Abstract
Objective:
To determine the convergent validity and responsiveness of the work functioning impairment scale (WFun) in workers with musculoskeletal disorder-related pain.
Methods:
Participants were extracted from an internet user study and prospectively examined using the pain intensity numerical rating scale (pain-NRS), the work ability numerical rating scale (productivity-NRS), and the WFun at baseline, 2 weeks, 6 weeks, and 3 months. The convergent validity and responsiveness of the WFun were examined by multilevel regression analysis.
Results:
A total of 786 workers participated and 593 completed all surveys. The WFun score gradually increased and decreased as the pain-NRS and the productivity-NRS increased, respectively. Changes in the WFun score steadily increased and decreased as changes in the pain-NRS and the productivity-NRS increased, respectively. Multilevel analyses showed that all linear associations were significant.
Conclusions:
The convergent validity and responsiveness of the WFun were consistent with the expected direction and magnitude.
Keywords: Convergent validity, Occupational Health, Pain, Patient reported outcome measures, Presenteeism, Responsiveness
Introduction
The concept of presenteeism refers to the phenomenon of a person attending work despite complaints and ill health that require prompt rest and absence1), and it underscores the decreased productivity and below-normal work quality of the person at work2). Presenteeism not only increases the risk of an individual's future health problems but can also affect his/her job performance. Previously, it was thought that absenteeism, or not attending work, was the main cause of productivity loss. Recent studies, however, indicate that presenteeism, rather than absenteeism, is the main factor associated with productivity loss3,4). Therefore, studies have sought to develop tools to assess the extent to which medically related problems negatively affect job performance and to evaluate the associated loss in productivity.
Many such tools have been devised, including the Work Limitation Questionnaire (WLQ)5), the Work Productivity and Activity Impairment Questionnaire (WPAI)6), the Endicott Work Productivity Scale (EWPS)7), and the Stanford Presenteeism Scale (SPS)8,9). Studies using these tools have revealed that presenteeism may result from any of several causes, including depression10-12), stress13), burnout14), and fatigue15). One factor with a particularly strong impact on presenteeism is pain16-18), which has been shown to be associated with depression and stress19,20). Further, individuals experiencing pain are associated with high levels of absenteeism and presenteeism, which often leads to work change or work loss21-24).
The various available productivity assessment tools are designed on the basis of differing concepts. While some center on the loss of productivity associated with the period of time for which the person was experiencing difficulties, others examine physical or emotional factors, which, for example, indicate the intensity of pain in patients with pain-related problems or the degree of mental problems in patients with depression. In contrast, few tools evaluate workers' health-related abilities in the workplace. There is a crucial distinction between a person's productivity and their ability to function. Productivity is associated with output, which is defined by various factors, including an individual's ability to function, the work environment, technology, and workers' knowledge. Productivity can be improved, even if an individual's ability to work is reduced, by modernizing old work environments and technology using such methods as implementing assembly lines. In the health management of workers, evaluation tools focusing on workers' health-related abilities may be more suitable. Furthermore, tools that are not affected by illness type are preferable.
Fujino et al. developed an original questionnaire, the "work functioning impairment scale" (WFun), which evaluates a worker's health-related ability to complete their work tasks25). "Functioning" refers to "the ability of the individual to perform particular defined tasks." 26) The WFun was developed to correlate the severity of a person's health problems with the degree by which they limit the person's "functioning" at work. This concept is closely related to quality of life, but it differs from worker performance and behavior25). One of the features of the WFun was based on the Rasch model, a common statistical method used to evaluate individuals' latent abilities according to item responses27-30). The inclusion of this model means that the WFun can assess the ability of individual workers to perform at work at the time of measurement. Past studies have assessed and proven the quality of the WFun25,31) in accordance with consensus-based standards for the selection of health measurement instruments (COSMIN)32,33), a guide that is used to evaluate the methodological quality of newly developed health-related patient-reported outcomes. However, quality assessment of the WFun is not yet sufficient because it has not been verified for responsiveness, a requirement of COSMIN.
