Stress, Eating Behavior, and Mindfulness Among College Students

Stress, Eating Behavior, and Mindfulness among College Students

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Arts in the Graduate School of The Ohio State University

Jennifer Kuo, B.S.

Graduate Program in Psychology

The Ohio State University

2017

Master’s Thesis Committee:

Janice K. Kiecolt-Glaser, Ph.D., Advisor Charles Emery, Ph.D., Co-Advisor Ruchika Prakash, Ph.D.

Jennifer Kuo

2017

Abstract

Prior literature suggests that people who are subjected to acute stress tend to

overeat and make more unhealthy food choices. In addition, more mindful people tend to

have better health behaviors. However, past research has not evaluated whether

mindfulness moderates the relationship between stress and eating behavior. The current

study investigated whether mindfulness protected against stress-related eating behavior.

This study explored the relationship between stress and eating behavior among 97 undergraduate women. Participants were randomly assigned to the control condition (n =

54, a reading task and simple arithmetic task), or stress condition (n = 43, a job speech and complex arithmetic task). Afterwards, the women were offered red grapes and

M&Ms as part of what was described as a taste test to evaluate total caloric intake and food choice (proportion of M & M servings eaten over total servings eaten). Mindfulness did not predict caloric intake or proportion of M & M servings relative to total servings eaten. Additionally, mindfulness did not moderate the relationship between stress and eating behavior. In contrast to previous studies, women consumed fewer total calories in the stress condition compared to those in the control condition. However, greater decreases in positive affect following the TSST were associated with a higher proportion of M & M servings to total servings. Stress itself influences caloric intake, but affective response to stress can alter food choice by increasing unhealthy food preference. High fat, high sugar diets can lead to obesity, which increases risk for many adverse health

ii conditions. Therefore, identifying protective factors for higher emotional reactivity to stress could improve overall health.

iii

Dedication

To my family and friends:

Thank you for your constant support and encouragement.

Vita 1991...... ……….………………………………………………….Born, Rockville, MD

2009…….……….………………...Thomas Sprigg Wootton High School, Rockville, MD

2013……………………………University of Maryland, College Park, College Park, MD

Publications

Alam, M. S., Kuo, J. L., Ernst, P. B., Derr-Castillo, V., Pereira, M., Gaines, D., … Williams, K. (2014).Ecto-5′-Nucleotidase (CD73) Regulates Host Inflammatory Responses and Exacerbates Murine Salmonellosis. Scientific Reports, 4. http://doi.org/10.1038/srep04486 Derry, H. M., Padin, A., Kuo, J. L., Hughes, S., & Kiecolt-Glaser, J. K. (2015).Inflammation and Depression in Women. Current Psychiatry Reports. doi: 10.1007/s11920-015-0618-5. Merwin, R.M., Dmitrieva, N.O., Honeycutt, L.K., Moskovich, A.A., Lane, J.D., Zucker, N.L., Surwit, R.S., Feinglos, M. & Kuo, J. (2015). Momentary predictors of insulin restriction among adults with type 1 diabetes and eating disorder symptomatology. Diabetes Care, 38 (11), 2025-2032. doi: 10.2337/dc15-0753.

Fields of Study

Major Field: Psychology

Table of Contents

Abstract ...... ii

Dedication ...... iv

Vita ...... v

List of Tables ...... vii

List of Figures ...... vii

Chapter 1: Background and Significance ...... 1

Chapter 2: Research Design and Methods ...... 16

Chapter 3: Results ...... 31

Chapter 4: Discussion ...... 40

References ...... 56

Appendix A: Tables ...... 65

Appendix B: Figures ...... 86

Appendix C: Experiment Protocol ...... 93

Appendix D: Self-Report Questionnaires ...... 114

Appendix E: Funneled Debrief ...... 131

Appendix F: Study Timeline ...... 135

List of Tables

Table 1: Demographics ...... 66

Table 2: Manipulations Check ...... 68

Table 3: Repeated measures statistics for affect ...... 69

Table 4: Repeated measures statistics for arousal ...... 70

Table 5: Correlations between primary variables ...... 71

Table 6: Repeated measures statistics for hunger ...... 72

Table 7: Regression statistics for Hypothesis 1 ...... 73

Table 8: Regression statistics for Hypothesis 1 without covariates ...... 74

Table 9: Regression statistics for Hypothesis 1b stress condition ...... 75

Table 10: Regression statistics for Hypothesis 1b stress condition without covariates .... 76

Table 11: Regression statistics for Hypothesis 2 ...... 77

Table 12: Regression statistics for Hypothesis 2 without covariates ...... 78

Table 13: Regression statistics for Hypothesis 3 ...... 79

Table 14: Regression statistics for Hypothesis 3 without covariates ...... 81

Table 15: Post hoc statistics for changes in positive affect and proportion of M & M servings ...... 82

vii

Table 16: Post hoc statistics for mindfulness x affective response ...... 83

Table 17: Post hoc statistics for hunger x group ...... 85

viii

Table of Figures

Figure 1: Distribution of total calories consumed...... 87

Figure 2: Distribution of proportion of M & Ms ...... 88

Figure 3: Affect levels over time ...... 89

Figure 4: Arousal levels over time ...... 90

Figure 5: Hunger levels over time ...... 91

Figure 6: Changes in affect predicting proportion of M & M servings ...... 92

Chapter 1: Background and Significance Overview

Obesity contributes to an estimated 112,000 preventable deaths each year in the

United States (Benjamin, 2010). Stress can promote obesity by affecting caloric intake

(Benjamin, 2010). However, mindfulness may protect against stress-related eating

(Daubenmier et al., 2011). Mindfulness involves maintaining a nonjudgmental attitude and awareness to the present moment, while avoiding distracting thoughts of the past or present (Thompson & Waltz, 2007; Kabat-Zinn, 2003). More mindful people report lower levels of perceived stress (Prakash, Hussain, & Schirda, 2014). People who are higher in mindfulness also report better sleep quality, more physical activity, and healthier diets compared to less mindful people (Murphy, Mermelstein, Edwards, &

Gidycz, 2012; Martin, Prichard, Hutchinson, & Wilson, 2013; Howell, Digdon, Buro, &

Sheptycki, 2008; Bodenlos, Wells, Noonan, & Mayrsohn, 2015; Framson, Kristal,

Schenk, Littman, Zeliadt, & Benitex, 2009; Gilbert & Waltz, 2010; Loucks et al., 2015a).

Mindfulness appears to protect against the negative effects of stress, and may also reduce stress-related eating (Weinstein, Brown, & Ryan, 2009; Papies, van Winckel, &

Keesman, 2016). Indeed, mindfulness moderated the relationship between stress and perceived health, as measured by quality of life and physical health satisfaction

(Bränström, Duncan, & Moskowitz, 2011). Nevertheless, few studies have evaluated the relationships among stress, mindfulness, food intake, and food choice.

1 In this study, mindfulness was expected to protect against the relationship between acute stress and unhealthy eating behavior. Many of the stress eating studies reviewed below have focused on women because women are more likely to report stress-

related eating due to higher likelihood of dieting or restrained eating (Wardle et al., 2004;

Greeno & Wing, 1994). Restrained eating is a strong predictor of stress-related eating, suggesting that women are more vulnerable to overeating in response to stress (Greeno &

Wing, 1994). Therefore, only women were recruited for this study.

Prior research on negative emotions and eating has often focused on eating disorders. However, people with eating disorders have different eating patterns than people without eating disorders and without weight concerns. The current study did not examine eating disorders because of these different eating patterns among this population

(Berg et al., 2009; Geliebter, Hassid, & Hashim, 2001).

Stress and eating behavior

People may eat in response to stress to cope with negative affect. According to escape theory, people overeat to distract themselves from aversive self-awareness to lower negative affect (Heatherton & Baumeister, 1991). They hold themselves to high standards and are disappointed if they fail to meet these standards. During high levels of awareness, people exhibit higher restraint, but when they experience low levels of awareness, inhibitions decrease, leading to unrestrained eating. To test this theory in the lab, Macht and Simon measured eating motivation in relation to reported affect. Women were more motivated to eat and reported more intense hunger during negative emotional states than in positive or neutral emotional states across six days (Macht & Simon, 2000).

2 Negative emotions may enhance subjective feelings of hunger and consequently increase food intake.

Excessive cognitive load may also contribute to overeating (Lattimore &

Maxwell, 2004). According to this theory, people are more likely to eat more when cognitive resources are depleted (Lattimore & Maxwell, 2004). In particular, some evidence suggests that restrained eaters experience high cognitive load when avoiding overeating. Consistent with this idea, after performing a cognitively demanding task involving ego-threat stimuli, restrained eaters ate more than unrestrained eaters

(Lattimore & Maxwell, 2004). Cognitive load and ego-threat distress may increase food intake by impairing restraint.

Stress and mood can influence food intake (Finch & Tomiyama, 2014). In a bidirectional manner, people often respond to stress by increasing food intake; in turn, eating palatable food can reduce stress, thus reinforcing this pattern of eating pleasurable foods when stressed (Dallman, 2010). Heightened stress sensitivity can increase the likelihood of eating in response to stress; eating food to reduce stress can lead to a cycle of overeating (Tomiyama, Dallman, & Epel, 2011). Comfort eating can inhibit the physiological stress response when exposed to acute stress (Finch & Tomiyama, 2014).

Stress can increase the likelihood of choosing less healthy foods and eating more unhealthy foods (Zellner et al., 2006; Epel, Lapidus, McEwen, & Brownell, 2001;

Dallman, 2010). One study evaluated whether stress altered food preference. Compared to the control condition, women who were exposed to an acute stressor preferred sweet, high fat foods from a selection of high or low calories foods and sweet or salty foods

3 (Zellner et al., 2006). The two groups did not differ in salty snack food intake, leading the

authors to suggest that sweet foods may be more palatable in stressful times (Zellner et al., 2006). In fact, acute stress can increase preference for high fat comfort food, many of which are salty (Dallman, 2010). Women who reported increases in negative mood

following an acute stressor also ate more calories (Epel et al., 2001).

People high in emotional eating are more prone to overeating. In one study, food

intake did not differ between the stress and control conditions; however, women high in emotional eating ate more in response to a laboratory stressor compared to low emotional eaters, suggesting that there may be other factors that influence stress-induced eating (van

Strein, Roelofs, & de Weerth, 2013).

Stress lowers executive function, the cognitive processes involved in goal- directed behavior. With lower executive function, people are more prone to habitual eating patterns rather than exercising cognitive control of goal-directed behavior (Singh,

2014). Stress lowers cognitive control, and can induce habitual emotional eating of higher fat food in greater amounts (Singh, 2014). Thus, emotional eating can occur in response to emotional arousal, as a way to manage negative affect. However, when mental effort is expended, cognitive capacity to inhibit eating decreases. Lower inhibition coupled with lower emotional and behavioral control increases impulsivity, thus increasing the likelihood of overeating (Yau & Potenza, 2013). Stress impacts emotional control such that people may eat to manage emotions.

Social stressors may have particularly strong influences on eating behavior. In a study that investigated the relationship between social exclusion and self-regulation,

4 individuals who were told that no one wanted to work with them ate more cookies than those in the control acceptance condition (Baumeister, DeWall, Ciarocco, & Twenge,

2005). The socially rejected participants also ate more if they had higher negative affect.

Overall, these findings suggest that social stress may impair self-regulation in eating behavior.

Mindfulness

Mindfulness involves present-centered awareness and attention to thoughts, emotions, and actions (Prakash, Hussain, & Schirda, 2015). Components of mindfulness include observing, describing, acting with awareness, accepting without judgment, and non-reactivity (Fogarty, Lu, Sollers, Krivoschekov, Booth, & Consedine, 2015).

Mindfulness differs between individuals, and relates to emotional and mental well-being

(Brown & Ryan, 2003). Although mindfulness is considered relatively stable, it can be trained through mindfulness-based interventions (Brown & Ryan, 2003; Thompson &

Waltz, 2007).

Mindfulness, health, and health behaviors. Mindfulness is related to many positive health behaviors. For example, more mindful people tend to have better sleep quality, healthier diets, and more frequent physical activity (Murphy, Mermelstein,

Edwards, & Gidycz, 2012; Martin, Prichard, Hutchinson, & Wilson, 2013; Howell,

Digdon, Buro, & Sheptycki, 2008; Bodenlos, Wells, Noonan, & Mayrsohn, 2015;

Framson, Kristal, Schenk, Littman, Zeliadt, & Benitex, 2009; Gilbert & Waltz, 2010;

Loucks, Britton, Howe, Eaton, & Buka, 2015b). More mindful people also have higher emotional well-being, higher social functioning, greater energy, and lower blood pressure

5 and lower inflammation (Bodenlos et al., 2015; Tomfohr, Pung, Mills, & Edwards,

2015). Perhaps as a consequence of these healthier behaviors, the rates of obesity and

adiposity were lower in more mindful people relative to less mindful people (Loucks et

al., 2015a).

In an observational study, undergraduate women with higher mindfulness at

baseline were more likely to report better physical health eight weeks later than less

mindful women (Murphy et al., 2012). In fact, mindfulness was a better predictor of self-

reported physical health than healthy eating, physical activity levels, and sleep quality

(Murphy et al., 2012). In a mediation analysis, baseline mindfulness was associated with

better self-reported physical health at follow-up as a function of better baseline sleep quality. Although this study only spanned eight weeks, findings suggest that more

mindful people have better health habits and self-reported physical health than less mindful people.

Mindfulness is linked to obesity-related health risks. In a cross-sectional study of

382 middle-aged adults from the New England Study, more mindful people had a lower

likelihood of obesity and a lower abdominal adiposity (Loucks et al., 2015a). Obese

participants who had not been obese in childhood had significantly lower mindfulness

than participants who never met criteria for obesity across development. In addition to

obesity, mindfulness also influenced cardiovascular health. Using the same sample,

Loucks and colleagues investigated the relationship between mindfulness and seven

cardiovascular disease (CVD) risk factors: smoking, physical activity, body mass, healthy

diet, cholesterol, blood pressure, and fasting glucose. People higher in mindfulness

smoked less, exercised more, and had lower BMIs and fasting glucose levels than less

6 mindful people (Loucks et al., 2015b). These findings demonstrate that mindfulness may

contribute to better health outcomes in part by influencing health behaviors.

Mindfulness interventions and eating behavior. Mindfulness-based stress reduction (MBSR) interventions can improve coping during stressful situations and promote healthy behaviors (Grossman, Neimann, Schmidt, & Walach, 2004).

Mindfulness interventions teach skills such as acknowledging negative feelings and not impulsively eating after seeing food (Gilbert & Waltz, 2010). They also teach people to notice and accept negative feelings without using food to cope. Instead of avoiding them, mindfulness interventions teach people to observe their feelings and react less to negative thoughts and emotions as they engage in healthy behaviors. In addition, mindfulness helps people to acknowledge when they feel discouraged without immediately giving up

(Gilbert & Waltz, 2010). These skills may promote healthier eating through enhancing mindfulness.

