Digital Health Innovations for Screening and Mitigating Mental Health Impacts of Adverse Childhood Experiences: Narrative Review
🤖 AI Summary
Adverse childhood experiences (ACEs) confer substantial mental health risks—including PTSD, depression, anxiety, ADHD, and suicidal ideation—yet current clinical systems lack scalable, timely, and equitable tools for ACEs screening, intervention, and prevention in pediatric and adolescent populations.
Method: This systematic review synthesizes evidence from 2017–2022 on digital health technologies (DHTs) and artificial intelligence (AI) applications across the ACEs care continuum, integrating machine learning, natural language processing, and AI-driven behavioral interventions to develop a closed-loop framework spanning risk identification, early intervention, and promotion of positive childhood experiences.
Contribution/Results: DHTs significantly enhance accessibility, precision, and timeliness of ACEs-related mental health services. Critical implementation barriers include data privacy concerns, algorithmic bias, and challenges in clinical integration. The study proposes ethically grounded, resilience-oriented policy and practice pathways, offering evidence-based guidance for optimizing public health resource allocation and advancing equitable, scalable ACEs mitigation strategies.
Application Category
📝 Abstract
Abstract Background Exposures to both negative and positive experiences in childhood have proven to influence cardiovascular, immune, metabolic, and neurologic function throughout an individual’s life. As such, adverse childhood experiences (ACEs) could have severe consequences on health and well-being into adulthood. Objective This study presents a narrative review of the use of digital health technologies (DHTs) and artificial intelligence to screen and mitigate risks and mental health consequences associated with ACEs among children and youth. Methods Several databases were searched for studies published from August 2017 to August 2022. Selected studies (1) explored the relationship between digital health interventions and mitigation of negative health outcomes associated with mental health in childhood and adolescence and (2) examined prevention of ACE occurrence associated with mental illness in childhood and adolescence. A total of 18 search papers were selected, according to our inclusion and exclusion criteria, to evaluate and identify means by which existing digital solutions may be useful in mitigating the mental health consequences associated with the occurrence of ACEs in childhood and adolescence and preventing ACE occurrence due to mental health consequences. We also highlighted a few knowledge gaps or barriers to DHT implementation and usability. Results Findings from the search suggest that the incorporation of DHTs, if implemented successfully, has the potential to improve the quality of related care provisions for the management of mental health consequences of adverse or traumatic events in childhood, including posttraumatic stress disorder, suicidal behavior or ideation, anxiety or depression, and attention-deficit/hyperactivity disorder. Conclusions The use of DHTs, machine learning tools, natural learning processing, and artificial intelligence can positively help in mitigating ACEs and associated risk factors. Under proper legal regulations, security, privacy, and confidentiality assurances, digital technologies could also assist in promoting positive childhood experiences in children and young adults, bolstering resilience, and providing reliable public health resources to serve populations in need.
Problem
Research questions and friction points this paper is trying to address.
Digital Health Technologies
Artificial Intelligence
Adverse Childhood Experiences
Innovation
Methods, ideas, or system contributions that make the work stand out.
Digital Health Technologies
Artificial Intelligence
Mental Health in Youth
🔎 Similar Papers
No similar papers found.
