PURPOSE: \u00a0This study investigated the prevalence of disordered eating behaviors among male high school cross country runners.\u00a0 The study identified behaviors and feelings about being an athlete, and determined relationships between motivations to exercise and disordered eating behaviors.\u00a0 METHODS:\u00a0 Sixty-eight male high school cross country runners from 12 high schools in one urban school district completed three questionnaire packets on one occasion pre-season.\u00a0 The EAT-26 questionnaire was used to determine prevalence of disordered eating.\u00a0 The ATHLETE questionnaire was used to determine psychological factors for relationships with disordered eating.\u00a0 The EMI-2 was used to determine motivations to exercise and the relationship to disordered eating.\u00a0 EAT-26 scores and data from the EMI-2 and ATHLETE questionnaires were analyzed via a Pearson Correlation Coefficient.\u00a0 RESULTS:\u00a0 A modest positive relationship existed between exercising for disordered eating behaviors versus exercising for weight management (r <\/em>= 0.31: p <\/em>< 0.05), the Your Body in Sports subscale (which measured drive for thinness and performance) (r<\/em> = 0.36: p<\/em> < 0.05), and the Feelings about Performance subscale (or Performance Perfectionism) (r<\/em> = 0.26: p<\/em> < 0.05).\u00a0 CONCLUSIONS:\u00a0 Risk factors associated with eating disorders exist in high school male cross country runners.\u00a0 Underreporting and lack of recognition of disordered eating may affect prevalence rates.\u00a0 Recommendations include a longitudinal study of male high school runners across the school year to determine relationships with the timing of questionnaire administration.\u00a0 APPLICATIONS IN SPORT:\u00a0 Disordered eating behaviors should be acknowledged as more than a \u201cfemale only\u201d issue.\u00a0 Parents, teachers, coaches, and athletic trainers may be better able to understand and help male athletes with disordered eating behaviors or an active eating disorder.<\/p>\n <\/p>\n INTRODUCTION<\/strong><\/p>\n According to the National Association of Anorexia Nervosa and Associated Disorders (2010), \u201cup to twenty-four million people of all ages and genders suffer from an eating disorder (anorexia, bulimia and binge eating disorder) in the U.S.\u201d (p. 1).\u00a0 Adolescents and young adults are a high-risk group (1, 2).\u00a0 Some researchers have suggested that the percentages of eating disorders in athletes may be greater versus non-athletes (31).\u00a0 Further, the research suggests that athletes in sports such as distance running or sports that require thinness are more at risk for eating disorders (10, 32, 36), while others suggest that this may vary by gender (19, 22).<\/p>\n A number of studies have focused on the prevalence of eating disorders among athletes (13, 31, 35).\u00a0 Gender, race, sports that require a thin or lean body type, competition level and age, performance pressure, social pressure, and personality characteristics are related to disordered eating in athletes (7, 13, 14).\u00a0 The research examining the relationship between the risk factors for eating disorders and athletes in general is equivocal (13, 18, 31).\u00a0 Some studies have determined factors that may provide a greater risk of disordered eating among athletes, while other studies have determined that some factors are not predictive of greater risk in athletes.\u00a0 Regardless of which risk factors are related to eating disorders in athletes, the prevalence of eating disorders in female athletes is unequivocal (13, 21, 32) .<\/p>\n The prevalence of eating disorders in male athletes is unclear.\u00a0 Eating disorders in male athletes may be more prevalent than previously thought, with the sport environment actually increasing the risk (10, 13, 30).\u00a0 The existence of eating disorders among male athletes may be more prevalent in aesthetic sports such as cross country and marathon running, which are similar to the categories for female athletes (3). \u00a0In general, research suggests that eating disorders are a rapidly growing phenomenon among male athletes.\u00a0 Male risk factors for eating disorders may be different versus females, and the natural course of eating disorders may differ between men and women (4, 8, 38).