Why should clinical practitioners ask about their patients’ concerns about falling?
Bibliographic record
Abstract
Concerns (or 'fears') about falling (CaF) are common in older adults. As part of the 'World Falls Guidelines Working Group on Concerns about Falling', we recommended that clinicians working in falls prevention services should regularly assess CaF. Here, we expand upon these recommendations and argue that CaF can be both 'adaptive' and 'maladaptive' with respect to falls risk. On the one hand, high CaF can lead to overly cautious or hypervigilant behaviours that increase the risk of falling, and may also cause undue activity restriction ('maladaptive CaF'). But concerns can also encourage individuals to make appropriate modifications to their behaviour to maximise safety ('adaptive CaF'). We discuss this paradox and argue that high CaF-irrespective of whether 'adaptive' or 'maladaptive'-should be considered an indication that 'something is not right', and that is represents an opportunity for clinical engagement. We also highlight how CaF can be maladaptive in terms of inappropriately high confidence about one's balance. We present different routes for clinical intervention based on the types of concerns disclosed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".