CHAPTER 1

INTRODUCTION

1.0 Purpose of this Study

Myocardial infarction is a major public health problem in Australia in terms of both

mortality and morbidity (Tonkin, 1988; Worcester, 1986). A number of controllable risk

factors contribute to coronary atherosclerosis such as smoking, high cholesterol and poor

dietary habits, excess alcohol, less exercise and increased stress. The modification of

these lifestyle factors is a major aim of cardiac rehabilitation in an attempt to attenuate

atherosclerotic changes and prevent further infarction. Therefore, the standard cardiac

rehabilitation program consists of providing patients with written information about diet,

quitting smoking, exercise and stress. Some programs also include video tapes providing

relevant health information. Physicians and nurses also reinforce the need to change

behaviour and provide additional advice as necessary. Unfortunately, despite these

efforts, compliance with desirable lifestyle change is often poor (Mayou, 1981;

Oldenburg, Perkins & Andrews, 1985; Worcester, 1986).

Explanations for this failure to comply with recommended health behaviour in the face of

a life threatening condition can be found in the health psychology literature where a

number of psychological models and theories based on Social Learning Theory and Value

Expectancy Theory have been shown to explain compliance. The models and theories

selected for investigation in this study were the Health Belief Model (Rosenstock, 1966;

Janz & Becker, 1984), self-efficacy and outcome expectation (Bandura, 1977a, 1986),

and Multidimensional Health Locus of Control (Wallston, Maides & Wallston, 1976;

Wallston, Wallston & DeVellis, 1978). Psychological distress and psychological ill health

are common among patients experiencing myocardial infarction and were included for

investigation as predictors that might also affect compliance with recommended health

behaviour.

The principal aim of this study was to determine the extent to which self-efficacy,

perceived health threat, cardiac health locus of control, psychological health and the

degree of psychological distress, at the time of hospitalisation, in men experiencing a

myocardial infarction would predict self-reported compliance with recommended health

behaviour over a 6 month period following discharge from hospital.

An additional aim of the study was to explore the relationship between the predictors to

investigate recent claims about how the various models might be integrated. Rosenstock

(1988) and Rosenstock, Strecher and Becker (1988) have argued that there is some

similarity between the models and that health behaviour might be best explained by a

combination of variables from the models rather than by the individual variables.

Finally, the stability of efficacy expectations, health threat beliefs, multidimensional

health locus of control beliefs, psychological health and psychological distress over the 6

month period was also investigated.

The rest of this chapter will examine in detail the theoretical basis for the present study

and supporting research. It begins by looking at the issue of cardiovascular disease as a

public health issue then moves on to the theoretical foundations of Social Learning

Theory and Value Expectancy Theory. Each model is then considered in detail and the

variables derived from the theories are described.

2.0 Cardiovascular Disease

Atherosclerotic heart disease and its sequelae, cardiac ischaemia and myocardial

infarction, are major public health issues in the industrialised world. Approximately 50%

of Australians die from cardiovascular disease, many prematurely (Tonkin, 1988).

Coronary atherosclerosis is hardening and narrowing of the principal arteries supplying

blood to the heart muscle. The process begins with the deposition of fats on the surface of

the arterial lumen. These roughened areas then provide a medium for the formation of

fibrous plaque consisting of smooth muscle cells, collagen, calcium, platelets, cellular

debris and lipids (Blumenthal & Emery, 1988). The plaque grows in size over time

eventually blocking off all or most of the artery. In some cases a clot may form to further

accelerate the process.

When narrowing prevents sufficient blood flow to supply the oxygen needs of the

myocardium on demand, angina pectoris may result. Complete obstruction causes

myocardial infarction which involves necrosis of cardiac muscle tissue. Infarction may

result in death or severe damage to the heart if not treated quickly and effectively.

2.1 Risk Factors for Coronary Atherosclerosis

It is generally acknowledged that the development of coronary atherosclerosis involves a

complex amalgam of multiple causative factors (Jenkins, 1988; Razin, 1982). These

consist of genetic predisposition, smoking, hypertension, hypercholesteraemia and

hyperlipidaemia. Other significant secondary factors that may play a role are stress,

moderate to heavy alcohol consumption, lack of exercise and certain personality

characteristics. Some of these causative factors may be controlled by changes in

behaviour, as described below.

Smoking is a major preventable risk factor for ischaemic heart disease contributing to

atherosclerotic changes, constriction of the coronary arteries, increased blood carbon

dioxide levels, decreased oxygen carrying capacity of the blood and increased potential

for clotting. Men who smoke more than 20 cigarettes a day have two to three times the

risk of experiencing a major cardiac episode, including sudden cardiac death, than those

who do not smoke (Jenkins, 1988). Importantly, cardiac risk decreases by about 50%

about 1 year after cessation of smoking and approximates the risk of a non-smoker after

about 10 years (Tonkin, 1988). Following a myocardial infarction or the development of

other signs of coronary atherosclerosis, such as angina pectoris, the need to quit smoking

is even more acute.

Poor dietary habits, which are also controllable, may contribute to hypercholesterolaemia

and hyperlipidaemia. These are major components in the formation of atherosclerosis by

increasing intake of fats and cholesterol. Raised low density lipoproteins, which carry

cholesterol, have been shown in a number of studies, including the Multiple Risk Factor

Intervention Trial (Stamler, Wentworth & Neaton, 1986), to be associated with cardiac

mortality. In fact, a 1% reduction in serum cholesterol lowers the risk of fatal coronary

artery disease by about 2% (The Lipid Research Clinics Program, 1984).

There is still some debate about the direct effect of stress on coronary risk. A recent report

by the National Heart Foundation of Australia (Stress Working Party, 1988) has stated

that '...there is good evidence that stress and its psychological consequences do affect

several conventional coronary risk factors' (p. 514). Stress, for example, is thought to

increase cholesterol and circulating fat through activation of hormones secreted by the

adrenal cortex. A number of studies have demonstrated that acute stress raises total blood

cholesterol levels between 8% and 65% (Stress Working Party, 1988). Thus, increased

stress may be an important mediating factor in the development of plaques. Sympathetic

activity resulting from stress also increases blood pressure which is a major contributing

factor in heart disease.

While there is some controversy about the protective nature of aerobic exercise in the

development of ischaemic heart disease and mortality, there is evidence that regular

aerobic exercise may assist in reducing weight, blood lipids, smoking, blood pressure

and the negative effects of stress and hostility (Jenkins, 1988; Siegal, Grady, Browner &

Hulley, 1988). Exercise may act to increase high density lipoproteins which appear to

have a protective capacity. Much of the effect of exercise, however, on coronary risk

factors may be indirect. For example, people who exercise are more likely to be health

conscious and therefore smoke less, watch what they eat and keep their weight down.

Not least of all, smoking and obesity make exercise difficult. Exercise also appears to

help in 'working off stress.

Moderate to heavy alcohol consumption is associated with cardiomyopathy, obesity,

hypertension, hypercholesteraemia and electrical disturbance of the cardiac muscle, all of

which predispose to the development of cardiac disease and morbidity (Ponh, 1990).

2.2 Modification of Risk Factors

Some of the risk factors for the development of heart disease and myocardial infarction,

namely smoking, hypercholesteraemia and hyperlipidaemia, exercise, stress and alcohol

consumption are directly or indirectly modifiable by alteration in behaviour associated

with lifestyle (Blumenthal & Emery, 1988; King & Remenyi, 1986; Pomeroy, 1987;

Siegal et al, 1988; Tonkin, 1988).

Risk factor modification following myocardial infarction is a central concern in

rehabilitation of these patients as a means to attenuating the disease process. Attempts to

change behaviour usually start in the coronary care unit and most cardiac rehabilitation

programs include structured patient education. This consists of written material, video

tapes and counselling from nurses and physicians (Jeffery, 1988; Murray, 1989).

However, there is evidence that compliance with required behaviour change is relatively

poor and that many return to their previous lifestyle within 12 months (Oldenburg,

Perkins & Andrews, 1985). Havik and Maeland (1988) found that in a group of 230

smokers who had experienced a myocardial infarction, 40.6% had resumed smoking after

6 months and 49.4% after 3 to 5 years. Similarly, compliance with recommended diet

(Jeffery, 1988; Sackett & Haynes, 1976) and exercise (Mayou, 1981) has been shown to

be poor.

More complex interventions, other than education, that involve counselling and

behavioural techniques have been shown to be more successful in improving compliance

and knowledge (Baile & Engel, 1978). Unfortunately, as a recent review of cardiac

rehabilitation in Australia has shown (Worcester, 1986), such interventions are rare.

Short staffing in hospitals as a result of the dwindling health dollar and a general lack of

recognition of the importance of psychological treatment compared to physical care may

account for this failure to intervene. In addition, hospital stay is generally limited to 8 to

11 days in uncomplicated cases, which is not enough time in which to provide effective

behavioural intervention.

If patients at risk of not changing their behaviour could be identified early in the acute

period following infarction then further reinforcement of the need for compliance and

behavioural interventions could be undertaken. It is for this reason that this study

attempted to predict self-reported compliance by using variables derived from Self-

efficacy Theory, the Health Belief Model, Locus of Control Theory, and measures of

psychological health and psychological distress. These theories and variables are

described in detail below in subsequent sections.

2 . 3 Summary

Myocardial infarction is a major health problem in Australia for which a number of risk

factors have been identified. Some of these factors, namely, smoking, diet, exercise,

stress and alcohol consumption are associated with the person's lifestyle. Rehabilitation

following infarction includes helping patients change their health behaviour and modify

these risk factors. Unfortunately, despite the severity of this disease, compliance with

recommended health behaviour is often poor.

This study was designed to predict self-reported compliance with recommended health

behaviour following myocardial infarction using a number of theories and models derived

from the health psychology literature. In the first instance, the focus of the study

promised to have utility beyond heuristic purposes by investigating behaviour change

likely to affect the outcome from a life threatening condition. Secondly, the study

provided an opportunity to further investigate a number of psychological models and

theories that attempt to explain health behaviour. It is to these theories and models, and

the variables that are derived from them, that the discussion now turns.

3.0 Theories of Health Behaviour

Rosenstock, Strecher and Becker (1988) have suggested that a number of recently

developed models may be applied to our understanding of health behaviour. These

models are derived from cognitive-behavioural theory.

Following on from the seminal work of Lewin (1935) and Tolman (1932), who

emphasised the role of cognition in the determination of behaviour, cognitive-

behavioural theory has given rise to two other important theories: Social Cognitive

Theory (Bandura, 1977a, 1986) and Value Expectancy Theory (Becker & Maiman,

1975; Rosenstock, 1966; Rosenstock, Strecher & Becker, 1988).

3.1 Bandura's Social Learning/Cognitive Theory

One of the major cognitive-behavioural theories, developed by Bandura, was termed

Social Learning Theory (Bandura, 1969, 1977a) but has more recently been renamed

Social Cognitive Theory (Bandura, 1986), presumably due to its emphasis on the role

of cognitive factors in the determination of behaviour.

Social Cognitive Theory attempts to draw together the principles of classical

conditioning, applied behavioural analysis and cognitive theory into one theoretical

framework (Wilson & O'Leary, 1980). In what Bandura (1977a, 1986) has termed

'triadic reciprocity', psychological functioning can be described in terms of the mutual

interaction of behaviour, cognitive factors and environmental influences.

Bandura (1986) has suggested that the degree of influence of each of these three

components on psychological functioning will vary according to the individual, the

particular activity and the circumstances. Similarly, reciprocity between the

components does not occur simultaneously, instead the interaction creates influences

over variable periods of time.

The strength of this model is that it enables a broader analysis of behaviour compared

to applied behaviour analysis which tends to emphasise environmental influences to

the exclusion of other factors. Social Cognitive Theory sees people as being able to

exert influence on what they do rather than, as suggested by Skinner (1971), simply

'being acted upon' by the world. People, then, are agents of their own behaviour in

this cognitive view.

Bandura (1977a, 1986) has described a number of cognitive processes, called

capabilities, that are hypothesised to play a role in determining behaviour. These are:

symbolism, which transforms experiences into an internal code to guide future action;

forethought, that enables anticipation of the consequences of behaviour; vicarious

learning or modelling (Bandura and Walters, 1963); self-regulation, which involves

the regulation of behaviour by the use of internal standards; and self-reflection, which

enables people to consider their experiences and to reflect on their own thoughts.