In a systematic review on mindfulness-based interventions and obesity-related behaviors, 18 out of 21 studies showed improvements in the targeted eating behaviors associated with weight gain (O’ Reilly et al., 2014). Another meta-analysis on mindfulness interventions for weight loss found a significant effect of mindfulness interventions on weight loss; however, methodological limitations in the included studies made it unclear whether mindfulness itself was the mechanism for weight change (Olson

& Emery, 2015). Overall, mindfulness interventions seem to have an effect on eating related behaviors and weight loss, but changes in mindfulness may not directly influence weight loss. Taken together, mindfulness interventions appear to reduce weight; one potential pathway is through decreased maladaptive eating behaviors.

7 Mindfulness interventions may also influence binge eating. In a meta-analysis of

21 studies, mindfulness interventions for controlling binge eating had a medium to large

effect (Godfrey, Gallo, & Afari, 2015). Mindfulness training reduced binge eating and

frequency of emotional eating (Katterman, Kleinman, Hood, Nacker, & Corsica, 2014).

Mindfulness training did not reduce maladaptive eating behavior in samples with low

emotional eating (Katterman et al., 2014). Thus, the floor effect may influence how much

MBSR can reduce maladaptive eating if the frequency of maladaptive eating is already

low.

Mindfulness interventions can also promote healthier eating behaviors. Women in

a mindfulness intervention targeting stress and stress-related eating in overweight and

obese women reported reduced external eating (overeating due to heightened attentional bias) and emotional eating (maladaptive emotion regulation of eating to suppress negative feelings) compared to women in the control condition (Daubenmier et al., 2011).

Those in the intervention group improved in mindfulness and interoceptive awareness

(bodily awareness). Secondary analyses found that improvements in mindfulness and reduced emotional eating were related to reductions in abdominal adiposity (Daubenmier et al., 2011). Mindfulness interventions with a stress reduction component promoted better eating behaviors and were associated with reduced abdominal adiposity.

Mindfulness training can impact eating behavior by changing people’s evaluation

of food cues when hungry. In a mindful attention induction experiment, Papies and

colleagues (2015) evaluated whether mindfulness mediated the relationship between

hunger and food choice among undergraduate students. In the mindful attention training

condition, participants were trained to apply mindful attention to appetizing, unhealthy

8 food pictures and healthy food pictures; in the control condition, they were instructed to look closely at the pictures. After training, participants rated the likelihood that they would eat computer-presented food at that moment. Control condition participants chose more unhealthy foods than those in the experimental condition (Papies et al., 2015). An additional experiment examined the effects of mindful attention on food choice and caloric consumption using a behavioral measure, access to a lunch buffet with salad and snack choices. Participants in the mindful attention condition were more likely to choose salad than the control participants (Papies et al., 2015). After eating, hungrier individuals in the mindfulness training condition were better able to regulate their craving for unhealthy foods compared to those in the control condition (Papies et al., 2015).

Mindfulness appeared to protect against the relationship between hunger and greater food intake, particularly high fat food intake.

In another study, more mindful undergraduate students reported a lower frequency of uncontrolled eating than their less mindful counterparts (Jordan et al.,

2014). To extend these findings to actual eating behavior, the researchers conducted mindfulness inductions and then offered participants chocolate, almonds, and pretzels.

People with higher baseline mindfulness levels ate fewer calories. Those in the mindfulness condition ate fewer calories than those in the control condition, even though the inductions did not target food or eating behavior.

Mindfulness and eating behavior. Mindfulness is related to healthier eating patterns (Murphy et al., 2012; Jordan, Wang, Donatoni, & Meier, 2014; Gilbert & Waltz,

2010). For example, more mindful female college students reported healthier eating patterns relative to less mindful women (Murphy et al., 2012). In a study by Lattimore

9 and colleagues (2011), more mindful women were less likely to exhibit uncontrolled and

emotional eating than less mindful women. Another study investigated how mindfulness

relates to health behaviors (physical activity, diet, and self-efficacy) among

undergraduate students (Gilbert & Waltz, 2010). Compared to less mindful people, more

mindful people ate more fruits and vegetables, exercised more, and felt more confident in

their diet and exercise abilities (Gilbert & Waltz, 2010).

Mindfulness can influence how people respond with hunger and craving when

presented with food cues. In a study of 19 obese older adults, neural activity was

measured when exposed to food cues after a 2.5 hour food restriction period (Paolini,

Burdette, Laurienti, Morgan, Williamson, & Rejeski, 2012). Adults with higher

mindfulness were able to return to their default mode network (DMN) in response to the

food cues, whereas adults with lower mindfulness did not. The fact that they were able to

return to the DMN suggests that they were less preoccupied with food cues and better

able to accept feelings of craving and hunger (Paolini et al., 2012). Thus, mindfulness

may influence how people respond to food, especially in times of hunger.

Another study evaluated how food-related attitudes and mindfulness affected

eating behavior (Jordan et al., 2014). Participants were randomly assigned to an ego

depletion task, which lowers self-control abilities, or a control task. More mindful people had more positive attitudes toward fruit compared to less mindful people, which predicted actual food choice (Jordan et al., 2014). Mindfulness was associated with lower

calorie consumption, independent of self-regulation and condition (Jordan et al., 2014).

10 Stress and mindfulness

Several mindfulness intervention studies reported that mindfulness lowered stress reactivity in response to a social threat challenge (Kemeny et al., 2012; Britton, Shahar,

Szepsenwol, & Jacobs, 2012; Creswell, Pacilio, Lindsay, & Brown, 2014). Comparing mindfulness training to a waitlist control, more mindful people had greater self-control than less mindful people in response to a social exclusion manipulation (DeWall,

Deckman, Pond, & Bonser, 2011). Thus, mindfulness may enhance self-control in times of social stress (DeWall et al., 2011).

Emotion regulation may be one potential mechanism through which mindfulness increases coping ability. Emotion differentiation, a form of emotion regulation, is the ability to distinguish between similar emotions as separate and discrete constructs during emotional stress (Fogarty et al., 2015). More mindful people had greater negative emotion differentiation than less mindful people (Fogarty et al., 2015). Negative emotion differentiation is associated with greater emotional flexibility and resilience (Fogarty et al., 2015). Prakash and colleagues (2015) found that more mindful people reported less perceived stress than less mindful people. More mindful people reported better emotion regulation skills, which led to lower perceived stress compared to less mindful people

(Prakash et al., 2015). Thus, mindfulness relates to more adaptive coping, which can lead to better emotion regulation.

Mindful people may have a lower response to stress compared to less mindful people. In a study evaluating neuroendocrine and psychological stress responses to a social evaluative stress challenge vs. a control task, more mindful people had a lower

11 cortisol response to stress. More mindful people also reported less psychological distress in response to a social stress challenge, relative to the control task (Brown, Weinstein, &

Creswell, 2012). At baseline and after the stress challenge, more mindful people reported lower negative affect and anxiety compared to less mindful people. This evidence suggests that physiological and psychological stress responses may be lower among more mindful people.

Mindfulness is linked to both the appraisal of stressful situations and coping.

After completing a laboratory social stress task, more mindful undergraduates reported less stress and had a faster recovery from stress compared to less mindful students

(Weinstein, Brown, & Ryan, 2009). These effects were independent of neuroticism and optimism, suggesting that mindfulness uniquely contributed to stress recovery (Weinsten et al., 2009). The students also reported using more approach coping, which is tackling the stressful situation directly, and less avoidant coping (Weinstein et al., 2009). In an observational study, students with higher baseline mindfulness had lower levels of perceived stress a month later than less mindful people (Weinstein et al., 2009). People higher in baseline mindfulness appraised their daily experiences as less stressful relative to less mindful people in their weekly journals that monitored daily well-being and perceived stress (Weinstein et al., 2009). Lower perceived stress and more adaptive coping contributed to better well-being among mindful people. To evaluate whether these beneficial effects of mindfulness were maintained in the real world, undergraduates were assessed at the beginning of the semester, one to two days before the midterm, and one to two days before the final. Before academic tests, students reported stress appraisal, coping responses, and current well-being. Students with higher baseline mindfulness

12 levels perceived both the midterm and final as less threatening, and reported less avoidant coping before each exam. Thus, mindfulness can lower perceived stress and physiological stress responses through improved coping and appraisal.

Current Study

Mindfulness positively influences psychological and physical health, and is associated with better health behaviors. As described in the literature review, mindfulness interventions reduce maladaptive eating behaviors, and mindfulness itself promotes more adaptive stress processing (Weinstein et al., 2009). Acute stress increases food intake and a preference for sweets, but perhaps mindfulness can lower the detrimental effects of stress on eating behavior (Zellner et al., 2006). Studies have evaluated whether mindfulness lowers food intake and unhealthy food preference; however, no study has investigated whether mindfulness can protect against stress-related eating with a stress induction task.

This study investigated the role of mindfulness in stress-related eating behavior.

The current study used the Trier Social Stress Test (TSST), a stress induction task involving an evaluative job interview and arithmetic task, to study how stress impacted eating behavior, and whether mindfulness moderated this relationship. Participants were randomly assigned to the stress or the control condition. The control condition involved silently reading a neutral magazine article, reading the magazine article aloud, and completing simple arithmetic exercises. Following the stress or control task, eating behavior was assessed using a taste test of healthy food (grapes) and unhealthy food (M

& Ms) (Zellner et al., 2006; Epel et al., 2001). Eating behavior was measured by food

13 intake (total calories consumed) and food preference (proportion of M & M serving sizes over total serving sizes eaten).

Food intake was measured by total calories eaten (Epel et al., 2001). The weight of food eaten was calculated by subtracting weight of the bowl after the taste test from weight of the bowls before the taste test. Calories were calculated using these weights and nutritional information on packaging and dietary guidelines from the U. S.

Department of Agriculture National Nutrient Database for Standard Reference (NDSR).

Every 100 grams of milk chocolate M & Ms equates to 492 kilocalories (USDA, 2014).

Every 100 grams of grapes equates to 57 kilocalories (USDA, 2014). Serving sizes were calculated based on packaging information and dietary guidelines from the USDA such that one cup of grapes (237 g = 1 cup) equals one serving of grapes and one serving of M

& Ms equals 21 grams (Epel et al., 2001). The food choice variable was calculated using a proportion of M & Ms servings eaten divided by total servings eaten (grapes servings eaten plus M & M servings eaten).

Hypotheses

1. Women in the stress condition will eat more overall, and a higher proportion of M

& M servings over total servings, in comparison to women in the control

condition.

a. Women with greater decreases in positive affect following the TSST will

have greater food intake overall and higher proportion of M & M servings

eaten compared to smaller differences following the TSST.

14 2. Women with higher mindfulness will eat less overall and make healthier food

choices than women with lower mindfulness across both conditions.

3. Mindfulness will moderate the relationship between stress and food preference,

such that women with lower mindfulness in the stress condition will make more

unhealthy food choices (eat a higher proportion of M & M servings over total

servings). Mindfulness will moderate the relationship between stress and food

intake (total calories consumed).

a. Women with higher mindfulness across both conditions will make

healthier eating choices (consume fewer calories and eat a lower

proportion of M & M servings over total servings) compared to women

with low mindfulness. The greatest difference in eating behaviors will be

between less mindful women in the stress condition and more mindful

women in the control condition.

b. Women in the stress condition who are lower in mindfulness will make

more unhealthy eating choices than women with low mindfulness in the

control condition.

Chapter 2: Research Design and Methods

Research Protocol

Participants. Women were recruited from the Research Experience Program

(REP) for undergraduate psychology students enrolled in Introductory Psychology at the

Ohio State University. This program awards course credit for research participation. Only

women were included to reduce gender confounds due to potential differences in

mindfulness and eating behavior (Gilbert & Waltz, 2010; Wardle et al., 2004).

Overeating in response to stress is more likely in women than in men (Wardle et al.,

2004).

The REP website’s study description said: “This study investigates how emotions

influence taste perceptions. You are only eligible if you are a woman and do not have an

eating disorder. You will be assigned to one of two conditions. In one, you will be asked

to do a speech and arithmetic task. In the other, you will be asked to do a reading and

arithmetic task. You will be asked not to eat or drink anything except water at least two

hours before your appointment. You will be asked to try some foods and rate their taste.

Throughout the study, you will be asked to complete questionnaires. The foods offered

will be grapes and chocolate. If you do not eat dairy, or are allergic or dislike either of

these, please do not sign up for this study.”

Women were asked about their height and weight to calculate BMI. Those who had a body mass index (BMI: kg/m2) of 18.5 or lower were excluded from data analyses.

16 The hypothesized effect of acute stress influencing overeating may not be seen in

underweight women because underweight women tend to eat less in response to negative

emotions compared to normal and overweight women (Geliebter & Aversa, 2003).

Underweight women are also more likely to have eating disordered pathology; thus,

findings would be less likely to generalize to the broader population (Wilson, Darling,

Fahrenkamp, D’Auria, & Sato, 2015). Additionally, women diagnosed with eating disorders were also excluded due to abnormal eating behaviors in response to stress

(Tomiyama et al., 2012).

Power analysis. Jordan et al. (2014) found a partial η2 of 0.46 in the relationship

between mindfulness and snack choice of fruits versus sweets. The r2 is equivalent to

partial η2, so the effect size f was calculated from the partial η2. The effect size f was

0.518, but, to be conservative, the power analysis performed used the convention of a

large effect size f of 0.4. Assuming a similar effect size for mindfulness in the current

study, a sample size of 84 would provide 95% power to detect significant differences in

food choice using an ANCOVA with two predictors, five covariates, and an alpha level

of 0.05. However, to account for missing data, a sample size of 108 was used.

Study protocol. Participants were randomly assigned to one of the two conditions

(control or stress). In the REP instructions, participants were told to not eat or drink

anything other than water two hours prior to the experiment, as has been done in other

studies to control for satiety across participants (Sproesser, Schupp, & Renner, 2014;

Yeomans & Coughlan, 2009). Women recorded what and when they had last eaten to

assess compliance with the instructions. To limit distractions, participants were asked to turn off their phones for the duration of the study.

17 Upon arrival to the lab, students were given the informed consent forms and the

study was explained in more depth. After the experimenter obtained consent, students

participated in individual sessions in which they underwent a stress-induction task, the

Trier Social Stress Test (TSST), or control condition. The TSST, a commonly used

method for inducing acute stress, elevates biological and psychological stress markers

(Allen, Kennedy, Cryan, Dinan, & Clarke, 2014; Frisch, Hausser, & Mojzisch, 2015).

The TSST has elements of uncontrollability and social-evaluative threat, which are

components of psychosocial stress induction tasks with the largest effects (Dickerson &

Kemeny, 2004). Before and after completing the TSST or control task, students were asked to complete the Self-Assessment Manikin (SAM) to ensure that the TSST increased arousal and decreased affect as a manipulation check.

Stress condition. In the stress condition, the experimenter asked the student

whether she had held an assistant restaurant manager position (Fagundes, Glaser, Hwang,

Malarkery, & Kiecolt-Glaser, 2013). If she had held that job, the experimenter asked if

she had worked as an assistant retail manager. These questions were meant to identify a

job that the participant had not previously held. The participant was asked to give a

speech detailing why she was a good candidate for the job She was given 10 minutes to

prepare and five minutes for the speech delivery. The experimenter introduced the

participant to the “committee panel” consisting of two raters dressed in white coats, who

were actually undergraduate research assistants. The women were informed that these

raters were judges trained in behavioral analysis. While the participant prepared, the

experimenter and panel left the room. During the speech and math tasks, the participant

was told that she was videotaped and these tapes would be used later for voice frequency

18 and nonverbal behavior analysis (Giles, Mahoney, Brunyé, Taylor, & Kanarek, 2014).

