Do Feelings and Knowledge About Aging Predict Ageism?

Abstract

Experiencing ageism has been shown to negatively impact older adults. This study investigated predictors of ageism to examine which are most important in accounting for ageist attitudes. Participants (N = 419) between the ages of 18 and 86 completed an online survey assessing ageism and several predictors of ageism. Higher levels of anxiety about aging, lower levels of knowledge of aging, and less frequent and lower quality of contact with older adults uniquely predicted ageism beyond the influence of demographic and well-being factors. Anxiety about aging fully mediated the relationship between death anxiety and ageism, and the relationship between attitudes toward own aging and ageism. Moderation analyses showed that knowledge of aging buffered the impact of anxiety about aging on ageism such that low knowledge of aging and high anxiety about aging were particularly impactful in predicting ageism in younger adults, as compared with older adults.

Keywords

age stereotypes anxiety about aging intergenerational contact attitudes toward own aging

Ageism, a term first defined by Butler (1969), refers to prejudice directed toward one group by virtue of their age and comprises both stereotypes and discrimination based on age. Although ageism can be directed toward younger individuals, it typically refers to negative associations and behaviors directed toward older adults. Palmore (2004) reported that 85% of the adults in a sample of individuals over the age of 60 years reported that they had experienced ageism in the United States, and in Canada the percentage was 91%. As the proportion of older adults in the U.S. population continues to increase, ageism is becoming an increasingly widespread issue (e.g., Butler, 2005).

Although age-associated stereotypes can comprise both positive (e.g., older adults are wise) and negative (e.g., older adults are bitter) qualities, negative stereotypes are thought to be more characteristic of increased age (Hummert, 1990). Palmore (1999) suggests that there are at least nine major categories of negative stereotypes associated with old age: illness, impotency, ugliness, mental decline, mental illness, uselessness, isolation, poverty, and depression. As such, older adults are often perceived to be sick, lonely, bored, living in poverty, and often irritable and angry (Palmore, 1999). Older adults are also perceived to be incompetent, despite evidence to the contrary (Cuddy et al., 2005).

Ageism has been shown to impact disparate outcomes such as job satisfaction (Macdonald & Levy, 2016), cognitive functioning (Hess et al., 2004), and psychological well-being (Sabik, 2015). Levy’s (2009) Stereotype Embodiment Theory provides a framework for understanding the impact of ageism on health and well-being. Stereotypes about aging become internalized over the course of one’s life which consequently develop into expectations about and beliefs regarding one’s own aging process. Negative beliefs about aging may manifest via psychological, physiological, or behavioral pathways.

Theoretical Framework

One framework for explaining the psychological antecedents of ageism is the terror management theory (TMT; e.g., Martens et al., 2004; O’Conner & McFadden, 2012). TMT suggests that awareness of one’s own mortality causes feelings of anxiety (and terror) that can be managed through an investment in a cultural worldview and maintenance of self-esteem (e.g., Pyszczynski et al., 2004). Martens et al. (2004) argue,

Given a human drive to be concerned about and defensive in response to the idea of one’s own mortality, we believe that people may under some circumstances find elderly people threatening because they are reminders of one’s own death. Specifically, we posit that this is the case because they are uniquely vivid and thus unsettling reminders of the human aging process that leads to death. (p. 1525)

Thus, one way to manage terror associated with impending death is to create distance between oneself and older individuals via negative attitudes and behaviors (Martens et al., 2004).

Death anxiety is defined as “an emotional state of death awareness in which people experience terror as a response to the knowledge of their mortality” (Bodner et al., 2015, p. 16). Consistent with TMT, previous research has demonstrated a relationship between death anxiety and ageism such that increased death anxiety is associated with greater levels of ageism (Bodner et al., 2015; Depaola et al., 2003). Anxiety about aging, defined as “combined concern and anticipation of losses centered around the aging process” (Lasher & Faulkender, 1993, p. 247), is a related concept that has also been examined as a predictor of ageism. A number of studies have demonstrated a relationship between increased anxiety about aging and increased ageism (Allan et al., 2014; Allan & Johnson, 2009; Boswell, 2012).

