<.60) will be selected to be the variables of the TPB model

in this research. The research will take the items of outcome evaluation, subjective norm and

control power that according to their beliefs which is satisfied the above requirement.

3.5 Multiple Regression

Multiple regression are used in predicting the unknown value from a known value in statistic.

As TPB model is about predicting to the behaviour, therefore multiple regression is used in

this research. According to TPB intervention (Ajzen, 2006), to predict the intention towards 28

the behaviour, the attitude towards behaviour, subjective norm and perceived behaviour

control will be run in multiple regression. As intention is weighted by these three elements,

which it use multiple instead of single regression. The regression coefficient will be

calculated and display the weight of each elements towards the intention and the path between

different elements. The score of the regression will between 0-1, with the larger score. It

represent that the elements is highly predicted to have such behaviour. The path between

attitude, subjective norm and perceived behavioural control will show how possible that the

variable predict or affect the other variable to be happened.

Chapter 4

4.1 Demographics Descriptive (Frequencies and Frequency Table)

Respondents (secondary students) of the study (N=102) are proportionally drawn from

secondary schools with different exercise habit (exercise regularly, exercise irregularly)

across the four districts (Hong Kong Island, Kowloon, New Territories East and West) of

Hong Kong. The school is randomly selected within each four different districts: Shau Kei

Wan Government Secondary School (HKI), Po Leung Kuk No.1 W.H. Cheung College

(KWL), SKH Lam Kau Mow Secondary School (NTE), and CUHK FAA Thomas Cheung

Secondary School (NTW). Students of secondary 1 to 6 (F1-6) of each four schools are

invited randomly to participate in the present study. Among these respondents, 44 are male

students and 58 are female students of the ages between 11-14, 15-18 or above 18. The

distribution (by age, gender, form and district) is shown in Table 1. We can see that

respondents above 18 has little sample, and the most respondents are come from junior, which

have 63 and senior have 39.

Table 4.1: Demographic characteristic of respondents

Districts HKI KWL NTE NTW Total

Gender Male 11(61.6%) 10(31.3%) 12(50%) 11(39.3%) 44(43.1%)

Female 7(38.9%) 22(68.8) 12(50%) 17(60.7%) 58(56.9%)

Total 18(100%) 32(100%) 24(100%) 28(100%) 102(100%)

Age 11-14 5(27.85%) 20(62.5%) 14(58.3%) 9(32.1%) 48(47.1%)

14-18 13(72.7%) 12(37.5%) 9(37.5%) 18(64.3%) 52(51%)

Above 18 0(0.0%) 0(0.0%) 1(4.2%) 1(3.6%) 2(2.0%)

29

Total 18(100%) 32(100%) 24(100%) 28(100%) 102(100%)

Form Form 1 0(0.0%) 5(18.8%) 3(12.5%) 5(14.3%) 13(12.7%)

Form 2 1(5.6%) 14(43.8%) 11(45.8%) 5(14.3%) 30(29.4%)

Form 3 7(38.9%) 4(12.5%) 4(16.7%) 5(17.9%) 20(19.6%)

Form 4 5(27.8%) 5(15.6%) 0(0.0%) 5(17.9) 15(14.7%)

Form 5 5(27.8%) 3(9.4%) 3(12.5%) 7(25.0%) 18(17.6%)

Form 6 0(0.0%) 0(0.0%) 3(12.5%) 3(10.7%) 6(5.9%)

Total 18(100%) 32(100%) 24(100%) 28(100%) 102(100%)

Male students and female students have significant relationship in exercise habits, from

Pearson Chi-Square, the significant is 0.008. It displayed in Table 2 below. Using crosstab,

male with exercise habit have 59.1%, compare with female, there only 32.8%, they tend to

have no exercise habit in the past three months, which has 67.2% of female respondents.

Table 4.2: Cross tabulation of respondents ‘exercise habit with different gender .

Exercise Habit

TotalYes No

Gender

Male

Count 26 18 44

% within Gender 59.1% 40.9% 100.0%

% within Exercise Habit 57.8% 31.6% 43.1%

% of Total 25.5% 17.6% 43.1%

Female

Count 19 39 58

% within Gender 32.8% 67.2% 100%

% within Exercise Habit 42.2% 68.4% 56.9%

% of Total 18.6% 38.2% 56.9%

Total Count 45 57 102

% within Gender 44.1% 55.9% 100%

% within Exercise Habit 100% 100% 100%

% of Total 44.1% 55.9% 100%

30

Chi-Square Tests

Value df Asymp. Sig.

(2-sided)

Exact Sig.

(2-sided)

Exact Sig.

(1-sided)

Pearson Chi-Square 7.037a 1 0.008

Continuity Correctionb 6.009 1 0.14

Likelihood Ratio 7.088 1 0.008

Fisher's Exact Test

Linear-by-Linear

Association

6.968 1 0.008 0.009 0.007

N of Valid Cases 102

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 19.41.

b. Computed only for a 2x2 table

Compare with gender and sports they prefer, using crosstab, the Pearson Chi-Square is 0.000,

it has an important relationship between each other. It has shown in Table 3. We can found

out that male respondents like to play basketball, which has 45.5%, following would be

running and football, male respondents prefer ball sports that are quite sporty and outgoing.

However, female respondents like to running, there is 56.9%, and following would be

badminton and swimming, which is 13.8% and 8.6%. Female choose badminton are more

than male, compare with male students, they only have 6.8%, girls prefers this leisure sports.

Overall, both of them like running for their prefer exercise.

Table 3 Crosstabulation of respondent’s prefer sports with different gender.

Prefer Sports

TotalBasketbal

l

Football Swimmin

g

Running Badminto

n

Dancing Other

Gender Male Count 20 4 3 7 3 1 6 5

% within

Gender

45.5% 9.1% 6.8% 15.9% 6.8% 2.3% 13.6% 100%

% within

Prefer

87.0% 100.0% 37.5% 17.5% 27.3% 25.0% 50.0% 43.1%

31

sports

% of

Total

19.6% 3.9% 2.9% 6.9% 2.9% 1.0% 5.9% 43.1%

Female Count 3 0 5 33 8 3 6 58

% within

Gender

5.2% 0.0% 8.6% 56.9% 13.8% 5.2% 10.3% 100.0%

% within

Prefer

sports

13.0% 0.0% 62.5% 82.5% 72.7% 75.0% 50.0% 56.9%

% of

Total

2.9% 0.0% 4.9% 32.4% 7.8% 2.9% 5.9% 56.9%

Total Count 23 4 8 40 11 4 12 102

% within

Gender

22.5% 3.9% 7.8% 39.2% 10.8% 3.9% 11.8% 100.0%

% within

Prefer

sports

100.0% 100.0 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of

Total

22.5% 3.9% 7.8% 39.2% 10.8% 3.9% 11.8% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 35.994a 6 0.000

Likelihood Ratio 39.954 6 0.000

Linear-by-Linear

Association

13.892 1 0.000

N of Valid Cases 102

a. 7 cells (50.0%) have expected count less than 5. The minimum expected count is 1.73.

The number of times per week in which students participated in “moderate” physical activity

outside of school hours, separated by sex and exercise habit is shown in Table 4. As we are

doing the research of a behavior of people doing exercise for at least 20 minutes in three times

a week, in the four different districts in total, only 69.2% of male and 52.6% of female can

reach this standard to do exercise up to three times a week, and there are 7.7% of male and

32

15.8% of female students with an exercise habit tend to 5 times per week. For students with

no exercise habit, there are 20.5% of female that perform zero physical activity per week,

compared to only 11.1% of male. These differences were significant between exercise

frequency per week (p < 0.05), and between sexes with different exercise habit (<0.05).

Moreover, significantly there are 55.6% of male and 53.8% of female students with no

exercise habit still manage to participate one time of “moderate” physical activity per week,

and 33.3% of male and 17.9% of female perform two times a week.

Table 4 Crosstabulation of average times spent exercising per week for two genders with

their exercise habit .

