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Research Reports |
JM Fritz, PT, PhD, ATC, is Assistant Professor, Department of Physical Therapy, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA 15260 (USA) (jfritz{at}pitt.edu). Address all correspondence to Dr Fritz
SZ George, PT, MS, is a doctoral student in the School of Health and Rehabilitation Sciences, University of Pittsburgh
Submitted November 7, 2001;
Accepted April 9, 2002
 | Abstract |
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Key Words: Disability • Fear-avoidance beliefs • Likelihood ratio • Low back pain • Work-related low back pain
| Introduction |
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An emphasis on secondary prevention is supported by data that demonstrate the majority of patients with work-related LBP are able to return to work within 4 to 8 weeks after the onset of pain.7–9 Patients who are unable to return to work in this time frame, however, become increasingly unlikely to ever return to work, and these individuals account for the majority of the costs associated with occupational LBP.7,10 Hashemi et al,7 in a study of 16,987 people with work-related LBP requiring work absence in 1996, found that 66% of the injured workers returned to work within 4 weeks. After 1 year, 95% of the workers had returned to work, but those remaining off work accounted for 65% of the total costs for all of the workers. Williams et al10 studied approximately 29,000 injured workers and found that 66% returned to work within 8 weeks, but those remaining off work accounted for 75% of the costs. The early identification of patients who are at risk for prolonged work absence and disability could allow for targeted interventions within the acute phase that may reduce costs and the likelihood of chronic disability.
Researchers have examined various factors for their potential value in identifying patients with acute LBP who are at risk for prolonged work absence. Most researchers have found little predictive value from patient characteristics, such as age and sex, or findings from clinical examinations.11–16 Variables that have shown some ability to predict prolonged disability and work absence have generally been psychological in nature.17–20 For example, depression, anxiety, coping strategies, fear-avoidance beliefs, and health locus of control have been linked to chronic disability from LBP.15,17,21–23 Uncertainty remains, however, regarding the psychosocial variables that are most associated with the development of prolonged work restrictions and the optimal methods of measurement and interpretation for these variables. The purposes of our study were: (1) to identify variables measured during the initial examination of patients with acute work-related LBP that are predictive of prolonged work restrictions and (2) to determine which psychosocial variables had the most value in predicting prolonged work restrictions.
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Measures
All subjects underwent an baseline examination performed by a licensed physical therapist. The following measures were used:
Measure of impairment.
The Physical Impairment Index, a 7-item index of physical impairment due to LBP that was described by Waddell et al,24 was used. The 7 items are 4 range of motion variables (total flexion, total extension, average side bending, and average straight leg raise), 2 muscle force variables (active sit-up and bilateral straight leg raise), and 1 pain variable (spinal tenderness). Each item is scored as positive (1) or negative (0) based on published values, resulting in a total score of from 0 to 7.24 The developers of the scale found high levels of interrater reliability on 120 patients with chronic LBP for each item measured (kappa or intraclass correlation coefficient [ICC] values ranging from .86 to .96), and they reported that the scale successfully discriminated between individuals with and without LBP.24
Measure of pain.
Subjects were asked to rate their current level of LBP intensity using an 11-point pain rating scale ranging from 0 (no pain) to 10 (worst imaginable pain).25 We did not assess the reliability of the measurements.
Measures of disability.
Low back–related disability was measured with a modified Oswestry Questionnaire (OSW), a 10-item scale originally described by Fairbank et al.26 Each item is scored from 0 to 5, and the final score is expressed as a percentage, with higher numbers indicating greater disability. The OSW that we used was modified by substituting a section regarding employment or homemaking ability for the section related to sex life. We have found scores obtained with this modified version of the OSW to have high levels of reliability (ICC=.90), construct validity (correlations with global patient ratings and other region-specific disability measures greater than .80), and responsiveness (effect size of 1.8 in 69 patients who were receiving physical therapy interventions for work-related LBP).27 These findings are similar to those reported for the original version.26
The Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) was used to measure general health status. The SF-36 measures 8 dimensions of health (general health, physical function, role-physical, bodily pain, social functioning, mental health, role-emotional, and vitality).28 Each subscale is reported on a scale of 0 to 100, with higher numbers indicating better health status. The SF-36 has well-established psychometric properties for the general population28 and people with LBP.29
Psychosocial measures.
