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This article was downloaded by: [University of Texas Libraries]On: 23 December 2014, At: 08:56Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH,UK
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Testing Generational, LifeCycle, and Period Effects ofAge on Agenda SettingJae Kook Lee a & Renita Coleman ba School of Journalism Indiana Universityb School of Journalism University of Texas at AustinPublished online: 28 Aug 2013.
To cite this article: Jae Kook Lee & Renita Coleman (2014) Testing Generational, LifeCycle, and Period Effects of Age on Agenda Setting, Mass Communication and Society,17:1, 3-25, DOI: 10.1080/15205436.2013.788721
To link to this article: http://dx.doi.org/10.1080/15205436.2013.788721
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Testing Generational, Life Cycle,and Period Effects of Age
on Agenda Setting
Jae Kook LeeSchool of JournalismIndiana University
Renita ColemanSchool of Journalism
University of Texas at Austin
This study explores the relationship between age and the media’s agenda-setting effects both by cross-sectional and longitudinal analysis. UsingAmerican National Election Studies surveys and the New York Times Indexdata from 1960 to 2004, we test three possible effects of age on the agenda-setting process: generational, life-cycle, and period effects. Findings show thepublic agenda is fairly stable across generations and age cohorts despite increas-ing signs of media diversification and audience specialization. More important,different generations’ agendas were overall correlated with the media agendain each year, indicating robust agenda-setting effects of the media on the public,except for baby boomers. The findings generally support the hypothesis ofperiod effects. Implications of the findings are discussed.
Jae Kook Lee (Ph. D., University of Texas at Austin, 2009) is an Assistant Professor in the
School of Journalism at Indiana University. His research interests include media effects and
public opinion in the changing media environment.
Renita Coleman (Ph. D., University of Missouri, 2001) is an Associate Professor in the
School of Journalism at University of Texas at Austin. Her research interests include agenda
setting, visual communication, and ethics.
Correspondence should be addressed to Jae Kook Lee, School of Journalism, Indiana
University, 940 E. Seventh Street, Ernie Pyle Hall 200, Bloomington, IN 47405-7108. E-mail:
Mass Communication and Society, 17:3–25, 2014Copyright # Mass Communication & Society Division
of the Association for Education in Journalism and Mass Communication
ISSN: 1520-5436 print=1532-7825 online
DOI: 10.1080/15205436.2013.788721
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INTRODUCTION
Whenever young people in a society are studied, differences among the gen-erations seem to be the focus more so than similarities. Younger generationsadapt to new technology faster and are more strongly influenced by newmedia than older generations, so the recent changes in new media have madethe differences even more salient. Young people get their news about publicaffairs from nontraditional media more than from traditional sources suchas newspaper and network TV news (Bimber, 1999, 2000; Pew ResearchCenter, 2004, 2011). These differences should have effects on the opinionsand political involvement of the different generations, especially on theyoung. This raises the question of whether age functions as a contingentcondition in agenda setting. If generations have different patterns of mediause and opinion formation, it is possible that agenda-setting effects varywith age. This study investigates the possibility of age as a contingent con-dition of agenda setting using theoretical mechanisms pertaining to age—generational, life-cycle, and period effects (Eisenstadt, 1956; Glenn, 2005;Hellevik, 2002; Klecka, 1971). This study touches on the important questionraised by Bennett and Iyengar (2008) regarding whether we have entered anew era of minimal media effects; its longitudinal design spanning nearly 30years allows us to explore the media’s agenda-setting effects across time.
This study does not directly examine the new media environment or mediafragmentation; this link between audience age and media use is frequentlymade by scholars speculating on the future of agenda setting, but age andmedia use are distinct and should not be conflated. The introduction of cableand the Internet has dramatically broadened the content of media across the30 years of this study; however, more information sources do not necessarilymean that people using the newer sources are doing so at the expense ofolder, traditional sources. Nor is there any reason to believe that the issuescovered by newer sources are different from those covered by traditionalsources. This is an intuitively appealing idea, one that is often conflated withaudience age. In this study, we directly examine age using three theoreticaldefinitions, and do not purport to equate content, source availability, anddiversification of sources with age. The literature on these topics is examinedas it relates to age, but these assumptions do not ground this study. Wepresent these findings as context, for the media technology of the time isinevitable. Two of the hypotheses offered implicate the media environmentand media use as explanations for the effects of age, whereas the third doesnot. However, our purpose is to see whether agenda-setting effects differ byage or generational cohort. Specifically, we conduct an examination of oneage group after another, over time, to ascertain agenda-setting effects.
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This study is important because the direct connection between age andagenda setting has been examined in only one study (Coleman & McCombs,2007), and in a much more limited way than is done here. Furthermore, thelongitudinal nature of this study allows us to examine the pure effects of agein different media environments. Technological change was vast across theperiods in this data set; if there are effects of age regardless of the technologyof the time, we will have a greater understanding of the importance ofindividual differences; if there are no effects of age, then we can focusfuture research on technological and social conditions, confident that agealone matters less than has been proposed. This study expands our knowl-edge of the role of age in agenda setting using three theoretical conceptionsof age:
Generational effects denote the experiences shared by certain age groupsthat distinguish characteristics of group members from those of others.Life-cycle effects represent the chronological amount of time that has elapsedsince birth and explain how an individual’s position in his or her life spanaffects attitudes toward public affairs. Period effects are those that influencepeople in particular periods regardless of their age. Findings of period effectswould show a blanket influence of the media and, thus, a relatively homo-geneous agenda among the generations and through a life cycle.