Gender Average time

0 1 time

per

week

2 times

per

week

3 times

per

week

4 times

per week

5 times

per week

Total

Male Exercise

Habit

Yes Count 0 2 6 7 9 2 26

% within

Exercise

Habit

0.0% 7.7% 23.1% 26.9% 34.6% 7.7% 100.0%

% within

average

time

0.0% 16.7% 50.0% 100.0% 100.0% 100.0% 59.1%

Total 0.0% 4.5% 13.6% 15.9% 20.5% 4.5% 59.1%

No Count 2 10 6 0 0 6 18

% within

Exercise

Habit

11.1% 55.6% 33.3% 0.0% 0.0% 0.0% 100.0%

% within

average

time

100% 83.3% 50.0% 0.0% 0.0% 0.0% 40.9%

Total 4.5% 22.7% 13.6% 0.0% 0.0% 0.0% 40.9%

Total Count 2 12 12 7 9 2 44

% within

Exercise

Habit

0.0% 27.3% 27.3% 15.9% 20.5% 4.5% 100.0%

33

% within

average

time

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Total 4.5% 27.3% 27.3% 15.9% 20.5% 4.5% 100.0%

Female Exercise

Habit

Yes Count 0 2 7 4 3 3 19

% within

Exercise

Habit

0.0% 10.5% 36.8% 21.1% 15.8% 15.8% 100.0%

% within

average

time

0.0% 8.7% 50.0% 57.1% 100.0% 100.0% 32.8%

Total 0.0% 3.4% 12.1% 6.9% 5.2% 5.2% 32.8%

No Count 8 21 7 3 0 0 39

% within

Exercise

Habit

20.5% 53.8% 17.9% 7.7% 0.0% 0.0% 100.0%

% within

average

time

100.0% 91.3% 50.0% 42.9% .0% .0% 67.2%

Total 13.8% 36.2% 12.1% 5.2% .0% .0% 67.2%

Total Count 8 23 14 7 3 3 58

% within

Exercise

Habit

13.8% 39.7% 24.1% 12.1% 5.2% 5.2% 100.0%

% within

average

time

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Total 13.8% 39.7% 24.1% 12.1% 5.2% 5.2% 100.0%

Chi-Square Tests

Gender Value df Asymp. Sig. (2-

sided)

Male Pearson Chi-

Square

24.695a 5 .000

34

Likelihood Ratio 32.085 5 .000

Linear-by-Linear

Association

21.601 1 .000

N of Valid Cases 44

Female Pearson Chi-

Square

26.038b 5 .000

Likelihood Ratio 30.806 5 .000

Linear-by-Linear

Association

23.668 1 .000

N of Valid Cases 58

a. 9 cells (75.0%) have expected count less than 5. The minimum expected

count is .82.

b. 8 cells (66.7%) have expected count less than 5. The minimum expected

count is .98.

Table 5 shows the perceived frequency between the four types of factor (family,

classmates/friends, school or oneself) which driven the respondents to exercise at first and the

four types of person (family, classmate/friends, oneself or others) the respondent often

exercise with. With regards of the respondents being driven by the same type of factor at first

and still exercise with them in the present, a significant difference in genders is found, with

greater frequency coming from female students. Data shows that 87.5% of female students are

driven by family members to exercise at first and still remain exercising with them in the

present, compare to male students with only 42.9%. Moreover, 35.7% of female students that

are driven by classmate/friend and 42.9% of female students that are driven by school prefer

exercising with classmate or friends. Overall, data shows that female students are more likely

to exercise with the same type of person which driven them to exercise at first. However,

male students in major prefer exercising with friends/classmates even when they are not

driven to exercise by friends/classmates or school at first. So, the obvious difference is female

prefer to do exercise with their family member, and male students prefers to do with their

classmates and friends.

35

Table 5. Crosstabulation of frequency score between the active person and the person to

exercise with.

Gender Sport with Total

family classmate/friend alone other

Male Active

person

Family Count 3 4 1 0 8

% within

activate

sport

person

37.5% 50.0% 12.5% .0% 100.0%

% within

Sport

with

42.9% 14.8% 11.1% .0% 18.2%

% of

Total

6.8% 9.1% 2.3% .0% 18.2%

Classmate/friend Count 2 13 1 1 17

% within

activate

sport

person

11.8% 76.5% 5.9% 5.9% 100.0%

% within

Sport

with

28.6% 48.1% 11.1% 100.0% 38.6%

% of

Total

4.5% 29.5% 2.3% 2.3% 38.6%

School Count 1 4 1 0 6

% within

activate

sport

person

16.7% 66.7% 16.7% .0% 100.0%

% within

Sport

with

14.3% 14.8% 11.1% .0% 13.6%

% of

Total

2.3% 9.1% 2.3% .0% 13.6%

36

Myself Count 1 6 6 0 13

% within

activate

sport

person

7.7% 46.2% 46.2% .0% 100.0%

% within

Sport

with

14.3% 22.2% 66.7% .0% 29.5%

% of

Total

2.3% 13.6% 13.6% .0% 29.5%

Total Count 7 27 9 1 44

% within

activate

sport

person

15.9% 61.4% 20.5% 2.3% 100.0%

% within

Sport

with

100.0% 100.0% 100.0% 100.0% 100.0%

% of

Total

15.9% 61.4% 20.5% 2.3% 100.0%

Female Active

person

Family Count 14 2 2 18

% within

activate

sport

person

77.8% 11.1% 11.1% 100.0%

% within

Sport

with

87.5% 7.1% 14.3% 31.0%

% of

Total

24.1% 3.4% 3.4% 31.0%

Classmate/friend Count 0 10 6 16

% within

activate

sport

.0% 62.5% 37.5% 100.0%

37

person

% within

Sport

with

.0% 35.7% 42.9% 27.6%

% of

Total

.0% 17.2% 10.3% 27.6%

School Count 0 12 2 14

% within

activate

sport

person

.0% 85.7% 14.3% 100.0%

% within

Sport

with

.0% 42.9% 14.3% 24.1%

% of

Total

.0% 20.7% 3.4% 24.1%

Myself Count 2 4 4 10

% within

activate

sport

person

20.0% 40.0% 40.0% 100.0%

% within

Sport

with

12.5% 14.3% 28.6% 17.2%

% of

Total

3.4% 6.9% 6.9% 17.2%

Total Count 16 28 14 58

% within

activate

sport

person

27.6% 48.3% 24.1% 100.0%

% within

Sport

with

100.0% 100.0% 100.0% 100.0%

38

% of

Total

27.6% 48.3% 24.1% 100.0%

Chi-Square Tests

Gender Value df Asymp. Sig. (2-sided)

Male Pearson Chi-Square 12.240a 9 .200

Likelihood Ratio 11.686 9 .232

Linear-by-Linear Association 3.990 1 .046

N of Valid Cases 44

Female Pearson Chi-Square 39.004b 6 .000

Likelihood Ratio 43.425 6 .000

Linear-by-Linear Association 9.698 1 .002

N of Valid Cases 58

a. 14 cells (87.5%) have expected count less than 5. The minimum

expected count is .14.

b. 9 cells (75.0%) have expected count less than 5. The minimum

expected count is 2.41.

Attitude towards the behaviour

Descriptive Data of Attitude (direct measure)

Mean

SD

1. Beneficial-harmful 6.22 0.09

2. Pleasant-unpleasant 5.31 0.15

3. Relaxing-stress 5.02 0.14

4. Saving-waste time 4.18 0.15

5. Satisfaction-

exhausted4.96 0.15

6. Spiritual-tired 4.74 0.17

Reliability 0.769

39

The reliability of the direct measure of attitude is good, which have a 0.769 Cronbach’s

Alpha. In the data, we revealed that respondents have a positive attitude towards physical

activity when it comes to physical health and mental health. The direct attitude mean shows

that respondent think doing physical activity for 3 times per week, at least 20 minutes each

time is mostly beneficial for them. The weakest attitude towards the behaviour is the matter of

time. Which most of them think doing physical activity are waste of time, which the mean

score are the lowest among all?

The factor analysis of the direct measure of the attitude shown a KMO of 0.778. Only 1

component is extracted in the factor analysis, as there is low percentage in variance of the

component to the sample.

