{"id":6762,"date":"2019-12-20T06:30:00","date_gmt":"2019-12-20T12:30:00","guid":{"rendered":"http:\/\/thesportjournal.org\/?p=6762"},"modified":"2019-12-12T14:21:11","modified_gmt":"2019-12-12T20:21:11","slug":"weight-discrimination-among-students-from-a-diverse-urban-university","status":"publish","type":"post","link":"https:\/\/thesportjournal.org\/article\/weight-discrimination-among-students-from-a-diverse-urban-university\/","title":{"rendered":"Weight Discrimination among Students from a Diverse Urban University"},"content":{"rendered":"\n

Authors:<\/strong> Guillermo Escalante1<\/sup>, Rafael Alamilla1<\/sup>, Eric Vogelsang2<\/sup>, Christopher Gentry1<\/sup>, Jason Ng1<\/sup><\/p>\n\n\n\n

1<\/sup>Department of Kinesiology, California\nState University, San Bernardino, USA; 2<\/sup>Department of Sociology, California\nState University, San Bernardino, USA<\/p>\n\n\n\n

Corresponding Author:<\/strong>
Guillermo Escalante, DSc, MBA, ATC, CSCS, CISSN
California State University- San Bernardino, Department of Kinesiology
5500 University Parkway
San Bernardino, CA 92407
gescalan@csusb.edu<\/a>
(909) 537-7236<\/p>\n\n\n\n

Weight <\/strong>D<\/strong>iscrimination <\/strong>a<\/strong>mong <\/strong>S<\/strong>tudents from a <\/strong>D<\/strong>iverse <\/strong>U<\/strong>rban <\/strong>U<\/strong>niversity<\/strong> <\/h3>\n\n\n\n

ABSTRACT<\/strong><\/p>\n\n\n\n

Purpose:<\/em> To examine the\nassociation between university students\u2019 weight discrimination and their\nacademic discipline, gender, ethnicity, body mass index (BMI), body fat\npercentage, explicit overweight bias, personal body perceptions, and their\npersonal experiences with weight loss. Methods:<\/em> Sixty-two students (Age: 23.9 \u00b1 4.7 y) from various\ndisciplines completed 1) a 41-question survey that addressed the participant\u2019s\nexplicit overweight bias, prior struggles with body weight, and body\nperceptions; 2) the Weight-Implicit Association Test (WIAT) to address overweight\nimplicit bias; and 3) measurement of height, weight, and body fat. Chi-Square\ntests were performed between the participant\u2019s WIAT results and academic\ndiscipline, BMI, body fat, explicit bias, personal experience with\ntheir body fat, and body perception. Moreover, differences in BMI and body fat\npercentage were examined with two separate 2 (gender) \u00d7 2 (academic discipline)\nrepeated measures ANOVAs. Results: <\/em>ANOVA results revealed a relationship between an\nexplicit bias and WIAT implicit bias. No relationships were found\nbetween the results of the WIAT and academic discipline, BMI\nclassification, body fat classification, personal experience with body\nfat, or perceptions of their body. Conclusions:\n<\/em>An implicit anti-fat bias exists\nregardless of academic discipline, percent body fat, BMI, explicit anti-fat\nbias, prior struggles with body fat, or perceptions of their body. These\nfindings support previous literature that suggests individuals have an\nunconscious negative prejudgment of overweight people. Applications in Sport: <\/em>Current physical educators, healthcare\nprofessionals, fitness professionals, sport coaches, and university faculty\npreparing students for these professions must begin to take the steps necessary\nto eliminate weight bias from their environments. The authors recommend that\nall members of the aforementioned communities develop an understanding of the\nfactors that may lead to weight gain and develop strategies of encouraging\noverweight individuals to reduce their weight without further perpetuating\nweight stigma.  <\/em> <\/p>\n\n\n\n\n\n\n\n

Key words: <\/strong>discrimination, weight-bias, implicit association<\/p>\n\n\n\n

INTRODUCTION<\/strong><\/p>\n\n\n\n

Weight discrimination and stigmatization, partly a consequence\nof the United States\u2019 high overweight\/obesity rates, has had a substantial\nimpact on the lives of many Americans. Over the past 30 years, there has\nbeen an increase in perceived weight discrimination among Americans. Andreyeva et al. (3) determined\nthat the prevalence of weight discrimination increased from 7.3% in 1995-1996\nto 12.2% in 2004-2005. In another study, Sutin et al. (29) determined\nthat weight discrimination has the greatest consequences on people who are\nalready overweight or obese; they also reported that people who\nexperienced weight discrimination during initial testing were three\ntimes more likely to remain obese at the follow up. <\/p>\n\n\n\n

Weight bias literature has\ncharacterized bias as either explicit or implicit. Explicit bias is any belief\nor attitude that is expressed at the conscious level\u2014measured using self-report\nquestionnaires. Implicit bias is any belief or attitude that impacts our\nunderstanding, actions, and decisions in an unconscious manner. Implicit weight\nbias has been traditionally measured using the Implicit Association Test, a\nresponse-latency task that measures the strength of association between a\nsocial attitude (i.e. weight bias) and an attribute (i.e. lazy). Previous\nliterature has shown that implicit and explicit bias are moderately related to\neach other (12) and are both predictive of bias (10, 12). <\/p>\n\n\n\n

Previous\ninvestigations have indicated the relationship between descriptive\ncharacteristics\u2014such as BMI, ethnicity, college major, etc.\u2014and expression of\nweight bias. Latner et al. (14) undertook a 356-participant study that assessed\nthe prevalence of weight stigmatization among young adults. Their results\ndemonstrated that weight stigmatization was prevalent among all\nparticipants\u2014irrespective of gender, ethnicity, and BMI. Interestingly,\ninvestigators found that African Americans and women were less stigmatizing\nthan Caucasians and men, respectively. Similarly, a study measuring the\nimplicit and explicit weight bias of a large medical student population\ndemonstrated that bias is dependent of several demographic factors. Namely, men\nexpressed more bias than women, Caucasians and Hispanics expressed more bias\nthan African Americans, and individuals with a lower BMI expressed greater bias\n(19). <\/p>\n\n\n\n

How individuals\nperceive others who are overweight or obese might be affected by their own struggles\nwith their weight. Previous investigations have shown that perceptions of obese individuals\ncan change positively after they lose weight (8). However, other studies have\nshown that\u2014regardless of the manner in which weight is lost\u2014individuals are\nstill subject to negative weight stigmatization (15). As such, clarification as\nto how prior weight struggles impact an individual’s weight bias needs to be\naddressed.<\/p>\n\n\n\n