These three age-related effects generate much different predictions withregard to the media’s agenda-setting function. The generational hypothesiscontends that diversification of media outlets and audience specializationleads to the formation of different public agendas across generations, withthe different pattern of media use among generations being the main predic-tors. The life-cycle hypothesis argues that the location of an individual in hisor her life span affects selective exposure to media content and leads to theformation of different agendas at different ages. Both generational andlife-cycle hypotheses predict that age makes a difference in the media’sagenda-setting effects; however, the hypothesis of period effects maintainsthat agenda-setting effects will be similar for all of the people in each period,regardless of generational or life-cycle variables, and differential media use.
For two of these explanations, differences between ages and=or groupssupport the notion of age as a contingent condition of agenda setting,whereas similarities argue against it. This study seeks to understand which,if any, of the three effects of age influence agenda setting. Although manystudies have explored the contingent conditions that regulate agenda-settingeffects, there is a paucity of research on this important demographic as anintervening variable. This study contributes to the understanding of publicopinion formation by using longitudinal data to explore the three age-relatedeffects and their role in the agenda-setting process.
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LITERATURE REVIEW
The hypothesis of agenda setting is that the media transfer issue salienceto the public (McCombs & Shaw, 1972). By covering certain issues morethan others, the media make those issues more salient and set the agendaof important problems in the public’s mind (McCombs, 2004). Numerousstudies provide evidence supporting this hypothesis.
Since the introduction of the agenda-setting concept (McCombs & Shaw,1972), studies also have examined the contingent conditions that regulatethe process. Research has identified audience characteristics such as needfor orientation (Weaver, 1977) and issue obtrusiveness (Zucker, 1978)among the conditions that weaken or strengthen agenda-setting effects.Bennett and Iyengar (2008) specifically addressed the role of age, positingthat media effects may be weaker among the young because of their interestin ‘‘coproduction’’ (p. 717) of information, boredom with politics, lack ofuse of conventional media such as TV, and more ‘‘flexible identity forma-tions’’ (p. 716). They also said that senior citizens ‘‘may more resemblethe group membership mass audiences of an earlier era’’ (p. 723). However,these propositions about age have not been tested. If generational orlife-cycle effects rather than period effects are found to influence thetransfer of issue salience, age should be considered as another contingentcondition.
Research has explored age as a contingent condition of agenda setting, butthe function of age is not clearly explained yet. In the earliest study, youngerand older people were found to have increasingly similar issue agendas asboth groups read local newspapers more frequently (Shaw & Martin,1992). A study in Spain found a curvilinear relationship of attention to polit-ical information with consensus between younger people’s issue and attributeagendas and older people’s (Lopez-Escobar, Llamas, & McCombs, 1998).Wanta (1997) found that age’s effects on agenda setting were mediated bypolitical interest. Compared to younger generations, older people were morelikely to be influenced by agenda setting because they were more interested inpublic affairs and exposed to more news. However, a direct investigation ofage found that agenda setting occurred regardless of generational differencesin media use (Coleman &McCombs, 2007). There were no significant differ-ences in rank-order correlations of agendas among three different genera-tions. However, that study used only cross-sectional data; the lack ofeffects could be due to studying only a single point in time. This study directlyinvestigates the role played by age in the agenda-setting process in a longi-tudinal analysis, employing the theoretical framework of generational,life-cycle, and period effects.
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Effects of Age
People naturally change their perceptions of issues and their attitudes towardthem as they age, and this individual phenomenon inevitably plays an impor-tant role in society. Eisenstadt (1956) noted, ‘‘Age and differences of age areamong the most basic and crucial aspects of human life and determinants ofhuman destiny’’ (p. 21). This claim also should be applicable to research inpublic opinion and political behavior such as agenda setting.
The effects of age have three distinct elements: generational, life-cycle, andperiod effects (Glenn, 2005). The definition of a generation is ‘‘those personswho have been socialized in a similar fashion because of their exposure tothe same prevailing events’’ (Klecka, 1971, p. 358). Generational differencesfound in a cross-section can be affected both by exposure to historicalevents—a generation effect—and by changes in the processes and content ofsocialization as one ages—a life-cycle effect (Klecka, 1971). However, peoplein a specific period are often influenced by environmental factors regardless oftheir age. The period effect refers to this sort of phenomenon (Glenn, 2005).
Thus, effects of age on agenda setting can be conceptualized in three ways.If people have been exposed to different historical events, such as the firstlanding on the moon or the assassination of President John F. Kennedy, thatmay affect their judgment of issue importance for the rest of their life, and agenerational effect is evident. For example, Baby Boomers who experiencedthe turmoil of the Watergate scandal as young adults may be more likely toregard the functioning of government as more important than other genera-tions. On the other hand, if an individual’s location in his or her life spaninfluences agenda-setting effects, it can be considered a life-cycle effect. Forinstance, middle-aged people who are likely to have children in grade schoolmay be more prone to think of education as an important issue because theirage as young parents influences their perceptions. When these same peoplebecome seniors, however, health issues such as insurance and Medicare maybecome more important to them than education. This represents a life-cycleeffect of age on agenda setting. Both explanations also imply that differentialmedia use caused by generational and life-cycle factors has a significant impacton differences in agenda-setting effects. On the contrary, the period effect ofage does not have such an assumption, because the definition of period effectsis that environmental factors influence people in each period, regardless oftheir age. There is no room for differential media use in the concept of periodeffects. Note that influences associated with each particular period are concep-tualized as period effects (Wimmer & Dominick, 2006, p. 215).
