Enabling elderly cancer patients to become more mobile: Analyzing the post-implementation acceptance and usability of the Hospitality App at elderly patients visiting the Gastro-Intestinal Oncology Center Amsterdam (GIO

Enabling elderly cancer patients to become more mobile

Analyzing the post-implementation acceptance and usability of the Hospitality App at

elderly patients visiting the Gastro-Intestinal Oncology Center Amsterdam (GIOCA)

Gaby Anne Wildenbos

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ENABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE – GABY ANNE WILDENBOS 3

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Analyzing the post-implementation acceptance and usability of the Hospitality App at

elderly patients visiting the Gastro-Intestinal Oncology Center Amsterdam (GIOCA)

Student: G.A. Wildenbos MA.

Department of Medical Informatics

Academic Medical Center / University of Amsterdam Meibergdreef 15

1105 AZ Amsterdam Z.O., The Netherlands PA2-118

e-mail: g.a.wildenbos@amc.uva.nl

Mentor I: L.W.P. Dusseljee-Peute PhD. Department of Medical Informatics

Academic Medical Center / University of Amsterdam Meibergdreef 15

1105 AZ Amsterdam Z.O., The Netherlands J1b-115-2

e-mail: l.w.peute@amc.uva.nl

Mentor II: M.P. Schijven MD. PhD.

Department of Surgery / Academic Medical Center University of Amsterdam

Meibergdreef 15

1105 AZ Amsterdam Z.O., The Netherlands G4-133-1

e-mail: m.p.schijven@amc.uva.nl Tutor: M.W.M. Jaspers Prof. Dr.

Department of Medical Informatics

Academic Medical Center / University of Amsterdam Meibergdreef 15

1105 AZ Amsterdam Z.O., The Netherlands J1b-114-2

e-mail: m.w.jaspers@amc.uva.nl Study site: Academic Medical Center

- Department of Medical Informatics - Department of Surgery

- Gastro Intestinal Oncologic Center Amsterdam (GIOCA) - Program EVA

Duration: November 2013 – July 2014 Date of submission: 17th of July 2014

Table of Contents

INTRODUCTION

5

R

EFERENCES

7

ACCEPTANCE

8

E

NABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE

.

I

NHIBITORS AND ENABLERS REGARDING THE ACCEPTANCE OF M

H

EALTH APPS BY ELDERLY PATIENTS

:

A POST

-IMPLEMENTATION CASE STUDY OF THE

H

OSPITALITY

A

PP AT THE

G

ASTRO

-I

NTESTINAL

O

NCOLOGY

C

ENTER

A

MSTERDAM

(GIOCA)

9

A

BSTRACT

9

I

NTRODUCTION

10

B

ACKGROUND ON THE

H

OSPITALITY

A

PP

11

M

ETHODS

14

R

ESULTS

18

D

ISCUSSION AND CONCLUSION

24

A

CKNOWLEDGEMENTS

27

R

EFERENCES

28

USABILITY

30

E

VALUATING THE EASE OF USE OF AN M

H

EALTH APP FOR ELDERLY PATIENTS

:

A USABILITY STUDY

31

A

BSTRACT

31

I

NTRODUCTION

32

M

ETHODS

33

R

ESULTS

35

D

ISCUSSION AND CONCLUSION

38

A

CKNOWLEDGEMENTS

40

R

EFERENCES

41

DISCUSSION & CONCLUSION

42

B

ACKGROUND

43

S

UMMARY OF FINDINGS

43

C

ONCLUSION

43

R

EFERENCES

45

DUTCH SUMMARY

46

S

AMENVATTING

47

ACKNOWLEDGEMENTS

49

A

PPENDIX

1

–

S

EARCH STRATEGY LITERATURE REVIEW ON

‘

NON

-

INVASIVE METHODS ON

MEASURING THE STRESS LEVEL OF CANCER PATIENTS

’

50

A

PPENDIX

2

–

F

ACTORS INFLUENCING ACCEPTANCE OF TECHNOLOGY FOR AGING IN PLACE

51

A

PPENDIX

3

–

I

NTERVIEW CARDS

52

A

PPENDIX

4

–

P

OST

-

IMPLEMENTATION CODING TREE ACCEPTANCE

HA

AND PROCEDURAL

SERVICE M

H

EALTH APPS

56

A

PPENDIX

5

–

M

AIN SCREENS OF THE

H

OSPITALITY

A

PP

64

A

PPENDIX

6

–

U

SABILITY ASSIGNMENTS MASTER

M

EDICAL

I

NFORMATICS STUDENTS

65

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ENABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE – GABY ANNE WILDENBOS 5

Introduction

The elderly population is rising: 38% of the total European population was over 50 years old in 2013, of which 18% was over 65 years old [1]. In addition, there is an increase in the number of chronically ill elderly [2]. The growing number of elderly patients causes a rise in healthcare costs [3]. On top of that, in 2011 more than 25% of the Dutch elderly people above 65 years old was living alone [4]. With this growth of the elderly patient population and the pressure to lower the expenditures within healthcare, it is expected that the percentage of elderly with a disease living alone will increase. These elderly often face the challenge of disease management due to one or more (chronic) conditions [5]. At present patients can benefit from mobile health (mHealth) solutions offered through smartphones assisting them in managing their health condition. Since elderly are novice smartphone users, it is unclear if elderly patients will embrace these benefits of mHealth.

The developments regarding modern smartphone features, access and usage paves the way for mHealth. MHealth is a broad term used in many varieties, ranging from examples such as ‘remote patient monitoring’ to hardware examples as ‘smart watches’ to measure one’s heart rate [6]–[8]. This thesis combines the definitions of mHealth given by the World Health Organization and the National Institutes of Health Consensus Group: mHealth is an area of electronic health (eHealth) and it is the provision as well as usage of health services and information via mobile and wireless technologies to improve health outcomes, healthcare services and health research [9], [10]. This thesis therein focuses on consumer mHealth apps and more specifically consumer apps that offer a procedural service: software programs and/or accessories of smartphones or other mobile devices that aim to support personal health management by improving healthcare processes, such as appointment attendance [11].

