The Impact of Aging Policy on Societal Age Stereotypes and Ageism

Abstract

Background and objectives: While studies have researched ageism in public policy, few investigated the impact of aging policy on ageism-typically, an unintended consequence. Ageism is linked to $63 billion in health care costs, so its antecedents are of interest. We test the association between Aging Policy Agenda Setting and Societal Age Stereotypes and hypothesize a mediating pathway via Medicalization of Aging, moderated by demographics.

Research design and methods: Scholars identified Singapore's Pioneer Generation Policy (PGP) as one of the largest policy implementations in recent years, where the agenda was set by the Prime Minister at an equivalent State of the Union address in 2013, and US$7 billion allocated to fund outpatient health care costs for aged 65 years or older. More than 400,000 older adults received a PGP card and home visits by trained volunteers who co-devised a personalized utilization plan. We leveraged a 10-billion-word data set with more than 30 million newspaper and magazine articles to dynamically track Societal Age Stereotype scores over 8 years from pre- to postpolicy implementation.

Results: Societal Age Stereotypes followed a quadratic trend: Prior to the Aging Policy Agenda Setting from 2010 to 2014, stereotypes were trending positive; after 2014, it trended downward to become more negative. Medicalization of Aging mediated the relationship between Aging Policy Agenda Setting and Societal Age Stereotypes. Furthermore, Old-age Support Ratio moderated the mediational model, suggesting that the impact of policy on medicalization is stronger when a society is more aged.

Discussion and implications: We provided a framework for policymakers to ameliorate the unintended consequences of aging policies on societal ageism-if unaddressed, it will exert an insidious toll on older adults, even if initial policies are well-intentioned.

Keywords: Medicalization of aging; Moderated mediation; Old-age support ratio; Policy agenda setting; Text as data.