Interventions to support caregivers of older adults undergoing surgery: A systematic review
Bibliographic record
Abstract
INTRODUCTION: Increasing numbers of caregivers provide support to older adults after surgery, which is associated with stress and negative impacts on their health. Our review questions were: METHODS: The databases searched included PubMed, OVID MEDLINE, OVID PsycINFO, EBSCO CINAHL, OVID EMBASE, Web of Science Core Collection, Wiley Cochrane CENTRAL on February 14, 2024. Studies eligible for inclusion were randomized controlled trial (RCT) or quasi-experimental design with control groups, published in English, Dutch, German, French and Persian, included any unpaid caregiver, and the intervention must include a component specifically designed to meet the caregivers' needs. RESULTS: in total 27,845 were screened and 45 full texts were reviewed. Seven RCTs, two pilot RCTS, and four quasi RCTs were included. Only five interventions had any positive impact and included self-management, telehealth, education and a family-centered care model. CONCLUSION: Few effective interventions were identified and more engagement with caregivers may identify interventions that better target the caregivers' needs. PROSPERO REGISTRATION NUMBER: CRD42024519637.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".