Effect of Osteopathic Manipulative Therapy on Generalized Anxiety Disorder
Bibliographic record
Abstract
CONTEXT: Traditional management options for generalized anxiety disorder (GAD) have produced low remission rates. As a result, the medical community has turned to complementary and alternative medicine for adjunctive treatment. OBJECTIVE: To investigate the efficacy of adjunctive osteopathic manipulative therapy (OMTh; manipulative care provided by foreign-trained osteopaths) in individuals with GAD. METHODS: This open-label, nonrandomized, black-box study took place at a tertiary care mental health clinic in Toronto, Canada. Adult outpatient participants aged 18 to 65 years with a primary diagnosis of moderate-severe GAD (HAM-A score of ≥20) with or without comorbidities were enrolled in the study between June 2014 and January 2015. Patients who qualified and completed the study received 5 individually tailored OMTh sessions over the course of 8 to 9 weeks. A diagnostic psychiatric assessment (Mini International Neuropsychiatric Interview version 6.0.0) was conducted to confirm diagnoses, along with physician-administered and self-reported measures of anxiety, including the Hamilton Anxiety Scale (HAM-A), the Beck Anxiety Inventory, and the Intolerance for Uncertainty Scale. RESULTS: Significant reductions in total HAM-A scores after OMTh were observed (P<.0001). Significant reductions in total Intolerance for Uncertainty Scale scores were also observed (P<.0001). Beck Anxiety Inventory scores were not found to change significantly with OMTh. Response (defined as 50% reduction of symptoms) and remission (defined as HAM-A score of ≤7) rates were found to be 62% and 26.9%, respectively. CONCLUSION: Osteopathic manipulative therapy may be a valuable adjunct to conventional therapy in patients with GAD, thus warranting further investigation using double-blind procedures.
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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 | 0.001 |
| 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) | 0.002 | 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".