Adverse Childhood Experiences and Primary Headache Disorders
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Headache disorders are among the leading causes of disability worldwide. While an association between adverse childhood experiences and primary headaches has been reported, the pooled magnitude across studies and pathways of the association are unknown. Our objectives were (1) to estimate the pooled effect of ≥1 adverse childhood experience (ACE) on primary headache disorders in adulthood and (2) to test the hypothesis that ACEs categorized as "threat" traumas or "deprivation" traumas have distinct effects on primary headaches based on a selected theory from our narrative review of how ACEs affect human development along the life course. METHODS: PubMed, EMBASE, MEDLINE, Web of Science, Google Scholar, Biological Psychiatry, and gray literature were searched up to March 16, 2023 (PROSPERO, CRD42020223403). Selected articles included (1) observational studies with a comparator group, (2) ACEs that occurred before 18 years of age, and (3) primary headaches occurring at or after 21 years of age. Pooled odds ratios (ORs) were calculated using multilevel linear random-effects modeling. The narrative review included theories that describe how ACEs affect human development and disease across the life course. We selected a theory from our narrative review and tested ACEs categorized according to this theory for any modification of point estimates. RESULTS: = 0.021). DISCUSSION: This systematic review and meta-analysis confirm that ACEs are important risk factors of primary headache disorders in adulthood. Our findings provide epidemiologic support that ACEs categorized as threat and deprivation may manifest as distinct pathways of early adversity.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".