\u00a0 Patel et al. (28) noted that eating disorders in male athletes are relatively uncommon and the sports where eating disorders exist are where control behaviors are prominent.\u00a0 Female athletes are more at risk than males (22, 28, 31).\u00a0 In summary, there is a paucity of and conflicting research available on the prevalence of eating disorders and symptomatology in male athletes.<\/p>\n Purpose<\/em><\/p>\n The purpose of this study was to investigate the prevalence of disordered eating behaviors in male high school cross country runners, identify risk factors, and to relate the motivations to exercise with responses from the Eating Attitudes Test-26 (EAT-26), the ATHLETE questionnaire, and the Exercise Motivations Inventory-2 (EMI-2).<\/p>\n METHODS<\/strong><\/p>\n Participants<\/em><\/p>\n \u00a0<\/em>The runners were selected from 12 of the thirty-two public high schools in the local school district sponsoring sports teams.\u00a0 The school district is located in the southwestern part of the United States and is comprised of 49 public high schools considered a large urban school system.\u00a0 Some of the public schools within the school district did not sponsor athletic programs.\u00a0 Overall, 68 high school male cross country runners completed the EAT-26, EMI-2, and the ATHLETE questionnaires.\u00a0 Of the 68 participants, 48 (70.6%) were White, while only 2 (2.9%) were African-American.<\/p>\n All participants were current members of a high school cross-country team.\u00a0 The participants were in grades 9-12 and between the ages of 14-18.\u00a0 The M<\/em>age<\/sub> was 15.9 with a SD<\/em> of 1.0.\u00a0 The most common ethnicity was White (70.6%), followed by Asian-American and Pacific Islander (11.8%), 2 or more races (8.8%), Hispanic and Latino (5.9%), and African-American (2.9%).\u00a0 Table 1 shows the demographic information.<\/p>\n Instrumentation <\/em><\/p>\n \u00a0<\/em>Questionnaires were used to gather demographic and health history information, feelings and behaviors about being an athlete, prevalence and symptoms of disordered eating behaviors and eating attitudes, and motivations for exercise.\u00a0 The questionnaires included the EAT\u201326 (9), ATHLETE Questionnaire, and Exercise Motivation Inventory\u20132 (EMI\u20132).<\/p>\n Several self-report attitudes toward eating questionnaires assess eating disorder prevalence and symptoms in clinical and nonclinical populations.\u00a0 The most common measure and most often used among athletic populations is the EAT-26 (8, 13, 22, 23, 32).\u00a0 The EAT\u201326 assesses the likelihood that an athlete would be susceptible to disordered eating.\u00a0 The questionnaire uses a 6-point Likert scale ranging from \u201cnever\u201d to \u201calways\u201d.\u00a0 The items marked \u201cnever\u201d, \u201crarely\u201d, or \u201csometimes\u201d are scored 0, \u201coften\u201d is scored 1, \u201cusually\u201d is scored 2, and \u201calways\u201d scored 3.\u00a0 The sum of the points determines the likelihood of disordered eating.\u00a0 A cut-off score of 20 indicates the athlete could be at risk for disordered eating (the higher the score, the greater the risk of disordered eating).\u00a0 Despite the limitations and gender biases, the Eating Attitudes Test is one of the most widely used tools showing merit in diagnosing eating disorders among men (37).<\/p>\n A more recently developed measure is the ATHLETE questionnaire, designed to assess the psychological predictors of disordered eating in athletics.\u00a0 The ATHLETE questionnaire is useful in studying the etiology of disordered eating in athletes (15).\u00a0 The ATHLETE questionnaire is composed of 40 items in a 5-point Likert Scale divided among subscales.\u00a0 The subscales include Feelings about Being an Athlete (Athlete Identity), Your Body and Sports (Drive for Thinness and Performance), Feelings about Performance (Performance Perfectionism), Support from Your Coach and Teammates (Team Trust), Feelings about Your Body (Social Pressure on Body Shape), and Feelings about Eating (Social Pressure on Eating).\u00a0 All subscales were used in the present study.\u00a0 The values assigned range from \u201cStrongly Disagree\u201d = 1 to \u201cStrongly Agree\u201d = 5.\u00a0 Boldface items were reversed scored, from \u201cStrongly Disagree\u201d = 5 to \u201cStrongly Agree\u201d = 1.