The interest in mHealth apps is growing and this is becoming a booming industry; in 2012 there were more than 13.000 mHealth apps available for consumers in the Apple app store [12]. Now that mHealth apps developments have been set into motion, a lot is said on the opportunities of mHealth apps with regard to the global challenges that the healthcare industry faces: making healthcare more accessible, faster, better and cheaper [7], [13]. Some examples from respectively 2011 and 2013 are [6], [14]:

“There’s 5.6 billion people using wireless today in the world. To put that in a health care context, that’s more people using cell phones than toothbrushes.”

- Paul Jacobs, Ph.D., CEO, Qualcomm

“We want to connect healthcare professional experiences on mobile with patient experiences on mobile and the first step is to allow doctors to prescribe educational materials to their patients from app to app.”

- Todd Zander, VP of Mobile and Emerging Media, WebMD

These quotes indicate that not solely healthcare institutions take part in mHealth apps; a broad variety of stakeholders are involved. Stakeholders that play a part in mHealth apps include – amongst others – patients, healthcare professionals, healthcare institutions, technology and telecommunication service providers, researchers, policy makers and entrepreneurs [7], [8].

Whereas traditional healthcare interventions are based upon theory and evidence-based research, a weakness of mHealth and its apps is the lack of theory to guide and evaluate the mHealth innovations to drive them forward [15], [16]. On the other hand, the current investments in mHealth are extensive: in 2013, 1.9 billion dollars was spend on digital health funding in United States of America (USA), growing 39% over the previous year [17]. 119 million of that funding was spend on healthcare consumer engagement [17]. Consequently a considerable risk is created: a vast amount of effort, time and money is spend on mHealth apps for the greater good – more accessible, faster, better and cheaper healthcare – without knowing how to reach that spot on the horizon. To fully utilize and grasp the benefits of mHealth apps it is important for all stakeholders involved to look beyond the ideal utopia of mHealth apps and to explore how they can become fruitful in healthcare by using theory to drive the development and evaluations of mHealth apps interventions.

For this reason this thesis is of importance, since it reports on a evaluation of a mHealth app case study supported by a theoretical framework of technology acceptance and usability – both important for the adoption of mHealth [18], [19]. The case study that is analyzed is the ‘Hospitality App’ (HA), an app for elderly patients, aged 50 years and older, which was evaluated after its first implementation at the Gastro-Intestinal Oncology Center Amsterdam (GIOCA), an outpatient oncology

clinic of the Amsterdam Medical Center (AMC). The HA intended to assist the elderly cancer patients in managing their hospital visit by offering them: information on their appointment schedule, a taxi transport service to attend the hospital visit in time and in-hospital personal navigation and mental support by a medical student. Because of the functionalities and services the HA offers, it is characterized as a procedural mHealth app. The prior aim of this study was to evaluate the effectiveness of the HA, including a usability study amongst the users of the app. Just after its implementation, it became apparent that few patients started to use the app and it became impossible to gain sufficient data to evaluate the app on effectiveness and usability with its users. Therefore, the focus of the study shifted towards analyzing the acceptance of the functionalities and services of the HA amongst the elderly cancer patients of GIOCA. Since ‘ease of use’ is an important factor of technology acceptance [18], [19], the usability of the HA was still assessed as well. However, due to a deficiency of patients using the HA within the set time period of the study to gather data (February 2014 – May 2014) the usability study was performed by master Medical Informatics students and experts on industrial design engineering.

The first aim of this research is to gain insights on the enablers and inhibitors related to the acceptance of the functionalities and services of the HA. The second aim is to investigate the ease of use of the HA by assessing usability issues that the elderly cancer patients could encounter while using the HA. This study is valuable for stakeholders involved with the further development and implementation of the HA, including the project team managing the HA, developers and designers of the HA, the outpatient clinic of the AMC and possible other healthcare institutions that might want to implement the HA. Since the study took place within an oncology setting and assessed a procedural mHealth app, it identifies insights specifically applicable to such a setting and such apps. These insights are of value to stakeholders concerned with the development and implementation of apps offering a service to facilitate elderly’s procedural and personal health management within a setting of severe precarious diseases.

The research questions that are addressed in this thesis are:

Question 1: What are the enablers and inhibitors related to the acceptance of the

offered procedural functionalities and services of the HA by elderly cancer patients after its first implementation at GIOCA?

Question 2: What are the usability issues elderly patients could encounter using the HA? Question 3: How does expert-based feedback of skilled industrial design engineers assess the

usability of the HA compared to standard rigorous usability evaluation methods performed by novice usability testers?

Regarding the structure of this thesis, Chapter 2 describes the study regarding the acceptance of the functionalities and services of HA and aims to answer research question 1. Chapter 3 is dedicated to a usability study performed on the HA and aims to answer research questions 2 and 3.

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ENABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE – GABY ANNE WILDENBOS 7

References

[1] European Commission Eurostat, “Population statistics Europe.” [Online]. Available: http://epp.eurostat.ec.europa.eu/portal/page/portal/population/data/main_tables . [Accessed: 24-May-2014].

[2] Rijksinstituut voor Volksgezondheid en Milieu, “Een gezonder Nederland,” 2014. [Online]. Available: http://www.rivm.nl/dsresource?objectid=rivmp:251654&type=org&disposition=inline. [Accessed: 11-Jul-2014].

[3] European Digital Agenda Scoreboard, “Life online,” 2014. [Online]. Available: http://ec.europa.eu/digital-agenda/sites/digital-agenda/files/scoreboard_life_online.pdf . [Accessed: 11-Jul-2014].

[4] ITpreneurs Argos Zorgroep Seniorenwelzijn, “Een iPad-app voor senioren. Onderzoeksrapport OpStap,” 2014. [Online]. Available: http://www.itpreneurs.nl/docs/publicaties/20120615_opstap_rapport.pdf. [Accessed: 11-Jul-2014].

[5] R. George Demiris, PhD; Ardith Z. Doorenbos, PhD, RN; and Cara Towle, MSN, “Ethical Considerations Regarding the Use of Technology for Older Adults,” Res. Gerontol. Nurs., vol. 2, no. 2, pp. 128–137, 2009.

[6] B. Dolan, “31 Memorable Mobile Health Quotes from 2013.” [Online]. Available: http://mobihealthnews.com/26234/31-memorable-mobile-health-quotes-from-2013/ . [Accessed: 28-May-2014].

[7] PriceWaterhouseCoopers, “Emerging mHealth: Paths for growth,” 2012.

[8] Research2Guidance The App Market Specialist, “mHealth App Developer Economics,” 2014. [Online]. Available: www.mHealthEconomics.com. [Accessed: 11-Jul-2014].

