IntroductionMillions of children in India still suffer from poor health and under-nutrition, despite substantial improvement over decades of public health programmes. The Anganwadi centres under the Integrated Child Development Scheme (ICDS) provide a range of health and nutrition services to pregnant women, children <6 years and their mothers. However, major gaps exist in ICDS service delivery. The government is currently strengthening ICDS through an mHealth intervention called Common Application Software (ICDS-CAS) installed on smart phones, with accompanying multilevel data dashboards. This system is intended to be a job aid for frontline workers, supervisors and managers, aims to ensure better service delivery and supervision, and enable real-time monitoring and data-based decision-making. However, there is little to no evidence on the effectiveness of such large-scale mHealth interventions integrated with public health programmes in resource-constrained settings on the service delivery and subsequent health and nutrition outcomes.Methods and analysisThis study uses a village-matched controlled design with repeated cross-sectional surveys to evaluate whether ICDS-CAS can enable more timely and appropriate services to pregnant women, children <12 months and their mothers, compared with the standard ICDS programme. The study will recruit approximately 1500 Anganwadi workers and 6000+ mother-child dyads from 400+ matched-pair villages in Bihar and Madhya Pradesh. The primary outcomes are the proportion of beneficiaries receiving (a) adequate number of home visits and (b) appropriate level of counselling by the Anganwadi workers. Secondary outcomes are related to improvements in other ICDS services, and knowledge and practices of the Anganwadi workers and beneficiaries.Ethics and disseminationEthical oversight is provided by the Committee for the Protection of Human Subjects at the University of California at Berkeley, and the Suraksha Independent Ethics Committee in India. The results will be published in peer-reviewed journals and analysis data will be made public.Trial registration numberISRCTN83902145
Background Anganwadi Workers (AWWs) are a group of 1.4 million community health workers that operate throughout rural India as a part of the Integrated Child Development Services program. AWWs are responsible for disseminating key health information regarding nutrition, family planning, and immunizations to the women and children in their catchment area, while maintaining detailed registers that track key beneficiary data, updates on health status, and supply inventory beneficiaries. There is a need to understand how AWWs spend their time on all of these activities given all of their responsibilities, and the factors that are associated with their time use. Methods This cross-sectional study conducted in Madhya Pradesh, collected time use data from AWWs using a standard approach in which we asked participants how much time they spent on various activities. Additionally, we estimated a logistic regression model to elucidate what AWW characteristics are associated with time use. Results We found that AWWs spend substantial amounts of time on administrative tasks, such as filling out their paper registers. Additionally, we explored the associations between various AWW characteristics and their likelihood of spending the expected amount of time on preschool work, filling out their registers, feeding children, and conducting home visits. We found a positive significant association between AWW education and their likelihood of filling out their registers. Conclusions AWWs spend substantial amounts of time on administrative tasks, which could take away from their ability to spend time on providing direct care. Additionally, future research should explore why AWW characteristics matter and how such factors can be addressed to improve AWWs’ performance and should explore the associations between Anganwadi Center characteristics and AWW time use.
Objectives An mHealth job aid and real time monitoring tool currently targets over 1 million community health workers in India (Anganwadi workers – AWWs). Previous studies have shown that mHealth interventions can be effective at a small scale. In this study, we evaluate whether this at-scale mHealth intervention improved the quantity and quality of AWW home visits and counseling. We also examined whether these improvements led to better infant and young child feeding (IYCF) practices among beneficiaries. Methods The mHealth intervention (Common Application Software – CAS) is currently being used by 581,282 AWWs across India. We conducted a village-matched, quasi-experimental design to examine program effectiveness across 428 villages in Madhya Pradesh (MP) and Bihar (BH). Repeated cross-sectional surveys were completed 17–24 months apart with AWWs (n = 1344) and mothers of children < 12 m (n = 6635). We compared post-intervention outcomes between matched groups, controlling for average baseline outcome levels and other covariates to correct for imbalances and improve precision. Program effects were assessed separately within each state. Results In both states, mothers in the intervention group were more likely to receive adequate number of home visits (MP: control = 42%; ß = 9.1%; P < 0.05; BH: control = 24%; ß = 7.7%; P < 0.05). A larger proportion of mothers in the intervention group could recall at least half the life-stage appropriate counseling messages (MP: control = 28.1%; ß = 11.8%. BH: control = 9.5%; ß = 7.7%). However, no improvements in IYCF practices were associated with the intervention. Conclusions mHealth interventions like CAS can support gains in immediate term service delivery outcomes by enabling more age-appropriate home-visits and counseling. However, impacts on nutrition and health behaviors will require a longer-term evaluation and parallel efforts to improve a range of other outcomes, including structural poverty, gender norms, and larger socio-economic and political factors. Funding Sources The Bill and Melinda Gates Foundation.
