The Effects of the Media on Body Image: A Meta-Analysis

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The Effects of the Media on Body Image: A Meta-AnalysisAmanda J. HolmstromPublished online: 07 Jun 2010.

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The Effects of the Media on Body Image: A Meta-Analysis

Amanda J. Holmstrom

The media have been criticized for depicting the thin woman as ideal. Some argue these images create unrealistic expectations for young women and cause body dissatisfaction and disordered eating. This study cumu- lates findings of empirical studies that examine the effects of media on body image. An estimate of overall effect size, trends in the research, and the influence of moderating variables are examined and reported. Results suggest depictions of thin women may have little to no effect on viewers. However, images of overweight women seem to have a positive effect on women's body image. Suggestions for future research are offered.

Highly publicized cases of celebrities with eating disorders, such as Princess Diana, Karen Carpenter, and Tracey Gold, have directed public concern to the causes of eating disorders. Women in particular are most plagued by eating disorders such as anorexia nervosa and bulimia nervosa, with the ratio of men to women afflicted somewhere between 1.6 and l : l O , according to the American Psychiatric Association Work Group on Eating Disorders (2000). In addition, eating disorders are becoming more prevalent in other cultures, even those in which the diseases were previously rare. Japanese and Chinese women are increasingly affected by eating disorders, and the incidence of these disorders i s rising rapidly in other non-English speaking countries such as Spain, Argentina, and Fiji (American Psychiatric Associ- ation Work Group on Eating Disorders, 2000).

The increasingly evident problem of eating disorders amongst young women has led to speculation about its cause. One prominent theory is that the media's constant depiction of extremely thin women leads women to believe they should try to meet this ideal. The claim that the media can cause eating disorders has led researchers to question whether this relationship exists. However, the results of studies designed to clarify this issue'have been far from conclusive. Though public concern is directed mainly toward the cause of eating disorders, researchers have measured media's influence not only on eating pathology but also on other constructs, such as body dissatisfaction and body size estimation. For the purpose of this study, these constructs will collectively be called "body image."

Amanda /. Holmstrom (M.A., Purdue University) is a doctoral sfudent in the Department of Communication at Purdue University. Her research interests include the relationship between media and body image.

The author wishes to extend her appreciation to Dr. john Sherry for his assistance on this project.

0 2004 Broadcast Education Association journal of Broadcasting & Electronic Media 48(2), 2004, pp. 796-217

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Some researchers claim that media have an effect on young women’s body image (e.g., Baker, Sivyer, & Towell, 1998; Botta, 1999; Harrison & Cantor, 1997; Hof- schire & Greenberg, 2002). Specifically, these researchers report that results from their studies indicate a relationship between media consumption and eating disorders, body dissatisfaction, or a number of other related outcomes. However, other researchers have come to contradictory conclusions. In fact, results of studies by Crouch and Degelman (1998) and Myers and Biocca (1992) have indicated that rather than causing an increase in body dissatisfaction, media promote positive body attitudes in young women. Other researchers claim that no relationship exists between media and body image (e.g., Borzekowski, Robinson, & Killen, 2000; Cusumano & Thompson, 1997; Jane, Hunter, & Lozzi, 1999; Stice, 1998).

At this point, a meta-analysis is a useful step toward sorting out these conflicting results. Meta-analytic reviews are more systematic, explicit, and exhaustive than qualitative reviews (Rosenthal, 1991). The number of variables included in this meta-analysis wil l allow for the examination of trends among studies including the

’ use of different media types, media exposure lengths, outcome measures, comparison stimuli, and participant ages. Meta-analysis at this stage of research on the relationship between media and body image can offer a greater understanding of the consequences of the prevalence of thin images in the media, as well as provide direction for future studies.

Literature Review

Theory

Researchers have used various theoretical underpinnings for studying the relationship between media and body image. Here, I review the theories that have been used by researchers in the area. The most common of these theories i s Festinger’s social comparison theory (Botta, 1999, 2000; Dunkley, Wertheim, & Paxton, 2001; Gro- gan, Williams, & Conner, 1996; Heinberg & Thompson, 1995; Irving, 1990; Kalod- ner, 1997; Martin & Gentry, 1997; Martin & Kennedy, 1993; Myers & Biocca, 1992; Ogden & Mundray, 1996; Posavac, Posavac, & Posavac, 1998; Richins, 1991; Shaw, 1995; Turner, Hamilton, Jacobs, Angood, & Dwyer, 1997; Wegener, Hartmann, & Geist, 2000; Wilcox & Laird, 2000). Festinger (1954) argues that people evaluate themselves through comparison with others and are more likely to compare themselves to those who are similar to them and who are attractive. This comparison is supposed to motivate one to improve if she finds herself lacking. However, researchers who use social comparison theory as a backdrop for media and body image studies suggest such comparisons could have potential negative effects. The average model portrayed in the media is approximately 5’1 1” and 120 pounds. By contrast, the average American woman is 5’4“ and 140 pounds (Wolf, 1991). Research has shown that a discrepancy between the “actual” self (attributes you and others believe

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you possess) and the "ideal" self (attributes you or others believe you should possess) can produce negative emotional states such as sadness, discouragement, and de- pression (Hatter, 1998). An average woman may be discouraged by the discrepancy between her body and that of the media ideal. Therefore, if social comparison is the mechanism at play, researchers would expect that a discrepancy between a woman's ideal body shape and her actual body shape leads to negative feelings, including body dissatisfaction.