[9] Y.-M. Schoenberger, J. Phillips, M. O. Mohiuddin, P. McNees, and I. Scarinci, “Acceptability of Delivering and Accessing Health Information Through Text Messaging Among Community Health Advisors,” JMIR

mhealth uhealth, vol. 1, no. 2, p. e22, Sep. 2013.

[10] World Health Organization, “New horizons for health through mobile technologies.” [Online]. Available: http://www.who.int/goe/publications/goe_mhealth_web.pdf.

[11] X. Guo, Y. Sun, N. Wang, Z. Peng, and Z. Yan, “The dark side of elderly acceptance of preventive mobile health services in China,” Electron. Mark., vol. 23, no. 1, pp. 49–61, Dec. 2012.

[12] J. Burgess, “The iPhone Moment, the Apple Brand and the creative consumer!: From ‘hackability and usability’ to cultural generativity,” in Studying Mobile Media: Cultural Technologies, Mobile

Communication, and the iPhone, J. Hjorth, Larissa, Richardson, Ingrid, & Burgess, Ed. New York,

London: Routledge, 2012, pp. 28–42.

[13] Nictiz, “Summary eHealth Monitor 2013,” 2014. [Online]. Available: http://www.nictiz.nl/page/Publicaties/Summary-eHealth-monitor. [Accessed: 11-Jul-2014].

[14] C. Torgan, “The 2011 mHealth Summit Summed Up in 5 Quotes, Words and Companies, Plus 1 Jacket.” [Online]. Available: http://www.caroltorgan.com/2011-mhealth-summit-summed-up/ . [Accessed: 28-May-2014].

[15] M. Arief, N. Thi, T. Hai, and K. Saranto, “Barriers to and advantages of e _{‐ health from the perspective of} elderly people!: A literature review,” vol. 5, pp. 50–56, 2013.

[16] C. Armstrong, “Mobile Health Research Highlight: Theory-driven mHealth.” [Online]. Available: http://www.t2.health.mil/blogs/mobile-health/mobile-health-research-highlight-theory-driven-mhealth. [Accessed: 28-Apr-2014].

[17] “Digital Health Funding 2013 - Year in a review by Rockhealth,” 2014. [Online]. Available: http://www.slideshare.net/RockHealth/digital-health-funding-2013-year-in-review-by-rockhealth . [Accessed: 11-Jul-2011].

[18] E. Kaasinen, “User acceptance of mobile services - value, ease of use and ease of adoption,” VTT Publ.

566.

[19] M. W. M. Jaspers, “A comparison of usability methods for testing interactive health technologies: methodological aspects and empirical evidence.,” Int. J. Med. Inform., vol. 78, no. 5, pp. 340–53, May 2009.

Acceptance

“I am not that in need of help (...) I don’t need it at the moment. But I can

imagine that it [the HA] can be a solution for people who do not have

partner (...) But it could be that in the future it would suit me, then I might

use it (...) At this moment, you don’t know what to expect [regarding the

cancer treatment] really”

- Patient, 58 years old

“ Well, I would be able to use it [a

smartphone], but most people can’t

deal with them (...) People can’t

live without it anymore. If people

are talking [to each other] and the

phone bleeps then the phone is

more important”

– Patient, 59 years old

“ I like it to have everything compiled

together. Then you can always recall

[appointments], without having to dig into

a pile of papers thinking ‘where did I

leave it?’ So, the ease of having access

to information you need [on a

smartphone device is an advantage]”

- Patient, 61 years old

“I don’t like technology that finds

progress so quickly. Today you have

this [smart] phone and tomorrow that

will be old already; then they will have

something new again”

- Patient, 83 years old

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ENABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE – GABY ANNE WILDENBOS 9

Enabling elderly cancer patients to become more mobile. Inhibitors

and enablers regarding the acceptance of mHealth apps by elderly

patients: a post-implementation case study of the Hospitality App at

the Gastro-Intestinal Oncology Center Amsterdam (GIOCA)

Abstract

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Background: The significance of smartphone applications’ usefulness for patients is increasingly

being recognized, especially regarding personal health management. However, there is little understanding of the challenges and barriers of elderly patients in accepting such apps. An example is the Hospitality app (HA), which intends to assist elderly patients, aged 50 years and older, in managing their hospital visit by offering them information on their appointment schedule, a taxi transport service and personal in-hospital navigation and mental support by a medical student.

Objective: This study aimed to assess the factors influencing the intention of elderly to use the HA

and to identify these factors in terms of ‘inhibitors’ or ‘enablers’ to the acceptance of procedural services offered via a smartphone app, within the context of individual assistance to manage one’s personal health condition.

Methods: Factors influencing technology acceptance by older adults, derived from a systematic

review, provided a theoretical framework for conducting semi-structured interviews. The interviews focused on the HA’s functionalities regarding appointment information and its provided services of taxi transport and personal in-hospital support. For interviewees unfamiliar to the HA, the focus was on conceivable apps offering a procedural service in relation to personal health management, exemplified by means of the HA. Fifty-seven elderly patients at an oncology outpatient clinic, the implementation setting of the HA, were transcribed, coded and analyzed.

Results: Four main inhibitors for the acceptance of the HA were lack of perceived need for the

provided functionalities and services of the application, the feeling of stigmatization of ‘elderly’ by patients aged 50 – 80 years old, concerns regarding mobile devices resulting in a low smartphone ownership of patients aged 80+ and an experienced obtrusive push regarding smartphone use. In relation to lack of perceived need, alternatives for the HA functionality and its provided services were mentioned for managing hospital appointments and traveling to and navigation within the hospital. Personal support by caregivers when visiting the oncology center was preferred. Main enablers of the acceptance of the HA were the awareness of personal in-hospital navigation guidance by a medical student and the usefulness of the HA if patients visits’ would become more frequent in a later stage of the oncology treatment. These enablers could enhance the perceived need for the HA.

Conclusion: Stakeholders involved with the development and implementation of apps offering a

procedural service in relation to personal health management for elderly should take into account that perceived need is an important aspect of today’s elderly acceptance of such apps. Type of illness and age are stigmatizing factors negatively influencing this perceived need. Perceived need by elderly for assistance in traveling to the hospital and in-hospital personal guidance is influenced by their expected course of disease and their preference for caregivers support during patient visits. Perceived need on these two aspects is positively influenced by the notion of increased physical burden during the course of the disease.

