Heart rate variability predicts outcome of short-term psychotherapy at the workplace

Heart Rate Variability, Hypnosis, and Psychotherapy

Hypnotherapy is increasingly recognized as an effective treatment option for a wide range of psychological conditions and the psychological elements of physiologic health concerns. Despite its growing use, the mechanisms underlying hypnotherapy's therapeutic benefits remain unknown. Heart rate variability (HRV), a non-invasive biomarker of autonomic nervous system (ANS) activity and other processes relevant to the psychophysiological stress response, has been used to study the physiological effects of hypnosis. HRV is associated with adaptability to stress and overall mental and physical health. We review how HRV changes during hypnosis treatment and propose mechanisms by which hypnotherapy influences the stress response and psychological flexibility and improves wellbeing. Additionally, we highlight the use of HRV biofeedback as an adjunct to hypnotherapy and psychotherapy and illustrate its potential to enhance therapeutic outcomes. To showcase practical applications, we present a case study of hypnotherapy's impact on HRV in the treatment of hot flashes in post-menopausal women. We conclude by calling for further empirical research, particularly randomized controlled trials, to solidify the integration of HRV metrics in hypnotherapy practice. Understanding the interaction between hypnotherapy and HRV will support more targeted and effective interventions, benefiting both clinicians and patients.

Nomogram Based on HRV for Predicting the Therapeutic Effects of Orthostatic Training in Children with Vasovagal Syncope

BACKGROUND

This study intended to find out whether the parameters of heart rate variability (HRV) can predict the treatment efficacy of orthostatic training among pediatric cases of vasovagal syncope (VVS).

METHODS

Patients with VVS who underwent orthostatic training were retrospectively enrolled. Lasso and logistic regression were used to sift through variables and build the model, which is visualized using a nomogram. The model's performance was evaluated through calibration plots, a receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) for both datasets.

RESULTS

In total, 119 participants were included in the analysis, and 73 and 46 were assigned to the training and validation datasets, respectively. Five factors with nonzero coefficients were chosen based on lasso regression: age, the root means square of successive differences between normal sinus beats (rMSSD), standard deviation of the averages normal-to-normal intervals in all 5-min segments, minimum heart rate, and high frequency. Drawing from the logistic regression analysis results, the visual predictive model incorporated two variables, namely age and rMSSD. For the training dataset, the sensitivity was 0.686 and the specificity was 0.868 with an area under the curve (AUC) of 0.81 (95% CI, 0.71-0.91) for the ROC curve. For the validation dataset, the AUC of the ROC was 0.80 (95% CI, 0.66-0.93), while sensitivity and specificity were recorded at 0.625 and 0.909, respectively. In the calibration plots for both datasets, the predicted probabilities correlated well with the actual probabilities. According to the DCA, the visual predictive model gained a significant net benefit across a wide threshold range.

CONCLUSIONS

Pediatric patients with VVS can benefit from orthostatic training using a visual predictive model comprising age and rMSSD.

Evaluation of low vagally-mediated heart rate variability as an early marker of depression risk

BACKGROUND

Both low vagally-mediated heart rate variability (HRV) and depression have been shown to be risk factors for cardiovascular disease (CVD). We recently identified an HRV cutpoint below which persons have an increased risk for several cardiometabolic disorders. However, no cutpoint exists to identify those at risk for depression.

METHODS

The association between daytime HRV and diagnostically validated depression cutoffs using the five-item World Health Organization Well-being Index (WHO-5) was examined in adults from the Mannheim Industrial Cohort Study (n = 9973; Mage = 41.9[10.9]; 20 % women [n = 1934]). The aim was to identify HRV cutpoints for individuals who may have clinical depression.

RESULTS

Regression adjusting for age, sex, and linear trend showed a significant quadratic association between depression, indexed by WHO-5 scores and HRV, indexed by the root mean square successive differences (RMSSD) in milliseconds (ms) (p < 0.001). Logistic regression models adjusting for age, sex, and heart period (i.e., inter-beat intervals) compared the clinically depressed (WHO-5 ≤ 28) and those with a screening diagnosis of depression (WHO-5 ≤ 50) to the rest of the population. Significant odds ratios suggested two RMSSD values 25 ± 2 ms (OR = 1.39 [1.17, 1.64]) and 35 ± 2 ms (OR = 1.17 [1.02, 1.34]) that may be used to identify those with an elevated risk for depression.

LIMITATIONS

The sample was primarily German men. Fitness and anti-depressant use were not available.

CONCLUSIONS

As HRV is a brief measure that can be used in clinical settings, our HRV cutpoints have implications for the early detection of those at risk for psychological and cardiometabolic disorders.

Predicting response to stepped-care cognitive behavioral therapy for insomnia using pre-treatment heart rate variability in cancer patients

OBJECTIVE

This study examined whether high frequency heart-rate variability (HF-HRV) and HF-HRV reactivity to worry moderate response to cognitive behavioural therapy for insomnia (CBT-I) within both a standard and stepped-care framework among cancer patients with comorbid insomnia. Biomarkers such as HF-HRV may predict response to CBT-I, a finding which could potentially inform patient allocation to different treatment intensities within a stepped-care framework.

METHODS

177 participants (86.3 % female; Mage = 55.3, SD = 10.4) were randomized to receive either stepped-care or standard CBT-I. 145 participants had their HRV assessed at pre-treatment during a rest and worry period. Insomnia symptoms were assessed using the Insomnia Severity Index (ISI) and daily sleep diary across five timepoints from pre-treatment to a 12-month post-treatment follow-up.

