Search

Objective To review the literature on work-life interfaces in the sport industry, focusing on athletic trainers, coaches, athletes, and other sport personnel. Data Sources Studies were identified using SPORTDiscus, PsychINFO, and Google Scholar. Search terms included work-family balance, work-life balance, work-family conflict, work-life conflict, work-family enrichment, and work-life enrichment. These search terms were used in different combinations and configurations in the search process. Study Selection Included studies were peer-reviewed journal articles, with primary data collection, and published in English. In the articles, researchers also examined some aspect of the work-family interface in relation to the sport industry. Data Extraction The initial searches returned 110 articles. Of these, 21 articles were removed for a lack of focus on the sport industry, for being a duplicate, or for focusing outside the work-life interface in sport. A total of 89 articles remained for a full analysis. An additional 20 articles were then removed because the authors either did not collect primary data or focused outside our study purpose. Therefore, 69 articles were included in the review. Data Synthesis The theoretical framework, study population, population region, methods, article focus, and findings from the articles were recorded. Articles were then grouped based on the study population focus (eg, athletic trainer, coach, or other). Conclusions The results suggested that investigators' primary interests were athletic trainers and coaches, primarily with respect to work-life balance and work-life conflict. Less attention was paid to international participants, athletes, and topics related to work-life enrichment. The field will continue to progress as more populations and perspectives are studied. Furthermore, an additional emphasis on positive organizational behaviors, such as work-life enrichment and life-work enrichment, will move the literature forward and answer useful questions with both theoretical and practical outcomes.

Background Marching band artists are a physically active population, composed of approximately 27,000 people in the United States. University marching band artists face many of the same physically active demands and mental stressors as student athletes, potentially predisposing them to injury, illness, and risk for eating disorders (EDs). The purpose of this study was to examine ED risk across sex in university marching band artists, and to determine the type of risk based on the Eating Disorder Inventory-3 (EDI-3) and Eating Disorder Inventory-3 Symptom Check List (EDI-3 SC). A secondary aim examined marching band artists and pathogenic weight control behavior use across sex. Methods This was a cross-sectional study. A total of 150 marching band artists (female: n = 84, male: n = 66, age = 19.9 ± 1.1 years) from three National Collegiate Athletic Association Division I university marching bands participated in the study. We screened for ED risk using the EDI-3, and the EDI-3 SC. Results Overall, marching band artists were at risk for EDs, using only the EDI-3, 45.3% (n = 68) were at risk, with females at significant higher risk than males [χ2 = 5.228, p = .022]; using only the EDI-3 SC, 54% (n = 81) were at risk and no significant differences were found across sex. Overall, 48% of all participants reported dieting and 20.7% engaged in excessive exercise to control weight. Significant differences were found between sex and purging to control weight [χ2 = 3.94, p = .047] and laxative use [χ2 = 4.064, p = .044], with females engaging in behavior more than males. Conclusions Eating disorder risk was prevalent for both female and male marching band artists, with females displaying higher risk for EDs than males. Furthermore, marching band artists are engaging in pathogenic behaviors to control their weight. Healthcare providers (e.g., physicians, athletic trainers, physical therapist, dietitians, etc.) working in this setting should be aware of the risk factors displayed in marching band artists, and be able to provide education, prevention, and clinical interventions to this population. Additionally, marching band administrators should be aware of all medical risk factors and the benefit of having a healthcare provider (e.g., athletic trainer) to oversee the healthcare and wellness of marching band artists.

