Caregiver Fear of Falling and Functional Ability among Seniors Residing in Long-Term Care Facilities
Bibliographic record
Abstract
BACKGROUND: Consistent with fear-avoidance models of falling and pain, past research has demonstrated that, among adults living in the community, excessive fear of falling and fear of pain result in activity restriction and predict functional outcomes including falls (possibly because self-imposed activity restriction, due to fear of pain or falling, can lead to muscular decline and deconditioning). Among seniors with dementia, who rely on others for their care, decisions concerning activity restrictions are made by caregivers. As such, caregivers' fear about the possibility of care recipient falls and pain is important to examine. OBJECTIVE: In this investigation of patients with dementia, our goal was to conduct a longitudinal investigation of the relationship between professional caregivers' fears (about the possibility that care recipients will experience falls and pain) with long-term care (LTC) resident functional ability and falls. METHODS: For the purposes of our 3-month longitudinal study, nurses' and special care aides' fears that specific residents might experience pain and falls were examined. Resident functional ability was assessed, based on an established and well-validated caregiver-administered questionnaire, both before and after the 3-month period. Falls and fall-related injuries sustained by residents were recorded. RESULTS: After controlling for physical risk factors for falling and functional ability at the beginning of the study, caregiver fears that residents might experience pain or falls were found to be predictive of restraint/restriction use. In turn, the use of restraints/restrictions was found to be predictive of future functional ability of residents with dementia (after controlling for functional ability at the beginning of the study) and injurious falls (after controlling for physical risk factors for falling). CONCLUSIONS: This is the first study to apply a modified fear-avoidance model of falls and pain to seniors with dementia who reside in LTC facilities. Our results demonstrate the importance of considering caregiver fears concerning falls and pain, when developing programs designed to optimize the use of physical restrictions (to prevent falls and minimize functional decline) in LTC facilities.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".