| | Perceived Control is a Concurrent Predictor of Activity Limitations in Patients With Chronic Idiopathic Axonal PolyneuropathyAbstract Schröder C, Johnston M, Teunissen L, Notermans N, Helders P, van Meeteren N. Perceived control is a concurrent predictor of activity limitations in patients with chronic idiopathic axonal polyneuropathy. ObjectivesTo investigate (1) whether control perceptions (person’s perception of ease or difficulty of performing behavior) and emotions contribute to activity limitations and if so (2) whether these variables mediate the relation between impairment and activity limitations in patients with chronic idiopathic axonal polyneuropathy (CIAP). DesignCross-sectional study. SettingOutpatient clinics of a university medical center. ParticipantsFifty-six patients diagnosed with CIAP. InterventionsNot applicable. Main Outcome MeasuresControl perceptions about performing activities (questionnaire based on the theory of planned behavior), emotions (Hospital Anxiety and Depression Scale), activity limitations (performance: Shuttle Walk Test [SWT]; self-report: Medical Outcomes Study 36-Item Short-Form Health Survey [SF-36] physical functioning subscale, self-reported ability to walk), and physical impairments (muscle strength, sensory function). ResultsControl perceptions significantly (P<.01) correlated with all measures of activity limitations (r range, .58−.69). Hierarchical multiple regression analyses showed that perceived control explained 9% of the variance in the SWT (β=.34, P<.01), 12% in the SF-36 (β=.40, P<.01), and 24% in ability to walk (β=.54, P<.01). In all measures of activity limitations, perceived control significantly mediated the effect of impairment. ConclusionsPerceived control explained and mediated variance in activity limitations, whereas emotions did not. This suggests that increasing patients’ perceptions of control might enhance performance of activities, even without changes in impairment. THE PREVALENCE OF chronic polyneuropathy in the general population is estimated at 2.4 to 8 per 100,000.1 In 10% to 15%, a cause cannot be found after extensive evaluation.2, 3, 4 This polyneuropathy is now referred to as chronic idiopathic axonal polyneuropathy (CIAP).5 Patients with polyneuropathy suffer from sensory impairments, pain, and weakness, which affect their daily functioning. Although progression is slow and initial symptoms are mild, patients with CIAP report more activity limitations compared with a reference population of healthy adults.1, 6 Rehabilitation or therapeutic exercises are recommended by several experts7, 8 to preserve functional health status, although effects and determinants of this kind of treatment have not been investigated yet. Previous studies9, 10 on activity limitations in patients with polyneuropathy have focused primarily on physical factors, but psychologic, social, and environmental factors are less well investigated. Besides age and disease duration, muscle strength has been found to be the strongest explanatory variable in activity limitations; however, it cannot fully explain the individual differences in groups of patients with polyneuropathy.9, 10 Rehabilitation therapists are trained to improve the performance of activities by predominantly addressing factors related to pathophysiology such as impaired muscle strength. However, most clinicians also acknowledge that psychosocial factors have a profound effect on the performance of activities. Therefore, it might be appropriate to investigate psychologic factors.9 A model for exploring consequences of a health condition is the International Classification of Functioning, Disability and Health (ICF),11 in which activity limitation is defined as “the difficulties an individual may have in the execution of a task or action”11(p10) and can be seen as behavior per se.12 Psychologic factors that have been shown to explain variance in activity limitations are emotions, especially anxiety and depression,13 and perceptions of control.14 However, there is evidence that effects of emotional state are possibly mediated by perceptions of control.15 According to the theory of planned behavior, perceived behavioral control—a person’s perception of the ease or difficulty of performing behavior—is an important factor in predicting behavior, for example, performing daily activities. Perceived control has predicted activity limitations in patients with other health conditions including stroke, osteoarthritis, chronic pain, and hip fracture.14, 16, 17 In this study we used the model suggested by Johnston,12 which incorporates a psychologic theory—the theory of planned behavior—into the ICF. This integrated model proposes that impairments may affect activity limitations directly and indirectly via perceptions, which can be regarded as process variables. For example, a person is more likely to walk up stairs when he/she (1) intends to and (2) believes that it is possible or easy to do so. An advantage of this integrated model is that it allows