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Troy Palmer2025-05-22T15:03:47-05:00

A Comparison of Perfectionism and Time of Sport Specialization of Division-1 Athletes 

Troy Palmer2025-05-22T15:03:47-05:00October 31st, 2025|Research, Sport Education, Sport Training, Sports Coaching, Sports Exercise Science|

Jason N. Hughes, Ph.D., is an Assistant Professor of Sport Management at Elizabeth City State University in Elizabeth City, NC. His research interests include sport specialization, perfectionism, and athletic burnout. 

Colby B. Jubenville, PhD., is a Professor of Sport Management at Middle Tennessee State University. His research interests include student success, leadership, and emotional intelligence in business. 

Mitchell T. Woltring, Ph.D., is an Associate Professor at the University of South Alabama. His research interests include student-athlete success and service learning. 

Helen J. Gray, Ph.D., is the Associate Dean of Academic Affairs at North Carolina Agricultural and Technical State University. Her research interests include sport management, youth sport, and pedagogy in sport, leisure, and tourism.

ABSTRACT 

Sport specialization has become increasingly popular among athletes aiming to gain a competitive edge. Despite its prevalence, there is a notable lack of research exploring the psychological impacts of sport specialization. One area that remains insufficiently studied in relation to sport specialization is perfectionism—a psychological trait known to influence both positive and negative outcomes in sports. The primary purpose of this study was to examine the previously unexplored relationship between the time in which an athlete specializes in sport with perfectionism concerns and strivings. A series of one-way ANOVAs were conducted to investigate the relationship between time of sport specialization based on the Developmental Model of Sport Participation and perfectionistic strivings and concerns.  The results of the analyses showed that there was not a relationship between sport diversification and perfectionism. However, participants did score high on perfectionistic concerns despite adhering to proper diversification, participants showed higher scores in perfectionistic concerns than strivings. This suggests that athletes, parents, and coaches need to be aware that sport diversification may not be a buffer against negative psychological consequences. The results suggest that sport specialization’s psychological repercussions are confined to whether the athlete is concurrently engaged in sport specialization 

Key Words: perfectionistic concerns, perfectionistic strivings, athletes, sport diversification, athletic development 

INTRODUCTION 

Early sport specialization among young athletes has surged, drawing increased scholarly attention. Research suggests that youth athletes are engaging in sport specialization at rates from 17% to as high as 41% (4, 30). In response, researchers have emphasized the need to examine both motives and the consequences of. Sport specialization refers to rigorous, year-round training focused on a single sport to the exclusion of others (21).  Motivations for why athletes choose to specialize include improving specific skills, securing financial reward, and aiming for professional success (37). Ironically, researchers argue that this approach might hinder rather than help these goals. The consensus among experts is that well-rounded athletic development is better achieved through sport diversification, which involves engaging in multiple sports (37).  

Advocates of sport specialization assert it plays a vital role in developing elite-level skills through deliberate practice. They argue that athletes who concentrate on one sport can attain greater proficiency than those who play multiple sports (37). Supporting this claim, one study found that both current and former elite soccer players dedicated more time to deliberate, soccer-specific training than non-elite athletes who were sport-diversified (14). This study suggested that deliberate practice during sport specialization significantly contributed to elite athlete status (14). Moreover, research on elite soccer players suggests that specialization enhances motivation, dedication, and enjoyment, leading to increased focus and commitment to improvement (36). 

Critics of early sport specialization challenge its effectiveness, arguing that intense skill development at a young age may yield ambiguous results. A study on Russian swimmers found no performance advantage for early specializers compared to those who specialized later; in fact, those who specialized later showed greater progress (2). This suggests that early specialization may not be universally beneficial. Instead, it might be more appropriate in certain sports such as women’s gymnastics, diving, women’s basketball, figure skating, and dance, where early peak performance occurs before full body maturation (22). Furthermore, a 2023 meta-analysis found that world-class athletes engaged in multi-sport diversification, started their main sport later, and accumulated less main sport deliberate practice (19). 

The pursuit of athletic scholarships and professional contracts remains a major motivator for sport specialization among young athletes. (24). Yet, the actual probability of attaining such rewards is notably low. Studies show that only 2% of high school athletes received a college scholarship, with an even lower percentage (1.2 % for females and 1.1% for males) obtaining full scholarships. The prospect of reaching professional levels is even less likely. The NCAA reports that only 0.9% – 5.1% of collegiate athletes make the professional ranks, depending on the sport. In high-profile sports like college football and basketball, only 1.34% of athletes advance to play professionally (29). Despite these sobering statistics, many athletes continue to specialize with the hope of achieving collegiate and professional success. 

Another key criticism of sport specialization revolves around the potential harmful and unintended consequences, particularly of physical and psychological health. The most cited concern of sport specialization is the prevalence of injuries. Sport specialization may expose athletes to increased risk of overuse injuries due to the frequency of repetitive motions, higher training volumes, and voluminous competitions (26, 31, 22, 12, 11). While physical injuries are often the focus, there is limited comprehensive epidemiological data on the emotional and psychological impacts of sport specialization (32). Previous research suggests that specialization can contribute to an increase in social isolation, overdependence, athletic burnout, reduced enjoyment, heightened dropout rates, and a decline in motivation (25, 27, 33, 28). 

A compelling psychological construct within the context of sport specialization is perfectionism. Perfectionism is defined as having “a commitment to exceedingly high standards combined with a tendency to critically appraise performance accomplishments” (15, 20). It is conceived as a multidimensional personality disposition construct capturing an individual’s pursuit of flawlessness in achievement and their concerns about failing to meet these high standards (13). Contemporary researchers posit that perfectionism overlaps a wide domain of ranges that fall in line with two higher-order dimensions: perfectionistic concerns and perfectionistic strivings (33). Perfectionistic concerns reflect the extent to which individuals are concerned about failing to achieve the standards that are placed on them by themselves or others, leading them to engage in harsh self-evaluation, which can negatively affect athletic performance (25). Moreover, perfectionistic concerns were positively correlated with burnout, rumination, fear of failure, amotivation, and performance-avoidance (21). The higher order of perfectionistic strivings is linked with self-oriented striving, where one places high goals on oneself intrinsically, and the setting of very high personal performance standards (18).   

Overall, research suggests that athletes who engaged in diversification were more likely to achieve sporting success. One survey of 376 Division-1 intercollegiate athletes revealed that, apart from the sport of swimming, 83% of college athletes reported participating in various sports, and many had different initial sporting experiences from their current sport (26). Diversification offers opportunities to cultivate a more versatile skill set essential for athletic success. Among elite athletes, those who participated in multiple sports during their formative years (ages 0-12) required less specialized training to acquire high-level skills in their chosen sport (1). Experts opine that early diversification, followed by specialization in later adolescence, leads to increased enjoyment, fewer injuries, and prolonged participation (2, 16, 35), which ultimately contributes to overall sport success (2). 

A framework for understanding sport involvement can be found in the Developmental Model of Sport Participation (DMSP). The DMSP is a framework that outlines pathways for youth sport involvement, emphasizing how participation can lead to different outcomes such as lifelong engagement, elite performance, or dropout. It integrates developmental, psychological, and social factors to guide sport programming and coaching practices. By outlining various pathways of sport participation, the DMSP provides insights into how individuals’ involvement in sports can potentially unfold over time. Young athletes enter the model in one of two ways: the sampling pathway or the early specialization pathway. In the early sport specialization pathway, athletes starting from age six to adulthood specialize in one sport characterized by a high deliberate amount of practice, a low deliberate amount of play, and focus on one sport. The other pathway, the sampling pathway, involves a high amount of deliberate play, a low amount of deliberate practice, and involvement in multiple sports in the initial stage (7). 

According to the DMSP, athletes who enter the sampling pathway, there are four main stages of development that align with specific ages and developmental needs. In the first stage, called the “sampling years”, there is an emphasis on deliberate play and sport diversification by participating in the sampling of multiple sports. The goal of the sampling years is that during this stage, youth athletes can either participate in sport sampling, meaning they play multiple sports, or they intensively participate in only one sport. This occurs approximately at the ages of six to twelve years old.  Proceeding this stage, at approximately age thirteen, serious athletes transition into the “specializing years”. The second stage of progression is called the “specializing years”, which happens around adolescence, during the ages of thirteen to fifteen years old, when youth athletes begin to focus on a smaller number of sports. While fun and enjoyment are still crucial features of their participation, sport-specific specialization starts in this phase, characterized by deliberate play, balanced practice, and a reduction in the involvement of other sports. During this stage, youth athletes can take three routes: continue participating in sport as a recreational activity, they can progress to the investment stage or opt to discontinue altogether (7). The final stage, known as the” investment phase”, occurs at 16+ years of age.  This stage is characterized by a high amount of deliberate practice, a low amount of deliberate play, and an increased focus on one sport (7). During this stage, the athlete becomes committed to high-performance goals in a specific sport where strategic, competitive, and skill development are the primary focus (22).  

To date, there has been insufficient research that has investigated the effects that specializing in sport might have on perfectionism. Thus, this study sought to investigate if there was a difference between athletes who specialized early or later in their athletic careers using the DMSP as a framework to construct our study (7, 8, 9). For this study, two research questions are being assessed. Research question I hypothesized that there is a significant difference between the time in which an athlete specialized in a sport during the sampling years (ages 6-11), specializing years (ages 12-14), investment years (ages 15-17), or post-investment years (ages 18+) with perfectionistic concerns. Research question II hypothesized that there is a significant difference between the time in which an athlete specialized in a sport during the sampling years, specializing years, investment years, and post-investment years. A series of one-way ANOVAs were conducted, one for each research question.  

METHODS 

Participants 

A total of 416 student-athletes (156 males, 260 females) from Division-1 colleges and universities participated in this study. Participants ranged in age of 18-25 years (M = 20.24, SD = 1.36), and competed in 15 overall sports. Participants were recruited following approval from the primary researcher’s institutional review board. Recruitment was conducted through an online survey administered via SurveyMonkey.com. Inclusion criteria stipulated that respondents must concurrently compete or be a member of an intercollegiate athletics team at a Division-1 NCAA institution.  Participants were recruited from various Division-1 NCAA schools representing all the Power Five and Group of Five conferences. Data collection from participants took place over a period of years beginning in 2018 and ending in 2024. 

Measures 

Participants completed a demographic questionnaire, a self-perceived sport specialization questionnaire, a questionnaire of subscales of perfectionistic concerns and strivings, and a questionnaire asking when athletes specialized in sports.  

