Estimating the smallest worthwhile difference of recommended psychotherapies for depression: observational study
Bibliographic record
Abstract
Background The smallest worthwhile difference (SWD) represents the smallest beneficial effect of an intervention that patients deem worthwhile given the harms, expenses and inconveniences of the intervention. The SWD facilitates interpretation of the patient-perceived importance of intervention effects. We previously estimated the SWD for antidepressants for depression, but the SWD for psychotherapy remains unknown. Aims To estimate the SWD of recommended psychotherapies for depression compared with no treatment. Method We estimated the SWD through a patient required difference in response rates between psychotherapy and no treatment after 2 months. We recruited using Prolific, an online cross-sectional survey platform, in the UK and USA in January 2025. We also queried a random subset of respondents to replicate our previous SWD estimation for antidepressants. Results In the primary study, we recruited 526 participants (mean age: 36.7 years (s.d. = 12.5); 54% women and 61% White individuals). Of these, 6% reported that they would not initiate psychotherapy with a 100% treatment response. For those willing to initiate psychotherapy, 87 reported moderate-to-severe depressive symptoms but were not in treatment, 184 were in treatment and 131 reported absent-to-mild symptoms with or without previous treatment. The median SWD for people with moderate-to-severe depressive symptoms, not in treatment and willing to consider psychotherapies was a 20% (interquartile range: 10–35%) difference in response rates comparing psychotherapy with no treatment. This was similar to the SWD for antidepressant drugs (SWD = 20%, interquartile range: 10–30%; n = 104). Participant characteristics were not meaningfully associated with the SWD. Conclusions Current empirically supported psychotherapy response rates of 15% were sufficient for one in three people to initiate psychotherapy given the burdens, but two in three expected greater treatment benefits or fewer burdens. The SWD for psychotherapy was not materially different from the estimated SWD for antidepressants. Individual patient value judgements and preferences merit greater attention. These findings should be replicated with diverse samples from different geographical locations.
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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 | 0.027 | 0.099 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".