the possibility that patients may benefit from treatment interventions, which reduce their activity limitations by changing perceptions, without reducing the impairment. This is especially valuable in the CIAP population: because the cause of polyneuropathy is unknown, only symptomatic treatment is available.18 The aim of the current study was to examine the value of psychologic variables, namely, perceptions defined by the theory of planned behavior (intention, perceived behavioral control) in explaining variance in activity limitations. This study investigated the following research questions: (1) Do theory of planned behavior perceptions (intention, perceived behavioral control) add to emotional and impairment variables in explaining variance in activity limitations, observed and self-reported, in patients with CIAP? (2) Do psychologic variables mediate the relation between impairment and activity limitations in patients with CIAP? Methods  Design A cross-sectional design was used. Patients with CIAP completed measures of theory of planned behavior perceptions, emotions, impairment, and activity limitations. Participants Seventy-five consecutive patients who had been diagnosed with CIAP and were registered in the outpatient clinics of the University Medical Centre (UMC) Utrecht were invited to participate in the project when they came for their annual check-ups. The diagnosis of CIAP is made after exclusion of other causes of axonal polyneuropathy.2, 5 The search includes a thorough screening of the metabolism for renal insufficiency and andocrinopathy. Vitamin deficiency must also be excluded. Exposure to toxic agents and hereditary causes can be suspected at careful history taking and neurologic examination. Patients in whom no cause can be found share common clinical features.2 We have denominated this syndrome as chronic idiopathic axonal polyenruopathy.2 All patients fulfilled the electrophysiologic criteria of axonal polyneuropathy. Fifty-six patients agreed to have their data anonymously entered into the database, a response rate of 75% (table 1). Patients were mildly to moderately affected as indicated by the Modified Rankin Scale (MRS).19 The grades of this disability scale range from 0 (no symptoms at all) to 5 (severe disability, bedridden, incontinent, and requiring constant nursing care and attention). The Rankin scores for these patients varied between 1 (no significant disability despite symptoms, able to perform usual duties and activities; n=19), 2 (slight disability, unable to perform all previous activities but able to look after own affairs; n=30), and 3 (moderate disability, requiring some help but able to walk without assistance; n=7). No patients had MRS of 4 and 5. The ethics committee of the UMC Utrecht confirmed that no formal approval for the use of anonymous databases is needed (http://www.fmwv.nl). Dependent Variables: Activity Limitation Shuttle Walk Test Performance of activity was assessed by the (incremental) Shuttle Walk Test (SWT).20, 21 Each participant was asked to walk up and down a 10-m course, with an increasing walking speed dictated by a timed audio signal that sounded at the end of a shuttle when the participant should be making the turn. To give the participants more time to adapt to the physiologic demand of the test, which enables them to give their maximal performance on the test, we used a protocol with 7 speed levels. The initial walking speed was 3.0km/h and increased every 2 minutes by 0.5km/h, giving a maximal walking speed of 7.0km/h. At the end of each level the participants were told to go a little bit faster; no further encouragement was given during the test. The end of the test was determined by each patient if he/she became unable to maintain the required speed or by the instructor if a participant failed to complete a 10-m course in the time allowed. The distance traveled was recorded in number of 10-m courses achieved, with higher numbers indicating better performance on the test. Medical Outcomes Study 36-Item Short-Form Health Survey physical functioning subscale To assess the self-reported activity limitations we used the Medical Outcomes Study (MOS) 36-Item Short-Form Health Survey (SF-36), which is a general quality-of-life questionnaire and is equivalent to the Dutch version of the MOS SF-36 questionnaire.22, 23 To use a measure of activity limitations compatible with the definition by the ICF11 we used the subscale physical functioning. Based on a study of Pollard et al,24 we selected 7 out of the original 10 items that are pure measures of activity limitation. The 3 excluded items were not only referring to the domain activity (limitation) but also to the domain participation (restrictions)24 and were therefore excluded from further analysis. The 7 item scores were coded, summed, and transformed into a scale ranging from 0 to 100, where 100 is the best possible rating. The Cronbach α for the internal consistency of this modified physical functioning subscale in this population was .86. Self-reported ability to walk Participants were asked to estimate the time they were able to walk using the following question: For how long are you able to walk without taking a rest? Time was reported in minutes. Independent Variables: Impairment Muscle strength The maximal isometric strength of the muscles of the lower extremity was measured bilaterally using a hand-held dynamometer. Muscle strength was measured for the hip (flexion, abduction), the knee (flexion, extension), and the ankle (dorsiflexion) according to Andrews et al.25 All the scores were summed, with higher scores indicating better muscle strength. The scale had a good internal consistency (Cronbach α=.93). Sensory function Bilaterally, sensory function was graded following a standardized protocol.26 The touch and pinprick sense: normal, 4; distal to ankle abnormal, 3; distal half leg abnormal, 2; distal to knee abnormal, 1; and distal to groin abnormal, 0. Vibration sense: tuning fork perception (128Hz) on middle hallux, 4; medial malleolus, 3; knee, 2; iliac crest, 1; and no perception, 0. Joint position sense of hallux: normal, 2; diminished, 1; and absent, 0. Summations of all modalities lead to a total score with a maximum of 28, with higher numbers indicating better (normal) sensory function.26 The internal consistency of this scale was good (Cronbach α=.87). Pain To assess pain we used the present pain intensity (PPI) from the Dutch version of the McGill Pain Questionnaire (MPQ).27 This is a pain-intensity visual analog scale (VAS). A horizontal 10-cm line was used for the VAS anchored with no pain (0) and worst pain (100). Participants marked their level of pain “right now” on this line with a slash. Emotional Variables: Anxiety and Depression The Hospital Anxiety and Depression Scale (HADS) is a brief measure of mood designed to avoid confounding of mood with somatic symptoms. Anxiety and depression are each measured on 7 four-point scales giving scores ranging from 0 to 21.28 Higher scores indicate greater anxiety or depression. In this study, the Dutch version of the HADS was used. In a population of general medical patients, the internal consistency of the 2 subscales as assessed by the Cronbach α, was .84 for both the anxiety and depression scales.29, 30 In this population of patients with CIAP, the Cronbach α of the depression scale was .63 and of the anxiety scale .57. Theory of Planned Behavior: Perceived Behavioral Control and Intention Perceived behavioral control and intention were assessed using a questionnaire developed for this study using instructions from Ajzen31 and Conner and Sparks.32 To tailor the measure to each person and to gauge only relevant activities, we used a semistructured interview based on the McMaster-Toronto Arthritis Patient Function Preference Questionnaire (MACTAR).33 The MACTAR interview was originally developed for arthritis patients but has been useful in identifying target activities in patients with hemophilia.34 First, participants were asked the following question: Please tell me which activities are affected by your CIAP. Second, the rank order of the activities listed was elicited by using the question, Which of these activities would you most like to be able to do? The activity that was ranked as most important was used in the questionnaire measuring perceived behavioral control and intention to perform this target activity. Fifty-seven percent (n=32) of the CIAP patients identified walking as the most important activity. For example, for “walking for 30 minutes,” the intention to perform the target activity was assessed by 2 items (Do you intend to—walk for 30 minutes—in the next half year? and Do you expect to—walk for 30 minutes—in next half year?). Answers were scored on two 5-point rating scales, respectively: 1 (definitely not) to 5 (definitely yes) and 1 (very unlikely) to 5 (very likely). The mean of the 2 intention items was calculated and represents a generalized intention to perform the target activity, with higher scores indicating higher intentions. The correlation between these 2 items was r equal to .46 (P<.001). Perceived behavioral control was assessed by asking participants to rate their control over performing their target activity (eg, walking for 30min). The perceived control scale consisted of 6 items, using 5-point rating scales. Scores were summed to give a total score (range, 6−30), with higher scores indicating more perceived behavioral control over the target activity. This scale had good internal consistency with the Cronbach α of .86. Statistical Analysis Hierarchical multiple regression analysis was conducted on the 3 measures of activity limitation.35 First, correlation analyses (Pearson) were performed between each of the independent and the dependent variables. Second, the independent variables that were significantly associated with each of the dependent variables were entered into a hierarchical multiple linear regression model. The .01 level of significance was used to restrict the number of