J Occup Rehabil DOI 10.1007/s10926-012-9370-4
Distressed, Immobilized, or Lacking Employer Support? A Sub-classification of Acute Work-Related Low Back Pain Silje Endresen Reme • William S. Shaw • Ivan A. Steenstra • Mary Jane Woiszwillo Glenn Pransky • Steven J. Linton
•
! Springer Science+Business Media, LLC 2012
Abstract Introduction One possibility for reducing the disabling effects of low back pain (LBP) is to identify subgroups of patients who might benefit from different disability prevention strategies. The aim of this study was to test the ability to discern meaningful patient clusters for early intervention based on self-reported concerns and expectations at the time of an initial medical evaluation. Methods Workers seeking an initial evaluation for acute, work-related LBP (N = 496; 58 % male) completed selfreport measures comprising of 11 possible risk factors for chronicity of pain and disability. Outcomes of pain, function, and return-to-work were assessed at 3-month followup. A K-means cluster analysis was used to derive patient subgroups based on risk factor patterns, and then these subgroups were compared with respect to 3-month outcomes. Results Eight of the 11 measures showed significant
associations with functional recovery and return-to-work, and these were entered into the cluster analysis. A 4-cluster solution met criteria for cluster separation and interpretability, and the four clusters were labeled: (a) minimal risk (29 %), (b) workplace concerns (26 %); (c) activity limitations (27 %); and (d) emotional distress (19 %). Functional outcomes were best in the minimal risk group, poorest in the emotional distress group, and intermediate in the other two groups. A global severity index at baseline also showed highest overall risk in the emotional distressed group. Conclusions Patterns of early disability risk factors from this study suggest patients have differential needs with respect to overcoming emotional distress, resuming normal activity, and obtaining workplace support. Classifying patients in this manner may improve the cost-benefit of early intervention strategies to prevent long-term sickness absence and disability due to LBP.
S. E. Reme (&) Department of Environmental Health, Harvard School of Public Health, 450 Brookline Avenue, Boston, MA 02215, USA e-mail:
[email protected]
Keywords Low back pain ! Screening ! Subgroups ! Sub-classification ! Disability risk factors
S. E. Reme ! W. S. Shaw ! M. J. Woiszwillo ! G. Pransky Liberty Mutual Research Institute for Safety, Hopkinton, MA, USA
Introduction
S. E. Reme Uni Health, Uni Research, Bergen, Norway W. S. Shaw ! G. Pransky University of Massachusetts Medical School, Worcester, MA, USA I. A. Steenstra Institute for Work and Health, Toronto, ON, Canada S. J. Linton ¨ rebro School of Law, Psychology and Social Work, CHAMP, O ¨ rebro, Sweden University, O
Low back pain (LBP) is one of the 15 most expensive medical conditions in the US, and the prevalence of LBP is rising steadily, with 28 % of adults now reporting LBP over the last 3 months [1]. As many as 10–20 % of American workers report persistent or recurrent back pain that limits their ability to work [2], and LBP is the most common cause of disability in US adults under age 45 [3]. Most people recover from an acute episode of LBP and are able to return to work within a few days or weeks [4], but for some, the pain develops into a chronic and disabling condition with life-long implications [1, 5–7]. Prognostic
123
J Occup Rehabil
studies of patients with acute LBP have shown that close to 40 % are at elevated risk (and 10–15 % at high risk) of developing chronic disability based on the number of risk factors present [8]. Multidisciplinary and behavioral treatments have shown promise in reducing the disability associated with chronic and sub-acute LBP [9–12], but these interventions are generally not recommended in earlier (acute) stages of LBP, when a majority of individuals show spontaneous improvement without intervention [4]. For those at high risk of transitioning to chronic pain and disability, however, earlier intervention may be helpful, especially if the content of early intervention (i.e., physical or psychological) can be tailored to the needs of homogeneous subgroups of patients describing similar pain-related challenges [13, 14]. A variety of methods have been proposed to sub-classify cases of LBP, but most have been based on pathoanatomic and clinical features rather than on psychosocial factors [15, 16]. One strategy has been to empirically define patient sub-types who respond preferentially to one treatment over another in post hoc analyses [13]. For example, it has been shown that the benefits of physical treatments for LBP (manipulation, stabilization exercises, or specific exercise treatment) can be improved when patients are divided into subgroups and matched to treatments using a clinical prediction rule involving initial clinical characteristics [17, 18]. Pain pattern classification is another approach, but with a large proportion of unclassifiable patients and equivocal results from tailored treatments, this classification strategy appears limited [19]. A third approach is to subgroup patients on self-reported psychosocial factors. Despite an extensive focus on psychosocial aspects of LBP in the literature [20], a review of LBP classification systems found that only 4 of 39 studies incorporated a biopsychosocial framework [15]. Psychosocial classifications may be more telling than strictly biomechanical and diagnostic groupings. For example, a recent study employing a 9-item self-report questionnaire to classify primary care patients with varying lengths of LBP as low, medium, or high risk of persistent pain and disability, showed improved outcomes and cost effectiveness when applying psychologically informed physical therapy interventions [12]. In addition to risk severity, there is preliminary evidence that patients differ with respect to the types of problems and concerns that might be a focus of intervention. Data from two previous LBP cohorts have identified tentative patient subgroups reporting problems that are primarily emotion-focused, physical-focused, or workplace-focused [21, 22]; but both studies applied only brief screening devices (often using single items to assess whole domains), with insufficient external validity for use in individual-level clinical decision-making [12]. The goal of the current study was to provide further evaluation of
123
possible early intervention subgroups among working adults with acute LBP (\14 days) using full-length self-report questionnaires and including a variety of psychosocial and physical risk factors. Criteria for scale inclusion in the screening inventory were consistent with our conceptual model of 3 patient clusters for early intervention [21], the scale’s demonstrated validity for predicting return-to-work outcomes, the scale’s appropriateness and acceptability for administration soon after pain onset without insinuating blame, basic psychometric properties of the scale (reliability, internal consistency, face validity), and length and ease of administration. The conceptual model was based on a literature review identifying the strongest areas of concordance between disability factors in prospective cohort studies and the most effective return-to-work strategies [14]. The specific aims of the current paper were thus to provide early subgroup classification of workers with acute, workrelated LBP to guide treatment approaches to prevent work disability.
