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FIRST CLASS
APR21'97
0.78
MICH
6840970
8L
FROM L R HUESMANN THE UNIVERSITY OF MICHIGAN
PROJECT NO.
INSTITUTE FOR SOCIAL RESEARCH
481480
ISR
SURVEY RESEARCH CENTER
RESEARCH CENTER FOR GROUP DYNAMICS
CENTER FOR POLITICAL STUDIES
426 THOMPSON STREET
BOX 1248, ANN ARBOR, MICHIGAN 48106-1248
X
FIRST CLASS/PRIORITY
AIR MAIL BOOK RATE
THIRD CLASS/FOURTH CLASS
AIRMAIL PRINTED MATTER
LIBRARY RATE
AIR MAIL
BOOK RATE
TO
MS JENNIFER KLEIN
SECOND FLOOR WEST WING
313-764-3409
THE WHITE HOUSE
WASHINGTON D C 20502
313-647-3662
PHOTOCOPY
PRESERVATION
PHOTOCOPY
PRESERVATION
INSPECTED
BY USSS
X-RAY
Rough TV tied to
real-life violence
Kids' viewing affects adult behavior
By Marilyn Elias
17% of the other women had.
USA TODAY
In the previous five
years, adult women who fa-
The more violent TV shows
vored aggressive shows had
watched in childhood, the
physically attacked a friend
more aggressive adults may
or close relative twice as of-
be by their early 20s, suggests
ten as women least exposed
a new 15-year study of Gener-
to violent TV as children.
ation X kids.
Men watching the most
"Serious adult aggression
violent shows had about twice
is influenced by what chil-
as many moving traffic viola-
dren watch in the mass me-
tions in the last five years as
dia," says University of Mich-
those seeing the least violent
igan psychologist Rowell
TV as kids.
Huesmann. Starting in the
Huesmann adjusted for
'70s, his study tracked 331
each child's intellectual func-
Chicago children from age 6
tioning, aggression level in
to 8 until their 20s. Research-
childhood and parents' socio-
ers surveyed their TV prefer-
economic status - all known
ences and how much time
to influence adult violence
they spent watching shows.
levels. The link between
Asked to name their eight
watching violent TV shows in
favorite programs, children
childhood and adult aggres-
in the top 25% for violence
sion remained statistically
exposure were those who fa-
significant, he says.
vored programs rated high in
But ABC-TV spokeswoman
violent acts, and they
Julie Hoover challenged the
watched these shows always
alleged link: "If somebody
or often. The bottom 25% of
emerges as a young adult
violence-exposed youngsters
with truly antisocial tenden-
seldom or never watched
cies, to blame it on television
more aggressive shows.
is SO facile.
You can be
Kids in the top and bottom
darn sure these kids also
25% for violence exposure
were watching more violent
had different aggression lev-
movies, they're hanging out
els as adults in their 20s:
with more violent friends and
44% of men in the high-
they have less impulse con-
watching group said they'd
trol.
Genetics definitely
pushed, grabbed or shoved
plays a role too."
wives in the last year VS. 21%
The new TV ratings system
of low watchers; 12% of high-
"permits parents to screen
viewing men had hit spouses
out programs inappropriate
VS. 3% of those who seldom
for children," adds Dennis
watched such shows.
Wharton of the National Asso-
For women, 37% of fre-
ciation of Broadcasters. "Re-
quent violence viewers had
sponsible parenting is the key
thrown something at mates;
to rearing healthy children."
April 1, 1997
Longitudinal Relations between Early Exposure to Television Violence and
Young Adult Aggression: 1977-1992
Rowell Huesmann, Jessica Moise, Cheryl-Lynn Podolski and Leonard Eron
The University of Michigan
Paper presented at the meetings of the Society for Research on Child Development, Washington, DC,
April 1997. Darren Loomer assisted greatly in the analyses for this paper. Requests for reprints
should be sent to Rowell Huesmann, Research Center for Group Dynamics, Institute for Social
Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI, 48106-1248. Tel: 313-647-
3662, Fax: 313-763-1202, E-mail: [email protected]
Acknowledgements for
Television and Aggression Project
Len Eron
Kirsti Lagerspetz (Finland)
Monroe Lefkowitz
Vappu Viemero (Finland)
Leopold Walder
Adam Fraczek (Poland)
Peter Sheehan (Australia)
Riva Bachrach (Israel)
Simha Landau (Israel)
Drew Battiger
Rebecca Mermelstein (70s)
Jennifer Blom
Laurie Miller
Pat Brice (70s)
Jessica Moise
Marla Commons
Patty Mullally
Vicki Crawshaw
Cheryl-Lynn Podolski
Julie Crews
Richard Romanoff (70s)
Eric Dubow (70s)
Erica Rosenfeld (70s)
Paulette Fischer (70s)
Pam Sama
Kathryn Foley
Evelyn Seebauer (70s)
Janet Garcia (70s)
Jean Shin
Nancy Guerra
Jane Swanson
Sheree Hemphill
David Tulsky (70s)
Gary Hudson (70s)
Linda White (70s)
Rosmary Klein-Smith (70s)
Joe Wisler
Debbie Kopp
Patty Yarmel (70s)
Darren Loomer
Amaldo Zelli
Cathy McGuire
Lara Zuckert
Megan Malecek
The University of Illinois at Chicago
2
Over the past 40 years a body of literature has emerged which strongly supports the notion
that media violence viewing is one factor contributing to the development of aggression. The
majority of studies have focused on the effects of watching dramatic violence on television and film.
