research paper on yoga and meditation

SYSTEMATIC REVIEW article

The effects of meditation, yoga, and mindfulness on depression, anxiety, and stress in tertiary education students: a meta-analysis.

• 1 Department of Psychiatry, Academic Medical Center, Amsterdam University Medical Center, Amsterdam, Netherlands
• 2 Research Department, Mental Health Foundation, London, United Kingdom
• 3 Department of Clinical, Neuro-, and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
• 4 Department of Psychology, Clinical Psychology and Psychotherapy, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
• 5 Mental Health and Addictions Research Group, Department of Health Sciences, University of York, York, United Kingdom

Background: Meditation, yoga, and mindfulness are popular interventions at universities and tertiary education institutes to improve mental health. However, the effects on depression, anxiety, and stress are unclear. This study assessed the effectiveness of meditation, yoga, and mindfulness on symptoms of depression, anxiety, and stress in tertiary education students.

Methods: We searched Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, PsycINFO and identified 11,936 articles. After retrieving 181 papers for full-text screening, 24 randomized controlled trials were included in the qualitative analysis. We conducted a random-effects meta-analysis amongst 23 studies with 1,373 participants.

Results: At post-test, after exclusion of outliers, effect sizes for depression, g = 0.42 (95% CI: 0.16–0.69), anxiety g = 0.46 (95% CI: 0.34–0.59), stress g = 0.42 (95% CI: 0.27–0.57) were moderate. Heterogeneity was low ( I 2 = 6%). When compared to active control, the effect decreased to g = 0.13 (95% CI: −0.18–0.43). No RCT reported on safety, only two studies reported on academic achievement, most studies had a high risk of bias.

Conclusions: Most studies were of poor quality and results should be interpreted with caution. Overall moderate effects were found which decreased substantially when interventions were compared to active control. It is unclear whether meditation, yoga or mindfulness affect academic achievement or affect have any negative side effects.

Introduction

Every 12 months, between 7 and 16% of students in tertiary education experience a mood or anxiety disorder and a further 30% of students report experiencing moderate to severe levels of stress ( 1 – 4 ).

It is important to tackle poor mental health early as unattended symptoms can contribute to poorer clinical outcomes such as an increased risk of developing a clinical diagnosis or relapse ( 5 ). When in distress, few students seek or receive treatment ( 6 ). This is due to several barriers such as stigma and lack of awareness of services ( 6 ).

Mindfulness, meditation, and yoga have been coined as a non-stigmatizing alternative to traditional mental health support. They are highly popular tools at tertiary education institutes and used for stress reduction, improve productivity and general mental health ( 7 ). Yoga, mindfulness, and meditation are part of a suite of interventions called mind-body interventions ( 8 ). They are closely related practices and share underlying common principles and therapeutic elements grounded in religion and spirituality ( 9 – 12 ).

The most commonly known and offered mindfulness program is Mindfulness-Based Stress Reduction ( 13 ). MBSR includes a set of specific mindfulness practices including focused attention on the breath, “body-scanning,” prosocial meditation (e.g., loving kindness and compassion), and gentle hatha yoga. MBSR is different from Mindfulness-Based Cognitive Therapy (MBCT) as it includes cognitive therapeutic elements such as cognitive restructuring and is aimed at reducing depressive relapse ( 14 ). Yoga is defined as a variety of practices which includes postures, breathing exercises, meditation, mantras, lifestyle changes spiritual beliefs, and/or rituals ( 15 ). A frequently practiced form of yoga is Hatha Yoga, which includes asanas (postures, pranayama (breathing exercises) and meditation, usually integrated throughout the practice ( 16 ).

Several reviews have been conducted to assess the effects of mindfulness and yoga-based interventions on a range of outcomes and populations. Reviews assessing the evidence for yoga have covered PTSD ( 17 ), depression ( 18 , 19 ), anxiety ( 20 ), and physiological measures of stress ( 21 , 22 ). For mindfulness and meditation interventions, reviews have assessed mood, and general functioning of students ( 23 ), employee mental health ( 24 ), stress management ( 25 , 26 ), depression, stress and wellbeing ( 27 ), recurrent depression ( 28 ), and anxiety ( 27 , 29 ). The reviews are wide-ranging in their conclusions and offer mixed results. Whilst the majority of reviews suggest preliminary evidence for their effectiveness, the authors often comment on the need for more rigorous research in this area.

The debate about the effects of these alternative medicine interventions thus remains. A recent review by Goyal et al. ( 27 ) found a pool of low-quality studies, with limited evidence for effect especially when compared to specific active treatment control conditions such as behavioral therapies, relaxation interventions, or exercise.

It is important to address the effects of these interventions for students, clinicians and commissioners to make evidence-based decisions about the provision of mental health support at university. Whilst widely accessed, it is unclear whether yoga, mindfulness, or meditation have a beneficial effect on mental health or academic achievement in young adults beyond placebo.

This systematic review and meta-analysis aims to study the effectiveness of both yoga and mindfulness-based interventions on stress, depression, anxiety, and academic achievement for students in tertiary education.

Research Question

What are the effects of mindfulness, meditation, and yoga on depression, anxiety stress and academic achievement in tertiary education students vs. control?

Study Design

This study utilized a systematic review and meta-analysis in order to answer the above research question.

Participants, Interventions, Comparators, Outcomes

Included studies were randomized controlled trials, published in English, in which a meditation, yoga or mindfulness intervention was compared to an active or non-active control group (wait-list, treatment-as-usual, placebo or active treatment control). Participants had to be enrolled in tertiary education when they were randomized into treatment group in the study (i.e., a university, college or other postsecondary higher education). Studies in which measured depression, anxiety, stress (i.e., Beck Depression Inventory (BDI), the State-Trait Anxiety Inventory (STAI), academic achievement (i.e., productivity, GPA, absenteeism) or a combination of these, as measured via a validated questionnaire were included. Additionally, enough information needed to be provided to calculate the effect size. We contacted authors when we were unable to calculate effect sizes based on the information provided in the paper.

Systematic Review Protocol

The procedure for this systematic review is outlined according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P) guidelines ( 30 ).

Search Strategy and Data Sources

Publications were identified by searching Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, and PsycINFO by combining terms (text words, MeSH terms and subject headings) on (1) student population, (2) psychological interventions, (3) mental health or academic outcomes, and (4) randomized controlled trials. We conducted the searches on 27.04.17. We included studies with any date of publication which were either published, under review or “in press.” We contacted authors of study protocols that were suitable for inclusion to assess whether any unpublished results were available for inclusion. The search string can be found in Appendix 1 in Supplementary Material. Additionally, we searched for references in prior meta-analyses and included studies until 02.03.18.

Study Selection and Data Extraction

Study selection.

Titles and abstracts of articles identified through the database search were screened by two independent researchers. The researchers coded all retrieved results to separate categories, including one pool of “alternative medicine” studies. Please see Appendix 2 for an overview of study coding procedures. From the alternative medicine study pool, studies were coded as yoga, mindfulness or meditation and these were then retrieved for full-text screening. In this second step full texts of all studies that were deemed suitable were retrieved and reviewed for eligibility by two researchers (JB and YA). When there was any disagreement the authors convened for a discussion; senior researchers (DE or PC) were consulted if disagreement could not otherwise be resolved. Figure 1 shows the PRISMA-P flow chart.

Figure 1 . Prisma-P flow chart.

Data Extraction

A standardized electronic data collection form following Cochrane Good practice guidance was used to extract data. The following variables were extracted: (1) bibliographical data, (2) study design, (3), sample characteristics (e.g., gender, % female, ethnicity), (4), intervention type (mindfulness, MBSR, yoga, meditation) (5) exposure to the intervention [e.g., duration of each session, duration of home practice, length of intervention period (weeks)]. Exposure was calculated as the duration of meditation each week (in session and home practice) (in minutes) × length of intervention (weeks). (6) Setting (country), (7) intervention modality (e.g., face to face, online, group setting) (9) outcomes (depression, anxiety, stress, academic achievement), and (10) drop-out and handling of missing data. Two reviewers (JB and YA) independently extracted the study data and resolved any discrepancies by consulting a third reviewer (MH). When studies conducted assessments for the above outcomes during an exam and in non-exam settings, we extracted the non-exam setting only. Please see Table 1 for an overview of interventions and intervention descriptions.

Table 1 . Definitions of intervention categories.

Risk of Bias

Two researchers assessed the risk of bias (JB and YA), which was extracted using an approach based on the Cochrane Collaboration risk of bias assessment criteria for RCTs described by Furlan et al. ( 34 ). The criteria were: (1) random sequence generation, (2) allocation concealment, (3) blinding of participants, (4) blinding of personnel, (5) blinding of outcome assessors, (6) incomplete outcome data, (7) selective outcome reporting (which was established searching for the protocol on PubMed and Google Scholar and assess discrepancies between included outcomes and reported outcomes, if no protocol was available we examined the methods for any unreported outcomes), (8) serious flaw. Studies were scored as “low,” “high,” or “unclear” risk of bias on each of these domains. If the researchers scored six criteria as “low” and if there were no serious flaws detected, the study was scored to have a low risk of bias.

Researcher Allegiance

For researcher allegiance assessment, the reprint approach with criteria operationalized to assess the “belief [of the investigators] in the superiority of a treatment [and] … the superior validity of the theory of change that is associated with the treatment” was applied ( 35 ). A six-point rating scale indicating various degrees of risk for researcher allegiance derived and adapted from Wampold et al. ( 36 ) was used.

Convenience Sampling Rating

We defined studies as employing convenience samples when either: (1) the sample only contains students of the investigators institute, (2) the sample was recruited through an internal study recruitment system used for the recruitment of research participants, (3) course credit was given, or (4) the article states a convenience sample was used.

Data Analysis

Comprehensive Meta-Analysis (CMA) software (Biostat, Inc.) and STATA version 15 were used for the analysis ( 37 ). For each study included in the quantitative analysis, between-group effect sizes between intervention and control group at post-intervention were calculated (Hedges' g ). For the main outcome analysis, three separate analyses were conducted to quantify the effects of studies on depression, anxiety, and stress. In the case of multiple treatment groups, the mean effect sizes were pooled for each study. When studies only recorded outcomes taken during an exam, we extracted these and conducted a sensitivity analysis to assess whether results were comparable.

A random effects model was used to pool effect sizes as we expect considerable heterogeneity amongst studies ( 38 ). To improve clinical interpretation, g -values were converted into the numbers-needed-to-treat (NNT) using Furakawa's method ( 39 ). The assumed response rate (50% reduction in symptoms) in the control group was 19% ( 40 ). The response rate was estimated from studies that assessed psychotherapy for depression and we assumed similar rates could be achieved in these studies. The NNT reflects the number of participants that need to receive the intervention in order for a positive outcome for one participant ( 41 ). 95% confidence intervals and two-sided P -values for each outcome were calculated.

The I 2 statistic was used to determine heterogeneity ( 42 ). I 2 heterogeneity of 25% was deemed low, 50% moderate, and 75% as substantial heterogeneity ( 43 ). The 95% confidence intervals were calculated using the STATA module heterogi ( 44 ). In this, a non-central chi-square based approach was used. Sensitivity analyses were conducted to assess whether study quality was related to effect sizes by comparing studies indicating a low risk of bias with all other studies. In addition, we examined the association between researcher allegiance, the use of a convenience sample and the treatment effects. Publication bias was tested by inspection of the funnel plot on primary outcome measures. Egger's test, a test for asymmetry of the funnel plot, was performed to attain quantitative results on publication bias ( 45 ).

When funnel plot inspection or Egger's test suggested the presence of bias, we applied the Duval and Tweedie trim and fill-procedure. This procedure estimates the number of missing studies and adjusts the effect size accordingly to attain a more unbiased estimate of the pooled effect size ( 46 ).

Subgroup Analysis and Meta-Regression

Subgroup analyses and bivariate regression analyses were conducted to explore the following moderators; type of control, researcher allegiance, risk of bias, country of study, intervention type, exposure of intervention [duration of meditation each week (in session and home practice) (in minutes) x length of intervention (weeks)], and delivery of intervention (therapist, group, self-help).

Selection and Inclusion of Studies

After screening 11,936 abstracts, 181 studies were retrieved and coded. Of these 181 studies, 58 studies covered a meditation, yoga or mindfulness intervention. Subsequently, we identified 24 studies as fitting our inclusion criteria, for further detail on study selection, please see Figure 1 .

Study Characteristics

Out of 24 included studies in both the quantitative and qualitative analysis, nine were conducted on the North American continent, 12 in Asia, and three in Europe. Eighty-three percent of participants were female. All studies used a “convenience sample” and most studies were conducted with participants from a medical faculty ( N = 14). With regards to symptom levels in the sample, only one study excluded participants with low scores on the Penn State Worry Questionnaire ( 47 ). All other studies were aimed at a healthy or subclinical population. A further overview of study characteristics can be found in Table 2 .

Table 2 . Study characteristics.

Out of 24 studies, the average rating of research allegiance was 2.63 and three studies scored 5/5. Eight studies provided information on ethnicity, of these, most participants were Caucasian (68%, N = 484), followed by Asian (12%, N = 88) and African/ African American (10%, N = 72).

The average length of the intervention was ~7 weeks. On average, participants practiced meditation yoga or mindfulness for 153 min each week, totalling to overall average exposure at 19 h and 36 min. All studies but two were offered in a group setting, with two offered as self-help, one of these approaches was an internet-based intervention. Four treatment-control comparisons utilized an active control, 10 studies used wait-list control and 10 provided no treatment. Please see Table 3 for a further specification of intervention characteristics.

Table 3 . Intervention characteristics.

In two comparisons symptom scores were higher in the intervention group at post-test. In one case this was when the intervention was compared to an inactive control ( 69 ). In the other, the intervention performed worse compared to an active control ( 66 ). No studies reported any further adverse effects.

Synthesized Findings

In the quantitative analysis, we included a total of 23 studies. The studies included 1,373 participants with 660 in the intervention and 713 in control. For the quantitative analysis, we could not include academic outcomes as there were only two eligible studies reporting these ( 54 , 61 ). The study by Paholpak et al. ( 61 ) assessed breathing meditation on memory, academic functioning and psychiatric symptoms in medical students ( N = 58). No significant difference was found between intervention and control group (effect size and significance here). Nemati ( 54 ) did find a significant difference between intervention (pranayama yoga) and control ( N = 107) on academic functioning (effect size and significance here). Test anxiety (i.e., anxiety related to performing a particular test) was measured in two studies ( 50 , 54 ). We thought the sample too small to pool in a sensitivity analysis and a further analysis was not conducted.

