Changing society, changing research: integrating gender to better understand physical and psychological treatments use in chronic pain management
Bibliographic record
Abstract
ABSTRACT: Treatment of chronic pain should be multimodal and include pharmacological, physical, and psychological treatments. However, because various barriers to physical and psychological treatments (PPTs) exist, a better understanding of biopsychosocial factors leading to their use is relevant. This study aimed to explore the association between gender identity, gender-stereotyped personality traits, and the use of PPTs in chronic pain management. The ChrOnic Pain trEatment cohort, a self-reported data infrastructure resulting from a web-based recruitment of 1935 people living with chronic pain (Quebec, Canada) was analyzed. Gender identity was operationalized as women, men, and nonbinary. Gender-stereotyped personality traits were measured using the Bem Sex-Role Inventory (feminine, masculine, androgynous, undifferentiated). A checklist of 31 types of PPTs that can be used for chronic pain management was presented to participants (yes/no). From the 1433 participants, 85.5% reported using at least one PPT. Hot-cold therapies (43.4%), exercise (41.9%), and meditation (35.2%) were the most frequently used PPTs, but most popular PPTs were not the same among women and men. Women reported a significantly higher use of PPTs in general (87.2% vs 77.2%; P < 0.001). Multivariable and interaction analyses showed that identifying as a man decreased the odds of reporting the use of PPTs (odds ratio: 0.32, 95% confidence interval: 0.11-0.92) but only among participants who scored high on both masculine and feminine personality traits (those classified as androgynous). The high prevalence of PPTs use found in our study is positive. Our results are relevant for a more personalized promotion of PPTs for chronic pain management.
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How this classification was reachedexpand
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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".