Keywords
burnout, direct current stimulation, attention, working memory, prefrontal cortex
This article is included in the All trials matter collection.
burnout, direct current stimulation, attention, working memory, prefrontal cortex
All changes made are in response to the comments of reviewer 1. The introduction has been extended with a brief paragraph on the necessity of multiple sessions and the possible neurophysiological mechanism in burnout. In addition, it has been stressed that this is, to our knowledge, the first study investigating the effect of tDCS in burnout patients. The methodology has been clarified on how tDCS was administered to ensure effective stimulation. In the results section, Table 2 has been extended to provide more information about the participants (concerning medication, education level, etc.). The limitations section has also been extended to point out some weaknesses of our study that should be addressed in future studies (recruitment issues, impact of medication, efficacy of blinding, electrode placement, relation with the dopaminergic system). The discussion was also updated to clarify which results were expected and which were unexpected due to the left DLPFC stimulation. Some paragraphs have also been added about the effect of the behavioral therapy since this could also have played a role in the improvement of the patients' scores.
See the authors' detailed response to the review by Choi Deblieck
atDCS anodal transcranial Direct Current Stimulation
BDI Beck’s Depression Inventory
BNT Boston Naming Test
DSM-V 5th edition of the Diagnostic and Statistical Manual for Mental Disorders
ICD-10 10th edition of the International Statistical Classification of Diseases and Related Health Problems
MBS Maslach Burnout Scale
NMDA N-Methyl-D-Aspartate
RBANS Repeatable Battery for the Assessment of Neuropsychological Status
SD Standard Deviation
tDCS transcranial Direct Current Stimulation
TMT Trail Making Test
WCST Wisconsin Card Sorting Test
QoL McGill Quality of Life Questionnaire
The percentage of employees experiencing burnout is dramatically increasing in Europe (Eurofound, 2018), which has a significant socio-economic impact. Burnout consists of three components: (1) exhaustion at the physical level (energy loss, fatigue, weakness, physical and psychosomatic complaints), the mental level (negative behavior towards oneself, work, or life in general), or the emotional level (feelings of being trapped in a situation, helplessness, or hopelessness); (2) depersonalization or alienation towards the actual work, towards patients or pupils, etc. (Demerouti et al., 2001; Schaufeli & Enzmann, 1998); (3) and reduced professional performance, which can be attributed to depersonalization and alienation (Demerouti et al., 2001). Since the beginning of 2011, burnout has been added to the 10th edition of the International Statistical Classification of Diseases and Related Health Problems (ICD-10: Z73.0: Word Health Organization, 2011), which describes burnout as a 'state of vital exhaustion'. The 5th edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM-V: American Psychiatric Association, 2013), on the other hand, categorizes burnout under 'somatic symptoms and related disorders'.
Patients with burnout are impaired in one or more of the four components of working memory, i.e. the central executive, the phonological loop, the visuospatial sketchpad and/or the episodic buffer (see Figure 1) (Baddeley, 2000; Deligkaris et al., 2014). The working memory, or the short-term memory, refers to a limited-capacity cognitive system that allows the temporary storage and manipulation of information from different modalities, provided by the sensory memory, that are necessary for complex tasks. (1) The phonological loop is responsible for encoding language in the long-term memory and for short-term retention of phonological information through repetition (Baddeley et al., 1998). (2) The visuospatial sketchpad temporarily stores visual and spatial information. (3) The episodic buffer temporarily stores and integrates information from the other components, and links information to time and space to make storage and invocation easier (Baddeley, 2000). These three components are controlled by the fourth component, i.e. (4) the central executive, which ensures that targeted actions can be taken by guiding attention towards relevant information in the sensory memory (Baddeley, 1996). The central executive operates by (1) inhibition, i.e. the suppression of dominant, automatic answers, and the resistance to interference caused by distractors; (2) shifting, which refers to the possibility to switch cognitively between various tasks, mental states, or operations; and (3) updating of the working memory (Miyake et al., 2000).
The working memory does not only monitor and direct attention, it is also responsible for the storage of information in the long-term memory (encoding) and recall of information from that same memory (retrieval) (Baddeley, 1996; Baddeley & Sala, 1996).
Based on this model, deficits of executive functions and attention could be attributed to dysfunction of the central executive component (Baddeley, 1996). Accordingly, impairment of nonverbal memory deficits could be associated with the visuospatial sketchpad (Papagno, 2002), verbal memory deficits could be connected to the phonological loop (Vallar & Baddeley, 1984), and episodic (long-term) memory disruption could be attributed to dysfunction of the episodic buffer (Quinette et al., 2006). However, not all components of the working memory model are equally affected in burnout. A recent meta-analysis stated that burnout primarily affects attention, vigilance (i.e. sustained attention), and the central executive, more specifically memory updating and monitoring (Riedrich et al., 2017).
Transcranial direct current stimulation (tDCS) is a non-invasive neurostimulation technique that modulates cortical excitability to enhance brain function by means of a low electrical current applied over the skull (Brunoni et al., 2012; Nitsche & Paulus, 2011). tDCS is increasingly used in the treatmentof motor, cognitive, and affective symptoms in different patient populations, both in neurological (e.g. Alzheimer’s disease; Flöel, 2014), and psychiatric disorders (e.g. major depressive disorder Nitsche et al., 2009) (Brunoni et al., 2012). The therapeutic potential of tDCS is gaining interest. In a double-blind sham-controlled trial consisting of three weeks (15 sessions) of active or sham anodal tDCS (atDCS) (2mA) over the left dorsolateral prefrontal cortex (DLPFC), Loo et al. confirmed the antidepressant efficacy of atDCS in patients with depression. In addition, mood, attention skills, and working memory also significantly improved after active tDCS treatment (Loo et al., 2012). Moreover, a recent study by Miler, Meron, Baldwin, and Garner showed that a single session of DLPFC stimulation can improve executive control of attention in healthy adults (Miler et al., 2018). However, to induce a longer-lasting effect, repeated sessions are advised and it has already been shown that this can have a cumulative effect which is associated with greater magnitude and longer duration of the behavioral effects (Brunoni et al., 2012).