Waddell and colleagues identified 7 nonorganic symptoms30 and 5 nonorganic signs,31 which they proposed would indicate by their presence abnormal illness behavior. They defined abnormal illness behavior as "maladaptive overt illness related behavior which is out of proportion to the underlying physical disease and more readily attributable to associated cognitive and affective disturbances."32(p739) The nonorganic index is created by adding the number of positive symptoms and signs, resulting in a total possible score ranging between 0 and 12. Preliminary work has indicated that the nonorganic index may have better predictive value than symptoms or signs alone, demonstrating higher sensitivity (64%) and specificity (62%) values for predicting return to work in patients with acute work-related LBP.33 The nonorganic signs and symptoms have been shown to have high levels of agreement between examiners, with percentages of agreement ranging between 78% and 100%.31,32
Depressive symptoms were measured with the Center for Epidemiological Studies Depression Scale (CES-D), a 20-item scale designed for use with community-dwelling adults.34 Each item asks the subject to rate the frequency of a depressive symptom on a scale of 0 to 3, for a total possible score of 0 to 60. Higher numbers indicate greater severity of depressive symptoms. The CES-D has been tested in general samples and in groups with psychiatric diagnoses and has been shown to yield measurements with some reliability (ICC=.85–.91 for individual items) and predictive validity (sensitivity=86%–100% and specificity=53%–84% for detecting depression using a cutoff score of 16).35–37
The Fear-Avoidance Beliefs Questionnaire (FABQ) is used to quantify the level of fear of pain and beliefs about the need to change behavior to avoid pain in individuals with LBP.38 The FABQ has 16 items, each scored from 0 to 6, with higher numbers indicating increased levels of fear-avoidance beliefs. The FABQ contains 2 subscales: a 7-item work subscale (score range=0–42) and a 4-item physical activity subscale (score range=0–24). Researchers have found the FABQ work subscale to be associated with current and future disability and work loss in patients with chronic LBP16,38,39 and acute LBP.40 We did not assess the reliability of the FABQ data. The test-retest reliability of scores for the work and physical activity subscales of the FABQ has been reported to be high (ICC values of .90 and .77, respectively).41
The Beck Anxiety Index (BAI) was used to determine the presence and magnitude of anxiety symptoms.42 The BAI consists of 21 items, each scored between 0 and 3, for a total score ranging from 0 to 63. Higher scores indicate higher levels of anxiety. The BAI has been reported to have good reliability (ICC=.75 for 1-week test-retest reliability in 1,086 patients with various psychiatric diagnoses).42,43
Intervention
Following the baseline examination, subjects were randomly assigned to 1 of 2 intervention groups. Thirty-seven subjects received physical therapy based on the recommendations of the Agency for Health Care Policy and Research (AHCPR) clinical practice guidelines,44 and 41 subjects received therapy based on the classification system developed by Delitto and colleagues.45,46 All subjects in the first group received therapy based on the guidelines regardless of their individual signs and symptoms and history. The treatment for this group consisted of low-stress aerobic exercise (walking on a treadmill or stationary cycling), general muscle reconditioning exercises (eg, abdominal curls, quadruped arm and leg extensions), and advice to remain as active as possible within the limits of pain. Participants also were reassured by the therapist that they would recover and return to full work capacity. Subjects in the second group were re-examined during each appointment by the treating physical therapist, and they were placed into 1 of 4 treatment classifications based on the subjects' signs and symptoms. Subjects then received treatment based on their classification. The 4 classifications were: (1) manipulation followed by active range of motion exercises, (2) repeated end-range exercises (ie, flexion or extension exercises), (3) spinal stabilization exercises, and (4) traction. Further description of the classification categories and associated interventions has been published elsewhere.45,46 All subjects were scheduled for 2 to 3 therapy sessions per week, and they were re-examined by the occupational medicine physician on a weekly or biweekly basis. Return to work and therapy discharge decisions were made by the occupational medicine physician, who was blinded to the treatment group. Outcomes were assessed after 4 weeks.
Outcomes
All measurements taken at baseline were taken again 4 weeks after randomization. In addition, the subjects' work status was categorized as either "returned to work without restrictions" or "continued work restrictions." A subject was considered returned to work without restrictions if he or she returned to his or her previous job, performing the same duties, without any restrictions. If a subject had any restrictions on his or her work duties (eg, reduced hours, lifting limitations, placed on light duty, off work entirely), he or she was considered to have continued work restrictions. The primary outcome measure used for this study was work status after 4 weeks.
