Health Education Research, Vol. 18, No. 5, 525-537,
October 2003
© 2003 Oxford University Press
When more is better: number of motives and reasons for quitting as correlates of physical activity in women
Department of Pediatrics, Baylor College of Medicine, Children’s Nutrition Research Center, 1100 Bates, Houston, TX 77030, USA
E–mail: cheryla{at}bmc.tmc.edu
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Abstract |
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Understanding the mechanisms by which physical activity is influenced is particularly relevant for health promotion efforts aimed at women, who display lower levels of physical activity and may experience more barriers to exercise than men. This study examined the number of motives for exercise and the number of reasons for previous quitting as predictors of exercise behavior. Specifically, the cognitive complexity of motives for exercise and reasons for quitting, as indicators of exercise-related memory associations that reflect cognitive structure, were evaluated. In a sample of 394 women aged 17–54, number of reasons for quitting did not predict current exercise level. However, more elaborated memory networks for motives were highly related to current exercise behavior, except among women with high Center for Epidemiologic Studies Depression Scale scores. These results support the predictive superiority of positive over negative memory associations found in studies on attitude accessibility in other behaviors, such as substance use, among women of normal mood and suggest a moderating effect of depression.
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Introduction |
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Individuals can substantially improve their health and quality of life by including even moderate amounts of exercise in their daily lives (Stofan et al., 1998
). An alarming 78% of the US adult population, however, does no regular or sustained physical activity (Centers for Disease Control and Prevention, 2001). Population surveys that assess physical activity generally show that women are more sedentary than men, a finding that tends to hold in every age group, and they experience higher rates of obesity (US Department of Health and Human Services, 2000, 2001). There is evidence that although women and men share some common motives for exercise, such as maintaining health, other motives are significantly different (Ashford et al., 1993; Finkenberg et al., 1994). In addition, women have been shown to think about reasons or ‘excuses’ for not exercising more than men (Kendzierski and Johnson, 1993), as well as have more negative emotions with regard to exercise (Auweele et al., 1997). These gender differences emphasize the need to better understand the determinants of physical activity among women in order to develop more effective interventions to increase their physical activity (Baranowski et al., 1998).
High rates of attrition affect virtually all exercise programs, whether formally or informally engaged. Typically, over 60% of individuals who start a regular exercise program drop out within 6 months (Pate et al., 1995). What accounts for people’s inability to stay with an exercise regimen? Numerous determinants of physical activity level have been identified in cross-sectional research. These correlates include demographic, psychological, social and cultural factors, physical environment factors, and physical activity characteristics (Sallis and Owen, 1999). Situational barriers, such as lack of time, are among the many reasons that are given for failing to exercise (Pate et al., 1995). It is often argued that women, who are likely to have domestic responsibilities in addition to vocational work (Dyer, 1982), encounter more barriers to activity than men (Jaffee et al., 1999; Sternfeld et al., 1999; Artazcoz et al., 2001). The multiple responsibilities and roles that women sustain in contrast to men contribute to chronic strain, which likely hampers women’s exercise efforts and serves as a vulnerability factor in depression (Nolen-Hoeksema et al., 1999).
The current study focused on motives for exercise and barriers to activity as reasons for attrition or exercise relapse among women, and the impact of depressed mood. ‘Reasons-for-quitting’ were defined as exercise barriers that had been personally experienced and resulted in exercise attrition. This definition is conceptually different from the traditional construct of perceived barriers and may also be differentially predictive of behavior. Some individuals, for example, may have many barriers to exercise, yet they overcome these obstacles and are regularly active. Others may find that perceptions of potential barriers upon starting an exercise program are not what really cause them to quit. Indeed, although usually regarded as strong and consistent exercise correlates (Sallis et al., 1999), perceived barriers have not always predicted who will drop out. For example, in a recent study on attrition from a church-based exercise program, perceived barriers at baseline did not predict attrition (Prochaska et al., 2000). A clearer understanding of physical activity determinants, such as perceived barriers that are ‘reasons-for-quitting’, is needed to facilitate effective programs to help individuals resume or continue regular exercise, especially among women.
