Intermittent theta burst stimulation for non-suicidal self-injury in adolescents with major depressive disorder: a randomized, sham-controlled trial
Bibliographic record
Abstract
Non-suicidal self-injury (NSSI) poses a significant threat to adolescents with major depressive disorder (MDD) owing to elevated hospitalization and suicidality risks. Intermittent theta burst stimulation (iTBS) shows promise for treating NSSI in adolescents with depression. The efficacy of iTBS for treating NSSI in adolescents with MDD was evaluated in this study. In this sham-controlled, randomized clinical trial, adolescents with MDD were allocated randomly to active or sham treatment groups in a 1:1 ratio. They received active or sham iTBS over the left dorsolateral prefrontal cortex (LDLPFC) for five sessions daily for 5 days. The primary outcome was the difference in NSSI frequency and severity at 4-week follow-up, assessed using the Deliberate Self-Harm Inventory-Adolescent Revised version (DSHI-AR). Additional measures included changes in the Deliberate Self-Harm Ideation Scale for Adolescents Revised (DSHI-AR ideation) and Ottawa Self-Injury Inventory-addiction subscale (OSI-addiction). Of the 60 participants (mean [standard deviation] age, 14.2 [1.5] years; female sex, 55 patients [91.7%]), 85% completed the intervention. At 4 weeks post-intervention, the active treatment group showed greater DSHI-AR score reduction than the sham treatment group (mean difference, -18.66; 95% confidence interval [CI], -28.35--8.97). Active treatment led to a greater decline in DSHI-AR ideation (mean difference, -9.23; 95% CI, -14.41--4.05) and OSI-addiction (mean difference, -6.16; 95% CI, -10.58--1.74) scores compared with the sham treatment. Mild headaches were reported during the intervention, without significant group differences. The findings indicate that iTBS targeting the LDLPFC is an effective and well-tolerated strategy for treating NSSI in adolescents with MDD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".