Experimental studies, static observational studies, longitudinal studies and meta-analyses all indicate
that exposure to dramatic violence on television and in the movies is related to violent behavior
(Huesmann & Miller, 1994; Huesmann, Moise & Podolski, in press). In contrived experimental
studies, children (both boys and girls) exposed to violent behavior on film or television behave more
aggressively immediately afterwards. Large numbers of laboratory and field experiments have
demonstrated this fact (see reviews by Comstock, 1980; Geen, 1983, 1990; Geen and Thomas,
1986). The typical paradigm is that randomly selected children who are shown either a violent or
non-violent short film are observed as they play with each other or with objects such as "Bobo" dolls
(Bandura, Ross, & Ross, 1961, 1963a, 1963b). The consistent finding is that children who see the
violent film clip behave more aggressively immediately afterwards. Just as children learn cognitive
and social skills from watching people act out cognitive social skills, they learn violent behaviors
from watching other people behave violently. Such results have been obtained both for aggression
directed at inanimate objects (e.g., "Bobo" dolls) and for aggression directed at peers (Bjorkqvist,
1985; Josephson, 1987).
The demonstration of a relation between the observation of dramatic television/film violence
and the commission of aggressive behavior has not been limited to the laboratory. Evidence from
field studies over the past 20 years has led most reviewers to conclude that a child's current
aggressiveness and the amount of television and film violence the child is regularly watching are
positively related to some degree. Children who watch more violence on television and in the
movies behave more violently and express beliefs more accepting of aggressive behavior (see
reviews by Andison, 1977; Chaffee, 1972; Comstock, 1980; Eysenck & Nias, 1978; Hearold, 1979;
Huesmann, 1982; Huesmann & Miller, 1994; Paik & Comstock, 1994; Wood, Wong & Chachere,
1991). Clearly, this relation is robust, though the effect size is not large by standards used in the
measurement of intellectual abilities, and varies as a function of environmental, familial, cognitive,
and television programming variables. However, the relation is usually statistically significant and is
substantial by the standards of personality measurements with children. Correlations of the
magnitude usually obtained in the field can have real social significance (Rosenthal, 1986).
Moreover, the relation is highly replicable even across researchers who disagree about the reasons
(e.g., Huesmann, Lagerspetz, & Eron, 1984; Milavsky, Kessler, Stipp, & Rubens, 1982) and across
countries (Huesmann & Eron, 1986).
Many of these early field studies only studied boys. Of those pre-1970 investigations that
studied both genders, most reported finding significant relations between actual violence viewing and
aggression among young girls as well as boys (e.g. Chaffee, 1972), but no study reported significant
relations between a preference for violence viewing and aggressive behavior among girls. For
example, Eron, Huesmann, Lefkowitz, & Walder (1972) report a significant correlation of .21 for a
sample of 211 3rd grade boys in 1960 but a correlation of only .02 for a comparable sample of 216
girls. It may be that during the 1960s girls' preferences for TV shows were influenced by gender
stereotypes; so that girls who watched more violent programs still 'preferred' other programs.
While these one-shot field studies showing a correlation between media violence viewing and
aggression suggest that the causal conclusions of the experimental studies may well generalize to the
real world, longitudinal studies can test the plausibility of causal hypotheses more directly. The data
available from the few existing longitudinal studies, in fact, do provide additional support for the
hypothesis that television violence viewing leads to the development of aggressive behavior. These
longitudinal studies have employed a wide range of samples and methodologies, but all of the studies
3
done with children seem to reveal long term effects of exposure to television violence.
In perhaps the first longitudinal study on this topic, initiated in 1960 on 870 youth in New
York State, this research team found that a boy's early childhood viewing of violence on TV was
statistically related to his aggressive and antisocial behavior ten years later (after graduating from
high school), even controlling for initial aggressiveness, social class, education, and other relevant
variables (Eron et al., 1972; Lefkowitz, Eron, Walder, and Huesmann, 1977). Structural modeling
analyses suggested that the most plausible model was that early exposure to media violence was
stimulating later aggression. A 22-year follow-up of these same boys revealed that their early
violence viewing also was weakly related to their adult criminality at age 30 (Huesmann, 1986;
Huesmann, 1995). Consistent with the outcomes reported above for other early field studies of
children growing up in the early 60's, these longitudinal results were obtained only for boys. No
longitudinal relation between aggression and media violence viewing was found for girls.
A more representative longitudinal study was initiated by Huesmann and his colleagues in
1977 (Huesmann & Eron, 1986; Huesmann, Lagerspetz, & Eron, 1984). This three-year longitudinal
study of children in five countries revealed that the television habits of children as young as first-
graders also predicted subsequent childhood aggression even controlling for initial level of
aggression. In contrast to earlier longitudinal studies, this effect was obtained for both boys and girls
even in countries without large amounts of violent programming such as Israel, Finland, and Poland
(Huesmann & Eron, 1986). In most countries the more aggressive children also watched more
television, preferred more violent programs, identified more with aggressive characters, and perceived
television violence as more like real life than did the less aggressive children. The combination of
extensive exposure to violence coupled with identification with aggressive characters was a
particularly potent predictor of subsequent aggression for many children. A field experiment
conducted as part of this study also provided evidence that normative beliefs about what kinds of
behaviors are acceptable can moderate the effect of observational learning. In this field experiment
aggression in a randomly-selected experimental group of third-graders was reduced relative to a
control group by changing their attitudes about the acceptability of the violence shown on television
(Huesmann, Eron, Klein, Brice, & Fischer, 1983).
A few longitudinal studies have seemed to produce results at variance with the thesis that
media violence causes aggression, but closer inspection of most of these studies reveals that their
results are not discrepant, but simply not strongly supportive of the thesis. (For a review, see
Huesmann & Miller, 1994). For example, while NBC's longitudinal study of middle-childhood
youth conducted in the 1970's (Milavsky et al., 1982) only reports significant regression coefficients
for 2 out of the 15 critical tests of the causal theory for boys, an additional 10 are in the predicted
direction. Furthermore, for girls 3 out of the 15 critical tests were significant and an additional 7
were in the predicted direction.