The primary purpose of this study is to examine predictors of ageism and to combine disparate perspectives into a single study. As such, death anxiety and anxiety about aging are included as predictors of ageism, along with related variables that have demonstrated links with ageism, including knowledge of aging and intergenerational contact (Funderburk et al., 2006).

Knowledge of aging has been examined as a predictor of ageism in combination with anxiety about aging. For example, Harris and Dollinger (2001) conducted a study on two groups of college students. One group was enrolled in a semester-long psychology of aging course, and the other group was enrolled in a semester-long introductory psychology course. They found that the two groups differed significantly in their knowledge about aging and their attitudes toward older adults, such that students who were enrolled in the course about aging had greater knowledge of aging as well as fewer ageist attitudes toward older adults. However, contrary to the researchers’ hypothesis, there were no significant differences in anxiety about aging between the two groups, suggesting, somewhat surprisingly, a minimal relationship between knowledge of aging and anxiety about aging (but see Allan & Johnson, 2009). Additional research found that undergraduate students who have taken at least one of nine gerontology electives had more positive attitudes toward older adults than undergraduate participants who had not taken the aging elective courses (Funderburk et al., 2006).

Knowledge about aging can be acquired through not only instruction but also interactions with older adults. The intergroup contact theory (e.g., Allport, 1954) suggests that interpersonal contact with outgroup members (e.g., older adults) can improve prejudicial attitudes toward that group. Thus, researchers have speculated that intergenerational contact should be related to more favorable attitudes toward older adults (e.g., Caspi, 1984). Funderburk et al. (2006) found that participants with higher levels of contact with older adults reported more positive attitudes toward older adults. Furthermore, Allan and Johnson (2009) found that, within a sample of college students, contact with older adults (at work) and knowledge of aging influence ageism but indirectly, through their effects on anxiety about aging. These results are consistent with Drury et al. (2016), who found that anxiety about aging mediated the relationship between direct and long-term intergenerational contact and ageism. Lasher and Faulkender (1993) also found that contact and quality of contact were associated with lower levels of anxiety about aging. In contrast, other researchers have failed to find a relationship between intergenerational contact and ageist beliefs in samples of university undergraduates (e.g., Boswell, 2012) or found that frequency of contact was unrelated to ageist attitudes, but quality of contact was predictive of less ageist attitudes (Schwartz & Simmons, 2001). Thus, there are conflicting findings on the role of intergenerational contact on reducing ageist attitudes. These inconsistent results may be partly attributed to how intergenerational contact is operationalized; quality of contact may be a more reliable predictor of ageist attitudes as compared with the frequency of contact (i.e., Schwartz & Simmons, 2001).

A relevant concept that has been understudied in its relationship to ageism is an individual’s self-perceptions of aging, which refers to one’s own beliefs and evaluations about the aging process. Like stereotypes associated with aging, self-perceptions of aging can comprise positive and negative aspects. In older adults, negative perceptions of one’s own aging have been associated with a diverse array of outcomes, such as lower cognitive functioning (Robertson et al., 2016) and lower ratings of self-rated health (Moor et al., 2006), and positive perceptions of aging have been associated with increased longevity (Levy et al., 2002). Positive views toward one’s own aging may be associated with reduced anxiety about aging, and consequently less ageist attitudes. However, to our knowledge, the link between self-perceptions of aging and ageist attitudes has not been examined previously.

Demographic and Other Individual Difference Predictors

In regards to demographic and other individual difference predictors of ageist attitudes, men have been found to have higher levels of ageism as compared with women (e.g., Allan et al., 2014; Allan & Johnson, 2009), and there is also evidence that age is negatively associated with ageism (e.g., Kalavar, 2001; Rupp et al., 2005). Furthermore, Allan and colleagues (2014) speculated that individuals with a positive outlook (which they operationalized as gratitude) may be less likely to be anxious about aging and less likely to hold ageist beliefs. And, in fact, they found that increased gratitude was associated with both less anxiety about aging and ageism, and notably anxiety about aging also mediated the relationship between gratitude and ageism.

