Brain Injury, July 2011; 25(7–8): 698–706

ORIGINAL ARTICLE

Injury severity, age and pre-injury exercise history predictadherence to a home-based exercise programme in adults withtraumatic brain injury

LEANNE M. HASSETT1, ROBYN L. TATE2, ANNE M. MOSELEY3, &LAUREN E. GILLETT1

1Brain Injury Rehabilitation Unit, Liverpool Hospital, Sydney, Australia, 2Rehabilitation Studies Unit, Sydney School

of Medicine, The University of Sydney, Australia, and 3The George Institute for Global Health, Sydney, Australia

(Received 7 September 2010; revised 21 February 2011; accepted 29 March 2011)

AbstractPurpose: To explore factors that may influence exercise adherence in adults with traumatic brain injury (TBI) within theInternational Classification of Functioning, Disability and Health (ICF) theoretical model.Participants: Thirty participants with TBI who had been randomized to a home-based exercise programme in a recentlyconducted randomized controlled trial.Methods: Impairments in body functions, environmental factors and personal factors were explored as predictors for exerciseadherence. Significant variables were entered into binary logistic regression analyses to determine their combined power topredict exercise adherence.Results: Greater injury severity, older age and a pre-injury exercise history of walking or jogging positively influenced exerciseadherence. As a combined set the three predictor variables accurately classified 82% of participants as adherent or non-adherent and were able to explain 49% of the variance (sensitivity¼ 67%; specificity¼ 89%).Conclusion: These results demonstrate people with severe injuries are able to exercise independently and suggest thatin order to maximize adherence to an exercise programme, clinicians need to consider exercise history when prescribingthe type of exercise. The results also provide factors within the ICF theoretical model to investigate in a large-scale studyof exercise adherence after TBI.

Keywords: Exercise, brain injuries, physical therapy (specialty), patient compliance

Introduction

On discharge from hospital, people who sustain asevere traumatic brain injury (TBI) are oftenextremely physically deconditioned, primarily asa result of prolonged physical inactivity [1, 2].Cardiorespiratory deconditioning can hinder aspectsof one of the key goals of rehabilitation, reintegrationback into the community, as the individual may haveinsufficient aerobic capacity to initiate or sustainparticipation in work and leisure activities [3]. Forthis reason, prescription of a fitness training pro-gramme is often indicated.

One commonly prescribed fitness training pro-gramme is an individualized home-based exerciseprogramme. Home-based exercise programmes areconvenient, cost-effective and an efficient way toprescribe fitness training in able-bodied and otherclinical populations [4], however this has not beenfully evaluated in people with TBI [5]. Home-basedexercise programmes may be the preferred option forsome people with TBI, but they are often the onlyoption for many people due to limited financialresources to join in community exercise programmes(e.g. a fitness centre-based exercise programme) [6]and due to the paucity of suitable community-based

Correspondence: Leanne Hassett, Senior Physiotherapist/Research Fellow, Brain Injury Rehabilitation Unit, Liverpool Hospital, Locked Bag 7103, LiverpoolBC, NSW 1871, Australia. Tel: þ61-2-9828-5495. Fax: þ61-2-9828-5497. E-mail: leanne.hassett@sswahs.nsw.gov.au

ISSN 0269–9052 print/ISSN 1362–301X online � 2011 Informa UK Ltd.DOI: 10.3109/02699052.2011.579934

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exercise programmes [7]. The feasibility and effec-tiveness of implementing a home-based exerciseprogramme in people with TBI should therefore beinvestigated.

In our recent randomised controlled trial, we com-pared the effectiveness of an unsupervised home-based exercise programme to a supervised fitnesscentre-based exercise programme for adults withTBI when first discharged home from hospital [8].While both exercise programmes were comparablein terms of clinical outcomes, exercise adherence(defined as the degree to which the participantcompleted the prescribed exercise programme) wassignificantly higher for the fitness centre group(average adherence to prescribed sessions was 77%and 44% for the fitness centre and home groups,respectively). It was hypothesized that commoncognitive impairments and psychological changes(e.g. poor memory, diminished drive and depres-sion), in addition to the lack of external structure andorganization of the programme, contributed to thelower adherence in the home group [9, 10]. Thispreliminary analysis indicated that an unsupervisedhome-based exercise programme was not feasible forachieving regular aerobic exercise in people with TBI.

On closer examination of the home-based exercisegroup, however, there was a small proportion ofparticipants who successfully completed the pre-scribed 36 exercise sessions (and even some partic-ipants who exceeded the requirements by exercisingmore frequently and for a longer duration thanprescribed). This finding suggests that an unsuper-vised home-based exercise programme may be asuitable method to prescribe fitness training for asub-group of people with TBI. Because all partici-pants in the home-based group were prescribed thesame exercise programme, the diversity of adherencerates within this group raises the question as towhether there were particular factors that influencedindividual adherence to the programme. The iden-tification of factors to predict exercise adherence inpeople with TBI would allow better matchingof an exercise programme with the needs of theindividual, which may then lead to greater success ofthe programme [7].