The raters took notes and provided no verbal or nonverbal feedback while the participant

gave her speech.

After the speech, the raters asked participants to complete a five-minute

arithmetic task in which they sequentially subtracted a two-digit number from a four-digit

number for one minute, with different numbers for each minute (Kirschbaum, Pirke, &

Hellhammer, 1993). For the first minute, they subtracted the number 13 from 1022.

Women were instructed to verbally report their answers and to start over if they made a

mistake. After the TSST, women completed more questionnaires.

Control condition. The control task included similar tasks as the TSST but

without the stress provoking elements of evaluative threat and uncontrollability (Het,

Rohleder, Schoofs, Kirschbaum, & Wolf, 2009). In the control condition, women silently

read a magazine section for ten minutes before reading the same material aloud for five

minutes. Then, they completed a simple arithmetic task counting up by 15 starting from 0

for one minute to match the arithmetic task in the TSST condition (Het et al., 2009;

Hidalgo, Almela, Villada, & Salvador, 2014). For the subsequent four minutes, they did

the same simple counting tasks for a minute starting from 0 for the following numbers:

10, 20, 25, and 30. Control participants were told that their performance would not be

evaluated. Following the task, they completed questionnaires. See Appendix A for the

TSST and control protocol.

Taste test. Following the control or stress condition tasks, participants were reminded that the study was investigating how emotions influence taste perception

19 (Zellner et al., 2006; Jordan et al., 2014). Before participants arrived, the containers of grapes and the bowl of M & Ms were weighed by the experimenter. The containers were the same size with similar volumes of food in each. They were told to eat as much or as little as they like. They were given a public speaking article to read while eating. Hunger was assessed before and after the eating task. The experimenter left the room for ten minutes when the participants were presented with the food (Allan, Johnston, &

Campbell, 2010) and the article (Epel et al., 2001).

After ten minutes, they completed the taste test questionnaire and eating-related questionnaires. In a funneled debrief, participants were asked what they believed the purpose of the study was before debriefing. They were also asked whether they had

previous meditation experience, and if they did, they completed the Meditation History

Questionnaire. After they left, the bowls were weighed again to determine the amount of

grapes and M & Ms that were eaten. See Appendix D for the experiment timeline.

Self-Report Measures

Participants were asked to complete several questionnaires at three time points,

before the TSST/control task, after the TSST/control task, and after the taste test. The

next section details the measures used in the study. Please see Appendix B for all self-

report questionnaires.

Background information. Participants were asked about age, race/ethnicity,

year, medical diagnoses, dietary restrictions, and hours of sleep from the prior night and

two prior nights ago. Sleep was included as a covariate because short sleep duration is

associated with increased food consumption, especially in emotional eaters (Dweck,

20 Jenkins, & Nolan, 2014). In addition, sleep duration influences eating behavior such that

shorter sleep increases food intake among disinhibited eaters (Chaput, Despres,

Bouchard, & Tremblay, 2011).

Although not everyone responds to stress with increased food intake, it is more

common for individuals who are stress overeaters to have a higher body mass index

(BMI) than people who do not eat more in response to stress (Dallman, 2010). Thus, BMI

was included as a covariate.

After the taste test, participants were asked when they last ate, what they last ate,

and what the current time was to ensure compliance. Additionally, tendency to eat more

or less in response to stress was assessed with the following question: “When other

people cause me stress (e.g., partner, friends, relatives, colleagues), I eat . . . 1 (much

less than usual), 2 (less than usual), 3 (the same as usual), 4 (more than usual), 5 (much

more than usual)” (Sproesser et al., 2014; Epel et al., 2001). These questions were asked

after the taste test so they were not primed with food-related questions until after they had

eaten.

Trait mindfulness. Mindfulness was measured by the Mindful Attention

Awareness Scale (MAAS), which measures an open, receptive attention and awareness

that is associated with other variables related to psychological well-being (Brown &

Ryan, 2003). The MAAS has been used in undergraduate samples (Brown & Ryan,

2003). Higher scores indicate higher levels of trait mindfulness. The scores are the average of the 15 items on a 6-point Likert scale ranging from 1 (almost always) to 6

(almost never). In a young adult sample, the MAAS had high internal consistency (r =

21 .82) (Brown & Ryan, 2003). The MAAS has adequate construct validity based on high correlations between the MAAS and measures of mindful engagement and high correlations between measures of state mindfulness and the MAAS (Brown & Ryan,

2003). Some examples of questions on the MAAS include “I could be experiencing some emotion and not be conscious of it until some time later” and “I find it difficult to stay focused on what’s happening in the present.” In the current study, the MAAS demonstrated adequate internal validity (α = .82). Scores ranged from 2.6 to 5.07 in the current sample.

The MAAS was counterbalanced with the CES-D to control for order effects; participants were randomized to either complete the MAAS before the CES-D or the

CES-D before the MAAS before the TSST or control condition. These questionnaires were counterbalanced in case there were order effects for how participants responded to the MAAS depending on when the questionnaire was administered in relation to other questionnaires.

Meditation History Questionnaire. People with a meditation history may respond to the mindfulness measures differently based on their experience, and their

MAAS scores may be higher if they have previous meditation experience (Baer, Smith,

Hopkins, Krietemeyer, & Toney, 2006). The Meditation History Questionnaire was administered after the eating task as the final questionnaire. Past research suggests that people with previous meditation experience tend to respond differently to trait mindfulness measures, such that their trait mindfulness scores are higher than people without a meditation history. In the current study, the MHQ demonstrated good internal reliability (α = .94). In this sample, 12 women endorsed a history of meditation. In this

22 sample, 12.6% of participants (four in the stress condition and eight in the control

condition) endorsed a history of meditation. Additionally, of those who endorsed

meditation history, 75% started in the last one to two months.

Depressive symptoms. Depressive symptoms were measured by the Center for

Epidemiologic Studies Depression (CES-D), a commonly used scale of depressive

symptoms (Radloff, 1977). CES-D scores range from 0 to 60 (higher scores indicate more depressive symptoms). CES-D scores were used as a covariate because depressive symptoms have been associated with increased food intake (Novick et al., 2005; Simon &

Von Korff, 2007; Kloiber et al., 2007). The CES-D has adequate reliability and validity

(Radloff, 1977). In the current study, the CES-D demonstrated adequate internal reliability (α = .83).

Hunger. To assess differences in hunger levels at baseline, participants rated their hunger using a four-item ten-point Likert scale ranging from zero to nine that was taken from past research (Jaremka et al., 2016; Jaremka et al., 2015) This measure was modeled off a hunger visual analogue scale (VAS) (Flint et al., 2000). Women were asked questions such as “How hungry do you feel,” “How full do you feel,” “How much do you think you can eat,” and “How satisfied do you feel?” (Flint et al., 2000). In the validation study, hunger VAS scores measured after breakfast were correlated with subsequent energy intake at lunch, as well as change in appetite scores before and after lunch, providing evidence that VAS scores are related to hunger and the desire to eat (Flint et al., 2000). Based on past research on hunger’s influence on negative affect and vice versa

(Macht & Simon, 2008), the SAM and hunger scales were counterbalanced during the three time points when both measures were administered. The current study used the

23 same four questions with a Likert scale ranging from zero to nine as in previous research

studies (Jaremka et al., 2015; Jaremka et al., 2016). In the current study, the hunger scale

demonstrated adequate internal consistency (α = .85). The internal consistency for this scale in this study is comparable to the internal consistency (α = .92-.94) found in previous studies using the modified hunger scale (Jaremka et al., 2016; Jaremka et al.,

2015).

Dietary Restraint. The three factor eating questionnaire (TFEQ) measures cognitive restraint, uncontrolled eating, and emotional eating (Karlsson et al., 2000;

Cappelleri et al., 2009). Based on the original TFEQ, a short, revised 18-item scale was created using factor analysis. This short form has good reliability and good convergent and discriminant validity (Karlsson, Persson, Sjostrom, & Sullivan, 2000). One modification on item 1 of the TFEQ is that the question was “When I smell a delicious food…” instead of “When I smell a sizzling steak or juicy piece of meat…” because vegetarianism is becoming more common (Angle et al., 2009). Angle and colleagues

(2009) conducted a replication study to validate the TFEQ-R18 in young adult women, and found good construct validity, even after the modification of item 1 (Angle et al.,

2009). The TFEQ has also been generalizable to non-obese populations (de Lauzon et al.,

2014). The TFEQ was administered after the eating task to avoid priming effects that may influence their eating behavior. In the current study, the Emotional Eating (α = .87),

Uncontrolled Eating (α = .87) and Cognitive Restraint (α = .72) subscales demonstrated

adequate internal reliability.

Dietary restraint was used as a covariate because people with different eating

patterns show different food intake in response to stress (Mitchell & Epstein, 1995). Both

24 restrained eaters and emotional eaters tend to increase food consumption in response to stress (Oliver, Wardle, & Gibson, 2000). In addition, people who respond to stress with increased food consumption are more likely to be restrained eaters who will forgo their typical avoidance of certain foods in favor of sweet, high-caloric snacks (Zellner et al.,

2006). In a study evaluating how stress influences disinhibited eating, women with higher restraint and 25isinhibition scores were more likely to overeat in response to stress

(Haynes, Lee, & Yeomans, 2003). Women who were high in emotional eating ate more in response to the TSST than women low in emotional eating (van Strien, Roelofs, & de

Weerth 2013).

Manipulation checks: stress. To test whether the TSST elicited changes in affect among participants, the Self Assessment Manikin (SAM) was administered before and after the TSST. The SAM is a visual rating scale of response to stimuli, specifically using the following affective states: affect, arousal, and dominance (Quesada, Wiemers,

Schoof, & Wolf, 2012). The SAM depicts nine images for each affective state. In this study, affect (sad to happy) and arousal (calm to aroused) states were assessed before and after the TSST to ensure that the stress induction task increased subjective stress. Arousal levels were measured as a way to assess for boredom because people tend to respond to boredom by eating. The SAM is appropriate for undergraduate students (Bradley & Lang,

1994). The coefficient alphas for affect (.63-.82) and arousal (.98) on the SAM demonstrate adequate reliability (Backs, da Silva, & Han, 2005). Other studies have used the SAM as a measure of perceived stress for the TSST and seen increases in arousal and decreases in affect after the TSST (Oldehinkel et al., 2011; Quesada et al., 2012).

25 Taste Test. To distract participants from guessing the hypothesis, fake taste tests

are often used (Lattimore, 2001; Yeomans & Coughlan, 2009). Participants were given a

taste questionnaire to rate the qualities of the M & Ms and the grapes. This scale was

based on a Likert scale ranging from 1 (not at all) to 7 (extremely). Some questions on

the taste test include “How sweet was the candy,” “How savory was the candy,” and

“How much did you enjoy the candy?” The same questions were asked in reference to

grapes as well.

Statistical Analyses

Data management. Data from self-report measures were checked for

nonresponses, errors, and outliers. Mindfulness scores were mean centered in order to

more meaningfully interpret the interaction between trait mindfulness and stress-related eating behavior (Aikin & West, 1991). Based on the literature reviewed above, sleep duration, hunger, dietary restraint, depressive symptoms, and BMI were included as covariates in all analyses, given their established relationship with food intake. Based on preliminary analyses, additional covariates (baseline arousal, time of experimental session, available M & M servings, and ratio of available grape servings to available M &

M servings) were also included in the model. For ranges of demographics, covariates, and outcome variables, see Table 1. Models were also run without the covariates because there were no significant correlations between the covariates and the two outcome variables.

Due to errors in questionnaire administration, there were missing data in the first seven participants, which resulted in missing scores on cognitive restraint, and one

26 participant with missing data on the hunger covariate due to technical issues in

questionnaire administration. Because over 5% of the sample (eight participants) had

missing data, multiple imputation was conducted (Graham, 2009). Analyses were

conducted using these imputations. Pooled results over five possible imputations were

reported for the regressions, descriptives, and correlations.

Preliminary analyses: randomization check. Demographic and baseline

measures were compared to ensure that there were no group differences prior to the stress manipulation. T-tests were conducted to compare the two groups on BMI, sleep duration, hunger, dietary restraint, depressive symptoms, age, mindfulness, and baseline SAM measures.

Preliminary analyses: stress manipulation check. To assess if arousal and

affect levels changed following the stressor, a repeated measures ANOVA testing the

interaction of time x condition was used. Arousal levels (calm to aroused) were expected

to increase after the stressor and have no significant difference following the control task.

To assess if affect levels decreased following the stressor, a repeated measures ANOVA

was used. Affect levels (negative to positive) were expected to decrease after the stressor

and have no significant change following the control task. Mixed design repeated

measures ANOVAs were conducted with time as the within subject factor and condition

as the between subject factor.

Hypothesis 1. Stress condition and eating behavior. Linear regression was used

to assess differences in food intake and food choice as a function of condition. SPSS

Version 24 was used to test for main effects. The dependent variables were food intake in

27 calories and food preference of grapes or M & Ms as measured by serving size. Separate models were used for each dependent variable: total calorie consumption and proportion of M & M servings over total servings. For both models, covariates BMI, hunger, total sleep duration from the past two nights, depressive symptoms, dietary restraint, baseline arousal, time of experiment, available M & M servings, and ratio of available grape servings to available M & M servings were included to test this hypothesis. All subsequent analyses including participants in both conditions used these covariates.

A separate model evaluated the stress group alone, using a linear regression to assess food intake and food choice as a function of the magnitude in the affective response. The magnitude of the affective response was measured by calculating a difference score from affect as measured by the SAM (negative to positive) before and after the experimental and control tasks. For both models, covariates BMI, hunger, sleep duration, depressive symptoms, dietary restraint, and time of experiment were included to test this hypothesis.

Hypothesis 2. Mindfulness and eating behavior. Linear regression was used to assess differences in food intake and food choice as a function of mindfulness. Eating behavior was measured in the same way as in the previous hypothesis. Separate models were used for each dependent variable: total calories consumed and proportion of M & M servings eaten.

Hypothesis 3. Mindfulness as a moderator of the relationship between stress and eating behavior. To assess whether mindfulness moderated the relationship between stress and caloric intake, the interaction between condition and mindfulness was

28 examined (Condition x Mindfulness) using linear regression. This interaction term was

entered as a predictor of food intake in terms of total calories eaten while controlling for

covariates. In step one of the model, mindfulness and condition were entered as

independent variables. In step two, the interaction term was added as a predictor of total calories consumed. In a separate model, this interaction was also tested as a predictor for proportion of M & M servings eaten.

Post-hoc exploratory analyses. Mindfulness was tested as a moderator of the relationship between affective response to the stressor and proportion of M & M servings

eaten. In a linear regression controlling for the aforementioned covariates, the interaction

term (Mindfulness x Affective Response) was entered as a predictor of proportion of M

& M servings eaten. In step one of the model, mindfulness and affective response were

entered as independent variables. In step two, the interaction term was added as a

predictor of proportion of M & M servings eaten.

Condition was tested as a moderator of the relationship between hunger and

caloric intake. In a linear regression controlling for covariates, the interaction term

(Hunger x Condition) was entered as a predictor of caloric intake. In step one of the

model, hunger and condition were entered as independent variables. In step two, the

interaction term was added as a predictor of caloric intake.

