Echoes from the past: how technology mediated reflection improves well-being
Abstract
As people document more of their lives online, some recent systems are encouraging people to later revisit those recordings, a practice we're calling technology-mediated reflection (TMR). Since we know that unmediated reflection benefits psychological well-being, we explored whether and how TMR affects well-being. We built Echo, a smartphone application for recording everyday experiences and reflecting on them later. We conducted three system deployments with 44 users who generated over 12,000 recordings and reflections. We found that TMR improves well-being as assessed by four psychological metrics. By analyzing the content of these entries we discovered two mechanisms that explain this improvement. We also report benefits of very long-term TMR.
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Some users relied on simple heuristics and did not welcome complex explanations unless the situation seemed strikingly anomalous.
“We found that some users relied on simple heuristics and did not welcome complex explanations unless the situation seemed strikingly anomalous [41,43,67].”
From Progressive Disclosure: When, Why, and How Do Users Want Algorithmic Transparency Information? (2020) · cites this paper as [41]
When interacting with a system, users first engage in rapid, approximate, System 1 thinking and only engage in deeper, more analytic, System 2 thinking when directly prompted or confronted with clearly anomalous information.
“As with other areas of reasoning, it may be that when interacting with a system, users first engage in rapid, approximate, System 1 thinking and only engage in deeper, more analytic, System 2 thinking when directly prompted or confronted with clearly anomalous information [41,67].”
From Progressive Disclosure: When, Why, and How Do Users Want Algorithmic Transparency Information? (2020) · cites this paper as [41]
Engaging with externally stored information can lead individuals to change their views about themselves and maybe even to modify their behavior.
“Ultimately, this can lead individuals to change their views about themselves (DeVito et al., 2017) and maybe even to modify their behavior (Isaacs et al., 2013;Kersten-van Dijk et al., 2017).”
From Understanding Autobiographical Memory in the Digital Age: The AMEDIA-Model (2024) · cites this paper as Isaacs et al., 2013
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The Experience Sampling Method on Mobile Devices
van Berkel, N., Ferreira, D., & Kostakos, V. (2018) · ACM Computing Surveys · doi:10.1145/3123988 · Cited by 432 · see citing works
Reviewing reflection: on the use of reflection in interactive system design
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Revisiting Reflection in HCI: Four Design Resources for Technologies that Support Reflection
Bentvelzen, M., Woźniak, P. W., Herbes, P. S. F., Stefanidi, E., & Niess, J. (2022) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · doi:10.1145/3517233 · Cited by 137 · see citing works
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Self-citationProgressive Disclosure: When, Why, and How Do Users Want Algorithmic Transparency Information?
Springer, A., & Whittaker, S. (2020) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3374218 · Cited by 84 · see citing works
Self-citationOn Being Told How We Feel: How Algorithmic Sensor Feedback Influences Emotion Perception
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Self-citationReflective Informatics Through Family Storytelling: Self-discovering Physical Activity Predictors
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Memory Manipulations in Extended Reality
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Mood modeling: accuracy depends on active logging and reflection
Springer, A., Hollis, V., & Whittaker, S. (2018) · Personal and Ubiquitous Computing · doi:10.1007/s00779-018-1123-8 · Cited by 21 · see citing works
Self-citationPatient-Generated Health Photos and Videos Across Health and Well-being Contexts: Scoping Review
Ploderer, B., Rezaei Aghdam, A., & Burns, K. (2022) · Journal of Medical Internet Research · doi:10.2196/28867 · Cited by 18 · see citing works
Understanding Autobiographical Memory in the Digital Age: The AMEDIA-Model
Hutmacher, F., Appel, M., & Schwan, S. (2024) · Psychological Inquiry · doi:10.1080/1047840x.2024.2384125 · Cited by 12 · see citing works
- Authors
- Isaacs, E., Konrad, A., Walendowski, A., Lennig, T., Hollis, V., & Whittaker, S.
- Affiliations
- Palo Alto Research Center (US)
- University of California, Santa Cruz (US)
- Samsung Research America, San Jose, California, USA
- ORCID
- Whittaker, Steve
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2013-04-27
- Pages
- 1071-1080
- OpenAlex
- W2159361351
- Cited by
- 251
- References
- 3
- Citations by year
- 2026: 11 · 2025: 61 · 2024: 18 · 2023: 10 · 2022: 19 · 2021: 20 · 2020: 15 · 2019: 15 · 2018: 14 · 2017: 11 · 2016: 17 · 2015: 20 · 2014: 16 · 2013: 4
- FWCI
- 15.01
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- psychological well-being, reflective journals, mobile application, echo, reflection mechanism
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