Technical Challenges of a Mobile Application Supporting Intersession Processes in Psychotherapy [original]

Available online at www.sciencedirect.com

Procedia Computer Science 00 (2019) 000–000

www.elsevier.com/locate/procedia

The 17th International Conference on Mobile Systems and Pervasive Computing (MobiSPC)

August 9-12, 2020, Leuven, Belgium

Technical Challenges of a Mobile Application Supporting

Intersession Processes in Psychotherapy

Michael Stacha,∗, Carsten Vogelb, Thorsten-Christian Gablonskic, Sylke Andreasc,

Thomas Probstd, Manfred Reicherta, Marc Schicklera, R¨

udiger Pryssb

aInstitute of Databases and Information Systems, Ulm University, Germany

bInstitute of Clinical Epidemiology and Biometry, University of W¨urzburg, Germany

cInstitute of Psychology, University of Klagenfurt, Austria

dDepartment for Psychotherapy and Biopsychosocial Health, Danube University Krems, Austria

Abstract

The usage of mobile applications in healthcare is gaining popularity in recent years. The ubiquity of a sophisticated mobile ap-

pliance that is applicable to sample ecological patient data in real life by acquiring both mental state and environmental data has

enabled new possibilities for researchers and healthcare providers. Collecting data using the mentioned approach is often called

Ecological Momentary Assessment (EMA) and is characterized by an unidirectional data flow towards the platform provider. A

more challenging approach, in turn, is called Ecological Momentary Intervention (EMI). The latter requires a bidirectional data

flow in order to enable the possibility of sending feedback to the patients and controlling their experiences through interventions.

Although both approaches are established parts of IT-supported treatments in the field of psychology and psychotherapy until now,

the so-called intersession process has not been technically supported appropriately yet. Therefore, the Intersession-Online platform

was developed in order to (a) assess intersession processes systematically, (b) monitor a patient, and (c) intervene by suppressing

negative thoughts concerning the therapy. In this paper, the technical requirements, architecture, and features of the mobile appli-

cation of the Intersession-Online platform are presented. In this context, the development of a patient data sampling mechanism,

which consists of a sophisticated, inter-questionnaire dependent sampling schedule and synchronization strategy is particularly il-

lustrated and discussed. Altogether, the technical challenges will show that a mobile application supporting intersession processes

in psychotherapy is an endeavor which requires many considerations. However, on the other, such a mobile application may be the

basis for new technical as well as psychological insights.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Peer-review under responsibility of the Conference Program Chairs.

Keywords: Ecological Momentary Intervention; Ecological Momentary Assessment; Mobile Crowdsensing; Intersession Experience;

Psychotherapy; Intersession Processes

∗Corresponding author. Tel.: +49 731 50 24 225 ; fax: +49 731 50 24 134.

E-mail address: [email protected]

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Peer-review under responsibility of the Conference Program Chairs.

2M. Stach et al. /Procedia Computer Science 00 (2019) 000–000

1. Introduction

In the field of Mobile Health (mHealth) research, several new paradigms have been introduced throughout the

last years that are able to support many questions in medicine and psychology. Especially the paradigms mobile

crowdsourcing, mobile crowdsensing, and Ecological Momentary Assessments have garnered a lot of attention [18,

15]. A major idea of these approaches is to utilize the powerful capabilities of smart mobile devices to assess healthcare

parameters of patients in daily life without burdening them much (as a particular advantage compared to clinical

procedures). As a result, new data sources and insights can be established [17]. However, still one major shortcoming

of all these approaches constitutes the way how patients are involved. To be more specific, in the aforementioned

approaches, only (or mainly) an unidirectional data flow strategy is applied [2].

In the work at hand, a framework was developed that mainly pursues the accomplishment of two aims that are

related to a bidirectional data flow strategy in the mHealth context: First, in the field of psychology and psychotherapy,

so-called intersession processes should be supported by a proper technical mHealth solution [5]. Second, with respect

to the latter aim, the pursued mHealth solution shall make use of Ecological Momentary Assessments and Ecological

Momentary Interventions [5].