Other researchers have both implicitly and explicitly explained a connection between media exposure and body image using Gerbner's cultivation theory as a framework (Borzekowski et al., 2000; Botta, 1999; Cusumano & Thompson, 1997; Henderson-King & Henderson-King, 1 997; Henderson-King, Henderson-King, & Hoffman, 2001; Jane et ai., 1999; Tiggeman & Pickering, 1996; Vartanian, Giant, & Passino, 2001). Cultivation theory posits that the more television a person watches, the more that person wil l believe television life is "real life" (Gerbner, Gross, Morgan, & Signorielli, 1994). Those who believe cultivation theory offers an expla- nation of the relationship between media and body image posit that thin images in the media lead people to believe the thin form is both realistic and ideal. If people do adopt the thin media ideal, researchers would expect a connection in survey research between length of media exposure and endorsement of the most prevalent body type portrayed by the media, the thin woman (Silverstein, Perdue, Peterson, & Kelly, 1986).

A third theoretical backdrop for researchers studying the relationship between media and body image is Bandura's social cognitive theory (Dunkley et al., 2001; Harrison, 1997, 2000; Harrison & Cantor, 1997; Hofschire & Greenberg, 2002; Waller, Hamilton, & Shaw, 1992). Social cognitive theory assumes that people learn and model the behaviors of attractive others (Bandura, 1994). Proponents of social cognitive theory posit that young women find thin models in the media attractive and try to imitate them through dieting and, eventually, the development of eating disorders. If young women do attempt to imitate the figures they see on television and in magazines, they would exhibit a greater degree of eating pathology.

Methodological Issues

Thus far, researchers have made some contribution to the understanding of the relationship between media and eating disorders. However, methodological inconsistencies persist, inhibiting our understanding of this relationship.

Construct clarity. A common inconsistency is the use of the term "body image." There has been no consensus on its definition. Therefore, it has been measured in a variety of ways. Some researchers have measured the degree to which subjects are dissatisfied with their bodies in response to media exposure (e.g., Hofschire & Greenberg, 2002; Irving, 1990). Other researchers have examined the degree to which subjects overestimate their body size, using the discrepancy between perceived and actual body size as an indication of body dissatisfaction (eg , Myers &

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Biocca, 1992; Vartanian et al., 2001). Others measure the degree of subjects‘ disordered eating using diagnostic scales for bulimia and anorexia (e.g., Dunkley et al., 2001; Harrison, 2000; Harrison & Cantor, 1997; Jane et al., 1999). Still others measure different constructs such as ”importance of appearance” (Borzekowski et al., 2000) and “endorsement of the thin ideal” (e.g., Botta, 1999, 2000; Stice, Schupak-Neuberg, Shaw, & Stein, 1994).

Inconsistencies in construct explication and measurement could mean that statistically significant results among these studies suggest drastically different consequences of media exposure, ranging from adopting a thin ideal to developing an eating disorder. The major concern that has been voiced, however, is whether or not media cause eating disorders. Therefore, it i s important to understand the relation of constructs such as “body dissatisfaction” and “overestimation of body size” to eating disorders. The use of such varied outcome measures leads to problems of construct validity. Claims must necessarily be consistent with measures. Since researchers and the public are primarily interested in the effect of media on eating disorder development, it is important that the outcome measure in these studies actually be an indication of eating disorder symptomatology. if a researcher measures women’s body dissatisfaction in response to a media manipulation, then it is incorrect to claim that media cause the development of an eating disorder, since eating disorder symptomatology i s not directly measured. This meta-analysis wil l allow for an examination of the relationship of a variety of different outcome measures to effect size estimates.

Media measures. in addition to different outcome measures, researchers have used a variety of media measures and manipulations. Some researchers have focused on the degree to which television viewing relates to body image (e.g., Myers & Biocca, 1992; Waller et al., 1992), while others focus on the effect of magazines on body image (e.g., Cusumano & Thompson, 1997; Dunkley et al., 2001). Others focus on one specific aspect of magazines: images of models (e.g., Crouch & Degelman, 1998; Kalodner, 1997; Martin & Kennedy, 1993). These researchers typically expose women in the experimental condition to advertisements pulled from magazines that portray thin women. The images stand alone in this condition; articles or other text contained in the magazine are removed. Many researchers focus on both television and magazine exposure (Harrison, 2000; Hofschire & Greenberg, 2001; Jane et al., 1999). Borzekowski et al. (2000) measured the degree to which both movies and computer/lnternet usage affect young women‘s body image. Understanding which media have a connection to body image may have important social implications. For example, if televised images have a large; negative impact on body image, the problem is more ubiquitous; after all, nearly everyone owns a television set, yet only 42% of young women claim they read fashion magazines (Cerbner et al., 1994; Levine, Smolak, & Hayden, 1994).

Design type. Another methodological inconsistency is design type. Survey designs typically include more participants, focus on more general trends, and measure more variables than experimental studies. Experimental designs allow researchers to have

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200 Journal of Broadcasting & Electronic Media/June 2004

greater control over extraneous variables to study the effect of specifically defined variable(s) on other variable(s) (Singleton & Straits, 1999), and to make more valid claims about causality of events. A consistent difference in effect size between the surveys and experiments will provide more specific information about the nature of the relationship of media to body image. A high effect for surveys might indicate that overall media use is related to body image, but does not provide information about causality. That is, a high effect size for survey studies could mean that media have a negative impact on body image. However, it also could be that for some reason, those with poor body image or eating disorders view more media. The controlled nature of experimental designs would provide more information about a high effect for experiments. The direction of causality would be clear and a high effect could be interpreted with more certainty that media do have a negative impact on body image.

