Social integration of adolescents with chronic pain: a social network analysis
Bibliographic record
Abstract
ABSTRACT: Adolescents with chronic pain (ACP) often experience impairments in their social functioning. Little is known about the consequences of these impairments on peer relationships of ACP. This study applied social network analysis to examine whether adolescents with more pain problems are less popular (RQ1), adolescents with similar pain problems name each other more often as being part of the same peer group (RQ2), dyads with an adolescent experiencing more pain problems report less positive (eg, support) and more negative (eg, conflict) friendship qualities (RQ3), and positive and negative friendship qualities moderate the relationship between pain and emotional distress (RQ4). This study used data from the first wave of a longitudinal study (N = 2767) which followed up Swedish adolescents from 19 public schools. For RQ1-3, Multiple Regression Quadratic Assignment Procedure was applied. For RQ4, standard multilevel models with observations of adolescents nested within schools were estimated. Results showed that ACP were not less popular than adolescents without chronic pain. Second, ACP nominated each other more often as being part of the same peer group. Third, results regarding friendship quality showed that adolescents with more pain problems perceived the relationship with their friends as less positive (eg, support) and more negative (eg, conflict) than adolescents with less pain problems. Finally, positive and negative friendship qualities moderated the relationship between pain and emotional distress. This study contributes to the literature on the importance of peer relationships of ACP. Clinical implications and directions for future research are discussed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".