The Multidimensional Nature of Ageism: Construct Validity and Group Differences

This article was downloaded by: [Illinois Wesleyan University]On: 06 October 2014, At: 13:58Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH,UK

The Journal of SocialPsychologyPublication details, including instructions forauthors and subscription information:http://www.tandfonline.com/loi/vsoc20

The Multidimensional Nature ofAgeism: Construct Validity andGroup DifferencesDeborah E. Rupp a , Stephen J. Vodanovich b &Marcus Credé ca University of Illinois Department of PsychologyUrbana-Champaignb University of West Florida Department ofPsychology Pensacola, FLc University of Illinois Department of PsychologyUrbana-ChampaignPublished online: 07 Aug 2010.

To cite this article: Deborah E. Rupp , Stephen J. Vodanovich & Marcus Credé (2005)The Multidimensional Nature of Ageism: Construct Validity and Group Differences, TheJournal of Social Psychology, 145:3, 335-362, DOI: 10.3200/SOCP.145.3.335-362

To link to this article: http://dx.doi.org/10.3200/SOCP.145.3.335-362

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all theinformation (the “Content”) contained in the publications on our platform.However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness,or suitability for any purpose of the Content. Any opinions and viewsexpressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor & Francis. The accuracy of theContent should not be relied upon and should be independently verified withprimary sources of information. Taylor and Francis shall not be liable for any

http://www.tandfonline.com/loi/vsoc20

http://www.tandfonline.com/action/showCitFormats?doi=10.3200/SOCP.145.3.335-362

http://dx.doi.org/10.3200/SOCP.145.3.335-362

losses, actions, claims, proceedings, demands, costs, expenses, damages,and other liabilities whatsoever or howsoever caused arising directly orindirectly in connection with, in relation to or arising out of the use of theContent.

This article may be used for research, teaching, and private study purposes.Any substantial or systematic reproduction, redistribution, reselling, loan,sub-licensing, systematic supply, or distribution in any form to anyone isexpressly forbidden. Terms & Conditions of access and use can be found athttp://www.tandfonline.com/page/terms-and-conditions

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

http://www.tandfonline.com/page/terms-and-conditions

335

The Journal of Social Psychology, 2005, 145(3), 335–362

The Multidimensional Nature of Ageism:Construct Validity and Group Differences

DEBORAH E. RUPPDepartment of Psychology and Institute of Labor and Industrial Relations

University of Illinois at Urbana-Champaign

STEPHEN J. VODANOVICHDepartment of Psychology

University of West Florida, Pensacola, FL

MARCUS CREDÉDepartment of Psychology

University of Illinois at Urbana-Champaign

ABSTRACT. The authors investigated the factor structure and construct validity of theFraboni Scale of Ageism (FSA; M. Fraboni, R. Saltstone, & S. Hughes, 1990) and the ageand gender differences in ageism scores. Confirmatory factor analyses supported the mul-tidimensional nature of FSA scores and generally corroborated the initial factor structurereported by M. Fraboni, with some notable exceptions. Essentially, the present findingswere aligned with theoretical models of ageism that emphasize both cognitive facets andaffective facets. That is, on the basis of their factor analytic findings, the authors redefinedFraboni’s original factors of Antilocution, Avoidance, and Discrimination as Stereotypes,Separation, and Affective Attitudes, respectively, because of the clustering of items with-in factors. The revised 3-factor structure accounted for 36.4% of the variance in FSAscores. FSA factor scores significantly related to other scores from other measures of age-related attitudes, with higher correlations among factors that were similar in terms of theircognitive nature versus their affective nature. Finally, younger individuals and men hadsignificantly higher ageism scores on the FSA than older individuals and women. Theauthors discussed the importance of adequately assessing ageism, with particular empha-sis devoted to the understanding of age bias.

Key words: age bias, ageism, group differences, older workers

THE TERM AGEISM was first used to describe prejudice and discriminationdirected toward older persons by Butler (1969). Ageism has been referred to asthe third great ism of our society (following racism and sexism; Butler, 1995).Palmore (1999) explained that ageism involves both prejudice and discrimina-tion, both stereotypes and attitudes, and therefore both cognitive and affective

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

processes. Research has indicated that ageism is quite prevalent in today’s soci-ety (Palmore, 2001), possibly even more prevalent than sexism and racism (Bana-ji, 1999), although it is typically much more difficult to detect (Levy & Banaji,2002).

Research has shown ageism to be a strong antecedent of age bias (Rupp,Vodanovich, & Credé, in press). Two recent meta-analytic investigations onageism have found that older individuals are generally perceived less favorablythan those who are younger (Gordon & Arvey, 2004; Kite & Stockdale, 2004).1

These facts, coupled with the rise of both the number of older people in society(Williams & Nussbaum, 2001), as well as the number of age discriminationclaims being filed (McCann & Giles, 2002), suggest that more research is need-ed that explores the construct of ageism and its measurement.

The persistence of age-related stereotypes is curious given the existence ofconsiderable evidence that older individuals are generally as capable as theiryounger counterparts. Workplace researchers have found chronological age notto be a valid (negative) predictor of performance for many tasks (Cleveland &Landy, 1983; Laczko & Philipson, 1991; Liden, Stilwell, & Ferris, 1996; Seg-rave, 2001; Wilkening, 2002). A meta-analysis by Waldman and Avolio (1986)detected significant positive correlations between age and productivity for both“professional” and “nonprofessional” jobs. On the other hand, negative relation-ships (suggestive of age bias) existed for supervisory ratings of performance, par-ticularly for those in nonprofessional positions.

Research on the construct of ageism also appears to be warranted given thepotential negative impact of ageism on both individuals and organizations. Forindividuals, ageism can lead to ageist discourse, expressed ageist attitudes, anddiscriminatory practices based on age (McCann & Giles, 2002), which have beenshown to cause lowered self-efficacy, decreased performance, and cardiovascu-lar stress (Levy, Ashman, & Dror, 2000; Levy, Hausdorff, Hencke, & Wei, 2000).For organizations, ageism can lead to costly age discrimination suits (McCann &Giles). Between 1994 and 2000, the median award in U.S. age discrimination law-suits was $268,926 (Employment Practice Liability, 2001), and recent settlements(e.g., Westinghouse, Lennox, Continental Airlines, First Union) have ranged from$6.2 million to $58.8 million (McCann & Giles). This rise in age discriminationis evident in both U.S. organizations and those of other nations (Bennington,2001; Chiu, Chan, Snape, & Redman, 2001; Ho, Wei, & Voon, 2000; McMullin& Marshall, 2001; Taylor & Walker, 1997; van den Heuvel, 1999).

336 The Journal of Social Psychology

We presented portions of this paper at the 18th annual meeting of the Society for Indus-trial and Organizational Psychology, April 2003, Orlando, FL.

We thank Silke Holub, Seth Spain, Koren Aragaki, and Demetria Gallagher for theirhelp with various elements of the project.

Address correspondence to Deborah E. Rupp, Department of Psychology and Insti-tute of Labor and Industrial Relations, University of Illinois at Urbana-Champaign, 603East Daniel Street, Champaign, IL 61820; [email protected] (e-mail).

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

Because the aforementioned figures are larger than those in cases involvingsex and race discrimination, there seems to be an increasing important need togain a better understanding of ageism and its measurement (Kite & Wagner, 2002;Levy et al., 2000). In the words of E. S. Cohen (2001, p. 576), “ageism has movedfrom the arena of morality and moral obligation to the arena of legal obligation.”However, despite this evidence, few researchers have investigated ageism, itsmeasurement, its structure, and both individual and group differences in the con-struct of ageism.

The Construct of Ageism, its Structure, and its Measurement

Early measures of age-related attitudes were developed to assess mostly uni-dimensional constructs involving commonly held opinions about older people.For example, Tuckman and Lorge (1953) developed the Old People Question-naire, which assessed the extent to which individuals possess misconceptions orstereotypes about older persons. The measure consisted of 137 items classifiedinto 13 evaluative categories (e.g., conservativeness). As a follow-up to this mea-sure, Golde and Kogan (1959) developed a 20-item, qualitative sentence-com-pletion measure for which participants formed sentences about “old people” and“people in general.” The scale was intended to measure general attitudes aboutolder individuals. Kogan (1961) then created a quantitative version of the mea-sure, termed the Attitudes Toward Old People Scale (OP), which required indi-viduals to rate such statements.