Factors influencing exercise adherence have beenexamined in able-bodied and other clinical popula-tions, but this has not been investigated in peoplewith TBI [11]. In able-bodied people, personal andenvironmental factors (and the interaction betweenthese factors) exert an influence on adherence [12].Personal factors that positively influence exerciseadherence include the individual’s sex (male), self-efficacy (the concept that a person feels capableof controlling their own behaviours and attaining

goals) [13], exercise enjoyment and past exerciseprogramme participation [14, 15]. Personal factorsthat negatively influence exercise adherence includethe individual’s age (older) and type of occupation(lower skilled) [14, 15]. Environmental factorsinclude barriers (e.g. the built environment or lackof time) and facilitators (e.g. social support orphysician influence) to exercise participation [15].

In clinical populations similar environmentalfactors as for able-bodied people have been foundto influence exercise adherence, however it has beenreported that external barriers have a greater impact[7, 16]. Arguably, personal factors similarly affectexercise adherence. As well as considering environ-mental and personal factors, it has been suggestedthat understanding the specific challenges to partic-ipating in exercise for a particular clinical populationis essential to understanding exercise adherence[11]. People who have sustained a severe TBI facea great number of challenges to participation inregular exercise due to the number and variety ofsequelae of the injury. Common cognitive andemotional problems such as memory problems,diminished drive and depression have been shownto negatively influence adherence to other rehabili-tation interventions [9, 17] and it is likely that theywill also affect exercise adherence. The physicalimpairment of cardiorespiratory deconditioningmay also negatively influence exercise adherencedue to the increased energy cost for exercise andincreased physiological fatigue [3, 18]. In summary,it is expected that personal factors, environmentalfactors and injury-related factors will all influenceexercise adherence in people with TBI and shouldbe tested as predictor factors to adherence in anexercise programme.

It has been recommended that factors that influ-ence adherence should be investigated within atheoretical model to enable clinicians and research-ers to understand how factors influence adherenceand, therefore, if adherence can be improved [11].The International Classification of Functioning,Disability and Health (ICF) [19], which incorpo-rates the interaction among the health condition,body functioning, activities, participation, environ-mental and personal factors, provides a suitabletheoretical framework. The ICF is a taxonomy of�1500 alphanumeric codes to describe health andhealth-related states. It is based on a biopsychosocialmodel and has two parts, each with two components.Part 1 encompasses the health condition and incor-porates body functions and structures and activitiesand participation. Part 2 encompasses contextualfactors and incorporates environmental factors andpersonal factors. Within the ICF, all of the different

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components are inter-related and as such can influ-ence each other. Prescription of an exercise pro-gramme is classified within the activities andparticipation component. Therefore, factors withinbody functions and structures, environmental factorsand personal factors can theoretically influenceadherence to the activity (i.e. an unsupervisedhome-based exercise programme).

The aim of this study was to explore factors thatmay positively or negatively influence exerciseadherence to an unsupervised home-based exerciseprogramme in adults with TBI when they are firstdischarged home from hospital. Factors that werehypothesized to positively and negatively influenceexercise adherence are presented within the ICFframework in Figure 1.

Methods

Participants

The 30 participants who were recruited into thehome-based group of the randomized controlled trial[8] were included in this analysis. The trial recruitedparticipants from consecutive inpatient dischargesfrom three brain injury rehabilitation units inSydney, Australia between October 2003 andSeptember 2006. The participants had sustainedat least a very severe TBI (measured by a post-traumatic amnesia (PTA) period greater than 1week), had been in hospital for at least 1 month andwere able to walk at a speed exceeding 1 m s�1 (i.e.the minimal speed required for safe communitymobility [20]). Written informed consent was

obtained from each participant. Ethical approvalwas obtained from the Sydney South West AreaHealth Service, Royal Rehabilitation Centre Sydney,Sydney West Area Health Service and TheUniversity of Sydney Human Research EthicsCommittees.

