A Scoping Review of Psychological Sense of Community among Community Dwelling Older Adults
Bibliographic record
Abstract
Abstract Psychological sense of community (PSOC) is an important construct for health and well-being outcomes for older adults. Drawing on the Ecological Theory of Aging and the Age-Friendly Cities (AFC) framework, this scoping review explored how PSOC has been used in research with community dwelling older adults. I followed Arksey and O’Malley's (2005) scoping review guidelines. Initial database searches yielded 860 articles. I included 33 in the final sample. I grouped articles based on study populations and conceptualization and operationalization of PSOC. I used thematic analysis to explore topic areas and main findings. The AFC framework guided development of themes and others emerged during analysis. Results show most studies used Asian or White samples and focused on geographic community or neighborhoods. Among the several measures of PSOC, the Brief Sense of Community Scale performed best with older adults. Topical research areas in the thematic analysis were built (1) built environment and neighborhoods, (2) social participation and connection, (3) civic participation, (4) PSOC as a protective factor, (5) health and well-being, (6) relocation, and (7) scale development. PSOC was a consistent predictor of health and well-being and served as a mediator to link neighborhood or environmental characteristics with health and well-being. Future research needs to examine PSOC in geographically and culturally diverse samples and conduct further psychometric testing of PSOC scales with older adults. PSOC is conceptually related to the AFC framework and serves as a mechanism that links AFC features and well-being outcomes. These results can inform practice and refine theory.
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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 | 0.011 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.021 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".