Finding Silver Linings: A Preliminary Examination of Benefit Finding in Youth With Chronic Pain
Bibliographic record
Abstract
Background: Chronic pain is a pervasive condition in adolescence and is associated with significant psychological distress, functional disability, social isolation, and decreased quality of life for a subset of affected youth. There is a paucity of research examining potential resilience factors and adaptive processes in pediatric chronic pain. Benefit finding refers to the process of perceiving positive consequences in the face of adversity. Previous research on benefit finding in pediatric samples (e.g., oncology; acute injury) has yielded inconsistent results. This is the first study to examine this construct in youth with chronic pain. Objective: The objective of the current investigation was to extend previous research on benefit finding to adolescents with chronic pain and to assess relationships between benefit finding, internalizing mental health symptoms (i.e., anxiety, depression, and posttraumatic stress disorder [PTSD]), pain outcomes (pain intensity and interference), and quality of life. Methods: Psychometrically sound self-report measures of benefit finding, anxiety, depressive, and PTSD symptoms, pain intensity, pain interference, and quality of life were completed by 145 youth (67.4% female, Mage = 13.3 years, SD = 2.6), referred to a tertiary-level chronic pain program. Results: Benefit finding was significantly correlated with internalizing mental health symptoms, pain outcomes, and quality of life. Further, benefit finding significantly predicted children's self-reported pain intensity, pain interference, and quality of life when controlling for age and sex. Conclusions: Findings suggest that benefit finding is associated with internalizing mental health symptoms, pain outcomes, and quality of life in youth with chronic pain. Future research examining this construct is 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".