Barriers to activity and exercise motives have been among the most widely studied correlates of exercise and physical activity, and figure prominently in several models of behavior that have been applied to physical activity (Becker and Maiman, 1975; Feather, 1982; Ajzen, 1985; Bandura, 1986; Duda and Tappe, 1988). As has been argued in other areas of research on attitudes and behavior, however, identification of relevant variables does not automatically reveal the mechanisms or processes by which they influence behavior (Rather et al., 1992). In the current study, first, cognitive differentiation is proposed as a mechanism of behavioral influence regarding exercise. Differentiation, which is operationalized through accessibility from memory, is a feature of cognitive structure that has also been termed ‘cognitive complexity’ (Linville, 1985). Second, depressed mood is proposed as a variable that may influence differentiation in exercise-related cognitive domains or act as a moderator that enhances or reduces the impact of this feature of cognition on behavior. Applying frameworks originating in cognitive psychology [e.g. (Bieri, 1955; Kelly, 1955; Fazio, 1986)], the present research contributes to a better understanding of the influence process.
In early models of cognitive structure (Bieri, 1955; Kelly, 1955) the organization of self-knowledge was thought to mediate behavior, as well as emotional experience. In the current study, total number of motives and reasons for quitting as indicators of cognitive differentiation are proposed as predictors of exercise behavior. As discussed in Rafaeli-Mor and Steinberg’s (Rafaeli-Mor and Steinberg, 2002) review of the history of the self-complexity construct, ‘differentiation’ has been described as the degree to which a cognitive domain contains multiple distinct elements. Seeing differentiation as a property of the individual, Kelly defined ‘complex’ individuals as those who utilized a larger number of constructs in perceiving their social environment. To other theorists [e.g. (Zajonc, 1960)], complexity was a property of the object or domain, rather than the individual. In all of these models, however, was the common notion that a person could hold a cognitively complex or differentiated view (or, in contrast, a non-complex or undifferentiated view) of any particular domain, such as nations and celebrities (Scott, 1969), self-attributes (Linville, 1985; Zajonc, 1960) or, as in the current study, differentiation of motives for exercise and reasons for quitting.
Related to differentiation is the idea of accessibility, i.e. the multiple elements that exist in the mind that comprise a particular cognitive domain must be accessed from the mind (Fazio, 1986). This process can be accomplished in two ways. In Linville’s (Linville, 1985) work, calculation of an index of self-complexity required subjects to select from a set of experimenter-provided traits (i.e. aided recall), while Zajonc (Zajonc, 1960) used participant-generated traits or attributes (i.e. unaided recall). Attitudes that are highly accessible from memory are proposed to be more predictive of subsequent behavior than are attitudes that are less or inaccessible (Fazio, 1986). Recent investigations in substance use have used a memory association approach to drug outcomes (Stacy et al., 1994, 1996). For example, listing greater numbers of positive expected outcomes from smoking has predicted current smoking in adolescents (Anderson et al., 2002). Drug-related memory associations have also predicted drug use prospectively (Stacy, 1997). No studies, however, on determinants of physical activity have been done using a cognitive structure/accessibility perspective.
This study evaluates depression as a factor in the relationship between cognitive differentiation of motives and reasons for quitting and exercise behavior. Depression, which affects twice as many women as men (Weissman et al., 1996), is a known correlate of physical inactivity (Farmer et al., 1988; Hassmen et al., 2000). It may be related to the degree of differentiation in the two exercise-determinant domains and/or act as a moderator to affect the relationship between differentiation of motives/reasons for quitting and exercise behavior. Depressed affect may facilitate retrieval from memory of more reasons for quitting (i.e. increase differentiation), in contrast to persons of normal mood (Bower, 1981; Woolfolk et al., 1999), and may decrease differentiation regarding motives for exercise (Gara et al., 1993). In addition, or alternatively, depression may moderate the relationship between differentiation or motives/reasons-to-quit complexity and exercise behavior, which may help explain lower physical activity levels among women with depressed mood. A better understanding of how depression is related to exercise behavior is important if interventions seek to ‘activate’ populations that likely include individuals with varying levels of depressed mood or use exercise as treatment for depression. Among clinically depressed populations, there is evidence that exercise is associated with alleviation of depressive symptoms (Craft and Landers, 1998) and that this effect may be a dose–response relationship (Dunn et al., 2001).