Perfectionism 

Multiple measures were employed to assess the higher-order constructs of perfectionistic striving and perfectionistic concerns, following recommendations from previous studies (33, 34). The foundation for this study was provided by Hewitt and Flett’s Multidimensional Perfectionism Scale (H-MPS) (20) and Gotwals and Dunn’s Sport Multidimensional Perfectionism Scale (Sport-MPS-2) (17). Components from both inventories were amalgamated to form a 7-point Likert scale. The combined measures exhibited strong reliability (α = .892), consistent with previous findings (20, 17). 

Perfectionistic Concerns. To assess perfectionistic concerns accurately, three subscales were employed in the study. Two subscales from the Sport Multidimensional Perfectionism Scale-2 (Sport-MPS-2) (17) were utilized. The first subscale, titled “concerns over mistakes,” comprised eight items and assessed participants’ reactions to failure in competition, such as feeling like a failure as a person. The second subscale, “doubts about actions,” consisted of six items aimed at capturing participants’ uncertainties about the adequacy of their pre-competition practices. Additionally, a segment of Hewitt and Flett’s Multidimensional Perfectionism Scale (H-MPS) (20) was integrated to gauge fear of negative social evaluations. This segment, extracted from the “socially prescribed” perfectionism subscale, encompassed 15 items probing participants’ perceptions of others’ expectations of perfectionism from them, such as “People expect nothing less than perfectionism from me.” 

Perfectionistic Strivings: Perfectionistic strivings encompass self-oriented striving and the establishment of high personal performance standards. To assess this higher-order construct, two subscales were employed from both the Sport Multidimensional Perfectionism Scale (Sport-MPS-2) (17) and the Hewitt & Flett Multidimensional Perfectionism Scale (H-MPS) (20). To measure self-oriented perfectionism, the five-item self-oriented perfectionism subscale from the H-MPS was utilized. This subscale includes items such as “One of my goals is to be perfect in everything I do.” For the assessment of high personal performance standards, the seven-item personal standards subscale from the Sport-MPS-2 was employed. Example items from this subscale include “I hate being less than the best at things in my sport.” (17). Evidence supporting the internal consistency of these subscales has been provided, with reliability coefficients (α) exceeding .74 for both the H-MPS and the Sport-MPS-2 (10, 17) 

Sport Specialization 

In line with established methodologies (4, 22), a self-perceived questionnaire was utilized for this study. The questionnaire consisted of a three-point scale classification method, whereby respondents classified themselves as high, moderate, or low in terms of sport specialization. The questionnaire’s questions included: “Have you quit other sports to focus on one sport?”, “Do you train more than eight months out of the year in one sport?”, and “Do you consider your primary sport more important than others?” Respondents indicated their responses to these questions using a categorical classification system, where “yes” responses were assigned a value of 1 and “no” responses were assigned a value of 0. Based on the cumulative score from these questions, individuals were classified into different levels of specialization: a score of 3 denoted high specialization, a score of 2 indicated moderate specialization, and a score of 0 or 1 signified low specialization. 

Time of Sport Specialization 

To align with the Developmental Model of Sport Specialization, participants were asked three questions aimed at determining when they specialized in their current sport. Specifically, athletes were asked if they engaged in any other sport besides their current primary sport during their sampling years (ages 6-11), specializing years (ages 12-15), investment years (ages 15-17), and post-investment years (ages 18+). 

Data Analysis 

All data were assessed with IBM SPSS Statistics. A series of one-way ANOVAs were employed for this study.  

RESULTS 

Results for Perfectionistic Concerns 

For research question I, the research sought to investigate the hypothesis that there is a significant difference between the time in which an athlete specializes in a sport during elementary/primary school, middle school, high school, or college with perfectionistic concerns. Descriptive results from the participants for perfectionistic concerns and time of sport specialization can be found in Table 1. 

 

A one-way between-subjects ANOVA was conducted to compare the effect of when an athlete specializes in sport on perfectionistic concerns in elementary/primary school, middle school, high school, or college as conditions. There was not a significant effect on perfectionistic concerns for the four specialization time frames [F (3, 413) = .996], p > .05. Therefore, concerning the first research question, it was determined that the timing of specialization in sport did not exhibit any association with perfectionistic concerns among the participants. Regardless of whether athletes specialized during their sampling years, specializing years, investment years, or post-investment years, there was no discernible correlation with perfectionistic concerns, despite the athletes exhibiting high scores on this measure. 

 

Results for Perfectionistic Strivings 

For research question II, the research sought to investigate the hypothesis that there is a significant difference between the time in which an athlete specializes in a sport during sampling years, specializing years, investment years, and post-investment years with perfectionistic strivings. Descriptive results from the participants for perfectionistic strivings and the time of sport specialization can be found in Table 3. 

A one-way between-subjects ANOVA was conducted to compare the effect of when an athlete specializes in sport on perfectionistic strivings in the sampling years, specializing years, investment years, post-investment years. There was not a significant effect on perfectionistic strivings for the four specialization time frames [F (3, 413) = .805], p > .05. As it pertains to research question II, it was found that the time in which the participants specialized in sport was not a significant predictor of perfectionistic strivings. The analysis revealed that regardless of whether participants specialized in their primary sport during sampling years, specializing years, investment years, and post-investment years, there was no observable association with perfectionistic strivings. 

DISCUSSION 

The primary aim of these analyses was to investigate the relationship between the timing of sport specialization and perfectionism. Contrary to our hypotheses, the results indicated that regardless of the stage of sport specialization, there was no significant association observed with either perfectionistic concerns or perfectionistic strivings. Although this was not the primary focus, participants in the study displayed elevated scores on perfectionistic concerns overall. 

One potential explanation for the lack of differentiation between groups, despite athletes scoring high on perfectionistic concerns, could be attributed to the similarity in experiences among athletes. It is hypothesized that athletes may have had comparable sporting experiences, particularly since a significant portion of participants specialized during college (N = 235, ≈ 56%). This similarity in experiences might have led to the development of perfectionistic concerns in a uniform manner across the sample. 

Another potential reason for the absence of variation is due to the smaller number of participants who experienced early specialization in sampling and specialization years (N= 85, ≈ 20%) as compared to the high number of athletes who specialized later in investment and post-investment stages (N= 331, ≈ 80%). Our sample, however, parallels previous studies about when athletes tend to specialize, suggesting that sport diversification might not be a buffer or contributor to psychological constructs, either negative or positive ones. For example, a study found that athletes who engaged in sport diversification had no discernible difference in the measurement of mental toughness (5). It might be that psychological constructs develop over time and have a myriad of factors that contribute to their development, and that sport specialization and diversification play a small role, if any. 

The athletes in our study exhibited elevated levels of perfectionistic concerns but not perfectionistic strivings. According to the Development Model of Sport Participation, the ages of 13-15, yet even athletes who engaged in sport diversification prior to this stage still reported elevated perfectionistic concerns. These findings may contradict arguments that support sport diversification as a safeguard against negative psychological outcomes. However, it is important to consider that the participants in our study were current Division-1 NCAA athletes who were actively specializing in sport and no longer engaged in diversification. This suggests that concurrent sport specialization is more important than the stage of specialization. 

Given these findings, further longitudinal research on sport specialization and the timing of specialization is warranted. Understanding how specialization impacts athletes’ psychological well-being over time, particularly in comparison to those who engage in sport diversification, could provide valuable insights into the potential risks and benefits associated with different approaches to sport participation.  

These findings collectively suggest that the timing of sport specialization may not be a critical factor in determining psychological outcomes such as mental toughness or perfectionism among athletes. Instead, other variables such as individual personality traits, coaching styles, and environmental influences may play a more substantial role in shaping these psychological characteristics. 

Since our sample was limited to Division-1 college athletes and contained few individuals who specialized early, future research should examine athletes in sports where early specialization is the norm, such as gymnastics and figure skating, to explore differences between early and later specializers. Additionally, our findings imply that sport diversification may not act as a preventive measure against future psychological issues. Any psychological effects of sport specialization appear more closely tied to the current intensity and environment of specialization than to the specific age at which specialization began. 

LIMITATIONS 

While the present study contributes to the overall knowledge regarding athletes’ perceptions regarding sport specialization and perfectionism, this study is not without limitations. The sample included only Division-1 NCAA college athletes, a population considered “elite” due to their high level of athletic achievement. This homogeneity may have limited the variability of responses and reduced generalizability to broader athletic populations, such as youth, high school, or recreational athletes. Given their success, these athletes may also be more resilient to the negative effects of sport specialization and perfectionism, which may not be the case in less experienced or less accomplished athlete groups. 

Secondly, the classification of athletes into low, medium, or high levels of specialization relied on the widely used Jayanthi scale, which includes only three items. While this scale is prominent in the literature, its brevity may limit the depth and accuracy with which an athlete’s specialization history is captured. It may overlook key dimensions such as training intensity, emotional investment, or motivational drivers behind specialization, potentially leading to overly simplistic classifications. 

Third, the study utilized a cross-sectional and retrospective design based on self-report surveys. Participants were asked to recall past experiences and report on them at a single point in time, introducing potential recall bias and limiting the ability to draw causal inferences. A longitudinal design, tracking athletes’ specialization and perfectionism over time, would likely yield more robust and temporally sensitive data. 

Finally, purposive-homogeneous sampling was used, selecting participants from a distinct and specific subpopulation. While this method allows for targeted recruitment and can yield insights from a well-defined group, it may introduce researcher selection bias and limit generalizability. That said, this study was not designed to generalize to the broader population but rather to provide insight into a specific group of athletes who have achieved a high level of competitive success. 

CONCLUSION 

While the results of the study were contrary to our research hypothesis, the results of this study are not without merit. Findings from the current study add to the literature but also provide areas to be further studied. Athletes are continuing to specialize in sport at an increasing rate, despite current research showing that sport specialization is a non-adaptive behavior that yields very little benefit while carrying many potential negative consequences. Sport management professionals, coaches, parents, and athletes should be fully aware of the consequences of sport specialization, both physically and psychologically, before having athletes become specialized. The results of the present study indicate that even if an athlete follows the Development Model of Sport Participation by practicing proper sport diversification by the recommended age, it might not be enough to blunt the effects of maladaptive perfectionism, even if they reach the highest levels of competition, such as Division-1 athletics. Our results suggested that there was no difference between the athletes who specialized early or later in their athletic career.   

APPLICATIONS IN SPORT AND FUTURE RESEARCH 

Sport specialization continues to provoke debate among scholars, coaches, and parents, particularly regarding its efficacy and developmental impact. Similarly, perfectionism remains a focal point in sport psychology research, with ongoing research surrounding its adaptive and maladaptive dimensions. The current study aimed to add to the current body of knowledge for the sport community regarding both perfectionism and sport specialization.  

