Psychosocial Mediators of Physical Activity Behavior Among Adults and Children

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1 Psychosocial Mediators of Physical Activity Behavior Among Adults and Children Beth A. Lewis, PhD, Bess H. Marcus, PhD, Russell R. Pate, PhD, Andrea L. Dunn, PhD Background: Methods: Results: Conclusions: Researchers examining theory-based, physical activity (PA) interventions postulate that interventions are effective by changing theoretical constructs hypothesized to mediate the relationship between the intervention and PA behavior. Research indicates that PA interventions are effective for increasing PA behavior. However, whether effective interventions are due to predicted changes in theoretical constructs remains poorly understood. Studies that examined theoretical constructs (i.e., mediators) in PA interventions of adults or children, which used experimental designs and met other criteria for evaluating mediation, were collected via literature searches, personal searches of files, and personal communications. Only studies examining the direct effect of the intervention on the hypothesized mediator were considered relevant for this study. Based on our criteria, the adult literature search yielded ten studies and the child literature search yielded two studies. The most common mediators examined included behavioral processes of change, cognitive processes of change, self-efficacy, decisional balance, social support, and enjoyment. Research indicates that behavioral processes are likely mediators. There was some support for the importance of self-efficacy as a mediator. Few studies have used statistically recommended methods to examine mediators in PA intervention studies. Therefore, definitive conclusions about the importance of the mediators reviewed are not possible at this time. Additional PA mediator intervention studies using recommended statistical methods are necessary to truly test if theory-based PA interventions are effective due to predicted changes in theoretical constructs. Medical Subject Headings (MeSH): adult, child, exercise, health behavior, intervention studies, physical fitness, psychological theory (Am J Prev Med 2002;23(2S):26 35) 2002 American Journal of Preventive Medicine Introduction Research indicates that theory-based, physical activity interventions successfully influence physical activity behavior. 1 4 However, why these interventions are effective in promoting physical activity behavior remains poorly understood. Researchers who conduct physical activity interventions based on theoretical frameworks such as social cognitive theory (SCT) 5 and the transtheoretical model (TTM) 6 postulate that interventions influence physical activity behavior by changing theoretical constructs that are primarily psychosocial in nature and that are believed to be important for behavior change, such as behavioral From the Centers for Behavioral and Preventive Medicine, Brown Medical School (Lewis, Marcus) and The Miriam Hospital (Lewis, Marcus), Providence, Rhode Island; Department of Exercise Science, University of South Carolina (Pate), Columbia, South Carolina; and The Cooper Institute (Dunn), Dallas, Texas Address correspondence and reprint requests to: Beth A. Lewis, PhD, Centers for Behavioral and Preventive Medicine, Brown Medical School and The Miriam Hospital, 1 Hoppin Street, Coro Building, Suite 500, Providence, RI blewis@lifespan.org. processes, cognitive processes, self-efficacy, and social support (e.g., Dunn et al. 2 and Pinto et al. 7 ). Even though the focus on theoretical constructs mediating physical activity behavior change has increased in recent years, only a few studies have examined whether interventions change postulated mediators and whether mediators influence physical activity behavior (e.g., Pinto et al. 7 and Sallis et al. 8 ). Mediators can be defined as intervening causal variables that are necessary to complete a cause effect pathway between an intervention and physical activity. 9 Baranowski et al. 10 recommended that researchers examine the role of mediators in successful interventions by specifying which mediators are targeted in an intervention, determining if the intervention successfully changed the targeted mediators, and evaluating if changes in mediators predict change in physical activity behavior. Because researchers hypothesize that theorybased interventions are effective due to changes in particular mediators (e.g., self-efficacy), it is important to measure both whether the intervention influences changes in the mediators and whether the mediators 26 Am J Prev Med 2002;23(2S) /02/$ see front matter 2002 American Journal of Preventive Medicine Published by Elsevier Science Inc. PII S (02)

2 Figure 1. Overview of mediation analysis examining self-efficacy influence physical activity behavior change. By examining several potential mediators, researchers may learn which mediators are most effective for increasing physical activity behavior, which in turn may lead to more effective interventions. As an example, a physical activity intervention may be hypothesized to increase selfefficacy and social support; however, if the intervention effectively increases physical activity by increasing selfefficacy but not social support, we learn that selfefficacy is the important component in this intervention. Baranowski et al. 10 recommended that mediator analyses be conducted using the framework suggested by Baron and Kenny. 11 According to Baron and Kenny, 11 a variable mediates the relationship between an intervention and an outcome if a positive relationship between the intervention and an outcome variable is attenuated after statistically controlling for the mediator. Physical activity intervention studies have examined the effect of the intervention on mediators 2,7,8,12 22 and the effect of mediators on outcome. 