Context Female athletes and performing artists can present with low energy availability (LEA) from either unintentional (eg, inadvertent undereating) or intentional (eg, eating disorder [ED]) methods. Whereas LEA and ED risk have been examined independently, few researchers have examined them simultaneously. Awareness of LEA with or without ED risk may provide clinicians with innovative prevention and intervention strategies. Objective To examine LEA with or without ED risk (eg, eating attitudes, pathogenic behaviors) in female collegiate athletes and performing artists and compare sport type and LEA with the overall ED risk. Design Cross-sectional study. Setting Free living in sport-specific settings. Patients or Other Participants A total of 121 collegiate female athletes and performing artists (age = 19.8 ± 2.0 years, height = 168.9 ± 7.7 cm, mass = 63.6 ± 9.3 kg) participating in equestrian (n = 28), soccer (n = 20), beach volleyball (n = 18), softball (n = 17), volleyball (n = 12), and ballet (n = 26). Main Outcome Measure(s) Anthropometric measurements (height, mass, body composition), resting metabolic rate, energy intake, total daily energy expenditure, exercise energy expenditure, Eating Disorder Inventory-3 (EDI-3), and EDI-3 Symptom Checklist were assessed. Chi-square analysis was used to examine differences between LEA and sport type, LEA and ED risk, ED risk and sport type, and pathogenic behaviors and sport type. Results Most (81%, n = 98) female athletes and performing artists displayed LEA and differences between LEA and sport type (\(\def\upalpha{\unicode[Times]{x3B1}}\)\(\def\upbeta{\unicode[Times]{x3B2}}\)\(\def\upgamma{\unicode[Times]{x3B3}}\)\(\def\updelta{\unicode[Times]{x3B4}}\)\(\def\upvarepsilon{\unicode[Times]{x3B5}}\)\(\def\upzeta{\unicode[Times]{x3B6}}\)\(\def\upeta{\unicode[Times]{x3B7}}\)\(\def\uptheta{\unicode[Times]{x3B8}}\)\(\def\upiota{\unicode[Times]{x3B9}}\)\(\def\upkappa{\unicode[Times]{x3BA}}\)\(\def\uplambda{\unicode[Times]{x3BB}}\)\(\def\upmu{\unicode[Times]{x3BC}}\)\(\def\upnu{\unicode[Times]{x3BD}}\)\(\def\upxi{\unicode[Times]{x3BE}}\)\(\def\upomicron{\unicode[Times]{x3BF}}\)\(\def\uppi{\unicode[Times]{x3C0}}\)\(\def\uprho{\unicode[Times]{x3C1}}\)\(\def\upsigma{\unicode[Times]{x3C3}}\)\(\def\uptau{\unicode[Times]{x3C4}}\)\(\def\upupsilon{\unicode[Times]{x3C5}}\)\(\def\upphi{\unicode[Times]{x3C6}}\)\(\def\upchi{\unicode[Times]{x3C7}}\)\(\def\uppsy{\unicode[Times]{x3C8}}\)\(\def\upomega{\unicode[Times]{x3C9}}\)\(\def\bialpha{\boldsymbol{\alpha}}\)\(\def\bibeta{\boldsymbol{\beta}}\)\(\def\bigamma{\boldsymbol{\gamma}}\)\(\def\bidelta{\boldsymbol{\delta}}\)\(\def\bivarepsilon{\boldsymbol{\varepsilon}}\)\(\def\bizeta{\boldsymbol{\zeta}}\)\(\def\bieta{\boldsymbol{\eta}}\)\(\def\bitheta{\boldsymbol{\theta}}\)\(\def\biiota{\boldsymbol{\iota}}\)\(\def\bikappa{\boldsymbol{\kappa}}\)\(\def\bilambda{\boldsymbol{\lambda}}\)\(\def\bimu{\boldsymbol{\mu}}\)\(\def\binu{\boldsymbol{\nu}}\)\(\def\bixi{\boldsymbol{\xi}}\)\(\def\biomicron{\boldsymbol{\micron}}\)\(\def\bipi{\boldsymbol{\pi}}\)\(\def\birho{\boldsymbol{\rho}}\)\(\def\bisigma{\boldsymbol{\sigma}}\)\(\def\bitau{\boldsymbol{\tau}}\)\(\def\biupsilon{\boldsymbol{\upsilon}}\)\(\def\biphi{\boldsymbol{\phi}}\)\(\def\bichi{\boldsymbol{\chi}}\)\(\def\bipsy{\boldsymbol{\psy}}\)\(\def\biomega{\boldsymbol{\omega}}\)\(\def\bupalpha{\bf{\alpha}}\)\(\def\bupbeta{\bf{\beta}}\)\(\def\bupgamma{\bf{\gamma}}\)\(\def\bupdelta{\bf{\delta}}\)\(\def\bupvarepsilon{\bf{\varepsilon}}\)\(\def\bupzeta{\bf{\zeta}}\)\(\def\bupeta{\bf{\eta}}\)\(\def\buptheta{\bf{\theta}}\)\(\def\bupiota{\bf{\iota}}\)\(\def\bupkappa{\bf{\kappa}}\)\(\def\buplambda{\bf{\lambda}}\)\(\def\bupmu{\bf{\mu}}\)\(\def\bupnu{\bf{\nu}}\)\(\def\bupxi{\bf{\xi}}\)\(\def\bupomicron{\bf{\micron}}\)\(\def\buppi{\bf{\pi}}\)\(\def\buprho{\bf{\rho}}\)\(\def\bupsigma{\bf{\sigma}}\)\(\def\buptau{\bf{\tau}}\)\(\def\bupupsilon{\bf{\upsilon}}\)\(\def\bupphi{\bf{\phi}}\)\(\def\bupchi{\bf{\chi}}\)\(\def\buppsy{\bf{\psy}}\)\(\def\bupomega{\bf{\omega}}\)\(\def\bGamma{\bf{\Gamma}}\)\(\def\bDelta{\bf{\Delta}}\)\(\def\bTheta{\bf{\Theta}}\)\(\def\bLambda{\bf{\Lambda}}\)\(\def\bXi{\bf{\Xi}}\)\(\def\bPi{\bf{\Pi}}\)\(\def\bSigma{\bf{\Sigma}}\)\(\def\bPhi{\bf{\Phi}}\)\(\def\bPsi{\bf{\Psi}}\)\(\def\bOmega{\bf{\Omega}}\)\({\rm{\chi }}_5^2\) = 43.8, P < .001). The majority (76.0%, n = 92) presented with an ED risk, but the ED risk did not differ by sport type (P = .94). The EDI-3 Symptom Checklist revealed that 61.2% (n = 74) engaged in pathogenic behaviors, with dieting being the most common (51.2%, n = 62). Most (76.0%, n = 92) displayed LEA with an ED risk. No differences were found in LEA by ED risk and sport type. Softball players reported the most LEA with an ED risk (82.4%, n = 14), followed by ballet dancers (76%, n = 19). Conclusions Our results suggested that a large proportion of collegiate female athletes and performing artists were at risk for LEA with an ED risk, thus warranting education, identification, prevention, and intervention strategies relative to fueling for performance.

