Background: Social determinants of health (SDoH), such as socioeconomics and neighborhoods, strongly influence health outcomes. However, the current state of standardized SDoH data in electronic health records (EHRs) is lacking, a significant barrier to research and care quality.Methods: We conducted a PubMed search using “SDOH” and “EHR” Medical Subject Headings terms, analyzing included articles across five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions.Results: Of 685 articles identified, 324 underwent full review. Key findings include implementation of tailored screening instruments, census and claims data linkage for contextual SDoH profiles, NLP systems extracting SDoH from notes, associations between SDoH and healthcare utilization and chronic disease control, and integrated care management programs. However, variability across data sources, tools, and outcomes underscores the need for standardization.Discussion: Despite progress in identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical for SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately, widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Korea’s suicide rate has increased steadily in recent years and it has become the leading cause of death among Korean youth. This paper aims to propose suicide risk identification strategies for South Korean youth by identifying profiles of suicide risk alongside reported somatic complaints. For several reasons, somatic complaints are more commonly reported than mental health concerns in Korea, where somatic complaints are likely to be representative of larger mental health worries. Nationally representative data of Korean first-year middle school students were used to identify mental health profiles by examining reported suicidal ideation, depression, and social anxiety and the prediction effect of reported somatic symptoms within these profiles. Results indicated that female students reported a greater level of suicidal ideation, depression, and social anxiety compared to male students. Each gender (females and males) exhibited five different mental health profile groups, which ranged from low risk to high risk. Somatic symptoms (sleep, stomach ache, tiredness, breathing, appetite, headache, fever, nausea) significantly predicted each profile group, with sleep issues serving as the strongest predictor for risk across both genders and all groups. Therefore, for mental health professionals working with Korean youth, it is encouraged to identify and recognize somatic complaints as potentially representative of mental health concerns and suicidality risk.

As the contemporary phenomenon of school bullying has become more widespread, diverse, and frequent among adolescents in Korea, social big data may offer a new methodological paradigm for understanding the trends of school bullying in the digital era. This study identified Term Frequency-Inverse Document Frequency (TF-IDF) and Future Signals of 177 school bullying forms to understand the current and future bullying experiences of adolescents from 436,508 web documents collected between 1 January 2013, and 31 December 2017. In social big data, sexual bullying rapidly increased, and physical and cyber bullying had high frequency with a high rate of growth. School bullying forms, such as “group assault” and “sexual harassment”, appeared as Weak Signals, and “cyber bullying” was a Strong Signal. Findings considering five school bullying forms (verbal, physical, relational, sexual, and cyber bullying) are valuable for developing insights into the burgeoning phenomenon of school bullying.

Teachers serving students with special needs, students from low-income backgrounds, students with disabilities, and students from underrepresented racial/ethnic backgrounds experienced a myriad of challenges due to the COVID-19 pandemic. This study aims to assess whether and to what extent teachers received resources during the pandemic, and to evaluate the impact of this on their perceptions of student academic engagement. Using the American Teacher Panel (ATP) data collected in October 2020, this research found that 41% of teachers working with diverse and marginalized students did not receive any resources tailored specifically for students with special needs. Teacher experiences with resources were clustered into four groups: Most Supported (35%), Least Supported (41%), Moderately Supported A (16%; received support primarily with students with disabilities), and Moderately Supported B (8%; received support primarily with students with racial/ethnic backgrounds). Across the four groups of teachers, teacher groups classified as less supported were more likely to be teaching in more urbanized settings with larger size schools than the other teacher groups. Additionally, they perceived their students as attending less often and being less ready for grade-level coursework than their counterparts. Discussions for school leaders and counselors are outlined to emphasize the importance of teacher support for effective education during the COVID-19 pandemic.