Exploring the impact of safety behaviour use on cognitive, psychophysiological, emotional and behavioural responses during a speech task
Bibliographic record
Abstract
BACKGROUND: There is a debate among researchers and clinicians regarding whether the judicious use of safety behaviours (SBs) during exposure therapy is helpful or detrimental. Central to this debate is the premise that SBs may interfere with one's ability to gather disconfirmatory evidence. AIMS: No study to date has assessed how SB use may impact cognitive mechanisms implicated during an exposure-like task. We investigated multiple cognitive, emotional, psychophysiological and behavioural underpinnings of exposure with and without SBs. METHOD: Speech anxious participants (n = 111) were randomly assigned to deliver an evaluated speech with or without SBs. Self-reported anxiety ratings and psychophysiological arousal measures were recorded at baseline, in anticipation of the speech, and following the speech. Measures of working memory, ability to gather disconfirmatory evidence, speech duration, objective and subjective speech performance, and speech task acceptability were administered. RESULTS: There were no differences between conditions on working memory, self-reported anxiety, psychophysiological arousal, ability to gather disconfirmatory evidence, speech duration, or objective and subjective speech performance. All participants were able to gather disconfirmatory evidence. However, condition did influence willingness to deliver future speeches. Our sample was largely female undergraduate students, and we offered only a small number of specific safety behaviours. CONCLUSIONS: Judicious SB use may not necessarily be detrimental, but clients may believe them to be more helpful than they actually are.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".