Properly reaching out to overweight individuals is\nimportant if they are to succeed in losing body fat. One of the many tasks for\nhealthcare and fitness professionals is to help guide overweight individuals in\nlosing excess body fat to improve their health. Therefore, it is important\nto recognize if an anti-fat bias might affect their ability to\nhelp overweight or obese individuals effectively. Unfortunately, researchers\nhave reported that healthcare specialists have strong negative associations\ntoward obese persons (26). It has also been reported that weight stigma in\nhealthcare settings leads to poor quality of care for overweight patients (30).\nA study on implicit weight bias among health professionals found that they held\nnegative implicit attitudes about weight as well as implicit anti-fat\nattitudes associating \u201cfat\u201d with bad, lazy, stupid, and worthless (20, 27). \nHence, improving self-awareness of biases may help improve the communication\nbetween health professionals and overweight clients to achieve better\noutcomes.   <\/p>\n\n\n\n

Kinesiology majors\u2014students seeking to enter a fitness, coaching,\nphysical educator, or healthcare career path\u2014 could play an important role in\nreducing anti-fat bias in their future careers. Previous studies have shown the\npresence of implicit anti-fat bias in pre-service physical education teachers (1,\n18, 24). As a result, it would seem necessary to discuss the possibility of\nsuch feelings within future physical educators to help curtail the impact it\nmay have in the actual kindergarten through twelfth grade (K-12) setting. A negative\nbody image can have a detrimental impact on K-12 students in the physical\neducation environment (13), so it is important to consider the views of future\nphysical educators who will be an influencing factor on the general population\nand future kinesiology majors.  <\/p>\n\n\n\n

In a study investigating implicit anti-fat\nbias among fitness professionals and regular\nexercisers, investigators reported that both fitness professionals and\nregular exercisers had a strong anti-fat bias. Furthermore, the authors\nstated that the bias was more pronounced for fitness\nprofessionals who had never been overweight themselves and\nwho believed that personal control dictated body weight (23). In another study\ninvestigating the efficacy of a multi-component intervention to reduce\nkinesiology pre-professionals\u2019 implicit and explicit anti-fat bias,\nauthors reported that the participants\u2019 strong implicit anti-fat bias\nremained unchanged after the intervention despite the reduction in the explicit\nbias (25). A similar strong implicit anti-fat bias was also reported by Sabin\net al. (26) among physicians and non-physicians alike. Investigators reported\nthat obese physicians as classified by BMI only had a moderate\nimplicit anti-fat bias while physicians that were overweight, normal weight, or\nunderweight had a strong implicit anti-fat bias; these results\nwere also similar among non-physicians (26).<\/p>\n\n\n\n

Since several studies have reported that an implicit\nanti-fat bias exists among the general population, healthcare professionals,\nfitness and education professionals, and kinesiology pre-professionals,\nthe objective of this study was to examine the results of the Weight Implicit\nAssociation Test (WIAT) among students from a diverse urban university that is\nconsidered a Hispanic Serving Institution. Specifically, the relationships\nbetween the results of the WIAT were examined among kinesiology and\nnon-kinesiology majors, gender, ethnicity, and race. Furthermore,\nthe relationship between the results of the WIAT and the participants\u2019 BMI,\npercentage of body fat, explicit feelings toward thin people, explicit feelings\ntoward overweight people, their personal experiences with their body fat,\nand the perceptions of their body were examined. <\/p>\n\n\n\n

Since kinesiology students generally like to exercise\nand are potentially in better physical condition than other\ncollege students,\nit was hypothesized that kinesiology majors\nwould have a stronger implicit anti-fat bias than\nnon-kinesiology majors. Furthermore, it was hypothesized that those\nstudents with a lower percentage of body fat, a lower BMI,\npositive explicit feelings toward thin people, negative explicit\nfeelings toward overweight people, positive experiences with controlling\ntheir body fat, and positive perceptions about their body\nwould have a stronger anti-fat bias than\nthose students with a higher percentage of body fat, a\nhigher BMI, negative explicit feelings toward thin people, positive explicit\nfeelings toward overweight people, difficult experiences with controlling\ntheir body fat, and negative perceptions about their body. No differences were hypothesized in anti-fat\nbias among gender, ethnicity, or race.  <\/p>\n\n\n\n