What mediates these longitudinal effects? The most common explanation is that aggressive
habits develop early in life and once these habits become firmly established they are resistant to
change. The more aggressive child is likely to become the more aggressive adult (Huesmann et al,
1984; Olweus, 1979); so whatever influences childhood aggression is likely to be related to adult
aggression through this continuity of aggression over time. Huesmann (1986) and others (Berkowitz,
1993; Dodge, Pettit, Bates, & Valente, 1995) have suggested that cognitions that develop early in life
influence social information processing in later life. As a result cognitions about what is appropriate
social behavior that are acquired through observing the mass media or by observing other people
may also contribute to the longitudinal effect.
There is also evidence that a variety of individual factors and media format factors may
exacerbate or mitigate the effect. Dorr & Kovaric (1980) and others have suggested that the effect is
4
strongest for children predisposed to behave aggressively, though Huesmann (Eron et al, 1972;
Huesmann et al., 1984) has argued that the effect is detectable even among relatively non-aggressive
children. Bandura (1969), Huesmann and Eron (1986; Huesmann, 1986), and others have also
suggested that identification with the aggressive character in a violent scene and perceiving the
violence as realistic are important moderators of the effects. That is, the more a child identifies with
a model (eg. television characters), the more likely it is that the child will be influenced by the
model. Likewise, the more realistic a child perceives the televised violence to be, the more likely it
is that the child will be influenced by the violence (Huesmann & Eron, 1986).
In summary, it seems clear that exposure to more media violence in childhood is correlated
with more aggressive behavior, and, at least in childhood, exposure to media violence seems to be
stimulating an increase in aggressive behavior over time for many children regardless of initial
aggressiveness. A number of theories suggest that this effect should extend into adulthood, though
how strong the effect should be is difficult to estimate. It is one goal of the current study to provide
a better estimate of the size of that effect.
Gender Differences
As the above review indicates, over the past several decades the relation between television
violence viewing and aggression has been unambiguously demonstrated. However, the extent of
gender differences in this relation has varied. A major meta-analysis aggregating data over the past
40 years concluded that the effects are slightly weaker for females than males (Paik & Comstock,
1994). However, the strength of the gender differences seems to have changed over time.
Laboratory studies since the early 1960's have consistently shown short term effects for boys and
girls. In contrast the early field studies of children growing up in the 1960's and the longitudinal
studies following children growing up in the 1960's showed relations for boys between media
violence and aggression that suggested causation but did not show any correlations for girls. But
more recent survey studies of children and longitudinal studies of childhood years have shown effects
for girls that are as strong as the relations for boys. No recent study has followed girls into young
adulthood; so it has been difficult to know if the longitudinal effects from childhood to adulthood
found earlier for boys now obtain for girls as well.
One possibility is that the change in social norms for appropriate female behavior that
occurred with the feminist movement of the late 1960's and 1970's has disinhibited female
aggression. In addition, the increase in aggressive female models in movies and TV would
theoretically engender a stronger observational learning effect. The combination of these two factors
may have lead to an increase in the size of the effect making detection easier. It is not that girls
were not subject to the observational effect in earlier years. They were as the laboratory experiments
showed. Rather it is that their use of the learned aggressive behaviors or aggressive scripts was
inhibited by their existing normative beliefs about appropriate female roles. This explanation is
consistent with the information processing perspectives on learning aggressive behavior that
Huesmann (1986; 1988, in press) and Dodge (1980) have offered. According to Huesmann's model,
learned scripts for aggressive behavior are not followed if they violate the individual's normative
beliefs about what is appropriate for them. If this explanation is true, then given the continuing trend
in changing social norms, it is clear that girls growing up in the 1970's who are now young women
should evidence longitudinal effects from childhood to young adulthood that are just about as strong
as boys. Therefore, a second goal of this study is to investigate if there now is a relation for females
between media violence viewing in childhood and aggression in young adulthood.
Both of these goals -- 1) examining the extent to which early childhood exposure to media
violence relates to adult aggression, and 2) examining gender differences in this effect -- will be
addressed by examining the data collected in a follow-up study of 21- to 25-year-olds who grew up
5
in the USA in the 1970's who were originally studied by Huesmann and Eron's (1986) in 1977.
Method
Subjects and Procedure
The subjects for this study constituted the follow-up sample of a longitudinal study on
television and behavior which began in 1977 (Huesmann & Eron, 1986). The longitudinal design is
summarized in Table
Insert Table 1 about here
In the original study 563 1st and 3rd graders from public schools in Oak Park, Illinois and
two parochial schools in Chicago, Illinois were tested and interviewed twice, in the spring of their
1st and 2nd grade years (younger cohort) or in the spring of their 3rd and 4th grade years (older
cohort). The children were interviewed in their classrooms and peer-nomination measures were
obtained about observed behaviors including aggression. The children's scores over the two year
period were averaged to provide more accurate single estimates of their TV viewing habits and
aggressive behaviors during that period. In addition, most parents were interviewed once during this
two year period, and achievement data on the older children were obtained from school records. The
exact procedures for subject selection and testing are described in Huesmann & Eron (1986).
Essentially all 1st and 3rd graders in Oak Park and all 1st and 3rd graders in the two Chicago
schools formed the pool from which subjects were recruited. We obtained permission from 758
children or about 76% of the eligible children, and collected the initial two years of data on 563 or
about 74% of the subjects.
Both the children and parents were then interviewed again in 1979 in the spring of the
younger cohort's 3rd grade year and the older cohort's 5th grade year. At that time 505 children
were reinterviewed, and their scores on peer-nominated aggression at that time served as a criterion
measure for the longitudinal analyses of childhood effects reported in Huesmann & Eron (1986) and
Huesmann, Lagerspetz, & Eron (1984) and summarized above.
Twelve years later, beginning in 1991, subjects were recontacted over the phone. Those
subjects who were living in the Chicago area were asked to come to the University of Illinois,
Chicago to complete the interview. Subjects sat a computer terminal and completed the
questionnaire. In addition, subjects were asked to give the name of their three closest friends who
were not family members and to rate how well that person knew the subject. The one with the
highest rating was then contacted (if the subject gave us permission to contact the person) and asked
to come in for an interview. The "second" person also completed a computer assisted interview.