Methods Participants The study included 496 volunteer patients (58 % male) seeking treatment for work-related, acute back pain at private occupational medicine clinics in the states of Massachusetts, Rhode Island, or Texas, USA. In these regions, employers are allowed to choose or recommend the initial medical provider for a work-related injury, so the majority of participants were employer-referred. Other participants were self-referred or referred from emergency rooms or primary care providers. Eligibility requirements were: (1) non-specific sacral or lumbar back pain; (2) acute onset or exacerbation (\14 days); (3) pain self-reported to be of occupational origin; (4) age 18 or older; and (5) fluency in English or Spanish. Of the 496 patients initially included in the study, 359 (72 %) could be reached for the 3-month follow-up assessment. This smaller sample size applies to all analyses involving follow-up measures. Comparisons of responders and non-responders at 3-month follow-up showed only that responders were older, more likely female, and of lower educational status (p \ 0.05). The only significant difference on psychosocial predictor variables was for responders to report more organizational support, t(490) = -2.96, p = 0.003. Procedures Front desk staff or clinicians identified eligible patients during an initial medical evaluation for acute back pain. The patients were informed about the details of the
J Occup Rehabil
research study, and a consent form was provided to review and sign. The consent form assured confidentiality of survey information (not to be placed in medical records or shared with employers) and notice of a $30 retail gift card for completing the initial survey and an additional $25 cash payment after completion of the 3-month follow-up survey. After any questions or concerns were addressed, patients were asked to complete a 10-page questionnaire that included demographic and contact information as well as the self-report predictor variables. The questionnaire took 15–20 min to complete. Based on a brief written description by participants of what happened at the time of pain onset, injuries were classified according to event or exposure codes used by the US Bureau of Labor Statistics for tracking workplace injuries [23]. At the clinic, the workers received standard care in compliance with current occupational guidelines [24]. That involved a medical evaluation, advice to resume normal activity as soon as possible, and pain medication if needed. Before leaving the clinic, participants returned the completed forms to the reception desk. Participants who returned to the clinic for a second visit, 337 (68 %), were asked to repeat the self-report questionnaire; this was typically within one week after the initial visit (range 4–10 days). Three months after the initial medical evaluation, participants were contacted (by letter and/or e-mail) to complete a brief follow-up questionnaire assessing pain, functional limitation, and work status. The 3-month time frame was chosen because of its significance in distinguishing acute from sub-acute medical care in LBP treatment guidelines. Questionnaires could be returned in three different ways: (1) by mail; (2) via a toll-free 24-h interactive voice-response telephone system; or (3) by accessing a web-based internet survey. If the participants did not respond within 10 days, a trained interviewer made attempts to reach the participant by telephone to administer the follow-up survey. All human subjects procedures were reviewed and approved by the Institutional Review Board for the Liberty Mutual Research Institute for Safety. Predictor Measures The measures included in the screening questionnaire were selected based on weighing theoretical, conceptual and practical considerations, including: (1) sufficient coverage of the three domains of physical function, psychological distress, and workplace factors; (2) prediction of return-towork outcomes; (3) suitability for administration soon after pain onset; (4) satisfactory quality of psychometric properties; and (5) length and ease of administration. Eleven measures were selected, but three of these (the Workplace Friendship Scale [25], the Physical Workload Survey [26], and a rating of job satisfaction) were dropped from
subsequent analyses due to a lack of significant correlation with 3-month outcome measures (data not shown). The remaining eight measures that formed the basis for data analyses are described below: Functional limitation: The Quebec Back Pain Disability Scale [27], a 20-item self-report scale, was used to assess functional limitation. The scale was designed to maximize measurement sensitivity across the full range of back disability within six activity categories: ambulation, bed/rest, bending/stooping, handling of large/heavy objects, movement, and sitting/standing. The scale has equal or better reliability and sensitivity to change when compared with competing self-report measures of function [27, 28]. The total score is a sum of all 20 items. Pain intensity: Pain intensity was reported on an 11-point numerical rating scale from 0 (‘‘no pain at all’’) to 10 (‘‘worst pain possible’’). The reliability and validity of the pain numerical rating scale has been well documented [29], and the scale has demonstrated sensitivity to change in LBP treatments [30]. Depressive symptoms: The Center for Epidemiologic Studies Depression (CES-D) scale is a short self-report scale designed to measure depressive symptomatology in the general population [31]. The items of the scale represent typical depressive symptoms featured in longer scales and assessment methods. It has been found to have very high internal consistency and adequate test–retest reliability [31]. It has also been found to have good predictive ability among pain patients, even when somatic items are removed [32]. Interpretation of pain: The Pain Catastrophizing Scale (PCS) [33] measures pain catastrophizing and ‘‘exaggerated negative orientation toward pain stimuli and pain experience’’ [34]. The scale consists of 13 items, and the full scale-score has high internal consistency and reliability. Pain catastrophizing explains variability in disability outcomes over and above that explained by pain intensity [34]. Activity avoidance: The Tampa Scale of Kinesiophobia (TSK) is a 17-item self-report scale that was developed to measure activity avoidance, or ‘‘kinesiophobia, the fear of movement or re-injury’’ [35]. Responses are reported on a 4-point Likert scale from ‘‘0’’ (strongly disagree) to ‘‘3’’ (strongly agree). In LBP, the TSK has been related to performance on lifting and trunk extension-flexion tasks [36]. A shorter, 11-item version of the TSK was chosen for the screening inventory due to similar psychometric properties to the longer version [37]. Organizational support: The Survey of Perceived Organizational Support (SPOS) is a 36-item self-report scale that was designed to assess perceived organizational support among employees across a wide range of potential employment concerns [38, 39]. For inclusion in the
123
J Occup Rehabil
screening inventory, we chose a shorter, 8-item version [40] that has been used successfully in a recent study of chronic pain and organizational support [41]. The rationale for including the SPOS in the patient screening inventory was that successful problem-solving at the time of a back injury or acute pain episode might depend on workers’ perceptions that the employer values their contribution and cares about their well-being. Life impact of pain: This 13-item self-report scale was developed by the research team to assess the personal significance that individuals place on an acute episode of LBP with regard to job, leisure activities, family, and life in general. Each item is a belief statement about the seriousness of the pain episode (e.g., ‘‘This episode of pain is a significant event in my life’’) and responses are on a 4-point Likert-scale from ‘‘1’’ (strongly disagree) to ‘‘4’’ (strongly agree). The rationale for developing and including this scale was to provide a subjective measure of life stress related to acute LBP. Psychometric data for this measure are pending. Recovery expectations: Three items were used to assess patient expectations about the likely duration of symptoms, physical activity restrictions, and job limitations, respectively. Wording of the three items was based on previous research linking LBP recovery expectations to patient outcomes [42, 43] and responses were provided on a Likert scale from ‘‘1’’ (0–2 days) to ‘‘5’’ ([60 days). A total score was the sum of the three items.