This Study

In this study, we incorporate diverse perspectives to comprehensively examine which predictors (death anxiety, anxiety about aging, knowledge of aging, intergenerational contact, and attitudes toward own aging) are most important in accounting for ageist attitudes in a sample that spans adulthood. Because increased age is associated with decreased ageism, we examine whether the predictors differ as a function of age; it may be the case that some predictors are less powerful predictors of ageism in individuals who are older (e.g., knowledge of aging). We are also interested in examining whether general positive outlook, operationalized with measures of well-being (life satisfaction, positive affect, and negative affect) and depression, is related to ageism, and we examine the predictive validity of predictors of ageism once variance associated with general positive outlook is accounted for. In addition, because anxiety about aging has been shown to mediate the relationships between predictors and ageism (e.g., Allan et al., 2014; Drury et al., 2016), a goal of this study is to examine whether anxiety about aging functions as a mediator in the current sample. Based on previous research, we hypothesize as follows:

Hypothesis 1: Death anxiety, anxiety about aging, knowledge of aging, intergenerational contact (frequency and quality), and attitudes toward own aging will significantly predict ageism.

Hypothesis 2: Anxiety about aging will mediate the relationship of death anxiety, knowledge of aging, intergenerational contact, and attitudes toward own aging to ageism.

Hypothesis 3: Knowledge of aging, intergenerational contact, and attitudes toward own aging will serve as protective buffers against the negative consequences of anxiety about aging on ageism (e.g., knowledge of aging will moderate the relationship between anxiety about aging and ageism).

Hypothesis 4: Age will moderate the relationship between death anxiety, anxiety about aging, knowledge of aging, intergenerational contact, and attitudes toward own aging and ageism such that the magnitude of the relationships will be stronger among younger adults as compared with older adults.

Hypothesis 5: Demographic and well-being variables will be associated with ageism.

Method

Participants

The sample included 434 participants, but 15 were excluded from the analyses because they responded to two or more of the attention confirmation items incorrectly, leaving 419 participants in the analytic sample. Attention confirmation items comprised 14 items interspersed throughout the survey to ensure that participants were paying attention to the questions and response items. An example attention confirmation item is as follows: “The purpose of this item is to check that you are paying attention. If you are paying attention, please select ‘Strongly disagree’.” Participants who responded incorrectly to more than two of these items were excluded from the dataset.

A total of 60 participants (14.3%) were recruited via GSAConnect, a forum for the members of the Gerontological Society of America, whereas 359 (85.7%) were recruited either from flyers posted around Fordham University’s campus, an online research credit system used for Foundations of Psychology students to earn research credit, via ResearchMatch, which is a website connecting interested participants to a wide range of research studies, or by referral. At completion of the survey, participants were given the option to enter their email address into a separate survey for a raffle for a gift card.

Given their professional background, individuals recruited from GSAConnect may have differences in their thoughts and feelings toward older adults; thus, all analyses were conducted both with and without these participants. However, there were no substantial differences in findings between the full sample and the sample excluding the GSAConnect subsample. Findings excluding the GSAConnect subsample can be found in Supplemental Material.

The sample comprised 333 females (79.5%), 85 males (20.3%), and one nonbinary individual (0.20%) with a mean age of 46.09 years (SD = 19.28; range = 18–86). A majority of the sample was White (85.7%). See Table 1 for additional participant characteristics.

Table 1.

Participant Characteristics.