This study investigates a possible mechanism through which motives and reasons for quitting affect behavior, as well as conditions under which they might have detrimental or beneficial effects on behavior. The purpose of the present investigation was to evaluate: (1) the relationship between cognitive differentiation of motives and reasons for quitting and current exercise behavior, (2) the relation of depression to differentiation of motives and reasons for quitting, and (3) depression as a moderator of differentiation and exercise behavior. Cognitive differentiation was operationalized as the total number of motives and reasons for quitting accessed from memory using aided and unaided recall.1 This measure of differentiation combines the methodologies used by Linville (Linville, 1985) and Zajonc (Zajonc, 1960), using both experimenter- and participant-generated elements.
It was hypothesized that higher numbers of motives would be related to higher levels of current exercise and that higher numbers of reasons for quitting would be related to lower current exercise levels. Similar to what has been found in the research on smoking, it may be that highly differentiated and highly accessible cognitive domains for positive associations (i.e. a high number of motives for exercise) are more predictive of behavior than those for negative associations (i.e. reasons for quitting) (Stacy et al., 1996; Anderson et al., 2002). On the other hand, it may be that having several factors that have actually been instrumental in exercise attrition or relapse in the past will continue to adversely affect current exercise participation (i.e. the longer the ‘negative’ laundry list, the more at risk for inactivity). If so, these sum totals may serve as simple and valuable indices to help explain activity or inactivity. It was also hypothesized that higher levels of depression would be related to greater numbers of reasons to quit and fewer numbers of motives. Finally, it was hypothesized that the predictive relationship between total number of motives or reasons for quitting and exercise behavior would be different for women with higher levels of depression. If so, this identifies a personal factor that affects the role of cognitive differentiation in exercise behavior.
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Method |
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Participants
Participants were 397 undergraduate and graduate student women at the University of Houston, a large, ethnically diverse, urban university of largely commuter/community dwelling individuals. The age range was 17–54 years, with 40% of the sample over age 21 and 25% of the sample age 25 or older (M = 23.0 years, SD = 6.99). The ethnic distribution was 53.4% white, 19.3% Asian, 13.5% Hispanic, 9.7% African-American and 2.0% other.
Procedure
Female students from the Departments of Psychology and Business, as well as the School of Law, completed a health behavior questionnaire over a 3-week period. Consent forms and surveys were distributed to participants in classes following verbal recruitment or placed in student mailboxes with a recruitment memo attached. Participants were asked to read and sign the informed consent, fill out a survey, and return to a drop box, through the campus mail, or to their instructor. Approximately 500 questionnaires were distributed and 397 were returned for a response rate of 79.4%. Among those who completed questionnaires, 90.5% were undergraduates, 5.5% were graduate students and 4% did not give information regarding their class status. Most undergraduate participants received credit toward a research requirement for participating in this study.
Measures
Exercise behavior
The exercise behavior measure was intended to identify current exercise level. It asked specifically:
Have you been exercising regularly in the past year? We are defining exercise to be physical activity that is planned, structured and repetitive with the objective of improving or maintaining physical fitness (Caspersen et al., 1985). If so, what types/frequency/where? (For example, going to a 1-hour exercise class 3 times per week, or regularly taking a 30 min walk twice a week in your neighborhood.) If not, say ‘I have not exercised in _ months or years’.
The number of hours of exercise per week was obtained from this information, as well as the type of activity so that moderate–vigorous activities could be identified [i.e. 
