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Associations between social integration, participation and productivity loss among persons with chronic pain: a registry based cross sectional study



To examine associations between factors of social inclusion and participation and productivity loss in employed persons with chronic pain, assessed for an interprofessional pain rehabilitation programme. We hypothesized that factors of social inclusion and participation and work related social factors are significantly associated with productivity when experiencing chronic pain and we expected a moderate effect.


Cross-sectional study using data collected prospectively in an interprofessional patient registry for chronic pain. The primary end point was productivity loss, measured with the iMTA Productivity Costs Questionnaire. We included data from 161 individuals. To be included, persons had to be 18 years old or older, in paid work, and had to have a medical diagnosis of chronic pain syndrome with actual or potential tissue damage. In addition, participants had to have indicators of significant impairments in psychosocial functions.


Linear regression analysis showed that a highly stressful professional situation, frequent problems regarding the compatibility of the family and job and not being Swiss were associated with a significantly higher total productivity loss. Similar results were found for productivity loss in paid work. However, problems concerning the compatibility of the family and job did not reach the significance level for productivity loss in paid work.


The results of this study underscore the importance of factors of social inclusion and participation for interprofessional rehabilitation programmes to manage chronic pain especially when focussing on productivity loss.

Peer Review reports


Chronic pain (CP) is a major challenge worldwide, not only for those directly affected, their families and their professional environment [1], but also for the health care system, the economy and public health [2,3,4,5]. On an individual level, chronic pain affects physical and mental functioning [6,7,8], reduces quality of life [2] and productivity [9, 10]. In Europe and the USA, about one in five persons suffer from chronic pain [11, 12]. This corresponds to around 95 million people in the EU and around 50 million people in the USA. CP is thus one of the main causes of inability to work and – on a societal level – is responsible for enormous direct medical costs and loss of productivity [11, 12]. In our understanding, productivity or the loss of it due to illness measured in hours is the measurable outcome of work ability. Productivity loss in paid work includes both absenteeism and presenteeism. However, it should be noted that many closely related but different concepts are used in literature to measure the work-related outcome of rehabilitation programmes (e.g., ability to work, return to work, productivity, employment success). This fact complicates the comparability and interpretation of results.

One of the main groups of CP is chronic musculoskeletal pain (CMP) [13]. As a complex biopsychosocial phenomenon, CMP is highly demanding both for interprofessional interventions [1, 14, 15] and in research. In chronic pain research, social factors have received little attention. The authors of recent studies largely agree that social factors play an important but previously underestimated role in both the aetiology of CMP and concerning outcomes of rehabilitation programmes such as productivity despite CMP [1, 14, 16,17,18]. We define social factors as factors that characterize individuals as an integral part of their environment at different societal levels. At the societal micro and meso level, this means inclusion in personal networks as well as a fulfilling professional situation.

In this study, particular focus was placed on the association between productivity and social factors related to the individuals work situation as well as social inclusion and participation. Our previous research has shown that inclusion in the family and a circle of friends and the social situation at the workplace are experienced by those affected as significant factors influencing the sustainability of the outcomes of our interprofessional outpatient rehabilitation programme [19].

In recent studies, the following social, socioeconomic or sociodemographic factors have been proven to influence productivity / the ability to work / the return to work of persons with CMP: disability or social security pension status [14, 17, 20], significant others/ family [21, 22], educational status [21, 23, 24], the workplace situation and related job perceptions [25], residence status [26], socioeconomic status [23, 24] and social functioning in general [16]. However, most of the recent studies focus on the return to (paid) work and few on productivity or productivity loss. Thus, little is known about the association between social factors such as social inclusion and participation and work-related social factors and the productivity of persons with chronic pain.

The knowledge about the role of social factors is of central importance for the development and advancement of specialized interprofessional pain rehabilitation programmes. Thus the research question of this study was as follows: Which social factors are associated with productivity loss among individuals who are in paid work and beeing assessed for an interprofessional pain rehabilitation programme?

Based on the state of research and our experience in rehabilitation practice, we hypothesized that the factors of social inclusion and participation and work-related social factors are significantly associated with productivity in chronic pain and expected a moderate effect.