Participant characteristics	Total sample	18–39 years	40–59 years	60–86 years
Participant characteristics	N = 419	n = 167	n = 121	n = 129
Age	46.09 (19.28)	25.40 (7.05)	51.13 (5.83)	68.15 (6.28)
%Female	79.50	82.00	85.10	70.50
Race
%American Indian/Alaska native	0.20	0.00	0.80	0.00
%Asian	5.00	10.80	2.50	0.00
%Black	2.90	2.40	4.10	2.30
%White	85.70	74.90	90.10	95.30
%More than one	2.10	4.80	0.0	0.80
%Other	1.00	1.20	1.70	0.00
%Hispanic/Latino	2.40	6.00	0.00	0.00
%Missing	0.50	0.00	0.80	1.60
Education (years)	17.07 (3.25)	15.96 (3.18)	17.92 (3.42)	17.65 (2.64)
Self-rated health	2.16 (0.93)	2.05 (0.94)	2.21 (0.96)	2.25 (0.90)
Functional limitations	4.24 (1.04)	4.51 (0.87)	4.12 (1.16)	4.01 (1.04)
Life satisfaction	25.19 (6.66)	24.98 (6.42)	24.27 (7.41)	26.26 (6.15)
Positive affect	30.79 (8.95)	28.19 (8.93)	31.55 (8.08)	33.57 (8.77)
Negative affect	14.3 (6.42)	16.98 (7.21)	13.41 (5.79)	11.72 (4.32)
Depressive symptoms	7.16 (5.61)	8.72 (5.85)	6.78 (5.73)	5.45 (4.49)
Ageism	42.77 (11.70)	45.72 (12.63)	39.25 (10.36)	42.29 (10.69)
Death anxiety	12.34 (8.67)	16.74 (9.97)	10.38 (6.43)	8.48 (5.76)
Anxiety about aging	47.36 (11.74)	50.79 (11.68)	45.96 (10.94)	44.11 (11.06)
Attitudes toward own aging	18.78 (4.00)	18.98 (3.80)	18.48 (4.26)	18.80 (3.97)
Knowledge of aging	0.71 (0.08)	0.69 (0.07)	0.72 (0.07)	0.74 (0.07)
Intergenerational contact frequency	4.2 (0.88)	3.89 (0.94)	4.32 (0.78)	4.47 (0.76)
Intergenerational contact quality	4.5 (0.76)	4.39 (0.86)	4.61 (0.58)	4.51 (0.73)

Note. Values represent means (standard deviations) or percentages (where noted).

Materials

Several scales were administered online through the Qualtrics survey platform. The scales were ordered randomly, except for the sociodemographic questionnaire, which appeared last.

Fraboni Scale of Ageism

A revised version of the Fraboni Scale of Ageism (FSA; Fraboni et al., 1990) developed by Rupp et al. (2005) was used to assess participants’ level of ageism against older adults. Participants reported on a five-point Likert-type scale their agreement with 23 statements regarding older adults that assessed three factors corresponding to stereotypes (e.g., “Many old people are stingy and hoard their money and possessions.”), separation (e.g., “I don’t like it when old people try to make conversation with me”), and affective attitudes (e.g., “It is sad to hear about the plight of the old in our society these days”). Responses ranged from 1 = “strongly disagree” to 5 = “strongly agree.” Five items were reverse scored so that higher scores indicated a higher level of ageism.

Death Anxiety Scale-Extended

The Death Anxiety Scale-Extended (DAS-E; Templer et al., 2006) is a 51-item scale used to assess participants’ anxiety about death. Participants reported whether each statement (e.g., “The thought of death never bothers me”) was true or false of them (0 = “false” and 1 = “true”). The 51 items were summed to create a total score (six items were reverse scored so that higher scores indicated higher death anxiety).

Anxiety about Aging Scale

The Anxiety about Aging Scale (AAS; Lasher & Faulkender, 1993) is a 20-item scale used to assess participants’ anxiety about aging using a five-point Likert-type scale ranging from 1 = “strongly disagree” to 5 = “strongly agree.” An example item is as follows: “The older I become, the more I worry about my health.” The 20 items were summed to create a total score (13 items were reverse scored so that higher scores represent higher anxiety about aging).

Facts on Aging Quiz

The Facts on Aging Quiz (FAQ; Breytspraak & Badura, 2015), which assesses participants’ knowledge of aging, comprises 50 true or false questions, such as “Physical strength declines in old age.” Correct responses were coded as 1 (incorrect = 0). Correct responses were summed, and a final percentage of correct divided by 50 (the total number of questions) was calculated. Higher scores indicated greater knowledge of aging.

Intergenerational contact

Questions regarding intergenerational contact were derived from Drury et al. (2016). Frequency of contact was assessed with the question “How often have you had contact with older adults?” with response options ranging from 1 = “very rarely” to 5 = “very often.” Quality of contact was assessed by asking participants to rate the quality of their previous intergenerational contact with older adults on a scale from 1 = “bad quality” to 5 = “good quality.” Pleasantness and voluntariness of contact were also assessed but were not examined in the present analyses.

Attitudes Toward Own Aging Scale

The Attitudes Toward Own Aging (ATOA) scale (Lawton, 1975) assessed participants’ subjective aging perceptions. Participants rated five statements (e.g., “Things keep getting worse as I get older”) about their attitudes toward their own aging on a scale from 1 = “strongly disagree” to 5 = “strongly agree.” A sum score was computed, where higher scores indicate more positive views toward one’s own aging.

