ATTENTIONAL BIASES IN WOMEN AT RISK FOR EATING DISORDERS: A COMPARISON OF THREE COGNITIVE TASKS DISSERTATION

Transcription

1 ATTENTIONAL BIASES IN WOMEN AT RISK FOR EATING DISORDERS: A COMPARISON OF THREE COGNITIVE TASKS DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Danette Salas Tressler, M. A. **** The Ohio State University 2008 Dissertation Committee: Dr. Michael W. Vasey, Adviser Dr. Daniel R. Strunk Dr. Tracy Tylka Approved by Adviser Psychology Graduate Program

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3 ABSTRACT Research has shown that females with eating disorders show attentional biases toward food and body words. This bias has been demonstrated less consistently in nonclinical samples of women at risk for eating disorders. The bulk of the research in this area has used a modified version of the Stroop color-naming task. Although this task has been widely used, it may not allow full interpretation of the attentional bias. The purpose of the present study was to replicate and extend previous results in a sample of women at risk for eating disorders. In order to extend previous research, participants completed a probe discrimination task, which permitted a distinction between attentional facilitation and delay of attentional disengagement, and a deployment of attention task in addition to a modified Stroop color-naming task. In order to maximize the likelihood of finding attentional biases toward food and body-words, one half of the participants were weighed prior to the completion of the cognitive tasks, whereas the other half was weighed after the cognitive tasks. The present study also examined the moderating effects of difficulties in emotion regulation, negative affectivity, and attentional control on attentional biases to food and body words. It was expected that high-risk women would demonstrate greater attentional biases to food- and body-words compared to low-risk women and that this bias would be magnified for those women who had been weighed before the tasks. The ii

4 analyses were conducted two ways: first, an extreme groups analysis was used to compare participants in the upper and lower quartiles for a composite score that was derived from measures of restrained eating and drive for thinness; then, the entire sample was examined in a secondary analyses. No clear pattern of findings emerged to suggest that high-risk women have attentional biases for food and body words compared to lowrisk women. Contrary to predictions, the weighing manipulation appeared to eliminate rather than magnify differences between high- and low-risk women. However, given the large number of analyses, it is possible that at least some of the results were obtained by chance. Limitations and directions for future research are discussed. iii

5 For He who gives me an eternal perspective iv

6 ACKNOWLEDGMENTS First I would like to thank the members of my dissertation committee, Drs. Daniel Strunk, Tracy Tylka, and especially my advisor Michael Vasey. His support and encouragement made the completion of this project possible, and for that I am truly thankful. I would also like to thank Sarah K. Davidson, Kate Sowder, Erin Silvert-Noftle, Amanda Fox, and Lauren Christensen, who assisted me it countless hours of data collection. I would like to thank my family and friends for all of their support and understanding as I completed this chapter of my life. In particular, I would like to thank my husband, Shane Tressler for all of his support and encouragement through each of the challenges I have faced while completing this program. v

7 VITA March, 30, Born Landstuhl, Germany B.A., Psychology, The University of Texas at San Antonio 2005 M. A., Psychology, The Ohio State University Department Fellow, The Ohio State University Graduate Teaching Associate, The Ohio State University 2007-present Graduate Fellow, The Ohio State University Research publications PUBLICATIONS 1. Wenzlaff, R. M., Meier, J., and Salas, D. M. (2002). Though suppression and memory biases during and after depressive moods. Cognition and Emotion, 16, Schmidt, N. B., Salas, D., Bernert, R., and Schatschneider, C. (2005). Diagnosing agoraphobia in the context of panic disorder: Examining the effect of DSM-IV criteria on diagnostic decision-making. Behaviour Research and Therapy, 43, Major Field: Psychology FIELDS OF STUDY vi

8 TABLE OF CONTENTS P a g e Abstract ii Dedication...iv Acknowledgments v Vita..vi List of Tables...x List of Figures...xiv Chapters 1. Introduction The Stroop as a Measure of Biased Information Processing.. 2 The Stroop effect in eating disordered samples...3 The Stroop effect in women at high-risk for eating disorders...6 Alternative Tasks of Information Processing Biases...16 The Present Study Method...26 Participants Measures Procedures vii

9 Stroop Task Probe Discrimination Task Deployment of Attention Task Results Sample Characteristics Statistical Approach Primary Analyses...39 Stroop. 39 Probe Discrimination Task Threat index scores 48 Facilitation scores..54 Delay of disengagement scores..59 DOAT Moderator Analyses Difficulties in Emotion Regulation Stroop bias scores..70 Threat index scores 71 Facilitation scores..72 Delay of disengagement scores..76 DOAT proportion scores 79 Negative Affectivity and Attentional Control Stroop bias scores..85 Threat index scores 94 Facilitation scores..98 Delay of disengagement scores 101 DOAT proportion scores Discussion 116 Comparing the Stroop, PDT, and DOAT Attentional Processing in Low- Versus High-risk Women The Effect of Weighing on Information Processing Difficulties in Emotion regulation, Negative Affectivity, and Attentional Control viii

