Pain and PTSD symptoms in female veterans⋆,⋆⋆
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 has been growing empirical examination of the co-occurrence of pain and post-traumatic stress disorder (PTSD) symptoms, and existing evidence suggests that the symptoms associated with each have a close association. To date, however, the association has only been examined within samples of mostly male participants. AIM: In the present study, pain and PTSD symptoms were examined in a sample of 221 female veterans who utilised the VA Healthcare System between 1998 and 1999. METHOD: Women who visited the clinic between 1998 and 1999 were mailed a self-report questionnaire package designed to elicit information regarding general health (including pain experiences), military and trauma history, childhood abuse and neglect, and PTSD symptoms. Analyses were conducted to identify differences in pain experience between those women classified as having PTSD, subsyndromal PTSD, and no PTSD. Analyses were also conducted to determine the degree to which pain-related (e.g., current pain, interference with activity) variables predicted PTSD symptom cluster scores. RESULTS: The three groups differed significantly on a number of pain-related variables. Analyses suggested that pain-related variables were significant predictors of PTSD symptom cluster scores. CONCLUSIONS: These results indicate that the association between pain and PTSD symptoms, previously observed in primarily male samples, is generalisable to females. Clinical implications and possible mechanisms of association are discussed.
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 | 0.015 | 0.001 |
| 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) | 0.001 | 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