3 METs (Pate et al., 1995; Ainsworth et al., 2000)].
Classification of physical activity level was made based on guidelines for physical activity established by the Centers for Disease Control and Prevention which recommend 30 min or more of at least moderate-intensity physical activity for 5 or more days per week (Pate et al., 1995; US Department of Health and Human Services, 1996). Participants were assigned to one of three levels of physical activity based on the MET intensity of their self-reported exercise activities (Ainsworth et al., 2000) and hours of participation per week: (1) no current, moderate–vigorous physical activity (37.9%), (2) some moderate–vigorous physical activity, but <2.5 h/week (17.6%) and (3) moderate–vigorous physical activity for 2.5 h/week, meeting the CDC guideline of at least 30 min/day over 5 days (44.5%). Exercise activities were generally very well described to allow the moderate–vigorous classification to be made. Two persons coded MET intensity, but reliability was not computed.
Motives for exercise and reasons for quitting
The motives and reasons for quitting measures each included a checklist component and a free-response component. The two checklists were comprised of variables that have been identified as motives for exercise and reasons given for drop-out from previous research (10 motive variables and 11 reasons for quitting) (Pollock, 1978; Snyder and Spreitzer, 1979; Dishman et al., 1980; Canada Fitness Survey, 1983; Godin et al., 1983; Sonstroem, 1984; Wankel, 1985; Tomporowski and Ellis, 1986; Franklin, 1988; Kendzierski, 1988). Each checklist was followed by a space for self-generated responses. Participants were asked to check as many motives for participation in current or past exercise that applied to them and to write in any additional motives that were not on the list. They were then asked to check all applicable reasons for ever quitting/not continuing a program of exercise in the past and write in any additional reasons for quitting.
Depressed mood
The Center for Epidemiologic Studies Depression (CES-D) Scale was used to measure risk for depressed mood. Leisure time physical activity has been found to be negatively associated with depression in examinations of national survey data [for a review, see (Dunn et al., 2001)]. The CES-D (Radloff, 1977), developed at the National Institute of Mental Health, consists of 20 items that were selected from other depression scales, including the Beck Depression Inventory [BDI (Beck et al., 1961)], the Zung depression scale (Zung, 1965) and the Minnesota Multiphasic Inventory (Dahlstrom and Welsh, 1960), and was designed to identify possible cases of depressive disorder in community samples. Scores range from 0 to 60, and scores of 16 or higher classify the respondent as possibly depressed and in need of further evaluation. The CES-D is correlated with other self- report depression scales (Radloff, 1977), and has been widely used and extensively validated (Comstock and Helsing, 1976; Radloff, 1977; Weissman et al., 1977; Roberts and Vernon, 1983; Radloff and Locke, 1986).
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Results |
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The five most frequent types of exercise performed by 80.5% of current exercisers were aerobics, walking, running, tennis/dance/calisthenics (tied for fourth) and exercise machines. Walking was classified as moderate activity since it was listed as being performed specifically for exercise [possible MET range for walking: 2.5–5.0 (Ainsworth et al., 1993
)]. Of the 397 participants, 391 (98.5%) gave the information required to determine their current physical activity level. Two individuals indicated they had never exercised and were dropped from subsequent analyses (n = 389), since they could have never discontinued exercise. Mean time since regular exercise for the non-exercising group was 17.5 months (SD = 21.3). Approximately 37% of the non-exercisers had not exercised in over 12 months and 16% had not exercised in over 2 years.
Current depression
The mean CES-D score for non-exercisers (0 h/week) was 16.1 (SD = 10.8), for ‘some’ exercisers (0 < h/week < 2.5) was 14.3 (SD = 9.1) and for ‘Guideline’ exercisers (2.5 h/week) was 13.8 (SD = 9.5). Higher depression scores were associated with less exercise (P = 0.06, controlled for age). Approximately 44% of the non-exercisers had scores at or above the standard cut-off score of 16, as opposed to 37% of the ‘some’ exercisers and 37% of the ‘Guideline’ exercisers. Using a cut-off score of 34, which has recently been suggested for college student populations (Santor et al., 1995), 13% of the non-exercisers, 7% of the ‘some’ and 6% of the ‘Guideline’ exercisers had scores suggestive of clinical depression. Depression group status, high (CES-D 34) versus low (CES-D < 20) predicted exercise group status, F(1, 304) = 5.25, P = 0.02. A CES-D < 20 has been shown to correspond to a BDI < 10 (Santor et al., 1995), which is the established non-depressed range for the BDI (Kendall et al., 1987).
