Prevalence of Normal Weight Obesity Amongst Young Adults in the Southeastern United States

Authors: ¹Helena Pavlovic, ²Tristen Dolesh, ³Christian Barnes, ⁴Angila Berni, ⁵Nicholas Castro, ⁶Michel Heijnen, ⁷Alexander McDaniel, ⁸Sarah Noland, ⁹Lindsey Schroeder, ¹⁰Tamlyn Shields, ¹¹Jessica Van Meter, and ¹²Wayland Tseh*

¹Northern Kentucky University, Highland Heights, Kentucky, USA

AUTHORS INSTITUATIONAL AFFILIATION:

School of Health and Applied Human Sciences, University of North Carolina Wilmington, Wilmington, North Carolina, United States of America

Corresponding Author:

*CORRESPONDING AUTHOR:

Wayland Tseh, Ph.D.

University of North Carolina Wilmington

School of Health and Applied Human Sciences

601 South College Road

Wilmington, North Carolina, 28403-5956

Phone Number: 910.962.2484

E-Mail: [email protected]

ABSTRACT

‘Normal weight obesity (NWO) is characterized by a normal or low body mass index (BMI) alongside a high percentage of body fat, which increases the risk for hypokinetic diseases. This study aims to investigate the prevalence of NWO among a sample of young, non-sedentary adults. Two hundred and fifty-four apparently healthy volunteers (Age = 22.2 ± 7.2 yrs; Height = 171.5 ± 9.6 cm; Body Mass = 69.9 ± 13.4 kg) provided informed consent prior to participation. Body mass index was calculated by dividing body mass (kg) by height squared (m2). Body fat percentage was measured using the BODPOD® G/S, which utilizes air displacement plethysmography to accurately estimate body composition. Class I Obesity and Low/Normal BMI categorizations were defined by the American College of Sports Medicine. Data revealed that 12.2% of the overall sample exhibited NWO, with a higher prevalence among males (17.2%) compared to females (9.8%). The study also seeks to evaluate whether individuals with NWO face greater health risks than those with similar BMI but lower body fat percentages. From a practical perspective, identifying individuals with NWO is an opportunity for clinicians to proactively educate their clients regarding the health risks associated with hypokinetic disease(s).

KEYWORDS: Body Mass Index, BODPOD, Percent Body Fat, Normal Weight Obesity

INTRODUCTION

Within the United States, the prevalence of obesity has dramatically increased over the past 50 years given the ubiquitous obesogenic environment (31). In 2019, Ward and colleagues yielded compelling predictive insights indicating a trajectory wherein, by the year 2030, nearly 50% of adults will be afflicted by obesity (48.9%) with heightened prevalence exceeding 50% in 29 states, demonstrating a pervasive nationwide trend (50). Moreover, no state is anticipated to exhibit a prevalence below 35% (50). Projections also indicate that a substantial proportion of the adult population is anticipated to experience severe obesity, with an estimated 24.2% affected by 2030 (50). Against this backdrop, the predictive analyses conducted by Ward and associates (50) underscored the widespread and escalating severity of the obesity epidemic across the United States. These findings are indicative of an impending public health challenge, necessitating strategic interventions and policy considerations to mitigate the escalating burden of obesity and its associated health implications. When delineating the magnitude of obesity, clinicians and practitioners must employ precise instrumentation capable of quantifying a client’s body composition in terms of percentage body fat. Numerous methodologies exist for this purpose, encompassing hydrostatic weighing, bioelectrical impedance analysis, air displacement plethysmography, skinfold assessment, and dual-energy x-ray absorptiometry scan.

Drawing from antecedent research studies, dual-energy X-ray absorptiometry (DXA) is acknowledged as the clinical gold standard for appraising body composition (9, 10, 12, 21, 25, 26, 42, 47). However, a notable drawback of DXA lies in its emission of low-level radiation (6, 9, 32, 45, 47), thereby subjecting clients to unnecessary radiation exposure (1, 33). An alternative method is utilizing the BOD POD® Gold Standard (GS), which employs air displacement plethysmography to estimate body composition. Previous literature has heralded the BOD POD® GS as the applied, pragmatic gold standard for assessing body composition due to its validity (2, 7, 38), as well as its within- and between-day reliability (48). Additionally, owing to the BOD POD® GS’s facile and non-invasive procedures, most individuals can attain accurate measures of body composition values, specifically pertaining to percent body fat, enabling the discernment of pounds of fat-free mass and fat mass.

According to the American College of Sports Medicine (ACSM), males with a percent body fat ≥ 25% and females ≥ 32% (4) are predisposed to an elevated risk of developing a myriad of hypokinetic diseases, notably cardiovascular disease(s), metabolic syndrome, and cardiometabolic dysfunction (14, 27, 35, 37, 39, 40, 43, 44, 46, 51, 56). Another evaluative approach involves the calculation of Body Mass Index (BMI), derived from dividing body weight in kilograms by square of height in meters (4). Given the ease and efficiency of calculating BMI, the obesity-related classification in which it provides at the individual level is potentially flawed (3, 8, 22, 24, 41, 53, 56).

Presently, within the United States, a dearth of research exists on the prevalence of normal weight obesity (NWO) amongst apparently healthy young adults (11,52). Normal weight obesity is characterized by individuals exhibiting a low BMI (<18.5 kg∙m-2) or normal BMI (18.5 – 24.9 kg∙m-2) yet manifesting obesity-related percentage body fat values (male = ≥20%; female = ≥30%) (5, 14, 20, 36, 37, 40, 43, 44, 57). Individuals with low/normal BMI and high percentage body fat values face an augmented risk of hypokinetic diseases, as their seemingly normal exterior masks a deleteriously high amount of body fat beneath the surface layer. Previous research endeavors have revealed the prevalence of NWO amongst a population of South Americans (14, 34, 40, 44), Central Europeans (15), and Asians (28-30, 37, 54, 55, 57, 58). Given that most aforesaid research studies on NWO have been conducted internationally, it is of paramount interest to ascertain the prevalence of NWO domestically. Consequently, the primary objective of this research study is to investigate the prevalence of normal-weight obesity among a sample of ostensibly healthy males and females.

METHODS

Participants

All participants were required to report to the Body Composition Laboratory to complete a singular session. Before the participants arrived, volunteers were instructed to abstain from consuming caffeinated sustenance or beverages that may acutely influence body mass. Moreover, researchers advised participants to refrain from vigorous physical activity/exercise the night before and prior to their appointed session. Upon arrival, volunteers read and signed an informed consent form approved by the University’s Institutional Review Board for human subject use (IRB#: H23-0499). As displayed in Table 1, a cohort comprising 254 male and female volunteers were recruited to participate in this study.

Table 1. Descriptive characteristics (Mean ± SD) of all male and female participants (N = 254).

Variables	Overall (N = 254)	Male (n = 101)	Female (n = 153)
Age (yrs)	22.2 ± 7.2	22.5 ± 7.7	22.0 ± 6.8
Height (cm)	171.5 ± 9.6	179.5 ± 7.2	166.2 ± 7.0
Body Mass (kg)	69.9 ± 13.4	79.9 ± 11.6	63.2 ± 10.0

Below highlights the details of the singular Session required for each participant.

Body Mass Index (BMI)

Before each assessment, participants were asked to remove any unattached item(s) from their body, such as shoes, socks, rings, bracelets, and/or glasses. Height was measured to the nearest 0.5 cm as participants stood barefoot, with both legs together, with their back to a Seca 217 Mobile Stadiometer (Model Number 2171821009, USA). Body mass was measured on a Tanita Multi-Frequency Total Body Composition Analyzer with Column (Model DC-430U, Tanita Corporation, Japan) to the nearest 0.1 kg. Body mass index was calculated using body mass expressed in kilograms (kg) divided by height expressed in meters squared (m2). Body mass index categorizations, set forth via ACSM (4), for low BMI was (<18.5 kg∙m-2) and normal BMI was (18.5 – 24.9 kg∙m-2).

BOD POD® Gold Standard (GS)

BOD POD® Gold Standard (GS) (COSMED USA Inc., USA) was calibrated daily according to the manufacturer’s instructions with a 50.238 Liter cylindrical volume provided by COSMED USA Inc. Specific details illustrating the technicalities of the calibration mechanism are published elsewhere (16, 18). Because different clothing schemes have been shown to underestimate percentage body fat (%BF) results from the BOD POD® (19, 49), female participants were instructed to wear one- or two-piece bathing suit or sports bra and compression shorts, while male participants were instructed to wear form-fitted compression shorts. All participants wore a swim-like cap provided by COSMED USA Inc. After race, height, and age were inputted by a technician into the BOD POD® GS kiosk, participants were asked to step on an electronic scale to determine body mass to the nearest .045 kg. Once the BOD POD® GS system recorded body mass, participants were instructed to sit comfortably and breathe normally within the BOD POD® GS for two trials lasting 40 seconds per trial. A third trial was conducted if Trials 1 and 2 had high variability. Once both (or three) trials were conducted, body composition values, specifically, body mass, percent body fat, fat-free mass, and fat mass, were immediately displayed on the kiosk viewer and recorded by a technician. Once height, body mass, and body composition assessments were completed, participants dressed back into their original clothing and exited the Body Composition Lab.

Statistical Analyses

Descriptive statistics (mean ± SD) were derived to describe the sample population. A Chi-Square Goodness of Fit Test was used to determine the prevalence of low/normal BMI values with obesity-related percent body fat. For all analyses, statistical significance was established at p < 0.05.

RESULTS

At the conclusion of the study, 254 volunteers were recruited, and zero dropped out, therefore, all 254 participants’ results were included in the statistical analyses. Table 2 displays the descriptive measures of the study participants.

Table 2. Body Mass Index, Class I Obesity, and Percent Normal Weight Obesity Amongst Males and Females.

	Total	Male	Female
Participants	254	101	153
Low BMI (≤ 18.4 kg∙m^-2)	2	0	2
Normal BMI (18.5 – 24.9 kg∙m^-2)	181	58	123
Class I Obesity (F ≥ 32%; M ≥ 25%)	22	10	12
Masked Obesity	12.2%	17.2%	9.8%
High BMI (≥ 25.0 kg∙m^-2)	71	43	28

The chi-squared statistic was 1.886 (df = 1, p = 0.17) indicating no statistical difference in NWO between males (17.2%) and females (9.8%).

DISCUSSION

As stated previously, there is a dearth of data determining the prevalence of NWO domestically, more specifically, within the southeast region of the United States. Therefore, the primary objective of this research study was to investigate the frequency of NWO amongst a sample of apparently healthy individuals. Participants completed a singular data collection session whereby height, body mass, and percentage body fat were quantified via BOD POD® GS. Within this current study, low and normal BMI classifications were <18.5 kg∙m-2 and 18.5 – 24.9 kg∙m-2, respectively. Class I obesity for females and males were ≥ 32% and ≥ 25%, respectively. Given said thresholds, data revealed that 12.2% of the overall sample exhibited NWO, with a higher prevalence amongst males (17.2%) compared to females (9.8%). These findings are relatively comparable within other research investigating the prevalence of NWO amongst a sample of young adults (5, 35, 44, 57).

In 2017, Ramsaran and Maharaj investigated the prevalence of NWO within a cohort of 236 young adults (mean age = 21.3 ± 2.5 years). The quantification of %BF was accomplished using the Tanita Ironman body composition analyzer. Subsequent data analyses unveiled a heightened prevalence of NWO among the male participants (14.4%), surpassing their female counterparts (5.5%). The outcomes of the current study align with the findings reported by Ramsaran and Maharaj (44), wherein NWO manifested in 17.2% of males and 9.8% of females. A nuanced distinction between the two investigations lies in the designated thresholds for %BF. Ramsaran and Maharaj (44) set the elevated %BF thresholds at ≥ 23.1% for males and ≥ 33.3% for females. In contrast, the current study employed thresholds of ≥ 25.0% for males and ≥ 32.0% for females. Notwithstanding the marginal elevation (+1.9%) in the %BF threshold within the current study, males exhibited a greater prevalence (+2.8%) compared to Ramsaran and Maharaj’s (44) dataset. Conversely, the current study adopted a lower %BF threshold (–1.3%) for females and uncovered a higher prevalence of NWO (+4.4%). These subtle yet discernible variations in %BF thresholds may elucidate the divergent prevalence rates of NWO observed between the two scholarly investigations.

Akin to Ramsaran and Maharaj (44) and the present investigation, Anderson and colleagues (5) examined the incidence of NWO within a more modest cohort of 94 young adults (mean age = 19.6 ± 1.5 years). The quantification of %BF was assessed via DXA. The %BF thresholds were predicated on National Health and Nutrition Examination Survey standards, establishing obesity values of ≥ 30.0% for males and ≥ 35.0% for females. Findings elucidated an NWO prevalence in males (26.7%) and females (7.8%). Noteworthy is the marked elevation in male NWO rates (+9.5%) and marginal reduction (–2.0%) in female NWO rates compared to the current study. While discrepancies may be attributed to variances in sample size (254 in the present study vs. 94 in Anderson et al.), divergent methodologies for %BF assessment (utilizing BOD POD® GS presently as opposed to DXA in Anderson et al.), and distinct %BF thresholds (ACSM criteria in the current study versus NHANES in Anderson et al.), the overarching findings remain concordant. Specifically, data from all three research investigations underscore the consistent pattern wherein males manifest elevated NWO prevalence rates relative to their female counterparts.

In contradistinction to the two previous research investigations and the current study, Zhang et al. (57) explored the NWO prevalence amongst 383 young adults (mean age = 20.4 ± 1.6 years). Assessment of %BF was executed through bioelectrical impedance analyses (BIA) employing the InBody 720 device. Obesity classification was contingent upon threshold values of ≥20.0% for males and ≥30.0% for females, as established by Zhang and associates (57). Analyses unveiled an NWO prevalence of 13.2% in males and 27.5% in females, a prominent deviation from the present study’s findings. The contrasting NWO prevalence patterns observed between the two studies are notably discernible. Specifically, Zhang and colleagues (57) reported a higher prevalence in females than males, whereas the current investigation revealed the converse. This discordance is seemingly attributable to variances in the %BF thresholds implemented for obesity classification. Zhang et al. (57) utilized a considerably lower threshold for males at 20.0%, as opposed to the 25.0% threshold applied in the current study. Similarly, for females, Zhang et al. (57) employed a lower %BF threshold at 30.0%, whereas the present study utilized a more conservative threshold of 32.0%. Moreover, a salient methodological distinction lies in the apparatus employed for %BF quantification. The current study utilized the BOD POD® GS, acknowledged as the applied gold standard for assessing body composition, while Zhang et al. (57) employed the InBody 720 BIA. These methodological nuances likely contribute to the divergent findings between the present research and Zhang et al. (57), underscoring the importance of rigorously evaluating both threshold criteria and assessment modalities when interpreting and comparing NWO prevalence data.

In a recent investigation, Maitiniyazi et al. (35) endeavored to ascertain the prevalence of NWO within a cohort of 279 young adults (mean age = 21.7 ± 2.1 years). Percentage body fat was assessed utilizing the InBody 770 BIA method. Obesity classification thresholds were established at 20.0% for males and 30.0% for females. Parallel to the observed NWO patterns delineated by Zhang and colleagues (57), Maitiniyazi et al. also discerned a higher prevalence of NWO in females (40.1%) as opposed to males (25.5%). Notably, while these NWO trends align with the patterns identified by Zhang et al. (57), they markedly deviate from the outcomes of the current investigation. Such discordant findings may find elucidation in the nuanced disparities in the thresholds employed to categorize obesity and the instrumentation deployed for %BF quantification. Specifically, the divergence in %BF thresholds used for obesity classification emerges as a significant factor. Maitiniyazi et al. (35) employed thresholds different from those of Zhang et al. (57) and the current study, thereby contributing to the observed inconsistencies. Additionally, the equipment utilized to quantify %BF introduces another layer of methodological variation. While Zhang et al. (57) implemented InBody 720 BIA and the current study utilized BOD POD® GS, Maitiniyazi et al. deployed the InBody 770 BIA method. These divergent methodological approaches underscore the imperative of meticulous consideration when interpreting and comparing NWO prevalence data, highlighting the multifaceted nature of the interplay between obesity thresholds and assessment methodologies in elucidating NWO prevalence.

CONCLUSIONS

This comprehensive investigation contributes significantly to our understanding of NWO prevalence within a young adult population, particularly within the Southeast region of the United States. The study employed the BOD POD® GS for precise measurement of height, body mass, and percentage body fat, revealing a higher, but not statistically different, prevalence in NWO between males and females. These results align with similar studies collectively emphasizing the consistent pattern of elevated NWO prevalence in males relative to females. The study’s alignment with said research investigations further underscores the robustness of the findings, notwithstanding variations in sample size, methodology, and threshold criteria. Conversely, discrepancies with other research investigations highlight the sensitivity of NWO prevalence to %BF thresholds and assessment modalities. Despite the divergence in outcomes, these studies collectively reinforce the need for careful consideration of methodological nuances in interpreting and comparing NWO prevalence data.

APPLICATION IN SPORTS

From a practical perspective, the findings emphasize the importance of incorporating regional and demographic variations when assessing NWO prevalence. Furthermore, the study underscores the relevance of employing standardized methodologies in ensuring consistency and comparability across investigations. Future endeavors in this domain should continue to explore regional variations, refine %BF threshold criteria, and employ advanced methodologies for accurate NWO characterization. This knowledge is pivotal for tailoring preventive measures and interventions; more precisely, accurately identifying NWO individuals is an opportunity for clinicians to proactively educate their clients regarding the health risks associated with hypokinetic disease(s), particularly cardiovascular disease(s), metabolic syndrome, and cardiometabolic dysfunction.

ACKNOWLEDGMENTS

The author would like to personally thank the following research assistants that contributed to the success of this research investigation: Tristen, Brennan, Marisa, Maddie, Samantha, Caylin, and Ethan.

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George Minoso2024-10-24T15:50:50-05:00October 25th, 2024|Research, Sports Health & Fitness, Sports Nutrition|Comments Off

Low Energy Availability (LEA) in Male Athletes: A Review of the Literature

Authors:Brandon L. Lee¹

¹The Department of Exercise, Health, and Sport Sciences, Pennsylvania Western University

Corresponding Author:

Brandon L. Lee, MS, RD, CCRP
10263 4th Armored Division Dr.
Fort Drum, NY 13603
[email protected]
315-772-0689

Brandon L. Lee, MS, RD, CCRP is a Holistic Health and Fitness (H2F) Dietitian for the U.S. Army Forces Command and a Doctor of Health Science (DHSc) student at Pennsylvania Western University. Brandon’s research interests include energy systems and metabolism, energy availability, andragogical methods for adult learning, and reflective practice to enhance learning in formal education..

