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Objective To determine the effectiveness of a sanitation campaign that combines "shaming" (i.e. emotional motivators) with subsidies for poor households in rural Orissa, an Indian state with a disproportionately high share of India's child mortality. Methods Using a cluster-randomized design, we selected 20 treatment and 20 control villages in the coastal district of Bhadrak, rural Orissa, for a total sample of 1050 households. We collected sanitation and health data before and after a community-led sanitation project, and we used a difference-in-difference estimator to determine the extent to which the campaign influenced the number of households building and using a latrine. Findings Latrine ownership did not increase in control villages, but in treatment villages it rose from 6% to 32% in the overall sample, from 5% to 36% in households below the poverty line (eligible for a government subsidy) and from 7% to 26% in households above the poverty line (not eligible for a government subsidy). Conclusion Subsidies can overcome serious budget constraints but are not necessary to spur action, for shaming can be very effective by harnessing the power of social pressure and peer monitoring. Through a combination of shaming and subsidies, social marketing can improve sanitation worldwide.Une traduction en français de ce résumé figure à la fin de l'article. Al final del artículo se facilita una traducción al español. ‫املقالة.‬ ‫لهذه‬ ‫الكامل‬ ‫النص‬ ‫نهاية‬ ‫يف‬ ‫الخالصة‬ ‫لهذه‬ ‫العربية‬ ‫الرتجمة‬

To develop a tool for testing internal validity of discrete choice experiment (DCE) data, deploy the program, and collect summary test results from a sample of active health researchers to demonstrate the practical utility of the tool in a wide range of health applications. Methods: A previously developed Gauss program had been in use for testing internal validity. The program was translated to MATLAB and adapted, compiled, and deployed. Sixty-seven authors who had coauthored one or more published DCE studies between 2013 and 2016 were contacted by email; provided access to the tool, instructions, and an example data file; and invited to submit test summaries for tabulation. Results: Twenty-one researchers from 10 countries contributed test results from a total of 55 DCE data sets. Fifty-one studies included at least two out of a possible six tests. Attribute dominance was the most common test, and stability had the highest failure incidence. Only three summaries included a transitivity test, and no failures were detected. Conclusions: It was possible to evaluate multiple internal validity checks for most data sets even when the experimental design did not explicitly include tests. Nevertheless, internal validity is rarely reported. Free availability of the tool for testing data quality could improve both reporting and more careful design of DCE studies to help validate and interpret stated preference data.

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