2,7,8,12 16,18,19,21,22 However, we found only two studies 7,22 that specifically tested mediators as suggested by Baron and Kenny 11 and more recently, Kramer et al. 23,24 As an example, self-efficacy is one mediator that has been examined in physical activity interventions (e.g., Calfas et al. 12 and McAuley et al. 13 ). Self-efficacy can be considered a mediator if it meets the following criteria 11 : 1. The intervention causes an increase in self-efficacy. 2. Self-efficacy is associated with increases in physical activity behavior. 3. The relationship between the intervention and physical activity behavior is attenuated when controlling for changes in self-efficacy (see Figure 1). Perfect mediation occurs when the intervention has no effect on physical activity behavior when controlling for changes in self-efficacy (i.e., the mediator). Although theoretically possible, it would be unusual for perfect mediation to occur in clinical trials examining mediators. Therefore, self-efficacy would be conceptualized as a mediator if the relationship between the intervention and physical activity behavior is attenuated when controlling for self-efficacy (in addition to meeting the criteria described above). The higher the attenuation of the effect, the greater the potency of the mediator. The purpose of this article is to discuss findings and future directions regarding the physical activity intervention literature that examines mediators among adults and children. Method Adult Studies Studies for the present paper were collected via a literature search (e.g., PsycINFO, Medline), personal searches of files, and personal communications. The literature search yielded 3378 articles, using a combination of keywords, such as mediator, theory, behavior change, physical activity, sport, exercise, intervention, program, treatment, and several words associated with SCT, the TTM, health belief model, protection motivation theory, theory of planned behavior, and self-determination theory. Several studies identified in the literature examined the relationship between potential mediators and physical activity behavior without examining the effect of an intervention on the mediator. These can be considered studies of correlates of physical activity behavior; they are beyond the scope of this article and are discussed elsewhere. 25 Other exclusionary criteria for the adult search included studies not written in English, studies using nonexperimental designs, nontheoretical interventions, and intervention studies targeting multiple risk factors. Studies examining the effect of the intervention on the mediator but not the effect of the mediator on outcome were included. Ten overall studies described in 14 articles constitute the focus of the article for adults. Child Studies A similar process was used to search the literature for relevant studies with participants who were children or youth (age range, 0 to 18 years). The keyswords were similar to those used in the adult literature search described above. The search yielded 209 articles, but most were excluded from this review using similar criteria as were applied for studies of adults. However, unlike the adult literature search, multiple risk factor studies were included because there were very few studies in children. Two studies described in four publications constitute the focus of this article for children. Am J Prev Med 2002;23(2S) 27

3 Table 1. PA intervention studies examining mediators of PA behavior change Study Sample Design Intervention Theory Mediators Assessment time point Miller et al., Marcus, ; Marcus et al., Mothers Exp (grp/print/control) Group vs print target mothers 150 Adults Exp (Tx vs AHA) Tailored print Pinto et al., Elderly Exp, physician office (Tx vs control) Nichols et al., Adults at a work site Calfas et al., ; Sallis et al., University students Castro et al., 128 Ethnic minority women Hallam and Petosa, Adult employees Exp (grp vs control) Exp (Tx vs control) Exp (Tx vs AHA) Quasi-exp work site (tx vs control) Dunn et al., 235 Adults Exp (life style vs ,28 structured) Calfas et al., 1997 and , Adults Exp, physician office (tx vs control) McAuley et al., 114 Middle Exp (Tx vs control) aged adults Edmundson et al., 5106 Exp (Tx vs control ; Luepker Children schools) et al., ; in 96 Nader et al., schools Parcel et al., Children per school (4) Quasi-exp (Tx vs control schools) SCT TTM, SCT, DM intervention Physician counseling Course PA trainer 16-week PA course Phone/mail target walking Four face-toface sessions Lifestyle or structured PA Physician counseling Targeted PA selfefficacy School, CVD risk factors School-based PA and diet SE, partner support Baseline, 8-week post-test, 5-month follow-up B, C, SE, DB Baseline, 1 month, 3 months, 6-month post-test TTM, SCT B, C, SE, DB Baseline, 6 week follow-up, 8-month follow-up SCT, TTM TTM, SCT SCT SCT TTM, SCT, DM B, C, SE, barriers, benefits, support, enjoyment B, C, SE, support, benefit/barrier, enjoyment SE, support, barriers, enjoyment SE, selfregulation, outcome expectations Baseline, 3-month post-test, 9-month follow-up Baseline, 16-week post-test Baseline, 8-week post-test, 5-month follow-up Baseline, 4-week post-test B, C, SE, DB Baseline, 6-month post-test TTM, SCT B, C, SE, support Baseline, 4 to 6 week follow-up SCT SE Baseline, 1 month, 2 months, and 4 months SCT SE, social support Baseline, 1-year, 2- year, and 3-year follow-ups SCT SE, knowledge, skills Baseline, follow-up AHA, American Heart Association materials; B, behavioral; C, cognitive; CVD, cardiovascular disease; DB, decisional balance; DM, decision making; exp, experimental; grp, experimental intervention group; PA, physical activity; SCT, social cognitive theory; SE, self-efficacy; TTM, transtheoretical model; Tx, treatment. Results Overview of Mediator Studies Theory-based interventions examining potential mediators in physical activity intervention studies are highlighted in Table 1. The sample, design, setting, intervention, theory, potential mediators, and assessment time points for each study are presented. Studies were conducted in several settings (e.g., community, primary care, home, or university) and delivered by various channels (e.g., face-to-face, telephone, or tailored print materials). The most common theoretical frameworks used in these studies included SCT and the TTM. 7,8 SCT postulates that there are multiple multidirectional influences on behavior, including both cognitive and social factors. 5 For example, one aspect of SCT relevant to physical activity is self-efficacy, which refers to one s confidence (i.e., cognitive component) to engage in physical activity despite encountering social (e.g., family obligations) and environmental barriers (e.g., bad weather). TTM hypothesizes that individuals adopt physical activity by moving through the following stages: precontemplation (not intending to become physi- 28 American Journal of Preventive Medicine, Volume 23, Number 2S

