RESEARCH SYNTHESIS ESSAY

Positive Effects of Televisionon Children’s Social Interactions:

A Meta-Analysis

Marie-Louise MaresUniversity of Wisconsin–Madison

Emory WoodardVillanova University

We conducted a meta-analysis of 34 studies of the positive effects of television onchildren’s social interactions, levels of aggression, altruism, and levels of stereotyp-ing (a total of 108 effect sizes, 5,473 children). Across dependent measures, therewere consistent moderate positive effects for those who watched prosocial content inexperimental settings compared to control groups or those who watched antisocialcontent. Moreover, the positive effect of self-selected exposure to prosocial contentwas as strong as the negative effect of self-selected exposure to violent content. Ef-fects were largest for depictions of altruism, primarily because such content tendedto involve explicit modeling of desired behaviors. Strong negative effects occurredin the few studies where children watched aggressive prosocial content.

It is a commonly held belief that television viewing does more harm than good, es-pecially to young audiences. Particular public and scholarly attention has focusedon the negative effects of watching violent programming on social behavior. Tenyears ago, Paik and Comstock (1994) reviewed 217 studies on the link betweenviewing and aggression. In this article, we review the effect of exposure toprosocial audiovisual content on children’s social interactions.1 The goals are toupdate an earlier meta-analysis of prosocial effects conducted by Hearold (1986)

MEDIA PSYCHOLOGY, 7, 301–322Copyright © 2005, Lawrence Erlbaum Associates, Inc.

Requests for reprints should be sent to Marie-Louise Mares, 4010 Paunack Avenue, Madison,WI 53711. E-mail: asidelle@facstaff.wisc.edu

to identify the conditions under which prosocial effects of television viewing arestrongest and to compare effect sizes for prosocial content with the effects sizes forviolent content reported by Paik and Comstock.

A PRIORI REASONING

What might we expect if we compare prosocial with antisocial effects of mediacontent? Two contradictory hypotheses have been put forward.

The first (e.g., Rushton, 1979) is that prosocial effects of media content willtypically be weaker than antisocial effects. Why? Because prosocial acts often in-volve acting against one’s self-interest, whereas antisocial acts often involve act-ing out desires. Prosocial media content, then, may have to encourage people to actagainst their pre-existing motives (should I help this person or should I get to myappointment on time?). Antisocial depictions, to be effective, merely need to en-courage people to act in accordance with desires that are present but are normallysuppressed (I’d love to yell at that person who cut in front of me in line …) Wemight expect the weakest prosocial effects for attempts to bring about altruistic,self-sacrificing behaviors (rather than positive acts that are easily accomplished,are rewarded, etc.) and the strongest antisocial effects for content that disinhibitspre-existing antisocial desires. In addition, Abelman (1991) argued that the greaterexplicitness of violent (rather than prosocial) acts leads to greater retention ofthose acts and greater likelihood of subsequent re-enactment. Finally, it could bethat conflict is integral to dramatic presentations (Zillmann, 1991) and thus is moreengaging than prosocial depictions devoid of conflict and concomitant violence.

The second hypothesis takes the opposite stance—prosocial effects of mediacontent should be even stronger than antisocial effects. Why? Basically becausewe learn positive behaviors in the same way as negative behaviors (see Mares &Woodard, 2001, for further discussion), and prosocial behaviors are more in ac-cord with existing social norms.

If we asked a stranger in the street for directions, we would expect him or her to pro-vide the information if possible and to apologize if not. If the stranger were instead toturn to us and say “Yes, I do know where that place is but I can’t be bothered to tellyou,” we would be rather surprised. (Rushton, 1979, p. 324)

Prosocial media depictions are more consistent with social norms than violentdepictions, and imitation of the prosocial acts on television is more likely to be re-ceived positively than imitation of antisocial acts (i.e., Grusec, 1991, reported thatspontaneous altruism in young children is typically responded to with some formof social reinforcement such as thanks, hugs, or smiles). Therefore, the argumentgoes, prosocial effects of positive media content will be at least as powerful as an-tisocial effects of antisocial media content, other things (such as amount of expo-sure or attractiveness of the models) being equal.

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How equal are these “other things,” and which line of reasoning is supported byprior research?

MEDIA DEPICTIONS AND EXPOSURE

Content analyses continue to find high levels of violence and criminal activity ontelevision. Researchers for the National Television Violence Study (1996, 1997,1998) reported that about 60% of programming broadcast between 6 a.m. and 11p.m. contained violence. Moreover, children’s shows were more violent thanmany other types of programming—66% of the children’s programs sampled con-tained violence. Violence was often performed by heroic figures in the pursuit ofjustice without causing realistic pain or suffering to the victim and was frequentlydepicted as humorous.

What about prosocial content? Is it as prevalent or attractive? In their review ofearly content analyses, Liebert and Sprafkin (1988) concluded that children watch-ing during the 1970s (when a number of the studies analyzed in this article wereconducted) were exposed to a fair number of prosocial interpersonal behaviors(e.g., altruism or sympathy), but few instances of resisting temptation or control-ling aggressive impulses (see, e.g., Liebert & Poulos, 1975; Poulos, Harvey, &Liebert, 1976).

