Scand J Med Sci Sports 2008: 18: 798–809 Printed in Singapore . All rights reserved DOI: 10.1111/j.1600-0838.2007.00704.x Copyright & 2007 The Authors Journal compilation & 2007 Blackwell Munksgaard Adherence to sport injury rehabilitation programs: an integrated psycho-social approach A. R. Levy1, R. C. J. Polman2, P. J. Clough3 1 Centre for Sport and Exercise Science, The University of Leeds, West Yorkshire, Leeds, UK, 2Department of Sport, Health and Exercise Sciences, The University of Hull, Hull, UK, 3Department of Psychology, The University of Hull, Hull, UK Corresponding author: Andrew R. Levy, Centre for Sport and Exercise Science Exercise Science, The University of Leeds, West Yorkshire, LS2 9JT, UK. Tel: 144 (0)113 34 35085, E-mail: A.Levy@Leeds.ac.uk Accepted for publication 10 May 2007 The aim of the present study was to examine an adapted integrated psycho-social model to predict sport injury rehabilitation adherence. A longitudinal prospective design was used whereby 70 patients attending private physiotherapy clinics completed a battery of questionnaires both preand post-rehabilitation treatment based on the adapted framework. All participants were receiving treatment for tendonitis-related injuries. Adherence was monitored prospectively over the entire rehabilitation program using an observational measure of clinic adherence, a self-report measure of home-based adherence, in addition to monitoring attendance at rehabilitation sessions. In the initial phase of rehabilitation learning goal orientation, attitudes and perceived severity were found to predict rehabilitation intention. Intentions were also found to mediate the relationship between the aforementioned variables and clinic rehabilitation. Self-efficacy and self-motivation were predictors of clinic rehabilitation and attendance but not home rehabilitation. During the maintenance phase of rehabilitation coping ability and social support were predictors regarding all three measures of adherence. Implications for practitioners rehabilitating injured athletes are discussed. Due to a significant proportion of early research within the sport injury rehabilitation adherence literature being atheoretical, the deployment of theoretical frameworks to advance knowledge in this topic area has been recommended (Brewer, 1998; Spetch & Kolt, 2001). Since this assertion, there has been an emergence of psycho-social theoretical frameworks applied to the study of rehabilitation adherence within both sport and non-sporting populations (Brewer et al., 2000a, 2003a; Carroll & Whyte, 2003; Lippke et al., 2004). One such approach has recently been proposed by Levy et al. (2005), called the Adapted Planned Behavior Model (APBM: see Fig. 1). Their integrated psycho-social perspective is based on the theory of planned behavior (TPB; Ajzen, 1991) and provides a basis for predicting rehabilitation adherence among sporting populations. Specifically, the APBM uses Ajzen (1991) TPB as a vehicle to integrate two distinct phases: an initiation phase and a maintenance phase. This is in accordance with Horne and Weinman (1998), who recognized that many health behaviors can proceed in stages. That is factors underlying initiation of a particular behavior may be different from those involved in the maintenance of the behavior. The initiation phase outlined by the APBM is a decisionmaking stage as to whether one should undertake a rehabilitation program leading to an intention. This phase is characterized by the primary factors that influence the formation of rehabilitation intentions that can subsequently influence behavior. Alternatively, the maintenance phase is underpinned by secondary factors that are directly involved in initiating (action) rehabilitation behavior. The primary factors incorporated into the APBM consist of several psycho-social variables, namely, attitude, goal orientation (learning and performance orientations) and threat appraisals (perceived severity/susceptibility). Attitude toward rehabilitation was included due to previous research highlighting the importance of attitudes on intentions within a rehabilitation context (Taylor & Marlow, 2001; Carroll & Whyte, 2003). Given the equivocal findings relating to both threat appraisals and goal orientation on rehabilitation adherence, it was deemed that such psycho-social factors may be more influential on forming intentions during the initial part of rehabilitation. Indeed, two meta-analyses (Floyd et al., 2000; Milne et al., 2000) examining the performance of protection motivation theory, within the context of health, have found threat appraisals to have larger effect sizes on intentions compared with behavior. With respect to goal orientation, findings within a similar domain, exercise, have consistently found 798 Rehabilitation adherence in sport SELF-EFFICACY SELF-MOTIVATION INITIATION PHASE (cues to decision) PRIMARY FACTORS Threat appraisals Goal orientation Attitude INTENTION ADHERENCE SECONDARY FACTORS Coping ability Treatment efficacy Social support Repetition HABIT (cues to action) Fig. 1. Adapted planned behavior model. Table 1. Overview of the definitions and operationalization of primary variables Construct Sub-construct Definition Measurement Number of items Threat appraisal Perceived susceptibility A person’s evaluation of their degree of risk for a specific health threat if they continue to engage in unhealthy behaviors (Maddux, 1993) A person’s evaluation of the degree of harm, discomfort or damage that will result from a specified health threat (Maddux, 1993) A belief that one has the ability to engage in specific rehabilitation activities (Taylor & May, 1996) A generalized, non-specific tendency to persist in the long-term pursuit of behavioral goals regardless of extrinsic reinforcement and independent of situational influences (Dishman & Ickes, 1981) Striving to develop skills and master tasks for one’s own sake in which self-referent standards are used to judge personal competence (Button et al., 1996) Striving to seek favorable judgments regarding one’s competence in which social comparison processes are used