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PHYS THER
Vol. 88, No. 6, June 2008, pp. 712-719
DOI: 10.2522/ptj.20060301
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Research Reports

Physical Functioning Before and After Total Hip Arthroplasty: Perception and Performance

Inge van den Akker-Scheek, Wiebren Zijlstra, Johan W Groothoff, Sjoerd K Bulstra and Martin Stevens

I van den Akker-Scheek, PhD, is Human Movement Scientist and Epidemiologist, Department of Orthopedics, University Medical Center Groningen, University of Groningen, PO Box 30001, 9700 RB Groningen, the Netherlands.
W Zijlstra, PhD, is Human Movement Scientist, Center for Human Movement Sciences, University Medical Center Groningen, University of Groningen.
JW Groothoff, PhD, is Professor of Work and Health, Department of Health Sciences, University Medical Center Groningen, University of Groningen.
SK Bulstra, MD, PhD, is Orthopedic Surgeon, Professor of Orthopedics, and Head of Department, Department of Orthopedics, University Medical Center Groningen, University of Groningen.
M Stevens, PhD, is Research Coordinator and Human Movement Scientist, Department of Orthopedics, University Medical Center Groningen, University of Groningen.

Address all correspondence to Dr van den Akker-Scheek at: i.scheek{at}orth.umcg.nl


Submitted October 3, 2006; Accepted February 15, 2008


   Abstract
 
Background and Purpose: Self-report and performance-based measures of physical functioning in people before and after total hip arthroplasty seem to present different information. The relationship between these different measures is not well understood, and little information is available about changes in this relationship over time. The aims of this study were: (1) to determine the relationship between self-report and performance-based measures of physical functioning before and after total hip arthroplasty, (2) to assess the influence of pain on the relationship, and (3) to determine whether the relationship changes over time.

Subjects and Methods: Seventy-five subjects admitted for total hip arthroplasty were included and examined before and 6 and 26 weeks after surgery. The relationships between the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) physical functioning subscale and walking speed and gait variability were examined by use of generalized estimating equations, which included interactions with time and the WOMAC pain subscale.

Results: The relationship between self-report and performance-based measures of physical functioning was poor. Pain appeared to have a considerable influence on self-reported physical functioning. The relationship did not appear to change over time.

Discussion and Conclusion: The influence of pain on self-reported physical functioning serves as an explanation for the poor relationship between self-reported and performance-based physical functioning. When using a self-report measure such as the WOMAC, one should realize that it does not seem to assess the separate constructs—physical functioning and pain—that are claimed to be measured.


   Introduction
Top
 Abstract
 Introduction
Method
 Results
 Discussion
 Conclusion
 References
 
Outcomes after total hip arthroplasty can be assessed by means of self-report measures; the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) is a disease-specific questionnaire and is one of the most widely used and recommended measures.1,2 The questionnaire is completed by the patient; the score provides an indication of the patient's physical functioning, stiffness, and pain. Besides self-report measures, performance-based measures, in which the patient actually has to perform one or more activities of daily living, are available. Advantages and disadvantages have been reported for both kinds of measures.3,4 The advantages of self-report measures are that they are easy to administer, are inexpensive, and can evaluate multiple aspects of function in one test. Mentioned disadvantages are that self-report measures are influenced by expectations and beliefs of the patients and by impaired cognition and errors in memory; performance-based instruments do not have these disadvantages. However, the disadvantage of performance-based instruments is that activities often have to be assessed in an artificial laboratory environment, a task that can be time-consuming and expensive. With the introduction of ambulation measuring devices that use body-fixed sensors, physical functioning can be assessed objectively without these disadvantages.5 Spatiotemporal gait parameters, such as walking speed, can be accurately determined, and step-to-step variability as a measure of gait efficiency can be calculated from the obtained measurements.

Research into the relationship between self-report and performance-based measures has shown a poor to moderate relationship between these 2 types of measures.3,6,7 Each measure seems to assess different aspects of recovery. It is recommended, therefore, that both measures be used to obtain full insight into outcomes after total hip arthroplasty because these measures are considered to be complementary.3,8 However, research into the possible explanations for the poor to moderate relationship is scarce. Recently, Terwee et al9 investigated the influence of pain on the relationship between self-report and performance-based outcome measures before and after total knee arthroplasty. They discovered that self-report measures of physical functioning are influenced by pain more than are performance-based measures, a finding that could explain the low correlation between them. It is our hypothesis that this explanation also is valid for total hip arthroplasty.