variables, given the sample size. In the first step demographic variables were entered, followed by the impairment measure(s) in the second step. In the third step the emotional variables were entered, and in the fourth step theory of planned behavior perceptions entered the model. Residual analyses were performed to search for violations of necessary assumptions in multiple regression.35 Although it is difficult to disentangle the separate effects of impairment and control perceptions, mediation analysis to get insight in how impairment is having an effect on activity limitations was performed with the method of Baron and Kenny.36 Three regression equations as outlined by Baron and Kenny were computed. In the first equation, the psychologic variable was regressed on the impairment measure most highly correlated with the activity limitation indices. In the second equation, activity limitations were regressed on impairment, and in the third equation, activity limitations were regressed on both impairment and the psychologic variable. The Sobel test was used to examine whether β weight for impairment was significantly reduced in the third equation.4 Post hoc analysis To explore if activity limitation items (SF-36 physical functioning subscale) and perceived behavioral control items were measuring different constructs, a principal component analysis with varimax rotation was conducted. All analyses were performed using SPSSa for Windows. Results Sample Characteristics The descriptive statistics on all the variables of the 56 participants are shown in table 1. These participants had both impaired sensory function and muscle strength of the lower extremity compared with healthy adults. They reported pain; the highest level of reported pain was 70 on a scale of 0 to 100. Average levels of anxiety and depression were below clinical cutoff scores. The levels of perceived behavioral control over performing the activity varied from 6 to 30; the average level of perceived behavioral control ± standard deviation (SD) was 16.29±6.94. The average level of intention to perform the activity was 3.97±0.72, with a maximum score of 5. Bivariate Correlations All the measures of activity limitation were significantly (P≤.01) and highly correlated (range, .73−.81) with each other. Perceived behavioral control was significantly (at the .01 level) associated with the performance of activity (.58) and self-reported activity limitations (range, .62−.69), although correlations with the self-reported activity limitations were slightly higher (table 2). Intention was not associated with any of the measures of activity limitations. Depression correlated only with the SF-36 physical functioning subscale (−.30). Age and disease duration, but not sex, showed significant (at the .01 level) correlations with activity limitations. Explaining Variance in Activity Limitation: Hierarchical Multiple Regression Self-reported activity limitations The variables muscle strength and perceived behavioral control added significantly to the amount of explained variance. Muscle strength explained 31% of the variance in the SF-36 physical functioning subscale and 33% in self-reported ability to walk; perceived behavioral control added a further 12% and 24%, respectively. For all 3 measures of activity limitation the same analyses were repeated including variables correlated at the .05 level, which gives more variables and therefore is unstable. The same sets of variables were significant in the final regression equation. Furthermore, subgroup analyses were performed on the data of participants who indicated problems with mobility (walking, running, stair climbing) to be more compatible with the activities that were assessed. Although the number of participants dropped (n=35), which may have affected the power, we found the same pattern of significant results. In the SWT, muscle strength explained 18% and perceived behavioral control an additional 10% of the variance. In the SF-36 physical functioning, muscle strength explained 33% and perceived behavioral control an additional 22%; in the self-reported time muscle strength explained 21% and perceived behavioral control an additional 25%. To investigate further how the influence of impairment and perceived behavioral control affects activity limitations, mediation analyses were performed. Perceived Behavioral Control as a Mediator Between Impairment and Activity Limitations Correlations between muscle strength, perceived behavioral control, and all 3 measures of activity limitations were significant. Therefore, it was valid to test if perceived behavioral control mediated between impairment and activity limitation. The 3 regression equations to test mediation were computed for all 3 measures of activity limitation. In regression equation 1 (the same for all 3 measures), muscle strength had a significant effect on perceived behavioral control (β=.44, P<.01), accounting for 18% of the variance. For the SWT, in regression equation 2, muscle strength had a