Home‐ and community‐level predictors of social connection in nursing home residents: A scoping review
Bibliographic record
Abstract
Background and Aims: Social connection is associated with better physical and mental health and is an important aspect of the quality of care for nursing home residents. The primary objective of this scoping review was to answer the question: what nursing home and community characteristics have been tested as predictors of social connection in nursing home residents? The secondary objective was to describe the measures of social connection used in these studies. Methods: We searched MEDLINE(R) ALL (Ovid), CINAHL (EBSCO), APA PsycINFO (Ovid), Scopus, Sociological Abstracts (ProQuest), Embase and Embase Classic (Ovid), Emcare Nursing (Ovid), and AgeLine (EBSCO) for research that quantified associations between nursing home and/or community characteristics and resident social connection. Searches were limited to English-language articles published from database inception to search date (July 2019) and update (January 2021). Results: We found 45 studies that examined small-scale home-like settings (17 studies), facility characteristics (14 studies), staffing characteristics (11 studies), care philosophy (nine studies), and community characteristics (five studies). Eight studies assessed multiple home or community-level exposures. The most frequent measures of social connection were study-specific assessments of social engagement (11 studies), the Index of Social Engagement (eight studies) and Qualidem social relations (six studies), and/or social isolation (five studies) subscales. Ten studies assessed multiple social connection outcomes. Conclusion: Research has assessed small-scale home-like settings, facility characteristics, staffing characteristics, care philosophy, and community characteristics as predictors of social connection in nursing home residents. In these studies, there was no broad consensus on best approach(es) to the measurement of social connection. Further research is needed to build an evidence-base on how modifiable built environment, staffing and care philosophy characteristics-and the interactions between these factors-impact residents' social connection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".