“I Don’t Want to Feel Judged”: A Qualitative Study of Adolescents’ Experiences of Living With Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVES: Our aim in this study was to explore adolescents' experiences of type 2 diabetes (T2D), particularly those concerning 1) diagnosis and management and 2) emotional well-being. METHODS: Participants, recruited from an Australian tertiary pediatric hospital, took part in a focus group or semistructured interview. Data were analyzed using inductive thematic analysis. RESULTS: Eight adolescents participated in the study (7 female youths and 1 male youth; mean ± standard deviation age: 16.2±2.3 years; median [interquartile range] diabetes duration: 1.7 [0.8 to 2.5] years; glycated hemoglobin: 7.5% [6.2% to 8.4%]; and body mass index z score: 1.97 [0.70 to 2.29]). Most participants (n=6) were from linguistically diverse backgrounds. Their diabetes management varied from lifestyle measures alone to medication(s). The thematic analysis generated 3 themes relating to diagnosis and management: 1) "Dietary modification as the biggest encumbrance in managing T2D"; 2) "Medications pose a significant challenge to managing T2D"; and 3) "The value of reminders in managing T2D varies in adolescents." Furthermore, 4 themes were generated concerning emotional well-being: 1) "Diverse feelings are experienced at the time of diagnosis"; 2) "Diabetes has varying impacts on the daily lives of adolescents with T2D"; 3) "Young people fear stigma and judgement"; and 4) "Having a good support network matters." CONCLUSIONS: Adolescents with T2D experience difficulties with dietary modification and medication management. Adolescents' feelings at diagnosis and the impact of T2D on a young person's life vary. They fear judgement and stigma, and a diverse support network is paramount in supporting their T2D management and emotional well-being. The findings can assist health professionals in supporting adolescents with T2D.
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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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".