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this is not a multiple  choice test at all read article  and made the multiple choice
Copy and paste reaction papers here. Please be sure (1) 1/2 page (single spaced) and (2) include a multiple-choice item (see below example).
In the Robbers Cave Study what were the two group names?
A. Bears & Tigers
B. Rattlers & Eagles
C. Hawks & BulldogsD. Puppies & KittiesJournal of Social Issues, Vol. 61, No. 2, 2005, pp. 241–266
Attitudes Toward Younger and Older Adults: An
Updated Meta-Analytic Review
Mary E. Kite∗
Ball State University
Gary D. Stockdale
University of California-Davis
Bernard E. Whitley, Jr.
Ball State University
Blair T. Johnson
University of Connecticut
This meta-analytic review of 232 effect sizes showed that, across five categories,
attitudes were more negative toward older than younger adults. Perceived age differences
were largest for age stereotypes and smallest for evaluations. As predicted
by social role theory (Eagly, 1987), effect sizes were reduced when detailed information
was provided about the person being rated. The double standard of aging
emerged for evaluations and behavior/behavioral intentions, but was reversed for
the competence category. Perceptions depended on respondent age also. Results
demonstrated both the multi-dimensionality and the complexity of attitudes toward
older adults (Hummert, 1999; Kite & Wagner, 2002).
For over half a century, gerontologists have puzzled over North Americans’
fascination with youth and their reluctance to accept aging gracefully. Initially, research
on these issues was based on the assumption that negative attitudes toward
older adults were widespread (Butler, 1969). Subsequent reviewers have reached
different, and sometimes opposite conclusions. At the same time that Green (1981)
∗Correspondence concerning this article should be addressed to Mary E. Kite, Graduate School,
Ball State University, Muncie, IN 47306, 765-285-1300 [e-mail: mkite@bsu.edu]. This research was
supported by a grant (R03 AG17328-01) to the first author from the National Institute of Aging.
241
C 2005 The Society for the Psychological Study of Social Issues
242 Kite, Stockdale, Whitley, and Johnson
determined that negative age-related stereotypes were the norm, Lutsky (1980)
concluded that age, in and of itself, was less important in determining attitudes
toward older adults than were other types of information. More recent reviewers
(Hummert, 1999; Kite & Wagner, 2002) echoed McTavish’s (1971) conclusion;
the answer to the seemingly simply question “Does ageism exist?” is not an unequivocal
yes. Instead, people’s views about aging are multidimensional, with both
positive and negative elements.
This article examines the complexities of age-related attitudes and stereotypes
through a meta-analytic review of literature on ageism. Specifically, we update and
expand upon Kite and Johnson’s (1988) previous meta-analysis. Kite and Johnson
reviewed the literature on this topic prior to December 1985, examining a total of
43 independent effect sizes. Thirty of those effect sizes indicated that people were
more negative toward older than toward younger people, eleven indicated more
negative attitudes toward younger than toward older people, and two indicated
exactly no difference in attitudes toward the two groups. The overall effect size, as
indexed by the d statistic was 0.39, indicating that attitudes toward older persons
were more negative than attitudes toward younger persons by approximately onethird
of a standard deviation.
Although this finding indicated a bias against older adults, these effect sizes
were not homogeneous. That is, the difference in attitudes expressed about older
and younger adults varied widely across studies. Therefore, potential moderators
of the effect sizes were explored to account for this variation. Results supported
Lutsky’s (1980) contention that people do not rely solely on information about
age in judging older adults. Specifically, Kite and Johnson (1988) found that the
context provided for the ratings moderated the results. That is, when specific
information was provided about the target person, compared with when a general
target such as “old person” was used, age-based attitude differences were reduced
significantly. Results also depended on the types of questions asked; studies found
larger differences in attitudes toward older and younger adults when competence
was assessed and smaller differences when personality traits or willingness to
have contact with the target person was assessed. In addition, as Kogan (1979a)
had suggested, smaller differences between the evaluations of older and younger
adults emerged when a between-subjects, compared with a within-subjects, design
was used.
There are a number of reasons why the time is right for an updated metaanalytic
review of this literature. First, in the 15 years since Kite and Johnson’s
(1988) review was published, the literature on this topic has advanced considerably.
More sophisticated questions have been posed, and the methodological techniques
used to answer them have evolved also (Johnson & Eagly, 2000). Because of these
changes, our conceptualization of the issues is now much stronger. Although Kite
and Johnson’s results were consistent with social role theory (Eagly, 1987; Eagly,
Wood, & Diekman, 2000), their interpretation of their results in these terms was
Attitudes Toward Younger and Older Adults 243
post hoc; we now use this theory to frame a priori hypotheses. Moreover, rather
than considering attitude as a unidimensional construct for the overall analyses,
as Kite and Johnson did, we instead look at attitude components (e.g., evaluation,
stereotypes, competence) separately. Moreover, the present analysis is based on
nearly five times the number of effect sizes (232, compared with Kite & Johnson’s
original 43). Finally, in part because of this increase in the available literature,
we are now able to consider two critical issues concerning attitudes toward older
adults. One is the double standard of aging—the hypothesis that older women are
evaluated more negatively than older men (e.g., Sontag, 1979). Another is whether
younger and older adults view aging through the same lens. That is, are older
people more favorable toward aging because they themselves are old? We begin
with a review of social role theory and its relevance to this article.
Social Role Theory
The primary theoretical guide for our research was social role theory, which
proposes that viewing people in various social roles provides an important basis
for beliefs about social groups (Eagly, 1987; Eagly et al., 2000). According to this
theory, when we observe others, we pay attention to the social roles they occupy.
In making these observations, people are likely to exhibit the correspondence bias
(Ross, Amabile, & Steinmetz, 1977). That is, all things being equal, people give
relatively little weight to how situational constraints influence behavior; instead,
they believe a person’s actions tell about the person’s basic personality. Social
role theory proposes that this bias leads to the development of stereotypic beliefs.
Because people observe the role-driven behavior, which may or may not reflect
the real personality of the person being observed, perceivers come to associate the
characteristics of these roles with the individuals who occupy them.
One important social role is the employee role, which is occupied predominately
by younger people; in 1993, for example, only 2.7% of the work force
was 65 or older (U.S. Bureau of the Census, 1994). People perceive that this role
requires agentic traits, such as self-confidence and assertiveness (e.g., Eagly &
Steffen, 1984). Because those who occupy the employee role tend to be younger,
people draw the conclusion that younger people are more likely to have agentic
traits than are older people (e.g., Gekoski & Knox, 1990; Kite, Deaux, & Miele,
1991). However, when perceivers know that an older person is employed, their assessments
are based on that information rather than their stereotypes (Kite, 1996).
Other factors, such as health status, are also better predictors of attitudes toward
older adults than is target age (Gekoski & Knox, 1990), again highlighting the
importance of role information in people’s views of others.
Hummert’s (1993) work on subtypes of older individuals further supports
the proposition that beliefs about older adults are linked to the roles they are
perceived to occupy (see also Hummert, Garstka, & Shaner, 1997). Hummert
244 Kite, Stockdale, Whitley, and Johnson
and her colleagues have documented a set of stereotypes about older adults—
some positive and some negative—that correspond to consistent and identifiable
subtypes of older people. Examples include the positive subtypes of John Wayne
Conservative, Liberal matriarch/patriarch, and perfect grandparent and the negative
subtypes of severely impaired, shrew/curmudgeon, and inflexible senior citizen.
Subtypes that are seen as older have fewer positive traits associated with them
(Hummert et al., 1997) and memory problems are seen as more serious for some
subtypes (e.g., despondent) than for others (e.g., golden ager; Hummert, Garstka,
& Shaner, 1995). Consistent with social role theory, Hummert and her colleagues
have found that the role information contained within these subtypes outweighs
age per se as a predictor of evaluations. Finally, Kite and Johnson’s (1988) findings
support a social role perspective: As noted earlier, differences in evaluations due
to by target age were reduced significantly when specific information, compared
to general information, was provided about the person being rated.
What Represents a Negative Attitude Toward Older Adults?
The multidimensional nature of age-related stereotypes has long been noted
(Crockett & Hummert, 1987; McTavish, 1971), and we take this perspective
by classifying dependent measures into categories that reflect this complexity.
Although, arguably, all categories are evaluative to some degree, this approach
preserves important differences across categories and reflects the complexity of
the attitudes toward aging literature. We used five categories; evaluation, agerelated
stereotypes, behavior/behavioral intention, competence, and attractiveness.
The first three categories map onto the traditional tripartite division of
attitudes (see Eagly & Chaiken, 1993). The affective, or evaluative, category,
best represents the traditional meaning of attitude, defined as psychological tendencies
that are expressed by evaluating a particular entity with some degree of
favor or disfavor (Eagly & Chaiken, 1993). Representative items for this dimension
include the good/bad items from the Semantic Differential Scale (Osgood,
Suci, & Tannenbaum, 1957) and the personally acceptable/unacceptable items
from Aging Semantic Differential Scale (Rosencranz & McNevin, 1969). Agerelated
stereotypes are reflected in measures of stereotypic beliefs about older
adults (e.g., traditional, hard of hearing, dote on their grandchildren; Axelrod
& Eisdorfer, 1961; Kogan & Shelton, 1962; Stewart & Ryan, 1985). Behavior/
behavioral intention measures in the aging literature include the likelihood of recommending
evaluation by professionals following memory failure (Erber,
Szuchman, & Rothberg, 1990b), willingness to help (e.g., Weinberger, 1981),
preferences in hiring or other competitive venues (Gaetjens, 1997; Haefner, 1977),
and assessments based on observed interactions (e.g., instructions given to listeners;
Kemper, Vandeputte, Rice, Cheung, & Gubarchuk, 1995; Rubin & Brown,
1975).
Attitudes Toward Younger and Older Adults 245
The competence and attractiveness categories represent important dimensions
of age stereotypes also. Kite and Johnson (1988) found the largest bias against
older adults when competence was assessed and this continues to be a focus
of many studies; this category reflects the belief that competence declines with
age (see also Cuddy & Fiske, 2002). In the aging literature, competence assessments
include perceived intelligence or ability (e.g., Erber, Szuchman, & Rothberg,
1990a), and judgments of memory failure (e.g., Erber, Etheart, & Szuchman, 1992;
Erber, Szuchman, & Etheart, 1993; Matyi & Drevenstedt, 1989). Finally, physical
appearance is an important component of many stereotypic beliefs, particularly
those based on basic category memberships, such as age and gender (see Fiske,
1998, for a review). People perceive, specific to the aging literature, that attractiveness
and physical ability decrease with age (e.g., Deutsch, Zalenski, & Clark,
1986; O’Connell & Rotter, 1979). Wernick and Manaster (1984) found, for example,
that unattractive faces were consistently rated as older than were attractive
faces. Testing these multidimensional components is important because not only
do people hold a variety of beliefs and attitudes about older adults, those beliefs
are sometimes inconsistent. For example, people may believe that older people are
forgetful, but at the same time value their experience and wisdom (e.g., Kite &
Johnson, 1988).