Study design

This study was a secondary exploratory analysis thatstemmed from the diverse adherence results in thehome-based control group of the randomized con-trolled trial. Exercise adherence was calculated bythe number of exercise sessions recorded by theparticipant in the exercise diary as a percentage ofthe total prescribed exercise sessions (36 sessionsover 12-weeks). Twelve out of 30 participants didnot record any exercise sessions, eight out of 30participants recorded 24 or less exercise sessions and10 out of 30 participants recorded more than 24exercise sessions (with three participants recordingmore than 84 exercise sessions). For the purpose ofthis analysis, exercise adherence was viewed as adichotomous outcome. A pre-analysis threshold of>2 exercise sessions per week was determined by theresearch team to be defined as adherent, as it wasdeemed to be a clinically acceptable amount ofexercise per week. Participants were grouped asadherent (>2 exercise sessions recorded per week,n¼10) vs non-adherent (�2 exercise sessionsrecorded per week, n¼ 20). Predictor factorshypothesized to influence exercise adherence werepre-determined before commencing this analysis.Variables representing the predictor factors were

Health condition TBI

Activities and participation:

Unsupervised home-based exercise programme

Body function ŒŒŒŒŒ

Œ

cardiorespiratory fitness −ve memory−ve processing speed−ve executive function−ve depression−ve injury severity−ve

Environmental factors support family and friends +ve services provided +ve

Personal factors older age−ve sex (male)+ve higher occupation skill+ve similar exercise history+ve

Contextual factors

ŒŒ

Figure 1. Factors hypothesized to positively (þve) and negatively (�ve) influence adherence to an unsupervized home-based exerciseprogramme presented within the International Classification of Functioning, Disability and Health (ICF) framework.

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taken from baseline data of the trial and from resultsof routine neuropsychological testing.

Intervention

The home-based exercise programme was basedon guidelines set by the American College of SportsMedicine for people with a brain injury [21].Participants were prescribed the exercise programmebefore discharge from hospital by their treatingphysiotherapist, which is in line with usual care.The programme was to be undertaken indepen-dently at home for three 1-hour sessions per weekfor 12 weeks (36 sessions). Each session included a5-minute warm-up, 20 minutes of strength trainingfor six muscle groups (quadriceps, plantar flexors,abdominals, pectorals, triceps, back extensors)with a dosage for each muscle group of two sets of15 repetitions or three sets of 10 repetitions (180repetitions in total), 30 minutes of continuouscardiorespiratory fitness training set at a symptom-limited, moderate intensity such that they werebreathing hard but able to talk and a 5-minutecool-down. Cardiorespiratory fitness training waspredominantly a walking or jogging type exercise,but could include any exercise using large musclegroups in a rhythmical motion. The home-basedexercise programme was designed specifically for thisproject (although it represented ‘usual care’) andincluded photographs and written instructions. Foreach of the six muscle groups to be strengthened,four-to-six levels of progression were provided and,for the cardiorespiratory fitness training, suggestionsfor how to progress different types of exercise wereprovided (e.g. adding hills or jogging intervals withina walking circuit). The treating physiotherapistdetermined the initial level for each exercise atwhich the participant should commence and dem-onstrated how to progress the exercise difficulty.The participant practiced each exercise so that thetreating physiotherapist could ensure it was beingperformed correctly. Equipment (sandbags forweights; phone books as steps) was provided asnecessary to allow progression of exercises. In linewith current practice, no monitoring of adherencewas carried out during the intervention phase;however, an exercise diary was provided to eachparticipant to enable recording of amount andtype of exercise completed. The physiotherapistexplained how to complete the exercise diary,emphasized the importance of using the diary and,in collaboration with the participant, set 3-monthgoals relating to the intervention and 6-month goalsrelating to return to regular physical activity. Theexercise diary was returned to the Chief Investigatorat the end of intervention assessment (i.e. 12 weeks).

Outcome measures

Predictor factors and variables. Impairments in bodyfunctions as well as environmental and personalfactors were explored as factors hypothesized toinfluence exercise adherence to the prescribed home-based exercise programme.

Body functions. Impairments in cardiorespiratoryfitness and cognition, changes in psychologicalfunctioning and injury severity were explored asfactors to predict exercise adherence within the bodyfunctions component of the ICF. Cardiorespiratoryfitness was measured using the modified 20-metreshuttle test [22] which has been shown to be a valid[23] and highly reliable [22] assessment of fitnessin an adult TBI population. The maximal velocityattained [23] on the modified 20-metre shuttle testfor the baseline assessment of the trial was selectedas the variable to represent cardiorespiratory fitness.