Regarding the first aspect, intersession processes [26,5] characterize the processes happening in the period of time

between two sessions of a patient with his/her therapist. From a research perspective, this phase is still rather unex-

plored as it is complex to monitor patients during this phase properly without burdening them much. Therefore, having

the capabilities of modern smart mobile devices in mind, a technical solution was developed to support intersession

processes by Ecological Momentary Assessments (EMAs; [15]) and Ecological Momentary Interventions (EMIs; [8]).

EMIs shall be the basis of giving feedback and support back to a patient based on the following two aspects. First,

the applied EMIs shall consider personal aspects and gathered data of patients while they are being in the intersession

phase. Second, applied EMIs shall be applied similarly to EMAs in the daily life of patients in an efficient and unobtru-

sive manner; again, while patients are being in the intersession phase. To support the intersession processes properly,

the mHealth solution Intersession-Online was developed. This platform, in turn, comprises the following three distinct

components: (1) mobile applications for iOS and Android, (2) a server component providing the business logic, and

(3) a feature-rich web application for therapists and researchers to manage patients, data, and EMAs as well as EMIs

(see Figure 1). In this work, we focus on the mobile side of the Intersession-Online platform. More specifically, based

on the example of iOS, we delineate the technical challenges to deal with the two major aspects raised above for the

entire platform. As it will be shown, a complex mobile application had to be developed [28] in order to properly cope

with the requirements that emerge with respect to the mentioned two aims of the Intersession-Online platform.

Therapy Schedule

Intersession Intersession

01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21

WEEK 1 WEEK 2 WEEK 3

Mo Tu We Th Fr Sa Su

Therapy

Session

Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su

Questionnaire Questionnaire Activities Therapy

Session

Intersession Server Component

Database

RESTful API

Security Analysis Users

Intersession Business

Logic

Only

questionnaire

data is stored!

Calendar Questionnaire

Mobile Intersession

Application Intersession Web

Application

Answer data

sets

User activities

Questionnaire

data

Fig. 1: The Intersession-Online Platform at a Glance [5]

The remainder of this work is organized as follows. In Section 2, related works are discussed. As the overall

procedure that has to be accomplished by patients when using the developed platform is complex, the procedure and

important background information are introduced in Section 3. Based on this, Section 4discusses a key component of

M. Stach et al. /Procedia Computer Science 00 (2019) 000–000 3

the platform, the mobile application. In Section 5, the current practical use is discussed, while Section 6summarizes

the work and provides an outlook of future work.

2. Related Work

Regarding related approaches that are in the scope of this work, two perspectives are of interest. First, technical

approaches that support EMAs and EMIs. Second, technical approaches that directly support intersession processes.

Regarding the latter, also approaches that do not utilize mobile technology must be considered separately. Regarding

the first perspective, many solutions have been introduced in the field of EMAs [17,25,10]. These approaches im-

pressively show that daily life data is a very promising source for current healthcare research. By the nature of EMAs,

respective work mainly focus on the collection and less on the feedback procedure based on the gathered data. In

the field of EMIs, approaches using mobile technology have been already proposed that are related to this work. For

example, in the context of remote therapeutic interventions, the time period between the sessions with a therapist has

been addressed [23]. Another promising approach is to provide just-in-time interventions on the smartphone between

sessions [11]. Also, in clinical trials, intersession interventions were applied [27]. Interestingly, all mentioned ap-

proaches have two aspects in common. They are rather recent developments, which shows that EMIs are an emerging

topic. Second, they do not systematically focus on the technical challenges of a proper mobile application for interses-

sion processes in this context as done by this work. However, when looking at EMIs as a proper feedback mechanism

for patients, other works have impressively shown that promising possibilities are given [14,19]. Note that if methods

from the field of artificial intelligence are combined with EMIs, then they can be particularly powerful instruments

[16]. Regarding the second perspective, less approaches have been introduced that are directly related to the work

at hand. As an exception, [23] and [24] are similar to the work at hand. Although they utilize mobile technology

for therapeutic homework in the time period between sessions with a therapist, a mobile application like shown here

was not presented. An approach that focuses on the support of intersession processes particularly by the use of web

technologies can be found in [12]. Again, a complex mobile application is not a major focus of this work. Altogether,

the aims raised in this paper can be partly found in other works as well, a combination of them implemented in a

technical solution as shown here, to the best of the authors knowledge, is not pursued so far.