For Bandura (1986), the most important type of self-referent thought has to do with

people's judgements about their capabilities to deal with certain experiences. This

concept is called self-efficacy (Bandura, 1977a, 1986) and is central to Bandura's

theory. Perceptions of personal efficacy strongly influence what people choose to do,

how much effort they will put into a certain activity, how long they will persist in the

face of difficulties and the degree of anxiety associated with approaching the activity.

Another type of self-referent thought described by Bandura (1977a, 1986) is outcome

expectancy. This is the extent to which people believe that a certain behaviour will

achieve a particular outcome. Self-efficacy and outcome expectancy are two of the

independent variables investigated in this study and are described in greater detail in

Section Four.

In summary, Bandura's (1986) Social Cognitive Theory provides a modern,

psychologically interesting and potentially useful framework for understanding human

behaviour. Two concepts derived from Social Cognitive Theory, self-efficacy and

outcome expectation, have been used extensively in research investigating health

behaviour and health behaviour change.

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3.2 Value-Expectancy Theory

The second cognitive-behavioural theory to be considered here which also takes into

account cognitive factors is Value Expectancy Theory. Models derived from this

theoretical position emphasise both the motivational role of a person's expectancy of

success that a behaviour will attain a particular goal and the value of that goal

(Broome, 1989).

Like Social Cognitive Theory, Value Expectancy Theory arose from the work of Kurt

Lewin in social psychology (Becker & Maiman, 1975; Rosenstock, 1966;

Rosenstock, Strecher & Becker, 1988). Lewin's principal concept from Field Theory

was the interdependent relationship between the person and his or her environment

which proposed that it is the person's interpretation of the environment that guides

behaviour rather than just the environment itself.

Value Expectancy Theory attempts to describe behaviour under conditions of

uncertainty (Becker & Maiman, 1975). Thus, 'Behaviour is predicted from the value

of an outcome to an individual, and from the individual's expectation that a given

action will result in that outcome' (Becker & Maiman, 1975, p. 11). A person will be

motivated to act if there is a state of readiness and if some benefit for the effort can be

expected. According to this theory, compliance with recommended health behaviour

depends on a readiness to comply due to a belief that a threat actually exists, the belief

that compliance is in fact feasible and that a particular health behaviour or treatment

will indeed lead to beneficial results.

Rotter's (1954) Social Learning Theory and the Health Belief Model are two

important examples of Value-Expectancy models which have been used extensively as

a means to understanding health behaviour.

Rotter's social learning approach is an attempt to integrate stimulus-response theories

and cognitive theories into a coherent account of behaviour (Rotter, 1975; Rotter,

Chance & Phares, 1972) in a similar way to Bandura's theorising. Thus, behaviour is

predicted by the interaction of the person's values, expectancies and psychological

situation. Rotter's theory states that behaviour is a function of the expectancy that the

behaviour will lead to a particular reinforcement in that situation and the value of the

reinforcement to the individual (Rotter, 1954).

8

Expectancies in this formulation have a particular emphasis on reinforcement value

where reinforcement strengthens an expectancy that a particular behaviour will be

followed by a reinforcement in the future (Rotter, 1966). One general expectancy that

stems from this theory and that was used in the present study is Health Locus of

Control.

The Health Belief Model (Becker, 1974; Rosenstock, 1966, 1974) emphasises the

relative role of perceived gains and losses in determining the motivation to carry out a

particular health related behaviour. The model was developed by a group of public

health investigators in the United States during the 1950's, hence its specific

application to health related behaviour.

The model is based on the Lewinian (1935) concept of the life space in which there

are negatively valued, positively valued and neutral regions. According to this model,

disease represents a negative region from which the person is motivated to move away

and health represents a region towards which the individual is pulled. As Rosenstock

(1974, p. 330) put it, behaviour depends on being pulled by positive forces and

repelled by negative forces.

A number of dimensions are derived from this theoretical base and represent the

individual's beliefs about disease or health problems and about the effect of likely

health-related action. These dimensions are beliefs about susceptibility to, and beliefs

about, severity of an illness or health problem, perceived benefits of taking a

particular course of health action and the value of an outcome minus the barriers to

taking action (Becker, 1974).

The Health Belief Model and the research conducted with it are described in more

detail below in Section Five.

While both Social Cognitive Theory and Value Expectancy Theory are derived from

similar theoretical assumptions about the role of cognitive factors in the determination

of behaviour, there is competition between them with respect to explaining health

behaviour. As will be shown below, very few studies into health behaviour have

investigated variables from both models at the same time. This may explain why only

a relatively small amount of the variance in health behaviour is explained in these

studies.

9

Somewhat better predictions of behaviour may be obtained by measuring the

contribution of self-efficacy, outcome expectancy, health locus of control and

variables derived from the Health Belief Model in explaining the behaviour in question

(Rosenstock, 1988). Unlike other research in this area, the present study combined

variables derived from Social Cognitive Theory and Value Expectancy Theory in an

attempt to explain health behaviour following a myocardial infarction.

3.3 Summary

A number of psychological theories and models have been developed that may be

applied to the understanding of health behaviour. Some of the theories and models

used in this study are based on Cognitive-behavioural Theory which combines

stimulus-response and cognitive explanations of human behaviour into one

framework. Cognitive-behavioural Theory has resulted in the development of two

additional theories, Social Cognitive Theory and Value Expectancy Theory, from

which many of the models, theories and variables used in this study were derived.

This study attempted to investigate the extent to which variables obtained from Social

Cognitive Theory and Value Expectancy Theory might explain health behaviour,

while previous research has tended to emphasise one theory in isolation from the

other.

4.0 Self-Efficacy

4.1 Expectancies

As described above, one aspect of Social Cognitive Theory that has created considerable

interest in the analysis of behaviour change has been that of the role of self- referent

thought as a mediator between knowledge and action (Bandura, 1986). In this model,

perceived self-efficacy and outcome expectation are seen as the major determinants in the

prediction of behaviour. In this section self-efficacy and outcome expectation are

outlined, and their potential role in the prediction of health behaviour is described in

relation to research in the area.

Self-efficacy has been defined as a judgement of one's ability to successfully organise

and execute courses of action required to attain particular outcomes or performances

(Bandura, 1977b, 1986). A high degree of self-efficacy about performing a behaviour to

achieve some desired outcome refers to a person's judgement that he or she is very

confident of performing that behaviour. Conversely, low self-efficacy is a judgement of a

low confidence of success.

Application of self-efficacy theory to health behaviour would mean that people's ability to

engage in health behaviours that contribute to the prevention of myocardial infarction,

such as cessation of smoking, for example, might be affected by perceptions of self-

efficacy for these behaviours.

Self-efficacy can be measured in terms of magnitude or level, strength and generality

(Bandura, 1977a). Self-efficacy magnitude is a measure of the level of performance

people believe they are capable of achieving. Thus, in foundation research that tested self-

efficacy theory with subjects suffering from snake phobia, Bandura, Adams and Beyer

(1977) presented their subjects with a hierarchical list of 29 increasingly threatening

behaviours involving interaction with a boa constrictor. These behaviours ranged from

subjects approaching the snake in a glass case to them actually allowing the serpent to

crawl on their laps. The level of self-efficacy was taken as the most threatening behaviour

from the list that the subject thought they would be able to perform.

Self-efficacy strength is a measure of confidence about successfully performing a

particular behaviour. The subjects in the above mentioned experiment (Bandura, Adams

& Beyer, 1977) were asked to indicate on a 10-point scale, for those approach behaviours

they believed they could perform, the degree of their confidence that they would be

successful at performing them. The scale consisted of 10-point intervals ranging from 0

to 100 indicating high uncertainty through to complete certainty.

Generality of self-efficacy refers to the extent to which a self-efficacy belief can be

generalised beyond a specific behaviour or treatment situation (Bandura, 1977a). Some

experiences may create a sense of personal mastery for a number of actions whereas

others may not be generalised at all. Bandura and Adams (1982) obtained a measure of

generality in a snake phobia experiment by asking subjects to rate the level and strength of

their perceived ability to cope with other snakes. Self-efficacy measures were also

obtained for being able to approach other animals.

According to Bandura (1977a, 1977b, 1986) one's self-efficacy beliefs may be obtained

from four principal sources. These are, in order of influence on self-efficacy:

performance accomplishments; vicarious experience; verbal persuasion; and emotional

arousal.

The most powerful source of self-efficacy information is actually performing and being

successful in a particular task or behaviour since this involves personal mastery

(Bandura, 1977b). Conversely, failures and avoidance will decrease self-efficacy.

The next most influential means by which self-efficacy information is obtained is through

vicarious experiences or modelling. Like behaviour in general, beliefs are not learned

only from actual performance. Perceptions of self-efficacy can also be obtained from live

and symbolic modelling (Bandura, 1977a, 1986). Seeing other people perform

behaviours increases perceptions of the observer that they too can perform the behaviour.

Verbal persuasion is the third source of self-efficacy information and is probably the most

often used means used to help people change their behaviour, particularly health

behaviour. Like modelling, verbal persuasion also increases the likelihood that the person

will sustain effort and persist in the face of difficulties (Bandura, 1977a, 1986).

The final means by which self-efficacy information may be obtained is through feedback

obtained by one's level of emotional arousal (Bandura, 1977b, 1986). Anxiety is usually

interpreted by a person as a sign that the situation is difficult, taxing or likely to result in

some negative experience. Thus, the higher the anxiety, the greater the likelihood that

self-efficacy for dealing with the situation will be low.

Bandura (1983, 1986) argues that there is a contingent relationship between self-efficacy

and outcome expectancies based on the straightforward notion that people come to learn

that performance affects outcome. Despite this relationship between self-efficacy and

outcome expectancy (Bandura, 1983, 1986), the two concepts can be clearly

distinguished.

Perceived outcome expectancy refers to a judgement that a given behaviour will lead to

certain desired outcomes (Bandura, 1977b, 1986). Outcomes are the consequences of

behaviour and may be in the form of intrinsic satisfaction, reduction of threat, an extrinsic

reward, or achieving something one desires.

Thus, performance of a particular behaviour is dependent upon the beliefs (rather than

actual abilities or real outcomes) of individuals as to their self-efficacy and their outcome

expectancy. However, self-efficacy represents for Bandura (1977a, 1977b, 1982, 1986)

the central cognitive mechanism through which behaviour change is mediated. He

believes that expected outcomes add little to the prediction of behaviour (Bandura, 1983,

1986). In fact, Bandura (1978) argues that in the absence of strong self-efficacy beliefs,

outcome expectancies, skills and motivation are incapable of producing successful

behaviour change.

A major criticism of self-efficacy theory stems from Bandura's assertion that self-efficacy

is the chief determinant of behaviour (1977a, 1984, 1986). In discussing the application

of Self-efficacy Theory to health behaviour, Rosenstock (1988) suggests that self-

efficacy is but one factor in the determination of health behaviour. Rosenstock argues that

perceptions of health threat seriousness, the degree of perceived susceptibility to a health

threat, barriers to carrying out recommended courses of health behaviour and perceived

benefits of that behaviour also contribute to health behaviour. These beliefs are all

variables derived from the Health Belief Model which is described in Section Five below.

Rosenstock argues that these variables also consistently predict health behaviour and that

self-efficacy is a potential barrier to health behaviour change and only one small

component of the whole model.

Lee (1989), Eysenck (1978) and Skinner (1987) have claimed that self-efficacy cannot be

evoked to explain behaviour because it is more of a metaphor and descriptor of behaviour

rather than having explanatory power.

Despite these criticisms there is a growing body of research to support the role of self-

efficacy as a determinant of behaviour. Some of this research is described below and

provides a basis for the investigation of self-efficacy in the present study.

4.2 Research into Self-Efficacy

Judgements of one's ability to cope, ability to use available skills, or effectiveness in

particular situations, will affect one's choice of activities, the effort that will be given to

that activity and persistence of effort when confronted with difficulties (Bandura, 1986).

Several lines of evidence have been obtained to support this hypothesis starting with the

analysis of fearful and avoidant behaviour by Bandura and his colleagues. Some of this

foundation research has been mentioned above and will be detailed below.

As suggested earlier, support for self-efficacy theory has also been used extensively in

research investigating health behaviour and health behaviour change. This research will

also be examined.

4.2.1. Foundation Research

The early support for self-efficacy theory was obtained in the analysis and treatment of

fearful and avoidance behaviour (e.g., Bandura, 1982; Bandura & Adams, 1977;

Bandura, Adams & Beyer, 1977; Biran & Wilson, 1981) where self-efficacy has been

used widely as a model in the investigation of behaviour change initiation and

maintenance.