One of the mechanisms that might be responsible for the cognitive problems in burnout patients is a dopaminergic dysfunction in the prefrontal cortex. It has been shown that dopamine in the prefrontal cortex plays a critical role in working memory and cognitive control (Polizzotto et al., 2020; Cools & D’Esposito, 2011) and that (chronic) stress can have a deteriorating effect on the dopaminergic system in this area (Mizoguchi et al., 2000). tDCS has been known to interact with dopaminergic systems (Polizzotto et al., 2020) and therefore tDCS over the DLPFC might be able to restore dopaminergic prefrontal cortex function.
The effects of tDCS have not yet been extensively evaluated in burnout patients. Some studies have used tDCS in stress-related patient populations, such as professional nurses (Stanton et al., 2015) or post-traumatic stress disorder (Saunders et al., 2015), however, to our knowledge, our study is the first to use tDCS in a burnout population.
Studies have shown that burnout patients are primarily impaired in attention and the central executive (Riedrich et al., 2017). We tested the hypothesis that atDCS over the left DLPFC could improve the general well-being of recovering burnout patients by boosting the recovery of the executive control of attention. Since this is the first study using tDCS in the rehabilitation of burnout patients, other components of the working memory were also measured to monitor the impact of burnout and the effect of atDCS on these components.
Patients were recruited between January 2015 and December 2017 via a treatment center in Belgium specialized in the diagnosis and treatment of burnout (DIADIS NV, Oud-Turnhout). The definition of (Brenninkmeijer et al., 2001) was used to identify burnout patients, and a score of > 4 on the Dutch version of the Maslach Burnout Scale (MBS: Maslach-Pines, 2005) was considered an inclusion criterium. Patients with 1) excessive drug or alcohol use, 2) epilepsy, 3) depression, 4) bipolar syndrome, 5) chronic fatigue syndrome or any other history of psychiatric or neurological disorders, 6) implanted neurostimulator or pace-maker, 7) drugs interacting directly with the NMDA receptors, or 8) pregnancy were excluded. When new patients were diagnosed with burnout in the treatment center, they were asked whether they wanted to participate in the study. Included patients were pseudo-randomly assigned to a real atDCS or sham tDCS group using a pre-defined allocation code file in excel (to make sure that both groups were of equal size). Initially, 20 participants were targeted (10 per tDCS group) as a pilot study. This number was primarily based on practical issues, such as the average number of burnout patients that were treated every year at the treatment center, and the time the treating psychologist could devote to the study. All assessments were performed by the sole psychologist of the treatment center (PVN).
This study was approved by the ethical committee CME of the Vrije Universiteit Brussels (VUB) (B.U.N. 143201422009). All patients signed an informed consent. The trial was retrospectively registered at ISRCTN.com on 17/11/19 (ISRCTN94275121), since clinical trial registration was not explicitly required by the advising ethical committee for trials with an experimental device at the start of the trial. All protocol and trial details are available from the registration page.
After inclusion, baseline measures were taken to evaluate burnout, depression, quality of life, attention, and different components of the working memory. Burnout, depression, and overall quality of life were assessed by the MBS, the Beck’s Depression Inventory (BDI: Van der Does, 2002), and Question A of the Dutch version of the McGill Quality of Life Questionnaire (QoL: Cohen et al., 1997); translated by Kenniscentra Palliatieve Zorg) respectively.
Attention was measured by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS: Randolph, 1998) Attention Index, and vigilance by the s-score of the D2 test (variability in processing speed).
The central executive of the working memory was evaluated with the following tests. Inhibition and shifting were assessed with Card III of the Stroop Color-Word test (Golden, 1978), the Trail Making Test part B (TMT: Reitan, 1958) and the Wisconsin Card sorting test (WCST: Heaton et al., 1993). Processing speed, i.e., updating and control, was assessed by the TMT part A, Cards I and II of the Stroop Color-Word test, and the D2 test (Gz: total number of tokens scanned; F%: error percentage relative to Gz; Gz – F: number of correctly identified tokens) (Brickenkamp, 1962).
As regards to the other components of the working memory: the phonological loop was tested by the Language Index of the RBANS, the Boston naming test (BNT: Kaplan et al., 1983; Flemish version BNT: Mariën et al., 1998) and semantic fluency tasks (naming as many animals, vegetables, means of transportation and clothes as possible within one minute). To determine the percentile of semantic fluency, Dutch non-published age-, gender-, and education-related norms were used (These data were obtained by master students in Linguistics at the VUB of 200 healthy participants in Belgium of varying age, gender, education, and geographic location and are available as extended data (van Dun, 2020)). These data were used to calculate the z-scores that were then converted to percentiles. The visuospatial sketchpad was assessed using the Raven’s progressive matrices (Raven, 1965), and the Visuospatial Index of the RBANS. Encoding was evaluated with the Immediate Memory Index and retrieval with the Recent Memory Index of the RBANS.
A categorized overview of the different tests is presented in Table 1.