10 Differentiating between Attentional Facilitation and Delay of Disengagement..132 Limitations and Future Directions Conclusions References 143 Appendices A: Stroop Word Lists B: PDT Word Pairs C: DOAT Word Pairs ix

11 LIST OF TABLES Table Page 1. Demographic information and scores for self-report measures Means, standard deviations, and correlations between all self-report measures Correlations for food and body words derived from the Stroop, PDT, and DOAT Harmonic means and bias scores in milliseconds for Stroop food and body words by group, standard deviations in parentheses Hierarchical regression base model predicting Stroop food bias using extreme groups Hierarchical regression base model predicting Stroop food bias using the whole sample Hierarchical regression base model predicting Stroop body bias using extreme groups Hierarchical regression base model predicting Stroop body bias using the whole sample Harmonic means in milliseconds and standard deviations for neutral, food, and body words by threat and probe position Threat index, facilitation, and delay of disengagement scores for food and body words derived from the PDT Hierarchical regression base model predicting threat index scores for food words using extreme groups Hierarchical regression base model predicting threat index scores for food words using the whole sample..51 x

12 13. Hierarchical regression base model predicting threat index scores for body words using extreme groups Hierarchical regression base model predicting threat index scores for body words using the whole sample Hierarchical regression base model predicting facilitation scores for food words using extreme groups Hierarchical regression base model predicting facilitation scores for food words using the whole sample Hierarchical regression base model predicting facilitation scores for body words using extreme groups Hierarchical regression base model predicting facilitation scores for body words using the whole sample Hierarchical regression base model predicting delay of disengagement scores for food words using extreme groups Hierarchical regression base model predicting delay of disengagement scores for food words using the whole sample Hierarchical regression base model predicting delay of disengagement scores for body words using extreme groups Hierarchical regression base model predicting delay of disengagement scores for body words using the whole sample DOAT proportion scores for food and body words, standard deviations in parentheses Hierarchical regression base model predicting DOAT proportion scores for food words using extreme groups Hierarchical regression base model predicting DOAT proportion scores for food words using the whole sample Hierarchical regression base model predicting DOAT proportion scores for body words using extreme groups Hierarchical regression base model predicting DOAT proportion scores for body words using the whole sample...69 xi

13 28. Hierarchical regression using DERS as a moderator predicting facilitation scores for body words using extreme groups Hierarchical regression using DERS as a moderator predicting facilitation scores for body words using the whole sample Hierarchical regression using DERS as a moderator predicting delay of disengagement scores for body words using the whole sample Hierarchical regression using DERS as a moderator predicting DOAT proportion scores for food words using the whole sample Hierarchical regression using DERS as a moderator predicting DOAT proportion scores for body words using extreme groups Hierarchical regression using DERS as a moderator predicting DOAT proportion scores for body words using the whole sample Hierarchical regression with NA and ACS as moderators predicting Stroop food bias using the whole sample Hierarchical regression with NA and ACS as moderators predicting Stroop body bias using extreme groups Hierarchical regression with NA and ACS as moderators predicting Stroop body bias using the whole sample Hierarchical regression with NA and ACS as moderators predicting threat index scores for food words using extreme groups Hierarchical regression with NA and ACS as moderators predicting threat index scores for food words using the whole sample Hierarchical regression with NA and ACS as moderators predicting threat index scores for body words using extreme groups Hierarchical regression with NA and ACS as moderators predicting facilitation scores for body words using extreme groups..99 xii

14 41. Hierarchical regression with NA and ACS as moderators predicting delay of disengagement scores for food words using extreme groups Hierarchical regression with NA and ACS as moderators predicting delay of disengagement scores for food words using the whole sample Hierarchical regression with NA and ACS as moderators predicting delay of disengagement scores for body words using extreme groups Hierarchical regression with NA and ACS as moderators predicting delay of disengagement scores for body words using the whole sample Hierarchical regression with NA and ACS as moderators predicting DOAT proportion scores for food words using the whole sample Hierarchical regression with NA and ACS as moderators predicting DOAT proportion scores for body words using extreme groups Hierarchical regression with NA and ACS as moderators predicting DOAT proportion scores for body words using the whole sample xiii

15 LIST OF FIGURES Figure Page 1. Risk-group x BMI interaction for threat index scores for food words WT x CS interaction for threat index scores for body words WT x BMI interaction for facilitation scores for food words using extreme groups Risk-group x BMI interaction for delay of disengagement scores for food words WT x Risk-group interaction for DOAT proportion scores for body words WT x CS interaction for DOAT proportion scores for body words Risk-group x DERS interaction for facilitation scores for body words CS x DERS interaction for facilitation scores for body words CS x DERS interaction for delay of disengagement scores for body words CS x NA interaction for Stroop food bias NA x ACS interaction for Stroop body bias using extreme groups CS x BMI interaction for threat index scores for food words Risk-group x NA interaction for facilitation scores for body words WT x BMI interaction for facilitation scores for body words using extreme groups WT x BMI interaction for delay of disengagement scores for food words using extreme groups xiv