Keywords: Aging population – Technology Acceptance – Stigmatization – mHealth – Elderly –

Introduction

The usage of mobile technologies is becoming ubiquitous and changes the way patients are able to communicate with and utilize healthcare services [1]. Use of mobile healthcare applications, mHealth apps, is rapidly expanding amongst patients with experience in using mobile technologies and is considered to become essential for patients’ personal health management [2]–[8]. MHealth is defined as an area of electronic health (eHealth) and the provision as well as usage of health services and information via mobile and wireless devices to improve health outcomes, healthcare services and health research [5],[6]. The aging population has become a global issue and the number of chronically ill elderly is increasing [1], [9]–[11]. The growing number of elderly patients cause a rise in healthcare costs and the expansion of this patient population will outgrow the people at hand to take care of them in time [1], [10], [12]. Explorative studies describe the potential of mHealth apps’ functionalities and services in offering solutions to healthcare problems related to the expanding (chronically ill) elderly patient population [1]–[8], [13], [14]. On top of that a report of December 2013 by Startup Health and the American Association of Retired Persons (AARP) informs that digital health startups targeting the aging population, 50 years old and over, increased their funding from $413 million in 2010 to $928 million in 2013 [15]. Benefits and examples of mHealth apps for elderly include a decline of elderly hospitalizations by means of apps for fall-risks assessments, increase in self-management via activity trackers and decreased burden on the caregivers through apps offering medication reminders and social networking possibilities [1], [16], [17]. The focus of this study is on consumer mHealth apps for elderly and more specifically consumer apps that offer a procedural service: software programs and/or accessories of smartphones or other mobile devices that aim to support personal health management by improving healthcare processes, such as appointment attendance [18].

Most pressing dilemmas within this fast pace of app developments for elderly include the risk of fragmentation and the need to establish cost-effective mHealth apps while engaging elderly patients to integrate these apps’ services into their health management process [19]. Today’s elderly are novice smartphone users, not yet familiar with mHealth apps, and thus the potential benefits of mHealth apps and their services for elderly are jeopardized by the challenges and barriers for today’s elderly regarding their intention to use these apps [18], [20]–[24]. Barriers for elderly in accepting mHealth apps include technology anxiety, lack of perceived usefulness for mHealth apps and concerns regarding the usability of smartphone technologies [18], [23]. Perceived usefulness and perceived ease of use are key constructs in prominent technology acceptance models influencing the intention to use technology; such models include the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) [24]–[27]. However, studies that applied these models within the area of healthcare state that both TAM and UTAUT are insufficient for examining technology acceptance in a healthcare setting appropriately due to a lack of incorporating constructs, such as essential health determinants [18], [24], [28], [29]. Cho et.al. describe that an individuals’ health consciousness has a direct effect on their use of electronic health applications [30]. Wilson and Lankton illustrate that key antecedent characteristics of patients – satisfaction with medical care, information-seeking preference and internet dependence – influence patients’ eHealth acceptance [28]. Few studies report on the acceptance of eHealth or mHealth by elderly patients; one study (in Dutch) was found regarding the use of an iPad app for elderly [12]. This study focused on usability and lacked a theoretical basis in acceptance theory. Dohmen additionally sheds light on the implementation process of eHealth for elderly (in Dutch) and developed 15 critical success factors regarding implementing eHealth. A correct implementation influences the acceptance of eHealth by elderly positively [31]. Guo et.al. describe that typical characteristics of today’s elderly – technology anxiety and dispositional resistance to change – are of importance in understanding their acceptance of mHealth apps [18]. In addition, a systematic review by Peek et.al. on factors influencing the acceptance of technologies for aging in place by elderly shows that post-implementation research on technology acceptance by elderly is scarce and most of the factors influencing acceptance have not been tested by using quantitative methods [24]. Peek et.al. identified six major themes of relevance to technology acceptance for aging in place by elderly: concerns regarding technology, benefits expected of technology, need for technology, alternatives to technology, social influence and characteristics of older adults [24].

This study reports on an mHealth app, the Hospitality App (HA), intended to assist elderly patients, aged 50 years and older, in managing their hospital visit to an outpatient gastrointestinal oncology center. By offering the patients information on their appointment schedule, a taxi transport service and personal in-hospital navigation and mental support by a medical student, the HA aspires to lower the stress level and increase the experience notion of hospitality of elderly patients upon their arrival at their consult. One month after its implementation at the Gastro-Intestinal Oncology Center Amsterdam (GIOCA) of the Academic Medical Center (AMC), few elderly patients at GIOCA had used

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ENABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE – GABY ANNE WILDENBOS 11 the HA; the importance of user acceptance became apparent. For this reason the main aim of this research is to assess the factors influencing acceptance of the HA. A second goal is to identify these factors in terms of ‘inhibitors’ or ‘enablers’ to the acceptance of conceivable procedural services offered via a smartphone app, within the context of individual assistance to manage one’s personal health condition. This study therefore addressed the following research question: what are the enablers and inhibitors related to the acceptance of the offered procedural functionalities and services of HA by elderly cancer patients after its first implementation at GIOCA? The oncology research setting imposed several requirements regarding data collection, which made it impossible to obtain valid data on all influencing aspects on technology acceptance addressed in prominent laborious technology acceptance models. Consequently, this study used the factors influencing the acceptance of technologies for aging in place described by Peek et.al. as a theoretical basis in acceptance theory [24]. These factors identify both the enablers as the inhibitors for the acceptance of technology for aging in place. In this study it is researched to which extent these factors are valid for the acceptance of the procedural services and functionalities offered via the HA by today’s elderly patients.

This study is of importance, since prior research concluded that sound evaluations based upon theoretical and evidence-based guidance are needed to drive mHealth innovations forward [19], [20], [32]. The insights from this study are of value for stakeholders involved with the development, implementation and research of mHealth apps offering a service to facilitate elderly’s procedural and personal health management within a setting of severe precarious diseases.