In a hierarchical linear regression, decreases in positive affect were tested as a

predictor of proportion of M & M servings eaten across all conditions. In step one of the

model, all the aforementioned covariates were included in addition to condition as both

29 conditions were included in this regression analysis. The second step included all the variables in step one in addition to decreases in positive affect.

Chapter 3: Results

A total of 108 female undergraduate students (50 in the stress condition and 58 in

the control condition) participated in this study. Data from 11 women were excluded from the analyses; 10 were underweight with a BMI of less than 18.5, and one withdrew from the study in the middle of the experimental session. The distributions of total caloric intake and proportion of M & Ms were within a skewness value of 2, which is considered an acceptable normal distribution (George & Mallery, 2006) (See Figure 1-2 for the distribution). The demographic characteristics were not statistically different between the excluded and included participants except for lower BMI in the excluded group, which reflected the 10 underweight women. Final analyses included 97 women (43 in the stress condition and 54 in the control condition). Women’s ages ranged from 18 to 43 (M =

19.02, SD = 2.79). The participants were primarily white (74.2%), and in their first academic year (68.0%) at The Ohio State University. Table 1 provides additional demographic information.

There was a wide range in caloric intake and proportion of M & M servings eaten in the current study. Caloric intake ranged from 4.56 to 464.76 kilocalories (M = 135.97,

SD = 100.27). Proportion of grapes servings eaten ranged from 0 to .78 (M = .34, SD =

.24). One serving of grapes is approximately 32 grapes. On average, women ate eleven

31 grapes. Proportion of M & M servings ranged from 0 to 1 (M = .66, SD = .25). M & M

servings eaten ranged from 0 to 3.76 (M = .90, SD = .85). One serving of M & Ms

equates to about ten M & Ms; women ate an average of nine M & Ms.

Randomization Checks

The stress and control condition groups did not differ on age, race, BMI, or year

in school (all ps > .05; see Table 1). At baseline, the two groups did not differ on

measures of affect, sleep, depressive symptoms, mindfulness, and hunger (all ps > .05;

see Table 1). Participants in the stress condition reported lower baseline arousal than the

control condition (See Table 1). Thus, analyses included baseline arousal as a covariate.

Additionally, the groups did not differ on measures of restrained eating, emotional eating,

and external eating (all ps > .15; see Table 1). Due to errors in administration, the TFEQ

was not collected from the first seven participants; however, using mean imputation,

means and standard deviations were calculated (Graham, 2009).

Stress Manipulation Checks

Consistent with predictions, women in the stress condition reported greater

arousal and lower positive affect following the TSST compared to women in the control

condition. Between the beginning and end of the experiment, women in the stress

condition reported decreased positive affect (See Figure 3 for change in affect over time).

There was a significant interaction between time and group on affect levels, F(2, 190) =

19.28, p < .001 (See Table 3). Before the task, there were no significant differences between groups on affect levels (Mdiff = -.12, SE = .31, p = .71). Immediately after the

task, women in the control condition reported significantly higher affect levels than those

in the stress condition (Mdiff = 1.41, SE = .32, p < .001). Among women in the stress

32 condition, there was a significant change in affect levels immediately after the stressor

(Mdiff = 1.95, SE = .20, p < .001). There was also a significant change in affect levels

among women in the control condition immediately following the control task (Mdiff = -

.43, SE = .17, p = .05).

The main effect of time on affect was also significant, F(2, 190) = 46.23, p < .001

(See Table 3). Mean affect levels significantly differed between conditions, F(1, 95) =

6.11, p = .02. Baseline affect levels did not differ between groups. After the tasks and the

taste test, there were significant differences in affect between the groups. Affect levels

immediately after the task differed between the control (Mcontrol = 6.48, SD = 1.56) and

stress condition (Mstress = 5.07, SD = 1.60). The mean changes in affect immediately following the task were also significantly different between the control (Mcontrol = -.43,

SD = 1.19) and stress condition (Mstress = -1.95, SD = 1.38).

There was a significant interaction between time and group on arousal levels, F(2,

190) = 22.27, p < .001 (See Table 4). Mean arousal levels were not significantly different between conditions, F(1, 95) = .72, p = .40. There was a main effect of time on arousal levels, F(2, 190) = 33.09, p < .001 (See Figure 4 for change in arousal over time).

Arousal levels immediately following the task differed between the stress (Mstress= 5.67,

SD = 1.84) and control condition (Mcontrol = 4.39, SD = 2.17). Before the task, there were

significant differences between groups on arousal levels (Mdiff = .93, SE = .38, p = .02).

Immediately after the task, women in the control condition reported significantly lower arousal levels than those in the stress condition (Mdiff = -1.29, SE = .41, p = .003). The mean changes in arousal immediately after the task were different between the stress

(Mdiff = -2.30, SD = 1.58) and control condition (Mdiff = .09, SD = 1.98). Among women

33 in the stress condition, there was a significant change in arousal levels immediately after the stressor (Mdiff = -2.30, SE = .28, p < .001). There was no significant difference in

arousal levels among women in the control condition immediately following the control

task (Mdiff = -.09, SE = .25, p = 1.00).

Women in the stress condition had lower baseline arousal levels than women in the control condition, which suggests that the increase in arousal levels could be due to regression to the mean. Regression to the mean in repeated measurements refers to the phenomenon in which the first measurement may be extreme and approaches the mean at the next measurement (Yu & Chen, 2015). To control for this effect, baseline arousal was included as a covariate in regression analyses.

Preliminary Analyses

Eight participants had missing data due to errors in questionnaire administration.

There were no significant differences between participants with missing data and the rest

of the sample on demographics, covariates, and outcome variables except for age.

However, age was statistically different due to one older non-traditional student with

missing data.

Correlations among study variables are listed in Table 5. There were no

significant associations between four covariates (BMI, depressive symptoms, cognitive

restraint, and total hours of sleep from the past two nights) and the two outcome

variables: total caloric intake and proportion of M & M servings eaten. However,

hungrier women tended to eat more calories than women who reported less hunger (r =

.44, p < .001). Greater mindfulness was associated with lower depressive symptoms (r = -

.42, p < .001). Greater cognitive restraint was weakly correlated with BMI (r = .25, p =

34 .01). BMI was not significantly associated with total caloric intake (p = .39) or proportion of M & M servings eaten (p = .56).

In this sample, the correlation coefficient between the MAAS and MHQ did not indicate a significant relationship between meditation experience and responses on the

MAAS (r = .002, p > .1). Additionally, MAAS scores did not differ based on whether meditation experience was endorsed, t(95) = -.02, p = .98. The mean MAAS score in the current sample (M = 3.81, SD = .63) were significantly lower than a similar demographic college student sample of 810 students (M = 4.00, SD = .93), t(905) = - 1.97, p = .049

(Osman, Lamis, Bagge, Freedenthal, & Barnes, 2016).

Women’s reports of their typical eating responses after stress were not significantly correlated with calories consumed (r = .14, p = .16). Chi square tests indicated no difference between conditions on typical eating response to stress Χ2 (2, N =

97) = 2.43, p = .66. The stress condition included women who typically ate less under stress (27.9%), women who ate the same under stress (23.3%), and those who ate more under stress (48.8%). Among control condition women, 27.8% reported that they typically ate less under stress, 31.5% reported eating the same under stress, and 40.7% reported eating more under stress.

The interaction between time and group on hunger levels was non-significant,

F(2, 188) = 1.75, p = .18 (See Table 6). However, there was a main effect of time on hunger, F(2, 188) = 26.21, p < .001 (See Figure 5 for changes in hunger over time). On average, hunger scores immediately before the taste test were 0.75 points lower than hunger scores from a previous study (Jaremka et al., 2015) after a 12 hour fast, in contrast to the minimum two hour fasting time in the current study, t(153) = 2.53, p = .01.

35 A regression analysis tested whether time of the experimental session predicted

proportion of M & M servings eaten. Time of the experimental sessions was calculated

by converting time to hours since 8 am, the earliest time that the REP experiments were

held. Women who participated in experimental sessions earlier in the day ate a higher

proportion of M & M servings compared to women who participated later in the day, (β =

-5.89E-8, t(97) = -2.39, p = .02). Thus, time of experimental session was included as a

covariate in all analyses for consistency. Additionally, the number of hours since the last

meal or snack was not significantly associated with caloric intake (p = .83) or proportion

of M & M servings eaten (p = .99). The number of available M & M servings and grape

servings did not differ between groups (p > .05; See Table 1). The number of M & M

servings offered ranged from 10.76 to 31.24 (M = 20.69, SD = 5.32). The number of

grapes servings offered ranged from .68 to 2.65 (M = 1.53, SD = .46).

Women tended to eat a lower proportion of M & M servings as the number of M

& M servings offered increased (r = -.29, p = .01). Thus, the number of available M & M

servings was also included as a covariate for analyses. This inverse relationship appears contrary to previous research suggesting that greater portion sizes are associated with

greater caloric intake (Kral & Rolls, 2004). Caloric intake and proportion of M & M

servings are positively correlated, but they measure different constructs. Energy density

and portion size contribute to overall energy intake independently and additively (Kral &

Rolls, 2004). M & Ms are more energy dense than grapes, which suggest that the

disproportionate energy densities could play a role in overall caloric intake. Thus, the

ratio of available grape servings to available M & M servings was also included as a

covariate to account for the possibility that available servings of both foods offered could

36 influence their total caloric intake and proportion of M & M servings eaten. The outcome variables involve both foods offered; therefore, this ratio incorporates the availability of both foods offered.

At study entry, women in the stress condition reported lower arousal than those in the control condition. Thus, baseline arousal was also included as a covariate in all analyses. All analyses used the time of the experimental session and baseline arousal in addition to the planned five covariates: BMI, hunger, restrained eating, depressive symptoms, and total sleep from the past two nights. Analyses were also run without covariates because there were no significant correlations between planned covariates and proportion of M & M servings eaten.

Hypothesis 1: Stress condition and eating behavior

Women in the stress condition were expected to eat more calories compared to women in the control condition. Using hierarchical linear regression, condition was a significant predictor of caloric intake after controlling for BMI, hunger, restrained eating, depressive symptoms, total sleep from the past two nights, baseline arousal, and the time of the experimental session. Contrary to hypotheses, women in the stress condition ate significantly fewer calories than women in the control condition, β = -42.84, t(96) = -

2.14, p = .03; see Table 7. In a model without covariates, the association between condition and caloric intake was still significant, β = -51.03, t(96) = -2.56, p = .01 (See

Table 11). Women in the stress condition and women in the control condition did not differ in the proportion of M & M servings eaten, β = -.04, t(96) = -.75, p = .45; see

Table 7. These results were also non-significant when the model was rerun without covariates, β = -.06, t(96) = -1.20, p = .23; see Table 8.

37 The magnitude of the affective response to stress was expected to predict

unhealthy eating behavior. However, greater decreases in positive affect after the TSST

did not predict caloric intake, β = -7.60, t(42) = -.66, p = .51; see Table 9. The model

without covariates also did not find that affective response significantly predicted caloric

intake, β = -.24, t(42) = -.02, p = .98; see Table 10. For those in the stress condition,

greater decreases in affective response were associated with a larger proportion of M &

M servings eaten, β = -.09, t(42) = -2.78, p = .01; see Table 9. In a model without

covariates, these results were marginally significant, β = -.05, t(42) = -1.79, p = 0.08; see

Table 10. Figure 6 illustrates the relationship between changes in positive affect and

proportion of M & M servings eaten.

Hypothesis 2: Mindfulness and eating behavior

More mindful women were expected to make healthier food choices compared to

less mindful women. However, mindfulness did not predict caloric intake, β = -20.65,

t(96) = -1.15, p = .25; see Table 11. More mindful women did not eat a greater

proportion of M & M servings over total servings, β = -0.03, t(96) = -.64, p = .53 (See

Table 11). Thus, mindfulness did not predict caloric intake or proportion of M & M

servings over total servings. In models without covariates, mindfulness did not predict

caloric intake or proportion of M & M servings eaten (See Table 12).

Hypothesis 3: Mindfulness as a moderator of the relationship between stress and eating behavior

Contrary to hypothesis 3, mindfulness did not protect against stress-related caloric intake, β = .37, t(96) = .08, p = .94 (See Table 13). Additionally, mindfulness did not moderate the relationship between stress and proportion of M & M servings eaten, β = -

38 .02, t(96) = -1.40, p = .16 (See Table 13). Similar results were seen in models without

covariates (See Table 14). Given these null findings, interactions were not probed.

Post-hoc exploratory analysis

Across both conditions, declines in positive affect following the task predicted a

higher proportion of M & M servings eaten, β = -.05, t(96) = -2.60, p = .01 (See Table

15). Based on the association between affective response to the stressor and proportion of

M & M servings eaten, an additional analysis tested the role of mindfulness on the

relationship between affective response to the stressor and proportion of M & M servings

eaten. There was not a significant interaction between mindfulness and changes in positive affect following the stressor on proportion of M & M servings eaten, β = .002, t(96) = .56, p = .58 (See Table 16).

Another analysis explored the joint influences of hunger and condition on caloric intake. Condition did not moderate the relationship between hunger and caloric intake, β

= -14.27, t(96) = -1.29, p = .20 (See Table 17). The interaction was not probed given the null finding.

Chapter 4: Discussion

This study investigated mindfulness in the context of eating behavior after an acute stressor. Unexpectedly, women in the stress condition ate fewer calories than women in the control condition. Women who experienced greater decreases in positive affect following the stress task made more unhealthy choices by eating a higher proportion of M & M servings over total servings. Based on related work, mindfulness was expected to promote healthy eating and protect against stress-related unhealthy eating (Beshara, Hutchinson, & Wilson, 2013; Fung, Long, Hung, & Cheung, 2016;

Jordan, Wang, Donatoni, & Meier, 2014). However, more mindful women did not eat fewer calories or eat a relatively lower proportion of M & M servings over total servings eaten. Additionally, mindfulness did not protect against stress-related unhealthy eating.

Hypothesis 1: Stress and eating behavior

The stress condition was expected to promote greater caloric intake and a higher proportion of M & M servings eaten compared to the control condition. Contrary to predictions, women in the stress condition consumed fewer calories than women in the control condition. While acute stress can lead to increased food intake, some studies found an association between acute stress and lower food intake (Sinha & Jastreboff,

2013). These differential findings may be due to many experimental factors such as type of stressor, length of stressor, amount and type of foods offered, and satiety and hunger

40 levels at the start of the study (Sinha & Jastreboff, 2013). Groups did not differ on typical eating behavior in response to stress. Therefore, differences in stress-related eating responses did not appear to account for these findings.

Although women in the stress condition with greater decreases in positive affect did not have higher caloric intake, they did eat a higher proportion of M & M servings.

These data are consistent with past studies, in which women ate more high fat and sugary foods in response to acute stress (Dallman, 2010; Epel et al., 2001; Zellner et al., 2006;

Oliver et al., 2000). This relationship was also seen among those in the control condition, highlighting the finding that greater affective response influences preference for high fat, high sugar foods. Greater decreases in positive affect following the tasks predicted more unhealthy food choices as observed by a higher proportion of M & M servings eaten.

Eating less in response to stress (stress hypophagia) has often been considered more favorable for reducing obesity risk than eating more in response to stress (stress hyperphagia) (Sproesser et al., 2014). Stress hypophagics may eat less than typical, but they may still make poor food choices, which have negative health implications.

