Differential Distribution of Geriatric Depression and Its Determinants in Community and Old-Age Homes of Mysore

Background: Mental disorders in the elderly are always overlooked and underdiagnosed. The most common neuropsychiatric disorders in this age group are dementia and depression. The geriatric depression variation with respect to different environments will help us to understand its epidemiology. Methods: To estimate and compare the prevalence of geriatric depression and the associated factors in community and old-age homes, a cross-sectional study was carried out in both these settings between august 2017 and april 2018. A sample of 150 was taken in community and old-age homes each. Cluster random sampling and simple random sampling were employed. Geriatric depression scale -15 (GDS-15) was used to assess the depression and mini-mental state examination (MMSE-30) was used to assess cognitive status. Results: Prevalence of geriatric depression in old-age home was 33.3% and in community was 31.2%, but the difference was not statistically significant (p=0.702). However in a subgroup analysis, prevalence of depression in private old-age home was 21.6% and public old-age home was 46.3% and this difference was statistically significant (p = 0.002). Age, marital status, education, socioeconomic status, economic dependency, source of pension, physical dependency and uncorrected hearing/visual impairment were the important predictors of depression. Conclusion: Prevalence of geriatric depression does not significantly vary in community and Old-age home, but it varies with respect to type of Old-age home. Better facilities and good environment in old-age homes may help to reduce depression

­­Eleven tips for operational researchers working with health programmes: our experience based on implementing differentiated tuberculosis care in south India

Due to the workload and lack of a critical mass of trained operational researchers within their ranks, health systems and programmes may not be able to dedicate sufficient time to conducting operational research (OR). Hence, they may need the technical support of operational researchers from research/academic organisations. Additionally, there is a knowledge gap regarding implementing differentiated tuberculosis (TB) care in programme settings. In this ‘how we did it’ paper, we share our experience of implementing a differentiated TB care model along with an inbuilt OR component in Tamil Nadu, a southern state in India. This was a health system initiative through a collaboration of the State TB cell with the Indian Council of Medical Research institutes and the World Health Organisation country office in India. The learnings are in the form of eleven tips: four broad principles (OR on priority areas and make it a health system initiative, implement simple and holistic ideas, embed OR within routine programme settings, aim for long-term engagement), four related to strategic planning (big team of investigators, joint leadership, decentralised decision-making, working in advance) and three about implementation planning (conducting pilots, smart use of e-tools and operational research publications at frequent intervals). These may act as a guide for other Indian states, high TB burden countries that want to implement differentiated care, and for operational researchers in providing technical assistance for strengthening implementation and conducting OR in health systems and programmes (TB or other health programmes). Following these tips may increase the chances of i) an enriching engagement, ii) policy/practice change, and iii) sustainable implementation