Background on the Hospitality App

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The Hospitality App

By providing a ‘valet navigation service’ for outclinic patients over fifty, the HA aspires to lower their stress levels and to increase their experienced notion of hospitality. Prior to an appointment at an outpatient clinic, the patient is offered the HA, which can be downloaded from Apple’s App Store or the Google Play store by the patient him or herself. The app offers functionalities to view one’s appointment schedule. Besides that the app offers two services: firstly, a taxi transport service to take the patient from home to the hospital and back. The second service includes guidance inside the clinic by a medical student (Hospitality Host) in his or hers first, second or third year. The Hospitality Host will guide the patient from the hospital entrance to the place of the consult. With consent of the patient, the Hospitality Host can attend the consult in order to learn from this experience in practice and provide mental support to the patient. After the consult, the Hospitality Host guides the patient to the exit of the hospital (or to any other place in the hospital where the patient wants to go). If desired, the patient can order taxi transport homewards by means of the HA. The HA is funded by the Vodafone Mobiles for Good Challenge, an award won by surgeon Marlies Schijven who fostered the HA idea. Figure 1 displays a flowchart of the HA, divided by its main actors in the process: the hospital administration, the patient, the taxi company, the Hospitality Host and the ‘super Host’, the latter being responsible for ensuring that the demand of the patients matches the supply of the Hosts.

Setting first implementation of Hospitality App

The implementation of the HA was set at GIOCA, a special oncology outpatient clinic of the AMC. This setting was chosen for the first implementation, since this unit of the AMC has a clear overview of incoming patients and the number of new patients was manageable in terms of instructing the hospital staff on the HA, inviting new patients to download the HA and matching these patients to the student Hospitality Hosts.

General practitioners, clinicians from other hospitals or specialists from the AMC itself refer patients to GIOCA. The process of GIOCA is designed to assist the patient quickly. After referral the patient is admitted within 5 workdays, often this is within 1 to 3 workdays. At the day of admission patients have consults and tests in the morning. At noon the GIOCA team, consisting of surgeons, specialists on gastrointestinal medicine and nurses, has a multidisciplinary meeting regarding the treatment plan of the patient. In the afternoon – that same day – the patient is informed on its treatment plan, which can be carried out at either the AMC or another hospital. Figure 2 displays this process in which the intervention of the HA takes place on the day of admission, the GIOCA-day. Throughout the GIOCA-day a host or hostess, who is a volunteer of the AMC, guides the patient. This includes welcoming at the waiting room of GIOCA, assisting with navigation in the hospital and supporting the patients morally regarding the information they obtain during the day. The GIOCA host

awaits the patient after its registration at the GIOCA counter and thus does not meet the patient at the entrance of the hospital.

Implementing the HA at GIOCA had several consequences for the overall design of the HA flow, since GIOCA has a host(ess) of its own. Figure 3 displays the GIOCA-day in detail, including the moments of the HA interventions during the implementation. Accordingly, the patients were notified on the HA via a flyer that was accompanied with the postal letter on their appointment(s) and/or via telephone by the administrative nurses of GIOCA. Since most of the patients at GIOCA are above 50 years old, all new patients were notified on the HA. This was done to simplify the process for the nurses of inviting patients to use the HA. Consequently this could include patients younger than 50 years old as well. If the patient requested a Hospitality Host, this Host guided the patient to the waiting room of GIOCA. There the GIOCA host(ess) was the primary host(ess) throughout the day; thus the navigation to other places in the hospital was managed by the GIOCA host – the Hospitality Host could join along if wanted. In line with the regular flow the HA, the Hospitality Host was able to attend the consult if desired by the patient and the Hospitality Host guided the patient to the exit of the hospital if requested.

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ENABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE – GABY ANNE WILDENBOS 13

Figure 2: patient process at GIOCA, including HA intervention

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Figure 3: activities GIOCA-day, including HA intervention

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Methods

Research period

The HA was launched at AMC at the 19th of February by means of an event to gain attention for the HA. The HA went ‘live’ at GIOCA at the 5th of March, from this day onwards the patients were invited by the GIOCA staff to download and use the HA. The first month of the implementation – from the 5th of March till the 10th of April – research was performed on the effectiveness of the HA. This resulted in insufficient data; hence, the research regarding the acceptance of the HA was started from the second week of April 2014.

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Study design

To answer the research questions a qualitative approach by means of conducting semi-structured interviews was chosen, in which the gathered data was quantified in order to analyze the data. An overview of the study design is shown in figure 4. The several aspects of the design are explained in more detail in the paragraphs below.

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ENABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE – GABY ANNE WILDENBOS 15

Participants

Patients were asked face-to-face to participate in the research by the first researcher.1 Either the host(ess) of GIOCA or the researcher herself introduced herself as an independent researcher to the patients before requesting the patients to participate in the interview. Inclusion criteria to request patients to participate were if patients resembled the target group in age (above 50 years old). However, patients below the age of 50 were included in the research as well, since the HA at GIOCA was available for all new patients. Upon request it was emphasized that patients could terminate the interview at any point and that their data would be used anonymously. Six patients refused to participate; these patients were shown gratitude and let be. An exclusion criterion to request patients to participate was if a patient was considered to be too fragile to answer the interview questions, for example if the patient had trouble speaking or was transported in a bed. The first researcher made the choice ‘on the spot’ to request patients to participate or not. In total five patients were excluded for request because of age or a fragile condition.

The participants included new patients, patients with a first appointment at GIOCA, as well as patients who had visited GIOCA before. By agreement of the implementation process all these new patients at GIOCA should have been informed on the HA; the new patients were free of choice to either use the HA or not and thus could include both users as non-users. This resulted in a total of 65 patients that were interviewed from the 14th of April 2014 till the 2nd of May 2014. The interviews were held in the mornings, since new patients of GIOCA have their appointments in the morning.

Criteria for excluding the data of the interviews in the results were if the interviewed patient appeared not to be a patient visiting GIOCA or if the data contained too little information on age and smart phone usage. In total 8 interviews were excluded from the results. This contained 4 interviews of the first day of interviewing and 4 interviews of patients who were not visiting GIOCA. In total the results of 57 patient interviews were used for this study.

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Data collection

The oncology research setting imposed several requirements regarding data collection: the research had to be non-invasive to the patients and could not interrupt the patients’ activities at their GIOCA day. The first researcher performed a literature review on how to gather data from cancer patients in an efficient and non-invasive manner.2 The outcomes of that review resulted in the choice for conducting short semi-structured interviews at the waiting room of GIOCA, since this proved to be a means that allowed the researcher to collect sufficient and adequate data in a way that was least invasive to the patients. On top of that, the semi-structured interviews were a means to collect in-depth information and facilitated the exploration of unexpected responses immediately [33-35].

