Day-to-day body-image states: Prospective predictors of intra-individual level and variability

Body Image 4 (2007) 1–9 www.elsevier.com/locate/bodyimage

Day-to-day body-image states: Prospective predictors of intra-individual level and variability Jonathan A. Rudiger a, Thomas F. Cash a,b,*, Megan Roehrig c, J. Kevin Thompson c a

b

Virginia Consortium Program in Clinical Psychology, Virginia Beach, VA, United States Department of Psychology, Old Dominion University, Norfolk, VA 23529-0267, United States c University of South Florida, Tampa, FL, United States

Received 17 July 2006; received in revised form 28 October 2006; accepted 10 November 2006

Abstract Most body-image research has focused on the trait level of body-image evaluation, often neglecting the momentary fluctuations many people experience in everyday life. The present prospective study investigated whether theory-relevant body-image measures, perfectionistic self-presentation, and eating attitudes would predict average day-to-day body-image levels and their intra-individual variability. A convenience sample consisted of 121 women from two universities. In Phase 1 of the study, participants completed an online battery of selected body-image and personality questionnaires. In Phase 2, participants went online to complete the dependent measure, the Body Image States Scale, once per evening over 10 days. As hypothesized, more favorable body-image state levels were associated with less investment in appearance for self-worth, less body-image disturbance, fewer body-image cognitive distortions, less disturbed eating attitudes, and lower body mass. Moreover, greater day-to-day body-image variability was predicted by greater psychological investment in appearance, more body-image cognitive distortions, and higher perfectionistic self-presentation. Implications and future directions for research are discussed. # 2006 Elsevier Ltd. All rights reserved. Keywords: Body-image states; Body-image assessment; Body-image disturbance; Appearance self-schemas; Perfectionism; Eating attitudes

Introduction Body image is a multi-faceted construct defined by individuals’self-perceptions and attitudes regarding their bodies, especially their appearance (Cash & Pruzinsky, 2002; Thompson, Heinberg, Altabe, & Tantleff-Dunn, 1999). There is a noticeable dearth of research that directly assesses persons’ body-image experiences over time in everyday life. Body-image research characteristically focuses on stable traits of body-image satisfaction/dissatisfaction. Although body image may be

* Corresponding author. Tel.: +1 757 683 4439; fax: +1 757 683 5087. E-mail address: [email protected] (T.F. Cash). 1740-1445/$ – see front matter # 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.bodyim.2006.11.004

usefully understood at the trait level, real-life situational events and contexts can instigate fluctuations in bodyimage states for susceptible individuals (Amorose, 2001; Cash, 2002a, 2002b, 2002c; Melnyk, Cash, & Janda, 2004; Tiggemann, 2001). Most research on intra-individual variability (IIV) in self-evaluative states has focused broadly on feelings of self-worth or self-esteem (e.g., Greenier et al., 1999; Kernis, Cornell, Sun, Berry, & Harlow, 1993; Kernis, Greenier, Herlocker, Whisenhunt, & Abend, 1997; Kernis et al., 1998; Paradise & Kernis, 2002). Selfmonitored on multiple occasions over time (e.g., a week), self-esteem stability (or instability) is defined as short-term variations that individuals report in their momentary, situationally based feelings of self-worth. The standard deviation of these states is typically used

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to index IIV, and the mean of these states reflects their average level. Drawing from this literature, Melnyk et al. (2004) specifically assessed body-image states in the context of everyday life among college women. In this study, participants initially completed a battery of predictor measures and subsequently called an automated telephonic response system twice daily for 6 days to convey their current body-image experiences on the validated Body Image States Scale (Cash, Fleming, Alindogan, Steadman, & Whitehead, 2002). The researchers examined the extent to which selected pre-test variables predicted the level and variability of body-image states. As hypothesized, less favorable average body-image state levels were associated with lower trait body-image satisfaction, more body-image dysphoria, more schematic investment in appearance, more disturbed eating attitudes, and the use of less adaptive and more maladaptive body-image coping strategies. Also as expected, greater body-image IIV was predicted by more dysfunctional investment in one’s appearance, more disturbed eating attitudes, and greater reliance on appearance-fixing coping strategies. Heavier women had poorer average body-image levels but were not different in their IIV from lighter weight women. The central purpose of our prospective investigation was to build upon Melnyk et al. (2004) to further understand variables predictive of body-image states, both IIV and average level. Our different methodology had participants report body-image states via webbased data collection once per day over a 10-day period. In part because Melnyk et al.’s 6-day study did not find morning-evening differences in state body image, we elected to assess states only in the evenings but over more days. Presumably, evening assessments could capture the impact of body-image threats or challenges that occurred during the day and that were or were not effectively resolved. We sought to replicate several of the previous findings by including appearance investment (schematicity), eating attitudes, and body mass as predictors. Greater appearance investment and eating pathology were expected to predict poorer average levels and higher IIV of body-image states. Heavier participants were expected to have poorer state levels. We also tested hypotheses related to three new predictor variables—body-image disturbance, bodyimage cognitive distortions, and perfectionism in social self-presentations. Body-image disturbance refers to a continuum of persons’ body-image dissatisfaction, distress, and dysfunction (Cash,