Moderators of Age-Related Attitudes
Descriptors of the target. As discussed earlier, social role theory predicts
that the role-related information provided about the target influences evaluations
(Eagly, 1987; Eagly et al., 2000). In the aging literature, the detail provided about
the target ranges from age only (e.g., 70-year-old) or a young/old label (e.g.,
Carmel, Cwikel, & Galinsky, 1992; Luszcz & Fitzgerald, 1986), to detailed information
such as how they performed in an interview for a job (e.g., Avolio &
Barrett, 1987) or interacted with a therapist (e.g., Matyi & Drevenstedt, 1989).
Another common methodology involves using photographs to provide physical
appearance cues (e.g., Levin, 1988; Wernick & Manaster, 1984).
Because age is a basic social-cognitive category (e.g., Kunda, 1999), when
studies provided only age, we expected participants to rely on their general attitudes
and beliefs about older and younger adults when reporting their evaluations. When
more detail was available, people should have tempered their tendency to rely on
generalities, instead using the individuating information when making evaluations
(e.g., Deaux & Major, 1987; Fiske, Lin, & Neuberg, 1999). We expected agerelated
bias to be greatest when only demographic information about the target
is provided, somewhat smaller when minimal information about the target was
provided, and smallest when extensive information about the target was provided.
Theories suggesting that as information becomes more individuated, evaluations
are based less on social categories and more on the specific detail
246 Kite, Stockdale, Whitley, and Johnson
provided typically assume that this detail reflects positively on the target and is not
stereotype-confirming (e.g., Deaux & Major, 1987; Fiske, Lin, & Neuberg, 1999).
However, in the aging literature, many researchers manipulate the competence or
success of the person being rated so that either positive or negative information is
available to participants (e.g., Banziger & Drevenstedt, 1982; Matyi & Drevenstedt,
1989; Walsh & Connor, 1979). When possible, we considered the effects of
this manipulation.
Gender of person being rated. A limitation of the aging attitude literature is
the widespread use of labels such as elderly or older person that do not specify
whether the person to be rated is a man or a woman. It is highly likely that respondents
in these studies assumed or imagined the gender of the person they were
evaluating anyway. Research shows that people use male as the default category
and therefore assume maleness in the absence of specific information about a person’s
gender (see Matlin, 2004). Kite (1996) demonstrated that such assumptions
are related, also, to other types of information provided. Regardless of age, for example,
employed and older homemaker targets were imagined to be male whereas
younger homemaker targets were thought likely to be female. Such outcomes raise
questions about whether respondents can or will evaluate others without making
inferences about their gender also.
By failing to designate target gender, researchers overlook an important variable.
Women are thought to reach middle and old age (Drevenstedt, 1976; Kogan,
1979b) and the prime of life (Zepelin, Sills, & Heath, 1986) earlier than men.
Deutsch et al. (1986) found that older men were seen as more attractive than older
women, but found no differences in ratings of middle-aged or young women and
men. Hummert et al. (1997) found that women were likely to be stereotyped negatively
at a younger age than were men. Other research, however, has found no
evidence for an age-related double standard (Drevenstedt, 1981; Locke-Connor &
Walsh, 1980). Whether the sexes are viewed differently as they age may depend
on what you ask, with a double standard being more likely for physical appearance
ratings or gender-associated attributes than for competence. Erber et al. (1990a),
for example, found no differences in perceived forgetfulness of male and female
target persons. Canetto and her colleagues (1995) found older men were rated
higher on intellectual competence and autonomy whereas older women were rated
higher on nurturance. Because more researchers now have considered both the
age and the gender of the person being rated, we can consider the aging double
standard and the conditions under which it is or is not likely to emerge.
Respondent age. A number of studies have examined whether older people
are more favorable toward old age than are younger people. Results are mixed,
with some researchers finding this result (e.g., Anantharaman, 1979; Berg &
Sternberg, 1992; Erber, 1989; Guo, Erber, & Szuchman, 1999), others finding no
age differences (e.g., Bailey, 1991; Erber & Rothberg, 1991; Harris, Page, & Begay,
Attitudes Toward Younger and Older Adults 247
1988) or younger respondents being more positive than older respondents (Bell &
Stanfield, 1973; Rothbaum, 1983). Despite these mixed findings, the preponderance
of evidence suggests older people have more positive attitudes toward aging
than do younger people, leading us to expect this result.
Age of target. It has long been noted that attitudes toward the old-old (75
and older) are more negative than attitudes toward the young-old (55–64; e.g.,
Neugarten, 1975). As noted earlier, Hummert (1990) found that targets fitting a
positive subtype of older adults were perceived as younger than targets fitting
a negative subtype of older adults. Similarly, the number of positive stereotypes
associated with older people decreased significantly for photographs of the youngold
to middle-old to old-old (Hummert et al., 1997; Kogan, 1979a). Canetto et al.
(1995) found significant differences between 60- and 75-year-old targets. These
findings suggest that as target age increases, the age-related bias will increase; we
will examine this possibility.
Secondary moderators. There are a number of other factors that might moderate
the expected bias against older individuals. Age-related bias, for example,
depends on choice of experimental design (e.g., between- or within-subjects); as
Kogan (1979a) noted and Kite and Johnson (1988) confirmed, within-subjects
designs produce a greater age-related bias than do between-subjects designs. Publication
year may be important also: As noted previously, recent research has
been more likely to consider complex questions and may be more likely to use
dependent measures with well-established validity (see Kite & Johnson, 1988).
Similarly, studies that use multi-item attitude measures should produce more reliable
findings than studies with fewer items (e.g., Nunnally, 1978). Finally, there
may be differences due to the education, socioeconomic status, and ethnicity of
the sample (Whitley, 2002). We examine these secondary moderators, but do not
make predictions about which, if any, will prove important.
Method
Studies Sampled
To retrieve all the studies that had appeared by April, 2000, we carried out a
computerized literature search of PsycINFO (Psychological Abstracts) and Social
SciSearch. We searched for studies that compared attitudes toward the older adults
with attitudes toward the young by using the key words aged, old, elderly, attitudes,
stereotypes,senior citizen, attributions, and impression formation. In addition, bibliographies
of located studies were checked. We also hand searched all published
issues (up to April 2000) of Educational Gerontology, The Gerontologist, Journal
of Gerontology, and Psychology and Aging. We considered only studies that compared
older (55 years or older) to younger targets. Younger targets were categorized
248 Kite, Stockdale, Whitley, and Johnson
as either young (21–35 years) or middle aged (36–54 years). Only studies in which
the participants were at least 18 years of age and the younger target person was at
least 21 years old were included. Included studies are marked with an asterisk in
the reference section.
Effect Sizes
The effect size calculated was g, representing the standardized difference
between the ratings of younger and older targets. Positive effect sizes indicate
that the attitude toward the older target was more negative and negative effect
sizes indicate that the attitude toward the younger target was more negative; an
effect size of zero indicates exactly no difference between the attitudes expressed
toward older and younger targets. Whenever possible, g was derived directly from
means and standard deviations, or from F or t statistics (e.g., Lipsey & Wilson,
2001; Rosenthal, 1994). Otherwise, techniques such as probit transformations of
dichotomous frequencies were used to estimate the effect sizes. Effect sizes were
computed by two independent raters; a third rater randomly checked computations
for each study to ensure the method employed was appropriate. Disagreements
were resolved by discussion. The resulting effect sizes (ds) were corrected for bias
due to sample size (Hedges, 1982).
Categories of Effect Sizes
Because attitudes toward older adults are multidimensional, we placed effect
sizes into one of five categories: evaluation (e.g., generous, friendly), competence
(e.g., intelligent, good memory), attractiveness (e.g., pretty, wrinkled),
behavior/behavior intentions (e.g., willingness to interact with; make phone call),
and age stereotypes (e.g., old-fashioned, talks about past). To accomplish this,
we first compiled a list of all dependent measures used in the located studies.
Three raters categorized all dependent measures into one of the five categories,
with a 95% agreement rate. Disagreements were resolved by discussion. Our decisions
were guided by theoretical distinctions among the categories, as well as
the decisions of previous researchers. For example, items that appeared on the
evaluation component of the Semantic Differential (Osgood et al., 1957) and the
Aging Semantic Differential (Rosencranz & McNevin, 1969) were categorized as
evaluative. Items categorized as age stereotypes by others (Axelrod & Eisdorfer,
1961; Kogan & Shelton, 1962; Stewart & Ryan, 1985) were similarly categorized
for this analysis. Overall effect sizes were computed separately for each of these
categories by averaging across all items relevant to that category. In the reference
list, the categories for which a study produced effect sizes are marked by AS (Age
Stereotype), AE (Attractiveness-Evaluative), C (Competence), E (Evaluation), or
B (Behavior/Behavioral Intention).
Attitudes Toward Younger and Older Adults 249
Table 1. Summary Statistics for Categories of Dependent Variables
Category of Dependent Variable Number of Studies dz Qw
Age Stereotype 11 .47 11.53∗∗ 118.48∗∗
Attractiveness (Evaluative) 17 .38 16.21∗∗ 187.56∗∗
Competence 75 .33 23.10∗∗ 825.21
Behavior/Behavioral Intention 29 .21 11.34∗∗ 377.34∗∗
Evaluation 100 .24 19.92∗∗ 974.26∗∗
Note. A positive d indicates more negative attitudes toward older adults.
Qw represents within-category homogeneity. Higher values indicate less homogeneity of effect sizes.
p < .01 ∗∗∗p < .001.
Some categories of dependent measures are theoretically important, but were
represented by too few studies to be included (e.g., beliefs about language
performance; Hummert, Garstka, Shaner, & Strahm, 1995). Finally, some categories
of dependent measures fell outside the attitude domain; these included
measures of personal concern about the consequences of being old (e.g., Kiemmack,
1980), evaluations of luck or effort (e.g., Reno, 1979), and judgments about
the age at which various life markers such as middle and old age are reached (Hori,
1994). Dependent measures representing these domains were excluded from our
analysis.
The unit of analysis for our research was the individual study, defined as (a)
the only study reported within an article, (b) a separate study within an article
(e.g., Study One, Study Two), or (c) a separate sample within the same study
(e.g., a replication with a sample from a different population). In many cases, an
individual study assessed more than one category of dependent variable, such as
both competence and evaluation. In such cases, the effect size for each category
was analyzed as part of its category; thus, the total number of effect sizes analyzed
exceeds the total number of studies. Also, many studies used more than one measure
to assess a particular category of dependent variable. In those cases, ds were
computed for each dependent variable within a category and averaged to create
an effect size for that category. Thus, an individual study was presented only once
within a category to ensure independence of data (e.g., Johnson & Eagly, 2000).
Table 1 contains the number of studies in each of the five categories.
Study Characteristics
The following information was coded for each study: (a) publication year, (b)
respondent gender (recorded as the percentage of men in the sample), (c) number
of items in the dependent measure, (d) number of points on the rating scale (if
applicable), and (e) study design (between- or within-subjects). We coded, also,
respondent age as young, middle age, old, or unknown. When actual respondent age
was reported, we categorized those younger than 35 as young, those between the
250 Kite, Stockdale, Whitley, and Johnson
ages of 35 and 54 as middle aged, and those older than 55 as old. Respondents were
categorized, also, as undergraduates, graduate students/professionals, or from a
general population. Target gender was coded as male, female, both, or unspecified;
the both category was used when target gender was varied, but effect sizes could
not be computed separately by that factor.