Study design and setting

This is a cross-sectional study using data collected prospectively in a patient registry for chronic pain. The study was conducted at the Department of Rheumatology and Immunology of the Inselspital, Bern University Hospital in 2020. The services offered by the Department include interprofessional outpatient and inpatient rehabilitation programmes for patients with CMP. In this study, we used baseline-data of patients evaluated for participation in these rehabilitation programmes. Criteria for inclusion were (1) age between 18 and 75 years; (2) diagnosis of chronic musculoskeletal pain syndrome according to ICD-10 [27] with chronic pain either (a) associated with actual or potential tissue damage or (b) associated with tissue damage and a mental disorder; (3) indicators of significant impairment in psychosocial functions. The exclusion criteria were: (1) a primary mental disorder, (2) refusal to participate in an interprofessional outpatient rehabilitation, (3) and limited skills in German language.

Database and data collection

For this study, we used health-related data from a patient registry for chronic pain (Chronic Pain Registry). The Chronic Pain Registry was developed in 2017/2018 as an internal clinical registry and was implemented in May 2018 following international guidelines and national recommendations for the development and operation of health-related registries [28]. It was the first interprofessional registry for persons suffering from chronic pain in Switzerland [29]. One of its aims is to analyse the associations of risk factors and impairments. For the Chronic Pain Registry, we used REDCap [30] with an integrated audit trail as an electronic data capture software and database platform. For entering survey data, participants were given a tablet computer in which to enter their survey data. A personalized QR code gave them access to the corresponding assessments in REDCap.. To ensure the highest possible quality of measurements, we developed a step-by-step guide in simple language and scheduled sufficient time in the treatment plan to complete the assessments. For entering the results of clinical tests, we trained designated members of the interprofessional team and gave them direct access to REDCap.


Productivity loss

The primary endpoint for this study was the iMTA Productivity Cost Questionnaire (iPCQ) [31] to evaluate the productivity loss of persons with chronic pain. Participants self-rated their productivity loss using the iPCQ. For this purpose, productivity loss due to absenteeism, presenteeism, and unpaid work were calculated using a given formula and added together to obtain a total score of productivity loss. The iPCQ is an internationally standardized, generic (diagnosis-unspecific) assessment tool for recording disease-related productivity loss, including absenteeism, presenteeism, and unpaid work. Although the iPCQ is a relatively new instrument, it has already been internationally validated [32,33,34]. To ensure comparability, we only used data on short-term productivity loss (productivity loss in the last 4 weeks) in the calculations.

Social factors

Due to a lack of a standardized and validated questionnaire for all social factors, we created a tailored Case Report Form (CRF), in which the relevant factors were assessed using items from three large national and international surveys to ensure the quality and validity of single questions. These surveys are the Swiss Household Panel [35], the Swiss Health Survey [36], and the Survey of Health, Ageing and Retirement in Europe [37]. The items assessed are the perception of occupational situation, the compatibility of family and job, and inclusion in personal networks as indicators for the inclusion in communities and residence status as an indicator for societal participation.


Participants rated their average pain intensity over the previous 7 days using a digital Visual Analogue Scale (VAS) from 0 (no pain) to 100 (worst pain). Both paper-based and digital VAS are well-validated measures in self-assessing pain intensity [38]. The digital VAS in REDCap measures subjective pain by asking the participants to mark their perception of pain on a line with 100 units. They have to mark the point by moving a digital slider. The selected slider position correspondents to a score ranging from 0 to 100, where higher scores indicate greater intensity of pain.


Participants responded to questions about net income per person in their household, and educational level. Information about sex and age were extracted directly from the clinic information system into the registry. For educational level, we recoded the values in three groups (ISCED 0 and 1, ISCED 2–4, ISCED 6–8) and treated them as dummy variables in the regression analysis because of the educational situation in Switzerland and the nominal scale of the variable.

Ethics approval and trial registration

The use of anonymized data for this study was approved by the Ethics Committee of the Canton of Bern in December 2018 (Project-ID 2018–01583). For this study we strictly followed the principles of biomedical [39] and social science ethics [40]. All patients were informed verbally and in writing about the objectives of a patient and quality registry and the benefits and risks of the study. All participants signed an informed consent form prior to inclusion. Data collection, transmission, storage, and analysis within this study were conducted strictly according to the legal requirements of the Swiss government [41, 42].

Data diagnostics and preparation

From a total of 461 sets of health-related person data opened in the registry, 349 were eligible for this study, and 170 of these indicated that they were in paid work. In 49 cases, we conducted follow-up telephone interviews to complete or check data for consistency. Most, but not all of the inconsistent or incomplete data sets could be completed or validated as a result. This resulted in 161 participants in this study. For details, please see Fig. 1.

