Does tinnitus depend on time-of-day? An ecological momentary assessment study with the “TrackYourTinnitus” application [original]

ORIGINAL RESEARCH

published: 02 August 2017

doi: 10.3389/fnagi.2017.00253

Frontiers in Aging Neuroscience | www.frontiersin.org 1August 2017 | Volume 9 | Article 253

Edited by:

Christopher R. Cederroth,

Karolinska Institutet, Sweden

Reviewed by:

Karl Bechter,

University of Ulm, Germany

Robert D. Frisina,

University of South Florida,

United States

*Correspondence:

Thomas Probst

[email protected]

†These authors shared

senior-authorship.

Received: 07 January 2017

Accepted: 17 July 2017

Published: 02 August 2017

Citation:

Probst T, Pryss RC, Langguth B,

Rauschecker JP, Schobel J,

Reichert M, Spiliopoulou M, Schlee W

and Zimmermann J (2017) Does

Tinnitus Depend on Time-of-Day? An

Ecological Momentary Assessment

Study with the “TrackYourTinnitus”

Application.

Front. Aging Neurosci. 9:253.

doi: 10.3389/fnagi.2017.00253

Does Tinnitus Depend on

Time-of-Day? An Ecological

Momentary Assessment Study with

the “TrackYourTinnitus” Application

Thomas Probst1, 2*, Rüdiger C. Pryss2, Berthold Langguth3, Josef P. Rauschecker4, 5,

Johannes Schobel2, Manfred Reichert2, Myra Spiliopoulou6, Winfried Schlee3 † and

Johannes Zimmermann7 †

1Georg-Elias-Müller-Institute for Psychology, Georg-August-University Göttingen, Göttingen, Germany, 2Department for

Psychotherapy and Biopsychosocial Health, Danube University Krems, Krems an der Donau, Austria, 3Department of

Psychiatry and Psychotherapy of the University of Regensburg at Bezirksklinikum Regensburg, Regensburg, Germany,

4Program in Cognitive and Computational Systems, Georgetown University Washington, Washington, DC, United States,

5Institute for Advanced Study, Technical University Munich, Munich, Germany, 6Department of Technical and Business

Information Systems, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany, 7Psychologische Hochschule Berlin,

Berlin, Germany

Only few previous studies used ecological momentary assessments to explore the

time-of-day-dependence of tinnitus. The present study used data from the mobile

application “TrackYourTinnitus” to explore whether tinnitus loudness and tinnitus distress

fluctuate within a 24-h interval. Multilevel models were performed to account for the

nested structure of assessments (level 1: 17,209 daily life assessments) nested within

days (level 2: 3,570 days with at least three completed assessments), and days nested

within participants (level 3: 350 participants). Results revealed a time-of-day-dependence

of tinnitus. In particular, tinnitus was perceived as louder and more distressing during the

night and early morning hours (from 12 a.m. to 8 a.m.) than during the upcoming day.

Since previous studies suggested that stress (and stress-associated hormones) show

a circadian rhythm and this might influence the time-of-day-dependence of tinnitus,

we evaluated whether the described results change when statistically controlling for

subjectively reported stress-levels. Correcting for subjective stress-levels, however, did

not change the result that tinnitus (loudness and distress) was most severe at night

and early morning. These results show that time-of-day contributes to the level of both

tinnitus loudness and tinnitus distress. Possible implications of our results for the clinical

management of tinnitus are that tailoring the timing of therapeutic interventions to the

circadian rhythm of individual patients (chronotherapy) might be promising.

Keywords: tinnitus, stress, circadian fluctuation, time-of-day, ecological momentary assessment

INTRODUCTION

Tinnitus, the phantom perception of sound (Baguley et al., 2013; Langguth et al., 2013), is perceived

by 5.1% up to 42.7% of the population according to a recent review including 39 studies from 16

countries (McCormack et al., 2016). These percentages depend on age (with older persons showing

higher prevalence), gender (with male persons showing higher prevalence), and the definition of

Probst et al. Does Tinnitus Depend on Time-of-Day?

tinnitus used in the epidemiological study (McCormack et al.,

2016). Prevalence rates of tinnitus also have increased over the

years (Nondahl et al., 2012; Martinez et al., 2015), and one

can speculate about the reasons for this apparent increase. On

a neuronal basis, auditory-limbic interactions play a central

role in the development of (chronic) tinnitus (Rauschecker

et al., 2010; Leaver et al., 2011). In many cases, tinnitus is

associated with psychological distress and incapacity for work

(Bhatt et al., 2016) resulting in high socio-economic costs (Maes

et al., 2013). Cognitive-behavioral therapy (CBT) has proven

to have the potential to reduce the burden of tinnitus for the

individual (Hesser et al., 2011) as well as the society/economy

(Maes et al., 2014). But not all tinnitus patients reach clinically

relevant improvements with CBT (e.g., Jasper et al., 2014). Other

therapeutic approaches, including pharmacological therapy

(Langguth and Elgoyhen, 2012), auditory stimulation (Hobson

et al., 2012) or brain stimulation (Langguth and De Ridder, 2013),

have only revealed small and inconsistent effects in subgroups

of patients. It is assumed that an important reason for the

poor treatment response in clinical trials is the heterogeneity

of tinnitus (Landgrebe et al., 2012; Baguley et al., 2013), both

across patients (inter-individual heterogeneity) as well as within

patients over time (intra-individual heterogeneity, see Dauman

et al., 2015).

Therefore, it is important to understand the factors that

contribute to the heterogeneity of tinnitus. Psychological

variables, such as fear-related cognition (e.g., Cima et al.,

2011; Kleinstäuber et al., 2013), an accepting stance toward

tinnitus (e.g., Weise et al., 2013; Riedl et al., 2015), emotions

(e.g., Probst et al., 2016a,b), and avoidance/safety behaviors

(e.g., Hesser and Andersson, 2009; Kleinstäuber et al., 2013),

have been demonstrated to account for the heterogeneity of

tinnitus in several studies (see also the “scientific cognitive-

behavioral model of tinnitus”; McKenna et al., 2014). Moreover,

recent neuroscience studies imply that the moment-to-moment

variability of tinnitus is related to brain oscillatory patterns

like the alpha power in temporal regions (Schlee et al., 2014)

and time-of-day (Basinou et al., 2017); circadian fluctuations

have been shown, for example, in auditory pathway structures

related to tinnitus like the cochlea (Meltser et al., 2014) and

the inferior colliculus (Park et al., 2016). Another hint for a

link between tinnitus and circadian rhythms is provided by

findings of reduced tinnitus severity after intake of melatonin

(e.g., Pirodda et al., 2010; Ajayi et al., 2014; Miroddi et al., 2015).

Furthermore, pain, which shares many similarities with tinnitus

(De Ridder et al., 2011; Rauschecker et al., 2015), has been found

to underlie circadian variations (e.g., Strian et al., 1989; Gilron

and Ghasemlou, 2014; Buttgereit et al., 2015). Furthermore,

depression, which overlaps in its pathophysiology with tinnitus

(Langguth et al., 2011), is characterized by changes in circadian

rhythm (e.g., Germain and Kupfer, 2008; Wirz-Justice, 2008).