4 Table 2. Effect of intervention on behavioral processes and effects on outcome Study Effect of intervention on behavioral processes Effect of behavioral processes on outcome Marcus, ; Increased in both groups from base to post Marcus et al., (tailored and AHA) Pinto et al., Intervention increased more than control at 6 weeks but not 8 months Calfas et al., ; Intervention increased more than controls Sallis et al., (maintained at 1 and 2 years for women) Nichols et al., Intervention increased more than control for behavioral and cognitive processes (combined) Dunn et al., ,28 No differences across groups (lifestyle vs structured) Increases associated with three of three outcome variables for both groups Mediator at 6 weeks but not 8 months Related to none of the outcome variables Not assessed Increases from 0 to 24 months predicted meeting CDC/ACSM recommendations 3.5 years later Calfas et al., ; Intervention increased more than controls Increases predicted two of four outcomes Note: The behavioral process subscales of the Processes of Change Questionnaire consist of the following: counterconditioning (substituting alternative, helping relationships (enlisting social support), reinforcement management (rewarding yourself), self-liberation (committing yourself), and stimulus control (reminding yourself) (Marcus et al. 30 ). ACSM, American College of Sports Medicine; AHA, American Heart Association materials; CDC, Centers for Disease Control and Prevention. cally active); contemplation (intend to become physically active in the next 6 months); preparation (intend to become more physically active and physically active some but not regularly); action (regularly physically active but for 6 months); and maintenance (regularly physically active for 6 months). 30 Related to these theories, the most common theoretical constructs examined as mediators in the literature included behavioral processes of change (e.g., rewarding yourself); cognitive processes of change (e.g., increasing knowledge); self-efficacy (i.e., confidence in becoming physically active); decisional balance (i.e., weighing the pros and cons related to physical activity); social support; and enjoyment of physical activity. 2,7,8,12 22 A summary of the findings for each of these six theoretical constructs follows. Summary of Mediator Studies in Adults Behavioral processes of change. Table 2 summarizes the studies examining behavioral processes as mediators of physical activity interventions. All studies examining behavioral processes 2,7,8,12,16,20 administered the full or a shortened version of the Processes of Change Questionnaire, 30 which measures the following behavioral processes: substituting alternatives, enlisting social support, rewarding yourself, committing yourself, and reminding yourself. 31 Most of the studies indicated that physical activity interventions designed to change behavioral processes significantly increased use of behavioral processes, and increased use of behavioral processes was significantly related to increases in physical activity behavior. 2,7,8,16,20 However, findings are not entirely consistent across type of physical activity outcome variable 12 or time points. 7 Cognitive processes of change. Research examining cognitive processes as mediators of physical activity is described in Table 3. All studies examining cognitive processes 2,7,8,12,16,20 used the full or a shortened version of the Processes of Change Questionnaire, 30 which measures the following cognitive processes: increasing knowledge, warning of risks associated with physical inactivity, caring about consequences to others, comprehending benefits, and increasing health opportunities by becoming more physically active. Results from studies examining the effects of the intervention on cognitive processes have varied across studies, 2,7,8,12,16,20 in addition to varying within a study regarding gender 8,12 and time-point assessment. 7 A majority of the studies that investigated the link between cognitive processes and physical activity did not find that cognitive processes significantly influenced physical activity behavior. 7,8,16 Despite the inconsistent findings, results from other types of research indicate that cognitive processes are likely to be important in shaping behavior or moving individuals along the stage-of-change continuum as well as in changing physical activity behavior itself. 30,32 Perhaps cognitive processes change when an individual decides to participate in a physical activity intervention and prior to the actual start of the intervention. This is consistent with the TTM, as it postulates that cognitive processes change earlier and prior to behavioral processes. Self-efficacy. Studies examining self-efficacy as a mediator in intervention studies are summarized in Table 4. Self-efficacy for physical activity refers to one s confidence regarding participating in specific types of physical activity, or specific amounts of physical activity, or both. Some studies indicate that interventions significantly increase self-efficacy, or that self-efficacy is significantly related to physical activity behavior, or both, 2,7,8,12,13,16,22 although support for self-efficacy has Am J Prev Med 2002;23(2S) 29

