The vision of the MobileCoach team is to provide an open source behavioral intervention platform for fully-automated digital interventions. Due to a modular and extendable structure as well as an architecture rooted in the logics and legal claims of open-source software, the MobileCoach lays a fruitful ground for digital interventions in several application domains of behavior change. For example, the MobileCoach can be used to design and evaluate digital health interventions in the context of smoking cessation, nutrition or physical activity.

Based on personal characteristics and prior behavior assessed when participating in a digital intervention, the MobileCoach uses communication services (e.g. SMS) or sensor services (e.g. physical activity tracker) to monitor central indicators of the particular behavior on a regular basis. Building on individual data, MobileCoach users profit from individualized messages and valuable insights motivating for long-term behavior change.

An overview of a typical MobileCoach intervention is shown in Figure “A typical MobileCoach intervention” below. Following the registration process and an initial behavioral assessment at T0, the target behavior is monitored and according to it, participants receive a tailored intervention with individual feedback and recommendations until T1, for example, three to 12 months after T0. The long-term target behavior is finally evaluated in a follow-up assessment at T2, for example, three months after T1. This long-term target behavior is used as primary outcome variable to test the efficacy of the underlying MobileCoach intervention.

An overview of the various web based and SMS based user interfaces for participants of MobileCoach interventions is shown in Figure “The MobileCoach for participants” below. With the exception of the SMS based user interface, content and layout elements are fully customizable such that the target behavior can be supported as effective and efficient as possible. Native MobileCoach applications for mobile devices, desktop computers or ubiquitous computing environments will be made available as part of upcoming MobileCoach interventions and projects.

Domain experts such as physicians, psychologists or, more generally, behavioral intervention experts can use a lightweight web application to design and evaluate MobileCoach interventions. That is, no technical programming skills are required to design the baseline assessment, the tailored web-based feedback, the intervention rules or content elements. Some screenshots of the web application are shown in Figure “The MobileCoach for Domain Experts” below. Domain experts are also able to import and export interventions. This also includes an export of intervention data in the CSV format that allows further data processing and analyses with statistical packages such as R, Matlab or SPSS. However, real-time monitoring and longitudinal data analyses will be integrated directly in the MobileCoach web application in upcoming projects.

In the pilot phase, the MobileCoach will support two concrete health behaviors related to the public health context. For more information on these interventions, please go to the section Projects and read about our first projects MobileCoach Tobacco and MobileCoach Alcohol. Due to its open-source character, however, future research teams around the globe may contribute by adding features to the software and broadening the number of supported behaviors.

The first release of the open source MobileCoach platform can be downloaded in our section For Developers.

Features of the latest stable release (1.5.0 - DM7)

Last updated: April 5th, 2017

MESSAGES & INTERVENTION FLOW

1. Intervention rules are used to describe the flow of the intervention (e.g. when to send which messages):
   • Rules can send messages at specific points in time and define the time period in which an answer is expected
   • Rules can calculate and create new participant-specific variables
   • Hierarchical structures enable definition of sub-rules (i.e. control structures)
   • Reply rules can be defined to immediately react to answers of the participant
   • No-reply rules can be defined to react if the participant did not answer a question
   • A placeholder system allows to use all variables of a participant in all rules
   • Rules support date calculations (e.g. days until my birthday or days until a smoking quit day)
   • Rules support mathematical calculations / equations and regular expressions
   • NEW: Rules support lists and sorting operations
2. Messages are used to start a dialog with a participant:
   • Messages can be sent in a specific or random order
   • Messages can be sorted in question/answer/no-answer triples in order to increase the consistency of the dialog quality
   • Message rules can be used to skip messages for a specific participant
   • A placeholder system allows to use all variables of a participant in the messages
   • Messages are assigned to message groups, which allows the reduction of rule complexity in interventions (e.g. message groups for smokers / non-smokers)
   • Message groups can be defined to expect an answer by the participant (or not)
   • NEW: Messages can be saved in several-languages to enable authors to provide multi-language interventions
   • NEW: Messages can include links to intermediate surveys
   • NEW: Messages can be sent to the supervisor of a participant under specific circumstances