The variables to represent cognitive impairmentswere derived from routine clinical neuropsycholog-ical testing. The neuropsychological testing wasconducted by experienced neuropsychologists aspart of the routine care provided by the three braininjury rehabilitation units. The testing was usuallyconducted prior to discharge home from hospital(i.e. just prior to entry to the trial) and was onaverage 1.8 months post-injury. Data extraction wasconducted by the second author (RLT), who hashad previous experience extracting data in thismanner [24, 25]. Because collection of this data setwas not part of the original trial, ethical approvalwas obtained to access these data at each site. Theneuropsychological tests had been conducted as partof clinical practice and consequently some variationsin the choice of standardized tests occurred andaccount for some missing data. Virtually all partic-ipants had data on the Wechsler Memory Scale III[26], the Wechsler Adult Intelligence Scale III [27]and the Controlled Oral Word Association Test [28]and a selection of sub-tests afforded representationof the characteristic cognitive impairments associ-ated with TBI: memory, processing speed andexecutive functions. The age-scaled scores fromWechsler Memory Scale III and Wechsler AdultIntelligence Scale III sub-tests were taken as vari-ables to represent cognitive impairment (DigitSpan,Delayed Recall of Logical Memory [LogMem2],Delayed Recall of Faces [Faces2], DigitSymbol,Matrix Reasoning [MatrixR] and Similarities), alongwith the raw scores of the Controlled Oral WordAssociation Test.

Psychological functioning was measured usingthe depression sub-scale score of the Depression,Anxiety and Stress Scales [29], which was measuredat entry into the trial. The Depression, Anxiety and

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Stress Scales is a 42-item self-report instrument thatvalidly measures current symptoms of depression,anxiety and stress [30]. The depression sub-scalecontains 14 items, with a score ranging from 0–42and a higher score indicating higher levels ofdepression. Injury severity was also included asa factor to predict exercise adherence and PTAclassification (very severe (1–4 weeks) vs extremelysevere (>4 weeks)) was selected to represent thisfactor.

Environmental factors. The support of family andfriends and health services provided were the envi-ronmental factors hypothesized to influence exerciseadherence. Living arrangements on discharge fromhospital (dichotomized as living with family orfriends vs living alone) was the variable chosen torepresent support of family and friends. The lengthof inpatient rehabilitation, measured in days, wasused as the variable to represent health servicesprovided.

Personal factors. Age, sex, pre-injury occupationand exercise history were selected as personal factorshypothesized to influence exercise adherence. Pre-injury occupation was dichotomized into high skill(professional/managerial, skilled trades, senior cler-ical) vs low skill (sales/junior clericals, semiskilled,unskilled, school students and unemployed).Exercise history consisted of two variables: the typeof exercise completed in the 6 months prior to theinjury and its frequency. The type of exercise historywas dichotomized into whether or not walking/jogging was the primary form of exercise pre-injuryand the frequency was dichotomized into �3 exer-cise sessions per week vs <3 exercise sessionsper week.

Statistical procedures

Kolmogorov-Smirnov tests were conducted on thecontinuous predictor variables to test the normalityof the distribution and the appropriate parametricor non-parametric statistics were conducted.Independent-Samples T-tests were used for nor-mally distributed continuous variables and theMann-Whitney U-test was used for non-normallydistributed continuous variables to determine signif-icant continuous variables that influenced exerciseadherence. Categorical variables were comparedbetween adherent and non-adherent groups usingodds ratios and 95% confidence intervals (95%CI)to determine significant categorical variables thatinfluenced exercise adherence.

A series of bivariate correlations was conductedbetween the outcome variable (adherent grouping)

and the significant predictor variables, usingpoint biserial correlations for sets of continuous/dichotomous variables and contingency coefficientswhen both variables were dichotomous. Correlationswere conducted to ensure significant predictorvariables correlated with the outcome variable(p< 0.05) and to ensure predictor variables werenot highly inter-correlated (r>0.7) to avoid prob-lems with multicollinearity. Correlated significantpredictor variables were entered into a binary logisticregression analysis to test how well the set ofvariables combined as a predictive model for exerciseadherence. The Chi-square value was examinedto determine if the model was significant and theNagelkerke R2 value was used to determinethe amount of variance that was explained by thepredictive model. The overall classification accuracy,the positive and negative predictive powers and thesensitivity and specificity were then examined todetermine the predictive accuracy of the model.

Results

Participants

Participants were predominantly males (87%) intheir mid-30s (M¼ 33 years, SD¼ 12) who hadsustained an extremely severe TBI (mean lengthPTA¼ 38 days, SD¼ 21) from road traffic accidents(43%). Baseline measurements were taken on aver-age 2.3 months (range¼ 1.5–3.4) post-injury.

Predictor variables

Three of the 17 variables tested reached the specifiedsignificant levels for between-group differences andrepresented the ICF components of body functionsand personal factors (see Tables I and II). Withinbody functions, adherers were more likely to beclassified as having an extremely severe injury.Within personal factors, participants classified asadherers were more likely to be older and to havereported walking or jogging as their primary modeof exercise in the 6 months prior to sustainingtheir TBI.