The question of whether tinnitus varies systematically

over the course of the day, however, has not yet been

studied systematically. The limited possibilities of traditional

assessment methods to routinely track symptoms in the

daily routine have made it rather difficult to validly study

whether tinnitus shows time-of-day-dependence. To overcome

these limitations of traditional assessment methods, newer

technological developments can be used to electronically gather

valid daily life data (ecological momentary assessments, EMA;

Trull and Ebner-Priemer, 2013, 2014; Adams et al., 2017). Henry

et al. (2012), for example, used personal digital assistants (PDA)

in a 2-week pilot study with 24 participants to obtain EMA during

a 12-h interval (8 a.m.–8 p.m.) and showed that the scores of the

10-item screening version of the Tinnitus Handicap Inventory

(THI-S; Newman et al., 2008) were not significantly different

between 3-h time blocks (8 a.m.–11 a.m., 11 a.m.–2 p.m., 2 p.m.–

5 p.m., and 5 p.m.–8 p.m.). Although Henry et al. (2012) failed to

demonstrate time-of-day-dependence of tinnitus, a 2-week pilot

smartphone-based study with 20 participants on fluctuations of

tinnitus within an 11-h interval (9 a.m.–8 p.m.) suggested that

tinnitus does vary within a single day (Wilson et al., 2015).

But Wilson et al. (2015) did not report at which time-of-day

the participants rated their tinnitus as more or less severe. In

another diary study, Flor et al. (2004) reported tinnitus being

worst at the beginning of a day, thus supporting the time-of-day-

dependence of tinnitus. To our knowledge there are only these

three studies with ambivalent results that addressed the time-of-

day-dependence of tinnitus in daily life with EMA (Flor et al.,

2004; Henry et al., 2012; Wilson et al., 2015).

The current study used EMA from the “TrackYourTinnitus”

(TYT) mobile application (Pryss et al., 2015a,b; Schlee et al.,

2016) to explore whether tinnitus fluctuates within a 24-h

interval (night and upcoming day). Tinnitus is operationalized

by two questions in TYT, one question is on tinnitus loudness

and the other question on tinnitus distress. Prior research

suggested that an assessment of both tinnitus loudness and

tinnitus distress is necessary for a comprehensive assessment,

since tinnitus loudness and tinnitus distress are only moderately

correlated (e.g., Hiller and Goebel, 2007; Wallhäusser-Franke

et al., 2012) and processed in different but interconnected

brain areas (e.g., Leaver et al., 2012; Ueyama et al., 2013;

De Ridder et al., 2014; Vanneste et al., 2014). Therefore, it

appears possible that tinnitus loudness and tinnitus distress

show either similar or different ups and downs within a 24-h

interval. Accordingly, the present study investigated the time-

of-day-dependence of tinnitus loudness as well as of tinnitus

distress. Moreover, stress is known to be associated with tinnitus

(e.g., Hébert et al., 2004; Hébert and Lupien, 2007, 2009;

Alsalman et al., 2016) and stress-related hormones like cortisol

and adrenocorticotropic hormone (ACTH) underlie circadian

rhythms (e.g., Dickmeis, 2009; Lightman and Conway-Campbell,

2010; Conway-Campbell et al., 2012), which could influence

the potential time-of-day-dependence of tinnitus (loudness and

distress). Thus, we also explored whether the stress-level as

assessed with TYT depends on time-of-day and whether the 24-

h fluctuations of tinnitus loudness and tinnitus distress change

when taking the stress-level into account.

MATERIALS AND METHODS

The material and the methods were approved by the Ethics

Committee of the University Clinic of Regensburg and were

Frontiers in Aging Neuroscience | www.frontiersin.org 2August 2017 | Volume 9 | Article 253

Probst et al. Does Tinnitus Depend on Time-of-Day?

carried out in accordance with the approved guidelines.

Information that the TYT data will be used for scientific analyses

is included in the mobile applications of “TrackYourTinnitus”

as well as on the “TrackYourTinnitus” website and, therefore,

the TYT users were informed that the data will be used for

scientific purposes. Written consent, however, was not possible

to obtain given the nature of the study. The study participants

were anonymized.

“TrackYourTinnitus” Platform

The TYT platform (www.trackyourtinnitus.org, Pryss et al.,

2015a,b) consists of a website for registration, two mobile

applications (for iOS and Android), and a MySQL database as

a central repository for the data collected. Users can either use

TYT whenever they want or they can set a user-defined schedule

to receive random notifications. For the study at hand, only these

notification-triggered assessments were investigated. At each of

these notifications, the users are asked to rate their tinnitus

and other tinnitus-related variables (e.g., subjective stress-level).

Although the attention might be directed toward the tinnitus by

such notifications, Henry et al. (2012) and Schlee et al. (2016)

found that repeatedly rating tinnitus and associated variables in

daily life does not have detrimental effects. The present study

investigated the following variables the users were asked to

rate at each notification: “Current tinnitus loudness” (subjective

rating of current tinnitus loudness on a visual analog scale

[VAS], including a zero value for moments without loudness:

min: 0; max: 1), “current tinnitus distress” (subjective rating of

current tinnitus distress on a VAS including a zero value for

moments without distress: min: 0; max: 1), and “current stress-

level” (subjective rating of current stress-level on a VAS: min: 0;

max: 1). Moreover, the timestamps of the assessments were used

to explore the time-of-day-dependence of tinnitus. In TYT, the

timestamps represent the local time of the time zone a given user

is in when providing the assessments.

The data set used for the current study was exported in

June 2016. After excluding the self-initiated assessments and the

assessments given within the 15 min after the last assessment

(for the inter-assessment interval of 15 min see also Pryss

et al., 2015b), we had access to 25,863 notification-triggered

assessments. For the present study, we only included the 25,092

assessments without missing values in any of the three target

variables. Furthermore, as we were interested in within-day

variations, we only considered data from days with at least three

completed assessments, resulting in a total number of 17,209

assessments.

Sample

The final sample consisted of 350 participants. Two-hundred

and fifty three participants (72.2%) were male, 94 (26.9%)

were female, and 3 did not indicate their gender. On average,

participants were 45.4 (SD =12.1) years old (17 participants

did not report their age). The median number of years since

onset of tinnitus was 5.4, ranging from 0 to 61.8 years. According

to participants, onset of tinnitus was related to loud blast of

sound (n=48), whiplash (n=9), change in hearing (n=38),

stress (n=99), head trauma (n=12), and other causes (n=

141) (3 participants did not report events related to onset of

tinnitus). The median number of days per participant (with at

least three assessments) was 11, ranging from 1 to 415 days. This

corresponds to a total number of 3,570 days. The median number

of assessments per day was 4, ranging from 3 (the minimum

requirement to be included in this study) to 18 assessments.