40

Behavioural Belief x Outcome Evaluation

Descriptive Data of Attitude

Belief Outcome Evaluation

Mean SD Mean SD

1. Healthy Body 5.97 0.96 6.03 0.10

2. Enlarge Social

Network4.79 1.19 4.84 0.13

3. Ideal Body 4.93 1.12 4.74 0.11

4. Waste Time 4.36 1.35 3.72 0.13

5. Relax 5.22 0.95 5.23 0.10

6. Reduce Stress 5.25 1.18 5.28 0.12

7. Perseverance 5.27 1.26 5.17 0.12

8. Attract Opposite

Gender3.28 1.13 3.51 0.11

9. Set Goal 5.00 1.24 5.09 0.12

Reliability 0.737 0.821

The reliability of question 4 items, behavioural belief, is adequate by a Cronbach’s Alpha of

0.737. In these items, ‘healthy body’ is the belief which have the highest mean of 5.97±0.959.

Respondents have a relative high response to physical and mental health related questions,

which it can general said that students have a deep understanding to the benefits of physical

activity that related to health matters. As respondents have high means to aware the health

benefits from physical activity and see them as a highly positive outcomes. However,

response that related to other kinds of benefits of health like enlarge social network and attract

opposite gender attention is not obvious to respondents. Respondents don’t see these

alternative benefits will easily be get from physical activity and even have a relatively low

response to their outcome.

KMO and Bartlett's Test of Behavioural Belief

KMO 0.781

Chi-Square 200.439

df 36

Sig. 0.0041

42

Behavioural Beliefs Rotated Component Matrix

Component

1 2

1.Reduce Stress 0.756

2.Set Goal 0.702

3.Social Network 0.701

4.Relax 0.664

5.Perseverance 0.608

6.Healthy Body 0.583

7.Ideal Body

8.Attract opposite 0.73

9.Waste Time -0.725

The factor analysis of the behavioural belief is having a KMO of 0.781. In the factor analysis,

two major groups can be separated. In the factor analysis, 2 component is extracted. The

factors in the 2 component will have a cumulative variance of 50%. Which these factors can

change 50% of the total sampling. In the component 1, it can shows that these group of

respondent is majorly concern on the physical and mental health of themselves. In component

2, it shows that they are seeing physical activity as an opportunity to attract opposite gender,

therefore they are more willing to devote more times in it. ‘Ideal body’ is being removed from

the facto analysis, as it have a low component score that is less than 0.5. This factor will not

be used in the analysis in the further stages.

KMO and Bartlett's Test of Outcome 43

Evaluation

KMO 0.867

Chi-Square 309.708

df 36

Sig. 0.00

Outcome Evaluation Rotated Component Matrix

Component

1 2 3

1.Lower Stress 0.832

2.Relaxing 0.812

3.Social Network 0.781

4.Build

Perseverance 0.658

5.Achieve Goal 0.645

6.Healthier 0.635

7. Oppo. Genders 0.846

8.Body Shape 0.762

9.No Time 0.938

The factor analysis of the outcome evaluation is having a high KMO of 0.867. Items removal

is based on the factor analysis of the behavioural belief. As the outcome evaluation is the

stage to measure the strength of the beliefs. In this factor analysis, we can see three groups of

segments. The first groups are the respondents that have high preference to physical and

mental health, which they think that as a positive outcome. The second group can be seen as

the students that focus on attracting opposite genders. Therefore, they see better body shapes

as a positive outcome. The third group see physical activity as a bad activity, as they think it

is waste of their time and it is not an out outcome.

44

Attitude Correlation

Table 4.3: Correlation Matrix of Behavioural Belief

1 2 3 4 5 6 7 8 Mean SD

11 .338** .024 .311** .367** .326** .200* .241*

5.97

0.9

6

21 .088 .312** .381** .379** .308** .501**

4.79

1.1

9

31 .162 .066 -.030 -.225* .160

4.36

1.3

5

41 .518** .239* .090 .285**

5.22

0.9

5

51 .474** .303** .427**

5.25

1.1

8

6 1 .425** .386** 5.27 1.3

71 .120

3.28

1.1

3

81

5.00

1.2

4

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Keynotes: 1=Healthy Body 2=Social Network 3=Waste Time 4=Relax

5=Reduce Pressure 6=Perseverance 7=Attract Opposite Gender 8=Goal

In the correlation of the belief. We find that respondent have a high correlation between

relaxing and reducing pressure (r=0.518**), which relaxing and reducing pressure can be seen

as a whole in the benefits of the mental health. Respondent think that relaxing, also think that

physical activity can also help them to reduce their life pressure. Perseverance and reducing

pressure have a moderate degree of correlation (r=0.474**). Also, setting goal and social

network have a moderate correlation (r=0.501**) and reducing pressure (r=0.427**).

Respondent think that by doing physical activity can help them set up goal, as well as training

their perseverance. It can be interpret that respondent will benefits from high perseverance

after they achieve certain goal from physical activity. These three items can be seen as

45

correlated, which respondents see doing physical activity can help them to set up goals. By

achieving it, they can train up their perseverance and face more pressure in challenges.

Table 4.3: Correlation Matrix of Behavioural Belief (Male)

1 2 3 4 5 6 7 8 Mean SD

1 1 .279 .218 .323* .322* .018 .002 .175 6.2 0.85

2 1 .187 .269 .215 .344* .234 .526** 4.98 1

3 1 .228 .159 .053 -.112 .303* 4.41 1.42

4 1 .397** .135 .005 .356* 5.48 0.82

5 1 .099 .141 .154 5.66 0.94

6 1 .211 .405** 5.48 1.05

7 1 .102 3.66 0.86

8 1 5.11 1.24

AT .496** .689** .370* .544** .482** .516** .326* .708** 27.32 5.77

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Keynotes: 1=Healthy Body 2=Social Network 3=Waste Time 4=Relax

5=Reduce Pressure 6=Perseverance 7=Attract Opposite Gender 8=Goal

AT=Attitude

Table 4.3: Correlation Matrix of Behavioural Belief (Female)

1 2 3 4 5 6 7 8 Mean SD

1 1 .323*-

0.1220.248 .327* .445** 0.213 .266* 5.79 1.005

2 1 0.019 .280*.398*

*.369** .277* .486** 4.48 1.287

3 1 0.117 0.000 -0.090 -.329* 0.039 4.33 1.303

4 1.521*

*0.251 0.029 0.226 5.02 1.000

5 1 .610** .275* .583** 4.95 1.248

6 1.483*

*.371** 5.12 1.390

7 1 0.103 3.00 1.228

46

8 1 4.91 1.247

AT .612** .673** -.005 .453** .774** .702** .409** .684** 23.12 5.94

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Keynotes: 1=Healthy Body 2=Social Network 3=Waste Time 4=Relax

5=Reduce Pressure 6=Perseverance 7=Attract Opposite Gender 8=Goal

The correlation by different gender also shows an important results. In male, there is high

correlation of attitude towards enlarge social network (r=0.689) and setting goal (r=0.708). It

can explain that the attitude of physical activity of male is highly depends of meeting new

friends and achieve their goal. As meeting new friends and achieving their physical activity

goal can help new to have a high attitude to do physical activity. It can be interpret that male

respondent wish physical activity to make them face challenges and new teammates. To

female, physical activity is more alike to enrich their inner beauty. Female have a high

correlation of reducing pressure (r=0.774) and train up perseverance (r=0.684). It can interpret

that female respondent is having a high attitude to perform physical activity when they have

high belief of reduce pressure and train up themselves to be more tough.

Attitude Regression

Table 5.2: Regression of Attitude

Step Variables R2 R2 change β

1 0.824 0.822

BB 0.924**

2 0.830 0.828

OE 0.911**

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Keynotes: BB= Behavioural Beliefs OE= Outcome Evaluation

The results of the attitude’s regression have shown the weighting of the beliefs and outcome

evaluation. Both of the regressions are significant. Behavioural belief (β=0.924) have a

slightly higher weighting than outcome evaluation (β=0.911). Respondent is slightly focus on

the strength of the belief will happen more than how they judge their outcome. It is about the 47

possibility that students see what they are doing will make them to enjoy the results more than

how good it the results.