In sum, if a generational effect is working, different generations mayattend to different sets of issues at any given cross-section of time, whichleads to a public agenda for their cohort. If the life-cycle effect is working,
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people reflect their changing interests by the location in their lifetime. Thismay result in longitudinal differences in the agenda for people as they age.Finally, if the period effect is working, there will be no differences eitherin cross-sectional or in longitudinal analyses. Rather, strong correlationsbetween the media and the public agenda are expected, regardless ofgenerations or age.
Age Breaks
Studies have used different age breaks to address their unique researchquestions. For instance, a study on the Vietnam War used the ‘‘Munichgeneration’’ to describe people who lived through the 1930s and rememberedtheMunich Conference of 1938 as a symbol of American isolationism, and the‘‘Vietnam generation’’ designating those who experienced the war in SoutheastAsia to investigate effects of age (Holsti & Rosenau, 1980). Recent researchoften has used a three-generation grouping of civic generation, baby boomers,and generation X (e.g., Shah, Kwak, & Holbert, 2001).
The present study employed the most widely used three-generation group-ing, designated the civic generation, baby boomers, and the youngest gener-ation, which incorporates both Gen X and Gen Y, following Coleman andMcCombs (2007). It also used a second different but related definition ofage groups, because the research questions require both cross-sectional andlongitudinal analysis. For cross-sectional analyses investigating the genera-tional effect, the generations are defined as those who are in the 18 to 34,35 to 54, and 55þ age cohorts for cross-sectional comparisons. For longitudi-nal analyses exploring the life-cycle effect, three groups are defined as thosewho were born between 1926 and 1945, between 1946 and 1964, and 1965 orafter. We call them the civic generation, baby boomers, and youngest gener-ation, respectively, as suggested in the literature (Coleman & McCombs,2007; Shah et al., 2001).
A generational effect on agenda setting proposes that generational differ-ences affecting media use eventually lead to a distinct agenda-setting effectamong generations. If a generation effect occurs, this study expects to findthat people in the 18-to-34 age group will say different issues are importantthan those in 35-to-54 or 55-and-up group. Drawing from this logic, differ-ential media use and political involvement among generations may lead tothe argument of weaker agenda-setting effects on the young (Chaffee &Metzger, 2001). The argument also should meet the assumption of a hetero-geneous agenda across media outlets (McCombs, 2005), specifically betweenthe Internet and traditional media. Adding to a vast collection of findingsof redundancy among traditional media (Reese & Danielian, 1989; Whitney& Becker, 1982), recent findings suggest homogeneous rather than
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heterogeneous agendas across online and offline media (B. Lee,Lancendorfer, & Lee, 2005; J. K. Lee, 2007; Maier, 2010; Roberts, Wanta,& Dzwo, 2002). Online agendas are similar across public affairs blogs regard-less of political ideology of content providers (J. K. Lee, 2007). Other studies(Vliegenthart & Walgrave, 2008; Wallsten, 2007) delved into the moderatingvariables, directions, and contingent conditions of intermedia agenda settingthat results in this homogeneity. The homogeneity of agendas suggests thatyounger generations’ agendas should be similar to those of older generations.Further, Coleman and McCombs (2007) recently found that rank-ordercorrelations between the media agenda and youngest generation’s agendawere strong. For these reasons, it is appropriate to predict that periodeffects rather than the generational effect is working, and that agendas willbe similar across age groups. Thus, we make this prediction:
H1: The issue agendas of people in the 55-and-up, 35-to-54, and 18-to-34age groups will positively correlate with one another in cross-sectionalcomparisons.
A person’s age, or location in his or her life span, also has been found toinfluence media use and political communication (Cutler & Danowski, 1980;Stephens, 1981). Concerning agenda setting, the life-cycle effect is based onthe assumption that people’s different situations in their life span, or indi-vidual age, affects their use of media, which leads to different perceptionsof issue importance by people of different ages. Although Coleman andMcCombs (2007) found a positive relationship between the media agendaand the youngest generation’s agenda, they did not investigate the possi-bility of a life-cycle effect. They surmised that slight differences in agendasbetween the youngest generation and the two older ones were based onlife-cycle differences, for example, that the youngest people were more inter-ested in education than health care because they or their children were morelikely to be in college or K-12 schools; however, the study did not intend tofind direct evidence of this. Thus, the existence of a life-cycle effect is testedin the present study.
The core argument for a life-cycle effect on agenda setting is based ondifferent media use by different ages. In other words, selective exposure tomedia messages will have more powerful effects on people’s perception ofissue importance than media’s blanket influence on them. However, withstable agendas between and within traditional and online media (J. K. Lee2007; Lim, 2006; Maier, 2010; Reese & Danielian, 1989; Roberts et al.,2002; Whitney & Becker, 1982), differential media use is not expected toaffect agenda setting. Since McCombs and Shaw’s (1972) initial study, mostagenda-setting literature has consistently rejected the influence of selective
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perception on the process of issue importance judgment (McCombs, 2004). Ifthis is true, a generation’s agendas through their life span should positivelycorrelate with each other. The stable agendas across life cycles will beevidence against the life-cycle effect. Thus we predict the following:
H2: The agendas of the civic generation, baby boomers, and youngestgeneration will positively correlate with their individual issue agendasin different years.
