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Record W2100758079 · doi:10.1136/ebmh.8.2.38

Cognitive behaviour therapy reduces long term risk of relapse in recurrent major depressive disorder

2005· letter· en· W2100758079 on OpenAlexaff
Zindel V. Segal, Lucio Bizzini, Guido Bondolfi

Bibliographic record

VenueEvidence-Based Mental Health · 2005
Typeletter
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsDepression (economics)MedicineIMGInternal medicinePsychiatryWeb of sciencePediatrics

Abstract

fetched live from OpenAlex

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] Design: Randomised controlled trial. ### ![Graphic][6] Allocation: Unclear. ### ![Graphic][7] Blinding: Single blinded (assessor blinded). ### ![Graphic][8] Follow up period: 6 years. ### ![Graphic][9] Setting: University of Bologna, Italy; time frame not stated. ### ![Graphic][10] 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] 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

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.048
GPT teacher head0.365
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2005
Admission routes1
Has abstractyes

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