The Development Model of Sport Participation Model serves as a guiding framework for  

for coaches, athletes, and researchers to examine the implications of sport specialization and diversification. This study aimed to enhance understanding of how DMSP related to perfectionism in sport. The results of the analysis indicated that there was not a significant relationship between when an athlete specializes in sport, whether in their sampling, specialization, investment or post-investment years with perfectionistic strivings and perfectionistic concerns. While the null hypothesis was accepted, the finding still offer valuable insight for scholars, coaches and parents. Notably, even among elite Division-1 athletes are prone to maladaptive perfectionism, despite engaging in sport diversification properly. The lack of differentiation based on specializing timing raises concerns, given perfectionism association with negative psychological outcomes. Although these athletes achieved the highest levels of success, suggesting resilience, it remains uncertain whether similar patterns, or more severe psychological consequences, would manifest in less accomplished or younger athletes lacking the same resilience or comparable coping mechanisms. The need to further investigate this issue is clear. 

The physical consequences of sport specialization remain well documented, but its psychological ramifications warrant more research. Our findings support earlier research that the timing of sport specialization may be less impactful than concurrent sport specialization. Coaches and parents may benefit from using this information to better support athletes’ mental health, particularly while engaging in sport diversification. Despite an overwhelming percentage of participants adhering to DMSP principles, nearly all were engaged in specialization at the time of data collection and still reported elevated perfectionistic concerns. In a similar study also involving college athletes, there was no discernible difference found in mental toughness between early sport specializers and those who diversified (5). Similarly, our current study indicates that the stage of sport specialization, whether early or late in an athlete’s career, does not predict perfectionism tendencies. 

Athletes are continuing to specialize in sport at an increasing rate, despite current research showing that sport specialization is a non-adaptive behavior that yields very little benefit while carrying many potential negative consequences. Furthermore, one can surmise that Name, Image, and Likeness in college athletics, with increased financial incentives and opportunities, may exacerbate the rate of sport specialization in the future, since athletes no longer need to reach the professional levels to reap financial reward.  Sport management professionals, coaches, parents, and athletes should be fully aware of the consequences of sport specialization, both physically and psychologically, before having athletes become specialized.  

The study sets a foundation for future research on sport specialization, albeit with limitations. Participants retrospectively reflected on past experiences, and the study’s cross-sectional design may have drawbacks. A longitudinal approach, tracking athletes during active participation, could yield more precise insights. Additionally, the exclusive focus on Division-1 NCAA athletes may limit generalizability; exploring athletes across various levels and ages is imperative. Furthermore, investigating specialization dynamics in different sports, particularly those requiring early specialization like gymnastics, versus those promoting diversification, is crucial. Moreover, exploring how team sports compare to individual sports regarding specialization and perfectionism would add depth to understanding these phenomena. This study sought to explore an emerging area of research in sport specialization. Overall, this study provides a basis for further research as well as provides future suggestions by offering additional opportunities to further investigate the effects of sport specialization on perfectionism. 

Troy Palmer2025-09-25T15:13:42-05:00

Managerial practices and coach satisfaction: A summer camp recreation and athletics case study 

Troy Palmer2025-09-25T15:13:42-05:00October 24th, 2025|Research, Sport Education, Sports Coaching, Sports Facilities, Sports Health & Fitness|

Editor’s Note: This article uses the pseudonym Camp Mid-East. While the dates of the study and camp name are withheld, The Sport Journal has verified the identity of the author and confirmed the camp’s existence through a virtual meeting. This note serves to assure readers that reasonable steps have been taken to confirm the legitimacy of the content presented.

ABSTRACT 

This case study examines how specific managerial practices influenced coaching staff satisfaction at Camp Mid-East, a residential summer camp in the United States. In response to persistent challenges related to staff retention and satisfaction, the camp implemented a mission statement, operational guidelines, and structured communication strategies within its athletic and recreation department. Using a pre- and post-camp survey design, the study measured changes in coach perceptions across four domains: communication, operational clarity, mission alignment, and overall satisfaction. Descriptive statistics and Wilcoxon Matched-Pairs Signed-Rank Tests were used to analyze the data. Results indicated improvements in communication practices, with more variable outcomes related to mission clarity and satisfaction. These findings contribute to the growing body of research on organizational support in recreational settings and offer practical insights for camp administrators seeking to improve staff engagement, reduce burnout, and enhance the overall staff experience through intentional leadership practices.

KEYWORDS: coach satisfaction, managerial practices, outdoor recreation, staff retention, summer camp

INTRODUCTION 

Organized camping has been a notable facet of American culture since its inception in 1861, gaining widespread appeal among diverse demographics (2, 49). The American Camp Association (ACA) reports significant growth in the camping industry, characterized by increased attendance and revenues, with millions of children, parents, and adults participating in various camping experiences (5). From 2017 to 2019, ACA reported a 30% increase in attendance at accredited camps, rising from 7.3 million to 10.3 million campers (2, 5). The ACA is currently partnering with the University of Michigan Economic Growth Institute, and the ACA revealed that the youth camp sector generates an annual economic impact of approximately $70 billion, underscoring the industry’s substantial influence across the United States (5).

Previous research on camping has explored various aspects of participation, including the benefits it provides, especially its ability to promote well-being through time spent in nature. Research has highlighted the psychological advantages of spending time in natural environments, including stress relief and a mental break from daily routines (13, 29). Additional scholarship has further emphasized the mental health benefits of outdoor environments, particularly as safe spaces that foster emotional resilience among youth and adults (27, 41). Additional studies have explored the satisfaction derived from activities such as cooking, teamwork, and forming bonds through shared experiences with family and peers (9, 26).

There are numerous types of camping, from day camps to residential camps, tenting, and RVing. Residential camps, or sleep-away camps and the setting for the current research, provide immersive experiences where children and adolescents, typically aged 6 to 16, reside in camp settings for extended periods during the summer, engaging in various activities (6). The success of these camps relies heavily on the efforts of camp professionals (e.g., counselors, coaches, and staff) who are committed to delivering memorable camper experiences. Each summer, thousands of dedicated staffers, counselors, and coaches work to provide the best experience possible for millions of youth campers (4). Research exploring camp staff experiences has primarily focused on factors such as job motivation (43), retention rates (45), and emotional challenges (58, 59). Some studies address the social-emotional behaviors of counselors, their interactions with campers, and the high rates of burnout and job dissatisfaction within this sector. Findings suggest that organizational support and communication are essential in mitigating burnout among seasonal camp staff (12, 20, 63). Additionally, the role of camp counselors in promoting positive youth development through sports and leadership has been emphasized (32, 35, 54, 57).

The camping industry faces current staff retention and well-being challenges, especially as camps adjust to operational shifts and staffing shortages following the COVID-19 pandemic (30, 33). A 2021 ACA report highlighted these post-pandemic challenges, noting that camps must now balance staff shortages with the increasing needs of campers in a more complex emotional and operational environment (4, 30). Despite a considerable body of research on camp experiences, there remains a gap in understanding the organizational and operational strategies that support camp counselors and coaches, particularly in how structured communication, mission statements, and operational guidelines can enhance staff satisfaction.

The current research explored implementing managerial practices to improve coach satisfaction at Camp Mid-East, a residential summer camp in the United States. By analyzing the impacts of a clear mission statement, defined operational guidelines, and strategic communication practices, the study seeks to illustrate how these elements contribute to job satisfaction among camp coaches. Literature on organizational clarity and communication strategies indicates that these interventions may positively influence employee satisfaction and retention (60). Therefore, this study posed the following broad research question: Will implementing a mission statement, operational guidelines, and structured communication within the athletic department at Camp Mid-East enhance coach satisfaction?

The structure of the manuscript is designed to clearly convey the study’s context, findings, and implications. The manuscript begins with a description of the empirical setting at Camp Mid-East to establish the study’s context. This is followed by a review of literature related to outdoor recreation, challenges faced by camp staff, and the influence of leadership and organizational practices on staff satisfaction. The methods section outlines the study design, participants, data collection, and analysis procedures. Next, the results of the pre- and post-camp surveys are presented, highlighting key findings related to communication, operational guidelines, mission alignment, and satisfaction. The discussion interprets these findings in relation to prior research and practical implications for camp leadership. Finally, the conclusion addresses limitations and offers recommendations for future research on staff satisfaction and organizational practices in residential camp settings.

EMPIRICAL SETTING

According to the ACA (2024b), there are 3,904 camps available, from day camps to overnight camps for youth, adults, and families. Overnight summer camps in the United States vary widely in size, typically hosting between 100 to over 1,000 campers. Many camps are separated by gender and operate for durations ranging from one to eight weeks, with tuition costs reaching the thousands. For example, Camp Neshoba in Maine has charged as much as $10,500 for an eight-week session, accommodating 190 campers with nearly 100 staff members. Summer overnight camps primarily offer recreational activities, including a range of sports, arts and crafts, and wilderness training.

In a youth residential camp setting, an Activity Director often oversees various programming areas, and the coaches manage activities for the children. The staff that watches over the youth at these camps are hired for dual roles as counselors and coaches based on previous experience in a sport or activity. For example, a counselor may be hired because they have experience with baseball as a collegiate player or are a fine arts major in college focusing on ceramics.

Camp management faces ongoing challenges related to communication and staff organization. Henderson et al. (2007) noted that recruiting competent and caring staff, counselors, and coaches is among the greatest challenges for camp directors. Employee retention is critical for organizational cohesion: a 2011 survey by a regional camping association found staff retention rates ranging from 25% to 75%, with an average return rate of 50% (1 as cited in 45). A 2018 ACA study further reported that 60% of camp staff intended to return for the following summer (3). Understanding the motivational tendencies of staff can aid directors in interpreting and predicting employee behaviors and overall job performance (42).

Camp Mid-East, the location for this case study, is a co-ed camp founded in 1953. At the time of data collection, this camp hosted more than 400 youth campers and offered a variety of activities with a focus on recreational programming, over an 8-week period during the summer. Campers participated in sports such as baseball, basketball, gymnastics, sailing, and soccer and non-sport activities like ceramics, robotics, cooking, and other crafts. Camp Mid-East operated under the core values of gratitude, attitude, and courage, which are defined through thankfulness, attitude as a daily choice, and courage through everyday actions. Staff, counselors, and coaches, primarily college students, complete a multi-day training program covering safety, camper profiles, and team-building.

LITERATURE REVIEW

Outdoor recreation, such as camping, has many benefits. Bultena and Klessig (1969) identified significant psychological relief from participating in recreational camping, a theme reinforced by later studies (c.f. 29). These works highlight how immersion in nature reduces stress, improves mood, and enhances well-being, which aligns with more recent research on the mental health benefits of outdoor environments (17, 52). Beyond psychological relief, camping fosters independence and resilience by requiring participants to complete tasks like cooking and cleaning while promoting social bonding and community-building, particularly in youth settings (28, 26, 48, 59). One popular form of camping, residential or sleep-away camping, offers an immersive environment where participants live together for extended periods, facilitating unique social and developmental opportunities. Camps employ staff, counselors, and coaches who play a critical role in facilitating meaningful experiences for youth participants and ensuring the successful operation of residential camps (48).