(SCREENING) SURVEYS & FEEDBACK

1. Design of web-based surveys for screening purposes as part of the interventions:
   • Supported question types:
     • Select one of the provided answers (radio button, e.g. yes/no, Likert-scale type, semantic differential)
     • Select many of the provided answers (checkbox, multiple choice)
     • Number input
     • Text input
     • Multi-line text input
   • Support for multi-item slides (e.g. question page with several Likert-type items)
   • Support for media objects in the slides (e.g. PDF document, video, or audio clip)
   • Specific answers can be pre-selected (e.g. zero value, centered slider)
   • Answers can be stored in variables of the participant
   • Each intervention can contain several surveys (e.g. for branding purposes and survey variants)
   • HTML-templates can be used to layout surveys
   • Slide rules can be used to jump to specific slides based on the former answers of a participant
   • Slide rules can be used to calculate variables based on the answers of a participant
   • A placeholder system allows to use all variables of a participant in all survey texts
   • Variable values can be checked for validity (e.g. by use of regular expressions, rules, calculations, etc.)
   • Variables can have default values if a participant leaves a survey before finishing it
   • Surveys can be protected with a password
   • NEW: Intermediate surveys enable to send out surveys at any time during an intervention
2. Public list of active surveys (e.g. for bookmarking the screening survey)
3. Design of web-based feedback slides
   • Each feedback has a unique URL for each participant to be able to access/communicate the same also in later steps of the intervention
   • Support for media objects in the slides (e.g. PDF document, video or audio clips)
   • Each intervention can contain several feedbacks (e.g. for branding purposes and survey variants)
   • HTML-templates can be used to layout surveys
   • Slide rules can be used to skip/show specific slides to specific participants
   • A placeholder system allows to use all variables of a participant in all feedback texts
4. Surveys and feedbacks can be enabled/disabled

MAINTENANCE & RESULTS

1. Unexpected answers will be shown to the intervention author for manual processing (e.g. to set the correct value, to start a personal dialog with participant)
2. Robust exception handling of answers with the help of regular expressions (e.g. “!!!Yes!!! :-)” can be interpreted as “yes”)
3. Manual messages can be sent to a preselected subset of participants
4. Variables of participants can be directly reviewed or exported to a CSV file for further processing in R, SPSS or Matlab
5. Dialog-based results, i.e. the message dialog for each participant with meta-data such as timestamps, can be reviewed online or exported to a CSV file for further processing in R, SPSS or Matlab
6. Daily generation of a report with aggregated results of all running interventions (e.g. number of sent messages) in a simple property-value format for further processing or inclusion into websites

BASIC FEATURES

1. Access rights management for intervention authors and technical administrators
2. Interventions can be created, imported, exported, enabled, disabled, deleted, assigned to authors
3. Participants can be imported, exported, deleted, assigned to organizations and organization groups
4. Cellphone number is used as unique identifier, i.e. no additional identifier is required for subjects to participate.
5. Global default values for variables can be set as backup solution for interventions (if optional questions of the surveys are not answered.)
6. Automatic data and data model adaption for new features or changes in the case of a version update
7. SSL-secured administration interface
8. SSL-secured online surveys and feedbacks
9. Document-based database with separate media storage
10. NEW: Reporting feature allows to export the current state of an intervention as interactive HTML document
11. NEW: Dynamically configurable REST-interface allows the reading/writing of specific variables of a participant/group/intervention from a modern website or web application
12. NEW: Image storage and caching engine enables user-content upload and reuse

The first MobileCoach projects are conducted in the public health context. They focus on smoking cessation, binge drinking and life-skills training interventions.

MobileCoach ready4life: Training for adolescents, 2016-2017

Problems:

• Substance use is one of the biggest contributors to the health burden in 10-24-year olds.
• School-based life-skills trainings were effective in delaying or preventing problematic substance use among adolescents, but…
• the implementation and dissemination of scalable and low-cost public health interventions represent serious challenges.

Research Framework & Method:

• Baseline Survey: Dynamic web-based baseline survey on tablets/smartphones to identify participants and collect baseline variables.
• Feedback: Instant and individual feedback for each participant including statistics and graphs.
• Monitoring & Intervention: 24 weeks of dynamic monitoring and intervention based on 524 messaging rules and 68 groups with 607 placeholder messages, supported by quizzes, games, intermediate surveys and social web challenges.
• Final Survey: Dynamic web-based final survey on smartphone to collect final variables and get feedback on the intervention itself.