Statistical Analyses

To test our hypotheses, we used multilevel modeling (MLM;

Raudenbush and Bryk, 2002; Singer and Willett, 2003). MLM

is ideally suited to address the nested structure of our data,

with assessments (Level 1) nested in days (Level 2), and days

nested in participants (Level 3). First, we estimated two MLMs

predicting tinnitus loudness and tinnitus distress from time-

of-day, respectively. Time-of-day was dummy-coded using five

binary variables indicating whether the assessment was in the

early morning (T1, from 4 a.m. to 8 a.m.), in the late morning

(T2, from 8 a.m. to 12 p.m.), in the afternoon (T3, from 12 p.m.

to 4 p.m.), in the early evening (T4, from 4 p.m. to 8 p.m.), or in

the late evening (T5, from 8 p.m. to 12 a.m.). Assessments during

the night (from 12 a.m. to 4 a.m.) were defined as the reference

group. The full three-level MLM with random intercepts at Level

2 and 3 and random slopes at Level 3 (Model I) is summarized

below:

Level 1: yijk =π0jk +π1jk (T1)+π2jk (T2)+π3jk (T3)

+π4jk (T4)+π5jk (T5)+eijk

Level 2: π0jk =β00k+r0jk

π1jk =β10k

π2jk =β20k

π3jk =β30k

π4jk =β40k

π5jk =β50k

Level 3: β00k=γ000 +u00k

β10k=γ100 +u10k

β20k=γ200 +u20k

β30k=γ300 +u30k

β40k=γ400 +u40k

β50k=γ500 +u50k

The model decomposes the amount of tinnitus loudness/distress

(y) of participant kon day jat assessment iinto a series

of fixed and random effects. The fixed effect γ000 represents

the expected (population) tinnitus loudness/distress during the

night before an average day of an average participant. The fixed

effects γ100,γ200,γ300,γ400, and γ500 represent the expected

change in tinnitus loudness/distress from night to early and

late morning, afternoon and early and late evening, respectively.

The random effects at Level 3, u00k,u10k,u20k,u30k,u40k, and

u50k, indicate that the level of tinnitus loudness/distress at night

as well as its later change during the day may differ between

participants. The random intercept at Level 2, r0jk, indicates

that the baseline level of tinnitus loudness/distress may differ

between days within participants. We assumed random effects to

be multivariate normally distributed within levels, and residuals

to be independent and identically distributed across levels.

Frontiers in Aging Neuroscience | www.frontiersin.org 3August 2017 | Volume 9 | Article 253

Probst et al. Does Tinnitus Depend on Time-of-Day?

Second, we estimated the same MLM for stress-level as the

dependent variable (y). Moreover, we estimated two further

MLMs predicting tinnitus loudness and tinnitus distress from

time-of-day, this time including stress-level as an additional

predictor. As stress-level varied across all three levels, we

decomposed its variance into three separate mean-centered

variables capturing variation of stress within days (S1), variation

of stress within participants across days (S2), and variation of

stress across participants (S3) prior to estimating the MLMs. The

full three-level MLM with random intercepts at Level 2 and 3 and

random slopes at Level 3 (Model II) is summarized below:

Level 1: yijk =π0jk +π1jk (T1)+π2jk (T2)+π3jk (T3)

+π4jk (T4)+π5jk (T5)+π6jk (S1)+eijk

Level 2: π0jk =β00k+β01k(S2)+r0jk

π1jk =β10k

π2jk =β20k

π3jk =β30k

π4jk =β40k

π5jk =β50k

π6jk =β60k

Level 3: β00k=γ000 +γ001 (S3)+u00k

β01k=γ010 +u01k

β10k=γ100 +u10k

β20k=γ200 +u20k

β30k=γ300 +u30k

β40k=γ400 +u40k

β50k=γ500 +u50k

β60k=γ600 +u60k

The newly defined fixed effects, γ001,γ010, and γ600, represent

the expected between-participant, between-day, and within-day

effect of stress on tinnitus loudness/distress after controlling

for time-of-day. The remaining fixed effects, γ000,γ100,γ200,

γ300,γ400, and γ500, represent the expected level of tinnitus

loudness/distress at night as well as its later change during

the day after controlling for the influence of stress. The newly

defined random effects, u01kand u60k, indicate that the between-

and within-day effects of stress may differ between participants.

Due to model identification issues, we restricted the covariances

between random effects of stress and the remaining random

effects in the model to be zero.

All models were estimated using full maximum likelihood

estimation. Analyses were conducted with the package “lme4”

(Bates et al., 2015) of the statistical platform R (R Core Team,

2015). We used Satterthwaite’s approximations to derive p-values

for fixed effects. Pairwise comparisons between the six distinct

timeframes were explored using the Tukey Honest Significant

Difference method as implemented in the package “multcomp”

(Hothorn et al., 2008). Finally, we quantified the effect size of

time-of-day on tinnitus loudness/distress by means of a pseudo

R2statistic. This statistic can be computed by subtracting the

residual variance Var(eijk) of Model I from the residual variance

of an intercept-only model without any predictors, divided by

this latter residual variance. It represents the relative amount

of variance in tinnitus loudness/distress within days that is

explained by time-of-day (i.e., by the five variables T1–T5).

RESULTS

In total, 186 assessments (1.1%) were completed at night,

460 (2.7%) were completed in the early morning, 4,200

(24.4%) were completed in the late morning, 4,941 (28.7%)

in the afternoon, 4,724 (27.5%) in the early evening, and

2,698 (15.7%) were completed in the late evening (see

Figure 1). Table 1 summarizes the estimated fixed effects of

all MLMs (standard deviations and correlations of random

effects can be found in the Supplementary Material). Results

suggest that tinnitus was louder and more distressing during

the night and early morning hours than during all other

timeframes of the day (see Models I in the first and third

columns of Table 1). Tukey’s post-hoc tests revealed that

differences between late morning, afternoon, and early evening

were non-significant (see Table 2). However, tinnitus was

significantly louder in the late evening compared to the afternoon

and early evening. This pattern of results is visualized in

Figures 2A,B. The pseudo R2statistics revealed that time-of-

day explained 20.6% of the within-day variance of tinnitus

loudness, and 13.0% of the within-day variance of tinnitus

distress.

Next, we tested whether time-of-day influences the subjective

stress-level (see Model I in the right hand column of Table 1

and Figure 2C). Tukey’s post-hoc tests suggested that stress-level

increased from morning to afternoon, decreased from afternoon

to evening, and did not differ compared to the night (see Table 2).

Time-of-day explained 7.8% of the within-day variance of

stress.

Finally, the models predicting tinnitus loudness and tinnitus

distress from time-of-day and stress-level revealed that the

stress-level had incremental effects across all three levels (see

Models II in Table 1): Tinnitus was louder and more distressing

when the level of stress was higher at a specific time-of-

day compared to other times-of-day, when it was higher

during a whole day compared to other days, and when it

was higher during the whole assessment period for a given

participant (compared to other participants). Nevertheless, the

effects of time-of-day on tinnitus loudness and tinnitus distress

500

1000

1500

0 6 12 18 24

Hour

Data points

FIGURE 1 | Number of data points per hour.

Frontiers in Aging Neuroscience | www.frontiersin.org 4August 2017 | Volume 9 | Article 253

Probst et al. Does Tinnitus Depend on Time-of-Day?

TABLE 1 | Estimated fixed effects (and their standard errors) for five MLMs.