16 16. WT x BMI interaction for delay of disengagement scores for food words using the whole sample WT x Risk-group interaction for delay of disengagement scores for body words WT x BMI interaction for delay of disengagement scores for body words using extreme groups CS x NA interaction for delay of disengagement scores for body words 110 xv

17 CHAPTER 1 INTRODUCTION According to cognitive theories of eating disorders, distorted and overactive weight-and body-related schemata are crucial in both the etiology and maintenance of anorexia and bulimia (Vitousek & Hollon, 1990). Among individuals suffering from anorexia and bulimia, such schemata are thought to influence perceptions, thoughts, affect, and behavior in response to food-and body-related information (Vitousek and Hollon, 1990) In general, research supports Vitousek and Hollon s predictions that individuals with eating disorders exhibit biased information-processing of food- and body-related information. Specifically, compared to controls, such individuals show greater color-naming interference due to food- and body-related words (Faunce, 2002; Johansson, Ghaderi, & Andersson, 2005; Lee & Shafran, 2004), biased interpretation of ambiguous information as being related to shape or weight (Cooper, 1997), and biased memory for weight- and body-related information (Israeli & Stewart, 2001; Williamson, 1996). Vitousek and Hollon s (1990) prediction that weight-related schemata result in attentional biases toward food- and body-related information was the focus of this study. As noted above, a number of studies using a modified version of the Stroop color-naming 1

18 task (Stroop, 1935) show that women with eating disorders display delayed color naming for food- and body-relevant information compared to neutral information. For reasons that remain unclear, this effect has not been demonstrated consistently in non-clinical samples of women with eating and weight concerns (i.e., women at high risk for developing eating disorders). Although color-naming interference for food- and bodyrelated stimuli is typically interpreted as reflecting an attentional bias in favor of such cues, there are other potential sources of this effect. Therefore, the first aim of this study was to augment the use of a food- and body-related Stroop task with several other measures that are clearer measures of attentional bias. The second aim of the study was to yield a better understanding of the equivocal findings in high-risk non-clinical samples by evaluating the effect of a manipulation meant to activate body concerns. The third aim of the study was to evaluate the nature of an attentional bias to food- and body-related information by including one task, the probe-discrimination task, which allowed for a differentiation between attentional facilitation and delay of attentional disengagement from food- and body-related information. Finally, the study examined the effects of three potential moderating variables on the attentional bias to food and body words. The Stroop as a Measure of Biased Information Processing In the classic Stroop paradigm (1935), participants are presented with words or strings of characters and are asked to name the color of the ink while ignoring the content of the word. Studies consistently show that individuals are slower to name the color of a word when the semantic content of the word and the color of the ink are incongruent (i.e., the word BLUE written in red ink) compared to when the trial is composed of a control 2

19 word (non-color word) or a string of characters. This delayed color naming is referred to as Stroop interference (for a review, see MacLeod, 1991). The Stroop has been modified for use with several different clinical populations and researchers have found that individuals show slowed color-naming for words that are personally meaningful (Williams, Mathews, & MacLeod, 1996). This color-naming interference is typically interpreted as reflecting distraction of attention by threat cues. Slowed color-naming for disorder-relevant words has been found in panic disorder (Ehlers, Margraf, Davies, & Roth, 1988; McNally, Riemann, & Kim, 1990), social phobia (Hope, Rapee, Heimberg, & Dombeck, 1990), generalized anxiety disorder (Bradley, Mogg, Millar, & White, 1995; Mathews & MacLeod, 1985), and specific phobia (Watts, McKenna, Sharrock, & Trezise, 1986). Given the ability of the Stroop to reveal biased information processing in these disorders, researchers in the realm of eating disorders have employed this method in order to evaluate biased information processing toward food-, body-, and shape-relevant stimuli. The Stroop effect in eating disordered samples. Several studies have examined color-naming interference for food- (i.e., butter, chocolate) and body-relevant words (i.e., fat, thighs) in samples of anorexic (Channon, Hemsley, & de Silva, 1988; Green, Corr, & de Silva, 1999; Green, McKenna, & de Silva, 1994), bulimic (Cooper, Anastasiades, & Fairburn 1992; Cooper & Fairburn, 1993; Fairburn, Cooper, Cooper, McKenna, & Anastasiades, 1991), and mixed samples of eating disordered individuals (Ben-Tovim, Walker, Fok, & Yap, 1989; Cooper & Fairburn, 1992a; Cooper & Todd, 1997; Jones- 3