Funding: LUNGENLIGA

Contact: Severin Haug severin.haug@isgf.uzh.ch

MobileCoach Tobacco: Efficacy Study, 2014-2016

Background: Tobacco smoking prevalence continues to be high, particularly among adolescents and young adults with lower educational levels, and is therefore a serious public health problem. Tobacco smoking and problem drinking often co-occur and relapses after successful smoking cessation are often associated with alcohol use. This study aims at testing the efficacy of the integrated smoking cessation and alcohol intervention MobileCoach Tobacco+ by comparing it to the smoking cessation only intervention MobileCoach Tobacco for young people, delivered via the Internet and mobile phone.

Methods/Design: A two-arm cluster-randomised controlled trial with one follow-up assessment after 6 months will be conducted. Participants in the integrated intervention group will: (1) receive individually tailored web-based feedback on their drinking behaviour based on age and gender norms, (2) receive individually tailored mobile phone text messages to promote drinking within low-risk limits over a 3-month period, (3) receive individually tailored mobile phone text messages to support smoking cessation for 3 months, and (4) be offered the option of registering for a more intensive program that provides strategies for smoking cessation centred around a self-defined quit date. Participants in the smoking cessation only intervention group will only receive components (3) and (4). Study participants will be 1350 students who smoke tobacco daily/occasionally, from vocational schools in Switzerland. Main outcome criteria are 7-day point prevalence smoking abstinence and cigarette consumption assessed at the 6-month follow up.

Discussion: This is the first study testing a fully automated intervention for smoking cessation that simultaneously addresses alcohol use and interrelations between tobacco and alcohol use. The integrated intervention can be easily implemented in various settings and could be used with large groups of young people in a cost-effective way.

Funding: Swiss Tobacco Prevention Fund

Contact: Severin Haug severin.haug@isgf.uzh.ch

Publications:

• Haug, S., Paz Castro, R., Filler, A., Kowatsch, T., Fleisch, E. & Schaub, M.P. (2014). Efficacy of an internet and SMS-based integrated smoking cessation and alcohol intervention for smoking cessation in young people: study protocol of a two-arm cluster randomised controlled trial. BMC Public Health, 14: 1140. PDF Intervention Focus

MobileCoach Alcohol: Efficacy Study, 2014-2016

Background: Problem drinking, particularly risky single-occasion drinking is widespread among adolescents and young adults in most Western countries. Mobile phone text messaging allows a proactive and cost-effective delivery of short messages at any time and place and allows the delivery of individualised information at times when young people typically drink alcohol. The main objective of the project is to test the efficacy of a combined web- and text messaging-based Intervention, named MobileCoach Alcohol to reduce problem drinking in young people with heterogeneous educational level.

Methods/Design: A two-arm cluster-randomised controlled trial with one follow-up assessment after 6 months will be conducted to test the efficacy of the intervention in comparison to assessment only. The fully-automated intervention program will provide an online feedback based on the social norms approach as well as individually tailored mobile phone text messages to stimulate (1) positive outcome expectations to drink within low-risk limits, (2) self-efficacy to resist alcohol and (3) planning processes to translate intentions to resist alcohol into action. Program participants will receive up to two weekly text messages over a time period of 3 months. Study participants will be 934 students from approximately 93 upper secondary and vocational schools in Switzerland. Main outcome criterion will be risky single-occasion drinking in the past 30 days preceding the follow-up assessment.

Discussion: This is the first study testing the efficacy of a combined web- and text messaging-based intervention to reduce problem drinking in young people. Given that this intervention approach proves to be effective, it could be easily implemented in various settings, and it could reach large numbers of young people in a cost-effective way.

Funding: Swiss National Science Foundation

Contact: Severin Haug severin.haug@isgf.uzh.ch

Publications:

• Haug, S., Kowatsch, T., Paz Castro, R., Filler, A. and Schaub, M.P. (2014) Efficacy of a web- and text messaging-based intervention to reduce problem drinking in young people: study protocol of a cluster-randomised controlled trial. BMC Public Health, 14: 809. PDF Intervention Focus

Behavioral research teams all around the globe are invited to collaborate with the MobileCoach team or to simply download, setup and use their own instance of the MobileCoach platform. Moreover, healthcare providers or other companies interested in fully-automated behavioral interventions are also invited to contact the MobileCoach team for joint projects.

