During the COVID-19 pandemic, we face an exacerbation of ageism as well as a flourish of intergenerational solidarity. The use of chronological age is an unjustified threshold for the creation of public policies to control the spreading of the virus; doing so reinforces intrapersonal and interpersonal negative age stereotypes and violates older persons' human rights to autonomy, proper care treatment, work, and equality. By overlooking differences within age groups, measures formulated solely on the basis of age are unable to target beneficiaries' needs. Concurrently, several initiatives are trying to overcome ageist practices by providing different types of assistance to older adults on the basis of need rather than chronological age. The Marie Skłodowska-Curie Innovative Training Network EuroAgeism calls on policymakers to refrain from ageist practices and language, as they exacerbate our ability to meet the COVID-19 crisis and future emergencies.

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Technology acceptance models associate older age with lower intention to use digital technology although this assumption is often stereotypically-based and not sufficiently tested with older persons. This study investigated the association of ageism (rather than chronological age) with behavioral intention and actual use of technology within the theoretical framework of the Unified Theory of Acceptance and Use of Technology (UTAUT-2) model. 374 Dutch-speaking participants aged 50–97 completed the UTAUT-2 questionnaire, Expectations Regarding Aging, Attitudes Toward Older Adults Using Technology (ATOAUT-11) and experienced ageism scales. A path analysis found that expectations regarding aging partially mediated the association of age with negative attitudes. Mixed results were found regarding the fit of the new UTAUT-2-Ageism model. Negative ATOAUT moderated the associations of Effort Expectancy, Facilitating Conditions, and Habit with Behavioral Intention to use technology, and the explained variance increased. Further research is warranted to fully identify the potential role of ageism in technology acceptance.

Although the active ageing concept generally has positive connotations, with expected benefits at the micro, meso and macro levels, the application of this concept in terms of policy making presents challenges and risks to be avoided (for instance, a predominantly productivist interpretation and a top-down imposition with limited possibilities for bottom-up exchanges; or a disregard for the risk of excluding older people with more disadvantaged backgrounds). Two crucial strategies to minimise risks are the implementation of policies by considering and respecting territorial diversity, and the involvement of all the relevant stakeholders in a participatory consultative and co-decisional approach. This paper entwines both strategies together by focusing on Italian in-country differences in terms of active ageing, and employing the Active Ageing Index for policy-making purposes. This activity is part of a governmental national pilot project aimed at promoting multilevel co-managed co-ordination of active ageing policies across Italy. The analysis identified five groups of regions that differ from the classical, geographic and socio-economic division between the North, Centre and South. Additional in-group analyses were conducted to investigate within-cluster differences. This study will inform a large multilevel stakeholder network for evidence-based policies and their monitoring at both the national and regional levels, in line with the perspective of mainstreaming ageing.

This paper is aimed at the development of a tool analysing the AAI results for the Russian older citizens from different population groups, as well as at identifying factors underlying the inequalities in active ageing outcomes by calculation the AAI on the national and individual levels. The adaptation of the methodology of the AAI to the individual-level data and the limitations of the approach are explicitly explained. The older generations of Russia show relatively high levels of education, financial security and engagement in family care, especially in the care to children. The most significant potential for development have employment, volunteering, political engagement, physical activity, lifelong learning and use of the Internet. The calculation of the AAI at the individual level has revealed significant inequalities in the degree of realisation of potential in different areas of active ageing. The results of the project provide scientific evidence for the implementation of policy measures in the target groups. The high correlation of the index values with human capital indicators (health and education) underlines the importance of the early interventions aimed at promoting and supporting human capital at the earlier stages of the life course till the old age. The substantial positive connection of employment with other forms of activity stresses the necessity of developing a package of activation policy measures aimed at the retention of older adults in the labour market. At the same time, the statistical analysis showed the absence of a “dilemma of choice” between certain types of activity of the older generation, for example, between caring for grandchildren and employment, or employment and volunteering - the potential in different areas may be increased simultaneously.