[i] Legend: MBS = Maslach Burnout Scale; BDI = Beck’s Depression Inventory; QoL = McGill Quality of Life Questionnaire; RBANS = Repeatable Battery for the Assessment of Neuropsychological Status; Stroop = Stroop Color-Word test; TMT = TrailMaking Test; WCST = Wisconsin Card Sorting Test; BNT = Boston Naming Test; Raven = Raven’s progressive matrices; SS = Standard Score; Pct. = Percentile.
After treatment, all tests were repeated to evaluate the impact of atDCS. Therapy always started on a Monday, and re-evaluation was completed the first Monday after the final atDCS session.
The primary outcome measure was attention. Secondary outcome measures were general measures (burnout, depression, and quality of life), and other components of the working memory (central executive, phonological loop, visuospatial sketchpad, encoding and retrieval).
All patients received the standard behavioral therapy consisting of one session a week (for 3 weeks) focusing on 1) psycho-education and relaxation, 2) reducing mental overload, 3) defining and working to personal goals, 4) relapse prevention. 1) In the first session, the stress mechanism was explained, together with the characteristics that belong to it. Breathing exercises were taught to the patient through heart rhythm coherence, using EmWave2 software to visually guide the patients. 2) To reduce the mental overload, ‘don’t worry’-techniques were explained. Patients were advised to write down their worries and not get distracted by them continuously. Via cognitive behavioral therapy, using the ABCDE model (Ellis et al., 1997), they were taught to translate negative into positive thoughts. 3) During therapy, the patient’s life goals in different domains (e.g. work, personal relations, education, parenthood, friends, physical well-being, …) were established together with the therapist. In dialogue, priorities were established and possible (mental) barriers were discussed. This discussion primarily focused on rebalancing the different domains in the patient’s life. 4) Lastly, the therapy focused on reintegration on the work floor. Bad habits were identified and strategies were discussed to prevent the patients from falling back into these habits.
None of the patients had received psychotherapy before inclusion in this study.
In addition, patients received daily sessions of 2mA atDCS (TCT Research Limited, Hong Kong) over the left DLPFC (AF3 on the international 10/20 EEG system) (electrode size: 5x5cm2) and the reference electrode (5x7cm2) over the lateral aspect of the contralateral orbit (F8), as described in (Loo et al., 2012). The carbon electrodes were covered in sponges soaked in saline solution (0.9% NaCl) to improve conductivity. These were placed over the scalp using neoprene straps. Since these can absorb the saline solution, two different straps were used for both electrodes to avoid creating bridges, and throughout the sessions the absorption was monitored so that it would not spread beyond the surface of the electrodes. In the real tDCS group, stimulation lasted for 20min with a gradual ramp up over 30s. This resulted in a maximal current density of 0.08mA/cm2 and a total charge of 0.096C/cm2 per session. Impedance was continuously monitored during stimulation to stay below 10kOhm and was automatically disrupted for safety when it went above 15kOhm. During sham stimulation, the current was ramped up over 30s to 2mA after which it was immediately ramped down to simulate the cutaneous sensation of tDCS in the sham group. No therapy was given during stimulation. This resulted in 15 sessions in total (3 weeks, 5x/week). One group received real tDCS, the other received sham tDCS. The tDCS device was programmed by the therapist, but the patients did not know which type of tDCS they received. All test results were coded to blind the researcher who performed the analyses and data was unblinded only after the analyses were done. The protocol and electrode placement are illustrated in Figure 2.
All therapy and tDCS sessions were performed at the treatment center DIADIS NV in Oud-Turnhout, where the patients were recruited, by the same psychologist and co-author Pia Van Noppen.
Means and standard deviations (SDs) were reported to give a general overview of the results. An independent samples t-test was used to compare mean age between groups.
A full-factorial 2 (tDCS: sham, real) x 2 (time: pre, post) fixed effects linear mixed model with subject as a random effect was used to compare the results on all test measures between the sham and real tDCS groups before and after treatment. Normality and homoscedasticity of the residual data were checked via a normal quantile plot and residual plot, respectively. If model assumptions were violated, the outcome variable was transformed using the Box-Cox procedure (Box & Cox, 1964), as implemented in the MASS package in R version 7.3-51.4. Tukey HSD post-hoc pairwise comparisons were used to compare baseline scores between groups and to explore possible interaction effects. The level of significance was set at α = 0.05. All statistical analyses and figures were generated using the statistical software R version 3.6.0.
In total, 16 patients (11F, 5M) were recruited and received either real (n = 8) or sham (n = 8) treatment. Of these, 15 (10F, 5M) were included in the analysis. One participant (pp01, F, sham) was excluded after analysis because she was diagnosed with sensory processing sensitivity (SPS). Mean age of our final sample (n = 15) was 44.8y ± 5.8y, with no significant difference between the real (42.5y ± 5.5y) and sham group (47.4y ± 5.3y) (t(12.86) = 1.76, p = 0.103). No participants reported serious adverse events. Only one complained about dizziness at the end of the stimulation.
An overview of the demographic characteristics and the initial scores on the MBS, the Dutch version of the BDI, and question A of the Dutch version of the QoL are given in Table 2A (see underlying data (van Dun, 2020)). Table 2B contains additional demographic characteristics and working-related information. A flow chart is provided in Figure 3.
The linear mixed model revealed a significant effect of Time for the MBS (F(1, 13) = 15.10, p = 0.002), but no effect of tDCS (F(1, 13) = 0.00, p = 0.971) or an interaction (F(1, 13) = 0.73, p = 0.408) (see Figure 4A). Tukey HSD post-hoc multiple comparisons indicated that only the real tDCS group improved significantly on the MBS (real: t(13) = 3.886, p = 0.009; sham: t(13) = 2.465, p = 0.113).
