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Occupational Health Science

, Volume 2, Issue 4, pp 385–407 | Cite as

Neuropattern, a Translational Tool to Reduce Stress at Work – a Pilot Study

  • C. Contreras
  • Juliane Hellhammer
  • F. Gerhards
  • D. H. Hellhammer
Original Research Article
  • 219 Downloads

Abstract

Changing working conditions demand adaptation, resulting in higher stress levels in employees. In consequence, decreased productivity, increasing rates of sick leave, and cases of early retirement result in higher direct, indirect, and intangible costs. The aim of the study was to test the usefulness of a novel translational tool, Neuropattern, for early detection, prevention, and personalized treatment of stress-related disorders. The trial was designed as a pilot study with a wait list control group. In this study, 70 employees of the Forestry Department Rhineland-Palatinate, Germany were block-randomized and either underwent Neuropattern immediately, or after a waiting period of three months. After the diagnostic assessment, they received an explanatory disease model and individualized online counseling while their physicians were provided with diagnostic results and treatment recommendations. In order to assess possible beneficial effects of Neuropattern, questionnaires regarding health (SF-12), stress perception (PSS), emotional exhaustion (MBI), work stress (ERI) and work ability (WAI) as well as questions on health behavior were included at several time points. The application of Neuropattern resulted in significantly higher increase in measures of mental health and sporting activity and a significantly stronger decrease in perceived stress, emotional exhaustion and overcommitment, as compared to the control group. No such differences were found with regard to subjects’ physical health, current work ability, reward, effort-reward ratio and practice of relaxation methods. In addition, we unexpectedly found that subjects of the experimental group became significantly more pessimistic regarding their future work ability and showed higher rates of sick leave than control subjects did. These changes remained consistent during 3 and 6 months of follow-up. The present study encouraged the application of Neuropattern to early intervention in non-clinical populations. However, further research is required to determine the best operating conditions.

Keywords

Work stress Burnout Prevention Conceptual Endophenotypes Personalized Medicine Neuropattern 

Background and Rationale

Theoretical Background

The link between stress and a variety of physical and mental conditions seems to be soundly established (McEwen 1998; Hellhammer and Hellhammer 2008; de Kloet et al. 2005; Cohen et al. 2007). Reports on rising rates of absenteeism due to stress-related diseases (Badura et al. 2010) as well as research in the field of occupational psychology continue to emphasize the harmful impact of stress at work on public health (e.g. Tennant 2001; Lundberg 2005; Melchior et al. 2007). With respect to work-related stress, individual factors (e.g. a high aspiration level) seem to be of equally high influence as work-related structural factors, such as high demands combined with time pressure, low resources, low means of control, lack of positive feedback and social conflicts at work (e.g. Hackman and Lawler 1971). Preventive efforts usually focus on strengthening individual coping, imparting strategies for stress or time management, and conflict solution (Bellingrath and Kudielka 2008).

Burnout can be considered a risk state for the development of mental and physical stress-related disorders (DGPPN 2012). Ahola and colleagues found approximately half of the study population with severe burnout symptoms to fulfill the DSM-IV criteria for a depressive disorder (Ahola et al. 2005). Twelve studies particularly linked the dimension ‘Emotional Exhaustion’ to depression, both sharing about 25% of variance (Schaufeli and Enzmann 1998). Early intervention might help prevent burnout symptoms to become severe leading to a higher risk of developing a mental disorder such as depression.

Neuropattern is a newly developed tool aiming at translating psychobiological knowledge of stress pathology and scientific findings into clinical practice. Following a strategy advocated by the US National Research Council (2011) and the tradition of endophenotype-based research, we introduced “conceptual endophenotypes “(see Hellhammer et al. 2018). Neuropatterns are considered conceptual endophenotypes (CE), which serve to identify subgroups with specified characteristic psychological, social, biological (genetic, epigenetic), and symptomatic criteria. CEs are developed and validated in a continuous iterative crosstalk of basic research and application or praxis. Neuropattern is such a conceptual approach. Numerous experimental and empirical studies were performed to substantiate the Neuropattern concept, resulting in the construction of 13 CEs. These CEs assess theoretical states of Corticotropin Releasing Factor (CRF), Noradrenaline (NA), or Serotonin hyper- or hypoactivity. CEs are only indirectly assessed by selected psychological, biological and symptom measures.

Neuropattern comprehends 13 CEs of the stress-response network in the brain, addressing elements of the hypothalamic-pituitary adrenal (HPA) axis, the noradrenergic and serotonergic system, and the autonomic nervous system (for details see Hellhammer and Hellhammer 2008). For example, a hyperactivity of CRF neurons in the hypothalamus is expected to be associated with elevated basal salivary cortisol after awakening, characteristic psychological measures, such as rumination, worrying, low self-esteem and typical mental and physical disorders, such as sleep and metabolic disorders, general anxiety disorder, depression, etc. Evidence for the psychopathological relevance of a CE is fulfilled, once a patient or subject qualifies for a sufficient amount of a priori defined criteria of each of these three categories. To collect these data, a physician applies a systematic interview on the medical history of the patient or subject and then prescribes a low-dose dexamethasone test. At home, the patient or subject fills in questionnaires, collects saliva samples and uses a heart rate variability tool (see section below). Each of these CEs refers to specific patterns of concomitant psychological, biological, and symptom measures, which characterize a potential dysregulation of the stress-response network. Individual dysregulations are then illustrated in a disease model from which personalized pharmacological and psychological treatment and self-help recommendations can be derived. Beyond signs and symptoms, these recommendations provide the treating physician with additional psychobiological information, allowing him to optimize individualized treatments. The whole procedure is described in detail in Hellhammer et al. (2012). In randomized clinical trials, Neuropattern has shown to improve treatment of stress-related disorders (Bruhn 2014; Hero et al. 2012; Naeher 2015).

Aims of the Research Project

The present pilot study was designed to scrutinize whether the application of Neuropattern has beneficial effects also in a vocational setting. It was analyzed whether the application of Neuropattern a) improves health status and work ability and b) leads to a reduction of perceived stress, work-related stress and emotional exhaustion, days of sick leave and number of visits to the doctor.

