RESILIEN‐T: Field testing a lifestyle coaching app for subjective cognitive decline
Bibliographic record
Abstract
Abstract Background Links between subjective cognitive decline (SCD) and dementia are encouraging older adults to optimize their physical and mental health. Self‐managing lifestyle factors such as physical activity, healthy eating, social and cognitive stimulation can contribute to this optimization. RESILIEN‐T is an international project co‐producing and field testing an integrated goal‐setting and coaching app with and for older adults. Method Phase 1 iterative co‐production of the user interface, goal‐setting and coaching elements. Phase 2 mixed methods pilot trial with 15 participants with SCD (mean age 80 years) in four countries evaluated the prototype for two months. Phase 3 mixed‐methods field trial with 221 participants with SCD across four countries randomly assigned to the RESILIEN‐T intervention or control arm for three months. Minimum Data set of SCD (MAC‐Q) and health (EQ5D‐5L) were completed at baseline and end of trial, when usability (System Usability Scale) was also assessed. Result All pilot participants reported positive experiences with RESILIEN‐T, enjoying the easy‐to‐use interface and the daily suggestions to keep active. In the field study the MAC‐Q score improved in both groups, but this was only significant in the RESILIEN‐T group who improved significantly more than the control group. Health score improvement was higher in the RESILIEN‐T group but not significantly and SUS score was acceptable (71.9). Conclusion The RESILIEN‐T project confirms the interest among older adults with SCD of self‐managing lifestyle factors to promote cognitive health. The results of this short‐term intervention show promise for people with SCD to positively impact their cognition
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".