The information provided about the target was coded as demographics only
(e.g., only age provided), minimal information (e.g., sick or healthy; working
or not working), or extensive information (e.g., detailed description of person,
detailed work history, intake report for therapy). We also coded whether the information
provided was positive, negative, or neutral. The presentation of target
age information varied widely. Some researchers provided only general age categories
(e.g., young, old) and others provided specific ages. Also, the number of
age categories used varied widely, from 2 to 14. To reduce the complexity and to
ensure no one study was over-represented in the analysis of target age, we used
five age categories (21–37, 38–54, 55–70, 71–85, 86 and older) that allowed us to
make relative age comparisons; for example, 55–70 year olds could be compared
to 86 and older targets, even though both categories represented “older” adults.
In developing these cutoffs, we considered the actual age categories used by researchers
and the distinction between young, middle-age, young-old, middle-old,
and old-old targets (e.g., Neugarten, 1975). Also, we used categories with equal
age intervals. When studies provided comparisons for more than two age groups
within a category, we computed effect sizes separately for each comparison and
then averaged the effect sizes within categories. For example, if a study provided
ratings of 30- and 65-year-olds and of 35- and 65-year-olds, ds were averaged so
that the study had only one effect size which represented a 21-37-year-old target
compared to a 55-70-year-old target.
In all cases, coding was completed by two independent raters. Coders achieved
98.6% agreement; disagreements were resolved by discussion with a third rater.
For all analyses, results were collapsed across all categorical variables except the
variable of interest. If a study included data from more than one sample (e.g.,
undergraduates and general population), but separate effect sizes could not be
computed, the study was excluded from the analysis of that moderator variable.
Results
Within each category of dependent variable, stem and leaf plots were computed
to identify outliers. Outliers were found for evaluation (n = 3) and competence
(n = 3); for these categories, analyses were computed with and without outliers.
Only minor differences in the results emerged, so the analyses reported here include
outliers. Occasionally, researchers reported only that effects were not significant
or reported only a p value for significant results; in such cases, the accuracy of
the effect size estimate is questionable (e.g., Johnson & Eagly, 2000); however,
Attitudes Toward Younger and Older Adults 251
excluding these estimates did not materially affect the results, so we report findings
including those studies.
Overall Effect Sizes
Summary statistics for all categories of dependent variables are provided in
Table 1. For all categories, respondents showed a preference for younger rather
than older adults. Younger adults were rated less stereotypically, seen as more
attractive and more competent, and were evaluated more favorably than older
adults; also, behavioral preferences were given to younger adults. All mean effect
sizes were significantly different from zero, as evidenced by the z statistic. In no
case were effect sizes within a category homogeneous, as indicated by Qw, so there
was significant unexplained variance within each category. Therefore moderator
variables were examined to try to account for this additional variance.
Moderator Variable Analyses
We report results only when at least seven studies were available at each
level of categorical moderator variables and at least 15 studies were available for
continuous moderator variables. Because of these criteria, analyses of moderator
variables are limited to the competence, evaluation, and behavior/behavioral intention
categories. Summary statistics for the categorical moderator variables are
shown in Table 2 and those for the continuous moderator variables are shown in
Table 3.
Amount of information about the target person. When any individuating information
was provided about the people being rated, we expected smaller differences
between ratings of older and younger adults. Moreover, we expected differences
to be smallest when more detailed information was provided. As can be seen
in Table 2, regardless of the amount of information presented, older adults were
always perceived as less competent, evaluated less favorably, and treated more negatively
than younger adults. However, when extensive information was presented,
these age differences were smaller than when only target age was provided. When
minimal information was provided, differences in perceived competence were
larger than when no information or extensive information was presented. For the
evaluation dependent measure, effect sizes in the minimal information category fell
between the no information and extensive information categories. For the behavior/
behavioral intention measure, the effect sizes in the extensive and minimal information
categories were similar and both were smaller than the no information
category.
252 Kite, Stockdale, Whitley, and Johnson
Table 2. Analyses of Moderator Variables for Competence, Evaluation, and Behavior/Behavioral
Intention Dependent Measures
Behavior/Behavioral
Competence Evaluation Intention Moderator
Variable Condition d QB d QB d QB
Information None .39a 98.26∗ .30a 62.05∗ .34a 10.60∗
k = 23 k = 51 k = 7
Minimal .46b .15b .19b
k = 17 k = 25 k = 7
Extensive .11c .06c .18b
k = 36 k = 24 k = 15
Valence of Positive .16a 31.88∗ .04a 21.46∗ .55a 243.97∗∗
Information k = 21 k = 20 k = 9
Neutral .21a .10a –.25b
k = 21 k = 23 k = 7
Negative .38b .27b .19c
k = 25 k = 18 k = 11
Respondent Younger .34a 19.26∗ .21a 34.86∗ .32a 339.74∗∗
Age k = 59 k = 78 k = 15
Middle Age .50b .47b –
k = 11 k = 11
Older .26c .36c .14b
k = 10 k = 14 k = 11
Target Male .44a 146.14 .30a 60.44∗ .08a 28.79∗∗
Gender k = 23 k = 40 k = 10
Female .16b .36b .28b
k = 20 k = 24 k = 11
Unspecified .45a .25c .37c
k = 21 k = 34 k = 11
Both .03c .06d –
k = 14 k = 17
Design Between .21 79.98∗ .10 145.91∗ .02a 168.32∗∗
k = 57 k = 56 k = 17
Within .47 .39 .51b
k = 18 k = 44 k = 12
Population Undergraduates .37a 3.40 .23a < 1 .25a 157.04∗∗∗
k = 47 k = 72 k = 12
Graduate .31a .22a .51b
Students/ k = 8 k = 8 k = 9
Professionals
General .34a .20a –
Population k = 13 k = 12
Note. k = number of studies. Different subscripts indicate conditions within dependent measures
that differ at the .05 level of significance. QB represents between-category homogeneity. Significant
values indicate effect sizes vary by category.
∗p < .05; ∗∗p < .01; ∗∗∗p < .001.
Valence of information about the target person. When minimal or extensive
information was provided about the target, we coded its valence as positive,
negative, or neutral. For both the competence and the evaluation dependent measures,
perceived differences between younger and older targets were largest when
negative, rather than positive or neutral, information was provided; ds in these
Attitudes Toward Younger and Older Adults 253
Table 3. Standardized Regression Coefficients for Continuous Moderator Variables
Behavior/Behavioral
Competence Evaluation Intention
k B k Bk B
Target age differences 69 0.0005 83 –0.0055∗∗∗ 29 –0.0113∗∗∗
Number of items on scale 72 0.0043 94 0.0034 25 0.0006
Number of scale points 63 –0.0028 88 0.0015∗ 21 –0.0006
Percent male participants 63 0.0039∗∗∗ 82 0.0003 27 –0.0022∗∗∗
Date of publication 75 –0.0179∗∗∗ 100 –0.0019 27 0.0042
Note. k = number of studies. ∗p <.05. ∗∗∗p <.001.
latter two categories did not significantly differ. Age-related differences in behavior/behavioral
intentions were largest when the provided information was positive,
followed by when the information provided was negative. When neutral information
was presented, older individuals were treated more favorably than younger
individuals.
Respondent age. Middle-aged respondents showed a greater preference for
younger adults, both in assessments of their competence and in their evaluations
of those groups, compared to older and younger respondents. Also, older
respondents believed younger targets were more competent than older targets, but
this preference was the smallest of any age group; younger respondents’ competence
ratings fell between those of the other age groups. Older respondents’
evaluations, however, showed larger perceived age differences than did younger
respondents’ assessments. For behaviors/behavioral intentions, only younger and
older targets could be compared; there were larger age-related differences for
younger targets than for older targets.
Target gender. A double standard of aging suggests that perceived age differences
will be larger when women, rather than men, are rated. This pattern emerged
for evaluations and behaviors/behavioral intentions. However, raters saw greater
differences in the competence of older and younger men than in the competence
of older and younger women.
Often, when the gender of the target is unspecified, raters assume the person
being rated is male (Kite, 1996). This suggests that ratings in the target unspecified
category should be similar to those for the male target category. For the competence
dependent measure these two categories did not differ. For the evaluation
category, however, perceived age differences were smaller when target gender was
unspecified than when either male or female targets were rated. For the behavior/
behavioral intention dependent measure, perceived age differences were largest
in the unspecified category. Where both women and men were rated, but separate
254 Kite, Stockdale, Whitley, and Johnson
effect sizes for target gender could not be computed, older and younger targets
were rated similarly in both the evaluation and the competence categories.
Study characteristics. Between subjects designs resulted in smaller perceived
age differences in competence, smaller differences in the evaluations of younger
and older targets, and smaller differences in behaviors/behavioral intentions (see
Table 2). The number of items was not related to d for any of the dependent
variables (see Table 3). In addition, the number of scale points was not related to
d for competence or behavior/behavioral intentions. On the evaluation measure, d
increased by 0.002 units for each additional scale point.
Research population. Whether the respondents were drawn from a sample of
undergraduates, graduate students/professionals, or the general population made
no difference in the size of the perceived age differences on the competence or the
evaluation dependent measures. Graduate students/professionals did show a greater
preference for older adults than did undergraduates on the behavior/behavioral
intention measure.
Difference in ages of targets. The difference in ages between the older target
and the comparison target was not related to the magnitude of the effect sizes for
competence ratings (see Table 3). However, d became smaller for evaluations and
behavior/behavioral intentions as age differences increased, with d decreasing by
about 0.01 units (e.g., from 0.31 to 0.30) for each year the age difference increased.
Gender of research participant. Gender of research participant was not related
to d for evaluations, but was for competence ratings and behavior/behavioral
intentions. However, the pattern of these gender differences was mixed. For competence
ratings, d increased by 0.004 units for each 1% increase in men in the
sample. For behavior/behavioral intentions, d decreased by 0.002 units for each
1% increase in men in the sample.
Date of publication. Date of publication was not related to d for evaluations
or behavior/behavioral intentions. However, for competence ratings, d decreased
0.02 units for each year the publication date became more recent.
Discussion
Does ageism exist? When a broad view is taken, the answer is yes. Across
all categories of dependent variables, we found a bias against older adults. Yet
this bias was largest when stereotypic beliefs and perceptions of attractiveness
were assessed; the bias was reduced when behaviors/behavioral intentions or affective
evaluations were measured. Competence ratings fell roughly between these
Attitudes Toward Younger and Older Adults 255
two extremes. Our results, then, confirm what has often been stated: Perceptions
of older adults are complex and multidimensional (Crockett & Hummert, 1987;
Hummert, 1999; Lutsky, 1980). People do seem to hold clear stereotypic beliefs
that differentiate older and younger adults (Cuddy & Fiske, 2002), including beliefs
that age reduces attractiveness and, to a lesser extent in our data, competence.