Exposure length. In addition, the amount of time subjects are exposed to media varies greatly between experimental studies. Viewing time i s as short as 45 seconds (Crouch & Degelman, 1998) and as long as 26 minutes (Myers & Biocca, 1992). With this variation in the amount of time subjects are exposed to media, treatment strength varies widely. Because each study examines only a narrow portion of media for varying lengths of time, combining the studies in this meta-analysis wil l increase power by allowing for the examination of a variety of media measures and exposure lengths.

Age. The age of subjects participating in these studies varies as well. Researchers have studied elementary school students (eg , Harrison, 2000; Martin & Kennedy, 1993), high school students (e.g., Botta, 1999; Botta, 2000; Borzekowski et al., 2000; Shaw, 1995), and college students (e.g., Irving, 1990; Richins, 1991; Wegener et ai., 2000). Examining the correlation between age and effect size has theoretical implications. Cultivation theory would support the hypothesis that older subjects would be more greatly affected by mediated images of thin women. Older women would have been exposed to these images for a longer period of time and presum- ably have had more time to accept them as realistic. Researchers utilizing social comparison theory and social cognitive theory posit that the women who most directly identify with the models would be most likely to be affected by the images. Therefore, since most models are young women, young women are most likely to be affected.

Comparison stimuli. Another inconsistency in methodology is the type of comparison stimuli to which control groups are exposed in experimental studies. These conditions include a variety of stimuli, such as photos of normal-sized women or heavy women; television programs with normal-sized or heavy women; and photos of homes and gardens. Social comparison theory assumes that people wil l compare themselves with others they consider similar. If social comparison theory is the mechanism at work, the meta-analysis may shed light on the effects of subjects’ comparison with mediated images of thin women. It may also provide information about the varying effects of subjects who compare themselves with photos provided

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Holrnstrorn/MEDIA AND BODY IMAGE META-ANALYSIS 201

for the control conditions, including images of overweight or average-weight women. For example, it is possible that a young woman's body image i s affected similarly after exposure to photos of average-weight or thin women. In addition, the type of comparison stimulus raises questions of treatment strength: For example, photos of average-sized women may have more effect on body image than photos of gardens.

Meta-Analytic Objectives

A meta-analysis of the existing studies of the effects of media on body image wil l provide important information and direction for future research. This article wil l address seven objectives: (a) provide a cumulative measure of effect size across all studies, (b) test for consistent differences in effect size due to type of media measure, (c) test for differences in effect size due to outcome measure, (d) test for differences due to study type, (e) test for differences due to comparison stimulus, (0 demonstrate any relationship between effect size and age of subjects, and (g) demonstrate any relationship between effect size and treatment length.

Method

This section describes three phases of the meta-analysis: (a) the method of selecting and coding studies for inclusion, (b) the method of deriving effect size estimates from the studies, and (c) the procedure for statistical analysis of the effect sizes.

Study Selection and Coding

Literature search. A search of literature from January 1920 to January 2002 was undertaken using online data bases (ComAbstracts, Psyclnfo). Keywords for both indexes generally included "body" or "eating" and "media," "television," or "magazines," as well as variations of these terms such as "body image," "eat," or "N." indexes were searched as far back as they reached in order to obtain all available research on media and body image; the earliest usable study was published in 1990. The searches resulted in excess of 3,300 citations, many of which were redundant across indexes. Titles and abstracts were examined to locate literature reviews that addressed the effects of media on body image. Literature reviews fitting this descrip- tion were obtained and the reference sections were examined in order to locate additional studies. These additional studies were added to the collection, and their reference sections were scanned for other studies. The process continued until no new studies emerged. In addition, six authors of dissertations which fit the selection criteria were contacted for their data via e-mail, but none responded.

The narrowed search resulted in 54 independent studies in which some measure

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of media exposure was the independent variable, and some measure of participants' weight-based body image, valenced feelings about thinness, or eating pathology was the dependent variable. Of these, three studies were excluded because they were content analyses (Levine et al., 1994; Mondini, Favaro, & Santonastaso, 1996; Thompson & Heinberg, 1999). One experiment was excluded because participants in all experimental conditions saw images of thin women and there was no control group from which to calculate an effect size Clung, Lennon, & Rudd, 2001). Seven studies were excluded because they contained no direct measure of visual media exposure (Brewis, 1999; Cash, Cash, & Butters, 1983; Dittmar & Blayney, 1996; Dittmar, Lloyd, Dugan, Halliwell, Jacobs, & Cramer, 2000; Lavin & Cash, 2001; Ogden & Elder, 1998; Stice, 1998). Three studies were discarded because insuffi- cient data was available to calculate an effect size: For example, some studies did not include reports of standard deviations (Champion & Furnham, 1999; Edwards-Hewitt & Gray, 1993; Pinhas, Toner, Ali, Garfinkel, & Stuckless, 1999). Studies were also excluded because they did not measure the relationship between exposure to thin images in the media and the subjects' own body image, which is the definition of "body image" for this study. For example, two studies were discarded because subjects were asked to measure the attractiveness of a model rather than evaluating their own attractiveness (Kenrick & Gutierres, 1996; King, Touyz, & Charles, 2000). Another study was excluded because though it did include media exposure as an independent variable and eating pathology as a dependent variable, the researchers contrasted the eating pathology of two groups whose lifetime media exposure was drastically different (Baker et al., 1998). Some participants were sighted, while others had been blind from birth and had never seen thin images. It was ultimately decided that this study was too much of a departure from the other studies. Two studies were excluded because the outcome measure, body self-consciousness, measured trait awareness of one's body (items measuring body self-consciousness include: "I get up about the same time every day" and "1 eat about the same time every day"). To be included in this meta-analysis, the outcome measure must be some type of evaluation of one's body, primarily based on weight, and these studies did not include such measures (Kalodner, 1997; Wegener et al., 2000). One study was excluded because the outcome measure was amount of food eaten in an experimental study, which also did not directly measure feelings about one's body or eating pathology (Seddon & Berry, 1996). A total of 34 studies remained for which effect size estimates could be calculated (see Table 1 for descriptives of the 34 studies).