Academia

As of today, the following research institutes discuss, design, provide and/or evaluate MobileCoach interventions:

Center for Digital Health Interventions, Health-IS Lab, Department of Management, Technology and Economics, ETH Zurich
www.c4dhi.org

Prof. Dr. Elgar Fleisch
efleisch@ethz.ch

Center for Digital Health Interventions, Health-IS Lab, Institute of Technology Management, University of St.Gallen
www.c4dhi.org

Prof. Dr. Elgar Fleisch elgar.fleisch@unisg.ch

Public & Organizational Health Epidemiology, Biostatistics and Prevention Institute, University of Zurich
www.ebpi.uzh.ch

PD Dr. med. Georg F. Bauer, DrPH
gfbauer@ifspm.uzh.ch

Swiss Research Institute for Public Health and Addiction, University of Zurich
www.isgf.ch

PD Dr. Severin Haug severin.haug@isgf.uzh.ch

Companies & Public Institutions

The following companies or public institutions discuss, design, provide and/or evaluate MobileCoach interventions:

Corporate Health Solutions GmbH, Zurich, Switzerland

Dr. Rebecca Brauchli
Chairwoman of the management board

License

The initiators of the MobileCoach were eager to make this platform freely available to academia, public institutions and industry with the overall goal to promote further development resulting in useful evidence-based behavioral interventions. In this regard, the MobileCoach team has chosen the Apache 2 open source license such that the MobileCoach can even be used in commercial applications without any legal hassles.

Building Blocks of MobileCoach Interventions

Building on the foundations of automata theory, the technical design of the MobileCoach system follows the concepts of a state machine that uses intervention rules for state transitions, which can be referred to as a fully automated expert system. Here, the state is an aggregate of all relevant attributes related to the intervention progress of a participant (e.g. the messages received or answers provided) whereas state transitions triggered by intervention rules lead to a change in these attributes and thus, to a state change.

In particular, each participant of the intervention group is assigned to a particular intervention state based on her answers during the baseline assessment. In response to this assessment, a web-based feedback is generated individually by the system for each participant. Then, depending on a participant’s regular feedback (e.g. via text messages or sensor data from internet of things services) during the subsequent months, intervention rules trigger state transitions and the tailoring of the follow-up communication. In particular, intervention rules are traversed on a regular basis (e.g. once a day) for each participant, and, as a result, update the state of the corresponding participant and start communication (e.g. via text messages) in the form of a question, a feedback or a recommendation.

With upcoming projects, tailoring of interventions and prediction of state transitions with the help of machine learning algorithms will be the primary research focus of the MobileCoach team. As a summary, the three building blocks of MobileCoach interventions are depicted in Figure “Building Blocks of MobileCoaching”.

Technical Architecture

The technical architecture of this rule-based state machine as shown in Figure “The MobileCoach Architecture” is derived from the model-view-controller design pattern. It consists therefore of…

1. an application layer, i.e. the view based on the Vaadin web application framework with the template-engine Mustache for intervention administration and the assessment survey at the baseline,

2. a service layer, i.e. the primary controller that utilizes the Java programming language and the expression evaluator Javaluator for the evaluation of the intervention rules and, finally,

3. a persistence layer, i.e. the model based on the document database mongoDB and plain files for storing the intervention content including a detailed protocol of all incoming and outgoing communication.

Password protection and Secure Sockets Layer (SSL) encoding are used to ensure the privacy and safety of data transfer.