to judge the level of demonstrated ability (Button et al., 1996) The degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior in question (Ajzen, 1991) The degree to which a person has formulated conscious plans to perform or not perform a specified future behaviour (Warshaw & Davis, 1985) Sport Injury Rehabilitation Beliefs Survey (SIRBS) 5 SIRBS 5 SIRBS 4 Self-Motivation Inventory 10 General Learning and Performance Orientation Scale (GLPOS) GLPOS 8 Self-report 1 Self-report 1 Perceived severity Self-efficacy – Self-motivation – Goal orientation Learning goal orientation Performance goal orientation Attitude – Intention – task orientation to be associated with intentions (Biddle et al., 1999a, 1999b; Lintunen et al., 1999). Refer to Table 1 for a more precise explanation of the aforementioned primary factors. The secondary factors incorporated into the APBM concern coping ability, treatment efficacy and social support. These psycho-social variables have been reported previously to be important influences on adherence to sport injury rehabilitation programs, hence their inclusion within the APBM. 8 For example, Udry (1997) reported instrumental coping (i.e. strategies to alleviate health problem) to be associated with higher levels of adherence, while palliative coping (i.e. strategies to alleviate unpleasantness of a health problem) was associated with lower adherence rates. In conjunction with this, Brewer et al. (2003a) concluded that enhancing perceptions of the effectiveness of rehabilitation (or treatment efficacy) may increase adherence. Another study conducted by Brewer et al. (2003b) found 799 Levy et al. Table 2. Overview of the definitions and operationalization of secondary variables Construct Sub-construct Definition Measurement Number of items Coping ability Distraction coping Use of actions and cognitions that are aimed at avoiding pre-occupation with the health problem (Endler & Parker, 2000) Use of various self-help responses utilized to alleviate the unpleasantness of a situation (Endler & Parker, 2000) Focusing on various task-orientated strategies used to alleviate the source of stress (Endler & Parker, 2000) Focusing on the emotional consequences of the health problem (Endler & Parker, 2000) Others who acknowledge when a good performance has been accomplished (Richman et al., 1993) Others who act in a caring and comforting way during emotionally difficult times (Richman et al., 1993) Others who provide services or help, such as running an errand or driving the support recipient somewhere (Richman et al., 1993) Others who actively listen without giving advice or making judgments (Richman et al., 1993) Belief that a designated course of treatment will lead to the desired health outcomes (Taylor & May, 1996) Coping with Health Injuries and Problems (CHIP) CHIP 8 8 CHIP 8 CHIP 8 Modified Social Support Survey (MSSS) MSSS 3 3 MSSS 3 MSSS 3 Sport Injury Rehabilitation Beliefs Survey (SIRBS) 4 Palliative coping Instrumental coping Emotional preoccupation coping Social support Task appreciation Emotional support Personal assistance Listening support Treatment efficacy – social support to be positively associated with home rehabilitation adherence in older individuals. In addition, other findings have related social support to be facilitative with clinic rehabilitation adherence (Byerly et al., 1994). Table 2 provides a more precise explanation of secondary factor variables. Within the APBM, both self-efficacy and selfmotivation are deemed to be influential in the decision-making stage of a rehabilitation program, subsequently influencing the formation of intentions and also having an impact upon the maintenance of rehabilitation behavior. Self-efficacy has been identified as an important determinant of rehabilitation adherence (Taylor & May, 1996; Brewer et al., 2003a). Additionally, this construct has also been found to be a strong predictor of intentions among cardiac rehabilitation patients (Plotnikoff & Higginbottom, 2002) and with numerous other health behaviors (Milne et al., 2000). Given these findings, it was considered that self-efficacy warranted dual influence on rehabilitation intentions and behavior. Similarly, self-motivation is said to exhibit the same proposed relationships posited for self-efficacy. This is due to the plethora of research attesting to the predictive ability of self-motivation on rehabilitation adherence (Fisher et al., 1988; Fields et al., 1995; Brewer et al., 2000b). In addition, Dishman (1988) suggested self-motivation to be influential in the 800 adoption of a behavior. That is, an individual who is low in self-motivation in the initial phase of rehabilitation is unlikely to form favorable intentions to engage (adopt) in rehabilitation activity. Given this, the APBM proposes self-motivation to have not only a direct effect on rehabilitation adherence but also an indirect effect via intention. A final feature of the APBM concerns the notion of habit directly influencing rehabilitation adherence during the maintenance phase. Recent research within the context of rehabilitation behavior has highlighted the importance habit exhibits on adherence (Carroll & Whyte, 2003). Within the APBM, habit is based on the theory of habit development (Ronis et al., 1989). According to Ronis et al. (1989), habit is a repeatedly performed activity that has become automatic and is therefore performed without conscious thought or without benefit of a decision. In the APBM, habit is operationalized through two situational cues, namely, cues to decision and cues to action. Cues to decision refer to cues that trigger cognitions in the form of primary factors that lead to the formation of rehabilitation intentions. It is notable that such cues do not elicit rehabilitation behavior itself, but rather key primary factors involved in the decision making. However, if the decision-making process and the behavior are repeated frequently in the presence of the same cues, Rehabilitation adherence in sport then cues to decision may become cues to action and the behavior is elicited automatically by the stimulus