Feasibility and Acceptability of a Self-Guided Digital Family Skills Management Intervention for Children Newly Diagnosed With Type 1 Diabetes: Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Family dynamics play an important role in determining the glycemic outcomes of type 1 diabetes (T1D) in children. The time interval immediately following T1D diagnosis is particularly stressful for families, and interventions to support families in adjusting their family practices to support adjustment to and management of T1D in the months following diagnosis may improve glycemic outcomes. Self-guided digital interventions offer a sustainable model for interventions to support caregivers in learning evidence-based family management skills for adjustment to and management of T1D. OBJECTIVE: We hypothesized that a self-guided, web-based, family skills management program (addressing caregiver social support as well as family problem-solving, communication, and supportive behavior change strategies) initiated at the time of T1D diagnosis would improve glycemic outcomes in children with T1D. In this study, we report on the feasibility and acceptability of this program. METHODS: We prospectively evaluated a sample of 37 children newly diagnosed with T1D recruited from a pediatric endocrinology clinic. Parent participants were asked to complete web-based modules addressing social support, family problem-solving, communication, and supportive behavior change strategies. Module completion was analyzed for percentage completion, patterns of completion, and differences in completion rates by coparenting status. Qualitative open-ended feedback was collected at the completion of each module. RESULTS: A total of 31 (84%) of the 37 participants initiated the web-based program. Of those 31 participants, 25 (81%) completed some content and 15 (48%) completed all 5 modules. Completion rates were higher when coparenting partners engaged in the intervention together (P=.04). Of the 18 participants given a choice about the spacing of content delivery, 15 (83%) chose to have all sessions delivered at once and 3 (17%) chose to space sessions out at 2-week intervals. Qualitative feedback supported the acceptability of the program for delivery soon after T1D diagnosis. Families reported on positive benefits, including requesting future access to the program and describing helpful changes in personal or family processes for managing T1D. CONCLUSIONS: In this study, we found that a self-guided digital family support intervention initiated at the time of a child's T1D diagnosis was largely feasible and acceptable. Overall, rates of participation and module completion were similar to or higher than other self-guided digital prevention interventions for mental and physical health outcomes. Self-guided digital programs addressing family management skills may help prevent challenges common with T1D management and can decrease cost, increase access, and add flexibility compared to traditional interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT03720912; https://clinicaltrials.gov/study/NCT03720912.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".