Datafront Skill Surge: Integrating health data with lifestyle research

Course description

What do we mean when we talk about administrative data? Why is administrative data considered such a powerful tool?

Routinely collected administrative data captures interactions across the entire population, offering an unparalleled breadth and depth of information.

This on-demand series aims to equip researchers with the knowledge and skills to harness data for societal and sustainable change. This series covers important topics such as the use of administrative data in policymaking, circular economy models, climate resilience, and the impact of digital media on behaviour, with emphasis on the importance of interdisciplinary collaboration and innovative strategies to address global challenges.

Participants will gain insights from experts, study case studies, and explore practical examples that illustrate how data-driven approaches and emerging technologies are transforming urban planning, agriculture, and health – that will empower researchers to shape the future of the data landscape!

• Session 29 will explore how researchers can now collect and analyze real-time health data to better understand human behavior and long-term well-being.

 

Learning mode

On-demand, self-paced 

 

Who should attend

This course is intended for:

• Data Analysts and Researchers: Those working with administrative or big data who want to deepen their understanding of its characteristics and uses.
• Policymakers and Government Officials: Decision-makers who rely on data to shape public policies.
• Public Sector Managers: Managers in government institutions seeking to optimise data usage for service improvements.
• Health and Social Care Professionals: Individuals looking to use data for improving service delivery and outcomes.
• Urban Planners and Public Health Professionals: Individuals interested in using administrative data to inform planning and health policies.

 

Aims and objectives

• Explore the impact of AI and predictive analytics on health behavior research, focusing on personalized interventions and public health improvements.
• Analyze ethical concerns related to data privacy, algorithmic bias, and corporate influence in health tracking.
• Discuss the role of behavioral science in interpreting health data and designing effective interventions.

 

Skills area and competencies

Based on the Datacise Open Learning framework, the relevant skills and competencies for this video include:

Skills Areas:

• Health Data Analysis – Understanding how wearables, AI, and medical records contribute to health research.
• Digital and Data Literacy – Evaluating the use of AI-driven health tracking and predictive modeling.
• Behavioral Science Application – Using data insights to understand and modify health behaviors.

Competencies:

• Interpreting digital health data to assess lifestyle trends and health risks.
• Understanding the ethical implications of AI-driven health insights.
• Evaluating the benefits and risks of wearable health technology.
• Applying behavioral insights to improve health and wellness interventions.

 

Pre-requisite

• Basic knowledge of health sciences, digital health, or behavioral research is helpful but not required.
• No prior experience with AI or predictive analytics is necessary.
• Suitable for learners in public health, medical research, digital health, data science, and policy-making.

 

Learning outcomes

• Assess the impact of AI and wearable technology on personal health monitoring.
• Critically evaluate ethical challenges related to health data collection and privacy.
• Analyze how behavioral science and health tracking tools influence lifestyle interventions.

 

Transferable skills

• Digital and AI Literacy – Evaluating AI-driven insights in health tracking and behavioral science.
• Analytical Thinking – Assessing ethical, policy, and research challenges in health data use.
• Consumer Awareness – Understanding how personal health data is used by corporations and policymakers.

 

Assessment

Multiple choice quiz to self-check understanding. 

 

This training content was originally developed and produced by Professor Adam Chee, Datacise Education Lead at Swansea University, with narration enhanced by advanced text-to-speech technology.