We explored these complexities in more detail by examining a number of moderator
variables. As with any meta-analysis, however, we were limited by the available
literature. One outcome, in this case, was that moderators of the age stereotype or
the attractiveness categories could not be examined because too few studies exist.
Moderator analyses, then, were limited to the competence, behavior/behavioral
intention and evaluation categories.
Role Information
We proposed that contextual information would influence people’s perceptions
of older adults (Eagly, 1987; Eagly et al., 2000; Kite & Johnson, 1988) and
this was borne out in our results. Across the three categories of dependent variables
we considered, effect sizes were reduced significantly when judgments were
based on extensive, rather than minimal information. When participants knew, for
example, about the history of the person they evaluated, they perceived fewer age
differences. Providing even minimal additional information, such as employment
or health status, reduced, also, the effect sizes in the evaluation and behavior/
behavioral intention categories. The only exception was that, when judgments of
competence were assessed, providing minimal information actually resulted in a
larger bias against older adults. The reason for this discrepancy remains unclear;
a careful examination of the 17 studies in this category showed wide variability
in other factors affecting participants’ responses, such as valence of information
or gender of person to be rated. We suspect it is a combination of these factors
that produced the unexpected result, rather than any theoretically interesting differences
among the studies. Overall, our analysis of context effects supports our
contention that it is not growing old, per se, that produces negative perceptions,
but rather the roles that older adults occupy. Consistent with social role theory
(e.g., Eagly, 1987; Eagly et al., 2000), when contextual information was made
explicit, differences in evaluations of younger and older adults were significantly
reduced.
As Hummert and her colleagues have demonstrated, those roles can be positive
or negative (Hummert, 1993; Hummert et al., 1995; Hummert et al., 1997). Our
results suggest, also, that the valence of the information provided influences judgments.
When negative information was presented, perceived age differences were
larger in both the competence and evaluation categories, compared with when neutral
or positive information was presented. Positive information, however, produced
a larger age-related bias when behaviors/behavioral intentions were assessed. This
256 Kite, Stockdale, Whitley, and Johnson
may have been due to the fact that the three largest effects sizes, of the seven in
that group, emerged in studies of employment discrimination (Bendick, Brown,
& Wall, 1999; Bendick, Jackson, & Romero, 1996); a fourth positive effect size
was in a study of skill assessment (Walsh & Connor, 1979). These results may
reflect the actual workplace discrimination that older adults face (e.g., Finkelstein,
Burke, & Raju, 1995; Gordon et al., 2000). Overall, however, these results suggest
that negative perceptions of older adults can be reduced when evaluators see older
and younger people as behaving similarly, especially when that behavior is in a
positive context. Once again, providing additional information reduces the impact
age information alone has on perceptions.
Age of Rater
As we predicted, older adults saw fewer differences between the young and
old, and younger adults saw greater differences. The exception was for evaluative
judgments; for that category of dependent variables, younger adults saw smaller
age differences than older adults did. For younger adults, the competence and
behavior/behavioral intention results are consistent with Social Identity Theory
(SIT; Tajfel & Turner, 1979; Turner & Oakes, 1989), which proposes that people
strive to maintain positive images of their ingroups. When they are evaluating an
older person, younger adults are judging someone who is not a member of our
own age group; drawing larger distinctions between older and younger adults is a
way to maintain a positive social identity. More puzzling is why older evaluators
did not show a bias in favor of their own group (i.e., none of the mean effect sizes
were positive). One possibility is that, because they themselves were once young,
and thus a member of the other group, devaluing that group does not produce
a positive image. Older adults may, instead, use other options for maintaining a
positive self-image, such as social mobility, social creativity, or social competition
(see Harwood, Giles, & Ryan, 1995; Kite & Wagner, 2002 for discussions).
Interestingly, middle-aged respondents saw the largest age-related bias in the
two categories for which this comparison could be made, competence and evaluation.
As Kite and Wagner (2002) argued, this may be because middle-aged adults
see old age as right over the horizon, but still are not quite ready to accept its coming
(Montepare & Lachman, 1989). Accordingly, they may have a greater need
than younger people to maintain their positive self-image by devaluing older adults.
Only 11 studies employed a middle age sample, so any explanation is tentative. Yet
the possibilities, and the general questions our results raise about respondent age
differences in attitudes toward older adults, deserve attention in future research.
It should be noted that a large literature has examined rater age without also
exploring target age differences; those studies are, by definition, excluded from
this meta-analysis. As Kite and Wagner (2002) noted, a narrative review of this
literature is insufficient to draw conclusions. The field would benefit greatly from
Attitudes Toward Younger and Older Adults 257
a meta-analysis of this expanded literature which examined both the overall pattern
of effects and potential moderators of any uncovered respondent age differences.
SIT offers an obvious theoretical grounding for such an endeavor (see Harwood
et al., 1995 for a discussion of SIT and ageism).
Is There an Aging Double Standard?
The studies we reviewed in the introduction suggested that the aging double
standard might be elusive, or at least more complex than it appears at first glance,
and our results bear this out. When the assessments concerned competence, it was
the aging male who was viewed more negatively; age differences were comparatively
small when women were rated. Competence is a central component of the
male stereotype (e.g., Deaux & LaFrance, 1988; Eagly, 1987) and men are believed
to lose agency with age (Kite, 1996). It is not surprising, then, that the double standard
appears to be reversed when this dimension is assessed. In contrast, when
behaviors and behavioral intentions are assessed, the double standard does favor
men, with larger age differences emerging for female targets. Age differences
were also significantly larger for women then men when evaluative judgments
were measured, but the magnitude of this difference is not compelling (.30 for
male targets versus .36 for female targets).
Based on the findings that women reach middle and old age (Drevenstedt,
1976; Kogan, 1979b) and the prime of life (Zepelin et al., 1986) at a younger age
then men, it is reasonable to expect the double standard of aging is most likely
to operate when attractiveness is assessed. Unfortunately, too few studies were
available to test this hypothesis. A critical point is that target gender does influence
perceptions of older adults and researchers should, at minimum, specify this
variable even if they choose not to manipulate it, especially because respondents
make assumptions about target gender based on stereotypes and/or experimental
manipulations (e.g., Kite, 1996; Matlin, 2004). And, of course, there are theoretical
reasons, grounded in both the gender and the aging literature, to pursue this
question.
Study Characteristics
As Kite and Johnson (1988) showed, and our results confirm, within subjects
designs produced significantly larger perceived age differences, in some cases five
times as large as those produced by between-subjects designs. Other methodological
decisions, such as the properties of the rating scale, had negligible effects. Also,
different populations of raters viewed the age-related comparisons similarly. We
had hoped to consider cross-cultural differences in perceptions of older adults and
also whether ethnic groups within the United States viewed aging differently. Unfortunately,
too few studies have examined aging either cross-culturally or within
258 Kite, Stockdale, Whitley, and Johnson
subcultures of the United States and Canada. This is without a doubt a weakness
of this literature and one that deserves attention.
We did examine whether larger target age gaps (e.g., a 50-year age gap versus
a 15-year age gap) would produce larger age-related differences. Unfortunately,
analyses within the three categories showed either no target age effects or showed
smaller age differences as the target age differences increased, which is not the
pattern we predicted. Because our sample of studies represented such a mixture
of procedures for varying target age, and because other factors also often varied
across studies, we doubt we have provided the definitive answer. Many studies,
for example, used only global labels such as young and old. Those that specified
several ages were likely to use within-subjects designs, alerting participants to the
study’s focus. As we noted in the introduction, the declines associated with older
age groups are not likely to go unnoticed. What is needed is theoretically driven
research that can examine this complex issue in the context of specific predictions.
Gender of research participant produced a similarly confusing pattern of results,
although there is little reason to expect either gender to be more ageist.
Consistent with our early discussion of the importance of competence to the male
stereotype, it is interesting that having more male respondents did increase the
perceived age difference on that dimension. Finally, only for competence ratings
did more recent studies show a smaller age bias. Kite and Johnson (1988) found
somewhat stronger evidence that the age bias decreased by publication year, but
given that the vast majority of the studies examined in the present work were
published since then, it is perhaps not surprising that this effect has diminished.
Overall, as with any set of studies, methodological decisions can alter outcomes,
but these decisions are typically of less importance than theoretically chosen variables
(Whitley, 2002).
Summary and Conclusions
Perhaps the most heartening aspect of this updated meta-analysis is the explosion
of research that has taken place since our earlier meta-analysis. And, importantly,
this research has improved in quality and quantity. There is little doubt that
the research questions are more sophisticated and the problems being evaluated
more meaningful. When the questions addressed by Kite and Johnson (1988) were
reexamined here, the outcomes were similar. But certainly we can have more confidence
in these results because they are based on a larger, richer data set. Moreover,
we were able to pose new questions and suggest directions for future research. And
some questions, such as whether older workers experience discrimination, were
not reexamined because others have conducted meta-analyses specifically on that
topic (Finkelstein et al., 1995; Gordon et al., 2000).
It goes without saying that the results of this meta-analysis are limited by the
sample of studies that have examined this issue to date. Moreover, it seems obvious
Attitudes Toward Younger and Older Adults 259
that understanding ageism is not limited to the theoretical ideas or methodologies
employed in the past. As Nelson (2002) states, “age prejudice is one of the most
condoned, institutionalized forms of prejudice in the world—especially in the
United States—today” (p. ix). Gerontologists in all fields are taking a closer look
and, in doing so, are unmasking these hidden beliefs. Our review provides an upto-date
summary of this progress and suggests fruitful avenues for continuing the
work. Perhaps it is time to get aside the question of whether ageism exists and
continue to explore when and where the consequences are most severe.
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Note. References marked with an asterisk indicate studies included in the metaanalysis.
AS = Age Stereotype, AE = Attractiveness-Evaluative, C = Competence, E =
Evaluation), and B = Behavior/Behavioral Intention.
MARY E. KITE is Associate Dean of the Graduate School and Professor of Psychological
Science at Ball State University. She has published many articles and
book chapters about her research on stereotyping and prejudice. Kite is particularly
interested in gender-based prejudice and how those beliefs influence other
stereotypic judgments.
GARY STOCKDALE received a Master’s of Arts in clinical psychology from
Ball State University in 2000 and the Ball State University Alumni Association
Distinguished Master’s Thesis Award. He is now a doctoral student in quantitative
psychology at the University of California, Davis. His interests include modeling
human behavior and its determinants using latent growth curve analysis.
BERNARD E. WHITLEY, JR., is Professor of Psychological Science at Ball State
University, Muncie Indiana. His research centers on the role of individual difference
variables in prejudice. He is author, coauthor, or coeditor of four books,
including Principles of Research in Behavioral Science (McGraw-Hill, 2002).
BLAIR T. JOHNSON is Professor of Psychology at the University of Connecticut.
His research covers aspects of social influence and attitude change, the prediction
of behaviors from attitudes and other variables, and the social psychology of health
promotion including HIV prevention. Johnson is also the author of numerous
journal articles, chapters, notes, and reviews in his research specialties.