The Facts on Aging Quiz (Palmore, 1977) comprises 25 true–false items thatmeasure participants’ actual level of knowledge regarding the aging process.Although not a direct measure of ageism, this scale has been useful for researchon overall perceptions of the aged in that it measures participants’ actual level ofknowledge regarding the aging process.

The Aging Semantic Differential (ASD; Rosencranz & McNevin, 1969) hasbeen primarily used in gerontological research. As the first multi-dimensionalmeasure of age-related attitudes, this scale consists of 32 bipolar adjective pairson which participants rate different age groups. The scale was designed to mea-sure attitudes about older persons’ level of competence, autonomy, and accept-ability. However, a confirmatory factor analysis of the scale (Intrieri, von Eye, &Kelly, 1995) revealed that a four-factor model measuring instrumentality, auton-omy, acceptability, and integrity was superior to the original three-factor solution.

The Fraboni Scale of Ageism

Fraboni, Saltstone, and Hughes (1990) argued that the earlier ageism scaleswere limited to assessing only the cognitive components of ageism (only oneaspect of ageism as defined by Butler, 1980). Therefore, the Fraboni Scale ofAgeism (FSA) was developed to measure antagonistic, discriminatory attitudes

Rupp, Vodanovich, & Credé 337

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

and the tendency toward avoidance, to represent a more complete measure ofageism. In the present study, Allport’s (1958) levels of prejudice were used toguide the writing of the items. On the basis of Allport’s levels and Butler’s defi-nition of ageism, three factors were proposed: Antilocution (antagonism andantipathy fuelled by misconceptions, misinformation, or myths about older per-sons), Avoidance (withdrawal from social contact with older persons), and Dis-crimination (discriminatory opinions regarding the political rights, segregation,and activities of older persons).

Although the FSA has demonstrated potential as a well-balanced measure ofageism with which investigators can study age bias, research that validates thepsychometric qualities of the FSA has been sparse. In the construction of theFSA, Fraboni et al. (1990) used data from 100 high school students to pilot testtheir measure. Subsequently, those authors conducted an exploratory principle-components analysis on a sample of 230 Canadian college students and workers(averaging 66% female, mean age = 31.2 years, mean education level = 14.2years) to select their final items. Finally, 100 participants from their original sam-ple were reused to conduct an exploratory factor analysis on their final 29 items,which provided preliminary evidence for their proposed factor structure. Becauseearly results on the FSA suggested its potential as a promising and more com-plete measure of ageism, in the present study we sought to further explore its reli-ability and factor structure.

In addition, another objective was to investigate the construct validity of FSAsubscale scores. Following the nomological net approach to construct validity(Cronbach & Meehl, 1955), we proposed that the cognitively focused FSA fac-tor Discrimination would have a stronger relationship with scores on some of thepreviously mentioned age-related attitude and belief measures than would theaffectively oriented FSA factors (Antilocution and Avoidance).

Hypothesis 1: FSA scores obtained from a new, non-Canadian, adult sample willshow adequate internal consistency reliability and will support the factor structureproposed by Fraboni et al. (1990), and cognitively focused FSA subscales will bemore strongly related to past measures of age-related attitudes than will the moreaffectively or behaviorally toned subscales (providing preliminary construct validityevidence).

Group Differences in Ageism

Lastly, in the present study we sought to explore group differences in ageism.Specifically, we tested for age and gender effects in ageism scores.

Age differences. Past empirical research has found that younger people are moreageist than older people. That is, young individuals generally possess more neg-ative attitudes toward the older person than do their older counterparts (Bell &Stanfield, 1973a, 1973b; Kogan, 1961; Kogan & Shelton, 1962). Organizational


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

research has found a similar age effect on attitudes about the aged (Hassell &Perrewe, 1995) as well as an age effect regarding the severity of actions takenagainst older workers for performance errors (with younger workers makingharsher recommendations; Erber, Szuchman, & Rothberg, 1990; Finkelstein,Burke, & Raju, 1995; Rupp et al., in press). In addition, Kalavar (2001) found asignificant, negative correlation (−.19) between age scores and ageism scores. Incontrast, other researchers have indicated that older people are more biasedtoward their own age group than are younger people (Hellbusch, Corbin, Thorson,& Stacy, 1994). Still other researchers have failed to detect an age effect of anykind (Berg & Sternberg, 1992). Finally, meta-analytic studies have indicated thatyounger raters possess more ageist attitudes than do older raters (Gordon &Arvey, 2004; Kite & Stockdale, 2004). However, the findings of Kite andStockdale suggest that this relationship may not be linear. That is, middle-agedparticipants (on average) were found to have the highest ageism scores.

Given these contradictory findings, in the present study we sought to inves-tigate the effect of chronological age on ageism scores using the Fraboni Scaleof Ageism, which represents the most balanced measure of ageism to date. Basedon the research on Social Identity Theory (SIT; Tajfel & Turner, 1979), we pre-dicted that younger individuals would be more ageist than would older individu-als. SIT indicates that individuals are motivated to perceive their own group inmore positive terms relative to out-groups. Indeed, several researchers have usedthe basic tenets of SIT as a possible explanation for age effects on ageism scores(e.g., Cuddy & Fiske, 2002; Kite & Wagner, 2002; McCann & Giles, 2002).

Hypothesis 2: A main effect for participant age will exist for ageism scores such thatyounger participants will score higher in ageism than will older participants.

Gender differences. Kogan and Shelton (1962) have discussed the importance ofconsidering gender differences in ageism. Although their main finding was thatyounger participants had more negative beliefs about older people, Theseauthors also reported that significant age differences were related to the genderof the participant. That is, age differences on two items were found for male par-ticipants only, and age differences on three other items were found for femaleparticipants only.

Some research has found women to be less ageist than men (Fraboni et al.,1990; Kalavar, 2001). For instance, using a primarily female (66%), Caucasian(93%), and young (M = 20.2 years, SD = 4.9 years) sample of university stu-dents (N = 200), Kalavar found evidence that male participants (M = 70.6, SD= 13.3) possessed greater ageism scores on the FSA than did their female coun-terparts (M = 62.9, SD = 14.1). This finding is consistent with that of Fraboniet al., who reported that men (M = 61.0, SD = 11.6) had significantly greaterageism scores on the FSA than did women (M = 56.4, SD = 11.8). Finally, Kiteand Stockdale (2004) suggested that men generally give lower ratings to older


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

individuals on performance dimensions labeled as “competence” and “behav-ior/behavioral intentions” than do women. However, such gender differenceswere not consistently found across the studies that were examined. Although theevidence supporting a gender effect on ageism scores is somewhat inconclusive,we predicted that women would display less systematic ageism than would men.Such a finding would be congruent with the work of Deaux (1985) that foundwomen to be more warm, caring, and empathic, whereas men were more com-petitive and critical.

Hypothesis 3: A main effect for participant gender will exist for ageism scores suchthat male participants will score higher in ageism than will female participants.

Method

Participants

Two samples (Sample A, N = 353; Sample B, N = 201) of undergraduatestudents at a public university in the southeastern United States were used forthis study. Sample A was 70.5% female, and mean and median ages were 22.6years and 20.0 years, respectively. Ages of the participants ranged from 17 yearsto 58 years with 37.3% of the sample under the age of 20 years, 49.0% betweenthe ages of 20 years and 29 years, 7.55% between the ages of 30 years and 39years, and 6.15% over 40 years. The racial makeup of Sample A was 18.07%non-Caucasian.

Sample B was 71.5% female, and mean and median ages were 22.15 yearsand 20.0 years, respectively. Ages of the participants ranged from 17 years to 54years, with 38.0% of the sample under 20 years, 54% of the sample between 20years and 29 years, 4.75% of the sample between 30 years and 39 years, and3.25 % of the sample over 40 years. Sixteen percent of Sample B belonged to aracial or ethnic minority.

