CBT Guided Self-Help Compares Favourably to Gold Standard Therapist-Administered CBT and Shows Unique Benefits Over Traditional Treatment
Bibliographic record
Abstract
CBT guided self-help (CBTgsh) can produce treatment outcomes comparable to therapist-administered CBT (CBTta) for the treatment of anxiety and depression. The efficacy of CBTgsh compared to gold standard CBTta, however, remains to be examined. The current article addresses this issue, as well as how CBTgsh may have unique benefits over CBTta. It further highlights ways in which CBTgsh may be used for disorders of increasing severity, using eating disorders and personality pathology for illustrative purposes. A literature review of PsycINFO, PsyARTICLES, and PubMED was conducted to identify relevant studies published since 1990. Studies directly comparing CBTgsh to gold standard CBTta for anxiety and depression, as well as bulimia nervosa, revealed no significant differences between the two interventions. Furthermore, CBTgsh may have unique benefits by encouraging continued improvement over time. Innovative eating disorder studies also show that CBTgsh can be used for more severe disorders as a supplementary treatment, and produces treatment outcomes superior to CBTta or treatment as usual alone. Based on these findings, CBTgsh applications to personality pathology are suggested. Traditional stepped care models, as they pertain to CBTgsh, may gain to be broadened both in their focus and methods of delivery.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".