Tools used to assess and improve health problems must be validated to ensure that they can reliably detect changes over time. We aimed to assess the convergent validity and responsiveness of the WFun in workers with musculoskeletal disorder-related pain. In particular, we wanted to confirm that the constructs of interest are actually changed, rather than detecting general changes or clinically significant changes. We adopted the measurement definitions used by COSMIN32,33). In addition, we defined convergent validity as how well two theoretically related measures of constructs are actually related. Responsiveness was defined as the ability to detect changes in a measure of construct over time. According to COSMIN, responsiveness is an aspect of validity, and it is treated as a separate measurement to emphasize the difference between the validity of a single score and the validity of the change score32). Assuming that the WFun exhibits good convergent validity and good responsiveness, we hypothesized that 1) workers with high WFun scores would score higher on the pain numerical rating scale (pain-NRS) and lower on the work ability numerical rating scale (productivity-NRS) than workers with low WFun scores, and 2) workers with positive changes in the WFun would show more positive changes in the pain-NRS and more negative changes in the productivity-NRS than workers with negative changes in the WFun.
Methods
This series of studies was conducted via an internet investigation aimed at registered users. A commercial testing company performed an internet test user study. An email asking for participation in the study was sent to approximately 20,000 of 2 million registered internet test users. Users were screened for the use of statements such as "I am currently employed," "I currently have pain in muscles and joints that hinder my work or my daily life," and "I am between 20 and 59 years of age." We initially targeted 600 subjects for the study. To account for subjects dropping out during the follow-up, the first 786 respondents who satisfied the screening process and who agreed to participate in the questionnaires were enrolled in the study. We requested information about the respondents' age, sex, and job type, as well as their pain- and work-related conditions. All answers were self-reported and anonymized.
Evaluation of pain34)
Subjects were asked to indicate in which of the following body parts he/she felt pain: head, neck, shoulder, upper back, lower back, hip joint, upper extremities, lower extremities (including knees), and other. An 11-point pain-NRS was used to evaluate pain intensity, with 0 indicating no pain and 10 indicating the worst possible pain. Subjects were asked to indicate the average intensity of pain that he/she experienced within the last week.
Evaluation of work-related condition
The question "what is your current work capacity on a scale of 1 to 10 if '10' represents the best health condition you have experienced so far?" was used to generate a generic score on the productivity-NRS to evaluate subjects' self-reported work productivity.
The WFun assesses responses to seven items25): "I haven't been able to behave socially," "I haven't been able to maintain the quality of my work," "I have had trouble thinking clearly," "I have taken more rests during my work," "I have felt that my work isn't going well," "I haven't been able to make rational decisions," and "I haven't been proactive about my work." Respondents are required to choose from one of the following five response categories for each item: 1, "not at all"; 2, "one or more days a month"; 3, "about one day a week"; 4, "two or more days a week"; and 5, "almost every day." The final WFun score was the sum of the scores of the 7 items. Scores could range from 7 to 35, with higher scores indicating worse work ability.
Follow-up survey
Follow-up surveys were conducted at two weeks (wave 2), six weeks (wave 3), and three months (wave 4) after the baseline survey (wave 1). Respondents were asked questions related to the pain-NRS, the productivity-NRS, and the WFun at all waves.
Statistics
The convergent validity of the WFun for the pain-NRS and the productivity-NRS were examined by multilevel regression analyses in which repeated measurements were nested in individuals. The model used the WFun as a dependent variable and the pain-NRS and the productivity-NRS as independent variables.
The responsiveness of the WFun for the pain-NRS and the productivity-NRS were also examined by multilevel regression analyses. The change scores were calculated for the WFun, the pain-NRS, and the productivity-NRS by subtracting the follow-up score from the score at the previous wave. Change in the WFun was used as a dependent variable and changes in the pain-NRS and the productivity-NRS were used as independent variables.
All analyses were performed using STATA software (version 14). Statistical significance was determined using two-sided tests at a significance level of 0.05.
Results
Of the 786 subjects, 722 (92%), 680 (87%), and 593 (75%) subjects responded to the follow-up second, third, and fourth wave surveys, respectively. Since all items had to have a corresponding response, there were no missing data in the follow-up phases.
Table 1 shows the characteristics of the study subjects. Subjects' characteristics did not significantly differ among the waves. Low back pain was the most frequently reported symptom (30%), followed by pain in the shoulder (24%), lower extremities and knee (18%), and head and neck (12%).
Table 1.
