Scale-IT-up 2021 Abstracts

Area 1 - Scale-IT-up

Full Papers
Paper Nr: 1

Face(book)ing the Truth: Initial Lessons Learned using Facebook Advertisements for the Chatbot-delivered Elena+ Care for COVID-19 Intervention


Joseph Ollier, Prabhakaran Santhanam and Tobias Kowatsch

Abstract: Utilizing social media platforms to recruit participants for digital health interventions is becoming increasingly popular due to its ability to directly track advertising spend, number of app downloads and other metrics transparently. The following paper concerns the initial tests completed on the Facebook Ad Manager platform for the chatbot-delivered digital health intervention Elena+ Care for COVID-19. Eleven advertisements were run in the UK and Ireland during August/September 2020, with resulting downloads, post (i.e. advert) reactions, post shares and other advertisement engagement metrics tracked. Key findings from our advertising campaigns highlight that: (i) static images with text function better than carousel of images, (ii) Android users download and exhibit greater engagement behaviors than iOS users, and (iii) middle-aged and older women have the highest number of downloads and the most engaged behaviors (i.e. reacting to posts, sharing posts etc.). Lessons learned are discussed considering how other designers of digital health interventions may benefit and learn from our results when trialing and running their own ad campaigns. It is hoped that such discussions will be beneficial to other health practitioners seeking to scale-up their digital health interventions widely and reach individuals in need.

Paper Nr: 2

With a Little Help from My Conversational Agent: Towards a Voice Assistant for Improved Patient Compliance and Medication Therapy Safety


Jan T. Brinke, Christian Fitte, Eduard Anton, Pascal Meier and Frank Teuteberg

Abstract: The chronically ill and the elderly often need to take several drugs, which increases the complexity of medication management. This frequently results in a decrease in patient compliance and raises the risks of their drug therapy. To support patients in medication management, we developed a multimodal assistant that includes a conversational agent supplied with data from a database managed by healthcare professionals via a web service. The developed artifact analyzes medication plans, identifies adverse drug reactions and side effects, and reminds patients to take their medication correctly and on time. Applying the design science research paradigm, we systematically identified 16 issues, derived eight meta-requirements, and elaborated three design principles. Based on this, the artifact was implemented and evaluated by three experienced pharmacists, who highlighted the usefulness of the solution and provided feedback for further improvements. Finally, we present an evaluation concept for potential users and discuss the implications of the medication assistant. Overall, the medical assistant comprises valuable functionalities to support patients, and it increases medication therapy safety and patients’ compliance.

Paper Nr: 4

To What Scale Are Conversational Agents Used by Top-funded Companies Offering Digital Mental Health Services for Depression?


Aishah Alattas, Gisbert W. Teepe, Konstantin Leidenberger, Elgar Fleisch, Lorraine T. Car, Alicia Salamanca-Sanabria and Tobias Kowatsch

Abstract: There is strong support in the literature for the use of conversational agents (CAs) in digital mental healthcare along with a recent increase in funding within digital mental health, indicating the fast growth of the industry. However, it is unknown to what extent CAs are leveraged in these digital interventions for depression. The aim of this study is to therefore explore the scale of CA use in top-funded digital mental health companies targeting depression and describe what purposes they are used for. Companies were identified through searching venture capital databases and screened for the presence and purpose of use of CAs in their interventions for depression. It was found that only 7 out of the 29 top-funded companies used a CA in their intervention. The most common purpose of CA use was education, followed by assistance, training and onboarding. None of the interventions used CAs for elderly assistance, diagnosis or prevention. These results indicate that the industry uptake of CAs in digital interventions for depression within top-funded companies is low. Future work can look into using CAs in areas which this analysis found they are not currently used such as in tailoring to different target populations and in preventing depression.

Short Papers
Paper Nr: 3

Are Conversational Agents Used at Scale by Companies Offering Digital Health Services for the Management and Prevention of Diabetes?


Roman Keller, Jiali Yao, Gisbert W. Teepe, Sven Hartmann, Kim-Morgaine Lohse, Florian von Wangenheim, Falk Müller-Riemenschneider, Jacqueline L. Mair and Tobias Kowatsch

Abstract: Successful interventions to prevent and manage type 2 diabetes rely on long-term, day-to-day decisions which take place outside of clinical settings. In this context, human resources are difficult to scale up, and leveraging Conversational agents (CAs) could be one way to scale up healthcare to tackle the emerging epidemic of type 2 diabetes. The objective of this paper is to assess the degree to which CAs are employed by top-funded digital health companies that target the prevention and management of type 2 diabetes. Companies were identified via two venture capital databases, i.e. Crunchbase Pro and Pitchbook. Two independent reviewers screened results and the final list of companies was validated and revised by three independent digital health experts. The companies’ digital services (usually mobile applications) were accessed and reviewed for the utilisation of CAs. To better understand the purpose of identified CAs, relevant publications were identified via PubMed, Google Scholar, ACM Digital Library and on the companies’ website. Nine out of 15 companies’ digital services were accessible to the authors and only in one case a CA was employed. The uptake of CAs by top-funded digital health companies targeting type-2 diabetes is still low.

Paper Nr: 5

Proposed Use of a Conversational Agent for Patient Empowerment


Marco Alfano, John Kellett, Biagio Lenzitti and Markus Helfert

Abstract: Empowerment is a process through which people acquire the necessary knowledge and self-awareness to understand their conditions and treatment options, make informed choices and self-manage their health conditions in daily life, in collaboration with medical professionals. Conversational Agents in healthcare could play an important role in the process of empowering a person but, so far, they have been seldom been used for this purpose. This paper presents the basic principles and preliminary implementation of a conversational health agent for patient empowerment. It dialogues with the user in a “natural” way, collects health data from heterogeneous sources and provides the user with specific and relevant information. This allows a person/patient to create his/her own opinion on health matters in the most complete and objective way, and, therefore, it facilitates the empowerment process.

Paper Nr: 6

The Role of Text Analytics in Healthcare: A Review of Recent Developments and Applications


Mahmoud Elbattah, Émilien Arnaud, Maxime Gignon and Gilles Dequen

Abstract: The implementation of Data Analytics has achieved a significant momentum across a very wide range of domains. Part of that progress is directly linked to the implementation of Text Analytics solutions. Organisations increasingly seek to harness the power of Text Analytics to automate the process of gleaning insights from unstructured textual data. In this respect, this study aims to provide a meeting point for discussing the state-of-the-art applications of Text Analytics in the healthcare domain in particular. It is aimed to explore how healthcare providers could make use of Text Analytics for different purposes and contexts. To this end, the study reviews key studies published over the past 6 years in two major digital libraries including IEEE Xplore, and ScienceDirect. In general, the study provides a selective review that spans a broad spectrum of applications and use cases in healthcare. Further aspects are also discussed, which could help reinforce the utilisation of Text Analytics in the healthcare arena.