The overall post-treatment effect in the 23 comparisons between yoga and mindfulness-based therapies and control groups was g = 0.61 (95% CI: 0.40–0.81) with an NNT of 5 (please see Table 4 ). The heterogeneity was high ( I 2 = 74%, 95% CI: 61–83). Three studies were potential positive outliers with an extremely high effect size (g >1) ( 53 , 55 , 56 ). After exclusion of these studies, the effect size decreased to g = 0.42 (95% CI: 0.31–0.52), NNT = 7 for depression, anxiety, and stress combined. Heterogeneity also decreased substantially ( I 2 = 6%, 95% CI: 0–40).

Table 4 . Effects of meditation based interventions on depression, anxiety, and stress compared to control with Hedges g .

Five studies had more than two groups. Three studies used a second “active control” (relaxation, bio-feedback or dog therapy) condition aside from a no treatment control ( 49 , 66 , 67 ) and one study included two versions of yoga ( 56 ). A further study compared the effects of mindfulness or yoga techniques to control ( 47 ) (hatha yoga and body scan vs. wait-list control). Including multiple groups in the analysis may artificially reduce heterogeneity and thus introduce bias. To address this, we conducted an analysis where we first only included the study with the strongest effect size. A second analysis only included the lowest effect size. As Table 4 shows, effect sizes were similar, and heterogeneity increased ( I 2 high = 0% (95% CI: 0–48%), I 2 low = 16% (95% CI: 0–51).

Effects of Mindfulness and Yoga Interventions on Depression, Anxiety and Stress

Ten studies reported a depression outcome, 15 anxiety, and 10 stress. Figure 2 shows three forest plots on the separate outcome categories. Considering outcomes for depression, anxiety, and stress separately, the mean effect size for depression was g = 0.42 (95% CI: 0.16–0.69, I 2 = 62%, 95% CI: 24–81), anxiety g = 0.46 (95% CI: 0.34–0.59, I 2 = 0%, 95% CI: 0–54), and stress g = 0.42 (95%CI: 0.27–0.57, I 2 = 5%, 95% CI: 0–64), respectively. There was no significant difference between these outcome categories in subgroup analysis ( p = 0.41). Because depression, anxiety, and stress are highly interrelated and moderator characteristics were evenly distributed across outcomes, we conducted further subgroup analyses with pooled effect sizes across depression, anxiety, and stress outcomes.

Figure 2 . Forest plot for intervention effects on anxiety, depressing and stress symptoms with Hedges g.

Long Term Follow-Up

Six studies provided long term follow-up data (i.e., any assessment after post-intervention) ranging between 1 and 24 months. The pooled effect size was small to medium g = 0.39 (95% CI: 0.17–0.61), and heterogeneity was low ( I 2 = 11%, 95% CI: 0–77).

Subgroup Analysis

We conducted several subgroup analyses, for all results please see Table 4 . Stronger effects were found when questionnaires were taken during an exam setting. When compared to active and inactive controls, the continent in which the study was conducted was not associated with effect size ( p = 0.06). However, when we compared the effects to no-treatment control, we did identify a significant effect ( p = 0.03), with studies conducted in Asia g = 0.54 (95% CI: 0.34–0.74) yielding strongest effects compared to America g = 0.49 (95% CI: 0.34–0.64), and Europe g = 0.13 (95% CI: −0.13 to −0.39). A subgroup analysis which compared yoga, mindfulness meditation, and MBSR did not find any significant subgroup differences between the intervention types.

Meta-Regression Analyses

We conducted regression analyses on research allegiance, exposure to intervention, and overall Risk of Bias score. As a result, we did not find any significant explanatory value in these variables. Research allegiance (coefficient: 0; 95% CI: −0.11 to 0.08; p = 0.76) or the exposure to mindfulness, meditation or yoga (coefficient: 0; 95% CI: 0–0; p = 0.50). A further bivariate regression analysis on total RoB score and effect size did not identify significant subgroup differences either (coefficient: 0; 95% CI: −0.08 to 0.09; p = 0.91).

Overall, only one study was scored to have a low risk of bias ( 60 ). Most studies had an unclear risk of selection bias. Six studies reported adequate sequence generation, the remaining studies did not report methods or used inappropriate methods. Adequate blinding of participants and personnel was rare. None of the studies adequately blinded participants, which is common amongst psychological research trials. Two studies reported that outcome assessors were blinded and three reported blinding of personnel. Only four studies reported conducting an ITT analysis. In other studies, this was either unclear or a completer analysis was conducted. See Table 5 for an overview of the risk of bias assessments.

Table 5 . Risk of Bias.

We conducted subgroup analyses on each risk of bias category but did not identify any significant association between the risk of bias and effect size. A subgroup analysis comparing “high” and “low” risk did not identify a significant difference p = 0.80. A further bivariate analysis on total risk of bias score and effect size did not identify significant subgroup differences either (coefficient: 0; 95% CI: −0.08 to 0.09; p = 0.91). Because almost all studies had a high risk of bias we were unable to assess the impact of risk of bias on the outcomes as we had too little power to identify differences between the groups.

Publication Bias

A visual inspection of the funnel plots for three separate outcomes ( Figure 3 ) indicated no indication for publication bias for depression and anxiety but some risk of publication bias for the effects of mindfulness, yoga and meditation interventions on stress. Duval and Tweedie's trim and fill procedure under the random effects model did not impute any study effects, and the mean effect size remained unchanged except for studies assessing the effects of the intervention on stress from g = 0.44 (95%CI: 0.28–0.59) to g = 0.34 (95%CI: 0.16–0.51). The Egger's test did not find evidence for significant asymmetry of the funnel plot ( p = 0.12; Intercept: 1.47, 95% CI: −1.25 to 4.18).

Figure 3 . Visual inspection of the funnel plots for stress, anxiety, and depressive symptoms.

Summary of Main Findings

In this study, we set out to assess the efficacy of mindfulness, meditation, and yoga on student mental health and academic achievement. This is the first study to assess the effects of meditation-based interventions in this population across all outcomes specified above.

We found moderate positive effects for mindfulness, yoga or meditation-based interventions on symptoms of depression, anxiety, and stress, however, the quality of the studies included in this review was low.

Subgroup analyses did not identify any differences were between yoga, mindfulness or meditation interventions. Two studies collected academic achievement data, making it impossible to render conclusions on the effects of such interventions on academic achievement. Similar to other reviews on mindfulness in this population, there were few studies with a long term follow up ( 23 ).

Comparison to Previous Literature

When comparing our results to the previous literature on other interventions such as CBT or exercise, we find few studies that cover the same age range, inclusion criteria, similar outcomes and vs. similar controls.

From the few comparisons that we are able to make, we find that effects for CBT and exercise in non-clinical populations are more similar to our results compared to effects found in clinical interventions. A recent meta-analysis on preventative interventions for depression found g = 0.53 (95% CI: 0.38–0.68) for CBT ( 70 ). The effects of CBT on anxiety in a mixed (clinical and non-clinical population) are also within the range of our results g = 0.43 (95% CI: 0.14–0.73) ( 71 ). Effects of exercise on depression in non-clinical adolescent populations compared to control were not significant d = −0.52, (95% CI: −1.30 to 0.26) ( 72 ). For clinical populations, we identified slightly larger effect sizes for psychological treatment g = 0.89 (95% CI: 0.66–1.11) ( 73 ) and for exercise on depression g = −0.72, (95% CI: −1.15 to −0.30) ( 74 ).

In contrast, internet interventions for clinical and non-clinical populations overall had lower effects for depression g = 0.18, (95% CI: 0.08–0.27), anxiety g = 0.27 (95% CI: 0.13–0.40), and stress g = 0.20, (95% CI: 0.02–0.38) ( 75 ). Finally, comparing these results to mindfulness in students, mindfulness had somewhat similar effects depression in a previous analysis in a non-clinical sample g = 0.31 (95% CI: 0.15–0.42) ( 70 ). In another meta-analysis amongst healthy individuals, MBSR showed higher effect sizes across stress g = 0.74 (95% CI = 0.41–1.07), depression g = 0.80 (95% CI = 0.49–1.12), and anxiety g = 0.64 (95% CI: 0.33–0.94). However, across outcomes a subgroup analysis found more similar results for students g = 0.47 (95% CI = 0.30–0.64) ( 76 ).

To summarize, it seems our results are somewhat more in line with studies conducted in non-clinical samples compared to a clinical sample. Due to the heterogeneity found in the meta-analytic literature, it is not yet possible to compare exercise vs. mind-body interventions in a vis-à-vis manner although the above might give an indication of the comparative effectiveness of interventions.

Other similarities with previous include the high risk of bias which was similarly high in reviews on yoga ( 18 , 77 ), exercise and psychotherapy ( 73 , 74 ). A mixed risk of bias was found for internet interventions ( 75 ), it might be that such interventions carry a slightly lower risk to bias as blinding of participants and personnel might be easier compared to a face to face intervention.

Other similarities with previous include the high risk of bias which we noted, which was similar to reviews on yoga ( 18 , 77 ), exercise and psychotherapy ( 73 , 74 ). A mixed risk of bias was found for internet interventions ( 75 ), it might be that such interventions carry a slightly lower risk to bias as blinding of participants and personnel might be easier compared to a face to face intervention.

In addition, no adverse events were recorded and intervention elements were inadequately reported on, which is a common feature of the evidence base for yoga and meditation ( 27 , 77 – 79 ).

Comparison to Active Controls

In line with prior research on meditation programs, there was no evidence that meditation, yoga or mindfulness was more effective than active control ( 52 , 76 , 80 ). We had a limited number of subgroups so were unable to segment our analysis by active treatment (drugs, exercise or CBT) or active non-specific control ( 27 ). All our controls were deemed specific controls and thus are in line with ( 52 ) who found that meditation-based interventions were only more effective when compared to non-specific active control.

Research on psychotherapy in a similar population found that effects were also not more effective compared to active (specific) control ( 73 ). For exercise, these interventions were more effective compared to placebo control although further comparison with specific controls was not possible ( 74 ). Similar results were found for interventions ( 75 ) and other mental health interventions ( 81 ). The above summary indicates that the results are in line with previous research on both mindfulness and meditation interventions and behavioral interventions. As far as we are aware, we have not yet identified similar comparisons to specific or non-specific control conditions as detailed in Goyal et al. ( 27 ) for behavioral interventions, which would be an interesting element to explore in future research.

Length and Duration

We did not find that the number of hours of meditation, yoga, and mindfulness is associated with effect size. Other meta-analyses on internet interventions did not find an effect on treatment length (weeks) ( 75 ). Meta-analyses with a majority of interventions based on CBT did find that interventions with a longer duration (hours) were associated with effect size ( 71 , 81 ). In our analysis, we included both home practice as well as treatment duration, whilst the above analyses only specified the amount of treatment, this difference in coding might have altered our results. Also we were not always able to exactly specify the amount of home practice, which might again affect the validity of our result.

Limitations

In contrast to psychotherapeutic interventions, there remains a substantial degree of uncertainty about the robustness of our effect. Our study found that most studies were of lower quality and those improvements to reporting and procedures of studies in this area are required. High risk of bias is a concern as this impacts the validity of the findings and our confidence in making any conclusions from our analysis ( 82 ). Whilst risk of bias was not associated with effect size, this might be due to low power to detect such a difference. Due to the high risk of bias in most studies, it is difficult to determine the true value of these approaches and more rigorous research is clearly needed to assess for improving mental health in tertiary education. Whilst the quality of studies across behavioral interventions is low, we note that there are specific elements to meditation, yoga and mindfulness interventions that warrant improvement.

We found that intervention effects diminished when compared to active control, which implies that non-specific intervention elements such as peer-support, or activity scheduling, might have driven our results. To further study the differential effect of mindfulness, meditation, and yoga, a comprehensive typology of intervention elements is necessary. A shared understanding of differential intervention elements will allow development of adequate placebo control conditions to identify whether the contribution of mindfulness, meditation or yoga improves mental health or whether they are equally effective as non-specific placebo interventions.

Interestingly, we did not find an association between the exposure to yoga, mindfulness or meditation through treatment or home practice and effect size. This is surprising given the premise that yoga and mindfulness are seen as practices that improve over time ( 83 ). One might then expect to see a positive association between the amount of recent mindfulness practice and effect sizes. There is a caveat however as the amount of home practice was not always reported on consistently, thus due to a lack of clear reporting, we may have been unable to accurately estimate the exposure to such interventions.

Conclusions

To improve the evidence base, the conduct and reporting of studies on meditation, yoga, and mindfulness needs to be more rigorous to allow the delivery of results that are closer to their empirical truth. Furthermore, we recommend that a common typology for meditation, yoga and mindfulness interventions is developed and that future research includes comparisons between active placebo and control. This will allow us to determine the true differential effects between mindfulness, meditation, and yoga and in comparison, to other approaches to improve mental health. Ultimately, this will allow us to further our understanding of delivering effective non-clinical solutions for protecting and promoting mental health in student populations.

Author Contributions

JB selected and extracted the studies, conducted the analysis, prepared tables and prepared the first draft for review. YA selected and extracted the studies and prepared the tables for the first draft. Revising work critically for important content and accuracy. MH led on data acquisition and design of the work. Contributed strongly to the methods section and revised work critically after the first draft was prepared. EK led on conception and design of the work. Critically revised the first and second draft for accuracy and intellectual content. SG critically revised for intellectual content and reviewed first and second draft. Contributed to analysis plan. CB critically revised for intellectual content and contributed to plan of analysis. PC led on conception and design and provided support with analytical decisions in analysis stage critically reviewed the first and second draft for intellectual and conceptual relevance. DE led on conception and design of the work, critically revised the first and second draft for intellectual and conceptual relevance.

Conflict of Interest Statement

JB is employed by the Mental Health Foundation which offers an online Mindfulness Based Cognitive Therapy course titled BeMindful. She is not directly affiliated to the delivery or development of this programme.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank the Mental Health Foundation for their contribution to the publication fee.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2019.00193/full#supplementary-material

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Keywords: tertiary education, meditation, yoga, mindfulness, anxiety, depression, stress, university

Citation: Breedvelt JJF, Amanvermez Y, Harrer M, Karyotaki E, Gilbody S, Bockting CLH, Cuijpers P and Ebert DD (2019) The Effects of Meditation, Yoga, and Mindfulness on Depression, Anxiety, and Stress in Tertiary Education Students: A Meta-Analysis. Front. Psychiatry 10:193. doi: 10.3389/fpsyt.2019.00193

Received: 03 December 2018; Accepted: 18 March 2019; Published: 24 April 2019.