Characteristics of the study subjects
| Wave 1 | Wave 2 | Wave 3 | Wave 4 | |
|---|---|---|---|---|
| SD, standard deviation; Pain-NRS, pain numeric rating scale; Productivity-NRS, productivity numeric rating scale; WFun, work functioning impairment scale. Pain-NRS ranges from 0 to 10, where 0=no pain and 10=worst possible pain. Productivity-NRS ranges from 0 to 10, where 0=least productive and 10=most productive in his/her work experience. WFun ranges from 7 to 35. | ||||
| Number of subjects | 786 | 722 | 680 | 593 |
| Follow-up period from baseline | baseline | 2 weeks | 6 weeks | 3 months |
| Sex, male | 50% | 52% | 52% | 53% |
| Age, mean (SD) | 40.1 (10.1) | 40.3 (10.1) | 40.4 (10.1) | 41.0 (10.0) |
| Job type | ||||
| Mainly desk work | 50% | 49% | 49% | 50% |
| Jobs mainly involving interpersonal communication | 18% | 18% | 18% | 18% |
| Mainly labor | 32% | 33% | 33% | 33% |
| Part of body with pain | ||||
| Head and neck | 12% | |||
| Shoulder | 24% | |||
| Upper back | 4% | |||
| Lower back | 30% | |||
| Hip joint | 3% | |||
| Upper extremities | 9% | |||
| Lower extremities and knee | 18% | |||
| Other | 1% | |||
| Pain-NRS, mean (SD) | 4.6 (1.9) | 4.4 (2.0) | 4.6 (2.0) | 4.3 (2.1) |
| Productivity-NRS, mean (SD) | 6.4 (1.9) | 6.5 (2.0) | 6.5 (1.9) | 6.5 (2.0) |
| WFun, mean (SD) | 15.6 (7.1) | 15.3 (7.5) | 15.8 (7.3) | 15.3 (7.6) |
Table 2 summarizes the convergent validity of the WFun for the pain-NRS and the productivity-NRS. For convergent validity, the cumulative total number of respondents collected across all four waves was 2,781. The mean WFun score gradually increased as the pain-NRS increased. The mean WFun score was 10.2 in subjects with zero on the pain-NRS and 20.3 in those with the highest score on the pain-NRS. Multilevel analyses showed a significant linear association between the pain-NRS and the WFun scores. Moreover, the mean WFun score gradually increased as the productivity-NRS decreased. The productivity-NRS was also associated with the WFun in the multilevel analyses. These results support hypothesis 1.
Table 2.
Convergent validity of work functioning impairment scale (WFun) for pain numeric rating scale (NRS) and productivity-NRS.
| Measure | Cumulative total number across the 4 waves | Mean WFun score | SD | Multilevel analyses* | ||
|---|---|---|---|---|---|---|
| Coefficient | SE | p | ||||
| SD, standard deviation; SE, standard error. Higher scores on pain-NRS and WFun indicate worse pain and low ability to work due to pain, respectively. Higher scores on productivity-NRS indicate better ability to work. * Multilevel analyses were conducted such that repeated measurements were nested in individuals. | ||||||
| Pain-NRS | ||||||
| 0 | 79 | 10.2 | 5.1 | Reference | ||
| 1-2 | 410 | 11.8 | 6.0 | 1.5 | 0.7 | 0.034 |
| 3-4 | 766 | 14.4 | 6.6 | 2.9 | 0.7 | <0.001 |
| 5-6 | 1110 | 16.0 | 7.2 | 3.8 | 0.7 | <0.001 |
| 7-8 | 362 | 19.2 | 8.1 | 6.1 | 0.7 | <0.001 |
| 9-10 | 54 | 20.3 | 9.6 | 7.0 | 1.0 | <0.001 |
| Productivity-NRS | ||||||
| 9-10 | 310 | 11.4 | 6.7 | Reference | ||
| 7-8 | 1205 | 13.5 | 6.1 | 1.1 | 0.4 | 0.002 |
| 5-6 | 881 | 16.6 | 6.9 | 2.9 | 0.4 | <0.001 |
| 3-4 | 270 | 19.7 | 8.0 | 5.2 | 0.5 | <0.001 |
| 0-2 | 115 | 23.6 | 8.7 | 7.7 | 0.6 | <0.001 |
Table 3 shows the responsiveness of the WFun to changes in the pain-NRS and the productivity-NRS. For responsiveness, the cumulative total number of respondents collected across all four waves was 1,995. The mean WFun score steadily increased with increases on the pain-NRS. Multilevel analyses revealed that subjects who reported a decrease in the pain-NRS, indicating improved health conditions, reported a decreased change in the WFun, which indicates an improvement in the ability to function at work. Conversely, subjects who reported an increase in the pain-NRS experienced an increased change in the WFun. The change in the WFun was also linearly associated with a change in the productivity-NRS. Multilevel analyses showed that subjects who reported an increase in the productivity-NRS, indicating an improvement in the ability to work, reported a decrease in the WFun. These results support hypothesis 2.
