REACH LIFESTYLE INTERVENTION: FEASIBILITY OF DELIVERING AN INSTRUCTOR TRAINING COURSE
Bibliographic record
Abstract
Return to Everyday Activities in the Community and Home (REACH) is a lifestyle intervention model for middle-aged and older adults. The goal of REACH is to reduce sedentary behaviour, increase physical activity, and increase adoption of strength and balance exercises. In this feasibility study we completed a formative evaluation to assess the effectiveness, impact and reception of the REACH instructor training course. Our aim was to summarise perceptions of the model and identify gaps in curriculum delivery. The REACH Instructor training course occurred over four sessions, each of two hour duration. The training methods included didactic and participatory elements, plus a comprehensive instructors’ manual and handouts. The participants were provided with foundational knowledge, including principles of behaviour change theory. Participants also practiced teaching components of the program to their peers. We conducted semi-structured interviews at the end of the training session, and administered a Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P) and session feedback forms. There were three participants who completed the study; all were community-based exercise physiologists with an average of 17 (8) years of experience. Emerging themes from participants’ feedback included: credentials required, how to best prepare instructors for teaching REACH, the ideal learning setting and linking the instructor manual to presentation slides. The PEMAT-P scores for the instructor manual were 98 (0.03) % for understandability, and 100% for actionability. Each session was rated very good or excellent for presentation style and overall rating. We applied participant feedback to the existing instructor curriculum.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".