Narrative Accounts of Youth and Their Mothers With Chronic Headache
Bibliographic record
Abstract
OBJECTIVES: This study was the first to apply a socio-narratology framework to the narratives about child pain as told by youth with chronic pain and their parents, all of whom experience chronic headaches. BACKGROUND: Storytelling is a powerful social transaction that occurs within systems (eg, families, clinical encounters) and is both shaped by, and can shape, the pain experience. Narrative can be harnessed as a clinical tool to aid in the ability to listen, understand, and improve clinical encounters. METHODS: Twenty-six youth (aged 11 to 18 y) and their mothers, both with chronic headaches, recruited from a tertiary level pediatric pain clinic separately completed in-depth interviews about children's pain journey narratives. Data were analyzed using narrative analysis, which incorporated elements of socio-narratology to compare similarities and differences between and within dyads' narratives. RESULTS: Five narrative types were generated: (1) The trauma origin story-parents, but not youth, positing traumatic events as the causal link to children's pain; (2) mistreated by the medical system-neglect, harm, and broken promises resulting in learned hopelessness or relying on the family system; (3) the invalidated-invalidation of pain permeated youth's lives, with mothers as empathic buffers; (4) washed away by the pain-challenges perceived as insurmountable and letting the pain take over; and (5) taking power back from pain-youth's ability to live life and accomplish goals despite the pain. CONCLUSION: Findings support the clinical utility of narrative in pediatric pain, including both parents' and youths' narrative accounts to improve clinical encounters and cocreate more youth-centred, empowering narratives.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".