Materials and Method

Sample Description

The study was a randomized controlled trial reviewed and approved by the Ethics Committee of the Medical Chamber Rhineland-Palatinate (Ethikkommission der Landesärztekammer Rheinland-Pfalz), registered with ClinicalTrials.gov and conducted by [name deleted to maintain the integrity of the review process] in accordance with the Declaration of Helsinki. The trial was initiated and funded by ‘Landesforsten Rheinland-Pfalz’ (Forestry Department of Rhineland-Palatinate, Germany) aiming at detecting and preventing/ minimizing stress-related health impairments in their employees. Employees of Landesforsten Rheinland-Pfalz were informed about the intended study through an internal e-mail distributer, an in-house magazine, as well as by information of the in-house social worker. In case an employee decided to take part in the study, they had to order a voucher for free attendance. Those who had ordered a voucher were screened for inclusion and exclusion criteria by the social worker of Landesforsten Rheinland-Pfalz.

For study inclusion, subjects had to be aged 18 to 65, proficient in the German language and provide signed informed consent. Subjects were excluded from study participation, if they were under treatment of benzodiazepines or glucocorticoids, suffered from arrhythmia absoluta, or any acute mental or physical disorder, were in current psychotherapeutic treatment or currently participated in any other trial. Since we use the low-dose dexamethasone suppression test as an indirect measure of chronically elevated cortisol levels, the ethics committee did not allow us to apply this glucocorticoid to pregnant or breastfeeding women. Women were therefore excluded if pregnancy could not be ruled out securely or if they were breastfeeding. Additionally, any medical or mental condition impairing subjects’ ability to speak for themselves or provide informed consent led to exclusion from the study. Subjects could not participate if there were medical or personal reasons against the intake of 0.25 mg of dexamethasone. Subjects could withdraw from study participation at any time. Those subjects who had ordered a voucher and fulfilled all inclusion criteria received an informed consent form to be signed and sent back to [name deleted to maintain the integrity of the review process] study site.

Study Procedure

Enrollment and randomization of subjects took part upon arrival of signed informed consent at [name deleted to maintain the integrity of the review process] study site. Subjects were block-randomized, meaning blocks of five subjects within the same functional group were consecutively assigned to either the experimental group or the wait list control group. The distribution of vouchers followed categorization of the 2400 employees into functional groups according to their percentage of the collective: Executive Level (15 vouchers), Management Level (30 vouchers), Operational Planning Level (30 vouchers), Processing Level (10 vouchers) and Operational Execution Level (15 vouchers). After randomization, all participants were informed about the further study procedure according to group affiliation and received a package of questionnaires that had to be filled in for evaluation purposes and sent back to [name deleted to maintain the integrity of the review process] study site. The evaluation package comprised several questionnaires listed and described below.

The SF-12 Health Survey (Bullinger and Kirchberger 1998) is a short form of the SF-36 assessing health-related quality of life. The 12 items are assigned to the two major dimensions ‘mental health’ and ‘physical health’ (Bullinger and Kirchberger 1998; Ware et al. 1998, 2002; Nuebling et al. 2006; Wagner et al. 2007, Bullinger 1995), which have shown good (mental health: Cronbach’s ⍺ = 0.91) or satisfactory (physical health: Cronbach’s ⍺ = 0.84) reliability. The items vary in their predetermined response options (e.g. “In general, would you say your health is” rated as 1 = “excellent”, 2 = “very good”, 3 = “good”, 4 = “fair”, or 5 = “poor” or “How much of the time during the past four weeks have you felt calm and peaceful?” answered 1 = “all of the time”, 2 = “most of the time”, 3 = “a good bit of the time” 4 = “some of the time”, 5 = “a little of the time” and 6 = “none of the time”). In the present study, the inquired time frame covered the past three months.

The Perceived Stress Scale (PSS, Cohen et al. 1983) assesses “the degree to which situations in one’s life are appraised as stressful” (p. 387; Cohen et al. 1983) and is one of the more popular tools for measuring psychological stress (Lee 2012). The original 14-item scale was reduced to a 10-item version showing slightly improved reliability (Cronbach’s ⍺ = .78 vs. Cronbach’s ⍺ = .75) and equivalent validity, even higher for the German Version (Cronbach’s ⍺ = .84) (Klein et al. 2016). Items (e.g. “In the last month, how often have you felt nervous and “stressed”?“) are rated on a 5-point Likert scale (0 = “never“, 1 = “almost never“, 2 = “sometimes“, 3 = “fairly often“, 4 = “very often”). In the present study, the inquired time frame covered the past three months.

The Emotional Exhaustion subscale of the Maslach Burnout Inventory (MBI, Maslach & Jackson 1981, translation by [name deleted to maintain the integrity of the review process]) was used to measure work-related emotional exhaustion. The MBI is by far the most popular measure of burnout (Schaufeli et al. 2001). The subscale Emotional Exhaustion shows high reliability (Cronbach’s ⍺ = .90, see Maslach et al. 2006) and conceptually fits the Neuropattern concept. Emotional Exhaustion relates to feelings of being emotionally overextended and exhausted by one’s work. Personal statements such as “I feel burned out from my work.” are rated on a 7-point Likert scale (0 = “never”, 1 = “a few times a year”, 2 = “once a month or less”, 3 = “a few times a month”, 4 = “once a week”, 5 = “a few times a week”, 6 = “every day”).

The Effort-Reward Imbalance questionnaire (ERI, Siegrist 1996) measures potentially harmful psychosocial strains at work through its subscales Effort, Reward and Overcommitment. The relation between efforts invested into job performance and rewards received in turn (Effort-Reward Ratio) is assessed, hypothesizing that failed reciprocity elicits strong negative emotions and sustained stress reactions that in the long run adversely affect physical and mental health. Since extrinsic demands are often moderated by the workers motivations, the scale Overcommitment takes account of this component, measuring individuals’ tendency towards an exhaustive coping style. Its short form comprises 16 items (e.g. “I have constant time pressure due to a heavy work load.”) rated on a 4-point Likert scale (1 = “strongly disagree”, 2 = “disagree”, 3 = “agree”, 4 = “strongly agree”). Satisfactory reliability in terms of Cronbach’s ⍺ (> 0.70) have been reported for all of the three scales (Siegrist et al. 2009; Rödel et al. 2004).