20 Chesters, Monsell, & Cooper, 1998; Perpina, Hemsely, Treasure, & de Silva, 1993; Perpina, Leonard, Treasure, Bond, & Banos, 1998). In general, females with eating disorders show longer color-naming latencies for food- and body-words compared to disorder-free women (Johansson, Gharderi, & Andersson, 2004). Results from card-based Stroop presentations, in which eating-, weight- and shape-words are presented in the same array show slower color-naming in anorexics (Cooper and Fairburn, 1992a) and bulimics (Cooper, et al., 1992; Fairburn, et al., 1991) compared to control subjects. However, because all of the words are presented together as a group, it is impossible to evaluate color-naming latencies to food and body words separately. Consequently, based on the card-based Stroop in which the stimuli are clustered together, it is difficult to determine whether food- or body-relevant stimuli result in different patterns of information processing in anorexics compared to bulimics. Although Vitousek and Hollon (1990) suggest that the underlying concerns for anorexics and bulimics are the same, researchers have investigated separate effects for different categories of words in eating disordered samples. The majority of studies investigating Stroop interference for food- and bodywords have separated the stimuli. Doing so has led some researchers to conclude that food- and body-related information do not bias information processing equally among anorexics and bulimics. For example, Channon, et al., (1988) found Stroop interference for food words, but not body words in anorexic individuals. However, because this study only included a non-clinical control group, it is impossible to determine whether this effect would be different in a group of bulimic individuals. Ben-Tovim et al, (1989) 4

21 found that compared to control subjects, bulimics were slower to name both food and body words, but anorexic subjects were slower to name food words only. Later, Ben- Tovim and Walker (1991) found that anorexics and bulimics were slower to name both food- and shape-words compared to control subjects. Green, Corr, and de Silva (1999) also found that anorexics, compared to control subjects, were slower to name body shape words. Similarly, Cooper and Todd (1997) found that anorexics were slower to name shape-, weight-, and eating-words compared to control subjects. Further they also demonstrated that bulimics were slower to name eating- and weight-related words. Not all studies that have been conducted with clinical samples have found Stroop interference for disorder-relevant words. Carter, Bulik, McIntosh, and Joyce (2000) found no difference in color-naming latencies for food- or body-words in a sample of bulimic individuals. Black, Wilson, Labouvie, and Heffernan (1997) examined Stroop interference for food and weight/shape words and found that bulimics did not differ in color-naming speed compared to restrained or unrestrained eaters. Lovell, Williams, and Hill (1997) did not find Stroop interference for shape- or food- words in anorexics, although they found that bulimics and recovered anorexic displayed slowed color-naming for shape-words. In summary, although there have been some inconsistencies regarding specific patterns of information processing regarding food- and body-related words among anorexics and bulimics (see above), in general it has been found that women with clinically diagnosed eating disorders are slower to name words related to food, body weight, and shape compared to neutral words. In a recent meta-analysis, Johansson, et al. 5

22 (2004) found moderate effect sizes for color-naming disruption of food- and body wordscompared to neutral words in anorexics and bulimics. Thus, consistent with Vitousek and Hollon s (1990) model, it appears that weight-related schemata influence the processing of food- and body- related information in women with eating and weight concerns. One question that remains to be answered is the extent to which information processing differences are causes or effects of clinical states. Flynn and McNally (1999) and Cooper and Fairburn (1994) found that Stroop interference for body-words decreased after treatment. Ball, Mitchell, Touyz, and colleagues (2004) examined pre- and posttreatment color-naming interference for eating-, weight-, and shape- words in anorexics. They found that color-naming interference for food-words decreased after treatment. That is, before treatment, anorexics were slower to name food words than the food-control words. However, color-naming latencies for food words were virtually identical to colornaming latencies for food-control words after treatment. One inference that could be drawn based on the previous studies is that information-processing biases are associated with clinical status, and thus are the products of the clinical disorders rather than causes. However, the absence of such biases in recovered individuals is not sufficient to discount the possibility that information-processing biases play a causal role in the development of eating disorders. An important step in testing such causal assumptions would be to test for biases in non-clinical samples at risk for such disorders but whom have not yet reached clinical status. The Stroop effect in women at risk for eating disorders. Though some researchers suggest that biased processing of food- and body-relevant information is specific to 6

23 individuals with eating disorders (Ben-Tovim & Walker, 1991; Flynn & McNally, 1999), it has been suggested that non-disordered women judged to be at risk for developing such disorders should also exhibit this bias. However, whereas some studies have found evidence in support of this view (e.g., Williamson, 1996), others have not (Ben-Tovim & Walker, 1991). In order to examine information processing in non-clinical samples of women with eating and weight concerns, researchers have typically studied women who score high on measures of dietary restraint or drive for thinness. Selecting women on these variables may be especially important in testing the role of cognitive biases in the etiology of eating disorders, in that dietary restraint has been found to be a predictor of the development of eating disorder symptoms (Killen, et al., 1996) and eating disorders (Fairburn, Cooper, Doll, & Davies, 2005; Stice, 2002). Green and Rogers (1993) looked at restrained eaters who either were or were not currently dieting. Using a computerized Stroop, they found an effect for both food- and body-words in all high restrained eaters, regardless of dieting status. Stewart & Samoluk (1997) examined Stroop interference for food,- alcohol-, and leisure-words in low, moderate, and high restrained eaters. High restrained eaters showed slowed color-naming of both alcohol- and food-words compared to control words. Moderate restrained eaters showed slowed color naming for food words compared to alcohol and control words. Finally, color-naming latencies did not differ among word type for low restrained eaters. Francis, Stewart, and Hounsell (1997) also varied the types of words used in their study. They examined Stroop interference for forbidden and non-forbidden food words, versus 7

