Biopsychosocial Determinants for Total Knee Replacement Decisions Among Older Adults With Chronic Knee Osteoarthritis: A Scoping Review
Bibliographic record
Abstract
Background: Total knee replacement (TKR) is a common surgical intervention for older adults with chronic knee osteoarthritis (KOA). Given the prevalence of comorbidities in this population, health priorities may vary, influencing decision-making regarding TKR. Despite the increasing number of TKRs, no scoping review has systematically examined the determinants shaping older adults’ decisions using a biopsychosocial (BPS) model. Materials and Methods: Searches were undertaken in commercially produced and grey literature sources. Eligible studies included English-language qualitative and quantitative studies that investigated determinants influencing older adults’ decision towards TKR. Two independent reviewers screened the results. The data were then independently extracted, which was then collated and synthesized, using the BPS model. Results: Out of 999 abstracts screened, 23 studies met the inclusion criteria. The included studies took place in Australia, Canada, Germany, Japan, Kuwait, Sweden, Taiwan, Turkey, the United Kingdom and the United States. Ten studies used qualitative study designs while thirteen used varying quantitative study designs. Under BPS model, these determinants were grouped into biological determinants: baseline physical health, disease severity, and pain symptoms; psychological determinants, including coping strategies, feelings of loss, mental stress, depression, and anxiety; and social determinants: support networks, financial resources, health insurance, and access to referral systems and surgery. Conclusion: The decision for TKR in older adults with chronic KOA is shaped by an intricate interplay of biological, psychological, and social factors. The most consistent determinants included the desire for pain relief and the ability to regain physical function. Religion and spirituality significantly influence stress and anxiety in older adults and transportation system also presents significant challenges for TKR surgery. A multifaceted strategy that improves the structures, processes, and outcomes of decision for TKR surgery is required among older adults with chronic KOA. Future research with large, representative samples and a focus on the BPS framework is needed to further explore this complex decision-making process.
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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 | 0.013 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".