The students volunteered to participate during class time and received extracredit for their participation. They signed a consent form assuring them thattheir participation was voluntary, that they could withdraw from participationat any time, and that their responses would be kept confidential. At the end ofthe study, participants received both oral and written debriefings explaining thepurpose of the study and the broad research questions and providing them withreferences to pertinent papers that they could read if interested in the topic.They were also asked not to share any aspects of the present study or their par-ticipation in it with anyone until the end of the semester so as not to bias futurepotential participants.

Sample A completed the FSA (Fraboni et al., 1990), the ASD (Rosencranz& McNevin, 1969), the OP (Kogan, 1961), and a short measure of demograph-ics (i.e., age, gender, race). Sample B completed the FSA only.


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

Instrumentation

The FSA (Fraboni et al., 1990) consists of 29 items designed to assess bothcognitive and affective components of ageism. Participants responded to the itemsusing a Likert-type scale ranging from 1 (strongly disagree) to 4 (strongly agree).Fraboni et al.’s original study investigating the psychometric properties of the FSAconsisted of a total of 231 participants. Of these, 109 were university students(76% women, 24% men). The other participants (N = 122; 56% women, 44%men) were participants from disparate occupations (e.g., social workers, custodi-ans, mechanics, sales, education). As mentioned earlier, the mean age of the entiresample was reported to be 31.2 years with an average education of 14.2 years.

Fraboni et al. (1990) found FSA scores to have adequate internal-consisten-cy reliability with a Cronbach’s alpha coefficient of .86. The FSA’s items weredesigned to measure three of Allport’s (1958) five levels of prejudice as relatedto ageism: Antilocution (e.g., “Many old people just live in the past”), Avoidance(e.g., “I don’t like it when old people try to make conversation with me”), andDiscrimination (e.g., “Most old people should not be trusted to take care ofinfants”). A preliminary exploratory principle-components analysis supportedthese factors, accounting for 23.3%, 7.2%, and 7.0% of the variance, respective-ly. Cronbach’s coefficient alpha reliabilities of the Antilocution, Avoidance, andDiscrimination subscales were reported as .76, .77, and .65, respectively. In thepresent study, the alpha reliability estimates of these subscales were .75, .61, and.77, respectively. Fraboni et al. also presented evidence regarding the constructvalidity of the FSA. That is, they found scores on the FSA to possess significant,negative correlations with the Facts on Aging Quiz (−.28) and the Acceptance ofOthers Scale (−.22).

The ASD (Rosencranz & McNevin, 1969) was constructed to measure thevalences of stereotypic attitudes about age. The ASD consists of 32 bipolar adjec-tive scales on which participants judge an indicated social object on one of sevenresponse levels, with lower scores indicating a more positive attitude toward theobject. In the original construction of the ASD, the social objects were personsof all ages, a man between the ages of 20 years and 30 years, a man between theages of 40 years and 55 years, and a man between the ages of 70 years and 85years. An initial factor analysis of the ASD indicated three major dimensions:Instrumental–Ineffective, Autonomous–Dependent, and Personal Acceptability–Personal Unacceptability.

Subsequent investigators used a generalized social object, such as a nonspe-cific old person (Underwood, Eklund, & Whisler, 1985). Further examination ofthe ASD factor structure by Holtzman, Beck, and Kerber (1979) revealed fourdimensions: Instrumentality, Autonomy, Acceptability, and Integrity. A subsequentconfirmatory factor analysis by Intrieri et al. (1995) found the modified four-fac-tor model as having the best fit. Moderate-to-high intercorrelations existed amongthe factors (ranging from .56 to .96), and the internal consistency reliability of the


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

subscales varied from .75 to .85. In the present study, we used the four-factor solu-tion in subsequent statistical analyses. We found the internal consistency (alpha)of Instrumentality, Autonomy, Acceptability, and Integrity scores to be .78, .80,.78, and .80, respectively.

Kogan’s (1961) OP measures individuals’ attitudes toward older people. Thescale originally consisted of 34 “old people” items in the form of positive–nega-tive pairs. That is, 17 items expressed negative statements about older people(OP−; e.g., “most old people get set in their ways and are unable to change”), and17 items expressed analogous statements written in the positive direction (OP+;e.g., “most old people are capable of new adjustments when the situation demandsit”). Participants responded to items using a Likert-type response scale thatranged from 1 (strongly disagree) to 6 (strongly agree).

Kogan (1961) reported internal consistency reliability coefficients (alphas)ranging from .66 to .85 for the 34-item scale across three samples. Also, Pearsonproduct-moment coefficients between positively and negatively worded scaleswere found to be significant, ranging from .46 to .52. Because Kogan found theOP− scale to possess greater reliabilities than the OP+ scale, we used the OP−scale in the present study, and its alpha reliability estimate was .86.

Results

FSA Factor Structure and Construct Validity

We tested the three-factor model suggested by Fraboni et al. (1990) using aconfirmatory factor analysis with polychoric correlations. The model consistedof three intercorrelated first-order factors with each item loading onto one of thethree latent factors. We did not allow error variances to correlate, and, for eachlatent factor, we constrained the path from one item to a given factor to 1.00 forpurposes of statistical identification (Byrne, 1998). Item loadings are presentedin Table 1. Results indicated that this model did not provide a very good fit to thedata, χ2(374) = 877.75, RMSEA = .062, NNFI = .80, CFI = .81, GFI = .85, AGFI= .83. Therefore, we conducted a follow-up exploratory factor analysis with avarimax rotation on Sample B to revisit the factor structure of the measure. Itemswere included within a factor if their loadings were .40 or greater. A three-factorsolution emerged, which accounted for 36.4% of the variance in FSA scores.Table 2 shows the factor loadings for each item as well as its similarity or dis-crepancy from the Fraboni et al. three-factor solution.

The results from the preceding analysis revealed a factor structure that wassomewhat different from the one suggested by Fraboni et al. (1990). However, ourfactor structure appears to be more consistent with the original purpose of the FSA(i.e., to measure both the affective components of ageism and the cognitive ones)than Fraboni et al.’s original factor structure. Factor 1 (α = .79) consisted of 10items that describe beliefs about older persons as a group; see Table 2. Factor 1


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014


TABLE 1. Item Loadings for Initial Confirmatory Factor Analysis (N = 353)

Item Antilocution Avoidance Discrimination

1. Many old people are stingy and hoard their money and possessions. .51

3. Many old people just live in the past. .83

4. Most old people should not be trusted to take care of infants. .61

5. Many old people are happiest when they are with people their own age. .79

9. I would prefer not to go to an open house at a senior’s club,if invited. .56

16. Old people should feel welcome at the social gatherings of young people. .52

25. Old people deserve the same rights and freedoms as do other members of our society. .88

27. Old people can be very creative. 1.00a

28. I would prefer not to live with an old person. .85

29. Old people do not need much money to meet their needs. .58

2. Many old people are not interested in making newfriends, preferring instead the circle of friends they have had for years. –.15

8. Old people complain more than other people do. .46

17. Old people don’t really need to use our community sports facilities. .78

18. It is best that old people live where they won’t bother anyone. .67

20. It is sad to hear about the plight of the old in our society these days. .96

(table continues)

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014


TABLE 1. Continued

Item Antilocution Avoidance Discrimination

21. Old people should be encouraged to speak out politically. 1.00a

22. Most old people are interest-ing, individualistic people. .46

23. I personally would not want to spend much time with an old person. .71

24. There should be special clubs set aside within sports facilities so that old people can compete at their own level. .80

6. Most old people would be considered to have poor personal hygiene. .91

7. Most old people can be irritating because they tell thesame stories over and over again. 1.00

10. Teenage suicide is more tragic than suicide among the old. .62

11. I sometimes avoid eye contact with old people when I see them. .61

12. I don’t like it when old people try to make conversation with me. .54

13. Complex and interesting conversation cannot be ex-pected from most old people. .96

14. Feeling depressed when around old people is probably a common feeling. .78

15. Old people should find friends their own age. 1.00a

19. The company of most old people is quite enjoyable. .55

26. Most old people should not be allowed to renew their drivers licenses. .79

aPaths were constrained to be equal to 1.0.