Mean pre- and postscores on A. the Maslach Burnout Scale (MBS), B. Beck’s Depression Inventory (BDI), and C. McGill Quality of Life (QoL) questionnaire for the sham (dotted, triangles) and real (dashed, circles) group with 95% confidence intervals. Continuous lines indicate main effects, dashed and dotted lines indicate a significant difference between the pre- and postscores of the separate group (real: dashed; sham: dotted) as found by the post-hoc analyses. NS = non-significant; * = p≤0.05; ** = p≤0.01.
For the BDI, only an effect of Time was found ((F(1, 13) = 7.93, p = 0.015) (see Figure 4B). Post-hoc analyses revealed that only the sham group improved significantly after the intervention (t(13) = 3.58, p = 0.016) and the real group demonstrated a tendency towards improvement (t(13) = 2.82, p = 0.062).
The linear mixed model revealed no significant effects or interaction for the McGill Quality of Life (QoL) questionnaire. However, post-hoc analysis did reveal a significant improvement for the real group (t(13) = -3.21, p = 0.031) (see Figure 4C).
No significant differences were found at baseline for these three measures (MBS: t(13) = 0.04, p = 1.000; BDI: t(13) = -0.73, p = 0.883; QoL: t(13) = 0.00, p = 1.000). All means, SDs, and p-values of the post-hoc analyses are listed in Table 3. The results of the linear mixed model can be found in Table 7.
General | tDCS | pre | p (real vs sham) | post | p (pre vs post) |
---|---|---|---|---|---|
MBS | real | 4.49 ± 0.58 | 1.000 | 3.35 ± 0.93 | 0.009** |
sham | 4.47 ± 0.70 | 3.70 ± 1.11 | 0.113 | ||
BDI | real | 24.88 ± 6.83 | 0.883 | 14.88 ± 10.72 | 0.062 |
sham | 28.29 ± 9.46 | 14.71 ± 8.60 | 0.016* | ||
QoL | real | 5.00 ± 1.60 | 1.000 | 7.13 ± 1.13 | 0.031* |
sham | 5.00 ± 2.38 | 6.14 ± 1.57 | 0.406 |
Means, standard deviations, and p-values of the post-hoc analyses are shown in Table 4. The linear mixed model revealed a significant interaction between Time and tDCS for the RBANS Attention Index (F(1,13) = 14.80, p = 0.048), where the real group improved significantly more than the sham group (real: t(13) = -3.85, p = 0.010; sham: t(13) = -0.61, p = 0.929) (see Figure 5A). No significant difference was detected in the baseline scores (t(13) = 0.36, p = 0.984).
Attention | tDCS | pre | p (real vs sham) | post | p (pre vs post) |
---|---|---|---|---|---|
RBANS Attention | real | 106.25 ± 15.28 | 0.984 | 123.25 ± 10.15 | 0.010** |
sham | 103.29 ± 16.10 | 106.14 ± 21.57 | 0.929 | ||
D2 s# | real | 80.75 ± 13.58 | 0.061 | 72.00 ± 23.27 | 0.660 |
sham | 54.43 ± 17.41 | 84.14 ± 16.09 | 0.013* |
Continuous lines with X indicate interaction effects, dashed and dotted lines indicate a significant difference between the pre- and postscores of the separate group (real: dashed; sham: dotted) as found by the post-hoc analyses. X = interaction effect; NS = non-significant; * = p≤0.05; ** = p≤0.01.
A significant interaction effect was also found for vigilance (F(1,13) = 12.15, p = 0.004), as measured by the s-score of the D2 test, with the sham group improving significantly. However, the assumptions of homoscedasticity and normality of the residuals of the model were doubtful, but did not improve using the Box-Cox transformation, which makes it difficult to interpret the results. In addition, the real and sham tDCS group tended to differ significantly at baseline (t(13) = 2.82, p = 0.061), with the sham group performing worse than the real tDCS group.
All means, standard deviations, and p-values of the post-hoc analyses are shown in Table 5.
Central executive | tDCS | pre | p (real vs sham) | post | p (pre vs post) |
---|---|---|---|---|---|
Inhibition & Shifting | |||||
Stroop Card III | real | 47.94 ± 33.90 | 0.327 | 64.63 ± 26.67 | 0.118 |
sham | 73.57 ± 25.45 | 77.43 ± 23.44 | 0.951 | ||
WCST | real | 2.25 ± 1.49 | 0.323 | 3.00 ± 1.20 | 0.042* |
sham | 3.29 ± 0.76 | 3.43 ± 0.79 | 0.948 | ||
TMT B# | real | 72.25 ± 30.84 | 0.947 | 80.63 ± 15.26 | 0.546 |
sham | 65.86 ± 25.12 | 76.14 ± 15.73 | 0.433 | ||
Updating & Control | |||||
TMT A | real | 52.88 ± 39.08 | 0.925 | 70.88 ± 22.77 | 0.066 |
sham | 61.86 ± 24.95 | 75.71 ± 20.61 | 0.238 | ||
Stroop Card I | real | 41.00 ± 35.29 | 0.689 | 67.75 ± 26.89 | 0.105 |
sham | 59.43 ± 29.71 | 62.14 ± 35.62 | 0.995 | ||
Stroop Card II# | real | 49.38 ± 37.65 | 0.585 | 55.13 ± 30.77 | 0.935 |
sham | 71.29 ± 31.42 | 69.86 ± 30.43 | 0.999 | ||
D2 Gz | real | 39.81 ± 31.52 | 0.771 | 63.64 ± 23.82 | 0.074 |
sham | 54.00 ± 30.36 | 63.57 ± 27.42 | 0.741 | ||
D2 Gz – F | real | 45.26 ± 33.96 | 0.596 | 72.33 ± 20.48 | 0.059 |
sham | 62.86 ± 27.30 | 71.86 ± 22.87 | 0.812 | ||
D2 F% | real | 83.13 ± 13.70 | 0.952 | 75.00 ± 24.20 | 0.699 |
sham | 87.29 ± 9.25 | 93.29 ± 5.65 | 0.872 |
The linear mixed model demonstrated a significant effect of Time for inhibition and shifting on the Stroop Color-Word test (card III) (F(1,13) = 5.96, p = 0.030) (Figure 6A) and the WCST (F(1,13) = 9.20, p = 0.010) (Figure 6B). Post-hoc comparisons only revealed a significant improvement in the real tDCS group on the WCST (real: t(13) = -3.03, p = 0.042; sham: t(13) = -0.54, p = 0.948). For the Stroop (card III) no significant improvements were found for either group post-hoc (real: t(13) = -2.44, p = 0.118; sham: t(13) = -0.53, p = 0.951). For the TMT B, the assumption of homoscedasticity of the residuals was violated and did not improve using the Box-Cox transformation, making interpretation of the model difficult. No significant effects or interaction were found with the non-transformed data.
