Interplaying role of healthcare activist and homemaker: a mixed-methods exploration of the workload of community health workers (Accredited Social Health Activists) in India.

BACKGROUND: Globally, community health workers (CHWs) are integral contributors to many health systems. In India, Accredited Social Health Activists (ASHAs) have been deployed since 2005. Engaged in multiple health care activities, they are a key link between the health system and population. ASHAs are expected to participate in new health programmes prompting interest in their current workload from the perspective of the health system, community and their family. METHODS: This mixed-methods design study was conducted in rural and tribal Primary Health Centers (PHCs), in Pune district, Western Maharashtra, India. All ASHAs affiliated with these PHCs were invited to participate in the quantitative study, those agreeing to contribute in-depth interviews (IDI) were enrolled in an additional qualitative study. Key informants' interviews were conducted with the Auxiliary Nurse Midwife (ANM), Block Facilitators (BFF) and Medical Officers (MO) of the same PHCs. Quantitative data were analysed using descriptive statistics. Qualitative data were analysed thematically. RESULTS: We recruited 67 ASHAs from the two PHCs. ASHAs worked up to 20 h/week in their village of residence, serving populations of approximately 800-1200, embracing an increasing range of activities, despite a workload that contributed to feelings of being rushed and tiredness. They juggled household work, other paid jobs and their ASHA activities. Practical problems with travel added to time involved, especially in tribal areas where transport is lacking. Their sense of benefiting the community coupled with respect and recognition gained in village brought happiness and job satisfaction. They were willing to take on new tasks. ASHAs perceived themselves as 'voluntary community health workers' rather than as 'health activists". CONCLUSIONS: ASHAs were struggling to balance their significant ASHA work and domestic tasks. They were proud of their role as CHWs and willing to take on new activities. Strategies to recruit, train, skills enhancement, incentivise, and retain ASHAs, need to be prioritised. Evolving attitudes to the advantages/disadvantages of current voluntary status and role of ASHAs need to be understood and addressed if ASHAs are to be remain a key component in achieving universal health coverage in India.

Determinants and patterns of care-seeking for childhood illness in rural Pune District, India.

BACKGROUND: An estimated 1.2 million children under five years of age die each year in India, with pneumonia and diarrhea among the leading causes. Increasing care-seeking is important to reduce mortality and morbidity from these causes. This paper explores the determinants and patterns of care-seeking for childhood illness in rural Pune district, India. METHODS: Mothers having at least one child <5 years from the study area of the Vadu Health and Demographic Surveillance System were enrolled in a prospective cohort study. Household sociodemographic information was collected through a baseline questionnaire administered at enrollment. Participants were visited up to six times between July 2015 and February 2016 to collect information on recent childhood acute illness and associated care-seeking behavior. Multivariate logistic regression explored the associations between care-seeking and child, participant, and household characteristics. RESULTS: We enrolled 743 mothers with 1066 eligible children, completing 2585 follow-up interviews (90% completion). Overall acute illness prevalence in children was 26% with care sought from a health facility during 71% of episodes. Multivariable logistic regression showed care-seeking was associated with the number of reported symptoms (Odds ratio (OR) = 2.4, 95% confidence interval (CI) = 1.5-3.9) and household insurance coverage (OR = 2.2, 95% CI = 1.1-4.3). We observed an interaction between the associations of illness severity and maternal employment on care-seeking. Somewhat-to-very severe illness was associated with increased care-seeking among both employed (OR = 5.0, 95% CI = 2.2-11.1) and currently unemployed mothers (OR = 7.0, 95% CI = 3.9-12.6). Maternal employment was associated with reduced care-seeking for non-severe illness (OR = 0.3, 95% CI = 0.1-0.7), but not associated with care-seeking for somewhat-to-very severe illness. Child sex was not associated with care-seeking. CONCLUSIONS: This study demonstrates the importance of illness characteristics in determining facility-based care-seeking while also suggesting that maternal employment resulted in decreased care-seeking among non-severe illness episodes. The nature of the association between maternal employment and care-seeking is unclear and should be explored through additional studies. Similarly, the absence of male bias in care-seeking should be examined to assess for potential bias at other stages in the management of childhood illness.

Validating a GPS-based approach to detect health facility visits against maternal response to prompted recall survey.

