ORIGINAL RESEARCH
published: 21 April 2017
doi: 10.3389/fnagi.2017.00113
Outpatient Tinnitus Clinic, Self-Help
Web Platform, or Mobile Application
to Recruit Tinnitus Study Samples?
Thomas Probst1,2*, Rüdiger C. Pryss2,Berthold Langguth3,Myra Spiliopoulou4,
Michael Landgrebe3,5,Markku Vesala6,Stephen Harrison6,Johannes Schobel2,
Manfred Reichert2,Michael Stach2and Winfried Schlee3
1Georg-Elias-Müller Institute for Psychology, Georg-August University Göttingen, Göttingen, Germany, 2Institute
of Databases and Information Systems, Ulm University, Ulm, Germany, 3Department of Psychiatry and Psychotherapy of the
University of Regensburg at Bezirksklinikum Regensburg, University of Regensburg, Regensburg, Germany, 4Department of
Technical and Business Information Systems, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany, 5Clinic
Lech-Mangfall, Agatharied, Germany, 6Tinnitus Hub Ltd, Hemsworth, UK
Edited by:
Junming Wang,
University of Mississippi Medical
Center, USA
Reviewed by:
Jae-Jin Song,
Seoul National University Bundang
Hospital, South Korea
Thomas Lee Eby,
University of Mississippi, USA
*Correspondence:
Thomas Probst
thomas.probst@ur.de
Received: 02 February 2017
Accepted: 06 April 2017
Published: 21 April 2017
Citation:
Probst T, Pryss RC, Langguth B,
Spiliopoulou M, Landgrebe M,
Vesala M, Harrison S, Schobel J,
Reichert M, Stach M and Schlee W
(2017) Outpatient Tinnitus Clinic,
Self-Help Web Platform, or Mobile
Application to Recruit Tinnitus
Study Samples?
Front. Aging Neurosci. 9:113.
doi: 10.3389/fnagi.2017.00113
For understanding the heterogeneity of tinnitus, large samples are required. However,
investigations on how samples recruited by different methods differ from each other
are lacking. In the present study, three large samples each recruited by different means
were compared: N= 5017 individuals registered at a self-help web platform for tinnitus
(crowdsourcing platform Tinnitus Talk), N= 867 users of a smart mobile application for
tinnitus (crowdsensing platform TrackYourTinnitus), and N= 3786 patients contacting
an outpatient tinnitus clinic (Tinnitus Center of the University Hospital Regensburg).
The three samples were compared regarding age, gender, and duration of tinnitus
(month or years perceiving tinnitus; subjective report) using chi-squared tests. The
three samples significantly differed from each other in age, gender and tinnitus duration
(p<0.05). Users of the TrackYourTinnitus crowdsensing platform were younger, users
of the Tinnitus Talk crowdsourcing platform had more often female gender, and users
of both newer technologies (crowdsourcing and crowdsensing) had more frequently
acute/subacute tinnitus (<3 months and 4–6 months) as well as a very long tinnitus
duration (>20 years). The implications of these findings for clinical research are that
newer technologies such as crowdsourcing and crowdsensing platforms offer the
possibility to reach individuals hard to get in contact with at an outpatient tinnitus clinic.
Depending on the aims and the inclusion/exclusion criteria of a given study, different
recruiting strategies (clinic and/or newer technologies) offer different advantages and
disadvantages. In general, the representativeness of study results might be increased
when tinnitus study samples are recruited in the clinic as well as via crowdsourcing and
crowdsensing.