Moreover, prosocial content often appeared in the context of aggression.Greenberg, Atkin, Edison, and Korzenny (1980) analyzed the favorite programs ofa sample of fourth, sixth, and eighth graders. They found that these programs con-tained an average of 42.2 acts of antisocial behavior and 44.2 acts of prosocial be-havior (altruism, empathy, discussion of feelings) in an average hour. Liss andReinhardt (1980) analyzed prosocial cartoons (those with moral messages appar-ent to the adult researchers) and standard cartoons. They found that both types ofcartoons contained equal amounts of aggression. The flip side of this is a more re-cent finding reported by the National Television Violence Study (1998) that fewerthan 4% of the violent programs shown on television contained an antiviolencetheme. When prosocial content occurs, violence is often mixed in; when violenceoccurs, an antiviolence message is seldom attached.

The Annenberg Public Policy Center has conducted annual content analyses ofall children’s programs aired over the course of a composite week in Philadelphia,a large urban media market. Woodard (1999) examined the frequency with whichprograms contained social lessons about interpersonal skills such as acceptance ofdiversity, altruism, and cooperation. In the 1998–1999 sample, 25% of all chil-dren’s shows contained at least one such social lesson, although most appeared inprogramming for preschool children. How much prosocial content do children ac-tually see? Out of the 20 shows with the highest Nielsen ratings for children be-tween the ages of 2 and 17, only 2 contained prosocial lessons as defined in thisstudy, and only 1 of those was designed for children.

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Given this discrepancy—high levels of glamorized or humorous violence inchildren’s programming and relatively low levels of specific prosocial mes-sages—what does media effects research indicate? What are the effects of en-forced exposure to prosocial content (as in the experimental setting), and what arethe effects of self-selected exposure? Can prosocial messages have positive ef-fects? Do they do so in “real life?”

A PRIOR META-ANALYSIS

A meta-analysis of the early research on effects of television found support for thepowerful prosocial effects argument. Hearold (1986) reviewed 230 early studieson television and social behavior published prior to 1978. She concluded thatprosocial effects were stronger and more enduring than antisocial effects, both inthe laboratory and in more natural conditions. She reported an effect (d) of .63 forprosocial content on prosocial behavior, compared to an effect (d) of .30 for antiso-cial content on antisocial behavior. (Effect sizes reported as r would be approxi-mately half of that reported as d.)

Hearold’s (1986) work on antisocial effects has been partially updated in thePaik and Comstock’s (1994) meta-analysis of violence effects. They reported anoverall effect (d) of violent television content of .65, which was more than doublethe antisocial effect found by Hearold (she included a wider range of variables).Our study provides a partial update of the prosocial effects component of her work.It is only a partial update because Hearold included a much wider range of positiveoutcomes than are considered here (e.g., imagination, buying books, library use,safety activism, and “conversation activism”).

THIS STUDY

This study examines the prosocial effects of “television viewing” on children’s so-cial interactions. What does a prosocial effect size mean? In the experiments re-viewed here, the effect size is often the difference between a control group and agroup exposed to prosocial content, or between a group that sees some negativecontent and a group that sees some positive content. These differences are stan-dardized by dividing by the pooled standard deviation so that they can be com-pared across measures and studies. In surveys, the effect size is often the correla-tion between how much prosocial television content children watch and howpositively they behave—it can be thought of as the difference between heavy andlight viewers of prosocial television content.

Two other notions need explanation: television viewing and positive/prosocial.Television viewing is construed in its broadest sense here. That is, studies were in-cluded whether they measured number of hours of daily viewing or involved ex-

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posing participants to specially constructed 5-min videotapes of a model carryingout some particular behavior. In some of the early studies, “television viewing” re-ally means watching a film. One of the questions to be answered was whether theeffect size depends on the way television exposure was measured and conceived.

The notion of prosocial content is more difficult—it is not easy to sort outwhich behaviors are positive and which are negative. This is more than hazy moralrelativism. It is naive to assume that all groups in society place equal value on co-operation (rather than rugged individualism), tolerance of others (rather than will-ingness to stick up for one’s own group), nonviolent conflict resolution (ratherthan heroism), or ability to resist temptation (rather than ability to seize the mo-ment). Nonetheless, all of these have been used as prosocial outcomes in research.

There are two responses to this problem. The best would be to look at the in-terplay between the individual’s perceptions of social norms and that individ-ual’s reactions to specific types of content. After all, groups that value ma-chismo will probably react differently to a “prosocial” portrayal of two mendeciding not to fight than groups who value rational discussion as a solution tosocial conflict. This idea is not new to research on persuasion, but it generallyhas not informed the research on prosocial effects of television viewing. Atmost, a few researchers have compared children of high versus low socioeco-nomic status, or children who were initially high in aggression with those whowere less aggressive. So, unfortunately, this article investigates whether televi-sion has an influence on specific behaviors, with little regard for probable sub-group differences in responses.

Given this, it was necessary to make a pragmatic decision about what would beincluded as positive effects for the purposes of this article. In this review, four clus-ters of outcomes related to social interactions were considered: positive interac-tion, aggression, altruism, and stereotype reduction. These were chosen becausethey seemed to include most of the research that was self-identified as being about“prosocial effects” and because they made sense as a coherent set of variables. Weexcluded a whole separate set of research on attempts to encourage compliancewith medical guidelines (e.g., quit smoking, vaccinate children) as well as a mis-cellaneous set of stray variables included in Hearold’s (1986) meta-analysis (readmore, etc.).