homogenous groups of cases based on selected characteristics. K-means is one method from a family of statistical techniques that was developed to identify meaningful subgroups in population health and other scientific studies [45, 46]. The computational algorithm starts with k random clusters, and then moves subjects iteratively between those clusters with the goal of minimizing variability within clusters while maximizing variability between clusters [47]. As opposed to factor analysis that groups variables based on correlation, K-means cluster analysis groups objects based on proximity. The number of clusters, k, can be designated by the user to produce different cluster solutions. The relative locations of cluster centers were used to provide descriptive labels. Patients were assigned to the nearest cluster grouping and then compared on 3-month outcomes of pain, functional limitation, and work disability in one-way analysis of variance (ANOVA) or logistic regression analysis. In the present study, our criterion for number of clusters was to determine the maximum number of patient clusters that could be discriminated while still obtaining a Euclidian distance between neighboring cluster centers of at least 2.0 standard deviation units on all measures. The analysis was repeated in sequential steps, each time increasing the number of clusters by one.
Outcome Measures
Demographic characteristics of the 496 participants (Table 1) described a mostly White, blue-collar population of working adults with moderate levels of income and education, who were employed by medium (50–500 employees) to large ([500) employers. Ages of participants ranged from 18 to 65 years (M = 37.0, SD = 11.3). The most frequent occupational categories were health care, transportation, retail/restaurant, sanitation and maintenance, and distribution/warehousing. Previous analyses have shown the occupational, demographic, and back injury characteristics of this cohort to be similar to those of a US national injury database of reported occupational back injuries [48]. At the initial visit, most participants reported a moderate to high level of pain intensity (M = 6.83, SD = 1.97) and a moderate level of functional limitations (M = 50.9, SD = 22.1). The ten most frequent injury types were: overexertion (55.8 %), bodily reaction (15.0 %), bodily reaction and exertion, unspecified (7.9 %), fall on same level (6.9 %), highway accident (2.9 %), fall to lower level (2.7 %), struck by object (2.1 %), struck against object (0.2 %), fall, unspecified (0.4 %), and repetitive motion (0.4 %). These percentages were similar to those compiled by the US Occupational Safety and Health Administration
In addition to re-assessing pain intensity (visual analog scale) and functional limitation (Quebec Back Pain Disability Scale) at 3-month follow-up, participants provided details about current work status, any temporary modifications or physician restrictions, and the cumulative duration of work absences and work modifications. In order to provide an overall outcome measure that would distinguish those patients with a possible need for further monitoring, treatment, or referral, a composite clinical case rating was used. A clinical case (or caseness) was defined by experiencing continuing problems in any of the three outcome domains: work status (unable to resume full duty work), pain rating (C5), or physical dysfunction ([50 % items endorsed). Rationale for these cut-off scores can be found in an earlier cohort study [44]. Data Analysis All analyses were performed with SPSS version 18. The risk factors from the included measures were standardized (z-scores), and then subjected to a K-Means cluster analysis, which is a procedure for identifying relatively
123
Results
J Occup Rehabil Table 1 Demographic (N = 496)
characteristics
of
Variable
study
participants
Table 1 continued Variable
N
N
%
%
Gender
Public service (e.g., police, fire, post office)
9
Airport worker (e.g., ticketing, baggage)
8
1.8 1.6
21
4.2
Male
288
58.1
Machinist, machine operator
Female
208
41.9
Education, childcare
11
2.2
Office worker
18
3.6
9
1.8
Race Black
95
19.2
White
307
61.9
Asian or Pacific Islander American Indian/Alaskan native
11 14
2.2 2.8
(Other/not reported)
69
13.9
98
19.8
Ethnicity Hispanic Non-Hispanic
343
69.2
(Not reported)
55
11.1
18–30
173
34.9
31–45
187
37.7
46–65
132
26.6
4
0.8
Never married
191
38.5
Married
208
41.9
86 5
17.3 1.0
6
1.2
Age
(Not reported) Marital status
Divorced Widowed (Not reported) Education No high school diploma
92
18.5
High school or equivalent
160
32.3
Some college
175
35.3
College degree
65
13.1
(Not reported)
4
0.8
Personal annual income \$10,000
58
11.7
$10,000–$14,999
55
11.1
$15,000–$24,999
106
21.4
$25,000–$39,999
143
28.8
$40,000–$59,999
93
18.8
[$60,000
28
5.6
13
2.6
Health care
85
17.1
Transportation, delivery
63
12.7
108
21.8
Sanitation, housekeeping, landscaping
41
8.3
Distribution, warehousing, shipping
44
8.9
Electrical/mechanical, plumbing, auto repair
40
8.1
Manufacturing, assembly, materials handling
13
2.6
Construction trades
26
5.2
(not reported) Occupational categories
Retail, restaurant, flight attendant
(other/not reported)
based on mandatory employer reporting of workplace injuries (62.2 % for overexertion, 16.3 % for bodily reaction, 7.8 % for fall on same level, 3.5 % for fall to lower level) [49]. Bivariate intercorrelations among the eight predictormeasures are shown in Table 2, and their associations with 3-month return to work and composite clinical case ratings are shown in Table 3. All inter-correlations were low to moderate (B0.64), suggesting that none of the predictor variables were highly overlapping or redundant. The highest correlations among predictor variables were between activity avoidance and life impact of pain (r = 0.64) and between pain catastrophizing and depressive symptoms (r = 0.60). The only correlations that failed to meet statistical significance (p [ 0.05) were the correlations of organizational support with both functional limitation and pain intensity. At 3-month follow-up, mean pain intensity had improved to 2.92 (SD = 2.85) and functional limitation decreased to 23.43 (SD = 24.87). Seventy-seven percent of participants had resumed their normal work sometime before the 3-month follow-up, and 60 % were considered