Phillips, Santos, & Hrabosky, 2004). Body-image cognitive distortions are information-processing biases and errors that people may commit as they think about their appearance during body-image threats or challenges (Jakatdar, Cash, & Engle, 2006; Williamson, Stewart, White, & York-Crowe, 2002). A propensity toward such distortions represents a risk factor for body-image dysphoria in everyday life. Finally, unlike trait perfectionism (a need to be perfect), perfectionistic self-presentation refers to the need to seem perfect (and not imperfect) to others, which may be a risk factor for body-image and eating disturbances (McGee, Hewitt, Sherry, Parkin, & Flett, 2005). Hypotheses In sum, based on the aforementioned findings and literature, we hypothesized that women with higher (more satisfied) average levels and less variable bodyimage states over the 10-day period would have the following pre-test characteristics: (1) less body-image investment, especially investment in appearance for self-worth; (2) lower levels of multi-faceted bodyimage disturbance; (3) commission of fewer bodyimage cognitive distortions; (4) less perfectionistic selfpresentation; (5) fewer problematic eating attitudes. Finally, based on Melnyk et al.’s (2004) findings, women with a lower BMI were hypothesized to have slightly more favorable yet not necessarily more stable body-image states. Method Participants A total of 243 women from Old Dominion University (ODU) and the University of South Florida (USF) initially volunteered to participate for extra credit in their psychology courses. A large number of women (n = 122) were excluded from analysis because they did not comply with the study’s requirements. Noncompliance analyses are presented in the Results section. The remaining 121 participants (74 from USF and 47 from ODU) ranged in age from 18 to 61 years, with a median age of 21 (SD = 7.3). The sample consisted of 67.8% White women, 13.2% African Americans, 7.4% Hispanic/Latinas, 6.6% Asians, and 5% who reported no or ‘‘other’’ ethnicity. Most women were exclusively heterosexual (87.6%) and unmarried (90.1%). Body mass indices (BMI = kg/m2) ranged from 16.3 to 47.6 (M = 24.1, SD = 6.0). Participants were treated in

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compliance with the ethical standards of the American Psychological Association.

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good evidence of reliability and validity (Jakatdar et al., 2006). Internal consistency for this sample was .95.

Measures Body-Image Disturbance Questionnaire (BIDQ) The BIDQ (Cash, 2007; Cash & Grasso, 2005; Cash, Phillips, et al., 2004) is a 7-item measure of body-image dissatisfaction, distress, and dysfunction. The BIDQ contains items that pertain to appearance-related concerns, mental preoccupation with these concerns, associated experiences of emotional distress, resultant impairment in social, occupational, and other areas of functioning. Previous research has established that the measure has excellent internal consistency and test-retest reliability. Cronbach’s alpha for this sample was .93. Appearance Schemas Inventory-Revised (ASI-R) The ASI-R (Cash, 2007; Cash, Melnyk, & Hrabosky, 2004) is a 20-item scale intended to assess investment beliefs and assumptions about the importance of appearance in one’s life. All 20 items are rated on a 5-point scale from 1 = Strongly Disagree to 5 = Strongly Agree. There were two factor scales that were extracted from the ASI-R. Motivational Salience is the first factor scale consisting of eight items that reflect the cognitive-behavioral importance of being attractive and managing and enhancing one’s physical appearance. An example of Motivational Salience would be, ‘‘Before going out, I make sure that I look as good as I possibly can.’’ Self-Evaluative Salience is the second subscale of the ASI-R, consisting of 12 items that reflect beliefs that one’s appearance is an important determinant of one’s worth and one’s experiences. For example, ‘‘I seldom compare my appearance to that of other people I see’’ (reverse-scored). In this study, Cronbach’s alpha was .84 for the Self-Evaluative Salience scores and .83 for the Motivational Salience scores. Assessment of Body-Image Cognitive Distortions (ABCD) The ABCD (Cash, 2007; Jakatdar et al., 2006) measures the extent of persons’ problematic thought patterns when they process information about their physical appearance. The ABCD poses 18 potentially challenging situations and mental conversations that might take place in each context. Participants rate the extent to which each thought process would be characteristic of them on a scale from 0 = Not at all like me to 4 = Exactly like me. The ABCD has

