Heart rate variability biofeedback as a treatment for military PTSD: a meta-analysis

Abstract: INTRODUCTION: Emerging research has provided tentative support for the use of heart rate variability biofeedback (HRVB) as a treatment for several psychological disorders, with meta-analyses providing compelling evidence for HRVB as a promising treatment for anxiety, depression, and PTSD. Given the prevalence of PTSD in military veterans and the comparatively lower benefit and higher attrition rate of traditional psychological treatment for PTSD relative to civilian counterparts, it is important to examine complementary and alternative treatment approaches such as HRVB in this population. Although studies of HRVB for PTSD have been conducted with military veterans, they have involved relatively small sample sizes, limiting interpretation. To address this, the current article presents a comprehensive meta-analysis, consolidating existing literature to more accurately evaluate the efficacy of HRVB in reducing PTSD symptoms within military populations. MATERIALS AND METHODS: This meta-analysis was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, and our protocol was registered with PROSPERO to increase review transparency. A literature search of HRVB interventions was conducted using PubMed, PsycINFO, Military Database, PTSDPubs, and EBSCO's Psychological and Behavioral Sciences Collection. RESULTS: Five studies met eligibility criteria, providing a combined sample size of 95 military services members. For all studies, effect sizes were negative, indicating a reduction in PTSD symptoms. Effect sizes ranged from -1.614 to -0.414, resulting in an overall moderate to large mean effect for HRVB (Hedges's g = -0.557; 95% confidence interval = -0.818 to -0.296; P < .001). Additionally, cumulative attrition was 5.8%, significantly lower than commonly reported rates for evidence-based treatments (16%-36%). CONCLUSIONS: The present study is the first meta-analysis to examine HRVB as a treatment for military service members with PTSD. Results indicate that HRVB may be a viable treatment approach to reduce PTSD symptomatology. Low attrition rates, ease of accessibility, and favorable participant outlook serve as additional benefits for the use of HRVB.

Read the full article
Report a problem with this article

Related articles

  • More for Researchers

    Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data

    Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate the extraction of opioid relapses, and the timing of these occurrences, from veteran patients' electronic medical record. We then demonstrated the utility of our NLP tool via analysis of pre-/post-COVID-19 opioid relapse trends among veterans with OUD. For this demonstration, we analyzed data from 107,606 veterans OUD enrolled in Veterans Health Administration, comparing a pandemic-exposed cohort (n = 53,803; January 2019-March 2021) to a matched prepandemic cohort (n = 53,803; October 2017-December 2019). The recall of our NLP tool was 75% and our precision was 94%, demonstrating moderate sensitivity and excellent specificity. Using the NLP tool, we found that the odds of opioid relapse postpandemic onset were proportionally higher compared to prepandemic trends, despite patients having fewer mental health encounters from which to derive instances of relapse postpandemic onset. In this research application of the tool, and as hypothesized, we found that opioid relapse risk was elevated postpandemic. The application of NLP Methods: to identify and monitor relapse risk holds promise for future surveillance, risk prevention, and clinical outcome research.

    Mental Health Peer reviewed