In some cases, a study contributed multiple effect sizes. For example, one study might use multiple outcome measures or multiple media measures. Because many studies included multiple hypotheses with multiple effect sizes, the effect sizes were analyzed both by study (to avoid problems of non-independence) and when appropriate, by sub-analyses of individual hypotheses (n = 146).

Coding. Study coding sheets included entries for the following characteristics: study descriptives, sample characteristics, research design, media measure, and

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Table 1 Descriptives of the 34 Included Studies

Mean Age of Effect Size Study Participants Type of study N Estimate

Borzekowski et al. Botta, 1999 Botta, 2000 Crouch & Degelman Cusumano & Thompson Dunkley et al. Grogan et al. Hamilton & Waller Harrison, 1997 Harrison, 2000 Harrison & Cantor Heinberg & Thompson Henderson-King et al.,

Henderson-King et al.,

Henderson-King et al.,

Hofschire & Greenberg Irving Jane et al. Martin & Gentry Martin & Kennedy

1997

2001, Study 1

2001, Study 2

Myers & Biocca Ogden & Mundray Posavac et al., Study 1 Posavac et al., Study 2 Posavac et al., Study 3 Richins, Study 3 Richins, Study 4 Shaw Stice et al. Tiggemann & Pickering Turner et al. Vartanian et al. Waller et al. Wilcox & Laird

14.9 15.1 9 15.28 15.4 24

15.5 17-32 26.45

20 14.68

20 22.85

19

19

19 15

college 21.1 11.85

4'h, 8th, 12'h grade

20.8 18-24

18-25 18-25 18-25

college college

20.9 20

15.5 18.63 22.6

- 28 18-35

Survey Survey Survey Experiment Survey Survey Experiment Experiment

Survey Survey Experiment

Experiment

Experiment

Experiment Survey Experiment Survey Experiment Experiment

Experiment Experiment Experiment Experiment Experiment Experiment Experiment Experiment Survey Experiment Experiment Survey Experiment Experiment

Survey

83 7 214 145 40

175 577 45 48

232 178 232 138

82

222

112 3 82 162 87

2 68 144

76 40

136 181 53

145 80 48

238 94 49

2 78 64 41

.03

.oo - .02

.34 - .07

.I 5

.2 6

.07

.08

.oo

.I 8

.19

.03

.06

.09

.I 9

.I 1

.09

.oo

.oo

-.17 .52 .11 .05

-.11 .2 3 .24 .06 .18 .I 0 .08

- .03 .07 .39

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204 Journal of Broadcasting & Electronic MedialJune 2004

results. Study descriptives include: title, author(s), date of publication, and type of report (e.g., journal article, dissertation). Sample characteristics were recorded for treatment and control conditions across the following categories: sample size, age, percentage female, number of subjects with anorexia nervosa, and number of subjects with bulimia nervosa. The type of sampling used to select the participants was also recorded.

Research design was recorded for all included studies. Thirteen studies were surveys, accounting for 105 hypotheses. The remaining 2 1 studies were experimental designs (hypotheses, n = 41). The type of media measure was also recorded for both surveys and experiments. These media fell into six general categories: magazine, photo (images from magazines), television, generalized mass media, movies, and computerhternet. Ten studies including 32 hypotheses were examined using a measure of magazine exposure ranging from fitness to fashion magazines. Typically, this measure was used in survey studies to gauge the amount of time subjects spent looking at magazines during a week. Seventeen studies (hypotheses, n = 29) were examined using a “photo” measure. Researchers using the photo measure excerpted advertisements containing thin women, removed any text, and showed the images to participants in experimental studies. A television measure is the third type (studies, n = 11; hypotheses, n = 67), which typically involved either asking participants how much television they watch in a given time frame (for surveys), or exposing them to television programs (for experiments). Three studies (hypotheses, n = 7) included a general mass media measure, which measured general media use and did not include adequate information to interpret use more specifically. One study (hypotheses, n = 2) included a movie measure (survey items gauging how much time the participant spent watching movies), and one study (hypotheses, n = 2) included a computer measure (survey items gauging how much time the participant spent at the computer).

In addition, the measure of body image employed in the study was recorded. Over 30 different scales were used to measure a variety of different body image outcomes. These measures each fall under one of four broader categories: importance of appearance, eating pathology, body dissatisfaction, and endorsement of the thin ideal. The first of these is “importance of appearance” (studies, n = 2; hypotheses, n = 11). Importance of appearance is a measure developed by Borzekowski et al. (2000) in order to gauge how much value young women place on their physical appearance. Importance of appearance is assessed by asking participants how important they think it i s to have a thin body shape or to be physically attractive. A second general category of outcome measure relates to eating patterns, such as measures of restrained eating or eating pathology (studies, n = 13; hypotheses, n = 67). Diagnostic measures of eating disorders are included in this general category, such as the Eating Disorders Inventory (Garner, Olmstead, & Polivy, 1983) and the Bulimia Test (BULIT; Smith & Thelen, 1984). A third, more general outcome measure i s “body dissatisfaction” (studies, n = 27; hypotheses, n = 61). These scales include questions about how satisfied the subject is with her body shape and weight at the