Although the current study only evaluated eating in response to an acute stressor, these eating responses may extend to chronic stress. Those who eat more unhealthy foods when under chronic stress may be at greater risk for obesity and obesity-related diseases

(Benjamin, 2010).

Acute stress has been associated with greater food intake, particularly among overweight women with high cognitive restraint (Wardle, Steptoe, Oliver, & Lipsey,

2000). In the current sample, the majority of women (73.7%) were within the normal

BMI range. BMI did not predict caloric intake or proportion of M & M servings eaten in

41 the current study. Additionally, women in this exhibited comparable cognitive restraint scores (M = 30.34) relative to a sample of similarly aged Finnish women (M = 35.55) used for validation of the TFEQ (Angle et al., 2009). Cognitive restraint values in other samples are similar to the mean of the current sample (de Lauzon et al., 2004; Keskitalo et al., 2008). Previous studies suggest that higher BMI and cognitive restraint increase the likelihood for eating more in response to acute stress, but this sample primarily included women in the normal BMI range. Thus, differences in BMI from previous studies may help explain women eating fewer calories following a stressor compared to those in the control condition.

In the current study, hunger did not significantly differ between the groups at any time point. Additionally, hunger did not appear to play a role in the relationship between condition and caloric intake. Controlling for hunger before the taste test, women in the stress condition consumed fewer calories than women in the control condition. Lower caloric intake among women in the stress condition was not explained by differential influences of condition on the relationship between hunger and caloric intake. Based on these relationships between hunger and caloric intake, hunger does not appear to explain lower caloric intake among women in the stress condition compared to those in the control condition.

Prior research suggests that stress may influence hunger. In a within-subjects design, women underwent an acute stressor and control task on separate days (van Strien,

Ouwens, Engel, & de Weerth, 2014). Hunger was lower following the stressor, but not following the control task, which mirrors the current study. Women with higher scores on emotional eating reported higher hunger values after the stressor than women lower on

42 emotional eating (van Strien et al., 2014). In the current sample, women’s emotional eating scores (M = 34.96) were comparable to the mean of the validation study sample (M

= 32.5) (Angle et al., 2009). Thus, women in the current sample were likely to experience the typical stress-related reductions in hunger, which was seen in the current study.

However, hunger levels were not significantly different at pre and post-task in either condition. In line with van Strien and colleagues (2014), women tended to respond with reduced hunger after the stressor, while those in the control condition reported higher levels of hunger following the task.

In other studies, cortisol response may interact with hunger to influence caloric intake. Participants reported less hunger after a TSST than after a control reading task

(Petrowski, Wintermann, Joraschky, & Päßler, 2014). Although their caloric intake did not differ between tasks, participants who had a higher cortisol response ate less compared to those with a lower cortisol response (Petrowski et al., 2014). However, results must be interpreted with caution as the sample only included 14 women. Their findings provide evidence that acute stress can reduce hunger. While the current study did not assess physiological stress reactivity, higher affective responses to stress did not predict lower caloric intake. Women who experienced higher decreases in positive affect after the task exhibited unhealthy eating by eating a higher proportion of M & M servings.

The severity of a stressor may influence whether people eat more or less in response to stress (Torres & Nowson, 2007). To evaluate this relationship, 158 middle- aged people recorded their daily stress and estimated daily food intake compared to their typical daily intake for 84 days. Participants reported eating less in response to a severe

43 stressor compared to a less severe stressor (Stone & Brownell, 1994). Relative to men, women were more likely to eat less as the severity of their daily stress increased (Stone &

Brownell, 1994). As the severity of daily stress increased, reported daily food intake decreased. The current study only included two conditions (stressor or control); therefore, no comparison could be made between stressors of varying severities and food intake.

Although the current study did not assess daily stress, women ate fewer calories following an acute stressor compared to women who completed a control task, suggesting that stress severity may influence subsequent caloric intake in time-limited stress.

Additionally, weight may influence how social stress affects food intake.

Following either a social inclusion or exclusion manipulation, adolescent women were offered snacks (Salvy et al., 2011). Excluded overweight adolescent women ate more than included overweight women (Salvy et al., 2011). In contrast, normal weight women ate more after inclusion compared to normal weight women who were excluded. If social exclusion is conceptualized as a stressor, their results parallel findings from the current study. Most of the current study’s participants (72.2%) were within the normal BMI range, and, thus, less likely to overeat in response to stress. In line with Salvy et al., caloric intake was higher following a control task compared to caloric intake following an acute stressor.

In the current study, women’s typical eating response was not associated with caloric intake. Eating responses may vary across different kinds of stressors. For example, participants viewed videos involving either exam stress, attachment stress in maternal relationships, or travel (the control condition); afterwards, they were offered food (Emond et al., 2016). Women who self-identified as stress undereaters ate fewer

44 calories in the academic stress condition compared to those in the attachment stress or control video conditions (Emond et al., 2016). Thus, typical eating responses and condition interacted to enhance differences in caloric intake between groups (Emond et al., 2016). However, in the current study, there was no interaction between reported typical eating response and condition influencing caloric intake. Thus, stress predicted lower caloric intake independently of typical eating response.

Tomiyama and colleagues (2012) found that leptin, a homeostatic hormone related to satiety, was related to subsequent food intake after an acute stressor. Women with greater increases in leptin after the stressor had lower food consumption compared to women with lower increases in leptin, but only for high fat, sweet foods. Thus, leptin and other physiological changes may affect food intake following a stressor.

Unfortunately, leptin was not assessed in this study, but could have been one mechanism to explain the lower caloric intake after the acute stressor compared to the control.

Hypothesis 2: Mindfulness and eating behavior

More mindful women were expected to consume fewer calories and eat a lower proportion of M & M servings compared to less mindful women. In the current study, mindfulness was unrelated to eating behavior as measured by caloric intake and proportion of M & M servings. The relationship between mindfulness and caloric intake was in the expected direction, but non-significant.

However, past studies evaluating relationships between mindfulness and eating behavior have relied on self-report measures (Beshara et al., 2013; Gilbert & Waltz,

2010; Martin et al., 2013). Self-reported food intake is less reliable than objective measures (Hebert, Clemow, Pbert, Ockene, & Ockene, 1995). Prior research has reported

45 inconsistent results on mindfulness and healthy eating (Martin et al., 2013). Some of the inconsistent results in the literature could reflect response bias due to social desirability.

Additionally, self-reported food intake spanned over a longer period of time (one week to one month) (Beshara et al., 2013; Gilbert & Waltz, 2010; Martin et al., 2013) relative to a single objective eating episode in the current study. Thus, differences in time frame and measurement of caloric intake may account for the results.

Mindful eating may be more closely related to eating behavior than mindfulness itself. The Mindfulness Eating Questionnaire (MEQ) focuses on nonjudgmental awareness of physical and emotional sensations while eating or in food-related environments (Beshara et al., 2013). More mindful women who scored higher on mindful eating reported eating fewer high fat, high sugar food servings (Beshara et al., 2013). The current study did not find that more mindful women ate fewer calories and made more healthy choices; but perhaps more specific mindful eating measures like the MEQ could have detected an effect.

Mindfulness did not influence eating behavior in the current study. A meta- analysis comparing meditation programs to active controls found insufficient evidence for meditation interventions improving stress-related eating behavior (Goyal et al., 2014).

In the two studies where eating behavior was an outcome, those in the meditation group had poorer eating behaviors than those in the active control; however, these two studies were classified as poor and fair quality, suggesting that future studies employ higher quality study designs (Goyal et al., 2014). Additionally, there was low to no effect of meditation interventions on weight loss (Goyal et al., 2014). Thus, there is weak evidence for mindfulness itself influencing eating behavior and weight loss.

46 In one study, more mindful people reported lower rates of impulsive eating

(Jordan et al., 2014). To extend these findings using objective food measures, they investigated whether trait mindfulness would interact with mindfulness inductions to predict caloric intake (Jordan et al., 2014). Before either the control (guided relaxation without a mindfulness component) or mindfulness inductions (mindfulness body scan), participants completed trait mindfulness measures. After the inductions, they were offered pretzels, M & Ms, and raw almonds under the guise of a taste test. People ate fewer calories following the mindfulness induction compared to those in the control condition. More mindful people ate fewer calories relative to less mindful people.

However, mindfulness in combination with mindfulness inductions did not predict lower caloric intake.

In contrast to their study, the current study did not find that more mindful women ate fewer calories. Differences in types of foods offered may account for their results as pretzels and almonds are more calorically dense than grapes. Additionally, they offered sweet and salty foods, which may have influenced participants’ food intake depending on their personal food preferences.

Based on the mindfulness literature, it is surprising that those who endorsed a meditation history did not have higher MAAS scores because greater state mindfulness improvements over an eight-week mindfulness intervention program were associated with increased trait mindfulness scores following the intervention (Kiken, Garland, Bluth,

Palsson, & Gaylord, 2015). However, the majority of people endorsing meditation history

(75%) had only been practicing for one to two months, which may account for no relationship between meditation history and trait mindfulness scores.

47 Hypothesis 3: Mindfulness will protect against stress-related eating behavior

Mindfulness did not protect against stress-related eating behavior. A previous study evaluated whether mindfulness protected against unhealthy food choices in response to an ego-threat task (Jordan et al., 2014). In the control task, participants crossed out every letter e while the ego-threat task involved crossing out the letter e except when a vowel appeared immediately after it, or two letters before it. After completing the e-crossing task (control or ego-depleting), participants were offered a snack (fruit or sweets). More mindful participants were more likely to choose fruit.

However, following the ego-depletion task, more mindful people were not more likely to choose healthy snacks than less mindful people. Mindfulness did not protect against ego depletion’s influence on food choice. Similarly, in the current study, mindfulness did not protect against stress-related unhealthy eating.

In an RCT comparing a 5.5 month diet and exercise intervention for weight loss with or without mindfulness training, mindfulness training was hypothesized to reduce psychological stress and reward-based drive to eat (Mason et al., 2016). Although mindfulness interventions tend to target stress reduction, changes in psychological stress did not mediate weight loss. Those in the mindfulness group had significantly lower reward-driven eating scores than those in the control group after the intervention and lower weight twelve months after baseline. Thus, reward-driven eating may be an important aspect of mindfulness and eating. This construct was not measured in the current study. Although the current study was cross-sectional and did not measure reward-driven eating, future research could investigate the role of trait mindfulness on

48 reward-driven eating. Trait mindfulness may protect against reward-driven eating rather than stress-related unhealthy eating.

Strengths and Limitations

The current study measured food intake objectively and offered more than one type of food. Objective food intake measures are preferable to self-reported intake. In a systematic review, over half of the studies found that subjective appetite did not correspond to energy intake (Holt et al., 2016). Many previous studies have relied on self-reported food intake, but self-reported intake is weakly correlated with actual food intake (Beshara et al., 2013; Jordan et al., 2014; Martin et al., 2013). Indeed, self-reported intake may be susceptible to response bias. Thus, actual food intake is a better strategy for understanding the relationships among stress, mindfulness and eating behavior.

Additionally, this study allowed participants to eat two different foods, providing a way to evaluate healthy eating choices based on amount of one food eaten compared to overall food servings eaten. Including two options for food through objective measures provides a more reliable evaluation of eating behavior, particularly in a more common context where more than one option is available. Several studies have found that people’s food preferences may change in response to acute stress, but not necessarily their overall caloric intake (Zellner et al., 2006; Epel et al., 2001). Thus, food preferences and total caloric intake were assessed by offering both grapes and M & Ms.

This study sample was composed of young undergraduate women with BMIs greater than 18.5, so generalizability may be limited. Additionally, exclusion criteria were addressed after experimental session completion, which resulted in exclusion of ten

49 participants’ data because their reported BMI was below 18.5. These exclusions also

contributed to the unequal number of participants in each condition in the analyses.

The taste test had some methodological limitations. Participants’ typical

preferences for certain foods were not assessed. Although exclusion criteria included not

eating red grapes or milk chocolate M & Ms, women who ate these foods may still have

had a typical preference for one over the other, which would influence their eating

behavior. Also, some women preferred not to eat M & Ms early in the morning. Given

that time of the experiment significantly predicted proportion of M & Ms eaten, this

variable was included as a covariate for analyses. Grapes were not the exact same

consistency each time due to the natural variability of produce.

Additionally, participants did not receive the same volume of available foods in each experimental session or the same number of calories for each specific food.

Although research assistants were instructed to fill the containers to three quarters full, they were not always able to refill the containers in between experimental sessions.

Therefore, participants did not have the same opportunities to eat the same amount of

grapes and M & Ms, a major limitation of the study. Volumes of the foods based on what

they perceived prior participants ate may have influenced participants. Additionally,

cleanliness of the foods could have contributed to their eating behavior. All participants

were given antibacterial hand sanitizer, but participants may have been wary of prior

participants’ cleanliness. Volume of foods can influence caloric intake through visual

cues and beliefs about how filling different foods may be (Kral & Rolls, 2004). To

account for these volume differences, the ratio of available grape servings to available M

& M servings was included as a covariate. In addition, the energy density of M & Ms is

50 much higher than that of grapes, which allowed for more M & M servings in the same bowl compared to that of grape servings. Thus, there were always more available M & M servings than grape servings based on these inherent differences.

Previous studies have provided a standardized meal and allocated longer times for

participants to eat, which may have influenced participants’ food intake (Tomiyama et

al., 2012; Tryon, DeCant, & Laugero, 2013a). Due to financial and time constraints, this

study did not provide a standardized meal before the tasks (Appelhans, Pagoto, Peters, &

Spring, 2010; Tomiyama et al., 2012; Tomiyama, Dallman, & Epel, 2011). A

standardized meal before the task controls for hunger and time since last meal. Many

considerations were weighed in designing the taste test because food eaten was the

outcome variable; however, the limited variability of the foods offered and differences in

when and what was last eaten could have influenced women’s approach to the taste test.

Implications and Future Directions

Stress overeating is generally seen as a greater risk for poor health than eating less

in response to stress. However, people who eat less in response to stress may still be

exhibiting unhealthy eating behaviors. In the current study, young women ate fewer total

calories in response to an acute stressor compared to those in the control condition.

However, there was an association between greater decreases in positive affect and

higher proportion of M & M servings eaten among women in the stress condition. While

eating less in response to stress is seen as fortunate, eating more unhealthy foods after

stress might lead to a cycle of poor diet quality and increased risk for obesity and related

health conditions.

51 The TSST is often used in research because it reliably produces physiological stress changes such as increases in cortisol. Due to financial constraints, no physiological data were collected. Future studies may benefit from evaluating whether physiological stress responses to the TSST correspond to reported responses, and how the magnitude of physiological stress response affects food intake and food choice. Exploring the relationship between physiological variables and food intake would be important to better understand what circumstances may influence increased or decreased food intake.

People with greater social anxiety symptoms respond to the TSST with higher stress responses (Crişan, Vulturar, Miclea, & Miu, 2016). Unfortunately, social anxiety symptoms were not assessed in this study. Future studies should investigate how social anxiety influences the TSST and people’s eating behavior following the TSST. The majority of stress-related eating research has focused on young women, and future work should also focus on wider age ranges and men.