\u00a0 A score for each factor is determined by the sum of the values and divided by the number of items per factor. \u00a0The scoring of each subscale reflects higher scores with a greater degree of the construct being assessed (15).<\/p>\n The Exercise Motivations Inventory\u20132 (EMI\u20132) is a 51-item questionnaire developed concerning the reasons people give for exercising or reasons people might begin exercising.<\/p>\n The EMI-2 was developed as a means of assessing participation motives in order to examine such issues as the influence of motives on exercise participation, how such motives might influence the choice of activities undertaken, how affective responses to exercising may be influenced by reasons for exercising and how involvement in physical activity might have a reciprocal influence on participation motives(20).<\/p>\n Values assigned to the Likert scales include \u201cNot true at all for me\u201d = 0 to \u201cVery true for me\u201d = 5.\u00a0 The score for the questionnaire is calculated by totaling the score for each subscale and dividing by the number of items in each subscale.\u00a0 Stress Management, Revitalization, Enjoyment, Challenge, Social Recognition, Affiliation, Competition, Health Pressures, Ill-Health Avoidance, Positive Health, Weight Management, Appearance, Strength and Endurance, and Nimbleness comprise the 14 subscales of the EMI-2 (20).\u00a0 The weight management and appearance subscales were used in the present study.\u00a0 Sample items associated with the weight management and appearance subscales include \u201cBecause exercise helps me to burn calories\u201d and \u201cTo have a good body\u201d, respectively(20).<\/p>\n Procedures<\/em><\/p>\n A Notification of Action Research Project was submitted to the school district in order to obtain permission to conduct the study in the schools.\u00a0 Southern Utah University Institutional Review Board (IRB) certification and consent was obtained in order to begin collection of data.\u00a0 After permission was received from the school district and the IRB, contact with the athletes was made through the administration and coaching staff of high schools in the local area.\u00a0 Each principal and coach was provided information on the purpose of the study and the instrumentation to be administered.\u00a0 A consent form and informational letter detailing the purpose of the study was sent home with each athlete in order to obtain permission from parents or guardians to use the data from the questionnaires in this study.\u00a0 Since the participants were minors, informed consent was obtained from parents and assent forms were collected from the participants prior to gathering data.<\/p>\n Full instructions were provided on the first page of the questionnaire booklet and any further questions were addressed prior to assessment.\u00a0 The questionnaire packets were distributed by the coach and collected by the coach.\u00a0 The consent forms and completed questionnaires were sealed in separate envelopes.\u00a0 The study required approximately 20 to 30 minutes to complete.<\/p>\n Statistical Analysis<\/em><\/p>\n The Pearson correlation coefficients were determined between the intra-individual characteristics and eating disorders as measured on the ATHLETE and EMI\u20132 with the overall score on the EAT-26.\u00a0 A p-<\/em>value less than 0.05 was considered significant and the SPSS 19 (PASW Statistics 19) computer program was used for statistical analysis.\u00a0 The \u201cYour Body and Sports\u201d, \u201cFeelings About Eating\u201d, \u201cFeelings About Your Body\u201d,\u00a0 \u201cFeelings About Performance\u201d, \u201cSupport From Teammates\u201d, and \u201cFeelings About Being An Athlete\u201d subscales of the ATHLETE questionnaire were used.\u00a0 The EMI\u20132 subscales used were \u201cAppearance\u201d and \u201cWeight Management\u201d.<\/p>\n Athletes who scored a 14 or higher were included in the disordered eating group.\u00a0 A score of 14 was selected because this score is one standard deviation above the mean, according to population norms (M<\/em> = 6.97; SD<\/em> = 6.99) (5, 6).\u00a0 Patterns of disordered eating behaviors and disordered eating disturbances or diagnoses can be viewed along a continuum or spectrum. \u00a0Including athletes in this group expands the population of athletes in the present study to those with a clinical definition of an eating disorder and those with eating behaviors that remain subclinical, but may be detrimental to the health of the athletes (5, 18).