ABSTRACT

Purpose: Low energy availability (LEA) is a physiological state when there is inadequate energy to meet the demands placed on the body, often through physical activity, exercise, or sports. LEA can impact any athlete engaged in a sport with low energy intake or excessive energy expenditure. LEA is a precursor to the onset of The Male Athlete Triad (MAT) and Relative Energy Deficiency in Sport (RED-S). There is no defined low energy availability threshold specific to male athletes engaged in high-energy expenditure sports leading to MAT and RED-S. This literature review evaluates the literature on the relationship between LEA and signs or symptoms of MAT and RED-S to establish a low energy availability threshold specific to male athletes engaged in high-energy expenditure sports.

Methods: The Pennsylvania Western University library electronic database was used for the literature search. Search terms included “male athletes”, “low energy availability”, “male athlete triad”, “relative energy deficiency in sport”, and “energy deficiency”. Research studies included cross-sectional, experimental, systematic reviews, meta-analyses, case studies, and some narrative and literature reviews. Studies must have been peer-reviewed and published within five years of the literature search (12/2018- 12/2023).

Results: A review of the literature shows that it is difficult to determine a LEA threshold due to present research gaps and inconsistent findings related to health and performance consequences. Based on the results of experimental studies, practitioners can expect an LEA threshold of 20-25kcal per kilogram (kg) of fat-free mass (FFM) per day in male athletes engaged in high energy-expenditure sports.

Conclusions: Athletes engaged in sports that lead to inadequate energy intake or high energy expenditure are at risk for LEA, MAT, and RED-S. Experimental research on the LEA threshold in athletes engaged in physiologically demanding sports is the greatest research gap. Based on present findings, male athletes may have an LEA threshold of <30kcal/kg of FFM/day.

Applications in Sport: Healthy nutritional practices are essential to sports performance. Interdisciplinary sports performance teams must collaborate with nutrition professionals to develop effective LEA prevention, screening, and intervention protocols.

Keywords: energy intake, energy deficiency, energy expenditure of exercise, male athlete triad, relative energy deficiency in sport, sports nutrition

Low Energy Availability (LEA) in Male Athletes: A Review of the Literature

Energy availability (EA) is the energy dedicated to body system functions. In sports nutrition, energy availability is defined as the amount of energy remaining to support an athlete’s bodily functions after energy expenditure of exercise (EEE) is deducted from energy intake (EI) (2). Health and athletic performance issues arise when athletes have inadequate energy intake or excessive energy expenditure, depleting their EA. The designated term for this is low energy availability (LEA). LEA is defined as a physiological state when there is inadequate energy to meet the demands placed on the body, often through physical activity, exercise, or sports (23). Causes of LEA include obsessive causes (disordered eating or eating disorders), intentional causes (attempts to modify body mass or composition), and inadvertent causes (byproduct of high EEE) (1).
LEA can impact any athlete engaged in a sport with low energy intake or excessive energy expenditure. LEA is most common in sports of high intensity, duration, volume, or frequency and in sports that emphasize low body weight/fat, aesthetics, or thinness, including distance cycling and running, triathlons, tactical (i.e., military), swimming, gymnastics, wrestling, bodybuilding, martial arts, boxing, soccer, tennis, rowing, horse racing, and volleyball. LEA is a precursor to the onset of both The Male Athlete Triad (MAT) and Relative Energy Deficiency in Sport (RED-S), two conditions that result in weakened physiological functions, with the former focused on reproductive and bone health decline (22). The problem is the prevalence of LEA among male athletes participating in high-energy expenditure sports, leading to potential health and performance issues. Additionally, there is no defined low energy availability threshold specific to male athletes engaged in high-energy expenditure sports leading to MAT and RED-S (3, 4, 5, 9, 11, 14, 17, 22, 26).
This literature review aims to evaluate the literature on the relationship between LEA and signs or symptoms of MAT and RED-S to establish a defined low energy availability threshold specific to male athletes engaged in high-energy expenditure sports. This literature review will report on LEA’s impact on health, body composition, athletic performance; establish LEA thresholds, and address research gaps.

RELATIVE ENERGY DEFICIENCY IN SPORT (RED-S)
LEA is a common precursor to many health and athletic performance issues. In 2014, the International Olympic Committee (IOC) developed a consensus statement titled “Beyond the Female Athlete Triad: Relative Energy Deficiency in Sport (RED-S)” and established RED-S as a new condition that refers to diminished physiological processes due to relative energy deficiency. The most current IOC RED-S models show that RED-S can impact the following systems: immunological, menstrual/reproductive function and bone health (related to athlete triad), endocrine, metabolic, hematological, growth and development, psychological, cardiovascular, and gastrointestinal. Moreover, another IOC RED-S model shows the potential performance effects of RED-S, including decreased endurance performance, increased injury risk, decreased training response, impaired judgment, decreased coordination, decreased concentration, irritability, depression, decreased glycogen stores, and decreased muscle strength (19). Much of the research on the impact of LEA and the cascade of events that lead to RED-S has primarily been conducted on female athletes, and the findings are extrapolated to their male counterparts; however, this is changing.

MALE ATHLETE TRIAD
The Male Athlete Triad (MAT) was first introduced in the 64th Annual Meeting of the American College of Sports Medicine (ACSM) in 2017 (6). MAT has comprised three essential components: LEA (sometimes referred to as energy deficiency), impaired bone health, and suppression of the hypothalamic-pituitary-gonadal (HPG) axis (22).
Prevention and treatment methods of MAT hinge on the EA or energetic status of the athlete at risk. Nattiv et al. (2021) explain that energy deficiency or LEA is confirmed when one of the following metabolic adaptations is presented: reduced RMR compared to body size or fat-free mass (FFM), unintentional weight loss resulting in a new low set point, underweight body mass index (BMI), and reduced metabolic hormones such as triiodothyronine (T3), leptin, and several more. Hypogonadotropic hypogonadism can manifest as oligospermia (deficiency of sperm in the semen) or decreased libido (reduced sexual drive). Lastly, poor bone health can manifest as osteopenia, osteoporosis, or bone stress injury (22).
The energetic status of the athlete can vary greatly depending on frequency, intensity, duration, type of sport, volume, and progression. Nattiv et al. (2021) have surmised that male athletes engaged in leanness sports typically have low energy intake compared to recommended amounts from the Institute of Medicine Daily Recommended Intakes or Food and Agriculture Organization of the United Nations/World Health Organization. Unfortunately, male leanness sports or weight-class athletes potentially consume up to 1000kcal/day less than required to support their exercise demands (22). Athletes consistently at risk for MAT include runners and cyclists, primarily if they compete in long-distance competitions.

Cardiovascular Health
Cardiovascular health (CVH) is essential to every athlete engaged in any sport. A healthy cardiovascular system effectively moves blood from one location to another to transport oxygen-containing blood cells for muscular activity. Langan-Evans et al. (2021) studied the impact of incorporating daily fluctuations in LEA on cardiorespiratory capacity via treadmill test in one combat athlete preparing to make weight for competition. The athlete experienced microcycle EA fluctuations ranging from 7 to 31 kcal per kilogram (kg) of FFM/day (mean EA of 20kcal/kg of FFM/day) for seven days and did not experience any significant changes in resting heart rate, cardio output, or overall CVH (14). Theoretically, LEA would have significant structural, conduction, repolarization, and peripheral vascular effects on CVH (17). However, a scant amount of research establishes any correlation between CVH and LEA, and primary research studies conducted within the past five years have yet to establish causation between the two.
On the other hand, Fagerberg (2018) has found that EA <25kcal/kg FFM over six months in bodybuilders preparing for a competition can impact CVH by reducing heart rate. According to Fagerberg (2018), low body fat percentages in bodybuilders worsen CVH risk (4). This heart rate reduction, paired with low body fat, is likely a physiological adaptation to conserve energy and sustain life. There needs to be more consistency in the literature regarding the impact of LEA on CVH.

Physiological Health
LEA and RED-S are both physiological and psychological health risks. Sports that emphasize leanness (e.g., cycling) or have weight divisions (e.g., combat sports) often place additional mental stress on athletes to perform well and possess a specific physique. For example, Schofield et al. (2021) found that male cyclists are at risk for LEA and RED-S due to rigid weight management practices, desire for leanness, disordered eating and eating disorders, and body dissatisfaction (26).
Elevating psychological health is commonly conducted via a questionnaire or interview. Langbein et al. (2021) explored the subjective experience of RED-S in endurance athletes through semi-structured, open-ended interviews. The first male participant commented on hitting “rock bottom” and the body’s sensitivity to energy intake changes. In addition, the other male athlete appeared to have a transactional relationship with food and exercise, void of any joy or performance goals. Both male athletes reported negative psychological consequences regarding RED-S; these consequences included increased rates of irritability because they were obsessed with food and exercise and feelings of helplessness and despair (15).
Perelman et al. (2022) also examined the male athlete’s psychological state by evaluating and intervening on body dissatisfaction, drive for muscularity, body-ideal internalization, and muscle dysmorphia. Male athlete participants (n=79) were from various sports, including baseball, golf, soccer, swimming, track and field, volleyball, and wrestling. The results showed that group sessions focused on reframing ideal body perception, the consequences of RED-S, encouraging positive self-talk, and reviewing strategies to modify energy balance healthfully can significantly reduce body dissatisfaction, body-ideal internalization, and drive for muscularity (p < .05) (24). The results demonstrate the value of understanding, supporting, and guiding an athlete’s psychological state toward personal health and satisfaction.

Reproductive Health
Functional hypogonadotropic hypogonadism is one of the three primary pillars of the MAT. LEA can induce disruptions to the hypothalamic-pituitary-gonadal (HPG) axis, resulting in functional hypogonadotropic hypogonadism. Signs of hypogonadotropic hypogonadism include (1) reductions of testosterone (T) and luteinizing hormone (LH), (2) decreased T and responsiveness of gonadotropins to gonadotropin-releasing hormone (GnRH) stimulation after training, (3) alterations in spermatogenesis, and (4) self-reported data on decreased libido and sexual desire (22). Most current research studies examine free and total T as an indicator of HPG axis suppression. Lundy et al. (2022) categorize low total T (<16nmol/L) and low free T (<333 pmol/L) as primary indicators for LEA (16).
A significant contribution to this area comes from the work by Jurov et al. (2021) who conducted a non-randomized experimental study with a crossover design to investigate the reproductive health impacts of progressively reducing EA by 50% for 14 days in well-trained and elite endurance male athletes. The results demonstrated a positive correlation between T levels and measured EA; as EA declined, so did T (9).
The empirical evidence on the causal relationship between LEA and T has been growing over recent years, with studies such as one conducted by Dr. Iva Jurov and colleagues. In three progressive steps, their quasi-experimental study reduced EA (via increasing EEE and controlling EI) in well-trained and elite male endurance athletes. Participants had statistically significant T changes starting at the 50% EA reduction phase with a mean EA of 17.3 ± 5.0kcal/kg of FFM/day for 14 days (p < 0.037). Furthermore, T levels continued to significantly decline at 75% EA reduction phase with a mean EA of 8.83 ± 3.33 for ten days (p < 0.095) (10). Conversely, in another quasi-experimental study by Jurov et al. (2022b), endurance male athletes had their EA reduced by 25% by increasing EEE and controlling EI for 14 days. The mean EA was 22.4 ± 6.3kcal/kg of FFM/day. The results show no significant changes to T levels, potentially indicating that a greater EA reduction was required to induce change (11).
Stenqvist et al. (2020) conducted four weeks of intensified endurance training designed to increase aerobic performance and determine the impact of T and T: cortisol ratio on well-trained male athletes. After the four weeks of intensified endurance training, the results showed that total T significantly increased by 8.1% (p=0.011) while free T (+4.1%, p=0.326), total T: cortisol ratio (+1.6%, p=0.789), and free T: cortisol ratio (-3.2%, p=0.556) did not have significant changes when compared to baseline (27). It is complex to determine the EA threshold defined by HPG axis suppression. Research on LEA and suppression of the HPG axis (i.e., T reduction) have demonstrated varied results based on athlete EA study design features (e.g., high EEE intensity or low EI duration); however, endurance athletes remain at the highest risk (18, 22, 26).

Bone Health
The last pillar of the MAT is osteoporosis with or without bone stress injury (BSI). Impaired bone health is most common in athletes in sports that have low-impact loading patterns, such as cycling, swimming, or distance running. Bone mineral density (BMD) is the primary measurement method to evaluate overall bone health and risk for osteoporosis. Dual-energy x-ray absorptiometry (DXA) is the gold standard for assessing bone density, but quantitative computed tomography (QCT) is also emerging as an equally acceptable alternative. In outpatient or rehabilitation settings, frequency of DXA scans is recommended no sooner than every ten months to allow for detectable changes in bone mineral density (17).
Risk factors for low BMD include LEA, low body weight (<85% of ideal body weight), hypogonadism, running mileage >30/week, and a history of stress fractures (22). In addition to BMD, other indicators of bone health include bone mineral content (BMC), markers of bone formation including β-carboxyl-terminal cross-linked telopeptide of type I collagen (β-CTX), bone alkaline phosphatase, and osteocalcin, and markers of bone resorption including amino-terminal propeptide of type-1 procollagen (P1NP), tartrate-resistant acid phosphatase, and carboxy-terminal collagen cross-links (4, 17). Studies will occasionally implement biomarkers such as Vitamin D and calcium to evaluate dietary intake and risk of BSI or osteoporosis.
What is the prevalence of low BMD in athletes? Tam et al. (2018) evaluated the bone health and body composition of elite male Kenyan runners (n=15) compared to healthy individuals. The results showed that 40% of Kenyan runners have Z-scores indicating low bone mineral density in their lumbar spine for their respective age (z-score <−2.0). This study did not measure energy availability with bone mineral density (29). However, based on previous research, low bone mineral density may have LEA origins.
Heikura et al. (2018) studied the BMD of middle- and long-distance runners and race walkers and found that athletes had an LEA (21kcal/kg of FFM/day) (7). Athletes with a moderate EA generally had better z-scores than the LEA athletes; however, the differences were not statistically significant. Similarly, Õnnik et al. (2022) found that high-level Kenyan male distance runners had an average EI of 1581kcal, and male controls had an average EI of 1454kcal per day. The male athletes did not show a statistically significant difference in BMD (p = 0.293) compared to the male control group, with only one runner (out of 20) at risk for osteoporosis (lumbar spine z-score <1.0) (23).
Cyclists are at the highest risk for poor bone health due to chronic LEA, reduced osteogenic simulation, and low levels of impact or resistance (26). Keay et al. (2018) assessed the efficacy of a sport-specific EA questionnaire and clinical interview (SEAQ-I) in British professional cyclists at risk of developing RED-S. Based on the results of the SEAQ-I, 28% (n=14) were identified with LEA, and 44% of the cyclists had low lumbar spine BMD (z-score <-1.0) (p< 0.001). Also, cyclists with a history of lack of load-bearing sports or activities had the lowest BMD (p= 0.013) (13). This study demonstrates a clear association between LEA and reduced lumbar spine BMD in professional cyclists.
In a randomized controlled trial, Keay et al. (2019) investigated the efficacy of an educational intervention with British competitive cyclists to improve energy availability and bone health. The researchers induced LEA by 25% (mean EA of 22.4 ± 6.3kcal/kg of FFM/day) for 14 days. Athletes who implemented nutritional strategies (provided by nutrition professionals) to improve EA and strength training strategies to improve skeletal loading saw lumbar spine BMD improvements. Mean vitamin D levels significantly improved from pre-season (90.6 ± 23.8 nmol/L) to post-season (103.6nmol/L; p=0.0001). Calcium, correct calcium, and alkaline phosphatase had no statistically significant changes between pre-season and post-season (12). Keay et al. have established the prevalence of LEA and poor bone health in cyclists and demonstrated nutrition education efficacy for BMD improvements. Noteworthy findings such as these help to raise awareness in the cycling community and can inform preventative or rehabilitative strategies.

BODY COMPOSITION
Body composition is the distinction between fat mass and fat-free mass. Fat-free mass includes water, tissue, organs, bones, and muscle (e.g., skeletal muscle). Body composition control and maintenance are essential for an athlete’s health, performance, and mindset. Research measurements of body composition include weight, body mass index, body fat percentage, lean mass, and water content. According to Lundy et al. (2022), a body mass index <18.5 kg/m2 is a primary indicator of LEA; this suggests body composition changes in response to LEA (16).
What is the impact of LEA on body composition? Stenqvist et al. (2020) implemented a four-week intensified endurance training designed to increase aerobic performance and elevate body composition’s impact on well-trained cyclists. The results did not show statistically significant changes in energy intake, body weight, fat mass, or fat-free mass. Body weight loss was potentially averted due to reduced resting metabolic rate as a protective mechanism (27). Whereas Stenqvist et al. (2020) focused on increasing EEE, Jurov et al. (2021) attempted to induce LEA via EI manipulation. Jurov et al. (2021) progressively reduced EA by 50% for 14 days in well-trained and elite endurance male athletes; the results showed no significant changes in body mass and fat-free mass (9).
Regarding resistance training and LEA, Murphy and Koehler (2022) conducted a meta-analysis to quantify the discrepancy in lean mass accretion between interventions providing resistance training in an energy deficit and those without an energy deficit. The literature findings demonstrated lean mass gains impairment in athletes resistance training in an energy deficit compared to those training without an energy deficit (significantly, p = 0.02). The results also surmised that an energy deficit of as much as 500kcal/day could impede lean mass gains (21).
Roth et al. (2023) evaluated the impact of a relatively high- versus moderate volume resistance training program on alterations in lean mass during caloric restriction in male weightlifters. The results showed that whole-body lean mass significantly declined in both groups (high and moderate volume groups) following six weeks of energy restriction. The high-volume group had an EA of 31.7 ± 2.8kcal/kg of FFM/day, and the moderate-volume group had an EA of 29.3 ± 4.2kcal/kg of FFM/day (25). Both studies demonstrate that muscle hypertrophy is unattainable in the presence of LEA.
Furthermore, Murphy and Koehler (2020) found that three days of caloric restriction at an EA of 15kcal/kg of FFM/day in recreational weightlifters resulted in significant reductions in weight (p<0.01), fat mass (p<0.01), and lean mass (p<0.001). Also, the total mass loss was significant (p<0.01) when compared to a control group (EA of 40kcal/kg of FFM/day) (20). The results of studies focused on resistance training and caloric restriction hold applicability for athletes in sports that rely on lean mass gains while manipulating EI, such as bodybuilding (4).