BackgroundIndia’s 1.4 million community health and nutrition workers (CHNWs) serve 158 million beneficiaries under the Integrated Child Development Services (ICDS) programme. We assessed the impact of a data capture, decision support, and job-aid mobile app for the CHNWs on two primary outcomes—(1) timeliness of home visits and (2) appropriate counselling specific to the needs of pregnant women and mothers of children <12 months.MethodsWe used a quasi-experimental pair-matched controlled trial using repeated cross-sectional surveys to evaluate the intervention in Bihar and Madhya Pradesh (MP) separately using an intention-to-treat analysis. The study was powered to detect difference of 5–9 percentage points (pp) with type I error of 0.05 and type II error of 0.20 with endline sample of 6635 mothers of children <12 months and 2398 pregnant women from a panel of 841 villages.ResultsAmong pregnant women and mothers of children <12 months, recall of counselling specific to the trimester of pregnancy or age of the child as per ICDS guidelines was higher in both MP (11.5pp (95% CI 7.0pp to 16.0pp)) and Bihar (8.0pp (95% CI 5.3pp to 10.7pp)). Significant differences were observed in the proportion of mothers of children <12 months receiving adequate number of home visits as per ICDS guidelines (MP 8.3pp (95% CI 4.1pp to 12.5pp), Bihar: 7.9pp (95% CI 4.1pp to 11.6pp)). Coverage of children receiving growth monitoring increased in Bihar (22pp (95% CI 0.18 to 0.25)), but not in MP. No effects were observed on infant and young child feeding practices.ConclusionThe at-scale app integrated with ICDS improved provision of services under the purview of CHNWs but not those that depended on systemic factors, and was relatively more effective when baseline levels of services were low. Overall, digitally enabling CHNWs can complement but not substitute efforts for strengthening health systems and addressing structural barriers.Trial registration numberISRCTN83902145.
Objectives Implementation research can support iterative program improvement, yet limited examples of such dynamic experiences exist. We conducted a multi-stage and multi-method process evaluation (PE) of a large-scale m-Health intervention in India that currently reaches 581,282 frontline workers (FLWs). The intervention (Common Application Software (CAS)) includes a smartphone application that digitizes FLW service-tracking registers and acts as a job aid and multiple dashboards for real-time monitoring. We examined factors affecting the roll-out of CAS in two Indian states. Methods Program impact pathways were developed with implementers to inform research questions and methods. Data were collected across many time points between 2016 and 2018 to temporally align with program roll-out. In total, we did in-person surveys with FLWs (n = 100), supervisors (n = 55), other staff (n = 18), two phone surveys with FLWs (n = 404), interviews with national and state-level stakeholders (n = 21), and routine meetings with implementers. Short phone surveys were conducted between in-person surveys to give rapid feedback to implementers. Results Impediments to roll-out included state readiness, delays in device procurement and set-up, dashboard readiness, and low data storage space. Over time, FLWs satisfaction with training remained consistent (100–99%), use of CAS (82–100%), and preference to use it (74–80%) increased. Challenges declined over time [e.g., slow internet (79– >58%), battery heating (62– >45%), and network issues (68– >52%). Most FLWs were knowledgeable of CAS but were confused with symbols/colors in certain domains of CAS. Supervisors were satisfied with training, were knowledgeable of CAS, but hardware issues precluded some from using it. Use of the dashboard, a critical feedback mechanism, was limited due to gaps in staff training and version modifications. Conclusions A dynamic and engaged PE implemented with inputs from multiple stakeholders helped provide timely and meaningful feedback to a large-scale program, enabling corrective actions and increasing potential for impact of the program. Implementing a dynamic PE is time and resource intensive and required flexibility in timing and modalities of data collection. Funding Sources Bill & Melinda Gates Foundation, via grants to IFPRI and UCSF.
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