[HTML][HTML] Barriers to and facilitators for using nutrition apps: systematic review and conceptual framework

LM König, C Attig, T Franke… - JMIR mHealth and uHealth, 2021 - mhealth.jmir.org
Background: Nutrition apps are effective in changing eating behavior and diet-related health
risk factors. However, while they may curb growing overweight and obesity rates …

Machine learning techniques in adaptive and personalized systems for health and wellness

O Oyebode, J Fowles, D Steeves… - International Journal of …, 2023 - Taylor & Francis
Traditional health systems mostly rely on rules created by experts to offer adaptive
interventions to patients. However, with recent advances in artificial intelligence (AI) and …

[HTML][HTML] Efficacy of the mindfulness meditation mobile app “calm” to reduce stress among college students: Randomized controlled trial

J Huberty, J Green, C Glissmann, L Larkey… - JMIR mHealth and …, 2019 - mhealth.jmir.org
Background: College students experience high levels of stress. Mindfulness meditation
delivered via a mobile app may be an appealing, efficacious way to reduce stress in college …

Personal informatics in interpersonal contexts: towards the design of technology that supports the social ecologies of long-term mental health management

EL Murnane, TG Walker, B Tench, S Voida… - Proceedings of the ACM …, 2018 - dl.acm.org
Personal informatics systems for supporting health largely grew out of a" self"-centric
orientation: self-tracking, self-reflection, self-knowledge, self-experimentation, self …

User engagement and abandonment of mHealth: a cross-sectional survey

AS Mustafa, N Ali, JS Dhillon, G Alkawsi, Y Baashar - Healthcare, 2022 - mdpi.com
Mobile health (mHealth) apps have great potential to improve health outcomes. Given that
mHealth apps have become ubiquitous, there is limited focus on their abandonment. Data …

Designing reinforcement learning algorithms for digital interventions: pre-implementation guidelines

AL Trella, KW Zhang, I Nahum-Shani, V Shetty… - Algorithms, 2022 - mdpi.com
Online reinforcement learning (RL) algorithms are increasingly used to personalize digital
interventions in the fields of mobile health and online education. Common challenges in …

Factors influencing continued usage behavior on mobile health applications

P Wu, R Zhang, X Zhu, M Liu - Healthcare, 2022 - mdpi.com
(1) Background: As people pay more attention to health, mobile health applications
(mHealth apps) are becoming popular. These apps offer health services that run on mobile …

[HTML][HTML] Determinants for sustained use of an activity tracker: observational study

S Hermsen, J Moons, P Kerkhof… - JMIR mHealth and …, 2017 - mhealth.jmir.org
Background: A lack of physical activity is considered to cause 6% of deaths globally.
Feedback from wearables such as activity trackers has the potential to encourage daily …

[HTML][HTML] Habit formation in wearable activity tracker use among older adults: qualitative study

W Peng, L Li, A Kononova, S Cotten… - JMIR mHealth and …, 2021 - mhealth.jmir.org
Background: Wearable activity trackers are popular devices used to motivate behavior
change. Wearable activity trackers are especially beneficial for encouraging light physical …

Trackly: A customisable and pictorial self-tracking app to support agency in multiple sclerosis self-care

A Ayobi, P Marshall, AL Cox - Proceedings of the 2020 CHI Conference …, 2020 - dl.acm.org
Self-tracking is an important part of self-care. However, predefined self-tracking approaches
can impede people's agency in managing their health. We investigated a customisable and …