Tinnitus loudness Tinnitus distress Stress-level

Model I Model II Model I Model II Model I

Intercept (night) γ000 0.529*** (0.021) 0.521*** (0.018) 0.435*** (0.021) 0.423*** (0.016) 0.303*** (0.020)

Early morning (vs. night) effect γ100 −0.017 (0.021) −0.015 (0.019) −0.015 (0.022) −0.014 (0.018) −0.015 (0.020)

Late morning (vs. night) effect γ200 −0.089*** (0.019) −0.086*** (0.017) −0.083*** (0.020) −0.077*** (0.016) 0.009 (0.019)

Afternoon (vs. night) effect γ300 −0.098*** (0.019) −0.099*** (0.017) −0.083*** (0.019) −0.083*** (0.016) 0.023 (0.018)

Early evening (vs. night) effect γ400 −0.093*** (0.019) −0.092*** (0.017) −0.080*** (0.020) −0.074*** (0.015) 0.006 (0.018)

Late evening (vs. night) effect γ500 −0.071*** (0.019) −0.062*** (0.016) −0.066*** (0.019) −0.052*** (0.014) −0.023 (0.018)

Within-day effect of stress γ600 0.287*** (0.020) 0.370*** (0.022)

Between-day effect of stress γ010 0.470*** (0.037) 0.585*** (0.035)

Between-person effect of stress γ001 0.651*** (0.051) 0.810*** (0.041)

Total number of assessments was 17,209. p-values were based on Satterthwaite’s approximations. ***p<0.001. night =12 a.m.–4 a.m. early morning =4 a.m.–8 a.m. late morning

=8 a.m.–12 p.m. afternoon =12 p.m.–4 p.m. early evening =4 p.m.–8 p.m. late evening =8 p.m.–12 a.m.

TABLE 2 | Tukey’s post-hoc tests for five MLMs.

Tinnitus loudness Tinnitus distress Stress-level

Model I Model II Model I Model II Model I

Early_morning–night −0.017 (0.021) −0.015 (0.019) −0.015 (0.022) −0.014 (0.018) −0.015 (0.020)

Late_morning–night −0.089*** (0.019) −0.086*** (0.017) −0.083*** (0.020) −0.077*** (0.016) 0.009 (0.019)

Afternoon–night −0.098*** (0.019) −0.099*** (0.017) −0.083*** (0.019) −0.083*** (0.016) 0.023 (0.018)

Early_evening–night −0.093*** (0.019) −0.092*** (0.017) −0.080*** (0.020) −0.074*** (0.015) 0.006 (0.018)

Late_evening–night −0.071** (0.019) −0.062** (0.016) −0.066** (0.019) −0.052** (0.014) −0.023 (0.018)

Late_morning–early_morning −0.072*** (0.014) −0.071*** (0.013) −0.068*** (0.015) −0.063*** (0.013) 0.023 (0.012)

Afternoon–early_morning −0.080*** (0.016) −0.084*** (0.015) −0.068*** (0.016) −0.069*** (0.014) 0.038* (0.012)

Early_evening–early_morning −0.076*** (0.016) −0.077*** (0.015) −0.064*** (0.016) −0.060*** (0.014) 0.021 (0.013)

Late_evening–early_morning −0.053** (0.016) −0.047* (0.015) −0.050* (0.017) −0.038* (0.014) −0.009 (0.012)

Afternoon–late_morning −0.008 (0.005) −0.013#(0.005) −0.000 (0.005) −0.006 (0.004) 0.014** (0.004)

Early_evening–late_morning −0.004 (0.007) −0.005 (0.006) 0.004 (0.006) 0.003 (0.004) −0.003 (0.006)

Late_evening–late_morning 0.019 (0.009) 0.025* (0.008) 0.017 (0.008) 0.025** (0.007) −0.032*** (0.006)

Early_evening–afternoon 0.004 (0.003) 0.007 (0.003) 0.004 (0.004) 0.009* (0.003) −0.017*** (0.004)

Late_evening–afternoon 0.027** (0.007) 0.037*** (0.007) 0.017 (0.007) 0.031*** (0.006) −0.046*** (0.005)

Late_evening–early_evening 0.023** (0.006) 0.030*** (0.006) 0.014 (0.006) 0.022*** (0.005) −0.029*** (0.004)

Total number of assessments was 17,209. The table presents estimated differences (and their standard errors) for all comparisons between timeframes. p-values were adjusted using

the Tukey Honest Significant Difference method. #p<0.10. *p<0.05. **p<0.01. ***p<0.001. night =12 a.m.–4 a.m. early morning =4 a.m.–8 a.m. late morning =8 a.m.–12 p.m.

afternoon =12 p.m.–4 p.m. early evening =4 p.m.–8 p.m. late evening =8 p.m.–12 a.m.

were still significant (i.e., after controlling for the effects of

stress).

DISCUSSION

This study evaluated whether subjective tinnitus loudness and

subjective tinnitus distress depend on time-of-day with EMA

from the “TrackYourTinnitus” (TYT) mobile application (Pryss

et al., 2015a,b; Schlee et al., 2016). Strengths of the present study

are that a mobile application was used to obtain EMA of high

ecological validity (Trull and Ebner-Priemer, 2013, 2014; Adams

et al., 2017), a much higher sampling frequency was applied than

in typical clinical studies, and the sample size was much larger

than in previous EMA studies on the time-of-day-dependence of

tinnitus (Flor et al., 2004; Henry et al., 2012; Wilson et al., 2015).

The main result was that tinnitus (loudness and distress) was

rated as more severe during the night and the early morning

(from 12 a.m. to 8 a.m.) than during the upcoming day.

Interestingly, tinnitus loudness and tinnitus distress showed a

very similar time pattern although the neurobiological correlates

of loudness and distress differ to a certain degree (e.g., De Ridder

et al., 2011; Leaver et al., 2012; Ueyama et al., 2013; Vanneste et al.,

2014).

Contrary to the EMA study by Henry et al. (2012), the present

investigation found a time-of-day-dependence of tinnitus. The

most obvious reason for this discrepancy is that Henry et al.

(2012) assessed tinnitus only from 8 a.m. to 8 p.m. and could,

therefore, not evaluate tinnitus during the time interval that was

related to most severe tinnitus in our study (12 a.m.–8 a.m.).

During a time interval (8 a.m.–12 a.m.) that included the 12-h

Frontiers in Aging Neuroscience | www.frontiersin.org 5August 2017 | Volume 9 | Article 253

Probst et al. Does Tinnitus Depend on Time-of-Day?

0.40

0.45

0.50

0.55

0.60

0 4 8 12 16 20 24

Hour

Tinnitus Loudness

0.30

0.35

0.40

0.45

0.50

0 4 8 12 16 20 24

Hour

Tinnitus Distress

0.20

0.25

0.30

0.35

0.40

0 4 8 12 16 20 24

Hour

Stress

FIGURE 2 | Expected tinnitus loudness (A), tinnitus distress (B), and level of

stress (C) as a function of time-of-day. The blue lines represent expected

values for the average participant on an average day, the gray bands represent

95% confidence intervals.

interval analyzed by Henry et al. (2012) tinnitus did not vary

much in our study either (see Figures 2A,B). The result that

tinnitus was more severe in the early morning hours is in line

with a previous diary study (Flor et al., 2004) and fits to the

clinical impression of a “morning roar” as it is often anecdotally

reported by tinnitus patients. Yet, our result that tinnitus was

more severe during the night was not found by Flor et al. (2004).