RESULTS

Resting HF-HRV was significantly associated with pre-treatment sleep efficiency and sleep onset latency but not ISI score. However, resting HF-HRV did not predict overall changes in insomnia across treatment and follow-up. Similarly, resting HF-HRV did not differentially predict changes in sleep diary parameters across standard or stepped-care groups. HRV reactivity was not related to any of the assessed outcome measures in both cross-sectional and longitudinal analyses.

CONCLUSION

Although resting HF-HRV was related to initial daily sleep parameters, HF-HRV measures did not significantly predict longitudinal responses to CBT-I. These findings suggest that HF-HRV does not predict treatment responsiveness to CBT-I interventions of different intensity in cancer patients.

Compassionate mind training for people with Parkinson's disease: A pilot study and predictors of response

INTRODUCTION

People with Parkinson's disease (PD) often present with disabling neuropsychiatric symptoms. Compassionate mind training (CMT) is a psychological approach effective in reducing stress and promoting psychological well-being. Heart rate variability (HRV), a measure reflecting sympathovagal balance, has been associated with psychological well-being and a compassionate attitude.

AIM

To assess the feasibility and effectiveness of CMT in enhancing the quality of life and psychological well-being in PD patients. Additionally, we evaluated HRV as a physiomarker for assessing the CMT outcomes.

METHODS

Twenty-four PD patients participated in the study. A 6-week online CMT intervention was delivered on a weekly basis. At baseline and post-intervention patients completed questionnaires assessing depression, anxiety and quality of life. In a subsample of 11 patients, HRV was measured at baseline and post-intervention in three conditions: at rest, during stress and after 3 min of deep breathing.

RESULTS

The attendance rate was 94.3%. Quality of life and perceived stigma improved post-intervention as compared with baseline (p = 0.02 and p = 0.03 for PD Questionnaire-39 total score and Stigma subscore, respectively). After CMT, patients presented better physiological regulation to stress, as measured by higher HRV as compared with baseline (p = 0.005). Notably, patients who were more resilient to stress at baseline (less decrease in HRV during stress) experienced a more substantial reduction in anxiety and depression following CMT.

CONCLUSIONS

CMT is feasible and can improve quality of life and stigma in PD patients. HRV emerges as a promising physiomarker for predicting and measuring the outcomes of psychological interventions in PD.

The effect of an internet-based intervention for depression on cortisol and alpha-amylase

INTRODUCTION

Psychotherapeutic interventions for major depressive disorder (MDD) have been suggested to be associated with a normalization of biological stress system (i.e., the hypothalamic-pituitary-adrenal axis and the autonomic nervous system) dysregulation. Furthermore, pre-intervention cortisol parameters have been identified as prescriptive biological markers of treatment success. However, evidence of treatment effects on the biological stress systems is still sparse, and results are heterogeneous. The current study examined the effect of an internet-based intervention for MDD on salivary cortisol and alpha-amylase as well as hair cortisol concentrations. Moreover, the prescriptive capacity of pre-intervention cortisol and alpha-amylase concentrations on treatment response was explored.

METHODS

Thirty-eight participants suffering from mild to moderate MDD collected saliva and hair samples throughout the intervention. Biological outcome parameters were salivary cortisol and alpha-amylase (awakening response, total diurnal output, diurnal slope) and hair cortisol concentrations. Treatment response was indicated by change in depression severity and perceived chronic stress.

RESULTS

Treatment response on depression scores or chronic stress was not associated with changes in any of the cortisol or alpha-amylase parameters. Exploratory analysis indicated that non-responders showed a steeper alpha-amylase slope pre-intervention.

DISCUSSION

The results indicate that changes in depressive symptoms did not correspond to changes of the biological stress systems, contradicting the suggested normalization of dysregulated hypothalamic-pituitary-adrenal axis or autonomic nervous system activity through a psychotherapeutic intervention. However, the results point to a potential role of pre-intervention alpha-amylase slope as a prescriptive marker of treatment response for depression.

The cumulative effect of chronic stress and depressive symptoms affects heart rate in a working population

BACKGROUND

Chronic stress and depressive symptoms have both been linked to increased heart rate (HR) and reduced HR variability. However, up to date, it is not clear whether chronic stress, the mechanisms intrinsic to depression or a combination of both cause these alterations. Subclinical cases may help to answer these questions. In a healthy working population, we aimed to investigate whether the effect of chronic stress on HR circadian rhythm depends on the presence of depressive symptoms and whether chronic stress and depressive symptoms have differential effects on HR reactivity to an acute stressor.

METHODS

1,002 individuals of the SWEET study completed baseline questionnaires, including psychological information, and 5 days of electrocardiogram (ECG) measurements. Complete datasets were available for 516 individuals. In addition, a subset (n = 194) of these participants completed a stress task on a mobile device. Participants were grouped according to their scores for the Depression Anxiety Stress Scale (DASS) and Perceived Stress Scale (PSS). We explored the resulting groups for differences in HR circadian rhythm and stress reactivity using linear mixed effect models. Additionally, we explored the effect of stress and depressive symptoms on night-time HR variability [root mean square of successive differences (RMSSD)].

RESULTS

High and extreme stress alone did not alter HR circadian rhythm, apart from a limited increase in basal HR. Yet, if depressive symptoms were present, extreme chronic stress levels did lead to a blunted circadian rhythm and a lower basal HR. Furthermore, blunted stress reactivity was associated with depressive symptoms, but not chronic stress. Night-time RMSSD data was not influenced by chronic stress, depressive symptoms or their interaction.

CONCLUSION

The combination of stress and depressive symptoms, but not chronic stress by itself leads to a blunted HR circadian rhythm. Furthermore, blunted HR reactivity is associated with depressive symptoms and not chronic stress.