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Design and Evaluation of a Mobile Chat App for the Open Source Behavioral Health Intervention Platform MobileCoach

Authors:
Tobias Kowatsch at University of Zurich
Tobias Kowatsch
Dirk Volland at University of St. Gallen
Dirk Volland
Chen-Hsuan Iris Shih at ETH Zurich
Chen-Hsuan Iris Shih
Dominik Rüegger at ETH Zurich
Dominik Rüegger
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Abstract and Figures

The open source platform MobileCoach (mobile-coach.eu) has been used for various behavioral health interventions in the public health context. However, so far, MobileCoach is limited to text message-based interactions. That is, participants use error-prone and laborious text-input fields and have to bear the SMS costs. Moreover, MobileCoach does not provide a dedicated chat channel for individual requests beyond the processing capabilities of its chatbot. Intervention designers are also limited to text-based self-report data. In this paper, we thus present a mobile chat app with pre-defined answer options, a dedicated chat channel for patients and health professionals and sensor data integration for the MobileCoach platform. Results of a pretest (N = 11) and preliminary findings of a randomized controlled clinical trial (N = 14) with young patients, who participate in an intervention for the treatment of obesity, are promising with respect to the utility of the chat app.
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Design and Evaluation of a Mobile Chat App
for the Open Source Behavioral Health
Intervention Platform MobileCoach
Tobias Kowatsch
1(&)
, Dirk Volland
2
, Iris Shih
2
, Dominik Rüegger
2
,
Florian Künzler
2
, Filipe Barata
2
, Andreas Filler
1,3
, Dirk Büchter
4
,
Björn Brogle
4
, Katrin Heldt
4
, Pauline Gindrat
5
,
Nathalie Farpour-Lambert
6
, and Dagmar l’Allemand
4
1
Institute of Technology Management,
University of St. Gallen, St. Gallen, Switzerland
tobias.kowatsch@unisg.ch
2
Department of Management, Technology and Economics,
ETH Zurich, Zurich, Switzerland
3
Energy Efficient Systems Group, University of Bamberg, Bamberg, Germany
4
Children’s Hospital of Eastern Switzerland, St. Gallen, Switzerland
5
Fondation SportSmile, Nyon, Switzerland
6
Department of Community Medicine, Primary Care and Emergency,
University Hospital of Geneva/University of Geneva, Geneva, Switzerland
Abstract. The open source platform MobileCoach (mobile-coach.eu) has been
used for various behavioral health interventions in the public health context.
However, so far, MobileCoach is limited to text message-based interactions.
That is, participants use error-prone and laborious text-input fields and have to
bear the SMS costs. Moreover, MobileCoach does not provide a dedicated chat
channel for individual requests beyond the processing capabilities of its chatbot.
Intervention designers are also limited to text-based self-report data. In this
paper, we thus present a mobile chat app with pre-defined answer options, a
dedicated chat channel for patients and health professionals and sensor data
integration for the MobileCoach platform. Results of a pretest (N= 11) and
preliminary findings of a randomized controlled clinical trial (N= 14) with
young patients, who participate in an intervention for the treatment of obesity,
are promising with respect to the utility of the chat app.
Keywords: Health intervention Digital coaching Chat-based interaction
1 Introduction
Non communicable diseases (NCDs) such as heart diseases, asthma, obesity, diabetes
or chronic kidney disease impose the greatest burden on global health [14]. According
to WHO’s NCD global monitoring framework, many of these diseases are conse-
quences of adverse health behaviors, for example, harmful use of alcohol and tobacco
or physical inactivity [15]. However, health personnel is strongly limited [2]. Conse-
quently, scalable behavioral health interventions are required.
©Springer International Publishing AG 2017
A. Maedche et al. (Eds.): DESRIST 2017, LNCS 10243, pp. 485–489, 2017.
DOI: 10.1007/978-3-319-59144-5_36
Innovative digital health interventions (DHIs) have not only the potential to
improve the efficacy of preventive or therapeutic behavioral health interventions but
also to reduce their costs [1]. With the goal to provide an open source platform that
allows health professionals to design scalable, low-cost and evidence-based DHIs,
MobileCoach (mobile-coach.eu) was developed [5] and evaluated [9].
However, it uses the short message service (SMS) for delivering behavioral health
interventions, and thus comes with various shortcomings as outlined in the next
section. We therefore present in this paper the first mobile chat app for the Mobile-
Coach platform that addresses these shortcomings and thus, complements existing
communication such as personal exchange, SMS-based, phone-based or video-based
interactions.