Mean pre- and postscores for inhibition and shifting on A. the Stroop Color-Word test Card III, and B. the Wisconsin Card Sorting Test (WCST), for the sham (dotted, triangles) and real (dashed, circles) group with 95% confidence intervals. Continuous lines indicate main effects, dashed and dotted lines indicate a significant difference between the pre- and postscores of the separate group (real: dashed; sham: dotted) as found by the post-hoc analyses. NS = non-significant; * = p≤0.05; ** = p≤0.01.
No significant differences were found in the baseline measures (Stroop card III: t(13) = -1.78, p = 0.327; WCST: t(13) = -1.79, p = 0.323; TMT B: t(13) = 0.54, p = 0.947).
For updating and control, a significant effect of Time was found for the TMT A (F(1,13) = 7.69, p = 0.016) (Figure 7A), the Stroop Color-Word test (card I) (F(1,13) = 6.30, p = 0.026) (Figure 7B) and the D2 (Gz: F(1,13) = 7.38, p = 0.018; and Gz – F: F(1,13) = 8.10, p = 0.014) (Figure 7C and 7D). The post-hoc tests only revealed trends towards improvement in the real group for the TMT A (real: t(13) = -2.77, p = 0.067; sham: t(13) = -2.00, p = 0.238), the Stroop Color-Word test (card I) (real: t(13) = -2.51, p = 0.105; sham: t(13) = -0.24, p = 0.995), D2 Gz (real: t(13) = -2.72, p = 0.074; sham: t(13) = -1.02, p = 0.741), and D2 Gz – F (real: t(13) = -2.85, p = 0.059; sham: t(13) = -0.89, p = 0.812). No significant effects or interaction was found for the Stroop Color-Word test (card II) or F% of the D2 test. However, the assumption of homoscedasticity of the residuals was violated in the Stroop Color-Word test (card II), which might have resulted in unreliable p-values.
Mean pre- and postscores for updating and control on the A. Trail Making Test (TMT) part A, B. Stroop-Color Word test Card I, C. D2 Gz score, and D. D2 Gz – F score for the sham (dotted, triangles) and real (dashed, circles) group with 95% confidence intervals. Continuous lines indicate main effects, dashed and dotted lines indicate a significant difference between the pre- and postscores of the separate group (real: dashed; sham: dotted) as found by the post-hoc analyses. NS = non-significant; * = p≤0.05; ** = p≤0.01.
No significant differences were found in the baseline measures (TMT A: t(13) = 0.62, p = 0.925; Stroop card I: t(13) = -1.11, p = 0.689; Stroop card II: ; D2 Gz: t(13) = -0.97, p = 0.771; D2 Gz – F: t(13) = -1.27, p = 0.596; D2 F%: t(13) = -0.52, p = 0.952).
All mean scores, standard deviations, and p-values of the post-hoc analyses are listed in Table 6.