METHODS<\/strong><\/p>\n\n\n\n

Data<\/em> Collection<\/em><\/em><\/p>\n\n\n\n

A total of 62\nstudents of various disciplines from a diverse Hispanic serving university volunteered\nand completed this study; Table 1 displays their characteristics. Students were\nrecruited to participate in this study for a period of 12 weeks via fliers posted\naround campus and via word of mouth. Volunteers went to the Human Performance Laboratory\nwhere they met a member of the research team for their appointment. Each\nparticipant read and signed an informed consent document approved by\nthe university\u2019s institutional review board. Next, participants were provided a\ncomputer station where they completed a questionnaire on Qualtrics.com that\nincluded items about themselves, their explicit feelings toward thin and\noverweight people, their personal experiences with gaining\/losing weight, and\ntheir perceptions of their body. The survey was 41 questions in\nlength, but after answering the first 30 items of the survey\nthey were asked to move to another computer where they completed the WIAT.\u202fUpon\ncompleting the WIAT, the participants\u2019 height, weight, BMI (as calculated as\nweight in kg \u00f7 m2<\/sup>), and percentage of body fat were measured by\na member of the research team. Finally, the participants returned to the original survey computer\nstation and answered the final 11 questions.   <\/p>\n\n\n\nTable 1.<\/strong> Participant Characteristics (N = 62)\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
 <\/td>\n Kinesiology Majors<\/strong><\/td>\n Non-Kinesiology Majors<\/strong><\/td>\n Total<\/strong><\/td>\n <\/tr>\n
N <\/td>\n 44<\/td>\n 18<\/td>\n 62<\/td>\n <\/tr>\n
Age (y)<\/td>\n 24.5 (4.67)<\/td>\n 22.5 (4.54)<\/td>\n 23.9 (4.7)<\/td>\n <\/tr>\n
Race\/Ethnicity<\/strong><\/td>\n <\/td>\n <\/td>\n <\/td>\n <\/tr>\n
Hispanic<\/td>\n 75.0%<\/td>\n 66.7%<\/td>\n 72.6%<\/td>\n <\/tr>\n
White (Non-Hispanic)<\/td>\n 9.1%<\/td>\n 11.1%<\/td>\n 9.7%<\/td>\n <\/tr>\n
Multi-Race<\/td>\n 2.3%<\/td>\n 5.6%<\/td>\n 3.2%<\/td>\n <\/tr>\n
Asian<\/td>\n 6.8%<\/td>\n 5.6%<\/td>\n 6.4%<\/td>\n <\/tr>\n
Black<\/td>\n 4.6%<\/td>\n 5.6%<\/td>\n 4.8%<\/td>\n <\/tr>\n
Other<\/td>\n 2.3%<\/td>\n 5.6%<\/td>\n 3.2%<\/td>\n <\/tr>\n
Gender = Female<\/td>\n 59.1%<\/td>\n 55.6%<\/td>\n 56.1%<\/td>\n <\/tr>\n
Male BMI (kg\u00b7m-2)<\/td>\n 25.8 (3.0)<\/td>\n 26.8 (2.3)<\/td>\n 26.1 (2.8)<\/td>\n <\/tr>\n
Female BMI (kg\u00b7m-2)<\/td>\n 24.5 (4.6)<\/td>\n 25.2 (4.3)<\/td>\n 24.3 (4.7)<\/td>\n <\/tr>\n
BMI Categories<\/strong><\/td>\n <\/td>\n <\/td>\n <\/td>\n <\/tr>\n
Normal (18.5 \u2013 24.9 kg\u00b7m-2)<\/td>\n 45.4%<\/td>\n 50.0%<\/td>\n 46.8%<\/td>\n <\/tr>\n
Overweight\/Obese (25.0 \u2013 29.9\/>30 kg\u00b7m-2)<\/td>\n 54.6%<\/td>\n 50.0%<\/td>\n 53.2%<\/td>\n <\/tr>\n
Male Body Fat (%)<\/td>\n 16.8 (5.4)<\/td>\n 21.5 (5.8)<\/td>\n 18.3 (5.9)<\/td>\n <\/tr>\n
Female Body Fat (%)<\/td>\n 27.5 (7.1)<\/td>\n 27.3 (7.5)<\/td>\n 27.5 (7.1)<\/td>\n <\/tr>\n
Body Fat Categories<\/strong><\/td>\n <\/td>\n <\/td>\n <\/td>\n <\/tr>\n
Very lean\/Excellent<\/td>\n 20.5%<\/td>\n 27.8%<\/td>\n 22.6%<\/td>\n <\/tr>\n
Good\/Fair<\/td>\n 11.4%<\/td>\n 5.6%<\/td>\n 9.7%<\/td>\n <\/tr>\n
Poor\/Very poor<\/td>\n 68.2%<\/td>\n 66.7%<\/td>\n 67.7%<\/td>\n <\/tr>\n
Implicit Bias: Strong Anti-Fat Bias<\/td>\n 50.0%<\/td>\n 33.3%<\/td>\n 45.2%<\/td>\n <\/tr>\n
Explicit Bias<\/strong><\/td>\n <\/td>\n <\/td>\n <\/td>\n <\/tr>\n
None<\/td>\n 43.2%<\/td>\n 33.3%<\/td>\n 40.3%<\/td>\n <\/tr>\n
Slight Preference: Thin People<\/td>\n 22.7%<\/td>\n 22.2%<\/td>\n 22.6%<\/td>\n <\/tr>\n
Moderate Preference: Thin People<\/td>\n 18.2%<\/td>\n 22.2%<\/td>\n 19.4%<\/td>\n <\/tr>\n
Strong Preference: Thin People<\/td>\n 9.1%<\/td>\n 16.7%<\/td>\n 11.3%<\/td>\n <\/tr>\n
Preference: Overweight People<\/td>\n 6.8%<\/td>\n 5.6%<\/td>\n 6.4%<\/td>\n <\/tr>\n
Prior Struggle: Body Fat<\/strong><\/td>\n <\/td>\n <\/td>\n <\/td>\n <\/tr>\n
Never Struggled<\/td>\n 34.9%<\/td>\n 33.3%<\/td>\n 34.4%<\/td>\n <\/tr>\n
Never Struggled because effort<\/td>\n 20.9%<\/td>\n 5.6%<\/td>\n 16.4%<\/td>\n <\/tr>\n
Struggled Since High School<\/td>\n 14.0%<\/td>\n 16.7%<\/td>\n 14.8%<\/td>\n <\/tr>\n
Struggled Since College<\/td>\n 9.3%<\/td>\n 16.7%<\/td>\n 11.5%<\/td>\n <\/tr>\n
Struggled Since (Younger age)<\/td>\n 7.0%<\/td>\n 16.7%<\/td>\n 9.8%<\/td>\n <\/tr>\n
Used to struggle<\/td>\n 14.0%<\/td>\n 11.1%<\/td>\n 13.1%<\/td>\n <\/tr>\n
Data reported as mean (SD) where applicable, BMI: body mass index<\/td>\n <\/tr>\n <\/tbody>\n<\/table>\n\n\n\n