Satisfaction with Life Scale

The Satisfaction with Life Scale (SWLS; Diener et al., 1985) assessed participants’ life satisfaction through five items, such as “In most ways my life is close to my ideal.” Participants indicated to what extent they agreed with each statement on a scale ranging from 1 = “strongly disagree” to 7 = “strongly agree.” Scores were summed to create a composite score in which higher values represented higher levels of life satisfaction.

Positive and Negative Affect Scale

The Positive and Negative Affect Scale (PANAS; Watson et al., 1988) comprises 10 positive emotion words (e.g., “enthusiastic”) and 10 negative emotion words (e.g., “hostile”) to assess affective well-being. Participants rated the extent to which they presently felt each of these emotions on a scale from 1 = “very slightly or not at all” to 5 = “extremely.” Sum scores for positive and negative affect were calculated separately, such that higher scores indicated higher positive and negative affect, respectively.

Center of Epidemiological Studies-Depression Scale

A shortened Center of Epidemiological Studies-Depression (CES-D) scale (Radloff, 1977) comprising 10 items rated on a four-point Likert-type scale ranging from 0 = “rarely or none of the time (less than 1 day)” to 3 = “all of the time (5–7 days)” assessed the frequency of depressive symptoms. Higher scores reflected more frequent depressive symptoms.

Sociodemographic and functioning characteristics

Participants were asked questions regarding their sociodemographics and physical functioning, including assessments of self-rated health (i.e., “How would you rate your health at the current time?” with options ranging from 1= “excellent” to 5= “poor”) and functional limitations (i.e., “How much are your daily activities limited in any way by your health or health-related problems?” with options ranging from 1 = “a great deal” to 5 = “none at all”).

Results

Correlational Analysis

Pearson bivariate correlational analyses showed several significant relationships between several variables and ageism (see Table 2). As expected, anxiety about aging had the strongest relationship with ageism (r = .54), whereas death anxiety (r = .33), attitudes toward own aging (r = −.31), knowledge of aging (r = −.40), intergenerational contact frequency (r = −.31), and quality (r = −.49) were also significantly related (all ps < .01) in the expected directions. General well-being variables were also significantly related to ageism such that high well-being (e.g., life satisfaction and positive affect) was related to decreased ageism, whereas low well-being (e.g., depression and negative affect) was related to increased ageism. Being older, female, and having more years of education were associated with lower levels of ageism.

Table 2.

Correlations Among Participant Characteristics and Variables of Interest.

Variable	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
1. Ageism	(.88)
2. Age	−.20**	—
3. Gender	−.16**	−.12*	—
4. Education (years)	−.27**	.33**	.01	—
5. Self-rated health	.13**	.08	−.10*	−.05	—
6. Life satisfaction	−.23**	.08	−.02	.14**	−.43**	(.89)
7. Positive affect	−.25**	.24**	−.13**	.01	−.31**	.38**	(.92)
8. Negative affect	.29**	−.41**	−.02	−.19**	.12*	−.33**	−.04	(.91)
9. Depressive symptoms	.35**	−.29**	−.02	−.17**	.39**	−.55**	−.40**	.60**	(.86)
10. Anxiety about aging	.54**	−.32**	.04	−.20**	.23**	−.40**	−.41**	.36**	.52**	(.86)
11. Death anxiety	.33**	−.48**	.06	−.26**	.11*	−.21**	−.21**	.47**	.42**	.51**	(.92)
12. Knowledge of aging	−.40**	.37**	−.02	.40**	−.09	.23**	.13**	−.27**	−.30**	−.38**	−.31**	—
13. Contact frequency	−.31**	.31**	−.04	.13**	−.00	.08	.21**	−.13**	−.11*	−.29**	−.16**	.19**	—
14. Contact quality	−.49**	.13**	.06	.06	−.07	.19**	.26**	−.21**	−.19**	−.40**	−.19**	.25**	.36**	—
15. Attitudes toward own aging	−.31**	.02	.07	.13**	−.46**	.60**	.37**	−.29**	−.60**	−.47**	−.17**	.28**	.04	.16**	(.76)

Note. The values presented in the diagonal in the parentheses reflect the Cronbach alpha in the current sample for each respective scale.

p < .05. **p < .01.

