Factors affecting depression among people with chronic musculoskeletal pain: A structural equation model

Gloria K. Lee, Fong Chan, Norman L. Berven

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


Objective: To adapt and test P. M. Lewinsohn, H. M. Hoberman, L. Teri, and M. Hautzinger's (1985) integrative model of depression for individuals with chronic musculoskeletal pain. Design: Structural equation modeling. Participants: Individuals with chronic pain (N = 171), recruited from 6 outpatient rehabilitation facilities in Canada. Outcome Measures: Two measures of the latent variable, depression (the Center for Epidemiologic Studies-Depression Scale and the Zung Self-Rating Depression Scale), along with multiple measures of each of 5 latent predictors (pain, interferences, stress, coping, and social and family support) and 2 measured predictors (preinjury psychopathology and catastrophizing). Results: The normed fit index, comparative fit index, and parsimony ratio indicated an adequate fit for the model, suggesting that stress, perceived severity of pain, activity interferences, and catastrophizing contributed to increased depression (vulnerabilities), whereas pain coping skills and social and family support contributed to decreased depression (immunities). Conclusions: Empirical support was found for the proposed model of depression for people with chronic musculoskeletal pain, and the model appears to provide useful information for clinical rehabilitation interventions.

Original languageEnglish
Pages (from-to)33-43
Number of pages11
JournalRehabilitation Psychology
Issue number1
Publication statusPublished - 2007 Feb

All Science Journal Classification (ASJC) codes

  • Physical Therapy, Sports Therapy and Rehabilitation
  • Rehabilitation
  • Clinical Psychology
  • Psychiatry and Mental health

Fingerprint Dive into the research topics of 'Factors affecting depression among people with chronic musculoskeletal pain: A structural equation model'. Together they form a unique fingerprint.

Cite this