Difficulty finding help and prevalence rates.
Bibliographic record
Abstract
<div> There are growing concerns in Canada about access barriers to quality mental health care, which has worsened significantly by the COVID-19 pandemic and for some Canadians more than others. With a nationally representative sample of 1501 adults, surveyed by the Angus Reid Institute, this study examined the mental health conditions Canadians experience the most difficulties in accessing care. Among half of the respondents who sought mental health care, the majority encountered challenges in accessing help for posttraumatic stress disorder (PTSD) (34%) and depression (33%). When examining the data based only on those seeking care for specific conditions, attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), substance use disorders, and generalized anxiety disorder (GAD) emerged as those for which it was most difficult to find treatment. Indigenous and Black Canadians had significantly more difficulty finding care across several conditions. We discuss the implications of these findings, including the critical need to increase the supply and diversity of mental health providers across Canada. This study is one of the first to provide quantitative data on the perceived barriers in accessing mental health care, while exploring the role of race and ethnicity and other social identities. </div>
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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; both teacher heads agree on what is shown here.
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".