Regression Analyses Predicting Ageism

Predictors of ageism were examined using a hierarchical regression model. The full model included sociodemographic factors in the first block (gender, age, years of education, and self-rated health), general psychological well-being variables in the second block (positive affect, negative affect, life satisfaction, and depression), and the hypothesized predictors of ageism in the third block (e.g., death anxiety, anxiety about aging, knowledge of aging, intergenerational contact frequency and quality, and attitudes toward own aging). Well-being variables were included in the second block as we hypothesized that general positive outlook would be associated with less ageist attitudes, which was substantiated by the correlations reported in Table 2. The full model accounted for 47% of the variance in ageism, F(14, 393) = 24.45, p < .001 (see Table 3). While controlling for sociodemographic and well-being covariates, anxiety about aging, knowledge of aging, and frequency and quality of contact with older adults significantly predicted ageism in the full model. Anxiety about aging was the strongest significant predictor of ageism (β = 0.28).

Table 3.

Hierarchical Regression Analyses Predicting Ageism.

Variable	Model 1			Model 2			Model 3
Variable	B	SE of B	β	B	SE of B	β	B	SE of B	β
Age	−0.10**	0.03	−0.16	0.004	0.03	0.01	0.07*	0.03	0.11
Gender	−4.41**	1.38	−0.15	−5.07**	1.32	−0.17	−4.44**	1.12	−0.15
Education (years)	−0.79**	0.18	−0.22	−0.80**	0.17	−0.22	−0.45**	0.15	−0.12
Self-rated health	1.46*	0.59	0.12	−0.58	0.65	−0.05	−0.49	0.56	−0.04
Positive affect				−0.30**	0.07	−0.23	−0.09	0.06	−0.07
Negative affect				0.31**	0.11	0.17	0.09	0.10	0.05
Life satisfaction				−0.02	0.10	−0.01	0.14	0.09	0.08
Depressive symptoms				0.26	0.15	0.12	0.12	0.13	0.06
Death anxiety							0.08	0.07	0.06
Anxiety about aging							0.29**	0.05	0.28
Knowledge of aging							−23.66**	7.18	−0.15
Contact frequency							−1.23*	0.56	−0.09
Contact quality							−4.23**	0.68	−0.27
Attitudes toward own aging							−0.13	0.16	−0.05
R ²		.13			.24			.47
Adjusted R²		.12			.22			.45
F for change in R²		15.37**			13.37**			28.26**

p < .05. **p < .01.

Mediation Analyses

Path analyses were used to assess the mediating role of anxiety about aging for the relationship between the predictors of interest and ageism. Results of the mediation analyses are presented in Table 4. Anxiety about aging fully mediated the relationship between death anxiety and ageism. The relationship between death anxiety and ageism was reduced from .33 (p < .001) to .07 (ns), which is consistent with full mediation (Baron & Kenny, 1986). Anxiety about aging also fully mediated the relationship between attitudes toward own aging and ageism. Once anxiety about aging is included in the model, the relationship between attitudes toward own aging and ageism is reduced from −.31 (p < .01) to −.07 (ns). Anxiety about aging partially mediated the relationship of knowledge of aging, frequency of contact, and quality of contact with ageism (see Table 4). For each of the predictors, Sobel test indicated that anxiety about aging significantly mediated the relationship between the predictor and ageism.

Table 4.

Results of Path Analysis Mediation Models With Anxiety About Aging as the Mediator.

Relationship	Indirect	Direct	Total	Sobel test
Relationship	Indirect	Direct	Total	z	P
Death anxiety → ageism	.26	.07	.33**	7.99	<.001
Attitude toward own aging → ageism	−.24	−.07	−.31**	−7.73	<.001
Knowledge of aging → ageism	−.18	−.22**	−.40**	−6.70	<.001
Frequency of contact → ageism	−.14	−.17**	−.31**	−5.47	<.001
Quality of contact → ageism	−.16	−.33**	−.49**	−6.75	<.001

Note. Indirect coefficients are the product of the path between the predictor variable and anxiety about aging and the path between anxiety about aging and ageism.

p < .01.

