Research is critical to assess the prevalence, origins, and consequences of ageism as well as the potential effectiveness of various interventions to fight ageism. A major challenge associated with the assessment of ageism is the fact that being seen as ageist is generally considered to be negative. Most people do not wish to be seen as ageist (Cherry et al. 2015) and so will respond to questions about ageism with caution. Moreover, ageism is highly prevalent and often unnoticed, because it is so ingrained in our lives (Perdue and Gurtman 1990). This is why implicit measures of ageism are recommended to supplement explicit measures (Shiovitz-Ezra et al. 2016).

Another challenge associated with the assessment of ageism concerns its subjective nature (Ayalon 2016; Voss et al. 2017). In order to acknowledge an event as ageist, one has to notice the event, interpret it as ageist, and then cite ageism as the cause of the event. Any of these three processes can impact one’s willingness to acknowledge ageism. The social context plays an important role, as society clearly defines events as ageist or non-ageist based on current norms and expectations. For instance, whereas asking a job applicant his or her age is the norm in some countries, in other countries asking such a question is not considered acceptable. Hence, the subjective nature of ageism should be acknowledged (Ayalon 2016; Kornadt et al. 2015).

In the first chapter of this section (2018; Chap. 25), Snellman argues that most research on ageism to date has focused on empirical data. Less attention has been paid to aspects such as the normative value applied to ageism and theoretical or interpretive considerations. Snellman argues that the research training of the investigators, rather than the research questions, often guides the selection of the approach. He further suggests that more attention to the selection of a particular research approach would be beneficial and enriching for research in general and for research in the field of ageism in particular.

As international researchers, Wilińska, de Hontheim, and Anbäcken (2018; Chap. 26) give a reflexive personal account of conducting research on ageism in different countries and cultures. They argue that being physically away from your own culture is an opportunity to re-examine common assumptions about age and ageing and develop a more critical understanding of these issues in light of their varied manifestations in different cultures. To some degree, this chapter corresponds with Snellman’s chapter (2018; Chap. 25), as it indicates ways to broaden normative understandings of ageism through exposure to views and perspectives that do not represent the majority view in one’s own culture.

The chapter by Swift et al. (2018; Chap. 27) is an empirical account of ageism in Europe as assessed via the European Social Survey (ESS). The chapter highlights the ESS data as a means to understand ageism. It draws from social psychology theories to demonstrate the contribution of the findings to theory and empirical knowledge. In addition, the authors discuss the importance of multi-level analysis to account for the individual and country levels simultaneously. Given the fact that ageism has both micro- and macro-level origins and manifestations, the ESS provides a unique opportunity to enhance understanding of the intersections between the two levels.

Buttigieg, Ilinca, Sao Jose, and Taghizadeh Larsson (2018; Chap. 29) present a comprehensive overview of how ageism is defined and measured in health and long-term care. Like Snellman, these authors call for a division between empirical research and theoretical research, as most research in the field of health and long-term care is empirical and atheoretical in nature. The authors further call for the use of mixed research methods and perspectives in order to provide a more complete account of ageism in health and long-term care.

Abuladze and Perek-Bialas (2018; Chap. 28) similarly encourage the use of publicly available datasets to measure ageism. Their chapter focuses on the use of measures to assess ageism in the workforce. They use an empiricist approach (as defined by Snellman in this section) to classify measures according to five possible aspects of ageism in the labour market: recruitment/retention, performance, training, interaction with older colleagues, and structural ageism. This chapter, as well as the chapter by Swift et al. (2018; Chap. 27), provides an excellent resource for readers who wish to become familiar with the use of publicly available datasets.

Also in this section, Mendonça, Marques, and Abrams (2018; Chap. 30) outline the results of a review of measures to assess ageism in children. Research has consistently shown that ageism is common among young children and youth and not only among older adults. This supports claims about the automaticity of age categorization (Perdue and Gurtman 1990) and potentially about the evolutionary nature of ageism (Burnstein et al. 1994). Nevertheless, children have different language and test-taking skills that may require somewhat different measures. The authors suggest a classification of measures according to the tripartite model of attitudes (behavioural, cognitive, emotional) and their placement along a continuum of explicit versus implicit measures.

The last chapter in this section is by Phelan (2018; Chap. 31), who uses discourse analysis to demonstrate how ageism is constructed and deconstructed in everyday life. The chapter demonstrates how individuals can position and construct older people in an ageist or non-ageist framework. Using Snellman’s definitions, this chapter takes an interpretive approach, as it examines ageism from a more philosophical/theoretical stand.

These chapters provide potentially useful tools to assess ageism. The chapters by Snellman (2018; Chap. 25), Wilińska et al. (2018; Chap. 26), and Phelan (2018; Chap. 31) are more theoretical in nature. They suggest new ways to think about the phenomenon of ageism, which could potentially affect the ways we study it. The chapters by Swift et al. (2018; Chap. 27), Buttigieg et al. (2018; Chap. 29), Abuladze and Perek-Bialas (2018; Chap. 28), and Mendonça et al. (2018; Chap. 30), on the other hand, provide practical tools for the assessment of ageism in various settings (general society, health and long-term care, and the labour force) and among different target populations (older adults, professionals, adult children, family members, and young children). Swift et al. (2018), Abuladze and Perek-Bialas (2018), and Mendonça et al. (2018) take into account cross-cultural and national considerations. This is particularly important given the fact that ageism is a social phenomenon that does not only occur at the individual level, but rather is affected by socio-cultural aspects (Cuddy et al. 2005; Vauclair et al. 2016).

Although it is not specifically focused on in the chapters of this section, an additional aspect of ageism research is the assessment of ageism at the macro-level (Ayalon and Rothermund 2017). There are multiple macro-level indicators of inequality, such as the Gini coefficient and the coefficient of variation (Allison 1978). With regard to specific characteristics, there are measures of gender inequality such as the Gender Inequality Index and the Gender-Related Development Index (Dijkstra and Hanmer 2000; Gaye et al. 2010) that could potentially be applied to ageism. Consistently, the Active Ageing Index and the Age Watch Index both represent attempts to assess the conditions of older adults in society (AgeWatch 2015; Zaidi et al. 2013). Although informative, these studies evaluate the absolute status of older adults in society and do not provide a comparative analysis of the status of old versus young people in society, as was recently proposed by Ayalon and Rothermund (2017). Nonetheless, these studies indicate a macro-level direction, which is much needed given the manifestation of ageism at the individual level as well as at the social/structural/institutional level.

There has been great progress in researching ageism and there are multiple possibilities for future research. Research should take into account not only ageism at the individual level but also at societal and institutional levels, as ageism often co-occurs at both levels. The availability of public datasets on ageism provides a substantial resource for researchers wishing to explore the topic and develop cross-national comparisons. The limited theoretical grounding of a substantial portion of the research on ageism should be seen as an opportunity for researchers, who could potentially contribute to an emerging and growing field not only through the production of empirical data, but also through the construction and development of theoretical understandings of the phenomenon of ageism.