METHOD

Sample of Studies

We searched three databases (PsycLIT/PsychAbstracts, Social Sciences Index,and Communication Abstracts) looking for the combination of telev* and proso-cial, altruism, helping, sharing, empathy, friend*, cooperation, counterstereotyp*,nontrad*, charity, generosity, and moral*. Because some studies used videotaped

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or filmed models of prosocial behavior without describing it as a study of televi-sion’s effects, we then searched again, substituting “model*” for “television” incombination with all other terms. In addition, studies were culled from the refer-ence list for Hearold’s (1986) meta-analysis and from an expanding search of thereference lists of all studies found on the topic.

Studies were included if they (a) involved exposure to audiovisual contentdeemed prosocial or positive by the researchers, (b) measured one or more of ourfour dependent variables, (c) were published in academic journals, and (d) con-tained enough statistical information to allow for calculation of effect sizes. Thefourth criterion proved a major factor: Many early studies include minimal (or no)statistical information. Table 1 gives design and effect size information for thestudies ultimately included.

Defining Dependent Measures

Positive interaction. This was a broad variable used to capture measuressuch as “friendly play” or “peaceful conflict resolution.” Studies that simply gavea measure of “prosocial behavior” were coded in this category. In a typical study(e.g., Friedrich-Cofer, Huston-Stein, Kipnis, Susman, & Clewett, 1979), childrenwere assigned to watch Mister Rogers’ Neighborhood or some neutral content. Af-terward, observers rated the children’s play behavior, counting the number of ag-gressive acts, friendly behaviors, expressions of affection, and so on.

Aggression. Although it was possible to think of this as the other end of the“positive interaction” continuum, we decided to treat this as a separate, althoughrelated, variable. Both physical and verbal aggression were included. Unfortu-nately, studies often ran the two together, so we were not able to analyze them sep-arately. To be consistent with the direction of other variables, we reversed the signof effects on aggression so that a positive prosocial effect meant a reduction inaggression.

Altruism. This variable included any measures that the researchers calledsharing, donating, offering help, and comforting. In a typical study of altruism(e.g., Bryan & Walbek, 1970), children were brought into the laboratory and toldthat they would learn how to play a new game by watching a video. The childrenwatched one of several versions of the video, in which the model played the game,was rewarded by tokens that could be used to win a prize, and then immediatelydecided whether to behave altruistically (giving some of the tokens to charity oranother child) or selfishly (cashing in all the tokens for a big prize). The childrenthen played the game, won a fixed number of tokens, and were given the opportu-nity to donate some tokens. The measure of altruism was the number of tokensgiven.

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TABLE 1Design and Effect Size Information for Individual Studies

Authora Year Nb Agec Design Effect Sized

Abelman 1985 286 120 Correlational 0.4200*Ahammer 1979 30 58 Experimental –0.0770*Ahammer 1979 24 53 Experimental 0.2520*Bankart 1979 22 54 Quasi-experimental 0.9500*Baran 1979 81 96 Experimental 0.3170*Baran 1979 81 96 Experimental 0.3170*Baran 1979 81 96 Experimental 0.4310*Bryan 1970 72 108 Experimental 0.2170Collins 1976 54 158 Experimental 0.4760*Collins 1976 54 158 Experimental 0.3050*Collins 1976 54 158 Experimental 0.4650*Collins 1976 54 158 Experimental 0.3990Davidson 1979 36 66 Experimental 0.7090*Davidson 1979 36 66 Experimental 0.6330*Drabman 1977 40 60 Experimental 0.3980*Drabman 1977 40 60 Experimental 0.3380*Durkin 1984 99 150 Experimental 0.1860*Durkin 1984 99 150 Experimental –0.1170Durkin 1984 99 150 Experimental –0.0190Durkin 1984 99 150 Experimental –0.1690Durkin 1984 99 150 Experimental 0.1200Durkin 1984 99 150 Experimental –0.1370Durkin 1984 99 150 Experimental 0.2070Durkin 1984 99 150 Experimental 0.1730Elias 1983 109 132 Experimental 0.2920Elliott 1970 48 72 Experimental 0.7550*Elliott 1970 48 72 Experimental 0.7550*Elliott 1970 48 72 Experimental 0.8570*Forge 1987 40 50 Experimental 0.4020*Friedrich-Cofer 1979 141 50 Experimental 0.0000*Friedrich-Cofer 1979 141 50 Experimental 0.2880Friedrich-Cofer 1979 141 50 Experimental 0.2310*Friedrich-Cofer 1979 141 50 Experimental –0.0620*Friedrich-Cofer 1979 141 50 Experimental 0.3980Friedrich-Cofer 1979 141 50 Experimental –0.1600*Friedrich-Cofer 1979 141 50 Experimental 0.2490Friedrich-Cofer 1979 141 50 Experimental –0.2990*Friedrich-Cofer 1979 141 50 Experimental –0.1360*Geller 1978 24 57 Experimental 0.5670*Goldberg 1979 167 48 Experimental 0.2260*Goldberg 1979 167 48 Experimental 0.0000*Gorn 1976 205 54 Experimental 0.2390*Houser 1978 156 88 Experimental 0.6630*Houser 1978 156 88 Experimental 0.7040*

(continued)

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Authora Year Nb Agec Design Effect Sized

