Cognitive behaviour therapy reduces long term risk of relapse in recurrent major depressive disorder
Bibliographic record
Abstract
Fava GA, Ruini C, Rafanelli C, et al. Six-year outcome of cognitive behavior therapy for prevention of recurrent depression. Am J Psychiatry 2004;161:1872–6.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q Does adding cognitive behaviour therapy to pharmacotherapy reduce the long term risk of relapse of recurrent major depressive disorder? ### ![Graphic][5]</img>Design: Randomised controlled trial. ### ![Graphic][6]</img>Allocation: Unclear. ### ![Graphic][7]</img>Blinding: Single blinded (assessor blinded). ### ![Graphic][8]</img>Follow up period: 6 years. ### ![Graphic][9]</img>Setting: University of Bologna, Italy; time frame not stated. ### ![Graphic][10]</img>Patients: Forty five outpatients successfully treated with antidepressant drugs (tricyclics or SSRIs) for recurrent major depressive disorder. Excluded were: people with fewer than three prior episodes of depression; previous episode of depression over 2.5 years ago; history of substance abuse, personality disorder, or manic, hypomanic, or cyclothymic symptoms; or active medical comorbidity. ### ![Graphic][11]</img>Intervention: Pharmacotherapy plus cognitive behaviour treatment (CBT); pharmacotherapy plus clinical management. CBT and clinical management consisted of 10 fortnightly 30 minute sessions. Both groups had … [1]: {openurl}?query=rft.jtitle%253DAmerican%2BJournal%2Bof%2BPsychiatry%26rft.stitle%253DAm.%2BJ.%2BPsychiatry%26rft.aulast%253DFava%26rft.auinit1%253DG.%2BA.%26rft.volume%253D161%26rft.issue%253D10%26rft.spage%253D1872%26rft.epage%253D1876%26rft.atitle%253DSix-Year%2BOutcome%2Bof%2BCognitive%2BBehavior%2BTherapy%2Bfor%2BPrevention%2Bof%2BRecurrent%2BDepression%26rft_id%253Dinfo%253Adoi%252F10.1176%252Fappi.ajp.161.10.1872%26rft_id%253Dinfo%253Apmid%252F15465985%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=10.1176/appi.ajp.161.10.1872&link_type=DOI [3]: /lookup/external-ref?access_num=15465985&link_type=MED&atom=%2Febmental%2F8%2F2%2F38.atom [4]: /lookup/external-ref?access_num=000224279000022&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif [8]: /embed/inline-graphic-4.gif [9]: /embed/inline-graphic-5.gif [10]: /embed/inline-graphic-6.gif [11]: /embed/inline-graphic-7.gif
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".