conditions. Thus, as rehabilitation behavior is performed with consistency and frequency over a period of time, both primary and secondary factors may be superseded in importance by a more automatic response pattern elicited by situational cues. In summary, the aim of the present study is to use a prospective design in examining the theoretical tenets proposed by the APBM in predicting rehabilitation intentions and adherence with individuals undertaking sport injury rehabilitation programs for tendonitis-related conditions. Based on the APBM, it was first hypothesized that primary factors including self-efficacy and self-motivation would directly predict rehabilitation intention. Second, it was hypothesized that the intention would mediate the relationship between the aforementioned variables and rehabilitation adherence. Finally, it was hypothesized that self-efficacy, self-motivation and secondary factors including habit would directly predict rehabilitation adherence. Methods Participants Seventy patients were recruited from four private physiotherapy clinics (44 male and 26 female), with a mean age of 32.5 years [standard deviation (SD 5 10.2)]. Of the participants, 31% were competitive athletes and 69% were recreational athletes. All participants had a tendonitis-related overuse injury in which no prior surgery was required. Notably, tendonitis injuries sustained were mainly located at the ankle (41%), knee (28%), shoulder (20%) and elbow (11%). The rehabilitation protocol consisted of a structured/progressive program of stretching and exercise activities for the associated injured area. This was performed both in clinic and home settings in which attendance, the amount of exercise and duration was based on the participant’s initial examination. Typically, participants attended two clinic rehabilitation sessions per week, lasting between 40 and 60 min over a period between 8 and 10 weeks Treatment such as ice/heat therapy and ultrasound were also undertaken by participants, particularly during the early phase (1–3 weeks) at each clinic rehabilitation appointment. Participants were expected to complete home-based rehabilitation exercises once a week, lasting between 20 and 30 min again over a period of 8–10 weeks. It should be noted that all participants had not been involved in any previous rehabilitation programs. Ethical approval was obtained by The University of Hull Research Ethics Committee, alongside informal consent, which was provided by all participants. Measures Adherence A multifaceted approach toward the assessment of adherence was used. First, attendance to scheduled rehabilitation appointments was calculated by dividing the number of rehabilitation sessions attended by the number of rehabilitation sessions scheduled. Second, the Sport Injury Rehabilitation Adherence Scale (SIRAS: Brewer et al., 2000c) was utilized to assess adherence during clinic-based rehabilitation sessions. This instrument requires the physiotherapist to evaluate patients’ behavior on a five-point Likert scale with regard to (a) the intensity with which participants completed their prescribed exercises (end points: minimum effort–maximum effort), (b) the frequency with which participants followed instructions (end points: never–always) and (c) their receptiveness to changes toward the program (end points: very unreceptive–very receptive). A total clinic rehabilitation adherence score was derived from summing each of the SIRAS responses for each item. The SIRAS has good internal consistency, ranging between a 5 0.81 and 0.86 (Shaw et al., 2005) and has also been reported to have good test–retest reliability over a 1-week period (ICC 5 0.77; Brewer et al., 2000c). In addition, Brewer et al. (2002) demonstrated the construct validity of the SIRAS with a heterogeneous sample of 43 participants. They found a significant linear relationship (Po0.001) between SIRAS scores and observed video footage that depicted minimal, moderate and maximal clinic rehabilitation adherence. A self-report measure of home-based rehabilitation adherence, as recommended by Bassett (2003), was utilized. This required participants to indicate on a five-point Likert scale ranging from 1 (not at all) to 5 (as advised) the extent to which they have (a) completed recommended home exercises, (b) refrained from undertaking activity that could harm injury and (c) applied home cryotherapy (icing). A total home rehabilitation adherence score was derived from summing each of the self-report responses for each item. Due to sport injury rehabilitation being a contemporary area of study (Shaw et al., 2005), previous research has not extensively tested for reliability or validity regarding the home-based rehabilitation adherence measure used in the present study. Initial-rehabilitation survey Threat appraisals/self-efficacy The Sport Injury Rehabilitation Belief Survey (SIRBS: Taylor & May, 1996) is a 19-item questionnaire assessing rehabilitation value, perceived severity (a 5 0.63), perceived susceptibility (a 5 0.83), treatment efficacy (a 5 0.83) and self-efficacy (a 5 0.79). It is notable that for each of the latter, acceptable internal consistency has been demonstrated (Taylor & May, 1996). Ratings for the SIRBS are made on a seven-point Likert-type scales ranging from 1 (very strongly disagree) to 7 (very strongly agree). Note that due to treatment efficacy being a secondary factor within the APBM, this scale was measured at the end of rehabilitation. Rehabilitation value was not measured in the present study. Self-motivation Dishman RK (personal communication, August 12, 2004) Self Motivation Inventory 10-item (SMI-10) was used to assess self-motivation. This measure is a short version of the 40-item Self Motivation Inventory proposed by Dishman and Ickes (1981). Ratings for the SMI-10 are made on five-point Likert scales, with endpoints ranging from 1 (very unlike me) to 5 (very much like me). The internal consistency of the SMI-10 revealed by Dishman RK (personal communication, August 12, 2004) has found Chronbach coefficient a’s to range between 0.78 and 0.88. Alongside this, factorial validity