48

Subjective Norm

Descriptive Data of Attitude

Mean SD

1. Approval 5.94 1.00

2. Should 5.44 1.29

3. Motivation to Comply 5.21 1.14

Reliability 0.773

The reliability of the subjective norm items are adequate (α=0.773). In the data, normative

belief are measure by using approval of the others and whether other’s think that they should

do such behaviour. The mean score of ‘approval’ and ‘should do’ is relatedly close. Which

respondent perceived that most important person have a positive normative belief on doing

physical activity. The most important people to the respondent is classmate/friends (53%) and

family (42%). As the minimum score of approve to do physical activity is 4, which it can be

interpreted that the most important people to respondent don’t have a negative normative

belief on physical activity to the respondent. The mean of the whole subjective norm data is

relatively have a score of 5. It can represent that the respondents’ norm have a positive belief

about physical activity and willing to comply with it.

49

Subjective Norm Correlation

Correlation Matrix of Self-efficacy

SE RM MC

SE 1 0.154 0.424**

RM 1 0.245*

MC 1

**. Correlation is significant at the 0.01 level

(2-tailed).

*. Correlation is significant at the 0.05 level (2-

tailed).

SE= Self-efficacy

RM= Role modelling

MC= Motivation to Comply

The correlation shows that motivation to comply is having high relation to the self-control of

the respondent(r=0.424**). It display that hen the respondent have a higher self-efficacy, they

have high motivation to comply with the normative belief. As it is a moderating role of the

model between PBC and SN. Which the motivation to comply is highly related to self-control.

This correlation can explain the control power of the respondent, whether they control

themselves to do physical activity. This correlation shows that whether the respondent choose

to do the normative belief is mostly based on their control power more than role modelling

their most important person.

50

Subjective Norm Regression

Table 5.2: Regression of Subjective Norm

Step Variables R2 R2 change β

1 0.689 0.686

NB 0.830**

2 0.801 0.799

MC 0.895**

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Keynotes: NB= Normative Beliefs MC= Motivation to Comply

In the regression of the subjective norm, it can shows that the motivation to comply (β=0.895)

have a higher weighing to the subjective norm than the normative belief (β=0.830). As the

correlation stated. Respondents have control power to choose to listen the normative belief or

not.

The

determination of the subjective norm is highly based on the motivation to comply.

51

52

PBC 

Descriptive Data of PBC

Control Belief Control Power

Mean SD Mean SD

Academic 4.28 1.61 4.59 1.58

Accompan

y 4.43 1.67 5.23 1.32

Time 4.28 1.47 5.57 1.1

Reliability 0.33 0.757

Item Total Statistic of PBC

Scale Variance if Cronbach's Aplha

Item Deleted if Item Deleted

Academic 7.334 0.645

Accompan

y 4.565 -0.080

Time 5.334 -0.019

The measures of PBC have two parts, control belief multiply by control power. The data

represent a low reliability of control belief (α=0.33), ‘academic’ items is removed to improve

reliability to α=0.645. In the control belief, the means of all items are around 4, which shows

that respondent don’t have a strong opinion on the current situation about the existence of the

above items. Control power have an adequate reliability of (α =0.757). Control power shows

that ‘accompany’ and ‘time’ have a high means of above 5. It indicate that most respondents

think that with the existence of ‘accompany’ and ‘time’ can motivate them to do physical

activity.

PBC direct measure (self-efficacy)

Descriptive Data of Self-efficacy

Mean SD

Confidence 4.56 1.56

53

Self-control 4.41 1.39

Difficulties 4.3 1.54

Reliability 0.873

The reliability of the self-efficacy is having α=0.873. In the data, it don’t shows that

respondents mostly have a high mean to do physical exercise. Having confidence to do

physical activity have the highest mean of 4.56. The respondent don’t have a strong self-

efficacy in doing physical activity. Respondent are having a uncertainty to their control ability

of their own which they have neutral point of view on motivating themselves to do physical

activity. Factor to influence more than themselves.

54

PBC Correlation

Correlation Matrix of Self-Efficacy and PBC

SE1 SE2 SE3 CB1 CB2 CB3 Mean SD

SE1 1 0.781** 0.680** 0.244* 0.465** 0.491** 4.56 1.56

SE2 1 0.635** 0.16 0.481** 0.495** 4.41 1.39

SE3 1 0.129 0.479** 0.647** 4.3 1.54

CB1 1 -0.01 -0.04 4.28 1.61

CB2 1 0.480** 4.43 1.67

CB3 1 4.28 1.47

PB

C0.636** 0.643** 0.694** 0.17 0.773** 0.829** 24.16

10.5

2

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Keynotes: SE1= Confidence SE2= Self-Control SE3= Difficulties

CB1= Academic CB2= Accompany CB3= Time

In PBC, it shows that the Total PBC have a high correlation with ‘Adequate time’ and

‘Accompanies’ (r = 0.773**; r = 0.829**). The correlations explain that when respondent

have more time and more people to physical activity with, they will achieve a higher PBC in

controlling their physical activity. It can shows that having enough time and others to doing

exercise is, are the important factor to help secondary school students to do physical activity.

Other than having enough time to do physical activity, students also wish to have other people

to join them to do physical activity. Which these two factors are best to be together to help

students to have a higher control ability to do physical activity.

Also, in the correlation with the PBC direct measures. We discover that respondent have high

correlation with confidence and self-control with PBC of ‘accompany by others’. It can

display that when students have others to perform physical activity with them, they can have

more confidence and control ability on physical activity. Also, high correlation is between

‘difficulties’ and ‘time’. It can show that with more times provided, the respondents will see

physical activity as a more easy behaviour to achieve. It can explain that respondent control

ability is majorly from the external control environment instead of their self-control. External

control factors can give respondent assistance on their own confidence.

55

Correlation Matrix of Self-Efficacy and PBC (male)

SE1 SE2 SE3 CB1 CB2 CB3 Mean SD

SE1 1 0.748** 0.592** 0.234 0.556** 0.343* 4.56 1.56

SE2 1 0.521** 0.176 0.491** 0.360* 4.41 1.39

SE3 1 -0.420 0.590** 0.594** 4.3 1.54

CB1 1 0.480 -0.112 4.28 1.61

CB2 1 0.510** 4.43 1.67

CB3 1 4.28 1.47

PB

C0.716** 0.644** 0.642** 0.328* 0.723** 0.697** 27.77

11.7

6

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Keynotes: SE1= Confidence SE2= Self-Control SE3= Difficulties

CB1= Academic CB2= Accompany CB3= Time

Correlation Matrix of Self-Efficacy and PBC (female)

SE1 SE2 SE3 CB1 CB2 CB3 Mean SD

SE1 1 0.773** 0.687** 0.167 0.363 0.525** 4.56 1.56

SE2 1 0.668** 0.052 0.443** 0.535** 4.41 1.39

SE3 1 0.164 0.329* 0.634** 4.3 1.54

CB1 1 -0.139 -0.092 4.28 1.61

CB2 1 0.415** 4.43 1.67

CB3 1 4.28 1.47

PB

C0.556** 0.612** 0.635** 0.232 0.576** 0.765** 21.41 8.60

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Keynotes: SE1= Confidence SE2= Self-Control SE3= Difficulties

56

CB1= Academic CB2= Accompany CB3= Time

In male, we discover that PBC have a highest correlation with confidence (α=0.716). Male

required more confidence to achieve a higher PBC of doing physical activity. Also, male

respondent sees friends accompany (α=0.723) as the most correlated items with the PBC,

which males depends on more accompany from others to have a greater power of PBC to

motivate them to do physical activity. For female, confidence is the least correlated items to

PBC (α=0.556) but difficulties in doing physical activity is the most related item (α=0.635).