recovered according to the composite clinical case rating. All of the eight predictor-variables were significantly associated with both full-duty return to work and the composite clinical case rating at 3-month follow-up (p \ 0.05). The eight predictor-variables were standardized (z-scores), then subjected to a K-means cluster analysis. When 5 clusters were specified, the Euclidean distance fell below 2.0; thus, the 4-cluster solution (Table 4) was chosen which converged after 15 iterations with the Euclidian distances between cluster centers varying from 2.00 to 5.04. ANOVA results comparing group means for the 4-cluster solution (Table 4) show the relative contribution of each variable to the separation of groups overall. The omnibus test of group differences was statistically significant for all eight measures. Pain intensity had the lowest F value for discriminating groups overall, and pain catastrophizing the highest. Interpreting and labeling of clusters was accomplished by noting the largest deviations of cluster means from the
123
J Occup Rehabil Table 2 Intercorrelations (Pearson product-moment) among eight predictor variables assessed at an initial visit for acute LBP (N = 496) Predictor variable
LIFE
SUPPT
KINES
Recovery expectations (RECOV)
0.47**
-0.18**
0.47**
Life impact of pain (LIFE)
1.00
-0.25**
0.64**
1.00
0.21**
Organizational support (SUPPT) Kinesiophobia (KINES)
1.00
Functional limitation (FUNC)
FUNC
CATAS
DEPRES
0.37**
0.48**
0.37**
0.40**
0.55**
0.45**
-0.18**
-0.29**
-0.07
PAIN 0.28** 0.26** -0.02
0.44**
0.57**
0.40**
0.30**
1.00
0.50**
0.37**
0.49**
Pain catastrophizing (CATAS)
1.00
Depressive symptoms (DEPRES)
0.60**
0.41**
1.00
0.22**
Pain intensity (PAIN)
1.00
** Correlation significant at the 0.01 level
Table 3 Distribution characteristics of predictor variables and relation to 3-month outcomes (n = 359) Descriptive statistics
3-month outcome measures Full-duty return-to-worka
Mean Recovery expectations Life impact of pain Organizational support Kinesiophobia
SD
Median
OR
Composite clinical case ratingb p value
95 % CI
OR
p value
95 % CI
8.5
3.9
8.0
0.88
0.82–0.94
\0.001
1.21
1.13–1.29
\0.001
20.5
5.0
20.0
0.89
0.85–0.94
\0.001
1.14
1.09–1.20
\0.001
4.0
1.4
3.9
1.20
1.00–1.43
0.048
0.80
0.69–0.94
0.007
28.1
5.5
28.0
0.93
0.89–0.97
0.001
1.08
1.03–1.13
0.001
Functional limitation
50.9
22.0
52.0
0.98
0.97–0.99
\0.001
1.02
1.01–1.04
\0.001
Pain catastrophizing
18.9
13.5
17.0
0.97
0.95–0.99
\0.001
1.06
1.04–1.08
\0.001
Depressive symptoms
15.4
10.9
13.0
0.96
0.94–0.98
0.002
1.05
1.03–1.07
\0.001
6.8
2.0
7.0
0.76
0.66–0.89
\0.001
1.48
1.29–1.69
\0.001
Pain intensity a
Return to full duty work with no restrictions (77 % of respondents)
b
Clinical case defined as unable to resume full duty work, pain rating C5, or functional limitation C50 (40 % of respondents)
Table 4 Final cluster centers for a 4-cluster classification of patients with acute LBP (Visit 1) (n = 495) Final cluster centers (z-scores)
Clusters
Error
Significance
Cluster 4
MS
df
MS
df
0.54
-0.71
53.240
3
0.680
490
78.28
\0.001
-0.08
-0.65
64.490
3
0.597
473
107.97
\0.001
-0.04
-0.86
70.344
3
0.562
475
125.16
\0.001
-0.71
-0.45
69.610
3
0.578
488
120.39
\0.001
0.004
-0.87
71.857
3
0.553
476
129.84
\0.001
0.98
0.50
-0.85
78.069
3
0.515
477
151.50
\0.001
1.34 1.17
-0.02 -0.18
-0.81 -0.72
86.651 67.538
3 3
0.462 0.578
478 473
187.38 116.85
\0.001 \0.001
Cluster 1
Cluster 2
Pain intensity
-0.26
0.66
Recovery expectations
-0.06
1.22
Life impact of pain
0.16
1.08
Organizational support
0.86
0.48
Kinesiophobia
0.15
1.08
Physical limitation
-0.33
Pain catastrophizing Depressive symptoms
-0.08 0.15
Cluster 3
F
p
No scales are reversed but presented in its original form; cluster 1 = workplace concerns; cluster 2 = emotional distress; cluster 3 = activity limitation; cluster 4 = minimal risk
grand mean using a radar graph (Fig. 1). On each of the spokes of the radar graph, the mean standardized scores are plotted by cluster (a score of ‘‘0’’ representing the grand mean). Cluster 1 consisted of 127 patients (26 %) who
123
reported lack of organizational support as a more pronounced problem relative to other groups. Cluster 2 consisted of 95 patients (19 %) who reported problems in nearly all areas, but the greatest elevations were related to
J Occup Rehabil Fig. 1 A radar graph showing the relative scores (z-scores) of four patient clusters on eight psychosocial variables assessed at an initial assessment for acute LBP (scores furthest from the center indicate higher risk)
Recovery expectations 1.5
Organizational support
1
Life impact of pain
0.5
0
-0.5
Depressive symptoms
Activity avoidance
-1
Pain intensity
Pain catastrophizing
Functional limitation Cluster 1: Workplace concerns (26%) Cluster 2: Emotional distress (19%) Cluster 3: Activity limitation (27%) Cluster 4: Minimal risk (29%)
emotional distress (catastrophizing, depression, poor recovery expectations, life impact of pain). Cluster 3 consisted of 131 patients (27 %) who had elevations with regard to pain intensity and functional limitation but were average in other respects. Cluster 4 consisted of 142 patients (29 %) who reported few concerns on any of the predictor variables. Based on these characteristics, we labeled the four clusters as ‘‘organizational concerns’’, ‘‘emotional distress’’, ‘‘activity limitation’’, and ‘‘minimal risk’’. Patients were then assigned to the nearest cluster grouping and compared on outcomes of pain, functional limitation, return to work, and the composite clinical case rating at 3-month follow-up (Tables 5 and 6). There was a significant main effect for the 4 clusters on pain outcomes at 3 months, F(df = 3) = 27.99, p \ 0.001. Post hoc comparisons using the Tukey HSD test indicated that the mean score of the emotional distress group (cluster 2) was significantly different from all the other groups (p \ 0.001), while the activity limitation group (cluster 3) was significantly different from the minimal risk group (cluster 4) (p \ 0.001). There was also a significant main effect for the four clusters on functional limitations after three months, F(df, 3) = 28.9, p \ 0.001), with the post hoc comparisons indicating the same differences between the clusters as for the pain outcome, except the minimal risk and workplace concerns group significantly differed as well.
