The reliability of constructs derived from attitude-behavior theories: an application of generalizability theory in the health sector

Quality & Quantity 26: 291-305, 1992. 291 �9 1992 Kluwer Academic Publ&hers. Printed in the Netherlands.

The reliability of constructs derived from attitude-behavior theories: an application of generalizability theory in the health sector

PIERRE VALOIS 1'4, GASTON GODIN 1,3 & RICHARD BERTRAND 2 1Research Group on Psychosocial Aspects of Health (FCAR: 91-ER-0699); 2Department of Measurement and Evaluation, Laval University; 3School of Nursing, Laval University, Ste-Foy (Qu6bec), Canada, GIK 7P4; 4Department of Education Sciences, UQTR

Abstract. Theories of reasoned action, interpersonal behavior and self-efficacy have been frequently used for research into health-related behavior. The present study investigated two methods for assessing the reliability of their theories ' constructs: the test-retest me thod and generalizability theory. Firstly, it is demons t ra ted with a numerical example that the traditional test-retest coefficient has an anatomical link with the generalizability coefficient. Secondly, generalizability theory was applied in order to identify the number of occasions each construct mus t be measured to assure its reliability. This procedure was applied to the data collected in a study investigating the psychosocial factors influencing exercising and smoking behaviors among pregnant women. Measur ing the constructs of direct att i tude, habit, and intention on only one occasion was sufficient to ensure high levels of reliability. Moreover , reliability of the other constructs would be ensured if they were measured on more than one occasion.

In the sector of health, using attitude-behavior theories borrowed from the area of social psychology in order to further the understanding of health- related behaviors is becoming increasingly popular. Many studies have used the propositions of the self-efficacy theory (Bandura, 1977), the Triandis theory (1977), or the theory of reasoned action (Ajzen & Fishbein, 1980). Examples of such applications can be found for smoking (Grube et al . , 1986; Norman & Tedeshi, 1989; Sherman et al. , 1982), exercising (Godin et al . , 1987; Riddle, 1980; Valois et al . , 1988), family planning (Jaccard & Davidson, 1972), use of contraceptive devices (Davidson & Morrison, 1983), blood donation (Bagozzi, 1981; Brinberg, 1979; Pomazal & Jaccard, 1976; Zucker- man & Reis, 1978), dental brushing and flossing (McCaul et al . , 1988; Tone- atto & Binik, 1987), use of seat belt (Budd et al . , 1984; Mittal, 1988; Witten- braker et al . , 1983), alcoholism treatment (Brubaker et al . , 1987), self- examination to breast abnormalities (Seibold & Roper, 1979), calcium intake (Wurtele, 1988), and weight loss (Schifter & Ajzen, 1985).

This study was supported by a research grant f rom the Social Sciences and Humani t ies Research Council of Canada (#410-86-0611).

292 Pierre Valois et al.

A common feature of all these applications is the use of paper and pencil questionnaires in order to measure individuals' broad dispositions, such as traits. In these questionnaires, rating scales are used to measure peoples' self-reported opinions for different theoretical constructs. This latter problem highlights the necessity to verify the metrologic qualities of the instruments used.

Overall, it seems that few researchers report the metrologic qualities of such instruments in the health sector. For example, Lamp et al. (1989) have documented that less than 25% of the published studies in different health- related journals provided information concerning instrument reliability. Among the published manuscripts that report on this, the most popular strategy has been to calculate internal consistency indices (i.e., Cronbach's alpha coefficient). Although the reliability coefficients reported by the authors are relatively good, their atti tude-behavior relationship is rather low (Wicker, 1969). This means, for instance, that although the score of a ciga- rette smoker on a given attitude scale suggests that he or she is in favor of not smoking, he or she is and will remain a regular smoker.

Gulliksen (1950) and Cronbach et al. (1972) indicated that the reliability of a test is not exclusively a matter of the homogeneity of its items (i.e., internal consistency), but equally of its stability. Like these latter authors, Epstein (1979, 1980) claimed that a critical issue in psychological theory is whether stable traits exist or not. A trait like an attitude is stable when a person responds in a certain manner over a sufficient sample of events, thus reinforcing the possibility of generalization over time. Reliability is therefore defined as the stability of the classification of the scores of the individuals being tested, while measurement error is attributed to the effects of the sampling of test items and testing occasions. In support of this point of view, Schwartz (1978) showed that the attitude behavior correlation was higher over a 3-month interval (r = 0.47) than over a 6 -month interval (r = 0.13). It seems that these results support the oft-repeated contention that temporal instability in attitudes weakens the atti tude-behavior relation.