With media’s blanket effects in mind, we can argue for period effects inthe agenda-setting process. The agendas should correlate with the mediaagenda at different time points for all generations. The positive associationbetween the generation’s agenda and the media’s agenda at each comparisonwill serve as evidence for a period effect, regardless of their locations in lifecycles or of generational differences.
H3: The agendas of the civic generation, baby boomers, and youngestgeneration will positively correlate with the media agenda in each yearof comparison.
METHOD
This study used data from the American National Election Studies (ANES)from 1960 to 2004 to measure the public agenda. The test of generationaland life cycle effects on agenda setting requires comparisons of differentgenerations’ and ages’ agendas over a long period. Specifically, public opi-nion data from the civic generation, or those currently age 55 and older,(Shah et al., 2001) are necessary to compare agendas of that generation withtheir agendas at later points. ANES data are available from 1948, meetingthe conditions for this study.
To measure the media agenda, we used the New York Times Index dataprovided by Policy Agendas Project.1 The number of available years fromboth data sets totals 27. If correlation tests were conducted for all of the years,it may include many results significant only by chance, so we randomlysampled nine years of the 27 to reduce such risks. Considering the purpose
1The data used here were originally collected by Frank R. Baumgartner and Bryan D. Jones,
with the support of National Science Foundation grant number SBR 9320922, and were
distributed through the Department of Government at the University of Texas at Austin
and=or the Department of Political Science at Penn State University. Neither NSF nor the
original collectors of the data bear any responsibility for the analysis reported here.
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of this study, we made a condition that 1 or 2 years in each decade should beincluded. To verify the New York Times agenda as a representative of themedia agenda, we content analyzed the Washington Post and ran correlationanalysis between the New York Times and Washington Post. All of the ninecoefficients are positive, and seven are statistically significant, as reportedin Table 1. This shows that the New York Times agenda can represent themedia agenda to a significant extent. Results of the analysis are reported inthe Appendix. For the content analysis of the Washington Post, we usedtwo different databases of ProQuest and LexisNexis Academic. Three storiesper day were randomly selected in a given year and then coded by two humancoders. The total number of sample stories is 10,963, and intercoder reliabilitywas tested for 915 subsample stories. Scott’s Pi reliability coefficient was .85,which is acceptable in most standards (Riffe, Lacy, & Fico, 1998).
The main variables in this study are the public agendas of generationalsubgroups and the media agenda represented by the New York Times Index.Because our consistency check between the two showed high correlations,we used the New York Times Index as a proxy measure for mainstreammedia coverage, as has been done by others (Golan, 2006; Wallsten,2007). Because its coverage has served as a guide for what is important toother media outlets (Graber, 1997), both print and broadcast, it is appropri-ate to represent the media agenda.
For measurement of the agenda, we followed extant literature (McCombs& Shaw, 1972) using the ‘‘most important problem’’ questions.2 Followingagenda setting research (McCombs & Shaw, 1993), we conceptualized anagenda as a ranked list of issues based on frequencies of respondentsmentioning those issues.
2A typical wording of the most important problem question is, ‘‘What do you think is the
most important problem facing the country today?’’ There is much variation in most important
problem questions, suggesting the possibility of differing measurement of opinion. However, a
recent study found that there are strong correlations between agendas measured by various
forms of the most important problem question. See Min, Ghanem, and Evatt (2007).
TABLE 1
Correlations Between the New York Times and the Washington Post Agenda
1960 1968 1976 1980 1986 1990 1996 2000 2004
.52 .61 .81�� .83�� .71� .87�� .84�� .67� .74�
N 8 8 8 8 8 8 8 8 8
Note. N¼ number of issue categories.�p< .05 (one-tailed).��p< .01 (one-tailed).
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The most important problem question has been included in the ANESsince 1960, but the coding strategy of the open-ended question has changedslightly. The original number of issue categories was eight in 1960 but laterincreased to 11, excluding a category of nonpolitical problems. To addressthe overarching question in this study, comparisons of public agendas in dif-ferent years are necessary. For this reason, the number of categories wasadjusted to eight for all data sets from later years. ANES created a new issuecategory by dividing one into several. For instance, an original issue categoryof ‘‘racial and public order problems’’ in 1960 was later divided into ‘‘racialproblems’’ and ‘‘public order problems.’’ These two new categories werecombined back to the original category to compare agendas over time in thisstudy.3 On the media side, the Policy Agendas Project uses 27 different cate-gories of major topics in coding the Times stories. To compare the mediaagenda with the public agenda, we recoded major topics of the Times storiesfollowing ANES master code of the most important problem question. Forinstance, topics of macroeconomics and foreign trade were recoded intoeconomy. With the recoding process, we were able to measure the New YorkTimes agenda using eight issue categories. The use of eight issue categoriesalso more than covers the five to seven issues that the public agenda has beenfound to represent; there has been no significant increase in the number ofissues on the agenda over time, even with rising levels of education amongthe general public (McCombs & Zhu, 1995).
Analysis
Data analysis used the rank-order correlation of issue agenda, followingprevious agenda-setting literature (McCombs & Shaw, 1972). The studymeasured correlations between agendas of different generations with severalcross-sectional data sets for testing the generational effect hypotheses.Measurements followed extant literature (Coleman & McCombs, 2007;Shah et al., 2001) and used three generational categories: those who are inthe 18 to 34, 35 to 54, and 55þ age cohorts. This categorization was appliedto all cross-sectional analyses for clearer comparisons. In other words, threesubgroups were used in analysis of the 1960 survey as well as in that of the2004 survey.4
3The eight issue categories are social welfare, agriculture and natural resources, labor and
union-management relations, race and public order, economy, foreign affairs, national defense,
and functioning of the government.4Some studies used different age breaks in defining generational categories. We performed
the same analyses with 18 to 24, 25 to 34, 35 to 54, and 55þ age groups but found no signifi-
cantly different results.
