The Relationship Between the Pain Experience and Emotion Regulation in Older Adults
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationship of emotion regulation strategies (i.e., emotional suppression and reappraisal) with pain catastrophizing, fear of pain, pain intensity, worry, and depression as function of age in samples of older and younger adults. DESIGN: Cross-sectional design using validated questionnaires. SETTING: Participants resided in the community. They completed validated measures using online questionnaires. SUBJECTS: Two-hundred fifty-seven older adults and 254 younger adults with chronic pain participated. METHODS: Participants completed validated questionnaires of emotion regulation strategies, pain-related functioning and mental health. RESULTS: Emotion regulation varied as a function of age and gender. Among our chronic pain sample, older adult males reported lower use of reappraisal and suppression than younger adult males, while older adult females reported higher use of reappraisal than younger adult females. Emotional suppression was positively related to pain catastrophizing, pain intensity, worry, and depression. Reappraisal was negatively related to depression and worry. Interestingly, age showed a positive relationship with fear of pain, pain catastrophizing, worry, depression, and pain intensity, while gender was related to fear of pain and worry. Finally, emotional reappraisal partially mediated the relationship between the affective dimensions of pain intensity and pain catastrophizing among older adults. CONCLUSIONS: Our results indicate that reappraisal strategies are important for older and younger adults with chronic pain, pointing to the necessity of considering these strategies when working clinically with such populations. However, given our findings as well as those in the literature, gender should also be considered.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".