Prevalence of alcohol, tobacco, cannabis and other illicit substance use in a population of Canadian adolescents with type 1 diabetes compared to a general adolescent population
Bibliographic record
Abstract
BACKGROUND: Youth with chronic conditions may engage in risky behaviour to the same, if not higher, degree as their healthy peers. OBJECTIVES: To determine the prevalence of alcohol, tobacco, cannabis and illicit substance use in adolescents with type 1 diabetes (T1DM) compared to a general adolescent population. METHODS: Cross-sectional survey of adolescents with T1DM (13 to 18 years). A published contemporary Canadian youth survey on use of alcohol, tobacco and illicit drugs was used as data representative of the general adolescent population. Outcome measures between the T1DM and general group were compared using Chi-square and Fisher's exact test where appropriate. RESULTS: One hundred and sixty-four adolescents with T1DM (mean 15.6 years [SD 1.5]; 51.3% male) were participated. The proportions of adolescents with T1DM who have tried substances were: alcohol 51.8%, tobacco 27.4%, cannabis 22.6% and other illicit substances 7.3%. Compared to the general population (n=3469), there were no significant differences in the proportion of adolescents that reported ever consuming alcohol, tobacco or cannabis. Reported illicit substance use was significantly lower in adolescents with T1DM compared to general population (7.3% versus 36.0%, P<0.0001). CONCLUSIONS: Proportions reporting having ever consumed alcohol, tobacco or cannabis were not significantly different between the two groups. However, the proportion of adolescents with T1DM who reported ever consuming an illicit substance was different from the comparison group. It is important to explore risky behaviours with adolescents with T1DM and focus on prevention and education during routine clinic visits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".