The remainder of this paper is structured as follows. Next, we describe the design of
the chat app. Then, the app’s significance to research and practice is outlined. Finally,
we present results from an empirical study with 11 obese children who assessed the
new chat app as the first target group.
2 Design of the Chat App
Hands-on experience with several MobileCoach-based interventions [7–9] has revealed
four major shortcomings related to its text messaging approach. First, participants have
to bear the SMS costs which may be an entry barrier if the caregiver does not provide a
monetary compensation. Second, participants are always requested to manually type in
text to answer even Likert-scale type questions. These answers are then parsed by the
MobileCoach, which is error-prone in case the answer does not perfectly fit to the
question. Processing these answers is a time-consuming process for the caregiver, too.
Third, participant-initiated requests usually require an individual answer from a care-
giver instead of a scripted answer by a chatbot. A rule-based chatbot does therefore not
always fit to the communication needs of the participants. Fourth, text-messaging is
limited to self-report data, i.e. health professionals cannot use objective sensor data
from a smartphone (e.g., accelerometer data used to measure physical activity) or
sensor data from devices connected to that smartphone (e.g., Bluetooth-enabled blood
glucose or peak flow meters) for the design of their DHIs.
Regarding these shortcomings and against the background of smartphone perva-
siveness [4], the following requirements have been defined: (R1) The app must not rely
on the short message service for communication purposes; (R2) the app must imple-
ment pre-defined answer sets for efficient and error-free chat interaction; (R3) the app
must implement a chat channel for individual communication needs that complements
the scalable chatbot channel; (R4) the app must be able to access sensor data from the
smartphone or smartphone-connected devices.
By considering these four requirements, we built a first mock-up of a mobile app
and evaluated it with six behavioural health experts. As a result of that assessment, a
generic dashboard view was designed. Its purpose is to summarize key statistics of the
envisioned behavioural health interventions for self-monitoring purposes (e.g. steps
achieved per day, intervention progress or goals achieved). Based on this generic
486 T. Kowatsch et al.
mock-up, we implemented a native chat app for Android smartphones for the Mobi-
leCoach platform. Figures 1,2and 3show the graphical user interface of the chat app.
3 Significance to Research and Practice
The mobile chat app presented in this paper allows behavioral scientists and health
professionals to enrich self-report data with objective sensor data in the everyday life of
their clients. This paves the way for a better understanding of whether psychological/
self-report data and physiological/objective data are rather complement or alternative
measures, a recent research question in the field of NeuroIS [13].
Moreover, it is by far not clear how to design and frame chatbots for DHIs (e.g., as
an expert or a “patient like me”) and its interplay with a “physical”caregiver such that
they have a positive effect on the bond between caregiver and their clients and thus,
also on therapeutic outcomes [6]. In contrast to general purpose chat agents such as Siri
(Apple), Alexa (Amazon) or Cortana (Microsoft) and agents with a health focus such as
Florence (getflorence.co.uk), Molly (sense.ly) or Lark (lark.com), our chat app allows
full control of personal health data and a generic framework to manipulate the design
and communication style of chatbots in lab and field settings.
Finally and consistent with the MobileCoach platform, the chat app will be made
open source under the Apache 2.0 license to enable a community-driven design such
that research teams and (business) organizations interested in chat-based digital
coaching approaches do not have to start from scratch but can re-use, revise and
improve the existing code together with the MobileCoach platform.
Fig. 1. Dashboard view, indi-
vidual caregiver chat channel
PathMate and channel with
chatbot Anna
Fig. 2. Chatbot Anna, pre-
defined answer options and
sensor integration; steps are
tracked and used in the chat
Fig. 3. Chat channel with
the caregiver; the PathMate
study team of the children’s
hospital
Mobile Chat App for the Open Source Platform MobileCoach 487
4 Evaluation of the Artifact
Based on prior work demonstrating the acceptance of chat apps by adolescents [11], the
first test of the novel chat app was conducted in a children’s hospital in December 2016
with 11 patients (age
Mean
= 12.6 years, SD = 2.4; 8 girls), who participated in an
intervention for the treatment of obesity. The goal of this test was (1) to assess
enjoyment, ease of use, usefulness and the intention to use the app [10], and (2) to
identify and address major usability problems with the app [12] prior to a randomized
controlled trial (RCT), in which the efficacy of a chat-based six-month DHI for the
treatment of childhood obesity will be compared to a control group.