CARDIORESPIRATORY ENDURANCE
Cardiorespiratory endurance (CRE) is the ability of the lungs, heart, and blood vessels to deliver sufficient oxygen to cells to meet the physiological demands of exercise and physical activity (8). Evaluating maximal oxygen uptake or VO2max is a standard CRE measure. A VO2 max of 67.9 ± 7.4 mL/kg/min is categorized as a high fitness level (28).
What is the impact of induced LEA on CRE performance outcomes? Jurov et al. (2021) investigated the endurance performance impact of progressively reducing energy availability by 50% for 14 days in well-trained and elite endurance male athletes. The researchers increased EEE to achieve a mean energy availability of 17.3 ± 5 kcal/kg of FFM/day. The results showed lowered EA reduced endurance performance, as indicated by respiratory compensation point (RC) and VO2max. Jurov et al. (2022b) reduced EA by 25% (by increasing EEE and controlling EI) in trained endurance male athletes and monitored for aerobic performance changes. The results showed that inducing LEA by 25% (mean EA of 22.4 ± 6.3kcal/kg of FFM/day) for 14 days reduced hemoglobin levels, indirectly impacting VO2max and aerobic performance (11). Beyond research conducted by Dr. Iva Jurov and colleagues, there is insufficient experimental research on LEA and CRE.

MUSCULAR STRENGTH AND ENDURANCE
In recent years, few experimental studies have evaluated the impact of LEA on muscular strength, endurance, and athletic performance. Research on athletic performance and LEA has shown that endurance athletes with an EA of 17.3 ± 5 kcal/kg of FFM/day show no reductions in agility t-tests, power output, or countermovement jump results, indicating no association with EA (9). Also, Jurov et al. (2022b) found that a mean EA of 22.4 +/- 6.3kcal/kg of FFM/day in endurance male athletes for 14 days results in significant changes to explosive power (countermovement jump) but not agility t-tests (11).
Furthermore, Jurov et al. (2022a) also reduced EA (via increasing exercise energy expenditure and controlling energy intake) in male endurance athletes to evaluate performance and muscular power impact. The results showed significant reductions in explosive power (measured via vertical jump height test) at a mean EA of 22.4, 17.3, and 8.82 kcal/kg of FFM/day. Based on these findings, athletes reach the LEA threshold after a long time in an energy-deficient state, such as ten to 14 days (10).
However, Stenqvist et al. (2020) aimed to measure peak power in male cyclists after four weeks of intensified endurance training. The results showed that the cyclists significantly improved their peak power output (4.8%, p < 0.001) and functional threshold power (6.5%, p < 0.001) measured via stationary bike. Possibly, the EEE of the intervention was insufficient to induce LEA but instead induced the Specific Adaptation to Imposed Demands (SAID) principle in the athletes (27).
Regarding weightlifters, Murphy and Koehler (2022) studied whether energy deficiency impairs strength gains in response to resistance training. This research study was a meta-analysis of randomized controlled trials. The study findings showed that strength gains were comparable between resistance training groups in either an energy deficit or a balance state. These results demonstrated that low energy availability for prolonged periods (i.e., RED-S) did not impede strength output (21). There are a few studies that report bodybuilders with strength declines with estimations of EA <20 kcal/kg of FFM/day (4). The theory remains that inadequate energy intake will inevitably reduce muscular strength and output.

LOW ENERGY AVAILABILITY THRESHOLD
To date, optimal EA levels and the threshold for LEA in male athletes are under investigation. However, many research studies are cross-sectional, only demonstrating a correlation between athletes and energy availability (e.g., LEA commonly found in endurance athletes). The scant number of current experimental studies often fail to induce LEA and thereby fail to establish clear LEA thresholds.
To prevent LEA and subsequent conditions such as RED-S and MAT, athletes need to maintain their energy availability. Primarily, athletes need to ensure adequate EI and carefully manage their EEE. Current EA “zones” for female athletes are also applied to male athletes until experimental research can demonstrate a need for separate guidelines. EA >45kcal/kg of FFM/day supports body mass gain and maintains healthy physiological functions; 45kcal/kg of FFM/day is optimal for weight maintenance and healthy physiological functions; 30-45kcal/kg of FFM/day is considered suboptimal and at-risk for reduced physiological functions; and ≤30kcal/kg of FFM/day is considered low energy availability (1, 3, 4, 9, 10, 14, 17, 26).
Research by Jurov and colleagues has demonstrated mixed results regarding performance outcomes, body composition, and bone health (9, 10, 11). Mean energy availability in those studies ranged between 17-22 kcal/kg of FFM/day (9, 11). Based on their research findings, Jurov and colleagues have proposed a range of 9-25kcal/kg of FFM/day (mean value of 17kcal/kg of FFM/day) for an LEA threshold (10).
Regarding performance and body composition outcomes, Murphy and Koehler (2020) conducted a randomized, single-blind, repeated-measures crossover trial that showed three days of caloric restriction at an EA of 15kcal/kg of FFM/day induced considerable anabolic resistance to a heavy resistance training bout (20).
In a case study by Langan-Evans et al. (2021), an EA of 20kcal/kg per FFM/day led to weight loss and fat loss without signs of MAT and RED-S. However, an EA of <10kcal/kg of FFM/day did result in signs and symptoms of MAT and RED-S, including disruptions to the hypothalamic-pituitary-gonadal axis, resting metabolic rate (measured), and resting metabolic rate (ratio) (14). Additionally, some LEA thresholds may need to be sport-specific. For instance, Fagerberg et al. (2018) suggest an LEA threshold of 20-25kcal/kg of FFM/day for male bodybuilders with a lower body fat percentage (4). Research to establish EA zones and an LEA threshold for male athletes continues, and guidelines primarily still consider ≤30kcal/kg of FFM/day appropriate for male athletes. However, some researchers have also contested that male athletes can go lower before exhibiting signs and symptoms of MAT and RED-S.

RESEARCH GAPS
There are sizable research gaps regarding LEA and RED-S. First, this literature was unable to address the impact of LEA on endocrine, metabolic, hematological, and gastrointestinal health due to insufficient research published in the past five years. Mountjoy et al. (2018) identified the following research gaps: (1) lack of practical tools to measure and detect LEA and RED-S, (2) lack of validated prevention interventions for RED-S, (3) RED-s in male athlete research, (4) health and performance consequences of RED-S research, and (5) lack of evidence-based guidelines for treatment and return-to-play for athletes with RED-S. Research gaps focused on male athletes with MAT are even more prominent (19).

Moreover, Fredericson et al. (2021) listed several research gaps that need scientific attention, including screening protocols to detect MAT in adolescent and young males, identification of MAT energetic and metabolic impact factors, prevalence of DEED in male athletes with MAT, evaluating the efficacy and effectiveness of clearance and return-to-play protocols, risk assessment for BSI and poor bone health, prevalence of MAT in military recruits, health interventions on the prevention and treatment of MAT, and lastly, cutoff values (or threshold) for LEA (5). Addressing these research gaps would enable sports and health practitioners to effectively prevent and treat LEA, RED-S, and MAT, ensuring athlete health and sports performance.

SUMMARY
LEA is defined as a physiological state when there is inadequate energy to meet the demands placed on the body, often through physical activity, exercise, or sports (23). LEA can impact any athlete engaged in a sport with low energy intake or excessive energy expenditure. LEA is a precursor to the onset of both The Male Athlete Triad (MAT) and Relative Energy Deficiency in Sport (RED-S), two conditions that result in weakened physiological functions, with the former focused on reproductive and bone health decline (22).

Recent literature has shown mixed results on LEA’s impact on immunological health, metabolic markers, bone health, body composition, cardiorespiratory endurance, and muscular strength and endurance. There has been little evidence to connect LEA and endocrine, metabolic, hematological, and gastrointestinal health. However, a notable causal relationship exists between LEA and psychological health and reproductive health. Currently, there is still no defined low energy availability threshold specific to male athletes, however, EA zones from 15-25kcal/kg of FFM/day may be appropriate based on current literature (4, 20, 10, 18, 22, 26).

APPLICATION TO SPORT
Healthy nutritional practices are essential to sports performance. Interdisciplinary sports performance teams must collaborate with nutrition professionals such as Registered Dietitians accredited by the Commission on Dietetic Registration to develop effective LEA prevention, screening, and intervention protocols. Preventative measures must prioritize energy availability, modify sporting culture to encourage energy intake, and mitigate barriers to calorie- and nutrient-dense foods in male athletes. Screening protocols must include EA evaluations based on dietary intake, exercise energy expenditure, and fat-free mass measured via DXA or bioelectrical impedance analysis. Male athletes with an EA ≤20-25kcal/kg of FFM/day must receive nutritional guidance to reduce health and performance impairments. Intervention protocols must be enacted when LEA is confirmed and should primarily focus on increasing energy intake, decreasing energy expenditure, and addressing other associated aspects such as psychological health. Athletes, coaches, and practitioners must raise LEA awareness, dispel energy consumption stigmas, and foster an environment where food and nutrition fuel peak performance.

ACKNOWLEDGEMENTS
This work was supported by the Pennsylvania Western University Department of Exercise, Health, and Sport Sciences. The author would like to thank Dr. Marc Federico and Dr. Brian Oddi for their guidance and feedback on the manuscript

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George Minoso2024-10-21T09:45:40-05:00October 23rd, 2024|Book Reveiws, Research, Sports Nutrition|Comments Off

Order of passive and interactive sports consumption and its influences on consumer emotions and sports gambling

Authors:Anthony Palomba¹, Angela Zhang², and David Hedlund³

¹Department of Communication, Darden School of Business, University of Virginia, Charlottesville, VA, USA
²Department of Public Relations, Gaylord College of Journalism and Mass Communication, The University of Oklahoma, Norman, OK, USA
³Department of Sport Management, Collings College of Professional Studies, St. John’s University, Queens, NY, USA

Corresponding Author:

Anthony Palomba

100 Darden Blvd.

Charlottesville, VA, 22903

Anthony Palomba is an assistant professor of business administration at the Darden School of Business at the University of Virginia. He is fascinated by media, entertainment, and advertising firms. First, his research explores how and why audiences consume entertainment, and strives to understand how audience measurement can be enhanced to predict consumption patterns. Second, he studies how technological innovations influence competition among entertainment and media firms. Third, he is interested in incorporating machine learning and artificial intelligence tools to better understand consumer and firm behaviors.

Angela Zhang is an assistant professor in public relations. Her research interests span both corporate crisis communication and disaster risk communication in natural and manmade disasters. Her research primarily aims to understand how people process crisis and risk information and how we can communicate better during crises. For example, her work examines how linguistic cues in crisis messages affect people process crisis information, how and why risk information is propagated on social media, and how users communicate and cope on social media after crises. For corporate crisis communication, her research examines effectiveness of crisis prevention strategies such as CSR and DEI communication, as well as crisis response strategies.

Dr. Hedlund is an Associate Professor and the Chairperson of the Division of Sport Management, and he has more than twenty years of domestic and international experience in sport, esports, coaching, business and education. As an author, Dr. Hedlund is the lead editor of the first textbook ever published on esports titled Esports Business Management, and he has more than 30 additional journal, book chapter and related types of publications, in addition to approximately 50 research presentations. In recent years, Dr. Hedlund has acted as a journal, conference and book reviewer for sport, esports and business organizations from around the world, and he is an award-winning reviewer and editorial board member for the International Journal of Sports Marketing and Sponsorship.

ABSTRACT

This study explores how alternating between video game and television experiences influences consumer emotions and subsequent decision-making. Findings indicate that playing a video game after watching a video clip enhances positive emotions (H1 supported) and affects post-experiment betting scores based on pre-experiment gambling bets (H2 supported). Winning teams in video games and elevated positive emotions also positively influence post-experiment betting scores (H3 and H4 partially supported). The interaction effect shows that the sequence of media consumption (TV to video game) increases betting scores (H5 supported). The study contributes to understanding how appraisal tendency theory and mood management theory explain the impact of media consumption order on sports gambling decisions. Video games, as interactive stimuli, elevate consumer moods and influence betting behavior more than passive viewing. Practically, integrating video game and video clip data aids comprehensive audience measurement and targeted advertising strategies, advancing algorithmic forecasting in enhancing consumer engagement and decision-making.

Key Words: Mood management, Appraisal tendency theory, sports, gambling, video games

INTRODUCTION

The NFL is one of the most powerful media and entertainment brands in the marketplace, routinely curating legions of television and online video viewers for every annual season. In 2019, it averaged about 16.5 million viewers per game, roughly 33% above the 12.43 million viewing average for the top six non-sports programs (Porter, 2021). Additionally, over the last thirty years, the Madden NFL video game franchise has introduced generations to simulated immersive engagement. The legalization of sports gambling (Cason et al., 2020) has expanded how consumers can further engage with the NFL. NFL executives have discussed using mobile cell phones to aid sports fans in stadiums to make live bets throughout the course of a game (Martins, 2020). Audiences can watch the NFL and NFL game day content on the Xbox One, including up to date news and highlights from select NFL teams (Tuttle, 2016). Given these diverse modes of engagement, consumers often switch across a multitude of different activities. This frequent medium switching can significantly impact their moods and, subsequently, how they execute various tasks, including sports gambling. The phenomenon of media multitasking, where consumers engage with multiple forms of media simultaneously, complicates how they regulate their moods and make subsequent decisions (Deloitte, 2018). Younger consumers, in particular, are more inclined to switch between media than older consumers (Beuckels et al., 2021).

The increasingly diverse modes of engagement with the NFL, spanning from live game viewing and video game simulations to real-time betting, have led to a phenomenon of frequent media switching among consumers. This constant toggling between different platforms and activities can significantly impact their emotional states, subsequently influencing their decision-making processes, including those related to sports gambling. While previous research has examined task switching in general contexts (Yeykelis, Cummings, & Reeves, 2014) and the impact of media multitasking on advertising (Garaus, Wagner, & Back, 2017), the specific application of appraisal tendency theory to understand how these rapid emotional shifts induced by media switching affect sports gambling behaviors remains largely unexplored. Moreover, social media use while viewing television, a phenomenon that has grown in the last decade, has reconfigured the commodification of audiences, and has also created different markets to understand how consumers multi-task, and how to measure audience engagement (Kosterich & Napoli, 2016). Uniquely, social media may be used to track propensity to make season ticket purchases (Popp et al., 2023) among other sports consumption activities (Du et al., 2023). Recent studies have implicated the legalization of sports gambling as potentially increasing fandom and engagement among fans, and can further elevate communication across stakeholders involved in a sports event (Stadder & Naraine, 2020).

There is a gap in understanding, however, how consumer judgments and decisions are informed by emotions (Han, Lerner, & Keltner, 2007). Understanding this dynamic is critical for comprehending the evolution of fandom and identifying how sports teams can further engage fans. As consumers navigate between watching games, participating in video game simulations, and placing live bets, their engagement strategies and emotional states may significantly influence their decisions and loyalty. By examining these interactions, sports organizations can develop more effective methods to maintain and enhance fan engagement in an increasingly digital and interconnected world.

The implications of this study are broad and vast for academics along with sports and entertainment managers. The complex nature of media switching in sports consumption furthers our understanding of how affective disposition theory may be applied toward the multi-platform and multi-activity nature of modern sports engagement. It could lead to the development of a more nuanced understanding of how affective dispositions are formed and how they influence decision-making in this context. Microsoft (parent brand of Xbox console series) and the NFL have an agreement in which the NFL can provide fantasy football scores and updates on Xbox One consoles and allow fans to stream certain NFL games from their Xbox One consoles (Chansanchai, 2016). Additionally, Microsoft is able to trace not only what consumers play on Xbox One consoles, but also what TV or SVOD viewing apps fans engage to view content. Together, disparate information on video game play and video viewing can be combined to further identify trends in cross-platform sports consumption behavior and inferred consumer emotional states, which can help illuminate how consumer judgement surrounding sports gambling may be impacted.

NFL INDUSTRY

The National Football league has been a celebrated sports league in the United States and abroad over the last one hundred years. It draws the highest attendance per professional sports game in the United States, at about sixty-six thousand, and during its 2019 season, it hosted nearly sixteen million total viewers per game (Gough, 2021). The total revenue of all NFL teams was slightly over $15 billion in 2019, and average franchise value was just over $3 billion in 2020. Sports betting on Super bowls alone in Nevada accrued nearly $160 million in 2020 (Gough, 2021). While there are no clear figures regarding sports merchandise sales, NFL revenue by team in 2019 was led by the Dallas Cowboys ($980 million), New England Patriots ($630 million), NY Giants ($547 million) and Houston Texans ($530 million) through last place Las Vegas Raiders ($383 million) (Gough, 2020).

Aside from tickets, television revenue, and merchandise, the NFL has produced different avenues to engage fan bases. The league has recently embraced sports partnerships with Caesars Entertainment, Draft Kings and FanDuel. This allows these three external partners to engage in retail and online sports betting and engage with fans as well, using sports content from NFL media, as well as data, to market these experiences to fans (NFL, 2021). In fact, the NFL is expected to earn just over $2 billion annually from the sports gambling marketplace (Chiari, 2018). The NFL’s current TV media deals across CBS, ABC/ESPN, NBC, and Fox earn it just over $10 billion per season (Birnbaum, 2021). Arguably, one of the NFL’s highest profile merchandise revenue streams comes from its partnership with Electronic Arts (EA) to release an annual, updated version of Madden NFL, generating roughly $600 million annually for EA (Reyes, 2021). By embracing diverse engagement avenues, the NFL not only diversifies its revenue streams but also caters to the evolving preferences of modern sports consumers. This multi-faceted approach reflects the league’s recognition of the complex interplay between media consumption, mood, and fan behavior, ultimately enhancing the overall fan experience in an increasingly digital and interconnected world.

NFL FOOTBALL AS A VIDEO GAME EXPERIENCE: MADDEN NFL

There are few video games that possess the dominance and market monopolization as does the Madden NFL franchise. It exists as the only simulated NFL football video game available to consumers (Sarkar, 2020), and it is markedly popular among consumers. In fact, for the last twenty years, every Madden NFL video game installation has debuted as the top selling U.S. game in August each year (Wilson, 2022). The video game franchise itself has blossomed into its own celebrated video game season, as video game play expectedly rises during August in anticipation for the upcoming NFL season (Skiver, 2022). Madden NFL fans have been found to be more devoted and knowledgeable about the NFL. Additionally, they are less likely to miss viewing football games on Sundays, as 42% have stated they never miss a football game due to external activities. They are likely to attend at least one NFL game each annual season (IGN Staff, 2012).

Video gamers’ moods and subsequent judgment may be impacted by their own experiences. Video game play is an immersive experience, as the required technology helps to transport users into a digital world. The level of presence that is achieved can amplify mediated environment perceived quality, user effects, as well as overall experience (Tamborini & Bowman, 2010). Consumer familiarity with video game play may also influence how they experience presence (Lachlan & Krcmar, 2011). Consumers who view NFL games and play NFL video games may experience wins and loss outcomes in both passive and interactive manners. Sports video game play is motivated by possessing deep passion for the sport, gaming interest, entertainment value, competition, and identifying with the team or sport itself (Kim & Ross, 2006). Consumer emotions can be volatile during sports engagement, as winning and losing can impact overall game satisfaction (Yim & Byon, 2018). Emotions are tied to sports engagement in a primal manner, as consumers vicariously live through sports athletes and align themselves with sports teams, invoking a type of tribalism (Meir & Scott, 2007).