Fig. 1
figure 1

Flowchart of included cases

Before and after conducting the regression analyses, we tested data for violations of assumptions (pre-analysis-testing of data and post-analysis-testing of residuals): Pre-testing showed no non-linear correlations in scatterplots and no strong (r < .8) correlations between scaled variables (no multicollinearity). We winsorized two extreme cases in the variable “net income per person in household”. The testing of residuals after regression analysis showed independence of residuals with Durbin-Watson-statistics of 2.04 for total productivity loss, and 2.00 for paid work productivity loss. Tests for outliers showed that the values of the residuals were within the limits. The highest VIF was 4.05 for both models indicating no multicollinearity, but P-P-diagram and scatterplots showed violations of the assumption of normal distribution of residuals and homoscedasticity for both models. Based on these results, the regression analyses were performed again using bootstrapping.

Statistical analyses

We conducted all statistical analyses using SPSS v.25 with fix-packs 1–3. We calculated descriptive statistics for productivity loss, age, sex, educational level, net income per person in household, pain intensity, stress in professional situation, compatibility family-job, satisfaction with personal relationships, and residence status. For parametric correlations we performed Pearson correlation index and for nonparametric correlations Spearman’s-Rho in order to examine the correlation between productivity loss and social and demographical factors.

Since we wanted to know what additional variance was explained by the social factors beyond that explained by demographic variables and pain, we conducted two hierarchical multiple regression analyses to examine in detail the relationship between selected variables of social inclusion with participation in chronic pain conditions. In order to provide methodologically sound statements, we calculated the models for total productivity loss separately from productivity loss at paid work.

The relationship between productivity or work ability, chronic pain [9, 10] and socioeconomic factors [43, 44] is well known from the literature. Since we suspected that social factors explained additional variance, we included the demographic factors (age, sex, net income per person in household, and educational level) into a first block, VAS pain into a second block, and the social factors into a third block.

The third block of predictor variables consisted of three subjectively rated social variables (stress in professional situation, satisfaction with social relationships, compatibility of family and job), and residence status. Beta values with 95% confidence interval, standardized b and p values for all variables were calculated. For each step in the model, explained variance (R2 and R2-change) were calculated.


Participant demographics

Participants included 161 adults with CMP who were assessed at the University Hospital Bern, Department of Rheumatology and Immunology between May 2018 and July 2020 and who would potentially participate in one of the clinic’s interprofessional rehabilitation programmes. The participants were predominantly female (71.4%, n = 115). The average age was 44.68 years (SD = 11.88, range 18–63). Most participants had a lower (20.5%; n = 33) or upper secondary education qualification (including an apprenticeship qualification) (47.8%, n = 77) and 22.3% (n = 36) had a tertiary degree (bachelor’s or higher). The mean net income per person in the household was about 2185 USD (SD = 1944 USD). compared with the median net income in Switzerland of 4559 USD per month in 2019 [45]. Mean pain intensity for participants in the week before admission to hospital was 65.2 (SD = 17.5) on a digital VAS-scale from 0 (no pain at all) to 100 (worst pain). The average workload of the participants in the 4 weeks before hospitalization was 32.43 hours per week (SD = 12.14). Complete details on participant demographics are presented in Table 1.

Table 1 Sociodemographic characteristics of participants

Associations between social factors and productivity loss

Bivariate correlation analyses revealed significant associations between total productivity loss and stress in professional situation (rs = .593; p = < .001), difficulties with the compatibility family-job (rs = .192, p = .003), residence status (r = −.197; p = .0012), and sex (r = .212, p = .007).

No significant correlations were found between age, net income per person in household, pain intensity, satisfaction with familial relationships, satisfaction with relationships in social environment, participation in social groups and educational level.

Productivity loss in paid work correlated significantly with stress in professional situation (rs = .471, p = < .001), residence status (r = − 208, p = .008), and sex (r = .294, p = < .001). In contrast to the total productivity loss, the compatibility family-job was not significantly associated with productivity loss in paid work. No significant correlations were found for age, net income per person in household,pain intensity, satisfaction with familial relationships, satisfaction with relationships in social environment, participation in social groups, and educational level. For all details on bivariate correlations, please see Table 2.

