Assessing falls risk in older adult mental health patients: A Western Australian review
Bibliographic record
Abstract
Falls are a common and costly complication of hospitalization, particularly in older adult populations. This paper presents the results of a review of 139 falls at two older adult mental health services in Western Australia, Australia, over a 12-month period. Data were collected from the hospital incident report management system and from case file reviews of patients who sustained a fall during hospitalization. The results demonstrated that the use of different risk assessment and falls management tools led to variations in practice, policies, and management strategies. The review identified mental health-specific falls risk factors that place older people with a mental illness at risk when admitted to the acute mental health setting. With the expansion of community mental health care, many older people with a mental illness are now cared for in a variety of health-care settings. In assessing falls risk and implementing falls-prevention strategies, it is important for clinicians to recognize this group as an ambulant population with a fluctuating course of illness. They have related risks that require specialized falls assessment and management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".