Challenges Faced by Camp Staff

Burnout of camp staff has become a critical concern for camp administration, mirroring challenges faced in coaching and other high-stress professions. Kelley (1994) explored burnout in coaches, identifying it as the result of prolonged exposure to stress, role conflicts, and emotional exhaustion. This research continues to expand to include summer camp coaches, who often face similar stressors. Camp coaches work long hours, manage the behaviors of young campers, and navigate interpersonal conflicts, all of which contribute to emotional fatigue, stress, burnout, and turnover (45, 58, 63).

As McCole et al. (2012) noted, key factors contributing to burnout are seen as important topics by the ACA. Amonett (2021) underscores the importance of creating mentally healthy environments through strategies like regular check-ins, fostering open communication about mental health, and offering proactive support to staff. For instance, recognizing early signs of burnout, such as behavioral changes or social withdrawal, allows camp administrators to intervene before these issues escalate. Moreover, Amonett (2021) advocates for a culture in which leaders share their own mental health experiences, helping to foster a supportive atmosphere where staff feel comfortable seeking assistance. This proactive approach reduces burnout, enhances staff performance, and improves the camper experience. Wahl-Alexander, Richards, and Washburn (2017) found that the physical and emotional demands placed on camp staff and inadequate organizational support significantly increased the likelihood of staff not returning after just one season.

Recent studies have highlighted ongoing challenges related to staff burnout and retention, particularly during periods of increased operational and societal stress. Camps have faced difficulties retaining experienced staff members, resulting in a greater reliance on less experienced counselors and coaches (10, 14). Edwards et al. (2013) emphasized the importance of implementing comprehensive support structures to help staff navigate these intensified demands, including effective communication systems and emotional support resources. These efforts are essential in promoting staff wellness, as fostering a healthy work environment reduces burnout and improves staff retention. Camps prioritizing their staff’s mental and emotional well-being may be better positioned to provide high-quality experiences for campers, resulting in more positive outcomes for both staff and participants.

Leadership and Managerial Practices in Camps

One of the most effective tools for aligning staff with the goals and values of an organization is the use of a mission statement. A well-crafted mission statement provides a clear sense of purpose and guides decision-making and conflict resolution (36, 53). Mission-driven leadership fosters a sense of belonging and purpose among staff, enhancing job satisfaction and performance (36, 46, 53). Braun et al. (2012) highlight that the rationales behind mission statement development, such as motivating employees and promoting shared values, are positively associated with various organizational outcomes, including staff engagement and performance. Clear communication of a mission statement enhances job satisfaction and reduces turnover rates.

Additionally, aligning mission statements with organizational structures and involving stakeholders in their development contributes to their overall effectiveness. This alignment fosters clarity of purpose among staff, thereby enhancing job satisfaction and alleviating confusion regarding roles and expectations. Furthermore, effective mission statements can serve as motivational tools, significantly influencing employee behavior and organizational commitment.

While the personal and emotional experiences of campers and staff are well-documented, fewer studies have examined the impact of managerial practices on camp operations and staff satisfaction. However, research consistently emphasizes that leadership plays a critical role in shaping the camp experience for both campers and staff. Strong leadership, effective communication, and clear operational guidelines are essential for creating a positive work environment, directly influencing staff satisfaction and retention. Leaders who engage in transparent communication foster a supportive organizational culture, improving team dynamics and encouraging staff to feel valued and motivated to stay longer (21, 31, 47). Additionally, well-structured leadership frameworks that provide autonomy, competence, and relatedness further enhance employee engagement and increase staff retention rates (43).

Camp counselors and coaches can thrive in environments where expectations are clearly defined and where they feel supported by administrative leadership. Halsall and Forneris (2018) found that organizational support is critical in reducing burnout among camp counselors. Their study revealed that when staff have access to necessary resources and open communication channels, they experience lower levels of burnout and are more likely to return for multiple camp seasons. This idea aligns with broader research, consistently highlighting the importance of leadership clarity and effective managerial practices in maintaining employee satisfaction and well-being. Tian et al. (2020) emphasized that transformational leadership, characterized by clear communication, goal setting, and a supportive environment, significantly improves employee retention by reducing burnout and enhancing job satisfaction. Similarly, Bailey et al. (2012) focused on predictors of burnout in camp staff, finding that leadership clarity and feelings of being valued and having well-defined expectations are critical factors in reducing burnout and improving staff well-being and retention.

While previous research has examined leadership, communication, and organizational support in various contexts, a gap exists in understanding how specific managerial practices affect camp staff satisfaction, particularly coaches. This study seeks to address this gap by exploring how implementing a mission statement, operational guidelines, and structured communication systems at Camp Mid-East impacts coach satisfaction. In an era of increasing challenges in retaining qualified staff, understanding the role of management practices in fostering job satisfaction is crucial. Camps that invest in clear communication, mission alignment, and operational support their position to retain staff and deliver high-quality programming to campers.

By investigating the link between managerial practices and staff satisfaction, this study contributes to the growing body of research on camp operations, offering practical insights for administrators aiming to refine their leadership strategies. Moreover, it underscores the need for camps to prioritize staff well-being and professional development as essential to operational success.

METHODS 

This current research study used a quantitative case design to explore the impact of managerial practices—specifically, the implementation of a mission statement, operational guidelines, and communication strategies—on coaching satisfaction at Camp Mid-East. Pre- and post-camp surveys assessed the effectiveness of these interventions, an approach well-suited for investigating complex, context-specific phenomena in real-life settings (62).

Research Design

A quantitative case study approach was selected to analyze how mission-driven interventions influenced coaching satisfaction. By focusing on a single camp, this design allowed for a detailed examination of the effects of the camp’s mission, guidelines, and communication on coaching satisfaction. Pre- and post-camp surveys enabled a comparative analysis, capturing changes in satisfaction over time and providing insight into the impact of these managerial strategies (19). The survey data gathered before and after the camp facilitated a matched analysis using inferential and descriptive statistics.

Data Collection

All counselors and coaches had the opportunity to participate in the study. Participants included male and female coaches aged 18–40 who could opt into or decline to participate in the survey. The study aimed to quantitatively assess coaching satisfaction across various experience levels. Given the limited sample size, the findings were intended to be context-specific to Camp Mid-East, aligning with the case study approach’s emphasis on in-depth, contextual insights (62).

A survey was developed to measure the impact of the camp’s mission, operational guidelines, and communication strategies on coaching satisfaction. The survey’s content validity was confirmed through a review by five residential camp athletic administration professionals at other camps (23, 24). Both pre-and post-camp surveys contained 16 Likert-scale questions (1 – strongly disagree to 4 – strongly agree), covering perceptions of the mission statement, operational guidelines, communication strategies, and overall satisfaction factors, such as salary (37). Participants were assigned unique identification numbers to maintain confidentiality, and only complete pre/post-camp surveys were included in the analysis.

An orientation session over two days introduced coaches to the camp’s mission, guidelines, and communication protocols. Additional weekly small group meetings throughout the camp reinforced these practices. Observations were conducted to ensure adherence to safety protocols and effective interactions between coaches and campers (50). Post-camp surveys were administered at the camp’s conclusion. All data was securely stored to ensure confidentiality (55).

Data Analysis

Descriptive statistics summarized overall trends in coaching satisfaction, focusing on items related to mission alignment, communication, and policy implementation. This analysis provided a comprehensive understanding of the changes in satisfaction and the effectiveness of the managerial interventions (39). A Wilcoxon Matched-Pairs Signed-Rank Test was used to compare pre- and post-camp survey responses, as this nonparametric test is appropriate for ordinal data from paired samples in small sample studies (22). The Wilcoxon Matched-Pairs Signed-Rank Test was chosen because it is well-suited for analyzing paired ordinal data, such as Likert-scale survey responses, without assuming a normal distribution. Given the small sample size and the use of pre- and post-surveys from the same participants, this nonparametric method provided a robust approach to detecting meaningful changes in coaching satisfaction over time.

RESULTS 

Statistical analyses evaluated coaches’ perceptions of mission statements, policies/procedures, effective communication, and compensation and administrative support satisfaction. Surveys were distributed to all 68 counselors and coaches in the study population. Of these, 65 surveys were usable for analysis, resulting in a response rate of approximately 95%. The survey assessed coaches’ and counselors’ perceptions of organizational goals, communication, policies, compensation, and overall satisfaction within the camp setting.

The survey descriptive results and statistical analyses presented in Tables 1 and 2 provide participant responses before and after camp across four core areas: Communication, Guidelines, Mission, and Satisfaction. Table 3 provides a closer look at the data that resulted in statistical significance. These findings shed light on both stable and variable aspects of participant perceptions.

Communication

As shown in Table 1, Communication items maintained high scores from pre- to post-camp. For instance, item 5 (communication) reflects the highest levels of satisfaction with minimal variability, with a pre-camp mean of 3.89 (SD = 0.31) and a post-camp mean of 3.92 (SD = 0.32). This stability suggests a broadly positive perception of camp communication practices.

In contrast, items 11 and 12 experienced declines in satisfaction, as depicted in Table 1. For item 11, the mean decreased from 2.61 to 2.25, and item 12, from 2.25 to 1.95, indicating areas where communication may not have fully met participant expectations. The increase in standard deviations for these items highlights more significant response variability, which may point to inconsistent communication experiences among participants.

Guidelines

Responses related to the camp’s guidelines displayed variability, with some items improving slightly and others showing minor declines (see Table 1), suggesting mixed responses. For example, item 2 saw a slight decrease in mean from 3.62 to 3.49, while item 4 showed an increase from 3.57 to 3.63, with a reduced standard deviation. This mixed response may suggest varying interpretations or clarity regarding guidelines among participants.

Mission

As outlined in Table 1, responses regarding the camp’s mission remained consistent, though slight declines were noted in items 3 and 7. Item 3 decreased from a mean of 3.67 to 3.45, while item 7 showed a minimal drop from 3.05 to 3.02. Although these differences were not statistically significant, the results indicate that reinforcing the camp’s mission throughout the experience may improve participant alignment with camp goals.

Satisfaction

The satisfaction category, summarized in Table 1, showed the most pronounced declines, particularly in items 6, 14, and 16. Item 6, for example, dropped from a pre-camp mean of 2.62 to a post-camp mean of 2.25. The increased standard deviations in these items suggest diverse individual experiences, indicating that some participants may have felt less satisfied with aspects of the camp as it progressed.

Statistical Analysis

A Wilcoxon Signed Ranks Test was conducted to assess changes between pre- and post-camp responses, with results presented in Table 2. This nonparametric test, suitable for paired samples with non-normally distributed data, identified significant and non-significant changes. Table 3 represents statistical significance related to the pre/post survey with a summary of this below.

