Impact of Predictors on the Outcome of Mindfulness-Based Interventions: An Individual Participant Data Review
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Abstract
Introduction
The ever-urbanising landscape is correlated with worsening depression and mental health status[1]. This study explores the impact of different predictors on the outcome of mindfulness-based interventions (MBIs) in improving psychological symptoms.
Method
This study analyzed combined data from six RCTs[2-7] on MBIs for chronic pain, insomnia, menopause, anxiety, caregiver stress, and pregnancy. Well-being outcomes were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D), Five Facet Mindfulness Questionnaire (FFMQ), and SF-12 Physical and Mental Component Summary (PCS & MCS). ANCOVA models with standardized β coefficients assessed predictors (age, sex, religion, marital and employment status) of outcome scale changes, adjusting for baseline scores.
Results
Only statistically significant variables were included. Among adults aged 21-65 with psychological symptoms (n = 1,195), ANCOVA revealed key predictors of treatment outcomes. For depression (CES-D), being married provided the greatest reduction of depressive symptoms (β = -0.089, 95% CI: -0.168 to -0.009, p < 0.05). For SF-12, males demonstrated greater improvements in PCS (β = 0.182, 95% CI: 0.111-0.253, p < 0.001). Being married (β = 0.099, 95% CI: 0.029 to 0.169, p < 0.01) promoted MCS, whereas increasing age (β = -0.111, 95% CI: -0.191 to -0.030, p < 0.01) correlated with poorer mental health status. For mindfulness (FFMQ), religious affiliation demonstrated higher levels of mindfulness (β = 0.082, 95% CI: 0.022-0.141, p < 0.01), while older age showed the greatest reduction (β = -0.078, 95% CI: -0.147 to -0.008, p < 0.05).
Conclusion
Marriage was associated with reduced depressive symptoms and better mental health status, while males predicted greater physical health improvement. Older age was linked to poorer mental health and lower mindfulness, whereas religious affiliation correlated with higher mindfulness. These findings identify key predictors of MBI response, enabling personalized treatments based on patient subgroups.
Article Details
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References
World Health Organization. (2025, March 19). Urban health. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/urban-health
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