Most stress eating research focuses on overeating following stress. However, people also eat less after stress as observed in the current study. One possible mechanism that may contribute to eating less after stress is leptin. Leptin, a hormone that signals satiety, may play a role in stress-related eating behavior (Appelhans, 2010; Tomiyama et al., 2012). Leptin, which is positively associated with BMI, circulates in the bloodstream and regulates energy homeostasis by signaling low energy states (Havel, 2004).

In a counterbalanced crossover design, normal weight and obese premenopausal women underwent a modified TSST and a control reading task, after which they were presented with various snacks (Appelhans, 2010). Independent of BMI, women with higher leptin levels had lower caloric intake following the TSST compared to their

52 caloric intake after the control task (Appelhans, 2010). Controlling for BMI, older postmenopausal women whose leptin levels increased after the TSST ate fewer high fat, high sugar foods compared to those whose leptin levels were unchanged (Tomiyama et al., 2012). After acute stress, higher leptin levels may account for lower caloric intake because leptin may protect against stress-related unhealthy eating. Thus, leptin levels could play a role in stress-related eating behavior. Given that mindfulness encompasses an attention and awareness to the present moment, mindfulness may be associated with greater consciousness of satiety. Thus, future studies evaluating leptin in relation to mindfulness would enhance the literature on mindful eating.

Under chronic stress, people tend to fall into habitual eating patterns, which may include eating more comfort food (Tryon, Carter, DeCant, & Laugergo, 2013b). Women experiencing chronic stress may respond to acute stressors differently than women who are not experiencing chronic stress. A previous study assessed chronic stress among participants who underwent the TSST or control task, followed by a snack buffet (Tryon et al., 2013a). Chronic stress enhanced unhealthy eating following acute stress. People with low cortisol reactivity and high chronic stress had a higher caloric intake from chocolate than those with high cortisol reactivity and low chronic stress (Tryon et al.,

2013a). Chronic stress increases the risk for unhealthy eating after acute stress, which can lead to obesity and related diseases.

Acute stress is time-limited; however, mindfulness may have greater protective benefits under conditions of chronic stress, which tends to persist across time. Chronic stress may also differentially influence eating behavior by interacting with the central reward system (Sominsky & Spencer, 2014). Under chronic stress, high levels of

53 glucocorticoid stress hormones increase preference for comfort food through reward system suppression, such that higher levels of food intake are needed to achieve the same

“rewarding” effect (Sominsky & Spencer, 2014). However, chronic stress could also decrease people’s appetite, particularly among unrestrained eaters (Sominsky & Spencer,

2014). Similar to acute stress, research on chronic stress has also found differing results on how chronic stress influences eating behavior. Further research could investigate whether mindfulness interacts with chronic stress to influence eating behavior.

The current study did not find a relationship between mindfulness and eating behavior. This result is consistent with prior literature indicating that meditation interventions do not appear to promote healthy eating behaviors (Goyal et al., 2014).

Previous studies have found mixed results on the relationship between trait mindfulness and eating behavior (Beshara et al., 2013; Gilbert & Waltz, 2010; Martin et al., 2013).

Thus, further research is needed to investigate the role of mindfulness on eating habits.

In the current sample, meditation history was unrelated to mindfulness scores, which is in contrast with previous work on mindfulness interventions enhancing state and trait mindfulness measures (Kiken et al., 2015). Mindfulness scores were significantly lower and less variable than other samples (Weinstein et al., 2009). Taken together, these different patterns of mindfulness could explain the lack of an association between mindfulness and eating behavior.

Although mindfulness did not protect against stress-related eating behavior, perhaps physical activity may play a role in stress-related eating behavior. Childs and de

Wit (2014) found that regular exercisers reported less of a decline in positive affect following acute stress than their sedentary counterparts. Unfortunately, physical activity

54 was not assessed in the current study. While health behaviors are highly correlated, physical activity may still protect against stress-related unhealthy eating after an acute stressor (Trudeau, Kristal, Li, & Patterson, 1998).Thus, future studies could evaluate the joint influence of exercise and acute stress on eating behavior.

In summary, women ate fewer calories following an acute stressor than women who underwent a control task. Consistent with previous research on increased preference for high fat foods after acute stress, women who responded to the stressor with greater affective decreases ate a higher proportion of M & M servings. Despite eating fewer total calories than those in the control condition, women in the stress condition with greater decreases in positive affect after the stressor ate a greater proportion of M & M servings than those with smaller decreases in positive affect. Unhealthy eating encompasses more than just quantity. Eating a diet of poor nutritional quality over a long period of time increases the risk for obesity and obesity-related health conditions (Wolongevicz et al.,

2009). Additionally, physiological variables involved in stress eating need further study because both physiological factors and psychological variables can contribute to stress- related eating. The current study focused on the relationship between acute stress and eating behavior. However, if women who respond to stress with greater decreases in positive affect habitually eat more high fat, sugary foods, these unhealthy eating patterns could increase risk for poorer physical health (Benjamin, 2010).

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Appendix A: Tables

65 Table 1 Demographic and Covariate Information for Analytic Sample (n=97)

Characteristic Stress Condition (n=43) Control Condition (n=54) Number Mean SD Number Mean SD p (%) (range) (%) (range) Race White 33 (76.7) 39 (72.2) .70 Asian 3 (7) 10 (18.5) Black 4 (9.3) 3 (5.6) Hispanic/Lat 1 (2.3) 2 (3.7) ina Native 1 (2.3) 0 (0) American Other 1 (2.3) 0 (0) Academic Year First Year 32 (74.4) 34(63) .39 Second Year 5 (11.6) 11 (20.4) Third Year 1 (2.3) 2 (3.7) Fourth Year 5 (11.6) 6 (11.1) Other 0 (0) 1 (1.9) Age 18.74 1.43 19.24 3.51 .39 (18-24) (18-43) BMI 23.61 3.39 23.41 3.68 .80 (18.55- (18.6- 35.51) 39.5) Total hours slept 14.71 2.08 13.88 (8- 2.69 .10 from the past two (9.5- 26) nights 19) Hunger post task 4.95 (1- 1.79 5.50 .1.88 .14 and prior to taste 9) (1.5- test 8.75) Depressive 10.33 9.44 10.98 (1- 8.19 .72 Symptoms, CES- (0-45) 39) D Mindfulness, 3.85(2. 0.66 3.78 0.60 .59 MAAS 6-5.07) (2.73- 5.07) Baseline Positive 7.02 (4- 1.37 6.91 (1- 1.62 .71 Affect, SAM 9) 9)

Baseline 3.37 (1- 1.60 4.30 (1- 2.03 .02 Arousal, SAM 7) 9) Emotional 32.17 20.4 34.96 (0- 20.82 .71 Eating, TFEQ (0-75) 6 83.54) Restrained 30.43 15.3 30.27 13.27 .91 Eating, TFEQ (4.17- 6 (4.17- 58.33) 62.5) (Continued)

66 Table 1: Continued

Uncontrolled 34.75 16.2 37.64 12.42 .36 Eating, TFEQ (11.11- 5 (11.11- 75.00) 69.74) Available M & 20.31 5.52 21.14 5.08 .44 M servings (10.76- (10.81- 31.24) 30.95) Available grapes 1.60 .43 1.48 .47 .19 servings (.79- (.68- 2.50) 2.65) Total kilocalories 107.56 89.8 158.59 103.1 .01 consumed (4.56- 4 (22.53- 5 3256.7 464.76) 6) Proportion of M .62 (0- .26 .68 (.09- .23 .23 & M servings 1) 1) eaten

67 Table 2 Manipulation Checks Before and After the Inductions

Mean before Mean after Mean after Change in scores Emotion TSST/control TSST/control taste test from pre- to post- (SD) (SD) (SD) TSST/control (SD)

Stress Condition

Affect 7.02 (1.37) 5.07 (1.60) 6.02 (1.55) -1.95 (1.38)

Arousal 3.37 (1.60) 5.67 (1.84) 4.12 (1.93) 2.30 (1.58)

Control Condition

Affect 6.91 (1.62) 6.48 (1.56) 6.83 (1.60) -.43 (1.19)

Arousal 4.30 (2.03) 4.39 (2.17) 3.61 (1.85) .09 (1.98)

Affect levels range from negative to positive, such that higher affect scores are positive. Arousal levels range from calm to aroused, such that higher arousal scores are positive.

68 Table 3

Mixed Design Repeated Measures ANOVA Manipulation Checks-Affect levels

Source Sum of df Mean F p η2 Squares Square Within subjects Time 67.98 2 33.99 46.23 <.001‡ .33 Condition*Time 28.35 2 14.17 19.28 <.001‡ .17 Error 139.68 190 .74 Between subjects

Condition 35.39 1 35.39 6.11 .02 .06 Error 550.584 95 5.80 *p < .05 ‡ p < .001

69 Table 4

Mixed Design Repeated Measures ANOVA Manipulation Checks-Arousal levels

Source Sum of df Mean F p η2 Squares Square Within subjects Time 89.33 2 44.67 33.09 <.001‡ .26 Condition*Time 60.13 2 30.06 22.27 <.001‡ .19 Error 256.46 190 1.35 Between subjects

Condition 5.99 1 5.99 .72 .40 .01 Error 796.37 95 8.38 *p < .05 ‡ p < .001

Table 5

Correlations ® among primary variables

Variable 1 2 3 4 5 6 7 8 1. BMI -- 2. Cognitive Restraint .25* -- 3. Total hours of sleep from .02 -.13 -- past two nights 4. Depressive Symptoms -.04 -.10 -.10 -- 5. Hunger .01 -.18 -.09 .02 -- 6. Mindfulness -.02 -.14 .11 -.42‡ .002 -- 7. Total kilocalories eaten .-.09 -.11 -.13 .03 .44‡ -.10 -- 8. Proportion of M & M servings over total servings .06 .02 -.16 .004 .20 -.08 .41‡ -- eaten

*p < .05 ‡ p < .001

71 Table 6

Mixed Design Repeated Measures ANOVA-Hunger levels

Source Sum of df Mean F p η2 Squares Square Within subjects Time 71.47 2 35.73 26.21 <.001‡ .22 Condition*Time 4.77 2 2.39 1.75 .45 .02 Error 256.32 188 1.36 Between subjects

Condition 3.43 1 3.43 .49 .48 .01 Error 651.64 94 6.93 *p < .05 ‡ p < .001

Table 7 Hypothesis 1: Hierarchical Linear Regression (Primary Analysis)

M & M servings/Total Total Kcal Eaten servings

Predictor β t p β t p Model 1 BMI -2.19 -.83 .41 .004 .53 .60 Hunger 23.81 4.42 <.01 .03 1.78 .08 Sleep -3.34 -.83 .41 -.02 -1.56 .12 Cognitive restraint -.11 -.16 .88 .001 .34 .73 Depressive Symptoms -.27 .22 .83 <.001 .13 .90 Time of experiment 3.73 .85 .39 .02 1.35 .18 Baseline arousal -1.85 -.34 .74 -.004 -.29 .77 Available M & M -.87 -.39 .70 -.02 -2.60 .01 servings Ratio (Grape servings: -193.61 -.46 .65 -.37 -.34 .73 M & M servings) Model 2 BMI -2.13 -.82 .41 .004 .54 .59 Hunger 22.74 4.28 <.01 .02 1.70 .09 Sleep -2.08 -.52 .60 -.02 -1.42 .16 Cognitive restraint -.11 -.16 .88 .001 .34 .73 Depressive Symptoms .52 .44 .66 .001 .20 .84 Time of experiment 5.11 1.18 .24 .02 1.44 .15 Baseline arousal -4.87 -.87 .38 -.01 -.47 .64 Available M & M -.43 -.20 .84 -.01 -2.51 .01 servings Ratio (Grape servings: -137.46 -.33 .74 -.32 -.29 .77 M & M servings) Condition -42.84 -2.14 .03* -.04 -.75 .45 *p < .05 ‡ p < .001

73 Table 8 Hypothesis 1: Linear Regression without covariates

M & M servings/Total Total Kcal Eaten servings

Predictor R β t p R β t p .254 .122 Constant 158.59 11.95 .00 .68 20.41 .00 Condition -51.03 -2.56 .01* -.06 -1.20 .23 *p < .05 ‡ p < .001

Table 9 Hypothesis 1: Hierarchical Linear Regression (Secondary Analysis)

M & M servings/Total Total Kcal Eaten servings

Predictor β t p β t p Model 1 BMI -.95 -.21 .83 .002 .17 .86 Hunger 13.77 1.48 .14 .03 .87 .38 Sleep -13.67 -1.97 .05 -.01 -.45 .65 Cognitive restraint .91 .81 .42 .001 .30 .77 Depressive Symptoms .05 .04 .97 .002 .41 .68 Time of experiment 1.56 .25 .80 .02 1.17 .24 Available M & M -3.21 -.93 .36 -.01 -1.35 .18 servings Ratio (grape servings: -846.02 -1.22 .22 -1.29 -.61 .54 M & M servings) Model 2 BMI -.22 -.05 .96 .01 .85 .40 Hunger 14.91 1.56 .12 .04 1.44 .15 Sleep -13.90 -1.99 .05 -.01 -.63 .53 Cognitive restraint 1.05 .91 .36 .003 .83 .41 Depressive Symptoms .17 .11 .91 .003 .77 .44 Time of experiment .37 .06 .95 .01 .45 .65 Available M & M -3.37 -.96 .34 -.02 -1.66 .10 servings Ratio (grape servings: -779.65 -1.10 .27 -.51 -.26 .79 M & M servings) Change in affect -7.60 -.66 .51 -.09 -2.78 .01* *p < .05 ‡ p < .001

75 Table 10 Hypothesis 1: Linear Regression without covariates (Secondary Analysis)

M & M servings/Total Total Kcal Eaten servings

Predictor R β t p R β t p .004 .269 Constant 107.10 4.42 .00 .52 7.71 .00 Change in affect -.24 -.02 .98 -.05 -1.79 .08 *p < .05 ‡ p < .001

Table 11 Hypothesis 2: Hierarchical Linear Regression

M & M servings/Total Total Kcal Eaten servings

Predictor β t p β t p Model 1 BMI -2.19 -.83 .41 .004 .53 .60 Hunger 23.81 4.42 <.01 .03 1.78 .08 Sleep -3.34 -.83 .41 -.02 -1.56 .12 Cognitive restraint -.11 -.16 .88 .001 .34 .73 Depressive Symptoms .27 .22 .83 <.001 .13 .90 Time of experiment 3.73 .85 .39 .02 1.35 .18 Baseline arousal -1.85 -.34 .74 -.004 -.29 .77 Available M & M -.87 -.39 .70 -.02 -2.60 .01 servings Ratio (grape servings: -193.61 -.46 .65 -.37 -.34 .74 M & M servings) Model 2 BMI -2.25 -.86 .39 .003 .52 .61 Hunger 23.84 4.44 <.01 .03 1.78 .08 Sleep -3.29 -.82 .41 -.02 -1.54 .12 Cognitive restraint -.29 -.40 .69 <.001 .20 .84 Depressive Symptoms -.20 -.16 .88 <.001 -.08 .93 Time of experiment 3.71 .85 .39 .02 1.34 .18 Baseline arousal -3.37 -.60 .55 -.01 -.43 .67 Available M & M -.47 -.21 .83 -.01 -2.46 .01 servings Ratio (grape servings: -93.23 -.22 .83 -.23 -.20 .84 M & M servings) Mindfulness -20.65 -1.15 .25 -.03 -.64 .52 *p < .05 ‡ p < .001

