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Ally: A Smartphone-based Physical Activity Intervention

Authors:
Florian Künzler at ETH Zurich
Florian Künzler
Jan-Niklas Kramer at University of St. Gallen
Jan-Niklas Kramer
Varun Mishra at Northeastern University
Varun Mishra
Bastien Presset at University of Lausanne
Bastien Presset
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Abstract

No behavior has an impact on human health as great as physical activity (PA). We therefore developed Ally, a smartphone-based 6-week PA intervention. Ally seeks to exploit the ubiquity and sensing capabilities of mobile phones to adapt the provision of PA interventions to the context of the user. In this research we investigate the following research questions: (1) What are effective components of Ally, a mHealth physical activity intervention? and (2) Can mobile sensor data predict opportune moments for interventions?
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www.c4dhi.org
JITAI stands for Just-in-time adaptive Interventions (
NAH16)
Florian Künzler
1
, Jan-Niklas Kramer
2
, Varun Mishra
3
, Bastien Presset
4
,
Shwana N. Smith
5
, David Kotz
3
, Urte Scholz
6
, Elgar Fleisch
1,2
& Tobias Kowatsch
2
1 ETH Zurich, 2 University of St.Gallen, 3 Dartmouth College, 4 University of Lausanne, 5 University of Michigan, 6 University of Zurich
Ally: A Smartphone-based
Physical Activity Intervention
1. Background
No behavior has an impact on human health as great
as physical activity (PA). We therefore developed
Ally, a smartphone-based 6-week PA intervention.
Ally seeks to exploit the ubiquity and sensing
capabilities of mobile phones to adapt the provision
of PA interventions to the context of the user.
2. Research Questions
(1) What are effective components of Ally, a mHealth
physical activity intervention?
(2) Can mobile sensor data predict opportune
moments for interventions?
3. JITAI Framework
4. Ally Field Study
5. Recruitment Process
We conduct a longitudinal factorial experiment to test
intervention components and collect a variety of sensor data.
References
Florian Künzler, Jan-Niklas Kramer & Tobias Kowatsch (2017) Efficacy of mobile context-aware n otification management systems: A
systematic literature review and met a-analysis", 2017 IEEE 13th Intern ational Conference on Wireless and Mobile Comp uting,
Networking and Communications (WiMob), 131-138, doi:10.1109/WiMOB.2017.8115839
Nahum-Shani, I., S. N. Smith, B. J. Spring, L. M. Collins, K. Witkiewitz, A. Tewari & S. A. Murphy (2016). "Just-in-Time Adaptive
Interventions (JITAIs) in Mob ile Health: Key Components and Design Principles for Ongoing Health Behavior Support." Annals of
Behavioral Medicine, ePrint ahead doi:10.1007/s12160-016-9830-8.
Lucerne | December 4 | 2017CSS Meets & Greets CDHI
Partner
State of vulnerability
and opportunity
State of receptivity
JITAI
Proximal
Outcome
Distal
Outcome
Invitations sent to
N = 30.000 CSS customers
n = 749 (2.5%)
clicked the invitation link
n = 311 (42%)
completed T1 survey
n = 273 (88%)
registered in the Ally system
n = 55 not eligible
n = 321 declined to participate
n = 62 dropped out
n = 191
gave reasons for not participating
ResearchGate has not been able to resolve any citations for this publication.
Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support
Article
Full-text available
  • Sep 2016
Background The just-in-time adaptive intervention (JITAI) is an intervention design aiming to provide the right type/amount of support, at the right time, by adapting to an individual?s changing internal and contextual state. The availability of increasingly powerful mobile and sensing technologies underpins the use of JITAIs to support health behavior, as in such a setting an individual?s state can change rapidly, unexpectedly, and in his/her natural environment. PurposeDespite the increasing use and appeal of JITAIs, a major gap exists between the growing technological capabilities for delivering JITAIs and research on the development and evaluation of these interventions. Many JITAIs have been developed with minimal use of empirical evidence, theory, or accepted treatment guidelines. Here, we take an essential first step towards bridging this gap. Methods Building on health behavior theories and the extant literature on JITAIs, we clarify the scientific motivation for JITAIs, define their fundamental components, and highlight design principles related to these components. Examples of JITAIs from various domains of health behavior research are used for illustration. Conclusion As we enter a new era of technological capacity for delivering JITAIs, it is critical that researchers develop sophisticated and nuanced health behavior theories capable of guiding the construction of such interventions. Particular attention has to be given to better understanding the implications of providing timely and ecologically sound support for intervention adherence and retention.
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Efficacy of Mobile Context-aware Notification Management Systems: A Systematic Literature Review and Meta-Analysis
Conference Paper
  • Oct 2017
Notifications can be relevant but they can also decrease productivity when delivered at the wrong point in time. Smartphones are increasingly capable of detecting relevant context information with the goal to decrease the number of these badly timed interruptions. Accordingly, research on context- aware notification management systems (CNMSs) on mobile devices has received increasing attention recently, prototypes have been built and empirically evaluated. However, there exists no systematic overview of mobile CNMSs evaluating their efficacy. The objectives of the current work are therefore to identify relevant empirical studies that have assessed the efficacy of mobile CNMSs and to discuss the findings with respect to future work. A systematic literature review and meta-analysis was conducted to address these objectives. Consistent with prior work, two efficacy metrics were applied: response rate and response delay. A keyword-based search strategy was used and resulted in 1’634 studies, out of which 8 were relevant for the topic. Findings indicate that mobile CNMSs increase the response rate, while there was only little evidence that they reduce response time, too. Implications for researchers and practitioners are discussed and future research is outlined that aims at further increasing the efficacy of mobile CNMSs.
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