International Journal of Psychophysiology 94 (2014) 427–436

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International Journal of Psychophysiology journal homepage: www.elsevier.com/locate/ijpsycho

Alterations in attention capture to auditory emotional stimuli in job burnout: An event-related potential study Laura Sokka a,⁎, Minna Huotilainen a, Marianne Leinikka a, Jussi Korpela a, Andreas Henelius a, Claude Alain b,c, Kiti Müller a, Satu Pakarinen a a b c

Finnish Institute of Occupational Health, Topeliuksenkatu 41 a A, 00250 Helsinki, Finland Rotman Research Institute, Baycrest Centre for Geriatric Care, 3560 Bathurst Street, Toronto, Ontario, Canada M6A 2E1 Department of Psychology, University of Toronto, Toronto, Ontario, Canada

a r t i c l e

i n f o

Article history: Received 14 April 2014 Received in revised form 29 October 2014 Accepted 2 November 2014 Available online 7 November 2014 Keywords: Job burnout Attention Event-related potential (ERP) Mismatch negativity (MMN) P3a Emotion

a b s t r a c t Job burnout is a significant cause of work absenteeism. Evidence from behavioral studies and patient reports suggests that job burnout is associated with impairments of attention and decreased working capacity, and it has overlapping elements with depression, anxiety and sleep disturbances. Here, we examined the electrophysiological correlates of automatic sound change detection and involuntary attention allocation in job burnout using scalp recordings of event-related potentials (ERP). Volunteers with job burnout symptoms but without severe depression and anxiety disorders and their non-burnout controls were presented with natural speech sound stimuli (standard and nine deviants), as well as three rarely occurring speech sounds with strong emotional prosody. All stimuli elicited mismatch negativity (MMN) responses that were comparable in both groups. The groups differed with respect to the P3a, an ERP component reflecting involuntary shift of attention: job burnout group showed a shorter P3a latency in response to the emotionally negative stimulus, and a longer latency in response to the positive stimulus. Results indicate that in job burnout, automatic speech sound discrimination is intact, but there is an attention capture tendency that is faster for negative, and slower to positive information compared to that of controls. © 2014 Elsevier B.V. All rights reserved.

1. Introduction In recent years, job burnout has become a significant cause of decreased working capacity of workers in both developing and industrialized countries. More than 25% of working people have been observed to have symptoms of job burnout, in 2% estimated as severe (Ahola et al., 2006). The term ‘job burnout’ refers to a multidimensional, psychological condition with persistent work-related negative state of mind. It is characterized primarily by symptoms of exhaustion, accompanied by experienced distress as well as decreased effectiveness and motivation. Further, employees develop cynicism to distance themselves from the exhausting demands they encounter in their work. Job burnout develops gradually over time as a consequence of a prolonged stress situation at work (Schaufeli and Enzmann, 1998; Maslach et al., 2001). In their three-dimensional job burnout model of exhaustion, cynicism and reduced professional efficacy, Maslach et al. (2001) place the individual stress experience within the social context of the work-place, and the person's conception of both self and others is included. ⁎ Corresponding author at: Finnish Institute of Occupational Health, Brain Work Research Centre, Topeliuksenkatu 41 a A, 00250 Helsinki, Finland. Tel.: +358 30 474 2142; fax: +358 30 474 2008. E-mail address: laura.sokka@ttl.fi (L. Sokka).

http://dx.doi.org/10.1016/j.ijpsycho.2014.11.001 0167-8760/© 2014 Elsevier B.V. All rights reserved.

In working life, demands on various cognitive functions such as those of attention and working memory are present on a daily basis. Attention can easily be captured by unexpected acoustic or visual changes thereby disrupting task performance. People with job burnout often report having difficulties concentrating and remembering information (Maslach et al., 2001; Österberg et al., 2009). Researchers have suggested that job burnout is associated with impairments of attention (Sandström et al., 2005), reduced processing speed (Österberg et al., 2009), and reduced working memory updating (Oosterholt et al., 2012), but the findings are still at least partly controversial (van Luijtelaar et al., 2010; Castaneda et al., 2011), and non-specific to job burnout. However, neurophysiological studies on this topic are scarce. Scalp recordings of event-related potentials (ERPs) provide a means to evaluate the effects of job burnout on the time course of automatic processing and attention allocation. ERP recordings are widely used to study a variety of brain functions both in healthy people and in different clinical subgroups such as neurological patients (e.g., Polich and Squire, 1993), patients with depression (MacQueen et al., 2000; McNeely et al., 2008), schizophrenia (e.g., Weir et al., 1998; Alain et al., 2002), autism spectrum disorders (O'Connor et al., 2007), and attention deficit hyperactivity disorder (ADHD; Barry et al., 2003). The N1 wave of the auditory ERPs peaks at 50–150 ms from stimulus onset, and its amplitude is dependent on the acoustical properties as

