Osteopathic Manipulative Treatment for Allostatic Load Lowering
Bibliographic record
Abstract
CONTEXT: Limited research has been done to examine osteopathic manipulative treatment (OMT) effects on modulating a compilation of allostatic load (AL) biomarkers that work to measure the body's multisystem response to homeostatic deviation. OBJECTIVE: To examine the efficacy of OMT on graduate students' overall health through an objective index of representative AL biomarkers. METHODS: A within-subject pre- and postintervention study was conducted at Touro University College of Osteopathic Medicine in California during the fall 2017 semester. Graduate students enrolled in the Masters of Science in Medical Health Sciences program volunteered to participate in the study and received treatment by an osteopathic physician. The participants were evaluated using the following measures: Trier Inventory for the Assessment of Chronic Stress; diurnal urine cortisol and catecholamines; dried blood glycated hemoglobin, dehydroepiandrosterone, high-density lipoprotein, and high-sensitivity C-reactive protein; blood pressure, body mass index, and waist-to-hip ratio before (preintervention) and after (postintervention) OMT. RESULTS: The study consisted of 1 man (participant 1) and 1 woman (participant 2) aged 23 and 22 years, respectively. Participants were enrolled in the same academic program and received 3 OMT sessions in 7 weeks. Analysis of AL biomarkers revealed a decrease in overall AL scores from preintervention to postintervention in participant 1 (from 7 to 4) and participant 2 (from 9 to 7). Analysis of Trier Inventory for the Assessment of Chronic Stress scores revealed a decrease in self-perceived stress from preintervention to postintervention in participant 1 (from 18 to 15) and in participant 2 (from 40 to 13). CONCLUSION: The OMT protocol used in the current study decreased measures of overall AL and self-perceived stress in both participants. This finding suggests that OMT may represent a reasonable modality to reduce AL and self-perceived stress in graduate students. Since the current study is limited by its small sample size, further research is warranted.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".