Contributors to the Establishment, Maintenance, and Exacerbation of Comorbid Chronic Pain and Posttraumatic Stress Disorder
Bibliographic record
Abstract
There is a high comorbidity between posttraumatic stress disorder (PTSD) and chronic pain, yet the factors that contribute to this relationship are not well understood. Research suggests that PTSD and chronic pain might interact and aggravate each other through common vulnerabilities and symptoms. To illuminate this interaction, this mixed methods dissertation examined the relationship between pain and PTSD symptoms in Canadian Armed Forces (CAF) service members and veterans. It also investigated the role that traumatic memory processes play in facilitating pain and PTSD by examining “pain flashbacks,” a symptom of PTSD in which individuals report re-experiencing pain they felt during a physically traumatic event. In Study 1, I investigated the factors that mediate the relationship between PTSD and pain-related disability in military personnel. Pain catastrophizing and pain traumatization sensitivity significantly mediated the relationship between PTSD and pain-related disability. In Study 2, I described how military personnel think about their experiences of PTSD and chronic pain to elucidate contributing factors to the comorbidity. I also described participants’ pain flashbacks to elucidate the role that they play in facilitating pain and PTSD. Three themes were identified from this qualitative analysis: “Ghost Pains,” “Traumatization from Within and Without,” and “Struggling Past the Traumatized Self.”\n\nThese studies add to our understanding of the establishment, maintenance, and exacerbation of comorbid chronic pain and PTSD, and contribute to knowledge of pain flashbacks. An understanding of this pain manifestation is critical, as pain flashbacks may magnify PTSD symptoms and worsen chronic pain severity, creating a downward spiral of mental and physical health symptoms. Furthermore, increased knowledge of pain flashbacks is important to our understanding of pain more generally, as the phenomenon suggests that the context in which we experience pain contributes to the encoding of memories of pain, and may facilitate the retrieval of memories of pain, or pain itself, when reminders of the encoding context arise later. By better understanding the contributing factors to chronic pain and PTSD, it may be possible to prevent the development or exacerbation of these conditions through early intervention and treatment strategies targeting the factors driving the conditions.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".