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this is not a multiple  choice test at all read article  and made the multiple choice
Copy and paste reaction papers here. Please be sure (1) 1/2 page (single spaced) and (2) include a multiple-choice item (see below example).
In the Robbers Cave Study what were the two group names?
A. Bears & Tigers
B. Rattlers & Eagles
C. Hawks & BulldogsD. Puppies & KittiesJournal of Social Issues, Vol. 61, No. 2, 2005, pp. 241–266
Attitudes Toward Younger and Older Adults: An
Updated Meta-Analytic Review
Mary E. Kite∗
Ball State University
Gary D. Stockdale
University of California-Davis
Bernard E. Whitley, Jr.
Ball State University
Blair T. Johnson
University of Connecticut
This meta-analytic review of 232 effect sizes showed that, across five categories,
attitudes were more negative toward older than younger adults. Perceived age differences
were largest for age stereotypes and smallest for evaluations. As predicted
by social role theory (Eagly, 1987), effect sizes were reduced when detailed information
was provided about the person being rated. The double standard of aging
emerged for evaluations and behavior/behavioral intentions, but was reversed for
the competence category. Perceptions depended on respondent age also. Results
demonstrated both the multi-dimensionality and the complexity of attitudes toward
older adults (Hummert, 1999; Kite & Wagner, 2002).
For over half a century, gerontologists have puzzled over North Americans’
fascination with youth and their reluctance to accept aging gracefully. Initially, research
on these issues was based on the assumption that negative attitudes toward
older adults were widespread (Butler, 1969). Subsequent reviewers have reached
different, and sometimes opposite conclusions. At the same time that Green (1981)
∗Correspondence concerning this article should be addressed to Mary E. Kite, Graduate School,
Ball State University, Muncie, IN 47306, 765-285-1300 [e-mail: mkite@bsu.edu]. This research was
supported by a grant (R03 AG17328-01) to the first author from the National Institute of Aging.
241
C 2005 The Society for the Psychological Study of Social Issues
242 Kite, Stockdale, Whitley, and Johnson
determined that negative age-related stereotypes were the norm, Lutsky (1980)
concluded that age, in and of itself, was less important in determining attitudes
toward older adults than were other types of information. More recent reviewers
(Hummert, 1999; Kite & Wagner, 2002) echoed McTavish’s (1971) conclusion;
the answer to the seemingly simply question “Does ageism exist?” is not an unequivocal
yes. Instead, people’s views about aging are multidimensional, with both
positive and negative elements.
This article examines the complexities of age-related attitudes and stereotypes
through a meta-analytic review of literature on ageism. Specifically, we update and
expand upon Kite and Johnson’s (1988) previous meta-analysis. Kite and Johnson
reviewed the literature on this topic prior to December 1985, examining a total of
43 independent effect sizes. Thirty of those effect sizes indicated that people were
more negative toward older than toward younger people, eleven indicated more
negative attitudes toward younger than toward older people, and two indicated
exactly no difference in attitudes toward the two groups. The overall effect size, as
indexed by the d statistic was 0.39, indicating that attitudes toward older persons
were more negative than attitudes toward younger persons by approximately onethird
of a standard deviation.
Although this finding indicated a bias against older adults, these effect sizes
were not homogeneous. That is, the difference in attitudes expressed about older
and younger adults varied widely across studies. Therefore, potential moderators
of the effect sizes were explored to account for this variation. Results supported
Lutsky’s (1980) contention that people do not rely solely on information about
age in judging older adults. Specifically, Kite and Johnson (1988) found that the
context provided for the ratings moderated the results. That is, when specific
information was provided about the target person, compared with when a general
target such as “old person” was used, age-based attitude differences were reduced
significantly. Results also depended on the types of questions asked; studies found
larger differences in attitudes toward older and younger adults when competence
was assessed and smaller differences when personality traits or willingness to
have contact with the target person was assessed. In addition, as Kogan (1979a)
had suggested, smaller differences between the evaluations of older and younger
adults emerged when a between-subjects, compared with a within-subjects, design
was used.
There are a number of reasons why the time is right for an updated metaanalytic
review of this literature. First, in the 15 years since Kite and Johnson’s
(1988) review was published, the literature on this topic has advanced considerably.
More sophisticated questions have been posed, and the methodological techniques
used to answer them have evolved also (Johnson & Eagly, 2000). Because of these
changes, our conceptualization of the issues is now much stronger. Although Kite
and Johnson’s results were consistent with social role theory (Eagly, 1987; Eagly,
Wood, & Diekman, 2000), their interpretation of their results in these terms was
Attitudes Toward Younger and Older Adults 243
post hoc; we now use this theory to frame a priori hypotheses. Moreover, rather
than considering attitude as a unidimensional construct for the overall analyses,
as Kite and Johnson did, we instead look at attitude components (e.g., evaluation,
stereotypes, competence) separately. Moreover, the present analysis is based on
nearly five times the number of effect sizes (232, compared with Kite & Johnson’s
original 43). Finally, in part because of this increase in the available literature,
we are now able to consider two critical issues concerning attitudes toward older
adults. One is the double standard of aging—the hypothesis that older women are
evaluated more negatively than older men (e.g., Sontag, 1979). Another is whether
younger and older adults view aging through the same lens. That is, are older
people more favorable toward aging because they themselves are old? We begin
with a review of social role theory and its relevance to this article.
Social Role Theory
The primary theoretical guide for our research was social role theory, which
proposes that viewing people in various social roles provides an important basis
for beliefs about social groups (Eagly, 1987; Eagly et al., 2000). According to this
theory, when we observe others, we pay attention to the social roles they occupy.
In making these observations, people are likely to exhibit the correspondence bias
(Ross, Amabile, & Steinmetz, 1977). That is, all things being equal, people give
relatively little weight to how situational constraints influence behavior; instead,
they believe a person’s actions tell about the person’s basic personality. Social
role theory proposes that this bias leads to the development of stereotypic beliefs.
Because people observe the role-driven behavior, which may or may not reflect
the real personality of the person being observed, perceivers come to associate the
characteristics of these roles with the individuals who occupy them.
One important social role is the employee role, which is occupied predominately
by younger people; in 1993, for example, only 2.7% of the work force
was 65 or older (U.S. Bureau of the Census, 1994). People perceive that this role
requires agentic traits, such as self-confidence and assertiveness (e.g., Eagly &
Steffen, 1984). Because those who occupy the employee role tend to be younger,
people draw the conclusion that younger people are more likely to have agentic
traits than are older people (e.g., Gekoski & Knox, 1990; Kite, Deaux, & Miele,
1991). However, when perceivers know that an older person is employed, their assessments
are based on that information rather than their stereotypes (Kite, 1996).
Other factors, such as health status, are also better predictors of attitudes toward
older adults than is target age (Gekoski & Knox, 1990), again highlighting the
importance of role information in people’s views of others.
Hummert’s (1993) work on subtypes of older individuals further supports
the proposition that beliefs about older adults are linked to the roles they are
perceived to occupy (see also Hummert, Garstka, & Shaner, 1997). Hummert
244 Kite, Stockdale, Whitley, and Johnson
and her colleagues have documented a set of stereotypes about older adults—
some positive and some negative—that correspond to consistent and identifiable
subtypes of older people. Examples include the positive subtypes of John Wayne
Conservative, Liberal matriarch/patriarch, and perfect grandparent and the negative
subtypes of severely impaired, shrew/curmudgeon, and inflexible senior citizen.
Subtypes that are seen as older have fewer positive traits associated with them
(Hummert et al., 1997) and memory problems are seen as more serious for some
subtypes (e.g., despondent) than for others (e.g., golden ager; Hummert, Garstka,
& Shaner, 1995). Consistent with social role theory, Hummert and her colleagues
have found that the role information contained within these subtypes outweighs
age per se as a predictor of evaluations. Finally, Kite and Johnson’s (1988) findings
support a social role perspective: As noted earlier, differences in evaluations due
to by target age were reduced significantly when specific information, compared
to general information, was provided about the person being rated.
What Represents a Negative Attitude Toward Older Adults?
The multidimensional nature of age-related stereotypes has long been noted
(Crockett & Hummert, 1987; McTavish, 1971), and we take this perspective
by classifying dependent measures into categories that reflect this complexity.
Although, arguably, all categories are evaluative to some degree, this approach
preserves important differences across categories and reflects the complexity of
the attitudes toward aging literature. We used five categories; evaluation, agerelated
stereotypes, behavior/behavioral intention, competence, and attractiveness.
The first three categories map onto the traditional tripartite division of
attitudes (see Eagly & Chaiken, 1993). The affective, or evaluative, category,
best represents the traditional meaning of attitude, defined as psychological tendencies
that are expressed by evaluating a particular entity with some degree of
favor or disfavor (Eagly & Chaiken, 1993). Representative items for this dimension
include the good/bad items from the Semantic Differential Scale (Osgood,
Suci, & Tannenbaum, 1957) and the personally acceptable/unacceptable items
from Aging Semantic Differential Scale (Rosencranz & McNevin, 1969). Agerelated
stereotypes are reflected in measures of stereotypic beliefs about older
adults (e.g., traditional, hard of hearing, dote on their grandchildren; Axelrod
& Eisdorfer, 1961; Kogan & Shelton, 1962; Stewart & Ryan, 1985). Behavior/
behavioral intention measures in the aging literature include the likelihood of recommending
evaluation by professionals following memory failure (Erber,
Szuchman, & Rothberg, 1990b), willingness to help (e.g., Weinberger, 1981),
preferences in hiring or other competitive venues (Gaetjens, 1997; Haefner, 1977),
and assessments based on observed interactions (e.g., instructions given to listeners;
Kemper, Vandeputte, Rice, Cheung, & Gubarchuk, 1995; Rubin & Brown,
1975).
Attitudes Toward Younger and Older Adults 245
The competence and attractiveness categories represent important dimensions
of age stereotypes also. Kite and Johnson (1988) found the largest bias against
older adults when competence was assessed and this continues to be a focus
of many studies; this category reflects the belief that competence declines with
age (see also Cuddy & Fiske, 2002). In the aging literature, competence assessments
include perceived intelligence or ability (e.g., Erber, Szuchman, & Rothberg,
1990a), and judgments of memory failure (e.g., Erber, Etheart, & Szuchman, 1992;
Erber, Szuchman, & Etheart, 1993; Matyi & Drevenstedt, 1989). Finally, physical
appearance is an important component of many stereotypic beliefs, particularly
those based on basic category memberships, such as age and gender (see Fiske,
1998, for a review). People perceive, specific to the aging literature, that attractiveness
and physical ability decrease with age (e.g., Deutsch, Zalenski, & Clark,
1986; O’Connell & Rotter, 1979). Wernick and Manaster (1984) found, for example,
that unattractive faces were consistently rated as older than were attractive
faces. Testing these multidimensional components is important because not only
do people hold a variety of beliefs and attitudes about older adults, those beliefs
are sometimes inconsistent. For example, people may believe that older people are
forgetful, but at the same time value their experience and wisdom (e.g., Kite &
Johnson, 1988).
