Determining the Characteristics of Transition-Based Interventions most Effective in Enhancing Quality of Care for Seniors: A systematic Review
Bibliographic record
Abstract
Introduction: Seniors (65 years or older) often require additional support and resources during the transition from acute care to home. A comprehensive understanding of the transition-based literature will support the development and implementation of effective interventions, possibly resulting in organizational and individual benefits. Purpose: A systematic review was conducted to identify the characteristics of transition-based interventions most effective in enhancing quality of care for seniors transitioning from hospital to home. Methods: Primary research that evaluated a transitional care intervention for seniors and measured one of more quality of care outcome were included. Chi-square test for independence, ANOVA, and descriptive analysis were used. Results: Forty-six interventions were reviewed for their specific characteristics. Multicomponent interventions which used multiple delivery methods (face-to-face/telephone), over one-to-three months (p= <0.05), were most effective in enhancing quality of care. Implications/Conclusions: Understanding the most effective intervention characteristics may support the provision of effective/efficient transitional care for seniors moving from acute care to home.
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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 | 0.015 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".