Dyadic differences in friendships of adolescents with chronic pain compared with pain-free peers
Bibliographic record
Abstract
A multisite cross-sectional study was conducted to examine dyadic friendship features between adolescents with chronic pain (ACP) and their friends compared with non-pain adolescent friendship dyads and the association of these friendship features with loneliness and depressive symptoms. Participants completed a battery of standardized measures to capture friendship features (friendship quality, closeness, and perceived social support from friends) and indices of social-emotional well-being. Sixty-one same sex friendship dyads (122 adolescents) participated; 30 friendship dyads included an adolescent with chronic pain and 52 dyads were female. Adolescents with chronic pain scored significantly higher on measures of loneliness and depressive symptoms compared with all other participants. Hierarchical Multiple Regression analysis revealed that friendship features predicted loneliness and depressive symptoms. Chronic pain predicted loneliness and depressive symptoms above and beyond friendship features. Actor Partner Interdependence Modeling found perceived social support from friends had differing associations on loneliness and depressive symptoms for dyads with a chronic pain member compared with pain-free control dyads. Friendship features were associated with loneliness and depressive symptoms for adolescents, but friendship features alone did not explain loneliness and depressive symptoms for ACP. Further research is needed to understand whether pain-related social support improves loneliness and depressive symptoms for ACP. Furthermore, a more nuanced understanding of loneliness in this population is warranted. Strategies to help ACP garner needed social support from friends are needed to decrease rates of loneliness to improve long-term outcomes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".