<\/p>\n RESULTS<\/strong><\/p>\n The mean EAT-26 score for all participants was 6.0 (SD<\/em> = 6.5).\u00a0 The results show that three of the 68 (4.41%) male high school cross country runners scored 20 or higher, indicating at risk for disordered eating.\u00a0 An additional 13.2% (n <\/em>= 9) met the cut-off score of 14 for disordered eating behaviors, one standard deviation above the mean for population norms (5, 6).\u00a0 Figure 1 shows the breakdown of EAT-26 scores for the male high school cross country runners (N = <\/em>68).\u00a0 The present study examined the intra-individual characteristic associations of the ATHLETE and EMI-2 questionnaires with the EAT-26 scores for the participants.\u00a0 Table 2 shows the mean score, standard deviation, and a sample item from the questionnaires for all subscales.\u00a0 The \u201cYour Body and Sports\u201d subscale scores showed that 5.9% (n<\/em> = 4) runners scored 4 or higher on the items related to this subscale.\u00a0 The subscale, \u201cYour Body and Sports\u201d measures drive for thinness and the relationship to the performance in athletes.\u00a0 The \u201cPhysical Appearance\u201d subscale scores of the EMI-2 questionnaire showed 12 of 68 (17.6%) of male cross country runners scored 4 or higher on the items related to this subscale, indicating that the item was a strong motivation to exercise.\u00a0 Thirteen of 68 (19.1%) of male cross country runners scored 4 or higher on the items related to the \u201cWeight Management\u201d subscale of the EMI-2, indicating that the item was a strong motivation to exercise.<\/p>\n Table 3 shows the number and percentages of responses regarding desired weight on the ATHLETE questionnaire.\u00a0 The results show that 26 of 68 male runners (38.2%) reported a desire to gain weight.\u00a0 The results also demonstrate that there was dissatisfaction with current weight in that nearly 65% of the male runners desired a weight change.<\/p>\n Table 4 shows the correlation coefficients between the EAT-26 and the subscales of the EMI-2 and the ATHLETE questionnaires.\u00a0 There was a positive correlation between \u201cYour Body and Sports\u201d subscale and the EAT-26 score, r <\/em>= .36, p<\/em> = .003, indicating that as the runners felt more strongly about the items, the EAT-26 score was greater.\u00a0 Overall, there was a moderate positive correlation between the \u201cYour Body and Sports\u201d subscale of the ATHLETE questionnaire and the EAT-26 score.<\/p>\n The Pearson correlation coefficient for the \u201cWeight Management\u201d subscale and the EAT-26 score was r<\/em> = .31, p<\/em> = .011.\u00a0 This suggests that as the motivation to exercise for weight management purposes increases, the more likely the association with disordered eating behaviors.<\/p>\n There was a modest positive correlation (r = <\/em>.26, p = <\/em>.030) for the \u201cFeelings about performance\u201d subscale of The ATHLETE Questionnaire and the EAT-26 score.\u00a0 This suggests a positive relationship between the items of performance perfectionism of the ATHLETE Questionnaire and disordered eating behaviors as measured by the EAT-26 score.\u00a0 Engaging in disordered eating behaviors and \u201cpersonal expectation of superior athletic achievement and meeting the expectations of significant others\u201d (15) are associated in the athletes.<\/p>\n The Pearson correlation coefficient for the \u201cSupport from teammates\u201d subscale of the ATHLETE Questionnaire and the EAT-26 was r<\/em> = .21, p<\/em> = .093.\u00a0 This implies no relationship between support from teammates or the amount of trust in a teammate about disordered eating behaviors.<\/p>\n There was no significant correlation between the \u201cFeelings about being an athlete\u201d subscale and EAT-26 score, r <\/em>= .12, p <\/em>= .345.\u00a0 This demonstrates no significant relationship between the responses on the \u201cFeelings about being an athlete\u201d subscale of the ATHLETE Questionnaire and the EAT-26.\u00a0 This implies that among male high school runners, athletic identity has no relationship with runners engaging in disordered eating behaviors.