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Healthy Apps: Mobile Devices for Continuous Monitoring and Intervention

Bonnie Spring, Marientina Gotsis, Ana Paiva, Donna Spruijt-Metz
2013 IEEE Pulse  
It is now known that nearly half of the toll that illness takes in developed countries is linked to four unhealthy behaviors: smoking, excess alcohol intake, poor diet, and physical inactivity.  ...  As new technical capabilities to observe behavior continuously in context make it possible to tailor interventions in real time, the way we understand and try to influence behavior will change fundamentally  ...  Although we still rely on self-reported measures for some things (for instance, there is no objective measure of "toothache"), we now can elicit self-reported measures at designated times, in prespecified  ... 
doi:10.1109/mpul.2013.2279620 pmid:24233190 pmcid:PMC4930358 fatcat:3xevmmxyenfwhfqwtk2f3aj5qe

A Large Scale, App-Based Behaviour Change Experiment Persuading Sustainable Mobility Patterns: Methods, Results and Lessons Learnt

Francesca Cellina, Dominik Bucher, Francesca Mangili, José Veiga Simão, Roman Rudel, Martin Raubal
2019 Sustainability  
In Zurich, instead, where high quality public transport is already available, no statistically significant effects were found. In this paper we present the GoEco!  ...  , a smartphone application exploiting automatic mobility tracking, eco-feedback, social comparison and gamification elements to persuade individual modal change. We tested the effectiveness of GoEco!  ...  The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.  ... 
doi:10.3390/su11092674 fatcat:6g4ndtpbybcg7bn3lyks7oxg4a

Bodily sensation maps: Exploring a new direction for detecting emotions from user self-reported data

Iván García-Magariño, Luca Chittaro, Inmaculada Plaza
2018 International Journal of Human-Computer Studies  
Highlights We explore bodily sensation maps (BSMs) as a novel way to detect emotions We propose EmoPaint, a mobile app to collect BSMs and detect emotions from them A user study reveals that the app is  ...  easy to use and able to detect emotions The app improves accuracy over a traditional method: Affect Grid with Circumplex model Abstract The ability of detecting emotions is essential in different fields  ...  University of Udine) for his help with graphics resources for the EmoPaint app.  ... 
doi:10.1016/j.ijhcs.2018.01.010 fatcat:4yxehe6erzdjhcfsvxsyqx6cqe

Reflection in Theory and Reflection in Practice: An Exploration of the Gaps in Reflection Support among Personal Informatics Apps

Janghee Cho, Tian Xu, Abigail Zimmermann-Niefield, Stephen Voida
2022 CHI Conference on Human Factors in Computing Systems  
in current apps, and offer suggestions about how reflection could be better supported.  ...  While reflection is considered an indispensable activity in PI use, how and when reflection occurs is still under-studied.  ...  About half of the apps in the corpus leveraged only users' manual inputs, while the other half collected a combination of self-report data and smartphone sensor data.  ... 
doi:10.1145/3491102.3501991 fatcat:ax4gykwcnbafxmzlaurbddb7vi

This App is not for Me: Using Mobile and Wearable Technologies to Improve Adolescents' Smartphone Addiction through the Sharing of Personal Data with Parents

Pin-Chieh Chen, Min-Wei Hung, Hsueh-Sung Lu, Chien Wen (Tina) Yuan, Nanyi Bi, Wan-Chen Lee, Ming-Chyi Huang, Chuang-Wen You
2022 CHI Conference on Human Factors in Computing Systems  
CCS CONCEPTS • Human-centered computing → Empirical studies in collaborative and social computing.  ...  light on the means by which behavioral data obtained via sensors and self-reporting complement eforts to moderate smartphone usage. (3) Finally, we unravel the communication dynamics based on the sharing  ...  as subjective responses in the self-reports to make inferences.  ... 
doi:10.1145/3491102.3517478 fatcat:co3rhzbdqjbfvmmhu3ctc2wztq

