Changes in self-schema structure in cognitive therapy for major depressive disorder: A randomized clinical trial.
Bibliographic record
Abstract
Negative cognitive structure (particularly for interpersonal content) has been shown in some research to persist past a current episode of depression and potentially to be a stable marker of vulnerability for depression (D. J. A. Dozois, 2007; D. J. A. Dozois & K. S. Dobson, 2001a). Given that cognitive therapy (CT) is highly effective for treating the acute phase of a depressive episode and that this treatment also reduces the risk of relapse and recurrence, it is possible that CT may alter these stable cognitive structures. In the current study, patients were randomly assigned to CT+ pharmacotherapy (n = 21) or to pharmacotherapy alone (n = 21). Both groups evidenced significant and similar reductions in level of depression (as measured with the Beck Depression Inventory-II and the Hamilton Rating Scale for Depression), as well as automatic thoughts and dysfunctional attitudes. However, group differences were found on cognitive organization in favor of individuals who received the combination of CT+ pharmacotherapy. The implications of these results for understanding mechanisms of change in therapy and the prophylactic nature of CT are discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".