In a recent review paper concerning Generalizability Theory (GT), Shavel- son et al. (1989) wrote:

The concept of reliability so fundamental to CT (classical theory), is re- placed by the broader and more flexible notion of generalizability. Instead of asking how accurately observed scores reflect the corresponding true scores, GT (generalizability theory) asks how accurately observed scores

Generalizability theory 293

permit us to generalize about persons ' behavior in a defined universe of

situations (p. 922).

In opposit ion to the classical test theory, G T splits the error te rm into multiple sources of errors such as persons, items, and occasions, and states that these sources of errors should be est imated simultaneously; indeed, the sources of errors are not necessarily independent of each other. For example, the m o m e n t of measurement may influence the way a given subject answers on a given health atti tude scale; the answers given in a questionnaire on att i tude towards exercising for example, may differ depending on whether these answers were obtained in the winter or in the summer. Similarly, the nature of the health behavior under study may influence the way a given subject scores on the att i tude scale on separate occasions; a change over a two-week test-retest period may be observed for a given health behavior, but not for another. In this context, G T allows us to judge whether the score differences observed between the subjects could be generalized to all i tems and occasions. This means that the objective of G T is to know whether the means observed over a sample of items and a sample of occasions could be generalized to the theoretical universe of items and occasions (generally determined as unlimited).

F rom a practical point of view, the stability of the attitude construct over t ime is generally measured as follows. First, in a prel iminary study, a researcher administers a given questionnaire to a sample of persons on two different occasions (usually at one or two-week intervals). If the scores obtained on these two occasions are highly correlated, the researcher con- cludes that the questionnaire is stable over this period of t ime (e.g., one or two-week intervals). Second, in t h e main study the researcher administers the questionnaire on one occasion only. However , two questions remain unanswered: (1) are the scores obtained f rom the questionnaire administered once sufficient to generalize the results obtained over a longer period of t ime?, and (2) when they are not, how many times are necessary in order to obtain mean scores that are generalizable over t ime (i.e., to the universe of occasions and/or i tems)?

The aim of this article is to answer both questions. To answer the first question, using a numerical example based on the analysis of variance for- mulas, we would demonst ra te that the classical test-retest coefficient is a special case of generalizability coefficient, that is, an index of the degree of generalization over t ime for a measure obtained on one occasion. The second question would be answered by using a generalizability theory optimization design for two or more occasions.


Methods

Subjects and procedure for data collection

The subjects were 63 pregnant nullipara (i.e., first pregnancy) registered at prenatal education classes offered in different Local Centres for Community Services (CLSC) of the Quebec metropolitan area. These CLSCs were chosen on the basis of accessibility and convenience. The study was described to these pregnant women during a regular session of their prenatal class. At this time, they were invited to participate by completing two self-administered questionnaires, concerning exercising and smoking cigarettes after childbirth. Two weeks later, these women were invited to fill out the same questionnaires again. Forty-eight of these sixty three subjects completed this phase satisfac- torily.

Variables measured

Based on the theories advanced by Fishbein and Ajzen (1975), Triandis (1977) and Bandura (1977), and according to the recommendations made by Ajzen and Fishbein (1980) concerning questionnaire development, the following variables were measured on both occasions:

Intention (I). Intention regarding each behavior was measured by using the following questions: (a) "What is the probability out of 100 that you will not smoke cigarettes during the nine months after giving birth?"; and "What is the probability out of 100 that you will exercise regularly during your free time during the nine months after giving birth?". The responses were recorded on a 1 to 10 point scale represented by a sequence of percentages ranging from 0 to 10%, 11 to 20% and so forth until 91 to 100%.

Attitude-toward-the-act (Aact). The subjects reported their attitudes toward each of the behaviors on six semantic differential scales ranging from 1 to 7. The bipolar adjectives were (a) unpleasant~pleasant, (b) dull/interesting, (c) boring~stimulating, (d) unhealthy~healthy, (e) bad~good, and (f) useless~use- ful.