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present time. Some measures in this general category include the Body Esteem Scale (Franzoi & Shields, 1984) and the body dissatisfaction subscale of the Eating Disorders Inventory (Garner, et al., 1983). Another type of body dissatisfaction measure is body size estimation. These measures include body image detection devices (e.g., Ruff & Barrios, 1986). The subjects are asked to indicate the size they believe parts of their body to be, including their chests and waists. Subjects’ estimation of body size is compared with the subjects’ actual size, and the discrepancy between the two measures i s an indication of body dissatisfaction. A fourth category of outcome measure is endorsement of the thin ideal. Stice et al. (1 994) and Stice and Shaw (1994) created this measure by asking subjects in a pilot study to generate statements about the ideal female body. These statements were then used to create a measure including items like ”the ideal woman should be slender and thin” and “the ideal woman should always be dieting.” This measure differs from importance of appearance measures because it does not measure how important thinness is to young women but whether or not they believe thinness i s ideal. This scale was used to examine five hypotheses from three studies.

The type of images shown to the control group was also recorded. Categories of comparison stimuli included: images of average weight women (eg , pictures of women at a local college; studies, n = 10; hypotheses, n = 14), images of overweight women (e.g., pictures of plus-sized models; studies, n = 3; hypotheses, n = 6), and comparison with “non-human images” (e.g., pictures of homes or gardens; studies, n = 10; hypotheses, n = 18).

Effect size estimate. Pearson‘s r was used as the effect size estimate as it is more flexible and easy to interpret (Rosenthal, 1991). In the survey studies, reported correlations between media use and the body image outcome measure were used as the effect size. For experimental studies, an effect size was calculated when a comparison between treatment and control conditions was reported. When means, standard deviations, and cell sizes were reported, Cohen’s d (Cohen, 1988) was calculated and converted to Pearson’s r. Cohen’s d is the difference between treatment mean (YE) and control mean (Yc) standardized by dividing by an estimate of the within group standard deviationb) and was calculated using Equation 1 :

d=- Y E - Yc S

The within-group estimate of variance for the denominator (5’) was calculated as directed by Hunter, Schmidt, and Jackson (1982) to lower the standard error of the estimate (Equation 2):

(NE- 1)s: + (Nc - 1)s: 52 =

NE+ N c - 2

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The estimate of Cohen's d was converted to Pearson's r using Equation 3:

d 4 (N - 2)

In the remaining studies that did not provide means, standard deviations, and cell sizes, a variety of methods were used to extract an effect size estimate including conversion from t-tests, and conversion from F with 1 degree of freedom in the numerator (for formulas, see Rosenthal, 1991).

Effect sizes for each hypothesis were calculated then averaged so that each study contributed only one effect size. This estimation strategy guarantees that each sample contributes one effect size, and those studies that include only one effect size estimate carry the same weight as studies which include up to 10 or 20 effect sizes. The overall, unweighted effect size was calculated for the 34 studies included in the meta-analysis and i s reported as a Pearson correlation, r = . I 0. Mean weighted effect size was then calculated for the 34 studies. The weighted effect size i s an average in which each correlation is weighted by the number of participants in that study and i s the best estimate of cumulative effect size (Hunter et al., 1982). Thus, a study with 300 subjects contributes more to the mean effect size than one with only 40 subjects. The weighted effect sizes per study are reported in Table 1, and the overall mean weighted effect size for all studies was r = .08. Next, the amount of variance that is due to sampling error was calculated and subtracted from the residual variance. Subtracting the sampling error helps to eliminate variance in the studies due to imprecise measures (Hunter et al., 1982). Variance remained after sampling error was subtracted (ap = .02), suggesting that moderating variables are present.

Though it does account for non-independence of effect sizes, averaging effect sizes by study has some negative consequences. The methods, particularly the outcome measures, utilized in these studies are very different, and for some sub- analyses, averaging for one effect size per study does not provide as much detail about the relationship between media and body image. A mean effect size repre- senting the Pearson correlation between media use and body image measures was calculated for each of the 146 hypotheses included in the meta-analysis. The estimate of the unweighted mean effect size was r = .OO. Next, the estimate of the weighted mean effect size was calculated by hypothesis, r = .05. Variance remained after subtracting the effect of sampling error (up = .02).

The somewhat smaller overall effect size when calculated by hypothesis is likely due to a few studies that included up to 20 very small effect sizes. Once those effect sizes were cumulated by study, the overall effect size became slightly larger.

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Categorical Analysis-Methodology

A series of categorical analyses were undertaken to determine whether the residual unexplained variance was due to differences in methodology, including: survey vs. experiment, type of body image outcome measure, type of media measure, and type of comparison stimulus.

In the case of study design, there i s virtually no difference in effect size between experimental ( r = .08, n = 21) and survey studies ( r = .07, n = 13). There i s some variance for experimental studies and surveys that remains unexplained (experimental, up = .03 and survey, up = .01).