Subjects were paid $50 to complete the 3 to 4 hour interview and the "second" persons were paid
$30 for completing a 1 to 1.5 hour interview.
At the point when no additional subjects could be located who were available to do the
interview in-person in Chicago the questionnaire was converted into a combination phone and mail
interview. In this version subjects were again contacted initially by phone and asked to participate.
If they agreed, a short 20-30 minute interview was conducted on the phone and the remainder of the
interview was sent to the person. During the phone interview the subject was again asked to give the
name of their three closest friends who are not family members and to rate how well that person
knows the subjects. As with the Chicago subjects we contacted the friend with the highest rating (if
the subject gave us permission to contact the person) and asked if they would be willing to
participate in our study. If they agreed, they were sent a mail interview. Subjects and "second"
persons who participated by phone and mail were paid the same amount for their participation as
6
those who completed the in-person interview.
Using these procedures, we were able to reinterview a total of 398 subjects -- 299 through
personal interviews and 99 through phone mail interviews. In addition, we obtained a total of 356
"second" person interviews -- 181 in-person and 175 mail interviews, and we collected archival data
on 554 of our original subjects. However, of the 398 reinterviewed subjects, only 331 had
provided complete data during the first two waves of the study. Thus our final longitudinal sample
size, as shown in Table 1, was 331 -- 153 males and 178 females -- or almost 60% of the original
Wave 1-2 sample.
At the time of the follow-up the subjects ranged in age from 20 to 25 years old with a mean
age of 22 years old. The lag since their initial 1st or 3rd grade interview ranged from 15 to 18
years. The reinterviewed sample is split fairly evenly by gender with 191 males and 207 females.
While the majority of the reinterviewed sample is white about 7.5% are minorities and 23% are of
unknown race. At the time of the interview the subject's level of education ranged from having
completed 9th grade to having completed a graduate or profession degree with the average education
level attained being having completed some college. Finally, in terms of SES, the reinterviewed
sample is somewhat skewed toward the high end of the scale as measured by the Hollingshead status
rating of the subject's father's most recent education with 65.3% having high status jobs, 26.9%
having medium status jobs, 5.8% having low status jobs, and 2% having jobs with an unknown
status.
One additional question of importance is how do the subjects we have resampled differ from
those we have lost over 15 years? We can compare the two groups on their Wave 1-2 measures. As
expected, and as illustrated in Figure 1, the resampled subjects were less aggressive, higher
achieving, and of higher socio-economic status than those we lost. This is a typical pattern for
longitudinal studies of antisocial and aggressive behavior. The more aggressive and antisocial
subjects are underrepresented in the reinterview. Nevertheless, the reinterview process has not
truncated the distribution of aggression though the range is somewhat reduced. Given these kinds of
resampling differences, we must be somewhat judicious in not underestimating effects due to the loss
of more aggressive subjects, but the distribution is not likely to bias us toward detecting effects that
are not there.
Child Measures
The key child measures are listed in Table 2 with their reliability coefficients. Details of
these measures and the procedures of administering these measures have been published in
Huesmann, Lagerspetz and Eron (1984) and Huesmann and Eron (1986) and will only be
summarized below. One-month test-retest reliabilities were based on the analysis of a subset of 93
children who were retested one-month after their initial interviews.
Insert Table 2 about here
Childhood Television Violence Viewing. Each year children were presented with 8 lists of 10
television programs each and asked to mark their favorite program on each list and how often they
watched it -- "every time it's on," "a lot, but not always," or "once in a while." As described in
Huesmann & Eron (1986), the 80 programs used were the most popular for 6 to 11 year-old-children.
They were divided so that each list of 10 had several violent and several non-violent programs and
was balanced for popularity and time shown. The amount of on-screen physical violence portrayed
on each program was coded by two raters on a 5 point scale from "not violent" to "very violent".
The interrater reliability was .75 (Huesmann & Eron, 1986). Some examples of shows rated as "very
violent" are "Starsky and Hutch", the "Six Million Dollar Man", and "Road Runner Cartoon". A
7
child's overall violence score was computed by summing the violence scores for the favorite
programs weighted by how often they were watched as described in Huesmann and Eron (1986).
Shows that were watched only "once in a while" were weighted zero and did not contribute to the
violence score. The one-month test-retest reliability of the TV violence viewing scores was .75.
Childhood Identification with Aggressive TV Characters. As described in Huesmann & Eron
(1986), children were asked "How much do you act like or do things like" various aggressive
characters, such as the Bionic Woman and the Six Million Dollar Man. In each year two aggressive
male characters and two aggressive female characters were presented. The average identification
with aggressive television characters was then calculated separately for the male and female
characters. The coefficient alpha for the four aggressive characters was .71 and the test-retest
reliability over 1 month was .60.
Childhood Judgements of Realism of TV Violence. As described in Huesmann & Eron
(1986), children were asked to rate how realistic they judged various programs to be. They were
given a list of violent television shows, including cartoons, and asked, "How true do you think these
programs are in telling what life is really like: Just like it is in real life, A little like it is in real life,
or Not at all like it is in real life." Ten violent programs were evaluated in this way each year. The
coefficient alpha for this scale is .72 and the one month test-retest reliability was .74.
Childhood Aggressive Behavior. Aggressive behavior in the first three waves of the study
was measured using a modified version of the Peer Rating Index of Aggression (Huesmann & Eron,
1986; Walder, Abelson, Eron, Banta & Laulicht, 1961). In this procedure, each child is asked to
report which children in the class engage in ten different aggressive behaviors, such as "starts a fight
over nothing" and "pushes and shoves children". A child's aggression score was then computed by
adding up the number of times the child was named by his/her peers on all ten items divided by the
number of students in the class doing the ratings. This scale is extremely reliable with an internal
consistency of .97 and a one month test-retest reliability of .91.