Subjective norm (SN). With reference to significant others, the subjects were asked to answer the following questions: (a) "How strongly do you believe significant others think you should not smoke cigarettes during the nine months after giving birth?"; and (b) "How strongly do you believe significant others think you should exercise regularly during your free time during the


nine months after giving birth?". Each item was measured on a bipolar 7-point scale with opposite poles of unlikely and likely.

Perceived self-efficacy (PSE). For each behavior, perceived self-efficacy was measured by asking subjects to indicate on a bipolar 7-point scale, with definitively not and definitively at opposite poles, to what extent they expected to be capable of (a) not smoking cigarettes, and (b) exercising regularly during the nine months after giving birth.

Personal normative belief (PNB). The subjects were asked to indicate on 7-point scales, with disagree and agree at opposite ends, if they felt a moral obligation (a) to not smoke cigarettes, and (b) to exercise regularly during the nine months after giving birth.

Role belief (RB). The subjects were asked: "How strongly do you believe that other pregnant women think it is appropriate (a) to not smoke cigarettes, and (b) to exercise regularly during the nine months after giving birth?". Each item was measured on a bipolar 7-point scale with opposite poles of unlikely and likely.

Habit before onset of pregnancy (1-1). With respect to smoking, the subjects were asked to indicate their smoking status before the onset of their current pregnancy, using the following options: (a) nonsmoker; (b) occasional smoker; (c) regular smoker, but not on a daily basis; and (d) daily smoker. Concerning exercising, the following question was asked: "How often did you participate regularly in one or more physical activities during your free time before the onset of the current pregnancy?". The choices offered were (a) never, (b) sometimes, (c) frequently, and (d) always.

Indirect attitude (Eb x e). The questionnaires presented eight (not smoking) and ten (exercising) salient beliefs and outcomes. For each belief a 7-point scale, with unlikely and likely at opposite poles, was used to evaluate to what extent they believed that (a) not smoking cigarettes and (b) exercising regularly during the nine months after giving birth would lead to the presented outcomes. At this point, subjects were asked on a bipolar 7-point scale with bad and good at opposite ends the extent to which they valued each outcome relative to each questionnaire. Each measure of indirect attitude was obtained by summing all eight (not smoking) and ten (exercising) belief x outcome products, respectively.

Indirect subjective norm (ENB • MC). Women were asked to evaluate on a


bipolar 7-point scale (unlikely and likely) whether they thought their spouse thinks they should (a) not smoke cigarettes, and (b) exercise regularly during the nine months after giving birth. The corresponding motivation to comply was evaluated (disagree and agree) by asking the women to indicate how strongly they were inclined to act according to the expected belief of their spouse concerning each behavior. A similar measure was obtained with respect to physicians as normative referents. Finally, each measure of normative belief was multiplied by the score for corresponding motivation to comply and the products were summed.

Facilitating conditions (F). This construct was assessed only in the context of exercising, since it is unlikely to be relevant for predicting non smoking behavior. Subjects were informed that there were several constraints to the regular practice of physical activity after giving birth (problems with day care, difficulties with transportat ion, . . . ) . They were then asked, "Following an evaluation of your personal situation, how easy or difficult do you believe it would be to regularly practice one or more physical activities during your free time during the nine months after giving birth? The subjects recorded their response on a 7-point scale ranging from - 3 to +3.

Statistical analysis

The application of generalizability theory includes four steps. The first and second steps are based on the analysis of variance, whereas the other two steps are related to concepts particular to generalizability theory (Cardinet et al., 1981). The first step, the observation design, is descriptive and ident- ifies the choice of the facets (i.e., items, occasions, persons), the relationship among facets, and the number of observed levels per facet. In the second step, the estimation design, the researcher determines the number of admiss- ible levels for each facet and whether the facets are random or fixed. At step three, the measurement design specifies the differentiation facet (i.e., the facet where the differences between the levels have to be maximized: in the present case, the persons), and the instrumentation facets (i.e., occasions and items). Finally, the optimization design allows us to estimate the level of change in the coefficient of generalizability if the levels of differentiation facets are decreased or increased.

In the present study, the generalizability analyses differ according to the theoretical constructs measured on a single item (i.e., intention, subjective norm, role belief, personal normative belief, facilitating conditions, habit, and self-efficacy) or multiple items (i.e., direct and indirect attitudes and


social beliefs). The four steps described above are operationalized as follows according to the single and the multiple items constructs, respectively.

