Examining Preferences for Website Support to Parents of Adolescents With Diabetes
Bibliographic record
Abstract
Diabetes can be stressful as parents seek optimal outcomes for their adolescent with type 1 diabetes. This study examined parents' interest and perspectives related to online diabetes resources. Based on a qualitative description approach, 14 qualitative group interviews were conducted with (i) parents of adolescents with diabetes (n = 29), and (ii) pediatric health care providers (n = 31). Participants were recruited, through a purposive sampling approach, at pediatric centers in three Canadian cities. Qualitative data were subjected to thematic analysis comprising data coding, categorization, and ultimate theme generation. Participants described parental care for adolescents with diabetes as complex and reflective of difficult and nuanced tasks. They recommended the development of a comprehensive parent-based information and support website, and identified crucial elements of the website. Overarching themes comprised the following: complex parenting processes in diabetes care, parents' need for information and support, challenges and benefits of online support, key elements of an online resource, and caution regarding online resources. Based on these findings, website information and support emerged as a viable and desired resource for augmenting pediatric care within clinical settings. Caution was also offered in addressing potential challenges inherent in online support. Findings offer guidance for online support to parents.
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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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".