Effectiveness of App-Based Yoga of Immortals (YOI) Intervention for Insomnia in Asian Population during Pandemic Restrictions

Effect of Yoga Therapy on Insomnia Severity and Systolic Blood Pressure in Aged Women: A 12-Week Intervention Study Conducted in Kerala

This study aimed to investigate the effects of a 12-week yoga therapy intervention on insomnia severity and systolic blood pressure in older women experiencing insomnia. A sample of 30 participants, aged between 60 and 70 years, underwent interventions, starting with an initial full-day workshop followed by 60-minute sessions held six days per week in the mornings. Women screening positive for insomnia using the Insomnia Severity Index Questionnaire were eligible for participation. The majority of participants were aged between 60 and 65 years, with a slight majority residing with a spouse. Economically, the group exhibited a diverse distribution, with a significant proportion classified as middle class. Educationally, the group also displayed a varied profile, with a range of educational qualifications. Pretests and post-tests were conducted to assess outcomes. The results revealed a significant reduction in Insomnia Severity Scores, with a mean decrease of 5.17 (±1.05), indicating a substantial effect size, from an initial average of 23.03 (±2.47) to 17.87 (±2.61) after the intervention. Similarly, there was a significant decrease in systolic blood pressure, with scores declining by a mean of 9.67 (±6.87), demonstrating a considerable effect size, from an average of 140.33 (±8.65) to 130.67 (±7.52). These findings suggest that yoga therapy holds promise as a non-pharmacological approach for alleviating insomnia symptoms and reducing systolic blood pressure in older women experiencing insomnia.

Yoga for COVID-19: An ancient practice for a new condition - A literature review

A substantial proportion of people with acute COVID-19 develop post-COVID-19 condition (previously known as long-COVID) characterized by symptoms that persist for months after the initial infection, including neuropsychological sequelae. Post-COVID-19 condition frequency varies greatly according to different studies, with values ranging from 4 to 80% of the COVID-19 patients. Yoga is a psycho-somatic approach that increases physical, mental, emotional and spiritual strength, and connection. Yoga practice enhances innate immunity and mental health, so it can be used as complementary therapy in the COVID-19 treatment, namely the post-COVID-19 condition. In this article, we conducted a literature review on yoga and COVID-19, finding that an intervention comprising asana, pranayama, and meditation may be a strategy of choice for these patients' recovery. However, further studies are needed to show its effectiveness in this, still unknown, context.

Comparative efficacy and acceptability of interventions for insomnia in breast cancer patients: A protocol for systematic review and network meta-analysis

BACKGROUND

Symptoms of insomnia are highly prevalent in patients with breast cancer. There are a large number of pharmacological and non-pharmacological interventions that can be used for the management of insomnia in breast cancer patients; however, their comparative effectiveness and acceptability remain uncertain. This review aims to evaluate the efficacy and acceptability of different interventions for insomnia in breast cancer patients using a Bayesian network meta-analysis (NMA).

METHODS

We will perform a comprehensive literature search in PubMed, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, and PsycINFO from inception to November 2022. We will include randomized controlled trials (RCTs) that compared the effects of different interventions on the management of insomnia in breast cancer patients. We will assess the risk of bias assessment using a modified Cochrane instrument. We will conduct a Bayesian random-effects framework NMA to estimate relative effects of interventional procedures. We will use Grading of Recommendations Assessment, Development and Evaluation to rate the certainty of evidence.

DISCUSSION

To our knowledge, this will be the first systematic review and network meta-analysis to compare the effectiveness and acceptability of all currently available interventions for insomnia in patients with breast cancer. The results of our review will help provide more evidence for the treatment of insomnia in breast cancer patients.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number CRD42021282211.

Living through the psychological consequences of COVID-19 pandemic: a systematic review of effective mitigating interventions

OBJECTIVE

This review assesses interventions and their effectiveness in mitigating psychological consequences from pandemic.

METHOD

Published English literatures were searched from four databases (Medline, PubMed, Embase and PsycINFO) from January 2020 and September 2021. A total of 27 papers with 29 studies (one paper reported three studies) met inclusion criteria. Cochrane risk-of-bias tool is applied to assess the quality of all randomised controlled trials (RCT).

RESULTS

All studies were recently conducted in 2020. Publications were from high-income (13, 44.8%), upper middle-income (12, 41.4%) and lower middle-income countries (3, 10.3%) and global (1, 3.5%). Half of the studies conducted for general population (51.7%). One-third of studies (8, 27.6%) provided interventions to patients with COVID-19 and 20.7% to healthcare workers. Of the 29 studies, 14 (48.3%) were RCT. All RCTs were assessed for risk of biases; five studies (15, 35.7%) had low risk as measured against all six dimensions reflecting high-quality study.Of these 29 studies, 26 diagnostic or screening measures were applied; 8 (30.9%) for anxiety, 7 (26.9%) for depression, 5 (19.2%) for stress, 5 (19.2%) for insomnia and 1 (3.8%) for suicide. Measures used to assess the baseline and outcomes of interventions were standardised and widely applied by other studies with high level of reliability and validity. Of 11 RCT studies, 10 (90.9%) showed that anxiety interventions significantly lowered anxiety in intervention groups. Five of the six RCT studies (83.3%) had significantly reduced the level of depression. Most interventions for anxiety and stress were mindfulness and meditation based.

CONCLUSIONS

Results from RCT studies (11%, 78.6%) were effective in mitigating psychological consequences from COVID-19 pandemic when applied to healthcare workers, patients with COVID-19 and general population. These effective interventions can be applied and scaled up in other country settings through adaptation of modes of delivery suitable to country resources, pandemic and health system context.