24 animal control words. Restrained eaters demonstrated slowed-color naming for both types of food words compared to control subjects. Overduin and colleagues (1995) also found Stroop interference for food words in restrained eaters. In their study, control subjects did not demonstrate Stroop interference, unless they had eaten an appetizer before the start of the Stroop. Conversely, Stroop interference was evident in the restrained group regardless of whether or not they had been assigned to the appetizer condition. In contrast to the studies reviewed above, other studies have failed to find the predicted effect. Jansen, Huygens, and Tenney (1998) used body- and control-words in their investigation of Stroop interference in high and low restrained eaters. Restrained eaters did not show Stroop interference for body-words in this study. Mahamedi and Heatherton (1993) found interference for body-words in restrained eaters, and this effect was pronounced in those who had been assigned to a preloading condition, which required them to consume a milkshake before the start of the Stroop. Interestingly, regardless of preloading condition, Mahamedi and Heatherton did not find evidence for color-naming interference for forbidden or common food words among restrained eaters. This is in contrast to Francis, et al. (1997), who found interference for both types of food words. Stroop interference for food- and body-words were also found in another study of non-preloaded restrained eaters (Ogden & Greville, 1993). Finally, Sackville et al., (1998) used body words and food words, but found no interference for either type amongst restrained eaters. Thus, whereas a few studies have demonstrated slowed color- 8

25 naming for food and body words in non-clinical samples, an equal number of studies have failed to demonstrate the effect. There are several possible explanations for the equivocal findings of Stroop interference for food- and body-relevant information in non-clinical samples. One possibility is that schemas are not as easily accessible in high-risk samples as they are in clinical samples. For example, researchers have found Stroop interference for food and body words it at-risk women when they display clinical features of eating disorders. For example, Cooper and Fairburn (1992a) used a modified version of the Stroop to examine attention to eating-, weight-, and shape-words in anorexics, bulimics, symptomatic dieters, dieters, and controls. Women were classified as symptomatic dieters if they were currently dieting and had met criteria for an eating disorder in the past. Normal dieters were those women who were currently dieting, but had never met criteria for an eating disorder. They found that anorexic, bulimic, and symptomatic dieters showed Stroop interference for food-, body-, and shape-words but that there was no difference in Stroop performance between the control group and the normal dieters. Similarly, Lokken, Marx, and Ferraro (2006) found that the strength of the Stroop effect for eating-, weight-, and shape-words increased with clinical status amongst bulimic, subclinical bulimic, and a non-eating disordered control group of women. Moreover, they found symptom severity to be the best predictor of Stroop interference. It should be noted that the women in these studies were not exposed to experimental manipulations of schema activation. According to Williams and colleagues (1999), the activation of pathology-related schemas may be necessary in order to influence performance on subsequent cognitive 9

26 tasks. Whereas schemas are assumed to be highly, chronically activated and easily accessible in clinical samples, schema activation may be especially important if biased information processing is expected to manifest in non-clinical high-risk samples. For example, in recovered individuals, cognitive schemas related to the disorder may be latent, or inaccessible. Thus, schematic influence on information processing may be dependent on schema activation. Research with formerly depressed individuals who no longer meet clinical status supports this notion. For example, Miranda and Persons (1988) found that previously depressed individuals endorsed more dysfunctional attitudes compared to control subjects, but only when depressive schemata had been primed using a negative mood induction With regard to schema activation and information-processing biases to food- and body-relevant information, some researchers have attempted to activate food and body concerns by using a preloading technique in which the participants are asked to eat some type of forbidden food before the onset of the Stroop color naming task (i.e., Green, Elliman, & Rogers 1996; Mahamedi & Heatherton, 1993; Ogden & Greville, 1993). However, preloading may be an indirect method of priming body concerns as some researchers have found this manipulation to be successful in producing Stroop interference for body words (Mahamedi & Heatherton, 1993; Ogden & Greville, 1993) whereas others have not (Overduin, Jansen, & Louwerse, 1995). Other manipulations may also be successful in activating weight-related schemas. Cooper and Fairburn (1992b) were able to activate body-related schemas in a sample of eating-disordered and dieting females compared to controls. They found that behavioral manipulations, such as 10