The Work Ability Index questionnaire (WAI; Tuomi et al. 1998) was developed in Finland for the assessment of work ability among individuals and groups of workers. The WAI comprises 7 items, and is used in clinical occupational health practice as well as for research purposes worldwide (Ilmarinen 2007) to assess work ability reliably (De Zwart et al. 2002). In a large follow-up study among employees aged 15–64 years in the metal industry and in the retail trade, the reliability coefficients (Cronbach’s ⍺) were between 0.72 and 0.80 (Tuomi et al. 2004). According to Ilmarinen and Tuomi (2004) the WAI and all its subscales reliably predict work disability, retirement and mortality. In order to assess both, current work ability in relation to the demands of the job as own prognosis of work ability two years from now, we included the two respective WAI-items (items 2 and 6) in our evaluation package.

The evaluation package additionally comprised questions concerning the number of visits to the doctor and the number of days of sick leave during the last three months. Further questions concerned the frequency of practiced relaxation exercises (such as yoga, autogenic training, qi gong, or other relaxation methods) and the frequency of sporting activity per week. Frequency was rated on a 4-point Likert scale (1 = “never”, 2 = “1 or 2 times per week”, 3 = “3 or 4 times per week”, 4 = “at least 5 times per week”). Duration was rated on a 4-point Likert scale (1 = “for 5 to 20 minutes”, 2 = “for 30 to 50 minutes”, 3 = “for 1 to 2 hours”, 4 = “for more than 2 hours”) The evaluation questionnaires had to be filled in again after 3, 6 and, if applicable, 9 months (depending on assignment to the wait list control group or the experimental group; see Fig. 1).
Fig. 1

Diagram of the study design. Flow charts are shown for the experimental and control group. Note: t1 = baseline (N=70), t2 = 3 months after t1 (N=55), t3 = 6 months after t1 (N=48), t4 = 9 months after t1 (N=17)

After randomization, subjects also received the Neuropattern test set and a document designating the subject’s treating physician. In case the family physician was not willing to participate in the study, there was a list with the contact information of experienced study physicians for subjects to choose from. Subjects were asked to return the completed study material to the study site via mail. The Neuropattern Questionnaire for patients (NPQ-P) includes psychological and symptom measures of stress, the Neuropattern stress load Questionnaire (NPQ-S) assesses psychological responses to stress during the past month and life events considered responsible for the onset of stress-related symptoms. In addition, the Neuropattern pre-postnatal stress Questionnaire (NPQ-PSQ) retrospectively measures pre-, peri-, and postnatal stressors as indicators of subjects’ early adversity. The NPQ-PSQ has been validated and covers a broad array of stress factors in prenatal life, at birth and during childhood. It is based on the hypothesis that pre- and postnatal experiences during sensitive periods are important for normal development and that early adversity might have enduring effects throughout life (see Hero 2013). The test set further included a portable ECG device for recording data on heart rate variability before sleep, overnight, and after awakening as well as 16 Salivettes® (Sarstedt, Nümbrecht) for saliva cortisol determination on three consecutive work days. On the first two days, saliva cortisol measures were collected upon awakening, 30, 45 and 60 min after awakening as well as at 3 pm and 8 pm. Feedback sensitivity of the HPA axis was assessed via the low-dose dexamethasone suppression test using 0.25 mg of orally administered dexamethasone taken by each subject on the evening of the second day of data collection at home. On the following third day of saliva collection, measures were only taken upon awakening, 30, 45 and 60 min after awakening. The assessment of the cortisol awakening response (CAR) was in line with the expert consensus developed by Stalder et al. (2016) and followed the procedure described by Hellhammer et al. (2007). Study participants were instructed to immediately return the material after completion via mail.

Subjects were asked to arrange an appointment with their designated physician who completed the Neuropattern anamnestic Questionnaire (NPQ-A) and prescribed 0.25 mg of dexamethasone, granted its intake was assessed as safe. Physicians were reimbursed for their efforts with 50 € per subject.

Upon arrival of the Neuropattern test set and the diagnostic questionnaires at the study site, cortisol samples were analyzed by the laboratory of the Department of [name deleted to maintain the integrity of the review process], the ECG data were spectral-analyzed for heart rate variability ([name deleted to maintain the integrity of the review process]), and questionnaire data were entered. All data were merged and analyzed by software generating the Neuropattern Medical Report and the Neuropattern Patient Report including a selection of corresponding modules of Neuropattern Online Counseling. Results of the software calculations were finally checked and authorized by one of the authors ([name deleted to maintain the integrity of the review process]), who was blinded regarding randomization.

Intervention

Neuropattern has been originally developed for family physicians, who are interested to detect stress pathology in their patients. The physician completes a questionnaire on the medical history, and takes measures of blood pressure, BMI and waist-to-hip-ratio. He prescribes a low dose dexamethasone test (0.25 mg), if considered safe. The patient receives a Neuropattern test set and takes it home. Here, they fill in four questionnaires, collect 16 saliva samples, and ECG data. Answering the questionnaires takes about two hours. ECG recordings are collected over the period of one night. Salivary samples for cortisol measurements are collected on consecutive work days; each collection takes about one minute. Afterwards, they send the test set back to the laboratory, where data are analyzed for cortisol (with and without dexamethasone suppression), heart rate variability, and psychological measures of stress and stress pathology. A software checks for each of the 13 patterns, whether the necessary psychological, biological and symptomatic criteria are fulfilled. If so, an automatic report is provided which describes the individual dysregulations of the stress response network, and possible suggestions for interventions (Hellhammer et al. 2012).

In this study, the data for 27 dysregulations of ergotropic, trophotropic and glandotropic patterns were automatically generated. The Neuropattern Medical Report provided information on each of these conceptual endophenotypes and their possible pathological relevance, recommendations for pharmacological and psychotherapeutic treatment, and an explanatory disease model to the physician (Hellhammer and Hellhammer 2011). Study physicians received the medical report being instructed to explain the content to participants and possibly reassess their treatment accordingly, if medically advisable and appropriate. The Neuropattern Patient Report was made available to participants online providing a simplified explanatory disease model. They additionally received a personalized user account for Neuropattern Online Counseling with an individualized package of instructions/ recommendations for self-help. Modules included content and exercises applied in cognitive behavioral therapy on developing pleasurable activities, euthymic methods, physical activation, social interaction, trauma education, relaxation and imagination, dysfunctional cognitions, anticipatory worrying, stress monitoring, sleep hygiene, organization of breaks and eating habits. For each subject, modules were compiled in accordance with PEs fulfilled as described in the Neuropattern Medical Report and the Neuropattern Patient Report.