Almost as soon as the NCAA announced the cancelation its 2020 “March Madness” basketball tournament, college administrators began moving to cut sports from their schools’ portfolios. This study exp...

Social agents associated with cheerleading environments are increasingly linked to body image dissatisfaction (BID) and eating disorders (ED). This study examined ED risk across team type, squad type, and position. An additional purpose determined BID in clothing type (daily clothing, midriff uniform, and full uniform), and meta-perceptions from the perspective of peers (MP peers), parents (MP parents), and coaches (MP coaches). Female cheerleaders (n = 268) completed an online survey which included demographics, the Eating Attitudes Test-26, and pathogenic behavior questions. Body image perceptions were assessed by using the Sex-Specific Figural Stimuli Silhouettes. Overall, 34.4% of cheerleaders (n = 268; mean age: 17.9 ± 2.7 years) exhibited an ED risk. Compared to All-Star cheerleaders, college cheerleaders demonstrated significant higher ED risk (p = 0.021), dieting subscale scores (p = 0.045), and laxative, diet pill, and diuretic use (p = 0.008). Co-ed teams compared to all-girl teams revealed higher means for the total EAT-26 (p = 0.018) and oral control subscale (p = 0.002). The BID in clothing type revealed that cheerleaders wanted to be the smallest in the midriff option (p < 0.0001, η2 = 0.332). The BID from meta-perception revealed that cheerleaders felt that their coaches wanted them to be the smallest (p < 0.001, η2 = 0.106). Cheerleaders are at risk for EDs and BID at any level. Regarding the midriff uniform, MP from the perspective of coaches showed the greatest difference between perceived and desired body image.

The purpose of this study was to examine individual and combined Female Athlete Triad components within collegiate cheerleaders, an at-risk group. Cheerleaders (n = 19; age: 20.3 ± 1.2 years) completed anthropometric measurements, health history questionnaires, resting metabolic rate, the eating disorder inventory-3 and symptom checklist, blood sample, and DXA scan. Participants completed dietary and exercise logs for 7 days and used heart rate monitors to track daily and exercise energy expenditure. Proportions were calculated for low energy availability (LEA) risk, disordered eating risk, and pathogenic behaviors. Chi-square analysis was used to determine the difference between cheerleaders who experience low EA with or without disordered eating risk. All cheerleaders demonstrated LEA for the days they participated in cheerleading practice, 52.6% demonstrated LEA with eating disorder risk and 47.4% demonstrated LEA without eating disorder risk, 52.6% self-reported menstrual dysfunction, 14% experienced menstrual dysfunction via hormonal assessment, and 0% demonstrated low bone mineral density. Overall, 47.7% presented with one Triad component, 52.6% demonstrated two Triad components using self-reported menstrual data, and 10.5% demonstrated two Triad components using hormonal assessments. All cheerleaders displayed LEA. These findings support the need for increased education on the individual components of the Triad and their potential consequences by qualified personal.