Additionally, most research determining the relationship between self-report and performance-based measures is limited to measurement at one point in time (eg, before surgery or 12 months after surgery). Therefore, information about whether the relationship between these 2 types of measures changes over time is scarce. Research is needed on the relationship between self-report and performance-based measures in people before total hip arthroplasty as well as across the spectrum of recovery after surgery.3,10 Research on total knee arthroplasty demonstrated that the correlations between the self-report and performance-based measure scores changed over time after surgery; the correlations were somewhat better 3, 6, and 12 months after surgery than they were before surgery.9 This change in correlations over time can be explained by the influence of reduced pain. Before surgery, patients are in pain, which is hypothesized to influence the self-report measure; because of the pain, patients value their physical functioning less than is actually the case. There is an expectation that pain will decrease markedly shortly after surgery, and it is hypothesized that this sudden change will influence self-reported physical functioning: Patients overrate their physical functioning compared with what the performance-based measure shows because they suddenly do not perceive any pain while executing the activities. Over the long term after surgery, better concordance between self-reported and performance-based physical functioning is expected because patients do not perceive pain over time and, therefore, can provide a more accurate evaluation of their physical functioning. We hypothesize, therefore, that in patients with total hip arthroplasty, the relationship between self-report and performance-based outcome measures will change over time, as will the influence of pain.

The aims of this study were: (1) to determine the relationship between self-report and performance-based measures of physical functioning after total hip arthroplasty, (2) to assess the influence of pain on the relationship, and (3) to determine whether the relationship changes over time. In this study, the WOMAC physical functioning subscale (WOMAC-PF) was used as the self-report outcome measure and walking speed and step-to-step variability were used as the performance-based outcome measures in people before total hip arthroplasty and over the short term and long term after surgery.


   Method
Top
 Abstract
 Introduction
 Method
Results
 Discussion
 Conclusion
 References
 
Subjects

People admitted to a medical center orthopedic department for unilateral total hip arthroplasty and participating in the short-stay program between September 2002 and August 2004 were included in the study. The criteria for the short-stay program were as follows: estimated surgery time of less than 120 minutes, weight of less than 110 kg, estimated hospital stay of less than 6 days, no signs of severe mobility disablement or psychological dysfunction, and no severe deformity of the spine. Study participants were allowed to start walking with aids on the first day after surgery and were discharged on day 5 after surgery unless there were complications.

In total, 87 people were admitted for total hip arthroplasty during the study period. All were willing to participate in the study. Measurements were performed at the time of admission and 6 and 26 weeks after the surgery, when the study participants visited the outpatient clinic. The participants were asked to complete the WOMAC, and gait analysis was performed. Data on participant characteristics such as sex, age, and body mass index (BMI) were gathered at admission.

Of the 87 people willing to participate in the study, 12 were excluded from further analyses because they did not complete the questionnaire or the gait analysis at all 3 measurement times for various reasons: 1 had severe surgical complications, 1 moved out of the country, 1 died, 2 had health problems attributable to causes unrelated to the orthopedic surgery, 2 refused further participation because of personal circumstances, 4 did not visit the outpatient clinic, and 1 had a total hip arthroplasty on the contralateral side. The remaining 75 participants were predominantly women (n=53, 70.7%), with a mean age of 62.7 years (SD=11.7) and a mean BMI of 26.6 kg·m–2 (SD=3.4). The mean length of the hospital stay was 7.0 days (SD=3.3).

Measures

The Dutch version of the WOMAC was used; it has been proven valid and reliable for people before and after total hip arthroplasty.11,12 The WOMAC is a disease-specific, self-report outcome measure for people before and after hip arthroplasty and consists of the subscales physical functioning, stiffness, and pain. Two of the subscales, the WOMAC-PF (17 items) and the WOMAC pain subscale (WOMAC-P) (5 items), were used in this study. Responses were given on a 5-point Likert scale. Scores from both subscales were recoded into a 100-point scale, with a higher score representing better physical functioning or less pain.

