ArticleProceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies2019
ReVibe: A Context-assisted Evening Recall Approach to Improve Self-report Adherence.
Article in Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Digital and Technology-Enabled Approaches in Dietary Assessment: Addressing Bias, Error, and Feasibility in Population- and Community-Based Research.Advances in nutrition (Bethesda, Md.) · 2026Review
- "It felt more real": Investigating the User Experience of the MiWaves Personalizing JITAI Pilot Study.International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare · 2026Article
- A Context-Assisted, Semi-Automated Activity Recall Interface Allowing Uncertainty.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2025Article
- An Evaluation of Temporal and Categorical Uncertainty on Timelines: A Case Study in Human Activity Recall Visualizations.Visualization : proceedings of the ... IEEE Conference on Visualization. IEEE Conference on Visualization · 2025Article
- Article
- A Multi-Agent LLM Network for Suggesting and Correcting Human Activity and Posture Annotations.Proceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference) · 2025Article
- Collecting Self-reported Physical Activity and Posture Data Using Audio-based Ecological Momentary Assessment.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2024Article
- Time-varying model of engagement with digital self reporting: Evidence from smoking cessation longitudinal studies.Frontiers in digital health · 2023Article
- Using Wake-Up Tasks for Morning Behavior Change: Development and Usability Study.JMIR formative research · 2022Article
- Cost and Effort Considerations for the Development of Intervention Studies Using Mobile Health Platforms: Pragmatic Case Study.JMIR formative research · 2022Article
- Microrandomized trials for promoting engagement in mobile health data collection: Adolescent/young adult oral chemotherapy adherence as an example.Current opinion in systems biology · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Besides passive sensing, ecological momentary assessments (EMAs) are one of the primary methods to collect in-the-moment data in ubiquitous computing and mobile health. While EMAs have the advantage of low recall bias, a disadvantage is that they frequently interrupt the user and thus long-term adherence is generally poor. In this paper, we propose a less-disruptive self-reporting method, "assisted recall," in which in the evening individuals are asked to answer questions concerning a moment from earlier in the day assisted by contextual information such as location, physical activity, and ambient sounds collected around the moment to be recalled. Such contextual information is automatically collected from phone sensor data, so that self-reporting does not require devices other than a smartphone. We hypothesized that providing assistance based on such automatically collected contextual information would increase recall accuracy (i.e., if recall responses for a moment match the EMA responses at the same moment) as compared to no assistance, and we hypothesized that the overall completion rate of evening recalls (assisted or not) would be higher than for in-the-moment EMAs. We conducted a two-week study (N=54) where participants completed recalls and EMAs each day. We found that providing assistance via contextual information increased recall accuracy by 5.6% (
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.