What Wait Time in a Soiled Pad Is Acceptable to Older Patients and Their Direct Caregivers?
Bibliographic record
Abstract
PURPOSE: We sought to establish views on wait times and hypothesized that they may vary depending upon perspective, circumstance, and incontinence type. DESIGN: Cross-sectional, descriptive survey. SUBJECTS AND SETTING: Eligible patients were inpatients, 65 years and older, in a single tertiary acute care hospital. Eligible staff were regulated (licensed) and unregulated providers of direct care to patients. Patients may or may not have used absorbent continence products prior to their admission. METHODS: We examined views on acceptable and actual wait times of elderly acute care inpatients and their direct care providers (DCPs). Participants were asked about wait times for pads soiled with urine or feces during the day and at night. Differences between patients and DCPs and acceptable and actual wait times were compared. Factors associated with tolerance to the presence of urine or stool in absorptive products were analyzed by logistic regression. RESULTS: There was patient-provider mismatch for daytime urinary incontinence: 90% of patients but only 44% of DCPs reported urinary soiling more than 1 hour in the daytime as unacceptable (38.0 vs 85.0 minutes; P < .0001). A significant majority (80%-90%) of both groups reported short acceptable wait times for fecal incontinence (<15 minutes). The odds of being tolerant to any soiling were significantly higher in patients who were prior residents of care facilities (odds ratio [OR] = 6.2; 95% confidence interval [CI], 1.3-28.1; P = .019), previously used incontinence products (OR = 2.0; 95% CI, 1.0-3.8; P = .036), or used walking aids (OR = 4.0; 95% CI, 1.1-14.7; P = .039). Actual wait times were significantly longer than deemed acceptable by either patients or DCPs. CONCLUSIONS: There are significant gaps in patient-provider perspectives on acceptable wait times in soiled incontinence products. Direct care providers need to take patient preference into account when managing continence.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".