Psychosocial factors in knee osteoarthritis: Scoping review of evidence and future opportunities
Bibliographic record
Abstract
OBJECTIVE: Identify, describe and produce an evidence map of studies investigating psychosocial factors association with, or effect on, clinical outcomes for people with knee osteoarthritis. METHODS: Scoping review of interventional and observational studies was performed. Medline (Ovid), Embase (Ovid), Cumulated Index in Nursing and Allied Health Literature, PsycInfo and Web of Science were searched on the 15th May 2023. Screening, data extraction and analysis was performed by two independent researchers. Extracted information included characteristics of studies plus which psychosocial factors were used to investigate association with, or effect on, clinical outcome(s). Descriptive statistics summarized the study design, temporal trend, geographic distribution, frequency of each psychosocial factor and whether associations/effects were observed. RESULTS: 23,065 records were screened, with 108 studies selected. Eighty-two percent of studies (n = 89/108) were cross-sectional in design. Number of studies increased over time and spanned 28 countries. Most research originated from the Americas region (55 %, 59/108). Twenty-four psychosocial factors (11 psychological, 13 social) were identified. Depression (47 %, n = 48/102) and education (28 %, n = 29/102) were the most frequently reported psychological and social factors, respectively. Psychological factors were often reported to have an association with/effect on pain (81 %, n = 71/88) and physical function (75 %, n = 56/74). Social factors were less frequently reported to have an association with or effect on pain (57 %, n = 46/81) and physical function (50 %, n = 18/36). CONCLUSION: Psychosocial factors are often associated with clinical outcomes for people with knee osteoarthritis. High-quality longitudinal studies examining a wide range of psychosocial factors across diverse cultural and geographical settings are key to continue informing the development of biopsychosocial models of 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 | 0.025 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.028 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".