Rates and Correlates of Unemployment Across Four Common Chronic Pain Diagnostic Categories
- 384 Downloads
Purpose To examine rates and correlates of unemployment across distinct common chronic pain diagnoses. Methods Data were analyzed from a sample of 2,382 patients with chronic pain in the Quebec Pain Registry (QPR). Patients were grouped into the following diagnostic categories based on their primary pain diagnosis recorded in the QPR: musculoskeletal pain; myofascial pain; neuropathic pain, and visceral pain. Analyses were performed to examine the associations between pain diagnosis, patient demographics, pain intensity, depressive symptoms, and unemployment status. Results Pain diagnosis, age, marital status, education, pain intensity, and depressive symptoms were each significant unique predictors of unemployment status in a hierarchical logistic regression analysis; the addition of depressive symptoms in this model contributed to the greatest increment of model fit. Conclusions Depressive symptoms are associated with unemployment across a number of common chronic pain conditions, even when controlling for other factors that are associated with unemployment in these patients. Depressive symptoms, as a modifiable factor, may thus be an important target of intervention for unemployed patients with chronic pain.
KeywordsDepressive symptomatology Chronic pain Unemployment
This study was supported by unrestricted education and research grants from the Louise and Alan Edwards Foundation, Montreal, Canada. The authors thank Annie Trépanier for her assistance in accessing the Quebec Pain Registry and in extracting data. Hili Giladi was supported by a grant from the Louise and Alan Edwards Foundation, Montreal, Canada. The Quebec Pain Registry is supported by funds from the Fonds de la Recherche en Santé du Québec and Pfizer.
Conflict of interest
The authors declare no conflict of interest.
- 2.Merskey H, Bogduk N. International association for the study of pain (IASP) classification of chronic pain. Seattle, Washington: IASP Press; 1994.Google Scholar
- 11.Olaya-Contreras P, Styf J. Biopsychosocial function analyses changes the assessment of the ability to work in patients on long-term sick-leave due to chronic musculoskeletal pain: the role of undiagnosed mental health comorbidity. Scand J Public Health. 2013;41(3):247–55.CrossRefPubMedGoogle Scholar
- 22.Raftery MN, Sarma K, Murphy AW, De La Harpe D, Normand C, McGuire BE. Chronic pain in the Republic of Ireland—community prevalence, psychosocial profile and predictors of pain-related disability: results from the Prevalence, Impact and Cost of Chronic Pain (PRIME) study, part 1. Pain. 2011;152(5):1096–103.CrossRefPubMedGoogle Scholar
- 30.Dworkin RH, Turk DC, Farrar JT, Haythornthwaite JA, Jensen MP, Katz NP, Kerns RD, Stucki G, Allen RR, Bellamy N, Carr DB, Chandler J, Cowan P, Dionne R, Galer BS, Hertz S, Jadad AR, Kramer LD, Manning DC, Martin S, McCormick CG, McDermott MP, McGrath P, Quessy S, Rappaport BA, Robbins W, Robinson JP, Rothman M, Royal MA, Simon L, Stauffer JW, Stein W, Tollett J, Wernicke J, Witter J. IMMPACT. Core outcome measures for chronic pain clinical trials: IMMPACT recommendations. Pain. 2005;113(1–2):9–19.CrossRefPubMedGoogle Scholar
- 31.Gerwin RD. Diagnosing fibromyalgia and myofascial pain syndrome: a guide. J Family Pract. 2013;62(12 Suppl 1):s19–25.Google Scholar
- 38.Statistics Canada Website. Unemployment rate, Canada, provinces, health regions (2013 boundaries) and peer groups annual (percent). http://www5.statcan.gc.ca/cansim/pick-choisir?lang=eng&p2=33&id=1095324. Accessed 18 Sep 2014.
- 42.Hoogendoorn WE, Bongers PM, deVet HCW, Ariëns GAM, van Mechelen W, Bouter LM. High physical work load and low job satisfaction increase the risk of sickness absence due to low back pain: results of a prospective cohort study. Occup Environ Med. 2002;59(5):323–328.Google Scholar
- 50.Dworkin RH, Turk DC, Wyrwich KW, Beaton D, Cleeland CS, Farrar JT, Haythornthwaite JA, Jensen MP, Kerns RD, Ader DN, Brandenburg N, Burke LB, Cella D, Chandler J, Cowan P, Dimitrova R, Dionne R, Hertz S, Jadad AR, Katz NP, Kehlet H, Kramer LD, Manning DC, McCormick C, McDermott MP, McQuay HJ, Patel S, Porter L, Quessy S, Rappaport BA, Rauschkolb C, Revicki DA, Rothman M, Schmader KE, Stacey BR, Stauffer JW, von Stein T, White RE, Witter J, Zavisic S. Interpreting the clinical importance of treatment outcomes in chronic pain clinical trials: IMMPACT recommendations. J Pain. 2008;9(2):105–21.CrossRefPubMedGoogle Scholar