Data Analyses

After completion of the study, data were analyzed using IBM SPSS Statistics, Version 21.0 (IBM SPSS Inc., Chicago, USA). No interim analyses were conducted. Data were checked for normality and appropriate tests were chosen according to data structure and distribution. Descriptive analyses were used to describe the sample. Scales and sum or mean scores of questionnaires were computed according to the respective manual except for the SF-12. Because not all subjects answered each SF-12 item and with respect to the fact that algorithms for replacements of missing values exist only for the (SF-36) long version (Kosinski et al. 2000) we applied a procedure proposed for cases with missing SF-12 data by Lang et al. (2004). Each item was linearly transformed to equal scale width (of 5, from 0 to 4) and the scale was reversed, so high scores indicate a pronounced impairment of health. In order to prevent distortions in the transformation, scale margins were equated instead of scale centers. Finally, unweighted means were calculated for the sum scores of mental and physical health, only when 4 of 6 items were completed (Lang and colleagues) also tested replacement of missing values through the Expectation-Maximization Algorithm method, no significant differences were found to unweighted means). According to Lang and colleagues, the described procedure leads to higher response rates but also diminishes comparability with sum scores calculated in accordance with the original scale formation.

In order to analyze treatment effects of Neuropattern, change scores (score difference t2 – t1) were calculated and compared between groups. Improvements of health, effort-reward-imbalance and work ability as well as a reduction of perceived general and work-related stress, emotional exhaustion, days of sick leave and number of doctoral visits were expected to be more pronounced in the experimental group compared to the control group. Data that were not normally distributed were analyzed using the Mann-Whitney U test for group comparison (one-tailed). Parametric testing was conducted using the t-test for independent measures (one-tailed). Effect size was measured using r calculated in line with Rosenthal (1991) and Rosenthal et al. (2000), as proposed by Field (2009), indicating r ≥ 0.1 as low, r ≥ 0.3 as medium and r ≥ 0.5 as high effect sizes (see Cohen 1988). Cases with missing data were excluded case-wise.

Additionally to the analyses of group differences we tested whether the (short-term) changes that were observed immediately after the completion of the Neuropattern program differed from mid-term changes that were observed three months later. For each subject and each dependent variable a short-term change score was calculated (experimental subjects: t2-t1; control subjects: t3-t2; see Fig. 1). Analogously mid-term change scores were calculated (experimental subjects: t3-t1; control subjects: t4-t2; see Fig. 1). Differences between short-term and mid-term change scores were analyzed by means of the Wilcoxon-test or the t-test for dependent measures (two-tailed).

Results

Sample Characteristics

Sample characteristics are shown in Table 1. Altogether, 88 subjects received vouchers, of which nine were not redeemed. Accordingly, 79 subjects entered the study. Seven subjects did not return the medical package (NPQ-A, dexamethasone prescription). One subject was excluded from study participation after not returning their Neuropattern test set due to noncompliance and one subject withdrew from study participation after receiving the Neuropattern test set due to lack of time. Altogether, 70 subjects took part in the study and filled in the questionnaires listed above at at least one of the evaluation time points. Change scores of 55 participants could be analyzed (26 Neuropattern and 29 control). The experimental and the control group were compared for initial differences in age, body mass index (BMI), waste-to-hip ratio (WHR), sex, level of education and functional group (see Table 1). Both groups were also compared with regard to differences upon study entry in the dependent variables listed below. The respective Mann-Whitney U tests or t-tests did not show any significant group differences.
Table 1

Sample Characteristics

 

Experimental Group (n = 41)

Control Group (n = 29)

p

Age: M (SD)

49.20 (6.05)

51 (6.52)

0.24

BMI: M (SD)

27.04 (3.17)

27.52 (3.59)

0.55

WHR: M (SD)

0.97 (0.08)

0.97 (0.09)

0.93

Sex: n (male: female)

36: 7

27: 2

0.47

Level of Education (n)

0.38

 Lower Secondary Education

3

1

 

 Mid-level Secondary Educatition

8

3

 

 Higher Secondary Education

29

24

 

 Other

3

1

 

Functional Group (n)

0.49

 Executive Level

7

4

 

 Management Level

12

11

 

 Operational Planning Level

13

10

 

 Processing Level

5

4

 

 Operational Execution Level

4

0

 

Note: M = mean, SD = standard deviation, n = number of participants, BMI = Body Mass Index, WHR = Waste-to-Hip Ratio. Statistical comparisons by Student’s t-tests or χ2 tests

Health and Visits to the Doctor

Sf-12

The subjects of the experimental group did not differ significantly in their change of subjectively rated physical health from control subjects (experimental group: Mdn = 0, IQR = 0.56; control group: Mdn = 0, IQR = 0.44; U26,28 = 347, z = −0.31, p = 0.38). However, we found a marginally significant difference in mental health change between groups, indicating a more favorable change in subjects who had already completed Neuropattern than in wait-list control subjects (experimental group: Mdn = −0.25, IQR = 0.47; control group: Mdn = −0.03, IQR = 0.58; U26,29 = 299.5, z = −1.31, p = 0.1, r = −0.18).

Visits to the Doctor

There was no significant group difference regarding a change in the frequency of visits to the doctor, (experimental group: Mdn = 0.5, IQR = 1.25; control group: Mdn = 0, IQR = 1; U26,29 = 337, z = −0.7, p = 0.25).

Work Ability and Sick Leave

Work Ability

There was no significant group difference regarding the change in current work ability (experimental group: Mdn = 0, IQR = 1.75; control group: Mdn = 0.5, IQR = 1; U26,29 = 371.5, z = −0.09, p = 0.47). With respect to the subject’s own prognosis of future work ability we found subjects of the experimental group to significantly become more pessimistic in their ratings in comparison to control subjects (experimental group: Mdn = −6, IQR = 3; control group: Mdn = 0, IQR = 0; U26,29 = 59.5, z = −5.67, p < 0.001, r = −0.76).

Days of Sick Leave

There was an unexpected significant group difference concerning the change in the number of days of sick leave: Whereas the number of days increased in the experimental group, a decrease was observed in the control group (experimental group: Mdn = 0, IQR = 6; control group: Mdn = 0, IQR = 2; U26,29 = 237, z = −2.5, p = 0.01, r = −0.34).

