Coping behaviour and outcome in two pain populations : a general adult population with neck or low back pain & individuals suffering from pain due to motor-vehicle Injuries
Bibliographic record
Abstract
The role of coping behaviour in the adjustment of pain sufferers has received much attention in recent years. However, despite the abundance of research, there are still some gaps in the literature. For example, little research has been done to investigate how pain sufferers in the general population or individuals suffering from pain secondary to a motor vehicle collision cope with their pain, and how that affects their outcome. The present studies sought to clarify the role of coping strategies within the pain experience by reviewing the existing literature and addressing some of the gaps. Four separate studies were conducted. Study 1 consisted of a systematic review of the literature on coping with pain. Its purpose was to summarize the scientifically sound information regarding coping with pain. Study 2 consisted of a systematic review of the literature on the risk/prognostic factors for low back pain. Its purpose was to identify valid risk/prognostic factors and use this information to guide the analyses in the empirical studies. Study 3 examined the ability of passive coping strategies to predict the development of disabling neck and/or low back pain in a random sample of the general population who were suffering from non-disabling spinal pain. Study 4 examined the ability of passive coping strategies to predict recovery in a population of individuals suffering from whiplash or low back pain secondary to a motor vehicle collision. The findings show that the current literature on coping with pain highlights the maladaptive nature of passive coping strategies like catastrophizing or allowing the pain to restrict/decrease activities. Studies 3 and 4 further highlight the negative impact of passive coping behaviour, identifying it as an important risk factor for the development of disabling pain and as a prognostic factor for poor recovery from whiplash and low back pain resulting from a motor vehicle collision. These combined findings point to the need for disseminating information about the maladaptive nature of passive coping strategies and for developing programs that target the decreased use of this response to pain. In addition, it highlights the need for further research that examines the impact of decreasing these passive strategies and identifying coping behaviours and other factors that promote better adjustment.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".