<\/p>\n The Pearson correlation coefficient returned was r<\/em> = .17, p<\/em> = .167 for the \u201cPhysical Appearance\u201d subscale of the EMI-2 and the EAT-26 score.\u00a0 This implies that motivation to exercise for physical appearance has no relationship with the likelihood of a male high school runner engaging in disordered eating behaviors.<\/p>\n The Pearson correlation coefficient for the \u201cFeelings about Eating\u201d subscale of The ATHLETE questionnaire and the EAT-26 score was r<\/em> = .18, p<\/em> = .137.\u00a0 This indicates no significant relationship between that the social pressure toward eating versus disordered eating behaviors in the athletes.<\/p>\n There was no significant correlation between the \u201cFeelings about your body\u201d subscale of the ATHLETE questionnaire and the score on the EAT-26, r<\/em> = .19, p<\/em> = .109.\u00a0 This suggests that body shape has no association with the disordered eating behaviors of male high school cross country runners.<\/p>\n DISCUSSION<\/strong><\/p>\n Millions of people from all ages and genders in the U.S. suffer from eating disorders.\u00a0 Research has shown that females are at greater risk for eating disorders than males (17, 32, 39).\u00a0 Some studies have shown that athletes and adolescents in particular, are more susceptible to eating disorders than in non-athletic populations (28, 35).\u00a0 However, limited research about eating disorders is available in high school male cross country and distance runners.<\/p>\n Given the rising rates associated with eating disorders across all ages and genders and in particular adolescent males, understanding the prevalence with contributing factors was deemed necessary in a male athletic group.\u00a0 Therefore, the goals of this study were to determine the degree of disordered eating and contributing factors among high school male cross country runners.<\/p>\n The present study determined that 4.4% (n<\/em> = 3) males scored 20 or higher on the EAT-26.\u00a0 A score of 20 or higher indicates an individual is at-risk for an eating disorder and displays symptoms.\u00a0 An additional 13.2% (n <\/em>= 9) met the cut-off score of 14 for disordered eating behaviors.\u00a0 The results of the present study are in agreement with previous research that disordered eating among male athletes may be more of an issue than previously thought (10, 29, 30).\u00a0 Previous research on disordered eating behaviors in female athletes, using the EAT-26, revealed a mean score of 6.97 (SD <\/em>= 6.99) (5). \u00a0The present sample was similar for males (M <\/em>= 6.04, SD <\/em>= 6.52; N <\/em>= 68).\u00a0 Although the EAT-26 cannot diagnose a particular eating disorder, the symptoms can be predictive of risk status.\u00a0 Much of the previous research deals with eating disorders in males of all ages, versus the adolescent male athletes in the present study.\u00a0 While previous research focused on other characteristics that may have had an impact on the higher prevalence rates, the current study focused on factors more specific to male adolescent athletes. \u00a0These include the correlates of performance perfectionism, drive for thinness, and body dissatisfaction in athletes.<\/p>\n Modest positive correlation coefficients were found with the intra-individual characteristics on the EMI-2 and the ATHLETE questionnaires with overall EAT-26 scores.\u00a0 The \u201cYour Body and Sports\u201d subscale of the ATHLETE questionnaire measured drive for thinness and the connection to enhanced performance or appearance.\u00a0 This subscale included excessive or compulsive training above the requirement of the training program.\u00a0 The \u201cFeelings about performance\u201d subscale measured feelings toward performance perfectionism defined as \u201cthe excessive personal expectations for superior athletic performance and with respect to meeting expectations of significant others\u201d (15).\u00a0 A higher mean score on \u201cYour Body and Sports\u201d and \u201cFeelings about performance\u201d subscales of the ATHLETE questionnaire and \u201cWeight Management\u201d subscale of the EMI-2 are indicative of greater degrees of the three constructs.\u00a0 The performance factor is associated with disordered eating behaviors by the \u201cYour body and sports\u201d and \u201cFeelings about performance\u201d subscales versus the overall EAT-26 score.