Perceived Stress and Emotional Exhaustion

Perceived Stress

There was a significant group difference regarding a change in perceived stress: In the experimental group, there was a stronger reduction of perceived stress than in the control group (experimental group: M = −3.51, SD = 5.04; control group: M = −0.56, SD = 5.11; t52 = −2.15, p = 0.02, r = 029).

Emotional Exhaustion

We found a significant group difference in work related emotional exhaustion change indicating a more favorable change in subjects who had already completed Neuropattern than in subjects waiting (experimental group: M = −0.53, SD = 0.84; control group: M = −0.18, SD = 0.72; t53 = −1.67, p = 0.05, r = 0.22).

Work-Related Stress

Effort

There was a significant group difference with regard to a change in effort at work (or workload/demand): In the experimental group there was a stronger reduction of effort than in the control group (experimental group: Mdn = −1, IQR = 2; control group: Mdn = 0, IQR = 2; U26,29 = 262, z = −2.01, p = 0.02, r = −0.27).

Reward

Regarding a change in reward at work there was no significant difference between the experimental and the control group (experimental group: M = 0.58, SD = 2.9; control group: M = −0.04, SD = 2.05; t53 = 0.81, p = 0.24).

Effort-Reward Ratio

There was no significant group difference concerning the change in the Effort-Reward (ER) ratio (experimental group: Mdn = −0.06, IQR = 0.51; control group: Mdn = 0.02, IQR = 0.16; U26,29 = 325, z = −0.88, p = 0.19).

Overcommitment

We found a significant group difference regarding the change of overcommitment at work: In subjects of the experimental group overcommitment was reduced to a greater degree than in control subjects (experimental group: Mdn = −1, IQR = 2.25; control group: Mdn = 0, IQR = 1; U26,29 = 242.5, z = −2.34, p = 0.01, r = −0.32).

The numerous results reported so far can be caught visually from Fig. 2 (except for the WAI-item concerning the subject’s own prognosis of future work ability), the figure shows percentage change from baseline. Results concerning change scores (t2-t1 difference) for all dependent measures are summarized in Table 2.
Fig. 2

Mean change (t2-t1difference in %) for dependent measures in the evaluation package. Note: Percentage change was calculated for each subject [100*(t2-t1)/t1]. Error bars show standard error of mean (SEM), experimental group: n = 26, control group: n = 29

Table 2

Group Differences (Change t2 – t1)

 

Experimental

Control

N

p

Health – SF 12

  

 Impairment of physical health: Mdn (IQR)

0 (0.56)

0 (0.44)

54

0.38

 Impairment of mental health: Mdn (IQR)

−0.25 (0.47)

−0.03 (0.58)

55

0.1

Visits to the doctor: Mdn (IQR)

0.5 (1.25)

0 (1)

55

0.25

Current work ability – WAI: Mdn (IQR)

0 (1.75)

0.5 (1)

55

0.47

Days of sick leave: Mdn (IQR)

0 (6)

0 (2)

55

0.01

Perceived Stress – PSS: M (SD)

−3.51 (5.04)

−0.56 (5.11)

54

0.02

Emotional exhaustion – MBI: M (SD)

−0.53 (0.84)

−0.18 (0.72)

55

0.05

Work-related stress – ERI

 

 Effort: Mdn (IQR)

−1 (2)

0 (2)

55

0.02

 Reward: M (SD)

0.58 (2.9)

−0.04 (2.05)

55

0.24

 Effort-Reward Ratio: Mdn (IQR)

−0.06 (0.51)

0.02 (0.16)

55

0.19

 Overcommitment: M (SD)

−1 (2.25)

0 (1)

55

0.01

Sporting activity: Mdn (IQR)

0 (1)

0 (0)

51

0.04

Practice of relaxation methods: Mdn (IQR)

0 (0)

0 (0)

52

0.27

Note: M = mean, SD = standard deviation, Mdn = median, IQR = interquartile range, n = number of participants. Statistical comparisons by Student’s t-tests or Mann-Whitney U tests. Change scores were calculated for each subject t2 (after 3 months) - t1 (baseline)

Health-Related Behavior

Sporting Activity

Regarding a change in the frequency of sporting activities there was a significant group difference: The experimental group increased their sporting activity to a greater degree than the control group (experimental group: Mdn = 0, IQR = 1; control group: Mdn = 0, IQR = 0); U23,28 = 238, z = −1.9, p = 0.04, r = −0.27).

Practice of Relaxation Methods

Regarding a change in the number of relaxation exercises there was no significant group difference (experimental group: Mdn = 0, IQR = 0; control group: Mdn = 0, IQR = 0; U23,29 = 305.5, z = −1.12, p = 0.27).

Short-Term Versus Medium-Term Changes

A treatment gain score was calculated per subject and variable, subtracting baseline from post treatment measures (three and six months). Data that were not normally distributed were analyzed using the Wilcoxon signed-rank test. Parametric testing was conducted using the t-test for dependent measures. There were no significant differences regarding short versus long term treatment gain (see Table 3).
Table 3

Short-term (experimental: t2-t1; control: t3-t2) versus Medium-term (experimental: t3-t1; control: t4-t2) Effects

 

Short-term

Medium-term

n

p

Health – SF 12

  

 Impairment of physical health: Mdn (IQR)

0 (0.56)

0 (0.36)

34

0.55

 Impairment of mental health: Mdn (IQR)

−0.14 (0.44)

−0.14 (0.92)

35

0.72

Visits to the doctor: Mdn (IQR)

0 (1)

0 (2)

35

0.70

Current work ability – WAI: M (SD)

0.40 (1.38)

0.31 (1.53)

35

0.44

Days of sick leave: Mdn (IQR)

0 (4)

0 (5)

35

0.86

Perceived Stress – PSS: M (SD)

−2.84 (5.02)

−3.06 (5.88)

35

0.79

Emotional exhaustion – MBI: M (SD)

−0.43 (0.84)

−0.45 (1.07)

33

0.86

Work-related stress – ERI

 

 Effort: Mdn (IQR)

0 (1)

0 (2)

34

0.48

 Reward: M (SD)

0.58 (2.59)

0.09 (2.29)

34

0.12

 Effort-Reward Ratio: Mdn (IQR)

−0.05 (0.45)

