Protocol for a systematic review and meta-analysis of the prevalence of mental illness among nursing home residents
Bibliographic record
Abstract
Abstract Background There is a high prevalence of mental illness in nursing home residents compared to older adults living in the community. This was highlighted in the most recent comprehensive systematic review on the topic, published in 2010. In the context of a rapidly aging population and increased numbers of older adults requiring residential care, this study aims to provide a contemporary account of the prevalence of mental illness among nursing home residents. Methods This protocol was prepared in line with the PRISMA-P 2015 Statement. Systematic searches will be undertaken across six electronic databases: PubMed, Embase, Web of Science, PsycNET, CINAHL, and Abstracts in Social Gerontology. Peer-reviewed studies published from 2009 onwards which report the prevalence of mental illness within nursing home populations will be included. Database searches will be supplemented by forward and backward citation searching. Titles and abstracts of records will be screened using a semi-automated process. The full text of selected records will be assessed to confirm inclusion criteria are met. Study selection will be recorded in a PRISMA flowchart. A pilot-tested form will be used to extract data from included studies, alongside the JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data. A study characteristics and results table will be prepared to present key details from each included study, supported by a narrative synthesis. Random-effects restricted maximum likelihood meta-analyses will be performed to compute pooled prevalence estimates for mental illnesses represented in the identified studies. Heterogeneity will be assessed using Cochran’s Q and Higgins’ I 2 statistics. A Funnel plot and Egger’s test will be used to assess publication bias. The GRADE approach will be used to assess the quality of the body of evidence identified. Discussion The study will provide a comprehensive and contemporary account of the prevalence of mental illness among nursing home residents. Meta-analyses will provide robust prevalence estimates across a range of presentations. Key insights will be highlighted, including potential sources of heterogeneity. Implications for residents, researchers, care providers, and policymakers will be noted. Systematic review registration PROSPERO: CRD42023456226.
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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 | 0.119 | 0.190 |
| Meta-epidemiology (narrow) | 0.008 | 0.008 |
| Meta-epidemiology (broad) | 0.021 | 0.024 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.176 | 0.026 |
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".