Examining Parent Adverse Childhood Experiences as a Distal Risk Factor in Pediatric Chronic Pain
Bibliographic record
Abstract
OBJECTIVES: Adverse childhood experiences (ACEs; ie, exposure to abuse, neglect, household dysfunction in childhood) are associated with poor mental and physical health outcomes across the lifespan. Emerging research suggests parent ACEs also confer risk for poor child outcomes. The relation between parent ACEs and child pain in youth with chronic pain has not yet been examined. The aim of the current longitudinal study was to examine the associations among parent ACEs, parent health, and child pain, in a clinical sample of youth with chronic pain. METHODS: In total, 192 youth (75.5% female, 10 to 18 y old) and one of their parents (92.2% female) were recruited from tertiary pediatric chronic pain clinics in Canada. At baseline, parents completed self-report measures of ACEs, chronic pain status, anxiety and depressive symptoms, and posttraumatic stress disorder symptoms. At a 3-month follow-up, youth completed self-report measures of pain intensity and pain interference. RESULTS: Regression and mediation analyses revealed that parent ACEs significantly predicted parent chronic pain status and depressive symptoms, but not parent anxiety or posttraumatic stress disorder symptoms. Moreover, parent ACEs were not significantly related to youth pain, either directly or indirectly through parent health variables. DISCUSSION: Findings suggest that an intergenerational cascade from parent ACEs to parent health to child pain was not present in the current sample. Further research that examines the role of parent ACEs in the development of child chronic pain, as well as other risk and resiliency factors that may mediate or moderate the association between parent ACEs and child chronic pain, is needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".