Imagery and Pain: The Prevalence, Characteristics, and Potency of Imagery Associated with Pain
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: There is a dearth of information about imagery in pain sufferers. AIM: The aim of this study was to collect data on the characteristics, prevalence, and potency of imagery associated with pain. METHOD: The images of 59 pain sufferers were assessed by means of a semi-structured interview. The emotional, cognitive, behavioural, and pain-inducing properties (potency) of their index images were assessed by an image induction procedure and self-report scales of anxiety, depression and trauma symptoms. RESULTS: The results showed a remarkably high incidence of images in pain sufferers, with 78% of participants reporting one or more repetitive images when in pain. Exposure to their most powerful/distressing image (Index image) resulted in significant increases in negative emotions, negative cognitive appraisals, and in pain levels. In a sub-group of sufferers with significant levels of trauma symptoms, the index images elicited significantly higher levels of emotion and pain increment than did those respondents in a low/no trauma group. CONCLUSION: It was concluded that imagery is a prevalent, often "unobserved" but potent cognition in pain sufferers. The implications for CBT approaches to chronic pain, including image rescripting, are considered.
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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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