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Effect of Brahma Kumaris Rajyoga Meditation on Happiness Index: A Comparative Study among Regular Meditators and Non-Meditators

Shaila Homkar, Prachi Rohtagi

International Journal of Science and Research (IJSR) November 15, 2025 DOI: 10.21275/sr251109100009 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Comparative cross-sectional study Peer reviewed
Sample size 200
Population 100 regular Brahma Kumaris Rajyoga meditators practicing at least 2 years and 100 non-meditators matched for age, gender, and education
Intervention Brahma Kumaris Rajyoga meditation
Duration Practice duration of at least 2 years among meditators
Measures Oxford Happiness Questionnaire (OHQ), Subjective Happiness Scale (SHS)
Topics Meditation
Key findings The abstract states the study's aim and methods but reports no results, so whether Rajyoga meditators scored higher on happiness than non-meditators is not stated. It notes that meditation practices have been associated with increased happiness and psychological well-being, and describes Rajyoga as an open-eyed technique emphasizing soul-consciousness, connection with the Supreme, and self-transformation.

Abstract

Happiness, as an indicator of subjective well-being, reflects emotional balance, contentment, and life satisfaction. Meditation practices have been associated with increased happiness and psychological well-being. Rajyoga Meditation, taught by the Brahma Kumaris World Spiritual University, is a distinctive, open-eyed meditation technique emphasizing soul-consciousness, connection with the Supreme, and self-transformation through elevated thoughts and satvic living. To assess the effect of regular Brahma Kumaris Rajyoga meditation on the Happiness Index a comparative cross-sectional study was conducted among 200 participants?100 regular Rajyoga meditators (practicing ?2 years) and 100 non-meditators matched for age, gender, and education. The Oxford Happiness Questionnaire (OHQ) and Subjective Happiness Scale (SHS) were administered along with sociodemographic details and lifestyle factors. Statistical analyses included independent t-tests and multiple linear regression controlling for confounders (age, gender, education, physical activity, diet).