3. Intersession-Online Procedure

As already mentioned, the procedure that must be pursued to use the platform is complex. A detailed discussion

can be found in [5]. However, the major aspects that are important in the context of this work are briefly introduced.

Particularly, the patient participation follows a predefined procedure that is illustrated in Fig. 2. To use the platform,

first of all, patients have to download the mobile application from an app store that corresponds to their installed

operating system. Note that for Android and iOS apps have been officially released to the Google Play and the Apple

App Store. Then, after downloading the app and the creation and validation of an account, the pursued procedure is

split into a therapy-dependent and therapy-independent part that can be accomplished in parallel.

In the therapy-independent part, the sub-process shown in Fig. 2A is executed if the patient has a session ap-

pointment in the according week. The sub-process is responsible for the provision of a post-session questionnaires

and the creation of a system notification according to the following schema: The patient is notified two hours after the

completion of the session and is able to submit the questionnaires (see Table 1, A ) within 12 hours. If the submission

period begins after 8pm, then the starting point in time is postponed till the following day at 8am.

In the therapy-dependent part of the Intersession-Online procedure, the patient firstly has to pair its user account

with the therapist’s by creating a therapy instance. The pairing task is necessary to ensure that the patient has an

ongoing psychotherapeutic treatment and to prevent an app usage without professional help. For this reason, the

therapist provides the patient with an individual code that is used for the pairing task. After starting the therapy, the

pre-treatment sub-process (see Fig. 2, D1) is triggered. The latter notifies the patient to fill in several questionnaires

(see Table 1, D ). The therapy-dependent part itself is split into three looping routines: (1) a daily routine, (2) a weekly

routine, and (3) a routine that is only accessed in the weekend.

4M. Stach et al. /Procedia Computer Science 00 (2019) 000–000

Pre-

Treatment

Quest. Proc.

Intervention

Quest. Proc.

XOR XOR

Post-Session

Quest. Proc.

Therapy

ended

Sessions

completed

Follow-Up

Quest. Proc.

Study

completed

Event Process

Interface

XOR

Branch/Merge AND (Fork)

Therapy

started

Account

created

Notifications

registered

XOR

Dates

calculated XOR

Daily

Quest. Proc.

XORXOR

OR (Join)

XOR XOR

Weekend

Quest. Proc.

Post-

Treatment

Quest. Proc.

D2D3

Appointment

in Calendar

Pair Therapist

with Patient

Function

Complete

Therapy

Therapy-

dependent

Therapy-

independent

Retrieve

Notification

Dates

Calculate

Notification

Dates Ongoing Therapy & Mon-Fri

Ongoing Therapy & Mon-Sun

Weekly

Daily

Ongoing Therapy & Sat-Sun

Fig. 2: Intersession-Online-Procedure, denoted in an Event-driven Process Chain (EPC) [22]

The daily routine is triggered per day and starts with the retrieval of the notification dates. An algorithm (see

Algorithm 1) is responsible for the collision-free determination of three points in time, each in one of three distinct

periods of four hours starting at 8am and ending at 8pm. The daily questionnaire procedure (see Fig. 2, B ) is executed

locally on the mobile device and the patient is able to submit the daily questionnaire within 30 minutes after the

notification is displayed.

Furthermore, an intervention is triggered once a week. The latter, in turn, can have one of the following three

types: commendation, question, or task. For example, a question could be ”What happened in the last therapy session

and how did you feel?”. Further information to interventions can be found in [5]. The intervention sub-process (see

Fig. 2, E ) is responsible for the notification and provision of the intervention. Importantly, the calculation of the

notification time for interventions strongly depends on both the existence of an session appointment in the ongoing

week and the submission of the weekend questionnaire of the last week. Therefore, it is executed by the Intersession

Server Component. If the following conditions match, the intervention must be submitted starting at Monday 8am and

ending at the day of the session at 8pm: (i) the therapy is not yet completed, (ii) there is a session appointment in the

ongoing week and (iii) the questionnaire of the weekend routine was submitted.