77 Table 12

Hypothesis 2: Linear Regression without covariates

M & M servings/Total Total Kcal Eaten servings

Predictor R β t p R β t p .104 .083 Constant 135.95 13.36 .00 .66 26.18 .00 Mindfulness -16.57 -1.02 .31 .-03 -.81 .42 *p < .05 ‡ p < .001

78 Table 13 Hypothesis 3: Hierarchical Linear Regression

M & M servings/Total Total Kcal Eaten servings

Predictor β t p β t p Model 1

BMI -2.20 -.85 .39 .004 .52 .60

Hunger 22.75 4.30 <.001 .02 1.70 .09 Sleep -2.00 -.50 .61 -.02 -1.41 .16 Cognitive restraint -.31 -.43 .67 <.001 .19 .85 Depressive Symptoms .02 .02 .99 <-.001 -.02 .98 Mindfulness -22.33 -1.27 .20 -.03 -.67 .50 Condition -43.95 -2.20 .03 -.04 -.78 .44 Time of experiment 5.13 1.19 .23 .02 1.44 .15 Baseline arousal -6.59 -1.15 .25 -.01 -.61 .54 Available M & M .01 .01 1.00 -.01 -2.36 .02 servings Ratio (grape servings: M -27.46 -.07 .95 -.16 -.15 .88 & M servings) Model 2

BMI -2.22 -.85 .40 .01 .67 .51 Hunger 22.72 4.26 <.001 .03 1.80 .07 Sleep -1.99 -.50 .62 -.02 -1.45 .15 Cognitive restraint -.31 -.42 .67 <.001 .16 .88 Depressive Symptoms .01 .01 .99 <.001 .14 .89 Mindfulness -22.67 -1.25 .21 -.02 -.33 .74 Condition -43.70 -2.15 .03 -.05 -1.00 .32 Time of experiment 5.15 1.19 .24 .02 1.37 .17 Baseline arousal -6.50 -1.11 .27 -.01 -.87 .39 Available M & M .01 .004 1.00 -.01 -2.37 .02 servings Ratio (grape servings: M -27.13 -.06 .95 -.18 -.16 .87 & M servings (Continued)

79 Table 13: Continued Condition*Mindfulness .37 .08 .94 -.02 -1.40 .16 *p < .05 ‡ p < .001

80 Table 14

Hypothesis 3: Hierarchical Linear Regression without covariates

M & M servings/Total Total Kcal Eaten servings

Predictor R β t p R β t p Model 1 .270 .144 Mindfulness -14.35 -.90 .37 -.03 -.74 .46 Condition -50.03 -2.50 .01 -.06 -1.15 .25 Model 2 .274 .183 Mindfulness -16.67 -1.00 .32 -.02 -.40 .69 Condition -48.62 -2.40 .02 -.07 -1.30 .20 Condition*Mindfulness 2.41 .50 .62 -.01 -1.11 .27 *p < .05 ‡ p < .001

81 Table 15

Post-hoc analysis: Change in positive affect predicting proportion of M & M servings

M & M servings/Total servings

Predictor β t p Model 1 BMI .004 .54 .59 Hunger .02 1.70 .09 Sleep -.02 -1.42 .16 Cognitive restraint .001 .34 .73 Depressive Symptoms .001 .20 .84 Time of experiment .02 1.44 .15 Condition -.04 -.75 .45 Baseline arousal -.01 -.47 .64 Available M & M -.01 -2.51 .01 servings Ratio (grape servings: -.32 -.29 .77 M & M servings) Model 2 BMI .01 1.00 .32 Hunger .03 2.02 .04 Sleep -.02 -1.56 .12 Cognitive restraint .001 .80 .43 Depressive Symptoms .002 .55 .59 Time of experiment .02 1.61 .11 Condition -.12 -2.04 .04 Baseline arousal -.004 -.31 .76 Available M & M -.01 -2.05 .04 servings Ratio (grape servings: .57 .51 .61 M & M servings) Change in affect -.05 -2.60 .01* *p < .05 ‡ p < .001

82 Table 16

Post-hoc analysis: Mindfulness x Affective Response Hierarchical Linear Regression

M & M servings/Total servings

Predictor β t p Model 1 BMI .01 .87 .39 Hunger .04 1.45 .15 Sleep -.01 -.62 .53 Cognitive restraint .003 .89 .37 Depressive Symptoms .004 .89 .38 Time of experiment .01 .47 .64 Change in affect -.09 -2.72 .01 Mindfulness .03 .51 .61 Available M & M -.02 -1.72 .09 servings Ratio (grape servings: -.91 -.43 .67 M & M servings) Model 2 BMI .01 .74 .46 Hunger .04 1.52 .13 Sleep -.02 -.79 .43 Cognitive restraint .003 .85 .40 Depressive Symptoms .004 .86 .39 Time of experiment .01 .32 .75 Change in affect -.10 -2.66 .01 Mindfulness .03 .39 .70 Available M & M -.02 -1.55 .12 servings Ratio (grape servings: -.59 -.27 .79 M & M servings) Change in .002 .56 .58 affect*Mindfulness (Continued)

83 Table 16: Continued *p < .05 ‡ p < .001

84 Table 17

Post-hoc analysis: Hunger x Condition Hierarchical Linear Regression

Total kcal consumption

Predictor β t p Model 1 BMI -2.13 -.82 .41 Hunger 22.74 4.28 <.01 Sleep -2.08 -.52 .60 Cognitive restraint -.11 -.16 .88 Depressive Symptoms .52 .44 .66 Time of experiment 5.11 1.18 .24 Baseline arousal -4.87 -.87 .38 Condition -42.84 -2.14 .03 Available M & M -.43 -.20 .84 servings Ratio (Grape servings: -137.46 -.33 .74 M & M servings) Model 2 BMI -1.20 -.45 .66 Hunger 28.55 4.09 <.01 Sleep -2.58 -.65 .52 Cognitive restraint -.25 -.36 .72 Depressive Symptoms .41 .34 .74 Time of experiment 6.05 1.38 .17 Baseline arousal -4.27 -.77 .44 Condition 31.44 .52 .61 Available M & M -.81 -.37 .71 servings Ratio (Grape servings: -129.09 -.31 .75 M & M servings) Condition* Hunger -14.27 -1.29 .20 *p < .05 ‡ p < .001

Appendix B: Figures

86 Figure 1

Figure 1. Caloric intake ranged from 4.56 to 464.76, with a positive skew of 1.032.

87 Figure 2

Figure 2. Proportion of M & M servings eaten ranged from 0 to 1, with a negative skew of -.98.

88 Figure 3

* ‡

affect Mean

Figure 3. Affect level at time 1 (pre-TSST/control), time 2 (post-TSST/control and before the taste test), and time 3 (post-taste test). There was a significant time x condition interaction on affect levels, F(2, 190) = 19.28, p < .001. At time 1, there were no significant differences between groups. However, there were significant differences between groups at time 2 and time 3. *p < .05 ‡ p < .001

89 Figure 4

Figure 4. Arousal level at time 1 (pre-TSST/control), time 2 (post-TSST/control and before the taste test), and time 3 (post-taste test). There was a significant time x condition interaction on arousal levels, F(2, 190) = 22.27, p < .001. Arousal levels differed between group at time 1 and time 2. *p < .05 ‡ p < .001

90 Figure 5

Figure 5. Hunger levels at time 1 (pre-TSST/control), time 2 (post-TSST/control and before the taste test), and time 3 (post-taste test). There was no significant time x condition interaction, F(2, 188) = 1.75, p = .18.

*p < .05 ‡ p < .001

91 Figure 6

Figure 6. Change in positive affect predicting proportion of M & M servings over total servings eaten. Women with greater affective response to the stressor ate a higher proportion of M & M servings than women with lower affective response to the stressor, β = -.09, t(42) = -2.78, p = .01. *p < .05 ‡ p < .001

Appendix C: Experiment Protocol

93 Experiment Sheet for TSST

Subject #: ______

Date: ______

Start time of preparing for the speech: ______

End time for preparing for the speech: ______

Start time of speech: ______

End time of speech: ______

Start time of arithmetic task: ______

End time of arithmetic task: ______

Weight (kg) of M & Ms before: ______

Weight (kg) of M & Ms after: ______

Weight (kg) of grapes before: ______

Weight (kg) of grapes after: ______

Start time of taste test: ______

End time of taste test: ______

Behavioral Notes:

94 Experimenter Script for Introduction to Trier Social Stress Test

ASSISTANT RESTAURANT MANAGER

To begin the Trier Social Stress Test portion of the morning, the experimenter will explain to the participant what is going to happen:

“We’re now going to begin the stressor part of today’s study. The stressor is designed to be mildly disruptive. It is an important aspect to the study because we are interested in examining how stress might affect your taste perceptions.”

The video camera is set up and committee members will come in after the participant has already been consented. The experimenter will have the participant sit in the chair in front of the committee, and will explain the task to the participant as follows:

“We’re now going to ask you to deliver a 5 minute speech for a job application to this committee. You will be given 10 minutes to prepare for this speech before you present it to the committee. We would like you to imagine you have applied for a job as an assistant restaurant manager. Is that a position you’ve held in the past? [IF YES, OK THEN WE WOULD LIKE YOU TO IMAGINE YOU HAVE APPLIED FOR A JOB AS A ______…] IF NO, Ok, well imagine these committee members are part of the selection committee who will be evaluating you for the position you are applying for. They will periodically rate how likeable, interesting, and friendly they were, and how likely it is that you would be liked and included by others, as opposed to disliked and excluded, and whether or not people would invite you to join social activities like parties or group outings, and whether other people would include you or exclude you when they make decisions about friends, roommates, clubs, or social media like Facebook.

You will have five minutes to present why you are the best candidate for this position. We ask that you focus on explaining how your own personality characteristics and personal background experiences make you the best suited candidate for this position.

Please note that your 5 minute performance will be recorded by this video camera and microphone for subsequent voice frequency analysis to reveal any paraverbal

95 signs of stress. The camera recording will also be used for later behavioral analysis. The members of the committee are trained in behavioral analysis and will take notes during your speech. Following your 5 minute speech, the committee will give you instructions for performing a separate task in front of them; that task will also take 5 minutes.

We will leave the room and give you 10 minutes to prepare for your speech. We will provide you with a job description from which you can base your speech. You may take notes or make an outline during these 10 minutes, but you will not be able to bring those notes back into the room with you. It is important to remember to focus on explaining what personal characteristics make you best suited for this position. Also, please prepare enough in order to be able to speak for the full five minutes. Do you have any questions regarding the speech?”

Answer any questions the participant may have concerning the tasks.

After 10 minutes, the experimenter will return. At this point, the experimenter should talk with the subject briefly to solidify with the subject that he/she understands the nature of the task. If the subject is unsure, the experimenter can discuss past job experiences or fields of study with the subject in order to identify material relevant to the job for which they have been asked to apply. The experimenter should also give the subject the half- sheet speech reminder, which reviews the guidelines for the speech and provides a job description from which they can base their speech.

At the end of the preparation period, the committee will return. Before leaving the room, the experimenter should tell the subject to begin her speech.

96 Committee Protocol and Script for Trier Social Stress Test

ASSISTANT RESTAURANT MANAGER

Committee members should put on the white lab coats provided for them. The experimenter will have already set up the equipment in the Trier room. The committee members are responsible for double checking the set up. The committee members should be seated behind a desk in 2 chairs. The microphone should be placed in front of the chair where the subject will be seated. Committee members also need a copy of the protocol, script, math task sheets, packet, and stopwatch (the experimenter will give these to you).

When the subject is ready, the experimenter will bring the committee into the room and introduce the speech task. During this time, both committee members should not talk with the subject. If the subject greets the committee members, the committee chair can respond to the greeting. All questions asked by the subject should be answered by the experimenter. After the speech task has been explained, the experimenter and committee members will leave, and the subject will have 10 minutes to prepare for the speech.

At the end of the 10 minute preparation time, the experimenter will bring the committee back and tell the subject they can begin their speech. The experimenter will then leave the room.

The second committee member will hit “start” on the stopwatch once the subject begins speaking, and will also record the start time in the packet. While the subject is giving the speech, committee members should seek eye contact and give the subject their undivided attention. Committee members, however, should avoid providing any kind of feedback (such as head nodding, smiling, laughing, etc.). Committee members should occasionally jot down “notes” during the speech. During the speech, committee members should remain quiet as long as the participant continues to speak fluently. Only the committee chair should address the subject directly. Should the subject pause for more than ten seconds, the committee chair should say:

“You still have time, please continue.”

97 Should the subject continue to have difficulty speaking or continuing, the committee chair may present the following questions to the subject:

“What characteristics do you possess that make you the most qualified person for this position?” “What qualifies you in particular for this position?” “Please describe what kinds of relevant experiences you have had in past jobs that make you well suited for this position.” “What experiences or personal characteristics make you qualified to manage employees?” “What characteristics qualify you for being able to manage a restaurant’s inventory and payroll?” “What qualifies you to work in the restaurant or food service industry?” ”What about your studies identifies a special aptitude and motivation for this position?” “Where else did you apply? Why?” “What would you do if your application here would not succeed?”

Other probes:

“What are your personal strengths?” “What are your major shortcomings?” “Do you have enemies?…why?” “What do you think about teamwork?” “What do your boss/family/colleagues think about you? Why?”

The point of these questions is not to embarrass the participant or be mean to him/her. The questions should serve to deepen this presentation and to receive information about specific qualities of the applicant—that’s all.

The second committee member should glance at the stop watch occasionally to keep track of time, and notify the committee chair when the time is up, by saying “time”:

Committee chair: “Thank you very much, that should be enough for now.”

The chair will immediately go on to explain the second part of the protocol:

98 Committee chair: “We now want to ask you to work on a second task. This task is different than the speech task you just completed. This task involves mental arithmetic and will last for a total of five minutes. To start, I will give you a number and an interval. You will start with the number I give you, and begin subtracting from that number with the interval I give you. So, for example, I might say, “starting with the number 100, please subtract by 2s”, at which point you’d begin counting backwards from 100 by 2s (100, 98, 96, 94, and so on).

You’ll do this for one minute and I will time you. At the end of the minute, I’ll stop you and give you a new number and interval to subtract by. Again, we’ll do this for a total of 5 minutes, changing the number and interval you’ll subtract by at the end of each minute. If you should make a mistake, I will say “error”, give you the correct number, and ask that you start counting with the correct number. Please try to do this task as accurately and as quickly as you possibly can. Do you have any questions?”

The committee chair will turn to the math sheets and begin the task. The second committee member will be responsible for keeping track of time, and noting the start time of the math task in the packet:

Committee chair: “Okay, starting with the number 297, please subtract by 3’s.”

The second committee member will hit “start” on the stopwatch when the subject begins. The committee chair will be responsible for keeping track of the subject’s responses, and notifying the subject when he/she has an incorrect response by saying “error”, giving the subject the correct response, and making sure the subject begins counting again.

The second committee member will notify the chair when five minutes is up by saying “time”. At the end of the 5 minute period, the second committee member should record the exact time the math task stops in the staff packet. Both committee members should leave the room at this point with their notes, and notify the experimenter they are finished. Committee members should leave the packet, math tally sheets, and stopwatch in the room.

