Efficacy vs. Effectiveness Research in Psychotherapy: Implications for Clinical Hypnosis
Bibliographic record
Abstract
Empirically supported therapy (EST) has become a major focus and trend for mental health practice. When hypnosis is involved, this may mean satisfying a standard that is entirely too narrow in its emphasis. In this article "efficacy"-based research in clinical practice is contrasted with "effectiveness" -focused research, and they are discussed from the perspective of hypnosis. When clinicians can consider trans-theoretical factors as well as those that are treatment-enhancing, possibilities for improved treatment outcome increase. The "effectiveness" perspective also serves as a counter point for hypnosis in contrast with the dubious efficacy-based gold standard currently proposed for therapy in general, and hypnosis in particular.
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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 | 0.280 | 0.402 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.004 | 0.043 |
| Scholarly communication | 0.012 | 0.027 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.010 | 0.013 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".