5 Table 3. Effect of intervention on cognitive processes and effects on outcome Study Marcus, ; Marcus et al., Pinto et al., Calfas et al., ; Sallis et al., Nichols et al., Dunn et al., ,28 Effect of intervention on cognitive processes Effect of cognitive processes on outcome Decreased in both groups from base to post Related to none of the outcome variables (tailored and AHA) Intervention marginally increased relative to Was not a mediator at either time point control at 6 weeks but not 8 months Intervention more than controls for women, Related to none of the outcome variables not men (women maintained at 1 and 2 years Intervention increased more than control Not assessed for behavioral and cognitive processes (combined) No differences across groups (lifestyle vs Increases from 0 to 24 months predicted structured) meeting CDC/ACSM recommendation 3.5 years later Calfas et al., and Intervention increased more than controls Increases predicted one of four outcomes Note: The cognitive process subscales of the Processes of Change Questionnaire consist of the following: consciousness raising (increasing knowledge), dramatic relief (warning of risks), environmental re-evaluation (caring about consequence to others), self-re-evaluation (comprehending benefits), and social liberation (increasing healthy opportunities) (Marcus et al. 30 ). ACSM, American College of Sports Medicine; AHA, American Heart Association materials; CDC, Centers for Disease Control and Prevention. varied across time point, 7 gender, 8 and outcome variable. 8,12 The two studies that examined the effect of the intervention on self-efficacy but not the effect of selfefficacy on physical activity behavior found that the intervention group did not report more of an increase in self-efficacy than the control group. 17,20 Of the two studies that examined if self-efficacy was a mediator based on Baron and Kenny s 11 criteria, one of the studies 22 found self-efficacy to be a physical activity mediator among mothers, and another study conducted in a primary care setting found that self-efficacy was not a mediator. 7 Although studies that did not examine the direct effect of the intervention on the mediator are not the focus of this paper, it is important to note that many studies have found significant correlations between self-efficacy and physical activity behavior (e.g., Dzewaltowski 33, Garcia and King 34, and McAuley 35 ). Table 4. Effect of intervention on self-efficacy and effects on outcome Study Effect of intervention on self-efficacy Effect of self-efficacy on outcome Miller et al., Marcus, ; Marcus et al., Group-based intervention increased relative to other groups Increased in both groups from base to post (tailored and AHA) Pinto et al., Intervention increased more than control at 6 weeks but not 8 months Calfas et al., ; Intervention increased more than controls for Sallis et al., women but not men Nichols et al., No differences between intervention and control Hallam and Petosa, Intervention did not increase more than control Dunn et al., ,28 No differences across groups (lifestyle vs structured) Castro et al., Decreased from base to follow-up and from post to follow-up for both groups Calfas et al., and No differences between intervention and control for either measure A mediator based on Baron and Kenny 10 criteria Increases associated with two of three outcome variables for IT and three of three for ST Not a mediator at either time point based on Baron and Kenny 10 criteria Resisting relapse, SE related to two of five outcomes for men and one of five for women Not assessed Not assessed Increases 0 to 24 months predicted CDC/ACSM recommendations 3.5 years later Self-efficacy inversely related to change in walking from base to follow-up Making Time SE: two of four outcomes; Sticking to it SE: three of four outcomes McAuley et al., No direct effect of intervention on self-efficacy Related to exercise frequency ACSM, American College of Sports Medicine; AHA, American Heart Association materials; CDC, Centers for Disease Control and Prevention; IT, Intervention; SE, self-efficacy; ST, Standard Treatment. 30 American Journal of Preventive Medicine, Volume 23, Number 2S

6 Table 5. Effect of intervention on decisional balance and effects on outcome Study Effect of decisional balance on mediator Effect of decisional balance on outcome Marcus, ; Marcus et al., Pinto et al., Calfas et al., ; Sallis et al., Nichols et al., Dunn et al., ,28 Castro et al., No increase in either group from base to post (tailored and AHA) Intervention increased more than control at 6 weeks but not 8 months Intervention increased barriers for men, no effect for women No differences between intervention and control No differences across groups (lifestyle vs structured) Barriers decreased in both groups from base to post Related to none of the outcome variables Was a mediator at 6 weeks but not 8 months Women: zero of five outcomes; men: benefits and barriers positively related to one of five outcomes Not assessed Increases in pros, not cons, from 0 to 24 months predicted meeting CDC/ACSM recommendations 3.5 years later Not related to walking ACSM, American College of Sports Medicine; AHA, American Heart Association materials; CDC, Centers for Disease Control and Prevention. Decisional balance/benefits and barriers. Table 5 describes studies examining decisional balance and benefits and barriers as mediators in the physical activity interventions being targeted. One of the six studies indicated that the decisional balance index (i.e., pros minus cons) significantly increased more in the intervention group than in the control group at 6 weeks but not 8 months, 7 while another study found that barriers significantly decreased in both intervention and control groups. 14 The remaining studies indicated no effect of the intervention on decisional balance, 2,16,20 with the exception of one study showing a significant increase in barriers for men. 8 Two of the five studies reported a significant relationship between decisional balance and physical activity behavior. 