Data Analysis
Descriptive statistics (mean, standard deviation) were calculated for all variables measured at baseline. The distribution of measurements obtained for those variables was examined for normality. One-sample Kolmogorov-Smirnov (K-S) tests were used to test the hypothesis that the measurements of each variable came from a population with normally distributed values. If the K-S test statistic was not significant (P
.05), the null hypothesis that the measurements came from a normally distributed population was retained, and the variable was subsequently examined using parametric statistical tests. Variables with significant K-S test statistics were the nonorganic index, Physical Impairment Index, pain rating, FABQ physical activity subscale, and SF-36 role–physical, role–emotional, and bodily pain subscales. These variables were subsequently analyzed with nonparametric statistics.
Using the dichotomous outcome of work status after 4 weeks as the dependent variable, we analyzed the baseline measurements for univariate significance with work status. We used Pearson chi-square tests for dichotomous variables (sex, symptoms distal to the knee, prior history of LBP, and treatment group). We used independent sample t tests to examine the baseline measurements with a normal distribution, and we used Mann-Whitney U tests to analyze measurements with non-normal distributions. A significance level of P<.05 was used for all comparisons. We did not adjust the significance level because this step served as a filtering mechanism to identify variables with some relationship to work status.
We explored relationships among variables with significant univariate relationships to work status using Pearson or Spearman correlation coefficients as appropriate, based on the type of distribution. We further examined variables that reached statistical significance for validity to predict 4-week work status. This examination was performed in 2 steps. First, the predictive validity of each significant variable was determined through receiver operator characteristic (ROC) curves. An ROC curve is constructed by graphing the true positive rate (sensitivity) against the false positive rate (1–specificity) for each possible cutoff score of the variable.47 The area under the curve (AUC) was calculated using the nonparametric method described by Hanley and McNeil47 and Bamber.48 We chose the nonparametric method because it does not require a binormal data distribution.47 The AUC can be interpreted as the probability of correctly identifying the patient who will return to work from a randomly selected pair of patients, and may range between 0.50 (no predictive ability) and 1.00 (perfect predictive ability).49 The variable with the largest AUC represents the variable with the greatest predictive validity. The second step was to determine whether a multivariate model might offer greater predictive validity. A logistic regression was performed with work status as the dependent variable and all significant variables measured at baseline used as independent variables. Entry was stepwise, with a significance level of .05 to enter a variable and .15 to remove a variable.
We examined the baseline variable with the greatest AUC and any variables retained by the logistic regression for their ability to be used to predict work status after 4 weeks. Sensitivity, specificity, and positive and negative likelihood ratio (LR) values were calculated for all possible cutoff scores of these variables (ie, the score above which a score would be considered "positive").50 Continued work restrictions at 4 weeks served as the target condition (ie, "disease positive" state) for these calculations. Sensitivity was calculated as the proportion of subjects with continued work restrictions who had a positive test score. Specificity was calculated as the proportion of subjects without work restrictions with a negative test score. Positive and negative LR values combine sensitivity and specificity to describe the odds favoring the condition (ie, continued work restrictions) given a certain test result.51 The positive LR is calculated as sensitivity/(1–specificity) and indicates the increase in odds favoring the condition given a positive test result.52 The negative LR is calculated as (1–sensitivity)/specificity and indicates the change in odds favoring the condition given a negative test result.52 An LR of 1 indicates that the test result does nothing to change the odds favoring the condition, whereas an LR greater than 1 increases the odds of the condition and an LR less than 1 diminishes the odds favoring the condition.53
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| Discussion |
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Because of the economic impact of prolonged absence from work, early identification of individuals who are at risk for long-term altered work status, as indicated by having altered work status after 4 weeks, might benefit from early, targeted interventions designed to increase the likelihood of returning to work. Although such interventions have yet to be identified, it is likely, in our view, that they will require increased utilization of multidisciplinary services and increased costs. Given the small percentage of patients for whom this type of intervention may be indicated, the cost-effectiveness of implementing such an intervention for all patients with work-related LBP would be questionable. We contend that it would be valuable to have a method for detecting people who are at risk for long-term altered work status.