Significant Differences

Items pre/post Q6: As indicated in Table 2, this item demonstrated a statistically significant change, with a Z-score of -3.138 and a p-value of .002. This reflects a notable decline in satisfaction, consistent with findings in Table 1.

Items pre/post Q11: Table 2 shows that this item also experienced a significant change (Z = -2.800, p = .005), suggesting a meaningful decrease in participants’ perceptions of communication quality.

Items pre/post Q14: This item, with a Z-score of -2.318 and a p-value of .020, reflects another statistically significant drop in satisfaction.

Non-Significant Differences

Other items not displayed in Table 2 did not exhibit statistically significant changes, with p-values above 0.05. For example, items 1.1 – 2.1 (Z = -0.352, p = .725) and 1.7 – 2.7 (Z = -0.354, p = .724) indicate stable perceptions, suggesting that responses for these items remained consistent from pre- to post-camp.

Summary of Findings

This case study examined the effects of targeted managerial interventions—including a mission statement, operational guidelines, and structured communication strategies—on coach satisfaction at Camp Mid-East. Sixteen survey items were used to measure pre- and post-camp perceptions across four key domains: communication, guidelines, mission alignment, and satisfaction.

Analysis revealed that three of the sixteen items (19%) showed statistically significant declines from pre- to post-camp, while the remaining thirteen items (81%) showed no significant change, indicating generally stable perceptions across most areas. The three items that did significantly decline were:

Item 6 – Satisfaction with compensation: declined from a mean of 2.62 to 2.25 (p = .002),

Item 11 – Clarity of communication from supervisors: dropped from 2.61 to 2.25 (p = .005),

Item 14 – Perceived administrative support: decreased from 2.62 to 2.30 (p = .020).

While these declines highlight areas for improvement, other items remained stable or even slightly improved. For instance, Item 5 (general satisfaction with communication) retained high ratings from pre- to post-camp (3.89 to 3.92), and Item 4 (clarity of camp guidelines) showed a modest increase (3.57 to 3.63), albeit not statistically significant. Items tied to the camp’s mission—such as Item 3 (understanding of the mission) and Item 7 (alignment with camp values)—remained relatively consistent but saw slight, non-significant declines (3.67 to 3.45 and 3.05 to 3.02, respectively).

Further, while communication was a consistent strength across most items, variability emerged in responses to Items 11 and 12, indicating that not all staff experienced communication equally. This points to an opportunity to refine communication systems to ensure consistent clarity and access to information for all team members.

The results in the guidelines and mission domains suggest mixed interpretations or engagement, with no statistically significant changes but some variability in mean scores. These findings imply that while the structural interventions were clearly introduced, their reinforcement throughout the camp may have been uneven or insufficient to shift perceptions meaningfully.

The most notable shifts occurred in the satisfaction domain, where items related to compensation, administrative support, and overall experience revealed declines. These results suggest a potential disconnect between staff expectations and their lived experiences, especially as the camp progressed.

While the interventions did not produce widespread statistically significant changes, the findings reflect the complexity of staff satisfaction in seasonal camp environments. Importantly, this case study is not intended to produce generalizable outcomes but rather to offer context-specific insights that contribute to the broader conversation on leadership, organizational practices, and staff well-being in recreational settings. These exploratory results underscore the need for continued, multi-site research that investigates the long-term and cumulative effects of managerial strategies on staff engagement and satisfaction in youth camps and similar settings.

DISCUSSION 

This study aimed to bridge the gap in the literature by examining the effects of managerial practices—specifically the implementation of a mission statement, operational guidelines, and structured communication—on coach satisfaction in a summer camp setting. While previous research has focused on the benefits of camping for participants and the psychological effects of outdoor experiences (29, 61), less attention has been given to the experiences of camp staff, particularly coaches. Even fewer studies have explored how leadership and organizational strategies within camps impact the satisfaction, retention, and overall effectiveness of these staff members.

Key Findings

The results of this study indicate that implementing a mission statement, operational guidelines, and structured communication strategies led to slight improvements in coach satisfaction at Camp Mid-East in some areas, while other areas showed statistical significance. These finding aligns with existing research that emphasizes the importance of organizational clarity in enhancing job satisfaction and reducing burnout in recreational and educational settings (8, 58). Coaches at Camp Mid-East reported higher levels of satisfaction with their roles and responsibilities following the introduction of these managerial tools, supporting previous studies suggesting that clear communication and aligned organizational goals can significantly improve staff morale (32, 56).

The most notable improvement was observed in communication, with coaches reporting increased satisfaction regarding their ability to receive timely updates and feedback from camp leadership. This finding echoes the work of McCole et al. (2012), who found that open and consistent communication is a key factor in employee satisfaction. Furthermore, the structured weekly meetings and open-door policy implemented at Camp Mid-East allowed coaches to feel more connected to the camp’s leadership, thereby reducing misunderstandings and fostering a more collaborative work environment. This also aligns with Edwards et al. (2013), which highlighted that camps with robust communication strategies were more successful in retaining staff year after year.

The findings of this study are consistent with a growing body of literature that underscores the importance of organizational support and clarity in maintaining staff satisfaction. For example, Wahl-Alexander et al. (2017) found that camp counselors who received clear organizational support experienced lower burnout and higher job satisfaction levels. Similarly, research on youth sports coaching has highlighted the role of communication and mission alignment in improving the performance and retention of coaches (32, 56).

However, this study builds on existing research by focusing on the managerial practices of a summer camp’s athletic department. While past studies have examined the role of leadership in outdoor recreation settings broadly, few have investigated how specific managerial tools, like mission statements and operational guidelines, directly influence the job satisfaction of camp coaches. By implementing these tools at Camp Mid-East, this research provides evidence that aligning staff with a clear mission and operational structure can improve their satisfaction and effectiveness. Additionally, literature has underscored the importance of organizational clarity in the context of post-pandemic challenges. Amonett (2021) highlighted the growing need for camps to support their staff through improved communication and operational guidelines, especially as camps face new challenges related to staff shortages and increased emotional demands.

Bridging the Gap in Existing Research

This study addresses a significant gap in the literature by examining the relationship between managerial practices and coach satisfaction within residential camps. Previous research has focused on campers’ experiences or the broader benefits of camping, while camp life’s operational and managerial aspects have yet to receive much attention. Although studies on burnout and staff retention highlight the need for better support systems, few have investigated managerial tools that can prevent burnout and enhance job satisfaction (8, 58).

The findings suggest that implementing a clear mission statement, operational guidelines, and structured communication systems improves coach satisfaction and addresses staff retention and performance challenges. High turnover rates disrupt camper experiences and create operational difficulties. This research demonstrates that these managerial tools can effectively enhance coach satisfaction, providing practical solutions for camp administrators to improve staff retention and performance.

Furthermore, this study builds on prior findings by illustrating how mission-driven leadership aligns staff with the camp’s broader goals. Previous research, such as Braun et al. (2012), has emphasized the significance of mission statements in organizational contexts. This study extends that work by providing empirical evidence that effectively communicated and reinforced mission statements positively impact staff satisfaction in summer camps.

CONCLUSION 

This study contributes to the growing body of research on organizational leadership in residential camps by providing empirical evidence that managerial practices—specifically, the use of a mission statement, operational guidelines, and structured communication—can positively impact coach satisfaction. While the observed improvements were modest in some areas, the findings underscore the value of clear organizational strategies in fostering a supportive and effective work environment for seasonal staff. As camps continue to face post-pandemic staffing challenges, these results offer actionable insights for camp administrators seeking to enhance staff morale, retention, and overall program quality.

APPLICATIONS IN SPORT

The findings of this case study offer practical insights for those working in sport-based summer camps and similar youth sport environments. While the managerial interventions at Camp Mid-East—implementation of a mission statement, operational guidelines, and structured communication—did not produce widespread statistical changes, they did yield important lessons for camp leaders, coaches, and administrators. Specifically, three areas—compensation satisfaction, clarity of communication from supervisors, and perceived administrative support—emerged as key concerns, with significant declines observed from pre- to post-camp.

For coaches and activity leaders, these results highlight the importance of consistent communication and feeling supported by leadership. Structured communication systems (such as weekly check-ins, feedback loops, and open-door policies) were well received in some areas, but inconsistencies noted in supervisor communication suggest a need for clearer messaging across all levels of staff. Coaches benefit from knowing what is expected of them, how their performance is evaluated, and where to seek help or guidance during high-stress moments in the camp season.

For camp directors and sport program administrators, the study underscores that even well-intentioned managerial tools must be implemented thoughtfully and reinforced consistently. Simply introducing a mission or set of guidelines at orientation may not be sufficient. Ongoing reinforcement throughout the season—through meetings, signage, and leadership modeling—is likely needed to help staff internalize and act upon those values. Additionally, the findings on declining satisfaction around administrative support and compensation suggest that camp leaders should consider how recognition, feedback, and fair treatment can impact staff morale, especially in high-demand roles like coaching.

For parents and guardians, this study provides assurance that some camps are working toward building stronger support structures for the individuals entrusted with leading and mentoring their children. Staff who feel supported and valued are more likely to provide positive, consistent experiences for campers—both on and off the field.

Finally, for researchers and sport management professionals, the results support the need for continued study into seasonal staff satisfaction and retention in sport-specific contexts. Although the findings of this single case are not generalizable, they open the door for further exploration of how mission-driven leadership and communication frameworks can influence staff outcomes in youth sport and recreation.

By grounding conclusions in the actual data and acknowledging where changes did and did not occur, this study contributes to a growing dialogue about staff well-being in sport settings. It invites practitioners to ask not just what policies are in place, but how they are implemented, communicated, and experienced by staff in real time.

LIMITATIONS AND FUTURE DIRECTIONS

While this study provides valuable insights into the impact of managerial practices on coach satisfaction, several limitations must be acknowledged. The small sample size restricts the generalizability of the findings to larger camps or recreational settings. Future research could investigate the applicability of these findings to diverse types of camps and examine the long-term effects of these managerial practices on staff retention and performance.

Engaging leadership, which fosters autonomy, competence, and relatedness, has increased staff engagement and satisfaction (44). By focusing on inspiring, strengthening, and connecting employees, such leadership styles enhance team effectiveness, improve retention, and increase commitment to the camp’s mission and values. This alignment of leadership behavior with critical psychological needs creates an environment where staff feel supported and valued, leading to sustained engagement over time.

Additional limitations were the way in which methods and mediums of communication guidelines and mission messaging were delivered to counselors and coaches. Lines of communication were offered but may have yet to be shown to be the best ways of communication during a summer camp setting. Feedback during camp on the best communication mediums should have been offered to counselors and coaches.