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014


TABLE 2. Varimax Factor Loadings for Ageism Dimensions (N = 201)

Varimax factor loadings

Item 1 2 3

Factor 1: Stereotypes

1. Many old people are stingy and hoard their money and possessions. .57 .00 .24 Antilocution

2. Many old people are not interested in making new friends, preferring instead the circle of friends they have had for years. .64 .00 .00 Antilocution

3. Many old people just live in the past. .71 .00 .00 Antilocution

4. Most old people should not be trusted to take care of infants. .42 .28 .00 Antilocution

5. Many old people are happiest when they are with people their own age. .45 .20 .00 Antilocution

6. Most old people would be considered to have poor personal hygiene. .55 .18 .26 Antilocution

7. Most old people can be irritating because they tell the same stories over and over again. .64 .21 .26 Antilocution

8. Old people complain more than other people do. .56 .18 .25 Antilocution

9. I would prefer not to go to an open house at a senior’s club, if invited. .48 .29 .35 Avoidance

10. Teenage suicide is more tragic than suicide among the old. .40 .00 .21 Antilocution

Factor 2: Separation

11. I sometimes avoid eye contact withold people when I see them. .25 .70 .00 Avoidance

12. I don’t like it when old people try to make conversation with me. .22 .79 .10 Avoidance

13. Complex and interesting conversation cannot be expected from most old people. .18 .50 .15 Antilocution

14. Feeling depressed when around old people is probably a common feeling. .32 .42 .00 Avoidance

(table continues)

Fraboni et al. (1990) factor

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014


TABLE 2. Continued


Item 1 2 3

Factor 2: Separation (continued)

15. Old people should find friends their own age. .00 .57 .00 Avoidance

16. Old people should feel welcome at the social gatherings of young people. .00 .46 .26 Avoidance

17. Old people don’t really need to use our community sports facilities. .28 .42 .17 Discrimination

18. It is best that old people live where they won’t bother anyone. .41 .51 .16 Discrimination

Factor 3: Affective attitude

19. The company of most old people is quite enjoyable. .25 .21 .62 Discrimination

20. It is sad to hear about the plight of the old in our society these days. .00 .00 .66 Discrimination

21. Old people should be encouraged to speak out politically. .14 .13 .59 Discrimination

22. Most old people are interesting,individualistic people. .13 .20 .65 Discrimination

23. I personally would not want to spend much time with an old person. .32 .39 .47 Avoidance

Original item excluded from revised measure

24. There should be special clubs set aside within sports facilities so that old people can compete at their own level. .16 –.27 –.10 Discrimination

25. Old people deserve the same rights and freedoms as do other members of our society. .00 .33 .27 Discrimination

26. Most old people should not be allowed to renew their drivers licenses. .38 .15 .00 Antilocution

(table continues)


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

appears to measure the cognitive component of ageism identified in past research(e.g., Kogan, 1961; Tuckman & Lorge, 1953). Consequently, we relabeled Factor1, which was similar to Fraboni et al.’s Antilocution factor, Stereotypes.

Stereotypes

Factor 2 and Factor 3 appeared to measure ageism’s affective component (seeTable 2). Factor 2, which is comparable to Fraboni et al.’s (1990) Avoidance factor,consisted of 10 items (α = .76) that primarily assessed the desire of individuals toseparate themselves from older people. Consequently, this factor was relabeled Sep-aration. The items that loaded on Factor 3 (k = 5, α = .70) were mostly reflectiveof emotionally related attitudes toward older people (like Fraboni et al.’s Discrim-ination factor). Therefore, we relabeled Factor 3 Affective Attitudes. Six itemsincluded in the original FSA did not load highly on any of the three factors andwere therefore excluded from the measure in subsequent analyses (see Table 2).

To further validate this revised three-factor model, we conducted a secondconfirmatory factor analysis on the original sample of 353 participants usingthe revised factor structure. Results showed a significant improvement in fitover the original structure, χ2(227) = 479.41, RMSEA = .056, NNFI = .87, CFI= .88, GFI = .89, AGFI = .87 (see Table 3 for item loadings) and relatively lowcorrelations among factors; see Table 4. This revised three-factor model wascompared to (a) a single-factor model, χ2(230) = 677.58, RMSEA = .079, NNFI= .76; CFI = .78, GFI = .85, AGFI = .82, (b) a three-factor model with uncor-related latent factors, χ2(230) = 772.21, RMSEA = .082, NNFI = .73; CFI = .75,GFI = .84, AGFI = .87, and (c) three two-factor models, each of which con-tained one of the original latent factors as the first factor, with the combination


TABLE 2. Continued


Item 1 2 3

Original items excluded from revised measure

27. Old people can be very creative. .33 .23 .38 Avoidance28. I would prefer not to live with an

old person. .39 .18 .39 Avoidance29. Old people do not need much

money to meet their needs. .30 .34 .12 Antilocution

Note. Bold entries signify the strongest factor loadings.


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014


TABLE 3. Item Loadings for Confirmatory Factor Analysis Using RevisedFactor Structure (N = 353)

AffectiveItem from Fabroni Scale of Ageism Stereotypes Separation attitudes

Teenage suicide is more tragic than suicide among the old. .52

Many old people are stingy and hoard their money and possessions. .80

Many old people are not interested in making new friends, preferring instead the circle of friends they have had for years. .61

Many old people just live in the past. .80I would prefer not to go to an open

house at a senior’s club, if invited. .85Most old people should not be trusted to

take care of infants. .59Many old people are happiest when

they are with people their own age. .57Most old people would be considered to

have poor personal hygiene. .88Most old people can be irritating

because they tell the same stories over and over again. 1.00a

Old people complain more than other people do. .84

I sometimes avoid eye contact with old people when I see them. .89

I don’t like it when old people try to make conversation with me. 1.00a

Complex and interesting conversation cannot be expected from most old people. .56

Feeling depressed when around old people is probably a common feeling. .52

Old people should find friends their own age. .54

Old people should feel welcome at the social gatherings of young people. .33

Old people don’t really need to use our community sports facilities. .54

It is best that old people live where they won’t bother anyone. .72

(table continues)

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

of the two remaining latent factors as the second factor; see Table 5 for fit index-es. Chi-square difference tests indicated that the revised three-factor structure,with correlated factors, was the solution demonstrating the best fit. A post hocexamination of modification indexes did not suggest further meaningful modi-fications to the structure of the FSA. Given this evidence in support of the mul-tidimensionality of ageism, we used the revised FSA factor scores (as opposedto total scores) in all subsequent analyses. All remaining analyses were com-puted using this revised factor structure on the first group of 353 participants(Sample A).

Table 6 provides the summary statistics, coefficient alphas, and intercorrela-tions for the measures used in the present study. As the table indicates, significantcorrelations existed between the FSA factors and other measures of age-related atti-tudes. As expected, FSA Stereotypes, measuring ageism’s cognitive component,was most strongly related to the more cognitively focused ASD and OP subscales.


TABLE 3. Continued

AffectiveItem from Fabroni Scale of Ageism Stereotypes Separation attitudes

I personally would not want to spend much time with an old person. 1.00

The company of most old people is quite enjoyable. 1.00a

It is sad to hear about the plight of the old in our society these days. .53

Old people should be encouraged to speak out politically. .77

Most old people are interesting,individualistic people. .90

aPaths were constrained to be equal to 1.0.

TABLE 4. Factor Correlations of the Subscales of theRevised Fabroni Scale of Ageism (N = 353)

Variable 1 2

1. Stereotypes2. Separation .653. Affective attitudes .73 .66

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014


TA

BL

E 5

. Fit

Sta

tist

ics

for

Con

firm

ator

y F

acto

r A

naly

sis

Mod

el C

ompa

riso

n

Var

iabl

eχ2

dfR

MSE

AN

NFI

CFI

GFI

AG

FI∆χ

2∆d

f

Frab

oni t

hree

fac

tor

877.

7537

40.

062

0.80

0.81

0.85

0.83

Rev

ised

thre

e fa

ctor

47

9.41

227

0.05

60.

870.

880.

890.