First, a chat-based DHI was collaboratively designed by computer scientists,
physicians, a psychotherapist, diet and sport experts. The patients were then asked to
select a chatbot of their liking, i.e. they could choose between a female and male
chatbot (Anna or Lukas). Then, they interacted with the bot for 10 min including
various chat-based photo, physical activity and quiz interactions. The patients were
observed during these interactions by a computer scientist and physician. Afterwards,
patients were asked to fill out a questionnaire to assess the app and to provide quali-
tative feedback on their experience with the app. Similar to prior work [10], we
assessed technology perceptions and behavioral intentions with seven-point Likert
scales anchored from strongly disagree (1) to strongly agree (7). As young patients
deserve special consideration, we used single-item measures to reduce the burden of
evaluation [3].
The descriptive statistics of the evaluation are shown in Table 1. Results indicate
that the chat app was perceived positive regarding all four constructs. A sign test
against the neutral Likert-scale median of 4 supports this observation. Finally, we
found no major usability problems based on the observations and the qualitative
feedback.
First findings of the aforementioned RCT show that new young patients assigned to
the chat-based DHI (N= 14) completed successfully approx. 61% of the daily inter-
vention tasks over the first two months. The efficacy of this DHI will be finally
measured by the Body Mass Index after the six-month RCT. We hypothesize that the
chat-based DHI is more effective as the chatbot can provide everyday support on
therapy goals and tasks, thus increasing therapy adherence compared to patients of the
treatment-as-usual control group without everyday support.
Table 1. Descriptive statistics and results of a sign test against the neutral value 4 on a 7-point
Likert-scale (N= 11). Note: Perceived ease of use (PEU), Perceived enjoyment (PEN), Perceived
usefulness (PU) and Intention to use (IU); Significance */**/*** p < .05 /.01 /.001
# Item Mean Median SD p-value
PEU I found the chat easy to use 6.7 7.0 0.7 ***
PEN I enjoyed chatting 6.2 7.0 1.5 **
PU Chatting with Lukas/Anna could motivate me
to accomplish my intervention tasks
5.9 6.0 1.1 *
IU I could imagine chatting daily that way 5.6 6.0 1.4 *
488 T. Kowatsch et al.
In our future work, we will test chat-based DHIs with older patient populations and
different therapies to assess the degree to which our findings can be generalized.
Acknowledgements. We would like to thank the CSS Insurance and the Swiss National Science
Foundation for their support through grants 159289 and 162724.
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Mobile Chat App for the Open Source Platform MobileCoach 489

Supplementary resources (2)

DESRIST 2017 MobileCoach Chat Client 1Slide-v1
Data
June 2017
Tobias Kowatsch · Dirk Volland · Chen-Hsuan Iris Shih · Dominik Rüegger · Dagmar l'Allemand
DESRIST 2017 MobileCoach Chat App Poster
Data
June 2017
Tobias Kowatsch · Dirk Volland · Chen-Hsuan Iris Shih · Dominik Rüegger · Dagmar l'Allemand
... The study prototype apps were developed with the open-source (Apache-2.0 license) software platform MobileCoach [66][67][68]. This platform was used for various other digital interventions, for example, to prevent depression and type-2 diabetes with a holistic lifestyle intervention [69], to reduce distress in cancer patients [70] or students [71], to follow a balanced diet [72], to change a specific personality trait [73], to reduce headaches [74], to improve hypertension management [75] or sleep [76] or type-1 diabetes management [77]. ...
... The apps could be operated on Android as well as iOS operating systems. The system ensures data privacy and security through password-protected access to the MobileCoach Designer and Server, inapp encryption, and SSL encryption for data transfers between the mobile apps, MobileCoach Designer, and MobileCoach Server [66][67][68]. ...
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... Conversational agents (CAs), also known as chatbots or digital assistants, are increasingly being applied in both clinical [48][49][50] and nonclinical [51][52][53] health care settings to support disease management and behavioral lifestyle interventions. CAs engage users in humanlike conversations [48,[54][55][56], enabling factual, relational, and emotional communication. This interactive style enhances engagement by establishing a working alliance between the users and the CAs [57,58], reflecting the collaborative relationship between shared treatment goals and tasks [59], which is crucial for treatment success in psychotherapy and counseling [60]. ...
... BalanceUP, developed for iOS (Apple Inc) and Android (Google LLC) platforms using MobileCoach [54,69,70], provides a chat-based interface for communicating with the CA ( Figure 1B). The communication between users and the server is encrypted. ...