using confirmatory factor analysis (CFA) found the 10-item onefactor model of the Self Motivation Inventory to have a very good fit [w2 5 169.20, df 5 35, root mean square error of approximation (RMSEA) 5 0.049 (90% CI 5 0.042–0.056), 801 Levy et al. SRMR 5 0.038, comparative fit index (CFI) 5 0.985, nonnormed fit index (NNFI) 5 0.981]. The latter model was also found to have a good fit when cross validated with two independent samples, consisting of students and army-enlisted soldiers, using multi-group analysis of factorial invariance performed by CFA [w2 5 263.15, df 5 35, RMSEA 5 0.074 (90% CI 5 0.065–0.082), SRMR 5 0.045, CFI 5 0.978, NNFI 5 0.978]. Dishman RK (personal communication, August 12, 2004) also provided evidence of construct validity. In particular, convergent validity using Pearson’s product–moment correlations found the SMI-10 to have significant relationships with the Social Physique Anxiety Scale (r 5 0.36, Po0.01) and both Vigorous Exercise (r 5 0.42, Po0.01) and Moderate Exercise (r 5 0.18, Po0.05) as measured by the Godin LeisureTime Exercise Questionnaire (GLTEQ). Pearson’s product– moment correlations relating to discriminant validity found the SMI-10 to be unrelated with Rosenberg Self-Esteem Scale (r 5 0.16, P 5 0.06), subscales of the Self-Monitoring Scale [Ability to Modify Self-presentation (r 5 0.11, P 5 0.18); Sensitivity to the Expressive Behaviour of Others (r 5 0.08, P 5 0.37)] and Mild Exercise (r 5 0.03, P 5 0.72) assessed by GLTEQ. Attitude Attitude was assessed using a single-item measure asking ‘‘In general, how would you rate your attitude toward performing your rehabilitation exercises.’’ Responses were rated on a seven-point Likert scale anchored by the word pair 1 (extremely negative) to 7 (extremely positive). Ajzen (2002) acknowledges the use of single-item direct measures of attitude within psychological research, suggesting they can display high levels of reliability and correlate well with external criteria. Intention Intention was assessed by a single item on a seven-point Likert scale anchored by 1 (extremely unlikely) to 7 (extremely likely). The item was: ‘‘I intend to do my rehabilitation exercises as often as my physiotherapist prescribes over an eight to ten period.’’ The use of a single-item measure to assess this construct is consistent with the TPB (Ajzen, 1991). Goal orientation The General Learning and Performance Orientation Scale (GLPOS: Button et al., 1996) was used to assess learning goal orientation and performance goal orientation. Ratings are made on a seven-point Likert-type scales ranging from 1 (strongly disagree) to 7 (strongly agree). Internal consistencies for learning and performance goal orientations have been acceptable, ranging between a 5 0.79–0.85 and a 5 0.68–0.77, respectively (Button et al., 1996). Despite some support for the factorial validity of the GLPOS (Button et al., 1996), more recent research has raised concerns (Jagacinski & Duda, 2001). However, the GLPOS has displayed adequate construct validity when correlated with the Jackson Achievement Motivation Scale and beliefs about the importance of effort and ability in academics (Jagacinski & Duda, 2001). Post-rehabilitation survey measure of coping strategies in which ratings are outlined on a five-point Likert scale ranging from 1 (not at all) to 5 (very much). Coping strategies included in the CHIP are distraction coping (a 5 0.79), palliative coping (a 5 0.81), instrumental coping (a 5 0.82) and emotional pre-occupation (a 5 0.83). Notably, each of the latter has displayed good internal consistencies, alongside acceptable factorial validity using exploratory factor analysis (Endler & Parker, 2000). Social support A modified version of the Social Support Survey (MSSS: Richman et al., 1993) was adopted in order to assess social support. Owing to the plethora of items generated as a result of using a multidimensional measure, four common types of support and associated providers depicted from the sport injury rehabilitation literature were utilized. This included task appreciation provided by the physiotherapist, emotional support provided by friends, personal assistance provided by family and listening support provided by teammates. For each of these the same three questions were posed: (a) satisfaction with that support, ranging from 1 (very dissatisfied) to 5 (very satisfied), (b) difficulty of obtaining more of that support, ranging from 1 (very difficult) to 5 (very easy), and (c) importance to one’s overall well-being of that support, ranging from 1 (not at all) to 5 (very much). Scores were summed across the three questions for each support construct. The test–retest reliability reported by Richman et al. (1993) found multi-item subscale correlations to range between 0.44 (Po.01) and 0.87 (Po.001). Based on the inspection of 12 correlation matrices, Richman et al. (1993) suggested the SSS to have sufficient structural validity; however, its factorial validity has been questioned more recently by Rees et al. (2000). Habit A behavioral measure of habit was elicited by retrieving the frequency of participants’ actual engagement in clinic-based activities throughout the entire rehabilitation program. According to Ouellette and Wood (1998), frequency of past behavior has been traditionally used as an operationalization of habit. Indeed, previous research within the rehabilitation adherence literature has utilized frequency as a measure of past behavior (Carroll & Whyte, 2003). Procedure On their first physiotherapy appointment, participants completed a battery of questionnaires assessing demographic, injury-related information and primary factors measured by SIRBS, SMI-10, GLPOS and self-report measures of intention and attitude. At each rehabilitation appointment, the physiotherapists recorded participants’ attendance and completed SIRAS. Alongside this participants were informed to record their adherence to home-based rehabilitation activities. At the end of their rehabilitation (i.e. last clinic appointment), participants were required to complete a second battery of questionnaires pertaining