MOOD MANAGEMENT THEORY

Mood management theory concerns how consumers may manage their own moods through consumption of different mediums. Zillmann (1988) states that there are several traits that may impact whether a medium may repair or enhance a particular mood. First, there is the excitatory potential, or how exciting a message may be for consumers. Second, there is absorption potential, which examines how well a media message will be absorbed by an individual. Third, there is the semantic affinity, which relates to the connection from the current participant mood to a media message, which can moderate the impact of absorption potential. Finally, there is hedonic valence, in which pleasant messages can interrupt consumers’ bad moods (Zillmann, 1988). This study is focused on exploring how consumers’ gambling decisions are influenced by their experiences, both positive and negative, related to predicting scores between teams, and placing a bet on them. Specifically, it aims to investigate the impact of semantic affinity and the excitatory potential of stimuli involved in the process on consumer decision-making in gambling contexts.

Sports viewing or sports video game play can lead to evaluated states of physiological and psychological arousal, stirring hostile or expressive responses to game outcomes. Arousal has been found to be precipitated by aggressive or hostile states (Zillman, 1983), based on events during the game (Berkowitz, 1989). Hostility can be traced to the dissatisfaction with an outcome, or inability to attain a desired goal. Viewing violent sports competition can also heighten hostility and create greater inclinations toward aggressive behavior. Participants who had high identification with America and viewed an American boxer against a Russian boxer were found to have elevated blood pressure compared to those who had low identification with American (Branscombe & Wann, 1992). Additionally, spectators that have high team identification have higher levels of happiness compared to those with low team identification. The way a message is delivered can impact the effect of a message on consumers, as there are distinct characteristics related to each medium (Dijkstra, Buijtels & van Raaij, 2005).

Mood management is clearly influential as to how participants respond to video and video game play. Participants who may feel frustration may feel further frustration from viewing violent content (Zillmann & Johnson, 1973). One study by Bryant and Zillmann illustrated that participants who view violent sports did not experience mood repair (Donohew, Sypher, & Higgens,1988). Fulfillment of intrinsic needs can influence selection of video games with varying levels of participant demand (Reinecke et al., 2012). Television has been found to reduce boredom and stress among consumers (Bryant & Zillmann, 1984). In managing moods, this can also impact subsequent decision-making, sometimes surreptitiously and without awareness from participants.

APPRAISAL TENDENCY THEORY

Appraisal tendency theory considers how different types of emotions within similar valences (e.g., anger and fear) may impact judgement. There are two types of influences that may impact how consumers make judgments. Integral emotion is based on individual experiences that might preempt but be relevant to a subsequent decision. Differently, incidental emotion is due to conceivably irrelevant though impactful elements that can inform decision-making, which may include being influenced by traffic, watching television, or engaging in other non-relevant actions. These influences can carry over to the decision-making process (Schwarz & Clore, 1983; Bodenhausen, Kramer, & Susser, 1994). Moreover, consumers who are angry tend to perceive less risk from engaging in new situations (Han, Lerner, & Keltner, 2007).

Integral emotion is under examination in this study, as an outcome from a related medium stimulus can impact a subsequent decision that is likely informed by that stimulus. After finding that they have won in a video game, it may be that consumers are less inclined to bet against the team that they just lost against. This subjective pain(joy) based on the first stimulus may be stronger from playing a video game than from viewing a sports clip. Moreover, consumers may seek variety in consumption decisions when they are induced to a negative emotion (Chuang, Kung, & Sun, 2008). Therefore, subsequent decision-making may be informed by the order of passive and interactive media consumed by each individual.

MEDIUM MODALITY

Mediums that engage multiple senses are likely to lead to impactful communication with consumers (Jacoby, Hoyer & Zimmer, 1983). Television offers engagement through visual and auditory senses, while gaming stimulates both but creates an immersive experience, in which consumers are transported into a virtual world (Kuo, Hiler, & Lutz, 2017). Differently, consumers do not have control over passive mediums such as television, as the content is predetermined and is under the yolk of the sender, creating different delivery systems (Van Raaij, 1998). Video game play offers opportunities for players to speed up game play, based on gaming flexibility as well as how quickly a consumer can finish tasks. Video game play is positioned to evoke cognitive responses, through the speed of information dissemination, since the consumer possesses more control over the experience. Conflated with the demanded attention from video game play, consumers will likely have greater affective responses from video game play than from video viewing (Dijkstra, Buijtels, & van Raaij, 2005).

In consideration of this study, it follows that the simulated aspect of video game play can further influence decision-making. Consumers are inclined to experience improved decision-making and risk assessment through video game play (Reynaldo et al., 2020), as well as cognitive tasks (Chisholm & Kingstone, 2015). Video game play may also induce lowered physiological stress (Russoniello, O’Brien, & Parks, 2009), and emotional regulation (Villani et al., 2018). While there is scant research surrounding video game play simulations and making subsequent real-life decisions, it is ostensibly clear that video game play can heighten and sharpen decision-making skills as well as emotion regulation. Consumers who are attentive toward a simulated video game play experience may be influenced by its outcome in making a subsequent decision. This can include perceiving the winning team in the simulated game as likely to beat the same opposing team in a real-life match up.

H1: Consumers who play a video game (view a video clip) first will be more inclined to have lower (higher) positive emotions.

SPORTS GAMBLING

Recently, sports gambling has become legalized or recent legislation has been passed to make it legal in 50% of states in the United States (Rodenberg, 2021). While fans have placed bets on horse-racing and even major league sports, its legalization provides a lawful and safe forum for myriad fans to place bets on teams. However, since many gamblers may not invest time in understanding spreads and other esoteric metrics that gambling managers may use to measure likelihoods of outcomes, playing a Madden NFL game can serve consumers to anticipate potential outcomes in real life match ups. Madden NFL’s algorithms have been harvested in the past to predict Super Bowl outcomes. In fact, EA typically runs one hundred simulations to predict which team will win each year in the Super Bowl (Wiedey, 2020). Additionally, fans are also able to make wagers on major league baseball simulated video games (Cohen, 2020). Younger sports fans may be more inclined to play Madden NFL games as a way to simulate outcomes, and become more familiar with teams to anticipate actual game outcomes. Additionally, sports gamblers are betting on simulated sports, in which Madden NFL video games are simulated through the popular video game streaming site Twitch, and consumers are able to bet on the outcome (Campbell, 2021).

Previous studies have highlighted why consumers engage in sports gambling. One study found that consumers engage in sports gambling to seek out social interaction and relaxation through engagement with betting apps, though their effect on problematic gambling and non-problematic gambling varied across these dimensions (Whelan et al., 2021). Consumers may seek out consumer purchases as a way to blunt negative emotions, or may further satiate their positive mood by pursuing purchases that bring them joy. Video game play can engender excitatory potential, stimulating arousal levels and inspiring consumers in negative moods to make consumer purchases or execute notably different gambling bets. The heightened arousal levels experienced by consumers during video game play can create greater vacillation in subsequent decision-making, including sports gambling bets. Tangentially related to this, if a consumer is in a positive mood, this optimism may impact their inclination to bet more on a sports match up. Additionally, the order of engaging a passive medium versus an interactive medium is critical to analyze. Video game play can heighten immersion in content, and provide further confidence in a team. Consumers may be able to participate in high-scoring video game match ups. Additionally, consumers may be spurred to bet on characters with whom they have virtual relationships (Palomba, 2020). Finally, video game play can lead to experiencing dopamine release, leading to greater felt pleasure (Koepp et al., 1998). Together, these may lead consumers to have greater optimism for post-betting scores.

H2: Consumer pre-experiment bet scores will have an anchoring effect and still inform post-experiment bet scores.

H3: The team that wins in the video game will have a greater positive relationship with post experiment bet scores than the team with the highest score in the video clip.

H4: Consumers who experience strong positive (negative) emotions after viewing a video clip will positively (negatively) influence post-experiment bet scores.

H5: Consumption order and time will have an interaction effect that when consumption order is VG to TV, betting scores will decrease from pre-betting to post-betting (pre-betting will be higher than post-betting); when consumption order is TV to VG, betting scores will increase from pre-betting to post-betting (pre-betting will be lower than post-betting).

METHOD

A 4×2 experiment was conducted here, in which participants were exposed to one of four different video clips, and one of two outcomes in a video game play match up. The New York Giants and Dallas Cowboys were the two teams that were selected for this experiment. Since this experiment took place in the mid-Atlantic region, it was believed that participants were less inclined to like either team. Moreover, these two teams have a storied and high-profile rivalry between them. For the video stimulus, participants were exposed to a randomized video clip highlighting a matchup between the NY Giants and Dallas Cowboys, in which one of four scenarios appeared: a) The NY Giants win by a wide margin (20 points), b) The NY Giants win by a slim margin (3 points), c) The Dallas Cowboys win by a slim margin (3 points), and d) The Dallas Cowboys win by a wide margin (20 points). Each video clip was about five minutes long. The video game stimulus involved playing a Madden NFL video game match up on an Xbox One video game console between the NY Giants and Dallas Cowboys. Participants were able to select which team they desired to play as and in which stadium to play in. The quarters in the Madden NFL game were kept at the default setting of six minutes each, ensuring participants experienced immersion but also maintained the experience to be similar to viewing the video clip.

Participants in the A condition (VG to TV) first played the video game followed by viewing the video clip, and participants in the B condition (TV to VG) first viewed the video clip followed by the video game play. as well as playing a Madden NFL session implicating both teams. After each condition, participants were asked to evaluate their current emotions. After the video clip, participants were asked to state the final score and which team won in the clip to ensure that they were paying attention to the clip itself. Moreover, after the video game condition, participants were asked to state which team they played as, the final score, as well as what sports stadium they played in.

MEASURES

To measure fandom, a scale from (Wann, 2002) was used here. It consisted of statements regarding self-assessment of fandom, including statements such as “I consider myself to be a football fan,” “My friends see me as a football fan,” and “I believe that following football is the most enjoyable form of entertainment.” It was measured on a 1 (strongly disagree) to 5 (strongly agree) Likert scale.

To measure current emotions, a scale from Diener and Emmons (1984) was used here. The scale consisted of emotions statements including “joy,” “pleased,” “enjoyment,” “angry,” and other emotion statements. It was measured on a 1 (not at all) to 7 (extremely much) Likert scale.

It was believed that the current emotions scale, though exhaustive, did not capture extreme aggression that may be felt by sports fans. An ancillary aggression scale (Sinclair 2005; Spielberger, 1999) was used here. The scale consisted of aggression statements including “I feel like yelling at somebody,” “I am mad,” and “I feel like banging on the table.” It was measured on a 1 (not at all) to 5 (extremely) Likert scale.

To measure for team identification, a scale by Naylor, Hedlund, and Dickson (2017) was used here. The scale consisted of statements including “I know a lot of information about my favorite National Football League team,” “I am very knowledgeable about my favorite National Football League team,” and “I am very familiar with my favorite National Football League team.” It was measured on a 1 (not at all) to 5 (extremely) Likert scale.

To measure for commitment to team, a scale by Hedlund, Biscaia, and Leal (2020) was used here. The scale consisted of statements including “I am a true fan of the team,” “I am very committed to the team,” and “I will attend my team’s games in the future.” It was measured on a 1 (not at all) to 5 (definitely) Likert scale.

To measure for brand loyalty toward Madden NFL, a scale by Yoo and Donthu (2001) was used here. The scale consisted of statements including “I consider myself to be loyal to Madden football,” “Madden football would be my first football video game choice,” and “The likely quality of Madden NFL is extremely high.” It was measured on a 1 (strongly disagree) to 5 (strongly agree) Likert scale.

RESULTS

Descriptive analytics were run to break down video clip and video game play exposure to participants. After data-cleaning was executed, one hundred and thirteen participants (n=113) remained for analysis. 63.7% of participants were male. Additionally, across ethnicity, participants were Caucasian (58.4%), Asian-American (16.8%), African-American (8.8%), Hispanic (2.7%) and also identified as other races (13.3%). Among participants’ favorite NFL teams, they included the Washington Commodores (16.8%), New England Patriots (8.0%), and Philadelphia Eagles (8.0%). Less participants were fans of the New York Giants (4.4%) and Dallas Cowboys (1.8%). To gain a sense of faith participants had among each team, participants were asked to imagine making a bet between a pre bet on an imagined match up between the NY Giants and Dallas Cowboys. Participants on average placed the Dallas Cowboys (M=25.77, SD=9.102) past the NY Giants (M=20.67, SD=8.715) and bet roughly $14.37 on average.

Across all video clips, participants viewed the Giants winning by a lot (23.4%), Giants winning by a little (28.7%), Cowboys winning by a lot (25.5%), and Cowboys winning by a little (22.3%). Participants viewed the Giants winning 49.5% of the time and the Cowboys winning 50.5% of the time. In relation to video game difficulty level exposure, 51.3% of participants were exposed to pro-level difficulty (2/4 level of difficulty), and 48.7% were exposed to all-pro level difficulty (3/4 level of difficulty). This was done to ensure that Madden football players felt challenged and greater immersion during video game play (Csikszentmihalyi, 1975; Falstein, 2005; Nacke, 2012; Missura, 2015). 50.9% of participants played as the Dallas Cowboys, and 49.1% played as the NY Giants. In the video game itself, the Dallas Cowboys won 64% of the time, and the NY Giants won 36% of the time. Finally, participants won 74.8% of the time. Moreover, 58% of participants elected to play in NY Giants home stadium, MetLife Stadium, and 42% elected to play in AT&T Stadium, the Dallas Cowboys’ home stadium. Before analyses could be conducted, it was necessary to run factor analyses to reduce the amount of emotion statements necessary for analyses. For all factor analyses across pre-experimental mood, post video mood, and post video game mood, varimax rotations were run.

For post video emotions, the factor analysis had a KMO of .895 and the Bartlett’s Test of Sphericity was statistically significant. The first factor loading had 12.717 eigenvalue and explained 48.913% of variance in the data. The first loading, violent, included I feel like kicking somebody (.919), I feel like hitting someone (.908), I feel like breaking things (.880), I feel like pounding somebody (.880), and I feel like yelling at somebody (.874) and had a Cronbach’s alpha score of .972. The second factor loading had an eigenvalue of 5.022 and explained 19.317% of variance in the data. This scale, entitled irritated, included frustrated (.865), annoyed (.835), angry (.820), depressed (.800), and sad (.768), and had a Cronbach’s alpha score of .928. The third factor loading had an eigenvalue of 2.311 and explained 8.890% of variance in the data. This scale, entitled positive, included pleased (.919), joy (.914), glad (.904), delighted (.900), and fun (.898) and had a Cronbach’s alpha score of .953.

For post video game emotions, a factor analysis was run. The KMO =.879 and the Bartlett’s test of sphericity was statistically significant. The first factor loading had an eigenvalue of 13.119, and it explained 50.458% of variance in the data set. The first factor loading, violent, included I feel like hitting someone (.866), I feel like breaking things (.858), I feel like banging on the table (.853), I feel like pounding somebody (.840) and I feel like kicking somebody (.840) with a Cronbach’s alpha score of .965. The second factor loading had an eigenvalue of 4.640 and explained 17.846% of variance in the data set. This scale, positive, included joy (.915), glad (.910), delighted (.897), pleased (.884), and fun (.860), and possessed a Cronbach’s alpha score of .952. The third factor loading had an eigenvalue of 1.783 and explained 6.858% of variance in the data set. This scale, irritated, included gloomy (.832), depressed (.798), sad (.747), anxious (.628), and angry (.531) and had a Cronbach’s alpha score of .905.

There was emotional variance across mediums (Table 1). Paired T-tests were run across an assortment of feelings here. For most of the emotions that were measured for in this experiment, participants generally felt better after playing the video game against viewing the clip itself across both conditions. For instance, in total, joy (M=4.38, SD=1.928), glad (M=4.45,

SD=1.785), and delighted (M=4.32, SD=1.904) all increased across all conditions after the video game play condition. Hypothesis 1 is supported here.

Table 1

Emotion variance across mediums.

	Total			TV to VG			VG to TV
	Pre stimulus	Post video clip	Post video game	Pre stimulus	Post video clip	Post video game	Pre stimulus	Post video game	Post video clip
Joy	4.04(1.614)	3.75(1.864)*	4.38(1.928)***	4.33(1.492)	4.46(1.691)	4.98(1.742)*	3.73(1.689)	3.79(1.933)	3.04(1.768)**
Pleased	4.28(1.623)	4.63(1.665)	4.66(1.824)***	4.44(1.524)	4.63(1.665)	5.02(1.794)	4.13(1.717)	4.30(1.798)	3.54(1.629)***
Fun	4.48(1.553)	5.09(1.491)	5.46(1.705)***	4.61(1.449)	5.09(1.491)***	5.46(1.705)	4.34(1.654)	4.88(1.585)**	3.37(1.902)***
Glad	4.35(1.535)	3.81(1.827)***	4.45(1.785)***	4.70(1.414)	4.39(1.677)	4.89(1.723)*	4.00(1.584)	4.00(1.748)	3.21(1.796)**
Delighted	3.88(1.700)	3.83(1.827)	4.32(1.904)**	4.11(1.666)	4.26(1.798)	4.71(1.755)*	3.66(1.719)	3.93(1.980)	3.39(1.765)*
Contented	4.97(1.555)	4.39(1.775)***	4.55(1.729)	5.11(1.655)	4.82(1.754)	4.80(1.793)	4.84(1.449)	4.30(1.640)*	3.95(1.699)
Angry	1.45(1.106)	1.37(.771)	1.58(1.333)	1.38(1.001)	1.38(.702)	1.46(1.144)	1.52(1.206)	1.70(1.501)	1.36(.841)
Anxiety	2.33(1.550)	1.67(1.060)***	1.62(1.133)	2.25(1.338)	1.77(1.062)*	1.45(.851)*	2.41(1.745)	1.79(1.345)***	1.57(1.059)
Frustrated	1.88(1.309)	1.69(1.115)	2.10(1.682)**	1.77(1.079)	1.66(1.100)	1.84(1.424)	1.98(1.507)	2.36(1.882)	1.71(1.140)**
Depressed	1.76(1.187)	1.46(.958)***	1.45(.928)	1.71(1.107)	1.43(.892)**	1.38(.822)	1.80(1.271)	1.52(1.027)*	1.48(1.027)
Annoyed	1.86(1.293)	1.76(1.050)	2.13(1.688)*	1.59(.949)	1.66(.920)	1.91(1.621)	2.13(1.526)	2.34(1.740)	1.86(1.167)*
Sad	1.74(1.334)	1.42(.866)**	1.44(.918)	1.80(1.470)	1.38(.676)*	1.39(.908)	1.68(1.193)	1.48(.934)	1.46(1.026)
Gloomy	1.75(1.151)	1.50(.977)**	1.40(.895)	1.77(1.191)	1.41(.781)***	1.32(.741)	1.73(1.120)	1.48(1.027)*	1.59(1.141)
p < .05; p < .01; **p < .001.