As the overrepresentation of Black male collegiate athletes (BMCA) increases in National Collegiate Athletic Association (NCAA) Division I (DI) revenue-generating sports, coaches and athletic staff continue to overemphasize sport performance, while graduation rates for BMCA remain persistently lower than their peers and research continues to document transition out of sport concerns for this population. Proposing a multi-level approach, we explore the collegiate athletic factors that influence the holistic identity development of DI revenue generating BMCA at historically White institutions (HWIs) leading to difficulty transitioning out of sport. At the macro-level, the NCAA and its policies on eligibility are analyzed. At the meso-level, HWIs collegiate athletic departments and the impact of organizational practices are examined in regards to their impact on BMCA’s identity development, overall experiences and transition out of sport. Lastly, at the micro-level, we explore research focused on BMCAs’ experiences, expectations, and issues at HWIs. By identifying salient factors influencing BMCAs’ identity development and experiences, collegiate athletic stakeholders can use this information to create more effective programming and improve campus cultures that foster BMCAs’ holistic development on a systematized basis creating an environment where BMCAs are prepared to move into the next stage of life after sport ends.

Context To our knowledge, no researchers have investigated thermoregulatory responses and exertional heat illness (EHI) risk factors in marching band (MB) artists performing physical activity in high environmental temperatures. Objective To examine core temperature (Tc) and EHI risk factors in MB artists. Design Descriptive epidemiology study. Setting Three rehearsals and 2 football games for 2 National Collegiate Athletic Association Division I institution's MBs. Patients or Other Participants Nineteen volunteers (females = 13, males = 6; age = 20.5 ± 0.9 years, height = 165.1 ± 7.1 cm, mass = 75.0 ± 19.1 kg) completed the study. Main Outcome Measure(s) We measured Tc, wet bulb globe temperature, and relative humidity preactivity, during activity, and postactivity. Other variables were activity time and intensity, body surface area, hydration characteristics (fluid volume, sweat rate, urine specific gravity, percentage of body mass loss), and medical history (eg, previous EHI, medications). The statistical analysis consisted of descriptive information (mean ± standard deviation), comparative analyses that determined differences within days, and correlations that identified variables significantly associated with Tc. Results The mean time for rehearsals was 102.8 ± 19.8 minutes and for games was 260.5 ± 47.7 minutes. Mean maximum Tc was 39.1 ± 1.1°C for games and 38.4 ± 0.7°C for rehearsals; the highest Tc (41.2°C) occurred during a game. Fluid consumption did not match sweat rates (P < .001). Participants reported to games in a hypohydrated state 63.6% of the time. The maximum Tc correlated with the maximum wet bulb globe temperature (r = 0.618, P < .001) and was higher in individuals using mental health medications (rpb = −0.254, P = .022) and females (rpb = 0.330, P = .002). Body surface area (r = −0.449, P < .001) and instrument mass (r = −0.479, P < .001) were negatively correlated with Tc. Conclusions Marching band artists experienced high Tc during activity and should have access to athletic trainers who can implement EHI-prevention and -management strategies.

