Canadian study finds that antidepressant use has increased in people with major depression over the past decade
Bibliographic record
Abstract
Patten SB. Major depression and mental health care utilization in Canada: 1994 to 2000. Can J Psychiatry 2004;49:303–9.[OpenUrl][1][CrossRef][2][PubMed][3] Q What is the frequency and pattern of antidepressant use in Canadian people with major depression? ### ![Graphic][4]</img>Design: Prospective longitudinal study. ### ![Graphic][5]</img>Setting: General population, Canada; enrolment 1994–95. ### ![Graphic][6]</img>Population: 9438 people aged over 15 years at enrolment, randomly sampled from the general population. Exclusions: military bases, native reserves, and some remote areas. ### ![Graphic][7]</img>Assessment: Data were collected every two years on the frequency of healthcare use in relation to major depression as part of the National Population Health Survey. Episodes of depression in the year preceding assessment were identified using the Composite International Diagnostic Interview Short Form for Major Depression. Any medications used in the two days preceding the interview were … [1]: {openurl}?query=rft.jtitle%253DThe%2BCanadian%2BJournal%2Bof%2BPsychiatry%26rft.stitle%253DCan%2BJ%2BPsychiatry%26rft.aulast%253DPatten%26rft.auinit1%253DS.%2BB.%26rft.volume%253D49%26rft.issue%253D5%26rft.spage%253D303%26rft.epage%253D309%26rft.atitle%253DMajor%2BDepression%2Band%2BMental%2BHealth%2BCare%2BUtilization%2Bin%2BCanada%253A%2B1994%2Bto%2B2000%26rft_id%253Dinfo%253Adoi%252F10.1177%252F070674370404900505%26rft_id%253Dinfo%253Apmid%252F15198466%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1177/070674370404900505&link_type=DOI [3]: /lookup/external-ref?access_num=15198466&link_type=MED&atom=%2Febmental%2F8%2F1%2F26.atom [4]: /embed/inline-graphic-1.gif [5]: /embed/inline-graphic-2.gif [6]: /embed/inline-graphic-3.gif [7]: /embed/inline-graphic-4.gif
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".