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To test the generational effect hypothesis, rank-order correlation analyseswere performed for nine years, randomly sampled, from 1960 to 2004. Foreach year, the respondent sample was split into three generational groupsfollowing the previously described way of grouping, then rank-order corre-lation coefficients between the agendas of the three different generationswere calculated.
To test the life-cycle effect hypotheses, the issue agendas of three agegroups at certain years were compared with their own agendas in later timepoints. For example, the issue agendas of the civic generation in the 1960swere compared with their agendas in the 1970s, 1980s, 1990s, and 2000s.Standard cohort analysis compared the agendas of three age groups withtheir own issue agendas at different time points. For this analysis, membersof the civic generation are defined as those born between 1926 and 1945. Wecalculated correlations between agendas of the three generations and theNewYork Times agenda each year to see the correspondence between the mediaand the public agenda. For instance, the baby boomers’ agenda wascompared with the Times agenda in each year of 1968, 1972, 1976, 1980,1986, 1990, 1996, 2000, and 2004. Comparisons for older generations wereconducted for more years and younger generations for fewer years becauseof differences in length lived.
RESULTS
Table 2 illustrates the media agendas represented by the New York TimesIndex for 9 years from 1960 to 2004. Out of eight issue categories, economy,foreign affairs, and functioning of the government have consistently appearedin the top three spots. Economy was mentioned by the Timesmost frequentlyin all 9 years, except 1976 when it was mentioned second-most frequently. Theissue of foreign affairs was ranked second for 5 years, third for 3 years, andfourth for 1 year. Functioning of the government was the most frequentlycovered problem in 2 years, second in 1 year, and third in 4 years. Issuesother than these three appeared in the top three ranks only in 3 years.
The public agendas for the same years are shown in Table 3. Compared tothe media agenda, the public agenda captured by the ANES survey showsmore diversity in terms of most frequently mentioned issues. However, threeissues of foreign affairs, social welfare, and the economy are most likely toappear at the top three spots in the agendas. They were mentioned as the mostimportant problems in the ANES survey in 3 years. Further, at least two ofthe three issues appeared in the top three spots in the agenda in all years.
H1 predicted that the three generations’ agendas will be similar toeach other in a year. Correlation tests with cross-sectional data sets from
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TABLE2
AgendasoftheNew
York
Tim
esbyYear:Frequencies(andRanks)
1960
1968
1976
1980
1986
1990
1996
2000
2004
Economy
109(1)
165(1)
174(2)
225(1)
244(1)
229(1)
193(1)
282(1)
300(1)
Foreignaffairs
103(2)
97(3)
130(3)
74(3)
66(4)
69(2)
80(2)
129(2)
117(2)
Functioningofthegovernment
96(3)
165(1)
209(1)
137(2)
68(3)
30(6)
69(3)
109(3)
88(4)
Social
welfare
54(4)
84(4)
94(4)
50(7)
70(2)
55(3)
52(4)
76(4)
68(6)
Nationaldefense
52(5)
40(6)
40(7)
74(3)
44(6)
35(5)
11(7)
6(8)
97(3)
Racialandpublicorder
30(6)
83(5)
71(5)
58(6)
49(5)
54(4)
45(5)
63(5)
80(5)
Agriculture
&naturalresources
20(7)
23(7)
63(6)
60(5)
33(7)
26(7)
20(6)
25(6)
34(7)
Labor
13(8)
19(8)
22(8)
25(8)
12(8)
8(8)
9(8)
7(7)
26(8)
Total
476
724
803
668
586
506
479
697
799
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TABLE3
ThePublic
AgendasMeasuredin
ANESbyYear:Frequencies(andRanks)
1960
1968
1976
1980
1986
1990
1996
2000
2004
Foreignaffairs
592(1)
785(1)
61(5)
320(2)
279(4)
605(1)
21(5)
59(4)
271(2)
Social
welfare
155(2)
207(3)
606(2)
200(3)
555(1)
323(3)
294(1)
375(1)
75(4)
Economy
87(3)
102(4)
773(1)
626(1)
530(2)
447(2)
157(3)
133(3)
156(3)
Agriculture
&naturalresources
68(4)
17(6)
39(6)
34(5)
82(6)
120(5)
20(6)
23(7)
1(7)
Nationaldefense
66(5)
16(7)
28(7)
113(4)
279(4)
15(7)
15(7)
39(6)
26(6)
Racial&
publicorder
58(6)
449(2)
150(3)
18(7)
287(3)
213(4)
241(2)
192(2)
478(1)
Labor
23(7)
9(8)
8(8)
1(8)
2(8)
1(8)
0(8)
1(8)
0(8)
Functioningofgov’t
4(8)
27(5)
66(4)
33(6)
76(7)
49(6)
29(4)
45(5)
31(5)
Total
1,053
1,612
1,731
1,345
2,090
1,773
777
867
1,038
N(Survey
sample)
1,181
1,673
1,909
1,408
2,176
1,980
796
877
1,066
Note.Foreach
year,
thetotalnumber
ofmost
importantproblemsmentioned
by
survey
respondents
isdifferentbecause
mentionsof
non-politicalproblemsweretreatedasmissing.