−0.06 (0.46)

34

0.12

 Overcommitment: M (SD)

−0.87 (2)

−0.94 (2.1)

34

0.41

Sporting activity: Mdn (IQR)

0 (0)

0 (0)

30

0.73

Practice of relaxation methods: Mdn (IQR)

0 (1)

0 (1)

30

1

Note: M = mean, SD = standard deviation, Mdn = median, IQR = interquartile range, n = number of participants. Statistical comparisons by Student’s t-tests or Wilcoxon signed-rank tests. For each subject and each dependent variable a short-term change score was calculated (experimental subjects: t2-t1; control subjects: t3-t2). Analogously medium-term change scores were calculated (experimental subjects: t3-t1; control subjects: t4-t2

Discussion

Neuropattern has proven helpful in the treatment of stress-related disorders in various clinical settings. The present pilot study was a randomized controlled pilot study designed to scrutinize whether the application of Neuropattern potentially has beneficial effects also in a vocational setting.

It was analyzed whether the application of Neuropattern a) improves health status and work ability and leads b) to a reduction of perceived stress, work-related stress and emotional exhaustion, days of sick leave and number of visits to the doctor and c) to an augmentation of sporting activity and practicing of relaxation methods.

Van der Klink et al. (2001) recommended a controlled follow-up of at least 12 weeks to be part of the design of intervention studies. In the present study, data were collected at baseline (t1) as well as after 3 (t2), 6 (t3) and, if applicable, 9 months (t4), depending on assignment to the wait-list control group or the experimental group In order to analyze treatment effects of Neuropattern, change scores (score difference t2 – t1) were calculated and compared between groups. Improvements of health, effort-reward-imbalance and work ability as well as a reduction of perceived general and work-related stress, emotional exhaustion, days of sick leave and number of doctoral visits were expected to be more pronounced in the experimental group compared to the control group.

There was no significant effect of Neuropattern on subjects’ physical health (SF-12) but a tendentially significant positive effect on mental health (SF-12). Subjects of the experimental group changed to a more favorable view on their mental health when compared to subjects of the wait-list control group, indicating a positive influence of Neuropattern on mental health perception. The change scores regarding the number of visits to the doctor did not differ significantly.

Current work ability did not change significantly in response to Neuropattern. However, when asked about their estimated future work ability, subjects of the experimental group became significantly more pessimistic in their ratings than control subjects did. This effect was rather high. Also, Neuropattern surprisingly had a medium negative effect on days of sick leave. Employees of the experimental group increased in their days of sick leave while control subjects’ sick leave rates decreased. However, the change in perceived stress (PSS) did not correspond with change scores of the number of days of sick leave. Even though subjects showed higher rates of sick leave, their estimated stress levels decreased significantly after completing Neuropattern when compared to a three-months waiting-period. The same was shown for emotional exhaustion (MBI). Effect sizes, however, were rather low.

There were some significant findings regarding work-related stress (ERI). Both groups reduced their effort, but the experimental group did so significantly more than the control group (low effect size). There were no significant differences regarding reward or effort-reward ratio. Overcommitment was reduced significantly more after Neuropattern than after a three months waiting period with medium effect size.

Subjects of the experimental group showed a significantly higher increase in sporting activity when compared to subjects of the control group (low effect size). There were no significantly different changes between groups in practicing relaxation methods.

When looking at short-term versus medium-term changes, we found no significant difference for any dependent variable. This means that the changes due to the application of Neuropattern can be regarded as stable.

The most frequently diagnosed Neuropattern in this study were CRF Hyperreactivity, Serotonin Hypoactivity, NA Hyperreactivity, NA Hypoactivity and NA Hyperactivity. CRF Hyperreactivity is a Neuropattern of the glandotropic system (energy supply system). Its clinical presentation displays an elevated reactivity of personally relevant (often anticipatory) stressors, especially if they are seen as uncontrollable, unpredictable and novel. Early adversity during prenatal development or in early childhood development of the CNS play a major role at this. Since this poses a general vulnerability to stress, the modification of dysfunctional stress-enhancing cognitions, reduction of worrying and avoiding overload through appropriate time and resource management are particularly important in psychological interventions (see Hellhammer and Hellhammer 2008).

Serotonin Hypoactivity belongs to the group of trophotropic Neuropattern (regenerative system) and is characterized by a deficit of regenerative and protective mechanisms of the CNS. This manifests itself within the clinical presentation of various symptoms, such as inner restlessness, irritability with a tendency towards impulsive reactions, increased appetite to sweet foods, occasionally also difficulties maintaining sleep, and a shift in affectivity towards the depression. Cardiovascular diseases can accumulate due to an elevated preparedness of the SNS. A serotonergic deficit plays a role in a variety of disorders, especially in depressive and anxiety disorders. Psychological interventions should focus on strengthening trophotropic functions (relaxation methods, euthymic training, promotion of sleep hygiene) and reducing strain through appropriate time and resource management (see Hellhammer and Hellhammer 2008).

NA Hyperreactivity, NA Hypoactivity and NA Hyperactivity are allocated to the ergotropic system (work system). Accumulated frequencies of Neuropattern in this population indicate most subjects showing stress-related changes in the ergotropic system. An initially elevated performance level (power of concentration, vigilance, attention) switch completely under chronic stress, causing symptoms of exhaustion, sleeping disorders, digestive disorders, hypertension, irritability and anxiety. Most people suffering from burnout (45%) show NA hypoactivity (Hellhammer et al. 2012). Appropriate psychological interventions comprise mainly coping with stress, avoiding overload through the organization of breaks, sleep hygiene and creating relaxation ability (see Hellhammer and Hellhammer 2008). These dysregulations might be a consequence of the type of occupational stress and could therefore be relevant for interventions on an organizational level.

The participating employees of Landesforsten Rheinland-Pfalz turned out to be quite stressed, scoring high on the PSS (references in Cohen and Janicki-Deverts 2012), the MBI (references in Maslach et al. 1996) and the ERI (references in Nuebling et al. 2013; Unterbrink et al. 2007). Given this rather high stress load it is not surprising that Neuropattern detected measurable stress-related health impairments in most of the participants; only 12 subjects showed no stress-related symptoms.