The interviews’ length was approximately 5 to 10 minutes per interview; a single interview was performed once per patient, thus patients were not interviewed repeatedly. The interviews took place at the waiting room of GIOCA, after the instructions on the GIOCA day were given by the host(ess) of GIOCA and while the patients were waiting for their consult. Consequently, other patients, friends and/or family accompanying the patient and the GIOCA host(ess) could also present at the interview. The researcher conducting the interviews had previous work experience at a market research agency carrying out telephone surveys. To prepare for the interviews the researcher consulted literature on how to conduct short interviews in a scientific setting [33]–[35].

Due to the time restrictions of the interviews, prominent laborious technology acceptance models could not be used as a model to formulate interview questions regarding the acceptance of the HA. The factors influencing the acceptance of technology for aging in place described in the systematic review by Peek et. al. were believed to be most suitable to serve as a starting point to develop the questions of the interviews [24]. The factors described in the systematic review of Peek et. al. are shown in table 2 and their positive or negative influence is shown in figure 5. In appendix 2 all theme and factors are given a definition by the first and second researcher.

Based upon these factors, the topics of the interviews included:

o Benefits of the HA’s offered functionalities and services, and/or of conceivable procedural services of mHealth apps

o Concerns on and disadvantages of the HA’s offered functionalities and services, and/or of conceivable procedural services of mHealth apps

o Alternatives for the HA’s offered functionalities and services, and/or of conceivable procedural services of mHealth apps

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1 _{First researcher is Gaby Anne Wildenbos, a female student of the master Medical Informatics. The study was part of her} 2 _{The literature review examined non-invasive methods on measuring the stress level of cancer patients. An overview of the} search strategy is shown in appendix 1.

o Social influence regarding using smart phone devices and their apps

o Background information on patients (age, gender, education, nationality, usage of electronic devices)

Interview cards were used as an interview guide. As a ‘test run’ the researcher interviewed 4 elderly people with the interview cards in a home setting before conducting the interviews with patients. After this test the interview cards were adjusted in order and phrasing of the questions. The interview cards are shown in Appendix 3 (in Dutch). With consent of the participants the interviews were audio recorded to collect the data, supported by written and field notes of the researcher. Of 2 interviews the audio recordings failed; of these interviews solely the notes have been used as data. The first researcher transcribed the audio recordings. Patients were asked if they were interested in the results of the study; interested patients received a Dutch summary of the results. During the collection of the data, data saturation was discussed between the first and second researcher each week based upon the transcriptions.

Analysis

To analyze the results of the interviews the transcriptions were coded according to standard coding methods for qualitative research. The transcriptions were identified on common, recurrent, or emergent themes by means of concept mapping them on the six main themes mentioned by Peek et.al. [24]. A coding tree for defining post-implementation factors influencing the acceptance of the HA’s functionalities and services and conceivable procedural services of mHealth apps was developed through an iterative process. First, the pre-implementation factors of aging in place were provided with a definition. Second, based upon the first 16 interviews it was examined which factors of the pre-implementation model were still accurate and which post-pre-implementation factors for the acceptance of the HA’s functionalities and services and conceivable procedural services of mHealth apps needed to be added. The first and second researcher performed step one and two independently; afterwards the results were compared. This resulted in version 1 of the coding tree. Third, based upon all interviews version 1 was transformed into version 2 (the definite version) of the coding tree; several factors were added or redefined. The adjustments were made by the first researcher and reviewed by the second researcher. Themes and key factors of version 2 are shown in table 3.

Appendix 4 provides an overview of the full version (1 and 2) of the coding tree of post-implementation factors influencing the acceptance of the HA’s functionalities and services and conceivable procedural services of mHealth apps; including the definitions of the themes and factors, the sub-factors and adjustments made during the development of the coding tree. The first researcher coded the data by means of the coding tree and identified the data as enabler or inhibitor of the HA’s services and functionalities acceptance. This was done using Microsoft Word and Excel. The second researcher reviewed the coded transcriptions by means of taking random samples and checking if these were coded along the same perspective of the second researcher.

The data analysis contained a comparison on three main aspects:

o Most occurring factors influencing the acceptance of aging in place (pre-implementation) versus most occurring factors influencing the acceptance of the HA’s functionalities and services (post-implementation)

o Factors influencing the acceptance of the HA specifically versus factors influencing the acceptance of conceivable procedural services of mHealth apps in general

o Differences in factors influencing the acceptance of the HA’s functionalities and services and conceivable procedural services of mHealth apps, regarding the dependent variables of participants:

! Age and social background ! Information seeking preferences

! Familiarity with electronic devices and with the HA

The participants were clustered in four age groups: respectively 45-50, 51-65, 66-80 and 81-95 years old. The social background was clustered in participants with a professional or scientific education (higher education) and participants with an intermediate vocational education (lower education). Participants seeking health information online via a computer or tablet (with and/or without help from family or spouse) were classified as health information seeking patients. If participants mentioned that they used a mobile electronic device (tablet of cell phone) daily they were classified as being familiar with electronics. If participants had heard of the HA they were classified as being familiar with the HA. The data was analyzed using pivot tables in Microsoft Excel.

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ENABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE – GABY ANNE WILDENBOS 17

Table 2 – Pre-implementation themes and factors influencing technology acceptance of aging in place (by Peek et.al.)

Table 3 – Post-implementation themes & factors influencing technology acceptance of the HA’s functionalities and services and conceivable procedural service mHealth apps

* = Theme or factor of ‘pre-implementation tree – aging in place’ is adjusted or added to the ‘post-implementation tree – mHealth apps’

** = Factor was placed at another level in the ‘pre-implementation tree – aging in place’ then where it is placed in the ‘post-implementation tree – mHealth apps’

HA = Specific factor of the HA

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Figure 5: Positive / negative influence on pre-implementation acceptance of aging in place (by Peek et.al)

Results

Participant demographics and (m)Health apps related characteristics

Table 4 displays the number of patients interviewed on the specific interview dates, including the number of new patients interviewed and scheduled at GIOCA during the period of the 15th of April until the 2nd of May 2014. Over 50% of the interviewees comprise new patients (NP). Of the total number of participants, 25% was familiar with the concept of the HA; none of the participants had user experience with HA. Two participants were below the age of 50. Figures 5 and 6 display the ownership of respectively a smartphone and tablet per age group. Thirty percent of the total participants owned a smartphone (59% did not own a smartphone) and 40% of the participants owned a tablet. Figure 7 shows the education level of the patients. Figure 8 displays the number of participants searching health information online per age group. Three of the participants aged 51-80 years old answered that they do search for general health information, though do not want to search for information on cancer.