Keywords: tinnitus, recruitment, crowdsourcing, crowdsensing, clinical data
INTRODUCTION
Tinnitus is characterized by the perception of a sound without a corresponding external sound
source (Baguley et al., 2013; Langguth et al., 2013). A recent review on prevalence rates of
tinnitus in 16 countries found that between 5.1% and 42.7% of the population report tinnitus
(McCormack et al., 2016). The prevalence rates typically vary depending on the age, the birth cohort
Frontiers in Aging Neuroscience | www.frontiersin.org 1April 2017 | Volume 9 | Article 113
Probst et al. Differences between Tinnitus Study Samples
(Nondahl et al., 2012; Martinez et al., 2015), and the definition
of tinnitus used in the epidemiological study (McCormack
et al., 2016). A recent US study found that 9.6% of Americans
experienced tinnitus in the last year and that only 49.4%
discussed the tinnitus with a physician (Bhatt et al., 2016). In
case tinnitus patients seen by physicians are not representative
for the whole sample of individuals perceiving tinnitus, the
representativeness of studies recruiting patients only in medical
practices or hospitals might be limited. In the area of anxiety
and depression, for example, researchers found differences
between patients contacting an outpatient clinic, patients
being treated in an Internet-based clinic, and individuals with
anxiety or depressive disorders from a national epidemiological
survey (Titov et al., 2010). Another study on Internet-based
psychotherapy for depression found that patients recruited
by online advertisements differed from patients recruited by
newspaper advertisements in demographics and depression
severity (Lindner et al., 2015).
In the case of tinnitus, several patient databases have been
established with the aim to better understand the heterogeneity of
tinnitus (Meikle, 1997; Landgrebe et al., 2010; Witsell et al., 2011).
However, all these databases collect data from patients who
present themselves at a tinnitus clinic. For investigating tinnitus
heterogeneity, it is of high importance to know how samples
recruited by different methods vary and which recruitment
methods are most efficient for the recruitment of specific tinnitus
subgroups.
Although the recruitment of individuals not contacting
physicians is traditionally difficult, online-recruitment has been
shown to be promising in clinical and health science to
overcome this obstacle (e.g., Morgan et al., 2013; Bevelander
et al., 2014; Gioia et al., 2016; Kayrouz et al., 2016; Thornton
et al., 2016; Topolovec-Vranic and Natarajan, 2016). In a
recent review on online-recruitment in health studies, Lane
et al. (2015) stated, though, that ‘‘more empirical evidence is
needed to make specific recommendations’’ (p. 1). The claim
for more empirical research might be especially relevant for
the relatively new participant-led research paradigm (Vayena
and Tasioulas, 2013) including crowdsourcing (e.g., Swan,
2012; Ranard et al., 2014; Chandler and Shapiro, 2016) and
crowdsensing (e.g., Ganti et al., 2011; Guo et al., 2014,
2015). ‘‘Crowdsourcing is a type of participative online
activity in which an individual, an institution, a non-profit
organization, or company proposes to a group of individuals
of varying knowledge, heterogeneity, and number, via a
flexible open call, the voluntary undertaking of a task. The
undertaking of the task, of variable complexity and modularity,
and in which the crowd should participate bringing their
work, money, knowledge and/or experience, always entails
mutual benefit. The user will receive the satisfaction of
a given type of need, be it economic, social recognition,
self-esteem, or the development of individual skills, while
the crowdsourcer will obtain and utilize to their advantage
what the user has brought to the venture, whose form
will depend on the type of activity undertaken’’ (Estellés-
Arolas and González-Ladrón-de-Guevara, 2012, p. 197). Guo
et al. (2015) defined mobile crowdsensing and computing
(MCSC) as follows: ‘‘MCSC extends the vision of participatory
sensing by leveraging both participatory sensory data from
mobile devices (offline) and user-contributed data from mobile
social networking services (online). Further, it explores the
complementary roles and presents the fusion/collaboration
of machine and human intelligence in the crowdsensing
and computing processes’’ (Guo et al., 2015, p. 1). In
contrast to crowdsourcing, crowdsensing relies solely on
mobile technology and integrates sensors to collect data, for
example, behavioral (e.g., physical activity level, gait pattern),
physiological (e.g., heart rate, electrodermal activity), and
environmental (e.g., environmental sound level, GPS location)
variables.
As it remains unclear whether online-recruitment by
crowdsourcing and crowdsensing offers the potential to reach
individuals with tinnitus that are different from the ones directly
consulting a physician, the study at hand compared tinnitus
patients visiting an outpatient tinnitus clinic, users of a tinnitus
crowdsourcing platform (moderated self-help web platform) and
users of a tinnitus crowdsensing platform (mobile application).
