Abstract TMP94: Mental Health Outcomes In Parents with Children with Pediatric Arterial Ischemic Stroke
Bibliographic record
Abstract
Introduction: Previous single-center studies have found a higher prevalence of mental health disorders in parents of children with pediatric stroke compared to general population prevalences of 5% with depression and 6% with anxiety. Social determinants of health may influence mental health outcomes. We aimed to measure associations between social determinants of health and parental report of mental health symptoms following their child’s diagnosis of ischemic stroke. Methods: We performed a multicenter, international prospective study through the International Pediatric Stroke Study (IPSS). From 2016 to 2021, parents of children within 3.5 years after arterial ischemic stroke enrolled and completed validated and standardized surveys on anxiety (Beck’s Anxiety Inventory II), depression (Beck’s Depression Inventory), post-traumatic stress disorder (PTSD) (Post-Traumatic Stress Disorder Checklist for DSM-5), severity of their child’s stroke deficits (Recovery and Recurrence Questionnaire), and social determinants of health. For our statistical analysis we employed a linear mixed-effects model, both unadjusted and adjusted. Results: Fifty-two parents (13 fathers, 39 mothers) of 39 children enrolled. Of the 39 children 21 (54%) had perinatal stroke and 18 (46%) had childhood stroke. Median time from stroke diagnosis to parental survey completion was 1.3 years (interquartile range [IQR] 1.0-2.0). On parental surveys, parents scored in the clinical range for: depression in 35% of mothers and 23% of fathers; anxiety in 2% of mothers and 0% of fathers; PTSD in 26% of mothers and 8% of fathers. Lower parental education was significantly associated with higher levels of depression both in our unadjusted (0.02) and adjusted (0.03) models. Interestingly, the child’s functional outcome and parental income were not significantly associated with any parental mental health outcomes. Conclusion: Among social determinants of health, parental education level may be associated with depression in parents of children with pediatric arterial ischemic stroke and needs further exploration. Parents of children with pediatric arterial ischemic stroke had higher rates of depression and PTSD compared to general population estimates. Further research in this area will help facilitate understanding and development of interventions to prevent these mental health outcomes.
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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 | 0.005 |
| 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) | 0.004 | 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".