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well as the number of successive repetitions of the stimulus within the sound sequence. Traditionally, N1 has been interpreted as a marker of early perceptual auditory processing in primary and associative auditory cortices (for a review, see Näätänen and Picton, 1987). The mismatch negativity (MMN) is a negative component that peaks at about 100– 250 ms after deviance onset over fronto-central scalp areas (Näätänen et al., 1978; Näätänen, 1992; Näätänen and Winkler, 1999; for more recent reviews, see Picton et al., 2000; Näätänen et al., 2007). It is elicited by oddball stimuli in a sequence of repeating standard stimuli. According to the memory-trace theory, the MMN reflects a neural mismatch between the incoming stimulus and representations of those presented previously in the sequence (Näätänen, 1992). More recent theories view the MMN as an end result of a process aiming at predicting the future auditory stream on the basis of the previously heard sounds (Näätänen et al., 2011). The MMN is strongly correlated with the behavioral discrimination accuracy, depending upon the ability to perceive the difference between the standard and deviant stimuli and to maintain a memory of the presented stimulus characteristics (Pakarinen et al., 2009). The MMN can be elicited in the absence of attention (Näätänen et al., 1978; Alho, 1992; Näätänen, 1992), and therefore it is thought to represent a relatively automatic change detection process. Thus, the MMN provides a powerful tool with which to evaluate automatic change detection in a variety of clinical groups, e.g., stroke patients (Alain et al., 1998; Ilvonen et al., 2003), major depression (Kähkönen et al., 2007), schizophrenia (for a review, see Michie, 2001), dyslexia (Kujala et al., 2006), as well as in fetuses (Huotilainen et al., 2005), infants (Cheour-Luhtanen et al., 1996), and in aging (e.g., Alain and Woods, 1999). Typically, the MMN has been recorded using the oddball paradigm (Näätänen et al., 1978), where infrequent (probability P = 10–20%) deviant tones are scattered within a stream of continually repeated standard (P = 80–90%) tones. However, the oddball paradigm is timeconsuming, thereby diminishing its usability in clinical settings. Recently, new multi-feature MMN paradigms have been developed to shorten the recording time. They have enabled an unprecedentedly fast parametric evaluation of the central auditory processing of sound changes in simple tones (Näätänen et al., 2004; Pakarinen et al., 2010), musical sounds (Vuust et al., 2011) as well as in speech sounds (Pakarinen et al., 2009). Most typically the standard tone is alternated with several different types of deviants, each differing from the standard in one respect only, though MMN responses have also been recorded even without the standard stimulus (Pakarinen et al., 2010). Thönnesen et al. (2010) used the traditional oddball as well as the optimum MMN paradigms to investigate the processing of emotional prosody, i.e., nonverbal vocal expression of emotions. The stimuli were bisyllabic pseudowords varying in their emotional utterances (happy, angry, sad, and neutral). The authors showed that the MMN can be elicited by changes in emotional prosody independent of particular acoustic features. They suggested that processing of cognitive feature extraction and automatic emotion evaluation might overlap enabling rapid shifts of attention to socially important cues. If a deviant stimulus is sufficiently different from the standard one, the MMN is followed by a P3a wave, a positive response peaking approximately 250–400 ms following deviant onset (Escera et al., 1998), but also shorter P3a peak latencies have been reported when complex environmental sound stimuli are used (Alho et al., 1998). While the MMN has been proposed to play a role in the initiation of the possible attentional switch towards task-irrelevant acoustic changes (Näätänen, 1992), the P3a provides an index of the involuntary capture of attention to acoustic novelty and change (Escera et al., 1998; for a review, see Polich, 2007). There is evidence from magnetoelectrography (MEG), functional neuroimaging (fMRI), ERP, as well as from studies with patients with focal brain lesions suggesting that a wide-spread neural network brings about the automatic attention switching behavior. For instance, bilateral temporo-parietal and frontal association regions, lateral prefrontal cortex, and the left auditory cortex in the

auditory modality have been suggested as main regions of the P3a generation, the maximal being reached over the central and frontal scalp regions (Knight et al., 1989; Escera et al., 1998; Schröger et al., 2000; Yago et al., 2003; for reviews, see e.g., Soltani and Knight, 2000; Friedman et al., 2001; Polich, 2007). Several researchers have shown that novel environmental sounds that are irrelevant to the task at hand elicit a P3a, reflecting cerebral activity involved in involuntary orientation of attention towards novelty in the acoustic surrounding (Escera et al., 1998; Friedman et al., 2001; Gaeta et al., 2003; Cycowicz and Friedman, 2004; Escera and Corral, 2007). Such an attention capture may have consequences for behavior. For instance, when participants are working on a visual task, infrequent novel task-irrelevant auditory stimuli generate a P3a and disrupt performance at the visual task (Escera et al., 1998; Escera and Corral, 2007). If such disruptions of the original task are frequent, it is burdening for the participant and may feel like a loss of cognitive capacity. Emotional stimuli often elicit stronger and faster attention capture than neutral stimuli (Öhman et al., 2001; Campanella et al., 2002; Richards and Blanchette, 2004), especially for negative stimuli, such as those of threatening, fear inducing stimuli (Öhman et al., 2001), and angry faces (Esteves et al., 1994). Delplanque et al. (2005) showed that unpredictable visual stimuli, both highly emotional and neutral, elicited a clear P3a response, indicating reorientation of attention towards those stimuli. Combining the emotional context of visual stimuli with unexpected auditory events, Domínguez-Borràs et al. (2008) demonstrated that novel sounds yielded a stronger behavioral disruption on the participants' performance in a visual task when responding to negative pictures compared to neutral ones. The P3a was, accordingly, enhanced in amplitude in the negative context. These results suggest that mechanisms of involuntary attention are influenced by processing emotionally salient stimuli. Pakarinen et al. (2014) developed a variant of the multi-feature MMN paradigm with bisyllabic pseudoword speech sound stimuli where the probabilities of the standard and the nine deviant stimuli were identical. In addition to that, three rarely occurring variants of the standard sound stimulus with strong emotional prosody – happy, angry, and sad – were included in the sequence in order to achieve an attention-catching effect, similar to novel sounds. The authors showed an MMN that was evoked by all the deviants and the emotional speech sound stimuli. In addition to the MMN, the emotional stimuli generated a P3a which peaked earlier for the happy than for the angry and sad stimuli, compatible with the physical properties of the stimuli in the paradigm. 2. Methods The present study was a part of the “Job Burnout and Cognition” research project carried out at the Finnish Institute of Occupational Health (FIOH) in collaboration with the Occupational Health Centre of the city of Helsinki. Here, we investigated whether sound detection and automatic auditory change-detection processing, as reflected by the N1 and MMN, are affected by job burnout. Furthermore, we assessed the possible attentional alterations in people with mild to severe symptoms of job burnout, where the P3a was used as an index of involuntary attention switch to speech sound stimuli containing strong emotional prosody. As a method, we used a passive multi-feature pseudoword MMN paradigm containing emotional rarely occurring pseudowords reported in greater detail in Pakarinen et al. (2014). 2.1. Participants The participants (N = 67) were working people: experiencing symptoms of job burnout (N = 41, mean age 48.2 years, 4 men), and their non-burnout controls (N = 26, mean age 45.9 years, 3 men). The groups were matched on age, gender, education, and working experience, the age range being 27–62 years. The participants were city