In terms of return to work (Table 6), the emotional distress group was nearly six times more likely to have not resumed normal work responsibilities after 3 months, p \ 0.001. The workplace concerns and activity limitation groups showed some increased risk of not returning to work (OR = 1.96 and 1.47, respectively), but these effects did not reach statistical significance (p [ 0.05). The composite clinical case rating, however, showed statistically significant differences (p \ 0.05) between the minimal risk group and the other three groups. There was approximately a two-fold risk of caseness in the workplace concerns and activity limitation groups and a 13-fold increase in the emotional distress group. The workplace concerns group showed a slightly poorer response rate than the other groups (X2 = 11.4, p \ 0.001), and if attributed to job loss or job instability, could mean that the outcomes of this group are overly optimistic from our analysis. We tested whether the three variables that were excluded from cluster analysis showed any significant differences between the groups. The differences between the groups were consistent with our labeling of the clusters; the Workplace Friendship Scale and Job satisfaction were lower in the group lacking organizational support, and physical demands were greatest in the distress and the workplace group. To provide a common overall risk metric across the four clusters, a global severity index was computed for each
123
J Occup Rehabil Table 5 Analysis of variance comparing 3-month pain and functional limitation by initial patient clusters (n = 359) Pain—3 months Mean Cluster 4 (minimal risk)
SD
1.8
2.3
Functional limitation—3 months F
p value a
\.001
27.99
Mean
SD
F
p value
12.1
17.7
28.93
\.001b
Cluster 1 (workplace concerns)
2.5
2.5
21.4
22.3
Cluster 3 (activity limitation)
2.9
2.6
22.8
22.7
Cluster 2 (emotional distress)
5.4
2.9
44.4
27.4
a
Tukey post hoc test: emotional distress group [ activity limitation group [ workplace concerns group, minimal risk group
b
Tukey post hoc test: emotional distress group [ activity limitation group [ workplace concerns group, minimal risk group
Table 6 Logistic regression analysis comparing 3-month return-to-work and clinical caseness by initial patient clusters (n = 359) Subgroups
Unable to RTW (3 months)a OR (95 % CI)
Clinical case rating (3 months)b p value
OR (95 % CI)
p value
Cluster 4 (minimal risk)
1.00
Cluster 1 (workplace concerns)
1.96 (0.91–4.23)
0.086
1.00 2.18 (1.13–4.22)
0.021
Cluster 3 (activity limitation)
1.47 (0.69–3.11)
0.316
2.39 (1.29–4.41)
0.005
Cluster 2 (emotional distress)
5.88 (2.80–12.35)
\0.001
13.64 (6.40–29.0)
a
Unable to resume full duty work
b
Non-return to full duty work with or without limitations, or pain rating C5, or functional limitation C50
participant. The global severity index was the percentile rank score of an individual on the sum of all eight standardized measures. Thus, this index provided a global assessment of risk while giving equal weighting to each of the eight measures. Outcome results for each of the clusters are stratified by global severity index in Table 7. As shown in the table, all members of the emotional distress subgroup scored in the top 40th percentile on the global severity index, and all members of the minimal risk group scored in the lowest 40th percentile. The other two groups showed more intermediate values on the global severity index. This stratification of 3-month outcome measures also shows that individuals in the activity limitation and work concerns groups who scored in the lowest 60th percentile on global severity index had outcomes similar to the minimal risk group; thus, these individuals may not be in need of early intervention.
Discussion In the current study of acute, work-related LBP, we were able to distinguish four distinct subgroups of low and medium- to high-risk patients through a collection of selfreport questionnaires assessing symptom severity and patient concerns and expectations about recovery and return to work. The contrasting characteristics of these
123
\0.001
subgroups suggest early intervention strategies might be more effective if varied to meet the individual needs of patients at risk of developing chronic pain and back disability. Clinical care guidelines suggest minimal intervention in the acute stage of LBP to prevent overdependence on health care providers, to avoid unnecessary healthcare costs, and to avoid iatrogenic effects of over-pathologizing a non-serious medical condition [24, 50, 51]. However, our data provide some evidence that early intervention could be beneficial for appropriate subsets of high-risk patients, probably in the form of workplace coordination and support, physical activation, or cognitive-behavioral strategies to overcome emotional distress and negative pain beliefs. While further research is needed to test whether matching early intervention strategies to selected patients improves disability outcomes, this study provides further impetus for the development of tentative decision-making algorithms that could be tested in future research. The 4-group cluster solution and patient classification in this study mirrors that of two previous cohorts [21, 22] by showing some distinction between individuals with workplace barriers, those with marked activity limitations, and those reporting severe emotional distress. Unlike the previous studies, this study employed full-length scales with a total of 129 items to ensure that the constructs underlying group assignment had some reliability and validity for use in clinical decision-making and to avoid possible
J Occup Rehabil Table 7 Comparison of 3-month outcomes by cluster grouping and global severity index (N = 357 for all the 3-month outcomes) Global severity indexc
3-month outcome measures Functional limitation
Pain
%
M
SD
M
SD
%
Clinical case ratingb %
Minimal risk (n = 107)
Non RTWa
12.1
17.7
1.8
2.3
17 % (n = 14)
16 % (n = 22)
1 (n = 74)
0–20
10.8
17.0
1.7
2.4
15 %
21 %
2 (n = 33)
20–40
15.0
19.2
2.0
2.2
9%
21 %
3 (n = 0)
40–60
–
–
–
–
–
–
4 (n = 0)
60–80
–
–
–
–
–
–
5 (n = 0)
80–100
–
–
–
–
–
–
23 % (n = 19)
29 % (n = 40)
Activity limitation (n = 105) 1 (n = 1)
0–20
0
–
0
–
100 %
100 %
2 (n = 27) 3 (n = 40)
20–40
17.0
24.2
2.5
2.8
15 %
33 %
40–60
24.5
22.1
3.4
2.8
13 %
41 %
4 (n = 34)
60–80
25.9
20.8
2.7
2.3
21 %
35 %
5 (n = 3)
80–100
24.0
41.6
2.0
2.7
67 %
67 %
22 % (n = 18)
20 % (n = 28)
Workplace concerns (n = 79) 1 (n = 0) 2 (n = 15)
0–20 20–40
– 11.0
– 10.9
– 1.6
– 1.8
– 20 %
– 29 %
3 (n = 37)
40–60
18.2
23.3
2.2
2.7
19 %
30 %
4 (n = 25)
60–80
31.5
22.4
3.1
2.2
28 %
46 %
5 (n = 2)
80–100
34.5
26.2
6.0
1.4
50 %
100 %
38 % (n = 31)
36 % (n = 50)
Emotional distress (n = 66) 1 (n = 0)
0–20
–
–
–
–
–
–
2 (n = 0)
20–40
–
–
–
–
–
–
3 (n = 0)
40–60
–
–
–
–
–
–
4 (n = 4)
60–80
36.8
25.3
3.5
2.5
25 %
50 %
5 (n = 62)
80–100
44.9
5.5
3.0
48 %
80 %
27.7
a
Non-return to full duty work with or without limitations
b
Non-return to full duty work with or without limitations, or pain rating C5, or functional limitation C50 Higher percentage = more pain/disability/symptoms
c