Moderators of Age-Related Attitudes
Descriptors of the target. As discussed earlier, social role theory predicts
that the role-related information provided about the target influences evaluations
(Eagly, 1987; Eagly et al., 2000). In the aging literature, the detail provided about
the target ranges from age only (e.g., 70-year-old) or a young/old label (e.g.,
Carmel, Cwikel, & Galinsky, 1992; Luszcz & Fitzgerald, 1986), to detailed information
such as how they performed in an interview for a job (e.g., Avolio &
Barrett, 1987) or interacted with a therapist (e.g., Matyi & Drevenstedt, 1989).
Another common methodology involves using photographs to provide physical
appearance cues (e.g., Levin, 1988; Wernick & Manaster, 1984).
Because age is a basic social-cognitive category (e.g., Kunda, 1999), when
studies provided only age, we expected participants to rely on their general attitudes
and beliefs about older and younger adults when reporting their evaluations. When
more detail was available, people should have tempered their tendency to rely on
generalities, instead using the individuating information when making evaluations
(e.g., Deaux & Major, 1987; Fiske, Lin, & Neuberg, 1999). We expected agerelated
bias to be greatest when only demographic information about the target
is provided, somewhat smaller when minimal information about the target was
provided, and smallest when extensive information about the target was provided.
Theories suggesting that as information becomes more individuated, evaluations
are based less on social categories and more on the specific detail
246 Kite, Stockdale, Whitley, and Johnson
provided typically assume that this detail reflects positively on the target and is not
stereotype-confirming (e.g., Deaux & Major, 1987; Fiske, Lin, & Neuberg, 1999).
However, in the aging literature, many researchers manipulate the competence or
success of the person being rated so that either positive or negative information is
available to participants (e.g., Banziger & Drevenstedt, 1982; Matyi & Drevenstedt,
1989; Walsh & Connor, 1979). When possible, we considered the effects of
this manipulation.
Gender of person being rated. A limitation of the aging attitude literature is
the widespread use of labels such as elderly or older person that do not specify
whether the person to be rated is a man or a woman. It is highly likely that respondents
in these studies assumed or imagined the gender of the person they were
evaluating anyway. Research shows that people use male as the default category
and therefore assume maleness in the absence of specific information about a person’s
gender (see Matlin, 2004). Kite (1996) demonstrated that such assumptions
are related, also, to other types of information provided. Regardless of age, for example,
employed and older homemaker targets were imagined to be male whereas
younger homemaker targets were thought likely to be female. Such outcomes raise
questions about whether respondents can or will evaluate others without making
inferences about their gender also.
By failing to designate target gender, researchers overlook an important variable.
Women are thought to reach middle and old age (Drevenstedt, 1976; Kogan,
1979b) and the prime of life (Zepelin, Sills, & Heath, 1986) earlier than men.
Deutsch et al. (1986) found that older men were seen as more attractive than older
women, but found no differences in ratings of middle-aged or young women and
men. Hummert et al. (1997) found that women were likely to be stereotyped negatively
at a younger age than were men. Other research, however, has found no
evidence for an age-related double standard (Drevenstedt, 1981; Locke-Connor &
Walsh, 1980). Whether the sexes are viewed differently as they age may depend
on what you ask, with a double standard being more likely for physical appearance
ratings or gender-associated attributes than for competence. Erber et al. (1990a),
for example, found no differences in perceived forgetfulness of male and female
target persons. Canetto and her colleagues (1995) found older men were rated
higher on intellectual competence and autonomy whereas older women were rated
higher on nurturance. Because more researchers now have considered both the
age and the gender of the person being rated, we can consider the aging double
standard and the conditions under which it is or is not likely to emerge.
Respondent age. A number of studies have examined whether older people
are more favorable toward old age than are younger people. Results are mixed,
with some researchers finding this result (e.g., Anantharaman, 1979; Berg &
Sternberg, 1992; Erber, 1989; Guo, Erber, & Szuchman, 1999), others finding no
age differences (e.g., Bailey, 1991; Erber & Rothberg, 1991; Harris, Page, & Begay,
Attitudes Toward Younger and Older Adults 247
1988) or younger respondents being more positive than older respondents (Bell &
Stanfield, 1973; Rothbaum, 1983). Despite these mixed findings, the preponderance
of evidence suggests older people have more positive attitudes toward aging
than do younger people, leading us to expect this result.
Age of target. It has long been noted that attitudes toward the old-old (75
and older) are more negative than attitudes toward the young-old (55–64; e.g.,
Neugarten, 1975). As noted earlier, Hummert (1990) found that targets fitting a
positive subtype of older adults were perceived as younger than targets fitting
a negative subtype of older adults. Similarly, the number of positive stereotypes
associated with older people decreased significantly for photographs of the youngold
to middle-old to old-old (Hummert et al., 1997; Kogan, 1979a). Canetto et al.
(1995) found significant differences between 60- and 75-year-old targets. These
findings suggest that as target age increases, the age-related bias will increase; we
will examine this possibility.
Secondary moderators. There are a number of other factors that might moderate
the expected bias against older individuals. Age-related bias, for example,
depends on choice of experimental design (e.g., between- or within-subjects); as
Kogan (1979a) noted and Kite and Johnson (1988) confirmed, within-subjects
designs produce a greater age-related bias than do between-subjects designs. Publication
year may be important also: As noted previously, recent research has
been more likely to consider complex questions and may be more likely to use
dependent measures with well-established validity (see Kite & Johnson, 1988).
Similarly, studies that use multi-item attitude measures should produce more reliable
findings than studies with fewer items (e.g., Nunnally, 1978). Finally, there
may be differences due to the education, socioeconomic status, and ethnicity of
the sample (Whitley, 2002). We examine these secondary moderators, but do not
make predictions about which, if any, will prove important.
Method
Studies Sampled
To retrieve all the studies that had appeared by April, 2000, we carried out a
computerized literature search of PsycINFO (Psychological Abstracts) and Social
SciSearch. We searched for studies that compared attitudes toward the older adults
with attitudes toward the young by using the key words aged, old, elderly, attitudes,
stereotypes,senior citizen, attributions, and impression formation. In addition, bibliographies
of located studies were checked. We also hand searched all published
issues (up to April 2000) of Educational Gerontology, The Gerontologist, Journal
of Gerontology, and Psychology and Aging. We considered only studies that compared
older (55 years or older) to younger targets. Younger targets were categorized
248 Kite, Stockdale, Whitley, and Johnson
as either young (21–35 years) or middle aged (36–54 years). Only studies in which
the participants were at least 18 years of age and the younger target person was at
least 21 years old were included. Included studies are marked with an asterisk in
the reference section.
Effect Sizes
The effect size calculated was g, representing the standardized difference
between the ratings of younger and older targets. Positive effect sizes indicate
that the attitude toward the older target was more negative and negative effect
sizes indicate that the attitude toward the younger target was more negative; an
effect size of zero indicates exactly no difference between the attitudes expressed
toward older and younger targets. Whenever possible, g was derived directly from
means and standard deviations, or from F or t statistics (e.g., Lipsey & Wilson,
2001; Rosenthal, 1994). Otherwise, techniques such as probit transformations of
dichotomous frequencies were used to estimate the effect sizes. Effect sizes were
computed by two independent raters; a third rater randomly checked computations
for each study to ensure the method employed was appropriate. Disagreements
were resolved by discussion. The resulting effect sizes (ds) were corrected for bias
due to sample size (Hedges, 1982).
Categories of Effect Sizes
Because attitudes toward older adults are multidimensional, we placed effect
sizes into one of five categories: evaluation (e.g., generous, friendly), competence
(e.g., intelligent, good memory), attractiveness (e.g., pretty, wrinkled),
behavior/behavior intentions (e.g., willingness to interact with; make phone call),
and age stereotypes (e.g., old-fashioned, talks about past). To accomplish this,
we first compiled a list of all dependent measures used in the located studies.
Three raters categorized all dependent measures into one of the five categories,
with a 95% agreement rate. Disagreements were resolved by discussion. Our decisions
were guided by theoretical distinctions among the categories, as well as
the decisions of previous researchers. For example, items that appeared on the
evaluation component of the Semantic Differential (Osgood et al., 1957) and the
Aging Semantic Differential (Rosencranz & McNevin, 1969) were categorized as
evaluative. Items categorized as age stereotypes by others (Axelrod & Eisdorfer,
1961; Kogan & Shelton, 1962; Stewart & Ryan, 1985) were similarly categorized
for this analysis. Overall effect sizes were computed separately for each of these
categories by averaging across all items relevant to that category. In the reference
list, the categories for which a study produced effect sizes are marked by AS (Age
Stereotype), AE (Attractiveness-Evaluative), C (Competence), E (Evaluation), or
B (Behavior/Behavioral Intention).
Attitudes Toward Younger and Older Adults 249
Table 1. Summary Statistics for Categories of Dependent Variables
Category of Dependent Variable Number of Studies dz Qw
Age Stereotype 11 .47 11.53∗∗ 118.48∗∗
Attractiveness (Evaluative) 17 .38 16.21∗∗ 187.56∗∗
Competence 75 .33 23.10∗∗ 825.21
Behavior/Behavioral Intention 29 .21 11.34∗∗ 377.34∗∗
Evaluation 100 .24 19.92∗∗ 974.26∗∗
Note. A positive d indicates more negative attitudes toward older adults.
Qw represents within-category homogeneity. Higher values indicate less homogeneity of effect sizes.
p < .01 ∗∗∗p < .001.
Some categories of dependent measures are theoretically important, but were
represented by too few studies to be included (e.g., beliefs about language
performance; Hummert, Garstka, Shaner, & Strahm, 1995). Finally, some categories
of dependent measures fell outside the attitude domain; these included
measures of personal concern about the consequences of being old (e.g., Kiemmack,
1980), evaluations of luck or effort (e.g., Reno, 1979), and judgments about
the age at which various life markers such as middle and old age are reached (Hori,
1994). Dependent measures representing these domains were excluded from our
analysis.
The unit of analysis for our research was the individual study, defined as (a)
the only study reported within an article, (b) a separate study within an article
(e.g., Study One, Study Two), or (c) a separate sample within the same study
(e.g., a replication with a sample from a different population). In many cases, an
individual study assessed more than one category of dependent variable, such as
both competence and evaluation. In such cases, the effect size for each category
was analyzed as part of its category; thus, the total number of effect sizes analyzed
exceeds the total number of studies. Also, many studies used more than one measure
to assess a particular category of dependent variable. In those cases, ds were
computed for each dependent variable within a category and averaged to create
an effect size for that category. Thus, an individual study was presented only once
within a category to ensure independence of data (e.g., Johnson & Eagly, 2000).
Table 1 contains the number of studies in each of the five categories.
Study Characteristics
The following information was coded for each study: (a) publication year, (b)
respondent gender (recorded as the percentage of men in the sample), (c) number
of items in the dependent measure, (d) number of points on the rating scale (if
applicable), and (e) study design (between- or within-subjects). We coded, also,
respondent age as young, middle age, old, or unknown. When actual respondent age
was reported, we categorized those younger than 35 as young, those between the
250 Kite, Stockdale, Whitley, and Johnson
ages of 35 and 54 as middle aged, and those older than 55 as old. Respondents were
categorized, also, as undergraduates, graduate students/professionals, or from a
general population. Target gender was coded as male, female, both, or unspecified;
the both category was used when target gender was varied, but effect sizes could
not be computed separately by that factor.