The inter-correlation matrix for the outcome(adherent grouping) and the significant predictorvariables is presented in Table III. The threepredictor variables were significantly correlatedwith the outcome variable. All correlation co-efficients were <0.7 and therefore multicollinearitywas not an issue. The three predictor variables weretherefore included in the logistic regression analyses.

A binary logistic regression analysis was performedon the adherent grouping as outcome and thethree significant predictor variables: PTA classifica-tion, age and exercise history (see Table IV).

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After deletion of three cases with missing values,data from 27 participants were available for theanalysis: nine adherers and 18 non-adherers. Testingthe model against a constant-only model was statis-tically significant, indicating that the predictors, asa set, distinguished between adherers and non-adherers (see Table IV). The amount of varianceexplained by the predictor variables as a set was49%. The sensitivity was 67% and the specificity was89%. The positive predictive power of the modelwas 75%; the negative predictive power was 84%,for an overall classification accuracy of 82%.

Discussion

The main finding of this investigation was thatparticular injury-related and personal factors were

found to influence whether or not a home-basedexercise programme was adhered to in people withTBI. Greater injury severity, being of an olderage and walking or jogging as the primary type ofexercise pre-injury were found to positively influenceexercise adherence. Combining the three variables totest their predictive ability as a set was able to predictwith reasonable accuracy the participants who metthe criterion for clinically meaningful adherence.However, the sample size was smaller than recom-mended for regression analyses [31] and conse-quently the results will need confirmation in aprospective study with a larger cohort.

Self-efficacy and enjoyment of the chosen exercisehave been described as key factors that positivelyinfluence exercise adherence in able-bodied andclinical populations [16, 32] and self-efficacy hasbeen shown to predict physical activity participation

Table I. Predictor variables and between-group comparisons for continuous data for adherent vs non-adherent grouping.

Variable

Group statistic

Between-group comparison, t p-value

Adherers Non-adherers

n M (SD) n M (SD)

Body functions:MST: maximal velocity, m s�1 10 6.8 (1.9) 20 8.0 (1.3) �1.92 0.07WAIS IV: Digitspan 9 9 (4) 15 7 (3) 1.08 0.29WMS III: Logmem2 8 8 (3) 15 8 (2) �0.08 0.94WMS III: Faces2 8 8 (2) 13 9 (2) �0.97 0.35WAIS IV: Digitsymbol 10 5 (3) 15 6 (2) �0.61 0.55WAIS IV: Matrixr 10 11 (3) 15 10 (4) 0.22 0.83WAIS IV: Similarities 9 9 (3) 15 7 (2) 1.49 0.15COWAT 8 27 (14) 13 26 (7) 0.20 0.84DASS depression sub-score* 10 1 (0–2) 20 1 (0–4) �0.02 0.98Environmental factors:Length rehabilitation, days* 10 58 (24–132) 20 35 (18–48) �1.63 0.11Personal factors:Age, years 10 39 (14) 20 30 (9) 2.21 0.04**

MST¼modified 20-meter shuttle test; WAIS¼Wechsler Adult Intelligence Scale; WMS III¼Wechsler Memory Scale;COWAT¼Controlled Oral Word Association Test; DASS¼Depression, Anxiety and Stress Scale. *Descriptive statistics are median(interquartile ranges), between-group comparisons are z-scores. **Variables that reached �0.05 significance level.

Table II. Predictor variables and between-group comparisons for categorical data for adherent vs non-adherentgrouping.

Variable Adherers Non-adherers Odds ratio (95%CI)

Body functions:PTA classification (very severe:extremely severe) 1:9 10:10 9.0 (1.0–84.9)**Environmental factors:Living arrangements (family/friends:alone) 10:0 17:2 0.1 (�0.2–0.3)*Personal factors:Sex (female:male) 2:8 2:18 2.3 (0.3–18.9)Pre-injury occupation (high skill:low skill) 5:5 14:6 2.3 (0.5–11.2)Exercise history:Walk/jog primary exercise (yes:no) 7:2 5:13 9.1 (1.4–59.6)**Frequency (�3� /week: <3� /week) 6:4 12:6 1.3 (0.3–6.6)

PTA¼ post-traumatic amnesia. *Absolute risk reduction (95% confidence interval). **Variables that reached �0.05significance level.

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in people with TBI [33]. In this study, the findingthat pre-injury exercise history positively influencedexercise adherence may be linked to these twoissues. If the individual has previously participatedin similar exercise to that which is prescribed(i.e. walking or jogging) then it is likely that it is anexercise that they previously enjoyed and it is alsolikely that they will feel some confidence that theycan again participate in this type of exercise.A measure of self-efficacy such as the Self-Efficacyfor Exercise Scale [34] should be included in futureprospective trials investigating exercise adherence.

