Can ‘What Is Known’ about Social Isolation and Loneliness Interventions Sufficiently Inform the Clinical Practice of Health Care and Social Service Professionals Who Work with Older Adults? Exploring Knowledge-to-Practice Gaps
Bibliographic record
Abstract
Establishing intervention effectiveness is an important component of a broader knowledge translation (KT) process. However, mobilizing the implementation of these interventions into practice is perhaps the most important aspect of the KT cycle. The purpose of the current study was to conduct an umbrella review to (a) identify promising interventions for SI&L in older adults, (b) interpret (translate) the findings to inform clinical knowledge and practice interventions in different settings and contexts, and (c) highlight research gaps that may hinder the uptake of these interventions in practice. The broader purpose of this study was to inform evidence-based clinical practice guidelines on SI&L for HCSSPs. In line with other reviews, our study noted variations in methods and intervention designs that prohibit definitive statements about intervention effectiveness. Perhaps, the most significant contribution of the current review was in identifying knowledge-to-practice gaps that inhibit the implementation of interventions into practice-based realities.
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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 | 0.106 | 0.340 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.011 | 0.023 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".