Are They Still Friends? Friendship Stability of Adolescents With Chronic Pain: 1-Year Follow-Up
Bibliographic record
Abstract
Most adolescents identify their best friend as their main source of social support. Adolescents with chronic pain (ACP) report the loss of friendships due to pain. Friendships protect against loneliness and depression, yet adolescents with pain experience increased levels of loneliness and depression compared to peers. This longitudinal study examines the friendship stability of dyads that included an adolescent with chronic pain compared to non-pain friendship dyads as well as the factors contributing to a friendship breakup. Eighty-three participants from 61 same-sex friendship dyads across 3 sites participated in a 1-year follow-up survey designed to capture friendship features, indices of social-emotional well-being, pain characteristics, and friendship stability. Chi-square, repeated measures ANOVA, and logistic regression were used to analyze the data. Dyads that included an ACP experienced higher rates of friendship breakup. The shorter length of friendship and having chronic pain predicted a friendship breakup at time 2. ACP continues to experience worse scores on indices of social-emotional well-being that are not predicted with a friendship breakup. Understanding what contributes to positive long-term friendships for those with pain may inform strategies to maintain and improve friendships for those with pain and who experience social challenges.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".