Context Research exists on energy balances (EBs) and eating disorder (ED) risks in physically active populations and occupations by settings, but the EB and ED risk in athletic trainers (ATs) have not been investigated. Objective To assess ATs' energy needs, including the macronutrient profile, and examine ED risk and pathogenic behavioral differences between sexes (men, women) and job statuses (part time or full time) and among settings (college or university, high school, nontraditional). Design Cross-sectional study. Setting Free living in job settings. Patients or Other Participants Athletic trainers (n = 46; male part-time graduate assistant ATs = 12, male full-time ATs = 11, female part-time graduate assistant ATs = 11, female full-time ATs = 12) in the southeastern United States. Main Outcome Measure(s) Anthropometric measures (sex, age, height, weight, body composition), demographic characteristics (job status [full- or part-time AT], job setting [college/university, high school, nontraditional], years of AT experience, exercise background, alcohol use), resting metabolic rate, energy intake (EI), total daily energy expenditure (TDEE), EB, exercise energy expenditure, macronutrients (carbohydrates, protein, fats), the Eating Disorder Inventory-3, and the Eating Disorder Inventory-3 Symptom Checklist. Results The majority of participants (84.8%, n = 39) had an ED risk, with 26.1% (n = 12) engaging in at least 1 pathogenic behavior, 50% (n = 23) in 2 pathogenic behaviors, and 10.8% (n = 5) in >2 pathogenic behaviors. Also, 82.6% of ATs (n = 38) presented in negative EB (EI < TDEE). Differences were found in resting metabolic rate for sex and job status (F1,45 = 16.48, P = .001), EI (F1,45 = 12.01, P = .001), TDEE (F1,45 = 40.36, P < .001), and exercise energy expenditure (F1,38 = 5.353, P = .026). No differences were present in EB for sex and job status (F1,45 = 1.751, P = .193); χ2 analysis revealed no significant relationship between ATs' sex and EB (\(\def\upalpha{\unicode[Times]{x3B1}}\)\(\def\upbeta{\unicode[Times]{x3B2}}\)\(\def\upgamma{\unicode[Times]{x3B3}}\)\(\def\updelta{\unicode[Times]{x3B4}}\)\(\def\upvarepsilon{\unicode[Times]{x3B5}}\)\(\def\upzeta{\unicode[Times]{x3B6}}\)\(\def\upeta{\unicode[Times]{x3B7}}\)\(\def\uptheta{\unicode[Times]{x3B8}}\)\(\def\upiota{\unicode[Times]{x3B9}}\)\(\def\upkappa{\unicode[Times]{x3BA}}\)\(\def\uplambda{\unicode[Times]{x3BB}}\)\(\def\upmu{\unicode[Times]{x3BC}}\)\(\def\upnu{\unicode[Times]{x3BD}}\)\(\def\upxi{\unicode[Times]{x3BE}}\)\(\def\upomicron{\unicode[Times]{x3BF}}\)\(\def\uppi{\unicode[Times]{x3C0}}\)\(\def\uprho{\unicode[Times]{x3C1}}\)\(\def\upsigma{\unicode[Times]{x3C3}}\)\(\def\uptau{\unicode[Times]{x3C4}}\)\(\def\upupsilon{\unicode[Times]{x3C5}}\)\(\def\upphi{\unicode[Times]{x3C6}}\)\(\def\upchi{\unicode[Times]{x3C7}}\)\(\def\uppsy{\unicode[Times]{x3C8}}\)\(\def\upomega{\unicode[Times]{x3C9}}\)\(\def\bialpha{\boldsymbol{\alpha}}\)\(\def\bibeta{\boldsymbol{\beta}}\)\(\def\bigamma{\boldsymbol{\gamma}}\)\(\def\bidelta{\boldsymbol{\delta}}\)\(\def\bivarepsilon{\boldsymbol{\varepsilon}}\)\(\def\bizeta{\boldsymbol{\zeta}}\)\(\def\bieta{\boldsymbol{\eta}}\)\(\def\bitheta{\boldsymbol{\theta}}\)\(\def\biiota{\boldsymbol{\iota}}\)\(\def\bikappa{\boldsymbol{\kappa}}\)\(\def\bilambda{\boldsymbol{\lambda}}\)\(\def\bimu{\boldsymbol{\mu}}\)\(\def\binu{\boldsymbol{\nu}}\)\(\def\bixi{\boldsymbol{\xi}}\)\(\def\biomicron{\boldsymbol{\micron}}\)\(\def\bipi{\boldsymbol{\pi}}\)\(\def\birho{\boldsymbol{\rho}}\)\(\def\bisigma{\boldsymbol{\sigma}}\)\(\def\bitau{\boldsymbol{\tau}}\)\(\def\biupsilon{\boldsymbol{\upsilon}}\)\(\def\biphi{\boldsymbol{\phi}}\)\(\def\bichi{\boldsymbol{\chi}}\)\(\def\bipsy{\boldsymbol{\psy}}\)\(\def\biomega{\boldsymbol{\omega}}\)\(\def\bupalpha{\bf{\alpha}}\)\(\def\bupbeta{\bf{\beta}}\)\(\def\bupgamma{\bf{\gamma}}\)\(\def\bupdelta{\bf{\delta}}\)\(\def\bupvarepsilon{\bf{\varepsilon}}\)\(\def\bupzeta{\bf{\zeta}}\)\(\def\bupeta{\bf{\eta}}\)\(\def\buptheta{\bf{\theta}}\)\(\def\bupiota{\bf{\iota}}\)\(\def\bupkappa{\bf{\kappa}}\)\(\def\buplambda{\bf{\lambda}}\)\(\def\bupmu{\bf{\mu}}\)\(\def\bupnu{\bf{\nu}}\)\(\def\bupxi{\bf{\xi}}\)\(\def\bupomicron{\bf{\micron}}\)\(\def\buppi{\bf{\pi}}\)\(\def\buprho{\bf{\rho}}\)\(\def\bupsigma{\bf{\sigma}}\)\(\def\buptau{\bf{\tau}}\)\(\def\bupupsilon{\bf{\upsilon}}\)\(\def\bupphi{\bf{\phi}}\)\(\def\bupchi{\bf{\chi}}\)\(\def\buppsy{\bf{\psy}}\)\(\def\bupomega{\bf{\omega}}\)\(\def\bGamma{\bf{\Gamma}}\)\(\def\bDelta{\bf{\Delta}}\)\(\def\bTheta{\bf{\Theta}}\)\(\def\bLambda{\bf{\Lambda}}\)\(\def\bXi{\bf{\Xi}}\)\(\def\bPi{\bf{\Pi}}\)\(\def\bSigma{\bf{\Sigma}}\)\(\def\bPhi{\bf{\Phi}}\)\(\def\bPsi{\bf{\Psi}}\)\(\def\bOmega{\bf{\Omega}}\)\({\rm{\chi }}_{1,46}^2\)= 0.0, P = 1.00) and job status and EB (\({\rm{\chi }}_{1,46}^2\) = 2.42, P = .120). No significant relationship existed between Daily Reference Intakes recommendations for all macronutrients and sex or job status. Conclusions These athletic trainers experienced negative EB, similar to other professionals in high-demand occupations. Regardless of sex or job status, ATs had a high ED risk and participated in unhealthy pathogenic behaviors. The physical and mental concerns associated with these findings indicate a need for interventions targeted at ATs' health behaviors.