Reviewed by:

Copyright © 2019 Breedvelt, Amanvermez, Harrer, Karyotaki, Gilbody, Bockting, Cuijpers and Ebert. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Josefien J. F. Breedvelt, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Effectiveness of a short Yoga Nidra meditation on stress, sleep, and well-being in a large and diverse sample

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• Volume 41 , pages 5272–5286, ( 2022 )

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• Esther N. Moszeik   ORCID: orcid.org/0000-0002-3490-5743 1 ,
• Timo von Oertzen 1 &
• Karl-Heinz Renner 1  

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Previous studies have shown that meditation-based interventions can have a significant impact on stress and well-being in various populations. To further extend these findings, an 11-min Yoga Nidra meditation that may especially be integrated in a busy daily schedule by people who can only afford short time for breaks was adapted and analyzed in an experimental online study design. The effects of this short meditation on stress, sleep, well-being and mindfulness were examined for the first time. The meditation was provided as audio file and carried out during a period of 30 days by the participants of the meditation group. A Structural Equation Model (SEM) was used to analyze the data with Full Information Maximum Likelihood (FIML) in order to cope with missing data. As expected, the meditation group ( N  = 341) showed lower stress, higher well-being and improved sleep quality after the intervention (very small to small effect sizes) compared with a waitlist control group ( N  = 430). It turned out that the meditation had a stronger impact on the reduction of negative affect than on the increase of positive affect and also a stronger effect on affective components of well-being. Mindfulness, as a core element of the meditation, increased during the study within the meditation group. All effects remained stable at follow-up six weeks later. Overall, a large, heterogeneous sample showed that already a very short dose of meditation can positively influence stress, sleep, and well-being. Future research should consider biological markers as well as active control groups.

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“No time to live?” is the name of a bibliography by Müller ( 2012 ) in which he takes the value of time and moment philosophically and in relation to our current performance requirements. Awareness of the present moment is also a nucleus of mindfulness and meditation. The present study examined a short form of Yoga Nidra meditation that was designed to relax without big time investments or prior meditation experience. Yoga Nidra is traditionally carried out while lying down and consists of a systematic sequence of perception exercises, e.g., focusing on the breath or certain parts of the body. It has been increasingly examined in recent years regarding the effects on stress (e.g., Borchardt et al. 2012 ; Dwivedi and Singh 2016 ), sleep (e.g., Amita et al. 2009 ) and well-being (e.g., Bhogaonker 2012 ; Rani et al. 2011 ). Extant research seems promising but randomized controlled trials and larger samples are rare (e.g., Deuskar 2011 ; Rani et al. 2013 ). In addition, a standard Yoga Nidra session usually takes about 30 min. However, since this is already too long for many people, the meditation has been shortened to eleven minutes for the present study and has been empirically investigated for the first time in this form. The intervention was administered as an audio file which was presented online. Particularly those people who can only afford short time for breaks were addressed in this way. Mindfulness as the main mechanism of the meditation is negatively related to various dysfunctional variables that may emerge due to work-related stress, e.g. burnout or depression (e.g. Roche et al. 2014 ).

Meditation-Based Interventions and Mindfulness

When we consider the word meditation semantically, it means reflection . In everyday life, the word meditation is mostly associated with different spiritual practices (e.g., Chiesa and Malinowski 2011 ). In psychotherapy, meditation is increasingly applied as a method in cognitive-behavioral approaches, especially in a recent approach called mindfulness-based cognitive therapy (e.g., Kuyken et al. 2010 ). In general, meditation is primarily used to effectively relax patients and to reduce negative thoughts, anxieties or constraints (e.g., Ellis 2009 ). In Yoga, meditation can be carried out in motion, while sitting quietly or lying down. In addition, a core element of Yoga and many other forms of meditation is focusing on an “object”, e.g., the breath, for a certain time. Traditionally, the body is first detached from tensions, the breath consciously steered, the attention directed inwards from the sensory impressions, and finally, through concentration on an object, one reaches a state of meditation, which is characterized by deep insight and centering. An important feature of this condition is associated with an expansion of alpha-waves in the brain that reflects a state of deep relaxation (e.g., Parker et al. 2013 ). They decrease by visual or mental activity (Prakashananda 2010 ) and are more intensified when the person is temporarily not active but awake and alert (Desai et al. 2015 ).

A core component of meditation is mindfulness. It includes an orientation to the present moment and represents a specific form of non-judgemental attention (e.g., Kabat-Zinn 2003 ). The principle of mindfulness stems from Buddhist philosophy and has not only been used to deliberately relax, but also to develop personal values and an attentive attitude towards life. A mindful person is focused on the present moment without evaluating it and he or she is not distracted by the past and the future. In the words of the Dalai Lama ( 2012 ), mindfulness implies a conscious use of the mind . As so brilliantly titled and empirically underpinned by Killingsworth and Gilbert ( 2010 ), a wandering mind is an unhappy mind , even if they are pleasurable thoughts to which it drifts. In recent years, mindfulness has been explored as the key mechanism of meditation-based interventions (Sedlmeier et al. 2012 ) with mindfulness-based stress reduction (MBSR, e.g., Chiesa and Serretti 2009 ; Grossman et al. 2004 ; Kabat-Zinn 2003 ) being the bestseller-approach in this area. Much of the empirical research in the Western world has examined the effects of meditation on self-regulation (e.g., Shapiro 2009 ). It is argued that mindfulness promotes self-regulation by interrupting the so-called “autopilot”, i.e. automatic thoughts and behavior patterns, and thereby fostering self-determined and flexible reactions (e.g., Brown and Ryan 2003 ). Furthermore, perceiving the current moment without judging makes it possible to change the perspective and to recognize as well as to adapt important reaction patterns: “Reperceiving is seen as a meta-mechanism that allows meditators to stand back and witness their own thoughts and experiences instead of being immersed in them” (Sedlmeier et al. 2012 , p. 1144). Thus, the identification with thoughts and emotions is also to be modified in such a way that they are not perceived as part of the self, but as transitory, mental events (Lou et al. 1999 ; Satyananda Saraswati 2009 ). Therefore, mindfulness can promote a salutary treatment of thoughts, feelings and actions (Michalak et al. 2008 ).

Yoga Nidra was developed by Swami Satyananda Saraswati in 1976 as a relatively easy-to-learn meditation to be used by people of various backgrounds and cultures and independent of previous knowledge (Satyananda Saraswati 2009 ). The heart of Yoga Nidra meditation is a personal resolution, Sankalpa (Sanskrit for “intention, resolution”), that addresses a topic important to the person and that affects him or her in a positive way. This intention is put into a simple, short and positive sentence which will be repeated in the beginning and end of the meditation (e.g., “I am calm and relaxed” or “I am successful”). The purpose of this resolution is to train the unconscious to sustainably achieve the desired state through regular mental repetition. Studies that used such intentions during meditation have shown that cognitive restructuring processes are stimulated (e.g., Sedlmeier et al. 2012 ). For people who regularly practice Yoga Nidra, the realization of this intention is more important than pure relaxation. However, relaxation is a crucial prerequisite for giving the body and mind the opportunity to resolve underlying tension. For this purpose, Yoga Nidra contains a systematic sequence of body awareness and breathing exercises that can activate the parasympathetic nervous system and increase the amount of alpha-waves in the brain (e.g., Mandlik et al. 2002 ).

In the U.S., the concept of Yoga Nidra has been further adapted by the psychologist Richard Miller ( 2005 ) under the name iRest for western practitioners and has been used especially for the improvement of mental well-being. The iRest community has enjoyed increasing attention in recent years and offers an overview of current research on https://www.irest.us/research . Empirical studies on Yoga Nidra confirm positive effects on various physiological and psychological criteria such as insomnia, addictive behavior, chronic diseases, pain therapy, pregnancies, geriatrics, asthma as well as disorders of the cardiovascular system (e.g., Satyananda Saraswati 2009 ). Not only based on self-reports, but also by imaging techniques such as positron emission tomography (PET) and electroencephalography (EEG), sustained changes in the activation of the brain were recorded (e.g., Lou et al. 1999 ; Mandlik et al. 2002 ;). As examples for qualitative studies and case studies Datta et al. ( 2017 ) show positive effects of Yoga Nidra on chronic sleep disorders and several others find positive effects on PTSD (posttraumatic stress disorder) for veterans (e.g. Stankovic 2011 ) and women with sexual assault experience (e.g. Pence et al. 2014 ). It should, however, be noted that the sample sizes in these studies were partly very small or did not include control groups. In most cases information on the dependent variables or the intervention was poor or missing.

The Effects of Yoga Nidra on Stress, Well-Being, and Sleep

Yoga Nidra is already prescribed by scholars in several countries because of its potential to activate the parasympathetic nervous system and positively influence stress-related parameters such as skin conductivity and cortisol level (e.g., Kumar and Joshi 2009 ; Prakashananda 2010 ). This down-regulation of hyper-arousal may also contribute to increasing positive and decreasing negative affect and thus would also have an impact on the emotional components of well-being (Diener et al. 1999 ). Furthermore, Kjaer et al. ( 2002 ) found out that Dopamine is released whilst practicing Yoga Nidra, which can also stimulate positive affect and increase motivation.

In addition to purely relaxing and emotional effects, cognitive restructuring may occur as well, since a personal intention is used at the beginning and end of the meditation as mentioned above (e.g., Sedlmeier et al. 2012 ). A personal intention may be compared with positive self-instructions often applied in cognitive-behavioral therapy as well as in stress inoculation trainings (Meichenbaum 1985 ) in order to counteract the detrimental effects of dysfunctional cognitions. The detachment from such dysfunctional cognitions may also be fostered by the meta-mechanism of reperceiving described above. Potential positive changes on the cognitive level may then also influence life satisfaction and thus the cognitive component of subjective well-being (Diener et al. 1999 ).

Yoga Nidra was explained by Satyananda Saraswati ( 2009 ) as an activity or state of “conscious sleep” and is thus characterized by positively influencing the quality of sleep and – in its standard 30-min length – even said to compensate for lack of night sleep (e.g., Satyananda Saraswati 2009 ). Schulz et al. ( 2003 ) consider that an increased level of arousal is responsible for sleep disorders that have dramatically increased in recent years (e.g., Colten and Altevogt 2006 ; Lohmann-Haislah 2012 ). Meditation-based interventions can lower the level of arousal and thus positively affect sleep (e.g., Hülsheger et al. 2015 ; Klatt et al. 2009 ; Winbush et al. 2007 ).

As has been described above, there are several empirical studies that have already shown positive effects of Yoga Nidra on stress, well-being, and sleep (e.g., Bhogaonker 2012 ; Borchardt et al. 2012 ; Rani et al. 2013 ), some of which, however, only used very small samples or no control group. The present study aims at replicating these effects with a newly developed short form of Yoga Nidra meditation and at extending them to a large and diverse sample, employing a randomized waitlist control study design. The importance of replication and availability of larger samples is highlighted for appropriate generalization. A distinctive feature of our study is the use of an online administered audio file of the 11-min meditation. According to previous studies, interventions with a focus on relaxation reached small to medium effect sizes (e.g., Bhogaonker 2012 ; Eastman-Mueller et al. 2013 ; Pence et al. 2014 ). It is therefore expected that practicing eleven minutes of Yoga Nidra per day over a period of one month will lead to significant changes with at least small effect sizes. Most Yoga Nidra interventions focused on a meditation period of more than one month and emphasized a daily practice with personal training sessions (e.g., Kumar 2010 ; Rani et al. 2013 ; for a comprehensive overview see Moszeik 2016 , 18–21). As the present study aims to provide results for a period of only one month of practice and even referring to a short form of Yoga Nidra, which was completely administered online, we only expected small effect sizes. These effects should also remain stable over a medium-term period of six weeks. In particular, we tested the following hypotheses: compared to a waitlist control condition, practicing Yoga Nidra meditation eleven minutes a day for one month will…

…reduce stress and negative affect (NA; one of the emotional components of well-being) and

…improve positive affect (PA; the other emotional component of well-being), satisfaction with life (the cognitive component of well-being), sleep quality as well as mindfulness.

The Present Study

This study is the first to examine the effects of a newly developed short-form of Yoga Nidra that was independently conducted by each of the participants using an audio file. Instructions and data collections were carried out via EFS Survey, hosted by Unipark ( www.unipark.com ); the audio file with the Yoga Nidra meditation was provided via download link. A pilot study was conducted with five volunteers to clarify instructions, feasibility and to optimize the meditation (e.g. pauses and speed). The effect of this short meditation on stress, sleep, and well-being is compared with a randomized waitlist control condition in a large German sample, using a Likelihood Ratio test (LRT) in an ANOVA-style structural equation model.

Participants

There were no eligibility or exclusion criteria for selection of participants, rather the authors made advertising for participation in the snowball principle. Headline of the study was the slogan “Mind full or Mindful?”, anyone who felt addressed by this claim and who was interested in an easy-to-learn and short meditation could sign up for the study. Furthermore, it was highlighted that the time investment for participants would be only eleven minutes daily and no experience with meditation was needed. 859 participants registered on the study’s website. Participants were randomly assigned to one of two conditions automatically by Unipark software. In total, the following analyses include 341 participants in the meditation and 430 in the control condition. The age of the total sample of 771 participants ranged from 19 to 71 years ( M  = 38; SD  = 10.59). 575 participants were female (79.9%), 145 male (20.1%). Most of the participants were employees ( N  = 364, 51.4%), 379 people worked full-time (53.3%), 189 part-time (26.6%). In addition, 187 participants (26%) were active as managers in executive positions. Further demographic details can be found in Table 1 . The reduction from 859 to 771 valid cases was due to incorrect email addresses and double answers.

The study was carried out in accordance with the recommendations and ethical guidelines of the German Psychological Society and received a positive ethical approval of the Institutional Review Board of Universität der Bundeswehr München. All subjects participated anonymously and voluntarily and could quit their participation whenever they wanted without any disadvantages.

The study was announced as an online and only 11-min mindfulness meditation, free of charge and accessible without prior experience. Over half of the sample (53.6%) were recruited via the online platform Moodle of the department of psychology at FernUniversität in Hagen which is the only state-maintained distance learning university in Germany. The other participants were recruited by flyers and posters, internet forums (e.g., Facebook, LinkedIn), newsletters, yoga studios, universities, cafeterias, shopping centers, fairs and on the street.

