SleepTight: Low-burden, Self-monitoring Technology for Capturing and - - PowerPoint PPT Presentation

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Feb 24, 2023 122 likes •445 views

UbiComp 2015 SleepTight: Low-burden, Self-monitoring Technology for Capturing and Reflecting on Sleep Behaviors Eun Kyoung Choe, Penn State University Bongshin Lee, Microsoft Research Matthew Kay, University of Washington Wanda Pratt, University

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UbiComp 2015 1

SleepTight: Low-burden, Self-monitoring Technology for Capturing and Reflecting on Sleep Behaviors

Eun Kyoung Choe, Penn State University

Bongshin Lee, Microsoft Research Matthew Kay, University of Washington Wanda Pratt, University of Washington Julie Kientz, University of Washington

UbiComp 2015

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Self-monitoring

An activity of recording one’s own behaviors, thoughts, or feelings

[Kopp, J. (1988) Self-monitoring: A literature review of research and practice]

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Self-monitoring is important

Therapeutic Purpose

Being aware of how you are doing can result in reactivity* and enable you to change behavior or maintain appropriate behavior

* Reactivity: The change in the frequency of a target behavior

Nelson & Hayes. (1981)

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Data Capture Mechanisms

Manual Capture Automated Capture

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Manual Capture

Increased self-awareness Engagement with data Flexibility of choosing target behaviors Some data can only be tracked manually High capture burden Forgetting -> compromised data accuracy

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Automated Capture

Reduced mental load Better accuracy (depending on the data) Cumbersome to wear (wearable sensing) Reduce engagement with data

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Data Capture Mechanisms

Manual Capture Automated Capture Somnometer

(Shirazi et al., 2013)

Sleepful app

(Lawson et al., 2013)

Lullaby

(Kay et al., 2012)

SWP Toss ‘N’ Turn

(Min et al., 2014) (Chen et al., 2013)

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Sleep Tracking

http://www.swedish.org Sleep Center Patient Resource.

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Goal

To support easy & flexible manual capture of multiple behavior factors

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SleepTight Design Goals

Sleep A B C F D E

Contributing factors Target behaviors

1. Capture both target behaviors and contributing factors

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SleepTight Design Goals

1. Capture both target behaviors and contributing factors
2. Reduce the capture burden

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SleepTight Design Goals

1. Capture both target behaviors and contributing factors
2. Reduce the capture burden
3. Provide feedback to promote self-reflection

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SleepTight Design

Capturing Multiple Behaviors Leveraging App Widget Feedback

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Capturing Multiple Behaviors

Target behaviors: Sleep Contributing factors

Custom Behaviors

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Capturing Multiple Behaviors

Contributing factors Target behaviors: Sleep

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Leveraging App Widget

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Leveraging App Widget

Lock screen Home screen

# of unlocking event / day

4.8-105.3 times

Truong et al., (2014)

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Leveraging App Widget

Lower Access Burden Lower Capture Burden

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Feedback for Self-reflection

4-week View Daily View Comparison View

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Study Design

App-only System Condition

Regular app

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Full System Condition Lock screen widget Home screen widget Regular app

Study Design

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Study Design

A three-phased study 22 participants (9 Males, 13 Females) Average age—29.7 years old (range: 20-49) Random assignment

Interview
Questionnaire
Instruction
4-week deployment
Weekly survey
Debriefing interview
Questionnaire

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Findings

Data Capture Behaviors Information Access Self-reflection

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Data Capture Behavior [Diary adherence]

88% of the sleep diaries were captured from the widgets

92%

(M = 25.89, SD = 2.71)

>

73%

(M = 20.42, SD = 7.18)

p = .03

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Data Capture Behavior

[# of total contributing factors]

Full system: 151.11 (SD = 68.82) App-only system: 141.5 (SD = 78), p = N/S

9% of the contributing factors were captured from the widgets

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Time Difference b/w Event Time and Logging Time

Full System: 7.1 hours

(SD = 3.33)

App-only System: 11.7 hours

(SD = 5.00)

<

p = .02

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Self-reflection

Self-reflection during opportune moments: What did you learn? “…my time to go to bed is a little inconsistent” “…I don’t drink as much alcohol as I thought I did” “…drinking alcohol seems to lead to poor sleep.”

Finding-Sleep pattern (neutral statement) Hypothesis- Relationship between sleep and other factors Finding-Other activity (disproof)

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Designing Successful Manual Tracking Tools

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Lower the User Burden

Lower the Capture Burden Lower the Access Burden Leverage Visual Reminders

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Leverage Manual Tracking in Self-reflection

Configuration Data capture Feedback

Reflection during data capture Reflection when receiving feedback

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Thank you!

Eun Kyoung Choe echoe@ist.psu.edu

faculty.ist.psu.edu/choe

Funding:

Intel ISTC Pervasive Computing NSF Awards 1344613 Google