This course was presented in person at World Sleep 2025 in Singapore.

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Session Schedule

Find a specific presentation in the course by navigating to the timestamp indicated below.

0:00:00
Introduction
Mark Howard (Australia)
Sveta Postnova (Australia)

0:05:25
Shift work, internal desynchrony, and metabolic and cardiovascular health
Hans Van Dongen (United States)

0:51:40
Bench to the bedside: Translating individual shiftwork strategies for healthcare workers          
Mark Howard (Australia)

1:28:40
Discussion / Question and answer
Sveta Postnova (Australia)

1:56:30
From data to care: Personalized AI models for sleep and mental health in shift workers
Jaekyoung Kim (Korea, Republic of)

2:38:40
Prediction and optimization of circadian health in shift work    
Sveta Postnova (Australia)

3:10:45
Discussion / Question and answer 
Mark Howard (Australia)

Course Summary:

Shift work is essential in many critical industries but poses significant occupational health risks, including disrupted sleep, impaired cognitive performance, and increased vulnerability to metabolic, cardiovascular, and mental health disorders. Despite substantial research, there remains a gap in understanding individual responses to shift work and translating this knowledge into effective interventions. This course integrates experimental and modelling approaches with real-world applications to (i) explore how internal circadian desynchrony arises from shift work and its consequences for metabolic and cardiovascular health; (ii) gain insights into the pathways and impact of implementing individualized circadian and sleep health strategies; (iii) demonstrate how personalized AI techniques for predicting sleep and mental health outcomes enable tailored interventions, and lastly (iv) show how mathematical modelling can help us accurately predict circadian responses in field and optimize circadian health through behavioral interventions. Collectively, this course showcases research designed to bridge fundamental and applied science with practical strategies aimed at improving occupational health outcomes for shift workers.

Learning objectives:

Upon completion of this activity, participants will be able to:
 
·       Comprehend the mechanisms of internal desynchrony in shift workers and understand how it affects metabolism and cardiovascular health
·       Delineate a tailored package of strategies to assist individual shift workers and navigate pathways to implementing them in the healthcare sector
·       Describe how personalized AI-driven models utilize individual data to predict sleep and mental health outcomes in shift workers and identify practical applications for delivering tailored interventions and care strategies.
·       Explain how mathematical models can predict individual circadian responses to shift schedules and discuss practical approaches for optimizing circadian health and performance in shiftwork settings.