Mobile Crowdsensing for the Juxtaposition of Realtime Assessments and
Retrospective Reporting for Neuropsychiatric Symptoms
R¨
udiger Pryss1, Thomas Probst1, Winfried Schlee2, Johannes Schobel1,
Berthold Langguth2, Patrick Neff3, Myra Spiliopoulou4, Manfred Reichert1
1Institute of Databases and Information Systems, Ulm University, Germany
2Clinic and Policlinic for Psychiatry and Psychotherapy, University of Regensburg, Germany
3Neuroplasticity and Learning in the Healthy Aging Brain, University of Zurich, Switzerland
4Department of Technical and Business Information Systems, Otto-von-Guericke-University Magdeburg, Germany
1{ruediger.pryss, thomas.probst, johannes.schobel, manfred.reichert}@uni-ulm.de
Abstract—Many symptoms of neuropsychiatric disorders
such as tinnitus are subjective and vary over time. Usually,
in interviews or self-report questionnaires, patients are asked
to report symptoms as well as their severity and duration
retrospectively. However, only little is known to what degree
such retrospective reports reflect the symptoms experienced in
daily life some time ago. Mobile technologies can help to bridge
this gap: mobile self-help services allow patients to record their
symptoms prospectively when (or shortly after) they occur in
daily life. In this study, we present results that we obtained with
the mobile crowdsensing platform TrackYourTinnitus to show
that there is a discrepancy between the prospective assessment
of symptom variability and the retrospective report thereof. To
be more precise, we evaluated the real-time entries provided to
the platform by individuals experiencing tinnitus. The results
indicate that mobile technologies like the TrackYourTinnitus
crowdsensing platform may go beyond the role of an assistive
service for patients by contributing to more accurate diagnosis
and, hence, to a more elaborated treatment.
Keywords-Prospective assessment of neuropsychiatric symp-
toms, retrospective assessment of neuropsychiatric symptoms,
self-help mobile applications, tinnitus, mobile data collection,
mobile crowdsensing services
I. INTRODUCTION
The assessment of neuropsychiatric symptoms is essen-
tial in medicine and psychology. For many neuropsychi-
atric disorders, the duration of the symptoms constitutes
an essential factor for diagnosis. Hence, physicians and
psychologists need not only reliably assess symptoms and
their severity, but also the duration the patient suffers from
the symptoms. For example, a major depressive episode can
only be diagnosed when the patients suffer from depressive
symptoms for at least two weeks. As indicators for most
of these symptoms are subjective, the assessment of the
symptoms and their duration is typically based on subjective,
retrospective reports of the patients. In this context, the
question emerges, to what degree the patients are able to
remember the severity and duration of the symptoms they
actually experienced. Mobile technologies can effectively
help to shed light on this question, and also enrich the
retrospective reports of the patients with descriptions of the
symptoms as they were perceived at the time they occurred.
In this work, we describe how the mobile crowdsensing
platform TrackYourTinnitus [1]–[3] offers prospective self-
reporting facilities to patients. We present findings that aim
to discover differences between prospective and retrospec-
tive assessments of symptom “tinnitus loudness”. Tinnitus
can be described as the phantom perception of sound;
depending on the definition of tinnitus and its duration,
the age, and the birth cohort, between 5.1% and 42.7% of
the population worldwide experience tinnitus at least once
in their lifetime [4]. Tinnitus is variable between patients
(inter-individual variability) and also within patients (intra-
individual variability). The treatment of tinnitus and the
early diagnosis of potential comorbidities require assess-
ments on several symptoms, including loudness and vari-
ation of the perceived sound(s), distress caused by tinnitus,
impact of tinnitus on sleeping behavior, comorbidities, social
activity, concentration, and so forth.
The limited (ecological) validity of retrospective self-
reports has been shown in several studies on other neu-
ropsychiatric disorders. For example, [5] assessed physical
activities of patients with eating disorders by retrospective
self-reports as well as by prospective assessments with an
accelerometer. Patients reported significantly less physical
activity retrospectively than what was measured prospec-
tively by the accelerometer. The authors of [6], in turn,
investigated retrospectively as well as prospectively assessed
anxiety and cognition in patients with agoraphobia. While
anxiety did not differ between retrospective and prospective
assessments, cognition differed.
