Research & Outputs

Explore peer-reviewed publications, academic presentations, and research outputs generated using the ACEs in EHRs framework.

Selected publications and outputs using the ACEs in EHRs library.

Firstborns and siblings

Adverse childhood experiences in firstborns and mental health risk and health-care use in siblings

Children are nearly three-quarters (71%) more likely to develop mental health problems between the ages of five and 18, if the firstborn child in their family experienced adversity during their first....

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ACAMH Seminar

ACAMH Seminar - Interrelationships between parental mental health, intimate partner violence and child mental health

Watch our recent ACAMH presentation of our publication exploring clinically relevant family adversity indicators of IPV aimed at improving responses to affected families presenting to healthcare...

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Family adversity and health characteristics

Family adversity and health characteristics associated with intimate partner violence in children and parents

Intimate partner violence (IPV) is a significant public health issue that affects millions of women worldwide. One in three women experiences IPV, translating to over 800 million women globally...

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Validation Study

Identifying adverse childhood experiences with electronic health records of linked mothers and children in England

A multistage development and validation study establishing clinically relevant ACE indicators in routine healthcare data. A total of 63 distinct ACE indicators were developed and validated for use in routine EHRs...

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State of the art review

State of the art review: indicators of child maltreatment and intimate partner violence

Intimate partner violence (IPV) and child maltreatment (CM) are forms of family violence that often go unnoticed by services, despite recommendations to improve monitoring efforts by the World Health Organization (WHO)..

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Real-World Impact:
From Research to Results

100+
Weekly Global Visits
40+
Peer-Reviewed Citations

The ACEsinEHRs open-access platform shares essential coding algorithms, tutorials, and theoretical frameworks that have been widely adopted by researchers globally.

Advancing predictive algorithms: Our code lists have facilitated the creation of the first externally validated algorithms for identifying child maltreatment in routine care, and developed machine learning models predicting childhood mental health issues.
Informing population health: Our family-linkage methodologies actively support evaluating health visiting models for ACE mitigation, optimising ACE screening protocols, and integrating healthcare responses to intimate partner violence.

Latest Citing Research

Google Scholar

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review

Li et al. - 2026

Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts...

Artificial intelligence in applied family research involving families with young children: A scoping review

Lee et al. - 2025

This scoping review systematically examined the applied family science literature involving families raising young children to understand how relevant studies have applied...

Adverse childhood experiences in firstborns and mental health risk and health-care use in siblings: a population-based birth cohort study

Syed et al. - 2025

Adverse childhood experiences (ACEs) often affect multiple children within families, yet studies tend to focus on the health outcomes of individual children...

Applying analytics to sociodemographic disparities in mental health

Baird & Xia - 2025

Mental health services and treatment are unfortunately subject to sociodemographic disparities. To address this issue, recent studies have begun to apply analytics methods...

Machine learning for prediction of childhood mental health problems in social care

Crowley et al. - 2025

Rates of childhood mental health problems are increasing in the UK. Early identification of childhood mental health problems is challenging but critical to children's...

Examining the rollout of the Triple P system parenting program in Manitoba on rates of child maltreatment

Joshi et al. - 2025

Triple P is a multilevel parenting program aimed at promoting children's emotional, social, and behavioural competence and preventing behavioural problems...

Preconception indicators and associations with health outcomes reported in UK routine primary care data: a systematic review

Schoenaker et al. - 2024

Routine primary care data may be a valuable resource for preconception health research and informing provision of preconception care. Aim: To review how primary...

Revisiting the use of adverse childhood experience screening in healthcare settings

Danese et al. - 2024

Adverse childhood experiences (ACEs) are key modifiable risk factors for mental illness. The potential to detect and mitigate ACEs to improve population mental health...

The association between adverse childhood experiences and mental health, behaviour, and educational performance in adolescence

Lam et al. - 2024

Adverse childhood experiences (ACEs) are thought to have negative effects on mental health and well-being in adolescence. The definition of ACEs varies between studies...

Access without borders: a scoping review to identify solutions to creating portable identity, education and health records for refugee children

Ungar & Seymour - 2024

The focus of this scoping review is to identify studies, reports, and other relevant sources from the peer-reviewed and grey literature that reports on refugee children's access...

Master publication list

NIHR CPRU UCL ICH Oxford NIHR GOSH BRC GOSH Bristol HDRUK Caliber UCL