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Meena N. Shankar

dblp:374/8629 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0005-3792-966XORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Health and well-being technologies · 50% Ubiquitous computing and smart environments · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Ubiquitous computing and smart environments › context-aware computing
context-aware notifications
0.812024
Investigating Contextual Notifications to Drive Self-Monitoring in mHealth Apps for Weight Maintenance · CHI 2024
Health and well-being technologies
mobile health
0.812024
Investigating Contextual Notifications to Drive Self-Monitoring in mHealth Apps for Weight Maintenance · CHI 2024

Methods — techniques the papers use, named apart from their topics

in-the-wild study · 0.8
YearPublicationVenuePosition
2024 Investigating Contextual Notifications to Drive Self-Monitoring in mHealth Apps for Weight Maintenance
abstract
Mobile health applications for weight maintenance offer self-monitoring as a tool to empower users to achieve health goals (e.g., losing weight); yet maintaining consistent self-monitoring over time proves challenging for users. These apps use push notifications to help increase users’ app engagement and reduce long-term attrition, but they are often ignored by users due to appearing at inopportune moments. Therefore, we analyzed whether delivering push notifications based on time alone or also considering user context (e.g., current activity) affected users’ engagement in a weight maintenance app, in a 4-week in-the-wild study with 30 participants. We found no difference in participants’ overall (across the day) self-monitoring frequency between the two conditions, but in the context-based condition, participants responded faster and more frequently to notifications, and logged their data more timely (as eating/exercising occurs). Our work informs the design of notifications in weight maintenance apps to improve their efficacy in promoting self-monitoring.
Julia Woodward, Dinank Bista, Xuanpu Zhang, Ishvina Singh, Oluwatomisin Obajemu, Meena N. Shankar, Kathryn M. Ross, Jaime Ruiz 0002, Lisa Anthony
CHI7