27 being weighed or observing oneself in a full length mirror, increased the number of thoughts of eating-, weight-, and shape-concerns in a sample of eating disordered individuals and a sample of dieting individuals, but not in a control group. A second explanation of equivocal findings in high-risk samples is that the Stroop may be a relatively insensitive measure of attentional processes in non-eating disordered individuals. In the Stroop, participants are required to respond to an emotionally valenced, or personally relevant word while ignoring its content. Because the distractor (i.e., the word content) overlaps completely with the target stimulus property to which the participant is required to respond (i.e., the color of the ink), the task is particularly challenging. There is some evidence that even normal control samples of women exhibit some color-naming interference for food- or body-relevant stimuli (e.g., Ben-Tovim et al., 1989) suggesting the possibility that such words may recruit attention in many or most women. If so, such Stroop tasks may make it difficult to resolve the difference between normal attention to such stimuli and all but the most extreme attentional bias seen in clinical samples. In contrast, a task in which the distractors (e.g., food- or bodyrelated words) are separate from targets may prove more sensitive because it is much less difficult for low-risk women to inhibit attention to such distractors. This is analogous to findings reported by Kindt and Brosschot (1999) with regard to Stroop interference due to spider words in children with and without spider phobia. In the typical fully integrated Stroop task (spider-relevant words presented in various colored ink ) the two groups did not differ. Instead both showed heightened color-naming interference for spider-relevant versus neutral words. Thus, spider-relevant words appeared to capture the attention in all 11

28 children. However, when a version of this task was used in which spider words were not integrated with the target color the two groups differed in the expected manner. Specifically, spider-phobic children showed greater interference for spider-relevant words compared to neutral words whereas this difference was not seen in the non-phobic group. Thus, alternatives to the typical Stroop task may be more sensitive to differences between normal controls and women at risk to develop an eating disorder. Yet another possible explanation of equivocal findings in non-clinical samples involves the possible operation of moderating variables, such as emotional reactivity, emotion regulation, and attentional control. One concern with interpreting Stroop findings is that affective reactions may be ultimately responsible for the observed interference (Watts et al., 1986). Thus, an individual who has strong weight-related concerns might have an emotional reaction to high-calorie or forbidden food words such as cookies. Likewise, a woman with body concerns may be unsettled by seeing negative body-relevant words such as flabby. However, emotional distress in response to these types of stimuli might not characterize all women with eating and weight concerns. Women with eating and weight concerns who are particularly prone to strong negative affective responses, or who are deficient in emotion regulation skills, or who have poor ability to control their attention in the face of distractors may show a different pattern of responses than similar women who lack such proclivities. Despite having eating and weight concerns, a woman who is low in emotional reactivity, or who is skilled in emotion regulation, or who can garner the cognitive resources to focus on the task at hand may not show the expected pattern of information-processing for food- and 12

29 body-related cues. Thus studies that have identified women on the basis of some characteristic, such as drive for thinness or dietary restraint, without regard for such possible moderating factors may not provide an adequate context in which to observe attentional biases toward food- and body-related information. One factor that may moderate this relationship is emotion regulation. Difficulties in emotion regulation may be a risk factor for developing eating disorders. Sim and Zeman (2006) found that lack of emotional awareness interacted with body dissatisfaction to produce disordered eating in adolescent girls. It is worth examining emotional regulation in post-adolescent females because many women report body dissatisfaction or body concerns, but few go on to develop clinical levels of eating disorders. Thus, whereas it may be relatively easy to obtain a non-clinical sample of women high in eating and weight concerns, it may be expected that only a subset of those women who are also low in levels of emotional regulation will demonstrate attentional biases toward food- and body-related information. Whiteside, Chen, Neighbors, and colleagues (2007) recently found that emotion regulation difficulties were related to binge-eating. They used the Difficulties in Emotion Regulation Scale (Gratz & Roemer, 2004), which is composed of six subscales, including scales relevant to impulse control, goal-directed behavior, and coping strategies. Spoor, Bekker, Van Strien, and van Heck (2007) found evidence to suggest that coping has an influence on emotional eating after controlling for levels of negative affect. This is consistent with Heatherton and Baumeister s (1991) escape from awareness model, which states that binge eating serves to regulate negative emotional states. With regard to 13

30 this model, bulimic individuals are likely to engage in binge eating because of aversive affective states. In order to shift focus from the self, attention is focused on external properties of food, and binge eating becomes negatively reinforcing in the short-run. Based on these findings, it may be the case that women with eating and weight concerns who also have difficulties in emotion regulation, and thus are more likely to experience negative emotion will be more likely to focus attention on food-words compared to individuals with higher levels of emotional regulation. The present study will allow a test of this hypothesis. Another factor that may moderate the relationship between risk and attentional bias is negative affective reactivity, or neuroticism. Kitsantas, Gilligan, and Kamata (2003) found that college women with eating disorders report higher levels of negative affect, as measured by the PANAS than at-risk students, who, in turn, report higher levels than control subjects. Not only do high levels of negative affectivity seem to characterize women with eating and weight concerns, but it also predicts disturbed eating behavior. Cervera, Lahortiga, and colleagues (2003) found neuroticism to be a greater predictor of eating disorders than self-esteem in a longitudinal study of Spanish girls between the ages of 12 and 21 Similarly, Podar, Hannus, and Allik (1999) suggest that high levels of negative affectivity predispose individuals to eating problems. The moderating influence of negative affectivity on information-processing biases has been demonstrated in one study. Using the PANAS as a measure of negative affect, Rofey, Corcoran, and Tran (2004) found that amongst women with high levels of negative affect, women with more bulimic symptoms were slower to name food-words 14

