Task-sharing and telemedicine delivery of psychotherapy to treat perinatal depression: a pragmatic, noninferiority randomized trial
Bibliographic record
Abstract
Task-sharing and telemedicine can increase access to effective psychotherapies. Scaling Up Maternal Mental healthcare by Increasing access to Treatment (SUMMIT) is pragmatic, multisite, noninferiority, four-arm trial that tested the non-inferiority of provider (non-specialist vs. specialist providers) and modality (telemedicine vs. in-person) in delivering psychotherapy for perinatal depressive symptoms. Across three university-affiliated networks in the United States and Canada, pregnant and postpartum adult participants were randomized 1:1:1:1 to each arm (472 nonspecialist telemedicine, 145 nonspecialist in-person, 469 specialist telemedicine and 144 specialist in-person) and offered weekly behavioral activation treatment sessions. The primary outcome was depressive symptoms (Edinburgh Postnatal Depression Scale (EPDS)) and the secondary outcome was anxiety (Generalized Anxiety Disorder (GAD-7)) symptoms at 3 months post-randomization. Between 8 January 2020 and 4 October 2023, 1,230 participants were recruited. Noninferiority was met for the primary outcome comparing provider (EPDS: nonspecialist 9.27 (95% CI 8.85-9.70) versus specialist 8.91 (95% CI 8.49-9.33)) and modality (EPDS: telemedicine 9.15 (95% CI 8.79-9.50) versus in-person 8.92 (95% CI 8.39-9.45)) for both intention-to-treat and per protocol analyses. Noninferiority was also met for anxiety symptoms in both comparisons. There were no serious or adverse events related to the trial. This trial suggests compelling evidence for task-sharing and telemedicine to improve access to psychotherapies for perinatal depressive and anxiety symptoms. ClinicalTrials.gov NCT04153864.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".