Predictors of multidisciplinary treatment outcome in patients with chronic musculoskeletal pain

References

• Turk DC, Wilson HD, Cahana A. Treatment of chronic non-cancer pain, part 2. Lancet 2011;25:2226–34
   Google Scholar
• Vlaeyen FW, Morley S. Cognitive-behavioral treatments for chronic pain: what works for whom? Clin J Pain 2005;21:1–8
   PubMed Web of Science ®Google Scholar
• Turk DC, Wilson HD, Cahana A. Treatment of chronic non-cancer pain. Lancet 2011;337:2226–35
   Google Scholar
• Bremander AB, Holmström G, Bergman S. Depression and age as predictors of patient-reported outcome in a multidisciplinary rehabilitation programme for chronic musculoskeletal pain. Musculoskelet Care 2011;9:41–8
   PubMedGoogle Scholar
• Orenius TI, Koskela T, Koho P, et al. Anxiety and depression are independent predictors of quality of life in patients with chronic musculoskeletal pain. J Health Psychol 2013;18:167–75
   Google Scholar
• Van der H, Vollenbroek-Hutten MM, Groothuis-Oudshoorn KGM, Hermens HJ. Multidisciplinary rehabilitation treatments with chronic low back pain: a prognostic model for its outcome. Clin J Pain 2008;24:421–30
   PubMed Web of Science ®Google Scholar
• Michaelson P, Sjölander P, Johansson H. Factors predicting pain reduction in chronic back and neck pain after multimodal treatment. Clin J Pain 2004;20:447–54
   PubMed Web of Science ®Google Scholar
• Vollenbroek-Hutten MMR, Hermens HJ, Wever D, et al. Differences in outcome of a multidisciplinary treatment between subgroups of chronic low back pain patients defined using two multiaxial assessment instruments: the multidimensional pair inventory and lumbar dynamometry. Clin Rehabil 2004;18:566–79
   PubMed Web of Science ®Google Scholar
• Buchner M, Neubauer E, Zahlten-Hinguranage A, Schiltenwolf M. Age as a predicting factor in the therapy outcome of multidisciplinary treatment of patients with chronic low back pain – a prospective longitudinal clinical study in 405 patients. Clin Rheumatol 2007;26:385–92
   PubMed Web of Science ®Google Scholar
• Persson E, Lexell J, Eklund M, Rivano-Fischer M. Positive effects of a musculoskeletal pain rehabilitation program regardless of pain duration or diagnosis. PM&R 2012;4:355–66
   Google Scholar
• Keel PJ, Wittig R, Deutschmann R, et al. Effectiveness of in-patient rehabilitation for sub-chronic and chronic low back pain by an integrative group treatment program (Swiss multicentre study). Scand J Rehab Med 1998;30:211–19
   PubMedGoogle Scholar
• Hutten MMR, Hermens H, Zilvold G. Differences in treatment outcome between subgroups of patients with chronic low back pain using lumbar dynamometry and psychological aspects. Clin Rehabil 2001;15:479–88
   PubMed Web of Science ®Google Scholar
• Stigmar KGE, Petersson IF, Jöud A, Grahn BEM. Promoting work ability in a structured national rehabilitation program in patients with musculoskeletal disorders: outcomes and predictors in a prospective cohort study. BMC Musculoskel Disord 2013;14:57
   PubMed Web of Science ®Google Scholar
• Keogh E, McCracken LM, Eccleston C. Do men and women differ in their response to interdisciplinary chronic pain management? Pain 2005;114:37–46
   PubMed Web of Science ®Google Scholar
• Hampel P, Graef T, Krohn-Grimberghe B, Tlach L. Effects of gender and cognitive-behavioral management of depressive symptoms on rehabilitation outcome among orthopaedic patients with chronic low back pain: a 1 year longitudinal study. Eur Spine J 2009;181:1867–80
   Web of Science ®Google Scholar
• de Williams ACC, Richardson PH, Nicholas MK, et al. Inpatient vs. outpatient pain management: results of a randomized controlled trial. Pain 1996;66:13–22
   PubMed Web of Science ®Google Scholar
• de Rooij A, Roorda LD, Otten RHJ, et al. Predictors of multidisciplinary treatment outcome in fibromyalgia: a systematic review. Disabil Rehabil 2013;35:437–49