to secondary factors that contained treatment efficacy items from the SIRBS, MSSS and CHIP. Due to the temporal nature of the aforementioned factors, it was felt that responses would be more accurate when assessed at the end of rehabilitation. Coping ability The assessment of coping ability was measured using Endler and Parker’s, (2000) Coping with Health Injuries and Problems (CHIP). This instrument is a 32-item multidimensional 802 Data analyses Means, SDs and Pearson’s product–moment correlations were determined to examine the relationships among the central Rehabilitation adherence in sport Table 3. Descriptive statistics and bivariate correlations among the primary variables Variables 1 1. Self-efficacy 2. Self-motivation 3. Perceived severity 4. Perceived susceptibility 5. Learning orientation 6. Performance orientation 7. Attitude 8. Intention 9. Clinic adherence (transformed) 10. Home adherence (transformed) 11. Attendance (transformed) 2 (0.94) 0.44** 0.22 0.05 0.26* 0.19 0.04 0.27* 0.50** 0.36** 0.51** 3 (0.92) 0.19 0.17 0.43** 0.05 0.17 0.28* 0.45** 0.24* 0.46** 4 5 (0.83) 0.36** (0.80) 0.37** 0.10 0.19 0.06 0.05 0.17 0.45** 0.43** 0.32** 0.32** 0.11 0.26* 0.27* 0.21 6 (0.95) 0.30* 0.16 0.47** 0.30* 0.01 0.35** 7 8 9 M 10 13.36 30.06 21.24 24.49 29.67 (0.88) 32.13 0.05 – 4.19 0.13 0.39** – 4.76 0.24* 0.24* 0.48** (0.93) 3.07 0.46** 0.31* 0.27* 0.87** (0.93) 1.60 0.06 0.20 0.41** 0.79** 0.55** – 2.55 SD 2.69 9.34 2.46 2.83 6.23 5.96 0.80 1.16 1.37 0.68 1.72 Cronbach as are presented on the diagonals. Missing as were unobtainable. *Po0.05 (two-tailed). **Po0.01 (two-tailed). Table 4. Descriptive statistics and bivariate correlations among the secondary variables Variables 1 2 3 4 5 6 7 8 9 10 11 12 13 M 1. Treatment efficacy (0.82) 2. Coping distraction 0.03 (0.67) 3. Coping palliative 0.06 0.19 (0.60) 4. Coping instrumental 0.32** 0.19 0.20 (0.83) 5. Coping emotional 0.09 0.16 0.23 0.33** (0.68) 6. Habit frequency 0.24* 0.04 0.02 0.02 0.14 – 0.53** 0.37** 0.07 – 7. Listening support 0.21 0.37** 0.04 teammates 0.30* 0.47** 0.14 0.06 0.49* – 8. Task appreciation 0.37** 0.23 physiotherapist 9. Emotional 0.28* 0.05 0.17 0.46** 0.16 0.15 0.36** 0.52** – support friends 0.34** 0.29* 0.10 0.02 0.46** 0.50** 0.27* – 10. Personal 0.22 0.27* assistance family 11. Clinic adherence 0.27* 0.32** 0.41** 0.44** 0.33** (0.93) 0.37** 0.31** 0.46** 0.47** 0.01 (transformed) 0.17 0.87** 0.22 0.29* 0.26* 0.87** (0.93) 12. Home adherence 0.13 0.26** 0.40** 0.34** 0.05 (transformed) 0.28* 0.38** 0.03 0.40** 0.79** 0.43** 0.35** 0.25* 0.79** 0.55** – 13. Attendance 0.47** 0.30* (transformed) 17.21 23.87 25.03 32.44 29.01 20.11 7.06 SD 2.46 3.80 4.51 4.34 3.49 2.42 5.32 8.33 3.50 4.26 3.95 9.27 4.75 3.07 1.37 1.60 0.68 2.55 1.72 Cronbach as are presented on the diagonals. Missing as were unobtainable. *Po0.05 (two-tailed). **Po0.01 (two-tailed). tenets of the adapted planned behavior model toward rehabilitation adherence. In addition, standard multiple regressions using the enter method were performed to examine the predictions proposed by the adapted planned behavior approach. In order to determine whether intention mediates the relation between primary factors and the three measures of rehabilitation adherence, the Baron and Kenny (1986) mediation model was utilized. According to Baron and Kenny (1986), to establish mediation, three regression models are investigated, firstly, the independent variable (primary factor) on the mediator (intention), secondly, the independent variable on the dependent variable (rehabilitation adherence) and, thirdly, the dependent variable on both the independent variable and the mediator together. A pattern consistent with mediation is demonstrated if the b value is significant in the second regression equation but non-significant (full mediation) or reduced (partial mediation) in the combined third regression equation (Baron & Kenny, 1986). Normality of independent and criterion variables was assessed using skewness and kurtosis values. Results Descriptive statistics Cronbach a’s are shown along with means and SDs in Tables 3 and 4. Normality regarding APBM variables was found to be acceptable. However, the distribution regarding all three adherence criterion measures was negatively skewed, thus a reflect and square root transformation was used to establish a more normal distribution. These transformed values were used in subsequent analysis. 803 Levy et al. Table 5. Regression analysis for testing the mediating influence of intention on the relation between primary factors and clinic adherence Step Dependent variable Independent variable b R2 Standard error 1 2 3 Intention Clinic adherence Clinic adherence Intention Clinic adherence Clinic adherence 1 2 3 Intention Clinic adherence Clinic adherence 1 2 3 Intention Clinic adherence Clinic adherence 1 2 3 Intention Clinic adherence Clinic adherence 1 2 3 Intention Clinic adherence Clinic adherence 1 2 3 Intention Clinic adherence Clinic adherence 0.27* 0.50** 0.40** 0.37** 0.28* 0.45** 0.34** 0.38** 0.45** 0.32** 0.13 0.42** 0.43** 0.32** 0.24* 0.42** 0.39** 0.24* 0.07 0.45** 0.47** 0.30* 0.09 0.44** 0.13 – – – 0.07 0.25 0.38 1 2 3 Self-efficacy Self-efficacy Self-efficacy Intention Self-motivation Self-motivation Self-motivation Intention Perceived severity Perceived severity Perceived severity Intention Perceived susceptibility Perceived susceptibility Perceived susceptibility Intention Attitude Attitude Attitude Intention Learning goal orientation Learning goal orientation Learning goal orientation Intention Performance goal orientation Performance goal orientation Performance goal orientation Intention 0.050 3.793 3.608 8.356 0.014 1.125 1.078 8.680 0.051 4.535 4.691 9.938 0.045 3.930 4.021 9.816 0.161 14.179 14.020 9.714 0.020 1.802 1.881 3.099 0.023 – – – 0.08 0.20 0.32 0.20 0.10 0.24 0.18 0.10 0.25 0.15 0.06 0.23 0.22 0.09 0.24 0.02 – – – *Po0.05. **Po0.01. Correlation analysis Pearson’s product–moment correlations among all variables outlined by the APBM are shown in Tables 3 and 4. Consistent with the tenets of the APBM all primary variables, apart from