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Using AI chatbots to support families of children with cancer

This INSPIRE project aims to develop an artificial intelligence chatbot called DAPHNE, to address social needs in real-time for families of children with cancer.

Researcher: Micah Skeens
Grant type: INSPIRE Research Challenge
Countries: US
Cancer types: Childhood
Exposures: Stress
Status: Ongoing
Area: Cancer survivorship

INSPIRE grant title: Supporting families of children with cancer: DAPHNE, the conversational companion for social needs and toxic stress reduction

> More about our INSPIRE Research Challenge

As a recipient of an INSPIRE grant, our mission is clear: we are committed to creating innovative solutions that will not only screen for the social needs of paediatric cancer patients in real-time but also play a pivotal role in eliminating toxic stress from their lives.

This transformative project represents a significant step forward in our ongoing fight against cancer, ensuring that the youngest among us receive the holistic care they deserve. We extend our heartfelt gratitude to World Cancer Research Fund for their unwavering dedication to this project and countless others that serve as a beacon of hope for enhancing the care of individuals battling cancer. – Dr Micah Skeens

Background

Childhood cancer is a leading cause of disease-related death among children, and while survival rates have improved, the rate of childhood cancer continues to rise. Social needs, including financial, emotional and logistical support, can impact the ability of children and their families to cope with disease and access healthcare services.

Living in impoverished and unhealthy conditions puts children under chronic stress, which can negatively impacts a child’s brain structure and raises the likelihood of experiencing various health issues, including physical, behavioural, socio-emotional and cognitive problems.

Screening for social determinants of health is crucial to identify and address these needs and reduce health disparities. Chatbots, leveraging artificial intelligence (AI), have shown promise in healthcare settings and can be used to screen for social determinants of health. Therefore, developing a safe, secure and privacy-preserving chatbot app, such as DAPHNE, for paediatric cancer care can integrate the assessment and management of social needs, contribute to a holistic approach to cancer care, and serve as a model for other chronic disease management.

Aims

Develop and evaluate an innovative AI-based chatbot, DAPHNE©, to screen for social determinants of health and address social needs in real-time for families of children with cancer.

Objectives

The primary objectives include reducing toxic stress, improving clinical outcomes, and promoting health equity among paediatric cancer patients.

Methods

The study consists of a 2-phased approach. The first phase involves the development and co-design of DAPHNE through stakeholder focus groups comprising healthcare providers, social workers, community advocates and parents. The chatbot will utilise natural language processing and a user-friendly interface to identify social needs, provide personalised resources from reliable community databases, screen for toxic stress, and offer stress management techniques.

The second phase focuses on evaluating the acceptability and usability of DAPHNE among 40 caregivers of children diagnosed with cancer. Standardised measures of social determinants of health, toxic stress and usability will be employed. Data analysis will involve qualitative content analysis, descriptive statistics and correlational analysis.

Impact

The development and evaluation of DAPHNE has the potential to revolutionise the identification and management of social needs in paediatric oncology. By integrating AI technology into cancer care, this study can enhance the overall cancer care experience, reduce toxic stress and promote health equity.

The findings will not only have implications for paediatric cancer care but also pave the way for future AI innovations in managing other chronic diseases.