Bandura, Adams and Beyer (1977) investigated the relationship between self-efficacy and

approach behaviour among a group of 33 severely snake phobics. The degree of

approach by each subject to a boa constrictor was measured. Level of fear when

approaching the snake and self-efficacy strength for approach behaviours they thought

they might be able to perform on a scale of 10 (low confidence) to 100 (high confidence)

with the boa constrictor and with snakes in general were obtained. Subjects were then

randomly assigned to one of three treatment conditions consisting of participant

modelling, vicarious modelling and no-treatment control.

Following treatment, the participant modelling and the vicarious modelling groups

showed an increase in self-efficacy level, self-efficacy strength and approach behaviour

with the snake. Participant modelling was found to be the best procedure in increasing

self-efficacy followed by vicarious modelling. The congruence between self-efficacy and

actual performance was 89% for the participant modelling group and 86% for the

vicarious modelling group.

Higher levels of self-efficacy level and strength at the completion of treatment were

associated with higher levels of approach behaviour and personal efficacy with respect to

approaching the snakes. Self-efficacy level, but not self-efficacy strength, was associated

with lower levels of anticipatory fear.

Bandura, Reese and Adams (1982) more directly tested the effect of self-efficacy on

behaviour by creating pre-determined levels of self-efficacy in individuals and then testing

behavioural and arousal effects.

Severely snake phobic subjects were tested for their level of behavioural avoidance, fear

arousal and self-efficacy judgements with respect to 18 approach behaviours involving a

boa constrictor. Those who could handle the snake with a gloved hand were considered

insufficiently phobic for the experiment. Subjects were then randomly assigned to low,

medium or high efficacy-induction conditions. Participant modelling was used to raise the

level of approach behaviour of subjects to the level of the group to which they were

assigned. Self-efficacy level and strength were associated with higher levels of approach

behaviour and lower levels of fear arousal.

Bandura, Taylor, Williams, Mefford and Barchas (1985) demonstrated additional

support, but with a small sample of 10, for the mediating effect of self-efficacy on arousal

due to environmental events in a study involving women with severe arachnaphobia. The

women were allocated to one of three groups on the basis of having a low, medium or

high self-efficacy for approach behaviours involving a Wolf spider.

Self-efficacy was assessed in the usual way with subjects being presented with a list of

18 hierarchical approach behaviours involving the spider such as watching it in a plastic

bowl, handling the spider with gloves, allowing the spider to crawl on the arm, and so

forth. Subjects were asked to indicate which of the behaviours they felt they would be

able to perform (self-efficacy level). They then indicated, on a 100-point scale with 10-

point intervals, how confident they were that they could perform the behaviours.

The women were then asked to engage in three of the performance tasks with the spider.

Blood catecholamine levels were monitored as a measure of autonomic arousal.

Epinephrine and norepinephrine levels were found to be differentially related to self-

efficacy. During interaction with the spider high perception of self-efficacy for a

behaviour resulted in low levels of these catecholamines and moderate self-efficacy led to

an increase in plasma catecholamine levels. Interestingly, when subjects decided not to

perform behaviours for which they had an extremely low level of self-efficacy their level

of catecholamines dropped, presumably because the need to cope with an anxiety

provoking situation was removed.

There is some support from these studies that high self-efficacy results in lowered arousal

and vice versa. It seems likely that people with a high degree of confidence that they can

successfully perform a particular task or behaviour will feel better able to cope with, and

hence feel less anxiety about, the behaviour than those with less confidence.

This notion is in concert with recent evidence suggesting that a person's perception of

control over a threat rather than actual ability to deal with the stressor is an important

determinant of the level of stress experienced (Lazarus, 1982; Lazarus & Folkman,

1988). While actual ability to control the threat may be low, a perception that one can

cope with an aversive event will result in little stress compared to a perception that one is

helpless. Self-efficacy, then, is one cognitive mechanism whereby the person's perceived

ability or inability to deal with threatening situations will affect the level of stress

(Bandura, 1986).

Myocardial infarction, the focus of this study, is a frightening event. Thus, it could be

expected that levels of anxiety felt by these people might be affected by their level and

strength of self-efficacy.

Since these important foundation studies, self-efficacy has been applied in a wide variety

of contexts including health behaviour, to which this discussion now turns.

4.2.2 Research in Health Behaviour and Self-efficacy

A number of studies have investigated the relationship between self-efficacy and some of

the health behaviours that were the focus of this study (Chambliss & Murray, 1979;

Colletti, Supnick & Payne, 1985; Condiotte & Lichtenstein, 1981; Devins & Edwards,

1988; DiClemente, 1981; DiClemente, Prochaska & Gilbertini, 1985; Garcia, Godding &

Glasgow, 1989; Chambliss & Murray, 1979; Ewalt, Taylor, Reese & DeBusk, 1983;

Jeffrey, Bjornson-Benson, Rosenthal, Lindquits, Kurth & Johnson, 1984; Prochaska,

Crimi, Lapsanski, Martel & Reid, 1982; Schmitz & Doerfler, 1990; Strecher, Becker,

Kirscht, Eraker & Graham-Tomasi, 1985). These studies provide support for the role of

self-efficacy in predicting smoking, dietary behaviour, exercise, relaxation and alcohol

consumption following myocardial infarction.

Studies investigating the role of self-efficacy in smoking behaviour, cessation and relapse

have provided consistent evidence that self-efficacy measures for smoking behaviour

predicts future abstinence. Furthermore, self-efficacy has predicted relapse following

intention to quit and enhancement of self-efficacy has contributed to success at quitting

(Strecher, DeVellis, Becker, & Rosenstock, 1986).

Devins and Edwards (1988) evaluated the role of self-efficacy, among other social

cognitive variables, in predicting changes in smoking behaviour. Subjects were presented

with a list of common stop-smoking techniques, that is, relaxation, engaging in alternate

activity, avoiding smokers and smoking situations, thinking of the negative effects of

smoking, buying fewer cigarettes, rewarding oneself with incentives and attending a

workshop. Outcome expectancy was measured by asking subjects to rate, on a 9-point

scale, their perceptions of the effectiveness of each technique in helping people give up

smoking. Similarly, self-efficacy strength was measured by asking subjects to indicate,

on a 9-point scale, how confident they were of performing each technique. The authors

found that higher self-efficacy for a particular technique was associated with low smoking

behaviour 1 month and 3 months later. A combination of high outcome expectancy and

high self-efficacy also predicted smoking behaviour.

Self-efficacy has been show to be related to relapse in attempts to stop smoking in a

number of other studies. Condiotte and Lichtenstein (1981) measured self-efficacy

strength, level and generality for resisting the urge to smoke in 48 common situations.

Seventy eight subjects enrolled in two quit smoking programs responded to each item

with a confidence score of between 10 (low confidence) and 100 (high confidence) using

a 10-point scale. Higher levels of self-efficacy were associated with continued abstinence

during treatment and abstinence for longer periods after treatment. There was also a high

degree of congruence between the clusters of situations in which subjects reported low

self-efficacy and in which they reported having eventually relapsed.

More recently, Garcia, Schmitz and Doerfler (1990), using a questionnaire developed by

Condiotte and Lichtenstein (1981), demonstrated a significant but small correlation

between self-efficacy for resisting smoking and the number of cigarettes smoked in a 4

week quit smoking program. Self-efficacy measured before the quit date was not

significantly correlated with resisting the urge to smoke in the first 2 weeks of the quit

smoking program. However, self-efficacy taken 2 weeks into the program did correlate

with the percentage of high risk situations in which subjects managed to resist the urge to

smoke in the final 2 weeks of the program. It appears that self-efficacy may well have

changed by becoming more realistic as the program progressed.

With respect to cardiac rehabilitation, the topic of this research, Ewart et al (1983)

examined the relationship between self-efficacy and exercise performance in subjects

recovering from uncomplicated myocardial infarction. Subjects were asked to indicate on

a 100-point scale, ranging from 10 (uncertain) to 100 (complete certainty), their self-

efficacy judgements for walking, running distances ranging from 1 block to 5 miles,

climbing stairs from a few steps to 4 flights, engaging in sexual intercourse for 1 to 20

minutes, lifting objects from 10 to 75 pounds and overall ability to tolerate physical

activity. Those with higher self-efficacy for these tasks performed better on the treadmill

test than those with lower self-efficacy. Higher self-efficacy also predicted increased

tolerance for sexual intercourse, lifting and general exertion at home as recorded on an

activity log and by heart rate monitoring.

Self-efficacy research with respect to dietary behaviour has largely been confined to

weight loss. Weinberg, Hughes, Critilli, England and Jackson (1984) asked subjects

involved in a weight reduction program to estimate their self-efficacy strength for success

in losing weight. Subjects were then split into high and low self-efficacy groups on the

basis of this pre-treatment questionnaire. They were also given a number of psychological

tests designed to give the impression of a psychological evaluation. On the basis of these

tests, subjects were given bogus but convincing feedback about their self-efficacy. Thus,

some subjects were given high self-efficacy feedback and some low self-efficacy

feedback no matter what their self-efficacy was prior to the weight reduction program.

Those given high self-efficacy feedback lost more weight than those given low self-

efficacy feedback.

Few studies have investigated the relationship between self-efficacy and alcohol

consumption. In a study primarily designed to investigate the effect of assertiveness on

the treatment outcome of 145 female alcoholics, Rist and Watzl (1983) also assessed self-

efficacy for resisting the urge to drink alcohol. These subjects were involved in a social

skills training program and were asked to rate, on a 10-point scale, the extent to which

they would be able to resist the urge to drink alcohol in certain social situations. Ignoring

those subjects who failed to remain abstemious during actual treatment, greater

perceptions of ability to resist the urge to drink alcohol in social situations predicted

treatment success 3 months later.

In summary, studies involving the self-efficacy construct have consistently demonstrated

self-efficacy to be a significant predictor of health behaviour. High levels of confidence in

the ability to perform a prescribed or desired health behaviour seem to predict greater

compliance with, and success in, achieving the behaviour. Stronger support for the

explanatory power of self-efficacy is found in studies in which self-efficacy has been

manipulated.

In many of the studies described above, the researchers attempted to test the hypotheses

about the predictive ability of self-efficacy by correlating the self-efficacy measures with

the measures of behaviours under investigation. A look at the statistical results of the

studies shows that the correlations between self-efficacy and health behaviour are

significant but often low. These results mean that though self-efficacy is a significant

predictor of health behaviour, it accounts for only a small percentage of variance in health

behaviour. It appears from the result of the studies on self-efficacy and health behaviour

that, for a stronger prediction of health behaviour, variables other than self-efficacy

should be taken into account. The present study investigated the ability of variables

derived from the Health Belief Model, Health Locus of Control variables and

psychological distress variables, in addition to the variables derived from Self-efficacy

Theory, to predict health behaviour.

An additional predictor of health behaviour derived from Self-efficacy Theory is outcome

expectation which was mentioned as a part of Bandura's (1977a) early theorising and is

conceptually related to self-efficacy. It is towards this construct that the discussion now

turns.

4.3 Outcome expectancy

Outcome expectancy, within the context of Bandura's (1977a) theory, has not received as

much attention as self-efficacy. Most studies involving self-efficacy do not include

outcome expectancy as a predictor measure of behaviour (Strecher et al, 1986). The

reason for this lack of attention may rest with Bandura's (1986) more recent contention

that outcome expectancy is so dependent on self-efficacy expectations that it adds little to

the prediction of behaviour. However, where it has been included the findings about the

relationship between outcome expectancy and behaviour have been mixed (Bandura,

1986).

For example, Devins and Edwards (1988) in a study on smoking cessation among

subjects with Chronic Obstructive Airways Disease, described in the previous section,

measured outcome expectancies for stop-smoking techniques. Subjects were asked to rate

the extent to which they believed certain quit smoking techniques would help them stop

smoking. Outcome expectation for each quit smoking technique was measured on a 9-

point scale ranging from 'not at all effective' to 'very effective'. An average outcome

expectancy score was calculated. Outcome efficacy was not a significant predictor of the

number of cigarettes smoked.

However, Stanley and Maddux (1986) found more positive results in investigating the

effects of self-efficacy, outcome expectation and outcome value on the intention of

subjects (195 male and female undergraduate psychology students) to engage in an

exercise program. The study involved the manipulation of high or low levels of self-

efficacy, outcome expectancy and outcome value by way of persuasive written

communication in a 2 x 2 x 2 factorial design. In order to manipulate outcome expectation

bogus research was used to indicate the benefits or otherwise of exercise on health and

well-being. Outcome value was manipulated by information related to the value placed on

such a program by society. High or low levels of self-efficacy expectation were created

by providing subjects with bogus research that indicated the ability or inability of students

in other studies to complete exercise programs of this sort. Manipulation checks showed

that the communications had affected the independent variables in the desired direction.