Perfectionistic Self-Presentation Scale (PSPS) The PSPS (Hewitt et al., 2003) is a 27-item measure composed of three 9-item subscales: (1) perfectionistic self-promotion (e.g., ‘‘I try always to present a picture of perfection’’); (2) nondisplay of imperfection (e.g., ‘‘I do not want people to see me do something unless I am very good at it’’); (3) nondisclosure of imperfection (e.g., I should solve my own problems rather than admit them to others‘‘). Given relatively high correlations among the subscales, a composite score across subscales is acceptable and was used in this study. Participants rate their agreement with items on a 7-point scale, where higher scores indicate greater levels of perfectionistic self-presentation. The PSPS possesses excellent internal consistency and test-retest reliability, and good convergent, discriminant, and construct validity (e.g., Hewitt, Flett, & Ediger, 1995; Hewitt et al., 2003). Internal consistency of the total score for this sample was .94. Eating Attitudes Test (EAT-26) The EAT-26 (Garner, Olmsted, Bohr, & Garfinkel, 1982) is a well-established, abridged 26-item version of the original scale and is used to detect persons at risk for eating disorders vis-a`-vis their eating attitudes and behaviors. Participants rate items on a 6-point scale from 0 = ‘‘Never’’ to 5 = ‘‘Always.’’ Cronbach’s alpha for this sample was .92. Demographic Questionnaire This questionnaire collected data concerning age, gender, race, height, weight, education, relationship status, and sexual orientation. Body Image States Scale (BISS) The BISS (Cash, 2007; Cash et al., 2002) is a 6item scale that measures current body-image experiences at a particular point in time or in a specific context. These experiences focus on: (1) one’s overall physical appearance; (2) one’s body size and shape; (3) one’s weight; (4) one’s physical attractivenessunattractiveness; (5) current feelings regarding one’s looks compared to how one typically feels; (6) evaluation of one’s appearance compared to the average person’s appearance. Items are rated on a 9point, bipolar scales in terms of how the respondent feels ’’right now at this moment.’’ Cronbach’s alpha

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for the daily BISS scores in this study ranged from .81 to .92. Procedure Phase 1 After reading a consent form, participants anonymously completed a battery of pre-test measures (other than the BISS) that are described above. Materials were presented and stored on a secure server at http:// www.psychdata.com/.

participants being slightly more compliant, as Melnyk et al. (2004) also found. Prior to analysis, data were tested for assumptions and statistical abnormalities, such as skewness and kurtosis. Outliers were corrected by computing z scores and then recoding any items that fell beyond 3 standard deviations from the mean. The recoded value was a unit higher (or lower) that the highest (lowest) non-outlying value (Tabachnick & Fidell, 2001). BMI was recoded for two cases, the EAT-26 was recoded for one, and the BIDQ was recoded for three. BISS Analyses

Phase 2 The second phase required participants to complete the BISS online everyday for a 10-day period between 5 p.m. and 10 p.m. They received a daily email reminder to facilitate compliance. Email addresses could not be linked to participants’ data. Results Preliminary analyses Participants who did not comply with the requirements for the study were eliminated from the data set. Noncompliance was initially defined as failing to complete at least eight BISS daily surveys of the allotted time window of 5 p.m. to 10 p.m. Because many participants missed the window by only a few minutes, the original window was expanded to be 4 p.m. to 11 p.m. A total of 229 women completed at least one BISS daily survey; however, of these women, only 121 satisfied the requirements for compliance. While 152 women completed at least eight daily surveys, 31 did not complete them within the time window of 4 p.m. to 11 p.m. Therefore, we excluded their data from the analysis. Of the 121 women, all completed at least 8 daily BISS assessments, 99 completed 9, and 61 completed all 10. Using analyses of variance or chi-squares, we conducted attrition analyses to determine whether compliance produced self-selection on any of the study’s predictor variables (BIDQ, ASI-R, ABCD, PSPS, EAT-26), research site (ODU or USF), or participant age. Results indicated no significant differences among three compliance groups: (1) no or only one BISS completion, (2) two or more BISS completions but not in compliance, or (3) eight or more BISS completions (the current, compliant sample). Only one trend ( p < .08) was evident with older

