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Abstract
Objectives
Self-directed ageism is the application of stereotypic age-related beliefs to oneself, and is known to negatively impact health-related motivation (Levy, Citation2003; Citation2022). This study focused on the specific self-directed stereotype that ‘age causes illness’ and aimed to develop and test a multi-item measure to assess this implicit, limiting belief.
Methods and Measures
Survey data was collected from N = 347 adults in southeastern Idaho (ages 45–65 years old, 60% female). A variety of measures were used to assess the discriminant, convergent and predictive validity of the Age Causes Illness scale including: socio-demographics (age, sex, education), psychosocial resources (personality, optimism, social support, depressive symptoms), health/aging expectations, and indicators of physical health.
Results
The seven-item Age Causes Illness scale is reliable and shows an expected pattern of discriminant and convergent correlations with relevant socio-demographic, psychosocial, and aging-related measures. The belief that ‘age causes illness,’ as assessed with this new scale, is related to both objective and subjective indicators of physical health.
Conclusions
The Age Causes Illness scale is a brief screening tool, potentially applicable in behavioral health settings as an initial step toward discussion of the implicit, and often unchallenged, belief that age alone determines the onset, progression, and offset of illness.
Disclosure statement
The authors report there are no competing interests to declare.
Data availability statement
The data that support the findings of this study are available on request from the corresponding author (TS).
Notes
1 Middle-aged adults (45–65) were the focus of the Aging in Idaho study for two reasons: First, midlife is an under-researched stage of lifespan development (Lachman, Citation2015), and second, midlife is arguably the time during which generalized aging-related beliefs begin to become more salient and self-relevant (Levy, Citation2009).
2 According to a special issue of the Public Opinion Quarterly (Singer, Citation2006) response rates to community-based surveys have declined dramatically in the past decade. Empirical research has begun to examine the growing issue of survey nonresponse with particular focus on assessing the association between response rate and sampling bias. Recent studies have demonstrated that low-response surveys do not necessarily result in high levels of sampling bias; and quantitative comparisons suggest that increases in response rates do not necessarily alter survey estimates (Curtin et al., Citation2000; Keeter et al., Citation2000; Merkle & Edelman, Citation2002).
3 Prior to the general mailing, a pilot-test was conducted with a convenience sample of N = 57 adults (ages 24–83, M = 60.68, SD = 14.23; 61% female) in order to assess the appropriateness of questionnaire length, clarity of instructions, and psychometric properties of newly-created scales. As compared to the full sample, the pilot sample was more diverse in age range (24–83 vs. 45–65) slightly older on average (60.68 vs. 55.98), similar in gender distribution (61.4% female vs. X), and the modal response of highest level of education was higher (35% masters degree vs. 37% some post-secondary). Time to complete the questionnaire ranged from approximately 30–75 minutes. Based on feedback from pilot participants, questionnaire instructions were amended where necessary and problematic measures were modified or dropped. Newly-created measures (i.e. the Age Causes Illness scale) were modified based psychometric analyses and participant feedback.
4 The three excluded items read: Most serious illnesses are caused by aging; the majority of old people are ill; and, although many factors contribute to illness, in some cases old age is the only cause.