To test hypotheses 2-4, multiple linear regressions were running for predicting consumer post experiment score bets in table 2 and table 3. In table 2, Across both conditions, pre bet Giants score (β=.413, p<.001), pre bet Cowboys score (β=-.269, p<.012), and video Giants score (β=.225, p<.021) explained 34.6% of variance toward estimating Giants post experiment bet score. In the TV to VG condition, pre bet Giants score (β=.505, p<.003), pre bet Cowboys score (β=-.442, p<.008) explained 35.5% of variance toward estimating Giants post experiment bet score. In the VG to TV condition, pre bet Giants score (β=.430, p<.018) and Giants winning in VG (β=-.583, p<.024) explained 28.9% of variance toward estimating Giants post experiment bet score.

Table 2

Consumer post bets – Giants.

	NY Giants Total		NY Giants TV to VG		NY Giants VG to TV
	Beta	Sig.	Beta	Sig.	Beta	Sig.
Pre bet Giants score	.413	.001***	.505	.003**	.430	.018*
Pre bet Cowboys score	-.269	.012*	-.442	.008**	-.009	.969
Winning team in VG	-.282	.071	-.213	.442	-.583	.024*
Did player win in VG	.011	.921	-.276	.113	.334	.112
Team played as in VG	.010	.942	.190	.513	-.110	.610
Sports arena played in VG	.083	.462	.073	.695	.261	.296
Video Cowboy score	-.056	.550	-.089	.543	-.039	.801
Video Giants score	.225	.021*	.262	.096	.285	.079
VG Giants score	-.120	.388	.073	.738	-.281	.256
VG Cowboys score	-.115	.376	-.174	.409	-.009	.966
VC Violent	.085	.569	.138	.668	.011	.960
VC Irritated	-.012	.919	.007	.971	-.186	.458
VC Positive	-.079	.550	-.170	.397	-.043	.836
VG Violent Actions	-.164	.276	-.290	.423	.051	.815
VG Positive Actions	-.110	.454	.028	.894	-.207	.399
VG Irritated	-.006	.962	-.101	.608	.023	.937
F	3.814		2.448		2.068
R	.685		.775		.748
R²	.346		.355		.289
Significance	.001		.021		.048

In table 3, across both conditions, pre bet Cowboys score (β=.467, p<.001), Cowboys winning in video game (β= .342, p<.038), and video Cowboy score (β=.226, p<.024) explained 27.4% of variance toward estimating Giants post experiment bet score. In the TV to VG condition, pre bet Cowboys score (β=.394, p<.014), Cowboys winning in video game (β= .613, p<.029), Cowboys video score (β=.352, p<.020), Giants video game score (β=.470, p<.034), and feeling positive after viewing the video clip (β=.476, p<.020), explained 38.8% of variance toward estimating Giants post experiment bet score. In the VG to TV condition, Cowboys winning in the video game (β=.469, p<.035), Cowboys video score (β= .276, p<.047), Giants video game score (β=-.517, p<.021), Cowboys video game score (β=-.450, p<.022), and feeling violent after the video clip (β=-.583, p<.011) explained 46.2% of variance toward estimating Cowboys post experiment bet score. Together, these results supported hypothesis 2 and provided partial support for hypotheses 3 and 4.

Table 3

Consumer post bets – Cowboys.

	Dallas Cowboys Total		Dallas Cowboys TV to VG		Dallas Cowboys VG to TV
	Beta	Sig.	Beta	Sig.	Beta	Sig.
Pre bet Giants score	-.138	.195	.045	.767	-.277	.072
Pre bet Cowboys score	.467	.001***	.394	.014*	.370	.071
Winning team in VG	.342	.038*	.613	.029*	.469	.035*
Did player win in VG	.098	.422	.063	.705	.288	.115
Team played as in VG	-.066	.662	-.294	.300	-.263	.169
Sports arena played in VG	.004	.972	-.221	.231	-.242	.266
Video Cowboy score	.226	.024*	.352	.020*	.276	.047*
Video Giants score	-.120	.236	-.169	.261	.058	.675
VG Giants score	.009	.953	.470	.034*	-.517	.021*
VG Cowboys score	-.128	.349	-.129	.529	-.450	.022*
VC Violent	-.180	.255	.312	.323	-.538	.011*
VC Irritated	.099	.443	-.011	.954	.226	.303
VC Positive	.098	.484	.476	.020*	.088	.629
VG Violent Actions	.090	.569	-.547	.127	.160	.406
VG Positive Actions	-.033	.830	-.098	.634	-.287	.182
VG Irritated	-.019	.895	.383	.054	-.102	.684
F	3.008		2.663		3.251
R	.641		.788		.817
R²	.274		.388		.462
Significance	.001		.013		.004

To answer the fifth hypothesis, a mixed between-within subjects analysis of variance was conducted to understand the effects of consumption order (TV to VG vs. VG to TV) and game results (NY giant wins a lot vs. Cowboy wins a lot) on participants’ sports betting scores on the two teams (NY Giants and Dallas Cowboys, respectively), across two time periods (pre- and post-experiment).

For betting scores on NY Giants, a significant interaction effect was found between time and order (Wilks’ Lambda = .89, F (1, 35) = 4.54, p=.04). Both pre and post-betting scores for those under the order condition TV to VG ( = 15.83, SD=5.79 and = 18.72, SD=8.10) scored lower than those under the VG TO TV conditions ( = 23.57, SD=9.67 and = 20.19, SD=8.54). Betting scores for NY Giant has increased for order TV to VG ( = 15.83, SD=5.79 to = 18.72, SD=8.10) but betting scores for order VG to TV has decreased ( = 23.57, SD=9.67 to = 20.19, SD=8.54). However, the main effects for time were not significant, nor were the interaction effects between time and game results, and between time, game results, and order (Figure 1). For betting scores on Dallas Cowboys, no significant main effects or interaction effects were found on any of the variables.

Figure 1

Pre-betting and post-betting scores.

DISCUSSION

This study worked to demonstrate how toggling between video game and television experiences could influence consumer emotions and inform subsequent decision-making. Consumers who played a video game after viewing a video clip were more inclined to feel positive (H1 supported). Pre-experiment gambling bets informed post experiment bet scores (H2 supported). There was some evidence that suggested winning teams in video games held a positive influence over post experiment bet scores (H3 partially supported) and that high levels of positive emotions also held a positive influence over post experiment bet scores (H4 partially supported). Finally, there was an interaction effect in which consumption order and time, in which betting scores will increase in the TV to VG condition (H5 supported). Together, the evidence illustrates how powerful the order of medium engagement is for consumers, and that these particular sequences can not only impact post-moods, but also decision-making among consumers.

This study contributes to the understanding of how appraisal tendency theory and mood management theory further elucidate the influence of media consumption sequencing on subsequent sports gambling decision-making. Specifically, the sequential order of media engagement was found to affect consumers’ semantic affinities between their recent media exposures (such as watching sports clips or engaging in video game sports simulations) and their subsequent decisions regarding sports wagering, albeit to a limited extent. Additionally, consumers’ moods were elevated by video game play, compared to viewing sports clips, supporting the excitatory potential of interactive stimuli here (Zillmann, 1988; Reinecke et al., 2012). In particular, the winning team in a video game simulation was able to impact post-consumer scores for the Cowboys, and moderately impact post-consumer scores for the Giants. This illustrates that video game simulations can be used to inform subsequent decision-making including estimating a team’s score during a post bet, an advancement of appraisal tendency theory. Previously, this had not been applied to mixed media modality studies, and this illustrates that previous media consumption activities can impact subsequent decision-making. Overall, post-betting scores were elevated in part based on the video game to television media consumption order, illustrating the anchoring effect established from consumers’ first playing video game match ups. Additionally, while pre bets can inform how consumers may produce bets after engaging in media, playing simulated video games can be impactful, whether it is the final score or which team won. It should be stated that the bulk of consumers played as the Cowboys, which may illustrate why the Giants winning in the video game held a negative relationship toward the Giants post bet score. It may be that for some consumers, there is interest in proving a simulation wrong, whereas others are positively informed by this experience.

In regards to mood management theory, in particular semantic affinity and excitation potential, consumer moods were elevated during video game play. From a passive to an interactive activity, this illustrates that this can further intensify emotional valences across positive (e.g. joy, pleased, fun) and negative (gloomy, annoyed) states. This furthers our understanding of how order of media consumption can impact particular moods for consumers. Having agency over an experience, and allowing consumers to co-create their own experiences while playing a simulated matchup further elevates positive feelings. Differently viewing video clips can evoke a range of emotions in consumers, including contentment as well as feelings of anxiety, depression, sadness, or gloominess. A passive entertainment experience that does not include consumers in the co-creation process (especially if their favorite team is not featured in the clip itself), can create dower moods among consumers. Only 6% of participants possessed affinity for either the Cowboys or the Giants, which did not improve mood during video viewing. However, video game play was able to overcome this obstacle and uplift moods.

PRACTICAL IMPLICATIONS

Integrating video game data with video clip data collection facilitates the development of a comprehensive media audience measurement approach. This approach enables practitioners to gauge engagement across both passive and interactive consumption modes. Additionally, it contributes to establishing a new market information framework (Meyer & Rowan, 1977), potentially minimizing analytical redundancies as consumers’ behaviors are tracked seamlessly across various media platforms. The technological disruption of multi-tasking, task-switching, and sequential tasking have created multiple opportunities to measure audiences differently, particularly as 5G becomes widely available in NFL stadiums. Verizon has recently stated that its 5G ultra Wideband service can ensure connectivity for fans during live games (Ashraf, 2023). The ability to engage smart phone devices in a sports stadium allows audiences to gain a sense of how audiences are responding to a game, which may include measuring the amount of bets. For homebound patrons, consolidating data sets in a cohesive and aggregated fashion enables the development of advanced algorithms for forecasting. This helps in deciphering the audience’s mindset based on their past media consumption patterns leading up to watching an NFL game or engaging in Madden NFL gameplay. Currently, Amazon offers X-Ray for Thursday Night Football fans, which is a sophisticated graphical overlay that allows fans to follow statistics in real time along with generated two-minute highlight reels (Forristal, 2023). Therefore, calcified sport consumer profiles and proclivities for communication with each other can be further facilitated through these strategies (Kirkwood, Yap, & Xu, 2018).

This creates a vehicle for programmatic strategy advertising and public relations, by which automated advertisements and public relations addresses can be targeted toward participants after an activity in order to enhance or repair a sports fan experience. More attention from consumers may be given to positive television advertisements that follow engaging programming rather than calm programming (Lee, Potter & Han, 2023). Consumers gain greater joy on spending money on experiential products including sports events (Nicolao, Irwin, & Goodman, 2009) and so consumers may seek out experiences more so than merchandise. Moreover, the ability to track consumer behavior in virtual spaces has implications for how advertisements may be placed and how consumers may engage with them (Ahn, Kim & Kim, 2022). The order of consumption can aid practitioners in elevating video game play. Not only can it impact post betting video game scores, but it can also enhance positive moods for consumers. In particular, consumers who experience their own team or a favored team winning in a video game or simulated match up may feel delighted or joy, which may subsequently encourage them to increase the post experience bet score for one or both teams. This can therefore encourage more risk taking among consumers, and perhaps even more spending for that matter. Furthermore, when fans experience negative emotions after their favorite team loses a live match, the NFL team can strategically encourage them to replay the matchup in Madden NFL. This allows fans to reimagine the live game, thus re-writing the experience itself, and mitigating any temporary damage to brand loyalty or equity.

LIMITATIONS AND FUTURE STUDIES

There were several limitations in this study. First, most participants were inclined to push for in favor of the Cowboys in the pre-bet. Recall that the NY Giants pre bet score was less (M=20.67, SD=8.715) compared to the Dallas Cowboys (M=25.77, SD=9.102). This indicates markedly more confidence in the Dallas Cowboys’ abilities among the participants. However, while the Cowboys won 64% of the time in the video game, participants only played as them for roughly 51% of the time. Moreover, 58% of participants elected to play in the NY Giants arena. Consequently, many participants were surprised by losses to the NY Giants when playing in the Giants’ stadium. Future studies should consider allowing participants to play as their favorite teams or testing various types of advertisements on them. It may also be valuable to examine how participants respond to playing in stadiums that are geographically close to or far from their hometowns. Additionally, investigating how the order of media consumption affects consumer behavior related to memorabilia, tickets, and other sports-related purchases offers a promising area for academic research.

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Qshequilla Parham Mitchell2024-10-11T13:41:23-05:00October 11th, 2024|Research, Sports Studies|Comments Off

The Youth Olympic Games Educational Program

Through Experiential Learning Theory Lens

Authors: Jannicke Staalstroem OLY^1,2 , Marina Iskhakova ³, Alex C. Gang ⁴, and Zack P. Pedersen ⁵

¹School of Sport Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway

²Faculty of Education and Social Work, The University of Sydney, Sydney, Australia

³Research School of Economics, Australia National University, Canberra, Australia

⁴College of Education, Washington State University

⁵Department of Kinesiology & Sport Management, Texas Tech University

Abstract

Purpose: The Youth Olympic Games (YOG), the largest international sport event for young athletes, allows athletes to take part in an Olympic educational program. These programs have never been examined through the lens of Experiential Learning Theory (ELT). The purpose of this study is to provide in-depth analysis and evaluation of all YOG educational programs design by date (2010 – 2020) through the lens of ELT and to uncover the areas of where the strengthening of the programs impact is feasible and encouraged.

Methods: A thorough YOG documents analysis was performed on the six YOG`s educational programs by examining the place and role of each of the four elements of ELT and how prevalent they were.

Results: Results of our analysis show that YOG educational programs are not properly balanced and that concrete experiences turned to be the mostly and overly covered in the six games by the price of other critically important ELT stages. Reflective observations and abstract conceptualizations come into play sporadically and also only in later games, although still underwhelmingly. Active experimentations are covered through media activities in most of the games and the whole potential of the stage is due to be fully utilised.

Conclusions: YOG educational program impact on YOG athletes could be significantly enhanced by embracing and sufficiently incorporating all 4 ELT stages into the program design and delivery.

Applications in Sport: This study highlights the potential of ELT as a theoretical tool for addressing the impact learning and change the educational program can have on the YOG participants. The performed document analysis suggests on how learning can be enhanced for the YOG athletes. Suggestions for the future YOG educational program designers are formulated and provided.

Keywords: Educational Program, Youth Programs, Olympic Education, Experiential learning, Young Athletes

Examining The Youth Olympic Games Educational Program Through Experiential Learning Theory

The educational purpose of the Youth Olympic Games (YOG) is delivered to the athletes through the YOG educational program (IOC, 2016, 2019), founded on the concept of Olympism (Naul & Binder, 2017). The YOG was established to be more than a sporting event, whereby through the Olympism perspective and Olympic values (i.e., excellence, friendship, respect) young athletes could be instructed on topics like healthy lifestyles, doping issues, global challenges, and their potential role as sport ambassadors (IOC, 2011). Additionally, the YOG was intended to reignite Olympic ideals, which were perceived to be lacking in the contemporary Olympic Games (Naul, 2010, p. 23). The IOC hoped that the YOG athletes would carry positive values throughout their sporting event, and in their working and private lives (IOC, 2011).

Therefore, the Olympic movement saw the YOG as a way of instilling health, sport, and social values, in addition to Olympism (Parry, 2012). To accomplish this, the educational program was crucial for the IOC and the YOG, given that the young athletes are at such an important developmental stage in life. YOG educational programs have been modified to meet the four learning pillars stipulated by the IOC and the YOG Organizing Committee (i.e., learning to know, to do, to be, and to live together; YOGOC). Each YOGOC exercised its autonomy to establish various educational formats, which reveal limited consistency from one YOG to the next. Although the educational programs of the YOG carry significant importance in instilling positive values in the lives of young athletes, its effectiveness is hindered by inconsistencies within the learning formats and the network of partner organizations. This reveals an absence of a reliable mechanisms capable of adequately scrutinizing the foundations of the programs as well as their learning potentials. Reflecting on the need to better understand the educational programs, we suggest that Kolb’s Experimental learning theory (Kolb, 1984) is a valuable theoretical tool to assess and strengthen learning for the athletes who are in a critical developmental stage. According to Newman et al. (2018), historically this method of ELT programming and its related practises have found to be effective when working with youth (Conrad & Hedin, 1982; Gosen & Washbush, 2004; Kolb & Kolb 2008). Therefore, the IOC and the YOGOC educational program developers have the opportunity to implement experiential learning methods to increase youth athlete’s knowledge (Kolb & Kolb 2009a). Additionally, these programs have the chance to develop the young athletes’ skills on and off their field of play by highlighting their values and developing their capacities, such as contributing not only to themselves but to their communities as well (Kolb, 1984; 2015; Kolb & Kolb, 2005; 2008).

Literature Review

Experiential Learning Theory

Experiential learning theory (ELT) highlights the critical role that experience has on impacting learning and change (Kolb, 1984; 2015). ELT defines learning as a continuous process of adapting to an environment by acquiring new information, challenging existing knowledge, and re-learning/integrating new knowledge into action. Kolb (1984) defines it as “a dynamic process whereby knowledge is created through transformation of experiences” (p. 41). This theory postulates learning as a holistic process for the student (Kolb & Kolb, 2009b) adapting to the world, which requires the integrated functioning of the total person, such as thinking, feeling, perceiving, behaving, and interacting (Kolb, 2015). Some educational sport studies applying ELT have shown success with this model (Bethell & Morgan, 2012; Sato & Laughlin, 2018). Additionally, more studies within the broader spectrum of sports, encompassing areas such as sports education, management, psychology, and sociology, have utilized Experiential Learning Theory (ELT) to gain a deeper understanding of the influence of sporting activities on individuals, groups, and organizations (Newman et al., 2017). Although most of the existing research has focused on evaluating the educational potentials inherent in diverse sport activities, scholarly inquiry has swiftly expanded to encompass sport-related learning platforms (e.g., sport internships, sport-for-development programs) that leverage sport as a mechanism for effective learning (e.g., Brown et al., 2018; Sattler, 2018). It is noteworthy that ELT has not been applied in the context of the YOG or the Olympic athlete (Cisek, 2023).

