The Effects of a Brief Acceptance-Based Behavioral Treatment Versus Traditional Cognitive-Behavioral Treatment for Public Speaking Anxiety
Bibliographic record
Abstract
Individuals with public speaking anxiety (PSA) experience fear and avoidance that can cause extreme distress, impaired speaking performance, and associated problems in psychosocial functioning. Most extant interventions for PSA emphasize anxiety reduction rather than enhancing behavioral performance. We compared the efficacy of two brief cognitive-behavioral interventions, a traditional cognitive-behavior treatment (tCBT) and an acceptance-based behavior treatment (ABBT), on public speaking performance and anxiety in a clinical sample of persons with PSA. The effects of treatment on prefrontal brain activation were also examined. Participants (n = 21) were randomized to 90 min of an ABBT or a tCBT intervention. Assessments took place at pre- and post-treatment and included self-rated anxiety and observer-rated performance measures, a behavioral assessment, and prefrontal cortical activity measurements using functional near-infrared spectroscopy (fNIRS). Exploratory results indicated that participants in the ABBT condition experienced greater improvements in observer-rated performance relative to those in the tCBT condition, while those in the tCBT condition experienced greater reductions in subjective anxiety levels. Individuals in the ABBT condition also exhibited a trend toward greater treatment-related reductions in blood volume in the left dorsolateral prefrontal cortex relative to those who received tCBT. Overall, these findings preliminarily suggest that acceptance-based treatments may free more cognitive resources in comparison with tCBT, possibly resulting in greater improvements in objectively rated behavioral performances for ABBT interventions.
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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 | 0.001 |
| 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) | 0.003 | 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".