87Si

ngle

fac

tor

734.

3523

00.

079

0.76

0.78

0.85

0.82

254.

943

Thr

ee f

acto

r (u

ncor

rela

ted

fact

ors)

772.

2123

00.

082

0.73

0.75

0.84

0.81

292.

83

Two

fact

or (

ster

eoty

pe

& s

epar

atio

n co

mbi

ned)

663.

9722

90.

073

0.79

0.81

0.86

0.83

184.

562

Two

fact

or (

ster

eoty

pe &

af

fect

ive

com

bine

d)54

1.41

229

0.06

70.

830.

850.

870.

8562

2Tw

o fa

ctor

(se

para

tion

&

affe

ctiv

e co

mbi

ned)

593.

1622

90.

067

0.82

0.83

0.87

0.85

113.

752

Not

e. ∆

χ2re

fers

to

the

diff

eren

ce i

n ch

i sq

uare

bet

wee

n th

e re

vise

d th

ree-

fact

or s

truc

ture

and

the

pro

pose

d al

tern

ativ

e m

odel

. AG

FI =

adj

uste

d go

od-

ness

of

fit

inde

x; C

FI =

com

para

tive

fit

inde

x; G

FI =

goo

dnes

s of

fit

inde

x; N

NFI

= n

onno

rmed

fit

inde

x; R

MSE

A=

roo

t m

ean

squa

red

erro

r of

appr

oxim

atio

n.

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014


TA

BL

E 6

. Int

erco

rrel

atio

ns A

mon

g T

hree

Age

ism

Sca

les

and

Subs

cale

s

Subs

cale

Item

sM

SDC

ronb

ach’

s α

12

34

56

7

Fabr

oni

Scal

e of

Age

ism

1. S

tere

otyp

es10

2.04

0.43

6.7

92.

Sep

arat

ion

81.

600.

427

.76

.544

3. A

ffec

tive

attit

udes

51.

740.

465

.70

.503

.463

Agi

ng S

eman

tic

Diff

eren

tial

Sca

le

4. I

nstr

umen

tal

63.

790.

919

.77

.507

.340

.411

5. A

uton

omy

83.

360.

906

.79

.317

.298

.305

.650

6. A

ccep

tabi

lity

72.

990.

913

.78

.347

.307

.322

.596

.630

7. I

nteg

rity

53.

281.

045

.79

.332

.267

.197

.604

.675

.708

Att

itud

es T

owar

d O

ld P

eopl

e

8. N

egat

ive

attit

udes

tow

ard

old

peop

le14

2.28

0.67

9.8

6.7

33.5

20.5

08.5

08.3

85.3

55.3

22

Not

e. A

ll co

rrel

atio

ns a

re s

igni

fica

nt a

t the

leve

l of

p<

.01.

N=

353

.

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

Likewise, the relationship between FSA Affective Attitudes and these measures wasrelatively weak. Taken together, these analyses support Hypothesis 1.

Group Differences in Ageism

Prior to testing the effects of age and gender on ageism, we examined howboth ageism and age were distributed in our sample. In terms of ageism, none ofthe scales exhibited meaningful skewness or kurtosis (max skewness = .686, maxkurtosis = .501), although low ageist attitudes are probably considered to be desir-able. The distribution of age, however, exhibited both high skewness (2.556) andhigh kurtosis (7.433). This is not surprising given the nature of our sample (col-lege students). Although the presence of high skewness and kurtosis can attenu-ate observed effects in a downward direction, we decided not to transform the agevariable. This is because transformed variables are often difficult to interpret, par-ticularly when the original variable is easily interpretable, as was the case here.

Table 7 shows the results of the analyses of age and gender effects in ageismscores. Ageism scores exhibited significant negative relationships with age forfive of the examined subscales, supporting Hypothesis 2, although the strength ofthese effects was generally weak. Likewise, women, on average, exhibited lowerlevels of ageism (Wilks’s Λ = .900, p < .001) on all eight of the examined sub-scales; six of these differences were statistically significant and had moderateeffect sizes (J. Cohen, 1988), supporting Hypothesis 3.

In addition to the moderate linear relationship between age and ageism shownby Table 7, we also found significant curvilinear relationships between participantage and ageism scores. Table 8 illustrates that these curvilinear effects added sig-nificant incremental validity over a simple linear effect for age for six of the eightmeasures of age attitude. The direction of the curvilinear effects suggests anasymptotic effect. That is, the decline in ageism scores that is associated with beingolder becomes less pronounced at the higher end of the age spectrum.

Discussion

Summary and Limitations

In summary, a series of confirmatory factor analyses provide support for theexistence of three FSA factors that are similar to the ones initially proposed byFraboni et al. (1990). However, given the present findings, we suggest that the fac-tors are best labeled as stereotypes, separation, and affective attitudes. This struc-ture appears to be a more accurate reflection of the factorial composition of the scaleand offers an improved characterization of the cognitive and affective facets ofageism as defined by Butler (1969). This finding is bolstered by the specific rela-tionships that we detected between FSA factors and scores on additional ageismscales. That is, the cognitively oriented FSA factor of Stereotypes was significantly


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014


TA

BL

E 7

. Eff

ect

for

Gen

der

and

Age

on

the

Subs

cale

Sco

res

of t

he F

abro

ni S

cale

of A

geis

m,t

he A

ging

Sem

anti

c D

iffe

rent

ial

Scal

e,an

d th

e A

ttit

udes

Tow

ard

Old

Peo

ple

Scal

e

Wom

enM

en

Subs

cale

MSD

MSD

t(35

0)p

dp

Fabr

oni

Scal

e of

Age

ism

1. S

tere

otyp

es1.

980.

432.

190.

414.

32.0

00–.

50–0

.14

0.01

2. S

epar

atio

n1.

550.

391.

720.

493.

28.0

01–.

38–0

.15

0.00

53.

Aff

ectiv

e at

titud

es1.

670.

441.

930.

474.

88.0

00–.

59–0

.17

0.00

1

Agi

ng S

eman

tic

Diff

eren

tial

Sca

le

4. I

nstr

umen

tal

3.71

0.92

3.98

0.91

2.51

.013

–.28

–0.1

10.

039

5. A

uton

omy

3.34

0.91

3.43

0.91

0.82

.412

–.10

–0.0

40.

451

6. A

ccep

tabi

lity

2.91

0.91

3.17

0.91

2.44

.015

–.29

0.03

0.60

47.

Int

egri

ty3.

241.

083.

380.

961.

09.2

75–.

140.

060.

257

Att

itud

es T

owar

d O

ld P

eopl

e

8. N

egat

ive

attit

udes

tow

ard

old

peop

le2.

230.

672.

390.

681.

99.0

48–.

24–0

.26

0.00

0

Not

e. N

= 3

53.

Cor

rela

tion

with

age

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014


TA

BL

E 8

. Cur

vilin

ear

Rel

atio

nshi

ps B

etw

een

Par

tici

pant

Age

and

Sco

res

on M

easu

res

of A

geis

m

Fabr

oni S

cale

of A

geis

mA

ging

Sem

antic

Dif

fere

ntia

l Sca

le

Aff

ectiv

eV

aria

ble

Ster

eoty

pes

Sepa

ratio

nat

titud

esIn

stru

men

tal

Aut

onom

yA

ccep

tabi

lity

Inte

grity

Age

–1.0

1**

–1.3

6**

–.25

–1.0

8**

–.79

*–.

38–.

65*

–1.0

0**

Age

20.

881*

*1.

23**

.08

0.98

**.7

6*.4

2.7

2*0.

76*

Initi

al R

20.

019*

*0.

022*

*.0

29**

0.01

2*.0

02.0

01.0

040.

066*

*∆R

20.

023*

*0.

045*

*.0

00.

028*

*.0

17*

.005

.015

*0.

017*

Tota

l R2

0.04

2**

0.06

7**

.029

**0.

041*

*.0

19**

.006

.019

*0.

083*

*

*p<

.05.

**p

< .0

1.

