Effect of Motor Interference Therapy on Distress Related to Traumatic Memories: A Randomized, Double‐Blind, Controlled Feasibility Trial
Bibliographic record
Abstract
INTRODUCTION: Traumatic memories (TM) are a core feature of stress-related disorders, including posttraumatic stress disorder (PTSD). Treatment is often difficult, and specific pharmacological interventions are lacking. We present a novel non-pharmacological intervention called motor interference therapy (MIT) as a promising alternative for these symptoms. AIMS: To determine the feasibility of MIT, a brief, audio-delivered, and non-pharmacological intervention that uses cognitive and motor tasks to treat TM. METHODS: We designed a randomized, double-blind trial. Twenty-eight participants from an outpatient clinic with at least one TM were included to receive either MIT or progressive muscle relaxation (PMR). Spanish versions of the PTSD symptom severity scale (EGS), visual analog scale for TM (TM-VAS), and quality of life (EQ-VAS) were applied prior to intervention, 1 week, and 1 month following intervention. RESULTS: Mean scores on all measures improved from baseline to posttest for both groups. MIT participants showed significantly more positive scores at 1 week and 1 month (TM-VAS baseline: 9.8 ± 0.4; immediate: 6.0 ± 2.0; 1 week: 3.8 ± 3.1 [d = 1.57]; 1 month 2.9 ± 2.8 [d = 1.93]) than PMR participants on measures of distress due to TM, trauma re-experiencing, anxiety, and a composite measure of PTSD. CONCLUSION: MIT is a simple, effective, and easy-to-use tool for treating TM and other stress-related symptoms. It requires relatively few resources and could be adapted to many contexts. The results provide proof-of-principle support for conducting future research with larger cohorts and controls to improve clinical effectiveness and research on brief interventions. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03627078.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".