Search

Prior research in judgment and decision making (JDM) has investigated the effect of problem framing on human preferences. Furthermore, research in JDM documented the absence of such reversal of preferences when making decisions from experience. However, little is known about the effect of context on preferences under the combined influence of problem framing and problem format. Also, little is known about how cognitive models would account for human choices in different problem frames and types (general/specific) in the experience format. One of the primary objectives of this research is to investigate the presence of preference reversals under the influence of problem framing (gain/loss), problem format (experience/description), and problem type (general/specific). Another objective of this research is to develop cognitive models to account for human choices across different problem frames and types in the experience format. A total of 320 participants from India were randomly assigned to one of eight between‐subjects conditions that differed in problem frame, format, and type. Results revealed preference reversals in the description condition; however, they were absent in the experience condition. Moreover, preference reversals were less pronounced in the general problem framing compared to the specific problem framing. Furthermore, specific problems influenced risk‐seeking behavior among participants. We developed cognitive and heuristics models using instance‐based learning theory and natural mean heuristic. Results reveal models' dependency on recent and frequent observations during information sampling. These experience‐based cognitive models could help build artificial intelligence models with fewer preference reversals. This paper focuses on investigating the presence of preference reversals under the influence of problem framing (gain/loss), problem format (experience/description), and problem type (general/specific). Furthermore, Uttrani et al. develop cognitive models using instance‐based learning theory and natural mean heuristic to account for human choices across different problem frames and types in the experience format. [ABSTRACT FROM AUTHOR]

Maternal depression is an important public health concern. We investigated whether a national-scale initiative that provides cash transfers to women giving birth in government health facilities, the Janani Suraksha Yojana (JSY), reduced maternal depression in India’s largest state, Uttar Pradesh. Using primary data on 1695 women collected in early 2015, our quasi-experimental design exploited the fact that some women did not receive the JSY cash due to administrative problems in its disbursement – reasons that are unlikely to be correlated with determinants of maternal depression. We found that receipt of the cash was associated with an 8.5% reduction in the continuous measure of maternal depression and a 36% reduction in moderate depression. There was no evidence of an association with measures of emotional well-being, namely happiness and worry. The results suggest that the JSY had a clinically meaningful effect in reducing the burden of maternal depression, possibly by lessening the financial strain of delivery care. They contribute to the evidence that financial incentive schemes may have public health benefits beyond improving uptake of targeted health services. [ABSTRACT FROM AUTHOR]

Childhood vaccinations are among the most cost-effective health interventions. Yet, in India, where immunisation services are widely available free of charge, a substantial proportion of children remain unvaccinated. We revisit households 30 months after a randomised experiment of a health information intervention designed to educate mothers on the benefits of child vaccination in Uttar Pradesh, India. We find that the large short-term effects on the uptake of diphtheria–pertussis–tetanus and measles vaccination were sustained at 30 months, suggesting the intervention did not simply bring forward vaccinations. We apply causal forests and find that the intervention increased vaccination uptake, but that there was substantial variation in the magnitude of the estimated effects. We conclude that characterising those who benefited most and conversely those who benefited least provides policy-makers with insights on how the intervention worked, and how the targeting of households could be improved. [ABSTRACT FROM AUTHOR]

Background: A prominent strategy to engage private sector health providers in low- and middle-income countries is clinical social franchising, an organisational model that applies the principles of commercial franchising for socially beneficial goals. The Matrika programme, a multi-faceted social franchise model to improve maternal health, was implemented in three districts of Uttar Pradesh, India, between 2013 and 2016. Previous research indicates that the intervention was not effective in improving the quality and coverage of maternal health services at the population level. This paper reports findings from an independent external process evaluation, conducted alongside the impact evaluation, with the aim of explaining the impact findings. It focuses on the main component of the programme, the "Sky" social franchise.Methods: We first developed a theory of change, mapping the key mechanisms through which the programme was hypothesised to have impact. We then undertook a multi-methods study, drawing on both quantitative and qualitative primary data from a wide range of sources to assess the extent of implementation and to understand mechanisms of impact and the role of contextual factors. We analysed the quantitative data descriptively to generate indicators of implementation. We undertook a thematic analysis of the qualitative data before holding reflective meetings to triangulate across data sources, synthesise evidence, and identify the main findings. Finally, we used the framework provided by the theory of change to organise and interpret our findings.Results: We report six key findings. First, despite the franchisor achieving its recruitment targets, the competitive nature of the market for antenatal care meant social franchise providers achieved very low market share. Second, all Sky health providers were branded but community awareness of the franchise remained low. Third, using lower-level providers and community health volunteers to encourage women to attend franchised antenatal care services was ineffective. Fourth, referral linkages were not sufficiently strong between antenatal care providers in the franchise network and delivery care providers. Fifth, Sky health providers had better knowledge and self-reported practice than comparable health providers, but overall, the evidence pointed to poor quality of care across the board. Finally, telemedicine was perceived by clients as an attractive feature, but problems in the implementation of the technology meant its effect on quality of antenatal care was likely limited.Conclusions: These findings point towards the importance of designing programmes based on a strong theory of change, understanding market conditions and what patients value, and rigorously testing new technologies. The design of future social franchising programmes should take account of the challenges documented in this and other evaluations. [ABSTRACT FROM AUTHOR]