Previous studies have shown that one critical feature of successful online-administered studies could be the supply of personal video clips (e.g., Manthey et al. 2016 ). Therefore, a brief video clip with information on the study (length: 2:20 min) was shown to stimulate adherence. In the clip, the principle of mindfulness was introduced, the intervention presented and the chronological and organizational course of the study explained. It was the aim to motivate and commit subjects to their participation and to help define what really mattered - mindfulness.

The study was conducted in a pre-post-follow-up design with three measurement points. The intervention period between pre-test (t1) and post-test (t2) was 30 days; the follow-up measurement (t3) took place another six weeks later. At t1, participants created their personal, 6-digit pseudonymization code, which was used to anonymously combine the surveys (each the first letter of birthplace, first name, first name of mother and father, second digit of one’s own birthday and last digit of the year of birth). Therefore, it was not possible to identify individuals within the two groups.

The experimental group was informed that they will be given access to the audio file after completion of t1. Participants of the control group were given the information that different intervention waves take place between October 2015 and February 2016 and they would be informed in time when the meditation period begins. During the intervention period, participants of the meditation group received a weekly e-mail including information on certain aspects of the 11-min meditation they could particularly focus on (e.g., counting the breath, the role of observation and advice to find a personal intention). Furthermore, they were asked to indicate the days on which they carried out the meditation. In order to do so, they received a sample protocol (Excel file) to take real-time notes on frequency and general remarks which also included practical information on the body position and adequate surroundings.

11-Minute-Yoga Nidra Audio Intervention

The present short form of Yoga Nidra meditation was developed by the first author and recorded by a professional producer. The first author is a trained instructor for Yoga Nidra, performs the meditation almost daily and teaches it since 2012. Typically, the meditation takes about 30 min. In the present study, the effects of an 11-min short form of Yoga Nidra were tested for the first time. The usual length of the meditation was reduced as follows: The perception of individual body parts and the observation of the breath, the personal intention as well as the observation of thoughts and feelings were integrated. The perception of the body parts was limited to the left and the right side of the body, and did not address further repetitions of the front and back side. The breath was observed for about 20 s, in longer versions it is perceived for an average of two minutes. Additional contents such as the perception of contrary sensations as well as visualizations were excluded as those specifically are more difficult to implement for people with less meditation experience. The main reason for shortening the original form was to address people who have a busy daily schedule and who cannot invest more time for a break. Compared to physical yoga approaches, the present intervention could not cause any harm or injuries. The most important ingredient was mindfulness, which was explained in more detail in the video clip mentioned above. We recommended to carry out the meditation preferably once a day during the 30 days intervention period. Nevertheless, this was only a suggestion based on the literature of Yoga Nidra (e.g., Satyananda Saraswati 2009 ) and we still expected positive effects if carried out less frequently. The only requirement necessary to perform the meditation accurately was access to any form of audio player. No further experience in meditation was needed but if any questions would come up, participants had the chance to contact the first author via e-mail.

Our primary intention was to provide evidence for the effectiveness of this shortened form of Yoga Nidra. Referring to other short meditation-based interventions (e.g., Banks et al. 2015 ) we had a promising basis to expect at least small positive effects of the present meditation format.

Frequency of Meditation

At t2, participants were asked how often they actually performed the meditation during the 30 days intervention period (1 =  all 30 days , 6 =  once ); M  = 3.24 ( SD  = 1.33, N  = 227, due to missing values). 24 participants (10.5%) stated they had completed the meditation on all 30 days, 110 participants (48.1%) on at least every second day. 48 participants (21%) used the meditation on 9–15 days and 36 participants (15.7%) on 2–8 days. Nine participants (3.9%) performed the meditation only once. In addition, we asked at t3 whether the meditation was still used after the official intervention period (1 =  yes, almost every day , 2 = yes, several times a week, 3 = yes, several times a month, 4 = yes, once a month, 5 = yes, less than once a month, 6 =  not anymore ). There was a mean of 4.55 ( SD  = 1.69, N  = 194, due to missing values), with more than half of all participants (51.5%) actually continuing the meditation: Twelve participants (6.2%) stated they would still use the meditation almost every day, 18 participants (9.3%) several times per week, 32 participants (16.5%) several times a month, and 38 participants (19.6%) once or less than once a month. 94 participants (48.5%) didn’t continue using the meditation after the official intervention period.

To measure the self-estimated levels of stress and any changes in the course of the study, the screening scale for chronic stress (SSCS) of the Trier Inventory of Chronic Stress (TICS; Schulz et al. 2004 ) was presented before and after the intervention. The twelve SSCS items capture a global means for experienced stress and can be answered in about three minutes (sample item: “ experience that everything is too much what I have to do”). The participants answered on a 5-point scale (1 = never to 5 = very frequently) how often they experienced the presented situation. The internal consistency in this study showed very good values with α  = .89 for t1 and α  = .92 for t2 and t3. Participants of the present study reported moderate stress levels at t1 which were significantly higher than those of a representative German sample (Petrowski et al. 2012 ) with t (3057) = 20.64, p  < .0001. Petrowski and colleagues also present confirmatory factor analysis (CFA) to test the psychometric properties.

Well-being was assessed by two different scales: First, the two subscales for positive and negative affect of the German version of the Positive and Negative Affect Schedule (PANAS; Watson et al. 1988 ; German version of Krohne et al. 1996 ) were presented. The 20 items capture emotional states and can be answered in about five minutes (e.g.: active, enthusiastic, anxious, irritated). Participants answered on a 5-point scale (1 =  not at all to 5 =  extremely ) how strongly they felt the different emotions in the last four weeks. The internal consistency was very good with α  = .90 for t1, α  = .92 for t2 and α  = .91 for t3. Participants of the present study reported higher positive than negative affect scores at t1, which were distributed in a middle range. The PA scores did differ significantly from scores of a representative German sample (Krohne et al. 1996 ) t (1067) = 11.6, p  < .0001 and can be interpreted higher than average whereas the NA scores did also differ highly significantly as participants in the present study reported higher NA than the average German sample ( t (1067) = 17.32, p  < .0001). Crawford and Henry ( 2004 ) present the CFA to further test the psychometric properties and hypothesized dimensionalities of the scales.

In addition, the five items of the German version of the Satisfaction with Life Scale were retrieved (SWLS; Diener et al. 1985 ; German version of Schumacher 2003 ), which take about 1–2 min to complete. The SWLS records the overall life satisfaction and serves as the cognitive component of well-being on a 7-point scale (1 =  strongly disagree to 7 =  strongly agree ). Sample item: “I am satisfied with my life”. The internal consistency was excellent with α  = .90 for t1 and t2, α  = .92 for t3. Participants of the present study reported moderate-to-high satisfaction with life at t1. These scores differed highly significant compared with a representative German sample (Glaesmer et al. 2011 ) and showed that participants in the present study had lower mean values of satisfaction with life than the German average ( t (3237) = 6.85, p  < .0001). Glaesmer and colleagues also present CFA to test the psychometric properties.

Quality of Sleep

To measure the quality of sleep we used the following six subscales of the German version of the Pittsburgh Sleep Quality Index (PSQI; Buysse et al. 1989 ; German version of Riemann and Backhaus 1996 ): the subjectively perceived sleep quality, sleep latency, sleep duration, sleep disturbances, drug use and daytime sleepiness. Participants could assess their sleep habits on a 4-point scale (0–3). The wording of the response scale varied depending on the question. The selected six components were assessed with a total of 16 items and can be answered in about five to ten minutes, e.g.: “How long did it usually take during the last four weeks before you fell asleep at night?” (sleep latency; 0 =  less than 15 min to 3 =  more than 60 min ); “How many times have you slept badly because you woke up in the middle of the night or early in the morning during the past four weeks?” (sleep disturbances; 0 =  not at all to 3 =  three times or more per week ); “Did you have problems to do the usual everyday tasks with enough drive during the past four weeks?” (daytime sleepiness; 0 =  no problems to 3 =  major problems ). The total value of the PSQI can range between 0 and 18 points in the present study. The higher the value, the more chronic the sleep disorders. The internal consistency was reasonable with α  = .74 for all three measurement points. Participants of the present study reported moderate sleep disturbances at t1. A comparison to a representative sample is not possible as Buysse and colleagues don’t compare mean values but only cut-off values derived from the total score for people who don’t sleep well. The present version with six subscales cannot be compared with those cut-off norms. Zhong et al. ( 2015 ) present the CFA to further test the psychometric properties and hypothesized dimensionalities of the scales.

• Mindfulness

In addition, we assessed the extent of mindfulness with the German version of the Mindful Attention and Awareness Scale (MAAS; Brown and Ryan 2003 ; German version of Michalak et al. 2008 ). The 15 items of the scale are all formulated towards a careless attitude, because according to the authors, states with less mindfulness are more perceptible and less prone to false positive responses. In the sample of the authors, the following three items had particularly high values in the sense of a lack of mindfulness: “I forget the name of a person almost immediately after it was told the first time.”; “I notice that I’m lost in thoughts about the future or the past.”; “I notice that I listen to someone with little attentiveness while I do something else at the same time.” The items are answered on a 6-point scale (1 =  almost always to 6 =  almost never ) and can be answered in about five to ten minutes. The internal consistency of the scale showed very good values with α  = .90 for t1, α  = .91 for t2 and α  = .93 for t3. Participants of the present study reported moderate-to-high mindfulness at t1. These scores didn’t differ significantly compared with a representative sample (Brown and Ryan 2003 ) and showed that participants in the present study had average values of mindfulness at t1 ( t (768) = .24, p  = .81). Brown and Ryan ( 2003 ) also present CFA to test the psychometric properties.

Open Ended Question

In addition to the established quantitative measures, participants had the possibility to describe effects and experiences with the Yoga Nidra meditation in their own words at the end of the online questionnaire. It was pointed out to particularly refer to meditation-related changes over the 30-days intervention period.

Statistical Analyses

We used a Structural Equation Model (SEM) to analyze the data with Full Information Maximum Likelihood (FIML) in order to cope with the missing data. The SEM is shown in Fig.  1 ; it represents a multi-level structure for the repeated measures combined with a two-group model for the two treatment groups. The three measurement points are nested within individuals. This model can be seen as an ANOVA model implemented in a SEM setting. The model was set up using Onyx (von Oertzen et al. 2015 ). The corresponding structural equation for the i th time point of group g is given by

S EM to analyze the data with Full Information Maximum Likelihood (FIML) in order to cope with the missing data. The SEM represents an extended ANOVA design; the latent variables “Treatment”, “Training”, and “Follow up” describe the main effects, where “Follow up” is added in addition to the training effect. “Treat x Training” and “Treatment x Followup” describe the interaction effects. All these effects are modelled as mean effects only. The “Treatment” variable has a residual variance to model the common variance of the treatment group. An analogous variable “Control” provides the common variance of the control group; this variable has no mean so that the mean of treatment provides the additional effect of treatment on top of the grand mean, represented in the latent variable “GM”. Note that all residual variances are allowed to differ between groups and occasion of measurement

where all β are fixed effects, Y g is a group dependent upper-level random effect, and the residuals ε are independently distributed normally with different variances. The parameter β is the grand mean, β t 1 →  t 2 the main effect of the training period, β t 2 →  t 3 is the main effect of the follow-up period in addition to the training period, β treat is the main effect of being in the treatment group, and β treat  ×  t 1 →  t 2 and β treat  ×  t 2 →  t 3 are the two interaction effects. Z 1 and Z 2 are indicator variables which take on the value 1 after t2 and t3 respectively. The interaction effect β treat  ×  t 1 →  t 2 which describes how much more the treatment group benefits from the training phase compared to the control group is decisive for testing the effect of the Yoga Nidra intervention. We assume theoretically that the missingness is dominantly Missing At Random (MAR), i.e., the missingness itself can be predicted from the variables which are available and components independent from the data; this is likely to be the case since the three variables are correlated, and at least one is always available. For MAR missingness, FIML estimates are unbiased, so we assume that in the current situation the FIML estimates are only minimally biased.

In the model, we represented the six means as a grand mean, main effects for the treatment group, the period from t1 to t2, and the period from t2 to t3 as well as both interaction effects, i.e. t1 to t2 x group and t2 to t3 x group. For each parameter, we report the a-posteriori probability that the true effect is on either side of zero under the assumption of a flat (i.e., diffuse) prior. That is, we assume that before looking at the data, every parameter value is equally likely. In other words, there is no prior information included in the estimation process. Footnote 1 Asymptotically, the probability that the parameter is on the other side of zero compared to the estimate coincides with the p value for a one-sided test in a LRT against the null hypothesis that the parameter in question is zero. The LRT is based on the chi-square distribution and compares the effect of the groups in an ANOVA-style model.

Effect sizes are reported as confidence intervals (CI), additionally giving Cohen’s d (relative effect size) for every parameter. Cohen’s d of the single parameters was computed as the ratio of effect size over standard deviation, for each parameter separately. For the interaction effect of the follow up and the treatment group, we additionally report the a-posteriori probability that this interaction effect is cancelling out the expected treatment effect in the treatment group, again using a flat a-priori distribution of the parameter. In other words, we give the probability that the dependent variables drop to the pre-treatment level again. The common variance components in both groups reached from 0.3 to 1.25 (roughly 2 to 3 times larger than the residual variances) and are not reported separately for every variable.

Preliminary Analyses

The data were first prepared by correcting input errors and by identifying outlier values. The assumption of normality was supported by the theoretical consideration that the dependent variables are mean scores of multiple items, which in themselves can be assumed to have multiple independent contributors, which via the Central Limit Theorem supports normality. We checked this assumption using histograms and QQ plots as well as the values of skew and kurtosis.

Each dependent variable was analyzed regarding possible pre-test differences. Significant differences were only found for PA: t (518) = 2.71, p  = .007. Participants in the meditation group had a significantly higher pre-test score for PA compared with the participants of the control group. This pretest difference, however, is not relevant for the analyses of the interaction effects because the model explicitly separates the interaction effect from the group effect.

Effects of Yoga Nidra

The descriptive characteristics of the three dependent variables as well as of mindfulness are shown in Table 2 for both groups and for the three measurement points. The variables are listed in the order of presentation in the questionnaire. When considering these raw means, it is already possible to identify changes in favor of the meditation group, which will be explained in more detail in the following analyses. In particular, stress, negative affect and quality of sleep seem to be sustainably positively influenced by the meditation. Furthermore, mindfulness was successfully increased in the meditation group. The following statistical analyses display the effects of the 11-Minute-Yoga Nidra meditation on all dependent variables.