Ultimately the holistic nature of ELT will fit well with the complexity and holistic nature of learning in the YOG educational program formats. Indeed, the way in which athletes conduct their learning through the YOG educational programs (i.e., activities), shapes the course of their professional and personal development. The YOG educational programs offer an ideal immersion environment that facilitates intense experiential learning by impacting athletes and their multifaceted professional and personal development (see the full details in Appendix 1).

We suggest that the YOG’s educational programs are designed and capable of bringing participants through the four stages of the experiential learning cycle identified by Kolb and Kolb (2005), as shown in the ELT framework in Figure 1. The ‘concrete experiences’ are the cornerstone of each of the YOG educational program offerings, and are where the students (i.e., athletes) can participate in new learning (Sato & Laughlin, 2018). Furthermore, the ‘reflective observation’ stage is facilitated by reflection and feedback sessions to review the experiences (Kolb & Kolb, 2015). The ‘abstract conceptualization’ is enforced by analytical reflection during the duration of the program through the post-event stage. ‘Active experimentation’ occurs during the post-event stage and is where the individuals’ (i.e., athletes) experiences are formed through the realization of increased cultural abilities according, to Kolb et al. (2015).

Figure 1. Application of Experiential Learning Theory framework to YOG educational program (YOG EP). Experiential learning: Experience as the source of learning and development.

This completes the ELT cycle when new knowledge is applied to real-life tasks for the participants (Chan, 2012; Roark & Norling, 2010; Sato & Laughlin, 2018). Kolb (1984; 2015) claims that learning occurs through the combination of grasping (i.e., taking in information) and transforming (i.e., interpreting and acting on the information) experiences. Foundational experiences provide opportunities for observation and reflection for the YOG athlete. Reflection leads to new ideas or modification of old ideas. Changing ideas lead to new implications and form the basis for experimentation. The process of actively testing ideas through experimentation creates new experiences and the cycle continues for the athlete. The continual process of experience, reflection, thought, and action creates new knowledge and new behaviour (Sato & Laughlin, 2018). This means that athletes’ learning abilities must be involved in a continuous and cyclical learning process which focuses on experience and reflection in a holistic perspective (Kolb & Kolb, 2005). Additionally, according to Kolb et al. (2001), the learner can enter any of the four stages in the learning cycle, although for effective learning all four abilities of the ELT must be present. Arguably for a young athlete who takes part in one YOG in their life over a time of 10-14 days, it may be challenging to “act and reflection at the same time in a new environment and take some experience” (Lehan, 2020, p. 243). Although with the right implementation (and some previous learning experience in the athlete’s own life) the transition of the programs activity and learning has the potential to be meaningful (Lehan, 2020).

Therefore, through a document analysis we demonstrate which facets of ELT are most utilized, thereby allowing suggestions on how the educational programs of the YOG may benefit in the future with the implementation of a holistic ELT approach.

YOG Educational Themes and Principles

The educational programs that the YOG constructs for the athletes at each of the Games are based on Olympism and Olympic education (Naul & Binder, 2017; Staalstroem, 2021), and are optional for any of the athletes. These Olympic learning activities are grounded in five key educational themes (i.e., Olympism, skill development, well-being and healthy lifestyle, social responsibility, and expression) and are carefully selected by each host nation’s YOGOC in cooperation with the IOC (IOC, 2015). The skill development theme encourages athletes to develop new skills throughout life and in doing so also forge positive friendships based on mutual respect. The well-being and healthy lifestyle theme not only focus on athlete-centric health issues but also goes beyond the athletes’ immediate needs as they are encouraged to develop healthy living habits which will always remain with them. The social responsibility theme introduces the athletes to the idea of being role models in society for not only sport but also for environmental and/or humanitarian issues by drawing on the positive experiences they have gained from participating in the YOG education program. The expression theme encourages the athletes to fully appreciate that their pursuit of excellence in sport and life is a valuable contribution to society. Therefore, it is important for the athletes to be able to share their experiences in a responsible manner across all mediums (IOC, 2015, pp. 60–62; Staalstroem, 2021, p. 8).

Based on UNESCOS educational strategy and recommendations (IOC, 2008, p. 106), the IOC developed the YOG educational program learning strategy to address the five key themes with four fundamental learning pillars, conceptualized as the “4 pillars of Education.” These four pillars are classified as learning to know (e.g., educational sessions), learning to do (e.g., educational activities), learning to be (e.g., educational forums), and learning to live together (e.g., synergetic events consisting of celebrating cultures and traditions). Here we can see that the IOC and YOGOC program developers can set the athletes up for the opportunity to challenge their learning with activities that combine different learning modes representing Kolbs learning cycle. Through these four pillars there are opportunities to accommodate the different learning preferences for each individual (Kolb & Kolb, 2022).

Each YOGOC had to ensure the five themes were introduced through fun-filled activities to provide learning and development opportunities blended with sports and culture (IOC, 2012). The educational programs have continually developed into a more focused educational learning program for the elite athletes (IOC, 2019). Furthermore, the educational activities in the program are divided into two parts (IOC, 2015). First, the IOC includes a number of activities for the athletes which involve international partners such as the World Anti-Doping Agency, for example. Topics covered by these activities include Olympism, Olympic history, fair play, anti-doping, anti-betting, injury prevention, ethics in sport, abuse in sport, sexual harassment, healthy body image, athlete career management, the environment, humanitarian issues, peace, children’s rights, and social media. The second group of activities are proposed by the YOGOC with content based on the expertise of the local national organising committee and their partners.

Reflecting on the gap in current literature as described above, this study utilizes ELT to conduct a systematic analysis of all YOGs educational programs offered since their introduction in 2010. The following research question was established to guide the researchers through the research process:

RQ: How can the educational programs in the six YOG (and the way they evolved over time) be assessed and advanced through the experiential learning theory?

Methodology

Materials and Design

Before starting this section, a personality statement: It is important to acknowledge when this article was in its infancy one of the researchers is a three-time Olympian and had been involved in several YOGs in various roles over a decade (coaching and attaché). This researcher`s positionality influences this research including the choice of topic. Therefore, detachment and objectivity were a requirement for producing reliable knowledge during data collection (Bowen, 2009). Additionally, the rational for choosing one method was to suggest ELT in a practical setting for future research to add more value to the program.

To examine the research question stated above, a document analysis was conducted, which included all documents published by the IOC (see Appendix) that provided critical information (e.g., formats, designs, activities) on the educational programs implemented at the six previous YOGs. Viewed as a qualitative research method, document analysis entails a systematic process to review and assess both printed and online documents (Bowen, 2009). Documents are comprised of words and images that are created and shared independently from researchers’ involvement and interest in the YOG and its Olympic educational program. Scholars, such as Atkinson and Coffey (1997) consider documents as social facts to indicate that their usage and dissemination are compounded upon socially organized contexts. Through utilizing document analysis as the methodological lens, researchers aim to examine documents to elicit meaning and establish empirical knowledge (e.g., Corbin & Stratus, 2008) about the YOG educational programs activities over the six games in the history. While document analysis is often used in conjunction with other qualitative methods (e.g., interviews, participant observation) for the purpose of triangulation, it can be employed as the sole method, if its limitations are properly addressed. A common critique on employing a document analysis as the only method is related to its tendency to incur biased data selection and limitations on retrievability (Yin, 1994). However, these constraints were mitigated through applying a rigorous data collection strategy, wherein official documents and articles related to all YOG educational programs were collected in their entirety. Moreover, employing a document analysis is a suitable method to this research context, as it offers a sound way of tracking changes and developments of the phenomenon under scrutiny, which aligns with researchers’ intention to observe how the YOG educational programs have evolved over time.

Procedure

We used various databases to start with (e.g., PubMed, Google search, Google Scholar, EBSCOhost) searching for Youth Olympic Game AND education /educational/ program / programme and focused it inn on the Olympic World Library. To secure a comprehensive pool of documents to review and analyse, researchers identified official documents in the first round of the YOGs’ educational programs published by the previous YOGOCs and the IOC. The screening process excluded non-English documents, all per review articles (as non has used ELT in any YOG studies), Paralympic Games and duplicates. Such an approach allowed the researchers to include a diverse focused range of documents (e.g., YOGOCs’ official report, IOC documents on candidature procedure, event manuals, press release on educational programs, post-event reports, program description, YOGOCs’ pre-event promotion materials).

Through data extraction and analysis, we followed a thorough review of documents, data were organized into distinct formats from each YOG according to the activities held, and by reflecting on the research question. The use of thematic analysis enabled identification of emerging themes within each YOG context. This process entailed two authors individually coding the refined data and subsequently engaging in discussions to actively share their interpretations until a consensus was reached, which, in turn, ensured intercoder reliability (Creswell, 2012). Each author carefully examined the data and conducted coding and category construction (six YOG in total) to uncover formats used. They represented various contents from each of the six YOGs’ educational activities, which were then scrutinized through the four elements of ELT.

Results and Discussion

The YOG educational programs have constantly evolved since their inception in Singapore 2010, as they have become more complex and ambitious regarding what they hope to accomplish. Based on the analysis, a shift away from philosophical cantered objectives to more practical elite athlete focused, and individual personal development objectives has occurred over the course of 10 years. Within the following sections, the results of the document analysis and the specific educational formats offered by the YOG are introduced and then compared based on their fulfilment of ELT criteria.

YOG Singapore 2010 Educational program

Singapore held the inaugural YOG in 2010 focusing on the Olympic movement, athletes’ development, and their roles and responsibility in sports practice and society (IOC, 2011, p. 5). During the 13 days, 3,524 athletes from 205 nations were exposed to the five key themes implemented through 50 different activities in seven educational formats described hereafter (IOC, 2012, p. 7; SYOGOC, 2010). The activity, ‘Chat with Champions’ consisted of athlete role models sharing their experiences and mentoring athletes during competition and at other activities. The forums offered different topics for athletes to share the athlete role models’ experiences of excellence, friendship and respect, in addition to answering the young athletes’ questions in a talk show format. ‘Discovery Activities’ were interactive exhibitions and workshop activities that were held for athlete to learn about important topics to use in personal development. ‘World Culture Village’ was a booth area hosted by local Singaporeans where athletes were able to interreact with cultures of the countries represented in the YOG, and included dancing, singing, body paining and traditional games. ‘Community Project’ was where athletes could participate in activities together with local organizations to learn the importance of social responsibility and to be inspired to take part in their own local community at home. ‘Arts and Culture’ was a group of activities aimed at celebrating Olympic themes such as youth, culture, and friendship through the mediums of dance, art, and music. ‘Island Adventure’ was utilized for athletes to learn the values of mutual respect, friendship, and teamwork in sport through confidence building courses with water activities and other challenging physical activities. Finally, ‘Exploration Journey’ was a “green day” experience with a terrarium workshop and garden tour, as the athletes learned about the ecosystem.

YOG Innsbruck 2012 Educational program

Innsbruck 2012 in Austria, the inaugural games for winter sports, aimed to deliver lasting benefits and develop enthusiasm for sport among young people, building on the Olympic Spirit and using the Olympic values of excellence, respect, and friendship for the 1,022 athletes representing 69 nations (IOC, 2016, p. 4). Athletes were introduced to the education program by young ambassadors and athlete role models. The Innsbruck program delivered 27 activities based around six formats, described hereafter (IOC, 2012, p. 9: IYOGOC, 2012). An innovation at Innsbruck 2012 was the introduction of the Yogger, a USB device with information about the program and activities. The Yogger was created to build awareness of the education program and thereby increase attendance (IYOGOC, 2012). An activity called ‘Media Lab’ was available for athletes to become educated on how to create media content (including four workshops), how to express themselves, and how to safely use social media. ‘World Mile Project’ educated athletes on tradition in art, sport, music, culture, lifestyles, clothing, language, and famous personalities. Interactive workshops and exhibitions by the IOC’s partners on global topics were utilized. ‘Sustainability Project’ taught athletes about environmental issues and sustainable developments, such as being waste wise, saving water and electricity, mountain awareness, and minimizing nature risks. ‘Art Project’ allowed athletes to share experiences and express themselves through modern art, music and dance. A ‘Competence Project’ was used to facilitate interaction between athlete role models allowing them to educate the athletes on aspects that professional athletes need to balance and be aware of. Finally, a ‘Youth Olympic Festival’ educated athlete through teambuilding activities in hopes for new friendships and networking.

YOG Nanjing 2014 Educational program

The slogan for Nanjing 2014 in China was “Share the Games, Share our Dreams” for all the 3,759 athletes from 202 countries (NYOGOC, 2014). The vision of Nanjing YOG was “to praise young people, advocate for a balanced development of blending education and sport, and to raise awareness about Olympic spirit and the Olympic values of excellence, friendship and respect,” (IOC, 2016, p. 2) which all linked back to the core of the YOG. The 50 educational activities in five different formats are described below, “embodying the Olympic values” (NYOGOC, 2014, 2015, p. 17). The program was introduced to the athletes in a “Let’s Get Together” gathering to inspire them to be active and magnify their learning opportunities (NYOGOC, 2014). At Nanjing 2014, the Yogger innovation from Innsbruck 2012 was upgraded to online access. Nanjing 2014 also introduced the Learn and Share environment to describe the areas where the educational activities took place (NYOGOC, 2015). The ‘Youth Festival’ activity was used to educate athlete through experiencing different traditions and cultures with sport activities from the Chinese culture in dance, music, opera, and martial arts. ‘Boost Your Skills’ combined forums, discussion, mentoring and sharing to allow athletes to learn more about social issues through being exposed to global issues, workshops on fair play and peace promotion among others. This activity emphasized the importance of a supportive network to help athletes maintain a dual career, with a stronger understanding of time management to help them throughout their daily life as young athletes. ‘World Culture Village’ again hosted booths about cultural diversity around the world. ‘Discover Nanjing’ allowed athletes to visit interesting historical and cultural attractions, as athletes visited the famous Ancient City Wall. More trips were used to educate athletes on not just the Chinese culture but the importance of taking care of the environment as well. Finally, ‘Digital and Social Media’ was an activity for media training by experts, and the introduction of new technologies.

YOG Lillehammer 2016 Educational program

Lillehammer in Norway hosted the second YOG for winter sports in February 2016, with 1,060 athletes from 71 countries and the slogan of “Go beyond and create tomorrow”. The Lillehammer YOGOC wanted the educational activities to be the foundation of the YOG to offer the sports community the option “to share experiences for the local young people, athletes and other participants, equip them with the key skills to become sports champions on the field of play, and life champions off the field of play” (IOC, 2016, p. 6). The 33 interactive activities once again centred on the five key themes and were delivered by five formats summarised below (LYOGOC, 2016). The ‘Your Career’ activity allowed athletes to see what they would need to know after their sporting career had come to an end by teaching them about time management and networking. ‘Your Body and Mind’ educated athlete on injury prevent, clean sport without doping, safe sport, in addition to the emphasis on understanding the importance of motor skills, mental training, and good nutrition. ‘Your Stories’ gave insights into athletes on how to tell their own story (via media training). Finally, ‘Your Discovery’ educated athletes on Norwegian winter sport culture through the Olympic history.

YOG Buenos Aires 2018 Educational program

Buenos Aires hosted in 2018 with the motto feel the future. Doing so by implementing the vison to bring sport closer to the people in sport, cultural and educational celebration by celebrating younger and more urban games (BAYOGOC, 2018). It was also an event with a focus on gender equality with participation of 3997 YOG athletes with equal gender split from 206 nations. During these Games the educational program and formats had been developed further by representatives from the IOC and Olympic stakeholders by having less locations and comprised of activities that are focused on the athletes’ sports career and individual development” (IOC, 2018a, p. 97). The Athlete365 digital platform was also being actively seen for the first time at the games with hands on activities incorporated in Learn and Share education program area, Athlete365 Space, a program geared towards conveying the importance of clean (non-doping) athletes, good sportsmanship, and fair play in sport. ‘Performance Accelerator’ educated athlete on how to be responsible by learning more about injury prevention and strength training techniques. ‘Gamechangers Hub’ was a media training activity on how to maximize digital and social media in professional and personal lives. This activity allowed athletes to understand the best way to express their point of view and how to create awareness about themselves. ‘IF Focus Day’ was an activity with selected objectives linked to the young athlete’s development of new abilities and skills for personal and career development using the Olympic values of excellence, friendship and respect. ‘Chat with Champions’ was again introduced by having young athletes interreact with Olympians on personal, sport, and professional endeavours.

YOG Lausanne 2020 Educational program

The city of Lausanne held the 2020 YOG with the slogan “Start Now.” This was now the third winter YOG in the history, with 1788 athletes from 79 nations competing in the city of the IOC headquarters in Switzerland. For the first time we see that the education program is called “Athlete365 Education Programme” with activities that link to the IOCs Athlete365 universal digital platform developed by athletes for athletes in cooperation with the IOC (IOC, 2020a, p. 181). It incorporated Olympians, five educational formats, and around 20 educational activities (LAYOGOC, 2020; IOC, 2020b, pp. 3-6).

The activity named ‘Awareness’ educated athletes on how to be responsible young ambassadors of their sport by playing without doping, fighting against corruption, and learning to prevent abuse. Additional components of this activity allowed athletes to be taught how to balance sport and education, time management, and networking. The ‘Health for Performance’ activity educated young athletes to be aware of how to develop their performance, learn about injury prevention, and who to talk to in tough situations. ‘Game Changer HUB’ educated athletes on how to produce and show their own video content and prepared them to participate in a live TV show on the Olympic Channel. ‘Chat with Champions’ and ‘IF Focus Day’ were again introduced, highlighting the perceived benefit and success of running these types of educational program activities.

Using the Educational Learning Theory (ELT) as its foundational framework, this research rigorously investigates the extent to which the International Olympic Committee (IOC) is effectively accomplishing its objectives, delineated through the five fundamental themes that underpin the educational programs during their implementation. With new and former Olympians, it is important to continue to inspire development and monitor the YOG athletes’ educational needs as it is a valuable place for learning and sharing knowledge. The next section discusses the key application of the theoretical ELT (Kolb, 1984, 2015, 2022) concept to the YOG educational program.

YOG Educational Programs Comparison and Evolvement

The investigation revealed an imbalance in experiential educational activities within the YOG and that were offered to the 15,157 athletes, as this part of the ELT process was absent from most of the Games. It was also discovered that experiential educational YOG activities were not fully balanced as a majority of the formats and activities were the activities that utilized concrete experiences. Reflection observations became more prevalent with each iteration of the YOG, as was the same for abstract conceptualizations. The only active experimentation came from the ‘Game Changer HUB’ (former media and social activities), which obviously saw enough success and was easy enough to facilitate that it was worth incorporating in two separate Games. Although the athlete can enter Kolb’s learning cycle at any time, this activity shows opportunities to align new knowledge out in real life (Kolb, 2015). While the concrete experiences are clearly covered, as the other components of ELT are examined, demonstrated by the presence of certain dimensions are missed, indicating a gap between what has been seen as successful and beneficial constructions of ELT and what is currently utilized. The mapping of 6 YOGs educational programs formats across corresponding ELT components is presented in Table 1.