Neg

ativ

eat

titud

esto

war

dol

d pe

ople

Stan

dard

ized

βco

effi

cien

ts

Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

correlated with other cognitive ageism measures. FSA factors that were more affec-tive in nature (Separation and Affective Attitudes) were also significantly related toother ageism measures, although to a lesser extent than the Stereotypes factor.

However, several limitations should be noted. First, the factor structurereported here only accounted for approximately 36% of the variance in FSAscores and that fit indices showed only moderate-to-good fit. Consequently, addi-tional research on the FSA appears warranted. Specifically, it may be useful todevelop additional items for the factor Affective Responses. This factor possessedthe fewest number of items (k = 5) and the lowest internal consistency (α = .70).This is especially important in that the Affective Responses factor adds breadthto the cognitive nature of previous ageism measures.

A second limitation is the limited number and type of variables that havebeen used to provide construct validity for the FSA. To completely understandageism’s placement in a larger nomological network (Cronbach & Meehl, 1955),it would be beneficial for FSA scores to be compared with scores on many othersimilar and dissimilar measures. Such useful constructs could include personali-ty characteristics and general prejudice, stereotypes, and attitudes. Indeed, itwould be useful to know if a discriminatory profile exists or whether differenttypes of individuals hold negative attitudes toward different groups.

Third, our findings indicate that men are more ageist than women. This find-ing supports previous research on gender differences in ageism (e.g., Fraboni etal., 1990; Kalavar, 2001; Kite & Stockdale, 2004). This result may be partly dueto females’ having higher scores on the personality dimension of expressiveness(e.g., warmth, caring, empathy), whereas men generally possess higher instru-mentality scores (Deaux, 1985). Kalavar argued that such an effect may be theresult of lifespan developmental processes and greater experience with and expo-sure to older people. Nevertheless, investigators should interpret the gender effectfound herein with caution. That is, the difference in ageism scores attributed togender was relatively small (mean difference of .17) and could have been affect-ed by a variety of factors, most notably the size of the current sample. A genderdifference of this size, albeit statistically significant, casts some doubt on thepragmatic utility of the present finding. It is important to note, however, that oureffect sizes were moderate in strength and that they were strongest for the FSAsubscales. Further research is needed to determine the accuracy and generaliz-ability of the gender–ageism relationship.

Last, the present results indicate that a significant negative relationship existsbetween participants’ chronological age and ageism scores, indicating a tenden-cy for younger raters to be more ageist than older raters. This finding supportspast research that has found similar effects (e.g., Finkelstein et al., 1995) andcounters past research that has not detected such an effect (e.g., Hellbusch et al.,1994). In the present study, we also found evidence supporting the possibility thata curvilinear relationship may exist between chronological age and ageism, whichis congruent with the research of Kite and Stockdale (2004). However, the skew-


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

ness and kurtosis of the participants’ age was high. A log transformation couldhave been used to increase the heteroscedasticity of the age variable, but resultsthat are based on such transformations are often difficult to interpret. Also, giventhat the untransformed variable is a “real-life” variable, we believe that the atten-uation of our effects that was due to skewness and kurtosis is a likely artifact ofusing a college-age population. Future research should certainly attempt to repli-cate our findings on a less skewed sample of adults.

Perhaps the general finding that greater ageism is found among youngerraters is a manifestation of out-group derogation (see Fiske, 2002, and the workon SIT; Tajfel & Turner, 1979). Research in this area has generally found thatindividuals are biased in their evaluations, attributions, and expectations of thoseconsidered to be out-group members. Consistent with social comparison theory(Festinger, 1954; Wood, 1989), it is also likely that young people seldom inter-act with the aged and are primarily exposed to people of similar ages. This cir-cumstance can lead to a confined view of older individuals, especially because oftheir relatively rare—and often low-status—portrayal in books and the media(e.g., Whitbourne & Hulicka, 1990).

These findings are interesting in comparison to the research on generalstereotyping and prejudice. Although research has shown that older persons (asopposed to younger persons) are more prejudiced in general (von Hippel, Silver,& Lynch, 2000), the present results suggest that this may not be the case whenthe focus of the prejudice is one’s own group (i.e., older people). When age is thetarget of prejudice, an opposite effect occurs. That is, younger individuals showmore ageism than do older individuals. This finding is consistent with our SITargument and is also certainly an avenue for future research.

Implications

A deeper understanding of ageism’s correlates and measurement would beimportant to research on age bias—especially workplace age bias. Previousresearch indicates that older workers receive harsher evaluations, have their errorsattributed to their age as opposed to situational factors, and generally fall victimto the belief that job performance declines with age (Faley, Kleiman, & Leng-nick-Hall, 1984; Finkelstein et al., 1995; Issacharoff & Harris, 1997; Perry, Kulik,& Bourhis, 1996; Rupp et al., in press; Wilkening, 2002). It is important to notethat the belief that job performance declines with age exists despite the fact thatno differences have been found between older and younger workers when “objec-tive” or productivity indices are used (Cleveland & Landy, 1983; Forteza & Pri-eto, 1994; Laczko & Philipson, 1991; Landy, 1992; Mowery & Kamlet, 1996;Park, 1994; Waldman & Avolio, 1986; Warr, 1994). Supporting the significanceof work-related ageism have been findings of recent meta-analytic studies indi-cating that the impact of negative information on ageism is heightened withinemployment contexts (Kite & Stockdale, 2004) and that both job applicants andincumbents can be victims of ageism (Gordon & Arvey, 2004).


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

Another reason the study of ageism is warranted is that recent research hasfound that ageism can be reduced (Braithwaite, 2002; Chiu et al., 2001; Ragan &Bowen, 2001). Efforts have been aimed at both potentially ageist individuals (e.g.,those who have the power to engage in age discrimination, such as raters in per-formance evaluations or personnel-selection situations) and potential victims ofage bias (e.g., by providing opportunities for development in areas in which per-formance seems to decline with age). Other interventions have focused on orga-nization or community climate. Such a strategy attempts to sensitize individualsto the possibility of unconsciously engaging in stereotyping (Braithwaite, 2002),to educate individuals on the myths and realities of aging (Finkelstein et al.,1995), and to emphasize the negative consequences of age bias. Examples of suchstrategic actions include eliminating age types for jobs and holding organizationaldecision makers accountable for age discrimination (Maurer & Rafuse, 2001;Perry et al., 1996). This strategy reflects the more general literature on bias, whichhas shown that bias can be reduced through education and constructive intergroupcontact, including contact of equal status, shared goals, cooperation in pursuit ofgoals, and the support by authorities (Fiske, 2002).

Additional Future Research

Because of the importance of minimizing workplace age bias, one potentiallyfruitful area of future research would be that of developing an organizationallyfocused version of the FSA. This development would involve shifting the items’focus from “the elderly” to “older workers.” Also, item content could be added torefer explicitly to workplace situations. If such a measure was found to be reliableand valid, research on workplace age bias could explore the impact of age-relatedcognitive or affective beliefs and attitudes on discriminatory behaviors more direct-ly. For instance, research has indicated that older employees and job applicants areviewed more negatively (e.g., Finkelstein et al., 1995; Gordon & Arvey, 2004; Kite& Johnson, 1988), are perceived as possessing less interpersonal skills, stamina,competence, and dexterity (Finkelstein & Burke, 1998; Kite & Stockdale, 2004;McMullin & Marshall, 2001) and as being less affected by training efforts (Cleve-land & Shore, 1992; Maurer & Rafuse, 2001). Such views are most prominent forjobs involving extensive physical requirements (Young, Rinhart, & Baits, 1997).Also, recent research has suggested that older workers receive harsher sanctions forjob-related errors and that these may be the result of (a) ageist attitudes and (b) (sta-ble) attributions of poor performance (Rupp et al., in press).

Future research might also consider integrating the findings of the presentstudy with that of research looking at individual differences in age perceptions heldabout particular jobs. For example, Gordon and Arvey (1986) found that individ-uals classify many jobs in terms of the average age of persons holding the posi-tion. Further, these authors also found that this average-age perception was lowerfor younger participants. In predicting outcomes such as performance ratings,


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

future studies might consider exploring the interplay between supervisor age andageism, subordinate age, and the perceived age of the job as seen by subordinates.