Relation of number of motives/reasons for quitting to physical activity level
A total of 31 items reflecting motives and reasons for quitting were used in the analysis. The pool included the 10 items on the motives checklist and five self-generated motives, as well as the 11 items on the reasons for quitting checklist and five self-generated reasons for quitting. Sixty-six women (16.6%) utilized the self-generated response opportunity. Percents reflecting endorsement of specific motives and reasons to quit by exercise status and depression group are shown in Table I. Across all exercise and depression levels, improving physical appearance and controlling weight were the two most frequently cited motives for exercise, while lack of time/time conflict and loss of interest/motivation were the two most frequent reasons for quitting. Women with high depression scores (CES-D 34) were less likely to endorse cardiovascular fitness as a motive for exercise, more likely to express improving mood and time alone as motives, and more likely to express embarrassment, lack of progress and regimen/class difficulty as reasons for quitting, than were women with depression scores in the normal range (CES-D < 20).
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‘Yes’ responses were summed to create two continuous variables, number of motives and number of reasons for quitting. Means and standard deviations for the number of motives by exercise level were 2.96 (1.85) motives for no current moderate–vigorous exercise, 4.06 (1.79) for some moderate–vigorous (<2.5 h/week) and 4.59 (1.89) motives for women reporting
2.5 h of moderate–vigorous exercise per week. Mean numbers of reasons for quitting by exercise level were 1.76 (1.64), 1.80 (1.70) and 1.78 (1.62), respectively. A simultaneous multiple regression analysis using exercise level, as the dependent variable, and standardized number of motives and reasons for quitting, as independent variables, controlling for age and depressive symptoms, indicated that, as hypothesized, total number of motives for exercise was strongly related to exercise behavior (P < 0.0001), but that contrary to hypotheses, the number of reasons for quitting was not a significant predictor. Age was not related to exercise level, but depression was negatively related (P < 0.01). Age, CES-D depression score, total number of motives and total number of reasons for quitting explained 16.2% of the variability (R2adj = 0.153) in exercise level, F(4,379) = 18.33, P < 0.0001. Standardized parameter estimates and P values are shown in Table I.
Relation of depression to number of motives/reasons for quitting
As hypothesized, higher CES-D scores were associated with a greater number of reasons to quit (P = 0.0092, analysis controlled for age). However, contrary to hypotheses, higher CES-D scores were not associated with fewer motives for exercise.
Moderating role of depression
To further examine the relationship between motives for exercising, reasons for quitting and exercise level, depression was explored as a possible moderator (Baron and Kenny, 1986). Two simultaneous regression analyses were conducted, one for motives and one for reasons for quitting, adjusted for age, adding a motives x CES-D and quit x CES-D interaction term, respectively, to the previous main effects models. The depression x number of motives interaction was significant (P = 0.0494), indicating that the effect of number of motives on exercise behavior depended on the level of depressive symptoms, overall F(4,379) = 19.05, P < 0.0001, total R2 = 0.167. Plots of the motives x depression interaction (Figure 1) indicated that among women with high depression scores, more motives did not translate into more activity as it did among women with low depression scores. The depression x reasons to quit interaction was not significant (P = 0.6774).
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Total number versus individual motives/reasons for quitting as predictors
In order to compare the predictability of total number (i.e. quantity) to specific, individual motives for exercise and reasons for quitting, a simultaneous multiple regression analysis using exercise level as the dependent variable and the 31 items reflecting motives and reasons for quitting as dichotomous, independent variables, controlling for age and depressive symptoms, was performed. Results indicated that five motives were significantly related to exercise level: weight control, centering/time to be alone, reducing tension, cardiovascular/general fitness and fun/enjoyment, but that no specific reasons for quitting were significant predictors. Age, CES-D depression score, and the 15 motives and 16 reasons to quit variables explained 22.8% of the variability (R2adj = 0.155) in exercise level, F(33, 350) = 3.13, P < 0.0001. This analysis revealed that the amount of variance in exercise behavior, adjusted for degrees of freedom, explained by the specific-predictor model (0.155) was very close to that of the quantity model (0.153), supporting the use of the quantity model as an indicator of exercise behavior.