A categorical analysis was conducted comparing type of outcome measure used. Studies were categorized according to whether the measure related to importance of appearance, body dissatisfaction, eating pathology, or endorsement of the thin ideal. Effect sizes for outcome measures were averaged so that each study contributed only one effect size per outcome measure. By averaging effect sizes by study, each participant’s reported body image is recorded only once. The results of these analyses indicate differences in effect size between outcome measures (importance of appearance, r = .03, n = 2; body dissatisfaction, r = .08, n = 27; eating pathology, r = .08, n = 13; and endorsement of the thin ideal, r = .08, n = 3). In addition, there i s residual unexplained variance in all categories except importance of appearance (body dissatisfaction, up = .01; eating pathology, up = .01; and endorsement of the thin ideal, up = .02). Another categorical analysis was conducted comparing type of outcome measures used; this time, the level of analysis was by hypothesis. This analysis was conducted because some studies contained multiple operationalizations of the same measure types (i.e., multiple body dissatisfaction or eating pathology measures). When analyzed by hypothesis, the effect sizes are smaller but st i l l differ by outcome measure (importance of appearance, r = .03, n =

11; body dissatisfaction, r = .05, n = 61; eating pathology, r = .05, n = 67; endorsement of the thin ideal, r = .02, n = 5). However, when analyzed by hypothesis, there i s only residual unexplained variance for the body dissatisfaction category (up = .03).

Because variance remained only for the body dissatisfaction measure, a second, more specific sub-analysis was conducted with the hypothesis as the unit of analysis. This sub-analysis broke body dissatisfaction measures into five groups. The first group includes the body dissatisfaction scale of the Eating Disorder Inventory (n =

18). This group was isolated because this scale, unlike other body dissatisfaction measures, was specifically developed to be an indicator of eating disorder symptomatology. The second group of body dissatisfaction measures includes body size estimation measures such as body image detection devices (eg , Myers and Biocca, 1992). These measures include the discrepancy between participants’ actual and perceived size as an indication of body dissatisfaction (n = 10). The third group of body dissatisfaction measures includes measures that are designed to capture

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participants' overall, global body dissatisfaction (n = 13; items include "I am satisfied with my body" and "My weight is appropriate for my heighf'). These measures include Huddy's body dissatisfaction scale (Huddy, Nieman, & Johnson, 1993) and the Body Attitudes Questionnaire (Ben-Tovim & Walker, 1991). The fourth group of body dissatisfaction measures include items measuring participants' satisfaction with individual body parts (n = 30; items include "I am satisfied with my butt" and "1 am satisfied with my waist"). These scales include the Body Esteem Scale (Franzoi & Shields, 1984) and the Body Satisfaction Scale (Slade, Dewey, Newton, Brodie, & Kiemle, 1990). The last group of body dissatisfaction measures include those called "body dissatisfaction measure" and do not provide enough information for further interpretation (n = 6).

Effect size estimates for each category vary (body dissatisfaction subscale of the Eating Disorders Inventory, r = -.02; body size estimation measures, r = .03; global body dissatisfaction measures, r = .I 7; individual body parts measures, r = .02; and general, non-specific measures, r = .16). Variation within groups should not be great since the scales are designed not only to measure the same constructs but also do so in the same way. However, variance remained for all groups (body dissatisfaction subscale of the Eating Disorders Inventory, up = .01; body size estimation measures, up = .03; global body dissatisfaction measures, up = .02; individual body parts measures, up = .02; and general measures, up = .01).

Another categorical analysis was performed that compared the type of media measure used. Studies were categorized according to exposure to the medium type. The different media measure categories are: magazine, photo, television, mass media, movies, and computer. The mean effect sizes differ by media measure (magazine, r = .08, n = 39; photo, r = .lo, n = 29; television, r = .03, n = 67; mass media, r = .04, n = 7; movies, r = .OO; n = 2; and computer, r = .OO, n = 2). There i s residual unexplained variance remaining in the magazine, photo, television, and mass media measures (magazine, up = .01; photo, up = .04; television, up = .01; mass media, up = .01; movies, up = .OO; computer, up = .OO).

Next, a categorical analysis was performed for the type of comparison stimulus used in experimental studies. Studies were categorized according to the type of images the control group was exposed to. These include images of average weight women (e.g., pictures of women at a local college), overweight women (e.g., pictures of plus-sized models), and "nonhuman images" (e.g., pictures of homes or gardens). When compared by study, mean effect sizes differed for the comparison stimuli (average weight women, r = .11, n = 10; overweight women, r = .29, n = 3; nonhuman images, r = .03, n = 10). There is residual unexplained variance remaining for the average weight (up = .02), overweight (up = .02), and nonhuman category stimuli (up = .04).

Correlational Analysis-Theoretical Moderators

A number of theoretically significant variables may moderate the effect of media on body image, including the age of the subjects and length of exposure to the

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medium. These variables are ratio level data and can be examined correlationally by study.

For survey and experimental studies combined, effect size i s negatively correlated with the length of media exposure ( r = -.07), suggesting that the longer the subject is exposed to media, the better she feels about her body. However, the correlation between effect size and length of exposure differs for experiments and surveys. For experimental studies-in which “length of time” denotes the amount of time participants are exposed to images during experimental procedures (in this case, from 45 seconds to 26 minutes)-the relationship between effect size and length of exposure is similar to the overall correlation between these variables ( r = -.07). For surveys-in which “length of time” refers to the participants’ reports of weekly media exposure in hours-the correlation between effect size and length of exposure is negative but much larger ( r = -.39). This correlation suggests that the more time participants report viewing media, the better they feel about their bodies.

Lastly, there i s a small, negative correlation between effect size and age ( r = -.07), suggesting that the older the participant, the better she feels about her body.

Discussion

This meta-analysis was conducted in order to shed light on the methodological and theoretical issues surrounding the relationship between media and body image in hopes of providing direction for future research. The goals of the meta-analysis were to provide a cumulative effect size for all media and body image studies, test for consistent differences in effect size due to study type, test for differences in effect size due to type of media measure, test for differences in effect size due to type of outcome measure, test for differences in effect size due to type of comparison stimulus, test for differences due to length of viewing time, and to test for differences due to subject age.