Table 2 Correlations for study variables

A series of linear regression analyses were then performed examining the significant correlations of the above-mentioned variables with productivity loss at paid work and total productivity loss. In the first step, sex, age, and uncompleted compulsory education correlated significantly with productivity loss (see Tables 3 and 4). Whereby male sex, higher age and uncompleted compulsory education predicted higher productivity loss in patients with chronic pain (see Tables 3 and 4). Including the intensity of pain in the models as a second step did not significantly increase the amount of variance explained and pain was not significantly associated with productivity loss, either in paid work or in total (ΔR2 = .000 for productivity loss at paid work, .001 respectively for total productivity loss). However, including the variables of social inclusion and participation in the models resulted in a significant increase of explained variance (see Tables 3 and 4). A highly stressful professional situation, frequent problems with the compatibility of the family and job and not being a Swiss national predicted a significantly higher total productivity loss. Similar results were found for productivity loss in paid work. However, problems concerning the compatibility of the family and job did not reached the significance level for productivity loss at paid work.

Table 3 Hierarchical regression results for total productivity loss, bootstrapped (N = 161)
Table 4 Hierarchical regression results for productivity loss at paid work, bootstrapped (N = 161)


The primary aim of this study was to evaluate the association between productivity loss and factors of social inclusion and participation among adultss with CMP who were in paid work. Our results showed that the three factors stress in professional situation, compatibility of the family and job, and residence status explained a significant part of total productivity loss and of productivity loss in paid work. However, pain intensity was not associated with productivity loss.

Our findings support the results of earlier studies that factors of social inclusion and participation had an effect on productivity or the ability to work of persons with chronic pain [1, 16, 21].

In contrast to some other studies [46, 47] but in line with de Vries et al., and Lillefjell [48, 49], pain was not significantly associated with productivity loss. The divergent study results regarding pain could be explained by the fact that personal or work-related variables (in the case of de Vries et al. and Lillefjell et al.) or variables of social inclusion and participation may have moderated the effect of pain and that the studies with divergent results include a general working population and not exclusively persons with chronic pain.

In our data, we found a moderate association between the experience of a stressful professional situation and productivity loss. In this context, it seems important that experiencing a professional situation as stressful is more than a result of an individual’s lack of coping strategies, as it is also a result of structural / institutional workplace conditions. Earlier studies found that structural (system-related) job factors affected the experience of professional situations as stressful or burdensome [50, 51]. These include factors of social inclusion and participation like the employers attitudes, lack of co-worker support, lack of institutional resources for workplace adaptation, or social prejudice and stereotypes [51, 52]. Jetha et al. (2019) showed that a lack of institutional workplace support has a significant negative impact on the productivity of people suffering from a rheumatic disease [53]. With our study, there is growing evidence that stressful professional situations such as a lack of support from the employer or lack of understanding from work colleagues may negatively affect the productivity of people with chronic illnesses. Therefore, the requirements and knowledge of employers should be taken into account in the process of setting interprofessional rehabilitation goals, of planning and implementing interventions.

To our knowledge, there are no studies to date that have examined associations between the compatibility of family and job and productivity or ability to work in the case of chronic pain.

In our sample, the compatibility of family and job was significant only for total productivity loss, but not for productivity loss in paid work. We interpret this fact in the sense that people with chronic pain tend to invest all their remaining energy in paid work and, therefore, lose productivity in unpaid work. This interpretation is supported by the results of a qualitative study [19]. The significant association evident in our data may be related to Switzerland’s relatively poorly developed family policy [54]. The supply of childcare places is insufficient to meet demand [55]. In addition, parental contributions for a childcare place are very high, which makes access particularly difficult for lower-income families [54].

According to the Swiss Federal Statistical Office (BFS), in contrast to most other European countries, most employed persons with care responsibilities cite at least one important obstacle to reconciling family and work. In most EU/EFTA countries, however, a clear majority does not see any obstacles in the reconciliation of family and work [56]. Against this background, the results of the study, in which more than half of the participants live with children, are not surprising. Considering that reconciling family and work is demanding in itself, it can quickly become overwhelming in the case of chronic illness and a poorly developed state childcare system, leading to productivity losses, both for paid and unpaid work. It would be interesting to see whether the compatibility of job and family has less impact on productivity in chronic pain in countries with a better developed public childcare system.

In our data, residence status also correlates with productivity loss. Specifically, individuals without Swiss citizenship have higher productivity losses from chronic pain than Swiss citizens. This is in line with the findings of Hamer et al. [26] on workers with chronic pain in Canada. Like Hamer et al., we assume that this association is related to the type of work (jobs that are easily accessible to people who are not Swiss nationals are often physically very demanding),to barriers in the healthcare system (language barriers, lack of information services) and social barriers (lack of supportive networks). However, it is essential that this relationship be examined in more detail from a social science perspective in future studies in order to understand its complexity. Only a precise understanding of this association allows an appropriate adaptation of the interventions in interprofessional programmes.

