New Psychotherapies for Mood and Anxiety Disorders: Necessary Innovation or Waste of Resources?
Bibliographic record
Abstract
Dear Editor: With much interest we read the systematic review from Stirman et al1 about new psychotherapies for mood and anxiety disorders. Although the study has been well conducted, we think the authors have not sufficiently answered the question of whether we actually need new psychotherapies. On the one hand, there is a clear need for better treatments, as mood and anxiety disorders constitute a considerable burden for patients and society. Further, modelling studies have shown that current treatments can reduce only one-third of the disease burden of depression and less than one-half of anxiety disorders, even in optimal conditions.2 However, there are already dozens of different types of psychotherapy for mood and anxiety disorders, and there is very little evidence that the effects of treatments differ significantly from each other. In depression, we found that interpersonal psychotherapy is somewhat more effective than other therapies,3 but differences were very small (Cohen's d We think that new therapies are only needed if the additional effect compared with existing therapies is at least d = 0.20. Larger effect sizes are not reasonable to expect as 0.20 is the largest difference between therapies found until now. Further, this effect needs to be empirically demonstrated in high-quality trials. However, to show such an effect of 0.20 we would need huge numbers. A simple power calculation shows that this would require a trial of about 1000 participants (STATA [Statacorp, College Station, TX] sampsi command). As a comparison, the large National Institute of Mental Health Treatment of Depression Collaborative Trial examining the effects of treatments of depression included only 250 patients. We want to suggest, therefore, that the field stops with developing new psychotherapies for mood and anxiety disorders unless the developers can convince financers of research to conduct a well-powered comparative study that shows that this therapy is indeed more effective than existing therapies. In the meantime, the field should focus on the real problems that limit the contribution of therapies to the reduction of disease burden, including the large number of patients who do not respond to any treatment, the patients who still have considerable residual symptoms after successful treatments, and patients who relapse. References 1. Stirman SW, Toder K, Crits-Christoph P. New psychotherapies for mood and anxiety disorders. Can J Psychiatry. 2010;55:193-201. 2. Andrews G, Issakidis C, Sanderson K, et al. Utilising survey data to inform public policy: comparison of the cost-effectiveness of treatment often mental disorders. Br J Psychiatry. 2004;184:526-533. 3. Cuijpers P, van Straten A, Andersson G, et al. Psychotherapy for depression in adults: a meta-analysis of comparative outcome studies. J Consult Clin Psychol. 2008;76:909-922. Pim Cuijpers, PhD Annemieke van Straten, PhD Amsterdam, The Netherlands Reply Re: New Psychotherapies for Mood and Anxiety Disorders: Necessary Innovation or Waste of Resources? …
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 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 | 0.030 | 0.192 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.016 | 0.016 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".