Overall Effect

Increasing the number of subjects by combining studies provides a better overall estimate of the relationship between media and body image. Cohen (1 988) defines a small effect as d = .20, a medium effect as d = .50, and a large effect, d = .80. The overall effect size when converted and analyzed by study is d = .I6 and when analyzed by hypothesis i s d = .08. This analysis suggests that there is a relationship between media and body image, but that relationship is very small. The effect sizes were normally distributed (skewness = .64; kurtosis = 2.56). The mode effect size was r = .OO, and the correlation between media and outcome measure was zero or very small for many studies. Because most of the studies had relatively low effect sizes, when averaged, the overall effect size when averaged by study was also low.

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21 0 Journal of Broadcasting & Electronic MedidJune 2004

More sophisticated analyses led to important insights about the relationship between media and body image.

Thin is the Norm

A great deal of variance remains for the experimental studies (up = .04). Most of these studies are categorized in the "photo" experimental condition, in which participants are exposed to advertisements from magazines that depict thin models. Indeed, much variance remains in the photo condition (up = .04) and helps to explain the variance remaining within experimental studies. The experiments utilizing a photo measure are among the most similar and most controlled of all included in this meta-analysis: Subjects are shown advertisements of thin models with no overlaid text and are then questioned about their body image. One inconsistency among these studies, however, i s the comparison stimulus to which the control group is exposed. Some are exposed to images of average-weight women, some are exposed to images of overweight women, while others are exposed to non-human images, such as gardens or homes.

When analyzed separately, these differing control conditions produce greatly different effect sizes. The average effect sizes for studies using images of average- weight women or non-human images were small, r = .I 1 and r = .03, respectively (by hypothesis, r = .04 and r = .05). Since there is little difference between the control and experimental groups, these effect sizes suggest that viewing images of average-weight women or non-human images is equivalent to viewing images of thin women. The average effect size for studies using images of overweight women as the control stimulus was medium, r = .29 (by hypothesis, r = .38). This average effect size suggests either that the women who view the thin images feel worse about their bodies, or the women who view the overweight images feel better. Because there was little difference between the experimental and the control groups in the other two comparison stimuli categories (particularly when analyzed by hypothesis), it appears that viewing thin images has an effect that is similar to viewing images of homes and gardens-none. However, viewing images of overweight women changes the body image of participants in a positive manner-they actually feel better about their bodies.

It is commonly expected that women should feel bad about themselves after viewing thin images. However, this meta-analysis does not support that view. Social comparison theory lends insight to these findings. It i s possible that there is little to no effect for viewing thin images because women are not comparing themselves to the images. One reason women may not compare themselves with thin images is because these images are so common they no longer evoke a response. The media are saturated with depictions of thin women. They are on nearly every television program, magazine cover, and billboard. If a woman was to compare herself with every photo of a thin model she encounters, she would spend most of her day engaging in social comparison. Participants exposed to these thin images in an

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Holmstrom/MEDIA AND BODY IMAGE META-ANALYSIS 21 1

experimental condition could likely remain unfazed by the depictions since they are so common.

If viewing images of thin women does not change the participants’ body image, how can the significant effect size for those studies employing images of overweight women as the control stimuli be explained? Social comparison theory also posits that people engage in downward comparisons. By comparing themselves with those less fortunate, people increase their satisfaction with themselves (Suls & Wheeler, 2000). Since the participants are young women and therefore less likely to be overweight than those in other age groups (Mokdad, Bowman, & Ford, 2003), a comparison with images of heavy women should increase their satisfaction with their bodies. In such a case, the fairly large effect size for those studies is not due to the women in the “thin images” condition feeling worse about themselves, but rather to the women in the “overweight images” condition feeling better.

Though these findings are interesting, future research i s necessary to further explore and help explain them. In addition, addressing the issue of media saturation of thin images is important. Because these images are so prevalent, women may not attend to them, even in an experimental setting. Exposing an experimental group to either ultra-thin, anorexic women or very overweight women may have an effect on their body image since these images are much less common in the media. Such images might induce a downward social comparison, causing the participants to feel better about their bodies. Including striking, out-of-the-ordinary stimuli may prove to be valuable tactics for future research.

length of Exposure

The sub-analyses concerning length of media exposure led to results that warrant speculation. Overall, the relationship between length of exposure and effect size was very small and negative ( r = -.07). Experimental studies, in which length of exposure denotes the length of time participants were exposed to stimuli, followed this same trend ( r = -.07). Participants in experimental studies were exposed to anywhere from 45 seconds to 26 minutes of images. The correlation indicates that the longer the participants were exposed to mediated images, the better they felt about their bodies. The correlation, however, is rather small. The relationship between length of exposure and body image for survey studies is also negative but much larger ( r = -.39). Length of exposure for survey studies refers to the amount of time participants reported viewing media over the course of a week. This strong, negative correlation indicates that the more time participants reported using media, the better they felt about their bodies.

Overall, the effect size estimate for the relationship between media use and body image is very small. However, the correlation between length of exposure and body image for women who report watching more media suggests that for this subset of women, there may be a more sizable, positive effect. This correlation i s counter to the popular belief about the effect of media on body image. Cultivation theory posits

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that the more media we consume, the more we wil l accept the content of media as "real life." Therefore, women who consume a great deal of media should accept the thin ideal as realistic. If women accept the thin ideal and do not measure up to this ideal (most women do not), it follows that they would be less satisfied with their bodies, not more satisfied.