Keller 1974 19 46 Experimental 0.4900*Keller 1974 19 46 Experimental 0.3240*Liss 1983 60 67 Experimental 0.9611*Liss 1983 60 67 Experimental 0.9753*Liss 1983 60 67 Experimental 0.9765*Liss 1983 120 91 Experimental 0.2693*Liss 1983 120 91 Experimental 0.1049*McArthur 1976 20 49 Experimental 0.4630*McArthur 1976 20 49 Experimental 0.4670*O’Bryant 1978 67 87 Experimental 0.2160*O’Bryant 1978 67 87 Experimental 0.4060*O’Bryant 1978 67 87 Experimental 0.3830*O’Bryant 1978 67 87 Experimental –0.1020*O’Connor 1969 13 42 Experimental 0.6300*O’Connor 1972 31 42 Experimental 0.6010*Pingree 1978 227 132 Experimental –0.2760*Pingree 1978 227 132 Experimental –0.0610Pingree 1978 227 132 Experimental 0.2780Rao 1987 16 56 Experimental 0.5620*Rao 1987 16 56 Experimental 0.4850*Rao 1987 16 56 Experimental 0.4830*Rosenwasser 1989 114 66 Correlational –0.0250*Rosenwasser 1989 114 66 Correlational –0.0400Rosenwasser 1989 114 90 Correlational 0.4750Rosenwasser 1989 114 90 Correlational 0.1650*Rosenwasser 1989 114 66 Correlational 0.2300Rosenwasser 1989 114 66 Correlational 0.0650*Rosenwasser 1989 114 90 Correlational –0.0200Rosenwasser 1989 114 90 Correlational 0.3150Rosenwasser 1989 114 66 Correlational 0.0100*Rosenwasser 1989 114 66 Correlational 0.2530Rosenwasser 1989 114 90 Correlational 0.3950*Rosenwasser 1989 114 90 Correlational 0.1050*Rushton 1975 72 108 Experimental 0.2870Rushton 1975 72 108 Experimental 0.1970*Silverman 1980 90 60 Experimental 0.1070*Silverman 1980 90 60 Experimental 0.4350*Silverman 1980 90 60 Experimental –0.3520*Silverman 1980 24 36 Experimental –0.5090*Silverman 1980 24 36 Experimental –0.4790*Silverman 1980 24 36 Experimental 0.3670*Silverman 1980 24 36 Experimental 0.5880*Sprafkin 1975 30 78 Experimental 0.8560*Sprafkin 1975 30 78 Experimental 0.1360*Sprafkin 1979 393 102 Correlational 0.0800

(continued)

TABLE 1 (continued)

Stereotype reduction. This included measures of effects of counter-stereotypical portrayals of gender and ethnicity on attitudes, beliefs, and behav-iors. Most research has focused on simple short-term effects. For example, Gorn,Goldberg, and Kanungo (1976) showed children 12 min of Sesame Street pro-gramming with multicultural themes. They found strong effects on interest in play-ing with non-White hypothetical playmates, but, not surprisingly, these effectstended to be very short lived. Goldberg and Gorn (1979) found that the effects haddisappeared by the next day.

Comparisons

It is only possible to judge the effect of prosocial content by comparing groupswho watch prosocial material with those who watch less of it or who watchother content. Thus, there is no pure “prosocial effect.” Rather, the size of the ef-fect depends on what forms the comparison group. We examined the followingcontrasts: prosocial content versus control (no content), prosocial versus neutraltelevision content, prosocial versus antisocial television content, and correlationsbetween prosocial viewing and prosocial outcomes. In addition, we looked at thecomparison between aggressive prosocial content versus nonaggressive pro-

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Teachman 1981 120 108 Experimental 0.1450Teachman 1981 120 108 Experimental –0.0080*Teachman 1981 120 108 Experimental 0.4270Teachman 1981 120 108 Experimental 0.0850*Toeplitz-Winiewska

1977 152 200 Experimental –0.2490

Toeplitz-Winiewska

1977 152 200 Experimental –0.1440*

Toeplitz-Winiewska

1977 152 200 Experimental –0.3300*

Toeplitz-Winiewska

1977 152 202 Experimental 0.2300*

Toeplitz-Winiewska

1977 152 202 Experimental 0.0200*

Toeplitz-Winiewska

1977 152 202 Experimental 0.2800

Tower 1979 58 50 Experimental –0.0440*Tower 1979 58 50 Experimental –0.2000Tower 1979 58 50 Experimental 0.1290*Tower 1979 58 50 Experimental 0.2510*Tower 1979 58 50 Experimental 0.2900*Tower 1979 58 50 Experimental 0.3160*Tower 1979 58 50 Experimental 0.4190*

TABLE 1 (continued)

Authora Year Nb Agec Design Effect Sized

social content. Aggressive prosocial content was typically labeled as such by theresearcher involving some aggressive physical or verbal confrontation that wasthen resolved peacefully (thereby modeling prosocial conflict resolution). Fi-nally, we also looked at the effect of augmenting prosocial television contentwith additional materials or instruction: prosocial plus supplements versus con-trol, prosocial plus supplements versus neutral, and prosocial plus supplementsversus antisocial.

Deciding on Number of Effect Sizes Per Study

In calculating effect sizes, the goal was to divide the study’s research participantsinto homogenous samples to make as fine-grained comparisons as possible. Dif-ferent age groups and different sexes were treated as separate samples, and an ef-fect size was calculated for each sample within the study. In addition, studiessometimes reported on more than one variable of interest—for example, both al-truism and friendly play. A separate effect size was calculated for each of thesevariables for all the samples within a study. When the study reported on multiplemeasures of the same variable, however, those measures were averaged to formone effect size for that variable. The result was 34 usable sources and 108 effectsizes. This represented testing 5,473 children.