Female do not required as high confidence as female to have control over doing physical

activity. But they see difficulties on doing the physical activity, which they may related to

more easy and simple activity to get a high control. The most correlated control belief is the

time factor (α=0.765) to female. Unlike male, female respondent don’t see accompany so

related to control over physical activity. But they require more time on physical activity. With

the support of the frequency data of the people that they sport with, female have a less

percentage to sport with classmates/friends (male: 61.4%, female: 41.3%), but female is more

likely to sports alone or with family. (Male: 20.5%, 15.9%; female: 24.1%, 27.6%) It can

interpret that male is more outgoing that do physical activity with friends, but female is more

ingoing that like to do physical activity themselves or family, therefore, they have different

preference of the time control belief factors.

PBC Regression

Table 5.2: Regression to PBC

Step Variables R2 R2 change β

1 0.861 0.860

CB 0.928**

2 0.550 0.546

CP 0.742**

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Keynotes: CB= Control Beliefs CP= Control Powers

The regression of the PBC shows that control belief have a higher weighting (β=0.928) than

control power (β=0.742). The PBC situation is alike the regression of attitude. Respondents is 57

more focus on the expectation and the possibility that control belief will happen. In this

regression, it can say that respondent are more a passive position. The control power items

shows that they have a higher PBC in physical activity, but respondent are more focus on

whether the control belief is exist in current situation. It is important that respondent need to

perceived that the change of the external control factor

58

Intentions and Behaviour

Descriptive Data of Intention and Behaviour

Mean SD

Plan 4.824 1.512

Think 5.029 1.293

Expect 4.471 1.54

Intention 4.775 1.339

Reliabilit

y 0.911

Behaviou

r 4.01 1.626

Intention items is having a high reliability (α=0.911). The mean of the ‘expect to continue’ of

the physical activity is the lowest of 4.47. Which it can explain that most of the respondent

have an uncertainty of whether they can continuously do physical activity as a habits for 3

months. ‘Think’ of having physical activity have the highest mean among all items. Generally

speaking, respondent are only having a intention to have pre-working and try-working process

of the physical activity, however, they have low intention to complete on what they have

planned or keep up the habits.

In the measure of the behaviour, a mean of 4.01 is generated. In terms of doing physical

activity, respondents shows an uncertainty whether they will participate into the behaviour.

59

Intention Regression

Table 5.1: Regression to predict intention analysis

Step Variables R2 R2 change β

1 0.870 0.869

INT_Plan 0.933**

2 0.845 0.843

INT_Think 0.919**

3 0.847 0.845

INT_Expect 0.920**

60

Regression of intention is used with 3 items: Plan, Think and Expect. In the regression

‘planning’ of the behaviour have the highest weighting (β=0.933) followed by ‘expectation to

finish’ (β=0.920). The ‘think’ of doing physical activity intention is β=0.919. In the

correlation of the intention items, ‘Plan and think’ is highly correlated with α=808.

Respondent that have a planning of doing physical activity, may think to give it a try on work

it out. Correlation with expect to finish is less related with α=0.772. Which respondents may

have try out the physical activity behaviour, they are no expect that they can finish the

behaviour for 3 months.

In this regression, expectation to finish is a second high weighted item to intention, it can

related that respondent will evaluate whether they can finish the behaviour before they

starting it, when they have a high expectation to finish what they have decided, they will have

a higher intention to do the behaviour.

4.6 Others

4.6.1 Crosstabulation

According to our research result, 44.1% of respondent who has an experience to do physical

activity more than 30 minutes in at least 3 days a week in last three month (exercise habit)

while 55.9% of respondent have no exercise habit. Base on this question, a result of the

crosstabs shows that activate sport person, suitable times, average times and average minutes

are closely associated with exercise habit of respondents.

Refer to Table 28 below, respondent who has exercise habit is related to the person who

motivate them to do physical activities in the first time, the significant in Pearson-chi square

is 0.011. If the person who has exercise habit in the last three months, 42.2% of respondents

are motivated by their friends and classmates and only 6.7% of them are motivated by school.

In contrast, there are 29.8% and 28.1% of respondents who have no exercise habit are

motivated by school and family respectively. From the result, we observe that friends and

classmates are important to motivate the others to participate in physical activities. Moreover,

Students are relied on school to motivate them to participate in physical activities if they do

not have exercise habit. Although they are motivated by school and family, they failed to have

an exercise habit. As the result, school may not enhance the interest to do exercise of the

students.

Table 28. Crosstabulation of respondents ‘exercise habit and Active sport person with

different gender 61

Exercise Habit Total

Yes No

Active

sport

person

Family Count 10 16 26

% within

Exercise Habit

22.2% 28.1% 25.5%

% of Total 9.8% 15.7% 25.5%

Classmate/friend Count 19 14 33

% within

Exercise Habit

42.2% 24.6% 32.4%

% of Total 18.6% 13.7% 32.4%

School Count 3 17 20

% within

Exercise Habit

6.7% 29.8% 19.6%

% of Total 2.9% 16.7% 19.6%

Myself Count 13 10 23

% within

Exercise Habit

18.9% 17.5% 22.5%

% of Total 12.7 9.8% 22.5%

Total Count 45 57 102

% within

Exercise Habit

100.0% 100.0% 100.0%

% of Total 44.1% 55.9% 100.0%

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 11.075a 3 0.011

Likelihood Ratio 11.953 3 0.008

Linear-by-Linear

Association

0.060 1 0.806

N of Valid Cases 102

a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 8.82.

In the research, respondents are required to set a suitable standard times and minutes to do

physical activities per week. Result of crosstabs (Table 29) displays that the suitable times and

their exercise habit have a significant relationship which Pearson Chi-Square is 0.000, while it

62

is not related to suitable standard minutes. If the student has an exercise habit, they tend to do

more exercise per week. 40% of respondents set a standard which is do physical activities 3

times per week. The percentage of 2, 4 and 5 times per week are similar, they are 17.8%,

17.8% and 15.6%. For the people who do not has exercise habit, they set the standard lower.

43.9% of respondents set it as 2 times per week and there are 26.3% of students think that

the standard should be 1 time per week only. Moreover, respondents with exercise habit are

usually choose the suitable times as 2 to 5 times per week while respondents who do not have

exercise habit are usually choose 1 to 3 times. Refer to the result, it shows that students who

has exercise habit want higher standard and meet the standard set by Hong Kong. Whereas the

suitable standard set by the students who do not have exercise habit is lower than the Hong

Kong indicator.

Table 29. Crosstabulation of respondents ‘exercise habit and Suitable time

Exercise Habit Total

Yes No

Suitable times 1 time per week Count 3 15 18

% within Exercise Habit 6.7% 26.3% 17.6%

% of Total 2.9% 14.7% 17.6%

2 times per week Count 8 25 33

% within Exercise Habit 17.8% 43.9% 32.4%

% of Total 7.8% 24.5% 32.4%

3 times per week Count 18 13 2963

% within Exercise Habit 17.8% 5.3% 10.8%

% of Total 7.8% 2.9% 10.8%

4 times per week Count 7 2 9

% within Exercise Habit 15.6% 3.5% 8.8%

% of Total 6.9% 2.0% 8.8%

5 times per week Count 1 1 2

% within Exercise Habit 2.2% 1.8% 2.0%

% of Total 1.0% 1.0% 2.0%

Total Count 45 57 102

% within Exercise Habit 100.0% 100.0% 100.0%

% of Total 44.1% 55.9% 100.0%

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 22.396a 5 0.000

Likelihood Ratio 23.518 5 0.000

Linear-by-Linear

Association

15.749 1 0.000

N of Valid Cases 102

Same with the result of suitable standard times, there is a significant relationship between

exercise habit and average time to do physical activities per week of the respondents, which

the Pearson Chi-Square is 0.000. Table 30 shown that if the person who has exercise habit,

most of them do physical activities 2 to 4 times per week and there are 28.9%, 24.4% and

26.7% of the respondents respectively. Whereas average time of the respondents who do not

have exercise habit are much lower than the above students and there are only 0 to 2 times per

week to participate in physical activities. They are 17.5%, 54.4% and 22.8% respectively.

These students cannot meet the Hong Kong standard. Since the indicator of Hong Kong

measure both of the average times and minutes, we can combine the result of average times

and average minutes of the students’ exercise habit.