1) The data obtained can be organized as a factorial design with two crossed factors (persons x occasions) for the single item constructs, and with three crossed factors (persons x items • occasions) for the multiple items constructs.

2) Only the level of the occasion facet is random (i.e., drawn from an infinite population), for each kind of construct.

3) Since the comparisons are made between persons, 'person' is considered as the differentiation facet. 'Occasions' for the single item constructs, and 'occasions and items' for the multiple items constructs, are the instrumentation facets.

4) In this study, the optimization design is used in order to verify the effect of theoretically determining the number of occasions a construct is measured. This strategy gives hypothetical generalizability coefficients which correspond to each number of testing occasions. These coefficients suggest the number of occasions necessary for obtaining mean scores that are appropriately generalizable over time and can be obtained by placing the number of hypothetical (no) occasions in the following equations:

(a) Persons by occasions interaction

2

Ep 2 ( 6p ) - o-p 2 + (1) O'p

where Ep 2 (r is the expected generalizability coefficient; cr 2 is the estimated 2 is the estimated variance component variance component for persons; o-p0

for persons by occasions interaction; and no is the number of occasions observed.

(b) Persons by items by occasions interaction:

2

Ep2(6p[i.) = Crpli* 2 2 ' (2) O'pli. -F (O'poli./llO )

where Ep2(Spli .) is the expected generalizability coefficient when the items 2 facet is fixed; O-pli. is the estimated variance component for persons when

the items facet is fixed; O -2 is the estimated variance component for persons P0]I*


Table 1. Means and standard deviations of the theoretical constructs for exercising and not smoking cigarettes

Constructs Behaviours

Exercising Not smoking

Pretest Posttest Pretest Posttest

Direct attitude (Aact)" Indirect attitude (Eb • e) b Indirect subjective norm (ENB x MC) b Intention (I) c Direct subjective norm (SN) a Role beliefs (RB) a Personal normative beliefs (PNB) a Habit (H) d Self-efficacy (SE) ~ Facilitating conditions (F) a

5.85 -+ 0.84 6.06 --- 0.82 5.92 • 1.14 6.06 +_ 1.07 3.65 • 4.97 • 2.47 5.05--- 2.58 5.79 = 2.50 2,24 • 2.37 • 4.41 3.67 + 4.51 3.02• 5,40 7,31 • 7,44• 2.13 8.06-+ 3.34 8.10-- 3.05 5,35 • 1.47 5,77 +- 1.10 5.96-+ 1,11 6.02 + 1.33 5.12-+ 1,23 5.73 • 1.01 5.44 + 1.57 6,00-+ 1.22 5.00-+ 1,80 5.00 • 1.58 5.06 • 2,12 5,40• 1.99 2,46---0.77 2.44• 0.68 1.83 • 1,34 1.69 • 1.21 5.40• 1.38 5,29• 1.43 5,94 • 1.82 5,92-+ 1.96 4,77 + 1,56 4.92• t.37 -

Range values a: 1 to 7, b: - 9 to 9, c: 1 to 10, d: 1 to 4.

by occasions in te rac t ion when the i tems facet is fixed; a nd no is the n u m b e r

of occasions observed .

In summary , the a im of the statistical analysis is twofold: (1) to demon-

strate by a numer ica l example that the test-retest coefficient is an index of

the degree of genera l iza t ion of a const ruct measu re ob t a ined on one occasion

(i .e. , G T coefficient for n = 1); and (2) to de t e rmine how m a n y t imes the

constructs inves t iga ted in this s tudy, based on the F i shbe in and Ajzen , Tri-

andis , and B a n d u r a models , need to be measu red to be stable over t ime.

R e s u l t s

The average age of the sample was 26.6 years. Hal f of the subjects (55%)

had b e g u n or comple ted high school, whereas the o ther half (45%) had

some college or higher educat ion . The mean s a nd s tandard deviat ions of the

var iables for exercising and no t smoking at pre- and post-tests are p resen ted

in Tab le 1. The es t imated test-retest coefficients and general izabi l i ty coef-

ficients are p resen ted in Tables 2 and 3.

