Abstract
Objectives: To (i) identify predictors of outcome for the physiotherapy management of shoulder pain and (ii) enable clinicians to subgroup people into risk groups for persistent shoulder pain and disability.
Methods: 1030 people aged ≥18 years, referred to physiotherapy for the management of musculoskeletal shoulder pain were recruited. 810 provided data at 6 months for 4 outcomes: Shoulder Pain and Disability Index (SPADI) (total score, pain sub-scale, disability sub-scale) and Quick Disability of the Arm, Shoulder and Hand (QuickDASH). 34 potential prognostic factors were used in this analysis.
Results: Four classification trees (prognostic pathways or decision trees) were created, one for each outcome. The most important predictor was baseline pain and/or disability: higher or lower baseline levels were associated with higher or lower levels at follow up for all outcomes. One additional baseline factor split participants into four subgroups. For the SPADI trees, high pain self-efficacy reduced the likelihood of continued pain and disability. Notably, participants with low baseline pain but concomitant low pain self-efficacy had similar outcomes to patients with high baseline pain and high pain self-efficacy. Cut points for defining high and low pain self-efficacy differed according to baseline pain and disability. In the QuickDASH tree, the association between moderate baseline pain and disability with outcome was influenced by patient expectation: participants who expected to recover because of physiotherapy did better than those who expected no benefit.
Conclusions: Patient expectation and pain self-efficacy are associated with clinical outcome. These clinical elements should be included at the first assessment and a low pain self-efficacy response considered as a target for treatment intervention.
Methods: 1030 people aged ≥18 years, referred to physiotherapy for the management of musculoskeletal shoulder pain were recruited. 810 provided data at 6 months for 4 outcomes: Shoulder Pain and Disability Index (SPADI) (total score, pain sub-scale, disability sub-scale) and Quick Disability of the Arm, Shoulder and Hand (QuickDASH). 34 potential prognostic factors were used in this analysis.
Results: Four classification trees (prognostic pathways or decision trees) were created, one for each outcome. The most important predictor was baseline pain and/or disability: higher or lower baseline levels were associated with higher or lower levels at follow up for all outcomes. One additional baseline factor split participants into four subgroups. For the SPADI trees, high pain self-efficacy reduced the likelihood of continued pain and disability. Notably, participants with low baseline pain but concomitant low pain self-efficacy had similar outcomes to patients with high baseline pain and high pain self-efficacy. Cut points for defining high and low pain self-efficacy differed according to baseline pain and disability. In the QuickDASH tree, the association between moderate baseline pain and disability with outcome was influenced by patient expectation: participants who expected to recover because of physiotherapy did better than those who expected no benefit.
Conclusions: Patient expectation and pain self-efficacy are associated with clinical outcome. These clinical elements should be included at the first assessment and a low pain self-efficacy response considered as a target for treatment intervention.
Original language | English |
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Pages (from-to) | 825-834 |
Number of pages | 10 |
Journal | British Journal of Sports Medicine |
Volume | 53 |
Early online date | 9 Jan 2019 |
DOIs | |
Publication status | Published - 14 Jun 2019 |
Profiles
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Rachel Chester
- School of Health Sciences - Associate Professor
- Population Health - Member
- Rehabilitation - Member
Person: Research Group Member, Research Centre Member, Academic, Teaching & Research
-
Christina Jerosch-Herold
- School of Health Sciences - Emeritus Professor
- Rehabilitation - Member
Person: Honorary, Research Group Member
-
Mizanur Khondoker
- Norwich Medical School - Associate Professor in Medical Statistics
- Population Health - Member
- Norwich Epidemiology Centre - Member
- Epidemiology and Public Health - Member
Person: Research Group Member, Research Centre Member, Academic, Teaching & Research