In summary, in our sample of patients with chronic pain, we found associations between productivity loss and residence status, stress in the professional situation, and the compatibility of family and job. These factors of social inclusion and participation explain a significant part of the productivity losses in persons with CMP and, therefore, need to be addressed in interprofessional pain rehabilitation programmes to ensure the long-term benefit of such interventions. In practice, this can be implemented, for example, through a careful and comprehensive social diagnosis, help in finding a job adapted to the persons’s health situation, support for supplementary childcare or social work family counselling. In order to effectively, efficiently and sustainably address these systemic and work-related factors, interprofessional pain rehabilitation teams should, therefore, include specialists for systemic interventions such as clinical social workers and occupational therapists.

Our results are primarily valid for persons of working age in paid work who suffer from chronic pain and have been assessed for rehabilitation in our clinic. Since our clinic is a central hospital with a large geographical catchment area (e.g. urban and rural regions), it can be assumed that our sample represents well the total population of people with chronic pain in paid work in Switzerland.

The major strength of this study is that it is one of the first to examine the relationship between productivity and factors of social inclusion and participation. It thus provides indications that relatives and employers must be involved in the professional rehabilitation process, and that the factors mentioned should be in focus in interprofessional rehabilitation programmes. Involving employers means considering their knowledge and requirements, e.g. by providing information about support options through social insurances. This should enable them to support people with chronic pain at the workplace, but also meet the requirements of the company.


Nevertheless, several limitations should be considered when interpreting the findings from this study. First, with our cross-sectional data, it is not possible to determine causality or the direction of the relationships. For example, lack of participation can affect productivity, but low productivity at work and the resulting feelings of stress and demoralisation can conversely undermine personal relationships and lead to strain on work and family. Prospective studies are needed to explore these associations in more detail. A second limitation is the use of the German version of the iPCQ as an outcome measure. The German version of the iPCQ has been translated by the developers, but has not yet been culturally validated for use in Switzerland. Some terms in the questionnaire are not adapted to country-specific terminology and could lead to difficulties in completing the questionnaire (e.g. the German word “schaffen” for “to achieve something” means “to work” in Swiss German).

The high dropout rate is a further limitation. However, this was caused by the necessity to open registry cases before the actual date of hospital admission. This was to ensure that all patients had the opportunity to complete the questionnaires during the short two-day-period of hospitalisation. However, this procedure also leads to the fact that many cases have to be closed again due to a no-show or refusal to consent or that surveys were incomplete or were filled out inconsistently for linguistic reasons.


The results of this study underscore the importance of factors of social inclusion and participation for interprofessional rehabilitation programmes to manage chronic pain – especially when focussing on productivity loss. Therefore, we recommend that in interprofessional rehabilitation programmes, productivity should be understood from a systemic approach, including structural (system-related) factors. Future research should focus on how factors of social inclusion and participation can best be assessed, and effectively addressed in health care programmes. Furthermore, it seems important to us to qualitatively explore the complex mechanisms between pain, productivity and factors of social inclusion and participation in more detail.

Availability of data and materials

The datasets generated and analysed during the current study are not publicly available due to legal reasons but are available from the corresponding author on reasonable request.


  1. Dueñas M, Ojeda B, Salazar A, Mico JA, Failde I. A review of chronic pain impact on patients, their social environment and the health care system. J Pain Res. 2016;9:457–67.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Breivik H, Collett B, Ventafridda V, Cohen R, Gallacher D. Survey of chronic pain in Europe: prevalence, impact on daily life, and treatment. Eur J Pain. 2006;10(4):287–333.

    Article  PubMed  Google Scholar 

  3. Leadley RM, Armstrong N, Lee YC, Allen A, Kleijnen J. Chronic diseases in the European Union: the prevalence and health cost implications of chronic pain. J Pain Palliat Care Pharmacother. 2012;26(4):310–25.

    Article  PubMed  CAS  Google Scholar 

  4. Simon LS. Relieving pain in America: a blueprint for transforming prevention, care, education, and research. J Pain Palliat Care Pharmacother. 2012;26(2):197–8.

    Article  Google Scholar 

  5. Wieser S, Riguzzi M, Pletscher M, Huber CA, Telser H, Schwenkglenks M. How much does the treatment of each major disease cost? A decomposition of Swiss National Health Accounts. Eur J Health Econ. 2018;19(8):1149–61.

    Article  PubMed  Google Scholar 

  6. Björnsdóttir SV, Jónsson SH, Valdimarsdóttir UA. Functional limitations and physical symptoms of individuals with chronic pain. Scand J Rheumatol. 2013;42(1):59–70.