Such results highlight the potential of Ecological Mo-
mentary Assessment (EMA; also known as: ambulatory
assessment & experience sampling) to support clinicians
in assessing neuropsychiatric symptoms accurately and in
making valid diagnoses. In EMA, the variable in question
(e.g., symptoms) is assessed repeatedly in daily life [7].
Instead of retrospectively asking the individuals (through an
interview or questionnaire) how strongly they experienced a
symptom in a given past time interval, the individuals are
asked how they currently experience the symptom. In turn,
this is done at several time points within the given time
interval.
In the aforementioned studies, prospective and retro-
spective assessments were juxtaposed manually. To exploit
effectively the prospective assessments in a clinical setting,
an integrated solution is needed, i.e., the EMA of a given
patient should be transferred automatically to a database
and be made available to the responsible clinician(s), given
the consent of the patients. Note that it has been already
reported that electronic systems are appreciated by study
participants [8], increase data accuracy [9], lead to more
complete datasets [10], and reduce costs [11] compared to
traditional paper-based methods. However, the exploitation
of the prospective assessments next to the retrospective
reports has not been investigated in the area of tinnitus yet.
This paper presents the TrackYourTinnitus (TYT) mobile
crowdsensing platform [1]–[3] for the juxtaposition of retro-
spective and prospective assessments of tinnitus-associated
neuropsychiatric symptoms. Further, with a focus on tinnitus
loudness, we elaborate in what way the prospective data are
collected and maintained for further usage.
Related work is discussed in Section II. In Section III,
we illustrate the mobile crowdsensing platform of TYT and
explain the workflow for the collection and maintenance of
prospective assessments. Section IV presents the data and the
statistics used for the juxtaposition of the prospective with
the retrospective assessments. In Section V, we present the
results of the statistical analyses, which suggest that integrat-
ing prospective assessments into the diagnostic-therapeutic
process is important for optimizing diagnostics and, hence,
treatments. Finally, a summary and an outlook is provided
in Section VI.
II. RELATED WORK
In general, mobile crowdsensing is an emerging research
topic in various application domains [12], [13]. Interestingly,
in the medical domain, mobile crowdsensing applications
have been less proposed so far. The fact that the medical
domain is less considered might be related to legal and data
privacy issues [14]. However, using mobile crowdsensing
in the medical context is promising [15] as mobile crowd-
sensing has unique features to gather valuable data [16]. In
particular, it allows gathering context-aware [17] as well as
daily-life data [18] more effectively.
Besides TrackYourTinnitus, two other studies presented
EMA approaches to track tinnitus in daily life [19], [20].
Furthermore, EMA approaches capturing other aspects such
as pain [21] and feelings [22] in daily life were scientifically
evaluated. In addition, EMA approaches were studied in the
areas of mood disorders and mood dysregulation [23], [24]
as well as in the ones of substance use [25] and eating
disorders [26]. In psychotherapy research, EMA has been
investigated as predictors of patient progress [27]. Although
most neuropsychiatric symptoms are subjective experiences
and, thus, most EMA approaches use self-reports to cap-
ture these symptoms, some neuropsychiatric symptoms are
behavioral (e.g., avoidance in anxiety disorders) or physi-
ological (e.g., increase of heart rate in anxiety disorders)
symptoms. Note that mobile systems offer opportunities to
measure behavioral or physiological data in daily life [28]. In
summary, EMA approaches are considered to offer unprece-
dented opportunities to study neuropsychiatric symptoms
under ecologically valid conditions [29], even though the
utilization of its possibilities is still in its infancy, especially
in the medical domain.
III. TRACKYOURTINNITUS PLATFORM
TrackYourTinnitus (TYT) is a mobile crowdsensing [12]
platform, which comprises a website for user registration,
two mobile applications (for iOS and Android), and a
MySQL database as a central repository for the data col-
lected [2], which can be made available to the clinicians
and researchers. The website further provides two other
important features: (1) users can visualize recorded tinnitus
data and (2) they can report on their current tinnitus treat-
ment. In general, TYT was developed to track the individual
tinnitus perception of users. In order to be able to track the
daily tinnitus perception, the following procedure must be
accomplished by a user (cf. Fig. 1).
First, users have to create a TYT account. The account
can be either created through the website or with the use of
the mobile applications.