performance goal orientation was significantly correlated with intention. Excluding emotional pre-occupation coping, the remaining secondary factors including habit frequency were found to be significantly correlated with both the clinic-based adherence and attendance. Only palliative coping and emotion challenge-type support provided by the physiotherapist were found to have a negative relationship. Furthermore, instrumental/palliative coping and emotional support by friends/personal assistance by family alongside intention were the only variables to have a significant relationship with home-based rehabilitation adherence. Again, palliative coping was negatively associated with this outcome measure. attitude and learning goal orientation. Partial mediation patterns were found between self-efficacy and self-motivation and perceived susceptibility in relation to clinic adherence. However, no mediation was supported for performance goal orientation due to its non-significant regression on intention indicated by step 1. With regard to attendance, intention fully mediated the relations between perceived severity and learning goal orientation, while self-efficacy and self-motivation demonstrated a partial mediation. Together, no mediation was found for perceived susceptibility and attitude due to their influence on attendance at step 2 being non-significant. In addition, due to its lack of significance on intention highlighted by step 1, intention held no mediation for performance goal orientation on attendance. Similarly, no mediation patterns were evident between all primary factors and home-based adherence. Regression analyses Mediation analysis Predicting rehabilitation intentions The proposed mediating influence of intention on primary factors and the three measures of adherence are shown in Tables 5–7. The results suggest that intention demonstrates a full mediation pattern between clinic-based adherence and perceived severity, Multiple regression analysis using the enter method revealed that all primary factors accounted for 53% of the variance in rehabilitation intention (R2 5 0.53, F7, 62 5 12.09, Po0.001), with perceived susceptibility (b 5 0.229, Po0.05), perceived severity 804 Rehabilitation adherence in sport Table 6. Regression analysis for testing the mediating influence of intention on the relation between primary factors and home-based adherence Step Dependent variable Independent variable b R2 Standard error 1 2 3 Intention Home adherence Home adherence Intention Home adherence Home adherence 1 2 3 Intention Home adherence Home adherence 1 2 3 Intention Home adherence Home adherence 1 2 3 Intention Home adherence Home adherence 1 2 3 Intention Home adherence Home adherence 1 2 3 Intention Home adherence Home adherence 0.27* 0.36** 0.31** 0.19 0.28* 0.24* 0.18 0.22 0.45** 0.11 – – 0.43** 0.26* 0.17 0.19 0.39** 0.31* 0.24 0.18 0.47** 0.01 – – 0.13 – – – 0.07 0.13 0.16 1 2 3 Self-efficacy Self-efficacy Self-efficacy Intention Self-motivation Self-motivation Self-motivation Intention Perceived severity Perceived severity Perceived severity Intention Perceived susceptibility Perceived susceptibility Perceived susceptibility Intention Attitude Attitude Attitude Intention Learning goal orientation Learning goal orientation Learning goal orientation Intention Performance goal orientation Performance goal orientation Performance goal orientation Intention 0.050 1.139 1.168 2.706 0.014 0.341 0.350 2.815 0.051 1.326 – – 0.045 1.120 1.228 2.998 0.161 3.886 4.192 2.904 0.020 0.526 – – 0.023 – – – 0.08 0.06 0.10 0.20 0.01 – – 0.18 0.07 0.10 0.15 0.09 0.12 0.22 0.00 – – 0.02 – – – *Po0.05. **Po0.01. (b 5 0.221, Po0.05), learning goal orientation (b 5 0.418, Po0.001) and attitude (b 5 0.428, Po0.001) being the most significant predictors. Contrary to the predictions of the adapted planned behavior model self-motivation, self-efficacy and performance goal orientation were not significant predictors of rehabilitation intentions. Predicting clinic rehabilitation adherence As postulated by the APBM regression analysis revealed that self-efficacy (b 5 0.220, Po0.05), self motivation (b 5 0.345, Po0.01) and intention (b 5 0.234, Po0.05) significantly predicted clinic rehabilitation adherence. These primary factors accounted for 49% of the variance in clinic rehabilitation adherence (R2 5 0.49, F3, 64 5 14.50, Po0.001). In a separate regression analysis, secondary factors accounted for 68% of the variance in the prediction of clinic-based rehabilitation adherence (R2 5 0.68, F10, 50 5 8.80, Po0.001). The most significant predictors concerned coping ability, in particular distraction coping (b 5 0.186, Po.05) and palliative coping (b 5 0.409, Po0.001), treatment efficacy (b 5 0.306, Po0.01), habit (b 5 0.324, Po0.01) and two types of social support that concern task appreciation by the physiotherapist (b 5 0.303, Po0.05) and emotional support by friends (b 5 0.262, Po0.05). Predicting home-based adherence Self-efficacy, self-motivation and intention were not found to predict home-based rehabilitation adherence. In a separate regression analysis, secondary factors apart from treatment efficacy were found to predict 60% of the variance with regard to homebased rehabilitation adherence (R2 5 0.60, F10, 50 5 6.53, Po0.001). Specifically, distraction coping (b 5 0.223, Po0.05), palliative coping (b 5 0.453, Po0.001), habit (b 5 0.202, Po0.05) and social support in the form of task appreciation by the physiotherapist (b 5 0.370, Po0.01) and emotional support from friends (b 5 0.292, Po0.05) were significant predictors. Predicting attendance at rehabilitation sessions Self-efficacy (b 5 0.324, Po0.01), self-motivation (b 5 0.295, Po0.05) and intention (b 5 0.260, Po0.05) predicted attendance at rehabilitation sessions, accounting for 36% of the variance (R2 5 0.36, F3, 63 5 7.38, Po0.001). With regard to secondary factors, only palliative coping (b 5 0.245, Po0.05), treatment efficacy (b 5 0.358, Po0.01) and personal 805 Levy et al. Table 7. Regression analysis for testing the mediating influence of intention on the relation between primary factors and attendance