Reviewing Psychological Treatments for Adult Depression
Bibliographic record
Abstract
AbbreviationsAD antidepressantBA behavioural activationCAU care as usualCBT cognitive-behavioural therapyES effect sizeEXP experiential psychotherapyIPT interpersonal psychotherapyPST problem-solving therapyRCT randomized controlled trialThe 2 articles that comprise this In Review1·2 use different methods to review their respective literatures. In the first, Dr Pim Cuijpers and colleagues' conduct a meta-analysis of RCTs involving CBT in the treatment of adult depression and find CBT superior to various control conditions, comparable to alternative interventions, and better than medication alone when added in combination. In the second, Dr Jan Spijker and colleagues2 chose to do a qualitative review, given the limited number of relevant RCTs that focused on chronic major depressive disorder, and concluded that treatment was superior to its absence but that multiple successive interventions may be necessary. Both sets of conclusions seem reasonable given the available data.We come from different traditions and have different levels of comfort with the approaches used in the reviews. Dr Hollon has spent his career doing RCTs and prefers reviews that emphasize the findings from well-conducted studies. Dr Cuijpers is an experienced quantitative researcher who deals with concerns regarding study quality, using meta-regressions to explore the study characteristics that influence the estimated effects. As we concur that both reviews were nicely implemented examples of their genres, we chose to use this editorial to comment on differences arising from our different perspectives.Do quantitative reviews obscure differences between different treatments? Dr Cuijpers and colleagues' concluded, based on their meta-analysis, that CBT was superior to control conditions and not different than alternative interventions. Hollon and Ponniah1 arrived at similar but not identical conclusions in a recent qualitative review that required a minimum number of well-conducted studies to draw an inference regarding treatment impact. Using the criteria adapted from US Food and Drug Administration guidelines to identify empirically supported treatments, a treatment was said to be efficacious if it was better than its absence in at least 2 studies conducted by different research groups (possibly if only one) and specific if it was superior conditions that controlled for the generic effects of simply going into treatment.4 Using these criteria, Hollon and Ponniah1 concluded that CBT was efficacious and specific, and came to the same conclusions regarding IPT, and ADs. Where they differed from Dr Cuijpers and colleagues' was in concluding that both psychodynamic psychotherapy and EXP were only possibly efficacious (owing to the paucity of supportive trials in fully clinical populations) and drew no conclusions at all regarding supportive psychotherapy (to the extent that it differed from EXP). Quantitative reviews that estimate the average magnitude of effect across all published studies in a literature typically find no differences among bona fide therapies, whereas qualitative reviews that look for high-quality studies sometimes do. For example, ADs represent the current standard of treatment for depression and pill-placebos a particularly rigorous control. We can find studies in which the psychotherapy of interest was as efficacious as medications and superior pill-placebo for CBT/'' IPT,7 BA, and PST, but not for other kinds of psychotherap.ies.If we were to choose among the different psychotherapies, do we choose one that has been shown to be at least the equal of the AD (when it is superior to the pill-placebo)? The typical quantitative review suggests that this does not matter. The 2 approaches especially diverge when translated into treatment guidelines. Although quantitative reviews suggest that all bona fide treatments are equally effective, guidelines tend to emphasize the best-supported treatments. …
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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".