Subjects were then asked to indicate their intention of engaging in the exercise program

and were given the opportunity to actually sign up for an orientation to the program as a

measure of their motivation.

Both outcome expectancy and self-efficacy were significantly related to intention to

exercise. A hierarchical regression analysis revealed that outcome expectancy was the best

predictor of intention to exercise, accounting for 26% of the variance. Self-efficacy

accounted for an additional 17% of the explained variance.

It must be emphasised that intention to exercise, rather than actual exercise behaviour,

was used by Stanley and Maddux (1986). A much more robust test of the effectiveness of

outcome expectancy would be to compare the effects of outcome expectation on actual

future behaviour as tested by Devins and Edwards (1988), for example.

While there is marginal support for outcome expectation as a predictor of health behaviour

it has received little attention despite being an important component of Bandura's (1977a)

original model. There is also some evidence that there may be a relationship between self-

efficacy and outcome expectation that warrants further investigation. Devins and Edwards

(1988), for example, found a large correlation between self-efficacy and outcome

expectation in their research on smoking cessation.

It was decided, in the present study, to further investigate the role of outcome

expectation, in relation to self-efficacy, in predicting health behaviour. More specifically,

the extent to which beliefs about smoking less, eating a low fat diet, exercising more,

drinking less alcohol and relaxing more might help prevent future heart attacks would

affect a person's compliance with performing these behaviours following a heart attack,

was measured.

4 . 6 Summary

According to Bandura's (1977a, 1986) Social Cognitive Theory, behaviour is determined

by judgements about how successful one will be in executing the behaviour (self-

efficacy) and by judgements about the likely outcomes of the behaviour (outcome

expectation).

Self-efficacy judgements have consistently been shown to predict behaviour in a number

of contexts including health-related behaviour. Outcome expectation has not been shown

to be a good predictor of behaviour in the few studies in which it has been investigated

and it is often excluded from studies investigating self-efficacy. In the present study, both

self-efficacy and outcome expectation with respect to health behaviour following

myocardial infarction were measured to shed further light on the predictive power of each

construct and the relationship between them.

The amount of variance in health behaviour explained by these two variables is often quite

small, however, and suggests that self-efficacy and outcome expectation should be

included in the Health Belief Model (Rosenstock, Strecher and Becker, 1988). This

model is now described in detail.

5.0 The Health Belief Model

The Health Belief Model was developed in the 1950's as a means of explaining the failure

of disease prevention programs in the United States (Kirscht, 1974) rather than out of

mainstream psychological research. However, as described in Section Three of this

chapter, the model has theoretical underpinnings based in Value Expectancy Theory but

with specific reference to health-related behaviour. Value Expectancy Theory posits that

the potential performance of a particular health behaviour will depend on the value of

being healthy and the expectancy that the behaviour will in fact achieve that health state.

From a motivational point of view, Kirscht (1988) suggests that the model represents the

beliefs that will result in a state of readiness to act in the face of a threat.

This section will describe the specific components of the model and review the research

relating specifically to changing health habits, the focus of this study.

5.1 The Components of the Model

The Health Belief Model (Becker & Maiman, 1975; Janz & Becker, 1984; Rosenstock,

1974) consists of a number of components that affect a person's goal directed health

behaviour. These components are as follows:

Susceptibility

Susceptibility refers to the subjective perception by the individual of the actual risk of

contracting a condition or susceptibility to illness in general (Janz & Becker, 1984).

Seriousness or Severity

Health related behaviour is also determined by how serious an illness or potential health

threat is perceived by the person (Janz & Becker, 1984).

Benefits minus Barriers

It is hypothesised in the model that the perceived benefits minus the perceived costs of or

barriers to engaging in a particular health behaviour will affect motivation to proceed.

Benefits have been compared to outcome expectations as described in Social Cognitive

Theory (Rosenstock, Strecher & Becker, 1988). Barriers to health behaviour such as

exercising or attending quit-smoking classes, for example, consist of the time

commitment, inconvenience and financial cost.

Cues to Action

Previous experiences and knowledge are also considered important by providing cues to a

preferred path of action. Cues may be derived from internal bodily states or from external

sources such as the media or health professionals, for example.

Thus, according to Rosenstock (1974):

• the belief that one is susceptible to an illness and the belief that the consequences of the

illness are severe leads to a drive to act,

• an evaluation of perceived benefits minus perceived barriers provides a path of action,

and

• other cues to action are found in information provided by the media, advice from

people such as health care professionals, reading and real life experiences.

Thus, measures derived from the Health Belief Model were obtained from participants in

this study to determine their effect on engaging in health related behaviour following a

myocardial infarction.

Finally, the beliefs and understanding a person has about his or her actual health

behaviour and desired health behaviour leaves considerable room for conflict within the

individual. For example, a person might believe that he or she is at considerable risk of

developing heart disease due to smoking but feels unable to stop the habit because

smoking meets some special need. This state of affairs is likely to result in distress. The

relationship between distress and variables from the Health Belief Model was also

investigated in this study.

5.2 Measures of Health Beliefs

Health belief components are measured using questionnaires which vary from long, fairly

complex questionnaires (e.g., Becker, Maiman, Kirscht, Haefner & Drachman, 1977;

Wessfeld, Kirscht & Brock, 1990) to single questions representing each variable of the

model related to a particular health behaviour (e.g., Rundall & Wheeler, 1979; Beck &

Lund, 1882). Studies also vary as to the number of components investigated and often

ignore the interaction between the various components of the model.

Items relating to health beliefs are invariably put in a Likert format using 4-point to 10-

point scales and may refer to specific health behaviours or diseases (e.g., heart attacks,

cancer or influenza) or more general states of concern, susceptibility or seriousness.

Typically, items ask questions such as 'How likely is it that you will have a heart attack

(or some other disease) in the future?' or 'How concerned are you about getting cancer in

the future?'. Alternatively, questions involve statements such as, 'Diabetes can be a

serious disease if you don't control it', to which the subject responds with a degree of

agreement or disagreement (Given, Given, Gallin & Condon, 1983).

Janz and Becker (1984), in their comprehensive review of research with the Health Belief

Model between 1974 and 1984, reported a wide variety of 'self-made' health belief

questionnaires varying greatly in sophistication. They have argued, however, that '...it is

a testament to the robustness of the model that the dimensions remain predictive despite

these different measures' (1984, p. 45).

Two studies provide evidence that questions of this type actually measure the components

of the Health Belief Model. Weissfeld, Kirscht and Brock (1990) undertook a factor

analysis of a list of 32 questionnaire items from previous health belief research in an

investigation of health beliefs with respect to high blood pressure. The responses to 2802

interviews revealed six factors. These were: general health concern, general health threat,

belief in personal susceptibility to cardiovascular diseases, belief about severity of certain

cardiovascular diseases, beliefs about the medical benefits of treatment and beliefs about

what one can do personally about one's health (self-help benefits).

Jette, Cummings, Brock, Phelps and Naessens (1981) investigated the structure and

reliability of health belief indices. A questionnaire was constructed using 31 items from a

number of previous studies that measured specific and general health beliefs. These

beliefs were: susceptibility to, and severity of, specific illnesses such as heart attacks, flu,

dental cavities and a cold; general threat to health; concern about health matters; barriers to

taking prescribed medications; health locus of control; trust in physicians; and health

status.

The responses from two independent samples were factor analysed and eight factors were

identified. These were; general health threat, perceived barriers to taking medication,

perceived severity, perceived susceptibility, health locus of control, trust in physicians,

concern about health and perceived health status. The factor loadings and measures of

item reliability provided considerable support for the reliability of items used commonly

in health belief research and also for the independence of health belief components.

However, the absence of a standardised questionnaire for measuring the components of

the health belief model and the variety of items that are used can be seen as a limiting

factor in health belief research. Nonetheless, there appears to be considerable support for

the predictive value of the various components of the Health Belief Model.

5.3 Research with the Health Belief Model

A large number of studies have investigated the role of variables from the Health Belief

Model in determining health behaviour. Very few of these studies have involved health

behaviour and coronary artery disease, the focus of this study. However, compliance

with recommended health action, smoking and dietary behaviour, all components of this

study, have been investigated and lend support to the use of components of the Health

Belief Model in predicting health behaviour following myocardial infarction.

In a relatively recent review of 29 studies conducted over a 10 year period from 1974 to

1984, Janz and Becker (1984) concluded that there was considerable empirical support

for all the components of the Health Belief Model.

The research reviewed by Janz and Becker (1984) covered a wide range of preventive

health behaviours including inoculation (Aho, 1979; Cummings, Jette and Brock, 1979;

Rundall & Wheeler, 1979; Larsen, Bergman & Heidrich, 1982), screening behaviours

(Becker, Drachman & Kirscht, 1972; Hallal, 1982; King, 1982 ) and risk factor

behaviour (Aho, 1977; Becker et al, 1977; Langlie, 1977) as well as compliance with

medical advice such as diet and medication regimens (Hartman & Becker, 1978; Kirscht

& Rosenstock, 1977).

Unfortunately, most of the research reviewed was retrospective. Limits to generalisability

of these studies, other than the fact that they were retrospective, include small sample

sizes, low response rates and sometimes unclear explanations of how the dependent and

independent variables were measured.

However, 12 of the studies reviewed by Janz and Becker (1984) were prospective and

offer more convincing support for the Health Belief Model. One early prospective and

well constructed study was conducted by the Becker and Maiman team in which they

investigated dietary compliance (Becker et al, 1977). The study attempted to determine the

relationship between weight loss, as a measure of treatment compliance, in a group of

obese children and the health beliefs of their mothers or carers. Since the mothers or

carers spent a great deal of time with their children, it was argued that the mothers' or

carers' health beliefs would have a significant effect on the children's weight.

Perceptions about concern for the child's health, perceived susceptibility to illness,

perception of the severity of illness and feelings about of the child being overweight were

obtained by way of a structured interview. The mother's or carer's concern about the

child's health and beliefs about the susceptibility of the child to illness were predictive of

weight loss after 2 months. Beliefs in the severity of general illnesses and obesity were

also predictive of weight loss. Unfortunately, the correlations between these health beliefs

and weight loss, although significant, ranged from .21 to .31. Like much of the research

with the Health Belief Model, these correlations were very small and left a large

proportion of the variance in health behaviour unexplained.

Similarly, a more recent study by Contento and Murphy (1990) attempted to differentiate

between people who had made desirable dietary changes lasting for at least 12 months

and those who had not. Those who had made dietary changes in that period believed

themselves to be more susceptible to disease, perceived greater benefits from dietary

change and had greater overall health concern than those who had not. While a

discriminant function analysis demonstrated that perceived benefits to dietary change and

susceptibility to illness were predictive of dietary change, the coefficients were relatively

low suggesting that other factors influenced dietary change in this study as well as health

beliefs; a finding similar to many other studies. The investigation suffered from being

retrospective and from using only a convenience sample.

In an unpublished but prospective study reported by Kirscht (1988), Kirscht, Janz and

Becker investigated the relationship of health beliefs to smoking cessation among 250

patients who were attending an internal medicine clinic. Intention to quit smoking was the

best predictor of cessation at a 6 month follow-up. However, intention to quit was

predicted by beliefs about the reduction in susceptibility to health problems and perceived

susceptibility to health problems if smoking continued. Unfortunately, statistical data

were not reported by Kirscht so it is difficult to evaluate the efficacy of the findings.

With respect to heart disease, Aho (1977) investigated the health beliefs of 187 wives of

men who had suffered a myocardial infarction, in relation to their preventive health

orientation. The study of wives' health beliefs was considered important because the

author assumed that their health beliefs would influence their husbands' health behaviour.

The women were placed in a high, medium or low preventive orientation group,

depending on their response to an interview. A significant proportion of women in the

high preventive orientation group believed that their husbands were likely to suffer a heart

attack in the future.

The severity of having heart disease, as measured by a question about how normal a life

one might lead with a heart condition, was related to a high preventive health orientation

on the part of the wives. Twice as many women in the low preventative health orientation

group viewed heart disease as likely to interfere with a normal life as in the high

orientation group. However, measuring severity of heart disease with a question about

the chances of leading a normal life may be too indirect a measure. Beliefs about the

effectiveness of treatment for heart disease were significantly related to a high preventive

health orientation. Unfortunately preventive health orientation is rather a weak measure in

Aho's (1977) study. Better measures would have been specific health behaviours such as

smoking and dietary behaviour, for example.

