Creation and Testing of the Geriatric Self‐Efficacy Index for Urinary Incontinence
Bibliographic record
Abstract
OBJECTIVES: To report on the content development, construct validity, and reliability testing of the Geriatric Self-Efficacy Index for Urinary Incontinence (GSE-UI). DESIGN: Prospective cohort study. SETTING: Six UI outpatient clinics in Quebec, Canada. PARTICIPANTS: Community-dwelling incontinent men and women aged 65 and older. MEASUREMENTS: Thirty-eight items were generated using a literature search and interdisciplinary panel of experts. Item reduction was achieved through field-testing with 75 older men and women with UI attending an information session. The final 20-item draft, measuring older adults' level of confidence in preventing urine loss, was administered to a new group of consecutive patients 1 week before and at the time of their first visit to the UI clinic to enable evaluation of test-retest reliability. A 3-day voiding diary, quantifying the frequency of UI, and the Incontinence Quality of Life questionnaire were used to test construct validity. RESULTS: One hundred sixteen of 300 eligible patients (39%) participated (mean age+/-standard deviation 74+/-6, range 65-87). The GSE-UI items showed normal distributions and no ceiling effects. Self-efficacy scores ranged from 16 to 193 (mean 104+/-41, possible range 0-200) and correlated positively with quality of life scores (r=0.7, P<.001) and negatively with UI severity (r=-0.4, P<.001). Internal consistency for the GSE-UI was 0.94 (Cronbach alpha). Initial test-retest reliability of the 20 items using intraclass correlations ranged from 0.50 to 0.86. CONCLUSION: The GSE-UI will enable measurement of whether a person's confidence in their ability to prevent urine loss is an important mechanism contributing to improvements in UI.
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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 | 0.022 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".