<p>Pain experiences and intrapersonal change among patients with chronic non-cancer pain after using a pain diary: a mixed-methods study</p>
Bibliographic record
Abstract
OBJECTIVE: Pain diaries are a valuable self-assessment tool; however, their use in chronic non-cancer pain has received limited attention. In this study, we examined the effect of pain diary use on pain intensity, interference, and intrapersonal change in patients with chronic non-cancer pain. METHOD: A convergent mixed-methods design was used to prospectively evaluate a cohort of 72 patients. Daily pain intensity and weekly pain-interference were self-reported using pain diaries for a 4-week period. Outcomes were assessed by examining changes in pain scores (primary outcome) as well as the Brief Pain Inventory and Short-form McGill Pain Questionnaire-2. In addition, qualitative data obtained from pain diary entries and focus-group interviews were analyzed using thematic content analysis. RESULTS: Pain intensity and average pain scores were significantly lower after using the diaries. Participants reported less pain interference in mood, walking ability, normal work, and enjoyment of life. No differences were found in SF-MPQ-2 scores. Qualitative analysis indicated that better pain recognition and more effective communication with care providers led to improved self-management and more effectual treatment plans. CONCLUSION: Use of a pain diary in patients with chronic non-cancer pain was associated with reduced pain intensity and improved mood as well as function. Further controlled trials examining the long-term effects of pain diaries are warranted.
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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 | 0.007 | 0.007 |
| 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 | 0.000 |
| 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".