Coaching for parents of children with type 1 diabetes: A randomized controlled trial
Bibliographic record
Abstract
OBJECTIVE: To assess the effectiveness of a standardized bi-weekly six-month telephone coaching intervention for parents of children with type 1 diabetes. METHODS: This single-blind randomized controlled trial followed participants for 12 months. The primary outcome was children's health-related quality of life. Secondary outcomes included treatment adherence, diabetes-related family conflict, and hemoglobin A1c. Data was collected using validated questionnaires and health records. We compared groups using a linear mixed effects model. RESULTS: 102 families were randomized (control: n = 49; intervention: n = 53). Coaching had no impact on children's overall health-related quality of life or overall secondary outcomes; however, there were patterns in subsections that suggest the possible impact of coaching. Coaching was perceived as a positive addition to routine care by 80% of families and 82% would recommend working with a coach to another family. 58% of participants would continue coaching beyond the study. CONCLUSION: Coaching did not impact overall quality of life or secondary outcomes; however, coaching was well received by families who perceived significant benefits. Patterns in subsections warrant further study. PRACTICE IMPLICATIONS: Adding a health coach into diabetes multidisciplinary care supports families in a way that is unique from their routine clinical care.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".