Health Education Research, Vol. 14, No. 3, 305-313,
June 1999
© 1999 Oxford University Press
Psychological and perceived situational predictors of physical activity: a cross-sectional analysis
School of Exercise, Leisure and Sport, and
1 Department of Health Education, Kent State University, Kent, OH 44242, USA
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Abstract |
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The purpose of this study was to identify psychological and self-reported situational factors that are associated with degree of involvement in moderate-intensity physical activity at various stages of adult life. The study is grounded in Personal Investment Theory which proposes that personal incentives, sense of self and perceived options determine behavior. Participants aged 18 and above, selected by random-digit dialling, were invited to participate in a study on physical activity habits. Of 251 who agreed to participate, 41.4% were male (N = 104) and 58.6% were female (N = 147). These participants were asked the number of days per week that they engaged in physical activity which accumulated a total of 30 min or more. The 140 participants who indicated one or more days of activity answered questions concerning personal incentives for physical activity, sense of self and perceived barriers. Stepwise multiple regression analyses and discriminant function analysis indicated that Personal Investment Theory is able to predict up to 29% of the variance associated with voluntary participation in moderate-intensity physical activity. Discussion focuses on implications for physical activity programs for citizens at different stages of their adult life.
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Introduction |
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The contribution of regular moderate physical activity to health maintenance, disease prevention and enhanced quality of life is well documented (Ostrow, 1984
; Shephard, 1995; Blair and Connelly, 1996). Physical activity reduces the risk of premature mortality in general, and of coronary heart disease, hypertension, colon cancer and diabetes mellitus in particular. Physical activity also improves mental health, and is important for the health of muscles, bones and joints (USDHHS, 1996a). Despite increasing literature recognizing the value of physical activity, only 22% of American adults engage in physical activity at the level recommended in Healthy People 2000 (USDHHS, 1990). More than 60% are not regularly physically active, while 25% of all adults are sedentary (ACSM/USCDCP, 1993; USDHHS, 1996). These low participation rates give cause for alarm to the extent that the American College of Sports Medicine and the US Centers for Disease Control and Prevention recently issued a joint statement recommending that: `Every American adult should accumulate 30 min or more of moderate-intensity physical activity over the course of most days of the week' [(ACSM/USCDCP, 1993), p. 7]. This statement is further highlighted in the recently released Surgeon General's Report (SGR) on Physical Activity and Health (1996) which stresses the value of regular moderate-intensity physical activity in terms of its contribution to the health of the nation (USDHHS, 1996b). This report should be translated into public health policies and programs at the national, state and local levels. Increasing physical activity is an important public health challenge (USDHHS, 1996b), driven by the need to understand how to promote more active lifestyles (USDHHS, 1996).
Given the recognized public health value of physical activity, it is important to identify factors that predict regular activity. The National Center for Health Promotion and Disease Prevention at the Centers for Disease Control and Prevention has taken the lead in advancing a research agenda and program development that will help Americans increase their physical activity levels in order to improve public health. However, much of the associated research has focused more on predicting factors associated with inactivity than those associated with participation (Dishman and Sallis, 1994). This study seeks to identify factors associated with participation in an attempt to fill this gap in the literature.
A variety of theoretical models have been proposed to explain and predict physical activity involvement (Dishman, 1988). One strand of recent research has focused primarily on psychological variables as predictors of physical activity participation. Findings have been equivocal, possibly because studies have lacked an adequate theoretical base and because it seems apparent that psychological models alone cannot adequately predict participation in physical activity (Sonstroem, 1988; Dishman and Sallis, 1994). The present study is grounded in Personal Investment Theory which, though primarily a psychological model, also takes account of perceived situational predictors of physical activity.
Personal Investment Theory proposes that personal incentives, sense of self and perceived options are critical determinants of behavior (Maehr and Braskamp, 1986). Personal incentives refer to the reasons identified for involvement in an activity, and include such incentives as recognition, mastery, competition and affiliation. Sense of self is comprised of one's own perceived competence to engage in an activity, self-reliance, goal directedness and social identity. Perceived options might refer to possible alternatives that are available (e.g. television) and/or situational factors perceived as barriers to engagement in an activity. Several barriers have been identified as viable predictors of adherence to physical activity. These barriers include time, cost, lack of accessibility and lack of social support (Dishman, 1984). Hence, the scope of Personal Investment Theory encompasses both psychological and perceived situational factors as predictors of behavior, making it a more comprehensive framework than other conceptual models that focus more specifically on either psychological or situational predictors.