As can be seen in Table 3 , the interaction effects Treat x Train were in the hypothesized direction with at least 96% a posteriori probability under a flat prior (Bayes coefficient > = 37) for all dependent variables. In particular, all effects were significant in a one-sided LRT against the null hypothesis of no effect (Note that the a-posteriori probabilities for negatively coded constructs, e.g. stress, are close to zero, which means that there is a high probability for decrease). This means that the Yoga Nidra intervention led to substantial increases regarding PA, satisfaction with life, sleep quality and mindfulness and to substantial decreases regarding stress and NA compared with the waitlist control condition. The effect sizes indicate an improvement of roughly 10% of the respective SD in most cases except for mindfulness (20%). The 95% CIs (coinciding 95% Bayesian intervals) of the effect sizes are all completely above and below zero respectively except for the CI of the satisfaction with life effect size [−0.001; 0.233].

For all dependent variables other than satisfaction with life, the probability that the follow up effect cancels the treatment effect was below 2.37%, and even for satisfaction with life, it was only 14.04%. Thus, it can be concluded that the effects of Yoga Nidra were maintained at follow up (see Table 4 ). In particular, no interaction effect of follow up with treatment group was significantly different from zero at p  = 0.05 at a one-sided test.

We checked that all residual variances on the upper level were substantially larger than on the lower level, and significantly different from zero at p  = 0.05. This supports our earlier theoretical assumption that the data is dominantly MAR. The RMSEA for the model was close to 0.01 for most dependent variables, although model fit is irrelevant in this situation with saturated means and enforced covariance structure.

We derived open feedback of 95 participants at t2 and 45 participants at t3 to add qualitative data to our quantitative analyses. The following three remarks were most frequently named:

Relaxation, positive affect, satisfaction (40% at t2, 42.2% at t3)

Positive effect on sleep quality (13.7% at t2, 6.7% at t3)

Positive body awareness (11.6% at t2, 6.7% at t3)

Particular answers to this open format question indicate that for some participants, the intervention seemed to be particularly helpful in acute stress situations as before exams, during relationship problems or other critical life events: “[I] must confess that at first I did not believe I would see any changes. But I’m much more quiet driving the car, my girlfriend says.” Negative feedback was most frequently connected to feelings of boredom as the meditation was always the same, difficulties to integrate the meditation into the daily schedule and to get used to the speed of perception exercises. Participants who then stuck with the meditation also reported improvement: “[I] found the change of body parts initially too fast, towards the end rather positive, so there was no time to think about something else and the concentration worked better”.

This study aimed at developing a short form of Yoga Nidra meditation and at examining its effects on stress, sleep, and well-being in a large and diverse sample. Overall, we found preliminary support for the effects of the 30-days meditation-based intervention regarding these variables. The intervention showed the expected effects on all dependent variables and these effects remained stable at follow-up after six weeks. As already pointed out, the meditation considerably reduced NA more than it increased PA. This result pattern replicates findings from previous studies that also showed a stronger effect on NA (e.g., Agency for Healthcare Research and Quality 2014 ; Deuskar 2011 ). One possible explanation for this result pattern may be the fact that Yoga Nidra primarily regulates hyperarousal that is addressed in many items of the short NA-scale. As the meditation effect is more relaxing than activating in its present short form, several participants answered to an open-format question that they used the meditation to be able to fall asleep and were thankful that it did indeed work. For the authors it was also valuable to read about the sustainable use of the meditation and that about 10% of the sample integrated the meditation into their everyday routine. Furthermore, it is important to consider that the stability of the effects from post-test to follow-up presumably are attributable to the fact that many participants still used the meditation after the actual 30-days intervention period. On the other hand, participants in the meditation group might have benefitted from the good news of being selected first and therefore might have shown higher initial PA values as a sign of motivation.

General life satisfaction, the cognitive component of well-being, was also significantly increased by meditation in the study at hand compared to the control condition. Since the CI of the effect size for this dependent variable included zero, this effect has to be interpreted with caution. Altogether, the short form of Yoga Nidra seems to influence affective and cognitive components of well-being in the short and medium run. The present short form of Yoga Nidra focused on relaxing components such as the perception of the body and the breath and not on cognitive components such as the perception of contrasting sensations and visualizations that are present in the long form of Yoga Nidra. This issue could be addressed in future studies that compare the long and the short form to further analyze differences between affective and cognitive effects. Furthermore, the Sankalpa or personal resolution could also be considered in more detail in future research. As a cognitive component, such resolutions will differ more or less between Yoga Nidra practitioners and could be associated with different effects.

The present work is consistent with previous studies that have shown the positive effect of meditation- and mindfulness-based interventions on sleep quality (e.g., Hülsheger et al. 2015 ). This positive effect might also be explained with the reduction of hyperarousal through Yoga Nidra. Since Schulz et al. ( 2003 ) have shown that the cognitive component of worry is the critical determinant of sleep disorders, future studies could investigate in more detail whether Yoga Nidra may have an explicit impact on worry-related sleep disturbances. Finally, the study showed the strongest but still small effect (in terms of Cohen’s conventions) regarding the increase in mindfulness for participants of the meditation group. Thus, Yoga Nidra as a specific form of mindfulness meditation in fact does increase mindfulness.

Strengths, Limitations and Implications for Future Research

There are four core strengths regarding (the design of) our study: (1) This study has investigated the effects of Yoga Nidra in a randomized controlled trial and (2) includes a large sample of participants holding a broad range of jobs. (3) The entire Yoga Nidra intervention was very economic and cost-saving since it could be successfully administered online and thus reached a wide range of participants that (4) only had to invest eleven minutes per day in order to increase their well-being and sleep quality and to reduce stress.

Although the effects of the Yoga Nidra meditation were only very small to small (between 10% and 20% SD of the distributions of the respective variables), they may be considered important in terms of public health that aims at promoting health in large populations using cost-saving and low-threshold interventions. In terms of adherence, eleven minutes are easier to invest for employees who have to cope with a tight schedule. Furthermore, importance may also be defined as a function of “how minor the manipulation of the independent variable is and how resistant a dependent variable is to change” (Prentice & Miller, 1992, cited according to Manthey et al. 2016 , p. 334). As the intervention was highly economic, unlikely to produce harm and only took eleven minutes a day, it can be considered a minor manipulation. The significant results are supported by the high power the tests have due to the large sample size. The changes in statistics are supported by the participants’ personal responses to the optional open-format question through which the authors received diverse positive feedback about the intervention.

The shortness of our Yoga Nidra intervention may be criticized in terms of a currently inflationary use of mindfulness meditations that was accurately termed “McMindfulness”, first coined by Buddhist psychotherapist Miles Neale (Fisher 2010 ). Neale warns against the myopia of McMindfulness while advocating for a meditation practice that considers moral responsibility within our global interconnectivity. McMindfulness also means that big effects should be reached with small or fast meditation-related expenditure. These critical comments on the wide dissemination and sometimes probably superficial use of mindfulness, however, may also help to give the construct more pointedness. With regard to future studies it will be particularly interesting to compare the short form with the standard length to analyze a possible gain of effect sizes. Furthermore, real-time monitoring of Yoga Nidra meditation using mobile sensing (Harari et al. 2017 ) or other experience sampling technologies that enable to unobtrusively collect data would decisively improve the validity of the study. Through these new technologies, it is also possible to assess physiological indicators of stress like heart rate or skin conductance level (Ollander et al. 2016 ).

Referring to dropout rates, further techniques to increase motivation and self-efficacy could be introduced in future studies. Lederer and Middlestadt ( 2014 ) showed that the intention to meditate is related to attitudes, norms and behavioral control, and that this knowledge can be used to motivate individuals to take advantage of the positive effects of meditations. Furthermore, the present sample is very educated and doesn’t represent individuals with a lower educational background who should be included in future studies.

Probably most critical is the fact that we only used a waitlist control instead of another active control condition. For now, it cannot be said for sure if the intervention effect is caused by the meditation and not also by the fact that participants in the intervention group do something different in their routine, the fact that participants are maybe just happy that they have been sorted to the intervention first, or the effect that is created by just giving attention to their well-being and stress. Thus, future studies should include active control groups, e.g., other interventions like progressive muscular relaxation or autogenous training to further validate the specific effects of Yoga Nidra. Furthermore, one could argue that our results are due to social desirability since we only used self-report data and probably also because participants randomized to the intervention can have the intention to please the researcher and to comply with the expectations. In a similar vein, information on possible positive effects of mindfulness and meditation that were provided in a clip shown to all participants in the beginning of the study, might have influenced the participants’ answers. On the other hand, it would have been difficult with regard to the principle of informed consent to leave the participants in the dark with regard to these possible effects. A further limitation is the only short- and medium-term consideration of the effects; future studies could also examine the long-term effect of the 11-min meditation. Future studies should also include biological parameters, e.g., cortisol and heart rate variability, in order to further validate the promising effects of our short form of Yoga Nidra. Referring to the general population, it must be considered that participants of the present study reported significantly higher stress, NA and PA as well as lower SWLS than those of a representative German sample at t1. Therefore, the results cannot be generalized without caution.

Finally, the entire intervention was completely administered online without any real-life contact to a Yoga Nidra teacher. On the one hand, this is a big advantage in terms of costs and coverage. On the other hand, studies have shown that “blended interventions” which include real life contacts may foster adherence and thus the effectivity of a treatment (e.g., Goyal et al. 2014 ; Pracht and Renner 2016 ). Future studies could therefore integrate presence phases with personal and individualized instructions that could reinforce the effects of Yoga Nidra. There could also be introductory or in-depth training on the method of Yoga Nidra, e.g., for enterprises, which afterwards support the self-administered implementation with audio files.

It is true that meditation-based interventions can never be the same for all people and situations, as Pawson (2006, cited according to Biron et al. 2012 , p.1) emphasized: “Interventions are fragile creatures. Rarely, if ever, is the ‘same’ program equally effective in all circumstances.” Nevertheless, they can be further adapted so that people who are not yet inclined to meditation can also experience positive effects. Perhaps more people will be able to help themselves effectively, whether at home, at work or on the road, to relax and focus their lives on personal growth and satisfaction. In the end, this can be refined from seminars and workshops or even through short meditations such as the present one and may lead to an enduring mindful attitude. For this purpose, it would be particularly interesting to include different personality variables such as openness for experience to further understand and optimize the fit between person and intervention. Maybe it even gives insight about the fit of a short form versus standard length Yoga Nidra and personality traits. It would also be important to understand why more women approach similar interventions and how men could be increasingly and successfully addressed.

This experimental study showed small effects of a short audio-guided and online administered Yoga Nidra meditation on stress, sleep, and well-being in a large and diverse sample. Especially in stressful working days and in order to promote work-life balance, the meditation can be used easily to experience the positive effects of yoga without prior knowledge and without use of more or less difficult body-related exercises. Our study shows that it is not always essential to run costly day programs with a large structural, personnel and time effort, in order to be able to reduce stress and to promote well-being and sleep quality. Even this short form of Yoga Nidra seems helpful to interrupt the autopilot of thoughts in order to perceive the excellent moment in which reality takes place – now.

The dataset generated and analysed during the current study is available from the corresponding author on reasonable request.

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Moszeik, E.N., von Oertzen, T. & Renner, KH. Effectiveness of a short Yoga Nidra meditation on stress, sleep, and well-being in a large and diverse sample. Curr Psychol 41 , 5272–5286 (2022). https://doi.org/10.1007/s12144-020-01042-2

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Methodological issues in conducting yoga- and meditation-based research: A narrative review and research implications

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• 1 Department of Psychiatry, All India Institute of Medical Sciences, Bhopal, 462020, India. Electronic address: [email protected].
• 2 National Drug Dependence Treatment Centre (NDDTC) & Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, 110029, India.
• PMID: 36087391
• PMCID: PMC9451492
• DOI: 10.1016/j.jaim.2022.100620

Yoga and meditation-based interventions have been extensively utilized in the field of contemporary complementary and alternative medicine for various physical and mental health conditions. Ongoing COVID-19 pandemic has rekindled the interest of researchers in yoga and meditation for its preventive and therapeutic utilities. However, the available literature in this area has several methodological concerns, limiting formers' clinical utility. A comprehensive literature on this topic would stimulate researchers and guide them to conduct research on this topic with robust methodologies. The current review highlights the methodological issues with the yoga and meditation-based Research (henceforth, MBR), discusses some of the contentious issues, and provides future directions. The PubMed, Medline, and google scholar databases were searched to screen records dealing with the methodological issues on MBR. The search yielded 299 records, upon screening, only 24 articles were found suitable for the current study. Common methodological issues with MBR: lack of the consensus definitions of the yoga and meditations, interventions lacking theoretical framework of meditation; inadequate description of the study design; difficulty with participants recruitment, setting up the control groups, and blinding; difficulty in assessing the baseline characteristics of the participants, and validity issues with the outcome measures. A few research, however, have also highlighted the potential measures to overcome these methodological challenges. Yoga and meditation-based interventions are promising for several health conditions. However, literature suffers from considerable methodological issues, thus, limiting its utility in modern clinical practice. The study findings can stimulate and guide future research on this topic.

Keywords: Challenges; Interventions; Meditation; Methodological issues; Research; Yoga.

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Yoga and meditation, or running and weightlifting — which combination works best?

“your longevity is better when you’re doing yoga and meditation, because you’re reducing your heart rate,” says dimple jangda founder of prana healthcare centre.

In the debate about which fitness regimen is superior for overall well-being, the comparison between  ancient techniques of yoga and meditation versus running and weightlifting is a subject of curiosity and interest. 

In an episode of the Realign podcast, featuring Dimple Jangda founder of Prana Healthcare Centre, a discussion about whether yoga and meditation are better than running and weightlifting ensued. Jangda said, “Your longevity is better when you’re doing yoga and meditation because you’re reducing your heart rate.” 

To shed light on this matter, Ujjwal Kalra, corporate yoga trainer, and The Art of Living teacher, shares insights into the advantages of these contrasting fitness practices

How does practicing yoga and meditation compare to engaging in regular running and weightlifting routines?

“While running and weightlifting offer physical benefits like building strength, cardiovascular health, and endurance, yoga and meditation provide a more holistic approach to well-being,” Kalra says. 