These data o b t a i n e d were used here to i l lustrate the ana tomic l ink be tween

the test-retest coefficient and general izabi l i ty coefficient. This numer ica l ex-

ample was based on the results ob t a ined for the i n t en t ion to exercise con-

struct. More specifically, we descr ibed the calculat ion of the general izabi l i ty

coefficient on the basis of the test-retest cor re la t ion coefficient (r = 0.77),

General&ability theory 2 9 9

Table 2. Est imated test-retest coefficient and generalizability coefficient for the exercising constructs

Constructs Test-retest coefficient

Generalizability coefficient for each optimization design

no = 1 no = 2 no = 3 no = 4 no = 5

Direct att i tude (Aact) 0.66 0.66 0.80 0.85 0.89 0.91 O~pr e = 0.81; O~post = 0.87

Indirect att i tude (Eb • e) 0.59 0.58 0.74 0.81 0.85 0.88 O/pr e = 0.84; O~post = 0.89

Indirect subjective norm (ENB • MC) 0.51 0.51 0.67 0.76 0.81 0.84 OLpr e = 0.68; apost = 0.73

Intent ion (I) 0.77 0.76 0.87 0.91 0.93 0.94 Direct subjective norm (SN) 0.08 0.08 0.14 0.20 0.25 0.29 Role beliefs (RB) 0.48 0.47 0.64 0.72 0.78 0.81 Personal normat ive beliefs (PNB) 0.37 0.36 0.53 0.63 0.70 0.74 Habit (H) 0.70 0.70 0.82 0.87 0.90 0.92 Self-efficacy (SE) 0.40 0.40 0.58 0.67 0.73 0.77 Facilitating conditions (F) 0.63 0.62 0.77 0.83 0.87 0.89

Table 3. Est imated test-retest coefficient and generalizability coefficient for the not smoking constructs

Constructs Test-retest coefficient

Generalizability coefficient for each optimization design

n 0 = l n o = 2 n 0 = 3 no = 4 no = 5

Direct att i tude (Aact) 0.71 0.71 0.83 0.88 0.91 0.93 apre = 0.77; aport = 0.7

Indirect att i tude (Eb x e) 0.41 0.41 0.58 0.68 0.74 0.78 aprr = 0.60; apost = 0.68

Indirect subjective norm ( s • MC) 0.61 0.60 0.75 0.81 0.86 0.88 O~pr e = 0.67; Otpost = 0.90

Intent ion (I) 0.95 0.94 0.97 0.98 0.99 0.99 Direct subjectie no rm (SN) 0.16 0.16 0.27 0.36 0.43 0.48 Role beliefs (RB) 0.21 0.21 0.34 0.44 0.51 0.56 Personal normat ive beliefs (PNB) 0.47 0.47 0.64 0.73 0.78 0.82 Habit (H) 0.91 0.91 0.95 0.97 0.98 0.98 Self-efficacy (SE) 0.78 0.78 0.88 0.92 0.94 0.95

a n d t h e v a r i a n c e s o f i n t e n t i o n a t t h e p r e - (SD = 2 . 4 2 ) a n d p o s t - t e s t (SD = 2 . 1 3 ) .

F o r no = 2 , t h a t i s , a o n e - w e e k t e s t - r e t e s t p e r i o d ; w e h a d

2

G T c o e f f i c i e n t = p2 = O-p % + (@o/no)"

(3)

W e d e f i n e d o-p 2 a s a f u n c t i o n o f M S p a n d M S p 0 ,


0.p2 = (MSp - MSpo)/2 ,

and 0.20 as a funct ion of MSpo,

O'2o = MSpo-

Similarly, we wro te MSp and var iance and covar iance values.

(4)

(5)

MSp0 as a funct ion of their co r responding

MSpo =- MSresldual = V A R - C O V 2 2 2

= ( S 2 r e --~ S p o s t - 2 ( S p r e ) ( S p o s t ) ( r p r e _ p o s t ) ) / 2

= (2.422 + 2.132 - 2(2.42)2(2.13)2(0.77)) /2

= 1.23, (6)

and

MSp = MSbet . . . . people = V A R + (no - 1) C O V

= V A R + (2 - 1) C O V

= V A R + C O V 2

= (sZre + Spost + 2(Spre) (Spost)(rpre_post))/2

= (2.422 + 2.132 + 2(2.42)(2.13)(0.77)) /2

= 9.17.