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Table 1 Stimulus characteristics of the standard and deviant stimuli, and emotional variants of the standard. Stimulus

Utterance

Duration (ms)

Intensity (dB)

Frequency (Hz)

Total

Syllable

Syllable

336

Syllable 1st

2nd

168

168

Standard Deviants

/ta-ta/

Density

/ta-ta/

336

168

168

Frequency Intensity Location Noise Consonant duration Omission Vowel change

/ta-ta/ /ta-ta/ /ta-ta/ /ta-ta/ /ta-t:a/ /ta/ /ta-to/

336 336 336 336 420 172 336

168 168 168 168 144 168 168

168 168 168 168 176 0 168

Vowel duration

/ta-ta:/

400

168

232

Emotional variants (natural utterances) Happy /ta-ta:/ 388

125

263

Angry

/ta-ta/

337

125

212

Sad

/ta:-ta:/

436

218

218

1st

2nd

1st

2nd

−2.5

175

168.5

Deviance specifics Linear attenuation of the upper and/or lower harmonics within 100–5000 Hz (50% each); perceived as pressed vs. breathy voicing Frequency +/−25.5 Hz (50% each); perceived as pitch changes Intensity +/−6 dB (50% each); perceived as loudness changes Entire stimulus perceived from 90 ° left and right (50% each); 90 µs ITI Overlapping 60 ms (including 20 ms rise/fall times) of 20 dB of pink noise at 200–260 ms Removal of 16 ms at 140–160 ms, and addition of 100 ms silence between the syllables at 140-240 ms Linear fade out at 160–172 ms Natural utterance Intensity difference from Std: b1 dB Frequencies: 175 Hz and 168.5 Hz for the 1st and 2nd syllables, respectively⁎ Natural utterance Intensity difference of the 1st syllable from Std: −2 dB Frequencies: 168 Hz and 162 Hz⁎ Frequencies: 276 Hz and 177 Hz⁎ Intensities: +1 dB and −2 dB⁎ Frequencies: 276 Hz and 260 Hz⁎ Intensities: −1 dB and −2 dB⁎ Frequencies: 196 Hz and 163 Hz⁎ Intensities: +3 dB and −6 dB⁎

Note: All deviations occurred in the second syllable of the pseudoword, except for the location deviant in which the deviation appeared in the beginning of the pseudoword. Std denotes the Standard. ITI denotes interaural time difference between the stereo channels. ⁎ denotes the presented values for the 1st and 2nd syllables of the pseudoword, respectively.

employees who encounter cognitively demanding situations in their daily work day (e.g., interruption, repeated task switching), working in maximum of two shifts (i.e., shift work excluding night-shift employees). Participants were recruited from among customers of the Occupational Health Centre and employees of the city of Helsinki through advertisements displayed at the local occupational health care station, as well as on the intranet sites of the Occupational Health Centre and the city of Helsinki. Of the job burnout participants, 80% entered the study after noticing the advertisement, and 20% were referred by the physicians, psychologists, and nurses during appointments at the local occupational health care station. The candidates were first interviewed by telephone, and the inclusion criteria were that the subjectively experienced symptoms of burnout had to be viewed as deriving clearly from work by both the interviewer and the candidate. Exclusion criteria were excessive use of alcohol or drugs, diagnosed severe psychiatric or neurological disorders, and schizophrenia in first grade family members. Also other diagnosed illnesses that are of organic origin and result in fatigue, such as an organic sleep disorder or severe anemia, were considered as exclusion criteria. If the aforementioned criteria were met, the candidate was invited to participate in the study. Written informed consent for participation was obtained from all participants before entering the study. The protocol followed the Declaration of Helsinki for the rights of the participants and the procedures of the study. An ethical approval of the present research protocol for all participants was obtained from The Ethical Committee of the Hospital District of Helsinki and Uusimaa. Participants were given a modest gift. 2.2. Stimuli and procedure Participants were tested individually in two sessions, one consisting of electrophysiological recordings and the other of neuropsychological assessment. Participants were given the opportunity to attend the sessions consecutively within one day or on two separate days, according to their preference. Within 1–2 months after the sessions, the participants were offered a possibility to get individual oral feedback on