Second, after registering, users have to fill in three
registration questionnaires (cf. Fig. 1). First, they have to
fill in the “Mini-TQ-12” questionnaire (cf. Fig. 1, Mini-
TQ-12 [30]), which measures tinnitus-related psychological
problems. Second, they have to fill in the “Tinnitus Sample
Case History Questionnaire (TSCHQ)” (cf. Fig. 1, TSCHQ
[31]). The latter determines the current tinnitus status of the
user as well as his tinnitus history. Note that the TSCHQ
questionnaire comprises the question being important for the
results of this paper. To be more precise, the 11th item of
the TSCHQ questionnaire [31] asks the user retrospectively
whether or not the tinnitus loudness varies from day to day.
Finally, users have to fill in the “Worst Symptom” ques-
tionnaire (cf. Fig. 1, Worst Symptom Questionnaire), which
asks the users about the worst symptom currently caused by
their tinnitus. While the first two questionnaires constitute
already used instruments, the third one was newly developed.
Altogether, the completion of the three questionnaires with
their 58 questions in total constitutes a prerequisite to be
able to use the TYT website features as well as the mobile
applications.
Third, after completing the registration questionnaires,
the user can use the mobile applications to track the daily
Figure 1: TrackYourTinnitus Crowdsensing Platform
tinnitus perception. For this purpose, the user has to log in to
the Android or iOS mobile application. Then, they are asked
to fill in the assessment questionnaire developed for TYT
(cf. Fig. 1, Assessment Questionnaire). This questionnaire
comprises 8 questions and rates the tinnitus perception of
the user (e.g., current tinnitus loudness).
Fourth, the assessment questionnaire is provided in two
ways: (1) the mobile application automatically provides the
questionnaire to the users or (2) they make the conscious
decision to fill in the questionnaire. The first way is the
desired procedure, which is realized as follows: The assess-
ment questionnaire is randomly presented to the user up to
12 times per day (i.e., users can define an individual time
schedule). Therefore, notification features for Android and
iOS as well as a notification algorithm were realized [2].
This procedure ensures that (1) users cannot foresee the
time when being asked and (2) users are asked in various
daily situations. This randomized approach was realized to
improve the ecological validity of the applied method.
Fifth, while filling in the assessment questionnaire, the
smart mobile device of a user records the environmental
sound level.
Finally, results gathered with the assessment question-
naire and sound recording are transferred to the TYT
database. The latter, in turn, offers features enabling re-
searchers to evaluate gathered user data. Note that this
feature was used for obtaining the presented results.
The TYT crowdsensing platform is currently provided in
English, German, and Dutch. The current number (February
2017) of processed questionnaires and registered users can
be obtained from Fig. 1. As can be seen, the TYT mobile
crowdsensing platform is frequently used. So far, users
from 80 countries have provided data to the platform. It
is noteworthy that users from seven countries provide the
major part of all gathered data. To be more precise, 35.4%
users come from Germany, 14.6% from the US, 5.8% from
the Netherlands, 5.8% from the UK, 3.7% from Switzer-
land, 3.3% from Canada, and 2.9% from France. Further
note that analyzing data gathered with mobile crowdsensing
techniques might reveal new valuable insights to tinnitus
[32] in particular and other chronic diseases in general.
IV. DATA AND STATISTICS
The current analysis relies on an export of the TYT
database made in February 2017.1In the current study, we
analyzed two variables. The first one assessed the variability
of tinnitus retrospectively. The following question, which
was asked once during the TYT registration process, was
used to measure retrospectively whether or not the tinnitus
loudness varies: “Does the LOUDNESS of the tinnitus vary
from day to day?” with the options to respond with “yes”
or “no”. The second variable measured tinnitus loudness
1That means, the 1291 users coming from the 80 countries provided
meaningful data sets for the presented analysis
prospectively. Thereby, the users rated at several points in
time during their daily life the following question “How
LOUD is the tinnitus right now?” with a slider ranging
from 0(i.e., not audible) to 1(i.e., maximal loudness).
To be able to compare the retrospective assessments on
day-to-day variation with the variation of the prospective
assessments, we had to focus our analysis on the day-to-
day variation (i.e., excluding within-day variation) of the
prospective assessments. Therefore, for each patient with
more than one prospective tinnitus loudness assessment per
day, we calculated the mean of their within-day prospec-
tive assessments in order to have one prospective loudness
assessment per day.
