Beyond <scp>AIC</scp> : An Interpretive Descriptive Qualitative Study of Youth Experiences and Perceptions of Living With Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To generate an in-depth understanding of the perceptions and experiences of individuals with youth-onset type 2 diabetes (T2D) to inform knowledge translation initiatives and clinical care. DESIGN: Interpretive descriptive qualitative study. METHODS: Individuals were eligible to participate if they received a T2D diagnosis on or before 18 years of age, resided in Manitoba, and were between 10 and 25 years of age at the time of data collection. Twenty-two individuals (13 females, 7 males, 2 prefer not to indicate gender; mean age = 19.3 years) participated in 22 semi-structured interviews (mean length: 29:01 min) remotely using Zoom video conferencing software or by telephone. Data were analysed using inductive thematic analysis. RESULTS: Four themes were generated: (1) Low public knowledge, misconceptions, and stigma impact youth experiences including those of diagnosis, disclosure, treatment, and supports; (2) shared familial experiences impacts perception of the future; (3) mental and emotional wellness is critically important but requires more attention; and (4) T2D carries unanticipated positive and negative impacts for youth. CONCLUSIONS: Findings illustrate the complex interrelationships between public and personal conceptions of T2D, stigma, and T2D navigation, emphasising the centrality of emotional and mental well-being to participants' T2D experiences and management. This representation of experiences and perceptions of youth onset T2D offers direction for holistic and youth-centred research and care and highlights areas where further mental health and educational resources would be beneficial. PATIENT AND PUBLIC CONTRIBUTION: The knowledge translation resource being developed from this study involves input from patient and public partners.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".