Smart Continence Care for People With Profound Intellectual and Multiple Disabilities: Protocol for a Cluster Randomized Trial and Trial-Based Economic Evaluation
Bibliographic record
Abstract
BACKGROUND: People with profound intellectual and multiple disabilities (PIMD) cannot communicate the need to change their incontinence products. The smart continence care (SCC) product Abena Nova signals caregivers when change is needed. This provides the opportunity for more person-centered care, increased quality of life, and a decreased number of leakages. However, there is a need for evidence of the effectiveness and cost-effectiveness of such technology compared with regular continence care (RCC) for people with PIMD. OBJECTIVE: This paper presents the research protocol for an effectiveness and cost-effectiveness study with people with PIMD living in long-term care facilities in the Netherlands. METHODS: A cluster randomized trial will be conducted in 3 consecutive waves across 6 long-term care providers for people with disabilities and 160 participants with PIMD. Long-term care providers are randomized at a 1:1 ratio, resulting in an intervention group and a group continuing RCC. The intervention group will receive implementation guidance and use SCC for 3 months; the other group will continue their RCC as usual and then switch to SCC. This study consists of three components: effectiveness study, economic evaluation, and process evaluation. The primary outcome will be a change in the number of leakages. The secondary outcomes are quality of life, the difference in the number of changes, the work perception of caregivers, cost-effectiveness, and cost utility. Data collection will occur at T0 (baseline), T1 (6 weeks), T2 (12 weeks), and T3 (9-month follow-up) for the first 2 intervention groups. An intention-to-treat analysis will be performed. The economic evaluation will be conducted alongside the trial from the societal and long-term care provider perspectives. Qualitative data collection through interviews and field notes will complement these quantitative results and provide input for the process evaluation. RESULTS: This research was funded in December 2019 by ZonMw, the Netherlands Organization for Health Research and Development. As of June 2022, we enrolled 118 of the 160 participants. The enrollment of participants will continue in the third and fourth quarters of 2022. CONCLUSIONS: This study will provide insights into the effectiveness and cost-effectiveness of SCC for people with PIMD, allowing long-term care providers to make informed decisions about implementing such a technology. This is the first time that such a large-scale study is being conducted for people with PIMD. TRIAL REGISTRATION: ClinicalTrials.gov NCT05481840; https://clinicaltrials.gov/ct2/show/NCT05481840. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42555.
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 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 | 0.069 | 0.060 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.099 | 0.013 |
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".