Dropout in brief psychotherapy for major depressive disorder: Randomized clinical trial
Bibliographic record
Abstract
The aim of this paper is to analyse the factors associated with the dropout from brief psychotherapy for adults with major depressive disorder (MDD) treated at a mental health outpatient clinic. This is a randomized clinical trial with two models of psychotherapy: cognitive behavioural therapy (CBT) and supportive expressive dynamic psychotherapy (SEDP). MDD and anxiety disorders were evaluated through the Mini International Neuropsychiatric Interview-Plus. The personality disorders were evaluated by the Millon Clinical Multiaxial Inventory-III. The severity of depressive symptoms was measured using the Beck Depression Inventory-II and resilience through Resilience Scale. Of the 215 participants, 41.9% abandoned psychotherapy (n = 90), and, of these, 54.4% (n = 49) abandoned after the fourth session. The proportion of psychotherapy dropout was higher among those with nonwhite skin colour, belonging to economic classes C and D, who had children and whose depressive symptoms were moderate. Presence of obsessive-compulsive personality trait was protective against dropout. The damage caused by this abrupt interruption is evident for all those involved in the psychotherapeutic process, so the clinician should pay attention to the predictors found in this study in order to develop strategies that promote therapeutic adherence.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".