Yoga, which means ‘union’ in Sanskrit, emphasises the connection between body, breath, and mind. It incorporates physical postures (asanas) that improve flexibility and strength , he mentions, along with mindfulness techniques that enhance focus and reduce stress. 

Meditation, often practiced alongside yoga, he says, cultivates inner peace and emotional regulation. “Yoga and meditation offer a well-rounded approach to physical and mental health that can complement or even enhance a running or weightlifting routine,” he declares.

Physical and mental advantages of incorporating yoga and meditation into a fitness regimen

Running and weightlifting are essential for cardiovascular health and building a strong foundation; but they don’t necessarily address the mind-body connection in the same way as yoga postures (asanas) and meditation do. Yoga offers a unique set of advantages that complement these traditional exercises, according to Kalra.

Yoga excels at cultivating a balanced state of mind ( samatvam ). Through postures, breathing exercises ( pranayama ), and meditation, yoga helps you achieve equanimity, a state of composure in all situations. “This mental calmness translates into physical benefits as well. Yoga improves flexibility and strength, but it does so with a focus on mindfulness and breathwork, which can lead to better form and injury prevention. Additionally, yoga incorporates deep breathing techniques that promote relaxation and stress reduction, something that running and weightlifting may not target directly,” he says. 

In essence, yoga offers a holistic approach to fitness, working on both the physical body and the mind. When combined with traditional exercises like running and weightlifting, you get a well-rounded fitness routine that addresses your physical strength, cardiovascular health, and mental well-being.

Yoga and meditation for cardiovascular fitness and strength as compared to running and weightlifting

Kalra informs that yoga goes beyond gentle stretches and relaxation. While it might not be the first thing that comes to mind for cardio, some yoga practices can be quite vigorous.

“Take suryanamaskar , for example, a popular 12-step sequence that synchronises breath with movement, giving your whole body a workout and boosting your cardiovascular health.” he explains.

Ideal combination of yoga/meditation versus running/weightlifting in a weekly workout schedule

The trainer advocates that by incorporating the following structure into your workouts , you’ll get a balance of physical fitness from cardio and yoga postures, along with the mental well-being benefits of meditation and breathwork. “You can adjust the amount of time spent on each section based on your preferences and goals,” he notifies. 

Start with relaxation: Begin with 5-10 minutes of breathing exercises like pranayama to calm your mind and prepare your body.

Warm up with cardio: Follow with 5-7 minutes of light cardio to get your heart rate up. This could be a brisk walk, jumping jacks, or Sun salutations (s uryanamaskar ) from yoga.

Strength and flexibility: Move on to 10-15 minutes of yoga asanas (postures) to improve strength, flexibility, and balance.

Cool down and focus: End with 10-20 minutes of meditation or yoga nidra (yogic sleep) to relax your body and mind. This will help you integrate the benefits of your workout and leave you feeling refreshed.

• weightlifting

Maharashtra, a crucial state in the upcoming elections, has witnessed a significant shift in political dynamics as Shiv Sena and NCP split. The opposition has formed an unexpected coalition with Congress, Shiv Sena and NCP joining forces.

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• v.5(1); 2019

Yoga Effects on Brain Health: A Systematic Review of the Current Literature

Neha p. gothe.

a Department of Kinesiology and Community Health, University of Illinois at Urbana Champaign

Jessica Hayes

b Department of Psychology and Institute of Gerontology, Wayne State University

Emily Erlenbach

Jessica s. damoiseaux.

Yoga is the most popular complementary health approach practiced by adults in the United States. It is an ancient mind and body practice with origins in Indian philosophy. Yoga combines physical postures, rhythmic breathing and meditative exercise to offer the practitioners a unique holistic mind-body experience. While the health benefits of physical exercise are well established, in recent years, the active attentional component of breathing and meditation practice has garnered interest among exercise neuroscientists. As the scientific evidence for the physical and mental health benefits of yoga continues to grow, this article aims to summarize the current knowledge of yoga practice and its documented positive effects for brain structure and function, as assessed with MRI, fMRI, and SPECT. We reviewed 11 studies examining the effects of yoga practice on the brain structures, function and cerebral blood flow. Collectively, the studies demonstrate a positive effect of yoga practice on the structure and/or function of the hippocampus, amygdala, prefrontal cortex, cingulate cortex and brain networks including the default mode network (DMN). The studies offer promising early evidence that behavioral interventions like yoga may hold promise to mitigate age-related and neurodegenerative declines as many of the regions identified are known to demonstrate significant age-related atrophy.

INTRODUCTION

The practice of yoga dates back over 2000 years to ancient India, with a focus on the unification of the mind, body, and spirit through the practice of physical movements, meditation and breathing exercises. Over the course of its lengthy existence, many different schools of yoga have emerged, each placing a different emphasis on the practice. However, despite their different philosophies and combinations of exercises, they all are integrated in the common theme of uniting the mind and body. Yoga’s prominence in western civilization emerged in the late 20th century. Although a review of the PubMed search on yoga yields the earliest scientific studies dating to 1948, there has been an exponential increase in publications beginning in the 2000s (see Fig. 1 ). While its origins root from religious principles, modern day culture is primarily drawn to it for its relaxation benefits (meditation and breathing exercises) and stretching and strengthening movements (physical poses). According to the National Center for Complementary and Integrative Health (NCCIH), yoga is the most popular form of complementary therapy practiced by more than 13 million adults, with 58% of adults citing maintenance of health and well-being as their reason for practice [ 1 ]. One of the reasons for yoga’s increase in popularity is its versatility, in that it can be taught at a range of different intensities. A systematic review by Larson-Meyer examined [ 2 ] the metabolic energy expenditure during Hatha yoga, the most widely practiced style of yoga in the United States. The review found that, while some specific yoga poses can be metabolically exerting (with energy expenditures >3 METS), most yoga practices fall under the American College of Sport Medicine’s criteria of “light-intensity physical activity” (2–2.9 METS) [ 3 ]. Compared to traditional forms of aerobic and anaerobic exercise, the relatively low-impact, modifiable nature of yoga can offer a middle ground for individuals with movement limitations, clinical diagnoses, and is particularly suitable for aging populations. Yoga’s focus on improving the self through both physical and mental practices incorporates more mindful elements absent in traditional forms of exercise.

Search results from PubMed featuring the term “yoga” in the title and/or abstract of publications over the years shows an exponential growth in yoga research beginning in the 2000s.

Indeed, the practice of engaging the mind and body through meditation, breathing and physical poses has attracted significant attention from the medical community, and yoga has been frequently studied for its possible beneficial effects on physical and mental health outcomes. Systemic and meta-analytic reviews of randomized control trials have found positive associations between yoga practice and improvements in diabetes [ 4, 5 ], cardiovascular function [ 6 ], and musculoskeletal conditions [ 2, 3 ]. There is also considerable evidence for the beneficial effects of yoga practice on mental health including anxiety [ 9 ], stress [ 10, 11 ] depression [ 12, 13 ] and overall mental health [ 14 ]. Typically, yoga has been studied as an adjunct therapy in these studies conducted with adults and older adults often with clinical diagnoses. For example, Lin and colleagues [ 15 ] conducted a meta-analysis assessing the effects of yoga on psychological health, quality of life, and physical health of patients with cancer. They concluded that the yoga groups showed significantly greater improvements in psychological health, as indicated by anxiety, depression, distress, and stress levels, when compared with the waitlist or supportive groups.

Yoga’s acute and intervention effects on cognition are evident in a recent meta-analysis [ 16 ] which reported moderate effect sizes for attention, processing speed and executive function measures for studies conducted with adult populations. Yoga practice enables the practitioner to move in a controlled manner into modifiable physical postures concentrating initially on relaxing their body, breathing rhythmically, and developing awareness of the sensations in their body and thoughts in their mind. In addition to the physical benefits from sequentially completing the postures, the breathing ( pranayama ) and meditation exercises included in yoga are practiced to calm and focus the mind and develop greater self-awareness [ 17 ]. It is hypothesized that this combination of metacognitive thought and bodily proprioception during yoga practice could generalize to conventionally assessed cognitive functions including attention, memory, and higher-order executive functions. However, it is currently unknown if this relationship exists as a direct pathway, or if yoga indirectly influences cognitive functions through processes such as affective regulation. Negative affect including depression and stress are known to detrimentally impact both cognitive functioning [ 18 ] and brain structure [ 19 ] and systematic reviews discussed earlier have demonstrated the potential of yoga to improve anxiety, depression, stress and overall mental health.

Yoga has particularly gained traction as a research area of interest in its promising potential as a therapy to combat the alarming increase in age-related neurodegenerative diseases. Older adults are the fastest growing population in the US and around the world with over 2 billion people expected to be ≥60 years of age by 2050 [ 20 ]. Age is the biggest risk factor for Alzheimer’s disease, the most common cause of dementia in those aged 65 and older. In the absence of any effective treatments to cure the disease or manage its symptoms, researchers have explored the potential of modifying lifestyle behaviors such as nutrition and physical activity to drive beneficial plasticity of the aging brain and remediate age-related cognitive decline. Yoga may be an alternative form of physical activity which may help not only older adults achieve recommended levels of physical activity, but also for individuals who have disabilities or symptoms that prevent them from performing more vigorous forms of exercise.

The purpose of this review was to synthesize the current evidence for yoga’s effect on brain structure and function among adults and identify the regions and neural networks impacted by its short-term or long-term practice.

Literature search and study selection

The aim of this review was to examine the role of ‘holistic’ yoga practice, i.e. studies that explored the role of yoga practice which included each of its three elements: yoga postures, yoga-based breathing exercise and yoga-based meditative exercises. We used the following databases to identify studies from inception to July 2019 that have examined effects of yoga on brain health: MEDLINE, PsychINFO, PubMed, Indian Council of Medical Research, and Cochrane. We used the following a priori search terms to identify all the relevant published articles: ‘yoga’, ‘hatha yoga’ and ‘brain health’, ‘brain function’, ‘MRI’, ‘fMRI’, ‘brain volume’ ‘SPECT’, ‘PET’. Reference lists of relevant articles were also scanned to locate other published works.

Study inclusion criteria were peer reviewed and published cross-sectional, longitudinal or intervention studies examining the role of holistic yoga practice that included physical postures, breathing and meditation. Study outcomes needed to include brain health measures assessed using magnetic resonance imaging (MRI), including functional MRI (fMRI) or single photon emission computed tomography scan (SPECT) or position emission tomography (PET). Figure 2 presents the PRISMA flowchart that summarizes the study selection process. Studies examining the sole effects of meditation or mindfulness were excluded as they have been reviewed elsewhere (21, 22) and do not meet the holistic definition of yoga practice. After screening for inclusion criteria, 11 studies were included in this review. These studies were categorized based on the outcome variables measured, into two groups: “Effects of Yoga Practice on Brain Structure” that describes the structural characteristics of the brain associated with yoga practice, and “Effects of Yoga Practice on Brain Function” that describes investigations of regions showing differential activation or connectivity in the context of yoga practice.

Prisma flowchart.

Study characteristics

As seen in Table 1 , this literature is very nascent, as evident from our literature search returning 11 relevant studies published between 2009 and 2019. Most of the studies ( n  = 6) were cross-sectional and therefore exploratory in nature, whereas 5 intervention studies examined the yoga-brain outcome relationships over study durations ranging between 10 and 24 weeks. All studies have been conducted with adult populations, with 5 studies having a mean age greater than 65 years, suggesting older adult samples.

Study characteristics of the 11 publications examining the role of yoga on brain structures and functioning

Various styles of yoga were reported across the studies, with a majority ( n  = 9) classified as Hatha yoga practice (a style that focuses on physical postures, breathing, and meditation). Other styles of yoga reported in the studies included Kundalini yoga with Kirtan Kriya ( n  = 2), which focuses more on mediation and the chanting of mantras, and Iyengar ( n  = 1) which is a type of Hatha yoga with a greater emphasis on anatomical detail and alignment. The 5 intervention studies ranged from 10 to 24 weeks and examined the brain health outcomes at baseline and end of the intervention. The frequency of yoga practice varied across the interventions ranging from once a week to biweekly to daily practice. Studies that compared brain health outcomes for yoga practitioners or experts with age- and or sex-matched controls typically included yoga practitioners with at least 3 or more years of regular (weekly or biweekly) yoga practice. None of these cross-sectional studies offered a standardized definition or specific criterion to define a yoga practitioner. Based on the studies included in this review, a yoga practitioner was defined as an individual who had consistently practiced yoga for at least 3 years on a weekly basis.

Effects of yoga practice on brain structure

In order to identify the effects of yoga practice on brain structure, researchers have utilized MRI to investigate how the structure of the brain differs among those with experience practicing yoga (see Fig. 3 ).

Brain regions showing A) structural differences in yoga-practitioners compared to non-practitioners or B) a dose-dependent relationship between years of yoga practice and brain structure among practitioners. Yoga practitioners exhibited greater cortical thickness, gray matter (GM) volume, and GM density than non-practitioners in a variety of regions. Among yoga-practitioners, a positive relationship between the years of yoga practice and GM volume was also observed in a number of areas. All but one of the regions shown were created by making a 5 mm sphere around the coordinates provided in the studies reviewed. Since Gothe et al. (2018) did not investigate volume differences on a voxel-wise basis, a mask of the whole structure is shown.

Cross-sectional studies examining group differences

The majority of these studies have relied on comparing the brain structure of experienced yoga practitioners, with the brain structure of non-practitioners, or yoga-naïve controls, to detect cross-sectional differences existing between the groups. Afonso et al. [ 23 ] found differences in cortical thickness among female adults over the age of 60 with 8 or more years of Hatha yoga experience compared to a non-practitioner control group. The yoga-practitioners exhibited greater cortical thickness in an area of the left prefrontal cortex that included part of the middle frontal and superior frontal gyri. Importantly, participants between groups were matched for the typical amount of non-yoga physical activity they engage in, suggesting that the differences in cortical thickness are not just due to a potentially greater levels of overall physical activity among yoga-practitioners.