Table 30. Crosstabulation of respondents ‘exercise habit and Average time

64

Exercise Habit Total

Yes No

Average times 0 Count 0 10 10

% within Exercise Habit 0.0% 17.5% 9.8%

% of Total 0.0% 14.7% 17.6%

1 time per week Count 4 31 35

% within Exercise Habit 8.9% 54.4% 34.3%

% of Total 3.9% 30.4% 34.3%

2 times per week Count 13 13 26

% within Exercise Habit 28.9% 22.8% 25.5%

% of Total 12.7% 12.7% 25.5%

3 times per week Count 11 3 14

% within Exercise Habit 24.4% 5.3% 13.7%

% of Total 10.8% 2.9% 13.7%

4 times per week Count 12 0 12

% within Exercise Habit 26.7% 0.0% 11.8%

% of Total 11.8% 0.0% 11.8%

5 times per week Count 5 0 5

% within Exercise Habit 11.1% 0.0% 4.9%

% of Total 4.9% 0.0% 4.9%

Total Count 45 57 102

% within Exercise Habit 100.0% 100.0% 100.0%

% of Total 44.1% 55.9% 100.0%

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 51.701a 5 0.000

Likelihood Ratio 64.518 5 0.000

Linear-by-Linear

Association

48.515 1 0.000

N of Valid Cases 102

a. 3 cells (25.0%) have expected count less than 5. The minimum expected count is 2.21.

For the result of average minutes to participate in each exercise (Table 31), the Pearson-chi-

square in here is 0.002, which has significant relationship here, most of the students who have

65

exercise habit will do physical activities more than 21 minutes each time. 35.6%, 31.1% and

24.4% of respondents spend 21-40 minutes, 41-60 minutes and above 60 minutes in physical

activities respectively. Nevertheless, students who do not have exercise habit do exercise less

than 20 minutes mostly. There are 43.9%, 19.3% and 21.1% of respondents do physical

activities below 20 minutes, 21-40 minutes and 41-60 minutes.

Table 31. Crosstabulation of respondents ‘exercise habit and Average minutes

Exercise Habit Total

Yes No

Average minutes Below 20 minutes Count 4 25 29

% within Exercise Habit 8.9 43.9% 28.4%

% of Total 3.9% 24.5% 28.4%

21-40 minutes Count 16 11 27

% within Exercise Habit 35.6% 19.3% 26.5%

% of Total 15.7% 10.8% 26.5%

41-60 minutes Count 14 12 26

% within Exercise Habit 31.1% 21.1% 25.5%

% of Total 13.7% 11.8% 25.5%

Above 60 minutes Count 11 9 20

% within Exercise Habit 24.4% 15.8% 19.6%

% of Total 10.8% 8.8% 19.6%

Total Count 45 57 102

% within Exercise Habit 100.0% 100.0% 100.0%

% of Total 44.1% 55.9% 100.0%

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 15.286a 3 0.002

Likelihood Ratio 16.804 3 0.001

Linear-by-Linear

Association

8.118 1 0.004

N of Valid Cases 102

a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 8.82.

66

Combine with all of the above data, students who do not have exercise habits are relied to

school in order to motivate them participate in physical activities. The average time doing

physical activities is mostly 1 time and below 20 minutes per week. They cannot meet the

standard set by Hong Kong. Most of them may only do physical activities in the lesson of

Physical Education at school per week. Students set higher suitable times to do exercise and

they think it should be 2 times per week. It is more than the average times that they do and it

shows that the students know that they show do physical activities more. It can be an

opportunity to promote physical activities for them.

4.6.2 Correlation

If the respondent thinks that they are sporty, the intention and behaviour in doing physical

activities more than 30 minutes in at least 3 days a week even there are barriers will be larger

(Table 32). They have better planning, considering and expectation in doing physical

activities. If the respondent thinks that they are healthy, only behaviour becomes larger in

doing physical activity more than 30 minutes in at least 3 days a week. From the result of

correlation, it shows that healthy and sporty students are easier to meet the standard of Hong

Kong indicator.

Table 32 Correlations of intention and behavior

myself as

healthy

myself as

sporty

plan think expect barrier to do

myself as

healthy

Pearson

Correlation

1 0.494** 0.334** 0.306** 0.360** 0.456**

Sig. (2-

tailed)

0.000 0.001 0.002 0.000 0.00

N 102 102 102 102 102 102

myself as

sporty

Pearson

Correlation

1 0.424** 0.431** 0.428** 0.498**

Sig. (2-

tailed)

0.000 0.000 0.000 0.000

67

N 102 102 102 102 102

plan

Pearson

Correlation

1 0.808** 0.772** 0.722**

Sig. (2-

tailed)

0.000 0.000 0.000

N 102 102 102 102

think

Pearson

Correlation

1 0.764** 0.687**

Sig. (2-

tailed)

0.000 0.000

N 102 102 102

expect

Pearson

Correlation

1 0.777**

Sig. (2-

tailed)

0.000

N 102 102

barrier to do

Pearson

Correlation

1

Sig. (2-

tailed)

N 102

**. Correlation is significant at the 0.01 level (2-tailed).

68

Chapter 5 Discussion

5.1 Regression to predict intention

Multiple regression was run by SPSS and the prediction power of each factors towards the

intention. The regression analysis results is shown in table 5.1. Multiple regression is using

backward regression. The Attitude, subjective norm and PBC was first entered in the first

stage of regression and explained 45.9% variance of intention. Attitude and PBC have a

significance beta coefficient in the regression (β =0.213, P <0.05; β =0.552, P <0.01,

respectively) but subjective norm were non-significance. The R2 change of this step is 0.448.

Subjective norm shown the least predictive power (β = -0.13). A negative subjective norm,

suggesting that when other people wish them to do physical activity, they did not have the

intention to do what they advised.

In step 2, subjective norm was extracted advised by the SPSS because of its low significance.

Step 2 represented 45.9% variance of the intention. Attitude and PBC have significance beta

coefficient (β =0.209, P <0.05; β =0.547, P <0.01, respectively). The R2 change of this step is

0.459. Which it have a higher model fitting coefficient than step 1. However, this will remove

subjective norm in the model. Subjective norm was kept in the following process of analysis.

In step 3, the moderating variable, self-efficacy, is added into this model. By considering the

effectiveness of the predicting power of subjective norm. Subjective norm is included in this

model. By including self-efficacy as a variable in prediction of intention, it represented a

60.4% variance of intention. In step 3, only self-efficacy have a significant beta coefficient (β

=0.589, P <0.01). Self-efficacy shown as the most predictive variable towards intention,

followed by PBC and attitude (β =0.178, P >0.05; β =0.088, P >0.05). Still, subjective norm

serve as the weakest variable to predict intention (β = -0.1, P >0.05).

Table 5.1: Regression to predict intention analysis

Step Variables R2 R2 change β

1 0.459 0.448

Attitude 0.213*

Subjective Norm -0.13

PBC

0.552*

*

2 0.459 0.459

Attitude 0.209*

69

PBC0.547*

*

3 0.604 0.588

Attitude 0.88

Subjective Norm -0.1

PBC 0.178

Self-efficacy

0.589*

*

5.2 Regression to Predict Behaviour

In the regression to predict the behaviour, only one step is used. By using the behavioural

intention to predict the behaviour. The regression analysis result is shown in table 5.2. In step

1, the regression of behaviour using intention represent a 62.6% variance of the behaviour.

The variable of intention have a significant beta coefficient in the prediction (β = 0.791, P

<0.01). In this regression, it shown that intention is a good predictor to predict behaviour, as it

have a high R2 change of 0.622 which represent it is well fit into this model.

