A Self-management App for People Living With Mild Dementia (PRIDE): Protocol for a Pre-Post Feasibility Study
Bibliographic record
Abstract
BACKGROUND: With the rapid increase in the prevalence of dementia in the United Kingdom and beyond, the emotional, social, and economic burden on individuals, families, and health care services continues to rise. Currently, interventions that enable people living with dementia to better manage their condition and achieve a good quality of life are needed. OBJECTIVE: This study aimed to explore how the Promoting Independence in Dementia (PRIDE) app can promote and support the self-management of people living with mild dementia. METHODS: Feasibility of a pre-post study design incorporating the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework will be studied. We will use up to 6 National Health Service Trusts as research sites and the Join Dementia Research website and accept self-referrals to recruit 60 to 90 people living with mild dementia. Participants will complete the PRIDE app intervention over 8 weeks with support from a dementia adviser facilitator. Measures exploring mood, physical well-being, and quality of life will be collected at baseline and at follow-ups at 3 and 6 months. Facilitators and National Health Service staff will be invited to complete interviews shortly after the intervention phase. RESULTS: Data collection began in June 2021 and is predicted to cease by the end of August 2022. Analysis of the quantitative measures will explore the impact of the PRIDE app on participants' independence, mood, and quality of life. Interview data will discuss participant experiences, how the use of the app affected them, and if it has the potential to be successfully implemented and maintained in dementia services. CONCLUSIONS: This study will show the potential reach, effectiveness, and adoption of the PRIDE app intervention in the lives of people with mild dementia. The findings from this study will inform future research on the PRIDE app and any further developments to improve its effectiveness. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/33881.
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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 | 0.045 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.063 | 0.019 |
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".