misinterpretation of single-item questions. While a 10-page survey may not be feasible for screening all patients with LBP in an occupational health clinic or primary care setting, future work might be focused on reducing the number of total items while still preserving the reliability and validity of the underlying measures. In this way, a briefer assessment tool and decision-making algorithm could be developed to assist clinicians in sorting out those in more need of education, therapy, or support. Results of this study suggest that key psychosocial risk factors for chronic pain and disability can be reliably assessed almost immediately following pain onset; thus, this finding raises the question of whether clinicians should wait for several weeks (until there is an accumulated duration of pain and work absence) before applying new therapies or engaging other resources to prevent long-term disability. Perhaps future guidelines for LBP treatment might incorporate brief, routine psychosocial screening, even in the very early stages of pain.
Unlike previous studies of psychosocial risk indicators, this study involved very early assessment of psychosocial variables shortly after pain onset (mostly within 2 days). This is a rather unique finding that could imply that the psychosocial risk indicators are present already from the start of the acute LBP episode, as opposed to a slowdeveloping maladaptive response to unremitting pain. One direction for future studies could be to compare these immediate psychosocial responses with the same responses a few weeks later in the course to assess whether responses change during the course or remain unchanged. Emotional distress was a salient factor in the delayed functional recovery and return to work efforts of participants in this study, even when measured in the first few days after pain onset. While pain-related activity avoidance, depressive symptoms, and catastrophizing have received great attention in chronic pain, fewer studies have assessed emotional distress as a prognostic factor in the early weeks of LBP. In this
123
J Occup Rehabil
study, the rather high levels of depressive symptoms reported by a subset of patients emphasizes the need for front-line clinicians to provide reassurance and support and address unmet needs for coping with pain. Standardized cognitivebehavioral treatment strategies have been shown effective to improve coping of individuals with chronic pain [18, 52, 53], but behavioral treatments have just begun to be tested in the first 2 months after LBP onset [54]. The effectiveness of behavioral interventions for acute LBP might be improved if combined with patient screening to identify those reporting high levels of emotional distress. Though most clinical care guidelines (e.g., the Occupational Medicine Practice Guidelines) [24] suggest that psychosocial factors (e.g., expectations for recovery, concerns about re-injury, job satisfaction) be included in routine history taking for a new onset of LBP, there are no specific guidelines for dealing with acute emotional distress. The fear-avoidance model has been one of several key psychological frameworks to explain how acute or sub-acute pain might transition over time to a chronic state of depression, disability, and inactivity [55]. In this study, fear of movement (as measured by the TSK) was a predominant factor in the emotional distress group, and this was associated with delays in pain reduction, functional recovery, and return to work. However, a second group (the ‘‘activity limitation’’ group) displayed similar levels of pain and functional limitation, but without the corresponding elevations in psychological distress. While these individuals might be thought of as ‘‘adaptive copers’’, their 3-month outcomes were still poorer than that of the minimal risk group, so some of these individuals might benefit from early intervention, especially those involving graded activity instruction and gradual exposure to more physical tasks [56]. Both physical and psychosocial aspects of the workplace have been shown to influence return-to-work outcomes, especially for musculoskeletal disorders [57, 58]. Results of the study suggest that for a subgroup of individuals with acute, work-related LBP, a perceived lack of organizational support may be a bigger problem for returning to work than either emotional distress or activity limitation. These individuals might benefit from earlier employer communication, more explicit recommendations for job modification, and a worksite meeting to define responsibilities and to engage the help of immediate supervisors and co-workers. A variety of workplace-based return-to-work interventions, including an offer of job modification, have been shown to reduce disability duration [59], and these efforts may be especially important when individuals have less job tenure, less experience, more precarious employment arrangements, and weaker social and organizational ties at work. Perhaps more intensive efforts to plan and coordinate job modifications would be more cost-effective if targeted to this subgroup of workers.
123
This study is the first to apply cluster analysis among cases of acute, work-related LBP using full-length selfreport measures to quantify areas of patient concern and expectation in the first few days after pain onset. Other strengths of the study include a prospective design, use of multiple outcome measures, and a representative sampling from front-line occupational health clinics rather than from tertiary specialty clinics. Conclusions of the study, however, are limited by the population sampled and by reliance of the study on patient self-report data. Biological indicators (e.g., objective measurements and clinical exam findings) were not included in the clustering data, though all patients were evaluated for medical ‘‘red flags’’ as part of the initial visit (in keeping with our biopsychosocial framework). Previous studies have shown that both anatomical findings and clinician impressions after a physical exam add little to the prediction of outcomes, at least for non-specific, acute cases of LBP [15, 16, 44]. In contrast to traditional biomedical approaches, a more psychosocial approach to managing acute LBP may trigger concerns of social stigma or denial of workers compensation benefits, so these issues should be considered when applying psychological measures in patient screening. However, no adverse experiences were reported by respondents in the current study. Notwithstanding these study limitations, our primary conclusion is that the use of patient questionnaires of pain-related concerns and expectations can be useful to identify patients in greatest need of early intervention to alleviate emotional distress, overcome activity limitations, or increase workplace support, respectively. Randomized trials are needed to determine whether such a screening approach might improve functional recovery and return to work in these high-risk subgroups. Acknowledgments This research was supported by a 2006 visiting scholar award to SJ Linton from the Liberty Mutual Research Institute for Safety and a 2006 travel grant from the Scan/Design by Inger and Jens Brun Foundation, awarded to SJ Linton and WS Shaw by the International Association for the Study of Pain.
