Self‐reported use of mental health services versus administrative records: should we care?
Bibliographic record
Abstract
Studies of mental health services have emphasized that people in need are not receiving treatment. However, these studies, based on self-reported use, may not be consistent with administrative records. This study compared self-reports of mental health service use with administrative records in a large representative sample. Respondent reports within the Ontario portion of the 1994/95 Household Component of the National Population Health Survey (NPHS) were individually linked to the provincial mental-health physician reimbursement claims. A total of 5187 Ontarians, aged 12 years or more, reported on their use of mental healthcare within the NPHS and 4621 (89%) consented and were successfully linked to administrative records. Comparisons between the two sources identified that the agreement for any use and volume of use was moderate to low and varied according to select respondent characteristics. These differences affected estimates of the associations with use and volume of use. People who reported high levels of distress reported more visits than those who did not and this effect was stronger in the self-reported data. These results suggest that recall bias may be present. Regardless of the definition of care, access for those in need remains a concern despite universal medical insurance coverage.
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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 | 0.133 | 0.396 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| 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".