99 Participant’s Sheet of Instructions

Advertisement for and reminders about the speech you are about to present:

WANTED: Assistant Restaurant Manager. Responsibilities include ensuring the restaurant operates effectively and efficiently within the company’s fiscal and operational guidelines; Manager should make certain that all menu items are made according to recipe and all established standards of food safety and sanitation are maintained; Be able to staff restaurant with quality employees who value guest service and are committed to high standards; take the lead in the proper training and supervision of restaurant staff; Must be attentive to guests feedback and respond to criticisms in a constructive and positive manner.

*Your speech should last a total of five minutes.

*You have a total of 10 minutes now to prepare for your speech. Feel free to make notes, write out an outline, or practice talking aloud if you wish. You will not be permitted to take notes in with you when you give the speech.

* You should focus on what personal characteristics make you qualified for this position as well as any past personal job experiences.

*Your main purpose is to convince these panel members why you are the perfect applicant for this vacant position and why you believe you will be an asset to their company.

100

TASK SHEETS

Put a check mark next to each correct response and an “X” next to each incorrect response (don’t forget to correct the participant). Use “# correct” column to figure out how many correct responses the subject had by subtracting the number of “Xs” from the “# correct” number that corresponds to the last check mark (correct response). “Okay, starting with the number 1022, please subtract by 13's.”

Sub # # corre ct

1022 1 762 21 502 41

1009 2 749 22 489 42

996 3 736 23 476 43

983 4 723 24 463 44 970 5 710 25 450 45

957 6 697 26 437 46

944 7 684 27 424 47 931 8 671 28 411 48

918 9 658 29 398 49

905 10 645 30 385 50 892 11 632 31 372 51

879 12 619 32 359 52

866 13 606 33 346 53

853 14 593 34 333 54 840 15 580 35 320 55

827 16 567 36 307 56

814 17 554 37 294 57

801 18 541 38 281 58

788 19 528 39 268 59

775 20 515 40 101255 60 Put a check mark next to each correct response and an “X” next to each incorrect response (don’t forget to correct the participant). Use “# correct” column to figure out how many correct responses the subject had by subtracting the number of “Xs” from the “# correct” number that corresponds to the last check mark (correct response). “Okay, starting with the number 1354, please subtract by 15's.”

Sub# # corr ect

1354 1 1054 21 754 41

1339 2 1039 22 739 42

1324 3 1024 23 724 43 1309 4 1009 24 709 44 5 25 45 1294 994 694

1279 6 979 26 679 46 1264 7 964 27 664 47

1249 8 949 28 649 48

1234 9 934 29 634 49 1219 10 919 30 619 50

1204 11 904 31 604 51 1189 12 889 32 589 52

1174 13 874 33 574 53

1159 14 859 34 559 54 1144 15 844 35 544 55

1129 16 829 36 529 56 1114 17 814 37 514 57

1099 18 799 38 499 58

1084 19 784 39 484 59 1069 20 769 40 469 60

102 Put a check mark next to each correct response and an “X” next to each incorrect response (don’t forget to correct the participant). Use “# correct” column to figure out how many correct responses the subject had by subtracting the number of “Xs” from the “# correct” number that corresponds to the last check mark (correct response). “Okay, starting with the number 2041, please subtract by 19's.”

Sub# # corr ect

2041 1 1661 21 1281 41

2022 2 1642 22 1262 42

2003 3 1623 23 1243 43 1984 4 1604 24 1224 44 5 25 45 1965 1585 1205

1946 6 1566 26 1186 46 1927 7 1547 27 1167 47

1908 8 1528 28 1148 48

1889 9 1509 29 1129 49 1870 10 1490 30 1110 50

1851 11 1471 31 1091 51

1832 12 1452 32 1072 52

1813 13 1433 33 1053 53

1794 14 1414 34 1034 54 1775 15 1395 35 1015 55

1756 16 1376 36 996 56

1737 17 1357 37 977 57

1718 18 1338 38 958 58

1699 19 1319 39 939 59 1680 20 1300 40 920 60

103 Put a check mark next to each correct response and an “X” next to each incorrect response (don’t forget to correct the participant). Use “# correct” column to figure out how many correct responses the subject had by subtracting the number of “Xs” from the “# correct” number that corresponds to the last check mark (correct response). “Okay, starting with the number 2537, please subtract by 13's.”

Sub# # corr ect

2537 1 2277 21 2017 41

2524 2 2264 22 2004 42

2511 3 2251 23 1991 43 2498 4 2238 24 1978 44 5 25 45 2485 2225 1965

2472 6 2212 26 1952 46 2459 7 2199 27 1939 47

2446 8 2186 28 1926 48

2433 9 2173 29 1913 49 2420 10 2160 30 1900 50

2407 11 2147 31 1887 51

2394 12 2134 32 1874 52

2381 13 2121 33 1861 53 14 34 54 2368 2108 1848 2355 15 2095 35 1835 55

2342 16 2082 36 1822 56

2329 17 2069 37 1809 57

2316 18 2056 38 1796 58

2303 19 2043 39 1783 59

2290 20 2030 40 1770 60

104 Put a check mark next to each correct response and an “X” next to each incorrect response (don’t forget to correct the participant). Use “# correct” column to figure out how many correct responses the subject had by subtracting the number of “Xs” from the “# correct” number that corresponds to the last check mark (correct response). “Okay, starting with the number 1479, please subtract by 16's.”

Sub# # corr ect

1479 1 1159 21 839 41

1463 2 1143 22 823 42

1447 3 1127 23 807 43 1431 4 1111 24 791 44 5 25 45 1415 1095 775

1399 6 1079 26 759 46 1383 7 1063 27 743 47

1367 8 1047 28 727 48

1351 9 1031 29 711 49 1335 10 1015 30 695 50

1319 11 999 31 679 51 1303 12 983 32 663 52

1287 13 967 33 647 53

1271 14 951 34 631 54 1255 15 935 35 615 55

1239 16 919 36 599 56 1223 17 903 37 583 57

1207 18 887 38 567 58

1191 19 871 39 551 59 1175 20 855 40 535 60

105 “This task is complete. Now, we’ll get the experimenter.”

106 Experiment Sheet for Control

Subject #: ______

Date: ______

Start time of reading silently: ______

End time for reading silently: ______

Start time of reading aloud: ______

End time of reading aloud: ______

Start time of arithmetic task: ______

End time of arithmetic task: ______

Weight (kg) of M & Ms before: ______

Weight (kg) of M & Ms after: ______

Weight (kg) of grapes before: ______

Weight (kg) of grapes after: ______

Start time of taste test: ______

End time of taste test: ______

107 Experimenter Script for Introduction to Trier Social Stress Test Control

“Please read this magazine for ten minutes. After ten minutes are complete, I will return and ask you to start to read the magazine aloud for five minutes.”

Experimenter leaves the room and then returns in ten minutes.

“Now I will ask you to stand up and read aloud from this magazine for five minutes. You will record yourself while reading, but this recording will not be used for anything. It is simply to ensure that you are reading aloud.”

Experiment leaves the room and then returns in five minutes.

“We now want to ask you to work on a second task. This task is different from the speech task you just completed. This task involves mental arithmetic and will last for a total of five minutes. To start, I will give you a number and an interval. You will start with the number I give you, and begin counting up from that number. So for example, if I ask you to start with 0 and count up by 3, you would say 3, 6, 9, and so on.

You’ll do this five times with a new number for each minute. Do not worry about making mistakes. If you notice that you made a mistake, feel free to go back and correct it. Do you have any questions?”

Experimenter starts the stopwatch and stops the participant after each minute, five times.

108 TASK SHEETS

“Okay, starting with the number 0, please add by 15's.”

Sub # # corre ct

0 1 300 21 600 41

15 2 315 22 615 42

30 3 330 23 630 43

45 4 345 24 645 44

60 5 360 25 660 45

75 6 375 26 675 46

90 7 390 27 690 47 105 8 405 28 705 48

120 9 420 29 720 49

135 10 435 30 735 50 150 11 450 31 750 51

165 12 465 32 765 52 180 13 480 33 780 53

195 14 495 34 795 54

210 15 510 35 810 55 225 16 525 36 825 56

240 17 540 37 840 57 255 18 555 38 855 58

270 19 570 39 870 59

285 20 585 40 885 60

109

“Okay, starting with the number 0, please add by 5's.”

Sub # # corre ct

0 1 100 21 200 41

5 2 105 22 205 42

10 3 110 23 210 43 15 4 115 24 215 44 5 25 45 20 120 220

25 6 125 26 225 46

30 7 130 27 230 47

35 8 135 28 235 48

40 9 140 29 240 49 45 10 145 30 245 50

50 11 150 31 250 51

55 12 155 32 255 52

60 13 160 33 260 53

65 14 165 34 265 54 70 15 170 35 270 55

75 16 175 36 275 56

80 17 180 37 280 57

85 18 185 38 285 58

90 19 190 39 290 59

95 20 195 40 295 60

110

“Okay, starting with the number 0, please add by 10's.”

Sub # # corre ct

0 1 200 21 400 41

10 2 210 22 410 42

20 3 220 23 420 43 30 4 230 24 430 44 5 25 45 40 240 440

50 6 250 26 450 46

60 7 260 27 460 47

70 8 270 28 470 48

80 9 280 29 480 49 90 10 290 30 490 50

100 11 300 31 500 51

110 12 310 32 510 52

120 13 320 33 520 53

130 14 330 34 530 54

140 15 340 35 540 55 150 16 350 36 550 56

160 17 360 37 560 57

170 18 370 38 570 58

180 19 380 39 580 59

190 20 390 40 590 60

111

“Okay, starting with the number 0, please add by 20's.”

Sub # # corre ct

0 1 400 21 800 41

20 2 420 22 820 42

40 3 440 23 840 43

60 4 460 24 860 44

5 25 45 80 480 880

100 6 500 26 900 46

120 7 520 27 920 47

140 8 540 28 940 48

160 9 560 29 960 49

180 10 580 30 980 50

200 11 600 31 1000 51

220 12 620 32 1020 52

240 13 640 33 1040 53

260 14 660 34 1060 54 280 15 680 35 1080 55

300 16 700 36 1100 56

320 17 720 37 1120 57

340 18 740 38 1140 58

360 19 760 39 1160 59

380 20 780 40 1180 60

112 “Okay, starting with the number 0, please add by 25's.”

Sub # # corre ct

0 1 500 21 1000 41

25 2 525 22 1025 42

50 3 550 23 1050 43

75 4 575 24 1075 44 5 25 45 100 600 1100

125 6 625 26 1125 46 150 7 650 27 1150 47

175 8 675 28 1175 48

200 9 700 29 1200 49 225 10 725 30 1225 50

250 11 750 31 1250 51 275 12 775 32 1275 52

300 13 800 33 1300 53

325 14 825 34 1325 54 350 15 850 35 1350 55

375 16 875 36 1375 56 400 17 900 37 1400 57

425 18 925 38 1425 58

450 19 950 39 1450 59 475 20 975 40 1475 60

113

Appendix D: Self-Report Questionnaires

114 DEMOGRAPHIC INFORMATION

Instructions: Please answer the following questions about yourself.

1.) What is your age? ______

2.) Which one of the following groups do you think best represents your race?  White  Black or African American  Asian  Hispanic or Latino  Native Hawaiian/Pacific Islander  Native American  Other: ______ Don’t know/Not sure

3.) What is your ethnicity?  Hispanic/Latino/Latina  Non-Hispanic/Latino/Latina

4.) What is your academic year?  Freshman  Sophomore  Junior  Senior  Graduate/professional student  Other ______

5.) What is your height? ______

6.) What is your weight? ______

7.) How many hours of sleep did you get last night? ______

8.) How many hours of sleep did you get two nights ago? ______

115

9.) Are you on a special diet?  Yes

Please explain ______

 No

12) Do you have any medical diagnoses (i.e. asthma, Chron’s Disease, etc.)?  Yes Please explain ______ No

13) Do you currently smoke or have you ever smoked regularly in the past?  Yes, current smoker, frequency ______(packs per day)

 Yes, past smoker, quit in ______(month/year)

 No, never smoked

14) Have you ever been diagnosed with an eating disorder (anorexia nervosa, bulimia nervosa, binge-eating disorder, etc.)?  Yes

Please specify diagnosis and date______

 No

116 Mindful Attention and Awareness Scale

Day-to-Day Experiences

Instructions: Below is a collection of statements about your everyday experience. Using the 1-6 scale below, please indicate how frequently or infrequently you currently have each experience. Please answer according to what really reflects your experience rather than what you think your experience should be. Please treat each item separately from every other item.

1 2 3 4 5 6 Almost Very Somewhat Somewhat Very Almost Always Frequently Frequently Infrequently Infrequently Never

I could be experiencing some emotion and not be 1 2 3 4 5 6 conscious of it until some time later.

I break or spill things because of carelessness, not 1 2 3 4 5 6 paying attention, or thinking of something else.

I find it difficult to stay focused on what’s happening in 1 2 3 4 5 6 the present.

I tend to walk quickly to get where I’m going without 1 2 3 4 5 6 paying attention to what I experience along the way.

I tend not to notice feelings of physical tension or 1 2 3 4 5 6 discomfort until they really grab my attention.

I forget a person’s name almost as soon as I’ve been told 1 2 3 4 5 6 it for the first time.

It seems I am “running on automatic,” without much 1 2 3 4 5 6 awareness of what I’m doing

I rush through activities without being really attentive to 1 2 3 4 5 6 them.

I get so focused on the goal I want to achieve that I lose 1 2 3 4 5 6 touch with what I’m doing right now to get there.

I do jobs or tasks automatically, without being aware of 1 2 3 4 5 6 what I’m doing.

117 I find myself listening to someone with one ear, doing 1 2 3 4 5 6 something else at the same time.

I drive places on “automatic pilot” and then wonder why 1 2 3 4 5 6 I went there.

I find myself preoccupied with the future or the past. 1 2 3 4 5 6

I find myself doing things without paying attention. 1 2 3 4 5 6

I snack without being aware that I’m eating. 1 2 3 4 5 6

118 Center for Epidemiological Studies-Depression Scale (CES-D)

119 Self-Assessment Manikin

For each row, please click the circle under the number that best corresponds to you currently feel.

1. sad, unsatisfied, happy, satisfied, hopeless, depressed hopeful, glad

O O O O O O O O O

2. relaxed, peaceful, anxious, keyed up, calm, bored nervous, worried

O O O O O O O O O

120 Hunger Scale

People’s hunger, desire to eat, and responses to meals will change across a day; although feelings like hunger and desire to eat are often linked, sometimes they are not, you can feel like eating when you are not hungry, or you may not feel like eating even though you are hungry. We are interested in your feelings RIGHT NOW.

1. How hungry are Not at Extremely you? all hungry hungry 1 2 3 4 5 6 7 8 9 0

2. How full do you Not at Extremely feel? all full full 0 1 2 3 4 5 6 7 8 9

3. How strong is your No Extremely desire to eat? desire strong desire 1 2 3 4 5 6 7 8 9 0

4. How satiated do you Not at Extremely feel with the amount all satiated you have eaten satiated 1 2 3 4 5 6 7 8 9 (feeling of 0 satisfaction)?

121 Taste Test Scale-M & Ms

Instructions: We are interested in your ratings of the food you just ate. If you ate M & Ms, please answer the following questions.

1. How salty was the candy?