Social comparison theory can help to explain why women who report more media exposure feel better about their bodies. Social comparison theory has been used often in the media and body image literature to explain why women might feel bad about themselves when they do not compare favorably with thin models. However, social comparison theory maintains that in order to enhance their motivation to improve on a particular dimension (in this case, weight), people may compare themselves with others who are slightly better on that dimension. Social comparison may increase satisfaction on that dimension because people can see the results of an improvement and become motivated. Therefore, some women, particularly those who report engaging in more media use, may seek out thin images in order to gain motivation to lose weight and exercise. This inspiration could lead to increased body satisfaction. For example, a young woman who reports reading a number of fashion magazines may use the magazines to gather ideas to help her make fashion and exercise choices, which in turn make her feel good about her appearance.

In order to determine why women who report greater media consumption feel better about their bodies, it is important to move from experimental and cross- sectional survey designs. Focus groups may help us understand how media affects frequent viewers' body image. Longitudinal designs may offer insight about what effect media exposure has over time. Perhaps at one time, these viewers were affected negatively by thin images, but over time that effect diminished. Only longitudinal studies can answer this question.

Method, Outcome Measure, and Age

A number of variables included in the meta-analysis were revealed to be relatively unimportant, including method, outcome measure, and age of the participants. Very little difference was discovered between survey and experimental designs. The average effect size for the experimental studies was, by study, r = .08, and by hypothesis, r = .08, while the average effect size for the survey designs was, by study, r = .07, and by hypothesis, r = .04. This small difference is relatively negligible and thus indicates that regardless of the research technique utilized, very small effect sizes are obtained.

Researchers employed a variety of different outcome measures, ranging from measuring the participants' perception of the importance of their appearance to the participants' eating disorder symptomatology. The average effect sizes by hypothesis, when broken down by outcome measure, are all very small, ranging from r = .02 for

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endorsement of the thin ideal to r = .05 for body dissatisfaction. They range from r =

.03 to r = .08 by study. There are several potential reasons for the low average effect sizes garnered by

these studies. The first i s that the media do not have an effect on body image. The second i s that media do have an effect on body image, but it is not captured by our measures. In particular, body dissatisfaction measures are problematic. “Body dissatisfaction” was identified as the outcome measure in nearly all of the studies included in the meta-analysis ( n = 27) , but i t i s the only outcome measure for which variance remained after sampling error was subtracted. This remaining variance is likely due to the variation within body dissatisfaction measures themselves. When body dissatisfaction measures were broken down more specifically into groups, an interesting pattern emerged. Most body dissatisfaction measure groups had very low average effect size estimates (body dissatisfaction subscale of the Eating Disorder Inventory, r = - .02, body size estimation measures, r = .03, individual parts measures, r = .02). However,

. larger effect sizes were garnered when the body dissatisfaction measures were designed to capture general body image ( r = .17) or were unspecified ( r = .16). These varied results suggest that body dissatisfaction scales are probably not measuring the same construct. Researchers should consider what type of measure they are using and what statistically significant results garnered by their studies mean. For example, body size estimation may not be the same as global body dissatisfaction. In fact, body size estimation measures differ themselves and may not be measuring the same construct. The results from this sub-analysis indicate that media may impact global body satisfaction, and in the future, researchers should consider using measures designed to capture that effect.

Interestingly, the body dissatisfaction subscale of the Eating Disorders Inventory produced a very small effect size that indicates women feel more satisfied with their bodies after media exposure. This scale has been developed to be an indicator of eating disorder pathology. If researchers and the public are interested in the media’s impact on eating disorder development, this effect size coupled with the small overall effect size estimates calculated for eating disorder diagnostic scales ( r = .08 when analyzed by study; r = .05 when analyzed by hypothesis) may indicate that there i s no effect. The common belief i s that media do have an effect on eating disorder development, but that belief may be wrong.

Theoretically, type of outcome measure should be important. However, incon- sistent scales prevent us from seeing this difference. Body dissatisfaction measures are particularly important if social comparison processes are at work. Social comparison theory indicates that after comparison with another, we are likely to experience a change in satisfaction with ourselves on a particular dimension. Therefore, if social comparison processes do underlie the relationship between media and body image, we need to have a firm grasp on what “body satisfaction” truly means.

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Conclusion

This meta-analysis has shed light on some important trends in the research on the relationship between media and body image. First, the sub-analyses conducted on type of comparison stimulus revealed that thin images seem to have little effect on participants' body image. This result could indicate that women are so accustomed to seeing thin images that these images no longer lead to changes in body satisfaction. Overweight images, however, tended to substantially increase participants' body satisfaction. Downward social comparison theory lends support for the hypothesis that engaging in downward comparisons with overweight models has a positive effect. However, it is important to note that women who report viewing media for longer periods of time also report greater body satisfaction. These women may be engaging in social comparison processes that enhance their view of their bodies. Longitudinal designs and focus groups can offer more information about these findings.

Additionally, examination of the literature revealed methodological shortcomings that may have theoretical significance. Specifically, differences in outcome measures, including body dissatisfaction, could be clouding results. Explicating constructs and carefully choosing appropriate measures wil l aid in interpretation of these findings.

The findings of the meta-analysis should be interpreted carefully, however. A relatively small number of studies in the sub-analyses limit the conclusiveness of the findings. Future research i s needed to further explore the findings suggested by the meta-analysis. Specifically, a manipulation of exposure length, outcome measures, and stimulus materials wil l provide greater understanding of the relationship between media and body image.

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The Effects of the Media on Body Image: A Meta-Analysis