A Persuasive and Social mHealth Application for Physical Activity: A Usability and Feasibility Study

Soleh U Al Ayubi, Bambang Parmanto, Robert Branch, Dan Ding
2014 JMIR mHealth and uHealth  
Conclusions: Based on the fundamental characteristics, the application was successfully developed. The usability results suggest that the system is usable and user satisfaction was high.  ...  To that end, we developed a persuasive and social mHealth application designed to monitor and motivate users to walk more every day.  ...  Acknowledgments This work is partly funded by the following grants, Grant #R25 RR023274-03 from the National Center for Research Resources, National Institutes of Health, United States; Grant #1R21HD071810  ... 
doi:10.2196/mhealth.2902 pmid:25099928 pmcid:PMC4114463 fatcat:fx3h3eny6ffxbfqf4l6jwlvadm

Systematic review of context-aware digital behavior change interventions to improve health

Kelly J Thomas Craig, Laura C Morgan, Ching-Hua Chen, Susan Michie, Nicole Fusco, Jane L Snowdon, Elisabeth Scheufele, Thomas Gagliardi, Stewart Sill
2020 Translational Behavioral Medicine  
Thirty-three articles were included, comprising mobile health (mHealth) applications, Internet of Things wearables/sensors, and internet-based web applications.  ...  Context-aware DBCIs effectively supported behavior change to improve users' health behaviors.  ...  However, algorithms can automatically detect relevant events from sensor data, reducing the burden of self-reporting, and provide users with an awareness of their behavior and/or health risk.  ... 
doi:10.1093/tbm/ibaa099 pmid:33085767 pmcid:PMC8158169 fatcat:opywdluuebgpjf52enlqlnrlji

From black box to toolbox: Outlining device functionality, engagement activities, and the pervasive information architecture of mHealth interventions

Brian G. Danaher, Håvar Brendryen, John R. Seeley, Milagra S. Tyler, Tim Woolley
2015 Internet Interventions  
We posit that developers of mHealth interventions will be able to better achieve the promise of this burgeoning arena by leveraging the toolbox and functionality of mobile devices in order to engage participants  ...  and encourage meaningful behavior change within the context of a carefully designed pervasive information architecture.  ...  Sensor functionality The use of sensors in mHealth interventions is in its infancy.  ... 
doi:10.1016/j.invent.2015.01.002 pmid:25750862 pmcid:PMC4346786 fatcat:vh5wp3bxj5fktotp4tpiebo4jy

Using Location Lifelogs to Make Meaning of Food and Physical Activity Behaviors

Adrienne Andrew, Kevin Eustice, Andy Hickl
2013 Proceedings of the ICTs for improving Patients Rehabilitation Research Techniques  
As the ability to track and make sense of location is improving, it will be possible to associate high-quality data regarding the user location and location-derived activities to health and wellness logs  ...  This can significantly improve the ability of these logs to expose meaning to the user, specifically around food and physical activity behaviors.  ...  While the food diary relies on self-report (manual entry by the user), the other two components are primarily passive collection. IV.  ... 
doi:10.4108/icst.pervasivehealth.2013.252134 dblp:conf/ph/AndrewEH13 fatcat:mapd6tam7fdp3bfrpkn6mzvcmm

Happy: Cancer Prevention Using Smartphones

Nuno Ribeiro, Luís Moreira, Ana Margarida Almeida, Filipe Santos-Silva
2016 Procedia Computer Science  
The main purpose of the work presented in this paper is to develop a smartphone app, capable of inducing behaviour changes on individuals.  ...  A cancer prevention app called Happy was designed and is currently being tested.  ...  Acknowledgements The authors would like to thank all the volunteers that participated in the study.  ... 
doi:10.1016/j.procs.2016.09.183 fatcat:4ka24qqahvf4fdbdumkb7s5vsy

Feasibility and acceptability of smartphone-based auto-personalized physical activity recommendations for chronic pain self-management: A pilot study on adults with chronic back pain (Preprint)