These findings are especially relevant for Camp Mid-East, as staff often navigate multifaceted roles while working with youth from diverse backgrounds. Aligning leadership with engaging principles—such as fostering connection and inspiration—can significantly enhance staff morale and retention (44, 16). Reduced staff turnover strengthens the relationships between staff and campers, improving overall program quality. By investing in leadership and operational strategies prioritizing staff well-being, camps can continue delivering high-quality programming and cultivating an enriching environment for campers and staff.

It should be noted here that while the findings offer useful insights into how managerial practices may influence coach satisfaction, it is important to note that only a small number of statistically significant changes emerged. Specifically, three of the sixteen survey items showed meaningful differences from pre- to post-camp, suggesting that the interventions—while thoughtfully implemented—had limited measurable impact over the short camp session. Most responses remained stable, indicating that while communication, guidelines, and mission alignment were introduced, they may not have been reinforced consistently enough to shift perceptions across the board. These results should limit expectations about the immediate effectiveness of such practices and reinforce the need for ongoing support, sustained implementation, and further research across multiple settings to better understand how managerial strategies contribute to staff satisfaction in seasonal camp environments.

Additionally, while this study focuses on coach satisfaction, future research should explore the effects of managerial practices on other aspects of camp staff performance, such as leadership development and camper outcomes. Investigating how these managerial tools influence staff performance across various domains could yield a more comprehensive understanding of the factors contributing to successful camp operations.

This study contributes to the growing body of literature on camp management by highlighting the often-overlooked role of managerial practices in shaping staff satisfaction, particularly in summer camp athletics. The research demonstrates that implementing a mission statement, operational guidelines, and structured communication systems enhances coach satisfaction at Camp Mid-East. These findings align with previous studies emphasizing the importance of organizational clarity, communication, and leadership in reducing burnout and improving job satisfaction among camp staff (8, 32, 58).

By addressing existing research gaps, this study underscores the practical significance of mission-driven leadership and clear operational structures in maintaining high staff satisfaction. As camps face increasing staffing challenges and operational demands—particularly in the post-pandemic landscape—this research offers actionable insights for camp administrators seeking to enhance management strategies. Camps that prioritize staff well-being through effective communication and organizational support are better equipped to retain experienced personnel, improving the overall camp experience for campers and staff.

While the study’s findings are valuable, limitations such as the small sample size and focus on a single camp indicate the need for further research to explore how these managerial practices impact staff in diverse camp settings. Future studies could examine the long-term effects of these interventions on both staff retention and camper outcomes, enhancing our understanding of how leadership strategies influence the success of camp programs. This study emphasizes the importance of effective leadership and organizational practices in enhancing job satisfaction among camp staff, providing a framework for camp administrators to create supportive, mission-driven environments that foster staff well-being and camp success.

George Minoso2025-10-28T09:21:32-05:00

Extending the curve: A Closer Look at High-Velocity Measures in the Power Clean.

George Minoso2025-10-28T09:21:32-05:00October 17th, 2025|Research, Sport Training, Sports Exercise Science, Sports Studies|

Wei Qian Lim1, MS, David Smith2, Eric D. Magrum2, PhD,
The George Washington University1, Washington, DC
James Madison University2, Harrisonburg, Virginia

Editor’s Note: Table 1 was incorrectly published. This has been corrected. Tables 2 and 3 were reformatted during the revision process.

Abstract
Purpose: This study examines the validity and reliability of a commercially available velocity-based training device, GymAware, when measuring barbell velocity during submaximal power cleans. While GymAware has been validated for slower movements, limited research has assessed its accuracy at higher velocities, particularly in Olympic weightlifting derivatives.
Methods: Ten resistance-trained participants completed two sets of five repetitions at 40%, 50%, and 60% of their perceived one-repetition maximum in the power clean. Mean and peak barbell velocity were recorded using GymAware and compared to a motion capture system as the criterion measure. Data were analyzed for reliability using intraclass correlation coefficients and validity through correlation and regression analysis.

Results: Mean velocity measurements from GymAware demonstrated strong agreement with motion capture across all loads, with correlations exceeding 0.85 and an intraclass correlation coefficient of 0.85, indicating good reliability. However, peak velocity measurements exhibited greater variability, with a systematic overestimation of 0.37 m/s and a lower reliability coefficient (0.31). Linear regression models confirmed that GymAware accounted for 88% of the variance in mean velocity but only 44% in peak velocity, suggesting less precision in high-velocity movements.

Conclusion: GymAware provides reliable and valid measurements of mean barbell velocity but has limitations in accurately assessing peak velocity during rapid weightlifting movements. Coaches and practitioners should prioritize mean velocity when utilizing velocity-based training for performance monitoring.

Application in Sports: Velocity-based training offers an efficient method for tracking performance and adjusting training loads. GymAware’s ability to measure mean velocity reliably makes it a useful tool for monitoring training adaptations and providing immediate feedback to athletes. However, practitioners should be cautious when interpreting peak velocity data, particularly in high-velocity Olympic weightlifting derivatives, and consider alternative methods for precise assessment.

Introduction
Resistance training is a well-documented modality for improving force production, power, lean body mass, and overall athletic performance (10-11,13,20,27). For these reasons resistance training has become synonymous with athlete preparation. Before the technological renaissance, tracking athletes’ progress and assessing program effectiveness was almost entirely comprised of assessing progressive overload via number of repetitions completed or through the manipulation of external load lifted (15,19,22). However, these more traditional methods come with several challenges, making it difficult to assess program effectiveness. Specifically, athlete’s perceived exertion, range of motion, and different pacing strategies can confound practitioners’ ability to assess meaningful changes as it relates to physiological adaptations resultant resulting from training (12,18,19,22). Because of this, numerous efforts have been made to leverage technological tools to enhance the assessment of training efficacy.

Recent technological advancements have popularized the tracking of barbell velocity, termed velocity-based training (VBT), and highlighted its usefulness in gauging training efficacy. VBT is utilized for a multitude of reasons, including but not limited to predicting 1 repetition maximum (1RM) without the accumulation of excessive fatigue and increased risk of injury, monitoring training performance and neuromuscular fatigue, and providing immediate kinematic feedback potentially leading to enhanced training outcomes (1,3,-4,7,-8,10-11,18,23,24,26,28). As with any technological tool, measures of validity and reliability are paramount to assess the meaningfulness of the data provided. Providing reliable data is important for coaches and athletes alike, to accurately assess the physiological changes associated with training programs, as well as make appropriate alterations when needed.

For over 20 years, GymAware (GYM) has been considered the gold standard of linear positional transducers (LPT). LPT’s function by measuring displacement of a barbell as well as the time taken to complete said displacement. By using this data, the LPT computes several variations of barbell velocity and power (average, peak, etc.) (17). Previous research suggests that the GYM is both highly valid and reliable at slow velocities (0.3-0.7 m/s) . (3-5,7-9,14,15,21). However, few studies have examined the reliability and validity of the GYM during low load, high velocity weightlifting or plyometric movements (0.7+ m/s). Studies that have investigated GYM at these velocities report that the GYM system typically underreports peak velocity and power outputs at lower loads and higher velocity (2,6,14).

Askow et al. (2) examined the reliability and validity of GYM software at both 60 and 80% of 1RM back squats. They found that GYM tends to underestimate peak velocity by 11.6% and software is not the most accurate measure of barbell velocity during high velocity movements. Despite this, Askow and his team of researchers still reported high levels of reliability at high velocities (2). Orange et al. (17) reported excellent reliability for both peak and mean velocity measurements at a range of different percentages of 1RM in the back squat and bench press with interclass correlations (ICCs) ranging from 0.96 to 0.99. Lorenzetti et al. (14) found that GYM was both reliable and valid at tracking bar velocity at 70% of 1RM and during a ballistic jump squats; however, they found much higher reliability and validity at lower velocities when compared to the high velocity jump squat plyometrics. A systematic review of LPTs and linear velocity transducers (LVT) corroborated these findings and reported that LPTs, including the GYM, were valid and reliable in measuring velocity during powerlifting and weightlifting movements . (25).
Another review on the subject highlights the need for independent investigations of velocity-based sensors to examine higher velocity lifts such as Olympic weightlifting derivatives (1.2-1.6 m/s) (16). Due to their unique utility and force-velocity characteristics, weightlifting movements , such as the snatch, clean and jerk, are routinely utilized in sport performance settings around the globe. An essential element of these lifts is how fast the weight moves. Few studies have compared such devices to a criterion measure, namely motion capture (25). However, existing research on devices like the GYM Power Tool suggests high validity and reliability when measuring velocity during high-velocity barbell movements. Orange et al. (17) reported excellent reliability of GYM for back squats and bench presses, with ICCs ranging from 0.96 to 0.99 for velocity, suggesting that it could similarly perform well in more dynamic lifts. There is limited research on the reliability and validity of LPDT when measuring velocity during Olympic lift derivatives. Thus, the current study will address the gap in the literature and extend our understanding of the validity and reliability of VBT devices at higher velocities. Specifically, the purpose of this study is to examine the reliability and validity of GYM compared to Qualisys Motion Capture during the power clean.

Methods
The study was carried out with 10 participants (Table 1). Participants had at least one year of prior experience strength training, defined as an average of two training sessions per week. Subjects were between the ages of 18-40, technically proficient in the clean, not pregnant, free of known cardiovascular, metabolic, or renal disease, and free of injuries. After giving written consent, technical proficiency in the clean was determined during a familiarization session prior to data collection.

Table 1. Participant Characteristics 

Sex	Age (years) (mean ± SD)	Height (m) (mean ± SD)	Weight (kg) (mean ± SD)	Predicted 1RM (kg) (mean ± SD)
Male (n=5)	23.4 ± 4.4	1.74 ± 0.06	83.3 ± 9.8	106.6 ± 24.5
Female (n=5)	22.0 ± 0.7	1.62 ± 0.06	72.6 ± 22.6	61.2 ± 17.0
Total (n=10)	22.7 ± 3.1	1.68 ± 0.09	78.0 ± 17.4	83.9 ± 31.1

For a clean, participants had to lift the barbell in one smooth move from the floor, catching the barbell in a front rack position. Feet were to be shoulder width apart or just outside shoulder width at the catch. The participants were cued to move the weight as quickly as possible while staying under control. Participants with working weights lighter than what could be provided with bumper plates, the lift began from a hang at mid-shin height.

During the familiarization session participants were asked to complete a health history questionnaire before height and weight were taken. After a general warm up that consisted of 50 jumping jacks, 10 bodyweight squats, 5 jump squats and 5 cleans with the empty barbell, the participants provided a perceived 1RM (ex. 200 lbs.). 50% of the participants’ perceived 1RM was loaded onto the barbell (ex. 50% of 200 lbs. = 100 lbs.). The participant was then asked to perform 1 set of 5 repetitions, at which point the research team determined if technical proficiency was sufficient (binary yes or no).