Overall, 70 subjects entered the study, of which 55 subjects took part in at least one of the two assessments done after the application of Neuropattern. Subjects were block-randomized (blocks of five subjects for each functional group). The first five subjects of each functional group entered the experimental group, the second block of five subjects entered the control group etc. Since not all vouchers were requested, the last open slots in the control group could not be filled leading to an uneven distribution of subjects in the experimental and the control group. However, in both groups, subjects did not return the NPQ-A (four subjects of the experimental and five subjects of the control group, respectively). In both groups, there were missing responses to the evaluation questionnaires that lead to change scores of 55 subjects. Since all participants underwent the Neuropattern procedure, we would not conclude any relationship between dropout and NP. Since the subjects were randomly assigned to either the experimental or the control group and the procedures in both groups were not substantially different (except for the waiting period), differences in compliance could not be attributed to the study design.

Only three subjects who underwent Neuropattern belonged to the functional group of Operational Execution Level limiting the representative status of the data. This is in accordance with the findings of Toker and colleagues (2015) stating that employees having a blue-collar position are less likely to participate in worksite health promotion programs. Especially the highly negative ERI scores were remarkable: Subjects showed high levels of effort combined with medium reward being highly overcommitted. The actual working conditions at Landesforsten Rheinland-Pfalz (external factors) posed a high workload paired with a lack in personal and timely resources, demanding constant adjustment to changing working conditions from an aging pool of employees. On the individual level (internal factors) the employees mainly comprised of highly intrinsically motivated males with high performance standards explaining the tendency for overcommitment. An unbalanced ratio of effort and reward at work as seen in this study has previously been observed to be associated with various disorders (e.g. Van Vegchel et al. 2005), higher rates of absenteeism (Head et al. 2007), work dissatisfaction (de Jonge et al. 2000) and reduced productivity (Siegrist 2002). Internal factors such as ‘overcommitment’ also contribute to the risk of disease (de Jonge et al. 2000). Methods of reducing that risk should focus on changing structural as well as individual factors (Siegrist 1998).

To the best of our knowledge, this study is the first to explore the use of a psychobiological tool trying to assess individual dysregulations of the stress-response network in the vocational setting. Bakker et al. (2012) also proposed the use of data mining and predictive modeling for gaining insight in the effects of work stress on health and therefore enabling better stress management. In their approach, biological measures were not conceptualized, but treated as dependent variables. Knowledge from basic psychobiological research on the stress-response network in the brain was translated into a diagnostic tool comprising psychological, biological, and symptom measures. From these measures, Neuropattern derived hypotheses on potential dysregulations of the stress response network, which help the treating physician to choose the best treatment for a patient. Given the broad complexity and heterogeneity of psychobiological determinants of stress pathology, the small number of participants did not allow to analyze associations among such dysregulations, assigned treatments, and treatment success. This will be worthwhile, once a pilot study like this encourages running an adequate comprehensive study.

Neuropattern mainly aims at affecting internal factors by providing psychobiological information on the effects of stress on health, coping strategies as well as possible medical treatment. In the present study, an overall decrease of subjects’ effort-reward ratio was marginally steeper within the first three months. Changes of the effort-reward ratio and perceived reward did not differ significantly between groups. However, subjects of the experimental group reduced their ‘effort’ and ‘overcommitment’ significantly more than control subjects, indicating a small to medium effect of Neuropattern on these internal factors, potentially lowering the risk of disorders. Nevertheless, a sustainable reduction of stress at work also calls for implementing structural changes of external factors. With respect to mental health (SF-12), perceived stress (PSS) and emotional exhaustion (MBI), this study showed that subjects could benefit from Neuropattern. In addition, there were positive effects on health-related behavior such as sporting activity. In the clinical trials of Hero et al. (2012) and Bruhn (2014) we observed a spontaneous improvement of symptoms, once the disease model (stress triangle) was introduced. This may be considered a mindset effect (Crum et al. 2013, 2017), which refers to the contextually-dependent nature of testing. Here, the disease model can have influenced cognitive reappraisal, and the relief of having a satisfactory explanation of their health state, may have improved responses to measures of stress and depression.

Neuropattern seemed to affect work ability, leading to increasing days of sick leave and a more pessimistic view on future ability to perform their job. With regard to the last-mentioned result it has to be considered though that according to findings of Yang et al. (2013) the WAI-item concerning the subject’s prognosis of their own future work ability shows only moderate retest-reliability (r = 0.48). Therefore the informative value of this finding is limited. Nevertheless, informing subjects about detectable stress-related changes may have had a sensitizing effect. This, however, may lead to positive long-term outcomes if subjects begin to address their stress level resulting in higher self-care and less presenteeism (going to work sick). Presenteeism has been associated with subsequently higher rates of absenteeism, lower monthly income (Aronsson et al. 2000) and future health impairment (Bergström et al. 2009). Making up 64% of indirect costs, presenteeism poses a far bigger financial burden than absenteeism accounting for 6% (Hemp 2004). There is evidence for the effectiveness of some workplace health promotion programs on reducing presenteeism, especially when offering organizational leadership, health risk screening, individually tailored programs, and a supportive workplace culture (Cancelliere et al. 2011). Neuropattern fulfills some of these characteristics. However, in the present study, presenteeism has not been assessed. More research is required for a deeper understanding of the effect of Neuropattern on presenteeism.

As Murphy (1996) already reported, stress reduction at work rarely influences days of sick leave or work satisfaction. According to Murphy (1996), measures of stress-reduction at work should include organizational changes in order to produce effects on job/organization-relevant outcomes, such as absenteeism or job satisfaction. However, focusing only on changing organizational structures (e.g. job redesign, organizational development) showed mixed results (see van der Klink et al. 2001; Kompier et al. 1998). Best effects were achieved addressing both, individual and organizational levels (LaMontagne et al. 2007). Kompier and colleagues (2000) called for the “Big Five” of stress prevention:
  • A stepwise and systematic approach.

  • An adequate diagnosis or risk analysis (risk factors and risk groups).

  • A package of interventive measures that match the risk analysis and usually combine work-directed and person-directed measures.

  • A participatory approach assuring involvement and commitment of both, employees and middle management.

  • The sustained commitment of top management.