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9 years found significant correlations among all three generations’agendas for all 9 years (Table 4). The correlation coefficients are positiveand very strong. The cross-sectional analysis generated three correlationcoefficients for each year. The range of the coefficients is from þ.80 toþ1.0, and the median value of the coefficients is þ.98. Out of a totalof 27 correlations, the number of coefficients larger than þ.90 is 19.Further, all of the coefficients are larger than þ.80. To test the genera-tional effect hypothesis on agenda setting, three subtests of age groupswere examined.
First, we looked at whether the rank order of the older generation’s agen-das was positively correlated with the middle-aged generation’s agendas atcross-sectional comparisons. All of the nine comparisons of the older genera-tion’s agendas with the middle-aged generation agendas are positive andstatistically significant. The median value is þ.98, for all nine correlations.Next, we examined the rank order of the middle-aged generation’s agendasto see if it had a positive correlation with the youngest generation’s agendasat cross-sectional comparisons. All of nine comparisons of the middle-agedgeneration’s agenda with the youngest generation’s agenda are positiveand statistically significant. The median value is þ.98, for all nine correla-tions. Finally, we analyzed the rank order of the older generation’s agendasto see if there was a positive correlation with the youngest generation’sagendas at cross-sectional comparisons. All of nine comparisons of the oldergeneration’s agenda with the youngest generation’s agenda are positive andstatistically significant. The median value is þ.99, for all nine correlations.This strongly supports H1.
H2 predicted that an age cohort’s agenda at one time point will be similarto that at other time points, regardless of the many changes that occur overthe age cohort’s life span. Further, H2 also predicted that an age group’sagenda will be positively associated with the media agenda at different timepoints. Correlations tests were conducted for the issue agendas of the civicgeneration, baby boomers, and youngest generation.
TABLE 4
Correlations between Agendas of Three Age Groups in Different Years
Year 1960 1968 1976 1980 1986 1990 1996 2000 2004
55þ with 35–54 .99�� .98�� .97�� .98�� .86�� .99�� .80�� .98�� .99��
55þ with 18–34 .83�� .88�� .99�� .98�� .88�� .99�� .80�� .98�� .98��
35–54 with 18–34 .85�� .91�� .95�� 1.0�� .98�� 1.0�� 1.0�� 1.0�� .99��
N 8 8 8 8 8 8 8 8 8
��p< .01 (1-tailed); �p< .05 (1-tailed).
N¼number of issue categories.
16 LEE AND COLEMAN
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For the test of H2, the issue agendas of each age cohort in earlier yearswere compared with the issue agendas of its own agendas in different years.Correlation test analyses for the civic generation were conducted for eight datasets from 1968 to 2004. Because members of the cohort age range from 23 to42 in 1968, their issue agendas were captured in 1968 and can be comparedwith their agendas in the 1970s, 1980s, 1990s, and 2000s. The tests for babyboomers were performed for nine data sets from 1968 to 2004. The analysesfor the youngest generation were executed for five data sets from 1986 to2004. Members of the cohort age 21 or younger in 1986, so their issue agendascan be measured and compared with their agendas in the 1990s and 2000s.
H2 addresses correspondence of agendas of each age group with their ownagendas at different time points. Table 5 shows the correlation coefficientsgenerated in the relating analyses. To break down the results, we examinedthe agendas of the civic generation for positive correlations with that ofpeople 55 and older in different years. The left hand side section of Table 5reports all 28 Spearman’s rho correlation coefficients of longitudinal com-parisons of the 55þ-year-olds’ agendas for nine data sets from the 1968 to2004 elections. Out of the comparisons, all are positive, and 23 are statisti-cally significant. The median value is þ.78. The last row in Table 5 illustratesthe comparisons of the 1968 agenda of the civic generation with their agendasin later years. Eight of the nine coefficients generated in the analysis arestatistically significant and positive. The median value is þ.79, for all ninecomparisons.
We also examined the rank order of baby boomers’ agendas with theirown agendas in earlier years. In its middle section, Table 5 also reports allSpearman’s rho correlation coefficients of longitudinal comparisons of babyboomers’ agendas for nine data sets from 1968 to 2004. All 28 coefficients arepositive. Out of these, 11 are statistically significant. The median value isþ.54. As found in Table 5, the baby boomers’ agenda in 1968 correlates onlywith the 2000 and 2004 agenda. The results indicated that the life-cycle effectinfluenced the agenda-setting process for baby boomers.
Finally, we looked at the rank order of the agenda of the youngest gener-ation for correlations with their own agendas in other years. The right handside section of Table 5 reports all 10 Spearman’s rho correlation coefficientsof longitudinal comparisons of the youngest generation’s agendas for fivedata sets from the 1986 to 2004 elections. First, all coefficients are positive.Out of the 10 comparisons, seven are statistically significant. The medianvalue is þ.73. Further, the last row in the section of Table 5 illustrates thecomparisons of the 1986 agenda of the youngest generation with their agen-das in later years. Three of the four coefficients generated in the analysis arestatistically significant and positive. The median value is þ.76, for all fourcomparisons.
