Treatment expectations and clinical outcomes following repetitive transcranial magnetic stimulation for treatment-resistant depression
Bibliographic record
Abstract
BACKGROUND: Patient expectations, including both positive (placebo) and negative (nocebo) effects, influence treatment outcomes, yet their impact on acute repetitive transcranial magnetic stimulation (rTMS) for treatment-resistant depression (TRD) is unclear. METHODS: In this single-center retrospective chart review, 208 TRD patients completed the Stanford Expectation of Treatment Scale (SETS) before starting open-label rTMS treatment. Patients were offered two excitatory rTMS protocols (deep TMS or intermittent theta-burst stimulation), which stimulated the left dorsolateral prefrontal cortex. A minimum of 20 once daily treatments were provided, delivered over 4-6 weeks. Primary outcomes were 1) remission, measured by a post-treatment score of <8 on the Hamilton Depression Rating Scale (HAMD-17), and 2) premature discontinuation. The change in HAMD-17 scores over time was used as a secondary outcome. Physicians were blinded to SETS scores. Logistic and linear regression, adjusting for covariates, assessed SETS and HAMD-17 relationships. RESULTS: Of 208 patients, 177 had baseline and covariate data available. The mean positivity bias score (positive expectancy minus negative expectancy subscale averages) was 0.48 ± 2.21, indicating the cohort was neutral regarding the expectations of their treatment on average. Higher positive expectancy scores were significantly associated with greater odds of remission (OR = 1.90, p = 0.003) and greater reduction in HAMD-17 scores (β = 1.30, p = 0.005) at the end of acute treatment, after adjusting for covariates. Negative expectancy was not associated with decreased odds of remission (p = 0.2) or treatment discontinuation (p = 0.8). CONCLUSIONS: Higher pre-treatment positive expectations were associated with greater remission rates with open-label rTMS in a naturalistic cohort of patients with TRD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".