    Article  PubMed  Google Scholar 

  7. Park S-M, Kim G-U, Kim H-J, Kim H, Chang B-S, Lee C-K, et al. Low handgrip strength is closely associated with chronic low back pain among women aged 50 years or older: a cross-sectional study using a national health survey. Plos One. 2018;13(11) Available from: Cited 2020 May 19.

  8. Gómez Penedo JM, Rubel JA, Blättler L, Schmidt SJ, Stewart J, Egloff N, et al. The complex interplay of pain, depression, and anxiety symptoms in patients with chronic pain: a network approach. Clin J Pain. 2020;36(4):249–59.

    Article  PubMed  Google Scholar 

  9. de Vries HJ, Reneman MF, Groothoff JW, Geertzen JHB, Brouwer S. Self-reported work ability and work performance in workers with chronic nonspecific musculoskeletal pain. J Occup Rehabil. 2013;23(1):1–10.

    Article  PubMed  Google Scholar 

  10. Blyth FM, March LM, Nicholas MK, Cousins MJ. Chronic pain, work performance and litigation. Pain. 2003;103(1):41–7.

    Article  PubMed  Google Scholar 

  11. Pain Alliance Europe. Survey on chronic pain 2017. Diagnosis, treatment and impact of Pain 2017; Available from:

    Google Scholar 

  12. Dahlhamer J, Lucas J, Zelaya C, Nahin R, Mackey S, DeBar L, et al. Prevalence of chronic pain and high-impact chronic pain among adults — United States, 2016. MMWR Morb Mortal Wkly Rep. 2018;67(36):1001–6.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Dieppe P. Chronic musculoskeletal pain. BMJ. 2013;346 Available from: Cited 2020 Sep 15.

  14. Becker N, Hojsted J, Sjogren P, Eriksen J. Sociodemographic predictors of therapeutic results in patients with chronic, non-malignant pain. Ugeskr Laeger. 2001;163(22):3073–7.

    PubMed  CAS  Google Scholar 

  15. Köke AJA, Smeets RJEM, Schreurs KM, van Baalen B, de Haan P, Remerie SC, et al. Dutch dataset pain rehabilitation in daily practice: content, patient characteristics and reference data. Eur J Pain. 2017;21(3):434–44.

    Article  PubMed  Google Scholar 

  16. Hengstebeck E, Roskos S, Breejen K, Arnetz B, Arnetz J. Chronic pain disrupts ability to work by interfering with social function: a cross-sectional study. Scand J Pain. 2017;17:397–402.

    PubMed  Google Scholar 

  17. Gatchel RJ, Polatin PB, Mayer TG. The dominant role of psychosocial risk factors in the development of chronic low back pain disability. Spine. 1995;20(24):2702–9.

    Article  PubMed  CAS  Google Scholar 

  18. Sturgeon JA, Zautra AJ. Social pain and physical pain: shared paths to resilience. Pain Manag. 2016;6(1):63–74.

    Article  PubMed  Google Scholar 

  19. Friedli T, Gantschnig BE. The role of contextual factors on participation in the life area of work and employment after rehabilitation: A qualitative study on the views of persons with chronic pain. Work. 2022;71(1):119–32. Available from:

  20. Straaton KV, Maisiak R, Wrigley JM, White MB, Johnson P, Fine PR. Barriers to return to work among persons unemployed due to arthritis and musculoskeletal disorders. Arthritis Rheum. 1996;39(1):101–9.

    Article  PubMed  CAS  Google Scholar 

  21. de Sola H, Salazar A, Dueñas M, Ojeda B, Failde I. Nationwide cross-sectional study of the impact of chronic pain on an individual’s employment: relationship with the family and the social support. BMJ Open. 2016;6:e012246.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Snippen NC, de Vries HJ, van der Burg-Vermeulen SJ, Hagedoorn M, Brouwer S. Influence of significant others on work participation of individuals with chronic diseases: a systematic review. BMJ Open. 2019;9(1):e021742.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Cancelliere C, Donovan J, Stochkendahl MJ, Biscardi M, Ammendolia C, Myburgh C, et al. Factors affecting return to work after injury or illness: best evidence synthesis of systematic reviews. Chiropr Man Therap. 2016;24(1) Available from: cited 2020 Apr 27.