AGE AND AGENDA SETTING 17
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TABLE5
CorrelationsBetweentheDifferentYears’AgendasofThreeGenerations
Thecivicgeneration
Babyboomers
Youngest
generation
2004
2000
1996
1990
1986
1980
1976
2004
2000
1996
1990
1986
1980
1976
2004
2000
1996
1990
2000
.80��
.81��
.80��
1996
.83��
.98��
.55
.88��
.34
.74�
1990
.81��
.71�
.76�
.33
.45
.50
.77�
.71�
.33
1986
.64�
.81��
.76�
.79�
.62
.81��
.64�
.45
.72�
.86��
.59
.80��
1980
.37
.50
.45
.74�
.88��
.45
.45
.26
.12
.67�
1976
.73�
.86��
.91��
.74�
.81��
.55
.64�
.88��
.91��
.52
.71�
.52
1968
.95��
.79�
.81��
.83��
.64�
.41
.64�
.93��
.76�
.42
.27
.59
.49
.49
N8
88
88
88
88
88
88
88
8
Note.N
¼number
ofissuecategories.
� p<.05(one-tailed).
��p<.01(one-tailed).
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For the test of H3, three age groups’ agendas were compared with theNewYork Times agendas in different years. Correlations between the mediaagenda and the agendas of the three generations were calculated in nine dif-ferent years from 1968 to 2004 for the civic generation and for baby boomers,and in five from 1986 to 2004 for the youngest generation. All correlationcoefficients were positive and generally were statistically significant, exceptfor baby boomers. Findings are reported in Table 6.
To break down the results, we examined the agenda of the civic generationeach year to see how it correlates with the media agenda of that year. The firstrow of Table 6 shows the nine comparisons between the Times agenda andthe civic generation’s agenda from 1968 to 2004. All of the coefficients arepositive. Five of the nine coefficients generated in the analysis are statisticallysignificant. The median value is þ.68, for all comparisons.
Next, we examined the rank order of the baby boomers’ agenda with themedia agenda in a given year. The second row of Table 6 reports the ninecomparisons between the baby boomers’ agenda and the New York Timesagenda from 1968 to 2004. Out of the nine comparisons, four are statisticallysignificant. The median value of the coefficients is þ.57.
Finally, we looked at the agenda of the youngest generation to see itscorrelation with the media agenda in a given year. The third row of Table 6illustrates the five correlations between the Times agenda and the youngage group’s agenda. All of the five coefficients are positive. Three of thecoefficients are statistically significant. The median value is þ.74.
DISCUSSION
This study tests three possible effects of age on the agenda-setting processand found evidence generally supporting the period effect hypothesis. Unlikegenerational and life-cycle effects, the period effect represents the blanketinfluence of the media and thus predicts a relative homogeneity between
TABLE 6
Correlations Between the New York Times and Agendas of Three Generations in Each Year
2004 2000 1996 1990 1986 1980 1976 1972 1968
The civic generation .68� .45 .62 .91�� .83�� .52 .71� .67� .42
Baby boomers .74� .57 .52 .36 .74� .52 .74� .76� .23
Youngest generation .74� .57 .26 .87�� .74�
N 8 8 8 8 8 8 8 8 8
Note. N ¼number of issue categories.�p< .05 (one-tailed).��p< .01 (one-tailed).
AGE AND AGENDA SETTING 19
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agendas, of generations, and through a life cycle. Findings indicated that agein general does not influence the agenda-setting process, despite some strongsigns of life-cycle effects for baby boomers.
Three generations of oldest, middle-aged, and youngest cohorts con-sidered as important almost the same issues as the other generations in 9years of comparisons, from 1960 to 2004. In 27 comparisons among agendasof the three generations, the median correlation is þ.98, supporting thehypothesis that people have very similar issue priorities regardless of theirgeneration. This is evidence against the existence of a generational effecton agenda setting, supporting the results of the other study to directly inves-tigate this (Coleman & McCombs, 2007).
This study also found some evidence against the existence of a life-cycleeffect. Two of three generations were very similar along different locationsin their life span. The agenda of the civic generation and the youngest gener-ation did not change much as its members became older. In 28 longitudinalcomparisons of the civic generation agendas, the median value of the correla-tions is þ.78. The generation had significant and strong correlations on theissues in 23 of 28 pairwise year comparisons. Similar results were found forthe youngest generation—seven out of 10 pairwise year comparisons weresignificant with a median correlation of þ.73. However, baby boomersshowed differences within their generation across the years—in 28 pairwiseyear comparisons only 11 reached traditional significance levels and themedian value of correlations was .54. Overall, correlation coefficients in theseanalyses were significant and positive. These findings are support for thehypothesis that people’s agendas are stable across their life span and corre-lated with the media agenda. The evidence works against the argument ofa life-cycle effect on agenda setting, except for baby boomers.
The test of the period effect hypothesis (H3) showed very similar pattern tothat of the life-cycle effect hypothesis test. The agendas of the civic generationand the youngest generation were found to be very close to the New YorkTimes agenda in each year. In nine comparisons between the civic generationand theTimes agenda, five were significant with a median correlation ofþ.67.For the youngest generation, three correlations out of five comparisons weresignificant with a median value of þ.74. However, the results regarding babyboomers showed a different picture. In nine comparisons, only four correla-tions reached the traditional level of statistical significance and the medianvalue was þ.57. The period effect was observed for the civic generationand youngest generation, but it was much more limited for baby boomers.
It should be noted that only some of the baby boomers were included inthe analysis in 1968, 1972, and 1976, because the entire generation was notold enough for survey. The youngest generation has the same issue for 1986.The findings should be interpreted with this in mind.