Family Demographics. Among the many characteristics of the family that were assessed
during the early parent interviews, two will be utilized in this article. The parents' educational levels
were recorded from self-reports, and an average of the mother and fathers' levels was computed to
be used as a measure of family education. Similarly, the father's occupation was recorded and coded
according to Warner's scale for socioeconomic status. The scale scores were then reversed; so that a
higher score indicates higher socio-economic status.
Adult Measures
Adult Television Violence Viewing. During the personal or phone interviews subjects were
ask to report their three favorite regularly scheduled TV programs-during the current year and how
frequently they watched them. All three programs were then coded for their level of violence using
a scale from 0 (no visible or invisible violence) to 4 (high visible violence). Raters were instructed
to rate the shows on the basis of the frequency of both visible and invisible violence which is
physical, intentional and interpersonal and to only rate those programs which they had viewed
themselves. They were to ignore verbal, accidental violence and violence directed at or by a non-
human. Twenty-seven different raters evaluated the 1272 programs that partcipants listed. The mean
rating from all the raters who had viewed the show (two being the minimum acceptable) was then
used. Two approaches to intercoder reliability were used: interrater correlations and the average
discrepancy from the mean rating. The interrater correlations ranged from .39 to 96 with a mean of
.78 (using Fishers' z), and the mean discrepancy was .34 with no discrepancy being greater than .61.
Two scores were derived from these responses: 1) the average violence rating for the subject's 3
favorite regularly scheduled TV programs was calculated, 2) the average of these violence ratings
weighted by the frequency of viewing each show as was done with the children's data (10=almost
8
every time it is on, 5=usually, 1=sometimes, 0=hardly ever).
Adult Aggressive Behavior. Data about the participants' aggressive behavior was obtained
from three sources: self-reports, 'second-person'-reports, archival data. The measures used in the
subject interview and the 'second person' interview are listed in Table 3 with their internal
consistency reliability coefficients.
Insert Table 3 about here
Subjects were asked to report the frequency of engaging in indirect aggression, verbal
aggression and mild physical aggression when the subject "had problems with or got very angry at
another person" (Bjorkqvist, Osterman & Kaukiainen, 1992); general aggressive behavior (the peer
nominated aggression scale used in the early waves adapted for adults, Huesmann & Eron, 1986);
and severe physical aggression (Huesmann, Eron, Lefkowitz, & Walder, 1984). The indirect
aggression scale included items such as how often the subject responded by "taking the person's
things" and "trying to get others to dislike the person". The verbal aggression scale included items
such as how often the subject responded by "calling the person names" and "belittling the person's
physical abilities or looks". The mild physical aggression scale included items such as how often
the subject responded by hitting, kicking or shoving the person. The severe physical aggression scale
included items about how many times the subject had choked, punched, or beaten another adult;
slapped or kicked another adult; or had "threatened or actually cut someone with a knife or
threatened or shot at someone with a gun".
The subjects were also asked to report how frequently they aggressed against their 'spouse'
(or significant other) using Straus's conflict tactics scale (Straus, Gelles, & Steinmetz, 1980), and
they were assessed on the MMPI personality inventory with scales F, 4, and 9 being combined as a
measure of aggressive personality (Huesmann, Lefkowitz & Eron, 1978). Finally, the subjects
reported their frequency of arrests for different kinds of crimes using questions from the National
Youth Survey (Elliott, Dunford & Huizinga, 1987). Coefficient alpha is not reported for this
measure as it is not a 'scale.' The other coefficient alphas all are respectable as shown in Table 3.
As described above, a close friend or significant other of the subject was also asked to rate
the subject's frequency of engaging in aggressive and antisocial behavior on the same scales as the
subject minus the MMPI aggressive personality measure. This procedure has also been used
successfully in past studies (Huesmann et al., 1984). The coefficient alphas for the "second" person
aggression measures ranged from .53 to .91. The higher internal consistency reliability for the
"Aggression at 'Spouse'' scale is probably due to the fact that many of the 'second' persons
supplying the information were subjects' spouses.
Finally, archival data including criminal conviction records and moving traffic violation
records were obtained for each subject from state records. We used the existence of a drivers license
record as the mechanism for defining the sample on whom the state had records. In other words, if
someone with a drivers license did not appear in the criminal conviction registry, they were coded as
having no convictions.
Results
One of the first questions to resolve in our analyses is whether the multiple adult interview
measures of aggression represent a single construct of aggressive behavior that we can use in our
major analyses. A key question in constructing such a composite is whether to measure aggression
differently for males and females. Over the past decade substantial evidence has accumulated
suggesting that females are more likely to engage in indirect forms of aggression, males are more
likely to engage in direct physical aggression, and both genders are about equally likely to engage in
9
verbal aggression (Bjorkqvist, Lagerspetz, and Kaukiainen, 1992; Lagerspetz, Bjorkqvist & Peltonen,
1988; Lagerspetz & Bjorkqvist, 1992)¹. Because we wish to compare relations in males and
females, we did not want to construct different measures of aggression for the two genders, but we
also did not want to construct one measure that was biased toward assessing aggression in males.
Our solution was to construct a composite measure out of multiple indicators of aggression that
assessed both direct and indirect forms of aggression.
We constructed a structural model, displayed in Figure 2, for such a composite and estimated
its parameters from our follow-up data. As shown in Figure 2, the structural measurement model fits
the adult aggression data well (Chi Sq.=28.88, df=26, N=325, p=.32, RMSE=0183) and weights both
typically male and typically female behaviors. We used the coefficients of this model to combine
our multiple measures of self-report and other-report adult aggression into a single composite that we
could use in our subsequent analyses. For subjects, who only had self-reports or only had other
reports, we used a regression prediction of the composite to estimate their composite score.
Insert Figure 2 about here
In Table 4 the mean scores on the composite, its major components, and other measures of
aggressive behavior are displayed for the male and female subjects. While males and females scored
significantly differently in the predicted directions on the components, their mean scores on the
composite were not significantly different suggesting that the composite is measuring both male and
female dimensions of aggression.