Moderation Analyses: Anxiety About Aging

Anxiety about aging was found in the hierarchical regression to have the strongest influence on ageism, and thus we examined whether anxiety about aging interacted with other predictors to influence ageism. Sociodemographic variables that were significantly related to ageism (gender, age, and years of education) in the hierarchical regression model were included in the models. Well-being variables were excluded as they were not significant unique predictors of ageism in the hierarchical regression model. Standardized scores were calculated for each variable and interaction terms were created between each of the variables of interest and anxiety about aging utilizing standardized scores.

Knowledge about aging

In a multiple regression, gender (β = −0.16, p < .001), years of education (β = −0.11, p < .05), knowledge of aging (β = −0.20, p < .001), and anxiety about aging (β = 0.46, p < .001) significantly predicted ageism, F(6, 404) = 41.53, p < .001. The interaction of anxiety about aging and knowledge of aging (β = −0.09, p < .05) also significantly predicted ageism. This model accounted for 38% of variance in ageism. Knowledge of aging buffered the negative impact of anxiety about aging on ageism, meaning that, among participants with higher levels of anxiety about aging, those who also had high levels of knowledge of aging reported lower levels of ageism than those with lower levels of knowledge of aging. Figure 1 depicts a visual representation of the interaction effect.

Figure 1.

The interaction of anxiety about aging and knowledge of aging on ageism.

Additional moderation analyses examining whether anxiety about aging moderated the effects of frequency of contact, quality of contact, and attitude toward own anxiety on ageism yielded no significant interactions (see Supplemental Material for detailed results).

Moderation Analyses: Age

Moderation analyses were also conducted to examine whether the relationships between each of the predictors and ageism differed based on age. Standardized scores were calculated for each variable and interaction terms were created between each of the variables of interest and age utilizing the standardized scores.

Anxiety about aging

A multiple regression showed that gender (β = −0.16, p < .001), years of education (β = −0.14, p < .01), and anxiety about aging (β = 0.50, p < .001) significantly predicted ageism, F(5, 405) = 44.78, p < .001. The interaction of anxiety about aging and age (β = −0.10, p < .05) also significantly predicted ageism, meaning that high anxiety about aging was particularly harmful in contributing to ageism among younger compared with older individuals. This model accounted for 36% of variance in ageism.

Knowledge about aging

Results of a multiple regression analysis indicated that gender (β = −0.15, p < .01), years of education (β = −0.10, p < .05), and knowledge of aging (β = −0.33, p < .001) significantly predicted ageism, F(5, 405) = 23.16, p < .001. The interaction of age and knowledge of aging (β = 0.14, p < .01) also significantly predicted ageism, meaning that having low knowledge of aging was particularly harmful in contributing to ageism among younger compared with older individuals. This model accounted for 22% of variance in ageism.

Additional age moderation analyses with death anxiety, frequency of contact, quality of contact, and attitude toward own aging predicting ageism yielded no significant age interaction terms (see Supplemental Material for detailed results).

Notably, there were no substantial differences to any of the age moderation models when the GSAConnect subsample was excluded from the analyses, except that education was no longer a significant predictor of ageism.

Discussion

The findings of this study partially supported our hypotheses. As expected, each of the predictors was correlated with ageism. Anxiety about aging was associated with higher levels of ageist attitudes, which is consistent with many other studies (Allan et al., 2014; Allan & Johnson, 2009; Boswell, 2012; Harris & Dollinger, 2001), and provides support for the terror management explanation of ageism. Ageism may be the mechanism by which one may deal with anxiety associated with aging and death—namely, by viewing older adults in a negative light, to create psychological distance. This interpretation is substantiated by the results of mediation analyses which indicated that, consistent with our second hypothesis, anxiety about aging fully mediated the relationships between death anxiety and attitudes toward own aging to ageism and partially mediated the relationship between ageism and the other predictor variables (knowledge of aging, intergenerational contact frequency and quality). This is consistent with findings reported by Allan and Johnson (2009) who found that anxiety about aging mediated the relationship between knowledge about aging and ageism, and anxiety about aging also mediated the relationship between contact with the elderly (in a work setting) and ageism.

