The 2020 Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders: Major depression summary
Bibliographic record
Abstract
Abstract Objectives To provide a succinct, clinically useful summary of the management of major depression, based on the 2020 Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders (MDcpg 2020 ). Methods To develop the MDcpg 2020 , the mood disorders committee conducted an extensive review of the available literature to develop evidence‐based recommendations (EBR) based on National Health and Medical Research Council (NHMRC) guidelines. In the MDcpg 2020 , these recommendations sit alongside consensus‐based recommendations (CBR) that were derived from extensive deliberations of the mood disorders committee, drawing on their expertise and clinical experience. This guideline summary is an abridged version that focuses on major depression. In collaboration with international experts in the field, it synthesises the key recommendations made in relation to the diagnosis and management of major depression. Results The depression summary provides a systematic approach to diagnosis, and a logical clinical framework for management. The latter begins with Actions , which include important strategies that should be implemented from the outset. These include lifestyle changes, psychoeducation and psychological interventions. The summary advocates the use of antidepressants in the management of depression as Choices and nominates seven medications that can be trialled as clinically indicated before moving to Alternatives for managing depression. Subsequent strategies regarding Medication include Increasing Dose, Augmenting and Switching (MIDAS). The summary also recommends the use of electroconvulsive therapy (ECT), and discusses how to approach non‐response. Conclusions The major depression summary provides up to date guidance regarding the management of major depressive disorder, as set out in the MDcpg 2020 . The recommendations are informed by research evidence in conjunction with clinical expertise and experience. The summary is intended for use by psychiatrists, psychologists and primary care physicians, but will be of interest to all clinicians and carers involved in the management of patients with depressive disorders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.022 | 0.018 |
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 source (direct Gemma or distilled Codex), 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".