Interestingly, participants who adhered to theexercise programme had sustained a more severeTBI than participants who had not adhered. This isconsistent with another study that investigated exer-cise habits of community-dwelling people with TBIwhich found that participants who were classified asexercisers (participating in aerobic exercise �3 timesper week for the last 6 months) had significantlymore severe injuries than those classified as non-exercisers (participating in aerobic exercise <1 timeper week for the last 6 months) [35]. Collectively,these two studies highlight that individuals withsevere injuries can participate independently inregular exercise.

Contrary to the hypothesis and to findings in able-bodied studies, older age was associated withincreased adherence to the home-based exerciseprogramme. One explanation for this finding is thetype of exercise prescribed (a walking/jogging pro-gramme) for the age of participants in the study andthis is supported by the significant correlation found

between age and exercise history (see Table IV).A number of participants in this study were in earlyadulthood, a time where sports activities are stillthe major form of physical activity undertaken [36].As such, participating in a walking/jogging pro-gramme at home may not have been an enjoyabletype of exercise for younger participants.

Environmental factors were not found to influenceexercise adherence in this study. However, thisfinding may be due to the variables used to representenvironmental factors and the lack of data to enableinclusion of particular environmental factors thathave been previously shown to negatively influenceexercise adherence in other clinical populations(e.g. barriers such as the built and natural environ-ment) [7]. In this investigation, living arrangementswas the variable used to represent social support;however, it is acknowledged that this is an approx-imation of social support—cohabitation does notnecessarily mean one is supported. In future pro-spective studies, specific measures of social supportsuch as the Social Support and Exercise Survey [37]and measures of potential barriers within thelocal environment such as the NeighbourhoodEnvironment Scale [38] are needed to better testthe influence of environmental factors on exerciseadherence in TBI.

The ICF was chosen as the theoretical model toexamine exercise adherence for people with TBI as itwas hypothesized that factors within body functions,the environment and personal factors would interactto influence the activity of a home-based exerciseprogramme. Because of the a posteriori nature of

Table III. Correlation matrix between predictor variables.

1 2 3 4

1. Adherence split –2. Age �0.39* –

n¼ 303. PTA classification 0.36* 0.14 –

n¼ 30 n¼ 304. Walk or jog as primary exercise pre-injury 0.43** �0.47** 0.00 –

n¼ 27 n¼ 27 n¼ 27

*p� 0.05, **p� 0.01, PTA¼ post traumatic amnesia.

Table IV. Predictive modelling using binary logistic regression for adherence grouping.

Model Variables B Wald test p Odds ratio �2 p R2Overall classification

accuracy

1 Age �0.05 0.92 0.34 0.95 11.6 0.01 0.49 82%Walk or jog pre-injury �2.18 3.51 0.06 0.11PTA classification 2.31 2.94 0.09 10.09Constant 2.88 2.76 0.10 17.88

�2¼Chi-square, R2

¼Nagelkerke R2, PTA¼ post-traumatic amnesia. n¼27.

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variable selection for analysis, only an incompletetesting of the model was possible. The ICF didappear, however, to have potential as an effectivetheoretical model for its chosen purpose. Using theICF model, clinicians can understand the impor-tance of the contextual factors (environmental andpersonal) that may be modifiable or non-modifiableto enhance exercise adherence. For example, withinpersonal factors, incorporating the type of exercisethe individual used to participate in pre-injury mayincrease exercise adherence. If the patient did notpreviously exercise, then the clinician could ensurethey have sufficient practice of the prescribed home-based exercise programme within the supportedhospital environment before they are dischargedhome (i.e. increase their self-efficacy).

In terms of the more general issue of improvingadherence to a home-based exercise programme,the lack of supervision has been linked with pooradherence in able-bodied individuals [39]. Onemethod that has been successfully implementedin able-bodied individuals to overcome the lack ofsupervision, but still maintain the convenienceand cost-effectiveness of a home-based exerciseprogramme, is the use of staff initiated telephonecalls [32]. This idea could be utilized for peoplewith TBI to improve exercise adherence. Regularstaff-initiated telephone calls could detect thoseindividuals who were not managing to continuewith regular exercise independently and greatersupport could be provided to keep them exercising.

This study is the first (to the authors’ knowledge)to investigate factors that influence exercise adher-ence in adults with TBI, but it has a number oflimitations. First, as already mentioned, becauseof the small sample size the results of the regressionanalyses will need confirmation. Secondly, adher-ence to the home-based exercise programme wasbased on the participant-completed and returnedexercise diaries and therefore the reliability cannotbe verified, although the quantity of exerciserecorded in the exercise diaries did match subjectivefeedback from participants to the researcher.Additionally, variables available to investigate factorsthat predict exercise adherence were only thosevariables that were collected as part of the random-ized controlled trial and routine clinical neuropsy-chological testing. Because of this limitation, someof the variables chosen to represent the hypothesizedpredictor factors were probably not sensitivemeasures of the factor and no data existed on somefactors that have previously been demonstrated toinfluence exercise adherence. As such, some factorsthat may influence exercise adherence in people withTBI may not have been identified in this study.