MATERIALS AND METHODS
Samples
The following three samples were investigated:
1. Tinnitus crowdsourcing sample ‘‘Tinnitus Talk’’: Tinnitus
Hub1operates the moderated self-help platform Tinnitus
Talk2. The platform was established in March 2011 by Markku
Vesala. With 16,500 registered participants (as of December
2016) and over 210,000 unique readers every month, Tinnitus
Talk is one of the most active tinnitus-dedicated platforms
for information delivery, experience exchange, and self-help
among individuals with tinnitus. The data of the present
study relies on a survey ran from February 8th till March
13th 2016.
2. Tinnitus crowdsensing sample ‘‘TrackYourTinnitus’’:
TrackYourTinnitus (TYT; Pryss et al., 2015a,b)3is an
application for mobile-devices (iOS and Android) that allows
the tracking of tinnitus in daily life by ecological momentary
assessments. Although monitoring tinnitus repeatedly directs
the attention towards the tinnitus, Schlee et al. (2016) showed
that using TYT does not deteriorate the tinnitus. Other studies
on TYT investigated the role of emotional states (Probst et al.,
2016a) as well as emotion dynamics (Probst et al., 2016b) in
tinnitus. The data presented here was collected from April
2014 to June 2016.
3. Outpatient tinnitus clinic sample ‘‘Tinnitus Center
Regensburg’’: The University Hospital Regensburg hosts
a tinnitus center4, established 2007, and having about
300 tinnitus patients per annum. To date (December 2016),
the Tinnitus database encompasses medical records for about
3000 patients.
1www.tinnitushub.com
2www.tinnitustalk.com
3www.trackyourtinnitus.org
4www.tinnituszentrum-regensburg.de
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Probst et al. Differences between Tinnitus Study Samples
At the Tinnitus Center Regensburg, patients gave written
informed consent that data were gathered and analyzed for the
Tinnitus Research Initiative Database, which was approved by
the Ethics Committee of the University Hospital of Regensburg.
The material and the methods of TrackYourTinnitus were
approved by the Ethics Committee of the University Hospital
Regensburg and were carried out in accordance with the
approved guidelines; written consent, however, was not possible
to obtain for the users of TrackYourTinnitus. Information
that the data will be used for scientific analyses is included
in the mobile applications as well as on the website and,
therefore, the TrackYourTinnitus users were informed that the
data will be used for scientific purposes. Written informed
consent was also not possible to obtain for the users of
Tinnitus Hub/Tinnitus Talk, but the ‘‘Terms and Rules’’ of
the website informed the users that the collected data will
be analyzed for scientific purposes. All the data were saved
anonymously.
Measures
Three variables were assessed in the three samples by self-reports:
age, gender, and duration of tinnitus (month or years perceiving
tinnitus; subjective report). In the Tinnitus Talk survey, the
variables age (<18 years, 18–24 years, . . .; see Table 1) and
tinnitus duration (<3 months, 4–6 months, . . .; see Table 1) were
assessed in categories. Therefore, the metric scores of age and
tinnitus duration as assessed in the Tinnitus Center Regensburg
and TrackYourTinnitus were categorized accordingly to be able
to perform statistical analyses.
Statistical Analysis
Chi-squared tests were performed with R and the significance
value was set to p<0.05.
TABLE 1 | Description of the three samples and comparisons between the
samples.