at rehabilitation sessions Step Dependent variable Independent variable b R2 Standard error 1 2 3 Intention Attendance Attendance Intention Attendance Attendance 1 2 3 Intention Attendance Attendance 1 2 3 Intention Attendance Attendance 1 2 3 Intention Attendance Attendance 1 2 3 Intention Attendance Attendance 1 2 3 Intention Attendance Attendance 0.27* 0.51** 0.44** 0.30** 0.28* 0.46** 0.37** 0.30** 0.45** 0.27* 0.10 0.36** 0.43** 0.21 – – 0.39** 0.20 – – 0.47** 0.35** 0.20 0.31* 0.13 – – – 0.07 0.26 0.34 1 2 3 Self-efficacy Self-efficacy Self-efficacy Intention Self-motivation Self-motivation Self-motivation Intention Perceived severity Perceived severity Perceived severity Intention Perceived susceptibility Perceived susceptibility Perceived susceptibility Intention Attitude Attitude Attitude Intention Learning goal orientation Learning goal orientation Learning goal orientation Intention Performance goal orientation Performance goal orientation Performance goal orientation Intention 0.050 1.636 1.387 2.179 0.014 0.099 0.098 0.790 0.051 0.408 0.432 0.916 0.045 0.359 – – 0.161 1.267 – – 0.020 0.156 0.170 0.914 0.023 – – – 0.08 0.21 0.30 0.20 0.07 0.18 0.18 0.04 – – 0.15 0.04 – – 0.22 0.12 0.20 0.02 – – – *Po0.05. **Po0.01. assistance by family members (b 5 0.249, Po0.05) significantly predicted attendance, accounting for 56% of the variance (R2 5 0.56, F9, 50 5 5.65, Po0.001). Discussion This study examined predictors of rehabilitation intention and behavior, as postulated by the APBM. Regression analysis highlighted the importance of primary factors such as perceived severity/ susceptibility, learning goal orientation and attitude on the prediction of intention. Previous findings have found threat appraisals and learning (or task) orientation to predict rehabilitation adherence (Duda et al., 1989; Taylor & May, 1996). In addition, the role of attitude in explaining rehabilitation intention corroborates with the findings of Carroll and Whyte (2003) and Taylor and Marlow (2001) who recognized attitudes to be an important determinant of intention with a sport injury rehabilitation context. However, it was notable that both self-efficacy and self-motivation did not predict rehabilitation intention. This finding, particularly concerning self-efficacy, is contrary to studies conducted within exercise settings (Hagger et al., 2002). It is possible that both 806 self-efficacy and self-motivation when examined within a sports rehabilitation context are less influential in the formation of favorable rehabilitation intentions when other key primary factors, found in the present study, are taken into account. Despite the usefulness of the above findings, it is important to further establish which primary factors specifically influence rehabilitation adherence via intention. Therefore, a further aim of this study was to examine whether intention mediated the influence of primary factors including self-efficacy and self-motivation on rehabilitation adherence. The findings revealed that intention fully mediated the effects of perceived severity, learning goal orientation and attitude regarding clinic rehabilitation adherence. In addition, only perceived susceptibility and learning orientation had an indirect effect on attendance via intention. These findings suggest that during the initial stage of rehabilitation in order to develop strong intentions and to subsequently improve patient behavior during clinic rehabilitation, practitioners need to: (a) heighten an individual’s perceptions of perceived severity, (b) create a learning-oriented climate possibly by encouraging the use of goals related to the mastery of a task and (c) encourage favorable attitudes toward rehabilitation. Alternatively, the formation of strong intentions that Rehabilitation adherence in sport may lead to greater rehabilitation attendance may be enhanced through heightening an individual’s perceived risk associated with poor attendance and encouraging learning-oriented behavior. Interestingly, no mediation patterns through intention were evident for any of the primary factors in relation to home-based adherence. As postulated by the APBM self-efficacy, selfmotivation and intention were found to directly predict clinic-based rehabilitation adherence and attendance. These findings are in line with recent studies investigating rehabilitation adherence (Brewer et al., 2000b, 2003a). However, contrary to the APBM these findings did not apply to homebased rehabilitation adherence. A possible reason for this may be the self-reported nature of home-based adherence used, which may have been prone to bias/ distortion and subsequently may have reduced the accuracy of home rehabilitation data. Future research may wish to use more objective measures of home-based adherence. Several practical implications arise from the above findings to improve attendance and clinic rehabilitation adherence. First, practitioners may need to improve an individual’s sense of self-efficacy and facilitate self-motivated behavior. Second, it is important that practitioners help individuals to act on their rehabilitation intentions by possibly developing action plans. Examination of secondary factors identified by the APBM revealed that coping ability, social support and treatment efficacy predicted clinic/home-based adherence and attendance. Specifically, palliative coping was inversely related to all three indices of adherence, whereas distraction coping was predictive of clinic and home-based adherence. The notion that palliative coping exerts a negative influence on clinic and home rehabilitation adherence is consistent with previous research (Udry, 1997). For optimal rehabilitation adherence, such maladaptive coping strategies would need to be discouraged in favor of more adaptive coping strategies. The findings from the present study suggest that distraction coping strategies that use actions and cognitions that are aimed at avoiding pre-occupation with the injury (e.g. performing rehabilitation exercises with a partner or listening to music) may be more appropriate. According to Udry (1997), the type