View
... As an empirical case, we selected the open-source software platform MobileCoach 7 (Filler et al., 2015;Kowatsch et al., 2017) with two of its conversational IA instances that supports interdisciplinary teams of experts in their efforts to change people's health, lifestyle, and personality. Achieving such changes in the lives of individuals requires an interdisciplinary team of clinical or psychological experts, that work together. ...
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... The smartphone-based JITAI was developed with the latest version of the MobileCoach software platform (April 2024) [28,29] which has already been used for various health interventions [23,[30][31][32][33][34][35][36]. MobileCoach offers data collection capabilities (e.g., via self-reports and interaction logs) and the delivery of JITAIs with the help of a rule-based CA. ...
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Background: Dementia is projected to impact 152 million people by 2050, making it one of the most pressing global health challenges. The neurodegenerative process initiates well before clinical symptoms manifest, advancing from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) and ultimately to dementia. Despite the growing prevalence, awareness of dementia prevention is limited, and many individuals express a desire to cease living upon diagnosis. Lifestyle interventions can mitigate cognitive decline, but there is a need for effective, scalable approaches to deliver these interventions to older adults. Digital health interventions, such as app-based just-in-time adaptive interventions (JITAIs), offer a promising solution, but their application in cognitively impaired older populations remains underexplored. Objective: This study evaluated the feasibility, acceptability, and adherence to a smartphone-based JITAI delivered by a rule-based conversational agent (CA) among older adults with SCD or MCI. The primary focus was on adherence to the CA-initiated conversational turns (measured objectively via interaction logs), with secondary objectives including the perceptions of technology acceptance, the working alliance with the CA, self-reported adherence to the suggested health-promoting activity, and feedback for future improvements (through a questionnaire and short interview). Methods: This monocentric study investigated 15 participants (mean age = 70.3 years; 66.7% female and 33.3% male) with SCD (n=12) or MCI (n=3). Participants used the study app that delivered daily health-promoting activities through a CA over two weeks. Participants received notifications to engage in seven health-related activities, and adherence to the activity was self-reported. Post-intervention, participants rated their experience with the app and assessed their working alliance with the CA through the 6-item session alliance inventory. Data on smartphone usage, demographic information, and cognitive performance (via MoCA) were collected during a pre-intervention visit. Results: Participants rated the study app positively, especially regarding ease of use and a subset of the working alliance. Adherence to the CA-initiated conversational turn was measured at an average of 80.95% across 14 days. 27.14% of participants indicated as being vulnerable and 100% then responded with their state of receptivity, of which 82.65% were receptive to completing the activity, and 69.13% self-reporting adherence to the activity. There was no significant decline in adherence across the study period. Qualitative results support these findings and present two emerging themes: app enjoyment and enhancing engagement. Conclusions: This study demonstrates that smartphone-based JITAIs are feasible and generally well-accepted by older adults with SCD or MCI. However, the findings underscore the need for robust technological infrastructure and potential personal assistance to optimize adherence. Future interventions could benefit from integrating wearables to improve real-time engagement and accurately monitor adherence, ultimately supporting healthy aging and cognitive health in older populations.
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... mobile-coach.eu), an open-source software platform for behavioral health interventions and data collection purposes (Filler et al., 2015;Kowatsch et al., 2017). ...
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Full-text available
  • Sep 2016
Objective: To test the efficacy of a combined web- and text messaging-based intervention to reduce problem drinking in young people compared to assessment only. Method: Two-arm, parallel-group, cluster-randomized controlled trial with assessments at baseline and 6-month follow up. The automated intervention included online feedback, based on the social norms approach, and individually tailored text messages addressing social norms, outcome expectations, motivation, self-efficacy, and planning processes, provided over 3 months. The main outcome criterion was the prevalence of risky single-occasion drinking (RSOD, defined as drinking at least 5 standard drinks on a single occasion in men and 4 in women) in the past 30 days. Irrespective of alcohol consumption, 1,355 students from 80 Swiss vocational and upper secondary school classes, all of whom owned a mobile phone, were invited to participate in the study. Of these, 1,041 (76.8%) students participated in the study. Results: Based on intention-to-treat analyses, RSOD prevalence decreased by 5.9% in the intervention group and increased by 2.6% in the control group, relative to that of baseline assessment (odds ratio [OR] = 0.62, 95% confidence interval [CI] = 0.44-0.87). No significant group differences were observed for the following secondary outcomes: RSOD frequency, quantity of alcohol consumed, estimated peak blood alcohol concentration, and overestimation of peer drinking norms. Conclusions: The intervention program reduced RSOD, which is a major indicator of problem drinking in young people, effectively. (PsycINFO Database Record
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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
Article
Full-text available
  • Nov 2014
  • BMC PUBLIC HEALTH
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 an integrated smoking cessation and alcohol intervention by comparing it to a smoking cessation only intervention for young people, delivered via the Internet and mobile phone.