their performance in the neuropsychological assessment. During this visit, the participants were given a possibility to discuss their situation related to work with a psychologist (the corresponding author) and a neurologist. The ERP recordings were always carried out in the morning, lasting approximately 2–2.5 hours including breaks. The ERP sessions contained a total of five different paradigms, of which the last one, the multi-feature MMN paradigm, is reported here. In the beginning of the ERP session and just before the start of the MMN paradigm, the participants were asked to fill the 9-point Karolinska Sleepiness Scale (KSS; Åkerstedt and Gillberg, 1990), a subjective rating of sleepinessquestionnaire. In order to evaluate symptoms of job burnout, the Finnish version of the Maslach Burnout Inventory – General Survey (MBI-GS; Kalimo et al., 2006) was completed after the ERP recordings, and used as a criterion for grouping the participants into job burnout and control groups (cut-off point 1.5, i.e., at least mild job burnout). Furthermore, the following clinical measures were completed: the Finnish version of Beck's Depression Inventory (BDI-II, scoring range 0–63; Beck et al., 1996), Beck's Anxiety Inventory (BAI, scoring range 0–63; Beck and Steer, 1990), a modified version of the Basic Nordic Sleeping Questionnaire (BNSQ, scoring range 0–11; Partinen and Gislason, 1995) as well as a questionnaire concerning possible current medication for sleep disturbances and mood disorders. The stimuli in the multi-feature MMN paradigm were as follows: The standard stimulus was a 336-ms natural utterance of a bisyllabic Finnish pseudoword /ta-ta/, with the stress on the first syllable as indicated by slightly higher F0 (fundamental frequency, i.e., pitch) and intensity compared to the second syllable (Table 1). The deviants differed from the standard in spectral density, frequency, intensity, sound-source location (left/right), noise level, consonant duration (/ta-t:a/), omission (/ta-/), vowel change (/ta-to/), or the vowel duration (/ta-ta:/) of the second syllable of the pseudoword (referred to as Den, Fre, Int, Loc, Noi, ConDur, Om, VowCha, and VowDur, respectively; see Table 1). The deviation always occurred in the second syllable of the pseudoword, except for the location deviant in which the deviation

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750 ms

... DEN CONDUR LOC

INT VOWCHA STD

NOI VOWDUR EMO

FRE ...

Fig. 1. Schematic illustration of the stimulus sequence. Circles represent the sounds, and the slices represent different sound features, such as frequency. “Std” denotes the standard stimulus, “Emo” denotes the rare emotional stimuli (happy, angry, or sad), and the others, e.g., “Den” and “ConDur” denote the nine different deviants. Probability of the standard stimulus is Pstd ≈ 0.09, and the probability of each of the nine deviants is Pdev ≈ 0.09, each. The probability of the three emotional stimuli is Pemo ≈ 0.02, each. Stimulus-onset asynchrony (SOA) is 750 ms.

appeared in the beginning of the pseudoword. The vowel-change deviant (/ta-to/), and the vowel-duration deviant (/ta-ta:/) were recordings of natural utterances, and thus the physical characteristics of these deviants differed from the standard slightly on the first syllable too. The remaining seven deviants were created by digitally editing the standard stimulus and were thus identical to the standard except for the edited auditory attribute. Three variants of the standard sound with strong (exaggerated) emotional prosody, i.e., happy, angry, and sad, were used as rarely occurring, novelty-like variants of the standard. The physical characteristics of these emotional variants differed from those of the standard considerably, for example in length, pitch and momentary intensity. All stimuli were presented within the same stimulus sequence (Fig. 1) using the Presentation software (Neurobehavioral Systems, Inc., version 14.9). The standard stimulus and each deviant were presented 210 times each (P ≈ 0.09, each), and the three emotional stimuli were presented 42 times each (P ≈ 0.02). The stimuli were pseudorandomized in a way that neither the same deviant type nor the standard were ever repeated consecutively, and the emotional rare sounds were presented in varying intervals, once every 10–16 seconds. Thus, the arrangement of stimuli is similar to the no-standard multi-feature paradigm (Pakarinen et al., 2010), except that it includes the standard and the emotional rare stimuli. The stimulus-onset asynchrony (SOA; the amount of time between the onset of one stimulus and the onset of the next stimulus) was 750 ms, and the total recording time 28 min. 2.3. ERP recordings During the ERP recording, the participants watched a muted video film in a soundproofed measurement chamber, comfortably seated at an office workstation. They were instructed to relax, avoid excessive and unnecessary blinking, muscle tension and movements, as well as to ignore the sound stimuli. The stimuli were presented through loudspeakers placed on the wall of the chamber at a height of 160 cm. In addition, the loudspeakers were placed approximately 50 degrees to the left and right at a distance of 130 cm from the participant. Sound intensity was 57 dB sound pressure level (SPL) on average, and it was measured with an SPL meter placed at the position of the participants head. The EEG was recorded continuously (0–125 Hz, sampling rate 500 Hz) using a 32-channel active electrode system (actiCAP, Brain Products GmbH, Gilching, Germany) connected to a NeurOne amplifier (Mega Electronics Ltd, Kuopio, Finland). EEG data was collected from 26 electrodes placed according to the international 10–20 electrode system (excluding channels O1, O2, TP9, TP10, PO9 and PO10). The common reference and ground were placed in the electrode cap at electrode sites FCz and AFz, respectively. Two electrodes were placed at the left and right mastoids to allow re-referencing in later analyses. In addition, the bipolar horizontal electro-oculogram (HEOG) was recorded between two electrodes placed on the outer canthi of the eyes, and the vertical electro-oculogram (VEOG) between the electrodes placed above and below the left eye. Prior to recording, the impedances were checked twice, and if any significant noise appeared on the signal, the electrode contacts were checked again and an attempt was made to lower them according to the instructions provided by the manufacturer