Implicit bias: The\nimplicit association test <\/em><\/p>\n\n\n\n

The Implicit Association Test (IAT) is a widely used tool\nof implicit social cognition that measures\nrelative association strengths between two pairs of concepts (9) that was first\nreported in the literature in 2001 by Teachman et al. (30). The IAT is a\nvalidated method of measuring automatic and subconscious attitudes and has\nsatisfactory test-retest reliability (10, 12, 28). The IAT has been\nshown to capture evaluations that are related but different from self-report (12),\nhave good reliability in comparison with other implicit methods (6, 17), and are\nrelatively robust with repeated measures for pre-post evaluation (17). The web-based WIAT\nis a form of the original IAT that is designed to measure an individual\u2019s attitudes\nand beliefs they may be unwilling or unable to report about thin\nversus overweight people.  Test takers are required to organize\npictures of overweight and thin people and value laden words as they appear on\na computer screen by pressing one of two computer keys. In one condition, the\nparticipants categorize \u201cgood\u201d words with thin people and \u201cbad\u201d words with\noverweight people. In the second condition, the participants are asked to\ncategorize \u201cbad\u201d words with thin people and \u201cgood\u201d words with overweight\npeople. The difference in the average response time between the two groups is\nan indicator of the relative association bias toward one group rather than the\nother. The possible results of the WIAT that an individual can receive after\ncompleting it are: 1) strong preference for fat people, 2) moderate\npreference for fat people, 3) slight preference for fat people,\n4) No preference for thin or fat people, 5) slight preference\nfor thin people, 6) moderate preference\nfor thin people, 7) strong preference\nfor thin people.  A frequency table outlining the results\nof the test are found in Table 2.    <\/p>\n\n\n\nTable 2.<\/strong> Detailed Frequency of Weight Implicit Association Test Results (N = 62)\n\n \n \n \n \n \n \n \n \n \n
 <\/td>\n Kinesiology Majors<\/strong><\/td>\n Non-Kinesiology Majors<\/strong><\/td>\n Total<\/strong><\/td>\n %<\/strong><\/td>\n <\/tr>\n
Strong preference: overweight people<\/td>\n 0<\/td>\n 0<\/td>\n 0<\/td>\n –<\/td>\n <\/tr>\n
Moderate preference: overweight people<\/td>\n 0<\/td>\n 1<\/td>\n 1<\/td>\n 1.6%<\/td>\n <\/tr>\n
Slight preference: overweight people<\/td>\n 2<\/td>\n 4<\/td>\n 6<\/td>\n 9.7%<\/td>\n <\/tr>\n
No preference<\/td>\n 5<\/td>\n 2<\/td>\n 7<\/td>\n 11.3%<\/td>\n <\/tr>\n
Slight preference: thin people<\/td>\n 5<\/td>\n 3<\/td>\n 8<\/td>\n 12.9%<\/td>\n <\/tr>\n
Moderate preference: thin people<\/td>\n 10<\/td>\n 2<\/td>\n 12<\/td>\n 19.4%<\/td>\n <\/tr>\n
Strong preference: thin people<\/td>\n 22<\/td>\n 6<\/td>\n 27<\/td>\n 45.2%<\/td>\n <\/tr>\n <\/tbody>\n<\/table>\n\n\n\n

BMI and body fat<\/em><\/p>\n\n\n\n

Each\nparticipant’s\u202fheight, weight, and body composition were measured by a\ntrained research assistant. Height was measured with a stadiometer and\nweight was measured with an electronic scale.\u202fFat weight and fat\nfree weight were estimated with a\u202fhandheld bioelectrical impedance\nanalysis device (Omron, Hoffman Estates, IL). After the research\nassistant entered the participant\u2019s age, height, weight, and sex into the\ndevice, the participant\u202fwas instructed to grip the testing handles of\nthe device and hold it in front of the body while the device estimated body\ncomposition. \u200bBMI was calculated with the measurements gathered from\nheight and weight. The categories for BMI were as follows: 18.5-24.9 kg\u00b7m-2<\/sup>\n= Normal, 25.0-29.9 kg\u00b7m-2 <\/sup>= Overweight, \u2265 30.0 kg\u00b7m-2 <\/sup>=\nObese (2). Since few students fell into the obese category (n=5), they were\ncombined with the overweight category for the purpose of these\nanalyses. The categories for body fat percentage\nwere as follows for men ages 20-29 y: < 10.5% = Very lean\/Excellent,\n10.6 – 18.6% = Good\/Fair, > 18.6% = Poor\/Very Poor (2).  The\ncategories for body fat percentage were as follows for women ages 20-29: < 16.8%\n= Very lean\/Excellent, 16.9 \u2013 23.4% = Good\/Fair, > 23.4%\n= Poor\/Very poor (2).<\/p>\n\n\n\n

Explicit Bias<\/em><\/p>\n\n\n\n

The\nparticipant\u2019s explicit feelings toward thin and overweight people were measured\nby asking explicit questions about thin and overweight people in the\nsurvey. Specifically, participants were asked if they prefer thin people or fat\npeople. The available responses were: 1) I strongly prefer thin people to fat\npeople, 2) I moderately prefer thin people to fat people, 3) I slightly prefer\nthin people to fat people, 4) I do not prefer thin people more than fat people,\n5) I slightly prefer fat people to thin people, 6) I moderately prefer fat\npeople to thin people, 7) I strongly prefer fat people to thin people. \nFor the logistic regression, those that reported a \u201cstrongly prefer thin people\nto fat people\u201d (42% of respondents) were coded as a\n“1”.   <\/p>\n\n\n\n

Prior struggles with body fat<\/em><\/em><\/p>\n\n\n\n

The\nparticipants\u2019 experiences with their body fat was assessed by\nasking if they have ever struggled with their body fat in the survey. The\navailable responses were: 1) I have never struggled with my body fat, 2) I have\nnever struggled with my body fat only because I have always worked on it, 3) I\nhave struggled with my body fat since high school and still struggle, 4)\nI have struggled with my body fat since college and still struggle,\n5) I have struggled with my body fat since I was (specific younger age) and\nstill struggle, 6) I used to struggle with my body fat but I have learned to\nmanage it.   <\/p>\n\n\n\n

Body perceptions<\/em><\/p>\n\n\n\n

The\nparticipant\u2019s perception of their body was assessed by asking, in two\nseparate items, if they felt they could or should gain or lose weight\nand whether they thought other people would say they need to gain or lose\nweight in the survey. The available responses for the first question were: 1) I\nfeel I could\/should gain some body fat, 2) I feel no need to gain or lose body\nfat, 3) I feel I could\/should lose 5 or less pounds of body fat, 4) I feel I\ncould\/should lose 6-15 pounds of body fat, 5) I feel I could\/should lose 16-25\npounds of body fat, 7) I feel I could\/should lose 26-49 pounds of body fat, 8)\nI feel I could\/should lose 50+ pounds of body fat.  Similarly, the\navailable answers to the second question were: 1) Others would say I\ncould\/should gain some body fat, 2) Others would say I have no need to gain or\nlose body fat, 3) Others would say I could\/should lose 5 or less pounds of body\nfat, 4) Others would say I could\/should lose 6-15 pounds of body fat, 5) Others\nwould say I could\/should lose 16-25 pounds of body fat, 7) Others would say I\ncould\/should lose 26-49 pounds of body fat, 8) Others would say I could\/should\nlose 50+ pounds of body fat.    <\/p>\n\n\n\n

