Sleep, Learning and Wellbeing in NUS Undergraduates: The NUS1000 Study
Study Details
Study Description
Brief Summary
NUS1000 is a large scale freshman-year study of undergraduate sleep, well-being and learning patterns that has unique key features: (1) continuous objective multi-dimensional data gathered with passive sensing of sleep and stress over a semester, (2) utilisation of Learning Management System-based outcome data as a marker of study behaviour and academic achievement. The goal is to gather information that can be used to improve student sleep, mental wellbeing and performance.
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Detailed Description
The first year in university can be a challenging experience for undergraduates who must learn to cope with learning in an unfamiliar environment, form new relationships, live away from home and/or might have to manage personal finances for the first time. These academic, social, and personal demands can result in significant stress, affecting sleep, learning and mental/emotional wellbeing. Characterizing and understanding the time-course and inter-relationship of these demands and their consequences is crucial for making science-based improvements to a student's university experience. To this end, the investigators will longitudinally evaluate sleep, learning and wellbeing in ~1000 first-year students as they adapt to university life to understand how these behaviours fluctuate and interact throughout the academic term.
Study Design
Outcome Measures
Primary Outcome Measures
- Change in sleep duration and timing from the start to the end of the semester [20 weeks]
The Oura ring is a sleep-tracking device worn on the finger. During the study, participants will need to sync their devices to a mobile app.
- Change from baseline sleep habits from the start to the end of the semester [Week 1-2, Week 8-9, and Week 17-18]
Participants will also be required to complete a set of sleep questionnaires probing sleep habits (bedtime, wake time, time taken to fall asleep, etc.)
- Change in daily well-being from the start to the end of the semester [20 weeks]
Participants will be prompted to fill in brief questions on daily well-being. At the end of each assessment, participants will be required to record an audio clip of their day, without any personal identifiers, for mood/sentiment analysis.
- Change from baseline well being from the start to the end of the semester [Week 1-2, Week 8-9, and Week 17-18]
Participants will also be required to complete a set of well-being questionnaires (e.g., feelings of connectedness or isolation, levels of stress, etc.)
- Change in learning outcomes from the start to the end of the semester [20 weeks]
Grades from quiz/assignments for each module will be collected.
- Change in learning patterns from the start to the end of the semester [20 weeks]
Student interactions with the LMS-system will be collected, such as the number of page/file views.
- Change in mood from the start to the end of the semester [20 weeks]
At the end of each day, participants will be required to record an audio clip of their day, without any personal identifiers, for mood analysis.
- Change in time-use patterns from the start to the end of the semester [Week 1-2, Week 8-9, and Week 17-18]
Participants will be asked to fill out a time-use diary over three 2-week periods throughout the semester, indicating the activities they engaged in over the past day
- Change in smartphone touchscreen interaction patterns from the start to the end of the semester [20 weeks]
Phone taps will be tracked automatically through an EU-GDPR (the European Union's stringent privacy regulation) compliant smartphone app (QuantActions). This application logs human-smartphone screen interactions during regular use by logging a location-specific timestamp for each screen contact.
Secondary Outcome Measures
- Change in movement patterns from the start to the end of the semester [20 weeks]
The investigator's in-house smartphone app (Z4IP) will extract movement patterns from location data that will only be kept on the participant's phone up to 96 hours for these computations. The extracted movement patterns (and not geographical locations) will then be uploaded to secure servers, tagged to subject IDs without any personal identifiers, i.e., names and emails will not be linked to their movement patterns. As this component is optional, participants will be asked to indicate if they would like to opt-in at the informed consent stage.
Eligibility Criteria
Criteria
Inclusion Criteria:
- NUS first-year students with smartphones operating on Android 8.0 and up, or iOS 14.0 or later
Exclusion Criteria:
Participants will be required to :
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Have their sleep and physical activity rhythms will be recorded via wearable sensors, while they continue daily life as usual.
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Complete periodic questionnaires, short daily surveys and daily audio diaries on their smartphones.
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Agree to interactions with their smartphones and as well as grades tracked. Participants who do not agree to have these measures recorded will not be eligible for the study.
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- National University of Singapore
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- NUS1000