Two cross-temporal BISS scores were calculated for each participant (Melnyk et al., 2004): (1) the average level of state body-image satisfaction was computed as the mean score across all available BISS administrations (i.e., 8 to 10 observations). (2) IIV was computed as their standard deviation. Both metrics were normally distributed with a relatively large range of scores. Bodyimage levels ranged from 2.03 to 7.52 on the 9-point BISS (M = 5.39; SD = 1.11). Body-image IIV ranged from 0 to 2.01 (M = 0.86; SD = 0.42). Pearson correlations quantified the extent to which body-image variables, eating attitudes, perfectionistic self-presentation, and BMI predicted participants’ average level and variability of body-image states. Higher (more favorable) average levels of state body image and lower state body-image variability were expected to be associated with less dysfunctional investment in one’s appearance, less body-image disturbance, fewer body-image cognitive distortions, less perfectionistic self-presentation, less disturbed eating attitudes, and (for state level only) lower BMI. Because there was no relationship (r = .01, n.s.) between BISS mean and standard deviation, there was no need to control for either variable in analyses with the other. Table 1 presents the correlations of these measures with BISS mean (level) and day-to-day IIV. The analyses supported all but one hypothesis for bodyimage state levels. Body-image disturbance was the strongest correlate with state levels. Participants who reported less dysfunctional body-image investment, fewer body-image cognitive distortions, less disturbed eating attitudes, and lower BMIs had more favorable body-image levels over the 10-day period. Perfectionistic self-presentation was unrelated to average state levels. With regard to body-image state variability, three hypotheses were confirmed. As Table 1 shows, the

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Table 1 Correlations of body-image traits, eating attitudes, perfectionism, and Body Mass Index with BISS level and variability Predictor variables

BISS Mean (state level) **

Self-Evaluative Salience (ASI-R) Motivational Salience (ASI-R) Assessment of Body-Image Cognitive Distortions (ABCD) Body-Image Disturbance Questionnaire (BIDQ) Perfectionistic Self-Presentation Scale (PSPS) Eating Attitudes Test (EAT-26) Body Mass Index (BMI)

.409 .002 .504** .554** .163 .544** .367**

BISS Standard deviation (state variability) .224* .166 .251** .175 .201* .001 .058

dfs ranged from 118 to 119. * p < .05. ** p < .01.

strongest correlation with body-image IIV was with ABCD scores. Specifically, women who reported fewer body-image cognitive distortions were significantly less likely to experience day-to-day body-image variability. As was expected, self-evaluative investment in appearance and perfectionistic self-presentation were significantly positively correlated with day-to-day variability. Body-image disturbance, disturbed eating attitudes, motivational salience of body-image investment, and BMI were each unrelated to IIV. Multiple regression analyses In the prediction of average BISS levels, two hierarchical regression analyses were conducted to determine the unique contributions of ASI-R SelfEvaluative Salience, ABCD, and BIDQ scores, both including and excluding the EAT-26. The latter analysis was done in view of evidence that body-image Table 2 Summary of multiple regression analyses for the prediction of mean BISS level and day-to-day BISS variability Criterion BISS M Step 1 Step 2

BISS M Step 1 Step 2

BISS SD Step 1

p

sr2

4.29 .09 1.19 2.73 3.46

.001 .927 .237 .007 .001

.13 .00 .00 .03 .05

.37 .02 .27 .34

4.29 .24 2.57 3.42

.001 .810 .012 .001

.13 .00 .03 .06

.09 .07 .16

.70 .58 1.28

.486 .564 .205

.00 .00 .01

Predictors

B (SE)

t

BMI ASI-R SE ABCD BIDQ EAT-26

.07 .02 .14 .38 .02

(.02) (.16) (.12) (.14) (.01)

.37 .01 .13 .26 .30

BMI ASI-R SE ABCD BIDQ

.07 .04 .30 .49

(.02) (.17) (.12) (.14)

ASI-R SE PSPS ABCD

.05 (.08) .03 (.04) .07 (.05)

b

dissatisfaction is a precursor and correlate of eating disturbance (Stice, 2002b; Thompson, 2004a). BMI was held constant in the first step for both analyses to determine the role of each predictor independent of body mass. No collinearity violations were evident. In the hierarchical regressions, summarized in Table 2, BMI was included in Step 1, F(1, 118) = 18.38, p < .001, adjusted R2 = .13. The first hierarchical regression included the EAT-26 with ASIR Self-Evaluative Salience, ABCD, and BIDQ in the prediction of BISS level at Step 2, F-change (4, 114) = 17.30, p < .001, change in adjusted R2 = .31. As indicated in Table 2, in addition to BMI, body-image disturbance and eating attitudes explained variance in body-image state levels. The second regression excluded the EAT-26; and ASI-R Self-Evaluative Salience, ABCD, and BIDQ were entered in the prediction of BISS levels at Step 2, F-change (3, 115) = 17.41, p < .001, change in adjusted R2 = .26. Both regression analyses that included the BMI were significant and explained 44% and 38% of variance, respectively. Finally, a standard multiple regression analysis evaluated the importance of each predictor variable that was correlated significantly with body-image IIV (i.e., ASI-R Self-Evaluative Salience, PSPS, and ABCD). Table 2 shows that the model explained an adjusted 5% of the variance in BISS IIV, F(3, 117) = 3.02, p < .05, R = .27. The ABCD was the strongest predictor; however, no predictor accounted for a significant amount of unique variance when all three were entered into the model. A stepwise method of regression confirmed that the ABCD was the sole significant predictor, F(1, 119) = 7.98, p < .006, adjusted R2 = .06. Discussion Our prospective investigation examined predictors of women’s day-to-day body-image experiences. There is an unfortunate scarcity of research that assesses