Moderator Variables

A number of moderator variables were coded, many of which subsequently provedto have too few cases to provide meaningful comparisons. The list of variables andcoding decisions are summarized in the Appendix.

Coding and Reliability

All effect sizes were coded independently by both authors. After initial trainingsessions, reliability was higher than 95% as calculated by Krippendorff’s alpha.

Statistical Analysis

The effect size computed was r (Hunter & Schmidt, 1990). This r was weighted bysample size and converted to ZFisher to solve the skewness of r at the extreme endsof the distribution (Paik & Comstock, 1994) and as suggested by Hedges andOlkin (1985).2 In this analysis, positive correlation coefficients reflect a greater in-crease in prosocial outcomes in the prosocial condition than in the comparisoncondition (whether this was antisocial, neutral, control, or pretest) or higherprosocial scores among heavy viewers of prosocial content than among light view-ers. Positive values for r for the aggressive outcome reflect the prosocial contentbeing associated with less aggression than in other conditions.

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RESULTS

If we look across dependent variables, comparisons, and research designs, the av-erage effect size (ZFisher) for prosocial content on social interaction is .27. This is ofonly marginal interest given how many different issues are lumped together in thisnumber. Nonetheless, it is a starting point for assessing our rival hypotheses aboutthe relative ease or difficulty of persuading people to “be nice” as opposed to act-ing out mean desires. Paik and Comstock (1994) reported an overall ZFisher of .32for violence effects. Thus, at the aggregate level, the two types of content are quitesimilar in effectiveness, although prosocial effects are somewhat weaker.

What matters more are the conditions under which prosocial content is more orless effective. We discuss these conditions in the following. How should the num-bers in the tables be interpreted? Qualitative descriptions of effects sizes are con-troversial. A small change in behavior may be of critical importance, or it may betrivial. The rule of thumb (see Cohen & Cohen, 1983) is that an effect size (r) of .20(ZFisher = .20) or less should be considered small, an effect between .30 and .40(ZFisher between .31 and .42) is medium, and an effect above .50 (ZFisher = .54) islarge.

Design Effects

Prosocial content compared to other content. Table 2 shows the effectsizes for each comparison, both across and within the four dependent variables (al-truism, social interaction, aggression, and stereotype reduction). As the top part ofTable 2 indicates, across dependent variables, children who saw prosocial contentreceived higher prosocial scores than any of the comparison groups. The remain-der of Table 2 shows that this pattern was consistent within each of the four de-pendent variables: Of 19 comparisons, 18 showed a significant positive effect ofprosocial content. The only exception was for aggression, for which children whosaw prosocial content were not significantly less aggressive than those who did notwatch any television.

Effects of research setting. A one-way analysis of variance (ANOVA)found a marginally significant effect of comparison type on effect size across thefour dependent variables, F(5, 103) = 2.07, p = .08. That is, there weresmall-to-medium improvements in prosocial behavior for those who saw prosocialcontent in an experimental setting compared to control groups (r = .31) or com-pared to those who saw antisocial content (r = .26). The effects were smaller forthe (few) surveys that measured the correlation between self-selected exposureand behavior (r = .19).

How do these findings compare with violence effects reported by Paik andComstock (1994), and where do they leave our hypotheses? Paik and Comstock

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TABLE 2Effect Sizes by Outcome and Comparison Type

Outcome Behavior Comparison r ZFisher k N 95% CI

All outcomes All comparisons .23 .27 108 5473 (.25, .30)

Prosocial vs. control .31 .36 16 807 (.30, .42)

Prosocial vs. neutral .18 .21 43 2072 (.16, .25)

Prosocial vs. antisocial .26 .31 29 1133 (.25, .36)

Correlation with prosocial TV .19 .20 14 1021 (.14, .26)

Aggression prosocial vs.neutral

–.35 –.37 1 60 (–.56, –.11)

Aggression prosocial vs.prosocial

.39 .56 5 380 (.49, .63)

Altruism All comparisons .37 .47 20 856 (.42, .52)

Prosocial vs. control .50 .57 5 154 (.45, .67)

Prosocial vs. neutral .23 .26 6 170 (.11, .40)

Prosocial vs. antisocial .35 .45 7 372 (.37, .53)

Correlation with prosocial TV — — 0 0 —Aggression prosocial vs.

neutral— — 0 0 —

Aggression Prosocial vs.Prosocial

.44 .60 2 160 (.49, .69)

Social interaction All comparisons .24 .22 36 2056 (.21, .30)

Prosocial vs. control .30 .30 2 161 (.15, .44)

Prosocial vs. neutral .20 .21 26 980 (.15, .27)

Prosocial vs. antisocial .36 .36 4 116 (.18, .52)

Correlation with prosocial TV .22 .23 2 679 (.16, .30)

Aggression prosocial vs.neutral

–.35 –.37 1 60 (–.56,–.11)

Aggression prosocial vs.prosocial

.44 .47 1 60 (.20, .62)

Aggression All comparisons .16 .27 15 747 (.20, .34)

Prosocial vs. control –.01 –.01 2 76 (–.24, .22)

Prosocial vs. neutral .09 .20 7 359 (.09, .30)

Prosocial vs. antisocial .20 .22 4 152 (.05, .37)

Correlation with prosocial TV — — 0 0 —Aggression prosocial vs.

