Return to work program efficacy with Self-Regulation Therapy (SRT®): Case study with complex trauma and concurrent disorders
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background This study shows the efficacy of treating complex cases neurobiologically using Self-Regulation Therapy (SRT®) within the context of return to work goals. Case presentation This is a single case study of a 32-year-old white female. This case study follows a client with concurrent diagnoses of post-traumatic stress disorder (PTSD), bipolar disorder I and substance abuse over the course of 2 years of treatment with SRT®. Using SRT® as primary modality and Likert Scale self-report on the Zettl Scale of Dysregulation, psychiatric medication monitoring and pharmaceutical tracking, this study shows session summaries and progress. Results After six sessions the client was cleared by her psychiatrist for return to work. Her medications were reduced and her post-traumatic symptoms abated. She no longer met diagnostic criteria for PTSD or substance abuse after nine sessions. She returned to work successfully and maintained sobriety and continued symptom reduction. Follow up over a 2-year time period showed consistency and continued improvements in both her professional and her personal life. Conclusions Clients with complex traumatic history with concurrent diagnosis are typically difficult to treat in traditional psychotherapy with limited long-term success. This creates challenges in therapy because the traumas occur during key developmental periods of life. This study shows the efficacy of treating complex cases neurobiologically using SRT®. Using SRT®, clinicians are able to address both developmental and complex trauma to reduce sympathetic arousal in the nervous system providing symptom reduction and even resolution of previous clinical diagnoses.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it