Source Code

Download our MobileCoach source code from our GIT repository or as ZIP/GZ/BZ2 archive:

MobileCoach repository containing all repositories and instructions

MobileCoach CORE component: (required)

• README file
• GIT repository
• ZIP/GZ/BZ2 download

MobileCoach FileServletWrapper component:

• README file
• GIT repository
• ZIP/GZ/BZ2 download

MobileCoach Website component:

• README file
• GIT repository
• ZIP/GZ/BZ2 download

Requirements & Setup

Detailed information on how to setup MobileCoach on your own server can be found here:

• SlideShare presentation on Requirements & Setup
• README file of MobileCoach CORE
• README file of MobileCoach Website

Publications

• Filler, A., Kowatsch, T., Haug, S., Wahle, F., Staake, T. & Fleisch, E. (2015). MobileCoach: A Novel Open Source Platform for the Design of Evidence-based, Scalable and Low-Cost Behavioral Health Interventions - Overview and Preliminary Evaluation in the Public Health Context. Wireless Telecommunications Symposium 2015 (WTS 2015), New York, USA. PDF Technical Focus Outstanding Paper Award & Best Graduate Student Paper Award

• Filler, A., Haug, S. and Kowatsch, T. (2014). The MobileCoach – An Open Source Solution for Behavioral Change Interventions. Abstract presented at the 7th Scientific Meeting of The International Society for Research on Internet Interventions (ISRII), Valencia, Spain. PDF Technical Focus

• Kowatsch, T., Wahle, F., Filler, A. and Fleisch, E. (2014) Predicting Adverse Behavior with Early Warning Health Information Systems by Mining Association Rules on Multi-dimensional Behavior: A Proposal. Poster presented at the 7th Scientific Meeting of The International Society for Research on Internet Interventions (ISRII), Valencia, Spain. PDF Technical Focus

2016

Barata, F., Kowatsch, T., Tinschert, P., Filler, A. (2016). Personal MobileCoach: Tailoring Behavioral Interventions to the Needs of Individual Participants. UBICOMP 2016 Workshop Designing, Developing, and Evaluating The Internet of Personal Health (IoPH), Heidelberg, Germany. PDF

Haug, S., Paz, R., Kowatsch, T., Filler, A., Dickson-Spillmann, M., Dey, M., Schaub, M.P. (2016). Efficacy of a web- and text messaging-based intervention to reduce problem drinking in adolescents: Results of a cluster-randomised controlled trial, Journal of Consulting and Clinical Psychology.

2015

Haug, S., Paz, R., Kwon, M., Filler, A., Kowatsch, T., Schaub, M.P. (2015). Smartphone use and Smartphone addiction among young people in Switzerland. Journal of Behavioural Addictions 4(4), pp. 299-307. PDF

Filler, A., Kowatsch, T., Haug, S., Wahle, F., Staake, T. & Fleisch, E. (2015). MobileCoach: A Novel Open Source Platform for the Design of Evidence-based, Scalable and Low-Cost Behavioral Health Interventions - Overview and Preliminary Evaluation in the Public Health Context. Wireless Telecommunications Symposium 2015 (WTS 2015), New York, USA. PDF Technical Focus Outstanding Paper Award & Best Graduate Student Paper Award

2014

Haug, S., Paz Castro, R., Filler, A., Kowatsch, T., Fleisch, E. & Schaub, M.P. (2014). Efficacy of an internet and SMS-based integrated smoking cessation and alcohol intervention for smoking cessation in young people: study protocol of a two-arm cluster randomised controlled trial. BMC Public Health, 14: 1140. PDF Intervention Focus

Filler, A., Haug, S. and Kowatsch, T. (2014). The MobileCoach – An Open Source Solution for Behavioral Change Interventions. Abstract presented at the 7th Scientific Meeting of The International Society for Research on Internet Interventions (ISRII), Valencia, Spain. PDF Technical Focus

Kowatsch, T., Wahle, F., Filler, A. and Fleisch, E. (2014) Predicting Adverse Behavior with Early Warning Health Information Systems by Mining Association Rules on Multi-dimensional Behavior: A Proposal. Poster presented at the 7th Scientific Meeting of The International Society for Research on Internet Interventions (ISRII), Valencia, Spain. PDF Technical Focus

Haug, S., Kowatsch, T., Paz Castro, R., Filler, A. and Schaub, M.P. (2014) Efficacy of a web- and text messaging-based intervention to reduce problem drinking in young people: study protocol of a cluster-randomised controlled trial. BMC Public Health, 14: 809. PDF Intervention Focus