2,7,28 Overall, the support for decisional balance as a mediator in physical activity intervention studies appears mixed. The construct of decision making has been examined differently across studies (e.g., decisional balance index, and benefits and barriers), which may contribute to the mixed findings (e.g., Pinto et al. 7 and Sallis et al. 8 ). Similar to cognitive processes, perhaps individuals decisional-balance index changes prior to beginning an intervention, making it difficult to detect changes in decisional balance following initiation of the intervention. Social support. Table 6 summarizes studies examining social support as a mediator in the physical activity intervention being targeted. Contrary to hypotheses, one of the five studies indicated that social support among the intervention group significantly decreased from baseline to follow-up relative to the control group 20 ; another study found no significant differences between intervention and control groups 12 ; one study found that it significantly increased from baseline to post-test and follow-up 14 ; one study found that the intervention significantly increased social support more than the control for women but not men 8 ; and a final study found that social support significantly increased in the intervention group but not the control group. 17 The only study that examined social support based on Table 6. Effect of intervention on social support and effects on outcome Study Effect of intervention on social support Effect of social support on outcome Miller et al., Group intervention increased relative to other groups A mediator based on Baron and Kenny 10 criteria (partner support) Calfas et al., ; Sallis et al., Intervention increased more than controls for women but not men Friends related to one of five outcomes for women and zero of five for men Nichols et al., Intervention decreased more than control Not assessed Hallam and Petosa, Intervention increased more than control Not assessed Calfas et al., and No differences between intervention and controls for either measure Castro et al., Intervention increased from base to post and base to follow-up; intervention decreased from post to followup Increases predicted one of four outcomes for family and three of four for friend Not related to walking Am J Prev Med 2002;23(2S) 31

7 Table 7. Effect of intervention on enjoyment and effects on outcome Study Effect of intervention on enjoyment Effect of enjoyment on outcome Calfas et al., ; No significant differences between Sallis et al., intervention and control Nichols et al., No differences between intervention and control Castro et al., Decreased in both groups from base to post and base to follow-up Men: two of five outcomes (including one positive and one negative); women: one of five outcomes Not assessed Not related to outcome Baron and Kenny s 11 recommendation found that social support (i.e., spousal support) was a mediator among mothers with young children. 22 Because spousal support among this population is particularly important, this intervention emphasized spousal support and perhaps this emphasis increased the likelihood of finding a mediation effect. Overall, the relationship between social support and physical activity behavior was inconsistent across studies 8,12,14 ; however, it is important to note that other correlational studies that did not directly examine the influence of the intervention on the mediator have found social support to be an important predictor of physical activity behavior. 36,37 Enjoyment of physical activity. Studies investigating enjoyment of physical activity as a mediator are summarized in Table 7. Two of the three studies found that the intervention did not significantly influence enjoyment, 8,20 and the remaining study found that enjoyment decreased in both the intervention and control groups from baseline to post-test. 14 Thus, past research provides no support that enjoyment is a mediator of physical activity. However, our conclusion should be interpreted with caution, given that when compared to other mediators, fewer studies have examined enjoyment as a potential mediator. Other mediators. Hallam and Petosa 17 examined the effect of a physical activity intervention on outcome expectancy (i.e., individual s estimate that participating in physical activity will lead to a particular outcome and the value of the expected outcome) and self-regulation (i.e., skills used to carry out physical activity intentions and ability to overcome situational and personal barriers). Results indicated that participants in the intervention group increased their overall scores on the selfregulation and outcome-expectancy value relative to control. The effect of outcome-expectancy value and self-regulation on physical activity was not examined. Summary of Mediator Studies in Children and Youth Our review of the scientific literature on interventions to promote physical activity in children or youth revealed only two investigations in which the influence of the intervention on both physical activity and potential mediators was examined. Neither of these studies directly addressed the effects of mediators as has been recommended by Baron and Kenny 11 or Kraemer et al. 23,24 For one of the pertinent studies, the effects of the intervention on physical activity and mediators were presented in separate papers. Parcel et al. 21 observed the effects of an elementary school based intervention that included physical education and classroom health education components using a quasi-experimental design. They reported evidence that the intervention produced significant improvements in physical activity self-efficacy and behavioral capability (knowledge and skills). However, selfreported physical activity increased between baseline and follow-up in both control and intervention groups, and the difference between the groups was not significant. Perhaps the most extensive examination of potential mediators