The information provided about the target was coded as demographics only
(e.g., only age provided), minimal information (e.g., sick or healthy; working
or not working), or extensive information (e.g., detailed description of person,
detailed work history, intake report for therapy). We also coded whether the information
provided was positive, negative, or neutral. The presentation of target
age information varied widely. Some researchers provided only general age categories
(e.g., young, old) and others provided specific ages. Also, the number of
age categories used varied widely, from 2 to 14. To reduce the complexity and to
ensure no one study was over-represented in the analysis of target age, we used
five age categories (21–37, 38–54, 55–70, 71–85, 86 and older) that allowed us to
make relative age comparisons; for example, 55–70 year olds could be compared
to 86 and older targets, even though both categories represented “older” adults.
In developing these cutoffs, we considered the actual age categories used by researchers
and the distinction between young, middle-age, young-old, middle-old,
and old-old targets (e.g., Neugarten, 1975). Also, we used categories with equal
age intervals. When studies provided comparisons for more than two age groups
within a category, we computed effect sizes separately for each comparison and
then averaged the effect sizes within categories. For example, if a study provided
ratings of 30- and 65-year-olds and of 35- and 65-year-olds, ds were averaged so
that the study had only one effect size which represented a 21-37-year-old target
compared to a 55-70-year-old target.
In all cases, coding was completed by two independent raters. Coders achieved
98.6% agreement; disagreements were resolved by discussion with a third rater.
For all analyses, results were collapsed across all categorical variables except the
variable of interest. If a study included data from more than one sample (e.g.,
undergraduates and general population), but separate effect sizes could not be
computed, the study was excluded from the analysis of that moderator variable.
Results
Within each category of dependent variable, stem and leaf plots were computed
to identify outliers. Outliers were found for evaluation (n = 3) and competence
(n = 3); for these categories, analyses were computed with and without outliers.
Only minor differences in the results emerged, so the analyses reported here include
outliers. Occasionally, researchers reported only that effects were not significant
or reported only a p value for significant results; in such cases, the accuracy of
the effect size estimate is questionable (e.g., Johnson & Eagly, 2000); however,
Attitudes Toward Younger and Older Adults 251
excluding these estimates did not materially affect the results, so we report findings
including those studies.
Overall Effect Sizes
Summary statistics for all categories of dependent variables are provided in
Table 1. For all categories, respondents showed a preference for younger rather
than older adults. Younger adults were rated less stereotypically, seen as more
attractive and more competent, and were evaluated more favorably than older
adults; also, behavioral preferences were given to younger adults. All mean effect
sizes were significantly different from zero, as evidenced by the z statistic. In no
case were effect sizes within a category homogeneous, as indicated by Qw, so there
was significant unexplained variance within each category. Therefore moderator
variables were examined to try to account for this additional variance.
Moderator Variable Analyses
We report results only when at least seven studies were available at each
level of categorical moderator variables and at least 15 studies were available for
continuous moderator variables. Because of these criteria, analyses of moderator
variables are limited to the competence, evaluation, and behavior/behavioral intention
categories. Summary statistics for the categorical moderator variables are
shown in Table 2 and those for the continuous moderator variables are shown in
Table 3.
Amount of information about the target person. When any individuating information
was provided about the people being rated, we expected smaller differences
between ratings of older and younger adults. Moreover, we expected differences
to be smallest when more detailed information was provided. As can be seen
in Table 2, regardless of the amount of information presented, older adults were
always perceived as less competent, evaluated less favorably, and treated more negatively
than younger adults. However, when extensive information was presented,
these age differences were smaller than when only target age was provided. When
minimal information was provided, differences in perceived competence were
larger than when no information or extensive information was presented. For the
evaluation dependent measure, effect sizes in the minimal information category fell
between the no information and extensive information categories. For the behavior/
behavioral intention measure, the effect sizes in the extensive and minimal information
categories were similar and both were smaller than the no information
category.
252 Kite, Stockdale, Whitley, and Johnson
Table 2. Analyses of Moderator Variables for Competence, Evaluation, and Behavior/Behavioral
Intention Dependent Measures
Behavior/Behavioral
Competence Evaluation Intention Moderator
Variable Condition d QB d QB d QB
Information None .39a 98.26∗ .30a 62.05∗ .34a 10.60∗
k = 23 k = 51 k = 7
Minimal .46b .15b .19b
k = 17 k = 25 k = 7
Extensive .11c .06c .18b
k = 36 k = 24 k = 15
Valence of Positive .16a 31.88∗ .04a 21.46∗ .55a 243.97∗∗
Information k = 21 k = 20 k = 9
Neutral .21a .10a –.25b
k = 21 k = 23 k = 7
Negative .38b .27b .19c
k = 25 k = 18 k = 11
Respondent Younger .34a 19.26∗ .21a 34.86∗ .32a 339.74∗∗
Age k = 59 k = 78 k = 15
Middle Age .50b .47b –
k = 11 k = 11
Older .26c .36c .14b
k = 10 k = 14 k = 11
Target Male .44a 146.14 .30a 60.44∗ .08a 28.79∗∗
Gender k = 23 k = 40 k = 10
Female .16b .36b .28b
k = 20 k = 24 k = 11
Unspecified .45a .25c .37c
k = 21 k = 34 k = 11
Both .03c .06d –
k = 14 k = 17
Design Between .21 79.98∗ .10 145.91∗ .02a 168.32∗∗
k = 57 k = 56 k = 17
Within .47 .39 .51b
k = 18 k = 44 k = 12
Population Undergraduates .37a 3.40 .23a < 1 .25a 157.04∗∗∗
k = 47 k = 72 k = 12
Graduate .31a .22a .51b
Students/ k = 8 k = 8 k = 9
Professionals
General .34a .20a –
Population k = 13 k = 12
Note. k = number of studies. Different subscripts indicate conditions within dependent measures
that differ at the .05 level of significance. QB represents between-category homogeneity. Significant
values indicate effect sizes vary by category.
∗p < .05; ∗∗p < .01; ∗∗∗p < .001.
Valence of information about the target person. When minimal or extensive
information was provided about the target, we coded its valence as positive,
negative, or neutral. For both the competence and the evaluation dependent measures,
perceived differences between younger and older targets were largest when
negative, rather than positive or neutral, information was provided; ds in these
Attitudes Toward Younger and Older Adults 253
Table 3. Standardized Regression Coefficients for Continuous Moderator Variables
Behavior/Behavioral
Competence Evaluation Intention
k B k Bk B
Target age differences 69 0.0005 83 –0.0055∗∗∗ 29 –0.0113∗∗∗
Number of items on scale 72 0.0043 94 0.0034 25 0.0006
Number of scale points 63 –0.0028 88 0.0015∗ 21 –0.0006
Percent male participants 63 0.0039∗∗∗ 82 0.0003 27 –0.0022∗∗∗
Date of publication 75 –0.0179∗∗∗ 100 –0.0019 27 0.0042
Note. k = number of studies. ∗p <.05. ∗∗∗p <.001.
latter two categories did not significantly differ. Age-related differences in behavior/behavioral
intentions were largest when the provided information was positive,
followed by when the information provided was negative. When neutral information
was presented, older individuals were treated more favorably than younger
individuals.
Respondent age. Middle-aged respondents showed a greater preference for
younger adults, both in assessments of their competence and in their evaluations
of those groups, compared to older and younger respondents. Also, older
respondents believed younger targets were more competent than older targets, but
this preference was the smallest of any age group; younger respondents’ competence
ratings fell between those of the other age groups. Older respondents’
evaluations, however, showed larger perceived age differences than did younger
respondents’ assessments. For behaviors/behavioral intentions, only younger and
older targets could be compared; there were larger age-related differences for
younger targets than for older targets.
Target gender. A double standard of aging suggests that perceived age differences
will be larger when women, rather than men, are rated. This pattern emerged
for evaluations and behaviors/behavioral intentions. However, raters saw greater
differences in the competence of older and younger men than in the competence
of older and younger women.
Often, when the gender of the target is unspecified, raters assume the person
being rated is male (Kite, 1996). This suggests that ratings in the target unspecified
category should be similar to those for the male target category. For the competence
dependent measure these two categories did not differ. For the evaluation
category, however, perceived age differences were smaller when target gender was
unspecified than when either male or female targets were rated. For the behavior/
behavioral intention dependent measure, perceived age differences were largest
in the unspecified category. Where both women and men were rated, but separate
254 Kite, Stockdale, Whitley, and Johnson
effect sizes for target gender could not be computed, older and younger targets
were rated similarly in both the evaluation and the competence categories.
Study characteristics. Between subjects designs resulted in smaller perceived
age differences in competence, smaller differences in the evaluations of younger
and older targets, and smaller differences in behaviors/behavioral intentions (see
Table 2). The number of items was not related to d for any of the dependent
variables (see Table 3). In addition, the number of scale points was not related to
d for competence or behavior/behavioral intentions. On the evaluation measure, d
increased by 0.002 units for each additional scale point.
Research population. Whether the respondents were drawn from a sample of
undergraduates, graduate students/professionals, or the general population made
no difference in the size of the perceived age differences on the competence or the
evaluation dependent measures. Graduate students/professionals did show a greater
preference for older adults than did undergraduates on the behavior/behavioral
intention measure.
Difference in ages of targets. The difference in ages between the older target
and the comparison target was not related to the magnitude of the effect sizes for
competence ratings (see Table 3). However, d became smaller for evaluations and
behavior/behavioral intentions as age differences increased, with d decreasing by
about 0.01 units (e.g., from 0.31 to 0.30) for each year the age difference increased.
Gender of research participant. Gender of research participant was not related
to d for evaluations, but was for competence ratings and behavior/behavioral
intentions. However, the pattern of these gender differences was mixed. For competence
ratings, d increased by 0.004 units for each 1% increase in men in the
sample. For behavior/behavioral intentions, d decreased by 0.002 units for each
1% increase in men in the sample.
Date of publication. Date of publication was not related to d for evaluations
or behavior/behavioral intentions. However, for competence ratings, d decreased
0.02 units for each year the publication date became more recent.
Discussion
Does ageism exist? When a broad view is taken, the answer is yes. Across
all categories of dependent variables, we found a bias against older adults. Yet
this bias was largest when stereotypic beliefs and perceptions of attractiveness
were assessed; the bias was reduced when behaviors/behavioral intentions or affective
evaluations were measured. Competence ratings fell roughly between these
Attitudes Toward Younger and Older Adults 255
two extremes. Our results, then, confirm what has often been stated: Perceptions
of older adults are complex and multidimensional (Crockett & Hummert, 1987;
Hummert, 1999; Lutsky, 1980). People do seem to hold clear stereotypic beliefs
that differentiate older and younger adults (Cuddy & Fiske, 2002), including beliefs
that age reduces attractiveness and, to a lesser extent in our data, competence.
