Unemployment is a growing problem. The unemployment quota ranged at 18.3% at the beginning of this study in the year 2005 1. It is well known that unemployment brings to bear negative effects on the psychological 2345 and physical state of health of those affected 678, e. g. decline in self-esteem 9, increased prevalence of depression 10 and increased risk of cardiovascular disease 11 were observed. Even higher mortality rates 1213141516 and suicidal tendencies 1416 have been reported. Therefore it is even more important to research the influencing factors causing these negative results as well as evaluating intervention strategies to minimize these negative effects.

Unemployment is a chronic stressor potentially disturbing autonomic balance when adjustment to job loss fails. Heart rate variability (HRV) is an established marker of autonomic flexibility, or in the case of depressed HRV, of autonomic inflexibility in response to changing external and internal stressors 17. Jandackova, Paulik, and Steptoe (2012) demonstrated decreased HRV parameters in unemployed subjects 18. Unemployment may be associated with factors that negatively influence HRV parameters, such as smoking, drinking, physical inactivity and high body mass index that could account for the increased prevalence of cardiovascular diseases 18. HRV is defined as the beat to beat variability of consecutive heartbeats 19. It is regulated by the balanced interaction of the sympathetic and the parasympathetic nervous system. Parasympathetic activity is reflected in adjustments of the heart rate (HR) in response to changes in blood pressure or respiratory status; the sympathetic tone controls changes in HR in response to physical or mental stress 20. In medical science and practice, HRV has established itself as an independent predictor for an increased risk of mortality after a myocardial attack 21. In clinical psychological research, decreased HRV parameters were associated with negative affectivity, especially with anxiety 22 and anger 23 and with mental disorders such as depression 242526272829303132 and anxiety disorders 2233.

Up to now, there is little evidence for interventions providing support to unemployed subjects in reducing distress 34 and existing studies focused primarily on re-employment. Interventions supporting adjustment to job loss could also focus the associated negative health effects, e.g. the previous finding of reduced HRV 18. Studies documented a positive effect of HRV-biofeedback training on HRV 353637. Biofeedback is a scientifically based method in which physiological bodily processes, which normally are not perceived consciously, are made visible and, thus, individually amenable to influence. Physiological signals (e.g. heart rate) are registered, amplified, and visually or acoustically confirmed. Thus, seemingly unable to be influenced bodily functions can be controlled via biofeedback processes 38. Recent studies further indicate that HRV biofeedback is effective in the treatment of depression 394041, posttraumatic stress disorders 4243, sleeping disorders 43, stress disorders/stress reactions 444546, anxiety disorders 47, the attention-deficit-hyperactivity-syndrome 48, fibromyalgia 39, and bronchial asthma 4950.

The processes by which HRV biofeedback improves health and well-being are not yet understand. It is suggested that HRV biofeedback produces resonance condition between HR, breathing rate and baroreceptor activity allowing for maximized amplitudes of the HRV 37. Resonance frequency differs interindividually but on average it is 0.1 Hz, corresponding to 6 breathes per minute 37. Further, biofeedback improves interoceptive awareness of any senses stimulated within the body 51. With the help of biofeedback, participants learn to perceive and control somatic functions that actually are not perceived consciously. Thus biofeedback may help to improve well-being by increasing self-efficacy and the sense of control. This idea agrees with Turner, Kessler, and House (1991) who recommended providing interventions to unemployed subjects that bolster self-efficacy 52. Work is one major source of self-efficacy that declines following job loss and is regained with re-employment 9. Further self-efficacy is crucial in motivating job-seeking behavior since low self-esteem is associated with inhibition of job-seeking activities 53.

The aim of the present study is to evaluate the effectivity of HRV-biofeedback in normalizing HRV (increased RMSSD, decreased mean HR) and increasing ratings on self-efficacy in a sample of unemployed subjects.

Group differences in sociodemographic and clinical characteristics were tested using univariate ANOVA for continuous variables and chi-squared test for dichotomous variables. The effect of biofeedback on HRV (mean HR, RMSSD) was examined using repeated measures ANOVA with group 2 as between-subject factor and stress test condition 3 and measuring time 2 as within-subject factors. ANOVA results were corrected by Greenhouse-Geisser whenever necessary. Data analyses were performed using SPSS v. 22 (SPSS Inc., Chicago, IL, USA).

The group’s characteristics are described in Table 1. Groups were well-matched on sociodemographic and clinical variables.