Neutral— — 0 0 —

Aggression prosocial vs.Prosocial

.32 .56 2 160 (.44, .66)

Reducing stereotypes All comparisons .20 .22 37 1814 (.18, .27)

Prosocial vs. control .30 .36 7 416 (.27, .44)

Prosocial vs. neutral .18 .19 4 563 (.11, .27)

Prosocial vs. antisocial .19 .20 14 493 (.11, .28)

Correlation with prosocial TV .13 .13 12 342 (.02, .24)

Aggression prosocial vs.neutral

— — 0 0 —

Aggression prosocial vs.prosocial

— — 0 0 —

Note. r = weighted effect size computed by the Hunter and Schmidt Method; k = number of effectsizes averaged; N = total number of participants used to compute effect size; CI = confidence intervalsand are about the ZFisher.

reported an effect of .37 for experimental designs and an effect of .19 for surveys(self-selected exposure). We appear to have fallen neatly between our two rival hy-potheses. According to these data, it is as easy to persuade viewers to be pleasant asit is to persuade them to be violent.

Across variables, two further questions were examined. First, we looked at theeffect of enhancing viewing of prosocial content with additional classroom materi-als or activities. Despite reports within individual studies that children respondedmore positively in the context of additional materials, overall, we found no sucheffect in this meta-analysis. The average effect size for prosocial content with noadditional materials was .25 (number of effects = 100); for prosocial content withsupplements (number of effects = 8), the average effect size was .24 (p = .812).

The second question concerned the effect of aggressive prosocial content (i.e.,physical or verbal aggression resolved in a prosocial manner). Despite the tinysample size, there was evidence of pernicious effects of aggressive prosocial con-tent. For all three of the variables for which it was measured, the contrast betweenprosocial content and aggressive prosocial content was larger than the contrast be-tween pure antisocial and prosocial content. This is particularly alarming given thefindings of content analyses that “positive” messages are often combined withplenty of preceding action and violence.

Effect Size × Dependent Measure

A one-way ANOVA found a marginally significant effect of dependent measureon effect size, F(3, 104) = 2.55, p = .06. Examination of the confidence intervals(CIs) suggests that the strongest effects of prosocial content were on altruism. Ef-fect sizes for positive interaction, aggression reduction, and stereotype reductionwere remarkably similar to one another.

The strong effect on altruism runs counter to the argument posed earlier in thisarticle that it should be hardest for prosocial messages to persuade people to makealtruistic sacrifices (rather than to simply make them interact in a friendly manner).Why is this effect somewhat stronger? One explanation is that altruism was onlyinvestigated experimentally rather than in surveys (see Table 2), and effect sizestend to be larger in experimental settings. We also considered various treatment ef-fects as possible explanations.

Treatment Effects

Length of delay in testing. The correlation between testing lag (measuredin days between experimental exposure and time of testing) and effect size was notsignificant (r = .064, p = .512). This correlation must be interpreted with caution,given that 103 of the 108 effect sizes were measured with less than a day’s delay.

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There were no differences in time until testing between the dependent mea-sures, F(3, 104) = 1.28, p = .287. That is, altruism was no more likely to be mea-sured immediately than positive social interaction, aggression, or stereotype re-duction; hence, this was not a possible explanation for the relatively strong effectof prosocial depictions on altruistic behaviors.

Similarity of treatment and outcome. We coded the similarity of treat-ment and outcome: identical, similar, and general/mixed (see Appendix). Aone-way ANOVA indicated significant differences in effect sizes, F(2, 105) =5.78, p < .01. The mean effect size for identical treatment was .44, 95% CI (.36,.51); for similar treatment, it was .27, 95% CI (.19, .35); and for general messages,it was .26, 95% CI (.23, .29). Not surprisingly, prosocial effects were strongestwhen the prosocial treatment involved explicit modeling of the prosocial behaviorto be imitated.

Efforts to promote altruistic behavior were more likely to model behaviors thatwere identical to the dependent measure, whereas efforts to promote otherprosocial behaviors were less likely to have identical treatments and tasks, χ2 (6, N= 108) = 21.35, p = .002. This, then, seems to be one explanation of stronger altru-ism effects.

Effects of rewards. There were no significant effects of depicting a modelbeing rewarded for prosocial behavior: Children were no more likely to imitate arewarded model than one who was not rewarded. This is consistent with Paik andComstock’s (1994) finding that reward had no significant effect on the tendency toimitate violence. Nonetheless, it is worth noting that there are only 10 comparisonstesting the effects of reward on prosocial behavior.

Effects of external validity. We coded the realism (external validity) of thestimulus: self-selected content, whole television programs, edited programs, andcontent produced by the researchers. A one-way ANOVA found no significant dif-ferences in mean effect size.

Effects of specific programs. We tested whether three specific pro-grams—Sesame Street, Mister Rogers’ Neighborhood, and Barney & Friends—showed stronger positive effects than other types of content. We did this becausethese programs are often held up as the benchmark of excellence in prosocial pro-gramming. In these analyses, however, these programs did not show significantlystronger positive effects than other programs, perhaps because they are aimed atpreschool audiences, which, as we discuss following, tend to be less strongly af-fected than older groups.

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Participant Effects

We examined the effects of gender, ethnicity, and socioeconomic status on the re-lation between prosocial exposure and behavior (see Table 3). Paik and Comstock(1994) reported that males were more strongly affected by TV violence in experi-mental settings (although not as a result of self-selected exposure as reported insurveys). We found no such difference: Males and females were equally positivelyaffected by exposure to prosocial content. There were also no significant differ-ences between ethnic or racial groups. Only socioeconomic status showed signifi-cant differences, such that prosocial television had a greater effect on participantsfrom middle- to upper class settings than on participants from lower class settings.