Table 4 – number of patients interviewed at GIOCA, including characteristics

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Participant responses

In Table 5A and 5B the results per theme and key factors are shown. Most apparent factors are described below, including a comparison with the pre-implementation factors influencing technology acceptance of aging in place. This is followed by an explanation on the specific results for the HA and the results for conceivable procedural services of mHealth apps in general. Hereafter, the results regarding the specific participant characteristics with respect to the key influential factors are presented.

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Figure 5: number of participants with/without Figure 6: number of participants with/without smartphone per age group tablet per age group

0 5 10 15 20 Smartphone: yes Smartphone: no Answer on smartphone yes/no is n.a. 0 2 4 6 8 10 12 14 16 Tablet: yes Tablet: no Answer on tablet yes/no is n.a.

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ENABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE – GABY ANNE WILDENBOS 19

Figure 7: education level of participants Figure 8: number of participants searching health information online

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Concerns regarding technology

The most frequently mentioned factors at the theme concerns were respectively ‘high costs’, ‘pace of developments of mobile technology is too fast’, ‘no feeling of control over technology’ and ‘low ease of use’. For example, patients’ responses were: “If I had to come from home by taxi it would cost me a lot of money” (male patient, 68 years old) and “I don’t like technology that finds progress so quickly. Today you have this [smart] phone and tomorrow that will be old already; then they will have something new again” (male patient, 83 years old).

The factors regarding the acceptance of technology for aging in place partially corresponded on this theme. In the review by Peek et.al. ‘high costs’ and ‘privacy implications’ were mentioned most often in 44% in the articles. ‘Forgetting or losing technology’ was mentioned in a quarter in the articles reviewed by Peek et.al, whereas in the interviews this factor solely occurred 5% of the time.

One participant mentioned a specific HA factor as a concern: a ‘fear of a language barrier’ due to the English title of the app. Another specific HA factor was pointed out regarding the factor ‘high costs’, since it was expected that the taxi costs while using the HA would be considerably expensive. Table 6 shows the number of mentioned sub-factors on ‘high costs’ in detail. Participants familiar with the HA mentioned ‘ineffectiveness’ as a concern, because they could not register and/or be an approved user of the HA before visiting the hospital. The participants with a higher education had relatively more concerns than the participants with a lower education, as is shown in table 7. The participants without a smartphone most frequently mentioned concerns on using apps and smartphones in general.

Table 6 – Factor high costs with sub-factors per age group

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Table 7 – Number of concerns per education cluster

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Benefits expected or experienced of technology

During the interviews perceived usefulness was mentioned more often than in the articles reviewed by Peek et.al. and the factors influencing perceived usefulness became apparent during the interviews. Other benefits that occurred in the articles reviewed by Peek et.al. and were nearly not mentioned by the interviewees were ‘increased safety’ and ‘reduced burden on family and caregivers’.

Most benefits portrayed were on the HA’s offered services. A quarter of the interviewees mentioned the usefulness of the Hospitality Host as a guide through the hospital. To illustrate this, a patient responded: “if you are in need of help, it is easy to be guided to your appointment at the outpatient clinic” (male patient, 51 years old). One participant expressed the benefit of having a Host

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present at a consult. Besides that, 11% explained that they did not use the HA at this point in time (for their first visit to the hospital), though they regarded the HA as useful for a later stage of their disease provided that they would have to visit the hospital more frequently and become less physically fit. An example of what was mentioned on that topic is: “I am not that in need of help (...) I don’t need it at the moment. But I can imagine that it [the HA] can be a solution for people who do not have partner (...) But it could be that in the future it would suit me, then I might use it (...) At this moment, you don’t know what to expect [regarding the cancer treatment] really” (male patient, 58 years old).

Of the participants that searched health information online, 45% mentioned benefits of procedural services such as the HA offered. They accounted for 57% of the mentions on the factor ‘usefulness of host’ and 83% of the mentions on the factor ‘useful in a later phase’. There seemed to be no significant difference in mentioning benefits by participants with or without a smartphone. 17% of the participants familiar with the HA accounted for the total mentions on benefits of the HA’s offered services.

Need for technology

Perceived need for technology is mentioned in the article of Peek et.al. as the most influential factor regarding technology acceptance for aging in place. The interviewees repeatedly mentioned perceived need as well; it was the second most mentioned factor (82%). Peek et.al describe it was mostly stated in the reviewed articles that the technology was needed for a ‘hypothetical other older person’. The responses of the interviewees were similar to this description. Examples of participants replies on the question if they thought they would need the functionalities and services of the HA were: “It is not of use to me, I know how to navigate in the hospital, but for some people it would be really useful, especially older people” (male patient, 50 years old) and “It sounds useful, however up till now we can do everything by ourselves” (male patient, 75 years old). These answers were best labeled as ‘stigmatization’; therefore ‘stigmatization’ is placed at the theme perceived need, whereas the article of Peek et.al. did describe ‘stigmatization’ as a factor within the theme ‘concerns’

Table 8 – Perceived need per age group and smartphone ownership

Table 8 shows the details on the given answers regarding ‘perceived need’; most often the HA’s functionalities and services and the conceivable procedural services of mHealth apps in general were perceived as not needed since the interviewees did not own a smartphone; this specifically accounts for the participants within the age group 81-95 years old. Of the participants familiar with the HA, 7 participants answered not to need the HA due to not owning a smartphone. One participant familiar with the HA said that the HA was more suitable for another target group. The age group of 66-80 years old (42% of total participants) accounted for 47% of the answers on ‘perceived need’ and 6 of the participants within this age group responded that the HA was more suitable for another target group than themselves.

Alternatives to technology

The article of Peek et.al. reported little on the alternatives to technology for aging in place and its influence on the acceptance of this technology. It made a distinction between the alternatives ‘help by family or spouse’ and ‘current technology’, which both could influence acceptance negatively. During the interviews it became apparent that housing type (and the professional care that possibly is a part of a specific housing type) is an influential alternative to the services that the HA offered. For this reason this was placed at as factor of the theme ‘alternatives to technology’, whereas in the article by Peek et.al. ‘housing type’ was placed at ‘characteristics of older adults’.