Other studies that investigated cross-sectional differences in brain structure between yoga-practitioners and non-practitioners primarily focused on detecting differences in gray matter (GM) volume rather than cortical thickness. Our own work [ 24 ] sought to determine whether the volume of the hippocampus, a subcortical structure that plays an important role in memory, differed between yoga-practitioners with at least 3 years of experience compared to non-practitioners. We found the volume of the left hippocampus to be significantly greater among yoga-practitioners compared to age- and sex- matched controls with similar physical activity and fitness levels. We also tested differences between the thalamus and caudate nucleus, which are subcortical structures that served as control regions. No significant differences were found between the two groups, suggesting that yoga effects on the brain may be selective and similar to those observed in the aerobic exercise-cognition literature. Consistent with this result, another study [ 25 ] also identified volume differences in the left hippocampus and parahippocampal gyrus between healthy adults with and without yoga experience. A number of additional frontal (bilateral orbital frontal, right middle frontal, and left precentral gyri), temporal (left superior temporal gyrus), limbic (left parahippocampal gyrus, hippocampus, and insula), occipital (right lingual gyrus), and cerebellar regions were also larger among yoga-practitioners than non-practitioners. Given that this sample of yoga-practitioners reported fewer cognitive failures than their yoga-naïve counterparts, the researchers correlated the number of lapses in cognitive function that participants reported with the volume of regions where group differences were observed. A negative correlation was reported, such that higher numbers of cognitive failures were associated with smaller GM volumes in the frontal, limbic temporal, occipital, and cerebellar regions stated above.

Villemure and colleagues [ 26 ] investigated whether the correlation of age with total GM volume of the whole brain differed between a group of yoga-practitioners and non-practitioners. While within the group of healthy adults without yoga experience, a negative correlation was observed between age and the total GM volume of the brain, no relationship was found between age and brain structure within the group of yoga-practitioners. However, the difference in slopes between the groups was not statistically significant. Non-practitioners did not exhibit larger or thicker brain structures compared to experienced yoga-practitioners in any of these studies.

Intervention studies examining yoga training effects

In comparison to the aforementioned cross-sectional studies, studies employing yoga interventions have investigated how the structure of the brain changes as a result of relatively short-term yoga practice. Hariprasad and colleagues [ 27 ] measured changes in the GM volume of the bilateral hippocampus and the superior occipital gyrus, which served as a control region, following a 6-month yoga intervention. Participants consisted of healthy older adults who underwent an hour of formal training 5 days a week for 3 months and then completed the same daily regimen at home for an additional 3 months with regular booster training sessions. An increase in the volume of the bilateral hippocampus from pre- to post-intervention was observed; however, the sample of this study was quite small ( n  = 7) and did not compare these changes to changes in hippocampal volume of a control group. Another study [ 28 ] also evaluated changes in the GM volume of the bilateral hippocampus, as well as in the dorsal anterior cingulate cortex, but they did so in participants with mild cognitive impairment who completed a 12-week intervention consisting of weekly 1-hour sessions of either Kundalini yoga with Kirtan Kriya or memory-enhancement training. Both groups also completed 12 minutes of daily homework that was related to their intervention. Unlike previous studies, the results of a mixed effects model showed the volume change of the bilateral hippocampus did not differ between the two groups, but that the change in volume of the dorsal anterior cingulate cortex was different for the two intervention groups. Within the memory enhancement group, there was a trend toward increased volume of the dorsal anterior cingulate cortex following the intervention, a change that was not observed within the yoga group. It is possible that the shorter length of this intervention (12-weeks) in comparison to the 6-month intervention utilized by Hariprasad and colleagues [ 27 ] explains the differences in study results pertaining to hippocampal volume. However, since memory-enhancement training targets a single aspect of cognition and thus is likely to directly target areas involved in memory, it may not serve as an equal comparison group for yoga, whose effects are exerted in a more indirect fashion.

Garner and colleagues [ 29 ] investigated the impact of yoga training on GM density, which is related to a voxel’s signal intensity and is reflective of the amount of gray matter within each voxel. They did this by comparing changes in GM density among healthy young adults after a 10-week intervention in which participants self-selected enrollment in a Hatha yoga, sport control, or passive control group. Although the yoga and sport control groups both underwent 10 hours of weekly practice which involved similar body movements, the meditation and breathing components of holistic yoga practice were not incorporated into the workouts performed by the sport control group. Unlike participants in these groups, who had not participated in their selected activities for at least 6 months prior to the intervention, participants in the passive control group did not alter any of their daily habits. No differences were observed between the yoga and passive control groups, but compared to the sport group, GM density of the yoga group was shown to increase in five regions and decrease in three regions following intervention. The only region to show an effect specific to the yoga intervention was the right hippocampus, which showed increased GM density over time within the yoga group and decreased GM density over time within the sport control group. Interestingly, this region showed significantly lower GM density at baseline for the yoga group compared to the two control groups. Neither gender or height differences were found to explain this, and no other sociodemographic characteristics were found to differ between the groups, but based on known links between the hippocampus, stress, and blood pressure, the authors suggest that individuals who are vulnerable to stress may have been driven to select yoga due to its known relaxation benefits.

Dose-response relationships

The second general strategy employed by researchers to investigate the effects of yoga practice on brain structure is to characterize the specific nature of the relationship between yoga practice and brain structure among experienced yoga practitioners. Such analyses primarily consist of examining the “dose-dependent” relationship between years of yoga practice and brain structure (see Fig. 3 ). However, evaluating how each of the different components of yoga practice (i.e. postures, breathing, meditation) is related to the structure of the brain is also of interest. Two of the cross-sectional studies already mentioned (25, 26) investigated relationships of this nature. After identifying regions of the brain in which yoga-practitioners exhibited greater GM volume than non-practitioners, Froeliger and colleagues (25) looked within these regions to identify areas where years of yoga practice was correlated with GM volume. They found that the extent of yoga experience within yoga-practitioners was positively related to volume of frontal, limbic, temporal, occipital, and cerebellar regions, while no regions showed a negative association between years of yoga practice and GM volume.

Villemure and colleagues [ 26 ] also sought to identify a dose-dependent relationship between GM volume, years of yoga practice and current weekly yoga practice as reported by the yoga-practitioners. Volumes of the left mid-insula, frontal operculum, orbital frontal cortex, and right middle temporal gyrus were positively correlated with years of yoga practice, while volumes of the left hippocampus, midline precuneus/posterior cingulate cortex, right primary visual cortex, and right primary somatosensory cortex/superior parietal lobe were positively related to the weekly number of hours spent practicing yoga. In addition to investigating this dose-dependent relationship between yoga practice and brain structure, the researchers conducted multiple regressions to evaluate how well each aspect of yoga practice predicted GM volume in the areas found to correlate with weekly yoga practice. Commonality analysis allowed them to divide the amount of variation in GM volume that was accounted for by all the predictors into the percentage of the effect unique to each predictor and common to each combination of 2 or more predictors. A combination of the posture and meditation components of yoga practice accounted for 42% of the explained variance in hippocampal GM, 41% in precuneus/posterior cingulate cortex GM, and 45% in primary visual cortex GM. Meanwhile, 44% of the explained variance in primary somatosensory cortex/superior parietal lobe GM volume was accounted for by the meditation and breathing components of yoga practice.

Effects of yoga practice on brain function

Although the majority of studies investigating yoga’s relationship with the brain have focused on structural brain measures, a handful of studies ( n  = 5) have compared how brain functioning differs between those with and without yoga experience. Three of these studies were cross-sectional in nature, with two comparing task-related brain activation and the other comparing functional brain connectivity between experienced yoga-practitioners and non-practitioners.

Task-related fMRI findings

Figure 3 represents the brain regions identified across the 3 studies based on the task-related fMRI findings. In addition to investigating differences in GM volume, our own work [ 24 ] evaluated how yoga-practitioners and non-practitioners differed in brain function during subcomponents of a Sternberg working memory task. No differences between the groups were identified during the maintenance or retrieval portions of the task, but yoga-practitioners exhibited significantly less brain activation in the left dorsolateral prefrontal cortex (dlPFC) during encoding compared to yoga-naïve controls.

Froeliger and colleagues [ 30 ] used the same sample of yoga practitioners and non-practitioner controls who showed differences in GM volume [ 25 ] to investigate differences in task-related activation during an affective Stroop task. One focus of this fMRI study was to evaluate effects of yoga on emotional reactivity by considering the impact of group, the emotional valence of images viewed, and the interaction of group and valence on the BOLD response to viewing emotional images. A significant interaction was noted in the right dorsolateral prefrontal cortex (middle frontal gyrus), and further investigation demonstrated that the percent signal change in this region was greater when viewing neutral images compared to negative images among non-practitioners. Meanwhile, among yoga-practitioners, the percent signal change in this region was lesser than that observed in non-practitioners regardless of whether the image had a negative or neutral emotional valence. Across all participants, the percent signal change in the dorsolateral prefrontal cortex was negatively correlated with the percent signal change in the amygdala when viewing negative images, but not when viewing neutral images. The second aim of the study was to identify how yoga experience alters the impact of emotional distraction on the Stroop-BOLD response. To investigate this, the main effects of group, the emotional valence of the distractor image, and the interaction between these on the BOLD response during the Stroop contrast (incongruent vs congruent number grids) were considered. The non-practitioners showed less activation in the left superior frontal gyrus compared to yoga-practitioners regardless of distractor image’s emotional valence. Furthermore, the percent signal change of the left ventrolateral prefrontal cortex was greater among yoga-practitioners if a negative distractor was presented than if a neutral distractor was presented, while the opposite pattern was observed within the group of non-practitioners. Positive affect was shown to decrease significantly from baseline to the completion of the affective Stroop task among all participants and this change was positively correlated with the response to viewing negative images in the left amygdala. Furthermore, there was a significant interaction between this response and group, such that among non-practitioners a greater response to viewing negative emotional images was related to greater decreases in positive affect. Among yoga-practitioners, however, this relationship between amygdala BOLD response to negative emotional images and change in affect was not present.

Functional connectivity findings

Unlike the previous two studies, which utilized fMRI to identify brain activation occurring during engagement in a cognitive task, a recent cross-sectional study [ 31 ] utilized fMRI to identify whether yoga practice is related to functional brain connectivity. In response to interest surrounding yoga as a tool to combat aging, and the vulnerability of the default mode network (DMN) to typical and pathological aging processes, healthy older adults with at least 8 years of yoga experience were paired with age, education, and physical activity-matched yoga-naïve controls. Greater resting-state anteroposterior functional brain connectivity between the medial prefrontal cortex and right angular gyrus was observed among yoga practitioners compared to yoga-naïve controls. While a decrease in resting state functional connectivity is often associated with aging, this study suggests that yoga may reverse this age-related effect among older female subjects.

Other studies investigated longitudinal changes in the functional connectivity of the brain function following yoga intervention. One such study conducted by Eyre and colleagues [ 32 ] utilized fMRI to examine how the functional connectivity of the brain at rest changed following a 12-week intervention with either yoga or memory-enhancement training, as previously described in summarizing the results of Yang et al. [ 28 ]. Results showed that improvements in verbal memory recall were positively associated with changes in connectivity primarily within areas of the default mode network. Specifically, this effect was present in the pregenual anterior cingulate cortex, frontal medial cortex, posterior cingulate cortex, middle frontal gyrus, and lateral occipital cortex for both of the intervention groups. Similarly, changes in functional connectivity of the left inferior frontal gyrus, found in the language network, were also positively associated with changes in verbal memory recall for both groups. However, the relationship between changes in connectivity and memory was no longer significant in the posterior cingulate cortex or inferior frontal gyrus within the yoga intervention group after removal of an outlier. While an area within the superior parietal network near the precentral and postcentral gyri exhibited a negative relationship between changes in functional connectivity and changes in visuospatial memory, the authors interpreted this negative association to be reflective of enhanced efficiency following intervention. A 12-week intervention was used in another study [ 33 ] to investigate whether changes in cerebral blood flow (CBF) measured with single-photon emission computed tomography were influenced by Iyengar yoga during baseline and meditation scans among four patients with mild hypertension. The right amygdala, dorsal medial cortex and sensorimotor areas showed decreases in baseline CBF following the intervention. Meanwhile, activation was greater during meditation in the right prefrontal cortex, sensorimotor cortex, inferior frontal lobe, superior frontal lobe and the right and left dorsal medial frontal lobes following yoga training. Furthermore, the greater activity of the left anterior cingulate, dorsomedial frontal cortex, and superior temporal lobe, relative to the right, was more prominent after the intervention. Following yoga training, laterality preference for the left over the right during meditation compared to baseline also became more pronounced.

Our review of the yoga-imaging literature suggests that behavioral mind-body interventions such as yoga practice can affect the anatomy of the brain. Yoga practice appears to be linked to anatomical changes in the frontal cortex, hippocampus, anterior cingulate cortex and insula. Throughout the studies reviewed, yoga practice showed a consistent positive relationship with measures of brain structure (i.e. GM volume, GM density, cortical thickness), such that regions showing an effect of yoga practice were greater in experts or had more gain following intervention. Differences in brain function between yoga-practitioners and non-practitioners have been observed in the dorsolateral prefrontal cortex, with yoga-practitioners showing less activation during both working memory and affective Stroop tasks. Additionally, yoga-practitioners differed from non-practitioners within the ventrolateral prefrontal cortex, superior frontal gyrus, and amygdala during other aspects of the affective Stroop task. Studies investigating changes in the functional connectivity of the brain following yoga practice have primarily identified increases in the default mode network, one of which found that those changes were related to memory performance.

Although the direction of differences in brain function between yoga-practitioners and non-practitioners may be inconsistent, it is the interpretation of those differences and what they imply about the potential utility of yoga practice in maintaining brain health that are of ultimate interest. Given the complex nature of the brain, there is often more than one way something can exert an effect. This, in addition to the specific task being used, individual differences in the way participants strategize, and other differences in study design could account for differences in results across studies. While the nature of yoga’s relationship with brain function seems less straightforward than it does with structure, the evidence still points toward yoga exerting a beneficial effect on brain function. Findings that link the pattern of brain functioning observed in yoga-practitioners to performance or health outcomes offer support for the beneficial influence of yoga on brain function.

Evidence suggests that global GM declines with age [ 34 ] while physical activity and cardiovascular fitness [ 35, 36 ] as well as mindfulness [ 21, 22 ] have shown to confer neuro-protective effects. The holistic practice of yoga combines physical activity in the form of postures with yoga-based meditative and breathing exercises. The findings from studies reviewed in this paper are therefore not surprising and suggest that yoga confers similar cortical neuro-protective effects. These findings could not only have a significant public health impact on cognitive aging but also call for exercise neuroscientists to design systematic trials to test the efficacy and effectiveness of yoga practice in comparison to other forms of physical activity and mindfulness practices.

