An m-Health app that goes beyond screen time applications

Patel, Sarthak; Sasidhar, Kalyan; Vaghela, Maitri; Katrodia, Parth; Wagani, Rekha

doi:10.1109/r10-htc54060.2022.9929866

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…Educational and sociotechnical support NUDGE [41,80] AMSS [105] Power study [107] Actuflow [43] Happify [78,119] D-Crastinate [70] Socialize (app) [35,104] Pasue-board [75] FoMO_R [39] Facebook-investment [46] Pudelwohl [79] Serious game [51] Mindphone [112] Annotif [106] Smart planning course [114] Finesse (system) [49] Jump and jump [110] Chirp Twitter client [111] TRIPP [47] Unified mobile application [120] Human Behavior and Emerging Technologies technology that does not facilitate problematic attachment, but rather preserves users' DWB. A common limitation observed in a number of studies was the lack of preassessment for the user's behaviour before applying the intervention.…”

Section: Minimize and Manage Usage Timementioning

confidence: 99%

Designing for Digital Wellbeing: From Theory to Practice a Scoping Review

Mansoori

Al-Thani

Ali

2023

Human Behavior and Emerging Technologies

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In a world that is highly dependent on digital connectivity, technology use is becoming unavoidable, intense, and possibly harmful. The pervasiveness of technology which has been in tandem with the increasing number of reported cases of harmful usage styles, with some exhibiting symptoms of behavioural addiction, raised concerns around users’ psychological health and well-being. Digital Wellbeing is a new facet of human well-being that has recently emerged. While the term is yet to have a commonly agreed definition, it typically denotes a technology that promotes positivity, personal growth, and a usage that is balanced and healthy. In this paper, we aim to examine the extent, range, and nature of Digital Wellbeing research activity in human-computer interaction- (HCI-) related literature. We conducted a scoping review analysing 87 articles that researched Digital Wellbeing and its interrelation with technology design. Our analysis identified different meanings and constructs of the Digital Wellbeing concept, research trends, and a gap related to incorporating it in the design process. Accordingly, we recommend that an agreed-on definition for Digital Wellbeing and validated tools and frameworks are needed to ensure its integration in the digital design process. We also recommend that a wider research direction for HCI researchers and practitioners interested in Digital Wellbeing is needed to include the role of designers and societal institutions in the digital design process to ensure a design that is inclusive and well-being sensitive.

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Section: Minimize and Manage Usage Timementioning

confidence: 99%

Designing for Digital Wellbeing: From Theory to Practice a Scoping Review

Mansoori

Al-Thani

Ali

2023

Human Behavior and Emerging Technologies

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“…In contrast, our app collects any kind of sensor data and is an open source. A detailed description of our app is provided in [34].…”

Section: Phone and Other Platformsmentioning

confidence: 99%

Smartphone Mediated Tracking and Analysis of Sleep Patterns in Indian College Students

Vaghela

Sasidhar

2022

Hum-Cent Intell Syst

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Sleep is one of the essential bio-makers for human health. Poor sleep is associated with reduced cognitive performance. With most smartphone users in India being college students, the focus is now on exploring smartphone usage’s impact on students’ sleep. Umpteen news articles in India have reported binge-watching, social media use during the night, and other mobile phone-related interruptions as causes of improper sleep and irregular sleep patterns. However, such studies may involve bias while self-reporting and are limited to a one-time exercise. To understand the reality, we need to accurately quantify the sleep duration, patterns, mobile usage before and after bedtime, number and duration of interruptions. In this first-of-its-kind study in India, we infer novel insights into the sleep patterns of a cohort of 40 college students. We implement a mobile sensing-based approach for the study by installing a custom-developed mobile app on all phones. We extract sleep activity and infer the sleep duration, bed-in and wake-up times, and interruption duration from the sensor data collected from the phone’s built-in sensors. The study brings about new insights into college student sleep patterns and, interestingly, shows that students have a regular sleep cycle and good sleep quality. Only one-fourth of the students revealed irregular sleep patterns, and we did not observe any mobile-related interruptions 30 min past bedtime.

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