Insert Table 4 about here
In Table 5 the correlations are displayed between this composite measure of aggression, the
self-report and other-report components of the composite, and additional measures of aggression not
included in the composite. As one can see, our composite measure of aggression significantly
correlates with the majority of these other measures of aggression for both males and females,
indicating that it accurately represents these measures. In addition, one can see that those males and
females who scored higher on our composite measure of aggression were more likely to report
having engaged in criminal behavior and having been arrested. The more aggressive males also
reported having been arrested for crimes which we classified as more violent. Archival state records
also indicated that males and females who scored higher on our composite measure of aggression had
committed more moving traffic violations while males who scored higher had also been convicted of
more crimes. Finally, the 'other informants' reported significantly more 'aggression at spouse' from
both male and female subjects who scored higher on the composite. In summary, the composite
measure seems to be a valid measure of aggressive adult behavior for both males and females.
Consequently, the composite measure will be the adult criterion measure of aggression used in all
subsequent analyses.
Insert Table 5 about here
1
Crick & Grotpeter (1995) have renamed the indirect aggression construct developed by Lagerspetz and Bjorkqvist as
"relational aggression." However, we prefer to stick with the original label which seems to reflect the kind of aggression more
accurately.
10
In Table 6 the correlations between aggression and the early television viewing variables are
shown. As has been reported previously (Huesmann, Lagerspetz, & Eron, 1984), childhood
television violence viewing correlated with childhood aggression for both boys and girls in this
sample. The longitudinal correlations, on the other hand, are new. For both males and females,
childhood television violence viewing correlates significantly with adult aggression 15 years later. In
addition, childhood perceptions that TV violence reflects real life and childhood identification with
same-sex aggressive characters significantly predict adult aggression 15 years later.
Insert Table 6 about here
These correlations, while significant, are not large in magnitude. In Figures 3, 4, and 5 the
meaning of these correlations is illustrated with a series of bar graphs. For each childhood television
variable, the subjects are partitioned into three categories: those scoring in the upper quartile, those
scoring in the middle 50% and those scoring in the lower quartile of all children surveyed. Then the
mean adult aggression score is plotted for the subjects in each category. One can see that in each
case the correlations primarily reflect the higher scores on aggression obtained by the highest quartile
of TV violence viewers during childhood. In fact, in all three of these figures the high female
childhood TV group scores significantly higher on adult aggression than the other two groups. For
males, the high childhood TV realism group also scores significantly higher than the other two
groups on adult aggression and the high TV violence groups scores marginally higher than the other
two groups, but the high childhood identification with aggressive characters group does not.
Insert Figures 3, 4, and 5 about here
Of course these correlations and their representations as bar graphs, only illustrate bivariate
relations. To gain a better understanding of the meaning of these longitudinal relations, we have
computed multiple regressions in which we examine the effect of early violence viewing on later
aggression after partialing out early aggressive behavior and cohort. Effectively these regressions
examine the effect of early TV violence viewing on change in aggression. The regression for girls is
shown in Table 7 and the regression for boys in Table 8.
Insert Table 7 and 8 about here
One can see from these regressions that for both males and females early exposure to TV
violence has a significant positive relation to adult aggression even when childhood aggression is
partialed out of the relation. For females identification with same-sex character also has a significant
relation as does a belief that violent programs tell about life just like it is. For males the coefficients
for these two variables were positive but not significant.
One might ask the extent to which these relations might be explained by demographic
characteristics such as the educational level of the family or social class. Using parents' education
or family social class as covariates in these models essentially left the males' coefficients for all
three predictors -- TV violence viewing, identification with same-sex character, and perception of TV
violence as realistic -- unchanged. The positive effects remained just as strong. For females,
however, the positive regression coefficients were reduced in magnitude about 22% on the average
when parents' education was partialed out and about 12% on the average when family social class
was partialed out. For females parents' education was a strong inverse predictor of change in
aggression over time (B = -.248, N=95, P<.01) but was not significantly correlated with female
11
children's early violence viewing suggesting that in less educated families female aggression is
determined more by other factors than TV violence.
We next examined whether identification with same-sex characters or perception that TV
violence is realistic was exacerbating the effects of viewing TV violence. We had found such an
effect for boys during childhood in the early waves of this study (Huesmann, et al., 1984). To test
for such effects, we expanded the regressions in Tables 7 and 8 that predict adult aggression to
include the interactive effect of childhood TV violence viewing with identification with same-sex
characters and with perception that TV violence is realistic. For males we found a significant effect
for both interactions. Identifying with aggressive TV characters exacerbated the effect of TV
violence viewing (B=.17, t=1.98, df=141, p<.05) as did a belief that TV violence viewing was
realistic (B=.16, t=2.03, df=147, p<.05). For females we found a significant interaction only for
perception that TV was realistic (B=.17, t=2.19, df=170, p<.03). Girls who believed that TV was
realistic were more likely to be affected by early exposure to TV violence.
Given that the pattern of longitudinal relations for males and females were very similar, that
our adult aggression measure assessed both male and female aggression, and that the mean scores on
the composite adult measure were not significantly different for males and females, we next
combined males and females to achieve greater power in a longitudinal structural modeling analysis.
In this analysis, shown in Figure 6, we predict adult aggression from early TV violence viewing and
simultaneously predict adult TV violence viewing from childhood aggression. The estimated
parameters of the model provide a good fit as indicated by the non-significant Chi-Square statistic
and low root mean squared error. The model reveals a significant effect from early TV violence
viewing to adult aggression (B = .16, p < .005) but not from early aggression to adult TV violence
viewing. Such a finding is more consistent with the model that early violence viewing is stimulating
later aggression than with the model that early aggressive behavior stimulates later aggression.