Tinnitus
Talk
TrackYour
Tinnitus
Tinnitus Center
Regensburg
Between-group
statistics
Total number 5017 867 3786
Age in years X2= 366.7;
%<18 1.0 1.6 0.5 p<0.001
% 18–24 5.4 4.4 2.4
% 25–34 11.4 20.7 6.6
% 35–44 13.6 22.5 15.7
% 45–55 20.9 26.5 29.6
% 55–64 30.2 18.9 26.7
% 65–74 15.1 5.2 15.5
%>75 2.4 0.3 3.1
Gender X2= 103.5;
% female 42.8 27.1 35.1 p<0.001
% male 57.2 72.9 64.9
Tinnitus duration X2= 393.7;
%<3 months 6.4 14.2 2.1 p<0.001
% 4–6 months 5.7 6.8 3.4
% 6–12 months 10.1 7.0 9.3
% 1–2 years 14.7 7.6 16.2
% 3–5 years 13.1 15.4 20.6
% 5–10 years 18.3 16.0 17.1
% 10–20 years 15.3 16.9 20.7
%>20 years 16.4 16.1 10.6
RESULTS
The three samples comprised N= 9670 individuals. Information
on age was available for n= 8766 individuals, information on
gender for n= 9607, and information on tinnitus duration for
n= 8409. Full descriptions of the samples are presented in
Table 1.
Age
A chi-squared test was calculated to test whether the distribution
of age (see Table 1;Figure 1) is different between the samples.
With an X2= 366.7, the hypothesis that the samples had an
equal age distribution was rejected (p<0.001). The most obvious
differences emerged in the percentage of individuals with an
age between 25 and 44 years as well as in the percentage of
individuals with an age between 55 and 74 years: The 25–44 years
aged individuals were more often among the TrackYourTinnitus
users (25–34 years: 20.7%; 35–44 years: 22.5%) than among the
Tinnitus Talk users (25–34 years: 11.4%; 35–44 years: 13.6%)
and among the patients of the Tinnitus Center Regensburg
(25–34 years: 6.6%; 35–44 years: 15.7%). Yet, the 55–74 years
aged adults were more frequently among the Tinnitus Talk
users (55–64 years: 30.2%; 65–74 years: 15.1%) and among the
patients at the Tinnitus Center Regensburg (55–64 years: 26.7%;
65–74 years: 15.5%) than among the TrackYourTinnitus users
(55–64 years: 18.9%; 65–74 years: 5.2%).
Gender
A chi-squared test was also calculated to investigate whether
the gender distribution of the three sample groups is equal
or different (see Table 1;Figure 2). Based on an X2= 103.5,
the hypothesis of an equal gender distribution was rejected
(p<0.001). Although the participants were more frequently
men than women in all three samples, TrackYourTinnitus
FIGURE 1 | Distribution of age in the three samples.
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Probst et al. Differences between Tinnitus Study Samples
FIGURE 2 | Distribution of gender in the three samples.
had the lowest rate of females (27.1%) and Tinnitus Talk the
highest (42.8%).
Tinnitus Duration
Again a chi-squared test was calculated to test whether the
distribution of tinnitus duration is equal or different between the
three samples (see Table 1;Figure 3). With an X2of 393.7, the
hypothesis of an equal tinnitus duration distribution was rejected
(p<0.001). Differences were apparent for individuals with a
tinnitus duration <3 months: 14.2% of the TrackYourTinnitus
users were in this category, but only 6.4% of the Tinnitus
Talk users and only 2.1% of the Tinnitus Center Regensburg
patients. However, TrackYourTinnitus users reported less often
1–2 years of tinnitus duration (7.6%) than Tinnitus Talk users
(14.7%) and patients at the Tinnitus Center Regensburg (16.2%).
The Tinnitus Center Regensburg patients reported more often
3–5 years and 10–20 years of tinnitus duration (3–5 years: 20.6%;
10–20 years: 20.7%) than Tinnitus Talk users (3–5 years: 13.1%;
10–20 years: 15.3%) and TrackYourTinnitus users (3–5 years:
15.4%; 10–20 years: 16.9%). The individuals with tinnitus
duration >20 years, however, were more frequently among
the Tinnitus Talk users (16.4%) and the TrackYourTinnitus
FIGURE 3 | Distribution of tinnitus duration in the three samples.
users (16.1%) than among the patients at the Tinnitus Center
Regensburg (10.6%).