Working memory | tDCS | pre (Standard Scores) | p (real vs sham) | post (Standard Scores) | p (pre vs post) |
---|---|---|---|---|---|
Phonological loop | |||||
RBANS Language | real | 110.00 ± 6.82 | 0.352 | 116.00 ± 6.59 | 0.180 |
sham | 102.29 ± 9.43 | 104.57 ± 11.43 | 0.863 | ||
BNT | real | 0.34 ± 0.55 | 0.995 | 1.30 ± 0.67 | 0.015* |
sham | 0.27 ± 0.79 | 1.08 ± 0.30 | 0.060 | ||
Semantic fluency | real | 82.50 ± 7.45 | 0.921 | 89.50 ± 11.01 | 0.416 |
sham | 77.86 ± 18.21 | 88.43 ± 18.58 | 0.162 | ||
Visuospatial sketchpad | |||||
Raven# | real | 123.00 ± 4.21 | 0.999 | 124.50 ± 3.96 | 0.915 |
sham | 123.43 ± 6.48 | 125.00 ± 6.14 | 0.920 | ||
RBANS Visuospatial Memory | real | 115.88 ± 8.31 | 0.355 | 121.25 ± 6.11 | 0.452 |
sham | 107.43 ± 12.78 | 110.86 ± 10.22 | 0.800 | ||
Encoding | |||||
RBANS Immediate Memory | real | 109.00 ± 8.98 | 0.986 | 124.25 ± 14.34 | 0.020* |
sham | 106.29 ± 17.31 | 113.00 ± 20.15 | 0.508 | ||
Retrieval | |||||
RBANS Recent Memory | real | 103.88 ± 11.19 | 0.943 | 113.75 ± 9.51 | 0.051 |
sham | 106.71 ± 8.52 | 116.00 ± 9.87 | 0.094 |
For the phonological loop, the linear mixed model revealed a main effect of Time for the BNT (F(1,13) = 12.92, p = 0.003) (Figure 8A) and the Language index of the RBANS (F(1,13) = 4.76, p = 0.048) (Figure 8B). Tukey HSD post-hoc comparisons revealed that only the real tDCS group improved significantly on the BNT (t(13) = -3.60, p = 0.015), a trend towards improvement was observed in the sham group (t(13) = -2.83, p = 0.060). No significant improvements were found for the groups separately for the RBANS Language Index (real: t(13) = -2.18, p = 0.180; sham: t(13) = 0.78, p = 0.863). No significant effects or interactions were seen for semantic fluency. Baseline scores did not differ significantly for these measures (BNT: t(13) = 0.23, p = 0.995; RBANS Language Index: t(13) = 1.72, p = 0.352; Semantic fluency: t(13) = 0.63, p = 0.921).
Mean pre- and postscores for the phonological loop on the A. Boston Naming Test (BNT), and B. RBANS Language index for the sham (dotted, triangles) and real (dashed, circles) group with 95% confidence intervals. Continuous lines indicate main effects, dashed and dotted lines indicate a significant difference between the pre- and postscores of the separate group (real: dashed; sham: dotted) as found by the post-hoc analyses. NS = non-significant; * = p≤0.05; ** = p≤0.01.
No significant effects or interaction were observed for the visuospatial sketchpad (RBANS Visuospatial index and Raven). However, the assumptions for the linear mixed model of the Raven were violated, which could have affected the p-values. The Box-Cox transformation did not improve the data. Baseline scores did not differ significantly (RBANS Visuospatial Index: t(13) = 1.72, p = 0.452; Raven: t(13) = -0.16, p = 0.999).
A main effect of Time was observed for encoding, evaluated by the Immediate Memory index of the RBANS (F(1,13) = 11.93, p = 0.004) (Figure 9A). Post hoc analysis showed that this was mainly driven by a significant improvement of the real tDCS group (real: t(13) = -3.45, p = 0.020; sham: t(13) = -1.42, p = 0.508). Retrieval (RBANS Recent Memory index) also showed a significant effect of Time (F(1,13) = 8.58, p = 0.012) (Figure 9B). For retrieval, both groups trended towards significance (real: t(13) = -2.93, p = 0.051; sham: t(13) = -2.58, p = 0.094). No differences in baseline scores were observed for Immediate or Recent Memory (RBANS Immediate Memory Index: t(13) = 0.34, p = 0.986; RBANS Recent Memory Index: t(13) = -0.56, p = 0.943).
Mean pre- and postscores for encoding on the A. Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) Immediate Memory, and retrieval on the B. RBANS Recent Memory for the sham (dotted, triangles) and real (dashed, circles) group with 95% confidence intervals. Continuous lines indicate main effects, dashed and dotted lines indicate a significant difference between the pre- and postscores of the separate group (real: dashed; sham: dotted) as found by the post-hoc analyses. NS = non-significant; * = p≤0.05; ** = p≤0.01.
Test | Effect | F(1, 13) | p |
---|---|---|---|
GENERAL | |||
MBS | Time tDCS Time x tDCS | 15.10 0.00 0.73 | 0.002** 0.971 0.408 |
BDI | Time tDCS Time x tDCS | 7.93 0.53 0.47 | 0.015* 0.478 0.504 |
QoL | Time tDCS Time x tDCS | 2.60 0.00 1.02 | 0.131 1.000 0.330 |
ATTENTION | |||
RBANS Attention | Time tDCS Time x tDCS | 14.80 0.13 4.78 | 0.002** 0.727 0.048* |
D2 s# | Time tDCS Time x tDCS | 1.35 7.96 12.15 | 0.267 0.014* 0.004* |
CENTRAL EXECUTIVE Inhibition & Shifting | |||
Stroop Card III | Time tDCS Time x tDCS | 5.96 3.16 1.64 | 0.030* 0.099 0.222 |
WCST | Time tDCS Time x tDCS | 9.20 3.19 2.81 | 0.010** 0.097 0.117 |
TMT B# | Time tDCS Time x tDCS | 1.84 0.29 0.04 | 0.198 0.598 0.836 |
Updating & Control | |||
TMT A | Time tDCS Time x tDCS | 7.69 0.38 0.19 | 0.016* 0.548 0.670 |
Stroop Card I | Time tDCS Time x tDCS | 6.30 1.24 2.37 | 0.026* 0.287 0.147 |
Stroop Card II# | Time tDCS Time x tDCS | 0.34 1.66 0.25 | 0.568 0.220 0.626 |
D2 Gz | Time tDCS Time x tDCS | 7.38 0.93 1.23 | 0.018* 0.352 0.287 |
D2 Gz – F | Time tDCS Time x tDCS | 8.10 1.61 1.68 | 0.014* 0.226 0.217 |
D2 F% | Time tDCS Time x tDCS | 1.20 0.28 1.69 | 0.294 0.609 0.216 |
WORKING MEMORY Phonological loop | |||
RBANS Language | Time tDCS Time x tDCS | 4.76 2.97 0.85 | 0.048* 0.109 0.373 |
BNT | Time tDCS Time x tDCS | 12.92 0.05 0.15 | 0.003** 0.819 0.705 |
Semantic fluency | Time tDCS Time x tDCS | 2.53 0.40 0.31 | 0.136 0.541 0.589 |
Visuospatial sketchpad | |||
Raven# | Time tDCS Time x tDCS | 0.42 0.03 0.00 | 0.530 0.877 0.984 |
RBANS Visuospatial Memory | Time tDCS Time x tDCS | 2.32 2.95 0.14 | 0.151 0.110 0.712 |
ENCODING | |||
RBANS Immediate Memory | Time tDCS Time x tDCS | 11.93 0.11 1.75 | 0.004** 0.740 0.209 |
RETRIEVAL | |||
RBANS Recent Memory | Time tDCS Time x tDCS | 8.58 0.31 0.01 | 0.012* 0.588 0.907 |
*: p≤0.05
**: p≤0.01
Legend: tDCS = transcranial Direct Current Stimulation; MBS = Maslach Burnout Scale; BDI = Beck’s Depression Inventory; RBANS = Repeatable Battery for the Assessment of Neuropsychological Status; TMT = Trail Making Test; WCST = Wisconsin Card Sorting Test; BNT = Boston Naming Test; # = assumptions of the linear mixed model are violated.
