Mercian Daniel1, Pallab K Maulik2,3,4,5, Sudha Kallakuri6, Amanpreet Kaur1, Siddhardha Devarapalli6, Ankita Mukherjee1, Amritendu Bhattacharya1, Laurent Billot7, Graham Thornicroft8, Devarsetty Praveen9,10,6, Usha Raman11, Rajesh Sagar12, Shashi Kant12, Beverley Essue13, Susmita Chatterjee1,9,10, Shekhar Saxena14, Anushka Patel7, David Peiris7. 1. The George Institute for Global Health, New Delhi, India. 2. The George Institute for Global Health, New Delhi, India. pmaulik@georgeinstitute.org.in. 3. University of New South Wales, Sydney, Australia. pmaulik@georgeinstitute.org.in. 4. Prasanna School of Public Health, Manipal, India. pmaulik@georgeinstitute.org.in. 5. The George Institute for Global Health, Oxford, UK. pmaulik@georgeinstitute.org.in. 6. The George Institute for Global Health, Hyderabad, India. 7. The George Institute for Global Health, University of New South Wales, Sydney, Australia. 8. Centre for Global Mental Health and Centre for Implementation Science, Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. 9. University of New South Wales, Sydney, Australia. 10. Prasanna School of Public Health, Manipal, India. 11. University of Hyderabad, Hyderabad, India. 12. All India Institute of Medical Sciences, New Delhi, India. 13. Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada. 14. Harvard T H Chan School of Public Health, Boston, USA.
Abstract
BACKGROUND: Around 1 in 7 people in India are impacted by mental illness. The treatment gap for people with mental disorders is as high as 75-95%. Health care systems, especially in rural regions in India, face substantial challenges to address these gaps in care, and innovative strategies are needed. METHODS: We hypothesise that an intervention involving an anti-stigma campaign and a mobile-technology-based electronic decision support system will result in reduced stigma and improved mental health for adults at high risk of common mental disorders. It will be implemented as a parallel-group cluster randomised, controlled trial in 44 primary health centre clusters servicing 133 villages in rural Andhra Pradesh and Haryana. Adults aged ≥ 18 years will be screened for depression, anxiety and suicide based on Patient Health Questionnaire (PHQ-9) and Generalised Anxiety Disorders (GAD-7) scores. Two evaluation cohorts will be derived-a high-risk cohort with elevated PHQ-9, GAD-7 or suicide risk and a non-high-risk cohort comprising an equal number of people not at elevated risk based on these scores. Outcome analyses will be conducted blinded to intervention allocation. EXPECTED OUTCOMES: The primary study outcome is the difference in mean behaviour scores at 12 months in the combined 'high-risk' and 'non-high-risk' cohort and the mean difference in PHQ-9 scores at 12 months in the 'high-risk' cohort. Secondary outcomes include depression and anxiety remission rates in the high-risk cohort at 6 and 12 months, the proportion of high-risk individuals who have visited a doctor at least once in the previous 12 months, and change from baseline in mean stigma, mental health knowledge and attitude scores in the combined non-high-risk and high-risk cohort. Trial outcomes will be accompanied by detailed economic and process evaluations. SIGNIFICANCE: The findings are likely to inform policy on a low-cost scalable solution to destigmatise common mental disorders and reduce the treatment gap for under-served populations in low-and middle-income country settings. TRIAL REGISTRATION: Clinical Trial Registry India CTRI/2018/08/015355 . Registered on 16 August 2018.
BACKGROUND: Around 1 in 7 people in India are impacted by mental illness. The treatment gap for people with mental disorders is as high as 75-95%. Health care systems, especially in rural regions in India, face substantial challenges to address these gaps in care, and innovative strategies are needed. METHODS: We hypothesise that an intervention involving an anti-stigma campaign and a mobile-technology-based electronic decision support system will result in reduced stigma and improved mental health for adults at high risk of common mental disorders. It will be implemented as a parallel-group cluster randomised, controlled trial in 44 primary health centre clusters servicing 133 villages in rural Andhra Pradesh and Haryana. Adults aged ≥ 18 years will be screened for depression, anxiety and suicide based on Patient Health Questionnaire (PHQ-9) and Generalised Anxiety Disorders (GAD-7) scores. Two evaluation cohorts will be derived-a high-risk cohort with elevated PHQ-9, GAD-7 or suicide risk and a non-high-risk cohort comprising an equal number of people not at elevated risk based on these scores. Outcome analyses will be conducted blinded to intervention allocation. EXPECTED OUTCOMES: The primary study outcome is the difference in mean behaviour scores at 12 months in the combined 'high-risk' and 'non-high-risk' cohort and the mean difference in PHQ-9 scores at 12 months in the 'high-risk' cohort. Secondary outcomes include depression and anxiety remission rates in the high-risk cohort at 6 and 12 months, the proportion of high-risk individuals who have visited a doctor at least once in the previous 12 months, and change from baseline in mean stigma, mental health knowledge and attitude scores in the combined non-high-risk and high-risk cohort. Trial outcomes will be accompanied by detailed economic and process evaluations. SIGNIFICANCE: The findings are likely to inform policy on a low-cost scalable solution to destigmatise common mental disorders and reduce the treatment gap for under-served populations in low-and middle-income country settings. TRIAL REGISTRATION: Clinical Trial Registry India CTRI/2018/08/015355 . Registered on 16 August 2018.
Entities:
Keywords:
Anti-stigma campaign; Cluster randomised controlled trial; Common mental disorders; Electronic decision support systems; Implementation; India; Primary healthcare worker; SMART Mental Health
Authors: Brendan Mulhern; Clara Mukuria; Michael Barkham; Martin Knapp; Sarah Byford; Djøra Soeteman; John Brazier Journal: Br J Psychiatry Date: 2014-05-22 Impact factor: 9.319
Authors: Vikram Patel; Shekhar Saxena; Crick Lund; Graham Thornicroft; Florence Baingana; Paul Bolton; Dan Chisholm; Pamela Y Collins; Janice L Cooper; Julian Eaton; Helen Herrman; Mohammad M Herzallah; Yueqin Huang; Mark J D Jordans; Arthur Kleinman; Maria Elena Medina-Mora; Ellen Morgan; Unaiza Niaz; Olayinka Omigbodun; Martin Prince; Atif Rahman; Benedetto Saraceno; Bidyut K Sarkar; Mary De Silva; Ilina Singh; Dan J Stein; Charlene Sunkel; JÜrgen UnÜtzer Journal: Lancet Date: 2018-10-09 Impact factor: 79.321
Authors: Elizabeth Murray; Shaun Treweek; Catherine Pope; Anne MacFarlane; Luciana Ballini; Christopher Dowrick; Tracy Finch; Anne Kennedy; Frances Mair; Catherine O'Donnell; Bie Nio Ong; Tim Rapley; Anne Rogers; Carl May Journal: BMC Med Date: 2010-10-20 Impact factor: 8.775
Authors: Vikram Patel; Benedict Weobong; Helen A Weiss; Arpita Anand; Bhargav Bhat; Basavraj Katti; Sona Dimidjian; Ricardo Araya; Steve D Hollon; Michael King; Lakshmi Vijayakumar; A-La Park; David McDaid; Terry Wilson; Richard Velleman; Betty R Kirkwood; Christopher G Fairburn Journal: Lancet Date: 2016-12-15 Impact factor: 79.321