Then, the variability of these prospective loudness ratings
was calculated for each user as the standard deviation (SD)
of all their prospective loudness ratings (on a day-to-day
level). To obtain a meaningful day-to-day variability of
the prospective tinnitus loudness ratings, only those users
who provided a prospective tinnitus loudness assessment
at least at 10 days were investigated. We used a t-test for
independent samples (two-tailed, with p < 0.05 indicating a
statistically significant result) to evaluate whether the SD of
the prospective tinnitus loudness assessments belonging to
the users retrospectively describing their tinnitus loudness
as non-varying significantly differs from the SD of the
prospective tinnitus loudness assessments belonging to the
users retrospectively describing their tinnitus loudness as
varying. After applying these criteria, plus the exclusion of
assessments with an inter-assessment interval of 15 mins
or less [2], and the exclusion of a study sample recruited
differently (e.g., for specific studies) than the rest of the TYT
users, N= 260 users remained for the statistical analysis. Of
these N= 260 users, n= 47 (18%) reported retrospectively
that the tinnitus loudness does not vary from day to day and
n= 213 (82%) reported retrospectively that the tinnitus
loudness varies from day to day.
While the users retrospectively rating the tinnitus loud-
ness as stable provided prospective assessments of tinnitus
loudness for M= 37.57 (SE = 4.83) days (in an average
interval of M= 3.29 months), the users retrospectively
rating the tinnitus as varying provided data for M= 39.81
(SE = 3.65) days (in an average interval of M= 4.35
months). We also ran the statistical test for users with
prospective loudness assessments for at least 25 days in
order to investigate whether the results can be replicated.
After applying these stricter inclusion criteria, N= 128
users were remaining for the statistical analysis. Of these
users, n= 25 (20%) reported retrospectively that the tinnitus
loudness does not vary from day to day, whereas n= 103
(80%) reported retrospectively that the tinnitus loudness
varies from day to day. Here, the users retrospectively rating
the tinnitus loudness as stable provided prospective assess-
ments of tinnitus loudness for M= 56.60 (SE = 7.17)
days (average time interval the assessments were provided
in: M= 3.76 months), whereas the users retrospectively
rating the tinnitus as varying provided data for M= 66.16
(SE = 6.63) days (average time interval the assessments
were provided in: M= 4.87 months). In order to investigate
whether the TYT users retrospectively rating the tinnitus
loudness as non-varying differ in baseline variables from
users retrospectively rating the tinnitus loudness as varying,
independent t-tests and chi-squared tests were performed
(again two-tailed with p < 0.05 as statistical significance
level).
V. RESULTS
The comparisons between the users retrospectively rating
the tinnitus as not varying and the users retrospectively
rating the tinnitus as varying are given in Table I. It can
be seen that TYT users who retrospectively rated their
tinnitus loudness as non-varying from day to day did not
significantly differ in the average variation (SD) of the
prospective tinnitus loudness assessments from the TYT
users who retrospectively rated their tinnitus loudness as
varying from day to day. This result emerged when TYT
users providing prospective tinnitus loudness assessments
at least at 10 days were analyzed as well as when TYT
users providing prospective tinnitus loudness assessments at
least at 25 days were analyzed. Moreover, no significant
differences in baseline variables (i.e., gender, age, and tinni-
tus duration) were found between users with retrospectively
varying and users with retrospectively non-varying tinnitus
loudness. However, in the sample consisting of TYT users
with at least 10 prospective tinnitus loudness assessments,
male users (compared to female users) tended to retrospec-
tively rate the tinnitus loudness more frequently as non-
varying (p= 0.056) and the Mini-TQ-12 [30] score tended
to be higher for users who retrospectively rated the tinnitus
loudness as varying (p= 0.089). In summary, prospective
assessments offer information not covered by retrospective
ratings. This makes prospective assessments valuable for
diagnostics and treatments.
VI. SUMMARY AND OUTLOOK
The present study used data from a mobile crowdsens-
ing platform developed for tracking tinnitus in daily life.
Retrospective and prospective measurements of variations
of tinnitus loudness were compared against each other.
