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Abstract The proposed study investigates how technology-assisted behavioral interventions can help individuals improve their sleep habits in order to improve educational outcomes. In prior work, we find that incentives for meeting sleep goals increase sleep and also find suggestive evidence that the incentives improve academic performance. Building on these findings, we will test the impact of the following interventions among undergraduates: (1) Technology only and (2) Technology and Incentives. The Technology intervention aims to lower the costs of shifting and sustaining habits, including the costs of tracking sleep and remembering to go to bed on time. Through wearable technology (Fitbits) and a custom smartphone app, we will provide participants with reminders to go to bed and immediate feedback about sleep duration. The Technology and Incentives intervention aims to develop habits building on cue/reward models of habit formation. The Technology intervention will provide the cue to go to bed on time and sleep adequately; we will combine this with an associated reward (either Financial or Non-Financial) provided immediately each morning for meeting sleep goals. We will measure the impact of the interventions on sleep habits and academic performance. The proposed study investigates how technology-assisted behavioral interventions can help individuals improve their sleep habits in order to improve educational outcomes and health.
Last Published August 14, 2018 10:03 PM March 01, 2019 03:02 PM
Intervention (Public) We will test the impact of reminders, feedback, financial incentives and non-financial incentives.
Primary Outcomes (End Points) We will measure the impact of the interventions on sleep habits and academic performance. We will measure the impact of the interventions on sleep habits, academic performance and health.
Experimental Design (Public) we will test the impact of the following interventions among 3,000 undergraduates: (1) Technology only and (2) Technology and Incentives. The Technology intervention aims to lower the costs of shifting and sustaining habits, including the costs of tracking sleep and remembering to go to bed on time. Through wearable technology (Fitbits) and a custom smartphone app, we will provide participants with reminders to go to bed and immediate feedback about sleep duration. The Technology and Incentives intervention aims to develop habits building on cue/reward models of habit formation. The Technology intervention will provide the cue to go to bed on time and sleep adequately; we will combine this with an associated reward (either Financial or Non-Financial) provided immediately each morning for meeting sleep goals. We will test the impact of reminders, feedback, financial incentives and non-financial incentives.
Planned Number of Clusters 3,000 participants 2100
Planned Number of Observations 3,000 participants 2100
Sample size (or number of clusters) by treatment arms 600-900 per treatment arm Control n=600 Non-Financial Incentives: n=600 Financial Incentives: n=600 Delayed Financial Incentives: n=100 Delayed Financial Incentives, no reminders and feedback: n=100 Reminders and Feedback: n=100
Power calculation: Minimum Detectable Effect Size for Main Outcomes MDES for each incentive treatment: 0.16 MDES for pooled incentive treatments: 0.14
Secondary Outcomes (End Points) Physical and mental health
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Irbs
Field Before After

IRB Name

UC San Diego Human Research Protections Program University of Pittsburgh

IRB Approval Date

July 10, 2018 December 18, 2017

IRB Approval Number

180008 PRO17090135
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