Useful statistics for examining screening methods and risk levels in individual patients are LR values because they permit the calculation of probability revisions given a certain test result.57 A test result with a large positive LR is useful for identifying patients who are at increased risk for long-term altered work status because a positive test increases the odds of the condition. Conversely, a test with a small negative LR is useful for identifying patients with reduced risk because a negative test will diminish the odds of the condition. For example, we found that 29% of subjects with acute work-related LBP were unable to return to regular work duties within 4 weeks. The largest positive LR was 3.33 for a FABQ work subscale score greater than 34. Using the computational method described by Sackett et al,50 the risk of prolonged work restrictions would increase from 29% to 58% when a score greater than 34 is obtained. The smallest negative LR was 0.08 for an FABQ work subscale cutoff score of 29. Therefore, in a patient with a score of 29 or less, the risk of prolonged work restrictions would decrease from 29% to 3%.50
Although most of the psychosocial measures we used showed differences at baseline between subjects with and without prolonged work restrictions, the FABQ work subscale had the greatest predictive validity. This finding supports that of other authors who have advocated that fear-avoidance beliefs may be the most important cognitive factor influencing the development of chronic disability in patients with LBP.38,40,58 The FABQ was developed to quantify a patient's fear of pain and subsequent avoidance of activity due to that fear.38 The work subscale is designed to measure avoidance related to work activities. The FABQ is based on the Fear-Avoidance Model of Exaggerated Pain Perception developed by Lethem et al59 to help explain why some people with acute painful conditions progress to chronic pain, whereas others are able to recover. The model proposed by Lethem et al indicates that an individual experiencing acute pain exists along a continuum between 2 extremes: confrontation and avoidance.60 At what point on the continuum an individual patient will exist is determined by his or her fear of pain.59,61 Confrontation is generally considered to be adaptive, because according to this view the individual views pain as a nuisance and has strong motivation to return to activity, gradually leading to a reduction in fear and a resumption of activity.59 Avoidance is viewed as maladaptive, causing the patient to avoid certain activities anticipated to cause increased pain.62 Avoidance may lead to reduced activity levels, an exacerbation of the fear and avoidance behaviors, prolonged disability, and adverse physical and psychological effects.59,63,64
Investigators have demonstrated a strong relationship between elevated fear avoidance beliefs and chronic disability due to LBP.18,38,39 Pearson correlation coefficients between disability scores and measures of fear-avoidance beliefs in studies involving patients with chronic LBP have ranged between .37 and .55.38,39,63,65 In addition, investigators18,40 have suggested that excessive fear-avoidance beliefs in patients with acute LBP may be a precursor of future disability. In previous work, we found fear-avoidance beliefs about work to be predictors of 4-week disability and work status even after controlling for initial levels of pain intensity, physical impairment, disability, and the type of therapy received.40 Because of this relationship, several authors38–40,66 have advocated the use of the FABQ as a screening tool to identify excessive fear-avoidance beliefs in patients with acute LBP. Our study reported here is the first study in which the value of the FABQ as a screening tool was investigated and in which cutoff scores were identified to assist clinicians in interpretation of scores.
Our results suggest that the FABQ work subscale may be able to serve as a useful screening tool to identify increased risk for prolonged work absence for patients with acute work-related LBP. Caution must be used, however, when interpreting and applying the results of the FABQ work subscale to individual patients. Our results suggest that the FABQ work subscale is a potentially valuable predictor of patients who are at low risk for prolonged work restrictions. Based on our results, a score of 29 or less would reduce the risk for prolonged work restrictions from 29% to 3% in a patient receiving therapy for acute work-related LBP. However, the scale was less effective when it was used to identify patients who are at high risk for prolonged work restrictions. Even the best positive LR (for a score greater than 34) only increased the risk to 58%. We believe caution must be exercised in avoiding overinterpretation of a "positive" score on the FABQ work subscale. In addition, the confidence intervals for the LR values in our study were rather wide, indicating that further research is needed to determine these ratios with greater precision.
Our results also indicate the important role of the selection of particular intervention strategies on return to work. In the final logistic regression model (Tab. 5), the odds ratio of 0.31 for the treatment group of the patient approached statistical significance (P=.06), even after the FABQ work subscale was entered. In this study, successful return to work occurred more frequently in the group treated using a classification-based approach versus an approach based on the AHCPR clinical practice guidelines. Although more research is needed to identify optimal strategies for managing patients with acute LBP, this finding indicates that successful management likely requires both the selection of the appropriate intervention and attention to the psychological distress of the patient.