Table 1

Mapping of learning formats for YOG EP 2010-2020 through the lens of ELT.

YOG	Format	Corresponding ELT Components
		CE	RO	AC	AE
Singapore 2010	Chat with Champions	*	*
	Discovery Activities	*	*	*
	World Culture Village	*
	Community Project	*	*	*
	Arts and Culture	*
	Island Adventure	*
	Exploration Island	*	*
Innsbruck 2012	Media Lab	*	*	*	*
	World Mile Project	*
	Sustainability Project	*	*	*
	Arts Project	*	*
	Competence Project	*
	Youth Olympic Festival	*
Nanjing 2014	Youth Festival	*
	Boost Your Skills	*	*	*
	World Culture Village	*
	Discover Nanjing	*	*
	Digital and Social Media	*	*	*	*
Lillehammer 2016	Your Actions	*	*	*
	Your Career	*	*	*
	Your Body and Mind	*	*
	Your Stories	*	*	*	*
	Your Discovery	*
Buenos Aires 2018	Athlete365	*	*	*
	Performance Accelerator	*	*	*
	Gamechanger Hub	*	*	*	*
	IF Focus Days	*
	Chat with Champions	*	*
Lausanne 2020	Awareness	*	*	*
	Health for Performance	*	*	*
	Gamechanger Hub	*	*	*	*
	Chat with Champions	*	*
	IF Focus Day	*

Note: CE = Concrete Experience, RO = Reflective Observation, AC = Abstract Conceptualization, AE = Active Experimentation.

Active conceptualisation sessions (like sessions or activities capable of stimulating analytical reflection or challenging the current stereotypes and mind views) unfortunately are fragmented and cannot be described as equally represent in the curricula. With respect to the active experimentation stage, initiatives like Athlete365 activities in later games created actual opportunities for athletes to continue the developmental journey on the Athlete365 digital platform after the YOG. Meaning, the IOC have an opportunity to continue to influence the experiential learning to increase athlete’s knowledge (Kolb & Kolb 2009a). The only suitable example which we identified was the Gamechangers Hub format during 2018 and 2020, where the opportunity for reflection, awareness of unique selves, and experimenting with new conceptualizations was minimal. Still, though, active experimentation was undervalued and not utilized properly. We could conclude from the mapping in Table 1 above that predominant attention is given to unique memorable and diverse experiences, and to some extent physical tests for health and injury training prevention, with a slowly increasing number of reflection and conceptualisation opportunities.

Theoretical and Practical Applications

ELT has been employed in many academic disciplines, such as studying abroad (Iskhakova et al., 2020), music education (Russell-Bowie, 2013), physical education (Bethell & Morgan, 2012), sport psychology (Sato & Laughlin, 2018), engineering (Chan, 2012) and hospitality (Fallon & Daruwalla, 2004), including outdoor education (Roark & Norling, 2010) and global leader development (Fey, 2020).

Furthermore, previous results have demonstrated that when university courses utilize the ELT framework, students develop a deeper knowledge of the subject matter (Bethell & Morgan, 2012), increase their sense of competence in target skills (Roark & Norling, 2010; Iskhakova et al., 2020), gain a better understanding of the link between theory and practice, and achieve greater personal development (Sato & Laughlin, 2018; Chan, 2012; Fallon & Daruwalla, 2004; Russell Bowie, 2013; Fey, 2020). Despite the high potential that ELT has, as previously discussed, it has scarcely been utilized in in the context of Olympic athletes (Cisek, 2023).

The current investigation examined ELT and discovered a lacking adherence to each of the dimensions in this theory by the YOG educational programs, as is critical for learning to occur (Kolb, 2015). This novel finding aids literature pertaining to ELT as the document analysis clearly indicates the dimensions of the theory that are more heavily, or easily, incorporated in YOG educational programs. The goal of this investigation was to examine the application of ELT in a practical setting, in the YOG context, thereby allowing future researchers to evaluate which facets of the theory (Kolb, 1984, 2015) are underutilised and can be enhanced in the YOGs context. Utilizing a document analysis, Table 1 was constructed to illustrate and map the learning formats of past YOG educational programs through the lens of ELT. Examining each of the four stages of ELT (Kolb, 1984, 2015) in the context of the YOG educational programs indicates an underutilization of certain key stages across all YOGs programs. With the benefits that are derived from a full utilisation of ELT, it is posited that further incorporation of activities within certain stages would make the YOG educational programs more impactful in both the short and long term. In ELT studies development and change is essential, as the programs should be flexible and creative as they explore ways of facilitating athletes’ learning effectiveness (Kolb, 2001; Kolb, 2015; Sato & Laughlin, 2018). Demonstrably, at the inception of the YOG in 2010 very few reflection opportunities existed in the educational program, juxtaposed to the current prevalence of this activity.

As Sato and Laughlin (2018) state, a successful integration of ELT allows athletes to take control and responsibility of their learning, instead of passively receiving experience and knowledge. Kolb (2015, p. 299) call this to take active ownership and responsibility of their learning cycle. Therefore, more ‘reflective opportunities’ at each timepoint should be created. With a greater emphasis on experiential activities, accommodations such as time for in-depth reflections should be implemented. More ‘abstract conceptualizations’ and ‘active experimentations’ should be incorporated and facilitated. An increase in these stages means athletes will be given more opportunities to assimilate their lived experiences and reflections into abstract concepts, thereby challenging and evaluating their own world views and values and advancing own development for a long-term horizon (Kolb & Kolb, 2009a; Kolb, 2015).

If the IOC (2019) wants the YOG to be a steppingstone for these athletes before the Olympic Games and a developmental platform that focuses on the holistic athletic development, the IOC should implement Kolb’s theory to a greater extent.

Limitations and Future Studies

As majority of studies, our study is not free of limitations. The first limitation relates to the methodology. While novel findings pertaining to the usage of certain stages of ELT were discovered, the benefit of these activities were not measured. As the analysed documents were produced by the YOGOC and the IOC, understanding from the educators, administrators, and athletes viewpoint are not observed. While the methodology was purposefully selected to accomplish the desired analysis (Bowen, 2009), this limitation is present. Furthermore, there may have also been selected educational learning activities that were adjusted when they were presented. We suggest future scholars to examine the unique impact of the YOG educational programs through various other lens, such as other learning theories, social theories (Parent et al., 2019), personal development theories, and cultural theories.

Disclosure statement

The authors report there are no competing interests to declare.

Appendix 1

A description of the 14 core documents that were included in the data analysis.

Title	Author (year)	Document type	Description
Singapore 2010 YOG. Blazing the Trail.	SYOGOC (2010)	Report	This official document describes the beginning of the YOG -2010 games. Presentation of the games with sport, education and culture, to go beyond the games.

IOC. Factsheet: YOG.	IOC (2012)	Document	Discusses birth of the YOG, its vision, programs, and five educational key themes.

Innsbruck 2012 YOG. Be part of it.	IYOGOC (2012)	Report	Report on the implementation, management and delivery of the first Winter YOG

Chef de Mission Manual. Nanjing 2014 Summer YOG.	NYOGOC (2014)	Manual	Describes policies and procedures for the YOG-2014, with information on learning program and five educational key themes.

YOG Event Manual. 7th Edition. May 2015.	IOC (2015)	Manual	Contains the main requirements for planning, organisation and staging of the YOG, including its learning program.

Share the games share our dreams. Official Report of the 2nd Summer YOG Nanjing 2014.	NYOGOC (2015)	Report	This is the official report from Nanjing YOG 2014 presents the events timeline with sport, culture, and education.

The YOG learn and share beyond the field of play. Factsheet YOG	IOC (2016)	Document	This updated factsheet version brings up the vision and mission with culture and education in the YOG. With the learn and share activities concept it states the five key educational themes through formats with educational activities from the four first YOG in the history (2010-2012-2014 and 2016).
Lillehammer 2016 YOG. Be part of it! Go Beyond. Create tomorrow.	LYOGOC (2016)	Report	This is the official report of the Lillehammer 2016 Winter YOG. This report tells a chronological story step by step with texts and images through the games to includes sport, culture and education.

Buenos Aires 2018 Third summer YOG.	BAYOGOC (2018)	Report	This document is the official report of the Buenos Aires 2018 with imagery and texts that takes the reader through its history from the torch relay, to celebrate of sport and urban games with activities.

IOC. Chef de Mission Manual Buenos Aires 2018 YOG.	IOC (2018a)	Manual	Contains the main requirements for planning, organisation and staging of the Buenos Aires YOG for the NOC. It includes the learning program among other detailed information on game time aspects.

IF focus day booklet Buenos Aires 2018 YOG.	IOC (2018b)	Booklet	Contains the educational activities International Federation, in coordination with Buenos Aires 2018 YOG Organising Committee have develop for athletes to strengthen personal and career development.

IOC. Factsheet: The YOG compete, learn and share beyond the field of play.	IOC (2019)	Document	Provides a description of the YOG as a steppingstone in the young athletes learning pathway, in sport and beyond their sport. It explains how the IOC contributes with learning activities, and how the YOGOC has some flexibility within a now more athletes centred formats then previous YOGs. The document states some facts on all six YOG`s educational programs. (2010-2012-2014-2016-2018 and 2020).

IOC. Lausanne 2020 Chef de Mission Manual	IOC (2020a)	Manual	Contains main requirements for planning, organisation and staging of the Lausanne YOG for the NOC. learning program among other important aspects of the games to prepare the athletes for.

Athlete365 Education Programme. Lausanne 2020 YOG	IOC (2020b)	Document	Presents the Athlete365 educational programme to the athletes and their entourage during the Lausanne 2020 YOG.

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Qshequilla Parham Mitchell2024-09-05T09:14:19-05:00August 23rd, 2024|Olympics, Research|Comments Off

Perceptions of Former Collegiate Athletes on Career Transition Programs in the NCAA

Authors: Cameren Pryor¹ and Lindsay Ross-Stewart²

¹Department of Psychology, University of North Texas¹

²Department of Applied Health, Southern Illinois University Edwardsville

Corresponding Author:
Dr. Lindsay Ross-Stewart
Campus Box 1126
Southern Illinois University Edwardsville
Edwardsville, IL, 62026
[email protected]
(618) 650-2410

Cameren Pryor: Cameren Pryor is a third-year doctoral student in Counseling Psychology with a concentration in Sport Psychology at the University of North Texas. Cameren’s research interests focus on athletic career transition/sport retirement, athletic transition psychoeducation/programming, and student athlete mental health.

Lindsay Ross-Stewart: Dr. Ross-Stewart is an Associate Professor in the Department of Applied Health at Southern Illinois University Edwardsville. Dr. Ross-Stewart’s research is grounded in Bandura’s concept of self- efficacy and its role in behavior change. Dr. Ross-Stewart is an Association for Applied Sport Psychology Certified Mental Performance Consultant (CMPC®) and a Canadian Sport Psychology Association Mental Performance Consultant (MPC).

Perceptions of Former Collegiate Athletes on Career Transition Programs in the NCAA

ABSTRACT

Many student athletes experience feelings of grief, sadness, loss of motivation, and depressive symptoms due to improperly preparing for sport retirement (1). Past literature encourages practitioners to incorporate psychoeducational programming into NCAA athletic programs that better prepare athletes for transition. However, it has been found that there is a lack of consensus on when and what is being advised to student athletes about the transition process (2). Additionally, little research has investigated the overall effectiveness of NCAA collegiate career transitioning programs through the perceptions of student athletes. The purpose of this study was to investigate if current career transition programs in NCAA Athletic Departments were using best practices, as defined by the current research in the field, based on former collegiate athlete’s perceptions of their experience with career transition programming. A secondary and equally important purpose was to investigate the overall impact athletic career transition had on former collegiate athletes’ current lives. Former collegiate student athletes completed semi – structured interviews via Zoom to assess their experience with career transition programming during their time as an athlete and the level of effectiveness they felt the program offered. The findings of this study suggest that NCAA athletic departments need to implement effective athletic career transition programming that better prepares student athletes to transition from collegiate sport.

Keywords: career transition, qualitative research, sport psychology

College student athletes dedicate approximately 70 hours per week to athletic and academic demands (3). With less than two percent of National Collegiate Athletics Association (NCAA) student athletes competing on the professional level (4), most student athletes will transition out of athletics when they graduate from university. This transition time led to increased feelings of grief, sadness, loss of motivation, and depressive symptoms for some athletes (1). To prevent these negative experiences, career transition researchers have encouraged athletic departments to implement psychoeducational programming that better prepares student athletes for the psychological, behavioral, and social outcomes of sport retirement (5). However, it has been found that there is a lack of consensus on when and what is being advised to student athletes about the transition process (2). Additionally, little research has investigated the overall effectiveness of NCAA collegiate career transitioning programs through the perceptions of student athletes.

A recent literature review of career transition research (6) found there were very few studies conducted in the United States concerning athletic transition, with the limited findings highlighting retirement planning, identity loss, coping skills and support systems as the core areas that have been investigated. They reiterated the importance of psychoeducational interventions; however, they acknowledged that more research is needed to better understand the transition process and how to effectively implement career transition programing.

Past research has also highlighted the findings that career transitions appear through social, developmental, and psychological factors (5) and the importance of starting career transition education at the earliest stages of sports participation. The importance of social support has been supported by the work of Adams et al. (7) who found participants experienced a more positive transition if they felt cared for by the people that they believed understood them and what they were going through. Thus, a sense of closeness and trust between the recipient and the person providing support appeared to be crucial for support during career transitions. Of importance was the finding that athletes perceived coaches to provide more social support than parents and teammates indicating coaches should be a central part of career transition programming. Cummins and O’Boyle (8) found that athletes perceived their universities as unable to support them during the transition process with support, career advice and information on the professional role and guidance from past student athletes. Thus, the lack of career control was shown by all participants. Cummins and O’Boyle (8) recommended implementing mentoring into university programs from former student athletes to current student athletes on the transition process and potential career opportunities.

Along with social support, one’s athletic identity has been highlighted as impacting an athlete’s experience with career transition. Specifically, the more an athlete identifies with their athletic role, the less likely they are to have a well-defined career plan (9) and therefore struggle during career transition. Furthering this finding, researchers found that athletic identity was positively correlated to retirement outcomes and negatively correlated with decreased self-esteem, feelings of uncontrollability and ‘vagueness’ about the future (10). It has also been shown that athletes who retired due to injury have greater adjustment difficulties (10). Furthermore, researchers found that the strength and exclusivity of the athletic role during sport participation increased an athlete’s potential vulnerability to psychiatric distress after leaving sport (11), and higher levels of emotional adjustment difficulties (12). In contrast to these negative connections to athletic identity, Cabrita et. al, (13) found that athletes with higher athletic identity have higher levels of career decision making self- efficacy. They suggested this may be due to the efficacy they gain from sport transferring to their career decision making efficacy. Further research is needed to better understand these potentially conflicting findings on the relationship between athletic identity and career transition.

Menke and Germany (14), identified consistent themes athletes identified when discussing their feelings and thoughts related to coping with transition out of sport including the positive of gains or strength of transferable skills as well as the negative experiences of a loss of identity, feelings of loss, sadness, anxiety, loss of motivation and depressive symptoms. It has been shown that global self-esteem and physical self-perceptions decreased during the transition out of elite sport (15). Additionally, it was found that retired athletes that experience difficulties with their bodies have decreased feelings of pride, satisfaction, happiness, and confidence regarding their physical selves. These experiences can contribute to stressful reactions to retiring out of sport. Of extra importance is the finding that sport individuals that experience bodily changes accompanied with high athletic identity can experience increased psychiatric distress and self-esteem issues when transitioning (15).

Taken together, the above information highlights the need for career transition programming and combining a plan for post-sport retirement with talking about the emotions experienced during the transition process. Past researchers have suggested that sport psychology practitioners and mental health professionals work with athletic teams to encourage the development of the student athlete by consistently speaking to them about career related topics and encouraging student athletes to explore and engage in expanding their interests outside of sport as well as supporting the use of health care resources for former high-level athletes (16).

During sport retirement, many athletes cognitively make the decision to grieve the loss of their sport by participating in healthy and unhealthy coping behaviors for extra support. Acceptance, account making, positive reinterpretation, planning, active coping, mental disengagement and seeking social support for emotional reasons are all strategies that have been reported (12). Account-making (the construction of a story about a traumatic event (i.e., it’s nature, what happened, how one feel’s about it, and what it means for the future; citation) and confiding (portions of one’s account, are revealed to others) has also been shown to be an effective tool as it helps athletes to understand their retirement experience, understand their emotions and to acknowledge an identity that is outside of sport.

Recent literature reviews have encouraged viewing transition from a lifespan perspective involving pre-career, post-career, and other domains of an athlete’s life (17), and preparing for retirement before it happens, creating a strong alliance with trust (client and counselor), exploring the emotions accompanied with the transition, interventions, and knowledge of transferable skills, addressing athlete’s overall competency of transferable skills, developing a support network, and evaluating the effectiveness of the athletes transitions out of sport and the effectiveness of counseling interventions. Based on the literature review, the researchers recommended that counselors may be effective in assisting athletes to plan for life after sport by helping them understand and realize that the skills they have acquired through sport can help them be successful in other areas of life (18).

Furthering our understanding of best practice, researchers have recommended empathy and attentive listening need to be utilized to help athletes make sense of their experiences and it has been recommended that programming should look at the development of interventions from different psychological perspectives for athletes in transition (5). Overall, researchers suggest the need to examine the effectiveness of these models and devote attention to interventions from different psychological perspectives. Lastly, they highlight the finding that helping athletes become aware of the transferrable skills can help facilitate successful career planning.

Researchers have continuously suggested the need for psychoeducational interventions that address the psychological, behavioral, social effects and the loss of athletic identity has on a sport individual when transitioning from sport and the need to start this programming early in an athlete’s college career (e.g., 5). Being that there is a lack of consensus on when and how to speak to athletes about career transition, and a lack of connection between research suggested guidelines and applied programming at the college level, further understanding of this area is needed. Thus, the primary purpose of this study was to investigate former NCAA athlete’s perceptions of current career transition programs in NCAA Athletic Departments. A secondary purpose was to investigate former collegiate athlete’s perceptions of their experience transitioning from sport and how these experiences affected their current lives.

Materials and Methods
Methods
Setting, Recruiting, Sampling, and Consent

All participants were recruited via social media. Posts were made on both researchers’ Instagram, Facebook, and Twitter pages, as well as shared on their program social media sites. People were encouraged to share the posts with people they may have known who would be interested. Potential participants were instructed on how to reach the primary researcher if they were interested in participation. The primary researcher then spoke with each potential participant to make sure they were a former NCAA athlete who finished their career within the last five years but did not suffer a career ending injury or quit their college career (which were the exclusion criteria). Those that qualified were interviewed over zoom for this study. Zoom was chosen as it allowed for participants from across the United States and increased the accessibility of the study to participants. Prior to the interview the participants were sent the informed consent form and gave consent to participate. They then gave verbal consent on zoom while the session was being recorded. Participants were also given the opportunity to ask any clarification questions about the study they may have had after reading the informed consent.

