Compliance study of hip protector users for prevention of fragility fracture: A pilot randomized trial
Bibliographic record
Abstract
BACKGROUND: Hip protectors have been widely used for hip fracture prevention in the elderly, but its efficacy remains controversial. Users' compliance to hip protector is an important factor for its efficacy. However, the assessment of users' compliance tended to be subjective and unreliable in the past. OBJECTIVES: To quantify the elderly's compliance to hip protectors and investigate the effect of different underpant designs on the elderly's compliance. STUDY DESIGN: A pilot randomized trial. METHODS: Thirty-one participants were recruited and provided with hip protectors in which compliance monitors were installed and delivered with three pairs of either the conventional underpants or the purpose-design underpants randomly. Participants were encouraged to use the hip protectors with the assigned underpants for whole day. After 4 weeks, compliance data were downloaded from the compliance monitors. Participants were also asked to fill a survey form for acceptance analysis. The Spearman correlation coefficient and the Wilcoxon signed-rank test/2 independent samples t test/Mann-Whitney U test were used for the corresponding statistical analyses. RESULTS: Thirty-one participants were recruited initially. Eighteen participants were excluded from instrumented compliance analysis because of limited or no data collection. The data of the resting 13 participants (six in the conventional underpants group and seven in purpose-design underpants group) were analyzed and showed an average instrumented compliance of 77.5% which was lower than the average self-reporting compliance (83.3%) of all the available 23 participants (eight of 31 became wheelchair-bounded). Participants' compliance was positively correlated with their acceptance to the hip protectors and significantly higher in the purpose-design underpants group than in the conventional underpants group ( P < 0.05). CONCLUSIONS: This pilot study demonstrated a feasible protocol for compliance quantification of the elderly to the hip protectors, the importance to have an objective compliance measure to assess users' actual compliance, and purpose-design underpants could improve the users' compliance. Future studies with long-term observation and large sample size deserve further proof of the current findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".