of the active electrode system. During the recording, the EEG signal and the behavior of the participant were monitored via computer screen and online camera connection from the measurement chamber. The EEG/ERP analyses were conducted using EEGLAB (Delorme and Makeig, 2004). The EEG was bandpass-filtered offline (0.5–30 Hz), and re-referenced to the mean signal of the mastoid electrodes. The data was averaged in 600 ms epochs including a 100 ms pre-stimulus period, baseline corrected, and separately averaged for the standard, the nine deviants and the three emotional stimuli. The mean voltage of the pre-stimulus period served as a baseline for the amplitude measurements. Epochs contaminated by eye movement, or other extracerebral artifacts producing voltage changes exceeding a threshold value of +/− 65 μV at any electrode, as well as the large responses elicited by the first five stimuli of the stimulus sequence were omitted from averaging. Only data from the participants whose averaged ERP contained more than 65% of the total number of the presented stimuli (equals at least 137 standard trials, 137 of each of the deviant trials, and 28 of each of the emotional variant trials) were included in further analyses.

2.4. ERP analysis A complete data set from 61 participants, consisting of 37 participants with job burnout (mean age 47.8, standard deviation (sd) +/− 8.46 years, 3 men, 2 left-handed), and of 24 non-burnout control participants (mean age 46.2, sd +/− 9.15 years, 3 men, 3 lefthanded), was available for analyses. Data from six participants were discarded due to technical difficulties, or excessive artifacts. The averaged responses to the standard stimulus were used to calculate the N1 mean amplitudes and peak latencies. In order to calculate the MMN parameters, the averaged response to the standard was subtracted from those to the deviants and the emotional stimuli, resulting in nine difference signals for the deviant stimuli and three for the emotional rare sounds. Within the vowel-change, vowelduration, and omission deviant trials, two consecutive MMN responses were detected for each deviant due to the nature of the deviants (referred to as VowCha2, VowDur2, and Om2, respectively). The P3a properties were measured from the ERPs elicited by the three emotional rare sounds (happy, angry, and sad). The ERP analyses were conducted on measurements from the electrode site Fz where the grand average mean amplitudes were found to be most pronounced, as is typical for the MMN (for a review, see Kujala et al., 2007). For each participant, we first identified the N1 peak latency as the largest negative deflection between 50 and 150 ms after stimulus onset at Fz, and then calculated the mean amplitude for a 40-ms window centered on the peak latency. The MMN was defined as the most negative peaks between 100–220 ms from deviance onset in the grand average difference signals. As for N1, for each participant we first identified the MMN peak latency at Fz, and then measured the mean amplitude for a 40-ms window centered on the peak. The same was done for the MMN elicited by the emotional rare sounds, with the exception that we used a 60-ms window. The P3a was defined as the most positive peaks within a predetermined time windows from deviance onset (200− 300 ms for happy, and 250− 350 ms for angry

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and sad). The P3a mean amplitude was measured for a 60-ms window centered at the peak latency at Fz. 2.5. Statistical analysis Statistical analyses were carried out using the R software environment for statistical computing and graphics (version 2.15.3; http:// www.r-project.org/; R Core Team, 2014; Wickham, 2009). The N1 mean amplitudes and peak latencies were compared between the standard stimulus and study groups (job burnout vs. control group) with one-way analyses of variance (ANOVA). In order to test the effects of the stimulus type (12 MMNs for deviants and three for rare emotional stimuli) and the study group on the MMN mean amplitudes and peak latencies we used two-way repeated-measures ANOVA with study group as the between-subject factor, and the stimulus type as the within-subject factor. Similarly, the P3a mean amplitudes and peak latencies were compared between the stimulus type (happy, angry, and sad) and study group with rANOVA. The procedure included correction of sphericity using the Mauchly's procedure, and GreenhouseGeisser corrections for all ANOVAs were used where appropriate (the original F values, corrected p-values and effect sizes are reported). Holm-Bonferroni corrected post hoc t-tests were carried out for the significant main effects and interactions.

431

sounds, both the mean amplitudes and peak latencies (Figs. 2–4) were comparable between the groups (F1,59 = 0.67, p = 0.42, η2 = 0.002; F 1,59 = 0.08, p = 0.78, η 2 b 0.001, respectively). The main effects of stimulus type on MMN amplitude and latency were significant (F14,826 = 39.97, p b 0.001, η2 = 0.35; F14,826 = 977.13, p b 0.001, η2 = 0.94, respectively). For the MMN peak latencies, the interaction between group and stimulus type was significant (F 14,826 = 2.45, p = 0.009, η2 = 0.04). Pairwise post hoc tests revealed that the latencies in the job burnout group were significantly longer for consonant duration and shorter for the second MMN response for vowel duration than in the control group (Holm-Bonferroni: p b 0.001). The P3a mean amplitudes and peak latencies for the emotional variants and the study groups yielded no main effect of group (F1,59 = 1.11, p = 0.3, η2 = 0.01; F1,59 = 0.01, p = 0.91, η2 b 0.001, respectively). The emotional variant type had an effect on both the P3a amplitudes and latencies (F2,118 = 23.48, p b 0.001, η2 = 0.17; F2,118 = 176.67, p b 0.001, η2 = 0.69, respectively). For the peak latencies, a significant interaction between study group and emotional variant type was observed (F2,118 = 5.98, p = 0.005, η2 = 0.07). The P3a latencies for the job burnout group were shorter for the angry (p = 0.01), and longer for the happy (p = 0.02) variants as compared with those for the control group (Figs. 5 and 6). The P3a latencies for the sad variant were comparable between the groups (p = 0.25).