Gait analysis was performed with the DynaPort System.* This is an ambulation system consisting of a data recorder (dimensions=125x95x34 mm; weight=295 g) that is attached to an individual's lower back with a neoprene belt around the waist, over the individual's clothes. The data recorder contains 3 uniaxial, piezoelectricity-resistive accelerometers that measure acceleration in the frontal, sagittal, and transverse planes and a memory card on which data are stored. Three penlight batteries are attached to the belt. In this study, participants were asked to walk 20 m at their preferred speed in a hospital corridor. After each measurement, the data were transferred from the memory card to a personal computer and displayed graphically. The beginning and end of each test part were marked manually in the DynaPort software. Analysis of the accelerometer signals and extraction of data for the gait parameters were performed by McRoberts BV.* Several movement features can be determined from the accelerometer signals.13–15 Only the parameters of walking speed and step-to-step variability were used in this study as measures of gait steadiness because they reliably reflect changes in an individual's gait efficiency.16 Step-to-step variability is expressed as the coefficient of variation (CV), as follows: (SD of step duration/mean step duration)x100. The ambulation method is used to determine spatiotemporal gait parameters from lower-trunk accelerations. In previous studies,13–15 this method was proven to be a valid means for determining gait parameters.

Data Analysis

Descriptive statistics (mean and SD) were used to describe participant characteristics, scores on the WOMAC-PF and the WOMAC-P, preferred walking speed, and step-to-step variability (expressed as the CV) at the 3 measurement times (before surgery and 6 weeks and 6 months after surgery). General linear model repeated-measures analyses were used to determine whether the scores changed over time. General linear model repeated-contrast analyses were used to determine whether the scores changed between the measurements obtained before surgery and over the short term after surgery or between the measurements obtained over the short term and over the long term after surgery, or both. Pearson correlation coefficients were calculated for the scores obtained before surgery (Tab. 1).


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  		Table 1. Pearson Correlation Coefficients for the Measures Before Surgerya

 
The relationship between the WOMAC-PF and preferred walking speed was assessed by applying generalized estimating equations (GEEs) to longitudinal data to account for correlations between repeated observations for each subject. First, a "naive" linear regression analysis is carried out, and regression coefficients are estimated, assuming that the repeated observations within one subject are independent.17 Because this is not the case, a correction must be made for these within-subject correlations. This is done by adding to the regression model a correlation matrix that consists of an estimation of the correlations between the different time points within a subject. In this study, an exchangeable correlation structure was used, assuming all correlations to be the same. The regression coefficients are then reestimated, with correction for the dependency of the observations. Through standardization of the regression coefficients [(regression coefficient x SDx)/SDy], the coefficients can be interpreted as correlation coefficients.

In the first GEE model, the WOMAC-PF score was included as a dependent variable and preferred walking speed was included as an independent variable. In the second model, the WOMAC-P score was added. Additionally, a walking speed x time interaction and a pain x time interaction were included (models 3 and 4). The participant characteristics of sex, age, and BMI were included as potential confounders (model 5). The regression coefficients were standardized. The complete analysis was repeated with the CV [(SD of step duration/mean step duration)x100] instead of preferred walking speed as an independent variable.

The Statistical Package for the Social Sciences, version 14.0,{dagger} and STATA, version 9.1,{ddagger} were used for data analysis. A P value of less than .05 was considered statistically significant.


   Results
Top
 Abstract
 Introduction
 Method
 Results
Discussion
 Conclusion
 References
 
The mean WOMAC-PF and WOMAC-P scores, preferred walking speed, and CV at the 3 assessment times are shown in Table 2. For all variables, a significant improvement was seen over the 3 measurement times (overall time effect; P≤.001). For the WOMAC-PF, a significant improvement was seen between each of the 3 measurement times. The overall significant improvement seen for the WOMAC-P and CV was attributable to a significant improvement between the measurements before surgery and over the short term after surgery. For walking speed, the overall significant improvement was attributable to a significant improvement between the 2 measurements after surgery.


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  		Table 2. Mean (SD) of the Self-report and Performance-based Outcome Measures and Pain at the 3 Measurement Times and Results of the General Linear Model Repeated-Measures Analysisa

 
The results of the GEE analysis with WOMAC-PF as the dependent variable and preferred walking speed as the independent variable are shown in Table 3. In model 1, the standardized regression coefficient of preferred walking speed was .40; adding WOMAC-P to the regression model resulted in a decrease to .22 (model 2). Neither the interaction term preferred walking speed x time (model 3) nor the interaction term WOMAC-P x time (model 4) was significant; this result implies that the contributions of preferred walking speed and pain to the regression model do not change over time. On the basis of the fact that the regression coefficient of PWS showed only a minimal change when the participant characteristics of sex, age, and BMI were added to the regression model (.21 versus .22), these characteristics are not considered to be confounders (model 5).


