Lived and care experiences of young people with chronic musculoskeletal pain and mental health conditions: a systematic review with qualitative evidence synthesis
Bibliographic record
Abstract
ABSTRACT: Chronic musculoskeletal pain (CMP) and coexisting mental health conditions impact young people; however, little is known about their lived and care experiences. In a prospectively registered systematic review with qualitative evidence synthesis (PROSPERO: CRD42022369914), we explored the following: (1) lived physical, psychological, and social experiences; and (2) care experiences/preferences of young people living with CMP and mental health conditions. Inclusion criteria: studies using qualitative methods; participants aged 16 to 24 years with CMP and coexisting mental health condition(s); phenomenon explored included lived and/or care experiences. Seven databases were searched (inception to 19-May-2024), study quality was assessed, data were extracted and analysed thematically, and GRADE-CERQual was used to assess confidence in findings. Twenty-two studies (23 reports) were included (>239 participants, 82% women). Lived experiences yielded 4 themes (9 findings): 2-way relationship between CMP and mental health (2 findings, low to moderate confidence); psychosocial implications of CMP (3 findings, very low-moderate confidence); uncertainty about future (2 findings, low-moderate confidence); coping with CMP and mental health conditions (2 findings, low-moderate confidence). Care experiences/preferences yielded 3 themes (8 findings): navigating healthcare systems (2 findings, moderate confidence); receiving appropriate care (3 findings, very low-moderate confidence); point-of-care experiences and care preferences (3 findings, very low-moderate confidence). Chronic musculoskeletal pain and mental health conditions are interconnected, significantly impacting young people's lives, identities, and socialisation, yet services for CMP and mental health are often inadequate and poorly integrated. The mechanisms and interplay of CMP and mental health require deeper exploration, including how young people may be better supported with personalised, holistic, developmentally and/or life-stage-appropriate integrated care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.051 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".