Relationship Between Depression and Falls Among Nursing Home Residents: Protocol for an Integrative Review
Bibliographic record
Abstract
BACKGROUND: Aging exposes individuals to new health disorders and debilitating chronic diseases, yet most older adults, even in functional decline, do not want to leave their homes. Nevertheless, for many, institutionalization in a nursing home (NH) may become essential to ensure their continued safety and health. Depression is one of the most common psychiatric disorders among older adults, especially among those who are institutionalized. Depressed NH residents face a high risk of future functional decline and falls, decreasing their quality of life. The relationship between depression and falls is complex and bidirectional. Previous reviews have focused on home-dwelling older adults or explored the relationship between antidepressant drugs and falls. To the best of our knowledge, no integrative literature reviews have explored the relationship between depression and falls among NH residents. OBJECTIVE: Analyze studies on the relationship between depression and falls among NH residents. METHODS: We will conduct an integrative literature review of published articles in relevant scientific journals on the relationship between depression and depressive symptomatology and falls among NH residents. As usually defined, we will consider NH residents to be people aged 65 years and older who can no longer live safely and independently in their homes. We will also consider older adults on short-term stays in an NH for rehabilitation after hospital discharge. Retrieved articles will be screened for eligibility and analyzed following previously reported steps. The most pertinent bibliographical databases will be examined for qualitative, quantitative, and mixed methods studies, from inception until August 31, 2023, thus ensuring that all relevant literature is included. We will also hand-search the bibliographies of all the relevant articles found and search for unpublished studies in any language. If appropriate, we will consider conducting a meta-analysis of the studies retrieved. RESULTS: A first round of data collection was completed in March 2023. We retrieved a total of 2276 references. A supplementary literature search to ensure the most up-to-date evidence is ongoing. We anticipate that the review will be completed in late September 2023, and we expect to publish results at the end of December 2023. CONCLUSIONS: This integrative review will increase knowledge and understanding of the complex relationship between depression and falls in NH environments. Its findings will be important for developing integrated, multidisciplinary models and care recommendations, adaptable to each NH resident's situation and health status, and for creating preventive interventions to help them maintain or recover optimal health stability. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46995.
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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 | 0.040 | 0.050 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.016 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.070 | 0.008 |
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".