Table 3.
Responsiveness of change in work functioning impairment scale (WFun) for changes in pain numeric rating scale (NRS) and productivity-NRS.
| Change in measure | Cumulative total number across the 4 waves | Mean change in WFun score | SD | Multilevel analyses* | ||
|---|---|---|---|---|---|---|
| Coefficient | SE | p | ||||
| SD, standard deviation; SE, standard error. Positive change scores on pain-NRS and WFun indicate worsened pain and reduced ability to work due to pain, respectively. Positive change scores on productivity-NRS indicate improved ability to work. * Multilevel analyses were conducted such that repeated measurements were nested in individuals. | ||||||
| Pain-NRS | ||||||
| –9 to –4 | 78 | –2.6 | 8.0 | –2.4 | 0.7 | 0.001 |
| –3 to –2 | 280 | –1.1 | 6.7 | –1.0 | 0.4 | 0.018 |
| –1 to 1 | 1311 | –0.2 | 6.0 | Reference | ||
| 2 to 3 | 270 | 1.1 | 6.6 | 1.2 | 0.4 | 0.003 |
| 4 to 7 | 56 | 2.2 | 5.2 | 2.4 | 0.9 | 0.005 |
| Productivity-NRS | ||||||
| 5 to 10 | 30 | –2.2 | 9.3 | –2.3 | 1.2 | 0.044 |
| 1 to 4 | 659 | –1.3 | 6.3 | –1.4 | 0.3 | <0.001 |
| –1 to 0 | 1011 | 0.1 | 5.8 | Reference | ||
| –4 to –2 | 265 | 1.4 | 6.9 | 1.3 | 0.4 | 0.003 |
| –10 to –5 | 30 | 2.8 | 8.7 | 2.7 | 1.2 | 0.024 |
Discussion
We evaluated the convergent validity of the WFun for the pain-NRS and the productivity-NRS and the responsiveness of the WFun to changes in the pain-NRS and the productivity-NRS in workers with pain due to musculoskeletal disorders. We found significant linear associations in all cases.
A health-related patient-reported outcome is a subjective self-evaluation of a patient's health status that is not interpreted by a doctor or another individual. It is therefore important that the methodological quality of the tools used to obtain such outcomes is properly verified. According to COSMIN, when a gold standard is not available, hypothesis testing should be used to evaluate a tool's validity. Previous studies on the WFun have shown a good fit to the Rasch model in terms of specific objectivity and proven construct validity; and they have validated it against the hypothesis test of convergent validity by job disruptions, SPS, the Short Form 8 Health Survey (SF-8), and changes in employment status, and discriminant validity by sex, age, employment status, job type, and income31). In this study, we confirmed the convergent validity and responsiveness of the WFun in workers with pain. Our results were consistent with our hypotheses.
Recent systematic reviews have assessed the quality of evaluation tool measurement properties using the COSMIN checklist35,36). One such review37) showed that of 21 presenteeism evaluation tools, three had sufficient measurement properties, and only two tools, the EWPS and the SPS 6-item version (SPS-6), were adequate for assessing responsiveness to reveal important changes in constructs over time. In the responsiveness study described above38), work productivity and work ability were used to calculate change scores. Work productivity and work ability were assessed by single items that asked patients with rheumatoid arthritis or osteoarthritis to rate their changes in productivity from the baseline to being able to conduct their usual work activities. Our survey used a pain intensity assessment to calculate change scores due to the strong impact that pain has on presenteeism17,18). To our knowledge, this is the first report to use pain, determined by a numerical rating scale, in a presenteeism evaluation tool to assess responsiveness.