Previous studies investigating the ability of Personal Investment Theory to predict physical activity involvement have been limited in their findings. Duda and Tappe (Duda and Tappe, 1988), with a sample of 47 middle-aged and older adults, found that personal incentives predicted 30% of the variance in frequency, intensity and duration of physical activity, though only a single incentive, recognition, was found to be a statistically significant predictor. Neither sense of self nor perceived options were significant predictors of current physical activity behavior in this study. Again using participants enrolled in a structured exercise program, Duda and Tappe (Duda and Tappe, 1989) investigated age and gender-related differences in personal investment. Results indicated age group and gender differences in some incentives, notably recognition, competition, health benefits, affiliation and coping with stress. Gender, but not age, differences were also apparent for sense of self measures. In a study of adolescent motivation toward physical activity, Tappe et al. (Tappe et al., 1990) determined that factors such as perceived physical competence, perceived barriers, the incentive of strength, other's fitness and perceived control were significant predictors of frequency, intensity and duration of physical activity.
As with research grounded in alternative theoretical frameworks, the aforementioned studies utilizing Personal Investment Theory focused on participants currently involved in organized exercise programs. The present study differs in that participants were adults of all ages, ranging from 18 to 84, who engage in what Dishman (Dishman, 1988) refers to as `free-living physical activity' where participation is independent of any structured or organized program. The present study also differs from previous research in its use of the most recent guidelines for what constitutes an appropriate minimum level of physical activity for health promotion, i.e. accumulate 30 min or more of moderate-intensity physical activity over the course of most days of the week (ACSM/USCDCP, 1993; SGR, 1996).
Thus, the purpose of this study was to identify psychological and perceived situational factors that predict degree of involvement in health promoting physical activity across the adult lifespan. Since it is of value to identify reasons to be involved in physical activity, the population of interest in the study was that indicating at least 1 day per week of moderate-intensity physical activity. Learning more about why individuals engage in physical activity can have powerful implications for public health policy. Specifically, the study addressed two questions:
- What factors predict the activity habits of different age groups in the adult population?
- What factors explain different levels of involvement in voluntary, health promoting physical activity?
Level of involvement in appropriate physical activity was reflected in the number of days (during the course of a week) participants reported engaging in 30 min or more of moderate-intensity physical activity, with a minimum of 1 day necessary for inclusion in the study. Identification of potential predictors will support the development of population-based public health programs to promote physical activity for all ages and increase the likelihood of achieving the Healthy People 2000 objectives and those identified in the SGR (USDHHS, 1996a).
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Method |
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Participants and procedures
In a cross-sectional design, self-report data were collected from telephone interviews conducted by interviewers who were familiar with the instrumentation and trained in using telephone interviews for data collection. Training sessions were held until all interviewers were comfortable with the questions and with data collection procedures. Participants aged 18 and above, selected by random-digit dialing within a primarily suburban and rural Midwest county, were invited by the interviewer to participate in a study on physical activity habits. Of the 251 individuals who agreed to participate in the study, 41.4% were male (N = 104) and 58.6% were female (N = 147). These participants were asked to indicate the number of days per week that they engaged in intentional moderate-intensity physical activity which accumulated a total of 30 min or more. To clarify `moderate intensity', interviewers used examples such as cycling, swimming and brisk walking at 3–4 miles per hour (Pate et al., 1995
). The 140 participants who indicated a minimum of 1 day of physical activity received questions concerning personal incentives for physical activity participation and sense of self, followed by items reflecting perceived barriers. Interviewers completed data collection by directly entering responses into a computer program for analysis.
Instruments
Since the focus of the study was on psychological and perceived situational predictors of physical activity participation, existing instruments were refined and new items developed to reflect these factors within the framework of Personal Investment Theory. It was also desirable to keep the instrument brief in order to maintain a 5–7 min interview time frame.
Personal incentives
Items measuring personal incentives for involvement in physical activity were selected from the Personal Incentives for Exercise Questionnaire (PIEQ) (Duda and Tappe, 1988). Though the PIEQ includes subscales that measure a variety of possible incentives, both psychological and physical, items for this study were selected to reflect only psychological factors. Hence this modified version of the PIEQ contained 20 items measuring the five psychological incentives of competition, mastery, affiliation, social recognition and mental benefits (coping with stress). These items were presented on a five-point Likert scale (1 = strongly disagree, 5 = strongly agree). Cronbach 
reliability coefficients for these subscales ranged from 0.69 to 0.90 in the present study.
Sense of self
Seven sense of self items were developed to reflect self-confidence in factors critical to successful participation in physical activity, as identified by a panel of three experts in the area of exercise and fitness. Specifically, participants were asked to rate their confidence, on a five-point scale, in their own strength, flexibility, aerobic endurance, skill, and ability to perform in front of others, alone and with partners. These seven items were summed to yield a measure of self-confidence in ability to participate in physical activity. Cronbach reliability for these items was 0.78 in this study.