More severe tinnitus (loudness and distress) during the night

could at least partially result from the possibility that several

assessments at night were given by participants while having sleep

disturbances. Sleep disturbances are common among tinnitus

patients and their severity correlates positively with measures of

tinnitus severity (e.g., Crönlein et al., 2007; Schecklmann et al.,

2015; Crönlein et al., 2016). Although we aimed to control for

this potential confounder by excluding data from spontaneous

ratings and restricting the data analysis to the ratings provided at

notifications, the fact that sleep disturbances were not assessed on

a daily basis in the present study and, hence, were not available

for analysis is a limitation of our study. Future research could

explore whether the effect of time-of-day on tinnitus is different

between days with and without sleep disturbances. Besides sleep,

several other variables are time-of-day dependent and should

be considered as potential confounding variables: For example,

the environmental sound level depends on time-of-day and

tinnitus might be more severe during the night and the early

morning, because the environmental sound level in these time

intervals cannot mask the tinnitus. Furthermore, a trigger of

tinnitus might be (even slight) tension of specific muscles of

the craniocervical connection (Bechter et al., 2016), whereby the

tension depends mainly from posture, which is influenced by

different aspects during the night (e.g., sleeping posture, bed

pillow) and during the day. Moreover, the release of stress-related

hormones is controlled by a circadian clock (Dickmeis, 2009;

Lightman and Conway-Campbell, 2010; Conway-Campbell et al.,

2012) and future studies could explore the relationship between

circadian tinnitus variability and such stress-related hormones.

In the present study, we could only analyze subjective stress-

levels with the result that the 24-h course of the subjective stress-

level was not parallel to the course of tinnitus (loudness and

distress): While tinnitus (loudness and distress) showed their

maximum between 12 a.m. and 8 a.m., the maximum of the

subjective stress-level was found between 12 p.m. and 4 p.m.

The discrepant time curves of tinnitus and subjective stress-

level raise further questions, which need to be addressed in

future longitudinal studies regarding the tinnitus-stress link. For

example, it appears possible that tinnitus and subjective stress

interact more in a time-lagged than in an instant manner. Thus,

it should be clarified whether increases of subjective stress lead

to more severe tinnitus and whether increases of tinnitus severity

also lead to more subsequent subjective stress (which again might

affect tinnitus severity resulting in a vicious circle). Feedback

loops have been described already in research on the pituitary-

adrenal system: “positive, delayed, feedforward connection

between the pituitary and the adrenals” and “negative feedback

of glucocorticoids on ACTH release” (Lightman and Conway-

Campbell, 2010, p. 712). It should also be noted in this context

that the peaks of our self-reported stress-levels (12 p.m.–4 p.m.)

did not correspond to the peaks of cortisol and ACTH releases (4

a.m.–8 a.m.) as illustrated by Lightman and Conway-Campbell

(2010). Therefore, the longitudinal associations between tinnitus

and self-reported stress might be different from the ones between

tinnitus and stress-hormones.

Regarding the observed circadian variability of tinnitus

loudness, it is tempting to speculate relations to circadian

variations in neuronal sensitivity of peripheral and central

auditory structures, which have been identified in recent studies

(Park et al., 2016; Basinou et al., 2017). However, tinnitus

loudness does not directly reflect neuronal activity in auditory

pathways, but also depends on other factors such as attention

and emotions. For example, a previous study found that

tinnitus becomes louder over time when participants experience

Frontiers in Aging Neuroscience | www.frontiersin.org 6August 2017 | Volume 9 | Article 253

Probst et al. Does Tinnitus Depend on Time-of-Day?

more qualitatively different feelings (Probst et al., 2016b).

Therefore, more research is needed to replicate the observed

circadian rhythm of tinnitus in large samples, to identify

the specific contribution of different factors (e.g., neuronal

activity in auditory pathways, attention, and emotion), and to

explore whether different persons show a different time-of-day

dependence of tinnitus. Moderating variables might, for example,

be gender, age (e.g., the time-of-day dependence of tinnitus

might be different between men and women or within women

before/after the menopause), and the etiology of tinnitus (e.g., the

time of time-of-day dependence might be different between noise

trauma as etiology and stress as etiology). Future translational

and clinical studies with samples large enough to analyze such

subgroups are required to explore potential moderators of the

time-of-day dependence of tinnitus. These further studies could

also measure tinnitus by different assessment methods, because

the study at hand only analyzed self-reported tinnitus. For

example, by the “gap-in-noise” paradigm (Lowe and Walton,

2015) or psychophysiological measurements such as tinnitus

matching. Yet, the reliability and validity of tinnitus matching is

an ongoing matter of debate (Hoare et al., 2014; De Ridder et al.,

2015). For mobile applications such as TYT, portable methods

to assess tinnitus more objectively (see for example, Hébert and

Fournier, 2017) that can be integrated in the mobile application

are needed. It is necessary to evaluate whether a similar time-

of-day dependence of tinnitus can be shown for self-reported

tinnitus as well as for more objectively measured tinnitus. Future

studies could also compare different statistical approaches and

identify the approach most suited to investigate time-of-day

dependencies. For example, harmonic regression was performed

in an animal study on circadian rhythm (Atger et al., 2015), and

an R package for nonparametric circular methods (NPCirc) is

available to analyze circular data (Oliveira et al., 2014). These

approaches were not performed in the present study due to the

nested structure of the data (assessments within days and days

within participants).

In summary, the results of our study have implications for

both tinnitus research and tinnitus management. Taking time-

of-day into account in the study design might be necessary in

clinical studies. Yet, the results of our study rely solely on TYT

users (who are not representative for clinical tinnitus patients,

see Probst et al., 2017) and on one-item questions on tinnitus

distress and tinnitus loudness making it difficult to conclude

whether the observed differences between night/early morning

and the upcoming day are clinically relevant. Future studies

using assessment instruments appropriate to distinguish between

clinically relevant and clinically irrelevant change (for example

the Tinnitus Handicap Inventory (THI), see Zeman et al., 2011)

with clinical tinnitus samples are necessary to address this

point. Chronobiological aspects should not only be considered

in tinnitus research but also in tinnitus treatment. Tailoring the

timing of therapeutic interventions to the circadian rhythm of

individual tinnitus patients (chronotherapy) might be promising.

Further translational and clinical studies are necessary to evaluate

the potential of chronotherapy for tinnitus. However, this is a

challenging task since “research in the topic is underfunded when

compared with other diseases for which the prevalence and cost

to society is relatively similar” (Cederroth et al., 2013, p. 972).

Nevertheless, the current study might motivate individuals with

tinnitus to observe their tinnitus fluctuations and to identify

time-intervals during which the access to and the use of tinnitus

coping strategies are most crucial.

AUTHOR CONTRIBUTIONS

TP substantially contributed to the design of the study

and data preparation, drafted and revised the manuscript.

RP substantially contributed to the design of the study,

data preparation, conception, implementation and maintenance

of the “TrackYourTinnitus” application, and revised the

manuscript. BL substantially contributed to the design of the

study and revised the manuscript. JR substantially contributed

to the design of the study and revised the manuscript. JS

substantially contributed to the conception, implementation

and maintenance of the “TrackYourTinnitus” application,

and revised the manuscript. MR substantially contributed

to the conception, implementation and maintenance of the

“TrackYourTinnitus” application, and revised the manuscript.

MS substantially contributed to the design of the study

and revised the manuscript. WS substantially contributed to

the design of the study, data preparation, conception and

implementation of the “TrackYourTinnitus” application, drafted

and revised the manuscript. JZ substantially contributed to the

design of the study and performed the statistical analysis, drafted

and revised the manuscript.

ACKNOWLEDGMENTS

This work was supported by the German Research Foundation

(DFG) and the Georg-August-University Göttingen

(Germany) within the funding programme Open Access

Publishing.

SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found

online at: http://journal.frontiersin.org/article/10.3389/fnagi.

2017.00253/full#supplementary-material

REFERENCES

Adams, W. Z., McClure, E. A., Gray, K. M., Danielson, C. K., Treiber,

F. A., and Ruggiero, K. J. (2017). Mobile devices for the remote

acquisition of physiological and behavioral biomarkers in psychiatric

clinical research. J. Psychiatr. Res. 85, 1–14. doi: 10.1016/j.jpsychires.2016.