in physical activity interventions in children was performed in the CATCH (Child and Adolescent Trial for Cardiovascular Health) investigation, a multicenter randomized controlled trial based in 96 elementary schools. CATCH examined the effects of a schoolbased intervention to increase physical activity and improve diet in students who were initially in the third grade. As reported by Leupker et al., 18 both physical activity observed in physical education classes and selfreported, vigorous physical activity, when measured in the students as fifth graders, were significantly greater in the intervention group than the control group. In a separate paper based on the same sample of children, the CATCH investigators 15 reported that physical activity self-efficacy and perceived social support for physical activity were significantly greater in the intervention children than controls in observations made when the students were in the third and fourth grades. However, at the conclusion of the active intervention phase of the study, when the children were fifth graders, no differences between intervention and control groups were observed. When follow-up observations of the CATCH cohort were made during the subjects eighth-grade year, self-reported, vigorous physical activity remained greater in in the intervention group than in the control group. However, positive social support for physical activity was not different between the groups. 32 American Journal of Preventive Medicine, Volume 23, Number 2S

8 Discussion Behavioral processes of change have received the most consistent support for mediating the relationship between theory-based, physical activity interventions and physical activity behavior, although self-efficacy has also received some support as a mediator. There are several potential reasons why certain mediators were supported and others were not, such as statistical, methodologic, and measurement differences across studies. For example, statistical procedures varied across studies, interventions differed regarding their effectiveness, mediator measures were delivered at various time points, and different measures were used to examine mediators. 2,7,8,12 22 Since 1998, when Baranowki et al. 10 recommended that studies examine mediators as instructed by Baron and Kenny, 11 only two research studies 7,22 that we are aware of have conducted a mediator analysis according to this or similar recommendations. 11,23,24 Therefore, definitive conclusions about the importance of mediators in theoretically based, physical activity intervention studies are not possible at this time. One problem with conducting mediator studies as recommended by Baron and Kenny 11 and Kraemer et al. 23,24 is that it is not always possible to fully test mediation because some studies lack a true control group, or have a crosssectional (i.e., examining mediator and outcome at the same time point) rather than a prospective design (i.e., how change in mediator effects outcome at a later time point), or both. It is important to note that it is not always possible to have a true control group due to ethical reasons. In addition, it may be premature for studies examining new mediators to conduct a full analysis of mediators before the effect of the intervention on the potential mediator is established. Another problem with the existing physical activity literature on mediators is that some studies did not find differences between the intervention and control groups. For example, one study found that the intervention was effective for women but not for men 8 ; another study found that both the intervention and control groups increased walking 14 ; and still another study found that both groups increased physical activity. 2 In these studies, the effect of the intervention on the mediator and the effect of the mediator on physical activity behavior can be assessed. However, when no physical activity differences are found between the intervention and control groups, one of the criteria for mediation is not met and consequently, a full mediator analysis as recommended by previous studies 11,23,24 will indicate that the theoretical construct is not a mediator. Another limitation of the existing physical activity intervention studies examining mediators is the inconsistency of measures administered across studies. This inconsistency creates difficulty in comparing findings across studies. Another measurement problem is that some studies have used shortened versions, adapted versions, or both shortened and adapted versions of previously validated measures of mediators. 8,14,20 It is important to note that a few studies found effects of the mediator in the opposite direction as hypothesized. 8,14,16,20 For example, one study found that the intervention was associated with subsequent decreases in self-efficacy for physical activity. 14 A possible explanation is that participants became more realistic in their expectations and therefore, became more accurate at estimating their self-efficacy after attempts to maintain their physical activity. Another potential measurement problem is that changes in mediators (e.g., decisional balance and cognitive processes) may occur prior to the start of the intervention. For example, changes in one s beliefs about the pros and cons associated with becoming physically active (i.e., decisional balance) may lead an individual to enroll in a physical activity study. This makes it difficult to detect mediator changes following the intervention due to ceiling effects. Future studies should take steps to better understand findings such as these (e.g., assessments at multiple time points and collecting qualitative data). Research Recommendations Measurement issues. In order to adequately test if a mediator is important in physical activity intervention studies, psychometrically sound measurement tools should be used. A formal review of the measures available for examining mediators is beyond the scope of this paper; however, the following summarizes recommendations regarding measurement issues. 