Fear-avoidance beliefs appear to be an important factor in the development of prolonged work restrictions and chronic LBP for at least some patients. The use of screening tools such as the FABQ may assist clinicians in determining a particular patient's risk for prolonged work restrictions and in tailoring the intervention to more specifically address the patient's needs. For example, patients whose risk level is determined to be low may not require modifications or additions to their physical therapy management. Those whose risk level is heightened, however, may need intervention strategies that take into account those risk factors. Although further research is needed, the intervention for patients with LBP and a high level of fear-avoidance beliefs may require a cognitive behavioral approach utilizing graded exposure to the activities creating the fear.67,68 There has been integration of cognitive behavioral interventions into the rehabilitation of patients with chronic LBP69–72;however, patients with acute LBP have not been studied. Researchers have not attempted to classify patients prior to the intervention with respect to their risk status for prolonged disability.
All subjects in our study had work-related LBP. Research has shown that compensation status may affect outcome in patients with LBP.73 The results of our study, therefore, may not be generalized to patients with LBP that is not work related. In patients with LBP that is not work related, there may be different psychosocial variables influencing the transition from acute pain to chronic disability. The FABQ physical activity subscale may prove useful in determining risk based on fear-avoidance beliefs related to general physical activity. This hypothesis, however, warrants further study.
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| Footnotes |
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This study was approved by the Institutional Review Board at the University of Pittsburgh.
This work was supported by a Clinical Research Grant from the Foundation for Physical Therapy.
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This article has been cited by other articles:
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  R A Iles, M Davidson, and N F Taylor Psychosocial predictors of failure to return to work in non-chronic non-specific low back pain: a systematic review Occup. Environ. Med., August 1, 2008; 65(8): 507 - 517. [Abstract] [Full Text] [PDF]
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 J. J Godges, M. A Anger, G. Zimmerman, and A. Delitto Effects of Education on Return-to-Work Status for People With Fear-Avoidance Beliefs and Acute Low Back Pain Physical Therapy, February 1, 2008; 88(2): 231 - 239. [Abstract] [Full Text] [PDF]
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P. F Beattie and R. M Nelson Evaluating Research Studies That Address Prognosis for Patients Receiving Physical Therapy Care: A Clinical Update Physical Therapy, November 1, 2007; 87(11): 1527 - 1535. [Abstract] [Full Text] [PDF]
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I A Steenstra, J R Anema, P M Bongers, H C W de Vet, D L Knol, and W van Mechelen The effectiveness of graded activity for low back pain in occupational healthcare Occup. Environ. Med., November 1, 2006; 63(11): 718 - 725. [Abstract] [Full Text] [PDF]
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 J. D. Childs, J. M. Fritz, T. W. Flynn, J. J. Irrgang, K. K. Johnson, G. R. Majkowski, and A. Delitto A Clinical Prediction Rule To Identify Patients with Low Back Pain Most Likely To Benefit from Spinal Manipulation: A Validation Study Ann Intern Med, December 21, 2004; 141(12): 920 - 928. [Abstract] [Full Text] [PDF]
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S. Z George, J. E Bialosky, and J. M Fritz Physical Therapist Management of a Patient With Acute Low Back Pain and Elevated Fear-Avoidance Beliefs Physical Therapy, June 1, 2004; 84(6): 538 - 549. [Abstract] [Full Text] [PDF]
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M. W Werneke and D. L Hart Categorizing Patients With Occupational Low Back Pain by Use of the Quebec Task Force Classification System Versus Pain Pattern Classification Procedures: Discriminant and Predictive Validity Physical Therapy, March 1, 2004; 84(3): 243 - 254. [Abstract] [Full Text] [PDF]
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L. Resnik and D. L Hart Using Clinical Outcomes to Identify Expert Physical Therapists Physical Therapy, November 1, 2003; 83(11): 990 - 1002. [Abstract] [Full Text] [PDF]
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E. J. Hendriks, J. J Kerssens, J. Dekker, R. M Nelson, R. A. Oostendorp, and J. van der Zee One-Time Physical Therapist Consultation in Primary Health Care Physical Therapy, October 1, 2003; 83(10): 918 - 931. [Abstract] [Full Text] [PDF]
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