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body-image level and variability in everyday life (Cash, 2002a; Melnyk et al., 2004). The latter is rarely studied despite the clinical and conceptual importance of understanding persons who are susceptible to unstable body-image states from day-to-day or context-to-context. The use of web-based and other technologies to record persons’ fluid body-image experiences in their actual lives is promising if we are to move beyond a single-assessment, trait-oriented perspective on body image. Prediction of body-image state levels Our results provide support for a majority of the hypothesized predictors of average day-to-day bodyimage levels. Less investment in one’s appearance for self-worth was significantly associated with more positive average levels. Because ASI-R Self-Evaluative Salience is the more dysfunctional dimension of the ASI-R, it is not surprising that scores on this subscale were significantly predictive of lower BISS levels. On the other hand, ASI-R Motivational Salience, which measures one’s cognitive-behavioral investment in appearing attractive and managing one’s appearance, did not correlate significantly with average levels. This finding is consistent with evidence that the latter investment dimension is not inherently maladaptive (Cash, Melnyk, et al., 2004; Jakatdar et al., 2006). Women who are motivated to look attractive do not necessarily have greater body dissatisfaction in everyday life. On the other hand, appearance investment that dictates self-worth entails a vulnerability to less favorable body-image states. As measured by the BIDQ, body-image disturbance had the strongest significant relationship with less favorable body-image levels (r = .55). This finding supports the validity of the BIDQ, which assesses multiple facets of body-image functioning (i.e., concerns, preoccupation, distress, and adverse consequences). Lower levels of body-image cognitive distortions on the ABCD assessment were also prospectively related to more positive state bodyimage levels. Furthermore, women with less disturbed eating attitudes had more favorable body-image levels. Finally, women who reported a lower BMI were somewhat more likely to have positive day-to-day body-image levels. The relationship between perfectionistic self-presentation and more self-critical bodyimage states (r = .16) was not significant. Our standard regression analyses highlighted the unique contributions of body-image disturbance and eating attitudes in predicting average body-image states.

Moreover, when ignoring eating attitudes in the analysis, both body-image disturbance and body-image cognitive distortions were reliable predictors. Prediction of state body-image IIV Three predictors were significantly associated with body-image state IIV, as indexed by the standard deviation of BISS scores over the 10-day period. The near-zero correlation between level and variability supports the distinction between the two constructs. Confirmed hypotheses indicated that greater day-to-day variability was predicted by higher levels of appearance investment, in terms of Self-Evaluative Salience but not Motivational Salience. Greater body-image IIV was also predicted by more body-image cognitive distortions and more perfectionistic self-presentation. State IIV was unrelated to body-image disturbance, eating attitudes, or BMI. Standard regression analysis did not identify any of these predictors as explaining body-image IIV independent of the others. Although not sufficiently collinear to violate regression requirements, the overlap among these three variables (rs = .54 to .65) likely prevented any one predictor to explain IIV uniquely. However, a consideration of the bivariate relationships and a stepwise regression suggests that women whose body-image thought processes reflect more distortions may be particularly susceptible to fluctuations in their day-to-day body-image states. Jakatdar et al. (2006) found that this variable does make persons more at risk for body-image shifts in response to various bodyimage threats and challenges. Consistent with cognitive perspectives on body image (Cash, 2002b; Williamson et al., 2002), biased or distorted processing of appearance-related information increases the likelihood of dysphoric body-image experiences in daily life contexts. Findings considered in relation to extant research Contrary to Melnyk et al.’s (2004) results, ASI-R Motivational Salience was not significantly correlated with body-image IIV in this study. Neither study found motivational salience to be related to body-image state levels. Both studies found body-image investment for self-worth to be inversely predictive of IIV. Such selfschematic investment (sometimes termed ‘‘overvaluation’’) constitutes a vulnerability to potential contextual triggers of body-image dysphoria (Cash, 2002b; Cash, Melnyk, et al., 2004). Kernis and colleagues (1993) found similar results with regard to self-esteem states;

