Grab Bar Use Influences Fall Hazard During Bathtub Exit
Bibliographic record
Abstract
OBJECTIVE: This study evaluated the hazard (risk of unrecovered balance loss and hazardous fall) and strategies associated with grab bar use, compared to no grab bar use, during unexpected balance loss initiated whilst exiting a bathtub. BACKGROUND: While independent bathing is critical for maintaining self-sufficiency, injurious falls during bathing transfer tasks are common. Grab bars are recommended to support bathing tasks, but no evidence exists regarding fall prevention efficacy. METHOD: Sixty-three adults completed a hazardous bathtub transfer task, experiencing an unpredictable external balance perturbation while stepping from a slippery bathtub to a dry surface. Thirty-two were provided a grab bar, while 31 had no grab bar available. Slips and grab bar use were recorded via four video cameras. Slip occurrence and strategy were identified by two independent video coders. RESULTS: Participants who had a grab bar were 75.8% more likely to recover their balance during the task than those who did not have a grab bar. Successful grab bar grasp was associated with balance recovery in all cases. Attempts to stabilize using other environmental elements, or using internal strategies only, were less successful balance recovery strategies. Grab bar presence appeared to cue use of the environment for stability. Proactive grasp and other strategies modified grasping success. CONCLUSION: Grab bars appear to provide effective support for recovery from unexpected balance loss. Grab bar presence may instigate development of fall prevention strategies prior to loss of balance. APPLICATION: Bathroom designs with grab bars may reduce frequency of fall-related injuries during bathing transfer tasks.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".