<\/p>\n A higher mean score on the weight management subscale of the EMI-2 is related to weight management and motivation to exercise.\u00a0 The current study revealed 32% (n = <\/em>22) <\/em>of male high school runners scored 3.25 or higher on the weight management subscale.\u00a0 This indicates perception of current weight as the items centered on \u201cstaying slim\u201d, \u201closing weight\u201d, or \u201cburning calories\u201d (20).\u00a0 A desire to control weight is associated with disordered eating behaviors in male high school cross country runners as determined from the modest correlation coefficient for the weight management subscale and the EAT-26 score.<\/p>\n Previous research (11) has suggested that males with disordered eating habits tended to exercise more for physical appearance reasons.\u00a0 The present study determined that 50% (n = 34) male high school runners scored 3.25 on the items in the physical appearance subscale of the EMI-2.\u00a0 This suggests that this group of athletes may exercise in order to \u201clook more attractive\u201d, \u201chave a good body\u201d, or \u201cimprove one\u2019s body\u201d (20).\u00a0 However, there was no significant correlation for the \u201cPhysical Appearance\u201d subscale of the EMI-2 and the EAT-26 score.\u00a0 This suggests that although physical appearance may be desired, male high school runners exclude disordered eating behaviors for physical appearance as measured by the EAT-26.<\/p>\n Of the 68 participants in the study sample, 48 were White (70.6%), followed by Asian-American and Pacific Islander (11.8%, n <\/em>= 8), 2 or more races (8.8%, n<\/em> = 6), Hispanic and Latino (5.9%, n <\/em>= 4), and African-American (2.9%, n<\/em> = 2).\u00a0 This limitation may indicate that the results are generalizable only to school districts of similar size and demographic makeup.\u00a0 Further, the demographic makeup of the teams differs from the school district as a whole.\u00a0 For instance, the makeup of the school district is that of Hispanic and Latino (43.4%), White (30.2%), African-American (12.0%), Asian and Pacific Islander (8.1%), Multi-Racial (5.8 %), Native American, American Indian, and Alaskan Native (0.5%) (25). Therefore, demographic information on a larger scale of cross country teams may provide more information of the students participating in the sport.<\/p>\n Disordered eating behaviors may be more prevalent in both athletes and the general population versus previously thought.\u00a0 The research suggests that eating disorders among males are underreported (3, 10).\u00a0 Professionals estimate that in addition to diagnosed eating disorders, there are as many as 25 million more with disordered eating behaviors that remain sub-clinical or unreported (24).\u00a0 Therefore, underreporting by the athletes in the present study is plausible.<\/p>\n The questionnaires were completed on one occasion by runners during the summer prior to the start of the season.\u00a0 A longitudinal study over the course of the school year and across sports in which the runners participate (e.g., cross country and track and field) may yield different results.\u00a0 This might determine whether individual characteristics stabilize over time or are situational to the sport or feelings of the athlete at the time.\u00a0 Research suggests that longitudinal results may provide eating disorder prevalence rates for male participants similar to those for females (12, 13,16).<\/p>\n Sixty-eight high school male cross country runners participated in the present study.\u00a0 Among the male runners, twenty-six (38.2%) had a desire to increase body weight, although these athletes participated in a sport where a lean body type is more desirable.\u00a0 However, 26.5% (n <\/em>= 18) of the high school male runners had a desire to decrease body weight.\u00a0 The results of the current study appear to concur with the results of previous studies involving high school male and female athletes and non-athletes (27, 33, 34).\u00a0 In particular, Hague (11) shows remarkably similar results in male Division III college athletes where 37% (n<\/em> = 29) desired to lose weight and 38% (n <\/em>=34) desired to gain weight, although a sport-by-sport breakdown was not conducted (11).\u00a0 The athletes in the previous investigations desired a change in body weight, where females typically desired weight loss while males generally desired weight gain.