Other studies in areas unrelated to the health behaviours investigated in the present study

but which measure compliance with recommended courses of health action have

demonstrated that components of the Health Belief Model may play a role in determining

health behaviour.

For example, Carter, Beach, Inui, Kirscht and Prodzinski (1986) recommended to 874

patients with chronic illnesses that they have vaccinations the following year against

influenza. They found that beliefs about susceptibility to influenza accounted for some

25% of the variance in actual compliance 12 months later.

In a study not reviewed by Janz and Becker (1984), Wurtele, Roberts and Leeper (1982)

enrolled 553 people in a tuberculosis (TB) detection drive. The study investigated the

effect of health beliefs on compliance with an instruction to return to have a skin test

checked 48 hours after the initial test. Beliefs about the severity of TB, susceptibility to

TB, barriers to returning and outcome efficacy predicted return for the test.

Champion (1988), in another prospective study, found that susceptibility, seriousness,

barriers and health motivation accounted for 61% of the variance in predicting proficiency

in breast self-examination among 380 women. Beck and Lund (1982) manipulated

perceptions of seriousness and susceptibility to peridontal disease. Subjects with higher

levels of perceived seriousness flossed more frequently, in accordance with advice, than

those with lower levels. However, the correlation, while significant, was only .35.

In a study of smoking behaviour, Weinberger, Greene, Mamlin and Jerin (1981)

compared the health beliefs of heavy, moderate, and ex-smokers. Severity of the health

effects of smoking was measured by asking respondents why people should quit

smoking. Responses were coded as 'no reason', 'vague reasons' or 'clearly identified

specific health consequences of smoking'. Subjects were also asked to rate their

susceptibility to ill effects on their own health as a result of smoking and the likelihood of

their experiencing health problems as a result of smoking in the future.

Discriminant analysis produced two functions. The first function discriminated ex-

smokers from the other groups. Ex-smokers were more likely to cite reasons why people

should quit smoking and to perceive the complications smoking can create to their health.

The second function identified that moderate smokers were able to state acute

complications associated with smoking but did not feel susceptible to these diseases.

5 . 4 Summary

There has been a considerable amount of research with the Health Belief Model with a

wide variety of health behaviours. These studies have shown health belief variables to

predict compliance with recommended health behaviour and generally support the model.

However, the research also suggests that the Health Belief Model may need further

development. Many of the studies suffer from the problem of being retrospective. In

addition, the correlation coefficients between health beliefs and health behaviour are often

very low leaving a large proportion of variance unexplained, thereby suggesting that the

model needs further refinement in identifying other factors that play a role in health related

behaviour.

There is sufficient support for the inclusion of variables from the Health Belief Model,

particularly those that measure perceptions of health threat seriousness and susceptibility,

to include them in this study with other potential predictors.

Therefore, understanding the role of health beliefs in determining the likelihood of self-

reported health behaviour change following myocardial infarction was seen as being of

considerable utility in this study. As suggested previously, compliance with health

behaviour change such as modifying diet, cessation of smoking, relaxing more, limiting

alcohol and increasing exercise is an essential component of rehabilitation and prevention

of further infarction.

In particular, a person's health beliefs at the time of acute recovery were seen as potential

predictors of the likelihood of self-reported compliance with recommended health

behaviour in this study. It was thought that if health beliefs did in fact predict compliance,

then counselling could be directed towards modifying inappropriate beliefs during

rehabilitation.

The discussion now turns to the role of locus of control beliefs in predicting health

behaviour.

6.0 Locus of Control

6.1 Generalised Locus of Control

As described earlier, Rotter's (1954, 1966) Social Learning Theory emphasises the

interaction of expectancies or reinforcement, need value, experience and outcomes in the

prediction of behaviour. The generalisation of expectancies enables people to hypothesise

about expectancy of reinforcement in novel situations based on previous experiences.

Clearly the emphasis on generalised expectancy of reinforcement increases as the

individual's specific experience in the situation decreases (Rotter, 1966, 1975).

There are two kinds of generalised expectancies in Rotter's theory. One involves

expectancies for a particular kind of reinforcement and the other is a problem solving

expectancy. Problem solving expectancy refers to situations which involve different types

of reinforcements and where the person has to find ways to achieve outcomes in the face

of intervening factors. Generalised expectancies for a particular reinforcement and

problem solving represent a personality characteristic that enables a broad prediction of

behaviour.

One type of generalised expectancy is internal-external locus of control of reinforcement.

Locus of control of reinforcement is defined as the '...degree to which individuals

perceive events in their lives as being a consequence of their own actions, and thereby

controllable (internal control), or as being unrelated to their own behaviour, and therefore

beyond personal control (external control)' (Lefcourt, 1976, p. 145).

Individuals with a strong internal locus of control of reinforcement attribute rewards (the

achievement of desired outcomes) as resulting from their own actions. Conversely,

people with external locus of control of reinforcement believe that desired outcomes are

the result of fate, luck, chance or other forces beyond personal control.

One of the important variables that needs to be taken into consideration when evaluating

the effect of locus of control is the value of the reinforcement to the person (Rotter,

1975). Clearly, if a person does not value a particular outcome then motivation to behave

purposefully will be reduced, irrespective of locus of control.

According to Rotter, Chance and Phares (1972) a person with an internal locus of control

of reinforcement is likely to behave differently to a person with external locus of control

in four principal ways. Firstly, the person with an internal orientation will be more open

to seeking out and using information from the environment. Secondly, 'internals' will be

more likely to do things to influence environmental conditions to obtain benefit. Thirdly,

'internals' will place greater value on skill and personal ability. Lastly, 'internals' are

more resistant to attempts to influence them. More recently, studies have revealed that

'internals' have greater achievement motivation (Findlay & Cooper, 1983) and cope

better with stresses and difficulties (Lefcourt, 1982; Wolk & Bloom, 1977).

Originally, locus of control was measured as a unidimensional construct with Rotter's I-E

Scale (Rotter, 1966) being the most notable and widely used tool. Levenson (1973)

factor analysed Rotter's I-E Scale and found two other dimensions in addition to

internality-externality. These were the influence of powerful others and the influence of

chance or fate. People with high powerful others locus of control believe that what

happens to them results from the influence of significant people. People with a high

chance locus of control believe that they are the victims of fate or chance.

On the basis of this finding Levenson (1973) developed a multidimensional locus of

control scale consisting of three Liken scales, each consisting of eight items, which she

called Internality, Powerful Others and Chance. The Powerful Others and Chance scales

were positively (r = .59) correlated whereas neither was correlated with internality.

Since the development of general and multidimensional locus of control scales, the

construct has been more specifically applied to health behaviour.

6.2 Health Locus of Control

6.2.1. Measures of Health Locus of Control

It is not surprising that the concept of locus of control should be specifically applied to

health and illness behaviour. Strickland's (1978) review of a number of early studies

demonstrated a positive relationship between internal control of reinforcement and

physical health. As Strickland (1978) pointed out, one would expect that 'internals'

would seek out health knowledge, be more receptive to health messages and be more

active in health related behaviour than 'externals'.

However, Wallston, Maides and Wallston (1976) and Wallston and Wallston (1978) in

their reviews stated that Strickland failed to mention a number of negative findings that

showed no relationship between health behaviour and locus of control, These authors

also suggested that there are a number unpublished studies that also show no

relationship. Lau (1988) has stated that this is highly likely since the Wallston research

group have acted as a clearing house for locus of control research in health and had

access to considerable unpublished research.

Nonetheless, Wallston, Maides and Wallston (1976) claimed that expectancies for

specific situations are more likely to determine behaviour than generalised expectancies

Thus, they argued that a specific health locus of control scale would provide a more

sensitive measure of health related behaviour than a general locus of control scale.

The first real attempt to develop a health specific locus of control scale was undertaken by

Wallston, Maides and Wallston (1976). Rather than using a forced choice format, as in

previous scales such as Rotter's I-E Scale, they used a 6-point Likert scale ranging from

strongly disagree to strongly agree. The scale was designed to provide a single health

internality-externality score.

Following Levenson's (1974) contention that locus of control is a multidimensional

construct, Wallston, Wallston and DeVellis (1978) developed the Multidimensional

Health Locus of Control Scale (MHLCS). As described above, this consisted of three

constructs; internality, powerful others and chance health locus of control. People with a

high powerful others health locus of control believe that their health results from what

others such as doctors or nurses do for them. People with high chance health locus of

control beliefs attribute their health or ill health to fate or chance.

The MHLCS was developed using the original 11 items from the Health Locus of

Control scale (Wallston, Maides & Wallston, 1976) to which were added more

internality-externality items, as well as powerful others and chance items, to a total of 81.

A questionnaire containing these items, a desirability scale and two health status items

was distributed to 282 people waiting at an airport. These people were asked to mail the

completed questionnaires back to the authors. Eventually 115 questionnaires were

returned and analysed.

Item analysis was conducted on the internal, powerful others and chance items. Six pairs

of items were chosen for each group on the basis of closeness to the midpoint, wide

distribution of response alternatives on the item, significant correlation between the scale

and the scale minus the item itself, low correlation with the item and the social desirability

factor, and item wording. The pairs were used to construct two alternative scales, A and

B, each with 18 items equally divided into internal, powerful others and chance

constructs. There was a high degree of equivalency between the A and B scales.

For the combined scale (A & B), there was a small non-significant correlation between

powerful others and internality, a significant negative correlation between internality and

chance, and a positive but non-significant correlation between powerful others and

chance.

There have been mixed findings, since this original study, regarding the relationship

between the three constructs and the internal validity of the scale in unhealthy

populations.

Hartke and Kunce (1982) subjected all 18 items on Form A to factor analysis using a

sample of 86 medical patients and confirmed the independence of the three subscales.

Similarly, Russell and Ludenia (1983) demonstrated the factorial validity and

independence of both versions of the scale on an alcoholic population of 10. Hase and

Douglas (1987), in a small sample of 30 patients who had experienced myocardial

infarction, found that powerful others was independent of internality and chance.

Internality was found to be negatively correlated with chance.

Conversely, with a population of British university students, O'Looney and Barrett

(1983) found only two factors in a male sample of 70 and three factors in a female sample

of 77. The factors in the male sample consisted of the internality and chance subscales

together as the first factor, and the powerful others subscale as the second factor.

Umlauf and Frank (1986) investigated the scale with a sample of 107 rehabilitation

patients and were able to replicate only internality in their factor analysis. Cooper and

Fraboni (1988) demonstrated the distinctiveness of internality in the scale in a healthy

population of 82 staff in a psychiatric hospital. However, powerful others and chance did

not appear as independent factors.

It would appear that different populations yield somewhat different results in terms of the

relationship between the subscales. It is possible that specific health concerns in specific

circumstances are not adequately measured by a general health locus of control scale. It is

interesting to note that many of the studies utilising health locus of control scales with

patient populations have demonstrated significant relationships with respect to health

behaviour while research with non-patient populations has not (Wallston & Wallston,

1981). Wallston and Wallston (1981) have also suggested that the use of highly specific

health locus of control scales should be encouraged.

Thus, a specific scale to measure cardiac health locus of control beliefs was developed for

use in the present study. This scale was derived by taking Form A of the MHLCS and

substituting reference to 'health' or 'illness' with the more specific problem of 'heart

attack'. Subjects indicated on a 6-point scale, the extent to which they agreed or disagreed

with 18 statements relating to their health locus of control beliefs with respect to heart

attacks. A low score indicated strong disagreement and a high score indicated strong

agreement.

The complete questionnaire, the Multidimensional Cardiac Health Locus of Control Scale

(MCHLCS is provided in the Appendix to this thesis (Appendix A8) and consists of three

subscales, Internality, Powerful Others and Chance, each being composed of six

randomly distributed items. Thus, each subscale has a range of between 6 and 36.

To provide a measure of validity for the MCHLCS a sample of 28 male surgical patients

completed both the MHLCS and MCHLCS on subsequent days. The correlations

between the three subscales, internality, powerful others and chance on the two

questionnaires were .89, .83 and .78 respectively, lending support for the MCHLCS as a

measure of Cardiac Health Locus of Control.