Pain often becomes chronic and, as well as being associated with presenteeism, can lead to negative consequences, such as early retirement, work disability, and absenteeism21-24). According to a five-year registry-based follow-up study, 12.6% of women and 8.8% of men take long-term sick leave owing to musculoskeletal diagnoses39). Many studies have further confirmed that work-related outcomes worsen as severe pain increases40), which was also observed using the WFun in this study. There are many pain-related diseases, including arthritis, irritable bowel syndrome, fibromyalgia, repetitive strain injury, neuropathic disease, and cancer; and there are many types of pain, including back pain, musculoskeletal pain, shoulder pain, headache, and menstrual pain. There are disease-specific evaluation tools for some of these diseases, which are widely used to improve the understanding of a patient's health status and therapeutic outcomes. However, while these tools may be useful for characterizing the condition of a particular disease, they may not be useful for occupational health evaluations. The WFun can be used as a common management tool for all employees because it aims to assess an individual's ability to work in the workplace rather than the status of a specific disease. That is, it may be more effective to evaluate and manage occupational health using a broader assessment viewpoint than one that focuses on specific diseases or their degree of severity within a given individual.
The present findings may suggest that the WFun offers the following advantages in worker management: (1) it consists of a few (seven) simple question items; (2) it is a specialized index for evaluating workers' ability to function at work and is easy to interpret without being constrained by the type or severity of health problem; (3) its total score is associated with a sufficient statistical evaluation, so there is no need to analyze the answer31); (4) it does not include health information, so non-medical staff can handle the data41); and (5) it is an objective tool in which the differential test function has been examined, so it can be used regardless of age, industry type, or occupation31).
Several limitations of the present study should be mentioned. First, we did not confirm the diagnosis of the subjects' health problems. Second, we did not obtain information about interventions, including medical treatment or changes in working conditions, during the follow-up. In particular, changes in working conditions may improve a worker's health-related function, which can mitigate work-functioning impairments without improvement in the worker's actual health conditions. Third, in terms of hypothesis testing, the results only indicate the direction of the association, and it is difficult to explain the magnitude of difference. Fourth, we used the productivity-NRS, a single item question, to confirm convergent validity in this study because it has been widely used as a component of many existing presenteeism tools5,8,9,42). However, the productivity-NRS itself is also ambiguous, and its validity has not been fully confirmed. Convergent validity should be verified using other presenteeism or work functioning evaluation tools. Multi-item measurements are generally better for assessing complex constructs than single-item measurements43). Therefore, it is important to select the most appropriate tool for the study question. Finally, the WFun was originally developed in Japanese and, as such, the English translated items in this report might be found to be inaccurate by back translation or cross-cultural validation.
In conclusion, the present study verified the convergent validity and responsiveness of the WFun for pain intensity, measured by the pain-NRS, among individuals with musculoskeletal disorders. The WFun also showed good convergent validity and responsiveness of self-reported productivity, as measured by a generic numeric rating scale. Nevertheless, further verification of the validity and responsiveness of the WFun is required, such as by targeting other populations or by performing a comparison with other tools.
Sources of Funding: This study was partly funded by the Occupational Health Promotion Foundation (2014), Japan.
Conflicts of interest: None declared.