App-based Yoga of Immortals: A Novel, Easy-to-use Intervention in the Management of Urinary Incontinence

OBJECTIVE

To study the effectiveness Yoga of Immortals (YOI) intervention in participants with urinary incontinence (UI) of all types. YOI uniquely combines specific yogic postures, breathing exercises, sound therapy & meditation and is practiced by many for general well-being.

MATERIALS AND METHODS

In this App-based cohort study, a survey was sent to the YOI app subscribers. Those who identified with UI and consented were sent the ICIQ-UI- SF (for mean symptom score & severity of UI), and the ICIQ-LUTS-QOL (for impact of UI on QOL) Questionnaires at baseline, 4, and 8 weeks. Global impression of improvement was assessed by PGI-I scale.

RESULTS

258/422 participants (18-74 years) were included and showed significant decrease in mean scores on the ICIQ-UI-SF (4.06 ± 0.24 at baseline; 2.90 ± 0.22 at 4-weeks [p ≤ 0.001] and 3.44 ± 0.23 at 8 weeks [p ≤ 0.001]) and ICIQ-LUTS-QOL (28.36± 0.74 at baseline; 24.46± 0.70 at 4-weeks [p ≤ 0.001] and 25.78± 0.70 at 8 weeks [p≤ 0.001]). Additionally, the 55-60 year subgroup also had significant decrease in mean scores on ICIQ-LUTS-QOL (25.06 ±1.20 at base line; 21.69 ± 1.07 at 4 weeks [p ≤ 0.01] and 22.28 ± 0.96 at 8 weeks [p ≤ 0.01]).

CONCLUSION

YOI intervention resulted in significant improvement in mean scores on ICIQ-LUTS-QOL; ICIQ-UI-SF; frequency and severity of urinary leak; and daily life activity. Majority of the participants felt 'very much better' on PGI-scale. Being app- based, it has the added advantage of the ability to be used anytime and anywhere.

Online Isha Upa Yoga for student mental health and well-being during COVID-19: A randomized control trial

College students experienced increased stress and anxiety during the COVID-19 pandemic. This study evaluated the effect of brief online Isha Upa Yoga modules on undergraduates' mental health and well-being. Randomized control trial (RCT) with waitlist control crossover (N = 679). The intervention group was instructed to learn and practice the modules daily for 12 weeks. At the end of the 4-week RCT, the control group was instructed to learn and practice the modules for the remaining 8 weeks. Primary outcomes included stress and well-being. Secondary outcomes included anxiety, depression, resilience, positive affect and negative affect. Linear mixed-effects models were used for analyses. Isha Upa Yoga significantly reduced stress (Group [intervention, control] × Time [baseline, Week 4] interaction, p = .009, d = .27) and increased well-being (Group × Time interaction p = .002, d = .32). By the study's end, the intervention and control groups experienced significant improvements in well-being (p < .001, p < .001), stress (p < .001, p < .001), anxiety (p < .001, p < .001), depression (p < .001, p = .004), positive affect (p = .04, p < .001), and negative affect (p < .001, p < .001). Online Isha Upa Yoga shows promise for mitigating the pandemic's negative impact on undergraduates' mental health and improving their well-being.

Reductions in anxiety, depression and insomnia in health care workers using a non-pharmaceutical intervention

The COVID-19 pandemic has caused significant medical and psychological challenges worldwide, and not only exceeded the capacity of hospitals and intensive care units but also an individuals' ability to cope with life. Health-care workers have continued to provide care for patients despite exhaustion, fear of transmission to themselves and their family, illness or death of friends and colleagues, and losing many patients. They have also faced additional stress and anxiety due to long shifts combined with unprecedented population restrictions, including personal isolation. In this study, we study the effect of an app-based Yoga of Immortals (YOI) intervention on mental health of healthcare workers. In this study, the health care workers were digitally recruited, and their psychological parameters were measured using validated questionaries. The participants were randomly grouped into control and test groups. The validated psychological measures were the Patient Health Questionnaire-8 (PHQ-8), Insomnia Severity Index (ISI) and generalized anxiety disorder (GAD-7) scales. The digital YOI intervention significantly reduced the anxiety, depression symptoms, and insomnia in healthcare workers of all age groups. In contrast, there was no improvement in the control group. This study details the effectiveness of an app-based YOI intervention in healthcare workers.

Neural Network-Oriented Big Data Model for Yoga Movement Recognition

The use of computer vision for target detection and recognition has been an interesting and challenging area of research for the past three decades. Professional athletes and sports enthusiasts in general can be trained with appropriate systems for corrective training and assistive training. Such a need has motivated researchers to combine artificial intelligence with the field of sports to conduct research. In this paper, we propose a Mask Region-Convolutional Neural Network (MR-CNN)- based method for yoga movement recognition based on the image task of yoga movement recognition. The improved MR-CNN model is based on the framework and structure of the region-convolutional network, which proposes a certain number of candidate regions for the image by feature extraction and classifies them, then outputs these regions as detected bounding boxes, and does mask prediction for the candidate regions using segmentation branches. The improved MR-CNN model uses an improved deep residual network as the backbone network for feature extraction, bilinear interpolation of the extracted candidate regions using Region of Interest (RoI) Align, followed by target classification and detection, and segmentation of the image using the segmentation branch. The model improves the convolution part in the segmentation branch by replacing the original standard convolution with a depth-separable convolution to improve the network efficiency. Experimentally constructed polygon-labeled datasets are simulated using the algorithm. The deepening of the network and the use of depth-separable network improve the accuracy of detection while maintaining the reliability of the network and validate the effectiveness of the improved MR-CNN.