Analytic strategy<\/em><\/p>\n\n\n\n

Several statistical\ntests were performed to examine the relationships between the results\nof the WIAT and kinesiology versus non-kinesiology\nmajors, and among gender, ethnicity, race, the participants\u2019 BMI, percentage\nof body fat, explicit feelings toward thin people, explicit feelings toward\noverweight people, their personal experiences with their body fat, and\nthe perceptions of their body. First, nine Chi-Square tests of independence\nbetween each of the following pairs of categorical variables were\nperformed:  1. Academic major (kinesiology vs non-kinesiology) and\nthe participant\u2019s WIAT results, 2. Gender and the participant\u2019s WIAT\nresults, 3. Ethnicity and the participant\u2019s WIAT results, 4. Race and the\nparticipant\u2019s WIAT results, 5. BMI category (normal, overweight,\nobese) and the participant\u2019s WIAT results, 6. Body fat\npercentage (Very lean\/Excellent, Good\/Fair, Poor\/Very poor) and the\nparticipant\u2019s WIAT results, 7. Explicit bias (for thin or fat people)\nand the participant\u2019s WIAT results, 8. Personal experience with their body fat\nand the participant\u2019s WIAT results, and 9. Perceptions of their body and the\nparticipant\u2019s WIAT results.  Furthermore, two separate factorial\nANOVAs were conducted to compare the main effects of gender and academic discipline\nand the interaction between gender and academic discipline on BMI and on body\nfat percentage.\u202fFinally, a logistic regression was estimated with \u201cAn\nimplicit strong anti-fat bias\u201d as the dependent variable.  For this regression, a strong anti-fat bias (45%) was dichotomized\nversus all other responses (see Table 2). In this regression model, gender,\nHispanic ethnicity, BMI, explicit bias, past struggles with body fat, and\nwhether or not the student was a Kinesiology major were controlled. All data\nwere analyzed using SPSS version 24\n(IBM, Chicago, IL). <\/p>\n\n\n\n

RESULTS AND DISCUSSION<\/strong><\/p>\n\n\n\n

No\u00a0significant\u00a0main effects\u00a0or\u00a0interaction between gender and academic discipline on BMI\u00a0were found for the ANOVA\u2019s. Regarding body composition, there was a significant main effect\u00a0(F(1,3)<\/sub>\u2009=\u200919.80,\u202fp<\/em>\u2009<\u20090.001) for\u00a0gender where males\u00a0had a lower percentage of body fat than females (18.3 \u00b1 5.9% and 27.5 \u00b1 7.1%, respectively). There was no significant main effect for\u00a0academic discipline and body composition\u00a0or interaction between gender and academic discipline on body composition.\u00a0There was a significant\u00a0relationship between the participants\u2019 explicit bias and\u00a0WIAT\u00a0implicit bias.\u00a0No significant relationships were found between the results of the\u00a0participant\u2019s\u00a0WIAT and\u00a0academic discipline, gender,\u00a0ethnicity, race,\u00a0BMI rank, body fat percentage rank,\u00a0personal experience with their body fat, or the perceptions\u00a0of their body.\u00a0Table 2 displays the frequency of the results of the WIAT for kinesiology and non-kinesiology majors.\u00a0<\/p>\n\n\n\n

Results\nfrom the logistic regression can be found in Table 3.  Results from this\nanalysis did not find statistically significant relationships\nbetween a strong implicit anti-fat bias and either (a)\ndemographic characteristics, (b) explicit bias, or (c) prior struggle with body\nfat.  After controlling for other independent variables, students that\nwere overweight\/obese (OR=2.69) or Kinesiology majors (OR=2.38) were estimated\nto have greater odds of a strong implicit bias, but these results were only\nsignificant at p < 0.20. <\/p>\n\n\n\nTable 3.<\/strong> Odds Ratios of Having Strong Anti-Fat Bias (N = 62)\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
 <\/td>\n OR<\/strong><\/td>\n (SE)<\/strong><\/td>\n <\/tr>\n
Female (ref: Male)<\/td>\n 1.88<\/td>\n (1.53)<\/td>\n <\/tr>\n
Hispanic (ref: Non-Hispanic)<\/td>\n 0.90<\/td>\n (0.60)<\/td>\n <\/tr>\n
BMI Overweight\/Obese (ref: Normal)<\/td>\n 2.69<\/td>\n (1.83)<\/td>\n <\/tr>\n
Kinesiology Major (ref: Non-Kinesiology Major)<\/td>\n 2.38<\/td>\n (1.53)<\/td>\n <\/tr>\n
Explicit Bias (ref: None)<\/strong><\/td>\n  <\/td>\n  <\/td>\n <\/tr>\n
Slight Preference: Thin<\/td>\n 0.77<\/td>\n (0.56)<\/td>\n <\/tr>\n
Moderate Preference: Thin<\/td>\n 2.77<\/td>\n (2.19)<\/td>\n <\/tr>\n
Strong Preference: Thin<\/td>\n 1.19<\/td>\n (1.15)<\/td>\n <\/tr>\n
Prefer Fat<\/td>\n 0.18<\/td>\n (0.24)<\/td>\n <\/tr>\n
Prior Struggle with Body Fat<\/strong><\/td>\n  <\/td>\n  <\/td>\n <\/tr>\n
No Struggle (Reference)<\/td>\n 1.00<\/td>\n (0.00)<\/td>\n <\/tr>\n
Used to Struggle but worked on it<\/td>\n 0.46<\/td>\n (0.33)<\/td>\n <\/tr>\n
Has been and still is a struggle<\/td>\n 0.87<\/td>\n (0.66)<\/td>\n <\/tr>\n
AIC<\/td>\n 96.8<\/td>\n <\/tr>\n
N<\/td>\n 62<\/td>\n <\/tr>\n <\/tbody>\n<\/table>\n\n\n\n

The results of this study\ndemonstrate that kinesiology and non-kinesiology majors alike have\nan anti-fat bias. Much like previous studies (27, 30), participants\nwithin the current study exhibited negative implicit anti-fat attitudes. Our findings\nare similar to results from larger samples of the general public who\nvoluntarily complete the WIAT at the Project Implicit\u00ae website (26).  In\naddition, results of multiple studies examining bias in university\nstudents support the findings of the current study (18, 25). Specifically,\nO\u2019Brien et al. (18) explored the implicit bias of 340 university students and\nfound that physical education majors demonstrated higher levels of implicit\nanti-fat bias than psychology students and other health professionals. <\/p>\n\n\n\n

