While different groups in different contexts are likely to benefit from different interventions, and in some sense, this is especially true for behaviorally informed policies, it is still the case that the fundamental insights, and many of the corresponding barriers, are universal. All humans care about what others think of them, even if the specific reference class (peers, religious leaders, or other categories) varies by age and culture. One implication is that most of the biases discussed, as well as the impacts of targeted programs, do not differ greatly by gender or income, for example. That said, women may be especially receptive to interventions based on aspirations (for themselves or their children), while men are especially unlikely to seek health care and may need additional support in that domain.

Finally, it is worth facing the fact that all interventions, behavioral or otherwise, involve making tradeoffs and considering opportunity costs; this is particularly true in resource- and capacity-constrained settings across much of the world. Fortunately, many behavioral ‘nudges’ can be implemented essentially for free, making them even more relevant in such contexts. This still requires the capacity to take the initiative and to know what to do, for which there are existing sources of external support (such as the World Bank’s eMBeD team) but also a growing number of internal units (see OECD <u>Interactive BI Unit Map). Behavioral</u> organizations exist at either the national or sub-national level in Brazil, Chile, Colombia, India, Lebanon, Peru, South Africa, Tanzania, Tunisia, and Zambia – among others. It should be reiterated that all these policy approaches can be viewed as complements to, not substitutes for, traditional approaches (Bryan et al. 2017). Behavioral measures are often used to build on or leverage existing frameworks, which can therefore ease their adoption from both a financial and political perspective.

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