(7)

Placing the values ob ta ined in Equa t ions (6) and (7) in E q u a t i o n (4), we ob ta ined ,

9 . 1 7 - 1.23 o" 2 = 3.97

2

and

0.2 = 1.23. P0

Similarly, placing these two values in E q u a t i o n (3) we ob ta ined ,

3.97 p2 = = 0.87,

3.97 + (1.23/2)


that is, the value of GT coefficient for the construct of intention to exercise. The comparison of the first two columns of Tables 2 and 3 demonstrated

more obviously the link between the test-retest coefficient and generalizability coefficient. In fact, the classical test theory coefficients and GT coefficients for one occasion (n = 1) were of the same magnitude.

The results for the second question addressed by the study are presented in the last four columns of Tables 2 and 3. The GT optimization design allowed us to determine how many occasions a construct needed to be measured in order to be stable.

The direct (Aact) and indirect (Eb x e) measures of attitudes and the indirect measure of social norms (ENB x MC) were based upon multiple items. The alpha Cronbach's coefficients (a) for these three constructs are presented in Tables 2 and 3. At the pre-test, the values were, respectively, 0.81, 0.84, and 0.68 for exercising and 0.77, 0.60, and 0.67 for not smoking. The corresponding values at the post-test were 0.87, 0.89, and 0.73 for exercising and 0.77, 0.68, and 0.90 for not smoking. The values obtained at the post-test were higher than those obtained at the post-test. Concerning these three constructs, the results (top of Tables 2 and 3) indicated that the semantic differential measure of attitude had relatively high (p2 > 0.75) generalizability coefficients (0.75 for exercising and 0.79 for not smoking). The other constructs (Eb x e and ENB x MC) showed moderate (0.50 < p2 < 0.75) generalizability coefficients even though their alpha values were appropriated.

Regarding the single item constructs, the results (bottom of Tables 2 and 3) indicated that the intention and habit constructs had appropriate generalizability coefficients for exercising (0.87 for intention and 0.82 for habit), and not smoking (0.97 for intention and 0.95 for habit). The subjective norm construct had very weak (p2 < 0.50) generalizability values (0.14 for exercising and 0.27 for not smoking). All other constructs exhibited a moderate stability (0.50 < pz < 0.75).

It would appear that the measures of intention, direct attitude, and habit at one point in time yielded stable generalizability coefficients for both behaviors. The results also suggest that, for exercising, a proper generalizability coefficient (0.75) was obtained with two measures of facilitating conditions, three measures of indirect attitude and indirect social norms, and five measures of self-efficacy. Personal normative belief and subjective norm required more than five measures. Finally, for not smoking, the results


indicate that a proper generalizability coefficient was obtained with two measures of indirect social norm and self-efficacy, four measures of personal normative belief, and more than five measures of indirect attitude, role belief, and subjective norm.

Discussion

Generalizability theory offers a broader framework than the classical test theory for estimating reliability and errors of measurement. In fact, the alpha coefficient is a special case of GT, that is, generalization over the items, and the test-retest coefficient represents G T coefficient when generalization over time is required.

Indeed, as defined by the classical test theory, the test-retest coefficient represents the stability of the construct over the test-retest period, that is, two weeks in the present study. However , the main purpose of this type of analysis is to secure the stability of the construct not only for the next 2- week period, but over a longer period of time, that is, the period covered by the study (e.g., three months, six months, a year). Nonetheless, the present results show that the value of the test-retest coefficient was almost equal to the value of G T coefficient for one occasion (i.e., n = 1), thus the test-retest coefficient in some way represented an index of the stability of a construct over time when it is measured on only one occasion.

As expected, the coefficient of generalizability increased substantially when additional measures of the constructs were considered. Thus, in agreement with Epstein (1979, 1980) the mean of the scores resulting from several occasions' measurement for a given independent variable (e.g., attitude) should be more representative of this independent variable than the consider- ation of one score only: taking more than one measure of the psychosocial predictors would increase the accuracy of prediction of the behavior. This latter observation confirms the point of view of Sutton (1987), who suggested that a more precise test of att i tude-behavior models would require that attitudes be assessed at frequent intervals.

However , it would seem that a one-occasion measure may be sufficient to ensure stability for the intention, direct attitude (Aact), and habit constructs. Fur thermore , others constructs (i.e., indirect attitude, indirect social norm, role belief, personal normative belief, facilitating conditions, and the self- efficacy) require being measured on two or more occasions to ensure stability.