Our data suggest that the presence\nof implicit and explicit weight bias is present irrespective of academic discipline,\ngender, ethnicity, race, BMI, body fat percentage, personal\nexperience with their body fat, or the perceptions of their body. Miller et al. (16) reported similar\nresults for gender and race in a large cohort of medical students. Sabin et al.\n(26) assessed the implicit and explicit weight bias of medical doctors (N = 2,284)\nacross a five-year span. Their results demonstrated a strong implicit bias\ntowards thin individuals regardless of gender and BMI\u2014except for those who were\nclassified as obese. Caucasian and Hispanic medical doctors demonstrated a significant\nweight bias toward overweight individuals, but African Americans and Asians did\nnot. Although this disagrees with our results, it might be due to the smaller\nsample size and lack of heterogeneity of our population. Others demonstrated that weight stigmatization was prevalent\namong all participants irrespective of gender, ethnicity, and BMI (14). Of\nnote, we are the first group to document the weight bias of a primarily\nHispanic study cohort. The aforementioned investigations were composed\nprimarily of non-Hispanic White and African American participants, with only a\nsmall percentage of the study population being composed of Hispanics. Considering\nthe high rates of obesity among the Hispanic population, more studies should\ninvestigate the weight bias of this group.<\/p>\n\n\n\n

These results may point to\nweaknesses in the educational system in that it might neglect to challenge such\nbiases. Many kinesiology students continue on career paths to become\nfitness professionals, healthcare providers, coaches, or physical educators;\nmany are also currently regular exercisers. The anti-fat bias that Robertson et\nal. (23) reported among fitness professionals and regular exercisers is\ncomparable to the participants of this study. This may point towards many of\nthese kinesiology students maintaining their biases into their professional\ncareers unless some intervention is successfully implemented. <\/p>\n\n\n\n

Explicit and implicit bias extends\nbeyond the university setting, which would seem to\nsuggest that such bias may be deeply rooted, especially for those\nwhom one would assume that many years of education would help to\nminimize its prevalence. A large sample of medical doctors (N = 2,284) and individuals\nfrom the lay population (N = 359,261) voluntarily accessed Project\nImplicit<\/em>\u00ae to complete the WIAT. Results uncovered a strong implicit\nanti-fat bias among medical doctors (Cohen\u2019s d<\/em> = 0.93) and the\nlay population (Cohen\u2019s d<\/em> = 1.0) alike (26). In addition, all\ntest takers preferred thin individuals over fat people, which indicates an\nexplicit anti-fat bias (26). These results are similar to that of Teachman et\nal. (30) who reported that healthcare specialists have negative\nassociations toward obese people. Sabin et al. (26) found that the more\nnegative associations came from the population of doctors that were not obese\naccording to their BMI. <\/p>\n\n\n\n

Both explicit and implicit anti-fat\nbias need to be challenged within universities. In particular, universities\nwith kinesiology programs need to be aware of anti-fat bias since many\ngraduates will be required to work with individuals who are overweight or\nobese. In programs such as physical education teacher education, not only is it\nnecessary to educate future teachers about their potential implicit and\nexplicit bias, but it is also valuable to discuss the impact of perceived or\nexplicit bias among primary school students because of the role they play in\nattitudes toward overweight individuals (21). \nSuch attitudes must be challenged because physical education should\nprovide an accepting environment that encourages all to be active without fear\nof teacher or peer judgement. While Rukavina et al. (25) suggests that implicit\nweight bias is difficult to change, multiple studies have explored weight bias\nand have produced some evidence to suggest that purposeful education on the\nvarious causes of obesity\u2014such as genetics, hormones, and socioeconomic status,\namong other reasons, may reduce anti-fat bias (5,  7, 11, 22). <\/p>\n\n\n\n

Future research should focus on\ninterventions designed to reduce weight bias among university students,\nespecially those who enter careers that focus on promoting physical activity,\nhealthcare, and education. Additional information on the impact of\nmetacognition in having students challenge their own biases and\nconsciousness-raising of obesity bias\u2014i.e., making students aware of the impact\nof obesity bias (4)\u2014may also provide valuable information for\nuniversity faculty. Future research may also encompass interventions that\nrequire students to examine their own biases. Education on the various reasons\nfor overweight and obesity should be addressed in all programs. In addition,\ncommunication strategies should be discussed to educate kinesiology students on\nhow to support individuals (clients, primary school students, patients, etc.)\nwho struggle with exercise and physical activity settings due to their own negative\nbody image issues. <\/p>\n\n\n\n

Although this study is the\nfirst that the researchers are aware of that (a)\nexamines implicit weight bias among university students from a Hispanic Serving\nInstitution of various majors and (b) explores the implications of implicit anti-fat\nbias among kinesiology students, this project has four important\nlimitations. The first limitation is the small sample size. Although this\nstudy was conducted over a 12-week period and was\nadvertised across the university campus, only 62 students\nvolunteered to participate in this investigation; this might be indicative\nof the lack of interest in this subject matter among university\nstudents. The second limitation is that the study only\nexamined implicit attitudes at a diverse university \u2014 a regional,\nmostly-commuter, university that has the demographics of\na Hispanic Serving Institution (predominantly first-generation college\nstudents). The third limitation is the use of a volunteer\nsample accompanied by self-selection bias despite the fliers for\nthe study being displayed equitably across the university\ncampus. For example, the demographics characteristics clearly indicate that\nKinesiology students (70% of the participants) are much more likely to\nvolunteer for studies about BMI, body fat, and implicit weight\nbias when compared to non-Kinesiology students. Regardless, this\nselection bias was at least partially ameliorated by the fact that the\npercentage of female students (58%) and Hispanic students (72%) are similar to\nthose at the general university population (61% and 64%, respectively). \nLastly, the use of the WIAT test is accompanied by the limitation\nthat the test does not provide information\nabout actual behavior toward overweight individuals. Hence,\nit cannot be concluded that an implicit anti-fat bias will lead to poor\ntreatment of overweight individuals.<\/p>\n\n\n\n