6.2.2 Research With Health Locus of Control and Health Behaviour

As stated previously, early reviews (Strickland, 1978; Wallston & Wallston, 1981, 1982)

have demonstrated mixed findings regarding the role of locus of control in the

determination of health behaviour. The reasons for this may be the poorly refined

measurement of the construct and the lack of a specific health locus of control measure,

the use of different instruments and a failure to measure locus of control in the context of

health value (Wallston & Wallston, 1981).

According to Rotter (1975) the value of the reinforcement to the person is an important

variable affecting locus of control judgements. Clearly, if a person does not value a

particular outcome then motivation to behave purposefully will be reduced irrespective of

locus of control.

Rotter (1975) provided a very good example of how value interacts with locus of control.

A person with a general internal orientation may not belong to a protest group because he

or she does not believe in the objectives of the group and therefore does not act.

Conversely, an external may belong to the same group for any number of reasons such as

liking the other members, a desire to upset other people or simply for something to do.

There has been some research investigating the role of Health Locus of Control and the

health behaviours investigated in this study.

A number of recent studies have demonstrated a relationship between health locus of

control and health related behaviour. However, as Speake, Cowan and Pellet (1989)

showed in a study investigating the health behaviour of a large sample of elderly people,

the correlations are sometimes very small. Internal locus of control was significantly

correlated with positive exercise behaviour, low stress, nutrition, health responsiveness

and self-actualisation but the correlations were very low and ranged from .12 to .2.

Houts and Warland (1989) investigated the relationship between internal health locus of

control and dietary behaviour in a sample of 458 subjects (414 women and 44 men) who

prepared food for their household. Consistent with the notion of using specific locus of

control scales, Houts and Warland (1989) adapted five items from the Internal subscale

of the Health Locus of Control Scale (Wallston & Wallston, 1981) and related them to

eating behaviour.

Eating habits were measured by nine questions using a 3-point Likert scale. A high score

reflected the avoidance of cholesterol, salt, sugar and calories, and the eating of

vegetables and fruit. The value of food preparation was also measured and subjects were

grouped according to a positive or a negative value orientation. 'Internals' demonstrated

more nutritious eating habits than 'externals'. However, internal health locus of control

contributed to only 13% of the variance in nutritious food behaviour.

Some research, involving locus of control as a variable, has been conducted with patients

recovering from myocardial infarction. Cromwell, Butterfield, Brayfield and Curry

(1977) investigated, in part, how patients coped with the life threatening experience of a

myocardial infarction. Using Rotter's I-E scale, subjects were classified as having either

an internal or an external locus of control.

'Externals' were found to be more depressed and had significantly higher temperatures,

had poorer physiological outcome on three measures (sedimentation rates, serum

glutamic oxaloacetic transaminase and lactate dehydrogenase) and spent more days in the

coronary care unit than 'internals'. In general, 'externals' had a poorer prognostic rating.

It was found that 'internals' participated more in their own self care than 'externals' and

experienced a better outcome over a 12 week period. Unfortunately, no measure of health

value of these subjects was obtained by Cromwell et al (1977).

In a study investigating return to work following myocardial infarction, Smith and

O'Rourke (1988) included Rotter's I-E scale as a measure of locus of control.

'Internality' was not significantly related to early return to work. However, the study

failed to use a specific health locus of control scale nor was any measure of health value

taken.

Havik and Maeland (1988) investigated the smoking behaviour of 230 people who had

experienced a myocardial infarction. Smoking cessation is an important goal for patients

following an infarction and Havik and Maeland (1988) attempted to determine the reasons

for continuation of smoking in approximately half of all these patients. Among the

independent variables, an 11 item shortened version of the Health Locus of Control Scale

(Wallston, Wallston, Kaplan & Maides, 1976) was administered. Other variables

included cardiac health knowledge, psychological adjustment, severity of infarct, anxiety

and depression. It was found that high internal health locus of control beliefs tended to

delay relapse in smoking habits. However, it was not related to long term quitting.

Finally, some studies have shown internal health locus of control to change as a result of

illness or treatment (e.g., Bloom, 1979; Nicholson, 1980). Hase and Douglas (1987)

investigated the effect of teaching relaxation to patients recovering from uncomplicated

myocardial infarction on a number of recovery and psychological variables. Three of

these variables were internality, powerful others and chance as measured in the MHLC

Scale (Wallston, Wallston & Maides, 1978). It was found that compared with a non-

treatment control group, the relaxation group maintained their internal health locus of

control beliefs. The control group, however, become significantly more 'external' during

hospitalisation.

The present study investigated the stability of cardiac health locus of control beliefs as

well as their role in predicting self-reports of health behaviour following myocardial

infarction

6.4 Summary

There have been mixed findings about the role of internal health locus of control as a

predictor of the health behaviours investigated in this study, including recovery from

myocardial infarction.

The reasons for this inconsistency may have been the failure of many studies to consider

the value placed on health by subjects and that many have used general locus of control

scales rather than more specific scales to measure locus of control related to health

behaviour. However, locus of control has been shown to play a role in health-related

behaviour and may, in conjunction with other variables, add to the understanding of

health behaviour following myocardial infarction.

In the present study, both health value and cardiac health locus of control were used as

predictor variables for self-reported health behaviour.

The discussion now turns to the relationship between psychological distress and

psychological health, on the one hand, and health variables related to myocardial

infarction, on the other.

7.0 Psychological Distress and Psychological Health

In this study psychological distress specifically refers to self-reports of distress of

subjects with respect to their thoughts and to recent life events. Psychological health

refers to more general feelings of psychological well being.

Psychological distress and psychological health were of interest in this study for three

reasons. The first was that people who suffer from myocardial infarction experience

considerable distress and psychological morbidity both early and late in rehabilitation.

The second reason was that higher levels of distress and poorer psychological health have

been associated with lower compliance with health-related behaviour. Thirdly, both self-

efficacy and locus of control have been shown to predict psychological distress and

psychological health.

7.1 Psychological Distress and Psychological Health Following

Myocardial Infarction

There is evidence that a high proportion of patients recovering from myocardial infarction

experience emotional distress while in hospital (e.g., Byrne & Whyte, 1978; Byrne,

Whyte & Butler, 1981; Cay, Vetter, Phillip & Dugard, 1972; Dellipiani et al, 1976;

Hackett, Cassem & Wishnie, 1968; Hase & Douglas, 1987; Wynn, 1967).

In a review of a number of studies, Razin (1982) concluded that long lasting emotional

turmoil and occupational problems exist for perhaps 25% of these patients. Wiklund,

Same, Vedin and Wilhelmson (1984) found that 2 months after myocardial infarction and

1 year later, patients demonstrated emotional distress, a high number of self-reported

symptoms, avoidance behaviour, over-protection, pessimism and diminished sexual

activity. Moreover, depression, low morale and psychological distress have been shown

to be significant predictors of mortality (Mumford, Schlesinger & Glass, 1982).

Byrne and Whyte (1978) identified eight dimensions of illness behaviour following

myocardial infarction. These were somatic concern, a history of worry or stressful life

events, affective disruption, subjective tension, inability to express emotion, a recognition

of the seriousness of the illness, affirmation of the sick role and confidence in medical

care.

In an extension of the Byrne and Whyte (1978) study, Byrne, Whyte and Butler (1981)

prospectively examined the relationship of these dimensions of illness behaviour to a

number of outcomes over an 8 month period. Patients who identified areas of significant

stress in their lives and who attributed their initial infarction to stress experienced a higher

level of mortality and morbidity.

Subjects who adopted what Byrne, Whyte and Butler described as a 'sick role' were less

likely to return to work in the 8 month period than those who did not accept such a role.

The authors described the sick role as similar to cardiac neurosis, in which the person

expresses a high degree of self-preoccupation, particularly with cardiac symptoms, which

leads to a sense of invalidism. Interestingly, the study failed to show a significant

relationship between affective disruption and outcome although there was a small

association between subjective tension and putting off return to work. However, the

questionnaire used by Byrne, Whyte and Butler consisted of only two or three questions

measuring each of the eight dimensions and may not have been sufficiently sensitive to

measure changes in distress.

There is also some evidence that greater psychological distress and poorer psychological

health are associated with less compliance with recommended health behaviour.

Oldenburg, Perkins and Andrews (1985) compared the effects of counselling and

education on psychological function and lifestyle factors in 46 subjects following

myocardial infarction. The treatment groups showed less psychological dysfunction and

better adherence to healthy lifestyle factors than a control group. Lifestyle factors included

number of cigarettes smoked, alcohol consumption and frequency of vigorous physical

activity. Psychological dysfunction was measured by the General Health Questionnaire

(Goldberg, 1972), the Spielberger State Anxiety Scale (Spielberger, Gorsuch & Lushene,

1970) and the Attitudes Towards Illness Scale (Haynes, Levine, Scotch, Feinleib &

Kannel, 1978).

However, these authors failed to correlate psychological dysfunction and lifestyle, so the

relationship between the two remains unclear. It would be interesting to know if

psychological distress predicted healthy lifestyle behaviour independent of treatment. The

present study attempted to address this issue in relation to smoking, exercise, diet,

alcohol consumption and relaxation.

Compliance with smoking cessation and exercise behaviour has been associated with

increased distress. Havik and Maeland (1988), for example, investigated changes in

smoking behaviour among 230 patients following a myocardial infarction. Among other

variables, they measured anxiety and depression using a semantic differential

questionnaire. Short term quitters reported a decrease in anxiety and depression compared

to relapsers and non-quitters while early relapsers reported an increase in anxiety and

depression.

Prosser, Carson and Phillips (1985) examined the exercise behaviour of patients

following myocardial infarction. Of the 215 patients studied only 14 were exercising

vigorously as recommended in a cardiac rehabilitation program 6 to 9 years later. The

authors of this study suggested that anxiety may have been a cause of this failure to

comply.

There have been demonstrated relationships between measures of psychological distress,

and self-efficacy and locus of control. According to Bandura (1986), Lazarus (1982), and

Folkman and Lazarus (1984), anxiety (distress) arises from the perception that one will

not be able to cope with an aversive event. Thus, people with low self-efficacy for

performing a particular behaviour in an aversive situation will experience more anxiety

than people with high levels of self-efficacy.

A review of the research with the Health Belief Model has shown that psychological

distress does not appear to be normally measured in relation to health beliefs. One might

expect that high levels of health concern, beliefs about susceptibility to illness and beliefs

about the seriousness of illness might lead to high levels of distress. In turn, this distress

may immobilise people rather than lead them to change their behaviour and could account

for some of the unexplained variance in studies employing the Health Belief Model.

A number of studies have demonstrated a relationship between internal-external locus of

control and distress (e.g., Crisson & Keefe, 1988; Wolk & Bloom, 1977). Donham,

Ludenia, Sands and Holtzer (1983) found that external locus of control was related to

depression, anger and anxiety in a sample of medical inpatients. As described in Section

Six, Cromwell et al (1977) investigated the responses of myocardial infarction patients to

procedures conducted while they were patients in the coronary care unit. They found that

patients with internal locus of control experienced less depression compared to those with

an external locus of control orientation. Physiologically, 'externals' had worse prognostic

ratings, as measured by cardiac enzymes, than 'internals'.

The present study aimed to further investigate:

• the effect of psychological distress and psychological health on self-reported health

behaviour following myocardial infarction; and

• the relationship between psychological distress and psychological health, and self-

efficacy, outcome expectation, health beliefs and cardiac health locus of control.

7.2 Measures of Psychological Distress and Psychological Health

The General Health Questionnaire (Goldberg, 1972) was chosen to measure

psychological health and the Thoughts and Real Life Experiences Scale (Dua, 1987,

1990) was chosen to measure psychological distress in this study.

7.3.1 The General Health Questionnaire

Goldberg's (1972) General Health Questionnaire (GHQ) was constructed by carefully

examining symptoms, personality traits and adjustment identified by normal people and

by psychiatrists. Items were developed as questions with a 4-point Liken scale asking

respondents to indicate whether they experienced feelings or behaviours 'less than usual',

'no more than usual', 'rather more than usual' or 'much more than usual'. The GHQ 28,

used in the present study, is detailed in Appendix A9.

In constructing the questionnaire 140 items were calibrated using three psychiatric

groups; a severely ill group, a mildly ill group and a normal group. Forty seven items

were eliminated because they were not endorsed by the appropriate group. The remaining

93 items were subjected to a principal components analysis which revealed five

meaningful factors after varimax rotation (Goldberg, 1972).

