2003 RESEARCH CONSORTIUMGRADUATE STUDENT AWARD WINNER

Factors Influencing Physical ActivityAmong Adults With Physical DisabilitiesMaria Kosma, Bradley J. Cardinal*, and JeffMcCubbin, Oregon State University

The benefits of physical activity and/or exercise for in­I dividuals with disabilities have been reported by an

abundance of studies and governmental agencies (Centersfor Disease Control and Prevention, 1999; Guthrie, 1999).Some of the benefits include increased health-related fit­ness, movement skills, and independent functioning, pre­vention of obesity and other health-related conditions,decreased anxiety and depression, and increased positivemood, self-esteem, and self-confidence. Unfortunately, toofew people with disabilities enjoy those benefits, becausetoo few are active on a regular basis. For example, a 1997survey (Healthy People, 2010), reported that only 12% ofthe adult population with disabilities participated in physi­cal activityof moderate intensity, 5 days per week for 30 mineach day. Although these data do not seem to differ drasti­cally from the data of the same age-range nondisabled popu­lation (16% participating in the recommended activity),there is a much higher percentage of adults with disabili­ties (56%) who do not participate in any leisure-time physi­cal activity compared with adults without disabilities (36%).

The social minority model, which serves to at least par­tially regulate the physical activity behavior of individualswith disabilities, recognizes certain psychosocial factorsthat may decrease physical activity motivation (Kosma etaI., 2002). Therefore, it is essential to identify importantmotivational concepts and principles associated with ac­tive living (Durstine et aI., 2000). Given the limited theory­driven empirical evidence toward the identification ofmotivational strategies among this population segment,the purpose of this study was to explore the most influen­tial (motivational) factors in physical activity for adults withphysical disabilities based on the transtheoretical model(TM; Prochaska & DiClemente, 1983).

The TM is a contemporary action-oriented model thatrecognizes ways to increase physical activity behavior. Themajor dimensions of the TM are stages of change (i.e.,physical activity intention and behavior), processes ofchange (i.e., 10 cognitive and behavioral strategies to in­crease physical activity), self-efficacy (i.e., perceived self­confidence to overcome barriers toward physical activity),and decisional balance (i.e., perceived pros and cons to­ward exercise). Classifying individuals within a corre­sponding stage regarding physical activity intention andbehavior may facilitate the development of interventionprograms. Specifically, in this study there was an attemptto determine the most important exercise motivationalstrategies that can be used in intervention programs.

ROES: March 2003 Supplement

This was a national, cross-sectional survey of adults withphysical disabilities. The degree to which different inde­pendent variables (processes of change, decision balance,self-efficacy, and physical activity barriers) may affect ex­ercise stages of change was examined. A press release anda flyer were used as study dissemination sources for par­ticipant recruitment. Study participation was voluntary.

Research questions:

1. Which cognitive, behavioral, and environmental fac­tors (i.e., processes of change, self-efficacy, decisionalbalance, and exercise barriers) mostly affect stages ofchange (i.e., a physical activity indicator)?

2. In which stages of change are participants more ac­curately classified as a means to direct effective inter­vention programs?

On the basis of statistical power analysis (i.e., statisticalpower = .80, medium effect size [ES = .25], and a = .05;Kraemer & Thiemann, 1987), 200 participants wereneeded for the internal validity of the study. Initially, 411individuals volunteered to participate in the survey. Fromthe 334 individuals who responded to the survey (re­sponse rate = 81.3%), 322 participants (women = 62.1%,men = 37.3%; Mage = 52.5 years) qualified to remain inthe study. The most prevalent disability categories werepostpolio (17.7%), multiple sclerosis (11.8%), and spi­nal cord injury (10.9%). Most of the participants (91.9%)were Caucasians.

In this study, self-report standardized measures of exer­cise stages of change (Reed et al., 1997), processes ofchange(Marcus et al., 1992), self-efficacy (Marcus et al., 1994), de­cisional balance (Marcus et al., 1994), and exercise barriers(Zhu, 2001) were distributed to the study participants. Par­ticipants were asked to fill out the questionnaires and re­turn them to the principal investigator in a self-addressedprepaid envelope. A total of four mailings were conductedthrough the university's Survey Research Center.

The Statistical Package for Social Sciences (SPSS) ver­sion 11 was used to analyze the data. Two direct discrimi­nant function (DDF) analyses were conducted to identifyinfluential factors toward physical activity. In the first DDFanalysis, the behavioral and cognitive processes of changewere tested as two distinct higher order constructs (5 cog­nitive and 5 behavioral strategies). In the second DDFanalysis, each of the cognitive and behavioral processes of

A-xix

change was evaluated separately for their contribution toclassification within the stages of change.