Table 5.2: Regression to predict behaviour analysis

Step Variables R2 R2 change β

1 0.626 0.622

Intention 0.791**

5.3 Prediction of Intention

In the regression of the intention, it shown further support on the viewpoints from other

researches of theory of planned behaviour. By using subjective norm in TPB prediction, it

represent 45.9% of the variance in intention, also a slightly increase in R2 change, which

indicate a better model fitting than without subjective norm. The results have firstly shown

that PBC is the most predictive variable to prediction of the intention. Subjective norm,

support most of the researches to be the weakest (Conner, 2011; Hagger 2010) and an

irrelevant items (Shepard & Godin, 1986) to predict the intention, as it have a negative beta

coefficient and non-significance variable. Attitude have a low predicting level. Generally

speaking, secondary school students have intention to do behaviour is more based on the

control factor which they have circumstances, environment and people to facilitate and

motivate them to do physical activity. Although subjective norm have non-significance in the

prediction. It shown a high correlation level towards attitude and PBC. Subjective norm is

70

serve as a supporting role to PBC and attitude, which secondary school students may not have

intention directly based on subjective norm, but the advice from people they most concerned

will indirectly affect secondary school students on how they evaluate and perceived the PBC

and attitude.

However, without the self-efficacy, the moderating variable, of the TPB. It cannot explain in a

whole on why secondary school students involve in physical activity. Therefore, the final

stage of regression, self-efficacy is included. It shown a significant change in the prediction,

which self-efficacy proved as a more important role than PBC towards intention (Hagger et

al., 2002). More than external circumstance to facilitate students to have intention, self-

efficacy explain whether students have own control power and certainty to perform such

behaviour. It shown that self-efficacy is the most powerful predictor. The correlation between

self-efficacy and PBC, shown that with a positive circumstance to the students, the control

power is still based on whether they want to perform the behaviour or not. Confidence, self-

control and perceived difficulties is the major drive of self-efficacy. Which male students

required more confidence, and female require a lower perceived behavioural difficulties to

have a higher self-efficacy.

Finally, in the completed model to predict intention shown that both PBC and self-efficacy are

good to motivate a physical activity intention. With subjective norm, it support the students to

perceive they have more external factor to do physical activity.

5.4 Prediction of Behaviour

In the regression, it shown that with a 62.6% variance of the behaviour, a beta coefficient of

0.791. A student have high intention will directly have high possibility to perform physical

activity behaviour. Throughout the whole TPB, from the regression of attitude, subjective

norm, PBC and towards intention. It revealed different variables beliefs have a high predicting

power towards attitude, subjective norm and PBC. However, the attitude, subjective norm and

PBC predictive power is reducing when it is towards the intention. By the high mean of

behavioural outcome belief and evaluation and majorly a high approve from the normative

belief and with the existence of the control factor. Students seems to have low intention

towards physical activity. Therefore, confidence, perceived difficulty factor, which the self-

efficacy is added into the model fitting. Self-efficacy is a more direct based measure. Even

though with positive beliefs towards physical activity, students still have low intention.

Therefore, it is unwise for the government currently showing how physical activity is

beneficial for their body and mental health. Because the model shows that with strong belief,

the intention is still weak. Self-efficacy as a strongest predictor, it suggest that students do the

behaviour based on how confident they feel and how easy to do the behaviour. Therefore, to 71

effectively deliver the message of doing the behaviour of physical activity, policy and

promotion should no longer focus on physical activity benefits belief, instead it should put

more efforts on how easy they can do physical activity and ways to improve their confident.

While external control factor as a supportive role to facilitate the confidence and difficulties

to do physical activity.

5.5 Testing of hypothesis

In chapter 2, we have developed five hypothesis, it will be discuss whether the hypothesis is

correct or null.

Testing of Hypothesis 1

Hypothesis was raised for whether intention was affect and can be predicted with other

variable. In the regression of the research, moderating factor, self-efficacy, was discover to be

a stronger variable in predicting intention (β=0.589). Self-efficacy is also supported by other

researches (Hagger et al., 2002; Hagger 2001) which also shown a higher beta coefficient in

predicting intention and a more predictable variable. It shown that students self-controlling

power over doing physical activity is more important than other variables. The existence of

self-efficacy shown to be a more important variable than PBC. The hypothesis is tested to be a

positive result.

Testing of Hypothesis 2

In the research, we found that subjective norm is not a predictive variable towards intention or

more predictive than PBC (β=-0.010; β=0.178). Regression shown that subjective norm is

negative and non-significant. Which students are not likely to do what their other people

suggest them to do. It shown as the weakest variable among all the variables. However,

subjective norm serve as a supporting role for attitude and PBC. It have a high correlation 72

FIGURE 5.1 TPB MODEL TO PREDICT INTENTION FIGURE 5.1 TPB MODEL TO PREDICT

INTENTION (WITH SELF-EFFICACY)

level towards attitude and PBC (r=0.542; r=0.552). Subjective norm can help students to have

an increase of attitude and PBC. For example, parents tell their children about the benefits of

doing physical activity and approval of it. Students are unlikely follow what their parents said,

however, the message that deliver from the parents will affect the students on how they see

the beliefs and control belief of it. They are likely to see that physical activity is a healthy

activity which have a beneficial beliefs established. With the approval from the parents, they

are likely to perceive that they have more time in the future times. Which these can all support

attitude and PBC of the students and create a higher intention to do physical activity. This

hypothesis is proved as a null hypothesis.

Testing of Hypothesis 3

In gender difference, male and female shown an obvious difference. Generally speaking, male

is more an out-going segment, with liking of challenges. On the other hand, female, is a more

like to be alone or with family, liking of easiness. In the correlation of the PBC and self-

efficacy. Male shows a high correlation of ‘accompany with others’ towards the PBC

(r=0.723) and showing a high correlation of confidence to PBC (r=0.716). Male is more like

to have friends to do physical activity with. Also male do physical activity when they

perceived they have high confidence in doing the behaviour. Support of outgoing personality

is also based on the descriptive data on doing sports with classmates and friends with a 61.4%

of total. While female is more focus on the circumstances of whether there is enough time for

them to do physical activity in PBC. Female can concluded as more self-centred. Also in the

regression of the model, it shows that male have an intention based on PBC and self-efficacy

in balance (β=0.223; β=0.337), while female intention is majorly from the self-efficacy

instead of PBC (β=0.696; β= 0.270). In PBC, it talks about the external control factor like 73

FIGURE 5.2 TPB MODEL TO PREDICT INTENTION (MALE)

FIGURE 5.3 TPB MODEL TO PREDICT INTENTION (FEMALE)

friends accompany with or time, while self-efficacy is about the self-control power to do the

behaviour. This hypothesis is proved by this regression.

Testing of Hypothesis 4

In Hong Kong, government recently have put lots of effort in promoting physical activity in

different age groups. However, health related beliefs are not a good way to promote physical

activity towards students, especially male adolescents. In the correlation of attitude towards

behaviour, healthy body shown to be one of the weak variables towards the attitude of male

students. In the factor analysis, healthy body is also the component 1 with highest factor

score. It can show that healthy body belief is a popular concepts to students, one of the POP

of physical activity. Consistently showing physical activity can have healthy body is not

persuasive enough to promote it. To male students, other factors like meeting new friends and

achieve goals and challenges is more important in doing physical activity. To female students,

healthy body is not shown as one of the weak factor. However, the power of it is not strong

enough. In the research, instead of having a better physical health, female is more focus on the

mental health with a highest correlation of reduce stress and pressure towards attitude. It is

unwise for government promote physical activity merely on healthy body on different age

groups.

Testing of hypothesis 5

In the research, self-efficacy do not only affect the intention to do physical activity. Self-

efficacy also indirectly affect the subjective norm. Self-efficacy have correlation to subjective

(r=0.460) with a significant level higher than 0.01. A notable point is self-efficacy also have

correlation towards the motivation to comply (r=0.424, P< 0.01). Subjective norm is

correlated and explained that self-efficacy not only shows how students push themselves to do

physical activity. But also self-efficacy can have control power over whether they choose to

listen and act on what their most important people want them to do. Positive correlation

shows that student with higher confidence are more likely to comply on what their most

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important people want them to do. Generally speaking, self-efficacy can be explained as self-

autonomy. A variable to self-choosing to do physical exercise or not, and to listen to the

others’ advices or not.