10.019

Ajayi, O. V., Phillips, J. S., Laopaiboon, M., and McFerran, D. (2014).

Melatonin for tinnitus. Cochrane Database Syst. Rev. 12:CD011435.

doi: 10.1002/14651858.CD011435

Frontiers in Aging Neuroscience | www.frontiersin.org 7August 2017 | Volume 9 | Article 253

Probst et al. Does Tinnitus Depend on Time-of-Day?

Alsalman, O. A., Tucker, D., and Vanneste, S. (2016). Salivary stress-related

responses in tinnitus: a preliminary study in young male subjects with tinnitus.

Front. Neurosci. 10:338. doi: 10.3389/fnins.2016.00338

Atger, F., Gobet, C., Marquis, J., Martin, E., Wang, J., Weger, B., et al.

(2015). Circadian and feeding rhythms differentially affect rhythmic mRNA

transcription and translation in mouse liver. Proc. Natl. Acad. Sci. U.S.A. 112,

E6579–E6588. doi: 10.1073/pnas.1515308112

Baguley, D., McFerran, D., and Hall, D. (2013). Tinnitus. Lancet 382, 1600–1607.

doi: 10.1016/S0140-6736(13)60142-7

Basinou, V., Park, J.- S., Cederroth, C. R., and Canlon, B: (2017).

Circadian regulation of auditory function. Hear. Res. 347, 47–55.

doi: 10.1016/j.heares.2016.08.018

Bates, D., Maechler, M., Bolker, B, and Walker, S. (2015). Fitting linear mixed-

effects models using lme4. J. Stat. Softw. 67, 1–48. doi: 10.18637/jss.v067.i01

Bechter, K., Wieland, M., and Hamann, G. F. (2016). Chronic cervicogenic tinnitus

rapidly resolved by intermittent use of cervical collar. Front. Psychiatry 7:43.

doi: 10.3389/fpsyt.2016.00043

Bhatt, J. M., Bhattacharyya, N., and Lin, H. W. (2016). Relationships between

tinnitus and the prevalence of anxiety and depression. Laryngoscope 127,

466–469. doi: 10.1002/lary.26107

Buttgereit, F., Smolen, J. S., Coogan, A. N., and Cajochen, C. (2015). Clocking

in: chronobiology in rheumatoid arthritis. Nat. Rev. Rheumatol. 11, 349–356.

doi: 10.1038/nrrheum.2015.31

Cederroth, C. R., Canlon, B., and Langguth, B. (2013). Hearing loss and

tinnitus-are funders and industry listening? Nat. Biotechnol. 31, 972–974.

doi: 10.1038/nbt.2736

Cima, R. F., Crombez, G., and Vlaeyen, J. W. (2011). Catastrophizing and fear of

tinnitus predict quality of life in patients with chronic tinnitus. Ear. Hear. 32,

634–641. doi: 10.1097/AUD.0b013e31821106dd

Conway-Campbell, B. L., Pooley, J. R., Hager, G. L., and Lightman, S. L. (2012).

Molecular dynamics of ultradian glucocorticoid receptor action. Mol. Cell.

Endocrinol. 348, 383–393. doi: 10.1016/j.mce.2011.08.014

Crönlein, T., Langguth, B., Geisler, P., and Hajak, G. (2007). Tinnitus and

insomnia. Prog. Brain. Res. 166, 227–233. doi: 10.1016/S0079-6123(07)66021-X

Crönlein, T., Langguth, B., Pregler, M., Kreuzer, P. M., Wetter, T. C., and

Schecklmann, M. (2016). Insomnia in patients with chronic tinnitus: cognitive

and emotional distress as moderator variables. J. Psychosom. Res. 83, 65–68.

doi: 10.1016/j.jpsychores.2016.03.001

Dauman, N., Erlandsson, S., Lundlin, L., and Dauman, R. (2015). Intra-individual

variability in tinnitus patients: current thoughts and perspectives. HNO. 63,

302–306. doi: 10.1007/s00106-014-2978-2

De Ridder, D., Congedo, M., and Vanneste, S. (2015). The neural correlates

of subjectively perceived and passively matched loudness perception in

auditory phantom perception. Brain Behav. 5: e00331. doi: 10.1002/

brb3.331

De Ridder, D., Elgoyhen, A. B., Romo, R., and Langguth, B. (2011). Phantom

percepts: tinnitus and pain as persisting aversive memory networks. Proc. Natl.

Acad. Sci. U.S.A. 108, 8075–8080. doi: 10.1073/pnas.1018466108

De Ridder, D., Vanneste, S., Weisz, N., Londero, A., Schlee, W., Elgoyhen, A. B.,

et al. (2014). An integrative model of auditory phantom perception: tinnitus as

a unified percept of interacting separable subnetworks. Neurosci. Biobehav. Rev.

44, 16–32. doi: 10.1016/j.neubiorev.2013.03.021

Dickmeis, T. (2009). Glucocorticoids and the circadian clock. J. Endocrinol. 200,

3–22. doi: 10.1677/JOE-08-0415

Flor, H., Hoffmann, D., Struve, M., and Diesch, E. (2004). Auditory discrimination

training for the treatment of tinnitus. Appl. Psychophysiol. Biofeedback 29,

113–120. doi: 10.1023/B:APBI.0000026637.77671.f4

Germain, A., and Kupfer, D. J. (2008). Circadian rhythm disturbances in

depression. Hum. Psychopharmacol. 23, 571–585. doi: 10.1002/hup.964

Gilron, I., and Ghasemlou, N. (2014). Chronobiology of chronic pain: focus on

diurnal rhythmicity of neuropathic pain. Curr. Opin. Support. Palliat. Care 8,

429–436. doi: 10.1097/SPC.0000000000000085

Hébert, S., and Fournier, P. (2017). Clinical validation of a new tinnitus assessment

technology. Front. Neurol. 8:38. doi: 10.3389/fneur.2017.00038

Hébert, S., and Lupien, S. J. (2007). The sound of stress: blunted cortisol reactivity

to psychosocial stress in tinnitus sufferers. Neurosci. Lett. 411, 138–142.

doi: 10.1016/j.neulet.2006.10.028

Hébert, S., and Lupien, S. J. (2009). Salivary cortisol levels, subjective stress,

and tinnitus intensity in tinnitus sufferers during noise exposure in the

laboratory. Int. J. Hyg. Environ. Health 212, 37–44. doi: 10.1016/j.ijheh.2007.

11.005

Hébert, S., Paiement, P., and Lupien, S. J. (2004). A physiological correlate for

the intolerance to both internal and external sounds. Hear. Res. 190, 1–9.

doi: 10.1016/S0378-5955(04)00021-8

Henry, J. A., Galvez, G., Turbin, M. B., Thielman, E. J., McMillan, G. P., and

Istvan, J. A. (2012). Pilot study to evaluate ecological momentary assessment

of tinnitus. Ear. Hear. 33, 179–290. doi: 10.1097/AUD.0b013e31822f6740

Hesser, H., and Andersson, G. (2009). The role of anxiety sensitivity and

behavioral avoidance in tinnitus disability. Int. J. Audiol. 48, 295–299.

doi: 10.1080/14992020802635325

Hesser, H., Weise, C., Westin, V. Z., and Andersson, G. (2011). A systematic

review and meta-analysis of randomized controlled trials of cognitive-

behavioral therapy for tinnitus distress. Clin. Psychol. Rev. 31, 545–553.

doi: 10.1016/j.cpr.2010.12.006

Hiller, W., and Goebel, G. (2007). When tinnitus loudness and annoyance

are discrepant: audiological characteristics and psychological profile. Audiol.