References
- 1). Aronsson G, Gustafsson K, Dallner M. Sick but yet at work. An empirical study of sickness presenteeism. J Epidemiol Community Health 2000; 54: 502-509. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2). Hemp P. Presenteeism: At-work-but out of it. Harv Bus Rev 2004; 82 (10): 49-58. [PubMed] [Google Scholar]
- 3). Collins JJ, Baase CM, Sharda CE, et al. . The assessment of chronic health conditions on work preference, absence, and total economic impact for employers. J Occupy Environ Med 2005; 47 (6): 547-557. [DOI] [PubMed] [Google Scholar]
- 4). Loeppke R, Taitel M, Richling D, et al. . Health and productivity as a business strategy. J Occupy Environ Med 2007; 49 (7): 712-721. [DOI] [PubMed] [Google Scholar]
- 5). Lerner D, Amick BC 3rd, Rogers WH, et al. . The work limitations questionnaire. Med Care 2001; 39 (1): 72-85. [DOI] [PubMed] [Google Scholar]
- 6). Reilly MC, Zbrozek AS, Dukes EM. The validity and reproducibility of a work productivity and activity impairment instrument. Pharmacoeconomics 1993; 4 (5): 353-365. [DOI] [PubMed] [Google Scholar]
- 7). Endicott J, Nee J. Endicott Work Productivity Scale (EWPS): a new measure to assess treatment effects. Psychopharmacol Bull 1997; 33 (1): 13-16. [PubMed] [Google Scholar]
- 8). Brooks A, Hagen SE, Sathyanarayanan S, et al. . Presenteeism: critical issues. J Occup Environ Med 2010; 52 (11): 1055-1067. [DOI] [PubMed] [Google Scholar]
- 9). Koopman C, Pelletier KR, Murray JF, et al. . Stanford Presenteeism scale: health status and employee productivity. J Occup Environ Med 2002; 44 (1): 14-20. [DOI] [PubMed] [Google Scholar]
- 10). Burton WN, Pransky G, Conti DJ, et al. . The association of medical conditions and presenteeism. J Occup Environ Med 2004; 46: S38-45. [DOI] [PubMed] [Google Scholar]
- 11). Stewart WF, Ricci JA, Chee E, et al. . Cost of lost productive work time among US workers with depression. JAMA 2003; 289 (23): 3135-3144. [DOI] [PubMed] [Google Scholar]
- 12). Munir F, MacKay C, Yarker J, et al. . Back, but not better: ongoing mental health problems hamper return-to-work outcomes. Occupational Health at Work 2009; 5 (5): 17-20. [Google Scholar]
- 13).Medibank Private, Econtech, Economic Impact of Workplace Stress in Australia. Medibank Private, Econtech; 2008.
- 14). Dewa CS, Loong D, Bonato S, et al. . How does burnout affect physician productivity? A systematic literature review. BMC Health Serv Res 2014; 14: 325. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15). Swanson LM, Arnedt JT, Rosekind MR, et al. . Sleep disorders and work performance: findings from the 2008 National Sleep Foundation Sleep in America poll. J Sleep Res 2011; 20 (3): 487-494. [DOI] [PubMed] [Google Scholar]
- 16). Allen H, Hubbard D, Sullivan S. The burden of pain on employee health and productivity at a major provider of business services. J Occup Environ Med 2005; 47 (7): 658-670. [DOI] [PubMed] [Google Scholar]
- 17). Bielecky A, Chen C, Ibrahim S, et al. . The impact of co-morbid mental and physical disorders on presenteeism. Scand J Work Environ Health 2015; 41 (6): 554-564. [DOI] [PubMed] [Google Scholar]
- 18). Dibonaventura Md, Gupta S, McDonald M, et al. . Evaluating the health and economic impact of osteoarthritis pain in the workforce: results from the National Health and Wellness Survey. BMC Musculoskelet Disord 2011; 12: 83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19). Tsuji T, Matsudaira K, Sato H, et al. . The impact of depression among chronic low back pain patients in Japan. BMC Musculoskelet Disord 2016; 17 (1): 447. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20). Schell E, Theorell T, Hasson D, et al. . Stress biomarkers' associations to pain in the neck, shoulder and back in healthy media workers: 12-month prospective follow-up. Eur Spine J 2008; 17 (3): 393-405. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21). Wolfe F, Michaud K, Choi HK, et al. . Household income and earnings losses among 6,396 persons with rheumatoid arthritis. J Reumatol 2005; 32: 1875-1883. [PubMed] [Google Scholar]
- 22). Allaire S, Wolfe F, Niu J, et al. . Work disability and its economic effect on 55-64-years-old adults with rheumatoid arthritis. Arthritis Rheum 2005; 53 (4): 603-608. [DOI] [PubMed] [Google Scholar]
- 23). Hagberg M, Tornqvist EW, Toomingas A. Self-reported reduced productivity due to musculoskeletal symptoms: associations with workplace and individual factors among white-collar computer users. J Occup Rehabil 2002; 12 (3): 151-162. [DOI] [PubMed] [Google Scholar]