If one of the conditions is not matching, the end of the submission period is extended till Friday 8pm. The result

of the intervention is only visible for the patient and is therefore only stored locally. The weekend routine consists of

the weekend questionnaire sub-process (see Fig. 2, C ) and is executed every weekend in an ongoing therapy. The

questionnaire shall be submitted starting at Saturday 8am and ending at Sunday 4pm, but not between Saturday 8pm

and Sunday 8am.

After the completion of the therapy, the post-treatment sub-process (see Fig. 2, D2) is executed and the patient

is notified to fill out the questionnaires depicted in Table 1D . Then, the follow-up sub-process shown in Fig. 2,

D3is executed, which creates notifications by applying the patterns of three, six, and 12 months. Note that at each

notification, all the questionnaires of Table 1D shall be filled out.

Questionnaire Post-Session

Daily

Weekend

Pre-Treatment

Post-Treatment

Follow-Up

Intersession Daily ×

Intersession Questionnaire (ISF-K) [6]×

Working Alliance Inventory (WAI-SR) [29]×

SCL-K-9 [13]× ×

Childhood Trauma Questionnaire (CTQ) [30]× × ×

List of Pathogenic Beliefs (LPB) [21]× × ×

Mentalization Questionnaire (MZQ) [7]× × ×

Relationship Questionnaire (RQ) [1]× × ×

Inventory of Personality Organization (IPO-57) [3]× × ×

Personality Inventory for DSM-5 (PID-5-BF) [31]× × ×

Health-49 (Module A-F) [20]× × ×

Table 1: Questionnaire Groups (cf. Fig. 2, labeled process interfaces)

M. Stach et al. /Procedia Computer Science 00 (2019) 000–000 5

3.1. Questionnaire Management

As the number of used questionnaires for the Intersession-Online platform is high compared to other related plat-

forms, the used questionnaires are briefly introduced. They are also a key aspect that complex notification (see Sec-

tion 4.1) and synchronization (see Section 4.2) schemes became necessary. In Table 1, all used questionnaires are

listed. It is further distinguished at what point in time they are applied to a patient (see Table 1, A - D ). Impor-

tantly, the points in time are denoted in Fig. 2with the same labels A , B , C and D . All questionnaires except

the Intersession-Daily are generated and dynamically provided by the server component (see Fig. 1). The server also

calculates the notification dates for the questionnaire groups shown in Table 1, A , B , D . Further information to the

entire questionnaire management can be found in [5,28,9].

4. Mobile Application

A crucial component of the Intersession-Online platform constitutes the mobile application as it has to provide

most of the features on one hand, while supporting the patient in his/her ongoing therapy properly on the other. For

this reason, the Intersession-Online procedure requires the fulfillment of several technical requirements, which have

been elaborated in collaboration with the domain experts from the field of psychology [5]. They are summarized in

Table 2. Note that we discuss the mobile application based on the iOS-implementation [28]. Although technically

some aspects are different on Android, the basic strategy is the same for both mobile operating systems.

As the Intersession-Online platform constitutes a distributed system, the characteristics of such systems [4] have

to be carefully considered. For example, a sophisticated synchronization feature that handles the exchange of data

between the application modules and the RESTful API of the server component is crucially required. Therefore, a

synchronization module was designed as the central application module that handles the bidirectional data flow and

ensures full functionality of all application features even if no internet connection is available (see Table 2, No. 1, 2).

Due to the importance of a powerful synchronization, one use case, namely the synchronization of intervention meta

data (see Table 2, No. 10), is discussed in Section 4.2.

