Training peers to deliver mental health support to adults with type 1 diabetes using the <scp>REACHOUT</scp> mobile app
Bibliographic record
Abstract
AIMS: While peer support research is growing in the Type 1 diabetes (T1D) community, the peer supporter training (PST) process is rarely documented in detail. This study provides a comprehensive description of PST and evaluation for the REACHOUT mental health support intervention, and examines the feasibility and perceived utility of PST. METHODS: Fifty-three adults with T1D were recruited to participate in a 6-hour, zoom-based PST program for mental health support. The program was structured in three parts: (1) internal motivation, resilience and empathy; (2) mindfulness, emotions and diabetes distress; and (3) active listening and deferring clinical questions to professionals. Candidates were evaluated based on eight pre-established competency criteria during a 5-day support trial with an assigned standardized T1D participant. Perceived usefulness of training skills was also assessed 3 months into the REACHOUT mental health support intervention. RESULTS: Fifty-one of the fifty-three candidates who completed training achieved the criteria to graduate. Mean scores for the eight competency domains were: listens actively (4.55); asks open-ended questions (4.12); expresses empathy (4.42); avoids passing judgment (4.67); sits with strong emotions (4.44); refrains from giving advice (4.38); makes reflections (4.5); and defers medical questions (4.58). Of the skills learned during the PST, 95% rated interpreting and discussing diabetes distress profile and expressing empathy as moderately to extremely useful. CONCLUSIONS: Findings demonstrate that it is feasible to recruit and graduate the number of trainees needed using a rigorous process. Only by making training protocols available can the PST be replicated and translated to other T1D populations (e.g. adolescents, parents of children with T1D).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".