Effectiveness of yoga therapy as a complementary treatment for major psychiatric disorders: a meta-analysis

Abstract

Objective: To examine the efficacy of yoga therapy as a complementary treatment for psychiatric disorders such as schizophrenia, depression, anxiety, and posttraumatic stress disorder (PTSD).

Data sources: Eligible trials were identified by a literature search of PubMed/MEDLINE, Cochrane Control Trials Register, Google Scholar, and EBSCO on the basis of criteria of acceptable quality and relevance. The search was performed using the following terms: yoga for schizophrenia, yoga for depression, yoga for anxiety, yoga for PTSD, yoga therapy, yoga for psychiatric disorders, complementary treatment, and efficacy of yoga therapy. Trials both unpublished and published with no limitation placed on year of publication were included; however, the oldest article included in the final meta-analysis was published in 2000.

Study selection: All available randomized, controlled trials of yoga for the treatment of mental illness were reviewed, and 10 studies were eligible for inclusion. As very few randomized, controlled studies have examined yoga for mental illness, this meta-analysis includes studies with participants who were diagnosed with mental illness, as well as studies with participants who were not diagnosed with mental illness but reported symptoms of mental illness. Trials were excluded due to the following: (1) insufficient information, (2) inadequate statistical analysis, (3) yoga was not the central component of the intervention, (4) subjects were not diagnosed with or did not report experiencing symptoms of one of the psychiatric disorders of interest (ie, schizophrenia, depression, anxiety, and PTSD), (5) study was not reported in English, and (6) study did not include a control group.

Data extraction: Data were extracted on participant diagnosis, inclusion criteria, treatment and control groups, duration of intervention, and results (pre-post mean and standard deviations, t values, and f values). Number, age, and sex ratio of participants were also obtained when available.

Data synthesis: The combined analysis of all 10 studies provided a pooled effect size of -3.25 (95% CI, -5.36 to -1.14; P = .002), indicating that yoga-based interventions have a statistically significant effect as an adjunct treatment for major psychiatric disorders. Findings in support of alternative and complementary interventions may especially be an aid in the treatment of disorders for which current treatments are found to be inadequate or to carry severe liabilities.

Conclusions: As current psychopharmacologic interventions for severe mental illness are associated with increased risk of weight gain as well as other metabolic side effects that increase patients' risk for cardiovascular disease, yoga may be an effective, far less toxic adjunct treatment option for severe mental illness.

Figure 1

Forest Plot of the 10 Studies Included in the Analysis^{a a}The forest plot displays the measure of effect of each individual study, as well as the meta-analyzed measure of effect. The plot of measure of effect for each of these studies is represented by ■, <, or >, with confidence intervals represented by horizontal lines. The overall meta-analyzed measure of effect is plotted as the diamond, the lateral points of which indicate confidence intervals for this estimate. The plot reveals that the included studies significantly favor yoga treatment over the treatments other than yoga-based practices.

Figure 2

Funnel Plot of Standard Error by Standard Difference in Means^{a a}The funnel plot is asymmetric, with a relatively high number of studies falling toward the left of the mean effect and relatively few falling toward the right. The asymmetric plot revealed publication bias.

Figure 3

Funnel Plot of Standard Error by Log Odds Ratio^{a a}The trim and fill method asks how the effect would shift if there were no publication bias by allowing us to impute missing studies. Using the random-effects model, no studies are missing. However, under a fixed-effects model, the trim and fill method displays 4 missing studies to the right of the mean. This funnel plot, a representation of the fixed-effects model, includes both observed studies and the 4 imputed studies by the black dots as well as the shift in the effect size.