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Efficacy of a web- and text messaging-based intervention to reduce problem drinking in young people: Study protocol of a cluster-randomised controlled trial
Article
Full-text available
  • Aug 2014
  • BMC PUBLIC HEALTH
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 planned study is to test the efficacy of a combined web- and text messaging-based intervention 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. Trial registration Current Controlled Trials ISRCTN59944705.
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The workforce for health in a globalized context – global shortages and international migration
Article
Full-text available
  • Feb 2014
The 'crisis in human resources' in the health sector has been described as one of the most pressing global health issues of our time. The World Health Organization (WHO) estimates that the world faces a global shortage of almost 4.3 million doctors, midwives, nurses, and other healthcare professionals. A global undersupply of these threatens the quality and sustainability of health systems worldwide. This undersupply is concurrent with globalization and the resulting liberalization of markets, which allow health workers to offer their services in countries other than those of their origin. The opportunities of health workers to seek employment abroad has led to a complex migration pattern, characterized by a flow of health professionals from low- to high-income countries. This global migration pattern has sparked a broad international debate about the consequences for health systems worldwide, including questions about sustainability, justice, and global social accountabilities. This article provides a review of this phenomenon and gives an overview of the current scope of health workforce migration patterns. It further focuses on the scientific discourse regarding health workforce migration and its effects on both high- and low-income countries in an interdependent world. The article also reviews the internal and external factors that fuel health worker migration and illustrates how health workforce migration is a classic global health issue of our time. Accordingly, it elaborates on the international community's approach to solving the workforce crisis, focusing in particular on the WHO Code of Practice, established in 2010.
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A review of life expectancy and infant mortality estimations for Australian Aboriginal people
Article
Full-text available
  • Jan 2014
  • BMC PUBLIC HEALTH
Significant variation exists in published Aboriginal mortality and life expectancy (LE) estimates due to differing and evolving methodologies required to correct for inadequate recording of Aboriginality in death data, under-counting of Aboriginal people in population censuses, and unexplained growth in the Aboriginal population attributed to changes in the propensity of individuals to identify as Aboriginal at population censuses. The objective of this paper is to analyse variation in reported Australian Aboriginal mortality in terms of LE and infant mortality rates (IMR), compared with all Australians. Published data for Aboriginal LE and IMR were obtained and analysed for data quality and method of estimation. Trends in reported LE and IMR estimates were assessed and compared with those in the entire Australian population. LE estimates derived from different methodologies vary by as much as 7.2 years for the same comparison period. Indirect methods for estimating Aboriginal LE have produced LE estimates sensitive to small changes in underlying assumptions, some of which are subject to circular reasoning. Most indirect methods appear to under-estimate Aboriginal LE. Estimated LE gaps between Aboriginal people and the overall Australian population have varied between 11 and 20 years. Latest mortality estimates, based on linking census and death data, are likely to over-estimate Aboriginal LE. Temporal LE changes by each methodology indicate that Aboriginal LE has improved at rates similar to the Australian population overall. Consequently the gap in LE between Aboriginal people and the total Australian population appears to be unchanged since the early 1980s, and at the end of the first decade of the 21st century remains at least 11¿12 years. In contrast, focussing on the 1990¿2010 period Aboriginal IMR declined steeply over 2001¿08, from more than 12 to around 8 deaths per 1,000 live births, the same level as Australia overall in 1993¿95. The IMR gap between Aboriginal people and the total Australian population, while still unacceptable, has declined considerably, from over 8 before 2000 to around 4 per 1,000 live births by 2008. Regardless of estimation method used, mortality and LE gaps between Aboriginal and non-Aboriginal people are substantial, but remain difficult to estimate accurately.
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Using an Attribute-Based Decision Support System for User-Customized Products Online: An Experimental Investigation.