1. Studies should avoid using part of or adapting scales without validating the new version of the scale. There will be cases in which scales will not be appropriate for particular populations. In these cases, adapted measures should be validated prior to use in the study in order to increase confidence in the results of the mediator analysis. 2. Fewer physical activity intervention studies have examined mediators in children (e.g., Parcel et al. 21 ) than in adults (e.g., Pinto et al. 7 and Sallis et al. 8 ) and, therefore, fewer mediator measures are available for children. 15 Future studies should develop and test age-appropriate measures designed to examine mediators in children and youth. 3. All six of the adult studies examining behavioral and cognitive processes used the processes of change instrument. 30 Future studies should continue to use this scale; however, because of the inconsistent support for cognitive processes at different time points, 7,28 it will be especially important for researchers examining this mediator to examine it at several time points. 4. Studies have examined the pros, cons, and barriers related to physical activity using the decisional bal- Am J Prev Med 2002;23(2S) 33

9 ance instrument, 38 the Barriers to Physical Activity Scale, 39 and the Benefits of Physical Activity Scale. 39 In order to make comparisons across studies, additional studies are needed to determine which of these scales, or others, are most appropriate, or if some combination of these scales should be used. 5. A variety of scales have been used to examine self-efficacy (e.g., Garcia and King 34, Marcus et al. 40, and Sallis et al. 41 ) and social support 17,42 among adults. All three of the studies examining enjoyment used the Physical Activity Enjoyment Scale. 43 It is unclear whether inconsistent findings for these mediators are due to measurement problems or actual differences in the importance of a particular mediator. Therefore, it is premature to discard existing measures and future research regarding the appropriateness of the scales are needed. 6. To move the field forward, future studies should focus on determining if inconsistent findings are due to measurement error, lack of importance of a particular mediator, or interventions being unsuccessful at changing mediators. Even though consistency across studies is important, it is also noteworthy that particular scales may be more relevant to particular populations and this should be taken into consideration. For example, different scales may be more developmentally appropriate for different age groups. Methodologic issues. Based on the limitations of the studies highlighted in this paper, several methodologic issues should be addressed in future studies. 1. Studies including control groups and prospective designs are needed to adequately examine mediators as recommended by Baron and Kenny 11 and more recently, Kraemer et al. 23,24 to truly test if theory-based, physical activity interventions are effective due to predicted changes in theoretical constructs. Furthermore, the influence of mediators across different groups of individuals may vary and should be examined in future studies. For example, there is some evidence that the importance of mediators may differ between genders, 8 (i.e., gender may be a moderator of intervention-mediator intervention relationships) and this should be explored further. Also, additional research is needed among ethnically diverse populations and across different age groups, including children and older adults. 2. The first step for researchers examining new mediators or mediators with little or mixed support should be to examine if the intervention is more likely to produce changes in the theoretical construct than a control group. Because there are fewer studies examining mediators among children than among adults, this recommendation is particularly relevant for the former population. Furthermore, a full mediator analysis may be premature for interventions that have not been shown to be effective, given that one of the criteria for mediation is not met when an intervention is ineffective. For interventions that are not effective, the first step of a mediation analysis (i.e., the effect of the intervention on the theoretical construct) could be conducted to better understand why the intervention was ineffective. 3. Because there is some preliminary evidence that certain mediators may be more important at particular time points (e.g., cognitive processes), 7,28 future studies should examine mediators at multiple time points, including both short-term (i.e., weeks) and long-term time points (i.e., years). Optimally, studies would examine the effect of the intervention (i.e., Time Point 1) on changes in the mediators at a later time point (i.e., Time Point 2). Next, studies would examine the effect of changes in the mediators (i.e., Time Point 2) on physical activity behavior at a later time point (i.e., Time Point 3). This design is necessary to infer causality, such that changes in mediators caused changes in physical activity behavior rather than changes in physical activity causing changes in the mediators. 4. Finally, studies examining new theories (e.g., social ecologic) and additional theoretical constructs are needed to move the field forward to better understand how interventions influence physical activity behavior. For example, there is some preliminary evidence that self-regulation and outcome-expectancy value may be influenced by a physical activity intervention. 17 Because previous studies indicate that mediators account for a small percentage of the variance, it will be especially important to examine new theories to improve our understanding of physical activity behavior change. For example, theoretical constructs based on the theory of planned behavior and the theory of reasoned action have been shown to be predictive of physical activity behavior in correlational studies that did not examine the direct effect of the intervention on physical activity behavior. 44,45 It is likely that a plethora of theoretical constructs, including those extending beyond psychosocial domains (e.g., program-specific or environmental domains) 46 that have not been previously examined will significantly contribute to our understanding of physical activity behavior change. We are grateful to Ross Brownson, PhD, Cora Craig, PhD, and Bernardine Pinto, PhD, for their review of this manuscript. This project was supported in part through grants from the National Heart, Lung, and Blood Institute (HL68422 and HL64342). 34 American Journal of Preventive Medicine, Volume 23, Number 2S

