Efficiency of using community organisations as catalysts for recruitment to continence promotion trials
Bibliographic record
Abstract
BACKGROUND: A major challenge for determining the effectiveness of community-based continence promotion campaigns is recruitment of a representative sample of incontinent participants who have not previously sought care. PURPOSE: To evaluate the efficiency of engaging community organisations as catalysts for recruitment of community-dwelling older women with incontinence to the 'Continence across Continents' randomised controlled trial. METHODS: Seniors' and women's community-based organisations throughout the United Kingdom were solicited by telephone or email to assist recruitment for an open-label cluster randomised controlled trial testing three experimental continence promotion interventions and a control intervention for incontinent older women. Women aged 60 years and older who experienced at least weekly urinary incontinence and who had never sought treatment were eligible to participate. The response rate of the organisations and enrolment rate of eligible participants attending the continence promotion workshops were recorded. Differences in recruitment efficiency by intervention group were ascertained using analysis of variance statistics. RESULTS: We contacted 408 community organisations over a 1-year period. Seventy organisations (17%) agreed to host a workshop, 249 (61%) did not provide a response, and 89 (22%) refused. Workshops were administered in a group format to 61 organisations (15%); 667 women attended, 583 (87%) submitted the screening questionnaire, and 437 (66%) met eligibility criteria for inclusion. A total of 192 women consented to participate in the trial, yielding a 44% recruitment efficiency among workshop attendees known to be eligible, with no significant difference in enrolment rates between groups. However, the mean participant recruitment rate per number of attendees at each workshop was only 29%, varying substantially between groups from 19% to 37%, with the lowest rate observed for the control group. The mean annual recruitment rate expressed as the number of enrolled participants per community organisation contacted was 0.5. LIMITATIONS: Reasons for women's non-response were not collected. The findings may be country specific. CONCLUSIONS: The recruitment rate for a continence promotion trial among older women known to be eligible and attending workshops hosted by local community organisations was high (44%). Strategies are needed to bolster community organisations' involvement in health promotion trials in general and for continence issues in particular.
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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 | 0.041 | 0.160 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".