In addition, the mobile application has to meet general requirements when working in a multi-user environ-

ment like a general account management or the management of settings for the mobile application itself (see

Table 2, No. 3, 4, 15, 16). In order to be able to support the overall study design, the mobile application must provide

a feature to inform the patient about the study participation agreement, including the possibility to confirm or revoke

the agreement (see Table 2, No. 17-19). To ensure the professional help by a therapist, the application must enforce a

pairing procedure (see Table 2, No. 5-6) that is based on a shared individual code between therapist and patient. Fur-

thermore, a reliable data collection mechanism must be supported by guaranteeing the notification of questionnaires

to be submitted and the rendering of dynamic content inside the questionnaires (see Table 2, No. 7, 8, 14). Although

the intersession process should be interruptible in cases of unforeseen events, a sophisticated intervention module is

necessary that ensures both privacy and monitoring. Moreover, the therapy itself must be supported by guaranteeing

the creation of system notifications and the synchronization of intervention meta data (see Table 2, No. 9-11). The

architecture of the mobile applications follows the Model-View-Controller (MVC) software pattern and separates the

graphical user interface from the business logic and the data persistence layer. Each requirement group shown in

Table 2is developed as an independent module that communicates through well-defined interfaces.

4.1. Daily Notifications

Notifications are a key feature for each EMA-based data collection application to ensure a consistent sampling

rate. In general, all notifications for questionnaires are calculated by the server except the one for daily questionnaires.

The reason to calculate the daily notifications by the mobile application itself was to ensure the best possible offline

functionality. The algorithm for the daily notifications has the following characteristics. Within the three time win-

dows, a daily questionnaire notification appears on a random basis within one time period: 8am to 12pm, 12pm to

4pm, and 4pm to 8pm. After the notifications has appeared, the questionnaire can be filled out for 30 minutes. After

the 30 minutes, the questionnaire cannot be filled out any longer. Furthermore, if a daily notification appears at the

end of one of the three periods and the 30 minutes availability period intersects with the following period, the starting

6M. Stach et al. /Procedia Computer Science 00 (2019) 000–000

Requirement Group No Title Description

Synchronization 01 Offline Mode Ensure all features even without internet connectivity.

02 Multiple Devices Synchronize data between different mobile devices.

Account 03 Manage Create, validate, and authenticate user credentials.

04 Profile Show/Update user related information and settings.

Therapy 05 Pairing Pair patient and therapist.

06 Information Show therapist information.

Questionnaires 07 Submission List and submit questionnaires.

08 Rendering Render dynamic input structures of questionnaires.

Interventions 09 Manage Manage patient interventions.

10 Meta Data Synchronize intervention meta data.

11 Completion Save completed interventions locally.

Appointments 12 Manage List, create, edit, and delete appointments.

13 Calendar View Show appointments in calendar.

Notifications 14 System Notification Display custom notifications.

Settings 15 Notification Edit notification settings.

16 Profile Edit profile settings.

Data Privacy & Study Participation 17 Privacy Agreement Show information and confirm data privacy.

18 Study Participation Approve/Withdraw data sharing agreement.

19 Contact Data Show contact data of platform provider.

Table 2: Functional Requirements of the Mobile Application

time of the following period is adjusted to the future by the time that intersects with the former period. How these

notifications are calculated for the daily questionnaires is illustrated in the listing of Algorithm 1. To ensure that the

data of the filled out questionnaires is synchronized with the server, even when submitted in offline mode, a complex

synchronization mechanism was developed (see therefore the next section).

4.2. Intervention Synchronization

For the filled out data of the daily questionnaires as well as all other gathered data by the mobile application, two

aspects are of utmost importance. First of all, the pursued mechanism should be robust and reliable. Second, and more

importantly, it must be ensured that the mobile device can always work in an offline manner. Therefore, a complex

synchronization mechanism was developed for the mobile devices. Generally, relevant user inputs are stored locally

and, once a data set is completed, synchronized with the server, when reachable. Based on the selected example for

interventions, the mechanism is illustrated in Fig. 3. For more information, interested readers are referred to [28].