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Discussion |
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It has been suggested that the structural properties (Bieri, 1955
; Kelly, 1955) and the accessibility (Fazio, 1986) of an individual’s cognitions are critically important in understanding the process by which cognitions guide behavior. That is, if attitudes are to exert any influence on behavior, they must not only be accessed from memory, but the differentiation or cognitive complexity of the attitude domain itself will have behavioral implications. The current study provides important information on a previously unaddressed question: Is the relationship between exercise attitudes and exercise behavior a function of cognitive structure, specifically the cognitive complexity of those attitudes? This investigation on physical activity determinants provides evidence for an association between more elaborated or differentiated memory networks for motives (i.e. ‘positive’ associations or attitudes) and exercise behavior, but not for reasons to quit (i.e. ‘negative’ associations or attitudes), and yields suggestive evidence of a moderating effect of depression. For women of normal mood, regular exercise was highly related to the number of motives for exercise participation accessed from memory through aided and unaided recall, but this was not so among those experiencing significant depressive symptoms.
As an extension of the cognitive structure models of personality from the early 1950s and the more recent attitude accessibility studies, a growing body of research on motivation for substance use suggests that positive outcomes related to substance use, that are highly differentiated and accessible from memory, are associated with current and future drug use (Wetter et al., 1994; Benthin et al., 1995; McCusker et al., 1995; Stacy et al., 1996; Leung and McCusker, 1999; Anderson et al., 2002). The present results provide support for this basic assertion of the predictive superiority of positive over negative attitudes in another behavioral domain, that of exercise behavior. Highly differentiated, complex memory networks for motives were more strongly associated with exercise behavior than were those for previously experienced reasons for quitting. The inclusion of two established covariates of physical activity, age and depression, in the statistical models underscores the independent contribution of the number of motives for exercise to understanding exercise behavior.
The results of this research also support the usefulness of studying the relationship between cognitive structure and psychological factors, such as depression, in the realm of exercise behavior. The hypothesis that depressed affect is related to higher differentiation concerning reasons for quitting was supported. Congruent with Bower’s (Bower, 1981) associative network theory of mood and memory, the presence of negative mood appeared to activate significantly more thoughts of past failings in the form of reasons for quitting. On the other hand, depressive symptoms were not associated with less cognitive complexity for motives, as might be expected from previous work with depressives regarding differentiation related to positive aspects of the self and others (Gara et al., 1993).
Similar to findings in national surveys (Farmer et al., 1988; Hassmen et al., 2000), depressive symptoms were associated with a lack of physical exercise in this data. An unexpected finding concerned the moderating effect of depression on total motives, suggesting that perhaps not everyone is equally able to translate motives for exercise into action. The relationship between number of motives and exercise level was fairly linear for women of normal mood, but this was not so for women with high depression scores. A clear pattern emerged in which women who had high levels of depressive symptoms, although indicating a greater number of motives for exercise than women of normal mood, were less active. This could be related to self-efficacy, which was not measured in this study. As shown by Bandura and Abrams (Bandura and Abrams, 1986), depression is associated with perceived lack of efficacy when people continue to strive for difficult goals. It may be that those women with depressive symptoms lacked the perceived efficacy to attain regular exercise, but continued to demand this difficult goal of themselves, as the listing of a number of motives would imply. Interestingly, in spite of the activity handicap conveyed by depressed mood, there were a few women in the high depression group who did manage to exercise 2.5 h/week. Although these data cannot reveal why this was so, it may be that these physically active, depressive women experienced more facilitating factors, such as more social support. The enabling function of social support amplifies perceived coping efficacy (Major et al., 2001). Thus, social support could have affected exercise participation by increasing self-efficacy, as well as by direct influence (e.g. friend shows up at the front door every Monday, Wednesday and Friday after dinner for neighborhood walk).
