Mental Health of Emergent Adults Living with Type 1 Diabetes in Canada: Aggregated National Survey, 2009 to 2019
Bibliographic record
Abstract
While many aspects of the relationship between type 1 diabetes and mental health are known, that relationship has not often been assessed among emergent adults. There is even less research on the mental health of emergent adults living with type 1 diabetes in Canada. Literature about the link between type 1 diabetes and mental health generally indicates that type 1 diabetes is a risk factor for mental health concerns and may be exacerbated by racialized group status and lower socioeconomic status. Several other factors are considered as novel explorations. Immigrant status and living in a rural place are included based on federal policy and the geography of Canada, respectively. Household size and the presence of other chronic conditions are included as a measure of social contact and proxy for health and mental health access in this post-pandemic era, respectively. The potential moderating influences of age and gender were also explored. This dissertation examines the mental health of emergent adults living with type 1 diabetes via secondary data analysis. The data was collected by the Canadian Community Health Survey (CCHS) in five panels (2009 to 2019). A single hypothesis tested whether a diagnosis of type 1 diabetes among individuals aged 15 to 30 years negatively affected three mental health outcomes: self-perceived mental health, presence of a mood disorder, and presence of an anxiety disorder. Four secondary hypotheses were also tested: 1) whether risk for mental health concerns was moderated so that risk is even greater for individuals in marginalised racial groups, 2) whether risk was moderated so that the risk is even greater for those individuals with relatively low incomes, 3) whether risk was moderated so that the risk is different for different age groups, and 4) whether risk was moderated so that the risk differed by gender. Multivariable logistic regression analyses were completed with a total sample of 122, 393 individuals in the following breakdown: individuals living with type 1 diabetes (518) and individuals without type 1 diabetes (121,875). Results indicate that those individuals who live with type 1 diabetes were 45% to 50% more likely to report that their mental health was fair or poor. Further, the relationship between type 1 diabetes and the presence of a mood disorder (indicative of 30-40% elevated risk) approached statistical significance. No evidence was found for the hypothesised moderating effects of racialized groups, income, age, or gender. Though not statistically significant, these four null interactions were of seemingly great practical significance. It seems that the mental health risks that attend having type 1 diabetes among emergent adults in Canada are similar for White, Indigenous, and marginalised racial group members, those with relatively high or low household incomes, as well as for young men, men, young women, and women. The results from the present study greatly expand understanding of emergent adult mental health in the presence of type 1 diabetes in the unique Canadian context, providing novel insights into how emergent adults with type 1 diabetes in Canada differ from those similar individuals abroad. Furthermore, it can be used to deepen our understanding of the mental health concerns of all individuals aged 15 to 30 years who live in Canada as they may compare to their counterparts abroad.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".