Disparities in Screening for Adverse Childhood Experiences

Hector E. Alcala,Amanda E. Ng,Nicholas Tkach, Dahai Yue,Mienah Sharif

JOURNAL OF THE AMERICAN BOARD OF FAMILY MEDICINE(2024)

引用 0|浏览0
暂无评分
摘要
Introduction: Screening for adverse childhood experiences (ACEs) in the clinical setting is set to become more commonplace with continued efforts to reimburse clinicians for screening. However, an examination of disparities in ACEs screening and related attitudes and beliefs is needed. Methods: Using the 2021 California Health Interview Survey (CHIS), this study examined if several measures of socioeconomic status, access to care and identities were associated with 3 outcomes: 1) getting screened for ACEs by a clinician; 2) beliefs about the importance of screening and 3) satisfaction with efforts to address the impacts of ACEs. Logistic regressions were used to estimate odds of the outcomes. Results: Black, Latinx, and Asian individuals had lower odds of being screened for ACEs than nonHispanic Whites. A recent doctor's visit, higher burden of ACEs, and serious psychological distress were associated with higher odds of being screened. Latinx individuals, women, bisexual individuals, those with a recent doctor's visit and those with serious psychological distress had higher odds of believing clinicians asking about ACEs was very important, relative to their counterparts. Latinx individuals, American Indian or Alaska native individuals, Asian individuals, those with higher educational attainment and those with serious psychological distress had lower odds of being very satisfied with providers' efforts to address the impact of ACEs, relative to their counterparts. Conclusions: Efforts to expand ACEs screening should consider the disparities in screening that currently exist. Given the wide-ranging impacts that ACEs have on health, an equitable approach to screening is necessary.
更多
查看译文
关键词
Adverse Childhood Experiences,Health Care Disparities,Preventive Medicine,Primary Health Care,Public Health,Screening,Social Determinants of Health
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要