significant effect on performance of activity (β=.57, P<.01), accounting for 32% of the variance. In regression equation 3, muscle strength (β=.40, P<.01) and perceived behavioral control (β=.41, P<.01) entered together had a significant effect on performance of activity, accounting together for 45% of the variance. The reduction in the β weight for impairment from .57 to .40 was significant. When using the SF-36 physical functioning subscale, in regression equation 2, muscle strength (β=.55, P<.01) had a significant effect on self-reported activity limitations, accounting for 28% of the variance; in regression equation 3, muscle strength (β=.35, P<.01) and perceived behavioral control (β=.47, P<.01) entered together had a significant effect on activity limitation, accounting together for 47% of the variance. The reduction in the β weight for impairment from .55 to .35 was significant. For the self-reported ability to walk, in regression equation 2, muscle strength (β=.57, P<.01) had a significant effect on self-reported activity limitation, accounting for 31% of the variance. In regression equation 3 muscle strength (β=.33, P<.01) and perceived behavioral control (β=.54, P<.01) had a significant effect on self-reported activity limitation, accounting together for 54% of the variance. The reduction in the β weight for impairment from .57 to .33 was significant. In all 3 measures of activity limitation, the Sobel test showed that the β weight for impairment was significantly reduced while remaining significant; this indicates that perceived behavioral control partially mediates the relation between muscle strength and activity limitations. In addition, variance in activity limitations was explained by muscle strength that was not mediated by perceived behavioral control (see table 3). Post Hoc Analysis A principal components analysis was performed to determine if the perceived behavioral control items were distinguishable from items measuring self-reported activity limitations (SF-36 physical functioning). This analysis showed the presence of 3 factors. All the items measuring perceived behavioral control loaded to 1 separate factor (eigenvalue, 5.65). The SF-36 items, however, loaded on 2 separate factors (table 4). Factor 2 (eigenvalue, 1.82) refers to activities involving bending, climbing, and vertical movements, and factor 3 (eigenvalue, 1.28) refers to walking and horizontal movements. | | |  | Items | Factor 1 | Factor 2 | Factor 3 | |
|---|
| PBC | SF-36 Vertical Movements | SF-36 Horizontal Movements | |
|---|
| SF-36 physical functioning items | | | | | |  3d. Climbing several flights of stairs | .32 | .66 | .37 | | | 3e. Climbing one flight of stairs | .22 | .77 | .32 | | | 3f. Bending, kneeling, or stooping | .09 | .77 | .22 | | | 3j. Bathing or dressing yourself | .13 | .79 | .05 | | | 3g. Walking >1km | .19 | .25 | .78 | | | 3h. Walking 0.5km | .18 | .25 | .89 | | | 3i. Walking 100m | .15 | .17 | .84 | | | PBC items | | | | | | 1. How much control do you think you have over … | .82 | .08 | .10 | | | 2. How confident are you that you can … | .83 | .17 | .15 | | | 3. How much do you think you will have influence on … | .71 | .32 | −.01 | | | 4. I would like to . . . but I don’t know if I can … | .70 | −.08 | .30 | | | 5. If I wanted, it would be easy for me to … | .66 | .27 | .22 | | | 6. How difficult will it be for you to … | .66 | .24 | .16 | | | Percentage of variance explained | 43.49 | 14.02 | 9.82 | | | | |
Discussion In this study, we analyzed the impact of psychologic variables on performance of activity and self-reported activity limitations in patients with CIAP using a theoretic model that integrates a psychologic theory (theory of planned behavior) in the ICF. When controlling for age, impairment variables, and disease duration, perceived behavioral control added to the amount of explained variance in the performance of an activity (9%) and self-reported activity limitations (12%, 24%). Perceived behavioral control consistently explained variance, but intention to perform the activity and emotions did not. In addition, data supported the hypothesis that perceived behavioral control partially mediates the relation between impairment (muscle strength) and activity limitations (see fig 1) in all 3 measures of activity limitations. Explicitly, the observed relations between impairment (muscle strength) and activity limitations may arise because the impairment affects the person’s control beliefs and these beliefs then affect the activity limitation. Stronger belief in their ability to control their performance of activity may delay or minimize the extent to which a person is limited in his/her activities by the impairments of CIAP. These findings provide some evidence to support the theoretic model as proposed by Johnston12 and suggest that activity limitations (eg, walking) may be influenced, at least partly, through perceived behavioral control. The integration of a psychologic theory to the ICF provides a more detailed and