CONCLUSION<\/strong><\/p>\n\n\n\n

Results from this investigation demonstrate\nan implicit anti-fat bias exists among the college students surveyed regardless\nof academic discipline, gender, ethnicity, race, body fat levels, BMI,\nexplicit anti-fat bias, prior struggles with body fat, or perceptions of\ntheir body. In agreement with other studies, society in general\nappears to have an implicit anti-fat bias. Although it is difficult to\ndraw a direct relationship between having an implicit anti-fat\nbias and treating overweight people poorly, studies have suggested that people\nwith a strong implicit anti-fat bias may treat overweight people\ndifferently than they do thin people. Since research indicates that negative\ntreatment toward overweight people negatively affects their\nself-esteem and their ability to lose excess body fat, it is imperative that\npeople working with the overweight population become aware of their potential\nimplicit and explicit anti-fat biases. If they can be conscientious\nof their biases, they may try to treat overweight people in the same\nmanner that they treat thin\npeople.        <\/p>\n\n\n\n

APPLICATION IN SPORT<\/strong><\/p>\n\n\n\n

This study has a\ndirect impact on all members of the higher education, healthcare, fitness, and\nphysical activity communities. This study demonstrates that weight bias is\nprevalent amongst a diverse population and may be indicative of a greater\nsocietal problem yet to be addressed. Future research should expand the\npopulation sample size and include more students from different ethnicities and\/or\nnationalities. Moreover, future studies could include students from different\nclass standings (e.g. undergraduate and graduate)\u2014comparing the rates of\nimplicit and explicit bias among them.  Current physical\neducators, healthcare professionals, fitness professionals,\nsport coaches, and university faculty preparing students\nfor these professions must begin to take\nthe steps necessary to eliminate weight bias from their environments. The\nauthors recommend that all members of the aforementioned communities develop an\nunderstanding of the factors that may lead to weight gain and develop\nstrategies of encouraging overweight individuals to reduce their weight without\nfurther perpetuating weight stigma. <\/p>\n\n\n\n

ACKNOWLEDGEMENTS<\/strong><\/p>\n\n\n\n

None<\/p>\n\n\n\n

REFERENCES<\/strong><\/p>\n\n\n\n

  1. Alameda, M. W., & Whitehead, J. R. (2015). Comparing levels of anti-fat bias between American and Mexican athletes and undergraduate physical education and exercise science students. The Physical Educator, 72<\/em>, 1-22.<\/li>
  2. American College of Sports Medicine. (2009). ACSM Guidelines for Exercise Testing and Prescription <\/em>(8th\u00a0<\/sup>ed., pp. 71-72). Philadelphia, MA: Lippincott Williams Wilkins.<\/li>
  3. Andreyeva, T., Puhl, \u00a0R. M., & Brownell, K. D. (2004). Changes in\u00a0perceived weight discrimination among Americans, 1995-1996 through 2004-2006.<\/em>\u00a0Obesity, 16<\/em>, 1129-1134.\u00a0<\/li>
  4. Chambliss, H. O., Finley, C. E., & Blair, S. N. (2004). Attitudes toward obese individuals among exercise science students. Medicine and Science in Sports and Exercise, 36<\/em>, 468-474.<\/li>
  5. Crandall, D. P. (2004). Knowing human moral knowledge to be true: An essay on intellectual conviction. Journal of the Royal Anthropological Institute,10<\/em>, 307-326.<\/li>
  6. Cunningham, W. A., Preacher, K. J.,\u00a0& Banaji,\u00a0M. H. (2001). Implicit attitude measures: Consistency, stability, and convergent validity. Psychological Science, 12<\/em>, 163-170.\u00a0<\/li>
  7. Diedricks, P. C., & Barlow, F. K. (2011). How to lose weight bias fast! Evaluating a brief anti weight bias intervention. British Journal of Health Psychology, 16<\/em>, 846-861.<\/li>
  8. Fardouly, J., & Vartanian, L.R. (2012). Changes in weight bias following weight loss: The impact of weight-loss method. International Journal of Obesity, 36<\/em>, 314\u2013319.<\/li>
  9. Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. (1998) Measuring individual differences in Implicit cognition: The implicit association test. Journal of Personality and Social<\/em> Psychology, 74<\/em>, 1464-1480.\u00a0<\/li>
  10. Greenwald, A.G., Poehlman, T.A., Uhlmann, E.L., & Banaji, M.R. (2009). Understanding and using the implicit association test: III. Meta\u2010analysis of predictive validity. J Pers Soc Psychol, 97<\/em>,17\u201041.<\/li>
  11. Hague, A. L., & White, A. A. (2005). Web-based intervention for changing attitudes of obesity among current and future teachers. Journal of Nutrition Education and Behavior, 37<\/em>, 58-66.<\/li>
  12. Hofmann, W., Gawronski, B.,\u00a0Gschwender,\u00a0T., Le, H., & Schmitt, M. (2005). A meta-analysis on the correlation between the implicit\u00a0association\u00a0test and explicit self-report measures Personal and Social<\/em> Psychology Bulletin, 31<\/em>, 1369-1385.\u00a0<\/li>
  13. Kerner, C., Haerens, L., & Kirk, D. (2017). Understanding body image in physical education: Current knowledge and future directions. European Physical Education Review. 24<\/em>, 255-265.<\/li>
  14. Latner, J. D., Stunkard, A. J. and Wilson, G. T. (2005), Stigmatized Students: Age, Sex, and Ethnicity Effects in the Stigmatization of Obesity. Obesity Research, 13: 1226-1231. doi:10.1038\/oby.2005.145<\/li>
  15. Mattingly, B. A., Stambush, M. A. and Hill, A. E. (2009). Shedding the Pounds but not the Stigma: Negative Attributions as a Function of a Target’s Method of Weight Loss. Journal of Applied Biobehavioral Research, 14<\/em>, 128-144. doi:10.1111\/j.1751-9861.2009.00045.x.<\/li>
  16. Miller, D. P., Jr, Spangler, J. G., Vitolins, M. Z., Davis, S. W., Ip, E. H., Marion, G. S., & Crandall, S. J. (2013). Are medical students aware of their anti-obesity bias? Academic medicine: journal of the Association of American Medical Colleges, 88(7), 978\u2013982. doi:10.1097\/ACM.0b013e318294f817<\/li>
  17. Nosek, B. A., Greenwald, A. G., & Banaji,\u00a0M. R. (2007). The implicit association test at age 7: A methodical\u00a0and conceptual review. In: J. A. Bargh (Eds.), Automatic processes in social<\/em> thinking and behavior<\/em> (pp. 265-292). <\/em>New York: Psychology Press.<\/li>
  18. O’Brien, K. S., Hunter, J. A., & Banks, M. (2007). Implicit anti-fat bias in physical educators: Physical attributes, ideology and socialization. International Journal of Obesity, 31<\/em>, 308-314.<\/li>
  19. Phelan, S. M., Dovidio, J. F., Puhl, R. M., Burgess, D. J., Nelson, D. B., Yeazel, M. W., Hardeman, R. , Perry, S. and Ryn, M. (2014), Implicit and explicit weight bias in a national sample of 4,732 medical students: The medical student CHANGES study. Obesity, 22,<\/em> 1201-1208. doi:10.1002\/oby.20687<\/li>
  20. Puhl, R. M., & Heuer, C. A. (2010). Obesity stigma: Important considerations for public\u00a0health. American Journal of Public Health, 100<\/em>, 1019\u20131028.\u00a0<\/li>
  21. Puhl, R. M., & Heuer, C, A. (2011). Public opinion about laws to prohibit weight discrimination in the United States.<\/em>\u00a0Obesity, 19<\/em>, 74-82.\u00a0<\/li>
  22. Puhl, R. M., Schwartz, M. B., & Brownell, K. D. (2005). Impact of perceived consensus on Stereotypes about obese people: A new approach for reducing bias. Health Psychology, 24<\/em>, 517-525.<\/li>
  23. Robertson, N., & Vohora, R. (2008). Fitness vs. fatness: Implicit bias towards obesity among fitness professionals and regular exercisers. Psychology of Sport and Exercise, 9<\/em>, 547-557.<\/li>
  24. Readdy, T., & Wallhead, T. L. (2016). Manifestation of anti-fat bias in preservice physical education teachers. The Physical Educator, 73<\/em>, 450-470.<\/li>
  25. Rukavina, P. B., Li, W., Shen, B., & Sun, H. (2010). A service learning based project to change implicit and explicit bias toward obese individuals in kinesiology pre-professionals. Obesity<\/em> Facts, 3<\/em>, 117-126.<\/li>
  26. Sabin, J. A., Maddalena, M., & Nosek, B. A. (2012). Implicit and explicit anti-fat bias among a large sample of medical doctors by BMI, race\/ethnicity, and gender. PLOS One, 7<\/em>(11),\u00a0\u00a0\u00a0\u00a0 \u00a0https:\/\/doi.org\/10.1371\/journal.pone.0048448<\/li>
  27. Schwartz, M.B., Chambliss, H.O., Brownell, K.D., Blair, S.N., & Billington, C. (2003). Weight bias among health professionals specializing in obesity. Obesity Research, 11<\/em>(9), 1033-9.<\/li>
  28. Schmukle, S. C., & Egloff, B. (2005). A latent state-trait analysis of implicit and explicit personality measures. European Journal of Psychological Assessment, 21<\/em>(2), 100\u2013107.<\/li>
  29. Sutin, A. R., & Terracciano, A. (2013). Perceived weight discrimination and obesity.<\/em>\u00a0PLoS One, 8<\/em>(7), https:\/\/doi.org\/10.1371\/journal.pone.0070048.<\/li>
  30. Teachman, B. A., & Brownell,\u00a0K. D. (2001). Implicit anti-fat bias among health professionals: Is anyone immune? International Journal of Obesity, 25<\/em>(10), 1525-1531.\u00a0<\/li><\/ol>\n","protected":false},"excerpt":{"rendered":"

