Treatment of depression and mechanisms of change: Strengthening the links among theory, research, and practice.
Bibliographic record
Abstract
Greater knowledge of the mechanisms underlying cognitive change in the context of depression is an important goal of current clinical research. The thoughtful review by Garratt, Ingram, Rand, and Sawalani (2007) highlights the wealth of research that has been conducted in this area, while also drawing attention to the many complexities inherent in studying the cognitive mediation hypothesis in cognitive therapy. In this commentary, we use the review by Garratt et al. as a starting point from which to highlight some of the issues that we believe to be imperative to the advancement of knowledge in this field of research. These issues include the need for strong connections between theories of cognitive mediation and depression, the deployment of appropriate research paradigms and methods to advance the field, and the conduct of research in contexts that are relevant to clinical practice.
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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 | 0.036 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".