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One of the limitations of this study is that it does not have separate contentanalyses for print, television, and the Internet. Unlike legacy media, there isno source such as the New York Times Index that collects content from newswebsites, making it impossible to conduct a content analysis of news websites retroactively. Instead, we rely on the findings of others showing thehomogeneity of the media agenda online and offline. For example, Maier(2010) found that 60% of the top news stories on five prominent news websites in 2008 and 2009 were covered the same in the traditional media.Numerous other studies (J. K. Lee, 2007; Lim, 2006; Reese & Danielian,1989; Roberts et al., 2002; Whitney & Becker, 1982) show a homogeneousagenda between new and old media, including television and blogs (for ameta-analysis, see Tran, in press). Although it would be ideal to have a con-tent analysis for online news, previous research gives us confidence that thislimitation does not invalidate the findings of this study.
CONCLUSION
From the findings, we can conclude that there is no generational effect ofage in the agenda-setting process. However, results of the life-cycle andthe period effect hypothesis are mixed due to distinct patterns of the babyboomers. It is notable that baby boomers showed such different patternsfrom other generations in both cases of the life-cycle and the period effect.We did not theorize the roles played by specific generations and thus cannotprovide explanations for such patterns of the baby boomers. The question isbeyond the scope of this study. Future research should address the problem.However, it is interesting to note that it is not the younger generation, whichscholars have speculated most about, but the baby boomers that showdifferences in agenda-setting effects.
Easterlin (1987) proposed the most comprehensive explanation of the babyboom phenomenon, which says that the size of one’s birth cohort is a majorinfluence on one’s life because of its impact on the social and economic climateof society. Much research has been done on the baby boomers, and the generalconclusion is that they are, in fact, different (Whitbourne &Willis, 2006). Theyby and large grew up in suburbs with modern amenities, demanded con-venience products such as prepackaged foods to save time and work, have beentrendsetters on many fronts including their active lifestyles, and are expected towork longer than their predecessors. The boomer generation has beencharacterized as one of consumption and personal gratification (Thornhill &Martin, 2007). But no definitive findings can explain why the boomers wouldshow such differences in their own issue agendas at different times in their liveswhen others do not, or a much more limited effect of the media on their issue
AGE AND AGENDA SETTING 21
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agendas compared with others. Researchers have found evidence confirmingthe boomer’s reputation as the ‘‘me generation’’ but that as they age they havedeveloped social consciences and a greater feeling of connection to others(Whitbourne, Sayer, & Sneed, 2009). They showed an increasing sense of con-nection after the important social movements of their times that may havehelped them become less concerned with themselves. They were shaped byReagan-era social values and responded by working hard and making money.Discovering that something wasmissing, they embraced the volunteerism of theClinton years, developing real concerns for society’s well-being (Whitbourneet al., 2009). Perhaps these wholesale changes have made them more open tonew ideas and less resistant to change, helping to explain our findings thatshow boomers are more likely to change their own agendas over time.
The baby boomers are also the group best known for questioning auth-ority and challenging the status quo, leading to a crumbling social orderfrom the civil rights movement, hippie era, and Vietnam War. Boomers wereinstrumental in vast changes in the social order, and eventually returned toconservative and traditional values (Whitbourne et al., 2009). This alsosupports our speculations.
In addition, baby boomers are healthier, are better educated, and havemore disposable income than other generations (Whitbourne & Willis,2006). Perhaps the ability to think critically and be stable and confidentin their physical and economic situation can explain some of the boomers’independence from the media’s influence and even their own previousattitudes.
Although it appears to speak to a generational effect more so than thelife-cycle and limited period effects found here, the historical events of thebaby boomers’ generation also could offer explanations; they have livedthrough space exploration, racial tensions, the peace movement, VietnamWar, and times torn by different views on politics, war, and social justice.They’ve seen problems run the gamut in their lives; what was importantone day may not have been the next because some new pressing problem tookits place. Dramatic shifts in important issues are the norm for this group, andthat could help explain the shifts in issues of importance across their lives.Also, it is not clear that the difference found in their agendas originated inthe life-cycle effect or in a generation effect, because of the limitations ofour data. Nevertheless, this cohort still has many years to live; it is possiblethat the baby boomers’ agendas will show more similarity to their agendas ofthe past and to the media agenda in years to come. If that is the case, the pat-terns of the baby boomers are likely to resemble those of the civic generationalong the entire life span of the cohort. Social psychological research shouldbe examined for possible hints to these effects and then studies should bedesigned to test them in order to better understand the results of this study.
22 LEE AND COLEMAN
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This study has examined three different age groups at different times foragenda-setting effects; the next step would be to also examine the differentgroups living in specific time frames that are common to all to see whatagenda-setting effects there are among different age groups living in thesame era and experiencing the same issues.5
Despite the obvious assertion that age is one of the most crucial aspectsof human life (Eisenstadt, 1956), and the evidence of age differences in manyareas—ideology; civic engagement; attention to, knowledge of, and interestin politics, among others—that does not directly translate into an age effecton agenda setting. Age does not appear to be a clear contingent condition ofagenda setting, despite the intuitive and oft-proposed argument of weakeragenda-setting effects on the young. What small differences do exist, suchas young people placing more importance on education than the mediaand other age groups, can be better explained by personal relevance andobtrusiveness of issues—two well-established contingent conditions ofagenda setting. However, there is some sign of the life-cycle effect in the caseof baby boomers. Future research should address whether the baby boom-ers’ case is unique to the generation or if it can be generalized to other agegroups as a contingent condition.
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