Effective interventions for improving routine childhood immunisation in low and middle-income countries: a systematic review of systematic reviews.

OBJECTIVE: An umbrella review providing a comprehensive synthesis of the interventions that are effective in providing routine immunisation outcomes for children in low and middle-income countries (L&MICs). DESIGN: A systematic review of systematic reviews, or an umbrella review. DATA SOURCES: We comprehensively searched 11 academic databases and 23 grey literature sources. The search was adopted from an evidence gap map on routine child immunisation sector in L&MICs, which was done on 5 May 2020. We updated the search in October 2021. ELIGIBILITY CRITERIA: We included systematic reviews assessing the effectiveness of any intervention on routine childhood immunisation outcomes in L&MICs. DATA EXTRACTION AND SYNTHESIS: Search results were screened by two reviewers independently applying predefined inclusion and exclusion criteria. Data were extracted by two researchers independently. The Specialist Unit for Review Evidence checklist was used to assess review quality. A mixed-methods synthesis was employed focusing on meta-analytical and narrative elements to accommodate both the quantitative and qualitative information available from the included reviews. RESULTS: 62 systematic reviews are included in this umbrella review. We find caregiver-oriented interventions have large positive and statistically significant effects, especially those focusing on short-term sensitisation and education campaigns as well as written messages to caregivers. For health system-oriented interventions the evidence base is thin and derived from narrative synthesis suggesting positive effects for home visits, mixed effects for pay-for-performance schemes and inconclusive effects for contracting out services to non-governmental providers. For all other interventions under this category, the evidence is either limited or not available. For community-oriented interventions, a recent high-quality mixed-methods review suggests positive but small effects. Overall, the evidence base is highly heterogenous in terms of scope, intervention types and outcomes. CONCLUSION: Interventions oriented towards caregivers and communities are effective in improving routine child immunisation outcomes. The evidence base on health system-oriented interventions is scant not allowing us to reach firm conclusions, except for home visits. Large evidence gaps exist and need to be addressed. For example, more high-quality evidence is needed for specific caregiver-oriented interventions (eg, monetary incentives) as well as health system-oriented (eg, health workers and data systems) and community-oriented interventions. We also need to better understand complementarity of different intervention types.

Gender Inclusivity of India's Digital Financial Revolution for Attainment of SDGs: Macro Achievements and the Micro Experiences of Targeted Initiatives.

For decades, India has led the drive for financial inclusion of poor rural women to facilitate attainment of development objectives like poverty alleviation and women's empowerment. More recently, it has promoted digital financial inclusion to further its fight against poverty and gender inequality and support the attainment of UN's Sustainable Development Goals (SDGs). In this paper we take stock of how India's digital financial revolution has affected financial transactions and services with a focus on gender inclusivity for the attainment of the SDGs. We propose a framework to understand the gender inclusivity of digital financial inclusion initiatives that connects the macro developments in the sector with the micro-level experiences of improving women's access and use of these services. We draw on India's nationwide developments and present a case study of an initiative that specifically promotes gender inclusive finance. Our findings suggest that India has made great advances in promoting digital financial inclusion but at the same time, the country has struggled to achieve gender parity even within specific finance-focused programmes designed to improve gender inclusivity. We reflect on policy implications of these findings.

Pendant des décennies, l'Inde s'est positionnée en tête de l'élan en faveur de l'inclusion financière des femmes rurales vivant dans la pauvreté, dans le but d'atteindre des objectifs de développement tels que la réduction de la pauvreté et l'autonomisation des femmes. Plus récemment, le pays a promu l'inclusion financière numérique pour poursuivre sa lutte contre la pauvreté et l'inégalité entre les sexes et soutenir la réalisation des objectifs de développement durable (ODD) des Nations Unies. Dans cet article, nous faisons le point sur la façon dont la révolution financière numérique de l'Inde a affecté les transactions et les services financiers en mettant l'accent sur l'inclusion du genre pour la réalisation des ODD. Nous proposons un cadre pour comprendre l'inclusion de l'approche genre dans les initiatives d'inclusion financière numérique qui relie les développements macro dans le secteur avec les expériences au niveau micro de l'amélioration de l'accès et de l'utilisation de ces services par les femmes. Nous nous appuyons sur les développements à l'échelle nationale en Inde et présentons une étude de cas d'une initiative qui promeut spécifiquement la finance inclusive. Nos résultats suggèrent que l'Inde a fait de grands progrès dans la promotion de l'inclusion financière numérique, mais qu'en même temps, le pays a eu du mal à atteindre la parité entre les sexes, même dans le cadre de programmes spécifiques axés sur la finance conçus pour améliorer l'inclusion des femmes. Nous menons une réflexion quant aux implications politiques de ces résultats.

Quasi-experimental study designs series-paper 9: collecting data from quasi-experimental studies.

OBJECTIVE: To identify variables that must be coded when synthesizing primary studies that use quasi-experimental designs. STUDY DESIGN AND SETTING: All quasi-experimental (QE) designs. RESULTS: When designing a systematic review of QE studies, potential sources of heterogeneity-both theory-based and methodological-must be identified. We outline key components of inclusion criteria for syntheses of quasi-experimental studies. We provide recommendations for coding content-relevant and methodological variables and outlined the distinction between bivariate effect sizes and partial (i.e., adjusted) effect sizes. Designs used and controls used are viewed as of greatest importance. Potential sources of bias and confounding are also addressed. CONCLUSION: Careful consideration must be given to inclusion criteria and the coding of theoretical and methodological variables during the design phase of a synthesis of quasi-experimental studies. The success of the meta-regression analysis relies on the data available to the meta-analyst. Omission of critical moderator variables (i.e., effect modifiers) will undermine the conclusions of a meta-analysis.

Quasi-experimental study designs series-paper 10: synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges.

OBJECTIVE: To outline issues of importance to analytic approaches to the synthesis of quasi-experiments (QEs) and to provide a statistical model for use in analysis. STUDY DESIGN AND SETTING: We drew on studies of statistics, epidemiology, and social-science methodology to outline methods for synthesis of QE studies. The design and conduct of QEs, effect sizes from QEs, and moderator variables for the analysis of those effect sizes were discussed. RESULTS: Biases, confounding, design complexities, and comparisons across designs offer serious challenges to syntheses of QEs. Key components of meta-analyses of QEs were identified, including the aspects of QE study design to be coded and analyzed. Of utmost importance are the design and statistical controls implemented in the QEs. Such controls and any potential sources of bias and confounding must be modeled in analyses, along with aspects of the interventions and populations studied. Because of such controls, effect sizes from QEs are more complex than those from randomized experiments. A statistical meta-regression model that incorporates important features of the QEs under review was presented. CONCLUSION: Meta-analyses of QEs provide particular challenges, but thorough coding of intervention characteristics and study methods, along with careful analysis, should allow for sound inferences.