Systematic Review of the Utility of Physiological Measures as Trauma Treatment Outcome Measures
Bibliographic record
Abstract
Background Psychophysiological abnormalities have been correlated with trauma, including exaggerated startle and delayed cardiac recovery to baseline. However, the reliability of standard subjective symptom assessments can be compromised by memory biases and declarative memory dysfunction. Comparatively, dynamic emotional changes may be objectively indicated by physiological responses. Aim Evaluate the utility and validity of psychophysiological markers as trauma intervention outcome measures. Methods Search Criteria A systematic review of trauma-focused interventions was conducted in PubMed, PsychInfo, and Medline databases for randomized controlled trials and longitudinal studies from inception to July 2019. Study selection Twenty-one studies reporting psychophysiological measurement values at post-treatment assessment points were included. Search Terms Three levels of search terms were used. This included terminology for Post-traumatic Stress Disorder, Psychophysiological measurement, and Treatment outcomes. Review process: Results were grouped by theme of intervention and interpreted for trends in treatment responses Results Physiological measures including heart rate, heart rate variability, and skin conductance had all been used repeatedly. Changes in these correlated moderately consistently with changes in psychometrics, and using sensing technology presented the added benefit of gathering real-time data. Improving intervention content by identifying specific components of intervention demonstrated clinical utility of biomarkers, and predictive utility was seen in the markers’ sensitivity in predicting levels of treatment response from baseline measures or initial treatment sessions. The greatest advantage of in-vitro physiological assessment from wearable sensor is real-time temporal tracking before, during, and post experimental paradigms. Continuous psychophysiological recordings created and aligned with crucial event markers of the given interventions. Conclusion Psychophysiological measures are a promising objective index of PTSD treatment response that can help verify clinical impressions and self-reports. Elevated psychophysiological responses could be a pathogenic mechanism in the etiology or expression of PTSD, and thus, a means or measure of intervention. Further research is needed to confirm clinical utility of psychophysiological measures, provide valid response cut-offs, and reduce measurement error from data processing.
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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 | 0.013 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".