Since a questionnaire consisting of 93 items was considered too long, these items were

reduced to 60 items and the questionnaire was called the GHQ-60 (Goldberg & Williams,

1988). The questionnaire has been subjected to intense investigation and has been found

to be a reliable and valid instrument (Goldberg & Williams, 1988). Goldberg and

colleagues have developed 30-item, 28-item and 12-item versions of the GHQ. The 28-

item version (GHQ-28) was developed by Goldberg and Hillier (1979) and was used in

the present study. A principal components analysis revealed four factors: somatic

symptoms, anxiety/insomnia, social dysfunction and severe depression.

All the versions of the GHQ have proved to be reliable and valid. However, since the

GHQ-28 was used in the present study because of its frequent use by researchers it is

worth noting that Goldberg and Williams (1988) reported 12 studies showing the GHQ-

28 to be a valid instrument for the assessment of the general psychological health of the

individual.

The GHQ has been used in some studies investigating myocardial infarction. Mayou,

MacMahon, Sleight and Florencio (1981) used the GHQ to measure the mental state of a

sample of patients entering a rehabilitation program after a myocardial infarction. The

questionnaire identified people to be suffering from significant distress 18 months later.

Oldenberg, Perkins and Andrews (1985) used the 12 item GHQ in their study, which has

been described previously, in which they compared the effects of education and

counselling on psychological functioning, life-style and use of health care resources

following myocardial infarction. The GHQ was included with a number of other scales to

measure psychological functioning and was found to be a good measure of psychological

dysfunction.

Finally, Philip (1987) noted that a number of different scales have been used to measure

psychological distress after myocardial infarction. Three measures of distress, the GHQ,

a psychiatric interview and the IPAT anxiety scale, were compared. The GHQ was found

to be a reasonably sensitive but very specific predictor of psychiatric illness among

myocardial infarction patients.

In summary, the GHQ is a valid measure of psychological health able to identify common

symptoms described by patients having experienced myocardial infarction such as

anxiety, depression and somatic symptoms.

7.3.2 The Thoughts and Real Life Experiences Scale

The Thoughts and Real Life Experiences scale (THARL scale) has recently been

developed (Dua, 1990) as a predictive measure of psychological distress.

It was developed in response to beliefs about the proposed inter-relationship between

cognitions, affect and behaviours posited by cognitive-behaviour therapists (Dua, 1990).

These therapists (e.g., Ellis, 1977; Meichenbaum, 1977) have argued that negative or

maladaptive thoughts produce negative feelings which in turn lead to maladaptive

behaviour. Positive thoughts, on the other hand, result in positive feelings and adaptive

behaviour. Our day-to-day experiences can also result in positive or negative feelings.

The complete scale, (see Appendix 10) consists of four subscales; Thought-related

Distress; Thought-related relaxation; Real-life related Distress; and Real-life related

Relaxation. In completing the scale, respondents are asked to indicate the degree of

distress due to thoughts, the degree of contentment due to thoughts, the degree of distress

due to real-life experiences and the degree of contentment due to real-life experiences for

14 items.

Respondents are asked to report their degree of distress and contentment on a scale of 0

(not at all) to 100 (extremely high) in a number of categories. A score of 5-15 indicates

very little distress, 25-35 , a little distress, 45-55, distress to some extent, 65-75, much

dristess and 85-95, very much distress. A total score or an average score may be obtained

for each subscale. An average score allows for items indicated by respondents as 'not

applicable' by obtaining a total score and dividing by the number of items actually rated

by the subject.

A number of studies by Dua and colleagues have demonstrated the reliability and validity

of the subscales of the THARL Scale (e.g., Dua, 1990; Dua & Price, 1992). These

studies showed that the more the reported negative affect or distress the more the anxiety,

stress and depression experienced by subjects and the lower the psychological health of

subjects.

7 . 4 Summary

Following myocardial infarction people experience a considerable degree of distress and

this may well affect their ability to comply with recommended health behaviour. Some

studies have also indicated that there is a relationship between psychological distress, and

self-efficacy and locus of control. These findings suggested that measures of

psychological distress and psychological health should be included in this study as

predictors of health behaviour.

Two scales were chosen to measure psychological health and psychological distress in

this study. The General Health Questionnaire (Goldberg, 1977) is a valid and reliable

measure of psychological health considered suitable for this study because it measures

feelings often experienced by patients following myocardial infarction such as anxiety,

depression and somatic symptoms. The Thought and Real-life Experiences Scale (Dua,

1990) has been shown to be a valid and reliable measure of psychological distress.

The next section attempts to draw together the ideas expressed in the discussion so far

and details the rationale, aims, design, and hypotheses of the present study.

8.0 The Present Study

8.1 Rationale and Aims

As indicated in the discussion so far, one of the principal aims of rehabilitation following

myocardial infarction is the modification of lifestyle factors that contribute to the disease

process. These lifestyle factors are cigarette smoking, high fat and cholesterol diet,

inadequate exercise, excessive alcohol intake and stress. All patients, following

infarction, are given advice and counselling about necessary lifestyle changes from

physicians, nurses and through National Heart Foundation literature while they are in

hospital. Unfortunately, compliance with this advice is often poor which leads to an

increased risk of further infarction for these patients in the future.

The research discussed in the previous sections shows that self-efficacy, outcome

expectation, factors constituting the Health Belief Model and health locus of control

predict health behaviours which may be important for the maintenance of good health

following myocardial infarction. In addition, the discussion on psychological distress and

psychological health indicates that, following myocardial infarction, patients are

psychologically distressed and tend to have low emotional or psychological health. The

high distress and the low emotional health experienced by these patients may also affect

compliance with health behaviour.

One aim of the present study was to investigate seperately the effects of self-efficacy,

outcome expectancy, health threat, cardiac health locus of control, psychological distress

as a result of real-life experiences and thoughts, and general psychological health at the

time of hospitalisation, on compliance with recommended health behaviours following

myocardial infarction 3 and 6 months later.

It is also likely that self-efficacy, outcome expectancy, components of the Health Belief

Model, cardiac health locus of control, psychological distress and psychological health

may be measuring common elements of behaviour. Thus, a second aim of this study was

to investigate the relationship between these variables measured while patients having

experienced a myocardial infarction were hospitalised.

The final aim of the study was to determine the stability of self-efficacy, outcome

expectancy, health threat, cardiac health locus of control, psychological distress as a

result of real-life experiences and thoughts, and general psychological health over a 6

month period.

8.2 Design of the Study

A sample of patients who had been admitted to the coronary care unit of a metropolitan

hospital suffering from an uncomplicated myocardial infarction was obtained.

Approximately 5 days after admission and after transfer from the coronary care unit,

subjects completed a questionnaire asking them to report their health behaviour prior to

their infarction in relation to smoking, diet, exercise, relaxation and alcohol consumption.

Subjects were also asked to determine the level and strength of self-efficacy for

achieving, within 6 months, recommended health behaviour in the same five categories.

Outcome expectations for the health behaviours were also obtained along with current

health threat beliefs, health value, cardiac health locus of control beliefs, psychological

health and psychological distress. Additional demographic data and a measure of severity

of infarction were also obtained.

Approximately 3 months and 6 months later, the subjects were asked to complete similar

questionnaires measuring their current health behaviour, self-efficacy, outcome

expectation, health threat beliefs, health value, cardiac health locus of control,

psychological distress and psychological health. Correlational, principal components

factor analysis and forward regression analyses were then performed to determine the

prediction of health behaviour and the relationships between the independent variables.

Repeated measures multiple analysis of variance was used to determine the stability of the

independent variables over the 6 month period.

8.3 Hypotheses

A number of hypotheses are described below that were developed to investigate the aims

of this study.

1) Perceptions of self-efficacy level and self-efficacy strength have consistently been

shown to predict health behaviour. In comparison, the role of outcome expectancy is

unclear since it is often not included in studies investigating Self-efficacy Theory, but

there is some evidence to support outcome expectancy as a predictor of behaviour.

Therefore, it was hypothesised that high self-efficacy level, self-efficacy strength and

outcome expectancy, at the time of hospitalisation, would predict self-reported

compliance with recommended courses of health action 3 months and 6 months after

experiencing a myocardial infarction.

2) The Health Belief Model has been used in a variety of contexts to predict health

behaviour. Three measures from the Health Belief Model that have been extensively

researched and that were considered here were health threat seriousness, the likelihood of

further health threat and concern about the particular health threat.

It was hypothesised that high levels of concern about having a myocardial infarction, a

strong belief in the likelihood of having another infarction in the future and a strong belief

in the seriousness of a myocardial infarction, at the time of hospitalisation, would predict

self-reported compliance with recommended courses of health action 3 months and 6

months after experiencing a myocardial infarction.

3) With respect to health locus of control, it is best measured as a multidimensional

construct, should be as specific as possible and needs to be considered with regard to

health value. Therefore, a Multidimensional Cardiac Health Locus of Control Scale

derived from the Multidimensional Health Locus of Control Scale was developed for use

in this study and the health value of subjects was also measured.

It was hypothesised that for subjects who place a high value on health, high levels of

internal cardiac health locus of control, and low levels of powerful others cardiac health

locus of control and low levels of chance cardiac health locus of control, at the time of

hospitalisation, would predict self-reported compliance with recommended courses of

health action 3 months and 6 months after experiencing a myocardial infarction.

4) The recovery period following myocardial infarction has been associated with high

levels of psychological distress and low levels of psychological health.

It was hypothesised that better psychological health and less distress as a result of real-life

experiences and thoughts, at the time of hospitalisation, would predict self-reported

compliance with recommended courses of health action 3 months and 6 months after

experiencing a myocardial infarction.

5) The introduction to this study sought to establish that there is a theoretical and

empirical relationship between the models and the variables derived from them.

Rosenstock (1988) has argued that despite this relationship self-efficacy has been largely

ignored in research with the Health Belief Model. He suggests that modifying behaviour

associated with long term habits such as smoking and drinking, for example, is a problem

that may well be better understood by incorporating self-efficacy into the Health Belief

Model.

However, Rosenstock (1988) also claims that self-efficacy theorists and researchers

(Bandura in particular) have staked too much on self-efficacy in attempting to explain

behaviour change and compliance. Rosenstock argues that self-efficacy is but one

dimension and health behaviour is more adequately explained by the interaction of a

number of factors, particularly those found in the Health Belief Model. Furthermore he

warns that self-efficacy, developed out of the need to understand snake phobias, should

not become a 'snake oil - a patent medicine to cure all ills' (Rosenstock, 1988, p. 180).

It can be seen from the above that there is competition about the relative contribution the

different variables make to health behaviour change and a question about the relationship

between the variables themselves. This study attempted to shed further light on this issue

and on the possible relationship between these concepts in the context of a life threatening

health problem.

It was hypothesised that self-efficacy level, self-efficacy strength, outcome expectancy,

concern about having a myocardial infarction, belief in the likelihood of having another

myocardial infarction, belief in the seriousness of having a myocardial infarction, and

internal, cardiac health locus of control would be positively correlated with each other.

Chance and powerful others cardiac health locus of control would be negatively correlated

with the above mentioned variables. It was further expected that these variables would be

negatively correlated with psychological health and distress as a result of real-life

experiences and thoughts.

As described above, a major issue of interest in this study was the relationship between

variables derived from the social learning models and the value expectancy models as to

their ability to predict health behaviour. Therefore, it was decided to determine how all the

independent variables interacted in predicting self-reported compliance with recommended

health behaviour 3 months and 6 months after experiencing a myocardial infarction.

6) This study sought to investigate the stability of self-efficacy, outcome expectation,

health threat beliefs, cardiac health locus of control beliefs, psychological distress and

psychological health.

It was hypothesised that self-efficacy level, self-efficacy strength, outcome expectancy,

concern about having a myocardial infarction, belief in the likelihood of having another

myocardial infarction, beliefs in the seriousness of having a myocardial infarction,

internal cardiac health locus of control, powerful others cardiac health locus of control,

chance cardiac health locus of control, psychological health, and distress as a result of

real-life experiences and thoughts would remain stable over a 6 month period.

The study method will now be described in detail.

CHAPTER 2

METHOD

1.0 Subjects

The subjects for this study were selected, over a 7 month period, from those patients

admitted to the coronary care unit of a major metropolitan public teaching hospital with a

diagnosis of acute myocardial infarction . This diagnosis was made by the unit medical

team on the presence of at least two of the following criteria: a clinical history of

infarction, elevated cardiac enzymes and appropriate electrocardiograph changes.

All male patients admitted during this period under the age of 70 years were considered

for inclusion in the study. Subsequently, those considered by the medical staff to have

severe physical complications such as advanced cardiac failure, renal failure, pulmonary

disease, diabetes and debilitating arthritis, for example, were also excluded.