Participants

The participants of this study were six retired collegiate student athletes who previously competed in NCAA athletic programs and completed their athletic careers in the five years. The participants were two males and four females. Participants were represented from various sports consisting of basketball, track & field, softball, baseball, and golf. The athletes were from Division I (n=four), Division II (n=one), and Division III (n=one).

Data Collection Tools

Career Transition Interview

As there is a lack of set tools for assessing the psychological impact of career transition for college athletes, and to hear the voices of those who have experiences career transition, – semi structured, questions (some open and some closed based on need) were developed for this study. The goal was to allow the participants to reflect on their personal experiences with career transition programming at the universities they competed in and their overall transition experience. The important themes recognized in previous athletic career transition literature were used to develop questions for the interviews focused on their career transition program experience and their experiences post-tradition career. A specific focus was made to keep the questions neutral in language so as not to lead the participants in any direction. During the interviews, based on the participant’s comments, follow up questions were asked, and discussion was encouraged with the athlete to gain their views outside of the predetermined questions, as needed the closed questions were aimed at understanding the organization of any career transition programing they may have had during their athletic career (e.g., “Did your university have an athletic career transition program or workshop? And “How often did this program occur at your university?”) as well as understanding their demographics (e.g., “What is your age” “What sport did you play”). year were you when you participated in this program?). To better understand their experiences and truly give the participants a chance to process their experiences in their own words, open-ended questions were used. Example questions included “What was your athletic career transition experience like?,” “How did transitioning from sport make you feel?” and “During your transition experience, what did you do/not do to cope?

Procedures

Data Analyses

A six phase Reflexive thematic approach was used with the essentialist/realist method for qualitative data (19-22). This method is used to identify, analyze, and report patterns (themes) within a given data set. Additionally, it is used to describe and interpret the meaning and importance of the patterns (themes) found. The Essentialist/Realist method is used to report experiences, meanings, and the reality of participants (19), which was used to analyze the perceptions and personalized experiences from former collegiate athletes. Of importance for this approach is to acknowledge that we all perceive the environment and impact it through those perceptions. Therefore, giving as much room for the exact voice of the participants is needed to minimize the participants experiences being reported through the researcher’s lens alone. Therefore, this paper gives significant space to each participant’s voice, which is possible due to the sample size of six people. Utilizing the ‘top-down approach’ also known as deductive approach (23), this study analyzed semantic themes that are suggested within previous career transition literature to implement into athletic career transition programming for student athletes However, ideas that emerged that did not fit within current literature were also noted and coded to add to the already existing literature. In qualitative research, the researchers and coders must assess their biases and perceptions as it relates to the research topic. In this study, the data was coded by two coders, the primary researcher, a former collegiate athlete whose career ended two years before data analysis recognized that her own experiences were a potential bias to the study. Therefore, several methods of checking trustworthiness were used (See Trustworthiness section below). The second coder was not involved in the study at all and was not a former collegiate athlete, nor were they familiar with the literature in the area.

Following the guidelines of Braun and Clarke (19-23) both coders followed a six-step process. Prior to coding all interviews were electronically transcribed using zoom transcription services, and all transcriptions were checked for accuracy against the recorded interviews. To start the coding process both coders familiarized themselves with the data by reading all the transcripts. The coders then independently recorded points of interest in the transcripts as they began to generate the initial codes, making sure to code each piece of data available. Data could be an individual word (e.g., the answer “yes” to a closed question) or as long as a few sentences (e.g., “Even though I did not struggle a lot, I think it still would have been nice to have a transition program in those later years of college just to learn how to be an adult on your own without sports ruling your life”). Focusing on the context of a comment opposed to the length when deciding on a code was done in line with the recommendations of past researchers (e.g., 20). Next, coders began to develop themes with past research in career transition in mind. Again, this deductive approach did not mean discarding data that did not fit in a prior identified theme, but instead recognized past information while new themes that emerged were also identified and titled with this new information being an addition to our current understanding of the career transition experience in the field. The coders then compared their codes and themes and when in disagreement engaged in thoughtful discourse explaining their rationale for their coding choice, while being cognizant of their potential biases. This process led to agreement between the coders in the few places where there was initial disagreement. Finally, the overall themes and codes are explained in detail in this manuscript as is noted as an important step in thematic analysis.

Trustworthiness

Trustworthiness was assessed in multiple ways to increase the credibility, transferability, dependability, and confirmability of the study (19-22;24, 25). In addition to an acknowledgement of the researcher’s viewpoint and the reality that all researcher’s perspective’s impact their analysis, both coders of the data assessed their own views and were systematic in assessing the impact of these views throughout the research. Furthermore, as the lead researcher of this study was a former NCAA athlete, and as such recognized that this may have led to potential biases peer debriefing was used to increase credibility. Furthermore, a third coder, who was familiar with the research in the field but did not conduct the interviews or participate in the original data analysis was brought in to engaged in negative case analysis to assess any divergent data and discuss these findings to make sure they were appropriately accounted for in the data coding. Internal auditing was also done by two researchers who were not a part of this study, nor familiar with the research on career transition in sport, to highlight and address any potentially biased interpretations of the data. The detailed documentation of the procedures used for this study at each stage following the guidelines of the APA Journal Article Reporting Standards for Qualitative Research (2018), along with using thick description in this manuscript was done to increase dependability and transferability.
Results
The major themes that emerged throughout the data were lack of athletic career transition programming, high athletic identity, lack of psychological support, social support, coping mechanisms and the Covid-19 pandemic. Note that participants’ names have been changed to maintain confidentiality. Pseudonyms given are representative of names that match the self- reported gender and race of each participant.

Lack of Athletic Career Transition Programming

It was found that four out of six participants experienced a positive overall career transition from athletics and described their experience as ‘easy’ and ‘smooth sailing.’ However, two of the participants in this study experienced a negative overall career transition from athletics. When it came to access to career transition programming, only two of the participants had access to transition programs from their universities. Example comments related to this are included Leah commenting, ‘I don’t even know where to begin, I felt so unprepared to go out into the world.’ and Andrea stating, ‘My transition experience was a little rocky and it had an effect on how I was mentally.’ Mary said, ‘Even though I did not struggle a lot, I think it still would have been nice to have a transition program in those later years of college just to learn how to be an adult on your own without sports ruling your life.’ Two participants recalled their athletic departments referring them to their on-campus career center for career assistance. For example, Kelly noted, ‘The programs that were available to me via the career center were focused on interviewing skills, portfolio/resume building and career fairs; none of these events catered to my athletic experience.’ Andrea who did have access to career transition programming, indicated that their school had the NCAA Life Skills Program (NCAA, 1994). She stated, ‘I definitely found this program to be helpful and I felt as though I needed those skills to be able to transition from college into the outside world.’ Although Andrea spoke highly of the Life skill program at her previous university, she still reported a negative transition due to the COVID-19 pandemic. Chance recalled his previous athletic department hosting optional career transition programming that he did not attend due to the programs conflicting with his schedule. ‘I felt like it would have been helpful, I just did not feel like I had the time to do it with athletics and my class schedule.’ When looking at the differences between programming across the three different division levels present in this study, both Andrea and Chance were in Division I programs. Chelsea, who participated within Division III stated, ‘We weren’t provided with a lot of resources being the lower level and I think it had to do with finances as well as compliance.’

When asked what participants would value within athletic career transition programming, participants noted the importance of programming on financial topics (budgeting, taxes, financing vehicles and homes), programs for juniors and seniors on resources for transition. For example, Chelsea stated, I think a big topic that needs to be talked about in depth is financials because as an athlete, you spend a lot of your time on the road, and you don’t necessarily go out all of the time to spend money because you are giving per- diem and gear etc. When you are not an athlete, you are not provided with those things anymore.

As well as making programming more accessible,

I think it would be helpful to make the programs more available for everybody else. I wasn’t able to attend some of the programs because I had night classes during the times, they had the events. ‘I also think having programs that teach athletes about finances could be helpful; specifically on financing things, insurance and buying a home. (Chance)

Implementing mentorship programming was noted by the athletes with this quote by Kelly being a good representation of the athletes’ comments ‘I think having talks that help athletes learn how to speak about their skills and how to speak about that when interviewing for jobs.’ ‘I also think it would be great to bring back sport alumni and have them speak to current athletes about their careers.’ Additionally, it was also recommended that athletic departments speak to athletes about degrees and course choices that suit that athletes’ interests. Leah noted ‘I wish my academic advisor helped me more with what I could do with my degree after I graduated.’ ‘I feel like the focus was for me to get classes that worked around my practice schedule mostly.’

High athletic identity

With years devoted to excelling within sport, many athletes find themselves identifying as an athletic individual even when their sport career ends (9). This finding was supported by the reflections from the participants in this study. Five out of six participants indicated they still identify as an athlete and considered themselves athletic. Chelsea noted, ‘I still try to live an athletic style similar to how I was when I was a competitive athlete’, while Chance noted ‘I still identify as a former athlete who still does athletic things.’ – and Leah said, ‘I still resemble as an athlete just because I’m still in shape and I’m still basically active.’ Of note, half of the participants in this study transitioned out of sport and into a career within or surrounding athletics. These participants openly discussed how this allowed them to stay identified within sport culture. For example, Kelly said ‘I now identify as a coach, which gives me sport identity; making it easier to take away the athlete part of me, but that identity is still very much part of who I am.’ Chelsea commented ‘I work within an athletic department and am still around sport every day. I enjoy that part of my job’ and Mary said,

After college I became a graduate assistant for an athletic department and it’s nice to still being in the sports world because I am still constantly around athletics.’ ‘The best thing about being a college athlete is you definitely have like a foot up; I feel like in a lot of the career world.

Two participants discussed the transferability of the skills they learned as athletes, and how these gave them an advantage throughout the job search process. For example, Chance said ‘Just from my experience playing in college athletics, it helped me in terms of interviews and getting in the position to get a job.’ When asked what skills from sport helped him get his current position, he discussed leadership, communication, teamwork/collaboration, and confidence. He commented, ‘Leadership and communication; these were big for coming out of college athletes. I think it helped. As well as just like you get the confidence for like playing in front of people, so that helped with confidence and interviews and everything like that.’ ‘Being able to do team work as well; a lot of jobs like that as you obviously have to work in teams and collaborate with other people within your company.’

Lack of Psychological support

Although the strength and exclusivity of the athletic role during sport participation may increase an athlete’s potential vulnerability to psychiatric distress after leaving sport (11), none of the participants reported experiencing athletic career transition programming that addressed the psychological effects that a transition can have on a sport individual. Although only one participant expressed experiencing mental health difficulties during her transition, five out of six participants spoke on the need for mental health to be addressed in athletic career transition programming. For example, Kelly noted,

“I think having a mental health professional to provide tools and be real with athletes, like hey it is not going to be a smooth sailing process once you finally hang up the cleats, here are some tools to help you cope with this process better.”

Leah on the other hand focused on the importance of wellness checks, ‘I do believe that for athletes who will transition, psychologists should come in and do a wellness check or just be an ear for somebody would be an amazing thing because college athletics is a mental trip.’

Coping

Coping strategies are used to help student athletes better adjust to sport retirement. Participants in this study reported that they coped with their transition out of sport by finding ways to get their mind off this process. Chelsea said, ‘I definitely did try to find ways to get my mind off of the fact that I’m not going to practice.’ Mary noted, ‘You try and find outlets you know, to still be competitive and find other ways to use your talents but it takes a little bit of time to find those things’ while Andrea stated, ‘I exercised to relieve the stress I had and that helped a lot.’ Although some of the participants found positive ways to cope with their transition, one participant utilized negative ways to cope with their transition. Leah said, ‘I was being real nonchalant. I was trying to like mask it with everything will work out fine, but I was panicking.’ During this time, she mentioned that she participated in drinking alcohol and smoking. She said, ‘another way that I coped truthfully during that time in all honesty; was drinking and smoking. I was like a spiral, like I did not know what to do.’ None of the participants indicated experiencing programming that spoke on positive ways to cope with transitioning out of athletics. By implementing this in programming, negative coping mechanisms during transitions can be prevented.

Social Support

During athletic transitions, the participants utilized social support and informal information given to them about the transition process before and during their journey. It was found that the participants recalled receiving support from coaches, athletic advisors, family, and friends. Although the participants in the study did not receive as much support within their athletic departments, it was noted that they all utilized their social networks as support systems during their transitions. Andrea said, ‘I definitely needed some social support and I talked to my coach. He would hit me and just ask me if I was doing okay and stuff like that.’ Kelly stated, ‘I connected with my coaches a lot about the transition process as a player and my plans to pursue coaching as a career’ and ‘My coaches had a good grasp on what transitioning was like especially when they have played sport for so long.’ Kelly also noted the importance of friends and family, ‘My friends and family were also a good support system.’ The role of professors was also noted, ‘The professors I interacted with were very helpful to prepare me for what comes next, and I had an older sibling that played college sports, so I definitely relied on help from him.’

Covid-19 Pandemic

The final theme that emerged from the data and affected two out of six participants in the year 2020 was the Covid-19 pandemic. The pandemic for the year 2020 ended college sports prematurely causing more athletes to experience a traumatic end to their athletic season and for some, a traumatic end to their athletic careers. The participants in this study who experienced this expressed not being supported by their athletic departments which increased their feelings of not being prepared for what was next for them. For example, Leah stated, ‘We were told that we weren’t going to get our season and that was it; our season was stripped away.’ When asked if there were any resources or emotional support provided for her, she said she could not recall any. She did reflect on being offered an extra season, which would grant her a fifth year of eligibility. She said she declined this opportunity in hopes of being able to put more time towards starting her career. Andrea, whose transition experience was also affected by the pandemic described her athletic career as ending suddenly, which took a toll on her mental health. She stated, ‘I never had anybody to talk to about how to move forward or continue on with the degree I earned.’ ‘I just remember thinking, what am I going to do next?’ ‘We never had a good closing statement.’ When asked if there were any resources or emotional support available to her, she recalled her athletic advisor reaching out to her via email and text message but decided to not respond due to feeling overwhelmed.

Discussion

This study examined athletic career transition programming within the NCAA through the perceptions of former student athletes. Additionally, the impact of an athletic career transition was further explored. The results from this study provide evidence that athletic departments may not be using best practices to better support student athletes in their transition out of collegiate athletics (2). From these findings, participants received little to no programming specific to how retiring from sport affects an individual psychologically, emotionally, behaviorally, and socially as well as how it affects their overall identity (5,7,8,9). The data further shows that athletic departments may not be listening to what the research says (5) should be implemented into programming; thus, demonstrating that athletic departments may not be prioritizing the overall well-being of student athletes. Past literature has continuously encouraged practitioners within athletic departments to include programming to provide student athletes the tools to adjust to sport retirement (4) and with the lack thereof, student athletes can potentially experience more negative reactions to retiring from collegiate sport (1,11,12).

The findings of this study were consistent with previous research with there still being a lack of consensus of what is told to student athletes about the transition process (2) shown throughout the perceptions of the former student athletes in this study. The themes (i.e., athletic career transition programming, athletic identity, psychological impact, and coping) from past research re-emerged when the participants were asked to reflect on their overall transition experience. Two additional themes that emerged were social support and the Covid-19 pandemic. Social support was not surprising as past literature has suggested it to be a positive coping mechanism for athletes in transition (7). However, the Covid-19 pandemic was a unique theme that has not often been discussed regarding athletic retirement. This provides a unique perspective to the overall findings. The perceptions of participants personal athletic transition experiences from collegiate sport were also consistent with previous literature in that most participants still resonated with the athletic role (athletic identity) (e.g., 9, 11,12), experienced mixed feelings about transitioning support and would have appreciated psychological support (8,12); utilizing positive and negative coping mechanisms and used social support networks that were available to them (7,8). With the difficulties and challenges of the unprecedented pandemic, this may have further exacerbated the lack of proper resources for student athletes transitioning from collegiate sport. This further provides evidence that proper exit strategies must be implemented within athletic departments for collegiate student athletes (5).

Limitations & Future Research

There were limitations to this study that should be discussed. The findings were derived from a participant sample consisting primarily of women or individuals that competed within the Division I level. The lack of participants from other divisions did not allow for comparison across divisions. Furthermore, although interviewing only six participants led to the ability to give each participant a voice in this paper, it was a small sample making it impossible to make set inferences on this data alone. Instead, these results should be seen as an additional piece of information, along with past research findings, that can be used for best practice in career transition. With the structured interviews conducted primarily over zoom, this may have impacted the participants openness to disclose sensitive information due to the interview format. This was demonstrated by one participant disclosing confidential information related to their mental health after the interview process was completed, and the recording of the zoom appointment stopped. Future research should consider replicating this study with an in-person structured interview, with a more diverse and larger participant sample. Future studies should consider looking at the differences in athletic career transition programming implemented within all division levels of the NCAA qualitatively.

Conclusions Implications for Practice

The purpose of this present study was to investigate if current career transition programs in NCAA Athletic Departments are using best practices, as defined by the current research in the field, based on former collegiate athlete’s perceptions of their experience with career transition programming. A secondary and equally important purpose was to investigate the overall impact athletic career transition has on former collegiate athletes’ lives. The findings of this study provided evidence on the overall impact transitioning from collegiate sport has on an athletic individual and along with past research highlight the lack of athletic career transition programming implementation into athletic departments. These findings add to the evidence that suggests that professionals should be creating programs and psychoeducational interventions that include how the transition affects an athlete psychologically, socially, emotionally, behaviorally, and how it affects their overall athletic identity, per previous athletic career transition literature. Furthermore, professionals should implement psychological support for athletic career transitions from qualified staff, programming that gives student athletes tools on mental health resources, programming on positive coping mechanisms, programming to student athletes on financial topics (e.g., budgeting, financing, housing, taxes) and implementing mentorship programs that feature student athlete alumni. Additionally, these findings support the recommendation that practitioners should consider making programming accessible to all student athletes with various schedules by having programming for student athletes in person and virtually if possible. Lastly, practitioners within athletic departments should consider receiving feedback from former student athletes like this study, to ensure that the programming implemented is using best practices to better support student athletes. It is with hope that the findings of this study encourage practitioners within NCAA athletic departments to implement effective athletic career transition programming that will provide student athletes the tools to properly prepare for the transition out of collegiate athletics.

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Qshequilla Parham Mitchell2024-08-23T10:19:26-05:00August 16th, 2024|Research, Sport Education, Sports Studies and Sports Psychology|Comments Off