2013

Haug, S. (2013). Mobile phone text messaging to reduce alcohol and tobacco use in young people – a narrative review. Smart Homecare Technology and TeleHealth, 1(1), 11-19. PDF Intervention Focus

Haug, S. Bitter, G., Hanke, M., Ulbricht, S. Meyer, C. & John, U. (2013). Kurzintervention zur Förderung der Tabakabstinenz via Short Message Service (SMS) bei Auszubildenden an beruflichen Schulen: Longitudinale Interventionsstudie zur Ergebnis- und Prozessevaluation. Das Gesundheitswesen, 75(10), 625-631. Intervention Focus

Haug, S., Schaub, M.P., Venzin, V. Meyer, C. & John, U. (2013). Differenzielle Wirksamkeit eines Short Message Service (SMS)-basierten Programms zur Förderung des Rauchstopps bei Jugendlichen. Psychiatrische Praxis, 40(6), 339-346. Intervention Focus

Haug, S., Schaub, M.P., Venzin, V., Meyer, C., John, U. & Gmel, G. (2013). A pre-post study on the appropriateness and effectiveness of a web- and text messaging-based intervention to reduce problem drinking in emerging adults. Journal of Medical Internet Research, 15(9), e196. PDF Intervention Focus

Haug, S., Schaub, M.P., Venzin, V., Meyer, C. & John, U. (2013). Efficacy of a text message-based smoking cessation intervention for young people: a cluster randomized controlled trial. Journal of Medical Internet Research, 15(8), e171. PDF Intervention Focus

2012

Haug, S., Venzin, V. & Meyer, C. (2012). Förderung des Rauchstopps an Berufsfachschulen via SMS. SuchtMagazin, 38(3/4), 38-42. Intervention Focus

The MobileCoach is continuously improved by an interdisciplinary research team. Among the various disciplines, team members are particularly experts in computer science, psychology and the field of public health.

Center for Digital Health Interventions, Health-IS Lab

Andreas Filler
Research Associate at the Health-IS Lab, Main Developer of the MobileCoach

M.Sc. in Computer Science in Media & Dipl.-Inform. (FH) in Computer Science in Media

afiller@ethz.ch

Dr. Dirk Volland
Research Associate at the Health-IS Lab, MobileCoach Developer

Doctor of Philosophy in Management (Ph.D.), Dipl.-Winf (M.Sc.) in Business Informatics

dvolland@ethz.ch

Dr. Tobias Kowatsch
Scientific Director of the Center for Digital Health Interventions

Doctor of Philosophy in Management (Ph.D.), MSc in Business Informatics, MSc in Computer Science in Media & Dipl.-Inform. (FH) in Computer Science in Media

tobias.kowatsch@unisg.ch

Prof. Dr. Elgar Fleisch
Chair and Research Director of the Center for Digital Health Interventions

Chair of Information Management at the Department of Management, Technology and Economics, ETH Zurich, and Chair of Operations Management at the Institute of Technology Management, University of St. Gallen

efleisch@ethz.ch

Swiss Research Institute for Public Health and Addiction

PD Dr. Severin Haug
Psychologist and Head of Research at the Swiss Research Institute for Public Health and Addiction

severin.haug@isgf.uzh.ch

Raquel Paz Castro
Psychologist at the Swiss Research Institute for Public Health and Addiction

M.Sc., Psychologist

raquel.paz@isgf.uzh.ch

Community Members

Jost Schweinfurther
Dipl.-Designer (FH)

jschweinfurther@ethz.ch

Please let us know if you have any further questions or comments regarding the MobileCoach platform. We are eager to learn from your experience to improve the MobileCoach.

• For general research activities or collaboration requests related to the MobileCoach, please contact Tobias Kowatsch tobias.kowatsch@unisg.ch.

• For details on addiction-related interventions or collaborations, please contact our domain expert Severin Haug severin.haug@isgf.uzh.ch.

• For technical questions, please contact our main developer Andreas Filler afiller@ethz.ch.

Imprint

Publisher: Center for Digital Health Interventions, Health-IS Lab, Chair of Operations Management at the Institute of Technology Management, University of St. Gallen.

Editor: Andreas Filler afiller@ethz.ch, Center for Digital Health Interventions, Health-IS Lab

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