An Integrated Care Model to Support Adolescents With Diabetes-related Quality-of-life Concerns: An Intervention Study
Bibliographic record
Abstract
BACKGROUND: Our aim in this study was to determine whether participating in an integrated stepped care model for adolescents with type 1 diabetes (T1D) would lead to improvements in overall quality of life (QoL), diabetes-related quality of life (DRQoL) and glycated hemoglobin (A1C) levels compared with usual care. METHODS: A nonrandomized, 2-group, pre/post, delayed-intervention design was used for this study. The Mind Youth Questionnaire (MY-Q) was used to assess QoL and DRQoL. Adolescents attending the diabetes clinic using the stepped care model formed the intervention group (n=77). These adolescents completed the MY-Q, and the identified concerns were discussed and addressed with them by their care team as part of the care model. Adolescents attending a pediatric diabetes clinic on another site completed the MY-Q as a comparison group (n=39), results were not shared with their care team, and they received the standard care. RESULTS: There were 116 adolescents between 13 to 17 years of age, who completed the MY-Q on 2 occasions. Baseline data were obtained on the first occasion, and, on the second occasion, an average of 12 months later, there was a follow-up assessment. At follow-up, adolescents in the intervention group had a significantly higher overall QoL and reported significantly fewer concerns on DRQoL domains than those in the comparison group. Participation in the intervention group, however, did not lead to improvements in A1C. CONCLUSION: This study shows that implementing an integrated stepped care model within an interprofessional pediatric diabetes clinic can lead to the improvement of adolescents' overall QoL and DRQoL.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".