2776 Leveraging Technology for Delivery of dementia prevention interventions remotely: through the Participant’s Lens
Bibliographic record
Abstract
Abstract Objectives The objective of this study was to examine participant’s experience with remote delivery during SYNERGIC@Home/SYNERGIE~Chez soi (NCT04997681), a home-based, double-blind, randomised controlled trial targeting older adults at risk for dementia. Metrics included study adherence, adverse events (AEs), participant’s attitudes towards technology, and protocol deviations (PDs) due to technological difficulties. Methods Participants underwent 16 weeks of physical and cognitive interventions (three sessions/week) remotely administered in their homes via Zoom for HealthcareTM. Participants used a laptop, webcam, and required email and internet access. Throughout the trial, adherence, AEs, and PDs were recorded. Post- intervention, survey questions about satisfaction with technology were administered and semi-structured interviews were conducted which underwent thematic analysis. Results Sixty participants, mean age 68.9 and 76.7% female, were randomised to one of four intervention arms, with 52 completing the 16-week intervention. Adherence rate was 87.5% with no significant difference between treatment arms (p = 0.656). There were 88 AEs reported in 42 participants. The majority (71.6%) of AEs were unrelated to the intervention, and 69.3% were classified as mild. There was one serious AE, unrelated to the intervention. Most (74.9%) participants reported overall satisfaction with technology, with Zoom being both enjoyable (81.0%) and easy to use (96%). Most enjoyed using the computer (87%), and the majority (87.0%) encountered few difficulties with connectivity. Of the 2496 intervention sessions, 14 (0.56%) were missed due to technical difficulties. Technical difficulties requiring modification to the intervention, such as an unstable internet connection, were reported on 79 occasions (3.0%). Themes from the interviews were: participants built rapport with the research assistants; felt better participating; had fun; and technology helped overcome barriers to participation. Conclusions Using technology to deliver dementia prevention interventions remotely was well received by participants Participation occurred safely from the comfort of their own home with few technical difficulties.
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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 | 0.028 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".