It is important to note, however, that social and industrial/organizational psy-chologists may assign very different meanings to the term “old” (Kite & Wagner,2002). Whereas the ageism research conducted in the field of gerontology hasfocused primarily on “the elderly” (i.e., those individuals over the age of 65 years),ageism as studied by researchers in the organizational sciences may involve per-ceptions about a slightly younger group of people. For example, in the UnitedStates, the Age Discrimination in Employment Act (ADEA, 1967) stipulates thatemployees over the age of 40 can file an age discrimination claim. Such an age ishardly considered elderly by most standards. Thus, such legislation requires botha broader definition of an “older” person or worker and caution in the applicationof gerontological research findings to organizational situations.

There is also a need for research that reconciles the applied research show-ing little decline in job performance with age (e.g., Wilkening, 2002), the cogni-tive aging research showing a sharp decline (e.g., Salthouse, 2003), and theageism literature. Salthouse (2004) argued that although there is a sharp declinein cognitive functioning as adults get older, the impairment rarely impacts every-day functioning. This is because factors such as motivation, persistence, adapta-tion, and experience inhibit performance declines. Also, many tasks (includingjob tasks) rarely require the level of cognitive functioning required in laboratorystudies of this effect. However, it appears that individuals continue to possess age-related attitudes regarding both people and jobs. An important goal for futureresearch would be to identify the antecedents of ageist attitudes and the mediat-ing variables explaining how such attitudes lead to age bias. Rupp et al. (in press)have offered causal attributions as one potential mediator, but much moreresearch is needed in this area.

Lastly, it would be fruitful for future research to study the construct of ageismacross cultures. Such studies should look toward the cross-cultural age bias liter-ature for informative models (e.g., Bennington, 2001; Bennington & Wein, 2002;Chiu et al., 2001; Ho et al., 2000; McMullin & Marshall, 2001; Taylor & Walk-er, 1997; Van den Heuvel, 1999). Such a pursuit is especially relevant becauseother countries are in the process of passing legislation outlawing age discrimi-nation. For example, Reade (2003) has estimated that in England, where such leg-islation is expected to pass by 2006, organizations not preparing themselves forthese new laws could expose themselves to £73 billion (over $118 billion) inclaims. Indeed, researchers must first seek to understand the construct of ageismbefore trying to understand its effects on individuals and societies. The presentstudy represents one step in this direction.

Conclusion

In conclusion, the present study offers additional psychometric evidence


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

that the FSA constitutes a reliable, valid, and multidimensional measure ofageism. The presence of both cognitive and affective components of ageism iscompatible with the theoretical work of Butler (1969) and extends the assess-ment of ageism beyond previous measures that have been primarily cognitive innature. It is hoped that other researchers will find the FSA to be a useful instru-ment for exploring the antecedents and consequences of ageism. The presentstudy also showed that men and younger individuals were significantly moreageist than women and older individuals. More research is needed exploring whysuch differences exist, as well as which additional variables might mediate ormoderate these effects.

NOTE

1. It should be noted that this overall finding was shown (Gordon & Arvey, 2004) tobe moderated, in various degrees, by numerous factors such as publication date, raterdemographics, research design, amount and type of target information, and dimensions orcriteria used.

REFERENCES

Age Discrimination in Employment Act of 1967, 42 U.S.C. § 6101 et seq.Allport, G. W. (1958). The nature of prejudice. Garden City, NY: Doubleday Anchor

Books.Banaji, M. R. (1999). Unconscious isms: Examples from racism, sexism, and ageism. Paper

presented at the Way Women Lean Conference, New Haven, CT.Bell, B. D., & Stanfield, G. G. (1973a). The aging stereotype in experimental perspective.

Gerontologist, 13, 341–344.Bell, B. D., & Stanfield, G. G. (1973b). Chronological age in relation to attitudinal judg-

ments: An experimental analysis. Journal of Gerontology, 28, 491–496.Bennington, L. (2001). Age discrimination: Converging evidence from four Australian

studies. Employee Responsibilities and Rights Journal, 13(3), 125–134.Bennington, L., & Wein, R. (2002). Aiding and abetting employer discrimination: The job

applicant’s role. Employee Responsibilities and Rights Journal, 14, 3–16.Berg, C. A., & Sternberg, R. J. (1992). Adults’ conceptions of intelligence across the life

span. Psychology and Aging, 7, 221–231.Braithwaite, V. (2002). Reducing ageism. In T. D. Nelson (Ed.), Ageism: Stereotyping and

prejudice against older persons (pp. 311–338). Cambridge, MA: MIT Press.Butler, R. N. (1969). Age-ism: Another form of bigotry. Gerontologist, 9, 243–246.Butler, R. N. (1980). Ageism: A foreword. Journal of Social Issues, 36, 8–11.Butler, R. N. (1995). Ageism. In G. Maddox (Ed.), The encyclopedia of aging (2nd ed.,

pp. 38–39). New York: Springer.Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS:

Basic concepts, applications, and programming. Mahwah, NJ: Erlbaum.Chiu, W. C. K., Chan, A. W., Snape, E., & Redman, T. (2001). Age stereotypes and dis-

criminatory attitudes towards older workers: An East-West comparison. Human Rela-tions, 54, 629–661.

Cleveland, J. N., & Landy, F. J. (1983). The effects of person and job stereotypes on twopersonnel decisions. Journal of Applied Psychology, 68, 609–619.

Cleveland, J. N., & Shore, L. M. (1992). Self- and supervisory perspectives on age and


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

work attitudes and performance. Journal of Applied Psychology, 77, 469–484.Cohen, E. S. (2001). The complex nature of ageism: What is it? Who does it? Who per-

ceives it? Gerontologist, 41, 576–577. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hills-

dale, NJ: Erlbaum.Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psycho-

logical Bulletin, 52, 281–302.Cuddy, A. J. C., & Fiske, S. T. (2002). Doddering but dear: Process, content, and function

in stereotyping of older persons. In T. D. Nelson (Ed.), Ageism: Stereotyping and prej-udice against older persons (pp. 3–26). Cambridge, MA: MIT Press.

Deaux, K. (1985). Sex and gender. Annual Review of Psychology, 36, 49–81.Employment practice liability: Jury award trends and statistics. (2001). Arlington, VA:

LRP Publications.Erber, J. T., Szuchman, L. T., & Rothberg, S. T. (1990). Everyday memory failure: Age

difference in appraisal and attribution. Psychology and Aging, 5, 236–241.Faley, R. H., Kleiman, L. S., & Lengnick-Hall, M. L. (1984). Age discrimination and per-

sonnel psychology: A review and synthesis of the legal literature with implications forfuture research. Personnel Psychology, 37, 327–350.

Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7,117–140.

Finkelstein, L. M., & Burke, M. J. (1998). Age stereotyping at work: The role of rater andcontextual factors on evaluations of job applicants. The Journal of General Psycholo-gy, 125, 317–345.

Finkelstein, L. M., Burke, M. J., & Raju, N. S. (1995). Age discrimination in simulatedemployment contexts: An integrative analysis. Journal of Applied Psychology, 80,652– 663.

Fiske, S. T. (2002). What we know about bias and intergroup conflict, the problem of thecentury. Current Directions in Psychological Science, 11(4), 123–128.

Forteza, J. A., & Prieto, J. M. (1994). Aging and work behavior. In H. C. Triandis & M.D. Dunnette (Eds.), Handbook of industrial and organizational psychology (pp.446–483). Palo Alto, CA: Consulting Psychologists Press.

Fraboni, M., Saltstone, R., & Hughes, S. (1990). The Fraboni Scale of Ageism (FSA):An attempt at a more precise measure of ageism. Canadian Journal on Aging, 9,56–66.

Golde, P., & Kogan, N. (1959). A sentence completion procedure for assessing attitudestoward old people. Journal of Gerontology, 14, 355–363.

Gordon, R. A., & Arvey, R. D. (1986). Perceived and actual ages of workers. Journal ofVocational Behavior, 28, 21–28.

Gordon, R. A., & Arvey, R. D. (2004). Age bias in laboratory and field settings: A meta-analytic investigation. Journal of Applied Social Psychology, 34, 1–27.