Moreover , the stability of these latter constructs may vary according to the behavior investigated. For example, in the case of exercising it seems that the indirect measure of attitude and role belief would be stable if they

General izabi l i ty theory 303

were measu red on three occasions. Wi th respect to no t smoking cigarettes

the same two constructs would be unstable even if they were measu red on

five occasions. In summary , the present results suggest that direct at t i tude (Aac t ) , habit

(H) , and in tent ion (I) , are stable constructs , regardless of the n u m b e r o f t imes they are assessed. Thus , it is no t surprising to observe that these three variables have been f requent ly found associated to heal th-re la ted behaviors

(Bagozzi , 1981; Bent le r & Speckar t , 1979, 1981; God in et al. , 1987; Sut ton, 1989). The present s tudy also suggests, as Miniard and C o h e n (1979, 1981) have observed , that subjective n o r m is an unstable construct . Concern ing the o thers constructs , stability varies according to the type of behav io r unde r

study. There fo re , these constructs mus t be measu red m o r e than once in o rder to ensure their stability as predic tors of behavior .

Finally, c o m p a r e d to a mult iple i tems construct , a single i tem construct was found to be m o r e susceptible to e r ro r of measu remen t , thus enhancing the probabi l i ty o f low stability. This finding suggests that single i tem constructs might no t be well covered. M o r e studies are needed to verify the

stability o f this type of const ruct (e.g. , SN) when they are measu red with m o r e than one i tem.

References

Ajzen, I. & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, NJ: Prentice-Hall.

Bagozzi, R.P. (1981). Attitudes, intentions and behavior: A test of some key hypotheses. Journal of Personality and Social Psychology, 41, 607-627.

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychology Review, 84, 191-215.

Bentler, P.M. & Speckart, G. (1981). Attitudes "cause" behaviors: A structural equation analysis. Journal of Personality and Social Psychology, 40, 226-238.

Bentler, P.M. & Speckart, G. (1979). Models of attitude-behavior relations. Psychological Review, 86, 452-464.

Brinberg, D. (1979). An examination of intention and behavior: A comparison of two models. Journal of Applied Social Psychology, 9, 560-575.

Brubaker, R.G., Prue, D.M., & Rychtarik, R.G. (1987). Determinants of disulfiram acceptance among alcohol patients: A test of the theory of reasoned action. Addictive Behaviors, 12, 43- 51.

Budd, R.J., North, D., & Spencer, C. (1984). Understanding seat-belt use: A test of Bentler and Speckart's extension of the theory of reasoned action. European Journal of Social Psychol- ogy, 14, 69-78.

Cardinet, J., Tourneur, Y., & Allal, L. (1981). Extension of generalizability theory and its applications in educational measurement. Journal of Educational Measurement, 18, 183-204.

Cronbach, L.J., Gleser, G.C., Nanda, H., & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. New York: Wiley.


Davidson, A.R., & Morrisson, D.M. (1983). Predicting contraceptive behavior from attitudes: A comparison of within - versus across - subjects procedures. Journal of Personality and Social Psychology, 45, 997-I009.

Epstein, S. (1979). The stability of behavior: On predicting most of the people much of the time. Journal of Personality and Social Psychology, 37, 1097-1126.

Epstein, S. (1980). The stability of behavior: Implications for psychological research. American Psychologist, 35, 790-806.

Fishbein, M. & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. MA: Addison-Wesley.

Godin, G., Valois, P., Shephard, R.J., & Desharnais, R. (1987). Prediction of leisure-time exercise behavior: A path analysis (LISREL V) model. Journal of Behavioral Medicine, 10, 145-168.

Grube, J.W., Morgan, M., & McGree, S.T. (1986). Attitudes and normative beliefs as predictors of smoking intentions and behaviours: A test of three models. British Model of Social Psychol- ogy, 25, 81-93.

Gulliksen, H. (1950). Theory of Mental Tests. New York: Wiley. Jaecard, J.J. & Davidson , A.R. (1972). Toward an understanding of family planning behaviors:

An initial investigation. Journal of Applied Social Psychology, 2, 228-235. Lamp, E., Price, J.H., & Desmond, S.M. (1989). Instrument validity and reliability in three

health education journals. Journal of School Health, 59, 105-108. McCaul, K.D., O'Neill, H.K., & Glasgow, R.E. (1988). Predicting the performance of dental

hygiene behaviors: An examination of the Fishbein and Ajzen model and self-efficacy expec- tations. Journal of Applied Social Psychology, 18, 114-128.