Our findings also support the intergroup contact theory which suggests that contact with outgroup members can improve attitudes toward that group. Both intergenerational contact frequency and quality explained significant and unique variance in ageism. Furthermore, ageism was much more strongly related to intergenerational contact quality than to intergenerational contact frequency, which is consistent with prior work (Schwartz & Simmons, 2001).

Our hypotheses regarding the moderating effect of anxiety about aging were partially supported. Results suggest that knowledge of aging significantly interacted with anxiety about aging to influence levels of ageism such that knowledge buffered the negative impact of anxiety about aging on ageism. In contrast to our hypothesis, intergenerational contact frequency and quality were not found to moderate the impact of anxiety about aging on ageism.

Consistent with previous research, we found that women had lower levels of ageist attitudes, and increased age was associated with reduced levels of ageist attitudes. We found that having high levels of anxiety about aging and low levels of knowledge of aging was particularly harmful for younger adults compared with older adults in terms of being related to higher levels of ageism. In addition, positive outlook, as operationalized via measures of well-being and depressive symptoms, was associated with lower levels of ageism, which is consistent with findings by Allan and colleagues (2014) who found that gratitude was associated with lower levels of ageism. Notably, even after controlling for demographics and general psychological well-being, several of the predictors made unique and significant contributions to ageism.

Our study is one of the first to establish a link between self-perceptions of aging (as measured by the ATOA scale) and ageism. We found that attitudes toward one’s own aging were significantly related to ageism. Furthermore, anxiety about aging fully mediated the relationship between attitudes toward own aging and ageism.

The experience of ageism is associated with negative outcomes and reduced well-being (e.g., Hess et al., 2004; Sabik, 2015). Our findings suggest that anxiety about aging plays an important role in ageism. In addition, knowledge of aging significantly moderated the impact of anxiety about aging on ageism. Although intergenerational contact did not moderate the impact of anxiety on ageism, intergenerational contact frequency and quality did have a negative relationship with ageism (and accounted for unique variance in ageism, independent of all the other predictors), suggesting that increasing intergenerational contact frequency and, in particular, quality may reduce ageism. Implications of this study include the identification of potential targets for reducing ageism. Based on our findings, one way to reduce anxiety about aging is through increasing knowledge of aging, which is consistent with a recent meta-analysis examining the effectiveness of different components of several ageism interventions (Burnes et al., 2019). Although increasing knowledge of aging may be relatively straightforward in educational settings, it is more difficult to address in other settings. The workplace may be a suitable target for increasing knowledge about aging through, for example, training modules or seminars. This may be especially beneficial as the workplace is a setting in which adults spend a substantial amount of time, and is an environment in which ageism has many negative impacts, including reduced job satisfaction, commitment, and engagement and lower self-esteem (e.g., Bayl-Smith & Griffin, 2014; Hassell & Perrewé, 1993; Macdonald & Levy, 2016).

Limitations of this study include the lack of gender and racial/ethnic diversity within the sample, likely due to the convenience-based nature of the sample. A majority of the participants were female (79.5%) and White (85.7%), which may have impacted the results. In addition, the study was entirely correlational; thus, no causal conclusions can be made.

In conclusion, this study was one of the first to simultaneously examine several important predictors of ageism in a sample spanning adulthood. Our findings suggest that anxiety about aging, knowledge of aging, and intergenerational contact are significant and unique predictors of ageism and may serve as targets for interventions to reduce ageism. Knowledge of aging may be especially important as it was found to buffer the negative influence of anxiety about aging on ageism. Death anxiety and attitudes toward own aging also predict ageism, but only indirectly via their relationship with anxiety about aging.

Supplemental Material

Supplemental_materials_2 – Supplemental material for Do Feelings and Knowledge About Aging Predict Ageism?

Supplemental material, Supplemental_materials_2 for Do Feelings and Knowledge About Aging Predict Ageism? by Cassandra Cooney, Jillian Minahan and Karen L. Siedlecki in Journal of Applied Gerontology

Footnotes

Authors’ Note

Institutional Review Board at Fordham University reviewed and approved this research protocol as exempt (IRB No. 841).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a Fordham College Rose Hill undergraduate research Grant awarded to C.C.

ORCID iD

Karen L. Siedlecki

Supplemental Material

Supplemental material for this article is available online.

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