Relationship Between Depression and Falls Among Nursing Home Residents: Integrative Review (Preprint)
Bibliographic record
Abstract
BACKGROUND Depression is a highly prevalent psychopathological condition among older adults, particularly those institutionalized in nursing homes (NHs). Unfortunately, it is poorly identified and diagnosed. NH residents are twice as likely to fall as community-dwelling older adults. There is a need for more knowledge about the mechanisms and relationships between depression and falls. OBJECTIVE This study aims to identify, analyze, and synthesize research on the relationships between depression and falls among NH residents. METHODS A literature search was conducted in October 2023 in the following bibliographic databases: MEDLINE ALL Ovid, Embase, CINAHL with Full Text EBSCO, APA PsycInfo Ovid, Web of Science Core Collection, the Cochrane Database of Systematic Reviews Wiley, and ProQuest Dissertations & Theses A&I. Clinical trials were searched for in the Cochrane Central Register of Controlled Trials Wiley, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform. Additional searches were performed using Google Scholar, the DART-Europe E-theses Portal, and backward citation tracking. The Newcastle-Ottawa Scale and the Appraisal tool for Cross-Sectional Studies were used to evaluate study quality. RESULTS The review included 7 quantitative studies published in 7 different countries from 3 continents; of these, 6 (86%) were cross-sectional studies, and 1 (14%) was a prospective cohort study. Results suggested high frequencies of depressive symptoms and falls among older adults living in NHs, and depressive symptoms were considered a risk factor for falls. The 15-item and 10-item versions of the Geriatric Depression Scale were the most commonly used measurement tools, followed by the Cornell Scale for Depression in Dementia and the Resident Assessment Instrument-Minimum Data Set 2.0. The prevalence of depression was heterogeneous, varying from 21.5% to 47.7% of NH residents. The studies used heterogeneous descriptions of a fall, and some considered the risk of falls, recurrent fallers, and near falls in their data. The prevalence of fallers was disparate, varying from 17.2% to 63.1%. Of the 7 retained studies, 6 (86%) reported a relationship between depression and falls or the risk of falls. Among the 19 other risk factors identified in the review as being associated with falls among NH residents were a history of falls in the last 180 days, >1 fall in the past 12 months, and respiratory illnesses. CONCLUSIONS There is a paucity of research examining falls among older adults with depressive symptoms in NHs. These findings should alert nurses to the need to consider depression as a risk factor in their work to prevent falls. More research is needed to gain a comprehensive understanding of fall risk among NH residents with depressive symptoms. INTERNATIONAL REGISTERED REPORT RR2-10.2196/46995
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".