31 than women with fewer bulimic symptoms. Amongst women with high positive affect, women with a greater number of bulimic symptoms were faster at responding to foodwords compared to women with fewer bulimic symptoms. Although this study provides evidence that negative affectivity, as measured by the PANAS influences informationprocessing biases, it should be noted that the authors had women respond to the PANAS by indicating how they felt right now. Thus, a variety of situational variables could have influenced the responses. If researchers wish to make stronger claims regarding the moderating effects of negative affect on information-processing biases, action must be taken to establish more stable measures of this trait. A third potential moderator between eating and weight concerns and attentional bias to food- and body-related information is effortful control. Effortful control refers to a strategic process by which an individual can shift attention and regulate thought and behavior. Effortful control (EC) is a self-regulatory resource that has implications for the relationship between negative affect and attentional biases to personally relevant information. EC, or its component attentional control, has been shown to moderate attentional biases to threat-relevant information in high trait anxious individuals. Many researchers have demonstrated an attentional bias toward threat in clinically anxious individuals. However, much like in the eating disorder literature reviewed here, that bias is seen less consistently in non-clinical groups. However, this attentional bias appears to be related to levels of attentional control. For example, in a sample of children high in negative affectivity/neuroticism, Lonigan and Vasey (in press) found a bias toward threat only in those children who were low in EC. However, there was no bias toward threat for 15

32 children high in NA/N, but who were also high in effortful control. Likewise, Derryberry and Reed (2002) found that attentional control moderated the relationship between anxiety and an attentional bias toward threat when stimuli were presented at an interval long enough to permit the voluntary allocation of attention toward different types of cues. Given these findings, attentional control may be an additional factor that moderates the relationship between risk for developing an eating disorder and attentional bias toward food- and body-relevant information in women with eating and weight concerns. Further, results from these studies highlight the importance of examining the interaction between negative affectivity and attentional control on biased attentional processing. The results of Lonigan and Vasey (in press) suggest that an attentional bias will be observed at high levels of negative affectivity if effortful control is low. When effortful control is high, individuals may be able to override an initial tendency to attend to threat, and may perhaps also be more likely to engage in defensive processing that may actually mask any initial attentional biases. Alternative Tasks of Information Processing Biases. As noted previously, the Stroop has limitations as a measure of selective attention. There are multiple interpretations for slowed color naming for certain classes of stimuli. For example, it could be due to attention being directed toward or away from the critical words (de Ruiter & Brosschot, 1994). That is, critical words might result in attentional capture, which diminishes processing capacity for the color-naming task but slowed-color naming might instead be due to cognitive avoidance of the critical words. However such interference need not reflect attentional processes at all. Instead, the content of the word 16

33 may lead to an emotional reaction, which results in slower color-naming latencies (Watts, et al., 1986). These limitations of the Stroop have been pointed out by researchers working with other clinical groups (MacLeod, et al. 1986) but only recently have researchers begun to use different measures of attentional processing involving food- and bodywords in women with eating disorders or women with concerns about weight and shape (Ainsworth, Waller, & Kennedy, 2002; Dobson & Dozois, 2004; Faunce, 2002). One such task that circumvents many of the limitations of the Stroop is the probe detection task (MacLeod, et al, 1986). MacLeod et al. (1986) used the probe detection task (PDT) to evaluate attentional biases toward threat words in a group of clinically anxious individuals. In their study, participants were presented with two words, located one above the other in the center of a computer screen. In each trial of the PDT, the word pairs were constructed from either two neutral words (baseline trials) or from one threat-relevant and one neutral word (critical trials). After each threat-neutral pair and after a subset of neutral-neutral pairs, a dot-probe appeared immediately after the word pair disappeared either in the upper or lower position. For example, on critical trials, the probe appeared in either the position previously held by the threat or neutral word. Participants were instructed to press a button as soon as they detected the probe. The measure of interest in this paradigm was the probe detection latency. Specifically, if probe detection latencies are faster on average for trials in which the probe follows a threat word than for those in which the probe follows a neutral word, it shows that attention was preferentially allocated to the location 17