During the interviews, ‘current technology’ was the most frequently mentioned factor as an alternative to the HA’s functionalities and services and conceivable procedural services of mHealth

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ENABLING ELDERLY CANCER PATIENTS TO BECOME MORE MOBILE – GABY ANNE WILDENBOS 21 apps. Table 9 displays the results of this factor in more detail and figure 7 displays the number of patients who visited GIOCA with company.

Table 9 – Current technology and sub-factors per age group and familiarity with the HA

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Being accompanied by family or friends to visit the hospital and navigate through the hospital was a frequent mentioned alternative. For example a patient replied: “Well, I mostly visit the hospital with my wife and she drives the car, so I do not see any benefits for me personally” (male patient, 65 years old). Other alternatives that accounted for the HA’s functionalities and services in particular were using postal mail or a (paper) agenda to track appointments and using ones own transport to visit the hospital.

The usage of a computer was widespread amongst most of the participants. The older part of the age groups (66-95) used a regular cell-phone or a landline. For 4 participants aged between 66-80 their housing type and/or the professional care surrounding them was an alternative to HA’s transport service specifically. Two of those participants were familiar with the HA.

Social influence

Regarding the social influence on technology acceptance, Peek et.al. distinguished three factors ‘influence of family and friends’, ‘influence of professional caregivers’ and ‘use by peers’. For the acceptance of the HA’s functionalities and services, the ‘use of peers’ has been conjoined with ‘influence of family and friends’. Peek et.al. did not differentiate between the types of social influence. This differentiation is made for the acceptance of procedural services offered via smartphone such as the HA, since the participants made clear that they experienced either a ‘obtrusive’ or ‘positive’ push towards using mobile technology; the former was experienced by a quarter of the interviewees. The age group 66-80 years old experienced the obtrusive push the most. By participants familiar with the HA, the obtrusive push is mentioned 5 times. An example of what a patient responded regarding the obtrusive push is: “Yes, all my children and even my grandchildren have such an iPhone, they talk with their friends and everything. However, for me and my wife I don’t see any benefits of having such a smartphone” (male patient, 75 years old).

0 10 20 30 With company Without company

Figure 7: number of participants visiting GIOCA with/without company per age group

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Table 5B – Theme and key factors mentioned per relevant participant characteristic

Discussion and conclusion

Principle findings

The aim of this study was to gain insight on the factors influencing the intention of elderly to use the HA and to identify these factors in terms of ‘inhibitors’ or ‘enablers’ to the acceptance of procedural services, offered via a smartphone app, within the context of individual assistance to manage one’s personal health condition. The HA is an mHealth app intended to assist elderly patients in visiting their hospital consult by offering functionalities regarding appointment information and services of taxi transport and personal in-hospital support. Factors influencing the acceptance of technology for aging in place – concerns, benefits, need, alternatives and social influence regarding technology and characteristics of elderly patients – served as a theoretical basis for technology acceptance. It was assessed to which extend those factors are valid regarding the acceptance of the HA and conceivable mHealth apps offering a similar procedural service. Fifty-seven semi-structured patient interviews on the HA have been transcribed, coded and analyzed.

This study provided insight into in four main inhibitors to the acceptance of the HA’s functionalities and services. These four inhibitors are lack of perceived need for the provided service of the application, the feeling of stigmatization of ‘elderly’ by patients aged 50 – 80 years old, concerns regarding smartphone technology and an experienced obtrusive push regarding smartphone technology use. Lack of perceived need was mentioned 42 times and related to ‘patients not experiencing the need for the HA functionalities and services as essential’ for personal assistance in navigating and visiting the hospital. This inhibitor specifically relates to the HA and several alternatives for the HA functionalities and services were mentioned by patients for managing hospital appointments, transport and navigation to the hospital, and navigation and personal support within the hospital. Therefore, this inhibitor also accounts for apps offering similar functionalities and services as the HA in terms of managing appointments, taxi transport and personalized in-hospital guidance. Alternatives to the offered functionalities and services of the HA and conceivable procedural services of mHealth apps included use of current technologies, such as a computer, (paper) agenda and regular cellphones. With regard to personal support a preference of caregivers support during patient visits at the oncology center is considered important by patients. The HA does not include specific functionalities targeted at caregivers support.

The second inhibitor is the feeling of stigmatization experienced by patients aged 50 - 80 years old; they feel to be characterized as fragile elderly cancer patients in need of support physically as well as mentally. This inhibitor relates to apps targeted at elderly patients and/or elderly patients with a severe disease such as cancer. Patients starting to visit GIOCA did not consider themselves part of this type of patients and therefore appeared to ignore possible benefits the HA could offer them. This relates to the fact that 48% of the participants aged 50-80 mentioned they do search health information online, though are not willing to search information on cancer, since this might confront them with uncertainties regarding their cancer diagnosis. By ignoring cancer related health information online, the patients aim to prevent considering (stigmatizing) themselves as fragile cancer patients.

Patients aged 80+ years old did not own a smartphone and have concerns regarding smartphone technology use. The notion that the pace of smartphone developments is too fast was mentioned by 3 of the 4 interviewees in this age group. Other concerns that were mentioned were the feeling that one has no control over the smartphone device and a presumably low ease of use of the device. Last main inhibitor is an experienced obtrusive push regarding the usage of smartphone technology by elderly cancer patients, which causes an aversion to these technologies. These last two inhibitors influence the acceptance of the HA, as well as of other procedural service mHealth apps and smartphone technology in general, by today’s elderly.

Main enablers of the acceptance of the HA are the awareness of guidance by a medical student as a personal host during the in-hospital navigation support and the usefulness of the HA’s taxi transport service if patients visits’ would become more frequent in a later stage of the oncology treatment. These enablers could enhance the perceived need for the HA as well as for other procedural service mHealth apps offering in-hospital navigation support and (taxi) transport for fragile patients. Functionalities of the HA that were mentioned as enablers were the inclusion of a hospital appointments’ overview on a digital mobile device and obtaining a text reminder when an appointment is approaching. Though the text reminder is considered as an enabler of the acceptance of the HA, the current version of the HA does not provide this functionality. Both enablers are of relevance to procedural service mHealth apps offering functionalities to manage hospital appointments.