We explored these complexities in more detail by examining a number of moderator
variables. As with any meta-analysis, however, we were limited by the available
literature. One outcome, in this case, was that moderators of the age stereotype or
the attractiveness categories could not be examined because too few studies exist.
Moderator analyses, then, were limited to the competence, behavior/behavioral
intention and evaluation categories.
Role Information
We proposed that contextual information would influence people’s perceptions
of older adults (Eagly, 1987; Eagly et al., 2000; Kite & Johnson, 1988) and
this was borne out in our results. Across the three categories of dependent variables
we considered, effect sizes were reduced significantly when judgments were
based on extensive, rather than minimal information. When participants knew, for
example, about the history of the person they evaluated, they perceived fewer age
differences. Providing even minimal additional information, such as employment
or health status, reduced, also, the effect sizes in the evaluation and behavior/
behavioral intention categories. The only exception was that, when judgments of
competence were assessed, providing minimal information actually resulted in a
larger bias against older adults. The reason for this discrepancy remains unclear;
a careful examination of the 17 studies in this category showed wide variability
in other factors affecting participants’ responses, such as valence of information
or gender of person to be rated. We suspect it is a combination of these factors
that produced the unexpected result, rather than any theoretically interesting differences
among the studies. Overall, our analysis of context effects supports our
contention that it is not growing old, per se, that produces negative perceptions,
but rather the roles that older adults occupy. Consistent with social role theory
(e.g., Eagly, 1987; Eagly et al., 2000), when contextual information was made
explicit, differences in evaluations of younger and older adults were significantly
reduced.
As Hummert and her colleagues have demonstrated, those roles can be positive
or negative (Hummert, 1993; Hummert et al., 1995; Hummert et al., 1997). Our
results suggest, also, that the valence of the information provided influences judgments.
When negative information was presented, perceived age differences were
larger in both the competence and evaluation categories, compared with when neutral
or positive information was presented. Positive information, however, produced
a larger age-related bias when behaviors/behavioral intentions were assessed. This
256 Kite, Stockdale, Whitley, and Johnson
may have been due to the fact that the three largest effects sizes, of the seven in
that group, emerged in studies of employment discrimination (Bendick, Brown,
& Wall, 1999; Bendick, Jackson, & Romero, 1996); a fourth positive effect size
was in a study of skill assessment (Walsh & Connor, 1979). These results may
reflect the actual workplace discrimination that older adults face (e.g., Finkelstein,
Burke, & Raju, 1995; Gordon et al., 2000). Overall, however, these results suggest
that negative perceptions of older adults can be reduced when evaluators see older
and younger people as behaving similarly, especially when that behavior is in a
positive context. Once again, providing additional information reduces the impact
age information alone has on perceptions.
Age of Rater
As we predicted, older adults saw fewer differences between the young and
old, and younger adults saw greater differences. The exception was for evaluative
judgments; for that category of dependent variables, younger adults saw smaller
age differences than older adults did. For younger adults, the competence and
behavior/behavioral intention results are consistent with Social Identity Theory
(SIT; Tajfel & Turner, 1979; Turner & Oakes, 1989), which proposes that people
strive to maintain positive images of their ingroups. When they are evaluating an
older person, younger adults are judging someone who is not a member of our
own age group; drawing larger distinctions between older and younger adults is a
way to maintain a positive social identity. More puzzling is why older evaluators
did not show a bias in favor of their own group (i.e., none of the mean effect sizes
were positive). One possibility is that, because they themselves were once young,
and thus a member of the other group, devaluing that group does not produce
a positive image. Older adults may, instead, use other options for maintaining a
positive self-image, such as social mobility, social creativity, or social competition
(see Harwood, Giles, & Ryan, 1995; Kite & Wagner, 2002 for discussions).
Interestingly, middle-aged respondents saw the largest age-related bias in the
two categories for which this comparison could be made, competence and evaluation.
As Kite and Wagner (2002) argued, this may be because middle-aged adults
see old age as right over the horizon, but still are not quite ready to accept its coming
(Montepare & Lachman, 1989). Accordingly, they may have a greater need
than younger people to maintain their positive self-image by devaluing older adults.
Only 11 studies employed a middle age sample, so any explanation is tentative. Yet
the possibilities, and the general questions our results raise about respondent age
differences in attitudes toward older adults, deserve attention in future research.
It should be noted that a large literature has examined rater age without also
exploring target age differences; those studies are, by definition, excluded from
this meta-analysis. As Kite and Wagner (2002) noted, a narrative review of this
literature is insufficient to draw conclusions. The field would benefit greatly from
Attitudes Toward Younger and Older Adults 257
a meta-analysis of this expanded literature which examined both the overall pattern
of effects and potential moderators of any uncovered respondent age differences.
SIT offers an obvious theoretical grounding for such an endeavor (see Harwood
et al., 1995 for a discussion of SIT and ageism).
Is There an Aging Double Standard?
The studies we reviewed in the introduction suggested that the aging double
standard might be elusive, or at least more complex than it appears at first glance,
and our results bear this out. When the assessments concerned competence, it was
the aging male who was viewed more negatively; age differences were comparatively
small when women were rated. Competence is a central component of the
male stereotype (e.g., Deaux & LaFrance, 1988; Eagly, 1987) and men are believed
to lose agency with age (Kite, 1996). It is not surprising, then, that the double standard
appears to be reversed when this dimension is assessed. In contrast, when
behaviors and behavioral intentions are assessed, the double standard does favor
men, with larger age differences emerging for female targets. Age differences
were also significantly larger for women then men when evaluative judgments
were measured, but the magnitude of this difference is not compelling (.30 for
male targets versus .36 for female targets).
Based on the findings that women reach middle and old age (Drevenstedt,
1976; Kogan, 1979b) and the prime of life (Zepelin et al., 1986) at a younger age
then men, it is reasonable to expect the double standard of aging is most likely
to operate when attractiveness is assessed. Unfortunately, too few studies were
available to test this hypothesis. A critical point is that target gender does influence
perceptions of older adults and researchers should, at minimum, specify this
variable even if they choose not to manipulate it, especially because respondents
make assumptions about target gender based on stereotypes and/or experimental
manipulations (e.g., Kite, 1996; Matlin, 2004). And, of course, there are theoretical
reasons, grounded in both the gender and the aging literature, to pursue this
question.
Study Characteristics
As Kite and Johnson (1988) showed, and our results confirm, within subjects
designs produced significantly larger perceived age differences, in some cases five
times as large as those produced by between-subjects designs. Other methodological
decisions, such as the properties of the rating scale, had negligible effects. Also,
different populations of raters viewed the age-related comparisons similarly. We
had hoped to consider cross-cultural differences in perceptions of older adults and
also whether ethnic groups within the United States viewed aging differently. Unfortunately,
too few studies have examined aging either cross-culturally or within
258 Kite, Stockdale, Whitley, and Johnson
subcultures of the United States and Canada. This is without a doubt a weakness
of this literature and one that deserves attention.
We did examine whether larger target age gaps (e.g., a 50-year age gap versus
a 15-year age gap) would produce larger age-related differences. Unfortunately,
analyses within the three categories showed either no target age effects or showed
smaller age differences as the target age differences increased, which is not the
pattern we predicted. Because our sample of studies represented such a mixture
of procedures for varying target age, and because other factors also often varied
across studies, we doubt we have provided the definitive answer. Many studies,
for example, used only global labels such as young and old. Those that specified
several ages were likely to use within-subjects designs, alerting participants to the
study’s focus. As we noted in the introduction, the declines associated with older
age groups are not likely to go unnoticed. What is needed is theoretically driven
research that can examine this complex issue in the context of specific predictions.
Gender of research participant produced a similarly confusing pattern of results,
although there is little reason to expect either gender to be more ageist.
Consistent with our early discussion of the importance of competence to the male
stereotype, it is interesting that having more male respondents did increase the
perceived age difference on that dimension. Finally, only for competence ratings
did more recent studies show a smaller age bias. Kite and Johnson (1988) found
somewhat stronger evidence that the age bias decreased by publication year, but
given that the vast majority of the studies examined in the present work were
published since then, it is perhaps not surprising that this effect has diminished.
Overall, as with any set of studies, methodological decisions can alter outcomes,
but these decisions are typically of less importance than theoretically chosen variables
(Whitley, 2002).
Summary and Conclusions
Perhaps the most heartening aspect of this updated meta-analysis is the explosion
of research that has taken place since our earlier meta-analysis. And, importantly,
this research has improved in quality and quantity. There is little doubt that
the research questions are more sophisticated and the problems being evaluated
more meaningful. When the questions addressed by Kite and Johnson (1988) were
reexamined here, the outcomes were similar. But certainly we can have more confidence
in these results because they are based on a larger, richer data set. Moreover,
we were able to pose new questions and suggest directions for future research. And
some questions, such as whether older workers experience discrimination, were
not reexamined because others have conducted meta-analyses specifically on that
topic (Finkelstein et al., 1995; Gordon et al., 2000).
It goes without saying that the results of this meta-analysis are limited by the
sample of studies that have examined this issue to date. Moreover, it seems obvious
Attitudes Toward Younger and Older Adults 259
that understanding ageism is not limited to the theoretical ideas or methodologies
employed in the past. As Nelson (2002) states, “age prejudice is one of the most
condoned, institutionalized forms of prejudice in the world—especially in the
United States—today” (p. ix). Gerontologists in all fields are taking a closer look
and, in doing so, are unmasking these hidden beliefs. Our review provides an upto-date
summary of this progress and suggests fruitful avenues for continuing the
work. Perhaps it is time to get aside the question of whether ageism exists and
continue to explore when and where the consequences are most severe.
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Note. References marked with an asterisk indicate studies included in the metaanalysis.
AS = Age Stereotype, AE = Attractiveness-Evaluative, C = Competence, E =
Evaluation), and B = Behavior/Behavioral Intention.
MARY E. KITE is Associate Dean of the Graduate School and Professor of Psychological
Science at Ball State University. She has published many articles and
book chapters about her research on stereotyping and prejudice. Kite is particularly
interested in gender-based prejudice and how those beliefs influence other
stereotypic judgments.
GARY STOCKDALE received a Master’s of Arts in clinical psychology from
Ball State University in 2000 and the Ball State University Alumni Association
Distinguished Master’s Thesis Award. He is now a doctoral student in quantitative
psychology at the University of California, Davis. His interests include modeling
human behavior and its determinants using latent growth curve analysis.
BERNARD E. WHITLEY, JR., is Professor of Psychological Science at Ball State
University, Muncie Indiana. His research centers on the role of individual difference
variables in prejudice. He is author, coauthor, or coeditor of four books,
including Principles of Research in Behavioral Science (McGraw-Hill, 2002).
BLAIR T. JOHNSON is Professor of Psychology at the University of Connecticut.
His research covers aspects of social influence and attitude change, the prediction
of behaviors from attitudes and other variables, and the social psychology of health
promotion including HIV prevention. Johnson is also the author of numerous
journal articles, chapters, notes, and reviews in his research specialties.

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