Article
Full-text available
  • Jan 2006
In the decision support systems literature, most studies have concentrated on the direct effects of DSS use and design on decision outcomes and user performance in the workplace. Fewer DSS studies have integrated decision process variables, such as user beliefs and attitudes, in their models. In this paper, we examine the mediating role of decision process variables in the use of an online customer DSS. We do so through an experimental study of an alternative-based and an attribute-based DSS for product customization by online customers. Using cognitive fit and flow theories, we develop a theoretical model with four mediating decision process variables (perceived usefulness, perceived ease of use, perceived enjoyment, and perceived control) and two of their antecedents: interface design (attribute-based versus alternative-based) and task complexity (choice set size). Our results show that the impact of DSS interface design on behavioral intentions is fully mediated by perceived usefulness and perceived enjoyment, although not by perceived control. Specifically, we verify that users of an attribute-based DSS express higher perceived usefulness and perceived enjoyment than users of an alternative-based one. In addition, we find that task complexity has an interesting relationship with usefulness and enjoyment, both of which follow an inverted U-shaped curve as choice set size increases. Finally, we find that for users of the alternative-based DSS, perceived ease of use and perceived control decrease as task complexity increases. However, the attribute-based DSS alleviates that decline for both variables. Among other contributions, our results indicate the importance of including decision process variables when studying DSS as well as the complex effect of task complexity on those variables. Our study also provides some important guidelines for online companies that provide customer DSS on their websites, especially the danger of providing too many product choice options that can overwhelm customers and harm their shopping experience.
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NeuroIS-Alternative or Complement to Existing Methods? Illustrating the Holistic Effects of Neuroscience and Self-Reported Data in the Context of Technostress Research
Article
  • Oct 2014
  • J ASSOC INF SYST
Recent research has made a strong case for the importance of NeuroIS methods for IS research. It has suggested that NeuroIS contributes to an improved explanation and prediction of IS phenomena. Yet, such research is unclear on the source of this improvement; while some studies indicate that NeuroIS constitutes an alternative to psychometrics, implying that the two methods assess the same dimension of an underlying IS construct, other studies indicate that NeuroIS constitutes a complement to psychometrics, implying that the two methods assess different dimensions of an IS construct. To clarify the role of NeuroIS in IS research and its contribution to IS research, in this study, we examine whether NeuroIS and psychometrics/psychological methods constitute alternatives or complements. We conduct this examination in the context of technostress, an emerging IS phenomenon to which both methods are relevant. We use the triangulation approach to explore the relationship between physiological and psychological/self-reported data. Using this approach, we argue that both kinds of data tap into different aspects of technostress and that, together, they can yield a more complete or holistic understanding of the impact of technostress on a theoretically-related outcome, rendering them complements. Then, we test this proposition empirically by probing the correlation between a psychological and a physiological measure of technostress in combination with an examination of their incremental validity in explaining performance on a computer-based task. The results show that the physiological stress measure (salivary alpha-amylase) explains and predicts variance in performance on the computer-based task over and above the prediction afforded by the self-reported stress measure. We conclude that NeuroIS is a critical complement to IS research. © 2014, Association for Information Systems. All rights reserved.
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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
Article
  • Jun 2015
Effective and efficient behavioral interventions are important and of high interest today. Due to shortcomings of related approaches, we introduce MobileCoach (mobile-coach.eu) as novel open source behavioral intervention platform. With its modular architecture, its rule-based engine that monitors behavioral states and triggers state transitions, we assume MobileCoach to lay a fruitful ground for evidence-based, scalable and low-cost behavioral interventions in various application domains. The code basis is made open source and thus, MobileCoach can be used and revised not only by interdisciplinary research teams but also by public bodies or business organizations without any legal constraints. Technical details of the platform are presented as well as preliminary empirical findings regarding the acceptance of one particular intervention in the public health context. Future work will integrate Internet of Things services that sense and process data streams in a way that MobileCoach interventions can be further tailored to the needs and characteristics of individual participants.
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The Digital Transformation of Healthcare: Current Status and the Road Ahead
Article
  • Dec 2010
As the United States expends extraordinary efforts toward the digitization of its health-care system, and as policy makers across the globe look to information technology (IT) as a means of making health-care systems safer, more affordable, and more accessible, a rare and remarkable opportunity has emerged for the information systems research community to leverage its in-depth knowledge to both advance theory and influence practice and policy. Although health IT (HIT) has tremendous potential to improve quality and reduce costs in healthcare, significant challenges need to be overcome to fully realize this potential. In this commentary, we survey the landscape of existing studies on HIT to provide an overview of the current status of HIT research. We then identify three major areas that warrant further research: (1) HIT design, implementation, and meaningful use; (2) measurement and quantification of HIT payoff and impact; and (3) extending the traditional realm of HIT. We discuss specific research questions in each domain and suggest appropriate methods to approach them. We encourage information systems scholars to become active participants in the global discourse on health-care transformation through IT.
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