Evidence-based strategies for achieving and sustaining full remission in depression: focus on metaanalyses.
Bibliographic record
Abstract
The goal of therapy in the management of patients with major depressive disorder is to achieve and sustain remission. Extensive data on strategies to achieve remission have been published, and more recently, many of these data have been subject to systematic review and metaanalyses. This review compares data from metaanalyses and more recent trials on some of the therapies that may help to achieve remission. Strategies that have demonstrated improved rates of full remission in the treatment of depression include venlafaxine as initial antidepressant therapy, which has been shown to provide higher rates of remission when compared with serotonin reuptake inhibitors and tricyclic antidepressants. For patients who do not respond to initial medication treatment, treatments such as psychotherapy, exercise, light therapy, alternative medicines, and counselling have demonstrated benefits over placebo and may enhance remission rates when used in combination with antidepressants. Preventing relapse and sustaining the fully remitted state over the long term is also important in the management of depression. Continuing antidepressant therapy has been associated with excellent long-term outcomes for many patients. Randomized controlled clinical trials conducted in the last 5 years provide very good evidence to show that achieving and sustaining the fully remitted state is an attainable goal in the management of patients with depression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 | 0.001 |
| 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".