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Physical-based activity counseling: intervention effects on mediators of motivational readiness for physical activity. Ann Behav Med 2001;23: Sallis JF, Calfas KJ, Alcaraz JE, Gehrman C, Johnson MF. Potential mediators of change in a physical activity promotion course of university students: Project GRAD. Ann Behav Med 1999;21: Bauman AE, Sallis JF, Dzewaltowski DA, Owen N. Toward a better understanding of the influences on physical activity: the role of determinants, correlates, causal variables, mediators, moderators, and confounders. Am J Prev Med 2002:23(suppl 2): Baranowski T, Anderson C, Carmack C. Mediating variable framework in physical activity interventions: How are we doing? How might we do better? Am J Prev Med 1998;15: Baron RM, Kenny DA. The moderator mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986;51: Calfas KJ, Sallis JF, Oldenburg B, French M. 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Outcomes of a field trial to improve children s dietary patterns and physical activity. JAMA 1996;275: Nader PR, Stone EJ, Lytle L, et al. Three-year maintenance of improved diet and physical activity, the CATCH cohort. Arch Pediatr Adolesc Med 1999;153: Nichols JF, Wellman E, Caparosa S, Sallis JF, Calfas KJ, Rowe R. Impact of a worksite behavioral skills intervention. Am J Health Promot 2000;14: Parcel GS, Simons-Morton B, O Hara NM, Baranowski T, Wilson B. School promotion of healthful diet and physical activity: impact on learning outcomes and self-reported behavior. Health Educ Q 1989;16: Miller YD, Trost SG, Brown WJ. Mediators of physical activity behavior change among women with young children. Am J Prev Med 2002;23(suppl 2): Kraemer HC, Stice E, Kazdin A, Offord D, Kupfer D. How do risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. Am J Psychiatry 2001;158: Kraemer HC, Wilson GT, Fairburn CG, Agras WS. Mediators and moderators of treatment effects in randomized clinical trials. Arch Gen Psychiatry. In press. 25. Sallis JF, Owen N. Physical activity and behavioral medicine. Thousand Oaks, CA: Sage, Marcus BH, Bock BC, Pinto BM, Forsyth LH, Roberts MB, Traficante RM. Efficacy of an individualized, motivationally-tailored physical activity intervention. Ann Behav Med 1998;20: Calfas KJ, Sallis JF, Nichols JF, et al. Project GRAD: two-year outcomes of a randomized controlled physical activity intervention among young adults. Am J Prev Med 2000;18: Dunn AL, Blair SN, Kohl HW, Kampert JB, Marcus BH, Garcia ME. Project Active: a randomized clinical trial of lifestyle and structured physical activity programs. Paper presented at annual meeting of American College of Sports Medicine, Denver, CO, May Calfas KJ, Long BJ, Sallis JF, Wooten WJ, Pratt M, Patrick K. A controlled trial of physical counseling to promote the adoption of physical activity. Prev Med 1996;13: Marcus BH, Rossi JS, Selby VC, Niaura RS, Abrams DB. The stages and processes of exercise adoption and maintenance in a worksite sample. Health Psychol 1992;11: Marcus BH, Forsyth LH. Motivating adults to be more active. Champaign, IL: Human Kinetics. In press. 32. Rosen, CS. Is the sequencing of change processes by stage consistent across health problems? A meta-analysis. Health Psychol 2000;19: Dzewaltowski DA. Toward a model of exercise motivation. J Sport Exerc Psychol 1989;11: Garcia AW, King AC. Predicting long-term adherence to aerobic exercise: a comparison of two models. J Sport Exerc Psychol 1991;13: McAuley E. The role of efficacy cognitions in the prediction of exercise behavior in middle-aged adults. J Behav Med 1992;15: Courneya KS, McAuley E. Cognitive mediators of the social influenceexercise adherence relationship: a test of the theory of planned behavior. J Behav Med 1995;18: Oka R, King AC, Young DR. Sources of social support as predictors of exercise adherence in women and men ages 50 to 65 years. Women Health Res Gender Behav Policy 1995;1: Marcus BH, Rakowski W, Rossi RS. Assessing motivational readiness and decision-making for exercise. Health Psychol 1992;11: Sallis JF, Hovell MF, Hofstter CR, et al. A multivariate study of determinants of vigorous exercise in a community sample. Prev Med 1989;18: Marcus BH, Selby VC, Niaura RS, Rossi JS. Self-efficacy and the stages of exercise behavior change. Res Q Exerc Sport 1992;63: Sallis JF, Pinski RB, Grossman RM, Patterson TL, Nader PR. The development of self-efficacy scales for health-related diet and exercise behaviors. Health Educ Res 1988;3: Sallis JF, Grossman RM, Pinski RB, Patterson TL, Nader PR. The development of scales to measure social support for diet and exercise behaviors. Prev Med 1987;16: Kendzierski D, DeCarlo KJ. Physical Activity Enjoyment Scale: two validation studies. J Sport Exerc Psychol 1991;13: Courneya KS, McAuley E. Cognitive mediators of social influence exercise adherence relationship: a test of the theory of planned behavior. J Behav Med1995;18: Smith RA, Biddle SJ. Attitudes and exercise adherence: test of the theories of reasoned action and planned behavior. J Sports Sci 1999;17: King AC, Stokols D, Talen E, Brassington GS, Killingsworth R. Theoretical approaches to the promotion of physical activity: forging a transdisciplinary paradigm. Am J Prev Med 2002;23(suppl 2): Am J Prev Med 2002;23(2S) 35

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