3. Results 4. Discussion The descriptive statistics as well as the correlations between job burnout, symptoms of anxiety and depression, and sleeping disturbances are presented in Tables 2 and 3, respectively. The self-reported prescribed medication within 24 hours prior to the recordings was as follows: medication for sleep disturbances 8% and 0%, and mood disorders 24% and 17% for the job burnout and control groups, respectively. The average score for the KSS questionnaire (Åkerstedt and Gillberg, 1990) before the onset of ERP recordings was higher for the job burnout group (M = 5.0, sd = 1.34) than for the control group (M = 4.0, sd = 1.67; t58 = 2.49, p = 0.02). Also the KSS score prior to the MMN paradigm (approximately 1.5 hours from the beginning of the ERP session) was higher for the job burnout group (M = 5.6, sd = 1.14) compared to the control group (M = 4.5, sd = 1.19; t58 = 3.30, p = 0.002). In the ERP analysis, we used depressive symptoms (BDI score) as covariate to assess whether the job burnout group's higher depressive symptoms would account for group differences in the ERPs. The N1 amplitudes and latencies elicited by the standard stimuli were comparable between the job burnout and control groups (F1,59 = 0.08, p = 0.78, η2 b 0.001; F1,59 = 0.85, p = 0.36, η2 = 0.01, respectively). The group mean average MMN and P3a peak latencies for the job burnout and control groups at Fz are presented in Table 4. For the MMNs elicited by the nine deviants and three emotional rare Table 2 The descriptive statistics of 61 participants included in the analyses in the job burnout and the control groups. Standard deviations are presented in parenthesis. Variable

Age Job burnout level (MBI-GS) Education (in years) Working experience (in years) Symptoms of anxiety (BAI) Depressive symptoms (BDI-II) Sleep disturbances (BNSQ)

Job burnout

Controls

Mean (sd)

Mean (sd)

47.78 (8.46) 3.13 0.93) 15.54 (2.02) 22.06 (10.83) 10.16 (5.7) 16.43 (6.14) 2.97 (1.92)

46.21 (9.16) 0.89 (0.4) 15.21 (1.91) 21.54 (13.26) 4.00 (3.64) 5.25 (5.18) 1.58 (1.56)

t value

−0.69, ns. 11.1*** −0.64, ns. 0.169, ns. −4.71*** −7.38*** 2.96**

Note: MBI-GS = Maslach Burnout Inventory – General Survey; BAI = Beck's Anxiety Inventory; BDI-II = Beck's Depression Inventory; BNSQ = a modified version of the Basic Nordic Sleeping Questionnaire. Results of two-tailed t-tests ⁎⁎ p b 0.01. ⁎⁎⁎ p b 0.001.

The present study was designed to examine the electrophysiological correlates of auditory perception, automatic change detection processes and involuntary attention capture in job burnout. We found typical N1 responses to standard sounds, which was comparable in both groups. However, no difference between the job burnout and control groups was found in the N1 and MMN amplitudes and latencies in response to the emotional stimuli. In response to the nine deviant stimuli giving rise to twelve MMN responses, the groups did not differ in respect to any of the MMN amplitudes, or ten of the latencies. Only one shorter and one longer MMN latency were observed in the job burnout group, related to duration changes. These highly similar response patterns suggest that an accurate memory trace is constructed for the invariant sound features of the auditory input for both groups (Näätänen, 1992; Näätänen et al., 2004; Pakarinen et al., 2010; Thönnesen et al., 2010). The emotional speech sound stimuli generated significant P3a responses consistent with the involuntary attention capture triggered to these rarely occurring stimuli. Overall, the ERP waveforms observed in the N1, MMN, and P3a latency ranges followed the acoustical properties of the stimuli, and were consistent with the findings of Pakarinen et al. (2014). For example, the responses to the happy stimulus peaked earlier than the responses to the stimulus with angry prosody. More importantly, the P3a latencies were significantly shorter to angrily uttered speech sounds, and slower to happy stimuli in the job burnout than in the control group, and this difference remained even after controlling for depressive symptoms in an analysis of covariance. The present results suggest that the detection of relevant speechsound changes in the auditory environment as reflected by the N1 and MMN are intact in our sample of participants with job burnout. Further, the P3a latencies were found to vary with the type of emotional stimuli. The observed P3a responses need to be considered in relation to the MMN and N1 signals as they reflect not only the novelty or the emotional content of the stimuli but also the physical deviation, the saliency from the standard (Escera et al., 1998; Polich, 2007). The fact that the N1 and MMN responses were comparable in both groups suggest that the divergent P3a latencies towards negative and positive emotions between the groups might be due to the emotional properties of the novelty-like stimuli, and not the detection of basic sound features such as frequency or intensity alone. These result suggest that our participants with job burnout displayed an attention capture tendency

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Table 3 Correlation matrix showing binary correlation coefficients (Pearson R), and the corresponding p-values for all significant variables presented in Table 2.