References 1. Institute of Medicine. Relieving pain in America: a blueprint for transforming prevention, care, education, and research. Washington, DC: National Academics Press; 2011. 2. Ricci JA, Stewart WF, Chee E, Leotta C, Foley K, Hochberg MC. Back pain exacerbations and lost productive time costs in United States workers. Spine (Phila Pa 1976). 2006;31(26):3052–60. 3. Centers for Disease Control and Prevention. Prevalence and most common causes of disability among adults—United States, 2005. MMWR. 2009;58:6. 4. Pengel LH, Herbert RD, Maher CG, Refshauge KM. Acute low back pain: systematic review of its prognosis. BMJ. 2003; 327(7410):323.
J Occup Rehabil 5. Wolter T, Szabo E, Becker R, Mohadjer M, Knoeller SM. Chronic low back pain: course of disease from the patient’s perspective. Int Orthop. 2011;35(5):717–24. 6. De Souza L, Oliver Frank A. Patients’ experiences of the impact of chronic back pain on family life and work. Disabil Rehabil. 2011;33(4):310–8. 7. Andersson GB. Epidemiological features of chronic low-back pain. Lancet. 1999;354(9178):581–5. 8. Linton SJ, Gross D, Schultz IZ, Main C, Cote P, Pransky G, et al. Prognosis and the identification of workers risking disability: research issues and directions for future research. J Occup Rehabil. 2005;15(4):459–74. 9. Hoffman BM, Papas RK, Chatkoff DK, Kerns RD. Meta-analysis of psychological interventions for chronic low back pain. Health Psychol. 2007;26(1):1–9. 10. Lambeek LC, van Mechelen W, Knol DL, Loisel P, Anema JR. Randomised controlled trial of integrated care to reduce disability from chronic low back pain in working and private life. BMJ. 2010;340:c1035. 11. Ostelo RW, van Tulder MW, Vlaeyen JW, Linton SJ, Morley SJ, Assendelft WJ. Behavioural treatment for chronic low-back pain. Cochrane Database Syst Rev. 2005;25(1):CD002014. 12. Hill JC, Whitehurst DG, Lewis M, Bryan S, Dunn KM, Foster NE, et al. Comparison of stratified primary care management for low back pain with current best practice (STarT Back): a randomised controlled trial. Lancet. 2011;378(9802):1560–71. 13. Foster NE, Hill JC, Hay EM. Subgrouping patients with low back pain in primary care: are we getting any better at it? Man Ther. 2011;16(1):3–8. 14. Shaw WS, Linton SJ, Pransky G. Reducing sickness absence from work due to low back pain: how well do intervention strategies match modifiable risk factors? J Occup Rehabil. 2006; 16(4):591–605. 15. Billis EV, McCarthy CJ, Oldham JA. Subclassification of low back pain: a cross-country comparison. Eur Spine J. 2007;16(7): 865–79. 16. Kamper SJ, Maher CG, Hancock MJ, Koes BW, Croft PR, Hay E. Treatment-based subgroups of low back pain: a guide to appraisal of research studies and a summary of current evidence. Best Pract Res Clin Rheumatol. 2010;24(2):181–91. 17. Fritz JM, Cleland JA, Childs JD. Subgrouping patients with low back pain: evolution of a classification approach to physical therapy. J Orthop Sports Phys Ther. 2007;37(6):290–302. 18. Brennan GP, Fritz JM, Hunter SJ, Thackeray A, Delitto A, Erhard RE. Identifying subgroups of patients with acute/subacute ‘‘nonspecific’’ low back pain: results of a randomized clinical trial. Spine (Phila Pa 1976). 2006;31(6):623–31. 19. Werneke MW, Hart DL, George SZ, Stratford PW, Matheson JW, Reyes A. Clinical outcomes for patients classified by fearavoidance beliefs and centralization phenomenon. Arch Phys Med Rehabil. 2009;90(5):768–77. 20. Nicholas MK, Linton SJ, Watson PJ, Main CJ. Early identification and management of psychological risk factors (‘‘yellow flags’’) in patients with low back pain: a reappraisal. Phys Ther. 2011;91(5):737–53. 21. Shaw WS, Pransky G, Patterson W, Linton SJ, Winters T. Patient clusters in acute, work-related back pain based on patterns of disability risk factors. J Occup Environ Med. 2007;49(2):185–93. 22. Steenstra IA, Ibrahim SA, Franche RL, Hogg-Johnson S, Shaw WS, Pransky GS. Validation of a risk factor-based intervention strategy model using data from the readiness for return to work cohort study. J Occup Rehabil. 2010;20(3):394–405. 23. US Department of Labor—Bureau of Labor Statistics. Occupational injury and illness classification manual: section 2. 2000. http://www.bls.gov/iif/oshsec2.htm. Accessed 30 July 2007.
