Quality of Life in Youth With Chronic Pain
Bibliographic record
Abstract
OBJECTIVES: Pediatric chronic pain has often been examined from a risk perspective, and relatively less is known about the individual and family-level resilience factors that help youth with chronic pain maintain their quality of life (QOL). This cross-sectional study: (1) examined the relations among purported youth and parent resilience (youth pain acceptance and pain self-efficacy, parent psychological flexibility) and risk (youth pain intensity and parent protectiveness) factors with youth QOL, and (2) tested exploratory statistical mechanisms that may explain relations between parent and youth variables. METHODS: Participants included 122 youth (10 to 17 y; M=14.26, SD=2.19) seen in an interdisciplinary pediatric chronic pain program and a parent. Youth completed measures of their average pain, QOL, pain acceptance, and pain self-efficacy. Parents completed measures of their pain-related psychological flexibility and behavioral responses to pain (ie, protectiveness, distraction, monitoring, minimizing). RESULTS: Youth pain acceptance, pain self-efficacy, and parent psychological flexibility were highly positively correlated with each other, and with overall youth QOL. Evidence for a buffering effect of pain acceptance and pain self-efficacy on the association between pain intensity and QOL was not found. Protectiveness was found to be a significant mediator of the relation between parental psychological flexibility and youth QOL. DISCUSSION: The results are discussed in the context of the resilience-risk framework and current understandings of the role of parental factors for pediatric chronic pain.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".