Limitation

There is two major limitation of this research. First is the time limitation, the research is to be

finished within five months, which the research cannot be studied into more depth

perspective. At the same time, the survey is conducted when the HKDSE is in progress, which

the research have a bias on junior form more than in senior form. Secondly, the guideline

provided by Ajzen, Constructing a TPB Questionnaire in2006 is in English. The

questionnaire are translated in Chinese without assistance from person majoring in

Translation. The questions may not deliver the best idea behind the questions and deliver a

different meaning to the respondents. This may affect the sample and the analysis of the

results.

Further Studies

In the research, significant idea is found. Male and female have high different in the self-

efficacy and the PBC. Unknown variables and reason did not be discovered by this research.

Research can further focus on the variable that affecting male and female have such

difference of the self-efficacy. Factors that affecting the gender difference in how female have

higher self-control ability than male is worth for further study.

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Chapter 6 Conclusions and Major Findings

The results of the research suggest that for examining adolescents’ behavior towards physical

activity, the TPB model is a suitable model to find out the impact of self and social factors.

Before discussing about the recommendations for future improvements in the promotion of

adolescents physical activity, the major findings that was discovered from the research are

summarized as follows:

Out of the three major factors in the TPB model (attitude, subjective norms, and perceived

behavioral control), result shows that attitude and perceived behavioral control are the two

major factors that have influence towards adolescents’ intention for physical activity.

Most adolescents’ attitude towards the perceived health benefits from physical activity is

positive where most of them aware the importance of having a healthy lifestyle and that

through physical activity, they will be able to get healthier physically and mentally.

There are three major groups of adolescents in general with different approach in being

physical active. The first group of adolescents perceives the importance of being healthy

physically and mentally and is willing to exercise for a healthier lifestyle. The second group

of adolescents believes that through exercising, it may allow them to receive an ideal body

shape which may help them with attracting opposite gender. The last groups of adolescents do

not see any benefits from being physical active and believe that it is a waste of time.

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Between male and female, both of the genders share a different correlation in the attitude

towards physical activity. Male adolescents have a high correlation of attitude towards

enlarging social circle and setting goals. Which shows that meeting new friends and having

new achievements are the main drive for male adolescents to exercise? Whereas, female

adolescents focus more on the internal benefits with a high correlation of attitude towards

reducing pressure and improve perseverance. Which shows that the benefit of reducing

pressure and improve persistence is the main drive for female adolescents to exercise.

Male adolescents with regular exercise habit (3 times per week for at least 20 minutes for

ongoing 3 months), prefer ball sports like basketball and badminton, whereas female

adolescents prefer aerobic exercises like running and swimming.

Subjective norm operationalized as motivate to comply with, self-control and role-modeling

in regards to adolescents’ physical activity. Adolescents in general are more capable of having

the control power to exercise than imitating their role-model’s behavior.

Adolescents in general believe that with more time and a individual to exercise with can

motivate them to participate in physical activities more often.

Males are more likely to participate in physical activities with friends or alone. Whereas,

females are more likely to participate in physical activities with family or alone.

Adolescents in general that are driven by school to exercise at first fail to turn exercise into a

habitual behavior. On the other hand, adolescents that are driven by friends/classmates at first

are more likely to successfully turn exercise into a habitual behavior.

6.2 Recommendation

To motivate adolescent to do physical activities for at least an accumulation of 30 minutes

every day and at least three days a week is an important work for Hong Kong. It will be a big

problem for their health and government if they cannot meet this target.

The recommendations are based on the result of our research. Both of the students who have

or have no exercise habits are holding positive attitude toward physical activities, they have

high preference to physical and mental health which think it can produce a positive outcome.

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Another would be attracting opposite gender. However students also think doing physical

activities are waste time, only this item has an negative attitude. Students who have no

exercise habit are tend to motivated by school to do exercise at first (29.8%), as the result

school plays an important role to encourage them to participate in physical activities.

Attitude toward to all student respondents are like to relax by doing physical activities and

reduce pressure, set goal combined with perseverance has high a moderate correlation and

also reducing pressure. These three items can combined with each other which have a strong

relationship here. However, promotions for male and female can be different since the

motivation and their reasons to start to have exercise are not the same. Female are tend to lack

of exercise habit than male (Male: 35.6%; Female: 64.4%), the promotion should more focus

on female. Research shown that male like outgoing activities with friends while female like

ingoing with family. School should take action and effort in the promotion of physical

activities. They should also deliver the importance of doing enough exercise and they should

less focus academic result only.

To promote physical activities effectively, school and government should have a good

planning. Since students stay at school for long time with friends and classmates every day, it

takes an important role for promotion. They should enhance the intention of students to do

exercise. Students have pre-working and try-working process but lack of intention to

complete. School should encourage them to set goal and let them achieve since they love to

set goals for increasing perseverance, for female, it can focus on their inner beauty, but for

male the benefits can be enhance social networks. This can solve the problem of low intention

to complete of physical activities. Moreover, time cost is the main reason for respondents to

avoid sports. School should educate them to have better time management to balance time for

study and sports, Hong Kong students have many pressures to study, school should promote

more sport activities for students. For example, more variety of exercise can offer to students,

as the students like to sport with friends, activities held by school can give a chance for them

to play with friends and classmate, especially advantages to male students since they have

bigger intention to do physical activities if they can enlarge the social network. Base on the

different interest of male and female, school can promote outgoing and ingoing activities for

students. The intention will be increased if there are more people join physical activities

which observed from the research. Activities can also reduce stress of students. Lack of time

to do physical activities can be solved if they held events. For example, they can organize

sport competition in lunch time or after school. To win the game, students are willing play 78

with friends and achieve goals, games which need team work can easily increase their interest

to participant. Also, build up the school teams and have regular training, students can join for

it to perfect their profile, challenge other school to win the awards can also create an

opportunity to encourage them to have exercise habit. Running can be the main activities for

the students since both of male and female prefer running as their favorite sport. Other would

be some ball games like basketball or badminton which suitable for different gender, school

can do this behavior to increase their students’ interest toward sports. According to the

research, family is another important people that can motivate students to do sports, so

schools can offer more information to the parents to encourage them to join in the exercise,

parents are more care about their kids’ health, their opinions and caring also have power to

influence teenager’s thinking.

Government also can provide more resources for school or social, and the government

promotion of physical activities. For example, it can build more facilities in districts in order

to participate in sports easier and it can reduce time for students to do physical activities,

some sports center near to their estates can decrease the time cost, offering discount or lower

price can attract people to sign up for doing exercise. If people want to free using facilities,

government can according running and ball games to establish playground or even running

path to satisfy both genders’ need. Also, government should cooperate with schools to

promote physical activities and deliver the message about the importance of exercise. Some

talks can be set up for students and parents, increase the knowledge about the benefit to do

exercise and the disadvantages of physical inactivity, context in the lecture can include a good

planning towards to sports, change or maintain their attitude positively to the behavior.

Government also can enhance the participate quota in younger age group for “Sports for all

day”, allow more teenagers to join in their prefer sports types, in the research, running and

ball games are people interest, another would be swimming and dancing, government should

put more effort on it, then provide an award scheme, like offering certificates to thank them to

participate in, also increase the attractiveness of the prize for the winners in the competition

items. In the promotion, instead of holding the school talk, government can produce TV

commercials to gain people awareness, point out the benefits to do sports, for example, it can

reduce the stress or lose weight. While promoting “Sports for all day”, widely publicized

should be included, such as put up the posters in streets, recreational venues and traffic tools,

since we are targeting to the teenagers, schools is an important channels to remain students

that the event is coming soon.

79

Schools and Government should take part in changing students’ behavior in doing sports,

trying to reach the standard of “at least 30 minutes every day and at least three days a week”

in Hong Kong. Subjective norm is non-significant to change the intention, but it can be a

supporting role for attitude and PBC, based on people they are concerned, like friends and

family, we can emphasize that they can accompany them to do the exercise. Moreover,

different gender have different prefer sports, it can separated in outgoing and ingoing, their

reasons to do sports are different too, female are focus on inner beauty but male are focus on

social enhancement, schools and government while promoting should noticed about it.

80

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