Background: Tai Chi, Qigong, and Yoga are recognized as the most popular complementary approaches for alleviating musculoskeletal pain, improving sleep quality, and reducing blood pressure. The therapeutic effects of these meditative movements for treating major depressive disorder (MDD) is yet to be determined. Therefore, we examined whether meditative movements (Tai Chi, Qigong, and Yoga) are effective for treating MDD. Seven electronic databases (SPORTDiscus, PubMed, PsycINFO, Cochrane Library, Web of Science, CNKI, and Wanfang) were used to search relevant articles. Randomized controlled trials (RCT) using Tai Chi, Qigong or Yoga as intervention for MDD were considered for the meta-analysis (standardized mean difference: SMD). Results: Meta-analysis on 15 fair-to-high quality RCTs showed a significant benefit in favor of meditative movement on depression severity (SMD = −0.56, 95% CI −0.76 to −0.37, p < 0.001, I² = 35.76%) and on anxiety severity (SMD = −0.46, 95% CI −0.71 to −0.21, p < 0.001, I² = 1.17%). Meditative movement interventions showed significantly improved treatment remission rate (OR = 6.7, 95% CI 2.38 to 18.86, p < 0.001) and response rate (OR = 5.2, 95% CI 1.73 to 15.59, p < 0.001) over passive controls. Conclusions: Emphasizing the therapeutic effects of meditative movements for treating MDD is critical because it may provide a useful alternative to existing mainstream treatments (drug therapy and psychotherapy) for MDD. Given the fact that meditative movements are safe and easily accessible, clinicians may consider recommending meditative movements for symptomatic management in this population.

Although a growing body of research suggests that mind-body therapies may be appropriate to integrate into the treatment of depression, studies consistently lack methodological sophistication particularly in the area of control groups. In order to better understand the relationship between control group selection and methodological rigor, we provide a brief review of the literature on control group design in yoga and tai chi studies for depression, and we discuss challenges we have faced in the design of control groups for our recent clinical trials of these mind-body complementary therapies for women with depression. To address the multiple challenges of research about mind-body therapies, we suggest that researchers should consider 4 key questions: whether the study design matches the research question; whether the control group addresses performance, expectation, and detection bias; whether the control group is ethical, feasible, and attractive; and whether the control group is designed to adequately control for nonspecific intervention effects. Based on these questions, we provide specific recommendations about control group design with the goal of minimizing bias and maximizing validity in future research.

Background: It is well-documented that the mental health of pregnant and postpartum women is essential for maternal, child, and family well-being. Of major public health concern is the perinatal mental health impacts that may occur during the ongoing COVID-19 pandemic. It is essential to explore the symptom experience and predictors of mental health status, including the relationship between media use and mental health. Materials and Methods: The purpose of this study is to evaluate the experiences of pregnant and postpartum women (n = 524) in the United States in the early phase of the COVID-19 pandemic. This cross-sectional online observational study collected psychosocial quantitative and qualitative survey data in adult pregnant and postpartum (up to 6 months postdelivery) women in April–June 2020. Results: Multivariable linear regression models were used to evaluate predictors of depressive symptoms, anxiety, and post-traumatic stress disorder. The most common predictors were job insecurity, family concerns, eating comfort foods, resilience/adaptability score, sleep, and use of social and news media. Qualitative themes centered on pervasive uncertainty and anxiety; grief about losses; gratitude for shifting priorities; and use of self-care methods including changing media use. Conclusions: This study provides information to identify risk for anxiety, depression, and PTSD symptoms in perinatal women during acute public health situations. Women with family and job concerns and low resilience/adaptability scores seem to be at high risk of psychological sequelae. Although use of social media is thought to improve social connectedness, our results indicate that increased media consumption is related to increased anxiety symptoms.

Background: Incidence estimates of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, also known as long COVID, have varied across studies and changed over time. We estimated long COVID incidence among adult and pediatric populations in 3 nationwide research networks of electronic health records (EHRs) participating in the RECOVER (Researching COVID to Enhance Recovery) Initiative using different classification algorithms (computable phenotypes). Methods: This EHR-based retrospective cohort study included adult and pediatric patients with documented acute SARS-CoV-2 infection and 2 control groups: contemporary coronavirus disease 2019 (COVID-19)–negative and historical patients (2019). We examined the proportion of individuals identified as having symptoms or conditions consistent with probable long COVID within 30–180 days after COVID-19 infection (incidence proportion). Each network (the National COVID Cohort Collaborative [N3C], National Patient-Centered Clinical Research Network [PCORnet], and PEDSnet) implemented its own long COVID definition. We introduced a harmonized definition for adults in a supplementary analysis. Results: Overall, 4% of children and 10%–26% of adults developed long COVID, depending on computable phenotype used. Excess incidence among SARS-CoV-2 patients was 1.5% in children and ranged from 5% to 6% among adults, representing a lower-bound incidence estimation based on our control groups. Temporal patterns were consistent across networks, with peaks associated with introduction of new viral variants. Conclusions: Our findings indicate that preventing and mitigating long COVID remains a public health priority. Examining temporal patterns and risk factors for long COVID incidence informs our understanding of etiology and can improve prevention and management.