Insert Figure 6 about here
12
Discussion
In this 15 year longitudinal study of 331 youth, we found that children's television violence
viewing between ages 6 and 9, children's identification with aggressive same-sex characters, and
children's perceptions that TV violence is real were significantly correlated with their adult
aggression. For both boys and girls more exposure to TV violence during these ages predicted more
aggression as an adult. These relations primarily reflected the behavior of the highest violence
viewing children. Regression analyses that partialed out the effects of early aggression showed that
early exposure to TV violence was not just correlated with aggression but predicted increases in
aggressive behavior. In addition, the perception that TV was realistic and identification with
aggressive TV characters seemed to exacerbate the effects. A longitudinal analysis of the
directionality of the effects suggested that it is more plausible that exposure to TV violence is
increasing aggression than that aggression is increasing TV violence viewing.
It is particularly interesting that we found longitudinal results that were of about the same
magnitude for females as for males. In the 1960 to 1982 Huesmann and Eron (Huesmann, 1986)
study of New York Children, longitudinal effects were only found for boys. It may be that recent
increases in violence in the media and in societal acceptance of aggression for girls are changing the
magnitude of the effect for females.
Some gender differences were found. While identification with same-sex characters
exacerbated the effect of violence viewing for males, it did not for females. It may be that
aggressive male characters have as much effect on females as identification with male characters.
Also, parental education seemed to account for some of the effect in females while it did not in
males. It may be that social norms related to educational status that affect the modeling of media
violence are more influential for females than males.
Overall, however, these results suggest that both males and females from all social strata and
all levels of initial aggressiveness may be influenced by early exposure to media violence. The next
step is to better understand the variables that mediate these relations over time.
13
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16
Table I
Data Collection Summary
Childhood
Adult
Childhood -> Adult
Wave
1+2
4
1+2 -> 4
Year
1977-78
1992
Older Cohort
Age 8-9
Age 23
Age 8-9 -> 23
Males
125
93
71
Females
133
98
83
Younger Cohort
Age 6-7
Age 21
Age 6-7 -> 21
Males
147
98
82
Females
158
109
95
Total
563
398
331
17
Table 2
Reliability of Childhood Measures
Coefficient Alpha
Test-Retest
(N=748)
(N=73-93)
Peer Nominated Aggression
.97
.91
TV Violence Viewing
---
.75
ID with Aggressive TV Characters
.71
.60
Perceived Realism of TV Violence
.72
.74
Table 3
Reliability of Adult Measures: Coefficient Alphas
Self-Reported
Other-Reported
(N=398)
(N=356)
Indirect Aggression
.66
.75
Verbal Aggression
.75
.80
Mild Physical Aggression
.69
.78
General Aggression
.82
.84
Severe Physical Aggression
.59
.53
Aggression at 'Spouse'
.78
.91
Aggressive Personality
.78
18
Table 4
Mean Differences in Major Individual Aggression Variables by Gender
Variable
Female
Male
p-value
(N=207)
(N=191)
Self-Reported:
Verbal Aggression
1.02
1.14
n.s.
Indirect Agression
.85
.72
< .05
Severe Physical Aggression
.19
.47
< .01
General Aggression
1.95
1.96
n.s.
Aggressive Personality
178.03
185.04
< .01
Aggression at 'Spouse'
.28
.13
< .05
Frequency of Arrests
.11
.90
< .001
Violence of Arrests
.01
.06
< .05
Frequency of Criminal Behavior
4.90
15.10
< .001
Other Reported:
Verbal Aggression
1.04
1.05
n.s.
Indirect Aggression
.87
.68
< .001
Severe Physical Aggression
.11
.27
< .02
General Aggression
1.86
1.85
n.s.
Aggression at 'Spouse'
.20
.14
n.s.
Archival Measures:
Ever Convicted
.01
.07
< .01
Frequency of all Traffic
.42
.94
< .001
Violations
Composite Aggression
-.02
.02
n.s.
19
Table 5
Correlations of Adult Composite Aggression Score with Other Adult Measures
Composite Aggression
Adult Measures
Females
Males
Measures in Composite:
Self-Reported
.75***
.82***
Composite Aggression
(N=205)
(N=188)
Other-Reported
.84***
.91***
Composite Aggression
(N=188)
(N=166)
Measures not in Composite:
Self-Reported
.11
.34***
Frequency of Arrests
(N=207)
(N=190)
Self-Reported
---
.15*
Violence of Arrests
(N=188)
Self-Reported Frequency
.39***
.36***
of Criminal Behavior
(N=205)
(N=187)
State Records:
---
.18*
Ever Convicted
(N=191)
State Records:
.15*
.15*
Frequency of all
(N=199)
(N=190)
Traffic Violations
Other Reported
.47***
.69***
Aggression at 'Spouse'
(N=78)
(N=69)
Note. Correlations less that .10 are not reported here.
+p<.10.
*p<.05.
**p<.01.
***p<.001.
20
Table 6
Correlations of Child Aggression and TV Variables with Child and Adult Aggression
Childhood
Adult
Peer-Nominated
Composite
Aggression
Aggression
(N=563)
(N=331)
Child Measures
Females
Males
Females
Males
Peer-Nominated Aggression
1.00
1.00
---
.17*
(N=153)
TV Violence Viewing
.25***
.23***
.18*
.16*
(N=288)
(N=269)
(N=176)
(N=153)
ID with Aggressive Male
---
.21***
.21**
.19*
TV Characters
(N=258)
(N=157)
(N=147)
ID with Aggressive Female
---
.19**
.25***
---
TV Characters
(N=240)
(N=165)
Perceived Realism of
---
.24***
.27***
.16*
TV Violence
(N=268)
(N=176)
(N=153)
Note.
Correlations less than .10 are not reported here.
+p<.10.
*p<.05.