\u00a0 The reasons for a desired weight change may be gender-dependent and based on body satisfaction.\u00a0 Although the present study did not investigate the reasons for dissatisfaction with current weight status, future studies may seek more information relative to the reasons.\u00a0 For example, do male cross country runners feel a need to be more muscular? \u00a0Do the bodies of male cross country runners not fit the ideal?<\/p>\n The present study was conducted on male cross country runners from 12 high schools in one large, urban school district.\u00a0 The study was limited by a low number of participants relative to the number of runners on the teams and number of high schools in the school district.\u00a0 Perhaps a larger and more diverse population of male runners would provide more information with respect to the research question.\u00a0 The complexity of disordered eating and contributing factors may limit the understanding.\u00a0 The results may contribute to the recognition by the athletes, coaches, athletic trainers, teachers, and parents that male athletes are vulnerable to eating disorders and disordered eating behaviors.<\/p>\n CONCLUSIONS<\/strong><\/p>\n This study suggests that disordered eating behaviors in high school male cross country runners are related to contributing factors.\u00a0 Factors that have a significant relationship with disordered eating are performance and weight management.\u00a0 No significant relationships were found between disordered eating behaviors in male cross country athletes and personal body feelings, feelings about eating, and being an athlete.\u00a0 Signs and symptoms may be different between male and female athletes, while prevalence rates may be similar and related to the rate of reporting<\/p>\n APPLICATIONS IN SPORT<\/strong><\/p>\n Most studies involving disordered eating behaviors have centered on females in general and female athletes in particular.\u00a0 Recognizing and identifying that disordered eating behaviors exist in males and may manifest differently can assist those directly involved with this group of athletes.\u00a0 Programs can be established to deal with the complexities of the issue especially among parents, coaches, trainers, counselors, and the athletes (26).\u00a0 Educating those directly involved with this group of athletes (coaches, parents, and trainers) may help deter these athletes from using disordered eating behaviors.\u00a0 Rather than equating thinness to performance, educating athletes about nutrition and healthful eating habits to demonstrate the positive impact these factors will make on performance is of critical importance.<\/p>\n ACKNOWLEDGMENTS<\/strong><\/p>\n Many thanks to the caring professors at SUU who helped shape this paper.\u00a0 A special thanks to Dr. Julie Taylor and Dr. Brian Lyons for the advice and suggestions in the early stages of developing this research topic.\u00a0 Thank you to all the anonymous high school male cross country runners and the coaches who participated in this study.<\/p>\n REFERENCES<\/strong><\/p>\n <\/p>\n FIGURES AND TABLES<\/strong><\/p>\n Table 1.\u00a0 <\/em><\/p>\n Demographic information<\/em><\/p>\n Note<\/em>: Six athletes did not complete the competition level item on the questionnaire.<\/p>\n <\/p>\n Table 2.<\/p>\n Descriptive statistics for the ATHLETE and EMI-2 questionnaires<\/em><\/p>\n Note:\u00a0 Mean scores were determined by summing the scores for each subscale and dividing by the number of items in each subscale for each athlete.\u00a0 The maximum score for each item is five.<\/em><\/p>\n <\/p>\n Table 3.<\/p>\n Responses to desired weight question on the ATHLETE questionnaire<\/em><\/p>\n\n
![\"Capture1\"](\"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2014\/04\/Capture11.jpg?resize=951%2C698\")
<\/a><\/p>\n![\"Capture11\"](\"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2014\/04\/Capture111.jpg?resize=678%2C681\")
<\/a><\/p>\n![\"Capture6\"](\"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2014\/04\/Capture6.jpg?resize=1026%2C670\")
<\/a><\/p>\n
![\"Capture8\"](\"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2014\/04\/Capture8.jpg?resize=698%2C141\")
<\/a><\/p>\n![\"Capture1\"](\"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2014\/04\/Capture12.jpg?resize=1036%2C582\")
<\/a><\/p>\n