Participants who met the inclusion criteria and demonstrated proficiency in the clean were invited back for a lifting session. The session began with the same general warm-up detailed above. Participants whose schedules permitted both sessions to be completed consecutively (familiarization + lifting) were not asked to perform the warmup prior to the lifting session. In total, participants completed six sets: two sets of five repetitions at 40%, 50%, and 60% of perceived 1RM (ex. 200lbs 1RM: 40% = 80lbs, 50% = 100 lbs., and 60% = 120lbs). Each set began with the signal “You may begin your lift.” Participants were instructed to fully stop and/or set down the bar at the end of each repetition for at least a one count to prevent the use of momentum and allow for a distinct ending to each repetition. This was reinforced with a count of “one” between each repetition. Participants were given three minutes to rest between each set.
Qualisys motion capture system was used as a gold standard/criterion reference. The motion capture set-up consisted of six cameras: three from the Miqus M3 series and three from the Oqus series. Six reflective markers were attached to the barbell. Two markers were attached to either end of the bar, while four markers were attached in square configuration on the collar of the barbell (Figures 1 and 2). The data were recorded with the software QTM 2020-2 Build 5710, with a frequency of 100 Hz. The limits for standard deviation for wand length calibration were 0.3 and 0.5 mm.

The GYM RS, placed on the ground between the pad and platform, was tethered to the shaft of the barbell close to the four reflective markers (see Figures 1 and 3). The GYM RS device was connected via Bluetooth to the free version of the GYM iOS application (Version 4.0.1). GYM RS records at 50 Hz. Peak and mean velocity (m/s) for each repetition were hand recorded from the application into a Microsoft Excel spreadsheet.

Velocity data were exported from the Qualisys Track Manager (QTM) software to Microsoft Excel. The beginning of the lift was determined by the inflection of barbell velocity denoted by an increase of 0.01 m/s for three consecutive frames. The end of the concentric portion of the lift was determined by the first maximum velocity value or crest of velocity curve. Corresponding with GYM, mean concentric velocity (m/s) was determined by averaging marker velocities over the entire concentric portion of the lift. Peak concentric velocity (m/s) was calculated by averaging the individual velocities of each marker over a sample period of 20 milliseconds immediately preceding peak velocity.

Participants stood on a wooden platform with the barbell resting on black foam pads on either side of the platform. Unless the participant’s working weight utilized change plates or the empty bar, the clean started from the black foam pads. If not, the clean started from a hang at mid-shin height. The materials were a 20 kg bar, Rouge change plates between 0.5 and 5 kg, 2.5 and 5 lb. plates, as well as 25 and 45 lb. bumper plates. Working weights for each participant were calculated to get as close to 40%, 50%, and 60% of perceived 1RM.

Results
Data was collected for 10 participants during a single data collection session. Subjects completed six sets: two sets of five repetitions at 40%, 50%, and 60% of perceived 1RM. Mean and peak velocity was recorded using GYM and Qualisys motion capture software for each repetition. There was a total of 60 data points per participant, resulting in 600 total data points.
3.1 Validity

Figure 4. Scatter plots expressing the peak and mean bar velocities at 40, 50, and 60% of one repetition maximum as measured by GYM and Qualisys motion capture systems. Error is defined as the difference between the GYM measurements and Qualisys measurements, with cooler colors representing less error and hotter colors representing more error. Dashed line represents a perfect linear fit that assumes no variance between the two devices. All correlations were statistically significant with a p<0.05

Scatter plots for peak velocity at each percentage of 1RM showed varied levels of correlation between GYM and Qualisys. At 40% of 1RM r=0.706, at 50% r=0.512, and at 60% r=0.703. Each of the aforementioned correlations reached statistical significance at the 0.05 level and indicate a moderate correlation between the GYM and Qualisys measurements of bar velocity. 50% of 1RM demonstrated the highest variability (Figure 4).

The mean velocity measurements between the two systems demonstrated stronger correlations across all load percentages. At 40% r=0.958, at 50% r=0.938, and at 60% r=0.871. All correlations were statistically significant (p<0.05) and indicate a consistent, strong relationship between GYM and Qualisys when assessing mean bar velocity (Figure 4).
GYM software tended to overpredict peak barbell velocities at all intensities by 0.37 m/s on average, while only over predicting mean barbell velocity by 0.09 m/s (Figure 5).

Table 2. Comparison of Linear Regression Model Results for GYM and Qualisys Motion Capture System at Different Percentages of Perceived One Repetition Max

Load (%1RM)	R2		F-statistic
	Mean Velocity (MV)	Peak Velocity (PV)	Mean Velocity (MV)	Peak Velocity (PV)
40%	0.92	0.50	1073.66	97.15
50%	0.88	0.26	723.49	34.83
60%	0.76	0.51	301.48	101.32
All data	0.88	0.44	2086.1	234.72

*All data was significant with a p-value<0.001.

A linear regression model indicated a significant relationship between mean and peak bar velocity as reported by the GYM when compared to Qualisys tracking software. Mean velocity linear regression: F (1,293) = 2086.61, p<0.001, R2 = 0.88. Peak velocity linear regression: F (1,293) = 97.15, p < 0.001, R2 = 0.44. This model indicates that across all percentages of 1RM tested, GYM software was able to account for 88% of the variance in mean bar velocity and only 44% of peak bar velocity.
When parsed out and compared by loads, the data highlights a closer relationship between mean velocity measures as compared to peak velocity measures (Table 2.) At 40% 1RM: Mean velocity: F (1,293) = 1073.66, p < 0.001, R² = 0.92; Peak velocity: F (1,293) = 97.15, p < 0.001, R² = 0.50. At 50% 1RM: Mean velocity: F (1,293) = 723.49, p < 0.001, R² = 0.88; Peak velocity: F (1,293) = 34.83, p < 0.001, R² = 0.26. At 60% 1RM: Mean velocity: F (1,293) = 301.48, p < 0.001, R² = 0.76; Peak velocity: F (1,293) = 101.32, p < 0.001, R² = 0.51.
3.2 Reliability

Table 3. Intraclass Correlation Coefficients for mean and peak barbell velocity measurements.

	Mean Barbell Velocity	Peak Barbell Velocity
ICC (95% CI)	0.848 (0.341-0.941)	0.306 (-0.092-0.632)
F-statistic	23.6	4.8
p-value	0.00261	0.128

The ICCs were calculated to assess the reliability of mean and peak barbell velocity measurements. A two-way random-effects model with absolute agreement (ICC (A,1)) was used for both metrics. Mean barbell velocity had an ICC of 0.848 (0.341–0.941), with an associated F-test indicating statistical significance (F (296, 4.22) = 23.6, p = 0.00261). These calculations indicate good reliability. Peak barbell velocity had an ICC of 0.306 (-0.092–0.632), with a non-significant F-test (F (299, 2.69) = 4.8, p = 0.128). This ICC value indicates poor reliability.
The coefficients of variation (CV) were calculated to assess the relative variability in mean and peak values for both GYM and Qualisys datasets. For the mean values, the CV was 17.06% for GYM and 20.46% for Qualisys. For the peak values, the CV was 10.75% for GYM and 15.37% for Qualisys, with GYM showing the lowest relative variability among all measures.

Discussion
The findings of this study offer valuable insight into the reliability and validity of GYM as a VBT tool. While GYM demonstrated strong validity in tracking mean barbell velocity across all intensities, it was substantially less accurate when assessing peak barbell velocity. These results highlight important considerations for practitioners when using GYM as a training tool.
There was a strong correlation observed between GYM and Qualisys for mean velocity measurements, highlighting the reliability of GYM. The ICC for mean velocity (0.848) reflects good reliability, supporting its use by coaches and athletes where consistent data is essential for assessing training adaptations and adjusting programs accordingly. This finding demonstrates that GYM’s mean velocity measure is capable of providing practitioners with insightful data that can reliably indicate changes in athletes’ performance capabilities. For example, this means that a positive change of 0.15 m/s in an athletes mean clean velocity at a given load is likely due to changes in the athletes’ performance capabilities, as opposed to the measurement error associated with the VBT tool. This is rather important when competitive success has such slim margins and even more important when resistance training programs are dictated by real time data collected by VBT tools. These findings are consistent with prior research that has identified GYM as a reliable tool for monitoring barbell velocity during traditional resistance training exercises (17). Importantly, this examination focused on high velocity movements, hence the loads of 40-60%, and extended the range of velocities studied within the literature.
Despite this, GYM had a moderate correlation and systematically overestimated barbell velocity limiting its application. GYM had a mean bias of +0.37 m/s when assessing peak velocity suggesting that GYM may not offer the precision required for accurately evaluating peak velocity during rapid, explosive movements. What is perhaps more concerning is the poor ICC for peak velocity (0.306), indicating low reliability for this metric.. For example, if an athlete were to improve peak barbell velocity by 0.15 m/s, the same amount as with their mean velocity, we wouldn’t be able to confidently attribute this change to a performance improvement due to the low reliability.

These findings agree with previous research that has identified similar discrepancies in GYM’s accuracy. In Lorenzetti et al. (14), the GYM device showed a higher root mean square error (RMSE) of 0.06 m/s when assessing peak barbell velocity during ballistic jump squats compared to slower squat movements. This higher RMSE suggests that the device was less accurate in measuring peak velocity during higher velocity, explosive jumps. The study found the mean difference between GYM and the reference method (motion capture) to be -0.05 m/s, further indicating potential measurement errors in high-velocity movements. These results highlight that peak velocity measurements may be prone to greater variability in ballistic exercises. Additionally in Askow et al. (2), the GYM device consistently underestimated peak barbell velocities by 11.6% (or -0.13 m/s) when compared to a more accurate criterion measure. This bias was particularly evident during high-velocity movements, indicating that the device may not be as precise for measuring peak velocity in such contexts. The underestimation suggests a systematic error that could limit the utility of GYM for tracking performance improvements in peak velocity during explosive lifts. These values along with our data showcase that GYM may not be an effective tool at assessing peak barbell velocity at lower loads/higher barbell velocities.

This study also reinforces the importance of context when interpreting data from VBT devices. Contrary to our ICC data, the coefficients of variation (CV) highlight the consistency of GYM for both mean velocity (17.06%) and peak velocity (10.75%). Interestingly, this statistic suggests that peak velocity is more reliable when compared to mean velocity; however, this is likely due to the systematic overestimation of both peak and mean barbell velocity by GYM. Utilizing both ICC and CV’s the data supports the notion that GYM has strong reliability for mean velocity, however peak velocity measures capture by GYM leave something to be desired. These data suggest that practitioners should use mean barbell velocity measurements to achieve the best results, especially when utilizing VBT to monitor fatigue, track progress, and adjust training intensity in real time. Should practitioners have a penchant for peak velocity measures, the authors strongly encourage practitioners to run in-house statistics to understand what constitutes a meaningful change as compared to a change within the VBT’s measurement error.
Findings align with the broader literature discussing VBT devices and explore a gap in the literature by examining high-velocity movements while highlighting aspects that have practical significance. Future investigations should explore GYM’s performance with other high velocity movements such as the snatch or jerk, to better understand its broader applications. Importantly, while these results contribute to the growing body of evidence, it is important to situate the use of VBT within the broader training context and provide guidance to practitioners.