Hassell, B. L., & Perrewe, P. L. (1995). An examination of beliefs about older workers:Do stereotypes still exist? Journal of Organizational Behavior, 16, 457–468.

Hellbusch, J. S., Corbin, D. E., Thorson, J. A., & Stacy, R. D. (1994). Physicians’ attitudestowards aging. Gerontology and Geriatrics Education, 15(2), 55–65.

Ho, L. S., Wei, X. D., & Voon, J. P. (2000). Are older workers disadvantaged in the HongKong labor market? Asian Economic Journal, 14, 283–300.

Holtzman, J. M., Beck, J. D., & Kerber, P. E. (1979). Dimensional aspects of attitudestoward the aged. Gerontologist, 19, 91.

Intrieri, R. C., von Eye, A., & Kelly, J. A. (1995). The aging semantic differential: A con-firmatory factor analysis. Gerontologist, 35, 616–621.

Issacharoff, S., & Harris, E. W. (1997). Is age discrimination really age discrimination?


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

The ADEA’s unnatural solution. New York University Law Review, 72, 780–840.Kalavar, J. M. (2001). Examining ageism: Do male and female college students differ?

Educational Gerontology, 27, 507–513.Kite, M. E., & Johnson, D. T. (1988). Attitudes toward older and younger adults: A meta-

analysis. Psychology and Aging, 3, 233–244.Kite, M. E., & Stockdale, G. D. (2004). Attitudes toward younger and older adults: An

updated meta-analytic review. Journal of Social Issues.Kite, M. E., & Wagner, L. S. (2002). Attitudes toward older and younger adults. In T. D.

Nelson (Ed.), Ageism: Stereotyping and prejudice against older persons (pp. 129–161).Cambridge, MA: MIT Press.

Kogan, N. (1961). Attitudes toward old people: The development of a scale and an exam-ination of correlates. Journal of Abnormal and Social Psychology, 62, 44–54.

Kogan, N., & Shelton, F. C. (1962). Images of “old people” and “people in general” in anolder sample. The Journal of Genetic Psychology, 100, 3–21.

Laczko, F., & Philipson, C. (1991). Changing work and retirement: Social policy and theolder worker. Milton Keynes, England: Open University Press.

Landy, F. J. (1992). Alternative to chronological age in determining standards of suitabilityfor public safety jobs. Volume 1: Technical report. University Park, PA: Center forApplied Behavioral Sciences.

Levy, B., Ashman, O., & Dror, I. (2000). To be or not to be: The effects of aging stereo-types on the will to live. Omega—Journal of Death and Dying, 40(3), 409–420.

Levy, B. R., & Banaji, M. R. (2002). Implicit ageism. In T. D. Nelson (Ed.), Ageism: Stereo-types and prejudice against older persons (pp. 49–75). Cambridge, MA: MIT Press.

Levy, B. R., Hausdorff, J. M., Hencke, R., & Wei, J. Y. (2000). Reducing cardiovascularstress with positive self-stereotypes of aging. Journal of Gerontology, 55, 205–213.

Liden, R. C., Stilwell, D., & Ferris, G. R. (1996). The effects of supervisor and subordi-nate age on objective performance and subjective performance ratings. Human Rela-tions, 48, 327– 347.

Maurer, T. J., & Rafuse, N. E. (2001). Learning, not litigating: Managing employee devel-opment and avoiding claims of age discrimination. Academy of Management Executive,15, 110–121.

McCann, R., & Giles, H. (2002). Ageism in the workplace: A communication perspective.In T. D. Nelson (Ed.), Ageism: Stereotyping and prejudice against older persons (pp.163–199). Cambridge, MA: MIT Press.

McMullin, J. A., & Marshall, V. W. (2001). Ageism, age relations, and garment industrywork in Montreal. Gerontologist, 41, 111–122.

Mowery, D. C., & Kamlet, M. S. (1996). New technologies and the aging work force. InS. A. Bass, F. G. Caro, & Y. Chen (Eds.), Achieving a productive aging society (pp.81–95). Westport, CT: Auburn House.

Palmore, E. B. (1977). Facts on aging: A short quiz. Gerontologist, 17, 315–320.Palmore, E. B. (1999). Ageism: Negative and positive. New York: Springer.Palmore, E. B. (2001). The Ageism Survey: First findings. Gerontologist, 41, 572–575.Park, D. C. (1994). Aging, cognition, and work. Human Performance, 7, 181–205.Perry, E. L., Kulik, C. T., & Bourhis, A. C. (1996). Moderating effects of personal and

contextual factors in age discrimination. Journal of Applied Psychology, 81, 628–647.Ragan, A. M., & Bowen, A. M. (2001). Improving attitudes regarding the elderly popula-

tion: The effects of information and reinforcement for change. Gerontologist, 41,511–515.

Reade, Q. (2003, April 8). Failure to prepare for ageism laws may cost firms billions. Per-sonnel Today, 7.

Rosencranz, H. A., & McNevin, T. E. (1969). A factor analysis of attitudes toward the


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

aged. Gerontologist, 9, 55–59.Rupp, D. E., Vodanovich, S. J., & Credé, M. (in press). Age bias in the workplace: The

impact of ageism and causal attributions. Journal of Applied Social Psychology.Salthouse, T. A. (2003). Interrelations of aging, knowledge, and cognitive performance. In

U. Staudinger & U. Lindenberger (Eds.), Understanding human development: Lifespanpsychology in exchange with other disciplines (pp. 265–287). Berlin, Germany: Kluw-er Academic.

Salthouse, T. A. (2004). What and when of cognitive aging. Current Directions in Psy-chological Science, 13, 140–144.

Segrave, K. (2001). Age discrimination by employers. Jefferson, NC: McFarland & Com-pany.

Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In W. G.Austin & S. Worschel (Eds.), The social psychology of intergroup relations. Monterey,CA: Brooks/Cole.

Taylor, P., & Walker, A. (1997). Age discrimination and public policy. Personnel Review,26, 307–318.

Tuckman, J., & Lorge, I. (1953). Attitudes toward old people. The Journal of Social Psy-chology, 37, 249–260.

Underwood, D. G., Eklund, S. J., & Whisler, S. (1985). A reexamination of the factor struc-ture of the aging semantic differential using a generalized social object. EducationGerontology, 11, 321–335.

van den Heuvel, A. (1999). Mature age workers: Are they a disadvantaged group in thelabour market? Australian Bulletin of Labour, 25(1), 11–22.

von Hippel, W., Silver, L. A., & Lynch, M. E. (2000). Stereotyping against your will: Therole of inhibitory ability in stereotyping and prejudice among the elderly. Personalityand Social Psychology Bulletin, 26, 523–532.

Waldman, D. A., & Avolio, B. J. (1986). A meta-analysis of age differences in job perfor-mance. Journal of Applied Psychology, 71, 33–38.

Warr, P. (1994). Age and employment. In H. C. Triandis & M. D. Dunnette (Eds.), Hand-book of industrial and organizational psychology (pp. 485–550). Palo Alto, CA: Con-sulting Psychologists Press.

Whitbourne, S. K., & Hulicka, I. M. (1990). Ageism in undergraduate texts. American Psy-chologist, 45, 1127–1136.

Wilkening, R. (2002). The age 60 rule: Age discrimination in commercial aviation. Avia-tion, Space, and Environmental Medicine, 73(3), 194–202.

Williams, A., & Nussbaum, J. F. (2001). Intergenerational communication across the life-span. Mahwah, NJ: Erlbaum.

Wood, J. V. (1989). Theory and research concerning social comparison of personal attrib-utes. Psychological Bulletin, 106, 231–248.

Young, P., Rinehart, J. S., & Baits, D. M. (1997). Age discrimination: Impact of chrono-logical age and perceived position demands on teacher screening decisions. Journal ofResearch and Development in Education, 30, 103–112.

Received January 23, 2004Accepted September 14, 2004


Dow

nloa

ded

by [

Illin

ois

Wes

leya

n U

nive

rsity

] at

13:

58 0

6 O

ctob

er 2

014

Documents

The Multidimensional Nature of Ageism: Construct Validity and Group Differences