Forward thinking: correlates of posttreatment outcome expectation among depressed outpatients / <i>Pensamiento prospectivo: correlatos de las expectativas de resultados post-tratamiento de pacientes ambulatorios que sufren depresión</i>
Bibliographic record
Abstract
Although patients’ expectation about a treatment’s efficacy correlate with beneficial therapy processes and outcomes, scant research addresses patients’ expectation for lasting improvement at treatment’s end. Given the influence of beliefs on psychological functioning, posttreatment outcome expectation reflects an important acute treatment outcome. In this study, we examined patient characteristics, treatment processes and clinical change factors in relation to the posttreatment outcome expectation of 65 depressed outpatients completing group cognitive-behavioural therapy. Less than 1% of variability in posttreatment outcome expectation was due to group effects; thus, we conducted single-level regressions. Patients with less severe baseline depression, higher session 3 outcome expectation, more during-treatment hope and a greater reduction in interpersonal problems reported greater posttreatment outcome expectancy. Various patient characteristics and change factors can help clinicians forecast, and respond to, those patients who will possess stronger or weaker belief in their ability to maintain therapy gains at treatment’s end.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".