24. American College of Occupational and Environmental Medicine. Occupational medicine practice guidelines: evaluation and management of common health problems and functional recovery in workers. 2nd ed. 2004. http://www.acoem.org/PracticeGuidelines. aspx. 2011. 25. Nielsen IK, Jex SM, Adams GA. Development and validation of scores on a two-dimensional workplace friendship scale. Educ Psychol Meas. 2000;60(4):628–43. 26. Dasinger LK, Krause N, Deegan LJ, Brand RJ, Rudolph L. Physical workplace factors and return to work after compensated low back injury: a disability phase-specific analysis. J Occup Environ Med. 2000;42(3):323–33. 27. Kopec JA, Esdaile JM, Abrahamowicz M, Abenhaim L, WoodDauphinee S, Lamping DL, et al. The quebec back pain disability scale. Measurement properties. Spine. (Phila Pa 1976). 1995; 20(3):341–52. 28. Davidson M, Keating JL. A comparison of five low back disability questionnaires: reliability and responsiveness. Phys Ther. 2002;82(1):8–24. 29. Jensen MP, Karoly P, Braver S. The measurement of clinical pain intensity: a comparison of six methods. Pain. 1986;27(1):117–26. 30. Childs JD, Piva SR, Fritz JM. Responsiveness of the numeric pain rating scale in patients with low back pain. Spine (Phila Pa 1976). 2005;30(11):1331–4. 31. Radloff LS. The CES-D scale. Appl Psychol Meas. 1977;1(3): 385–401. 32. Geisser ME, Roth RS, Robinson ME. Assessing depression among persons with chronic pain using the Center for Epidemiological Studies-Depression Scale and the Beck Depression Inventory: a comparative analysis. Clin J Pain. 1997;13(2):163–70. 33. Sullivan MJL, Bishop SR, Pivik J. The pain catastrophizing scale: development and validation. Psychol Assess. 1995;7(4):524–532. 34. Sullivan MJ, Stanish W, Waite H, Sullivan M, Tripp DA. Catastrophizing, pain, and disability in patients with soft-tissue injuries. Pain. 1998;77(3):253–60. 35. Kori SH, Miller RP, Todd DD. Kinesiophobia: a new view of chronic pain behavior. Pain Management. 1990(Jan/Feb):9. 36. Vlaeyen JW, Kole-Snijders AM, Boeren RG, van Eek H. Fear of movement/(re)injury in chronic low back pain and its relation to behavioral performance. Pain. 1995;62(3):363–72. 37. Woby SR, Roach NK, Urmston M, Watson PJ. Psychometric properties of the TSK-11: a shortened version of the tampa scale for kinesiophobia. Pain. 2005;117(1–2):137–44. 38. Eisenberger R, Huntington R, Hutchison S, Sowa D. Perceived organizational support. J Appl Psychol. 1986;71(3):500–7. 39. Eisenberger R, Fasolo PM, Davis-LaMastro V. Perceived organizational support and employee diligence, innovation, and commitment. J Appl Psychol. 1990;75(1):51–59. 40. Lynch PD, Eisenberger R, Armeli S. Perceived organizational support: inferior versus superior performance by wary employees. J Appl Psychol. 1999;84(4):7. 41. Byrne ZS, Hochwarter WA. I get by with a little help from my friends: the interaction of chronic pain and organizational support on performance. J Occup Health Psychol. 2006;11(3):215–27. 42. Myers SS, Phillips RS, Davis RB, Cherkin DC, Legedza A, Kaptchuk TJ, et al. Patient expectations as predictors of outcome in patients with acute low back pain. J Gen Intern Med. 2008; 23(2):148–53. 43. Heymans MW, de Vet HC, Knol DL, Bongers PM, Koes BW, van Mechelen W. Workers’ beliefs and expectations affect return to work over 12 months. J Occup Rehabil. 2006;16(4):685–95. 44. Shaw WS, Pransky G, Winters T. The back disability risk questionnaire for work-related, acute back pain: prediction of unresolved problems at 3-month follow-up. J Occup Environ Med. 2009;51(2):185–94.
123
J Occup Rehabil 45. Steinley D. K-means clustering: a half-century synthesis. Br J Math Stat Psychol. 2006;59(Pt 1):1–34. 46. Cormack RM. A review of classification. J Roy Stat Soc. 1971; 134(3):46. 47. Steinley D, Brusco MJ. Choosing the number of clusters in kappa-means clustering. Psychol Methods. 2011;16(3):285–97. 48. Shaw WS, Reme SE, Linton SJ, Huang YH, Pransky G. 3rd place, PREMUS best paper competition: development of the return-to-work self-efficacy (RTWSE-19) questionnaire–psychometric properties and predictive validity. Scand J Work Environ Health. 2011;37(2):109–19. 49. Bureau of Labor Statistics. Case and demographic characteristics for work-related injuries and illnesses involving days away from work (Tables R10, R50–R54). 2000. http://www.bls.gov/iif. Accessed 4 March 2003. 50. Chou R, Qaseem A, Snow V, Casey D, Cross JT Jr, Shekelle P, et al. Diagnosis and treatment of low back pain: a joint clinical practice guideline from the American College of Physicians and the American Pain Society. Ann Intern Med. 2007;147(7): 478–91. 51. Burton AK, Balague F, Cardon G, Eriksen HR, Henrotin Y, Lahad A, et al. Chapter 2. European guidelines for prevention in low back pain: November 2004. Eur Spine J. 2006;15(Suppl 2): S136–68. 52. Kerns RD, Sellinger J, Goodin BR. Psychological treatment of chronic pain. Annu Rev Clin Psychol. 2011;7:411–34.
123
53. Henschke N, Ostelo RW, van Tulder MW, Vlaeyen JW, Morley S, Assendelft WJ, et al. Behavioural treatment for chronic lowback pain. Cochrane Database Syst Rev. 2010;7(7):CD002014. 54. Slater MA, Weickgenant AL, Greenberg MA, Wahlgren DR, Williams RA, Carter C, et al. Preventing progression to chronicity in first onset, subacute low back pain: an exploratory study. Arch Phys Med Rehabil. 2009;90(4):545–52. 55. Linton SJ, Shaw WS. Impact of psychological factors in the experience of pain. Phys Ther. 2011;91(5):700–11. 56. Macedo LG, Smeets RJ, Maher CG, Latimer J, McAuley JH. Graded activity and graded exposure for persistent nonspecific low back pain: a systematic review. Phys Ther. 2010;90(6): 860–79. 57. Crook J, Milner R, Schultz IZ, Stringer B. Determinants of occupational disability following a low back injury: a critical review of the literature. J Occup Rehabil. 2002;12(4):277–95. 58. Steenstra IA, Verbeek JH, Heymans MW, Bongers PM. Prognostic factors for duration of sick leave in patients sick listed with acute low back pain: a systematic review of the literature. Occup Environ Med. 2005;62(12):851–60. 59. Franche RL, Cullen K, Clarke J, Irvin E, Sinclair S, Frank J. Workplace-based return-to-work interventions: a systematic review of the quantitative literature. J Occup Rehabil. 2005; 15(4):607–31.
