Quantifying outcome misclassification in multi-database studies: The case study of pertussis in the ADVANCE project

BACKGROUND: The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private collaboration aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines using European healthcare databases. Event misclassification can result in biased estimates. Using different algorithms for identifying cases of Bordetella pertussis (BorPer) infection as a test case, we aimed to describe a strategy to quantify event misclassification, when manual chart review is not feasible. METHODS: Four participating databases retrieved data from primary care (PC) setting: BIFAP: (Spain), THIN and RCGP RSC (UK) and PEDIANET (Italy); SIDIAP (Spain) retrieved data from both PC and hospital settings. BorPer algorithms were defined by healthcare setting, data domain (diagnoses, drugs, or laboratory tests) and concept sets (specific or unspecified pertussis). Algorithm- and database-specific BorPer incidence rates (IRs) were estimated in children aged 0-14 years enrolled in 2012 and 2014 and followed up until the end of each calendar year and compared with IRs of confirmed pertussis from the ECDC surveillance system (TESSy). Novel formulas were used to approximate validity indices, based on a small set of assumptions. They were applied to approximately estimate positive predictive value (PPV) and sensitivity in SIDIAP. RESULTS: The number of cases and the estimated BorPer IRs per 100,000 person-years in PC, using data representing 3,173,268 person-years, were 0 (IR = 0.0), 21 (IR = 4.3), 21 (IR = 5.1), 79 (IR = 5.7), and 2 (IR = 2.3) in BIFAP, SIDIAP, THIN, RCGP RSC and PEDIANET respectively. The IRs for combined specific/unspecified pertussis were higher than TESSy, suggesting that some false positives had been included. In SIDIAP the estimated IR was 45.0 when discharge diagnoses were included. The sensitivity and PPV of combined PC specific and unspecific diagnoses for BorPer cases in SIDIAP were approximately 85% and 72%, respectively. CONCLUSION: Retrieving BorPer cases using only specific concepts has low sensitivity in PC databases, while including cases retrieved by unspecified concepts introduces false positives, which were approximately estimated to be 28% in one database. The share of cases that cannot be retrieved from a PC database because they are only seen in hospital was approximately estimated to be 15% in one database. This study demonstrated that quantifying the impact of different event-finding algorithms across databases and benchmarking with disease surveillance data can provide approximate estimates of algorithm validity

Wellbeing research in developing countries: reviewing the role of qualitative methods

The authors review the contribution of qualitative methods to exploring concepts and experiences of wellbeing among children and adults living in developing countries. They provide examples illustrating the potential of these methods for gaining a holistic and contextual understanding of people’s perceptions and experiences. Some of these come from Young Lives, an innovative long-term international research project investigating the changing nature of child poverty in India, Ethiopia, Peru and Vietnam (http://www.younglives.org.uk), and others from the Wellbeing in Developing Countries ESRC research group (WeD), an international, inter-disciplinary project exploring the social and cultural construction of wellbeing in Bangladesh, Ethiopia, Peru and Thailand (http://www.welldev.org.uk). The authors show how qualitative methods can be used both alongside and as part of the development of sensitive and relevant quantitative measures, and provide some practical and methodological recommendations. They propose that qualitative approaches are essential in understanding people’s experiences of wellbeing, both now and in the future. However, the authors caution that while these offer many benefits, for example, a less structured and hierarchical engagement between researcher and participant; they require time, energy, and sensitivity. Qualitative methods also work best when used by trained and experienced researchers working in the local language/s in a community where some rapport has already been established. Finally, the paper recommends combining data from qualitative and quantitative approaches (e.g. psychological measures or household surveys) to enhance its explanatory power

A mixed-method taxonomy of child poverty - the case of Ethiopia

In this paper, we use mixed methods to develop a taxonomy of poverty and vulnerability to study the situation of children and their households in rural Ethiopia over time. The taxonomy is built using qualitative data from Young Lives, a long-term study of childhood poverty, with the specific purpose of analysing the context of children’s life trajectories using both quantitative and qualitative data. The approach aims to yield insights into changes over time as well as to reflect multiple dimensions and consider issues of current well-being and future ‘well-becoming’. It potentially allows for the identification of underlying mechanisms that influence and determine life trajectories. Until recently, quantitative and qualitative approaches towards the analysis of chronic and transient poverty have developed in isolation with little cross-disciplinary interaction. In this paper, we add to this body of research by using a mixed-method approach to develop a hybrid taxonomy of child poverty and well-being that can be used for a dynamic analysis. The paper also complements existing research and evidence on child poverty and well-being in the context of Ethiopia

Sanitation, Stress, and Life Stage: A Systematic Data Collection Study among Women in Odisha, India

Emerging evidence demonstrates how inadequate access to water and sanitation is linked to psychosocial stress, especially among women, forcing them to navigate social and physical barriers during their daily sanitation routines. We examine sanitation-related psychosocial stress (SRPS) across women's reproductive lives in three distinct geographic sites (urban slums, rural villages, and rural tribal villages) in Odisha, India. We explored daily sanitation practices of adolescent, newly married, pregnant, and established adult women (n = 60) and identified stressors encountered during sanitation. Responding to structured data collection methods, women ranked seven sanitation activities (defecation, urination, menstruation, bathing, post-defecation cleaning, carrying water, and changing clothes) based on stress (high to low) and level of freedom (associated with greatest freedom to having the most restrictions). Women then identified common stressors they encountered when practicing sanitation and sorted stressors in constrained piles based on frequency and severity of each issue. The constellation of factors influencing SRPS varies by life stage and location. Overall, sanitation behaviors that were most restricted (i.e., menstruation) were the most stressful. Women in different sites encountered different stressors, and the level of perceived severity varied based on site and life stage. Understanding the influence of place and life stage on SRPS provides a nuanced understanding of sanitation, and may help identify areas for intervention