This randomized blinded sham-controlled study investigated the impact of daily atDCS sessions (2mA, 20min) over the left DLPFC (AF3) with the reference over the contralateral orbit (F8) on attention and the central executive, as well as other components of the working memory in patients with burnout. This electrode montage has been shown to be effective in patients with depression, showing not only an antidepressant effect but also a positive effect on mood, attention skills, and working memory (Loo et al., 2012). We included 15 patients (7 sham, 8 tDCS) in a 3-week protocol and investigated their cognitive and attention skills, as well as their burnout severity, depression, and overall quality of life before and after treatment. Both groups improved on all these measures, which can be expected due to the behavioral therapy both groups received, but the improvement of burnout and overall quality of life was only significant after real tDCS. Surprisingly, however, only the sham group significantly improved on the depression scale. This might be due to the fact that depression scores were moderate, while in the study of Loo et al. only patients with a DSM IV major depression episode were included (Loo et al., 2012). Moreover, in the study of Loo et al. depression was rated by an experienced psychiatrist/psychologist using the Montgomery Asberg Depression Rating Scale (MADRS; Montgomery & Asberg, 1979), while in our study a self-assessment scale (BDI) was used (Loo et al., 2012).
For the main variable of interest (Attention index of the RBANS), a significant interaction between tDCS and Time was found, showing that real anodal tDCS over the left DLPFC can have an added value to conventional therapy in the rehabilitation of attention in burnout patients.
It is known that burnout primarily impairs functions of the central executive, whereas brain areas that regulate other components of the working memory are affected to a lesser degree. The central executive -mainly located in the prefrontal brain regions- could be the component that is most vulnerable to chronic stress because its higher order attention control functions are more demanding and complex than those performed by the other subcomponents (Deligkaris et al., 2014). Several studies investigating the impact of burnout on cognitive functions have confirmed that the most pronounced differences between patients and controls were seen on tests that are highly dependent upon the executive functions, e.g. prospective memory, processing speed, complex working memory, sustained attention, and letter fluency (Eskildsen et al., 2015; Jonsdottir et al., 2013; Öhman et al., 2007; Orena et al., 2013)(35–38)(Eskildsen et al., 2015; Jonsdottir et al., 2013; Öhman et al., 2007; Orena et al., 2013). This study showed that three weeks of therapy, combined with real or sham stimulation, significantly improved several components of the central executive. However, analyses revealed that improvement was driven by a significant improvement after real tDCS for inhibition and shifting (WCST), and was also primarily seen after real tDCS for updating and control (TMT A, D2 Gz, D2 Gz – F). These results are in line with the study of Miler et al. who found that atDCS over the left DLPFC significantly improves the executive control of attention (Miler et al., 2018). As in the study of Miler et al., no effect was seen on the percentage of mistakes, but the processing speed did improve more on the D2 test of attention after real tDCS than after sham tDCS (Miler et al., 2018). However, the improvement on inhibition and shifting after tDCS was somewhat unexpected, since this is primarily associated with the right DLPFC and the right inferior frontal gyrus (Lie et al., 2006; Hampshire et al., 2010). Since this effect was only observed for the WCST, this might be related to this specific task. Indeed, studies have shown that, although the right DLPFC seems to be the most prominent in handling complex/manipulative working memory operations in the WCST (Lie et al., 2006), the left DLPFC is also involved during this task (Lie et al., 2006; Nagahama et al., 2005).
atDCS also seemed to have a positive impact on other components of the working memory. The phonological loop might also be positively influenced by real tDCS as shown by a significant improvement of the real tDCS group on the BNT, although the sham group also trended towards a significant improvement. No effect was seen on the visuospatial sketchpad, which might not be surprising because this is believed to be situated primarily in the right prefrontal cortex (Suchan, 2008), but encoding clearly improved more after real atDCS than after sham tDCS (RBANS Immediate Memory Index). Transcranial magnetic stimulation (TMS) studies have shown a prominent role for the left DLPFC during encoding, observing shorter reaction times using a paired-pulse paradigm over this area (Gagnon et al., 2011). Though de Lara et al. (2017) did not find any effect of anodal tDCS over the left DLPFC on encoding, this might be due to the lesser intensity (1mA vs 2mA) they used in their study.
