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Clinical Guidelines for the Treatment of Depressive Disorders V. Combining Psychotherapy and Pharmacotherapy

2001· article· en· W144583544 on OpenAlexaffvenueabout
Zindel V. Segal, Sidney H. Kennedy, Nicole L. Cohen

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2001
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsThe Wilson CentreUniversity of Toronto
Fundersnot available
KeywordsPharmacotherapyPsychiatryMedicineMEDLINEPsychotherapistMoodAnxietyExpert opinionIntensive care medicinePsychology

Abstract

fetched live from OpenAlex

BACKGROUND: The Canadian Psychiatric Association and the Canadian Network for Mood and Anxiety Treatments partnered to produce clinical guidelines for psychiatrists for the treatment of depressive disorders. METHODS: A standard guidelines development process was followed. Relevant literature was identified using a computerized Medline search supplemented by review of bibliographies. Operational criteria were used to rate the quality of scientific evidence, and the line of treatment recommendations included consensus clinical opinion. This section, "Combining Psychotherapy and Pharmacotherapy," was 1 of 7 articles drafted and reviewed by clinicians. Revised drafts underwent national and international expert peer review. RESULTS: Recommendations are given for the use of combined psychotherapy and pharmacotherapy for the treatment of depressive disorders. Three methods of combined treatment are identified: concurrent treatment (psychotherapy plus pharmacotherapy) for the acute-treatment phase, sequential treatment (adding the other treatment for nonresponders or partial responders to monotherapy in the acute-treatment phase), and crossover treatment (switching to psychotherapy for the maintenance-treatment phase after response to pharmacotherapy in the acute phase). CONCLUSIONS: Combined treatment with psychotherapy and pharmacotherapy is widely used in clinical practice. The recommendations for use of combined treatment are, however, based on only a limited evidence base.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.443
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

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

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 head0.078
GPT teacher head0.416
Teacher spread0.338 · 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 teacher head, 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

Citations29
Published2001
Admission routes3
Has abstractyes

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