The a priori criterion for an accepted canonical corre­lation (i.e., the relationship between the combined scoresof the independent variables and stages of change) was ~.33 (Tabachnick & Fidell, 2001). Therefore, from the fourdiscriminant functions (i.e., combined scores of the in­dependent variables) produced in the initial DDF analy­sis, only the first two functions were statistically (Wilk'sLambda, = .394, X2 [20] = 294.3, P< .001; Wilk's Lambda,= .766, X2 [12] = 84.4, P< .001) and practically (r\ = .70;r2

= .44) significant. In the first discriminant function, thestructure coefficients (i.e., correlation between each pre­dictor and the corresponding discriminant function) re­vealed that behavioral processes of change were the mostimportant influential factors (r =.85), followed by self-ef­ficacy (r= .66), decisional balance (r= .54), and cognitiveprocesses (r= .33). In the second discriminant function,barriers (r = .71) and cognitive processes (r = .59) werethe most significant predictors. The stage-of-change classi­fication probabilities after weighting for group size indi­cated that the most stable stages were maintenance (89.6%),precontemplation (68.9%), and contemplation (51.7%),whereas the least stable stage was preparation (0%).

Similarly, in the second DDF analysis the first two dis­criminant functions were statistically (Wilk's Lambda, =

.310, X2 [52] = 365.9, P< .001; Wilk's Lambda, = .662, X2 [36]= 128.9, P< .001) and practically (r\ =.71; r2 = .50) signifi­cant. In the first discriminant function, the structure co­efficients showed that behavioral processes, self-efficacy,and decisional balance were the most important stage­of-ehange predictors. In the second discriminant func­tion, the cognitive processes of change and exercisebarriers were the most influential factors. The classifica­tion accuracy within the stages of change indicated thatmaintenance (89%), precontemplation (70.5%), andcontemplation (55.2%) were the most stable stages. In thissecond DDF analysis, classification accuracy was distrib­uted more evenly across the stages than in the first DDFanalysis. Specifically, 23.8% of cases in the preparationstage were correctly classified.

This is the first study to examine physical activity moti­vational factors for adults with physical disabilities on thebasis of the full TM. Results indicated that the behavioralprocesses of change, self-efficacy, and decisional balancewere very important to physical activity participation. Bar­riers toward physical activity and the cognitive processesof change were also very important to physical activity en-

hancement. These results are in agreement with currentevidence that behavioral and cognitive processes of changeare both important in physical activity initiation and main­tenance for the nondisabled population (Wallace &Buckworth, 2001) .

In the second DDF analysis, structure coefficients iden­tified certain processes of change that can influence physi­cal activity involvement. In particular, practitioners andscholars in adapted physical activity can use such exerciseintervention techniques as anxiety release, successfulexperiences, commitment to active lifestyles, environmen­tal cues, contingent-based reinforcement, awareness ofphysical activity benefits, as well as barrier identificationand elimination. Additionally, cognitive, emotional, andenvironmental consequences following physical activityand/or inactivity can act as triggers toward active lifestyles.As a whole, classification accuracy within the stages ofchange after controlling for group size was satisfactory (i.e.,67.1 % above chance accuracy in the first DDF analysis and69.9% above chance accuracy in the second DDF analy­sis). These results suggest that the aforementioned fac­tors are very important toward physical activity initiationand enhancement. The results also support the constructvalidity of the stages-of-ehange measure. However, the waythe preparation stage is conceptualized and measured,as well as the relationship with the study predictors, mayneed some refinement.

It is important to keep certain study limitations in mind.First, this was a cross-sectional study, and, therefore, de­velopmental trends in exercise behavior cannot be ob­served. Longitudinal designs are recommended in orderto examine the stability of different physical activity pre­dictors across time. Second, actual physical activity behav­ior was not measured in this study. Future studies shouldmeasure both physical activity and stages of change tobetter establish the concurrent validity of the results.Third, this study managed to capture mainly active Cau­casians with unequal group sizes across the differentstages of change, restricting the generalizability of theresults. Therefore, the study needs to be replicated withparticipants equally representing all stages of change. Itis also recommended that researchers examine differentage groups from diverse ethnic backgrounds and func­tional levels. Following the attempt of this project, futurestudies should try to develop physical activity motivationalstrategies based on theory-driven contemporary modelsaimed at understudied diverse populations. This studywas funded by NIDRR, USDE (CFDA No. 84.133b-9).

*Denotes Fellow status in the AAHPERD Research Consortium (as of December 2002).

A-xx ROES: March 2003 Supplement