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Record W2489205254 · doi:10.1177/0706743716659276

Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder

2016· review· en· W2489205254 on OpenAlexaffvenueabout
Glenda MacQueen, Benício N. Frey, Zahinoor Ismail, Natalia Jaworska, Meir Steiner, Ryan J. Van Lieshout, Sidney H. Kennedy, Raymond W. Lam, Roumen Milev, Sagar V. Parikh, Arun Ravindran

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2016
Typereview
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of British ColumbiaUniversity of CalgaryMcGill UniversityUniversity of TorontoQueen's UniversityMcMaster University
Fundersnot available
KeywordsEvidence-based practiceMoodAnxietySystematic reviewPopulationPsychiatryEvidence-based medicineExtant taxonMental healthMajor depressive disorderClinical psychologyMedicineMEDLINEPsychologyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The Canadian Network for Mood and Anxiety Treatments (CANMAT) conducted a revision of the 2009 guidelines by updating the evidence and recommendations. The scope of the 2016 guidelines remains the management of major depressive disorder (MDD) in adults, with a target audience of psychiatrists and other mental health professionals. METHODS: Using the question-answer format, we conducted a systematic literature search focusing on systematic reviews and meta-analyses. Evidence was graded using CANMAT-defined criteria for level of evidence. Recommendations for lines of treatment were based on the quality of evidence and clinical expert consensus. This section on "Special Populations" is the sixth of six guidelines articles. RESULTS: Recent studies inform the treatment of MDD in children and adolescents, pregnant and breastfeeding women, women in perimenopause or menopause, and the elderly. Evidence for efficacy of treatments in these populations is more limited than for the general adult population, however, and risks of treatment in these groups are often poorly studied and reported. CONCLUSIONS: Despite the limited evidence base, extant data and clinical experience suggest that each of these special populations can benefit from the systematic application of treatment guidelines for treatment of MDD.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.880
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.044
GPT teacher head0.363
Teacher spread0.319 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations250
Published2016
Admission routes3
Has abstractyes

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