INTRODUCTION: Common approaches to measure health behaviors rely on participant responses and are subject to bias. Technology-based alternatives, particularly using GPS, address these biases while opening new channels for research. This study describes the development and implementation of a GPS-based approach to detect health facility visits in rural Pune district, India. METHODS: Participants were mothers of under-five year old children within the Vadu Demographic Surveillance area. Participants received GPS-enabled smartphones pre-installed with a location-aware application to continuously record and transmit participant location data to a central server. Data were analyzed to identify health facility visits according to a parameter-based approach, optimal thresholds of which were calibrated through a simulation exercise. Lists of GPS-detected health facility visits were generated at each of six follow-up home visits and reviewed with participants through prompted recall survey, confirming visits which were correctly identified. Detected visits were analyzed using logistic regression to explore factors associated with the identification of false positive GPS-detected visits. RESULTS: We enrolled 200 participants and completed 1098 follow-up visits over the six-month study period. Prompted recall surveys were completed for 694 follow-up visits with one or more GPS-detected health facility visits. While the approach performed well during calibration (positive predictive value (PPV) 78%), performance was poor when applied to participant data. Only 440 of 22 251 detected visits were confirmed (PPV 2%). False positives increased as participants spent more time in areas of high health facility density (odds ratio (OR) = 2.29, 95% confidence interval (CI) = 1.62-3.25). Visits detected at facilities other than hospitals and clinics were also more likely to be false positives (OR = 2.78, 95% CI = 1.65-4.67) as were visits detected to facilities nearby participant homes, with the likelihood decreasing as distance increased (OR = 0.89, 95% CI = 0.82-0.97). Visit duration was not associated with confirmation status. CONCLUSIONS: The optimal parameter combination for health facility visits simulated by field workers substantially overestimated health visits from participant GPS data. This study provides useful insights into the challenges in detecting health facility visits where providers are numerous, highly clustered within urban centers and located near residential areas of the population which they serve.

Assessing the reactivity to mobile phones and repeated surveys on reported care-seeking for common childhood illnesses in rural India.

BACKGROUND: Traditionally, health care-seeking for child illness is assessed through population-based and nationally representative demographic and health surveys (DHS) that are conducted once every five to seven years and are based on maternal recall. These maternal reports are subject to recall bias. Mobile phones (with the use of GPS technology) have the potential to constantly track movements of phone owners and provide high quality and more accurate data at a population level in low and middle income countries (LMICs) to assess the validity of maternal recall. We provided a group of mothers with smartphones installed with a location-aware application and visited them monthly to administer a survey questionnaire on care-seeking for diarrhoea, fever and cough with fever. This paper assesses for any reactivity to smartphones or repeated study contacts for measuring care-seeking and if this resulted in change in health care provider preference. METHODS: We enrolled 749 mothers from rural areas of Pune district in Maharashtra, India and randomly allocated them to one of three groups - a longitudinal phone group, a longitudinal control group and a cross-sectional control group. We collected baseline information from mothers, including individual and household demographic and socio-economic characteristics and care-seeking preferences for child illness. We followed up both longitudinal groups monthly and each cross-sectional sub-group once over a period of 6 months. At each follow up, we administered questions identical to those in the National Family Health Survey (NFHS) questionnaire to determine an episode of diarrhoea, fever or cough within the last 15 days, care seeking for the same, and the type of provider. The data were analysed using the χ2 test or Fisher Exact Test for categorical variables, or with the Kruskall-Wallis non-parametric test for continuous variables (due to the non-normal nature of the data). Multivariable joint models of group and visit time were analysed with logistic regression methods. RESULTS: All three groups were similar in their socio-demographic characteristics at baseline. We did not observe any significant difference in care seeking for diarrhoea, fever or cough with fever between groups. Also, we did not observe any significant difference in proportion of children seeking care from the private sector. CONCLUSIONS: We did not observe any reactivity in this study due to the presence of the phone (Hawthorne effect) or repeated study visits. The study also shows the potential of using GPS enabled smartphones to enrich DHS surveys in LMICs like India. However, further studies need to be conducted in other population groups before the findings can be generalised.

Concordance between GPS-based smartphone app for continuous location tracking and mother's recall of care-seeking for child illness in India.

BACKGROUND: Traditionally, health care-seeking behaviour for child illness is assessed through population-based national demographic and health surveys. GPS-based technologies are increasingly used in human behavioural research including tracking human mobility and spatial behaviour. This paper assesses how well a care-seeking event to a health care facility for child illness, as recalled by the mother in a survey setting using questions sourced from Demographic and Health Surveys, concurs with one that is identified by TrackCare, a GPS-based location-aware smartphone application. METHODS: Mothers residing in the Vadu HDSS area in Pune district, India having at least one young child were randomly assigned to receive a GPS-enabled smartphone with a pre-installed TrackCare app configured to record the device location data at one-minute intervals over a 6-month period. Spatio-temporal parameters were derived from the location data and used to detect a care-seeking event to any of the health care facilities in the area. Mothers were asked to recall a child illness and if, where and when care was sought, using a questionnaire during monthly visits over a 6-month period. Concordance between the mother's recall and the TrackCare app to identify a care-seeking event was estimated according to percent positive agreement. RESULTS: Mean concordance for a care-seeking event between the two methods (mother's recall and TrackCare location data) ranged up to 45%, was significantly higher (P-value <0.001) for care-seeking at a hospital as compared to a clinic and for a health care facility in the private sector compared to that in the public sector. Overall, the proportion of disagreement for a care-seeking event not detected by TrackCare but reported by mother ranged up to 77% and was significantly higher (P-value <0.001) compared to those not reported by mother but detected by TrackCare. CONCLUSIONS: Given the uncertainty and limitations in use of continuous location tracking data in a field setting and the complexity of classifying human activity patterns, additional research is needed before continuous location tracking can serve as a gold standard substitute for other methods to determine health care-seeking behaviour. Future performance may be improved by incorporating other smartphone-based sensors, such as Wi-Fi and Bluetooth, to obtain more precise location estimates in areas where GPS signal is weakest.