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individuals who placed less self-worth emphasis on self-evaluations reported higher self-esteem and selfesteem stability. Although body-image disturbance and eating pathology were the strongest correlates of average body-image levels, neither was significantly associated with day-today body-image variability. While speculative, one interpretation is that greater body-image disturbance and eating pathology entail more consistently negative body-image experiences that preclude larger fluctuations that include positive and satisfying body-image experiences. Disturbed eating attitudes have been conclusively linked with body-image disturbances (Cash & Deagle, 1997; Garner, 2002; Stice, 2002a; Thompson, 2004a). Prospective research supports body image as a reliable risk factor as well as a possible maintenance factor for eating disturbances (Stice, 2002b). Certainly, individual differences that moderate body-image levels and IIV in everyday life and clarify IIV among persons with disturbed eating attitudes warrant further research. One such individual-difference variable is perfectionistic self-presentation (PSP). This type of perfectionism, the need to ‘‘appear’’ perfect to others, differs from ‘‘trait perfectionism’’ which is the need to be perfect (Hewitt et al., 2003; McGee et al., 2005). In the present prospective study, women who were less inclined to promote or protect a ‘‘perfect’’ selfpresentation were more stable in their day-to-day body-image states but, on average, were neither more nor less dissatisfied. Unpublished findings from a study of body-image coping (Cash, Santos, & Williams, 2005) indicate that PSP is reliably related to the use of appearance-fixing and avoidance strategies for coping with body-image threats. Melnyk et al. (2004) found that appearance-fixing coping was related to greater body-image IIV. Perhaps the greater body-image variability of high PSP women reflects inconsistency in whether they feel they have succeeded in managing their physical self-presentations with such strategies. Finally, confirming Melnyk et al. (2004), BMI was found to be significantly related to body-image level but not variability. Thus, while heavier women have more negative body-image states on average than lighter women, they are not more variable in these states. The findings for state levels confirm the literature on trait body-image evaluations—that heaver women are more body dissatisfied (Schwartz & Brownell, 2004). Limitations and implications for future research From the initial sample of 243 women, 50% failed to comply sufficiently with both phases of the study to

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include their data for analysis. This high noncompliance rate was probably due to a number of factors, including volunteers’ failure to adequately read instructions to understand the prospective nature of the study, as well as their misunderstanding, ignoring, or having conflicts with time window requirements for daily assessments. Despite daily email reminders, many participants failed to complete the brief (2-min) daily BISS assessments. While this shortcoming is certainly troubling, our analyses (like those of Melnyk et al., 2004) indicated that compliance was unrelated to any of the study’s predictor variables and therefore did not necessarily bias our results. Future researchers should anticipate and attempt to address the issue of compliance when designing their study. Perhaps the provision of material incentives for completing in vivo assessments could improve participants’ compliance. The use of the BISS as a state body-image assessment has certain advantages. It is brief, internally consistent, and taps a range of momentary body-image experiences. Two items pertain to weight/shape, and four refer to more global aspects of physical appearance, with two of the latter involving comparative evaluations (relative to usual experiences and in comparison to how others look). Despite use of the stem ‘‘Right now I feel . . .,’’ items elicit evaluations more than associated emotional states. Participants are not asked about feelings of self-consciousness, disgust, anxiety, dejection, anger, joy, pride, etc. Whether this is a limitation of the BISS is a reasonable matter for further study. Moreover, the BISS may not be the best assessment of body-image states among some populations, for example, individuals with visible appearancealtering conditions. Some populations may require measures that incorporate condition-specific content (Pruzinsky & Cash, 2002; Rumsey & Harcourt, 2004; Thompson, 2004b). The levels and IIV of body-image experiences in everyday life is worthy of continued investigation. Future studies should collect data on particular contextual cues that may be linked to body-image ups and downs—for example, in relation to eating, weight fluctuations, exercise, grooming behavior (e.g., getting dressed, applying or removing cosmetics, styling one’s hair), and interpersonal events that call attention to one’s appearance or prompt social comparisons, etc. (Cash, 2002c). Qualitative research may have value for enhancing our knowledge of the contributing contextual variables in body-image states (Dures & Rumsey, 2006). Moreover, what is the stability of instability? The collection of day-to-day data for longer periods than 6