Neurootol. 12, 391–400. doi: 10.1159/000106482

Hoare, D. J., Edmondson-Jones, M., Gander, P. E., and Hall, D. A. (2014).

Agreement and reliability of tinnitus loudness matching and pitch likeness

rating. PLoS ONE 9:e114553. doi: 10.1371/journal.pone.0114553

Hobson, J., Chisholm, E., and El Refaie, A. (2012). Sound therapy (masking) in the

management of tinnitus in adults. Cochrane Database Syst. Rev. 11:CD006371.

doi: 10.1002/14651858.cd006371.pub3

Hothorn, T., Bretz, F., and Westfall, P. (2008). Simultaneous inference in general

parametric models. Biom. J. 50, 346–363. doi: 10.1002/bimj.200810425

Jasper, K., Weise, C., Conrad, I., Andersson, G., Hiller, W., and Kleinstäuber,

M. (2014). Internet-based guided self-help versus group cognitive behavioral

therapy for chronic tinnitus: a randomized controlled trial. Psychother.

Psychosom. 83, 234–246. doi: 10.1159/000360705

Kleinstäuber, M., Jasper, K., Schweda, I., Hiller, W., Andersson, G.,

and Weise, C. (2013). The role of fear-avoidance cognitions and

behaviors in patients with chronic tinnitus. Cogn. Beh. Ther. 42, 84–99.

doi: 10.1080/16506073.2012.717301

Landgrebe, M., Azevedo, A., Baguley, D., Bauer, C., Cacace, A., Coelho,

C., et al. (2012). Methodological aspects of clinical trials in tinnitus: a

proposal for an international standard. J. Psychosom. Res. 73, 112–121.

doi: 10.1016/j.jpsychores.2012.05.002

Langguth, B., and De Ridder, D. (2013). Tinnitus: therapeutic use of

superficial brain stimulation. Handb. Clin. Neurol. 116, 441–467.

doi: 10.1016/B978-0-444-53497-2.00036-X

Langguth, B., and Elgoyhen, A. B. (2012). Current pharmacological

treatments for tinnitus. Expert Opin. Pharmacother. 13, 2495–2509.

doi: 10.1517/14656566.2012.739608

Langguth, B., Kreuzer, P. M., Kleinjung, T., and De Ridder, D. (2013).

Tinnitus: causes and clinical management. Lancet Neurol. 12, 920–930.

doi: 10.1016/S1474-4422(13)70160-1

Langguth, B., Landgrebe, M., Kleinjung, T., Sand, G. P., and Hajak, G.

(2011). Tinnitus and depression. World J. Biol. Psychiatry 12, 489–500.

doi: 10.3109/15622975.2011.575178

Leaver, A. M., Renier, L., Chevillet, M. A., Morgan, S., Kim, H. J., and Rauschecker,

J. P. (2011). Dysregulation of limbic and auditory networks in tinnitus. Neuron

69, 33–43. doi: 10.1016/j.neuron.2010.12.002

Leaver, A. M., Seydell-Greenwald, A., Turesky, T. K., Morgan, S., Kim, H. J., and

Rauschecker, J. P. (2012). Cortico-limbic morphology separates tinnitus from

tinnitus distress. Front. Syst. Neurosci. 6:21. doi: 10.3389/fnsys.2012.00021

Lightman, S. L., and Conway-Campbell, B. L. (2010). The crucial role of pulsatile

activity of the HPA axis for continuous dynamic equilibration. Nat. Rev.

Neurosci. 11, 710–718. doi: 10.1038/nrn2914

Lowe, A. S., and Walton, J. P. (2015). Alterations in peripheral and central

components of the auditory brainstem response: a neural assay of tinnitus. PLoS

ONE 10:e0117228. doi: 10.1371/journal.pone.0117228

Maes, I. H., Cima, R. F., Anteunis, L. J., Scheijen, D. J., Baguley, D. M., El Refaie,

A., et al. (2014). Cost-effectiveness of specialized treatment based on cognitive

behavioral therapy versus usual care for tinnitus. Otol. Neurotol. 35, 787–795.

doi: 10.1097/MAO.0000000000000331

Maes, I. H., Cima, R. F., Vlaeyen, J. W., Anteunis, L. J., and Joore,

M. A. (2013). Tinnitus: a cost study. Ear. Hear. 34, 508–514.

doi: 10.1097/AUD.0b013e31827d113a

Frontiers in Aging Neuroscience | www.frontiersin.org 8August 2017 | Volume 9 | Article 253

Probst et al. Does Tinnitus Depend on Time-of-Day?

Martinez, C., Wallenhorst, C., McFerran, D., and Hall, D. A. (2015). Incidence rates

of clinically significant tinnitus: 10-year trend from a cohort study in England.

Ear. Hear. 36, e69–75. doi: 10.1097/aud.0000000000000121

McCormack, A., Edmondson-Jones, M., Somerset, S, and Hall, D. (2016). A

systematic review of the reporting of tinnitus prevalence and severity. Hear.

Res. 337, 70–79. doi: 10.1016/j.heares.2016.05.009

McKenna, L., Handscomb, L., Hoare, D. J., and Hall, D. A. (2014). A scientific

cognitive-behavioral model of tinnitus: novel conceptualizations of tinnitus

distress. Front. Neurol. 5:196. doi: 10.3389/fneur.2014.00196

Meltser, I., Cederroth, C. R., Basinou, V., Savelyev, S., Lundkvist, G.

S., and Canlon, B. (2014). TrkB-mediated protection against circadian

sensitivity to noise trauma in the murine cochlea. Curr. Biol. 24, 658–663.

doi: 10.1016/j.cub.2014.01.047

Miroddi, M., Bruno, R., Galletti, F., Calapai, F., Navarra, M., Gangemi, S., et al.

(2015). Clinical pharmacology of melatonin in the treatment of tinnitus:

a review. Eur. J. Clin. Pharmacol. 71, 263–270. doi: 10.1007/s00228-015-

1805-3

Newman, C. W., Sandridge, S. A., and Bolek, L. (2008). Development and

psychometric adequacy of the screening version of the tinnitus handicap

inventory. Otol. Neurotol. 29, 276–281. doi: 10.1097/MAO.0b013e31816569c4

Nondahl, D. M., Cruickshanks, K. J., Huang, G. H., Klein, B. E., Klein, R., Tweed,

T. S., et al. (2012). Generational differences in the reporting of tinnitus. Ear.

Hear. 33, 640–644. doi: 10.1097/AUD.0b013e31825069e8

Oliveira, M., Crujeiras, R. M., and Rodríguez–Casal, A. (2014). NPCirc: an

R package for nonpara-metric circular methods. J. Stat. Soft. 61, 1–26.

doi: 10.18637/jss.v061.i09

Park, J., S., Cederroth, C. R., Basinou, V., Meltser, I., Lundkvist, G., and

Canlon, B. (2016). Identification of a circadian clock in the inferior

colliculus and its dysregulation by noise exposure. J. Neurosci. 36, 5509–5519.

doi: 10.1523/JNEUROSCI.3616-15.2016

Pirodda, A., Raimondi, M. C., and Ferri, G. G. (2010). Exploring the

reasons why melatonin can improve tinnitus. Med. Hypotheses 75, 190–191.

doi: 10.1016/j.mehy.2010.02.018

Probst, T., Pryss, R., Langguth, B., and Schlee, W. (2016a). Emotional states

as mediators between tinnitus loudness and tinnitus distress in daily

life: results from the “TrackYourTinnitus” application. Sci. Rep. 6:20382.

doi: 10.1038/srep20382

Probst, T., Pryss, R., Langguth, B., and Schlee, W. (2016b). Emotion dynamics

and tinnitus: daily life data from the “TrackYourTinnitus” application. Sci. Rep.

