P2-528 Adult perceptions of youth mental health issues in a Canadian province
Bibliographic record
Abstract
Although 15% of Canadian youth experience mental health problems, barriers to disclosure and treatment exist. This population-based study assessed adult's beliefs about the prevalence of mental illness among youth, treatment for mental illness, and comfort interacting with youth with moderate mental health problems. In 2010 a random sample of 1203 adults residing in Alberta Canada were surveyed. χ2 Tests and t-tests were used to understand responses by demographic factors. Logistic regression was used to determine factors predictive of Albertans comfort in interacting with youth with moderate mental health problems. Twenty percent were able to correctly identify the prevalence of youth mental health problems. Over 50% stated that they believed that <10% of youth with mental health problems received treatment. Approximately 70% of the sample reported they would be comfortable interacting with youth with moderate mental health problems in work, school, social and community settings. Consistent predictors of comfort interacting with youth with moderate mental health problems included: being between the ages of 18–24, high school completion, Caucasian ethnicity, and annual household income >$40 000/year. There are meaningful gaps in Albertans understanding of the prevalence of youth mental health issues, but the majority of adults would be comfortable interacting with youth with moderate mental health problems. Many respondents identified that youth with mental health problems may not be receiving treatment. Increased public awareness about the prevalence and detrimental impact of youth mental health issues may help policy makers allocate resources to effective screening and treatment for youth with mental health concerns.
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 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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".