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to 10 days would enable us to determine how reliable body-image IIV is from week-to-week or month-tomonth. In addition, there may be methodological advantages to the use of different technologies (e.g., hand-held personal digital assistants, mobile phones, etc.) to randomly sample momentary experiences, rather than allowing participants to report body-image states during a prescribed and anticipated window of time each day. Beyond a college female population, it is imperative to study more diverse populations, including males, noncollege community samples, people with disfiguring conditions, and clinical samples, such as persons with eating disorders or body dysmorphic disorder. Understanding the day-to-day body-image experiences of such clinical groups has potential benefits for the development of body-image prevention and treatment programs. In one treatment-outcome study, Cash and Hrabosky (2003) found that by providing participants psychoeducational information about body image and having them systematically monitor daily body-image states (from Cash, 1997), body-image improvements can ensue. The ongoing, contextual assessment of bodyimage thoughts, feelings, and behaviors is a crucial aspect of effective cognitive-behavioral body-image therapy (Cash & Hrabosky, 2004; Hrabosky & Cash, in press; Jarry & Ip, 2005). References Amorose, A. J. (2001). Intraindividual variability of self-evaluations in the physical domain: Prevalence, consequences, and antecedents. Journal of Sport and Exercise Psychology, 23, 222–244. Cash, T. F. (1997). The body image workbook. Oakland, CA: New Harbinger. Cash, T. F. (2002a). Beyond traits: Assessing body image states. In T. F. Cash, & T. Pruzinsky (Eds.), Body image: A handbook of theory, research, and clinical practice (pp. 163–170). New York: Guilford Press. Cash, T. F. (2002b). Cognitive-behavioral perspectives on body image. In T. F. Cash, & T. Pruzinsky (Eds.), Body image: A handbook of theory, research, and clinical practice (pp. 38–46). New York: Guilford Press. Cash, T. F. (2002c). The situational inventory of body-image dysphoria: Psychometric evidence and development of a short form. International Journal of Eating Disorders, 32, 362–366. Cash, T. F. (2007). Body-image assessments. Available from the author at www.body-images.com. Cash, T. F., & Deagle, E. A., III (1997). The nature and extent of body image disturbances in anorexia nervosa and bulimia nervosa: A meta-analysis. International Journal of Eating Disorders, 22, 107–125. Cash, T. F., Fleming, E. C., Alindogan, J., Steadman, L., & Whitehead, A. (2002). Beyond body image as a trait: The development and validation of the Body Image States Scale. Eating Disorders: A Journal of Treatment and Prevention, 10, 103–113.

Cash, T. F., & Grasso, K. (2005). The norms and stability of new measures of the multidimensional body image construct. Body Image: An International Journal of Research, 2, 199–203. Cash, T. F., & Hrabosky, J. I. (2003). The effects of psychoeducation and self-monitoring in a cognitive-behavioral program for bodyimage improvement. Eating Disorders: Journal of Treatment and Prevention, 11, 209–225. Cash, T. F., & Hrabosky, J. I. (2004). Treatment of body image disturbances. In J. K. Thompson (Ed.), Handbook of eating disorders and obesity (pp. 515–541). Hoboken, NJ: Wiley. Cash, T. F., Melnyk, S. E., & Hrabosky, J. I. (2004). The assessment of body image investment: An extensive revision of the appearance schemas inventory. International Journal of Eating Disorders, 35, 305–316. Cash, T. F., Phillips, K. A., Santos, M. T., & Hrabosky, J. I. (2004). Measuring ‘‘negative body image:’’ Validation of the body image disturbance questionnaire in a non-clinical population. Body Image: An International Journal of Research, 1, 363–372. Cash, T. F., & Pruzinsky, T. (Eds.). (2002). Body image: A handbook of theory, research, and clinical practice. New York: Guilford Press. Cash, T. F., Santos, M. T., & Williams, E. F. (2005). Coping with bodyimage threats and challenges: Validation of the body image coping strategies inventory. Journal of Psychosomatic Research, 58, 191– 199. Dures, E., & Rumsey, N. (2006). Fluctuations of body image states in daily life: An exploration of women’s experiences. University of the West of England Psychology Postgraduate Papers, 18–23. Garner, D. M. (2002). Body image and anorexia nervosa. In T. F. Cash, & T. Pruzinsky (Eds.), Body image: A handbook of theory, research, and clinical practice (pp. 295–303). New York: Guilford Press. Garner, D. M., Olmsted, M. P., Bohr, Y., & Garfinkel, P. E. (1982). The Eating Attitudes Test: Psychometric features and clinical correlates. Psychological Medicine, 12, 871–878. Greenier, K. D., Kernis, M. H., McNamara, C. W., Waschull, S. B., Berry, A. J., Herlocker, C. E., et al. (1999). Individual differences in reactivity to daily events: Examining the roles of stability and level of self-esteem. Journal of Personality, 67, 185–208. Hewitt, P. L., Flett, G. L., & Ediger, E. (1995). Perfectionism traits and perfectionistic self-presentation in eating disorder attitudes, characteristics, and symptoms. International Journal of Eating Disorders, 18, 317–326. Hewitt, P. L., Flett, G. L., Sherry, S. B., Habke, M., Parkin, M., Lam, R. W., et al. (2003). The interpersonal expression of perfectionism: Perfectionistic self-presentation and psychological distress. Journal of Personality and Social Psychology, 84, 1303–1325. Hrabosky, J. I., & Cash, T. F. (in press). Self-help treatment for body image disturbances. In J. Latner, & G. T. Wilson, (Eds.), Self-help for obesity and binge eating. New York: Guilford Press. Jakatdar, T. A., Cash, T. F., & Engle, E. K. (2006). Body-image thought processes: The development and initial validation of the Assessment of Body-Image Cognitive Distortions. Body Image: An International Journal of Research, 3, 325–333. Jarry, J. L., & Ip, K. (2005). The effectiveness of stand-alone cognitive-behavioural therapy for body image: A meta-analysis. Body Image: An International Journal of Research, 2, 317–331. Kernis, M. H., Cornell, D. P., Sun, C., Berry, A., & Harlow, T. (1993). There’s more to self-esteem than whether it is high or low: The importance of stability of self-esteem. Journal of Personality and Social Psychology, 65, 1190–1204. Kernis, M. H., Greenier, K. D., Herlocker, C. E., Whisenhunt, C. R., & Abend, T. A. (1997). Self-perceptions of reactions to doing well or

