Use of Mental Health Telemetry to Enhance Identification and Predictive Value of Early Changes During Augmentation Treatment of Major Depression
Bibliographic record
Abstract
Standard clinical trial methodology in depression does not allow for careful examination of early changes in symptom intensity. The purpose of this study was to use daily "Mental Health Telemetry" (MHT) to prospectively record change in depressive and anxiety symptoms for depressed patients receiving augmentation treatment, and determine the extent and predictive capacity of early changes. We report results of a 6-week, open-label study of the addition of quetiapine XR (range, 50-300 mg) for adult patients (n = 26) with major depressive disorder who were nonresponsive to antidepressant treatment. In addition to regular study visits, all participants completed daily, wirelessly transmitted self-report ratings of symptoms on a Smartphone. Daily and 3-day moving average mean scores were calculated, and associations between early symptom change and eventual response to treatment were determined. Improvement in depressive and anxiety symptoms was identified as early as day 1 of treatment. Of the total decline in depression severity over 6 weeks, 9% was present at day 1, 28% at day 2, 39% at days 3 and 4, 65% at day 7, and 80% at day 10. Self-report rating of early improvement (≥20%) in depressive symptoms at day 7 significantly predicted responder status at week 6 (P = 0.03). Clinician-rated depressive and anxiety symptoms only became significantly associated with responder status at day 14. In conclusion, very early changes in depressive symptoms were identified using MHT, early changes accounted for most of total change, and MHT-recorded improvement as early as day 7 significantly predicted response to treatment at study end point.
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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 | 0.000 |
| 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".