Pain characteristics, coping strategies and its relation with the quality of life in patients with chronic pain diseases
Bibliographic record
Abstract
OBJECTIVE: To determine the relationship among pain characteristics, coping strategies, and the perception of quality of life in patients with Rheumatoid Arthritis (RA), Osteoarthritis (OA) and Fibromyalgia (FM) through a descriptive correlational method. METHOD: 99 participants from a rheumatic diseases clinic in Bogota (Colombia) were surveyed. Variables were measured with the Visual Analog Scale (VAS), the McGill Pain Questionnaire (MPQ), the Coping Strategies Questionnaire (CSQ), and the Rheumatoid Arthritis Quality of Life Scale (RAQoL). RESULTS: The perception of quality of life was lower when patients reported higher intensity in the perception of pain and a higher score in the affective, sensorial, and evaluative domains of pain. Coping strategies varied among patients with RA, OA, and FM; however, catastrophic thinking is the cognitive strategy mostly used among the three pathologies. CONCLUSION: Intervention programs that help patients change or improve their coping strategies to reduce the intensity of pain and how it is valued are needed in order to produce a positive impact in the quality of life.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".