DISCUSSION
The study at hand compared individuals contacting an outpatient
tinnitus clinic (Tinnitus Center Regensburg), individuals
registered at a self-help web platform (crowdsourcing platform
Tinnitus Talk) and users of an application for mobile devices
(crowdsensing platform TrackYourTinnitus). The aim of
the study was to investigate whether newer technologies
(crowdsourcing and/or crowdsensing) offer possibilities for
future studies to reach individuals with tinnitus that are different
from the ones directly contacting an outpatient clinic. In
summary, we found that the samples differed in the investigated
variables. The result that patients of an outpatient clinic differed
from users of newer technologies is in line with a study on
anxiety and depression comparing patients of an outpatient
clinic with those attending an Internet clinic (Titov et al., 2010).
Moreover the results of the current study correspond with a
recent review (Topolovec-Vranic and Natarajan, 2016), which
reported that populations recruited by traditional methods were
not comparable to samples recruited by newer technologies
(the review focused on social media) in most of the studies
(12 vs. 2).
One of the variables investigated in the present study was
age. The results revealed that younger individuals (≤44 years)
used more frequently the crowdsensing platform for tinnitus,
whereas older individuals (≥55 years) were more often among
the users of the crowdsourcing platform for tinnitus as well
as among the patients of an outpatient tinnitus clinic. Thus,
crowdsensing might be potent to recruit younger individuals
but not as suited for the recruitment of older individuals.
Nevertheless, crowdsensing might be appropriate to recruit older
individuals in the future as the younger generation (which now
uses crowdsensing) becomes older.
Another evaluated variable in the current study was gender.
Gender was predominately male in all three samples and
this result is in line with previous research on tinnitus: ‘‘In
fact, most previous studies, but not all . . . showed higher
tinnitus prevalence in men than in women’’ (Gallus et al.,
2015; p. 16). The crowdsourcing platform Tinnitus Talk had
the highest percentage of female individuals, whereas the
crowdsensing platform TrackYourTinnitus had the lowest.
Therefore, crowdsourcing might be more appropriate than
crowdsensing when aiming to recruit women by newer
technologies.
The third investigated variable in the study at hand was
tinnitus duration (month or years perceiving tinnitus; subjective
report). Duration of tinnitus is clinically and scientifically
relevant to define acute, subacute and chronic tinnitus. The
results of the current study revealed that acute and subacute
tinnitus are more frequent among the users of crowdsourcing
and crowdsensing platforms than among the patients of an
outpatient clinic. Long waiting times for appointments in
specialized tinnitus clinic might contribute to this effect.
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Probst et al. Differences between Tinnitus Study Samples
Regardless the reasons for the delay in seeing a specialist, our data
indicate that individuals with tinnitus search for information
or help in the Internet already early after symptom onset. As
interventions are already helpful in the acute and subacute
stages of tinnitus (Nyenhuis et al., 2013b) and might prevent
a chronic course, offering helpful interventions for individuals
with acute and subacute tinnitus is crucial. As more of these
individuals can be reached by crowdsourcing or crowdsensing
platforms than by an outpatient clinic, the implementation
of appropriate self-help interventions in crowdsourcing or
crowdsensing platforms might be promising (e.g., Heron and
Smyth, 2010; Donker et al., 2013). The finding that Internet-
based self-help is as effective as face-to-face interventions for
tinnitus patients (e.g., Nyenhuis et al., 2013a; Jasper et al., 2014;
Andersson, 2015) supports this line of argumentation. Another
interesting result in the context of tinnitus duration was that
individuals who perceived their tinnitus for a very long time
(>20 years), were more frequent among the crowdsourcing and
crowdsensing samples than among the sample of the outpatient
clinic. It could be speculated that these individuals experienced
past treatments as ineffective and consequently gave up seeking
medical or psychological help (learned helplessness; Abramson
et al., 1978) or have already established effective coping strategies.
These individuals will not contact a physician or a clinic,
although interventions, which these individuals have not tried
yet, might be helpful. These findings at least suggest that it
might be useful to provide information about interventions and
current innovative treatment approaches in crowdsourcing or
crowdsensing platforms.