We found out that the prospectively measured variation
of tinnitus loudness is not significantly different between
individuals who retrospectively rated their tinnitus loudness
as non-varying and individuals who retrospectively rated
their tinnitus loudness as varying. This result is in line with
other studies showing that retrospective self-reports differ
from prospective assessments. Note that retrospective as-
sessments might be biased (i.e., recall bias). Another reason
in the context of our study could be that the individuals
who retrospectively rated their tinnitus as non-varying have
not understood the ups and downs of their tinnitus yet. In
psychotherapies with patients suffering from neuropsychi-
atric symptoms, it is often a first technique to assign the
homework to observe the symptoms in order to become
aware that the symptoms fluctuate and to learn which
factors influence the fluctuations. Possibly, individuals who
TYT users with prospective tinnitus loudness ratings for at least 10 days.
Retrospective
rating of
tinnitus
loudness
variation = no
Retrospective
rating of
tinnitus
loudness
variation = yes
Statistics
Male gender n
(%)
39 (84.8)150 (71.1)χ2(1) =
3.639;
p= 0.056
Age M
(SE)
45.6618
(1.8804)
47.4519
(0.7928)
t(235) =
−0.925;
p= 0.356
Tinnitus
duration
(subjective
report in years)
M (SE)
13.6569
(2.1066)
11.4626
(0.8217)
t(59.438) =
0.970;
p= 0.336
Mini-TQ-12
[30] score M
(SE)
11.9333
(0.7865)
13.5143
(0.3942)
t(253) =
−1.707;
p= 0.089
Variation (SD)
of the
prospective
tinnitus
loudness
assessments M
(SE)
0.148
(0.010)
0.145
(0.005)
t(258) =
0.194;
p= 0.846
TYT users with prospective tinnitus loudness ratings for at least 25 days.
Male gender n
(%)
21 (84.0)74 (72.5)χ2(1) =
1.397;
p= 0.237
Age M
(SE)
47.042
(2.430)
49.439
(1.047)
t(115) =
−0.976;
p= 0.331
Tinnitus
duration
(subjective
report in years)
M (SE)
16.563
(3.158)
12.215
(1.209)
t(31.393) =
1.286;
p= 0.208
Mini-TQ-12
[30] score M
(SE)
12.560
(1.033)
13.109
(0.525)
t(124) =
−0.467;
p= 0.641
Variation (SD)
of the
prospective
tinnitus
loudness
assessments M
(SE)
0.143
(0.014)
0.130
(0.006)
t(126) =
0.960;
p= 0.339
Results of the comparisons between TYT users retrospectively rating the
tinnitus loudness as non-varying and TYT users retrospectively rating the
tinnitus loudness as varying. Note: TYT = TrackYourTinnitus; M = Mean,
SD = Standard Deviation; Mini-TQ = Tinnitus Questionnaire Short Form
Table I: Results
retrospectively rate symptoms as varying are more trained
in self-observing strategies. It could be speculated in this
context that longer tinnitus duration increases self-observing
and that individuals with longer tinnitus duration rate the
tinnitus as non-varying more frequently. Yet, our results have
shown that the tinnitus duration did not significantly differ
between TYT users retrospectively rating the tinnitus as non-
varying and TYT users retrospectively rating the tinnitus
as varying. Nevertheless, individuals who retrospectively
assess the symptom as non-varying might gain a deeper
understanding of the symptom when receiving feedback on
the information that the symptom is prospectively varying.
In future studies, we plan to investigate whether it is helpful
for patients with tinnitus to receive feedback on tinnitus
fluctuations and on correlates of the fluctuations as stored in
the TYT platform.
Moreover, a database of EMA assessments could be used
to feed the patients’ experiences of neuropsychiatric symp-
toms in daily life back to the responsible clinician(s) (in case
the patient agrees with this procedure). This might be helpful
to improve the treatment [33] or to support the clinicians
in making diagnoses or case conceptualizations. The diag-
nostic procedure of neuropsychiatric symptoms is usually
time- and cost-intensive. Time and costs, in turn, might
be saved when patients use mobile systems in daily life
to assess neuropsychiatric symptoms prospectively before
the appointment for the diagnostic procedure takes place:
clinicians, who receive feedback on these assessments, could
then adjust the diagnostic procedures to the data and would
not have to evaluate the patients’ neuropsychiatric symptoms
retrospectively. In summary, mobile crowdsensing systems
capturing neuropsychiatric symptoms prospectively in daily
life appear to offer several advantages that warrant further
investigation and major breakthroughs in medical research.
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