In conclusion, age, injury severity and exercisehistory were identified to influence adherence to a

home-based exercise programme in adults after TBI.These results confirm that people with severe inju-ries are able to exercise independently and suggestthat, in order to maximize adherence to an exer-cise programme, clinicians need to consider exercisehistory when prescribing the type of exercise.Additionally, the ICF appears to be an appropriateframework to investigate exercise adherence inclinical populations. The results of this study requireconfirmation in a prospective study with adequatesample size for the number of variables to be tested.

Acknowledgements

The authors would like to thank the participants fortheir involvement in this study, and the support ofthe three participating Brain Injury RehabilitationUnits at Liverpool Hospital, Westmead Hospital andthe Royal Rehabilitation Centre Sydney, Australia.

Declaration of Interest: This research was fundedby a grant from the Motor Accidents Authorityof New South Wales, Australia; and a scholarshipfrom the Menzies Foundation to the first author.

References

1. Sullivan SJ, Richer E, Laurent F. The role of and possibilitiesfor physical conditioning programmes in the rehabilitationof traumatically brain-injured persons. Brain Injury 1990;4:407–14.

2. Becker E, Bar-Or O, Mendelson L, Najenson T. Pulmonaryfunctions and responses to exercise of patients following craniocerebral injury. Scandinavian Journal of RehabilitationMedicine 1978;10:47–50.

3. Jankowski LW, Sullivan SJ. Aerobic and neuromusculartraining: Effect on the capacity, efficiency, and fatigability ofpatients with traumatic brain injuries. Archives of PhysicalMedicine & Rehabilitation 1990;71:500–504.

4. Romberg A, Virtanen A, Ruutiainen J, Aunola S, Karppi SL,Vaara M, Surakka J, Pohjolainen T, Seppanen A. Effects of a6-month exercise program on patients with multiple sclerosis:A randomized study. Neurology 2004;63:2034–2038.

5. Hassett LM, Moseley AM, Tate R, Harmer A. Fitness trainingfor cardiorespiratory conditioning after traumatic brain injury.Cochrane Database of Systematic Reviews 2008; Issue 2. Art.No.: CD006123.

6. Rimmer JH. Health promotion for people with disabilities:The emerging paradigm shift from disability prevention toprevention of secondary conditions. Physical Therapy1999;79:495–502.

7. Rimmer JH, Riley B, Wang E, Rauworth A, Jurkowski J.Physical activity participation among persons with disabilities:Barriers and facilitators. American Journal of PreventiveMedicine 2004;26:419–425.

8. Hassett LM, Moseley AM, Tate RL, Harmer AR,Fairbairn TJ, Leung J. Efficacy of a fitness centre-basedexercise programme compared with a home-based exerciseprogramme in traumatic brain injury: A randomized controlledtrial. Journal of Rehabilitation Medicine 2009;41:247–255.

Exercise adherence in TBI 705

Bra

in I

nj D

ownl

oade

d fr

om in

form

ahea

lthca

re.c

om b

y M

ichi

gan

Uni

vers

ity o

n 10

/29/

14Fo

r pe

rson

al u

se o

nly.

9. Zencius AH, Lane I, Wesolowski MD. Assessing and treatingnon-compliance in brain-injured clients. Brain Injury 1991;5:369–374.

10. Broek van den, MD. Why does neurorehabilitation fail?Journal of Head Trauma Rehabilitation 2005;20:464–473.

11. Mutrie N. Exercise adherence and clinical populations. In:Bull S, editor. Adherence issues in sport and exercise.Chichester: John Wiley & Sons Ltd; 1999. pp 75–109.

12. Ready AE, Naimark BJ, Tate R, Boreskie SL. Fitness centremembership is related to healthy behaviours. Journal ofSports Medicine & Physical Fitness 2005;45:199–207.

13. Forkan R, Pumper B, Smyth N, Wirkkala H, Ciol MA,Shumway-Cook A. Exercise adherence following physicaltherapy intervention in older adults with impaired balance.Physical Therapy 2006;86:401–410.

14. King AC. Clinical and community interventions to promoteand support physical activity participation. In: Dishman RK,editor. Advances in exercise adherence. Champaign, IL:Human Kinetics; 1994. pp 183–212.

15. Trost SG, Owen N, Bauman AE, Sallis JF, Brown W.Correlates of adults’ participation in physical activity: Reviewand update. Medicine & Science in Sports & Exercise2002;34:1996–2001.

