Development and Evaluation of an Instrument to Measure Seniors' Attitudes Toward the Use of Bathroom Grab Bars
Bibliographic record
Abstract
Bath grab bars can minimize the effects of many age-related deficits that may contribute to bath-related falls. Despite their potential value, bathroom safety devices remain largely underutilized by many community-living older adults and knowledge concerning attitudinal factors that influence the use of grab bars is sparse. This void of knowledge is due, at least in part, to the lack of instruments to measure the psychosocial constructs influencing bathroom safety device use. This study examined the psychometric properties of a newly developed Grab Bar Use Attitude scale (GUAS). Instrument formation, including item generation, evaluation by a panel of experts, and pilot testing of the draft instrument to establish its face and content validity, was followed by instrument validation using 546 community-living seniors. Results of principal components analysis of the GUAS revealed a two-factor solution, explaining 56% of the variance. The two constructs may best be described as functional/safety and psychosocial consequences of using grab bars. Psychometric analyses of the 9-item scale provided empirical evidence of the internal consistency of the total scale and each subscale. Finally, the GUAS distinguished between regular grab bar users and nonregular users. Implications for use are discussed.
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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 | 0.018 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".