   PubMed Web of Science ®Google Scholar
• Scascighini L, Toma V, Dober-Spielmann S, Sprott H. Multidisciplinary treatment for chronic pain: a systematic review of interventions and outcomes. Rheumatology (Oxford) 2008;47:670–8
   PubMed Web of Science ®Google Scholar
• Aaronson NK, Muller M, Cohen PDA, et al. Translation, validation, and norming of the Dutch language version of the SF-36 Health Survey in community and chronic disease populations. J Clin Epidemiol 1998;51:1055–68
   PubMed Web of Science ®Google Scholar
• Bergman S, Jacobsson LTH, Herrström P, Petorsson IF. Health status as measured by SF-36 reflects changes and predicts outcome in chronic musculoskeletal pain: a 3-year follow up study in the general population. Pain 2004;108:115–23
   PubMed Web of Science ®Google Scholar
• Barelds DPH, Luteijn F. Measuring personality: a comparison of three personality questionnaires in the Netherlands. Personal Individ Differ 2002;33:499–510
   Web of Science ®Google Scholar
• Barelds DPH, Luteijn F, Van Dijk H, Starren J. Nederlandse Persoonlijkheids Vragenlijst-2, handleiding [manual for Dutch Personality Questionnaire, revised]. Lisse: Swets & Zeitlinger;2007 [in Dutch]
   Google Scholar
• Spinhoven P, ter Kuile MM, Linssen ACG. Coping met pijn vragenlijst; handleiding [The Coping with Pain Questionnaire: manual]. Lisse: Swets & Zeitlinger; 1994 [in Dutch]
   Google Scholar
• Rosenstiel AK, Keefe FJ. The use of coping strategies in chronic low back pain patients: relationship to patient characteristics and current adjustment. Pain 1983;17:33–44
   PubMed Web of Science ®Google Scholar
• 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;62:363–72
   PubMed Web of Science ®Google Scholar
• Arrindell W, Ettema H, Groenman N, et al. De groeiende inbedding van de Nederlandse SCL-90-R; psychodiagnostisch gereedschap. [Growing use of Dutch version of SCL-90-R psychodiagnostic instrument] De Psycholoog 2003;38:576–82
   Google Scholar
• Chapman JR, Norvell DC, Hermsmeyer JT, et al. Evaluating common outcomes for measuring treatment success for chronic low back pain. Spine 2011;36:s54–68
   PubMed Web of Science ®Google Scholar
• Turk DC, Dworkin RH, Burke LB, et al. Developing patient-reported outcome measures for pain clinical trials: IMMPACT recommendations. Pain 2006;215:208–15
   Web of Science ®Google Scholar
• Cohen J. Statistical power analysis for the behavioral sciences. New York: Academic Press, Inc; 1977
   Google Scholar
• Angst F, Brioschi R, Main CJ, et al. Interdisciplinary rehabilitation in fibromyalgia and chronic back pain: a prospective outcome study. J Pain 2006;7:807–15
   PubMed Web of Science ®Google Scholar
• Keller A, Hayden J, Bombardier C, Van Tulder M. Effect sizes of non-surgical treatments of non-specific low-back pain. Eur Spine J 2007;16:1776–88
   PubMed Web of Science ®Google Scholar
• Morley S, Williams A, Hussain S. Estimating the clinical effectiveness of cognitive behavioural therapy in the clinic: evaluation of a CBT informed pain management programme. Pain 2008;137:670–80
   PubMed Web of Science ®Google Scholar
• Lunde L-H, Nordhus IH, Pallesen S. The effectiveness of cognitive and behavioural treatment of chronic pain in the elderly: a quantitative review. J Clin Psychol Med Settings 2009;16:254–62
   PubMed Web of Science ®Google Scholar
• Mangels M, Schwartz S, Worringen U, et al. Evaluation of a behavioral-medical inpatient rehabilitation treatment including booster sessions: a randomized controlled trial. Clin J Pain 2009;25:356–64
   PubMed Web of Science ®Google Scholar
• Boonstra AM, Reneman MF, Schiphorst Preuper HR, et al. Differences between patients with chronic musculoskeletal pain treated in an inpatient or outpatient multidisciplinary rehabilitation program. IJRR 2014;37:187–91
   Google Scholar