**p<.01.
***p<.001.
21
Table 7: Predicting Adult Composite Aggression from Childhood Television Variables:
Females (N=165)
Standardized Regression Coefficients
PREDICTOR
Reg 1
Reg 2
Reg 3
Reg 4
Initial Grade
-.171'
-.178°
-.100
-.080
Childhood Aggression
.129
.089
.081
.091
TV Violence Viewing
.162'
ID w/ Same-Sex Agg. TV Characters
.214"
Television Realism
.262°
R² Increase over Reg 1
---
.024°
.040
.060
R²
.035
.059
.075
.095
Table 8: Predicting Adult Composite Aggression from Childhood Television Variables:
Males (N = 147)
Standardized Regression Coefficients
PREDICTOR
Reg 1
Reg 2
Reg 3
Reg 4
Initial Grade
-.118
-.117
-.093
-.092
Childhood Aggression
.190'
.160+
.158+
.168'
TV Violence Viewing
.171*
ID w/ Same-Sex Agg. TV Characters
.153+
Television Realism
.114
R² Increase over Step 1
---
.028*
.022+
.012
R²
.043
.071
.065
.055
Note. R² Increase is in relation to Step 1 R².
+p<.10.
*p<.05.
**p<.01.
***p<.001.
21
Table 7
Predicting Adult Composite Aggression from Childhood Television Variables:
Females (N=165)
Standardized Regression Coefficients
PREDICTOR
Reg 1
Reg 2
Reg 3
Reg 4
Initial Grade
-.171*
-.178*
-.100
-.080
Childhood Aggression
.129
.089
.081
.091
TV Violence Viewing
.162*
ID w/ Same-Sex Agg.
.214**
TV Characters
Television Realism
.262**
R² Increase over Reg 1
---
.024*
.040**
.060**
R²
.035
.059
.075
.095
Note. R² Increase is in relation to Reg 1 R².
+p<.10. *p<.05. **p<.01. ***p<.001.
22
Table 8
Predicting Adult Composite Aggression from Childhood Television Variables:
Males (N = 147)
Standardized Regression Coefficients
PREDICTOR
Reg 1
Reg 2
Reg 3
Reg 4
Initial Grade
-.118
-.117
-.093
-.092
Childhood Aggression
.190*
.160+
.158+
.168*
TV Violence Viewing
.171*
ID w/ Same-Sex Agg.
.153+
TV Characters
Television Realism
.114
R² Increase over Step 1
---
.028*
.022+
.012
R²
.043
.071
.065
.055
Note. R² Increase is in relation to Reg 1 R².
+p<.10. *p<.05. **p<.01. ***p<.001.
23
Figure Captions
Figure 1.
Box plots showing the differences in childhood aggression, family educational status,
and achievment for children who were reinterviewed as young adults and those who
were not reinterviewed.
Figure 2.
A structural model showing the parameters used to estimate the adult composite
aggression score for each participant.
Figure 3.
A box plot illustrating the relation between childhood TV violence viewing and adult
aggression for 153 males and 176 females. The high, medium and low groups
represent the upper quartile, the middle 50% and the lower quartile respectively. The
high group is significantly larger than the other two groups for females (t=2.24,
p=.03), but not for males (t=1.56, p=.125).
Figure 4.
A box plot illustrating the relation between childhood identification with same sex
aggressive TV characters and adult aggression for 153 males and 178 females. The
high, medium and low groups represent the upper quartile, the middle 50% and the
lower quartile respectively. The high group is significantly larger than the other two
groups for females (t=2.48, p=.015), but not for males (t=1.47, p=.146).
Figure 5.
A box plot illustrating the relation between childhood judgements of realism of TV
violence and adult aggression for 153 males and 176 females. The high, medium and
low groups represent the upper quartile, the middle 50% and the lower quartile
respectively. The high group is significantly larger than the other two groups for
females (t=2.57, p=.004) and males (t=2.75, p=.009).
Figure 6.
A structural model showing the effects of TV violence viewing and aggression in
childhood on TV violence viewing and aggression in adulthood, controlling for cohort.
Sample Attrition and Early Aggression
(t=4.32, df=436, p<.001)
1000.0
800.0
Peer-Nominated Aggression
600.0
@
000 0 8
400.0
200.0
0.0
-200.0
N =
232
331
Not Reinterviewed
Reinterviewed
Sample Attrition and Parent's Educational Level
(t=4.15, df=281, p<.001)
10.0
8.0
Parent's Educational Level
6.0
4.0
2.0
0.0
N =
81
202
Not Reinterviewed
Reinterviewed
Sample Attrition and Early Achievement for Older Cohort
(t=2.89, df=226, p<.01)
80.0
C
70.0
60.0
Achievement in 1977
50.0
40.0
30.0
20.0
10.0
N =
85
143
Not Reinterviewed
Reinterviewed
Figure 2: Measurement Model of Aggression
USA Subjects (N=325)
SELF
REPORT
.23
.82
.35
.43
.48
.37
.41
.22
General
Severe Physical
Mild Physical
Verbal
Indirect
MMPI Aggressive
Aggression
Aggression
Aggression
Aggression
Aggression
Personality
.38
31
.51
.24
27
.31
.12
.36
AGGRESSION
.13
.57
31
.48
27
.71
Severe Physical
Mild Physical
Verbal
General
Indirect
Aggression
Aggression
Aggression
Aggression
Aggression
41
22
.62
.63
.60
Chi Sq.=28.88 (df=26), p=.32
RMSE=.0183
OTHER
--- non-sig. paths
REPORT
0.2
ADULT COMPOSITE AGGRESSION
0.1
0.0
Child TV
-0.1
Violence Viewing
X HIGH
Z MED
-0.2
LOW
FEMALES
MALES
0.2
ADULT COMPOSITE AGGRESSION
0.1
0.0
Child ID w/
Same Sex Agg.
-0.1 -
TV Characters
X HIGH
MED
-0.2
LOW
FEMALES
MALES
0.2
ADULT COMPOSITE AGGRESSION
0.1
0.0
Child TV
-0.1
Realism
X HIGH
MED
LOW
-0.2
FEMALES
MALES
325 Subjects with 15 year data
Chi Sq. (2) = 4.26, p=.12; RMS = .0283
-.057
1.
Child TV
Adult TV
Violence
Violence
Viewing
.062
Viewing
.072
.156**
.241**
Cohort
X
.095
.206**
Child Peer-
.138*
Adult
Nominated
Composite
Aggression
Aggression
-.147**
* p<.05, ** p<.01