theoretically driven account of personal factors leading to activity limitations. Pain was not associated with any of the 3 measures of activity limitation and did not play an important role in the extent to which patients with CIAP have activity limitations. In this study pain, probably of neuropathic origin, seems to be unrelated to activity limitations. A possible explanation might be that the level of pain was not very high (median, 23; range, 0–70). Another explanation for this finding could be that patients with CIAP suffer from a neuropathic pain that is stimulus independent and may be less related to the performance of activities.37 Results from the factor analysis on the items of the measures of self-reported activity limitations and perceived behavioral control indicated that despite linguistic and contextual similarities, all activity limitation items were perceived differently from the perceived behavioral control items. This makes it unlikely that the results were caused by measurement confounds and is in line with the findings of Bonetti et al.38 In addition, these results showed that the self-report measure of activity limitations (modified physical functioning scale of the SF-36) fell apart in 2 factors, which were labeled as horizontal and vertical movements. These findings raise the question of whether this implies that horizontal and vertical movements differ considerably and that different impairment and psychologic variables may be of differential importance in relation to the extent of activity limitation. The current study was not designed to address this question, but future study is required to assess if it is necessary to make a distinction between horizontal and vertical movements when explaining and/or predicting activity limitations. In patients with CIAP, emotions (anxiety, depression) as measured with the HADS were below clinical cutoff scores, indicating that there was no indication for psychologic interventions. In addition, emotions did not explain a significant amount of variance in activity limitation. One might argue that this sample may be considered small, but to our knowledge this is the largest sample of CIAP patients investigating psychologic variables; furthermore, the results showed good consistency, and similar findings were obtained from 3 different measures of activity limitations (SWT, SF-36 physical functioning, self-reported ability to walk). That said, the results of this cross-sectional study justify further exploration of the relation between psychologic variables, in particular, perceived behavioral control and activity limitations. To understand if perceived behavioral control is a construct of causal importance in patients with CIAP, a longitudinal intervention study is needed to investigate whether changes in perceived behavioral control are related to changes in activity limitations. Perceptions of control can be changed by an intervention as simple as an invitation letter,39 but also a medical consultation can increase perceptions of control.40 Fisher and Johnston41 clearly showed in their study that changing perceptions of control were related to changes in performance of an activity in chronic pain patients. Conclusions Our results indicate that interventions that aim to reduce activity limitations should consider targeting modifiable perceptions like perceived behavioral control rather than nonmodifiable impairments. Longitudinal intervention studies may contribute to the development of rehabilitative interventions with beneficial outcomes for patients with CIAP. 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41. 41Fisher K, Johnston M. Experimental manipulation of perceived control and its effect on disability. Psychol Health. 1996;11:657–669. a Department of Neurology and Neurosurgery, Rudolf Magnus Institute of Neuroscience, Sections of Rehabilitation Medicine, University Medical Centre Utrecht, Utrecht, The Netherlands b Neuromuscular Disease, University Medical Centre Utrecht, Utrecht, The Netherlands c Department of Physiotherapy Research, Academy of Health Sciences Utrecht, Utrecht, The Netherlands d School of Psychology, University of Aberdeen, Aberdeen, UK e Department of Neurology, St Antonius Hospital Nieuwegein, Nieuwegein, The Netherlands f Department of Neurology, University Medical Centre Utrecht, Utrecht, The Netherlands g Department of Paediatric Physiotherapy and Exercise Physiology, Wilhelmina’s Children’s Hospital, University Medical Centre Utrecht, Utrecht, The Netherlands.  Reprint requests to Carin Schröder, PT, MSc, Dept of Physiotherapy Research, Academy of Health Sciences Utrecht, Huispostnr F00810, Postbox 85500, 3508 GA Utrecht, The Netherlands.
No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the author(s) or upon any organization with which the author(s) is/are associated. PII: S0003-9993(06)01432-8 doi:10.1016/j.apmr.2006.10.024 © 2007 American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved. | |
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