Age was a significant predictor of effect size, r(108) = –.22, p < .05. Age rangedfrom 3 years to 16 years 10 months, with a mean of 7 years 32/3 months (SD =44.33). A curve fit analysis suggested that a cubic function best described the rela-tion between age and effect size. The effect of prosocial content increased sharplybetween the ages of 3 and 7, peaked at age 7, declined steeply until age 12, and thendeclined more gradually after that. This age pattern is inconsistent with Paik andComstock’s (1994) report that the youngest viewers were the most strongly nega-tively affected by exposure to violence. Perhaps the difference may lie in the visualsalience and excitement of violent actions compared to somewhat less striking actsof cooperation or kindness (see Abelman, 1991). The peak at age 7 suggests thatyounger children may lack the cognitive ability to fully grasp the nature of prosocialacts and the contexts that require them when presented within a television program.

DISCUSSION

Both in experimental settings and at home, children who watched prosocial con-tent behaved significantly more positively or held significantly more positive atti-

PROSOCIAL TV META-ANALYSIS 315

TABLE 3Effect Sizes by Demographic Group

Demographic Group r ZFisher k N 95% CI

GenderMale .13 .13 27 1229 (.07, .19)Female .20 .22 16 474 (.13, .31)

EthnicityWhite .20 .27 44 2131 (.23, .31)Black .37 .37 2 80 (.16, .55)

Socioeconomic statusLow .14 .16 22 1175 (.10, .22)High .25 .32 47 2620 (.32, .39)

Note. r = weighted effect size computed by the Hunter and Schmidt Method; k = number of effectsizes averaged; N = total number of participants used to compute effect size; CI = confidence intervalsand are about the ZFisher.

tudes than others. This is striking news and should serve as something of an anti-dote to those who consider television to be nothing but detrimental. The results ofthis meta-analysis suggest the real potential for television and other media to helpchildren feel and behave more pleasantly toward each other.

In addition, the results suggest that television is no more prone to fostering vio-lence than it is to fostering prosocial behavior. Probably the most interesting com-parison is of the effect sizes for self-selected exposure to violence versus prosocialcontent (as measured by surveys). These effect sizes were small but identical. Inthe “real world” of viewing at home, violence and prosocial content had equal (al-though small) effects. Unfortunately, the strength of the relation says nothingabout “real world” typical levels of viewing violence versus prosocial content orabout the relative availability of TV violence versus prosocial content.

Taken as a whole, the results of this study do not suggest that violence is “easy”and prosocial behavior is “hard,” or even the reverse. Rather, the results point tothe critical junction between having seen a behavior modeled explicitly and per-ceiving a similar situation in which one could act that way. The more apparent theconnection between the situation shown and one’s own situation, the more likely itis that one will use the modeled behaviors. In this study, effect sizes for altruismwere marginally larger than for other dependent variables (despite our initial sug-gestions that it might be the most difficult prosocial behavior to promote) primar-ily because participants in studies of altruism were more likely to be placed in situ-ations that were identical with the film that they had just seen. Is this at all usefulbeyond the realm of academics? It suggests that producers of prosocial contentshould pay attention not only to the explicitness with which they model the desiredbehaviors, but also to making the contexts of the behaviors seem relevant and real-istic to viewers.

In any event, the conclusion is that television has the potential to fosterpositive social interactions, reduce aggression, and encourage viewers to bemore tolerant and helpful. Surely, this is good news. Why, then, does the researchon violence continue apace, whereas the number of studies on prosocial effectsdwindles from year to year? We found 39 studies (108 hypothesis tests) that couldbe analyzed compared to the 217 studies (1,142 hypothesis tests) analyzed by Paikand Comstock (1994). The range of methodologies and of populations studied ismuch broader for the violence literature than the prosocial literature. Consider Ta-ble 2: Numerous cells remain empty or are filled by one or two studies. In particu-lar, we have little sense of the everyday effects of television viewed at home: Thereare far fewer studies of self-selected exposure to prosocial content than to violentcontent.

Not only are we less confident of the effect size for prosocial content in the realworld, we also know less about how to make prosocial programming effectivethan we know about how to make violence maximally effective. There are morestudies on the effects of showing rewarded violence than on showing rewardedheroism or generosity or tolerance. There are more studies comparing cartoon ver-

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sus live violence than those comparing cartoon and live prosocial interactions. Al-though one can speculate that the mechanisms for prosocial and antisocial contentshould operate in the same way, it is unclear that they do.

Finally, we have little sense of the individual and interactive effects of demo-graphics such as ethnicity and socioeconomic status. This is problematic, giventhat television has been conceived of as a tool for eradicating these subgroup dif-ferences. The simplest example is the controversy that once surrounded SesameStreet: Would it reduce the preschool gap between advantaged and disadvantagedchildren, or would it increase that gap? Programmers who plead ignorance aboutwhat constitutes educational/prosocial programming often appear self-serving anddisingenuous, particularly in the face of the rather minimal 3-hr-per-week require-ment put in place by the “3-hr rule.”3 Nonetheless, they are correct to argue that itis often unclear what the effect of some seemingly positive program would be. Forinstance, our research suggests that the happy worlds of prosocial programmingmay resonate best with members of the audience who inhabit worlds of relativeaffluence.