Perceived options
In this study perceived options were operationalized by the identification of six perceived barriers to physical activity participation. These barriers were lack of time, lack of an exercise partner, lack of ability in the chosen activity, prohibitive financial cost, proximity of facilities and lack of family support. Perception of the barriers was measured on a five-point Likert scale (1 = strongly disagree, 5 = strongly agree). The six items were summed to yield a composite score for perceived barriers. Cronbach reliability for these items was 0.68 in this study.
Hence a total of 33 items measured personal incentives, sense of self and perceived barriers. This was adequate for the measurement of the psychological and perceived situational factors under investigation, yet sufficiently concise to keep telephone interviews to a maximum of 6 min in order to maintain cooperation of participants throughout the duration of each interview.
Data analysis
To provide a cross-sectional analysis of factors predicting involvement in voluntary physical activity, the participants who indicated at least 1 day per of moderate-intensity physical activity were placed into three age groups for data analysis. These groups contained participants age 18–29 (N = 45), 30–44 (N = 51) and 45+ (N = 44). Data analysis consisted of three parts. First, separate stepwise multiple regression analyses were conducted for each group to determine personal investment variables that predict the number of days in which participants accumulated 30 min or more of moderate-intensity physical activity. Second, a stepwise (Wilks' method) discriminant analysis was conducted to determine which personal investment variables would discriminate among groups defined by age. Third, another stepwise (Wilks' method) discriminant analysis was conducted to determined whether personal investment variables discriminated among groups defined by amount of activity.
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Results |
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Descriptive statistics for all personal investment variables are presented in Table I
. ANOVA results indicated only one significant age group difference among the variables, this on the competitiveness incentive. A Tukey (h.s.d.) post hoc analysis revealed that the 18–29 age group scored significantly higher than the 45+ age group. There was no significant difference between the 18–29 group and the 30–44 group nor between the two older groups.
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A comparison of personal incentives reveals a particularly high overall mean score for the mastery incentive, with lower mean scores for competitiveness and mental benefits, and particularly the recognition and affiliation incentives.
Predictors of physical activity by age group
Results of the stepwise multiple regression analyses, shown in Table II, indicate striking similarities between predictors of physical activity level across age groups. Personal investment variables that entered the equation at the 0.05 level accounted for a total of 27, 29 and 23% of the variance in activity level for the 18–29, 30–44 and 45+ age groups, respectively. As shown in Table II, perceived barriers was a statistically significant negative predictor of activity level (number of days per week of 30 min accumulated moderate-intensity physical activity) for all three age groups. The recognition incentive was an important positive predictor for all three age groups, while self-confidence was also a predictor for the youngest group.
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Factors discriminating between age groups
A stepwise (Wilks' method) discriminant analysis was conducted to determine which predictor variables would discriminate between groups defined by age. One significant function emerged containing four variables,
2(8) = 15.74, P < 0.05 (canonical correlation = 0.25). This function correctly classified only 48.5% of all cases, 51.2% of 18–29 year olds, 43.1% of 30–44 year olds and 52.3% of participants age 45+. Table III presents results for the variables entered in order up to step 4. Data include classification function coefficients (Fisher's linear discriminant functions), Wilks' 
and significance levels for each variable.
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Table III
suggests that age groups were significantly discriminated by the personal incentives of competitiveness, mastery, mental benefits and recognition. An examination of the classification function coefficients indicates that competitiveness is a more salient incentive to engage in physical activity for the 18–29 age group than for the other two groups. In addition, members of the 30–44 age group engage in activity more for reasons of mastery and mental benefits, and less for reasons of recognition, than participants in the other two groups. The three remaining variables, sense of self, perceived barriers and the affiliation incentive, did not discriminate significantly between age groups.
Factors discriminating between activity level
Recent guidelines suggest that adults should accumulate 30 min or more of moderate-intensity physical activity over the course of most days of the week (ACSM/USCDCP, 1993). To determine which personal investment variables discriminated between high and low exercisers, those participants indicating some degree of involvement in physical activity (N = 140) were grouped according to the number of days on which they fulfilled the criteria of an accumulated 30 min. Participants indicating adequate activity for four or more days were classified as high in activity (N = 57), while those indicating adequate activity for less than 4 days were classified as low in activity (N = 83). Discriminant analysis results are presented in Table IV.
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One discriminant function emerged from the analysis with all variables entered,
2(7) = 25.14, P < 0.001 (canonical correlation = 0.41). This function correctly classified 75.71% of all participants, 75.9% of low-activity group members and 75.4% of high-activity group members. The classification function coefficients indicate that high-activity group members have higher self-confidence, are active more for reasons of competitiveness and affiliation, and perceive fewer barriers than low-activity group participants. Conversely, low-activity members appear to be active more for reasons associated with recognition, mental benefits and mastery than high-activity members. |
Discussion |
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Since the majority of research on physical activity has focused on those not active, our preliminary work on those who are physically active provides some insight about public health strategies that could be tailored to appropriate segments of the population. It should be noted that the findings of this study are reported and discussed without reference to possible gender differences, providing a broad perspective on factors associated with participation in moderate-intensity physical activity.