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  		Table 3. Results of the Generalized Estimating Equation (GEE) Analysis With Physical Functioninga as the Dependent Variable and Preferred Walking Speed (PWS) as the Independent Variableb

 
Table 4 shows the results of the GEE analysis with WOMAC-PF as the dependent variable and CV as the independent variable. In model 1, the standardized regression coefficient of CV was –.14; adding WOMAC-P to the regression model resulted in a decrease to –.11, but there was an overlap of the 95% confidence intervals (model 2). As in the models with PWS as the independent variable, neither the interaction term CV x time (model 3) nor the interaction term WOMAC-P x time (model 4) was significant. The regression coefficient of CV showed only a minimal change when the participant characteristics of sex, age, and BMI were added to the regression model (–.11 versus –.09); therefore, these characteristics are not considered to be confounders (model 5).


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  		Table 4. Results of the Generalized Estimating Equation (GEE) Analysis With Physical Functioninga as the Dependent Variable and Coefficient of Variation (CV) as the Independent Variableb

 

   Discussion
Top
 Abstract
 Introduction
 Method
 Results
 Discussion
Conclusion
 References
 
The aims of the present study were to determine the relationship between self-report (WOMAC-PF) and performance-based (walking speed and step-to-step variability) outcome measures of physical functioning in people with total hip arthroplasty, to assess the influence of pain on the relationship, and to determine whether the relationship changes over time.

Pain and a deterioration in physical functioning are the primary reasons for a total hip arthroplasty. In the early period after surgery, pain is reduced, although physical functioning may be diminished compared with that before surgery because patients have just undergone surgery and usually walk with crutches in the first few weeks after surgery.16 However, the measurements that we obtained in the short term after surgery already indicated an improvement in the self-reported physical functioning outcome measure (WOMAC-PF). The performance-based measure CV also showed an improvement, but this value could be distorted by the use of crutches by most of the participants at this measurement time. The performance-based measure preferred walking speed, however, did not show an improvement at the 6-week measurement time over the value obtained before surgery. This difference in outcomes between a self-report measure and a performance-based measure of the same construct (physical functioning) is consistent with the findings of other investigators.9,18–20 These observations indicate a poor relationship between self-report and performance-based physical functioning measures.

The results of the GEE analyses performed on our results confirmed that conclusion: The regression coefficient in the model containing WOMAC-PF as a dependent variable and preferred walking speed as an independent variable, both measured 3 times, was only .40, and the regression coefficient in the model containing CV as an independent variable was even lower (–.14). The poorer relationship between CV and the WOMAC than between walking speed and the WOMAC was also found by Lindemann et al.16 Our findings are thus in accordance with our hypothesis of a poor relationship between self-report and performance-based measures of physical functioning. Determining the relationship with multiple assessments over time, with correction for the dependency of longitudinal data as we applied in our analyses, did not result in adverse findings compared with those of other investigators using correlation coefficients.

In order to examine the second aim of our study—to determine the influence of pain on the relationship—WOMAC-P was added to the models containing the self-report measure as a dependent variable and the performance-based measure as an independent variable. This method resulted in an even lower regression coefficient for preferred walking speed, whereas pain made a great contribution (.77). For the other performance-based measure, CV, the influence of pain was less profound; the regression coefficient for CV was slightly lower, but there was an overlap of the 95% confidence intervals. However, for pain there was an equally high regression coefficient (.82) in the model containing CV as an independent variable and in the model containing preferred walking speed as an independent variable. Adding participant characteristics (age, sex, and BMI) did not change the relationship between the self-report and performance-based measures. The WOMAC-P and the WOMAC-PF appeared to be closely linked. With the WOMAC-PF, pain— or diminishing pain after surgery—also is measured when the aim is to assess solely physical functioning. People seem to be unable to separate pain and physical functioning when pain is present or when a change in pain has occurred. Through differentiation with 3 subscales, the WOMAC is claimed to measure different constructs. However, our results and those of other investigators9,20 question the factorial validity of the WOMAC-PF.

The fact that pain was determined with the same questionnaires as those used to assess self-reported physical functioning can be considered a limitation of the present study. Because the present study was part of a larger study,21 we also had access to data from the Medical Outcomes Study 36-Item Health Survey Questionnaire (SF-36). We chose to initially use the WOMAC-P because the WOMAC is a disease-specific questionnaire and the SF-36 is a generic quality-of-life questionnaire. The WOMAC asks about difficulties with specific activities that are problematic for people with arthritis, whereas the SF-36 assesses overall health. Moreover, the WOMAC has been found to be more responsive than the SF-36.18,22 However, when the SF-36 pain subscale was used instead of the WOMAC-P, the regression coefficient was somewhat lower, albeit still high (preferred walking scale model: .77 with WOMAC-P and .64 with SF-36 pain subscale; CV model: .82 with WOMAC-P and .70 with SF-36 pain subscale). This finding strengthens our conclusion that pain has a significant influence on the self-report physical functioning outcome measure.