Mashfiqui Rabbi, Hane Aung, Geri Gay, M. Cary Reid, Tanzeem Choudhury
2018 Journal of Medical Internet Research  
Objective: MyBehaviorCBP is a mobile phone app that uses machine learning on sensor-based and self-reported physical activity data to find routine behaviors and automatically generate physical activity  ...  Since the recommendations are based on routine behavior, they are likely to be perceived as familiar and therefore likely to be actualized even in the presence of negative beliefs.  ...  Acknowledgments This project is funded by the Translational Research Institute for Pain in Later Life at Weill Cornell Medical College and the National Institute of Aging.  ... 
doi:10.2196/10147 pmid:30368433 pmcid:PMC6229514 fatcat:rqq2tbk5ynahhmi27wd4ygyx4a

Beyond quantified self

Jochen Meyer, Steven Simske, Katie A. Siek, Cathal G. Gurrin, Hermie Hermens
2014 Proceedings of the extended abstracts of the 32nd annual ACM conference on Human factors in computing systems - CHI EA '14  
Modifying behavior may be all that is necessary to prevent the disease.  ...  We draw out different purposes for which the data is used and question whether the design should focus so specifically on the data itself rather than the collection process.  ...  Acknowledgements The material reported in this document is supported by the SUTD-MIT International Design Centre (IDC).  ... 
doi:10.1145/2559206.2560469 dblp:conf/chi/MeyerSSGH14 fatcat:qtd7ldb64rab5jtuoqzdah5uxm

14 Years of Self-Tracking Technology for mHealth – Literature Review: Lessons Learnt and the PAST SELF Framework [article]

Sofia Yfantidou, Pavlos Sermpezis, Athena Vakali
2022 arXiv   pre-print
In today's connected society, many people rely on mHealth and self-tracking (ST) technology to help them adopt healthier habits with a focus on breaking their sedentary lifestyle and staying fit.  ...  Based on the review's findings, we propose PAST SELF, a framework to guide the design and evaluation of ST technology that has potential applications in industrial and scientific settings.  ...  ST and HBC research is highly interdisciplinary and almost always utilizes self-reports.  ... 
arXiv:2104.11483v3 fatcat:lvvmrs4okffpdikdkmvb2ou75y

Mobile phones as medical devices in mental disorder treatment: an overview

Franz Gravenhorst, Amir Muaremi, Jakob Bardram, Agnes Grünerbl, Oscar Mayora, Gabriel Wurzer, Mads Frost, Venet Osmani, Bert Arnrich, Paul Lukowicz, Gerhard Tröster
2014 Personal and Ubiquitous Computing  
Currently monitoring mental disorders relies on subjective clinical self reporting rating scales, which were developed more than 50 years ago.  ...  Approximately 25% of all people in Europe and the USA experience a mental disorder at least once in their lifetime.  ...  This project is sponsored by the European project MONARCA in the 7th Framework Program under contract Number: 248545.  ... 
doi:10.1007/s00779-014-0829-5 fatcat:unacdduktfbqvmynkht7tmwfgi

Virtual Coaches for Older Adults' Wellbeing: A Systematic Review

Mira El Kamali, Leonardo Angelini, Maurizio Caon, Francesco Carrino, Christina Rocke, Sabrina Guye, Giovanna Rizzo, Alfonso Mastropietro, Martin Sykora, Suzanna Elayan, Isabelle Kniestedt, Canan Ziylan (+3 others)
2020 IEEE Access  
In particular, we presented how previous studies defined their virtual coaches, which behavioral change models and techniques they adopted and the overall system architecture, in terms of monitoring solutions  ...  Such digital systems assume various forms, from classic apps, to more advanced conversational agents or robots.  ...  The opinions expressed in this paper are those of the authors and are not necessarily those of the project partners or the European Commission.  ... 
doi:10.1109/access.2020.2996404 fatcat:glpvec4ckrczfhjxjcyrptmmhi
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