Psychological Factors in Chronic Pelvic Pain in Women: Relevance and Application of the Fear-Avoidance Model of Pain
Bibliographic record
Abstract
Chronic pelvic pain in women is a debilitating, costly condition often treated by physical therapists. The etiology of this condition is multifactorial and poorly understood, given the complex interplay of muscles, bones, and soft tissue that comprise the pelvis. There are few guidelines directing treatment interventions for this condition. In the last decade, several investigators have highlighted the role of psychological variables in conditions such as vulvodynia and painful bladder syndrome. Pain-related fear is the focus of the fear-avoidance model (FAM) of pain, which theorizes that some people are more likely to develop and maintain pain after an injury because of their emotional and behavioral responses to pain. The FAM groups people into 2 classes on the basis of how they respond to pain: people who have low fear, confront pain, and recover from injury and people who catastrophize pain-a response that leads to avoidance/escape behaviors, disuse, and disability. Given the presence of pain-related cognitions in women with chronic pelvic pain, including hypervigilance, catastrophizing, and anxiety, research directed toward the application of the FAM to guide therapeutic interventions is warranted. Isolated segments of the FAM have been studied to theorize why traditional approaches (ie, medications and surgery) may not lead to successful outcomes. However, the explicit application of the FAM to guide physical therapy interventions for women with chronic pelvic pain is not routine. Integrating the FAM might direct physical therapists' clinical decision making on the basis of the pain-related cognitions and behaviors of patients. The aims of this article are to provide information about the FAM of musculoskeletal pain and to provide evidence for the relevance of the FAM to chronic pelvic pain in women.
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.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".