Ideally, meta-analysis is the answer to the customary call for “more research toclarify the issue” that dogs media effects research. In this case, our hope is that itserves as a wake-up call to researchers that the question of prosocial effects shouldnot languish as the topic of the 1970s, but should be the focus of more sophisti-cated attempts to use television as a tool for positive social change.

ACKNOWLEDGMENTS

This study was funded, in part, by a grant to Marie-Louise Mares from theAnnenberg Public Policy Center, University of Pennsylvania.

NOTES

1Some of the results presented here have been summarized as part of a literature review chapterpublished elsewhere (Mares & Woodard, 2001).

2The authors (Hedges & Olkin, 1985) stated, “Several approaches can be used to estimate r (overalleffect size) via weighted linear combinations of estimators. A central issue is whether we should weightthe product-moment correlations, r1, … ,rk; the unbiased estimators, G(r1), … , G(rk) the z-transformedversions, z1, … , zk; Kraemer’s t transforms, t1, … , tk; or perhaps some other functions of the rs. Themost direct approach—that of calculating a linear combination of r1, … , rk—has little to recommend itunless the sample sizes of all k studies are very, very large. An alternative is to estimate r from a linearcombination of the unbiased estimators G(r1), … , G(rk). Some simulation studies suggest that this ap-proach is superior to the approach of using linear combinations of r1, … , rk, but differs very little fromthe more standard approach based on linear combinations of z-transformed correlations” (p. 230).

3Federal Communications Commission. (1996). Policies and Rules Concerning Children’s Televi-sion Programming: Revision of Programming Policies for Television Broadcast Stations. MM DocketNo. 93–48.

PROSOCIAL TV META-ANALYSIS 317

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*Friedrich-Cofer, L. K., Huston-Stein, A., Kipnis, D. M., Susman, E. J., & Clewett, A. S. (1979). -Environmental enhancement of prosocial television content: Effect on interpersonal beha-vior, imaginative play, and self-regulation in a natural setting. Developmental Psychology, 15,637–646.

*Geller, M. I., & Scheirer, C. J. (1978). The effect of filmed modeling on cooperative play in disadvan-taged preschoolers. Journal of Abnormal Child Psychology, 6, 71–87.

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APPENDIXCoding Sheet Summary

Publication Information

Number of effect sizes for this referenceYear of publicationCountry (US, Canada, Europe, Australia/N.Z., Asia, other)

Subject Information

Number of subjectsAge range, mean ageSocioeconomic status: low; medium; high; mixedIQ/ability: low; mixed; highEthnicity: White/Caucasian; Black; Hispanic; Other; MixedSex: male; female; bothInstitutionalized: no; yesNote: “mixed” code only used if authors report it as mixed.

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Treatment Comparison

pretest/control vs. prosocial; neutral vs. prosocial; neutral vs. aggressiveprosocial;

antisocial vs. prosocial; antisocial vs. aggressive prosocial; neutral vs.prosocial + materials; neutral vs. prosocial + elaboration; correlation prosocial TVwith prosocial outcome; correlation prosocial TV with antisocial outcome

Treatment Information

Prosocial treatment content type: Mr. Rogers; Sesame Street; other educationalprogramming; comedy; drama; mixed TV/films; modeled behavior

Prosocial behavior rewarded: no; yes; don’t sayProduction of prosocial content: live; animated; mixRealism of prosocial treatment: self-selected prosocial content; whole TV pro-

grams/films; edited programs/films; content produced by researchersViewing time for prosocial content (minutes)Duration of prosocial treatment (days)Antisocial treatment content type: cartoon; comedy; drama; western; advertis-

ing; mixed TV/films; advertising; modeled behaviorNeutral treatment content type: cartoon; comedy; drama; nonprosocial educa-

tional program; mixed TV/films

Outcome Information

Type of outcome behavior: positive interaction (friendliness, cooperation, posi-tive affect, general prosocial play & interaction, includes increased social play byformer “isolates”); altruism (self-sacrificing kindness, generosity, helping at costto self); reduced stereotyping (attitudes or behavior); physical and mixed aggres-sion; verbal aggression.

Note: when there are multiple measures of the outcome, choose the most reli-able if reliability is given. If reliability is not given, but one measure is behavioraland one is attitudinal, use the behavioral measure. If neither of the above, averageacross the measures.

Choice of measure: only measure; most reliable measure/behavioral; averagedacross measures

How outcome was measured: researcher observation of natural behavior;teacher/parent report of natural behavior; child self-report of what they habituallydo; peer reports of children’s behavior; researcher designed behavioral task (in-cludes donating tokens/lollies in experimental situation; push–pull marble game,pressing help button); child’s reports of attitudes and hypothetical behavior; mixof natural measures; mix of measures

Time till tested: less than a day; number of days between treatment and measure

PROSOCIAL TV META-ANALYSIS 321

Design Information

Similarity of treatment and task: behavior is same as that modeled in film; sametype of thing (e.g., altruism is shown in treatment and a different altruistic outcomeis measured); general/mixed effects: general prosocial content was used, or re-searcher studied effects of one type of prosocial content on another type ofprosocial outcome (showing altruism on levels of aggression)

Assignment to treatment: random; prepost; matched (either by individual or bymatching classes); uncontrolled/self-selected

Significance of statistics used for effect size: no; yes; opposite direction to thatpredicted; mixed

322 MARES & WOODARD