Longitudinal investigation of pain catastrophizing, pain intensity, and suicidal ideation in women receiving residential treatment for an eating disorder
Bibliographic record
Abstract
Pain catastrophizing and pain intensity are related to suicidal thoughts and eating disorders. When individuals experience both high pain intensity and catastrophizing, they may experience higher levels of suicidal ideation (SI). Despite increased risk for SI in eating disorder (ED) populations, no research has examined the relationship between pain experience and suicidal thoughts using a longitudinal design. The current study tested the weekly relationships between pain catastrophizing and pain intensity on SI in a clinical sample of women engaged in residential ED treatment. Female participants (N = 79; Mage = 26.44, 92.4% White, 94.9% Non-Hispanic/Latina) sought treatment at a residential ED treatment facility and completed self-report measures each week. Random intercept, random slope models were specified to test the relationship between pain intensity and pain catastrophizing on SI over eight weeks of treatment. Individuals with higher pain catastrophizing demonstrated greater severity of SI. There were no significant effects for within-person pain catastrophizing, within-person pain intensity, or for the interaction between within-person pain catastrophizing and intensity variables on SI. Pain catastrophizing is associated with SI at the between person level across residential ED treatment. Pain catastrophizing may be an important target for the prevention or treatment of SI in at-risk populations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".