6:31166. doi: 10.1038/srep31166

Probst, T., Pryss, R. C., Langguth, B., Spiliopoulou, M., Landgrebe, M., Vesala,

M., et al. (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

Pryss, R., Reichert, M., Herrmann, J., Langguth, B., Schlee, W. (2015a). “Mobile

crowd sensing in clinical and psychological trials - a case study,” in 28th IEEE

Int’l Symposium on Computer-Based Medical Systems, 22–25 June 2015 (Sao

Carlos: IEEE Computer Society Press), 23–24. Available online at: http://dbis.

eprints.uni-ulm.de/1144/1/PCBMS_2015.pdf (Accessed July 15, 2017)

Pryss, R., Reichert, M., Langguth, B., and Schlee, W. (2015b). “Mobile crowd

sensing services for tinnitus assessment, therapy and research,” in IEEE 4th

International Conference on Mobile Services (MS 2015), June 27–July 2, 2015

(New York, NY: IEEE Computer Society Press), 352–359. Available online at:

http://dbis.eprints.uni-ulm.de/1152/1/ms2015rpmrblws.pdf (Accessed: July 15,

2017).

Raudenbush, S. W., and Bryk, A. S. (2002). Hierarchical Linear Models: Applications

and Data Analysis Methods. Newbury Park, CA: Sage Publications.

Rauschecker, J. P., Leaver, A. M., and Mühlau, M. (2010). Tuning out

the noise: limbic-auditory interactions in tinnitus. Neuron 66, 819–826.

doi: 10.1016/j.neuron.2010.04.032

Rauschecker, J. P., May, E. S., Maudoux, A., and Ploner, M. (2015). Frontostriatal

gating of tinnitus and chronic pain. Trends Cogn. Sci. 19, 567–578.

doi: 10.1016/j.tics.2015.08.002

R Core Team, A. (2015). R: A Language and Environment for Statistical Computing.

Vienna: R foundation for statistical computing. Available online at: https://

www.R-project.org/ (Accessed: November 25, 2016).

Riedl, D., Rumpold, G., Schmidt, A., Zorowka, P. G., Bliem, H. R., and Moschen,

R. (2015). The influence of tinnitus acceptance on the quality of life and

psychological distress in patients with chronic tinnitus. Noise Health 17,

374–381. doi: 10.4103/1463-1741.165068

Schecklmann, M., Pregler, M., Kreuzer, P. M., Poeppl, T. B., Lehner, A., Crönlein,

T., et al. (2015). Psychophysiological associations between chronic tinnitus and

sleep: a cross validation of tinnitus and insomnia questionnaires. BioMed. Res.

Int. 2015:461090. doi: 10.1155/2015/461090

Schlee, W., Pryss, R. C., Probst, T., Schobel, J., Bachmeier, A., Reichert, M.,

et al. (2016). Measuring the moment-to-moment variability of tinnitus:

the TrackYourTinnitus smart phone app. Front. Aging Neurosci. 8:294.

doi: 10.3389/fnagi.2016.00294

Schlee, W., Schecklmann, M., Lehner, A., Kreuzer, P. M., Vielsmeier, V., Poeppl,

T. B., et al. (2014). Reduced variability of auditory alpha activity in chronic

tinnitus. Neural. Plast. 2014:436146. doi: 10.1155/2014/436146

Singer, J. D., and Willett, J. B. (2003). Applied Longitudinal Data Analysis:

Modeling Change and Event Occurence. New York, NY: Oxford University

Press. doi: 10.1093/acprof:oso/9780195152968.001.0001

Strian, F., Lautenbacher, S., Galfe, G., and Hölzl, R. (1989). Diurnal

variations in pain perception and thermal sensitivity. Pain 36, 125–131.

doi: 10.1016/0304-3959(89)90120-6

Trull, T. J., and Ebner-Priemer, U. (2013). Ambulatory assessment. Annu. Rev.

Clin. Psychol. 9, 151–176. doi: 10.1146/annurev-clinpsy-050212-185510

Trull, T. J., and Ebner-Priemer, U. (2014). The role of ambulatory

assessment in psychological science. Curr. Dir. Psychol. Sci. 23, 466–470.

doi: 10.1177/0963721414550706

Ueyama, T., Donishi, T., Ukai, S., Ikeda, Y., Hotomi, M., Yamanaka, N.,

et al. (2013). Brain regions responsible for tinnitus distress and loudness: a

resting-state FMRI study. PLoS ONE 8:e67778. doi: 10.1371/journal.pone.00

67778

Vanneste, S., Congedo, M., and De Ridder, D. (2014). Pinpointing a highly specific

pathological functional connection that turns phantom sound into distress.

Cereb. Cortex 24, 2268–2282. doi: 10.1093/cercor/bht068

Wallhäusser-Franke, E., Brade, J., Balkenhol, T., D’Amelio, R., Seegmüller,

A., and Delb, W. (2012). Tinnitus: distinguishing between subjectively

perceived loudness and tinnitus-related distress. PLoS ONE 7:e34583.

doi: 10.1371/journal.pone.0034583

Weise, C., Kleinstäuber, M., Hesser, H., Westin, V. Z., and Andersson, G. (2013).

Acceptance of tinnitus: validation of the tinnitus acceptance questionnaire.

Cogn. Behav. Ther. 42, 100–115. doi: 10.1080/16506073.2013.781670

Wilson, M. B., Kallogjeri, D., Joplin, C. N., Gorman, M. D., Krings, J. G.,

Lenze, E. J., et al. (2015). Ecological momentary assessment of tinnitus using

smartphone technology: a pilot study. Otolaryngol. Head. Neck. Surg. 152,

897–903. doi: 10.1177/0194599815569692

Wirz-Justice, A. (2008). Diurnal variation of depressive symptoms. Dialogues Clin.

Neurosci. 10, 337–343.

Zeman, F., Koller, M., Figueiredo, R., Aazevedo, A., Rates, M., Coelho, C., et al.

(2011). Tinnitus handicap inventory for evaluating treatment effects: which

changes are clinically relevant? Otolaryngol. Head Neck Surg. 145, 282–287.

doi: 10.1177/0194599811403882

Conflict of Interest Statement: The other 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 handling Editor declared a co-authorship with the authors TP, RP, BL,

MR, MS and WS, and the handling Editor states that the process met the standards

of a fair and objective review.

Spiliopoulou, Schlee and Zimmermann. 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 journal

is cited, in accordance with accepted academic practice. No use, distribution or

reproduction is permitted which does not comply with these terms.

Frontiers in Aging Neuroscience | www.frontiersin.org 9August 2017 | Volume 9 | Article 253