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Momentary Stressor Logging and Reflective Visualizations: Implications for Stress Management with Wearables

Sameer Neupane, Mithun Saha, Nasir Ali, Timothy Hnat, Shahin Alan Samiei, Anandatirtha Nandugudi, David M. Almeida, Santosh Kumar

TL;DR

This study investigates leveraging sensor-triggered momentary stressor logging and weekly self-reflective visualizations to improve stress management with wearables. The MOODS system combines a WearOS smartwatch, a cross-platform mobile app, and cloud services to prompt stressor logging after stressful physiological events and to deliver cumulative visualizations over 14 weeks. In a 100-day field study with 122 participants, the approach yielded significant reductions in both stress intensity ($p<0.05$) and stress frequency ($p<0.05$), alongside high user engagement and perceived utility, with participants reporting increased stress awareness and adoption of14 self-initiated coping behaviors. While promising, the work acknowledges limitations of an observational design and calls for randomized trials to isolate the effects of stressor logging, visualizations, and interventions, and to assess clinical significance in broader health outcomes.

Abstract

Commercial wearables from Fitbit, Garmin, and Whoop have recently introduced real-time notifications based on detecting changes in physiological responses indicating potential stress. In this paper, we investigate how these new capabilities can be leveraged to improve stress management. We developed a smartwatch app, a smartphone app, and a cloud service, and conducted a 100-day field study with 122 participants who received prompts triggered by physiological responses several times a day. They were asked whether they were stressed, and if so, to log the most likely stressor. Each week, participants received new visualizations of their data to self-reflect on patterns and trends. Participants reported better awareness of their stressors, and self-initiating fourteen kinds of behavioral changes to reduce stress in their daily lives. Repeated self-reports over 14 weeks showed reductions in both stress intensity (in 26,521 momentary ratings) and stress frequency (in 1,057 weekly surveys).

Momentary Stressor Logging and Reflective Visualizations: Implications for Stress Management with Wearables

TL;DR

This study investigates leveraging sensor-triggered momentary stressor logging and weekly self-reflective visualizations to improve stress management with wearables. The MOODS system combines a WearOS smartwatch, a cross-platform mobile app, and cloud services to prompt stressor logging after stressful physiological events and to deliver cumulative visualizations over 14 weeks. In a 100-day field study with 122 participants, the approach yielded significant reductions in both stress intensity () and stress frequency (), alongside high user engagement and perceived utility, with participants reporting increased stress awareness and adoption of14 self-initiated coping behaviors. While promising, the work acknowledges limitations of an observational design and calls for randomized trials to isolate the effects of stressor logging, visualizations, and interventions, and to assess clinical significance in broader health outcomes.

Abstract

Commercial wearables from Fitbit, Garmin, and Whoop have recently introduced real-time notifications based on detecting changes in physiological responses indicating potential stress. In this paper, we investigate how these new capabilities can be leveraged to improve stress management. We developed a smartwatch app, a smartphone app, and a cloud service, and conducted a 100-day field study with 122 participants who received prompts triggered by physiological responses several times a day. They were asked whether they were stressed, and if so, to log the most likely stressor. Each week, participants received new visualizations of their data to self-reflect on patterns and trends. Participants reported better awareness of their stressors, and self-initiating fourteen kinds of behavioral changes to reduce stress in their daily lives. Repeated self-reports over 14 weeks showed reductions in both stress intensity (in 26,521 momentary ratings) and stress frequency (in 1,057 weekly surveys).
Paper Structure (53 sections, 11 figures, 1 table)

This paper contains 53 sections, 11 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Works
  3. Sensor-Triggered Prompting
  4. Logging and Journaling of Stressful Events for Stress Management
  5. Visualizations of Stress and Stressors
  6. Stress Interventions
  7. Methods
  8. Design Rationale for the MOODS Study
  9. MOODS System Design
  10. Physiological Events, Stress Ratings, and Stressor Annotations
  11. Weekly Visualizations to Increase Self-Awareness of Stress, Stressors, and their Surrounding Contexts
  12. Design Rationales for Weekly Visualizations
  13. Chronological Order of Weekly Visualizations
  14. MOODS Study Description
  15. Procedure
  16. ...and 38 more sections

Figures (11)

  • Figure 1: Key steps in the MOODS study along with impacts on study participants and implications for stress management apps.
  • Figure 2: MOODS app screenshots for events on smartwatch and stressor annotation, review, and edits on smartphone
  • Figure 3: Overall design of weekly visualizations, showing which visualizations (in the center column) used which data elements (left column) and aimed for what insights choe2015characterizing (right column).
  • Figure 4: Examples of 4 visualizations. Details on each visualization can be found in Supplementary materials.
  • Figure 5: (a) Chronological sequence of weeekly visualizations (blue box) and their frequency of positive and negative mentions in participants' exit interviews and (b) Participant retention
  • ...and 6 more figures