By using interventions, the intersession processes can be directed in a certain way. Yet, this can be disturbed if

patients fear that the outcome of the intervention is shared without their consent. For this reason, the result of an

intervention and its derived data is only stored locally on the mobile device and is never being synchronized with

the server component. In order to monitor the execution and the awareness of an intervention, the meta data seen

(i.e., intervention has been displayed) and submitted (i.e., intervention has been submitted locally) have to be tracked

and synchronized by the application. The platform, and in particular the therapist, must know the current state of an

intervention. Hence, possible states that can occur must be analyzed and considered. The developed model for this

purpose can be obtained from Fig. 3. After the server-side creation of the intervention, an intervention instance is

stored on the server. The synchronization module of the mobile application is from this point on responsible for the

synchronization of the intervention data. Being locally persisted, the intervention data may be deleted on the server’s

side and must be deleted locally as well. The latter is accomplished regardless of whether the patient has noticed and

has opened the intervention or not. If an intervention is not deleted and it was noticed or opened by the patient (e.g.,

after displaying a system notification), its state changes to locally seen. The state transition is either synchronized with

the server component or stored locally in case of lacking internet connectivity. In either cases, the patient is now able

to execute and to complete the intervention’s task. Note that the completion is bounded to a time period and cannot

be completed by the patient after the time period, whereas locally stored meta data (seen and submitted) will still be

synchronized with the server. For simplification reasons, the latter state transition is not included in Fig. 3. Eventually,

the intervention state is either deleted or completed on both the server and the mobile application side.

M. Stach et al. /Procedia Computer Science 00 (2019) 000–000 7

Algorithm 1: calcDates

Input : List l, where each element is a tuple of

integers. Integer d, the number of tuples

to be created.

Output: List l, where each element is a tuple of

integers.

Data:

•List t, where each element is a pair of integers,

specifying the start- & endpoint of a time interval

(minutes starting from 12am).

•Integer s, submission period (minutes).

1if sizeO f (l)>=dthen

2return l

3end if

4|t|=sizeO f (t)

5q← {}

6repeat

7qi=drandom(0..1) ∗(ti,1−ti,0)+ti,0e

8until ∀i=0..|t| − 1,qi>(qi−1+s);

9l←l∪q

10 return calcDates(l,d)

created, not

loaded

server creates intervention

synchronized,

unseen

synchronize()

(success)

synchronize()

(success) / (fail)

externally deleted,

locally stored/modified

externalDelete()

synchronize()

(fail)

/synchronize()

(success)

Legend

no local data

local data

synchronized

local data

changed

no server data

server data

synchronized

state

state transition

start

end

server deletes intervention

synchronize()

(fail)

locally seen, not

submitted

synchronize()

(fail)

externalDelete()

openIntervention()

locally seen,

locally submitted

(in time)

synchronize()

(fail)

submit()

seen, not

submitted

synchronize()

(success)

seen, locally

submitted

(in time)

synchronize()

(success)

submit()

seen, submitted

synchronize()

(success)

synchronize()

(fail)

synchronize()

(fail)

externalDelete()

+seen

submitted

Fig. 3: Intervention Synchronization States

5. Intersession-Online in Practice

The components of the Intersession-Online platform are all implemented and the deployed platform can be found

at the website www.intersession-online.de. In addition, the Android and iOS apps can be found in the respective

app stores. Currently, the entire platform is tested in an outpatient clinic in Austria. So far, 10 patients are using the

platform for a longer period of time. Further results are expected within the next 2-3 months.

6. Summary and Outlook

This work presented the Intersession-Online platform. The latter pursues two major goals, namely the proper

support of intersession processes by mobile technology and the integration of Ecological Momentary Assessments

as well as Ecological Momentary Interventions for the intersession processes. Based on the platform component of

the mobile iOS application, this work has shown that a technical complex implementation becomes necessary to

address the two goals. In particular, it was shown that the questionnaire, intervention, and notification management

– in combination with the technical demand to support an offline mode – are challenging. The elaborated technical

requirements were shown and to some of the requirements the technical solutions discussed. The current practical

use shows already promising results, but further adjustments are certainly required. In addition, in future work, the

integration of sensor measurements like the collection of GPS positions or vital signs (e.g., heart rate) are planned.

To conclude, although many technical requirements had to be met, a feasible solution through the combination of

different paradigms could be achieved that is able to address the requirements. We consider technical solutions like

the one shown in this work as being decisive in the future research of medical questions in the daily life of patients.

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