Miniard, P.W. & Cohen, J.B. (1979). Isolating attitudinal and normative influences in behavioral intentions models. Journal of Marketing Research, 16, 102-110.

Miniard, P.W. & Cohen, J.B. (1981). An examination of the Fishbein-Ajzen behavioral intentions model's concepts and measures. Journal of Experimental Social Psychology, 17, 309- 339.

Mittal, B. (1988). Achieving higher seat belt usage: The role of habit in bridging the attitude- behavior gap. Journal of Applied Social Psychology, 18, 993-1016.

Norman, N.N. & Tedeschi, J.T. (1989). Self-presentation, reasoned action, and adolescents' decisions to smoke cigarettes. Journal of Applied Social Psychology, 19, 543-558.

Pomazal, R.J. & Jaccard, J.J. (1976). An informational approach to illustrate behavior. Journal of Personality and Social Psychology, 33,317-326.

Riddle, P.K. (1980). Attitudes, beliefs, behavioral intentions and behaviors of women and men toward regular jogging. The Reearch Quarterly for Exercise and Sport, 51,663-674.

Schifter, D.B. & Ajzen, I. (1985). Intention, perceived control, and weight loss: An application of the theory of planned behavior. Journal of Personality and Social Psychology, 49, 843- 851.

Schwartz, S.H. (1978). Temporal instability as a moderator of the attitude-behavior relationship. Journal of Personality and Social Psychology, 36, 715-724.

Seibold, D.R. & Roper, R.E. (1979). Psychosocial determinants of health care intentions: Test of the Triandis and Fishbein models. In D. Nimmo (ed.), Communication Yearbook 3 (pp. 625-643). New-Brunswick, NJ: Transaction Books.

Shavelson, R.J., Webb, N.M., & Rowley, G.L. (1989). Generalizability theory. American Psychologist, 44, 922-932.

Sherman, S.J., Presson, C.C., Chassin, L., Bensenberg, M., Corty, E., & Olshavsky, R.W. (1982). Smoking intentions in adolescents: Direct experience and predictability. Personality and Social Psychology Bulletin, 8, 376-383.

Sutton, S. (1987). Social-psychological approaches to understanding addictive behaviours: Atti- tude-behaviour and decision-making models. British Journal of Addiction, 82, 355-370.

Sutton, S. (1989). Smoking attitudes and behavior: Applications of Fishbein and Ajzen's theory

General izabi l i ty theory 305

of reasoned action to predicting and understanding smoking decisions. T. Ney, & A. Gate (eds.), Smoking and Human Behavior, 289-312. Chichester: John Wiley & Sons.

Toneatto, T. & Binik, Y. (1987). The roles of intentions, social norms and attitudes in the performance of dental flossing: A test of the theory of reasoned action. Journal of Applied Social Psychology, 17, 593-603.

Triandis, H.C. (1977). Interpersonal Behavior. Brooks/Cole, Monterey, CA. Valois, P., Desharnais, R., & Godin, G. (1988). A comparison of the Fishbein and Ajzen and

the Triandis attitudinal models for the prediction of exercise intention and behavior. Journal of Behavioral Medicine, 11, 459-472.

Wicker, A.W. (1969). Attitudes versus actions: The relationship of verbal and overt behavioral responses to attitude objects. Journal of Social Issues, 25, 41-48.

Wittenbraker, J., Gibbs, B.L., & Kahle, L.R. (1983). Seat belt attitudes, habits and behaviors: An adaptative amendement to the Fishbein model. Journal of Applied Social Psychology, 13, 406-421.

Wurtele, S.K. (1988). Increasing women's calcium intake: The role of health beliefs, intentions and health value. Journal of Applied Social Psychology, 18, 627-639.

Zuckerman, M. & Reis, H.T. (1978). Comparison of three models for predicting altruistic behavior. Journal of Personality and Social Psychology, 36, 498-510.

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The reliability of constructs derived from attitude-behavior theories: an application of generalizability theory in the health sector