    Authors: Guillermo Escalante1, Rafael Alamilla1, Eric Vogelsang2, Christopher Gentry1, Jason […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true,"jetpack_social_options":[]},"categories":[994,898],"tags":[191,1538,1537],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p4btio-1L4","jetpack-related-posts":[{"id":7848,"url":"https:\/\/thesportjournal.org\/article\/the-relationship-between-hip-extensor-strength-and-contralateral-and-ipsilateral-hip-flexor-muscle-length-in-healthy-men-and-women\/","url_meta":{"origin":6762,"position":0},"title":"The relationship between hip extensor strength and contralateral and ipsilateral hip flexor muscle length in healthy men and women","date":"April 9, 2021","format":false,"excerpt":"Authors: Ashley Calvillo1, Guillermo Escalante2, and Morey J. 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Do high-visibility\u2026","rel":"","context":"In "Contemporary Sports Issues"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":471,"url":"https:\/\/thesportjournal.org\/article\/an-exploratory-study-of-physical-activity-patterns-of-college-students-at-a-midwest-state-university-in-the-united-states\/","url_meta":{"origin":6762,"position":4},"title":"An Exploratory Study of Physical Activity Patterns of College Students at a Midwest State University in the United States","date":"November 16, 2012","format":false,"excerpt":"Dr. Lawrence Judge, David Bellar, Don Lee, Jeffrey Petersen, Elizabeth Wanless, Karin Surber, Rick Ferkel, and Laura Simon Abstract This study examines physical activity (PA) patterns in the context of global leisure activity of undergraduate students in a large Midwest state university. A sample of students (n = 253) from\u2026","rel":"","context":"In "Contemporary Sports Issues"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":1549,"url":"https:\/\/thesportjournal.org\/article\/the-relationship-between-racial-diversity-and-winning-percentage-a-study-of-mens-and-womens-basketball-teams-and-coaching-staffs-in-the-atlantic-coast-conference-from-2005-2009\/","url_meta":{"origin":6762,"position":5},"title":"The Relationship Between Racial Diversity and Winning Percentage: A Study of Men’s and Women’s Basketball Teams and Coaching Staffs in the Atlantic Coast Conference From 2005-2009","date":"February 3, 2014","format":false,"excerpt":"Submitted by Craig T. Bogar, Ed.D. ABSTRACT Much attention has been devoted to the need for and importance of racial diversity in society. Studies have been conducted in business and industry which indicate that racial diversity is a positive attribute that contributes to success and positive performance. In intercollegiate athletics,\u2026","rel":"","context":"In "Contemporary Sports Issues"","img":{"alt_text":"Screen Shot 2014-02-03 at 4.30.09 PM","src":"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2014\/02\/Screen-Shot-2014-02-03-at-4.30.09-PM.png?resize=350%2C200","width":350,"height":200},"classes":[]}],"_links":{"self":[{"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/posts\/6762"}],"collection":[{"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/comments?post=6762"}],"version-history":[{"count":10,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/posts\/6762\/revisions"}],"predecessor-version":[{"id":6775,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/posts\/6762\/revisions\/6775"}],"wp:attachment":[{"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/media?parent=6762"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/categories?post=6762"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/tags?post=6762"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}