One limitation of the study at hand is that we analyzed
only one crowdsourcing platform for tinnitus, only one
crowdsensing platform for tinnitus, and only one outpatient
tinnitus clinic. Although our samples are relatively large, even
more representative results might be obtained by multicenter
studies including several clinics and several crowdsourcing (two
crowdsourcing platforms were investigated, for example, by
Briones and Benham, 2017) as well as several crowdsensing
platforms. Another shortcoming of the crowdsourced and
crowdsensed data is that the robustness and accuracy of the
online-collected data is difficult to verify. Previous studies could,
however, provide support for the trustworthiness of web-based
research (e.g., Meyerson and Tryon, 2003; Gosling et al.,
2004). Moreover comparisons with data from population-based
epidemiological studies (see Titov et al., 2010) would be desirable
to identify how representative the three samples of the current
study are for the total tinnitus population. We abstained from
such a comparison, since data from available epidemiological
studies are highly variable (McCormack et al., 2016). Finally,
since clinical variables were not assessed in all three samples,
we could not compare the three samples regarding clinical
characteristics of tinnitus (e.g., tinnitus severity). Tinnitus
severity is usually important in the recruitment process of clinical
studies and usually is measured by psychometrically sound
instruments such as the ‘‘Tinnitus Handicap Inventory’’ (THI;
Newman et al., 1996). Those who use an app or online site may
have less bothersome tinnitus and may have no intention of
seeking medical attention. At least some may be just curious but
not need any treatment or intervention. Comparing the severity
of these groups is an important task for future research to clarify
whether recruiting individuals with tinnitus using a tinnitus app
or website will aid our understanding of bothersome tinnitus.
Such further studies will aid to find the best recruitment strategy
for a given study.
Despite these limitations, the current study is the first one
comparing tinnitus patients of an outpatient clinic with users
of crowdsourcing and crowdsensing platforms for tinnitus.
We showed that these newer technologies offer promising
perspectives to reach individuals hard to get in contact with at
an outpatient tinnitus clinic (e.g., individuals with acute/subacute
tinnitus, younger individuals, as well as individuals perceiving
tinnitus for a very long time).
AUTHOR CONTRIBUTIONS
TP substantially contributed to the design of the study and
data preparation, drafted and revised the manuscript. RCP
substantially contributed to the design of the study, data
preparation, the TrackYourTinnitus platform and revised the
manuscript. BL substantially contributed to the design of the
study, data collection at the Tinnitus Center Regensburg,
the TrackYourTinnitus platform and revised the manuscript.
MS substantially contributed to the design of the study and
revised the manuscript. ML substantially contributed to the data
collection at the Tinnitus Center Regensburg and revised the
manuscript. MV and SH substantially contributed to the Tinnitus
Talk platform, and revised the manuscript. JS, MR and MS
substantially contributed to the TrackYourTinnitus platform,
and revised the manuscript. WS substantially contributed to the
design of the study, the TrackYourTinnitus platform, drafted and
revised the manuscript, and performed the statistical analyses.
ACKNOWLEDGMENTS
This work was supported by the German Research Foundation
(DFG) within the funding programme Open Access Publishing.
The authors would like to thank Ankur Bahre (Otto-von-
Guericke-University Magdeburg) for providing helpful
references and Vishnu Unnikrishnan (Otto-von-Guericke-
University Magdeburg) for the statistical work with the three
samples.
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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
The reviewer TLE and handling Editor declared their shared affiliation, and the
handling Editor states that the process nevertheless met the standards of a fair and
objective review.
Copyright © 2017 Probst, Pryss, Langguth, Spiliopoulou, Landgrebe, Vesala,
Harrison, Schobel, Reichert, Stach and Schlee. This is an open-access article
distributed under the terms of the Creative Commons Attribution License (CC BY).
The use, distribution or reproduction in other forums is permitted, provided the
original author(s) or licensor are credited and that the original publication in this
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or reproduction is permitted which does not comply with these terms.
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