A realist review to understand the efficacy and outcomes of interventions designed to minimise, reverse or prevent the progression of frailty
Bibliographic record
Abstract
Interventions to minimise, reverse or prevent the progression of frailty in older adults represent a potentially viable route to improving quality of life and care needs in older adults. Intervention methods used across European Innovation Partnership on Active and Healthy Ageing collaborators were analysed, along with findings from literature reviews to determine 'what works for whom in what circumstances'. A realist review of FOCUS study literature reviews, 'real-world' studies and grey literature was conducted according to RAMESES (Realist and Meta-narrative Evidence Synthesis: Evolving Standards), and used to populate a framework analysis of theories of why frailty interventions worked, and theories of why frailty interventions did not work. Factors were distilled into mechanisms deriving from theories of causes of frailty, management of frailty and those based on the intervention process. We found that studies based on resolution of a deficiency in an older adult were only successful when there was indeed a deficiency. Client-centred interventions worked well when they had a theoretical grounding in health psychology and offered choice over intervention elements. Healthcare organisational interventions were found to have an impact on success when they were sufficiently different from usual care. Compelling evidence for the reduction of frailty came from physical exercise, or multicomponent (exercise, cognitive, nutrition, social) interventions in group settings. The group context appears to improve participants' commitment and adherence to the programme. Suggested mechanisms included commitment to co-participants, enjoyment and social interaction. In conclusion, initial frailty levels, presence or absence of specific deficits, and full person and organisational contexts should be included as components of intervention design. Strategies to enhance social and psychological aspects should be included even in physically focused interventions.
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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 | 0.126 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".