Social Norms Measurement: Catching up With Programs and Moving the Field Forward

To date, there are numerous normative change programs for AYSRH in the field and going to scale [1]. Many of these are doing so, however, with scant evidence of the desired normative change outcomes, resulting largely from the fact that social norms' measurement has lagged behind [2], [3]. As programs are developed to shift social norms to improve adolescent and youth sexual and reproductive health (AYSRH) outcomes, rigorous but practical approaches are needed to identify the social norms that are influencing behaviors, measure changes in social norms, and understand how these changes impact behavioral outcomes. The Learning Collaborative (LC) Measurement Community was convened with the goal of enhancing the ability of practitioners to measure social norms. Over the last 2 years, we have endeavored to do so both through ongoing dialogue and by compiling and sharing social norms measurement approaches and tools, which are now publicly available on the Advancing Learning and Innovation in Gender Norms (ALIGN) platform (www.alignplatform.org). Through these efforts, we have discussed several of the central challenges to social norms measurement and come to consensus around some specific approaches that can be taken now to improve social norms measurement and a few of the questions that remain to be answered.

Perhaps, the most obvious challenge of social norms measurement is their multifaceted nature. Social norms measurement typically entails assessment of (1) a generally practiced behavior (descriptive norm), (2) beliefs or attitudes about what is acceptable (injunctive norms), (3) the group of people who share these practices and attitudes (reference group), and (4) whether complying or not complying with the norm results in positive or negative reactions from others (sanctions). Further adding to the measurement burden is the fact that individuals often identify as members of multiple reference groups and may hold different, possibly contrasting, normative beliefs within these different groups. For instance, youth may perceive approval of premarital sex among peers in their community but disapproval of premarital sex in their religious community. As part of our review of tools for the ALIGN platform, we documented that most programmatic tools use survey items with prespecified generalized reference groups, often without grounding their choice into context-specific evidence. Doing so, practitioners might focus their intervention on the wrong reference groups, thereby reducing the effectiveness of their work. However, the time and cost associated with measuring each of these facets comprehensively can render social norms measurement impractical within the scope of many programs.

The presence of common underlying norms suggests that some degree of generalization may reduce some of the measurement burden and offer advantages such as greater objectivity and comparability across contexts, and simplicity of interpretation. At present, however, there is little guidance on how to efficiently measure social norms, especially cross-culturally [4], [5]. Some progress is being made in the measurement of social norms related to certain AYSRH-related behaviors [6], but another challenge, as illustrated in the conceptual framework put forth by the LC Theory Community [7], is that social norms are highly context specific. For instance, while there are many common norms related to AYSRH that exist across many contexts, this does not mean that norms are uniformly associated with the same behavioral outcomes nor amenable to change via the same health intervention strategies.

A question arises, thus, as to whether the focus of current quantitative measures alone can inform intervention design. The theory of normative influence by Cislaghi and Heise, for instance, suggests that measuring the prevalence of a normative belief is not enough to understand the influence that the norm has on the behavior of interest [8]. Take as an example a context in which many in a group report that sexually active adolescents in their community are expected to get tested for HIV, but rates of testing are low, and there are no positive sanctions for those who actually do. An intervention might, thus, work on this protective norm and help people speak publicly and positively about those adolescents who comply with that norm. Strategies that practitioners can adopt to measure the strength of a norm are now emerging. An example is CARE's Social Norms Analysis Plot framework [9]. The Social Norms Analysis Plot helps elicit participants' opinions on the strength of anticipated sanctions for transgressing a norm.

Alternatively, and in the meantime, qualitative assessment may lend itself better to discerning some of the context-specific and dynamic aspects of social norms. For instance, we would suggest that formative approaches exist and can and should be used to determine if and what social norms are at play in a specific context and within the larger socioecological system [10]. Formative approaches, such as those using participatory learning and action techniques, can provide researchers and implementers with information to inform norms measures such as when and under what conditions social norms affect behavior and whether and what sanctions influence a behavior. Also during the formative phase, attention should be given to appropriately identifying reference groups. We advocate for allowing respondents, whether through qualitative inquiry, open-ended questions, or social network approaches, to identify their own reference groups as well as the actors or groups with the greatest influence over their behavior. Vignettes can also allow respondents to paint a more nuanced, holistic picture of how norms and reference groups fit into decision-making and behaviors within a given setting.

Another critical question that is currently being debated in the social norms measurement world is whether programs can repurpose indicators and measures in existing data sets as proxies of social norms. To date, aggregating individual-level responses (i.e., collective attitudes, collective behaviors, anticipation of sanctions) has been shown to be informative about normative behaviors and attitudes existing within a bounded area [11], [12], [13]. Nevertheless, research is ongoing and still needed to determine just how similar existing measures of personal attitudes are to perceived social norm responses, which are most closely linked to behavioral outcomes, what the programmatic implications are of these differences and what the most informative and feasible level of data aggregation should be [14], [15]. Specifically, with regard to the latter question, candidates for data aggregation level range from very small groups (e.g., households), to moderately sized groups (e.g., villages in rural areas, neighborhoods in urban areas), to much larger groups (e.g., countries as a whole). Also unclear is whether boundaries other than geographical ones (e.g., ethnicity, group membership etc.) could be used for the aggregation of social norms proxies as well as their corresponding reference groups. Fortunately, a variety of data sources exist with which these questions about the development of social norms proxies can be assessed. For instance, measures of attitudes around gender norms and the acceptability of violence are available for countries spanning nearly every continent through a number of international surveys such as the Demographic and Health Surveys and the International Men and Gender Equality Surveys. Many of these data sets include other data on related behaviors and attitudes (e.g., the India Demographic and Health Surveys includes extensive data on women's mobility and related attitudes) and if paired with other data sets (e.g. the World Value Survey or the Generations and Gender Programme) as well as sufficiently rigorous modeling techniques, such as multilevel modeling, could be powerful tools to approximate existence of norms [5].

Social norm change interventions will likely be a mainstay of AYSRH programming efforts. To ensure that evidence-based interventions are developed and scaled-up, more work is needed to improve social norm measurement. To address these challenges and critical questions, we must capitalize on the interest of the donor community in social norm interventions, openly share programmatic findings and experiences, and advocate for resources to advance the social norm measurement agenda.

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