Means and standard deviations for each HRV parameter are displayed in Table 2 as a function of stress test condition and measuring time. ANOVA revealed a main effect of stress test condition for the RMSSD (F_1.471;29.425 = 39.707, p < 0.001, ç² = 0.665) and mean HR (F_1.897;37.948 = 42.386, p < 0.001, ç² = 0.679). Pair-wise comparisons revealed significant differences for all stress test conditions (p ≤ 0.021), except for comparing mean HR during the d2-attention-stress-test and math-test (p = 1.000). As expected, increased RMSSD was observed during timed breathing with 0.1 HZ. ANOVA didn’t demonstrate a main effect of group neither for the RMSSD (F_1;20 = 2.400, p = 0.137, ç² = 0.107) nor for mean HR (F_1;20 = 0.011, p = 0.919, ç² = 0.001) as well as no interaction effect between study group and stress test condition.

Regarding ADNM sum score, ANOVA failed to reveal a main effect of time (F_1;18 = 1.029, p = .324, ç²= 0.054) and of group (F_1;18 = 1.121, p = .304, ç² = 0.059) or time x group interaction effect (F_1;18 = 2.085, p = .166, ç²= 0.104). With regards to the GSE sum score ANOVA didn’t demonstrate a main effect of time (F_1;20 = 1.547, p = .228, ç²= 0.072) or group (F_1;20 = 1.083, p = .310, ç² = 0.051) nor time x group interaction effect (F_1;20 = 2.614, p = .122, ç²= 0.116).

This study investigated the effectivity of heart rate variability (HRV)-biofeedback in improving HRV and general self-efficacy in unemployed subjects. To date, there is little research addressing intervention strategies to minimize negative effects on wellbeing following job loss. Previous studies demonstrated decreased HRV 18 and impaired general self-efficacy in unemployed subjects 9. HRV-biofeedback is suggested to improve HRV as well as self-efficacy 51. In this study, we found no significant effect of HRV-biofeedback on HRV and general self-efficacy.

Our results are in contrast to those of studies that reported increased HRV parameters following HRV-biofeedback-training 3536. Our findings didn’t show significant alterations in HRV parameters following HRV-Biofeedback. The samples of Bacior et al. (2004) as well as Larsen et al. (2004) included patients with chronic heart failure who showed decreased HRV. Since this study didn’t investigate a reference population, we couldn’t state if HRV parameters were decreased in our sample compared to healthy control participants. To reliably evaluate HRV parameters in reference to normal ranges, this study should have included a healthy control group that should have passed the stress tests as well to serve as a reference population. According to a study by Agelink et al. (2001) both male and female participants of our study showed RMSSD parameters that are in line with established standard values 64. This reduces the plasticity of improving initial RMSSD. Further, our data failed to show significant alterations regarding self-efficacy and the ADNM sum-score following HRV-biofeedback. On a descriptive level, the biofeedback group was able to improve their RMSSD and to decrease their mean HR in all stress-test-conditions. Failure to reach significance may result from the small sample size or short intervention time.

HRV assessment was largely performed in accordance with the recommendations of the Task Force 19. Two variations were made. First, HR was derived by way of the pulse wave, and not via recommended ECG recording. But this method appears just as well reliable and not more interference-prone like ECG recording. Second, the Task Force recommends 5 minutes duration of ECG recording for short-term HRV assessment. In the present study, stress conditions lasted only 3 minutes and paced breathing was performed for 1 minute. ECG analysis was restricted to RMSSD time domain measure, and previous findings report on the reliability of the RMSSD for HRV assessment from recording of 1 minute and even of 10 seconds 63. Hence the present recording duration appears to be sufficiently reliable.

There are some limitations that should be noted. First, the sample size was small. Another limitation of this study is that no baseline HRV resting condition had been included. Paced breathing can induce stress and hence doesn’t serve well as resting condition. Future studies should include a resting session to compare resting and stressful conditions in HRV assessment. Future studies should also include a real control group without adjustment disorder and a reference population for the establishment of normal ranges of HRV parameters. Moreover, the present study included only a short interval of two weeks to observe changes in HRV. This may be too short to detect adaptation in the autonomous nervous system. Future studies should extend the intervention interval.

In conclusion, we found no significant effect of a 2-week HRV-biofeedback-training. Thus, we didn’t find evidence to support HRV-biofeedback-training in the present form to be an efficacious intervention to increase HRV and self-efficacy. Future studies should include a control group and extend the intervention interval.

All authors declare that they have no conflicts of interest.

All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsiniki declaration and its later amendments or comparable ethical standards.