Context: No research has investigated thermoregulatory responses and exertional heat illness (EHI) risk factors in marching band (MB) artists performing physical activity in high environmental temperatures. Objective: Examine core temperature (Tc) and EHI risk factors in MB artists. Design: Descriptive epidemiology study. Setting: Three rehearsals and 2 football games for 2 NCAA Division I MBs. Participants: Nineteen volunteers completed the study (female = 13, males = 6; age = 20.5 ± 0.9 years; weight = 75.0 ± 19.1 kg; height = 165.1 ± 7.1 cm). Main Outcome Measures: We measured Tc pre-, post-, and every 15 minutes during activity and recorded wet-bulb globe temperature (WBGT) and relative humidity (RH) every 15 minutes. Other variables included activity time and intensity, ground surface, hydration characteristics (fluid volume, sweat rate, urine specific gravity, percent body mass loss [%BM]), and medical history (eg, previous EHI, medications). Statistical analysis included descriptives (mean ± standard deviation), comparative analyses determined differences within and between days, and linear regression identified variables that significantly explained Tc. Results: Mean rehearsal time = 102.8 ± 19.8 minutes and game time = 260.5 ± 47.7 minutes. Max game Tc (39.1 ± 1.1°C) was significantly higher than rehearsal (38.4 ± 0.7°C, P = .003). The highest max game Tc = 41.2°C. Participants consumed significantly more fluid than their sweat rates (P < .003), which minimized %BM loss, particularly during rehearsals (−0.4 ± 0.6%). Mean game %BM loss = −0.9 ± 2.0%; however, 63.6% of the time, participants reported hypohydrated to game day. Max Tc was significantly predicted by max WBGT, max RH, ground surface, using mental health medications, and hours of sleep (adjusted R2 = 0.542, P < .001). Conclusions: Marching band artists experience high Tc during activity and should have access to athletic trainers who can implement EHI prevention and management strategies.