It was determined that those over 70 were more likely to have other health problems that

might interfere with lifestyle changes. The severely ill were excluded on humanitarian

grounds as well as the fact that a debilitating condition would affect attitudes and the

ability to achieve the lifestyle changes in question. Females were also excluded as an

additional measure to obtain as homogeneous sample as possible since their numbers

were expected to be relatively small considering the short time frame of the study.

Thus, 71 male subjects met the selection criteria. However, not all of these participants

completed all the requirements of the study.

Two subjects refused to participate in the study. One had difficulties in understanding the

questionnaires due to a poor command of the English language. Two subjects declined to

participate further because of other commitments when they were asked to complete the

questionnaires 3 months after hospitalisation and one other could not be located, having

changed address.

Two subjects were eliminated from the study, one after 3 months and the other after 4

months due to their undergoing coronary artery by-pass surgery as a result of persistent

angina pectoris.

Sixty three men completed all requirements of the study. Their average age was 48.8 yrs

with a range of 33 yrs to 68 yrs. Thirty nine of these men were married, 19 single, 4

widowed and 1 was divorced.

2.0 Questionnaires

After indicating their consent on the form shown in Appendix Al, subjects completed the

questionnaires described below and which are provided in full in Appendix A of this

document.

2.1 Subject Information.

Name, address and telephone number were obtained from subjects to enable further

contact to be made after 3 and 6 months. Demographic information that might have had a

bearing on the findings of the study, namely age, marital status and occupation were also

obtained (Appendix A2).

Additional information was obtained from the subjects' medical files.

The Prognostic Index (Norris, Caughey & Mercer, 1970) is a measure of the severity of

infarction and was determined by the admitting doctor in the Coronary Care Unit and is

routinely noted in the subject's medical file. A higher Prognostic Index indicates a greater

degree of heart failure at the time of infarction and is correlated with a poorer outcome.

This measure was recovered from the medical notes to provide a check that the severity of

the infarct did not independently influence compliance with health behaviour.

Evidence of complications, as determined by each subject's doctor, was carefully noted

since severe cardiac failure, or other severe organ involvement, was cause for exclusion

from the study as described above.

2.2 Pre-heart Attack Health Behaviours Questionnaire

This questionnaire (Appendix A3), completed at the time of hospitalisation, asked

respondents to choose, with a tick, one of five behaviours from each of five health

behaviour categories which best represented their health behaviour prior to their

myocardial infarction.

The five health behaviour categories were smoking, diet, exercise, alcohol consumption

and relaxation. Each category consisted of five behaviours organised in a graded

hierarchical fashion with the most positive health behaviour at the top, scoring 5, and the

least positive at the bottom, scoring 1. A mean pre-heart attack health behaviour score

was calculated for the total scale.

These same categories and hierarchies were used for all other questionnaires in this study

relating to health behaviour such as the Current Health Behaviour Questionnaire, the Self-

efficacy Questionnaire and the Outcome Expectancy Questionnaire.

2.3 Self-efficacy Questionnaire

This questionnaire (Appendix A4) consisted of the same five health categories and the

same five behaviours organised hierarchically, as used in the Pre-heart Attack Health

Behaviour Questionnaire described above. However, in completing this questionnaire,

the respondents were asked to indicate that behaviour they expected to achieve in 6

months time (self-efficacy level) for each of the health categories.

Subjects were also asked to indicate, on a scale of 0 to 100, for the chosen behaviour in

each category, their degree of confidence (self-efficacy strength) that they would achieve

that behaviour in 6 months time. A low score indicated low self-efficacy strength (low

confidence of success) and a high score high self-efficacy strength (high confidence of

success).

The five behavioural levels in each of the categories were scored from 5 down to 1 in

order of health 'desirability'. Thus, giving up smoking was given a score of 5, smoking

less than 5 cigarettes per day a score of 4, and so on. The scores for the performance

level chosen by the subject in each of the 5 categories were summed and divided by 5 to

provide a mean health behaviour self-efficacy level score. The range of possible scores

was therefore between 1 and 5. The self-efficacy strength scores were also summed

across all five health categories and divided by five to compute a mean health behaviour

self-efficacy strength score.

This questionnaire was completed by subjects at the time of hospitalisation, then 3

months and 6 months later. On each occasion subjects were asked to indicate their self-

efficacy beliefs for achieving the health behaviours in 6 months time.

2.4. Outcome Expectancy Questionnaire

The same five health categories and levels of behaviour as for the self-efficacy

questionnaire were presented to measure outcome expectancy (Appendix A5). For each

category, subjects were asked to indicate, for the same level chosen by them in the Self-

efficacy Questionnaire, the degree, on a scale of 0 to 100, to which they believed that

achieving that behaviour would actually help in preventing a future heart attack. A high

score indicated a strong belief that the behaviour would be effective (high outcome

expectancy strength) and a low score to the contrary (low outcome expectancy strength).

The outcome expectancy strength scores were summed across the five categories and

divided by five to provide a mean health behaviour outcome expectancy strength score.

2.5 Health Threat Beliefs Questionnaire

As described in the introduction, the Health Belief Model consists of a number of

components. Three of these components, which are most widely used in investigations

with the Health Belief Model, were chosen for inclusion in this study. They were

perceptions of: how serious subjects thought having a heart attack was, how concerned

they were about having a heart attack and how likely they thought it was that they would

have a heart attack in the future. Together these three components measured a perception

of health threat.

This questionnaire (Appendix A6) consisted of three questions, one measuring the

subjects' perceptions of the seriousness of having a heart attack, another measuring

concern about having a heart attack and the third measuring beliefs about the likelihood of

having a future heart attack. Subjects were asked to circle, for each question, their

response on a 4-point Liken scale.

2.6 Multidimensional Cardiac Health Locus of Control

2.6.1. Health Value

As described in Chapter 1, both Rotter (1975) and Wallston and Wallston (1981) have

said that locus of control is only meaningful if the value of the reinforcement to the

individual is taken into account. Therefore, prior to measuring cardiac health locus of

control, a measure of the subjects' health value was obtained to differentiate between

those subjects with a positive and those with a negative health value orientation

(Appendix A7).

In accordance with previous research with health locus of control (Wallston, Maides &

Wallston, 1976; Wallston, Wallston & DeVellis, 1978), subjects were asked to place in

order of importance the 10 potentially valued states indicated in the questionnaire, one of

which was 'Good Health'. It was decided that, consistent with the original research

conducted by the Wallston group (Wallston, Maides & Wallston, 1976; Wallston,

Wallston & DeVellis, 1978), those subjects who placed 'Good Health' in the top half of

their list were classified as having a positive health value. Conversely, those relegating

'Good Health' to the bottom half were classified as having a negative health value.

Subjects could then be placed in one of four groups: high health value and high cardiac

health locus of control; high health value and low cardiac health locus of control; low

health value and high cardiac health locus of control; and low health value and low

cardiac health locus of control.

2.6.2 The Multidimensional Health Locus of Control Scale

The Multidimensional Cardiac Health Locus of Control Scale (Appendix A8) was adapted

from the Multidimensional Health Locus of Control Scale (Wallston & Wallston, 1979),

as described in detail in the introduction. The scale consists of three, 6-item subscales

measuring internal, powerful others and chance cardiac health locus of control. Items

belonging to each of the three subscales are indicated on the questionnaire in Appendix

A8. Respondents were asked to indicate on a scale of 1 (strongly disagree) to 6 (strongly

agree) the extent to which they agreed or disagreed with each of 18 statements relating to

cardiac health locus of control.

The sum of ratings for the 'internal' questions provided the internal cardiac health locus

of control score, the sum of ratings for the 'powerful others' questions provided the

powerful others cardiac health locus of control score and the sum of the 'chance'

questions provided the chance cardiac health locus of control score. A high score

indicated high internal, powerful others and chance beliefs.

Health value and cardiac health locus of control were measured at the time of

hospitalisation, and 3 months and 6 months later.

2.7 Psychological Distress and Psychological Health

As described in Chapter 1, the General Health Questionnaire (Goldberg, 1972) and the

Thoughts and Real-Life Experiences scale (Dua, 1990) are valuable measures of

psychological health and psychological distress. The GHQ-28 (Appendix A9) was used

because it offered a valid and reliable shorter (only 28 items) alternative to the 60 item

version. The shorter scale was preferred to minimise effort on the part of subjects

obviously susceptible to the cardiovascular effects of stress. A single score of

psychological distress was obtained by combining scores on each of the four, seven-item

sub-scales. Each item was scored from 1 to 4 on a Likert scale with a range of 28 to 112

for the whole questionnaire. A high score indicated poorer psychological health.

The two distress scales (Appendix A 10) were used from the Thoughts and Real-life

Experiences Scale (THARL Scale: Dua, 1990). Average scores for each of the two scales

were obtained by summing the scores for all items and then dividing by the total number

of items to which subjects responded. Average scores were computed since there were a

number of items which subjects would be likely to judge to be 'not applicable' to them.

Measures of psychological health, and distress as a result of real-life experiences and

thoughts were obtained at the time of hospitalisation, and 3 months and 6 months later.

2.8 Current Health Behaviour Questionnaire

The Current Health Behaviour Questionnaire (Appendix Al 1) was presented to subjects 3

months and 6 months after discharge from hospital. Subjects were asked to indicate their

current health behaviour in relation to the same five categories used in the Pre-Heart

Attack Health Behaviours Questionnaire.

3.0 Procedure

Following selection, as described above, prospective subjects were approached between

3 days and 5 days after being diagnosed as having had an uncomplicated myocardial

infarction and were still inpatients in either the coronary care unit or in a general ward of

the public teaching hospital chosen for this study. Permission involve patients in the

study was obtained from the physician in charge.

Initial contact with prospective subjects was by the researcher who introduced himself

and asked each man to '...help in a research project aimed at finding out more about how

people recover from heart attacks'. It was explained that they would be required to

complete fairly lengthy questionnaires on three occasions, that complete confidentiality

was assured and that they could decide to 'drop out' from the study at any time with no

prejudice. Subjects were also reassured that neither their treatment nor rehabilitation

would be altered in any way to that normally provided by their participation or non-

participation in the study.

Subjects were asked to give their written consent to be included in the study. The consent

form (Appendix A1) was cleared by the Ethics Committee of the University of New

England.

Once consent was obtained, the subject completed the Pre-Heart Attack Health

Behaviours Questionnaire, Self-efficacy Questionnaire, Outcome Expectancy

Questionnaire, Health Threat Beliefs Questionnaire, Health Value Questionnaire,

Multidimensional Cardiac Health Locus of Control Scale, GHQ, and the distressing

thoughts and real-life experiences parts of the THARL Scale.

The questionnaires were completed by the subject with the researcher present who was

able to answer any queries as they arose. Subjects were then reminded that further

questionnaires would be posted to them in 3 months and 6 months time and that they

would be contacted by telephone to discuss any problems with completing them.

Information about the subject's age, marital status, occupation and Prothrombin Index

was obtained from medical records.

Approximately 3 months and 6 months later, all the above questionnaires, with the

exception of the Pre Heart Attack Questionnaire, were sent with a stamp addressed

envelope to the subjects with a brief letter requesting their ongoing participation. Subjects

were also contacted by telephone to facilitate questionnaire return and deal with any

difficulties.

The schedule of questionnaires answered by the subjects on each of the three occasions is

shown in Table 1 below.

Table 1: Schedule of Questionnaires

Questionnaire Hospital 3 Months 6 Months

Pre Heart Attack Health Behaviour X

Current Health Behaviour X X

Self-efficacy X X X

Outcome Expectation X X X

Health Threat Beliefs X X X

Health Value X X X

Cardiac Health Locus of Control X X X

GHQ X X X

THARL Scale X X X

All subjects participated in the hospital's standard cardiac rehabilitation program which

principally involved education as a means to helping the person modify 'at risk'

behaviours such as smoking, diet, exercise and stress. Subjects received written

information from the National Heart Foundation and watched a video, during the first 5

days of hospitalisation, about heart attacks, their cause, effects, treatment and desirable

lifestyle changes following a heart attack. This information specifically recommended,

inter alia, cessation of smoking, dietary changes with respect to reducing cholesterol and

dietary fat intake, increasing exercise, relaxing more in the face of stress, and reducing

alcohol intake. This information was reinforced by nursing and medical staff and any

questions or misunderstanding subjects might have had were addressed.