- 24). Patel AS, Farquharson R, Carroll D, et al. . The impact and burden of chronic pain in the workplace: a qualitative systematic review. Pain Pract 2012; 12 (7): 578-589. [DOI] [PubMed] [Google Scholar]
- 25). Fujino Y, Masamichi U, Hiroyuki I, et al. . Development and validity of a work functioning impairment scale based on Rasch model among Japanese workers. J Occup Health 2015; 57: 521-531. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26). Wilson IB, Clea PD. Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA 1995; 273 (1): 59-65. [PubMed] [Google Scholar]
- 27). Rasch G. An item analysis which takes individual differences into account. Br J Math Stat Psychol 1966; 19 (1): 49-57. [DOI] [PubMed] [Google Scholar]
- 28). Andrich D. Rasch models for measurement. Newbury Park, London: Sage; 1988 [Google Scholar]
- 29). Fischer GH, Molenaar IW. Rasch models: foundation, recent developments, and applications. New York: Springer-Verlag; 1995 [Google Scholar]
- 30). Bond TG, Fox CM. Applying the Rasch model: fundamental measurement in the human sciences. 3rd ed, Mahwah: Lawrence Erlbaum Associates; 2015 [Google Scholar]
- 31). Fujino Y, Shuichiro S, Hiroyuki I, et al. . Prospective cohort study of work functioning impairment subsequent absenteeism among Japanese workers. J Occup Environ Med 2016; 58 (7): e264-267. [DOI] [PubMed] [Google Scholar]
- 32). de Vet HCW, Knol DL, Terwee CB, Mokkink LB. Measurement in medicine. Cambridge: Cambridge University Press; 2011 [Google Scholar]
- 33). Mokkink LB, Terwee CB, Patrick DL, et al. . The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Qual Life Res 2010; 19: 539-549. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34). Hawker GA, Mian S, Kendzerska T, et al. . Measures of adult pain: Visual Analog Scale for Pain (VAS Pain), Numeric Rating Scale for Pain (NRS Pain), McGill Pain Questionnaire (MPQ), Short-Form McGill Pain Questionnaire (SF-MPQ), Chronic Pain Grade Scale (CPGS), Short Form-36 Bodily Pain Scale (SF-36 BPS), and Measure of Intermittent and Constant Osteoarthritis Pain (ICOAP). Arthritis Care Res 2011; 63: S240-252. [DOI] [PubMed] [Google Scholar]
- 35). Wales K, Clemson L, Lannin N, et al. . Functional assessments used by occupational therapists with older adults at risk of activity and participation limitations: A systematic review. PLoS One 2016; 11 (2): e0147980. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36). Noben CY, Evers SM, Nijhuis FJ, et al. . Quality appraisal of generic self-reported instruments measuring health-related productivity changes: a systematic review. BMC Public Health 2014; 14: 115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37). Ospina MB, Dennett L, Waye A, et al. . A systematic review of measurement properties of instruments assessing presenteeism. Am J Manag Care 2015; 21 (2): e171-185. [PubMed] [Google Scholar]
- 38). Beaton DE, Tang K, Gignac MA, et al. . Reliability, validity, and responsiveness of five at-work productivity measures in patients with rheumatoid arthritis or osteoarthritis. Arthritis Care Res (Hoboken) 2010; 62 (1): 28-37. [DOI] [PubMed] [Google Scholar]
- 39). Foss L, Gravseth HM, Kristensen P, et al. . The impact of workplace risk factors on long-term musculoskeletal sickness absence: a registry-based 5-year follow-up from the Oslo health study. J Occup Environ Med 2011; 53 (12): 1478-1482. [DOI] [PubMed] [Google Scholar]
- 40). Zhang W, Bansback N, Boonen A, et al. . Validity of the work productivity and activity impairment questionnaire--general health version in patients with rheumatoid arthritis. Arthritis Res Ther 2010; 12 (5): R177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41). Nagata T, Fujino Y, Saito K, et al. . Diagnostic accuracy of the Work Functioning Impairment Scale (WFun), a method to detect workers who have health problems affecting their work and to evaluate fitness for work. J Occupy Environ Med 2017; 59 (6): 557-562. [DOI] [PubMed] [Google Scholar]
- 42). Kessler RC, Barber C, Beck A, et al. . The World Health Organization Health and Work Performance Questionnaire (HPQ). J Occup Environ Med 2003; 45 (2): 156-174. [DOI] [PubMed] [Google Scholar]
- 43). Sloan JA, Aaronson N, Cappelleri JC, et al. . Assessing the clinical significance of single items relative to summated scores. Mayo Clin Proc 2002; 77 (5): 479-487. [PubMed] [Google Scholar]