  24. Hara KW, Bjørngaard JH, Jacobsen HB, Borchgrevink PC, Johnsen R, Stiles TC, et al. Biopsychosocial predictors and trajectories of work participation after transdiagnostic occupational rehabilitation of participants with mental and somatic disorders: a cohort study. BMC Public Health. 2018;18(1):1014.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Fishbain DA, Cutler RB, Rosomoff HL, Khalil T, Steele-Rosomoff R. Impact of chronic pain patients’ job perception variables on actual return to work. Clin J Pain. 1997;13(3):197–206.

    Article  PubMed  CAS  Google Scholar 

  26. Hamer H, Gandhi R, Wong S, Mahomed NN. Predicting return to work following treatment of chronic pain disorder. Occup Med (Lond). 2013;63(4):253–9.

    Article  CAS  Google Scholar 

  27. World Health Organization, Deutsches Institut für Medizinische Dokumentation und Information. ICD-10-WHO. Internationale statistische Klassifikation der Krankheiten und verwandter Gesundheitsprobleme, 10. Revision, Version 2019. 2019. Available from: Cited 2020 May 20

    Google Scholar 

  28. ANQ, FMH, H+, SAMS, University Medicine Switzerland. Register Recommendations. In: Recommendations for the development and operation of health-related registries; 2019. Available from: Cited 2020 May 20.

    Google Scholar 

  29. Gantschnig BE, Friedli T. Gesundheitsbezogene Register: Perspektive für Praxis und Forschung der Ergotherapie? Ergotherapie. 2020;02:14–6.

    Google Scholar 

  30. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap) – a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.

    Article  PubMed  Google Scholar 

  31. Bouwmans C, Hakkaart-van Roijen L, Koopmanschap M, Krol M, Severens H, Brouwer W. Productivity costs questionnaire manual. Rotterdam: Institute for Medical Technology Assessment, Erasmus Universiteit Rotterdam; 2013.

    Google Scholar 

  32. Bouwmans C, Krol M, Severens H, Koopmanschap M, Brouwer W, Hakkaart-van RL. The iMTA productivity cost questionnaire: a standardized instrument for measuring and valuing health-related productivity losses. Value Health. 2015;18(6):753–8.

    Article  PubMed  Google Scholar 

  33. Munk R, Storheim K, Småstuen MC, Grotle M. Measuring productivity costs in patients with musculoskeletal disorders: measurement properties of the Institute for Medical Technology Assessment Productivity Cost Questionnaire. Value Health. 2019;22(12):1410–6.

    Article  PubMed  Google Scholar 

  34. Kim H, Park KS, Yoo J-E, Kim S, Han S, Suh HS. Cultural Adaptation and Validation of the Korean Version of the iMTA Productivity Cost Questionnaire. Healthcare. 2020;8(2):184.,

  35. Voorpostel M, Tillmann R, Lebert F, Kuhn U, Lipps O, Ryser V-A, et al. Swiss Household Panel Userguide (1999–2018), Wave 20, February2020. Lausanne: FORS; 2020.

    Google Scholar 

  36. Bundesamt für Statistik BFS. Die Schweizerische Gesundheitsbefragung 2017 in Kürze. 2018.

    Google Scholar 

  37. Börsch-Supan A, Brandt M, Hunkler C, Kneip T, Korbmacher J, Malter F, et al. The survey of health, ageing and retirement in Europe (SHARE). Int J Epidemiol. 2013;42(4):992–1001.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Delgado DA, Lambert BS, Boutris N, McCulloch PC, Robbins AB, Moreno MR, et al. Validation of digital visual analog scale pain scoring with a traditional paper-based visual analog scale in adults. J Am Acad Orthop Surg Glob Res Rev. 2018;2(3) Available from: Cited 2020 Sep 15.

  39. Beauchamp TL, Childress JF. Principles of biomedical ethics. 6th ed. Oxford: Oxford University Press; 2009.

    Google Scholar 

  40. Economic and Social Research Council. Research ethics 2020. Available from: Cited 2020 May 20

    Google Scholar 

  41. Bundesversammlung der Schweizerischen Eidgenossenschaft. Bundesgesetz vom 30. September 2011 über die Forschung am Menschen (Humanforschungsgesetz, HFG). SR 810.30. 2011. Available from:

  42. Bundesversammlung der Schweizerischen Eidgenossenschaft. Bundesgesetz über den Datenschutz (DSG). 1992. Available from:

    Google Scholar 

  43. Aittomäki A, Lahelma E, Roos E. Work conditions and socioeconomic inequalities in work ability. Scand J Work Environ Health. 2003;29(2):159–65.

