JOURNAL ARTICLE

B - 22 Self-Reported Traumatic Brain Injury and its Biopsychosocial Risk Factors in Siblings of Individuals with Neurodevelopmental Conditions.

  • Published In: Archives of Clinical Neuropsychology, 2024, v. 39, n. 7. P. 1111 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Wolff, Brittany; Glasson, Emma; Babikian, Talin; Pestell, Carmela 3 of 3

Abstract

This article focuses on self-reported traumatic brain injury (TBI) and its biopsychosocial risk factors among siblings of individuals with neurodevelopmental conditions (NDCs). Using data from an online survey of 632 siblings (207 with NDCs and 425 controls), the study found that siblings of individuals with NDCs reported a higher lifetime prevalence of TBI, often with multiple injuries and at younger ages. TBI history in these siblings was linked to psychiatric diagnoses and subclinical NDC traits such as hyperactivity, impulsivity, inattention, conduct problems, and autistic traits. Additionally, family and structural factors associated with TBI included poorer parent–child relationships, specific NDC diagnoses (autism or fetal alcohol spectrum disorder), minority ethnicity, and lower income. The findings highlight the need for targeted health literacy, TBI education, screening, prevention, intervention strategies, and family support addressing social and structural determinants affecting the wellbeing of NDC siblings.

Additional Information

  • Source:Archives of Clinical Neuropsychology. 2024/10, Vol. 39, Issue 7, p1111
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2024
  • ISSN:0887-6177
  • DOI:10.1093/arclin/acae067.183
  • Accession Number:184163474
  • Copyright Statement:Copyright of Archives of Clinical Neuropsychology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.