CONTEXT: Research exists on energy balance (EB) and eating disorder (ED) risk in physically active populations and occupations by settings, but EB and ED in athletic trainers (ATs) has not been investigated. OBJECTIVE: To assess ATs' energy needs, including macronutrient profile, and to examine ED risk and pathogenic behavior between sex (males, females), job status (part-time=PT-AT; full-time=FT-AT) and setting (college/university, high school, non-traditional). DESIGN: Cross-sectional and descriptive. SETTING: Free-living in job settings. PARTICIPANT: ATs (n=46; males PT-AT n=12, males FT-AT n=11; females PT-AT n=11, female FT-AT n=12) in Southeastern United States. MAIN OUTCOME MEASURES: Anthropometric measurements (age, height, weight, body composition), resting metabolic rate (RMR), energy intake (EI), total daily energy expenditure (TDEE), exercise energy expenditure (EEE), EB, macronutrients (carbohydrates, protein, fats), Eating Disorder Inventory-3, and the Eating Disorder Inventory-3 Symptom Checklist. RESULTS: Majority (84.8%, n=39) had ED risk, with 26.1% (n=12) engaging in at least 1 pathogenic behavior, 50% (n=23) in 2 pathogenic behaviors, and 10.8% (n=5) in more than 2 pathogenic behaviors. 82.6% of ATs (n=38) presented in negative EB (EI

Injury risk is multifactorial including non-modifiable and modifiable factors such as nutrition and mental health. The purpose of this study was to estimate eating disorder risk and body image (BI) dissatisfaction among Reserve Officers Training Corps (ROTC) cadets. A total of 102 (male: n = 75, female: n = 27, age: 20 &plusmn, 2 years) ROTC cadets self-reported height, current and ideal weight, and completed the Eating Attitudes Test-26 (EAT-26) and self-perceived BI current and perceived sex-specific figural stimuli. The overall eating disorder risk for ROTC cadets was 32.4%. No significant differences were found when comparing sex, ethnicity, or military branch. Overall risk of pathogenic behaviors included 11.8% who reported binge eating, 8.8% who used laxatives, diuretics, or diet pills, 8.8% who exercised for &gt, 60 min to control their weight, and 8.8% who lost 9.1 kg or more within the last 6 months. We identified significant interactions (p &le, 0.01) between sex of the solider, overall perceptions of male and female soldiers, and BI self-perceptions. The ROTC cadets in this study displayed eating disorder risk and BI dissatisfaction, which is concerning for tactical readiness, long-term behavioral health issues, and injury from pathogenic behaviors. Education and quality healthcare are necessary to mitigate the increased risk of eating and BI dissatisfaction within this population.

Athletic transition has been explored in sport management and sport psychology literature primarily focusing on transitioning into collegiate athletics, voluntary and involuntary transitions out of collegiate sport, and transitioning out of professional sport. This study compared NCAA Division I and III collegiate athletes’ perceptions regarding the athletic transition process. Semi-structured interviews were utilized to uncover the perceptions and experiences surrounding the transition process into, during, and out of collegiate sport (Lindlof & Taylor, 2019; Schlossberg, 1981). Three themes emerged from the data: Moving In: Compatability, Moving Through: Identity Directly Tied to Sport, and Moving Out: Redefining Oneself. More specifically, the participants explained coaches and proximity to home helped foster a sense of compatability in institution choice. All of the participants believed sport was important to their lives and tied to their current identity. Lastly, participants detailed the upcoming transition out of sport was either an opportunity for growth or accompanied with uncertainty and sadness surrounding this significant life change. These findings highlight the responsibility of intercollegiate athletic departments and institutions to provide assistance in these transitional processes through coach, administrator, and athlete education and programming.

