Associations between sociodemographic factors and receiving "ask and advise" services from healthcare providers in India: analysis of the national GATS-2 dataset.

BACKGROUND: India is home to about 12% of the world's tobacco users, with about 1.35 million tobacco-related deaths each year. The morbidity and mortality rates are socially patterned based on gender, rural vs. urban residence, education, and other factors. Following the World Health Organization's guidance, it is critical to offer tobacco users support for cessation as a complement to policy and environmental changes. Such guidance is typically unavailable in low-resource systems, despite the potential for population-level impact. Additionally, service delivery for tobacco control tends to be patterned by sociodemographic factors. To understand current activity in this area, we assessed the percentage of daily tobacco users being asked about tobacco use and advised to quit by a healthcare provider. We also examined social patterning of receipt of services (related to by rural vs. urban residence, age, gender, education, caste, and wealth). METHODS: We analyzed cross-sectional data from India's 2016-2017 Global Adult Tobacco Survey (GATS-2), a nationally representative survey. Among 74,037 respondents, about 25% were daily users of smoked and/or smokeless tobacco. We examined rates of being asked and advised about tobacco use overall and based on rural vs. urban residence, age, gender, education, caste, and wealth. We also conducted multivariate logistic regression to assess the association of demographic and socioeconomic conditions with participants' receipt of "ask and advise" services. RESULTS: Nationally, among daily tobacco users, we found low rates of individuals reporting being asked about tobacco use or advised to quit by a healthcare provider (22% and 19%, respectively). Being asked and advised about tobacco use was patterned by age, gender, education, caste, and wealth in our final regression model. CONCLUSIONS: This study offers a helpful starting point in identifying opportunities to address a critical service delivery gap in India. Given the existing burden on the public health and health systems, scale-up will require innovative, resource-appropriate solutions. The findings also point to the need to center equity in the design and scale-up of tobacco cessation supports so that marginalized and underserved groups will have equitable access to these critical services.

Measuring capacity to use evidence-based interventions in community-based organizations: A comprehensive, scoping review.

Introduction: Community-based organizations (CBOs) are well-positioned to incorporate research evidence, local expertise, and contextual factors to address health inequities. However, insufficient capacity limits use of evidence-based interventions (EBIs) in these settings. Capacity-building implementation strategies are popular, but a lack of standard models and validated measures hinders progress in the field. To advance the literature, we conducted a comprehensive scoping review. Methods: With a reference librarian, we executed a comprehensive search strategy of PubMed/Medline, Web of Science Core Collection, and EBSCO Global Health. We included articles that addressed implementation science, capacity-building, and CBOs. Of 5527 articles, 99 met our inclusion criteria, and we extracted data using a double-coding process. Results: Of the 99 articles, 47% defined capacity explicitly, 31% defined it indirectly, and 21% did not define it. Common concepts in definitions were skills, knowledge/expertise, and resources. Of the 57 articles with quantitative analysis, 48 (82%) measured capacity, and 11 (23%) offered psychometric data for the capacity measures. Of the 99 studies, 40% focused exclusively on populations experiencing inequities and 22% included those populations to some extent. The bulk of the studies came from high-income countries. Conclusions: Implementation scientists should 1) be explicit about models and definitions of capacity and strategies for building capacity, 2) specify expected multi-level implementation outcomes, 3) develop and use validated measures for quantitative work, and 4) integrate equity considerations into the conceptualization and measurement of capacity-building efforts. With these refinements, we can ensure that the necessary supports reach CBO practitioners and critical partners for addressing health inequities.