34 of the threat words versus neutral words. Similarly, if probe detection latencies are slower for probes that follow threat words than for those that follow neutral words, it implies that less attention was allocated to threat words than to neutral words. In other words, this task provides a measure of the extent to which attention is heightened or suppressed with regard to threat-relevant stimuli when they compete for attention with neutral stimuli. The PDT is superior to the Stroop task in several ways. First, the modified Stroop provides no neutral stimulus to which the participant may respond. Thus, the interference that is observed may be due to emotional interference that is caused by the word stimulus itself rather than an attentional process. This possibility is eliminated in the probe detection task because the participants are responding to a dot that appears on the screen, which is neutral. Further, the emotional Stroop evaluates attentional biases based on increased reaction time latencies only. With the probe detection task, an attentional bias is demonstrated by both speeding and slowing of reaction times to the neutral stimulus. Additionally, with the addition of probed trials in which both words are neutral, the PDT allows a test of the nature of the attention bias in that both attentional facilitation and delay of attentional disengagement can be evaluated. Attentional facilitation is considered to occur when participants are quicker to respond to probes that occur in the location previously held by target words than to probes in the same position when both word pairs are neutral. For example, if a participant is quicker to respond to a probe in the upper location when the preceding word pair stimulus contained a target word in the upper location compared to when the probe is in the upper location and the word pair was composed of two neutral words, the 18

35 participant s attention has been facilitated to the upper location by the target word. On the contrary, delay of attentional disengagement is considered to occur when participants are slower to respond to probes that occur in the location previously held by the neutral word in a target pair than to probes in the same position when both words are neutral. For example, if a participant is slower to respond to a probe in the upper location when the preceding word pair stimulus contained a target word in the lower location compared to when the probe is in the upper location and the word pair contained two neutral words, the slowed reaction time for the threat-neutral pair can be attributed to delayed disengagement of attention from the location previously occupied by threat. Several studies have examined attention to food and body words using a PDT. However, it should be noted that these studies only examined overall threat bias and did not differentiate between facilitation and disengagement. Rieger, Schotte, Touyz, and colleagues (1998) were the first to employ the use of a PDT to examine an attentional bias toward body words and affective words in women with anorexia and bulimia. Eating disordered females in this sample were slower at responding to words following a thinphysique and faster at responding to probes following fat-physique words. These results are consistent with Vitousek and Hollon s (1990) prediction that individuals with eating disorder are quicker to respond to information that is consistent with their schemata and also slower at processing information that runs counter to their schemata. Rieger et al. (1998) also included a control group of women who differed on levels of dietary restraint. However, the attentional biases seen in the clinical group were absent in these women. Whereas Rieger and colleagues used words that only described body shape, Boon, 19

36 Vogelzang, and Jansen (2000) attempted to evaluate a bias for food, shape, and weight stimuli in a sample of restrained eaters. They too found no evidence of an attentional bias. As of yet, studies using the PDT have failed to demonstrate a bias involving food and body words in non-clinical groups of restrained eaters. However, Placanica, Faunce, and Job (2002) categorized women as high or low Eating Disorder Inventory (EDI) scorers based on their responses to the subscales for drive for thinness (DFT) and body dissatisfaction (BD) and examined attentional biases to food words under fasted and nonfasted conditions. They found that both high and low scorers demonstrated an attention bias toward high calorie foods when fasted. However, only high scorers demonstrated a bias toward low calorie foods when non-fasted. The inconsistencies that exist among the few studies that have used the PDT as a measure of attentional bias in non-clinical samples of women with eating and weight concerns may be due to the nature of the attentional bias. For example, it is possible that biases to these words will be masked if participants show both delay disengagement from threat and anti-facilitation to threat. Whereas facilitated attention is indicated by faster reaction times to probes following a target word in a target/neutral pair compared to probes in the same location in a neutral/neutral pair, anti-facilitation is indicated by slower reaction times to probes following a target word in a target/neutral pair compared to probes in the same location in a neutral/neutral pair. That is, anti-facilitation occurs when participants are faster to respond to probes following neutral words in a neutral/neutral pair compared to probes in the same location as target words in a target/neutral pair. When delay of disengagement 20

37 and anti-facilitation occur, the overall bias scores will be zero, suggesting no bias. The PDT will allow for an interpretation of such effects. With the ability to examine these possibilities, the PDT offers promising advantages to the Stroop as a measure of biased information processing. The Present Study The main purpose of the present study was to evaluate information processing toward food and body words in women at risk for eating disorders. Further, in order to determine the nature of attentional biases involving food and body words in these women, three different cognitive tasks were used. The present study aimed to replicate past research findings by using a modified version of the Stroop color-naming task. However, in order to address some of the limitations imposed by the Stroop, the present study also included a probe discrimination task and a deployment of attention task (DOAT, Gotlib, McLachlan, & Katz, 1988). This task also has advantages to the modified Stroop task. In the DOAT, participants are presented with two words on a computer screen, one presented above the other. After the words are presented, they disappear and two color blocks appear on the screen in the place previously occupied by the words. Participants are instructed to identify which color block appeared first. Although participants are told that one of the blocks appears slightly before the other, in actuality they appear on the screen simultaneously. An attentional bias exists if participants are more likely to indicate that the color-block which follows the target word appears first more often rather than indicating that the color-block following the neutral word appears first. Although the DOAT does not allow researchers to differentiate 21