Impact of urine and mixed incontinence on long-term care preference: a vignette-survey study of community-dwelling older adults
Bibliographic record
Abstract
BACKGROUND: In view of population aging, a better knowledge of factors influencing the type of long-term care (LTC) among older adults is necessary. Previous studies reported a close relationship between incontinence and institutionalization, but little is known on opinions of older citizens regarding the most appropriate place of care. This study aimed at evaluating the impact of urine and/or fecal incontinence on preferences of community-dwelling older citizens. METHODS: We derived data from the Lausanne cohort 65+, a population-based study of individuals aged from 68 to 82 years. A total of 2974 community-dwelling persons were interviewed in 2017 on the most appropriate place of LTC delivery for three vignettes displaying a fixed level of disability with varying degrees of incontinence (none, urinary, urinary and fecal). Multinomial logistic regression analyses explored the effect of respondents' characteristics on their opinion according to Andersen's model. RESULTS: The level of incontinence described in vignettes strongly determined the likelihood of considering institutional care as most appropriate. Respondents' characteristics such as age, gender, educational level, being a caregiver, knowledge of shelter housing or feeling supported by family influenced LTC choices. Self-reported incontinence and other indicators of respondents' need, however, had no significant independent effect. CONCLUSION: Among older community-dwelling citizens, urinary and fecal incontinence play a decisive role in the perception of a need for institutionalization. Prevention and early initiation of support for sufferers may be a key to prevent this need and ensure familiar surrounding as long as possible.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".