Job burnout (MBI-GS) Depression (BDI-II) Anxiety (BAI) Sleep disturbances

Job burnout

Depression

Anxiety

Sleep

(MBI-GS)

(BDI-II)

(BAI)

disturbances

1 0.71, p b 0.001 0.58, p b 0.001 0.29, p = 0.05

1 0.66, p b 0.001 0.28, p = 0.05

1 0.24, p = 0.1

1

that is faster for negative, and slower for positive emotions compared to that of the non-burnout control participants. However, some of our findings should be interpreted cautiously because of the heterogeneity of our sample of participants reporting job burnout. Although we statistically controlled for depressive symptoms, one cannot easily assess the contribution of symptoms of anxiety and sleep disturbances. Nonetheless, as the participants were currently working and not diagnosed with clinical severe depression or anxiety disorders, or sleep problems, both groups can be considered representative of Finnish working life (Ahola et al., 2006). Secondly, the P3a peak latency differences between the groups were fairly small albeit significant. To our knowledge, this is the first investigation of neural correlates regarding speech sound discrimination and processing of emotional sounds in job burnout, and further research is needed to replicate and extend these findings to a larger sample, and to evaluate the results in relation to previous studies concerning related conditions such as major depression, or mental fatigue. The relationship especially between job burnout and depression has been under debate from the outset of burnout research (Bradley, 1969; Freudenberger, 1974). They have been argued to share some important characteristics, especially dysphoric symptoms, including fatigue, inability to concentrate, difficulty relaxing off work, and distancing, but they are not identical concepts (Bakker et al., 2000; Brenninkmeyer et al., 2001). A recent study of Ahola et al. (2014) suggest a conceptual similarity of burnout and depressive symptoms in the work context. Indeed, burnout is identified as a work-related syndrome (Maslach et al., 1996, 2001), whereas depression is non-specific in nature, and can Table 4 The group mean average MMN and P3a peak latencies (ms) for the job burnout and control groups at Fz in both the deviant and the emotional rare sound trials. Standard deviations are presented in parenthesis. The two rightmost columns show the ranges of the peak latencies from stimulus onset. Deviant

Latency

Range of peak latencies

Job burnout

Control

Job burnout

Control

MMN Density Frequency Intensity Location Noise Consonant duration Omission 1 Omission 2 Vowel change 1 Vowel change 2 Vowel duration 1 Vowel duration 2

329 (15) 317 (26) 352 (23) 139 (25) 306 (18) 248 (17) 238 (28) 356 (36) 136 (33) 361 (33) 145 (33) 315 (27)

326 (19) 319 (23) 345 (28) 134 (23) 310 (16) 230 (18) 239 (12) 360 (30) 142 (28) 359 (36) 141 (31) 344 (33)

294–354 270–366 314–400 88–184 260–348 214–298 196–296 306–406 88–188 302–402 98–198 270–360

284–360 276–368 298–398 102–176 280–344 192–254 218–274 306–404 98–192 306–404 82–182 302–400

Emotional rare sounds

Job burnout

Control

Job burnout

Control

MMN Happy Angry Sad

123 (19) 130 (22) 144 (19)

117 (11) 126 (18) 134 (14)

78–168 86–178 98–178

90–136 88–170 102–154

P3a Happy Angry Sad

229 (19) 284 (28) 290 (19)

217 (18) 302 (29) 295 (22)

190–278 246–340 244–326

176–240 260–360 250–330

develop in any domain of life influencing all aspects of life, including work (Bakker et al., 2000; Gruenberg and Goldstein, 2003; Warr, 1987). Evidence of the overlap with anxiety indicate that high levels of emotional exhaustion and self-control demands at work may increase individual's level of anxiety in stressful situations and may weaken their ability to cope with anxiety (Winnubst, 1993; Diestel and Schmidt, 2010). Earlier ERP results on patients with major depressive disorder are yet inconsistent regarding the MMN waveforms, suggesting both reduced (Takei et al., 2009; Qiao et al., 2013), and increased (Kähkönen et al., 2007) MMN amplitudes as well as shorter (Lepistö et al., 2004), and longer (Qiao et al., 2013) MMN latencies as compared with control participants. In addition, impairments of selective attention in depression have been reported as indicated by a reduction in the P300 amplitude (Urretavizcaya et al., 2003), and longer P300 peak latencies (Kemp et al., 2010). In their ERP study on emotional semantic material, McNeely et al. (2008) suggested that there is an association between increased electrophysiological activity to salient negative stimuli and higher levels of depression. The interpretation of auditory emotional features was also shown to be shifted towards negative emotions in people reporting depressive symptoms (Vuoskoski and Eerola, 2011). The same emotional sounds and musical excerpts were rated as more negative by individuals with depressive symptoms, indicating a topdown predisposition towards attending to negative emotions in the excerpts. Several studies have demonstrated that occupational stress is related to fatigue and disturbed sleep (Melamed et al., 1999; Åkerstedt et al., 2002; Dahlgren et al., 2005; Ekstedt et al., 2009), resulting in lower sleep quality, more awakenings, and insufficient sleep (Ekstedt et al., 2006). In our study, the subjective ratings of sleepiness (KSS; Åkerstedt and Gillberg, 1990) during the ERP session indicate that participants having job burnout symptoms were already significantly more exhausted than the control participants at the beginning of the recording session, and further, they became more exhausted than the control group during the cognitively demanding research day. The selfreported medication for sleep disturbances and mood disorders was found to be fairly low and nearly equal between the groups indicating that medication had little impact on the findings reported here. Given that we introduced depressive symptoms as a covariate in our analyses, one might argue that the observed P3a latency differences are due to increased fatigue. Evidence from ERP studies evaluating the effects of mental fatigue on attention during prolonged periods of cognitively demanding tasks suggest decreased N1 and N2b amplitudes with time on task (Boksem et al., 2005), as well as increased P3 latencies suggesting a delay in stimulus evaluation time due to mental fatigue (Kato et al., 2009). Consequently, if this were the case in our study, then differences in the N1 and MMN between the groups should have been expected, and the P3a peak latencies in the job burnout group should have been longer for all the emotional variants than in the control group, and not just for the positive stimuli. In previous studies, emotional context has been suggested to have a boosting effect on the activation on neural networks in the auditory novelty processing system (Domínguez-Borràs et al., 2008, 2009). Results from studies both in the auditory (Escera et al., 2003) and visual modality (Pessoa et al., 2002) indicate that attentional resources are, indeed, required for semantic analysis of significant stimuli and differential response to valence. Further, there is increasing