J.A. Rudiger et al. / Body Image 4 (2007) 1–9 poorly: The roles of stability and level of self-esteem. Personality and Individual Differences, 22, 845–854. Kernis, M. H., Whisenhunt, C. R., Waschull, S. B., Greenier, K. D., Berry, A. J., Herlocker, C. E., et al. (1998). Multiple facets of self-esteem and their relations to depressive symptoms. Personality and Social Psychology Bulletin, 24, 657– 669. McGee, B. J., Hewitt, P. L., Sherry, S. B., Parkin, M., & Flett, G. L. (2005). Perfectionistic self-presentation, body image, and eating disorder symptoms. Body Image: An International Journal of Research, 2, 29–40. Melnyk, S. E., Cash, T. F., & Janda, L. H. (2004). Body image ups and downs: Prediction of intra-individual level and variability of women’s daily body image experiences. Body Image: An International Journal of Research, 1, 225–235. Paradise, A. W., & Kernis, M. H. (2002). Self-esteem and psychological well-being: Implications of fragile self-esteem. Journal of Social and Clinical Psychology, 21, 345–361. Pruzinsky, T., & Cash, T. F. (2002). Assessing body image and quality of life in medical settings. In T. F. Cash, & T. Pruzinsky (Eds.), Body image: A handbook of theory, research, and clinical practice (pp. 171–179). New York: Guilford Press. Rumsey, N., & Harcourt, D. (2004). Body image and disfigurement: Issues and interventions. Body Image: An International Journal of Research, 1, 83–97.

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Schwartz, M. B., & Brownell, K. D. (2004). Obesity and body image. Body Image: An International Journal of Research, 1, 43–56. Stice, E. (2002a). Body image and bulimia nervosa. In T. F. Cash, & T. Pruzinsky (Eds.), Body image: A handbook of theory, research, and clinical practice (pp. 304–311). New York: Guilford Press. Stice, E. (2002b). Risk and maintenance factors for eating pathology: A meta-analytic review. Psychological Bulletin, 128, 825–848. Tabachnick, B. G., & Fidell, L. S. (2001). Computer-assisted research design and analysis. Boston: Allyn and Bacon. Thompson, J. K. (Ed.). (2004). Handbook of eating disorders and obesity. Hoboken, NJ: Wiley. Thompson, J. K. (2004b). The (mis)measurement of body image: Ten strategies to improve assessment for applied and research purposes. Body Image: An International Journal of Research, 1, 7–14. Thompson, J. K., Heinberg, L. J., Altabe, M., & Tantleff-Dunn, S. (1999). Exacting beauty: Theory, assessment, and treatment of body image disturbance. Washington, DC: American Psychological Association. Tiggemann, M. (2001). Person  situation interactions in body dissatisfaction. International Journal of Eating Disorders, 29, 65–70. Williamson, D. A., Stewart, T. M., White, M. A., & York-Crowe, E. (2002). An information-processing perspective on body image. In T. F. Cash, & T. Pruzinsky (Eds.), Body image: A handbook of theory, research, and clinical practice (pp. 47–54). New York: Guilford Press.