The third aim of the present study was to determine whether the relationship between self-report and performance-based outcome measures changes over time. On the basis of the observation that the WOMAC-PF scores and the walking speed values developed in different directions over time, we hypothesized that the relationship between them would change over time. The interaction term was not significant; this finding implies that the association did not change over time (Tab. 3). Even when pain was not included in the regression model, the interaction term was not significant (data not shown). In the model with CV as an independent variable, the interaction term was not significant either (Tab. 4). Lindemann et al16 found similar results; they performed a gait analysis and assessed the WOMAC in people before and after total hip arthroplasty and did not find changes in correlation coefficients after surgery compared with before surgery. Unfortunately, their study had the limitation of a small study group (N=17) and only one measurement after surgery (3 months after surgery). Other investigators did find a changing association. Terwee et al9 found changes in correlation coefficients over time between the DynaPort System knee score (performance-based functioning score) and the WOMAC for people before and after total knee arthroplasty. However, all mentioned studies used correlation coefficients to describe the association between self-reported and performance-based physical functioning. This method neglects the fact that the observations are repeated measures. With a longitudinal design like that used in the present study, a correction is made for the dependency of the data. Additionally, confounding and effect modification can be studied, resulting in a more in-depth analysis. Furthermore, in the present study, the sample size was considerable and measurements were obtained over the short term and long term after surgery, as suggested by Lindemann et al.16

Finally, we analyzed whether the influence of pain changed over time. From the results, it appeared that pain had a strong, consistent influence on self-reported physical functioning. However, the influence of pain did not change over time, even when pain levels were lower. Therefore, even low levels of pain have the potential to influence self-reported physical functioning, a conclusion counter to what was hypothesized and opposite to traditional thinking. It is not known what the influence of a total absence of pain is; people were not totally pain-free at 6 months (mean WOMAC-P score of 84.9 out of 100) (Tab. 2). This aspect should be the object of further research in which people are additionally assessed at 12 months or later.

A remark is needed regarding the fact that preferred walking speed and CV were used as performance-based measures of physical functioning. There is no gold standard for the measurement of physical functioning. Although walking is highly important in everyday life and, therefore, is closely linked to overall functioning, an individual needs more than good walking abilities alone in order to function well. On the other hand, improving walking abilities is one of the purposes of a total hip arthroplasty. Moreover, walking speed and gait variability have been related to independent living and the ability to perform various activities of daily living, such as safely crossing a traffic intersection, as well as to the risk of falling; therefore, we believe that they can be used as measures of overall physical functioning.23–25


   Conclusion
Top
 Abstract
 Introduction
 Method
 Results
 Discussion
 Conclusion
References
 
The relationship between self-report and performance-based measures of physical functioning is poor in people before and after total hip arthroplasty. Contrary to our hypothesis, the relationship does not appear to change over time. The finding that pain has a considerable influence on self-reported physical functioning is in accordance with our hypothesis. People appear to have problems separating pain and physical functioning. The practical implication is that when one is interested in physical functioning exclusively, a performance-based measure should be used. When using a self-report measure such as the WOMAC, one should realize that it does not seem to assess the separate constructs—physical functioning and pain—that are claimed to be measured.


   Footnotes
 
All authors provided concept/idea/research design. Dr van den Akker-Scheek, Dr Zijlstra, and Dr Stevens provided writing. Dr van den Akker-Scheek provided data collection. Dr van den Akker-Scheek and Dr Stevens provided data analysis and project management. Dr Stevens and Dr Bulstra provided fund procurement. Dr Groothoff and Dr Bulstra provided consultation (including review of manuscript before submission).

This study was conducted in accordance with the regulations of the Medical Ethical Committee of University Medical Center Groningen.

This study was supported by a grant from University Medical Center Groningen.

* McRoberts BV, Raamweg 43, 2596 HN, The Hague, the Netherlands. Back

{dagger} SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606. Back

{ddagger} StataCorp LP, 4905 Lakeway Dr, College Station, TX 77845. Back


   References
Top
 Abstract
 Introduction
 Method
 Results
 Discussion
 Conclusion
 References
 

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