    Article  PubMed  Google Scholar 

  44. Jensen NK, Thielen K, Andersen I, Brønnum-Hansen H, Burström B, Nylén L, et al. Social inequality in functional limitations and workability for people with musculoskeletal painNatasja Koitzsch Jensen. Eur J Public Health. 2017;27(suppl_3) Available from: Cited 2021 Jan 20.

  45. Bundesamt für Statistik. Einkommensverteilung. Available from: Cited 2021 Apr 27

  46. Miranda H, Kaila-Kangas L, Heliövaara M, Leino-Arjas P, Haukka E, Liira J, et al. Musculoskeletal pain at multiple sites and its effects on work ability in a general working population. Occup Environ Med. 2010;67(7):449–55.

    Article  PubMed  Google Scholar 

  47. Truchon M. Determinants of chronic disability related to low back pain: towards an integrative biopsychosocial model. Disabil Rehabil. 2001;23(17):758–67.

    Article  PubMed  CAS  Google Scholar 

  48. de Vries HJ, Reneman MF, Groothoff JW, Geertzen JHB, Brouwer S. Workers who stay at work despite chronic nonspecific musculoskeletal pain: do they differ from workers with sick leave? J Occup Rehabil. 2012;22(4):489–502.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Lillefjell M, Krokstad S, Espnes GA. Factors predicting work ability FollowingMultidisciplinary rehabilitation for ChronicMusculoskeletal pain. J Occup Rehabil. 2006;14(4):543–55.

    Article  Google Scholar 

  50. Sullivan MJL, Feuerstein M, Gatchel R, Linton SJ, Pransky G. Integrating psychosocial and behavioral interventions to achieve optimal rehabilitation outcomes. J Occup Rehabil. 2005;15(4):475–89.

    Article  PubMed  Google Scholar 

  51. Soklaridis S, Ammendolia C, Cassidy D. Looking upstream to understand low back pain and return to work: psychosocial factors as the product of system issues. Soc Sci Med. 2010;71(9):1557–66.

    Article  PubMed  Google Scholar 

  52. Sullivan MJL, Adams H, Horan S, Maher D, Boland D, Gross R. The role of perceived injustice in the experience of chronic pain and disability: scale development and validation. J Occup Rehabil. 2008;18(3):249–61.

    Article  PubMed  Google Scholar 

  53. Jetha A, Johnson SR, Gignac MAM. Unmet workplace support needs and lost productivity of workers with systemic sclerosis: a path analysis study. Arthritis Care Res. 2019; n/a(n/a). Available from: Cited 2021 Jan 25.

  54. Jacobs Foundation. Whitepaper zur Investition in die frühe Kindheit: Fokus volkswirtschaftlicher Nutzen. Zürich; 2020. Available from:

  55. Stern S, Gschwend E, Iten R, Schwab Cammarano S. Kinderbetreuung und Erwerbstätigkeit: Was sich Eltern wünschen. Jacobs Foundation, INFRAS, gfs.bern; 2018. Available from:

  56. Bundesamt für Statistik BFS. Vereinbarkeit von Beruf und Familie in der Schweiz und im europäischen Vergleich 2018. Neuchâtel; 2020. Available from:

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We would like to thank all people with chronic pain who participate in the pain register for making their data available. We would also like to thank the clinic employees for their tireless work and our academic peers for their constructive contributions to the discussion of this research and its findings. Furthermore, we would like to thank Prof. Dr. Daniel Gredig, and Prof. em. Dr. med. Peter M. Villiger, for their support.


This work was supported by an internal research fund, the Foundation Johanna Duermueller-Bol, Muri, SWITZERLAND and Sandoz Pharmaceuticals, Rotkreuz, SWITZERLAND, [PO 3003668404]. The external donors have had no influence on the research.

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Authors and Affiliations



All authors contributed to the study conception and design. Material preparation, data collection and analysis were conducted by TF and BEG. The first draft of the manuscript was written by TF and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Thomas Friedli.

Ethics declarations

Ethics approval and consent to participate

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the Canton of Bern (Switzerland) in December 2018 (Project-ID 2018–01583). Informed consent was obtained from all patients.

Consent for publication

Not applicable. We only used anonymized data.

Competing interests

TF declares that he has no competing interest. JB declares that she has no competing interest. BEG declares that she has no competing interest.

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Friedli, T., Brodbeck, J. & Gantschnig, B.E. Associations between social integration, participation and productivity loss among persons with chronic pain: a registry based cross sectional study. BMC Musculoskelet Disord 23, 956 (2022).

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  • Widespread chronic pain
  • Social context
  • Linear models
  • Work
  • Rehabilitation