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SleepBandits: Guided Flexible Self-Experiments for Sleep

Published: 23 April 2020 Publication History

Abstract

Self-experiments allow people to explore what behavioral changes lead to improved health and wellness. However, it is challenging to run such experiments in a scientifically valid way that is also flexible and able to accommodate the realities of daily life. We present a set of design principles for guided self-experiments that aim to lower this barrier to self-experimentation. We demonstrate the value of the principles by implementing them in SleepBandits, an integrated system that includes a smartphone application for sleep experiments. SleepBandits guides users through the steps of a single-case experiment, automatically collecting data from the built-in sensors and user input and calculating and presenting results in real-time. We released SleepBandits to the Google Play Store and people voluntarily downloaded and used it. Based on the data from 365 active users from this in-the-wild study, we discuss opportunities and challenges with the design principles and the SleepBandits system.

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cover image ACM Conferences
CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
April 2020
10688 pages
ISBN:9781450367080
DOI:10.1145/3313831
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 23 April 2020

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Author Tags

  1. personal informatics
  2. self-experiments
  3. sleep tracking

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  • Brown University Data Science Institute
  • National Science Foundation
  • Brown University Seed Award

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Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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  • (2024)Say You, Say Me: Investigating the Personal insights Generated from One's Own data and Other's dataProceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685345(1-14)Online publication date: 13-Oct-2024
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