Impacts of imagery-enhanced versus verbally-based cognitive behavioral group therapy on psychophysiological parameters in social anxiety disorder: Results from a randomized-controlled trial
Bibliographic record
Abstract
Social anxiety disorder (SAD) is associated with marked physiological reactivity in social-evaluative situations. However, objective measurement of biomarkers is rarely evaluated in treatment trials, despite potential utility in clarifying disorder-specific physiological correlates. This randomized controlled trial sought to examine the differential impact of imagery-enhanced vs. verbal-based cognitive behavioral group therapy (IE-CBGT, n = 53; VB-CBGT, n = 54) on biomarkers of emotion regulation and arousal during social stress in people with SAD (pre- and post-treatment differences in heart rate variability (HRV) and skin conductance). We acquired psychophysiological data from randomized participants across four social stress test phases (baseline, speech preparation, speech, interaction) at pre-treatment, and 1- and 6-months post-treatment. Analyses revealed that IE-CBGT selectively attenuated heart rate as indexed by increases in median heart rate interval (median-RR) compared to VB-CBGT at post-treatment, whereas one HRV index showed a larger increase in the VB-CBGT condition before but not after controlling for median-RR. Other psychophysiological indices did not differ between conditions. Lower sympathetic arousal in the IE-CBGT condition may have obviated the need for parasympathetic downregulation, whereas the opposite was true for VB-CBGT. These findings provide preliminary insights into the impact of imagery-enhanced and verbally-based psychotherapy for SAD on emotion regulation biomarkers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".