An innovation of the present study was the inclusion of experienced-based barriers to exercise that had been reasons for quitting, as well as indicators of exercise-related memory associations that reflect cognitive differentiation. The results of this investigation may have important clinical implications. The findings suggest that the number of motives one has for exercise may serve as a simple and valuable index, providing professionals with a brief and practical method for understanding and addressing inactivity. In the absence of depression, the longer a person’s list of motives, the more likely is exercise behavior (in the current study, having four or more motives was associated with exercise). People who are inactive may need help in identifying and focusing more on the multiple positive benefits of exercise than on reasons for past failures in exercising regularly. It may be that efforts to prevent relapse and/or maintain exercise may do little good unless participants have an array of motives for participation in the first place. This, however, does not negate focusing on relapse prevention and other strategies to maintain exercise, such as skill training in coping with exercise barriers that are reasons for quitting (e.g. lack of time/time conflicts). In this study, lack of time/time conflict and loss of interest or motivation were explanations of attrition regardless of current exercise level or depression level. The results of this study reinforce the emphasis placed in many intervention programs on identifying and overcoming barriers to exercise, and enhancing social support for behavior change (Marcus and Stanton, 1993; Heaney and Israel, 1997).
This study is limited in several respects. The limitations regarding generalizability due to the use of a university sample, the reliance on self-report measures, the lack of a validated measure of physical activity and a specific question on exercise intensity, and the dichotomous measurement of motives and reasons to quit, which precluded the degree to which specific determinant attitudes and perceptions were held by participants, may have affected the results. These results are in contrast to other studies where perceived barriers have been significantly negatively associated with physical activity (Mitchell and Olds, 1999; Sallis et al., 1999; King et al., 2000). The discrepant findings between this study and the larger literature could be related the current study’s focus on reasons for quitting as opposed to the more traditional construct of perceived barriers. Future research should continue to explore the construct of reasons for quitting and its relationship to exercise behavior, as well as the predictability of cognitive complexity as indexed by the number of motives accessed from memory. For example, although we have some indication from the work of Kendzierski and Johnson (Kendzierski and Johnson, 1993) that women may have more thoughts of reasons or excuses for not exercising than men, we know little about gender differences in the predictability of cognitive complexity in exercise-related cognitive domains, such as motives and reasons for quitting. There may also be different results if motives and reasons for quitting are completely self-generated by subjects, as opposed to the aided and unaided recall methodology used in the current study, and if accessibility itself is addressed by measuring latency. These remain interesting ideas to explore in future studies.
In conclusion, the present study has provided new and useful information on the relation and process of influence of motives, causes of exercise attrition, and depression to exercise behavior, including contrasts and replications to existing data in an ethnically diverse sample of women. A greater understanding of what accounts for women’s inability to exercise consistently will contribute to the development of strategies to improve adherence to long-term regular exercise.
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Acknowledgements |
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The data from this study was part of a Master’s Thesis by C. B. A., under the supervision of Richard Rozelle, Department of Psychology, University of Houston, Texas. A version of this paper was presented at the 47th Annual Meeting of the American College of Sports Medicine, 31 May–3 June 2000, Indianapolis, IN. The preparation of this article was funded in part by postdoctoral training grants from the National Cancer Institute at the University of Texas MD Anderson Cancer Center and School of Public Health (grants R25-CA57730 and R25-CA57712), as well as grants from the Cancer Research Foundation of America, American Cancer Society (IRG-9303406), Curtis Hankamer Basic Research Fund at Baylor College of Medicine and the National Cancer Institute (R03-CA90185) awarded to C. B. A.
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FOOTNOTES |
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1. Accessibility per se was not measured in this study. Attitude accessibility has been measured via the latency of response to an attitudinal question. Latency of response has served as an index of the strength of the object–evaluation association.
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Received on April 10, 2002; accepted on July 26, 2002
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