Massage for Combat Injuries in Veteran with Undisclosed PTSD: a Retrospective Case Report
Bibliographic record
Abstract
INTRODUCTION: Massage has shown promise in reducing symptoms related to dissociation and anxiety that can exacerbate chronic pain and suffering. The combat wounded, veteran population is increasing and requires a multidisciplinary approach for comprehensive treatment. This case study examines massage therapy use to improve veteran combat injury rehabilitation and recovery experience through purposive, retrospective, and comprehensive SOAP note review. METHODS: A 31-year-old White male received seven, 60-min, full body massages for combat related shoulder injury complications incurred approximately six years before presentation. The right shoulder sustained a broken humeral head and complete dislocation during a defensive maneuver in a life-threatening attack. This case study utilized data from three different assessments: goniometric measurements for shoulder range of motion, observation and documentation for environmental comfort behaviors, and client self-report for treatment goal attainment. Six weekly, full body, 60-min massages were completed sequentially. A follow-up 60-min treatment was completed at Week 8. Treatment to the injured area included focused trigger point therapy, myofascial release, and proprioceptive neuromuscular facilitation to the neck, shoulder, and chest. RESULTS: Total percent change for active flexion, extension, abduction, adduction, internal rotation, and external rotation were 12.5, 150, 40, 167, 14.3, and 0%, respectively. Total percent change for passive flexion, extension, abduction, adduction, internal rotation, and external rotation were 63.6, 350, 66.7, 450, 133, and 77.8%, respectively. Environmental comfort behaviors were reduced. Client treatment goals were attained. CONCLUSIONS: Massage therapy provided meaningful benefit to a combat injury for a veteran with PTSD.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".