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Fig. 2. Difference waves for both groups showing MMN responses for each deviant at electrode site Fz. The red and black line segments denote the time windows (for job burnout, n = 37, and control, n = 24, groups, respectively) where the mean voltages for each participant were calculated, based on peak latencies measured from the grand average waveforms (40-ms period centered at the peak latency). Peak latencies (ms) are presented in red and black (for job burnout and control groups, respectively). Sound onset is at 0.

evidence that involuntary attention switching is not fully determined by means of bottom-up processing, but top-down modulation of processing novelty plays a more significant role than previously thought (Berti and Schröger, 2003; Sussmann et al., 2003; Chong et al., 2008; Schomaker and Meeter, 2014). Indeed, Campanella et al. (2002) suggested that cognitive processing might be triggered by the explicit evaluation of the emotional load of the stimuli. Nevertheless, further refinement is needed to specify the role of mental fatigue in cognitive processing, and processing of emotional information in job burnout. Processing emotionally salient information influences mechanisms of involuntary attention so that unexpected auditory events

Fig. 3. Barplots showing the group mean average MMN mean amplitudes (μV) for both groups, as well as the nine deviant and three emotional variant types: consonant duration of the second syllable of the pseudoword (ConDur), density (Den), frequency (Fre), intensity (Int), sound-source location (left/right; Loc), noise level (Noise), and omission (Om and Om2), vowel change (VowCha and VowCha2) and the vowel duration (VowDur and VowDur2) of the second syllable of the pseudoword as well as happy, angry, and sad at electrode site Fz. Error bars represent standard error of the means.

may capture attention, providing crucial information for coping in emotionally and socially influential situations. Such processes are evolutionarily important, automatic, and strong in other mammals, too. Even though the emotional stimuli in our study were not novel as such, but rarely occurring novelty-like variants of the standard, our results are consistent with studies evaluating the detection of auditory deviant and novel events (Escera et al., 1998; Friedman et al., 2001; Gaeta et al., 2001). Although a significant MMN was elicited in both the job burnout and control groups by all nine deviants and two emotional rare sounds, a significant P3a was elicited only by the emotional stimuli – happy, angry, and sad – which could be considered as noticeably deviating. The observed P3a responses were frontally oriented, as is typical for the response (Friedman et al., 2001; Soltani and Knight, 2000). Further, there is evidence that when elicited

Fig. 4. Barplots showing the group mean average MMN peak latencies for both groups, and the deviants and emotional rare sounds at Fz. Error bars represent standard error of the means.

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Fig. 5. Grand average and difference signals from the emotional rare sounds for job burnout and control groups overlapped with time-amplitude illustrations of the stimuli (panel A). The red line denotes the job burnout group, the black line the control group. Time-amplitude illustrations of the stimuli appear in grey. Panel B: Topographical voltage maps for P3a peak latencies (Fz) for the emotional rare sounds for both groups (26 electrodes presented). * denotes p = 0.02 for happy; p = 0.01 for angry variants.

by environmental sounds, the scalp topography is even more frontally pronounced (Cycowicz and Friedman, 2004; Gaeta et al., 2003). The MMN as a change-detector mechanism may create a possibility for the involuntary capture of attention, but does not necessarily mean that the attention had shifted, whereas the P3a responses indicate that the novelty-like, emotionally valenced events had captured attention, reflecting the activation of an attentional switching process. As a general finding, momentary involuntary capture of attention to emotionally valenced speech sounds seems to be altered in job burnout. The present results are of assistance in characterizing this subject group with various work-related burnout symptoms. However, as electrophysiological mechanisms in job burnout are yet deficiently understood, more studies are needed to shed light on whether the differences in attention capture lie in the emotional content of

speech suggesting top-down modulation of novelty processing, fatigue, or specifically processing of certain auditory attributes. Acknowledgements The authors thank RN Nina Lapveteläinen and RN Riitta Velin for their assistance in data collection; MD Markku Sainio for his contribution as the responsible neurologist of the present study; MD Christer Hublin for his partial supervision of the data analysis concerning sleeping problems; clinical neuropsychologist Ritva Akila for her contribution in the neuropsychological questions; and development managers Anna-Maria Teperi and Ritva Teerimäki at the Occupational Health Centre, city of Helsinki for collaboration. The present study was supported by the SalWe Research Programme for Mind and Body (Tekes – The Finnish Funding Agency for Technology and Innovation, grant 1104/10). References

Fig. 6. Barplots showing the group mean average P3a peak latencies (ms) and the standard errors for the emotional rare sounds at electrode site Fz in the job burnout and control groups.

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