This study used Personal Investment Theory to identify variables that predict involvement in health promoting physical activity across the adult lifespan (research question 1). The finding that the recognition incentive and perceived barriers were significant predictors of physical activity is consistent with previous research (Dishman, 1984; Duda and Tappe, 1988), suggesting implications for the development of public health programs aimed at increasing the proportion of adults who are physically active on a regular basis. Programs that provide easy and flexible access, encourage goal-setting practices, and that ensure one-to-one encouragement and reinforcement might be particularly successful. That the competitiveness incentive was higher for younger adults is interesting, perhaps reflecting the norm among young adults. Nonetheless, the Surgeon General's Report encourages physical activity to promote public health (health fitness), not to address competitive fitness outcomes so often perceived as the norm by the public. Media campaigns by large athletic shoe companies reinforce this competitive fitness concept, and are likely to exacerbate the belief that exercise regimens are both too difficult and inconvenient to be embraced by the general public. Therefore, public health media campaigns need to communicate the message to society that being physically active is social, attainable and will yield positive outcomes. Public health policies need to be established that will provide opportunity and reduce the barriers that likely impede physical activity.
Recognition for participation in regular physical activity might take several forms, from verbal feedback to family support to extrinsic reward. However, program developers and participants should be cognizant of possible detrimental effects of extrinsic reward on intrinsic motivation under circumstances where reward is seen as controlling behavior (Deci, 1971; Frederick and Ryan, 1995).
That self-confidence was only a predictor for the youngest age group (18–29) is perhaps not surprising in light of past research suggesting this construct is a predictor of behavior in younger populations (Roberts et al., 1981; Tappe et al., 1990). It seems possible that middle-aged and older adults perceive less threat to sense of self from physical activities in which they do not perceive their ability to be particularly high.
Discriminant analysis correctly classified only about half of all participants into the appropriate age groups. This makes sense in light of the lack of apparent age group differences reported in Table I. Simply, age was not a particularly discriminating variable in this study. Nonetheless, competitiveness was a more salient incentive for physical activity participation in the 18–29 age group, while the mastery and mental benefits incentives were stronger for the 30–44 age group. The salience of the competitiveness and mastery incentives as discriminating variables might have implications for the development of physical activity programs for young and middle-aged adults. Participants in the older age group might respond in particular to activities and challenges in which progress is self-referenced (i.e. compared to personal progress rather than to the progress of others) and which provide an outlet for coping with stress. Should these age group differences be replicated in further research, it suggests the need to develop public health programs in community recreation centers, work sites and churches along with media campaigns that acknowledge these factors.
The study also sought to determine which personal investment variables discriminated between those who are frequently active and those who are less frequently active (research question 2). Discriminant analysis correctly classified a large percentage of participants into high- and low-activity groups, suggesting that Personal Investment Theory can provide a mechanism for distinguishing between those individuals who are most likely to be frequent and infrequent participants in health-related physical activity. Clearly self-confidence is associated with higher participation levels, suggesting that early physical activity experiences should be programmed for success in order to maximize the likelihood of adherence. This strategy is consistent with recent CDC/ACSM guidelines encouraging people to be physically active for health rather than competitive reasons (ACSM/USCDCP, 1993). The salience of the affiliation incentive as a discriminating variable also lends support to established guidelines that suggest physical activity is best carried out in pairs or small groups to provide social support (Dishman, 1984; Dishman and Sallis, 1994; USDHHS, 1996a). Because low-activity participants are active for recognition, mental benefits and mastery reasons, public health programs should consider embracing these concepts for such targeted individuals.
Learning more about why adults choose to be involved in moderate-intensity physical activity can be translated into public health programs to encourage others less active or sedentary to increase activity levels. Although the data in this study apply to those already active, public health policies that provide appropriate incentives and reduce barriers to physical activity must be established if the 60% of American adults who are inadequately active and 25% who are sedentary are to become healthier through physical activity.
Physical activity that supports health fitness can develop and maintain a high quality of life. Public health programming that intentionally embraces research findings that identify psychological and perceived situational factors which predict this type of health fitness are necessary for promoting public health. The present study has looked only at participants drawn from a suburban and rural Midwest county. The need to study similar factors in broader populations becomes apparent. Future samples must be larger, more geographically variant, and from more diverse ethnic and socio-economic backgrounds. Additional research about variables that influence and support active lifestyles is a necessary and important public health agenda.
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Acknowledgments |
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This study was sponsored by a grant from the Division of Research and Graduate Studies at Kent State University.
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Received on September 16, 1997; accepted on May 27, 1998
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