These data provide preliminary evidence for the value of tDCS over the left DLPFC in rehabilitating attention deficits, and possibly also central executive and encoding deficits, in burnout patients.
Our study has several important limitations. First, our group of patients was relatively small. This is an important limitation given the positive trends of the effect of real tDCS on several outcome measures. Studies with more power will have to show whether these trends failed to reach significance due to a lack of power. In addition, some variables of interest (D2 s-score, TMT B, Stroop Card II, Raven) could not be interpreted correctly with the linear mixed model analysis because of a violation of assumptions. More data points could help to resolve this issue. Setting up multi-site cooperations to recruit participants and maintaining close relationships with primary care providers making them aware of the safety of tDCS when applied in the correct manner, could also help to convince patients to participate in tDCS studies. Larger groups to validate the efficacy of tDCS are crucial to investigate the clinical usability of this therapeutic aid.
Second, patients were randomized over both groups, which led to an overrepresentation of men in the sham group. At the moment, it is not clear whether gender can have a significant impact on the effect of tDCS (Antal et al., 2017), or whether there are gender-related differences in the symptoms of burnout (Purvanova & Muros, 2010), but this imbalance of gender between both groups might have affected the results.
Third, our group of patients was very heterogeneous. For example, the moment of participation in the study was variable during the burnout process. Some participants were still at work, others were not yet able to start working, others were already re-integrated in their jobs. Due to the sample size, it was not possible to investigate the effects of different factors, such as living circumstances, age, gender, education, etc. on the progress of burnout. In addition, three of the patients were taking antidepressant medication during the study, of whom one received real stimulation. It has been shown that this type of medication (selective serotonin reuptake inhibitors or SSRIs) might enhance the LTP-like plasticity induced by anodal tDCS (Kuo et al., 2016). Future studies should focus on these parameters to elucidate the influence of these factors on burnout recovery and on tDCS outcome. In addition, it is recommended to test for the efficiency of blinding the type of stimulation by asking the participants afterwards whether they think they were actively stimulated or not. Gathering information about the amount of discomfort could also be of importance for future studies using tDCS.
Fourth, the placement of the electrodes might not have been optimal to target attention deficits. Our study was based on the outcome of Loo et al. (2012) who aimed to investigate the anti-depressant effect in patients with depression, but found an improvement of attention and working memory instead (Loo et al., 2012). By copying this electrode placement, we hoped to replicate these results in patients with burnout. However, by placing the cathode on F8, we might have unwantedly inhibited the right inferior frontal gyrus, which has been linked to inhibition and attentional control (Hampshire et al., 2010). Although cathodal tDCS over the right inferior frontal gyrus did not appear to have a significant effect on response stopping or reaction times in a stop-signal task (Stramaccia et al., 2015), another choice for the cathodal reference electrode might be warranted. In addition, AF3 targets primarily the more frontal site of the left DLPFC, while a more common placement to target DLPFC in attention studies is F3 (Coffman et al., 2014).
Lastly, research has shown that the effect of tDCS on working memory might be dependent on, amongst others, the initial dopaminergic level that can impact the excitation/inhibition balance (i.e. homeostasis between relative contributions of excitatory and inhibitory synaptic inputs) (Polizzotti et al., 2020). More insight into the exact working mechanisms underlying the cognitive and attention deficits in burnout patients might be beneficial for future research.
Despite these shortcomings, these data provide preliminary evidence for the value of atDCS over the left DLPFC in rehabilitating attention deficits in burnout. tDCS might prove to be a useful, affordable, and easy-to-use addition to conventional therapy to speed up reintegration of burnout patients.
Written informed consent for publication of the patients’ details was obtained from the patients.
Harvard Dataverse: Transcranial direct current stimulation and attention skills in burnout patients: a randomized blinded sham-controlled pilot study. https://doi.org/10.7910/DVN/4VG2XS (van Dun, 2020)
This project contains the following underlying data:
Harvard Dataverse: Transcranial direct current stimulation and attention skills in burnout patients: a randomized blinded sham-controlled pilot study. https://doi.org/10.7910/DVN/4VG2XS (van Dun, 2020)
This project contains the following extended data:
CONSORT checklist and flow chart for “Transcranial direct current stimulation and attention skills in burnout patients: a randomized blinded sham-controlled pilot study”. https://doi.org/10.7910/DVN/4VG2XS (van Dun, 2020)
Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).
We also want to dedicate this work to Prof. dr. Peter Mariën, who has left us prematurely and was one of the driving forces behind this research. He is also responsible for the data collection of the verbal (semantic) fluency task which was used here.
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Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
References
1. Wang HX, Wang L, Zhang WR, Xue Q, et al.: Effect of Transcranial Alternating Current Stimulation for the Treatment of Chronic Insomnia: A Randomized, Double-Blind, Parallel-Group, Placebo-Controlled Clinical Trial.Psychother Psychosom. 2020; 89 (1): 38-47 PubMed Abstract | Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: psychiatry, neuroscience, neuropsychoneurology. psychosomatics, neuromodulation, transcranial alterative current stimulation in different patients affected with brain disorders and psychitrical disorders.
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: non-invasive neuromodulation (TMS/tDCS), fMRI
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
Partly
Are the conclusions drawn adequately supported by the results?
Partly
References
1. Sack AT, Cohen Kadosh R, Schuhmann T, Moerel M, et al.: Optimizing functional accuracy of TMS in cognitive studies: a comparison of methods.J Cogn Neurosci. 2009; 21 (2): 207-21 PubMed Abstract | Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: non-invasive neuromodulation (TMS/tDCS), fMRI
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