After the application of Neuropattern, the majority of employees may show evidence for either ergotropic (e.g. time-pressure, work overload, poststress-disorders), or trophotropic (e.g. exhaustion, lack of resilience, impaired regeneration, sleep disorders), or glandotropic dysregulations (e.g. uncertainty, unpredictability, uncontrollability, novelty, worrying). If so, it is not unlikely, that such dysregulations are a consequence of the type of occupational stress and could therefore be relevant for tailored interventions on an organizational level. At present, Neuropattern fulfills points 1 and 2 of the “Big Five” mentioned above. In the future, Neuropattern could be expanded used to work with organizations (point 3) involving all levels of organizations (point 4) and continuously train employees of the management (point 5).

Limitations

Not all 100 vouchers have been redeemed. Reasons could have been limited resources to invest in the activities of the program, believing that participation may lead to resource loss or will not lead to resource gain, or that the value of the gain is not high (Toker et al. 2015). Additionally, the structure of Landesforsten Rheinland-Pfalz complicated recruitment. There are widely spread different locations of offices all attended by one social worker. In addition, many employees (e.g. the whole functional group of Operational Execution Level) have no internal e-mail account and could therefore not be included into the distributor. Future studies should either include a trained team of employees, creating a broad network of study related knowledge within an organization.

Physicians were not necessarily trained in the Neuropattern concept. Employees of Landesforsten Rheinland-Pfalz were distributed all over the state of Rhineland-Palatinate, mostly located in the forest areas, where they had local access to their family physicians. Medical care would not have been guaranteed nearby if only trained physicians had been included due to the structure of Landesforsten Rheinland-Pfalz. Once physicians received both the medical report and the patient report with the disease model, there should have been an understanding of a possible dysregulation of the stress response network and individual treatment recommendations derived from that model. If they had any questions, they could contact the study office. However, centralized medical expertise would have been more favorable and could be realized in future projects with differently structured companies.

Possible costs to the employees (e.g. supervisor backlash) of reducing their effort and overcommitment or higher rates of sick leave have not been assessed. The present study was a first pilot study applying NP to the vocational setting. Subjects did not report any negative consequences (as an AE). However, this cannot be ruled out and should be addressed in future projects.

Even though subjects reduced their effort and showed more days of sick leave, the incentive for agencies to apply Neuropattern on the basis of these findings could lie in long-term reduction of stress-related health issues of their employees. In the present study, mental health improved. Also, as stated above, now that Neuropattern has shown to be applicable to the vocational setting, it can be expanded in the future in order to tailor interventions for organizations in order to tackle the issue of work stress. Result suggest effects of Neuroattern to decline with time (see short-term vs. medium-term reduction of effort-reward ratio and overcommitment), so continuous training could ensure a long-term reduction of work stress.

The sample of this pilot study consisted primarily of males due to the structure of Landesforsten Rheinland-Pfalz. Neuropattern has shown to equally beneficial to both male and female patients in a clinical setting. Marginal significant but inconsistent differences were observed in the three clinical trials. Thus, we would not expect gender differences in the effect of Neuropattern in a non-clinical setting. However, in order to rule out the possibility of a gender-specific influence on the benefit of Neuropattern on work stress, further research should include an equal distribution of males and females in the study population.

Missing data were excluded case-wise, meaning only cases that did not contain any missing data for any of the variables selected for the analysis were included in the analysis. Case-wise deletion is the most common method for addressing missing data, even though missing data are required to be missing completely at random (MCAR) (Cole 2008). However, since it may yield biased parameter estimates, or lead to a loss of power, this method may be an undesirable option, unless the loss of cases due to missing data is less than about 5% since higher loss leads to substantial loss of power. This risk can be avoided using multiple imputation or maximum-likelihood procedures (see Graham 2009). The loss of cases due to case-wise exclusion in was not substantial in the present study, which had been conceptualized as a pilot study with no multivariate analyses. However, multiple imputation might have been more favorable, as it is known to perform very well in multivariate analyses of small samples (Graham and Schafer 1999).

The present study used a wait-list control group to evaluate the effects of Neuropattern. For a deeper understanding, further studies should ideally include a placebo condition.

Conclusion

The present project was a pilot study designed to explore the applicability of Neuropattern to workplace conditions. There were positive effects on mental health (SF-12), perceived stress (PSS), emotional exhaustion (MBI) and health-related behavior as well as clear indication since clinically relevant psychobiological dysregulations were found in most of the participants.

Informing employees about stress-related changes may lead to an elevated problem perception and, in turn, higher levels of self-care, as results of this study regarding days of sick leave and the reduction of effort and overcommitment might suggest.

Thus, Neuropattern has shown its potential to sensitively detect early changes in stress physiology leading to positive outcomes on health-related variables. However, further research is required for a deeper understanding of these findings.

Notes

Acknowledgments

The authors would like to thank [name deleted to maintain the integrity of the review process] for her contribution in planning this project, as well as [names deleted to maintain the integrity of the review process] and the participating employees of Landesforsten Rheinland-Pfalz for their support.

Conflict of Interests

[name deleted to maintain the integrity of the review process] owns a trade mark protection for Neuropattern in the US and her company provides Neuropattern for clinical trials and patients. [name deleted to maintain the integrity of the review process] received a salary from the [name deleted to maintain the integrity of the review process] as a study manager during data collection. Data management, data analysis as well as writing the manuscript were part of her dissertation project, conducted externally, not as an employee of the [name deleted to maintain the integrity of the review process]. [name deleted to maintain the integrity of the review process] applies Neuropattern in his private practice. The authors state that there are no further conflict of interests.

Statement of Authorship

[names deleted to maintain the integrity of the review process] and [name deleted to maintain the integrity of the review process] were responsible for conception and design of the RCT. [name deleted to maintain the integrity of the review process] drafted the manuscript, [name deleted to maintain the integrity of the review process] and [name deleted to maintain the integrity of the review process] performed the statistical analyses. [name deleted to maintain the integrity of the review process] helped with interpretation of the data. All authors helped writing and reviewing the manuscript and have approved the final article.

Supplementary material

41542_2018_25_MOESM1_ESM.pdf (656 kb)
ESM 1 (PDF 656 kb)
41542_2018_25_MOESM2_ESM.pdf (200 kb)
ESM 2 (PDF 199 kb)
41542_2018_25_MOESM3_ESM.pdf (394 kb)
ESM 3 (PDF 393 kb)

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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Stress Center TrierScience ParkTrierGermany
  2. 2.Department of Clinical and Physiological PsychologyTrier UniversityTrierGermany

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