A majority of the studies highlight changes in hippocampal volume following yoga practice. The hippocampus is known to be critically involved in learning and memory processes [ 37 ]. Yoga effects on the hippocampus are also aligned with findings from the aerobic exercise literature [ 38 ], as well as the mindfulness literature [ 39 ], suggesting that exercise alone and mindfulness alone, as well as a combination of the two in the form of yoga practice, have a positive effect on this critical brain structure implicated in age-related neurodegenerative diseases and chronic stress [ 19, 40 ]. Other than the hippocampus, work of Froelinger and colleagues [ 25 ] suggests that yoga practitioners have higher GM volume in a number of regions including frontal (i.e., bilateral orbital frontal, right middle frontal, and left precentral gyri) (see Fig. 3 ), limbic (i.e., left parahippocampal gyrus, hippocampus, and insula), temporal (i.e., left superior temporal gyrus), occipital (i.e., right lingual gyrus) and cerebellar regions. Experimental and lesion studies indicate these brain structures are involved with tasks of cognitive control [ 41 ], inhibition of automatized or prepotent responses [ 42 ], the contextually appropriate selection and coordination of actions [ 43 ], and reward evaluation and decision making [ 44, 45 ]. The cerebellum, a brain structure known for decades as integral to the precise coordination and timing of body movements [ 46 ], has more recently been acknowledged to be involved in cognition, specifically executive function [ 47, 48 ].

The studies reviewed also implicate the role of yoga in functioning of the dlPFC and the amygdala (see Fig. 4 ). Gothe et al. [ 24 ] found that yoga practitioners demonstrated decreased dlPFC activation during the encoding phase of a working memory task in comparison to the controls. Froelinger et al. [ 30 ] also found yoga practitioners to be less reactive in the right dlPFC when viewing the negatively valanced images on the affective Stroop task. Task-relevant targets activate the dlPFC, whereas emotional distractors activate the amygdala [ 49 ]. Exerting cognitive control over emotional processes leads to increased activation in the dlPFC, with corresponding reciprocal deactivation in the amygdala [ 50, 51 ]. The studies suggest that when emotional experience occurred within the context of a demanding task situation, yoga practitioners appeared to resolve emotional interference via recruitment of regions of the cortex that subserve cognitive control. Plausibly, these findings may indicate that yoga practitioners selectively recruit neurocognitive resources to disengage from negative emotional information processing and engage the cognitive demands presented by working memory and inhibitory control tasks demonstrating overall neurocognitive resource efficiency.

Brain regions showing differential task-related activation in yoga-practitioners. Yoga practitioners showed less activation than non-practitioners in the left dorsolateral prefrontal cortex during the encoding phase of a Sternberg Working Memory task (yellow). Yoga practitioners also showed less activation than non-practitioners in the right dorsolateral prefrontal cortex and right superior frontal gyri, but more activation in the left ventrolateral prefrontal cortex during various aspects of an Affective Stroop task (red). All regions shown were created by making a 5 mm sphere around the coordinates provided in the studies reviewed.

A network of neural structures including the frontal lobe, the anterior cingulate cortex, the infero-temporal lobe and the parietal cortex are known to be involved in cognitive operations including stimulus processing and memory updating [ 52, 53 ]. Specifically, the anterior cingulate cortex is part of the brain’s limbic system and has connections with multiple brain structures that process sensory, motor, emotional and cognitive information [ 54 ]. In our reviewed studies, Eyre et al. [ 32 ] found verbal memory performance to be correlated with increased connectivity between the pregenual anterior cingulate cortex, frontal medial cortex, posterior cingulate cortex, middle frontal gyrus, and lateral occipital cortex following a 12-week yoga intervention. Villemure et al. [ 26 ] also reported a positive correlation between the dose of weekly yoga practice and GM in the cingulate cortex. Collectively these results are promising and corroborate the aerobic exercise literature, as the anterior cingulate cortex is one of the brain structures that shows disproportional changes as a result of participation in moderate intensity physical activity [ 55 ]. Many of these regions are part of the default mode network, which is typically activated during rest and deactivated when an individual is engaged in an external task [ 56 ]. Following a yoga intervention, increases in connectivity of regions in the DMN were associated with improvements in verbal memory recall [ 32 ]. Given that functional connectivity of the DMN has been negatively associated with age-related pathologies such as Alzheimer’s disease [ 57 ], as well as in the context of typical aging [ 58 ], the increases in functional connectivity in regions of the DMN reported by Eyre et al. further indicate that yoga practice is a promising intervention for use among aging populations.

Future directions

Although yoga-cognition has emerged as a topical area in the field of exercise neuroscience, the studies are preliminary and lack the rigorous methodology that is applied in the exercise-cognition literature. Sample sizes for yoga studies have ranged from 4 to 102 participants and a majority of the work has been cross-sectional in nature. While the beauty of yoga lies in the diverse and modifiable combinations of postures, breathing and meditative exercises, this concurrently poses a challenge for scientists to compare findings across studies. Furthermore, there is no standardized definition for a yoga practitioner, nor a universal standard for certification. Of the yoga practitioners sampled in the reviewed studies, their experience ranged from regular practice 3–5 days a week for 3 to 16 years. This poses a challenge to compare research findings across studies.

Although cross-sectional studies limit us in our ability to draw casual conclusions, such a design can provide certain advantages over the use of interventional studies design in identifying the effects of yoga practice on the brain given that 9.3 years was the lowest average number of years of yoga practice reported by yoga-practitioners in these studies. Following yoga-practitioners for such an extended period in an intervention design would pose a variety of practical difficulties, and thus cross-sectional comparisons between yoga practitioners and yoga-naïve controls provide a unique opportunity to gain an idea of the maximal benefits that extensive yoga practice may lead to. Nonetheless, it is the promise of yoga as an intervention for individuals with various health issues that has sparked much of the growing interest in the effects of yoga practice on brain structure and function, since its established cognitive benefits and accessibility to people with a wide range of physical capabilities suggest it may be an effective intervention for typical and pathological cognitive decline among older adults. Yet for yoga interventions to have clinical utility in such circumstances, compliance to the intervention program is a necessity. None of the reviewed intervention studies provided information about participants’ compliance and adherence to the yoga program. Future studies need to document and report attendance and adherence rates. The intervention studies also employed different frequencies, intensities and doses of yoga practice which resulted in heterogeneity across intervention designs as well.

While the reviewed studies examined the relationship between yoga and brain structure or function, only one [ 24 ] employed cognitive or behavioral assessments which correlate with the studied brain regions. Future studies should administer such assessments to establish if the neural changes produced by yoga practice are indeed manifested into improved cognitive performance and/or behavioral changes. Another limitation among the reviewed studies is lack of reported data on the lifestyle characteristics of yoga practitioners. A national survey [ 59 ] found that, compared to the US average, yoga practitioners are more likely to be highly physically active, non-obese, and well-educated – each of which [ 60–62 ] are known to individually contribute to positive changes in brain structure and function. The same survey also found that yoga practitioners are almost four times more likely to follow vegetarian or plant-based diets compared to the US population which could also contribute to brain health [ 63 ]. Future research should examine how the lifestyle characteristics of yoga practitioners may interact with the physical practice of yoga and contribute towards brain function and structure.

Unlike intervention studies and randomized trials, the design of cross-sectional studies limits the control researchers can exert on possible confounding or mediating variables. Most of the cross-sectional studies compare the brains of yoga practitioners with several years of experience to age- and sex-matched yoga-naïve controls. However, only three of these studies matched the groups on the levels of physical activity between the groups or their cardiovascular fitness levels. Moving forward, researchers should conduct well-powered yoga interventions with appropriate controls to examine the neuroimaging outcomes. A variety of cognitive measures and neuroimaging analysis techniques have been used in the literature. Perhaps a foundation would be to test yoga interventions against the established evidence for aerobic exercise and mindfulness practices. Designing randomized controlled trials with exercise and mindfulness comparison groups will allow us to further the literature with the goal of identifying the unique and holistic effects of exercise vs. mindfulness vs. yoga practice.

The literature is too nascent, and it would be premature to dive into comparisons between different styles of yoga practice. This is evident from the studies reviewed as none of them compared the effectiveness of one style of yoga versus another. This question is intertwined with the ‘holistic’ definition of yoga practice as different styles of yoga place greater or lesser emphasis on one or more elements of physical postures, breathing, and meditation. Well-powered randomized control trials are needed not only to identify the ‘active ingredient’ that is driving the yoga effects on brain health, but also examine the synergistic neuro-protective effects of these elements. Lastly, it remains to be determined whether web-based yoga interventions will be as effective as in-person yoga interventions which were primarily utilized in the reviewed papers. There has been an exponential growth in the development of mobile health apps [ 64 ] and it remains to be determined whether web-delivered yoga interventions will be as effective as in-person often group based interventions.

This review of literature reveals promising early evidence that yoga practice can positively impact brain health. Studies suggest that yoga practice may have an effect on the functional connectivity of the DMN, the activity of the dorsolateral prefrontal cortex while engaged in cognitive tasks, and the structure of the hippocampus and prefrontal cortex- all regions known to show significant age-related changes [ 65, 66 ]. Therefore, behavioral interventions like yoga may hold promise to mitigate age-related and neurodegenerative declines. Systematic randomized trials of yoga and its comparison to other exercise-based interventions, as well as long term longitudinal studies on yoga practitioners are needed to identify the extent and scope of neurobiological changes. We hope this review can offer the preliminary groundwork for researchers to identify key brain networks and regions of interest as we move toward advancing the neuroscience of yoga.

Author contributions

NG, JD – conceptualization, analyses and writing. JH – structuring and writing results, figures and tables. IK – review of studies, extraction of data and preparation of Table 1 . EE – revision and writing of the manuscript.

CONFLICT OF INTEREST

The authors have no conflict of interest to report.

Add These 9 Yoga Poses to Your Routine to Boost Your Sleep

Yoga is a great way to relax your body and mind before bed. These are the top nine yoga poses to add to your routine for the ultimate night's sleep.

• Carl R. Greer/Andrew D. Hepburn Award for Best Nonfiction Essay (Miami University, 2020)

• Licensed Psychotherapist
• University of Pennsylvania, BA
• University of Chicago, MSW

Did you have trouble falling asleep last night because your mind was still racing from the day or you were worrying about the next? You aren't alone, and luckily, there are plenty of tricks that can help you fall asleep  (such as reading, drinking a hot cup of herbal tea or journaling ). But if those tips aren't enough, and you're still struggling to get some shut-eye, light exercise could help. 

Yoga for sleep calms your nervous system and helps you relax enough to fall asleep. We've rounded up the best yoga poses to help you drift off more easily.

For more natural ways to get better sleep, try these seven sleep aids for insomnia , or check out our sleep tips from CNET's wellness editors . 

Read more: Best Mattress

How yoga can help you sleep

Yoga, much like any form of exercise, can be a beneficial way to unwind and alleviate stress. Research suggests that engaging in yoga may lead to reduced levels of cortisol , the hormone associated with stress. However, the extent of cortisol reduction may vary depending on factors such as the frequency and intensity of yoga practice. Additionally, some studies have shown promising results regarding yoga's impact on depression symptoms. Yoga can complement traditional treatment approaches and promote overall well-being. So, what does this mean for your sleep? Well, cortisol levels have a significant influence on sleep patterns . Higher cortisol levels are often associated with difficulty falling asleep and staying asleep. A study conducted in 2019 found that incorporating yoga into one's routine can have a positive effect on treating and alleviating symptoms of insomnia. These findings suggest that practicing yoga may offer potential benefits for improving sleep quality and overall sleep health.

9 yoga poses to try before bed

These poses are for any level of experience and easy enough for beginner yogis. While moving between these poses, remember to pay attention to your breath and where you feel most tension in your body. Breathe and try to relax if you experience any discomfort. Move through these poses for about 20 to 30 minutes before bed. 

Read more:   Best Yoga Mats for 2024

Cat-cow pose

To get into this pose, start on your hands and knees. Your hands should be shoulder-width apart, and your knees should be below your hips. Take a deep breath and tilt your head towards the ceiling while also sticking up your pelvis -- this should mimic a "cow." Then, on your exhale, arch your back and bring both your head and pelvis down like a "cat." You can repeat these two motions a few times before moving on. 

Forward fold

This pose is as easy as standing up straight and leaning over to reach for your toes. If you are able, place your hands on the ground. If you are unable to touch your toes, you can do a half-forward fold and grab below your knees. Looking for a challenge? Try reaching around your ankles and hold. Make sure your back is straight and you are taking deep breaths.

Bridge pose

Start by lying down on your back, legs and arms stretched out and on the ground. Take a deep breath, raise your core off the ground and shift your arms closer to your body to balance. Your knees should be at a 90-degree angle. Your hands can lie flat, or you can bring them together underneath your core. 

An easy pose to transition into after Bridge -- start this pose on your back. Lift your legs to the ceiling and out a little past your shoulders (or however far you can go). Then, grab onto the outside of your feet with both hands. Gently rock left and right to relieve tension in your lower back. 

Legs-up-the-wall

You will need to clear a space beside a wall for this pose. Facing the wall, lie on your back and walk your legs up high or lift your hips with your arms. Your hips can be against the wall or a little away. Once you get in a comfortable spot and you feel like you can balance, stretch your arms out beside you. This pose is great for destressing and improving your circulation . 

Child's pose

You can start this pose by kneeling or getting on your hands and knees. Tuck your feet underneath your hips and bring your head close to the ground. Reach your hands out in front of you, stretching your spin. The further out you reach, the better the stretch will be for you. 

Seated twist

If you are coming out of Child's pose for this next one, sit back up and extend your legs out in front of you. Cross one leg over the other, pulling the heel of the crossed leg your outer thigh. With the opposite arm, cross your body and twist yourself, pushing with your elbow on the raised knee. Twist and breathe. Repeat with the other side before moving on. 

Butterfly pose

From a seated position, straighten your posture and press the bottom of both your feet together. Placing your hands on your feet, attempt to press your hips as low as you can to the ground. The lower you go, the bigger the stretch. If you are looking for more of a challenge, move your feet closer to your body. 

Head to knee pose

This is a basic pose. Start in a seated position with your legs out in front of you. Bring one foot to the inner thigh of your opposite leg and extend your hands out over your extended leg. Sit up taller, breath deeply and grab ahold of your foot in front of you. If you can't full reach your foot, no problem: Grab your ankle or the back of your knee. Lean into the stretch and try to bring your forehead to your knee. Repeat on the opposite side.  

Still want more? Learn how getting some sun can improve your sleep , which foods to eat for a happiness boost and how the Scandinavian sleep method might save your relationship.  

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