Background: Increased availability of evidence-based practices (EBPs) is essential to alleviating the negative public health and societal effects of behavioral health problems. A major challenge to implementing and sustaining EBPs broadly is the limited and fragmented nature of available funding. Method: We conducted a scoping review that assessed the current state of evidence on EBP financing strategies for behavioral health based on recent literature (i.e., post-Affordable Care Act). We defined financing strategies as techniques that secure and direct financial resources to support EBP implementation. This article introduces a conceptualization of financing strategies and then presents a compilation of identified strategies, following established reporting guidelines for the implementation strategies. We also describe the reported level of use for each financing strategy in the research literature. Results: Of 23 financing strategies, 13 were reported as being used within behavioral health services, 4 had potential for use, 5 had conceptual use only, and 1 was potentially contraindicated. Examples of strategies reported being used include increased fee-for-service reimbursement, grants, cost sharing, and pay-for-success contracts. No strategies had been evaluated in ways that allowed for strong conclusions about their impact on EBP implementation outcomes. Conclusion: The existing literature on EBP financing strategies in behavioral health raises far more questions than answers. Therefore, we propose a research agenda that will help better understand these financing strategies. We also discuss the implications of our findings for behavioral health professionals, system leaders, and policymakers who want to develop robust, sustainable financing for EBP implementation in behavioral health systems. Plain language abstract: Organizations that treat behavioral health problems (mental health and substance use) often seek to adopt and use evidence-based practices (EBPs). A challenge to adopting EBPs broadly is the limited funding available, often from various sources that are poorly coordinated with one another. To help organizations plan effectively to adopt EBPs, we conducted a review of recent evidence (i.e., since the passage of the 2010 Affordable Care Act) on strategies for financing EBP adoption in behavioral health systems. We present definitions of 23 identified strategies and describe each strategy’s reported (in the research literature) level of use to fund EBP adoption in behavioral health services. Of the 23 financing strategies, 13 strategies had evidence of use, 4 had potential for use, 5 had conceptual use only, and 1 was potentially contraindicated. Examples of strategies with evidence of use include increased fee-for-service reimbursement, grants, cost sharing, and pay-for-success contracts. This comprehensive list of EBP financing strategies may help guide decision-making by behavioral health professionals, system leaders, and policymakers. The article also presents a research agenda for building on the current research literature by (1) advancing methods to evaluate financing strategies’ effects, (2) partnering with stakeholders and decision-makers to examine promising financing strategies, (3) focusing on strategies and service systems with the greatest needs, (4) improving methods to guide the selection of financing strategies, and (5) paying greater attention to sustainable long-term financing of EBPs.

Research in the area of athletic identity has grown immensely since it was first brought forward in academic work nearly 20 years ago. The ideas of athletic identity have expanded into the areas of relating to injury and rehabilitation, transitioning into collegiate athletics, transitioning out of collegiate athletics, professional careers in sport, and even identity formation through sport. This research explored the experiences of 10 women who had completed their collegiate eligibility and had transitioned out of collegiate competition. Three themes emerged from the semi-structured interviews: (a) Sense of Loss, (b) Bewilderment, and (c) Enjoy the Experience. All the respondents agreed that transition was inevitable, but there were mixed results on whether the transition out of sport was positive or negative. The findings also revealed the struggle of creating an identity outside of sport. The participants indicated establishing new social circles, new routines with fitness, and separating from their sport were challenging. The respondents also believed it was their responsibility to offer advice to future transitioning student-athletes so they could be better prepared for their upcoming and inevitable transition out of sport.

Sexual harassment and sexism in the workplace is the unwanted sexual attention and discrimination based on sex or gender of employees by their colleagues or superiors. Male-dominated organizations ...

Disease resistance is often measured as plant survival, which involves taking multiple counts of plants before and after disease incidence. Often, survival data are analyzed by forming a single derived variable, namely final counts expressed as a percentage of initial counts. In this study we propose a bivariate linear mixed model approach in which the two variables are the initial and final counts. This approach is demonstrated using data from nine blackleg disease nurseries in the 2009 growing season in Australia. Replicated experiments were grown at each nursery with a mixture of commercial Australian canola cultivars and breeding lines (collectively called ‘entries’) being tested. Plant survival was determined by counting all the seedlings at emergence and then recounting the number surviving at maturity in each plot. The counts were considered as two ‘traits’, which were log transformed prior to a bivariate linear mixed model analysis. Each trait had different error variances, spatial components (both local and global) and outliers. The variance of entry effects was non-zero for both traits at all locations. The correlation of entry effects between the traits ranged from 0.218 to 0.935 across locations. Best Linear Unbiased Predictors (BLUPs) of entry effects at both sampling times provided three possible indices for selection: (log) counts at emergence, (log) counts at maturity and the difference between these two which could be exponentiated to provide percentage survival values. Thus the bivariate mixed model approach for the analysis of plant survival data provided a more detailed picture of the impact of disease resistance compared with the univariate analysis of percentage survival data. Additionally the predicted entry effects for survival were more accurate in the bivariate analysis.

In order to explore the link between multicultural service-learning (MSL) and the development of multicultural competence, a participatory action research paradigm and constructivist grounded theory were used to qualitatively explore the perceptions of multicultural competence development in 30 recreation and leisure studies majors. Major themes focused on student development as a result of MSL and the process by which this development occurred. Students reported increased awareness of their own culture and the cultural background of others, recognized privileges they hold on a variety of cultural factors, and developed an understanding of the process of MSL and the role it plays in developing multicultural competence.