Verbal Repetition in the Reappraisal of Contamination-Related Thoughts
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: Acceptance and Commitment Therapy advocates use of cognitive defusion techniques to reduce the distress evoked by negative thoughts, including verbal repetition (VR). In VR, a negative word is repeated until its semantic meaning is diluted (i.e. until semantic satiation is achieved). The present two studies examined whether VR is more effective than brief imaginal exposure (IE) and no intervention (CONT) in the reappraisal of contamination-related thoughts. METHOD: Participants high in contamination fears identified their most distressing thoughts and were randomly assigned to VR, IE, or CONT. A category membership decision task was also conducted to determine if VR produced semantic satiation. RESULTS: In Study 1, there was no evidence of semantic satiation. Significant reductions in negative response to the thoughts was observed immediately following VR, but not IE or CONT; however, at one-week follow-up, both VR and IE groups reported similar reductions. In Study 2, the effects of VR and IE practice between post-intervention and follow-up were examined, as well as changes in behavioural avoidance. VR was found to produce semantic satiation of contamination thoughts, and VR was associated with less negative response at follow-up relative to IE and CONT, but the degree of satiation was not associated with the decreases in negative response. Only IE produced decreases in behavioural avoidance and vigilance monitoring. CONCLUSIONS: Taken together, these results suggest that VR may have potential as an additional strategy for managing obsessional thoughts, but more research is warranted.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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