16. Kinne S, Patrick DL, Maher EJ. Correlates of exercisemaintenance among people with mobility impairments.Disability Rehabilitation 1999;21:15–22.

17. Watts R, Perlesz A. Psychosocial outcome risk indicator:Predicting psychosocial outcome following traumatic braininjury. Brain Injury 1999;13:113–124.

18. Rimmer JH, Rubin SS, Braddock D. Barriers to exercise inAfrican American women with physical disabilities. Archivesof Physical Medicine & Rehabilitation 2000;81:182–188.

19. World Health Organisation (WHO). International classifica-tion of functioning, disability and health. Geneva: WorldHealth Organisation; 2001.

20. Finlay O. Exercise training and walking speeds in elderlywomen following hip surgery: ‘‘Beating the little green man’’.Physiotherapy 1993;79:845–849.

21. Palmer-McLean K, Harbst K. Ch: 36 Stroke and braininjury. In: Durstine J, G Moore, editors. ACSM’s exercisemanagement for persons with chronic diseases and disabil-ities. 2nd ed. Champaign, IL: Human Kinetics; 2003.pp 238–246.

22. Vitale AE, Jankowski LW, Sullivan SJ. Reliability of a walk/run test to estimate aerobic capacity in a brain-injuredpopulation. Brain Injury 1997;11:67–76.

23. Hassett LM, Harmer AR, Moseley AM, Mackey MG.Validity of the modified 20-metre shuttle test: Assessmentof cardiorespiratory fitness in people who have sustaineda traumatic brain injury. Brain Injury 2007;21:1069–1077.

24. Tate R, Hodgkinson A, Veerabangsa A, Maggiotto S.Measuring psychosocial recovery after traumatic brain

injury: Psychometric properties of a new scale. Journal ofHead Trauma Rehabilitation 1999;14:543–557.

25. Simpson G, Tate R, Ferry K, Hodgkinson A, Blaszczynski A.Social, neuroradiologic, medical, and neuropsychologiccorrelates of sexually aberrant behavior after traumaticbrain injury: A controlled study. Journal of Head TraumaRehabilitation 2001;16:556–572.

26. Wechsler D. Wechsler Memory Scale – Revised Manual. SanAntonio, TX: The Psychological Corporation; 1987.

27. Wechsler D. Wechsler Adult Intelligence Scale – RevisedManual. San Antonia, TX: Psychology Corporation; 1981.

28. Benton A, Hamsher K. Multilingual aphasia examination.Iowa City, IA, University of Iowa; 1978.

29. Lovibond SH, Lovibond PF. Manual for the Depression,Anxiety and Stress Scales. Sydney: Psychological Foundationof Australia; 1996.

30. Brown TA, Chorpita BF, Korotitsch W, Barlow DH.Psychometric properties of the Depression Anxiety StressScales (DASS) in clinical samples. Behavioural ResearchTherapy 1997;35:79–89.

31. Tabachnick BG, Fidell LS. Using multivariate statistics.New York: Harper Collins; 1996.

32. King AC, Taylor CB, Haskell WL, Debusk RF. Strategiesfor increasing early adherence to and long-term maintenanceof home-based exercise training in healthy middle-agedmen and women. American Journal of Cardiology 1988;61:628–632.

33. Reavenall S, Blake H. Determinants of physical activityparticipation following traumatic brain injury. InternationalJournal of Therapy and Rehabilitation 2010;17:360–367.

34. Resnick B, Jenkins LS. Testing the reliability and validity ofthe self-efficacy for exercise scale. Nursing Research 2000;49:154–159.

35. Gordon WA, Sliwinski M, Echo J, McLoughlin M,Sheerer MS, Meili TE. The benefits of exercise in individualswith traumatic brain injury: A retrospective study. Journal ofHead Trauma Rehabilitation 1998;13:58–67.

36. Malina RM. Tracking of physical activity and physical fitnessacross the lifespan. Research Quarterly for Exercise and Sport1996;67:48–57.

37. Sallis JF, Grossman RM, Pinski RB, Patterson TL,Nader PR. The development of scales to measure socialsupport for diet and exercise behaviors. Preventive Medicine1987;16:825–836.

38. Sallis JF, Johnson MF, Calfas KJ, Caparosa S, Nichols JF.Assessing perceived physical environmental variables thatmay influence physical activity. Research Quarterly forExercise and Sport 1997;68:345–351.

39. King AC, Haskell WL, Taylor CB, Kraemer HC,DeBusk RF. Group- vs home-based exercise training inhealthy older men and women. A community-based clinicaltrial. Journal of the American Medical Association 1991;266:1535–1542.

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