of social support received during rehabilitation plays an important role in facilitating adherence. As such, the present study used a multidimensional measure of social support. The findings indicated that task appreciation (physiotherapist) and emotional support (friends) to be the most predictive of both clinic and home-based rehabilitation. Only personal assistance (family) significantly predicted attendance. These findings have been replicated by qualitative (Johnston & Carroll, 1998) and quantitative studies (Fisher et al., 1988; Duda et al., 1989). Notably, listening support provided by teammates was not influential on any measure of adherence. A possible reason for this may relate to the level of sport participation; indeed, the vast majority of participants in this study were recreational athletes. Possibly those who compete at elite/sub elite level may form more in-depth relationships with teammates and as such require their support. Despite some positive findings from this study, it is not known what type of social support is preferred at different stages during rehabilitation to promote effective adherence. Therefore, it is recommended that future research should focus on temporal aspects of social support in relation to rehabilitation adherence. Complementing the findings obtained by Brewer et al. (2003a), belief in the efficacy of treatment significantly predicted clinic rehabilitation adherence and attendance. Thus, it may be beneficial for practitioners to enhance individuals’ perceptions regarding the effectiveness of their sport injury rehabilitation program. This may take the form of practitioners yielding the benefits of treatment in order to enhance rehabilitation adherence. In addition to this, Spetch and Kolt (2001) ascertain that practitioners should ensure that rehabilitation programs are personalized to suit the individual’s unique characteristics and circumstances to promote favorable beliefs regarding treatment. Finally, habit was found to predict both clinic and home rehabilitation adherence significantly. This finding is in line with the exercise adherence literature, which suggests that involvement in volitional behaviors, such as rehabilitation exercises, entails both conscious and automatic influences (Hagger et al., 2002). Further to this, the quantitative findings of Carroll and Whyte (2003) found past behavior to be a significant predictor of clinic rehabilitation adherence among patients of chronic back pain. In the context of the APBM, the current findings suggest that in order to evoke habitual behavior it is important that behavior is performed repeatedly under identical or highly similar situations in the presence of a variety of and vivid situational cues. Despite the present findings, some key limitations warrant mention. First, although the retrospective time lag between completion of secondary factors and measures of adherence was minimal, secondary factors were measured retrospectively and consequently limit the conclusions drawn about their ability to predict adherence. Furthermore, secondary factors entered into the regression analysis for each adherence index, marginally exceeded the recommended participant to variable ratio of 10:1 recommended by Thomas et al. (2005) and as such, this may have led to spuriously high correlations. However, the difficulty of obtaining a large homogenous 807 Levy et al. sample with regard to injury type, as recommended by Brewer (1998), to satisfy the participant to variable ratio must be noted. Second, it is important to note that the findings from this study are correlational and therefore do not indicate causation. To fully evaluate the causal contribution of primary and secondary factors, experimental research is required in which APBM parameters are manipulated and the effects on adherence are evaluated. Third, despite the precedent for use of single-item measures of attitude (Ajzen, 2002) and intention (Chatzisarantis et al., 2005), these measures can be marred by measurement error. Finally, despite the virtues of using a homogenous sample in terms of injury type (Brewer, 1998), additional inquiry with different types of injuries and rehabilitation protocols is needed to assess the generalizability of the current findings. Perspectives The implications from this study revealed that strategies that focus on influencing threat appraisals, developing favorable attitudes and creating a learning-oriented approach to rehabilitation may aid the development of positive intentions, which can subsequently influence clinic rehabilitation adherence in the adoption phase of rehabilitation. Furthermore, to maintain clinic rehabilitation behavior, it would be beneficial for practitioners to develop an individual’s sense of mastery and ability to handle difficult situations that may arise during rehabilitation. Alongside this, demonstrating an appreciation for what their patients do during rehabilitation may also aid rehabilitation adherence. Emotional support would be better suited to those individuals whom the patient has a close relationship with. Further to this, adaptive coping strategies should be encouraged, possibly in the form of music, exercising in a small group or through the use of a personal rehabilitation trainer. Finally, aiding individuals establish routines through effective lifestyle management that helps accommodate rehabilitation into their everyday life may aid habitual behavior and subsequently aid adherence. Despite the positive findings, however, it is important not to narrow the conceptual field toward the APBM. Indeed, some variance in predicting rehabilitation adherence was unexplained by the APBM. Therefore, future studies would need to utilize an array of theoretical underpinnings to understand the complex nature of rehabilitation adherence in sport. Key words: rehabilitation, adherence, psycho-social. References Ajzen I. The theory of planned behavior. Organ Behav Hum Dec 1991: 50: 179– 211. Ajzen I. Attitudes. In: FernandezBallesteros R, ed. Encyclopaedia of psychological assessment. 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