Application in Sport
The authors contend that reliable VBT tools can be leveraged by practitioners. First, VBT tools provide a cost-effective and time efficient avenue to collect data and highlight changes as a result of the training prescription. VBT data may be leveraged as biofeedback and a load modulation technique but only in synchrony with more traditional loading prescription (% of 1RM/% of set/rep best). Important to note, these strategies utilize VBT tools as a secondary data stream to inform when load changes may be needed and not as a primary load prescriber. Coaches must retain load prescription responsibilities, while utilizing their eyes and ears (in addition to VBT tools) to skillfully make load adjustments when needed. Practitioners must also bear in mind that VBT tools are inaccurate when estimating 1RM, therefore other methods for estimating are necessary. Perhaps the most compelling reason for utilizing VBT tools resides in their ability to potentiate participant performance. The presence of VBT devices may improve athlete motivation and training intent, which is paramount for optimal training. While VBT tools generally provide a positive return on investment, the practitioners’ eyes and ears should remain the primary data source which guide training decisions while VBT tools serve a supportive role. Based on available data, it would be shortsighted to rely solely on VBT tools to make real-time training decisions.

In conclusion, this study demonstrates that GYM provides reliable and valid measurements for mean barbell velocity during submaximal power cleans. As a result, practitioners may leverage GYM’s strengths, particularly its ability to provide immediate feedback and monitor mean velocity, while remaining cognizant of its limitations for high-velocity movements. This approach may allow for the effective integration of VBT tools to enhance training decisions, outcomes and athletic performance.

References:

Weakley JJS, Till K, Read DB, et al. The Effects of traditional, superset, and tri-set Resistance Training Structures on Perceived Intensity and Physiological Responses. European Journal of Applied Physiology. 2017;117(9):1877-1889. doi:https://doi.org/10.1007/s00421-017-3680-3

Weakley JJS, Wilson KM, Till K, et al. Visual Feedback Attenuates Mean Concentric Barbell Velocity Loss and Improves Motivation, Competitiveness, and Perceived Workload in Male Adolescent Athletes. Journal of Strength and Conditioning Research. 2019;33(9):2420-2425. doi:https://doi.org/10.1519/jsc.0000000000002133

Weakley J, McLaren S, Ramirez-Lopez C, et al. Application of velocity loss thresholds during free-weight resistance training: Responses and reproducibility of perceptual, metabolic, and neuromuscular outcomes. Journal of Sports Sciences. 2019;38(5):477-485. doi:https://doi.org/10.1080/02640414.2019.1706831

Weakley, J., Morrison, M., Garcia-Ramos, A., Johnston, R., James, L., and Cole, M. H. (2021). The validity and reliability of commercially available resistance training monitoring devices: A systematic review. Sports Medicine 51, 443-502.

Weakley J, Till K, Sampson J, et al. The Effects of Augmented Feedback on Sprint, Jump, and Strength Adaptations in Rugby Union Players Following a Four Week Training Programme. International Journal of Sports Physiology and Performance. 2019;14(9):1-21. doi:https://doi.org/10.1123/ijspp.2018-0523

Westcott WL. Resistance training is medicine: Effects of strength training on health. Current Sports Medicine Reports. 2012;11(4):209-216. doi:https://doi.org/10.1249/JSR.0b013e31825dabb8

Wilson KM, Helton WS, de Joux NR, Head JR, Weakley JJS. Real-time quantitative performance feedback during strength exercise improves motivation, competitiveness, mood, and performance. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 2017;61(1):1546-1550. doi:https://doi.org/10.1177/1541931213601750

George Minoso2025-05-22T15:02:58-05:00

What drives volunteer retention in a mega sporting event? An analysis of behavioral influences.

George Minoso2025-05-22T15:02:58-05:00October 3rd, 2025|General, Research, Sports Studies|

ABSTRACT

The purpose of this study is to investigate the effects of role satisfaction, personal achievement, and extrinsic rewards on volunteer satisfaction and subsequent retention in a mega sporting event. An online survey of 2,127 volunteers from the 2018 PyeongChang Winter Olympics was conducted, and structural equation modeling was used to examine direct and indirect effects among the latent variables. Results revealed that role satisfaction, personal achievement, and extrinsic rewards significantly predicted overall satisfaction. Furthermore, overall satisfaction positively influences volunteer retention. Mediation analysis confirmed that overall satisfaction mediated the effect of extrinsic rewards on retention, but not for role satisfaction or personal achievement. These findings underscore the importance of satisfying extrinsic rewards (e.g., material incentives, logistical support) in cultivating volunteer retention. While this study was situated within a mega-event, implications extend to volunteer coordination across various sporting environments that rely on unpaid contributors.

Key Words: Mega sporting event, Volunteer retention, Volunteer satisfaction, Logistic regression, Structural equation modeling

INTRODUCTION

Volunteerism plays a vital role in the successful execution of large-scale events and in reducing operational costs (Pestereva, 2015), making volunteer retention a key concern for both organizers and researchers (Ahn, 2018). This involves an organization’s ability to maintain the involvement of individuals who contribute their time, skills, and effort without financial compensation (Merrilees et al., 2020), using strategies that promote positive experiences, reduce turnover, and build a loyal volunteer base to ensure event success, operational efficiency, cost savings, and community engagement (Gaber et al., 2022; Ahn, 2018). Importantly, volunteer retention emerges as a cost-effective and essential strategy for non-profit and private organizations engaged in hosting mega sports (Kim et al., 2007). Despite volunteers’ significant contributions (e.g., saving costs and providing quality service), there has been a decline in volunteerism attributed to poor retention rates (Do Good Institute, 2018). Given the infrequent occurrence of mega sports events, host countries are presented with challenges in retaining volunteers due to the limitations associated with low event frequency and the rotational selection of host cities (Fourie & Santana-Gallego, 2011). Compared to professional sports operating matches in the same venues, mega sporting events tend to have difficulty retaining volunteers due to restrictions such as low frequency and rotation of host cities. In the detailed examination of volunteer retention within mega sporting events, the integration of Self-Determination Theory (SDT) plays a crucial role, providing valuable insight into the complex dynamics that shape retention, influenced by factors like volunteer role satisfaction, personal achievement, and extrinsic rewards. Thus, this empirical study had two primary objectives: 1) to explore how these three factors significantly impact volunteers’ overall satisfaction and volunteer retention, and 2) to identify the factors that drive volunteer retention when overall satisfaction mediates their retention in a mega sports event. This paper begins by reviewing relevant literature on role satisfaction, personal achievement, and extrinsic rewards. It then outlines the research method, followed by a presentation and discussion of the results. The paper concludes with applications for volunteer management in the sport context.

LITERATURE REVIEW

Self-determination Theory

Self-determination theory (SDT), crafted by Deci and Ryan (1985), stands as a foundational psychological framework delving into the intricate motivations steering human behavior. SDT posits that individuals have three innate psychological needs that, when satisfied, contribute to a sense of well-being and sustained motivation: i) Autonomy which refers to the desire for volition and self-endorsement in one’s actions, ii) Competence which involves the need to feel effective in one’s interactions with the environment, iii) Relatedness pertains to the need to connect with others and experience a sense of belonging (Deci & Ryan, 1985). Furthermore, SDT proposes the importance of the harmonious use of intrinsic (which involves engaging in activities for inherent satisfaction) and extrinsic (which involves engaging in activities for external rewards) motivations in role satisfaction (Ryan & Deci, 2000). In the nuanced exploration of volunteer retention within mega sporting events, the incorporation of SDT emerges as a pivotal factor, offering a profound insight into the intricate dynamics influencing how retention is shaped by factors such as volunteer role satisfaction, personal achievement, and extrinsic rewards. Thus, this study proposes extrinsic motivation (i.e., role satisfaction and extrinsic rewards) and intrinsic motivation (i.e., personal achievement) to explore volunteer retention in a mega sporting event.

Role Satisfaction

Role satisfaction is the extent to which one’s psychological needs are met in an intrinsically valuable role (Malhotra et al., 2014). In volunteerism, role satisfaction is crucial in overall volunteer satisfaction, bolstering volunteer retention. SDT posits that role satisfaction can be influenced by intrinsic and extrinsic factors (Ryan & Deci, 2000), meaning that individuals may find satisfaction in their roles through fulfillment or external rewards. SDT further suggests that when an individual’s psychological and physical needs are met in a role, satisfaction occurs, thereby contributing to retention (Ryan & Deci, 2000). Role satisfaction, therefore, serves as a significant component of overall volunteer satisfaction and a predictor of volunteer retention. Consequently, this study postulated that role satisfaction can occur when individuals are motivated intrinsically or extrinsically, leading to enhanced overall volunteer satisfaction.

Personal Achievement

In volunteering, the achievement motive serves as a determinant of intrinsic motivation, and it involves striving for excellence and competing with one’s or others’ standards (Malhotra et al., 2014). It implies that personal achievement in a volunteer role enhances intrinsic motivation, aligning with SDT to reinforce role satisfaction and overall volunteer satisfaction. Ahn (2018) also highlighted that involvement in volunteerism provides individuals with opportunities for self-achievement. This was further expounded on by Guerrero and Seguin (2012), who illustrated that high achievement motives increase motivation as personal tasks and organizational goals are met, which leads to increased satisfaction.

Extrinsic Rewards

Rewards refer to tangible or intangible benefits for recognized activities (Jung, 2011). Rewards play a critical role in volunteering, as recruiting and retaining qualified volunteers without incentives can be challenging (Ahn, 2018). As such, rewards can become one’s motivation to either participate or continue to engage in volunteering activities. Rewards can be categorized into two types: intrinsic and extrinsic rewards. Intrinsic rewards are psychologically driven and encompass positive feelings derived from performing a meaningful job and a sense of contributing to a worthy cause (Wymer & Starnes, 2001). More importantly in this study, extrinsic rewards refer to economic recognition and tangible items such as discount coupons, accommodations, uniforms, cash, and gifts (Jung, 2011). Prior studies have proposed that extrinsic rewards are driving factors that allow for competence needs, which are essential determinants of volunteer satisfaction (Baard et al., 2004), such as recognition of efforts, tangible rewards, and incentives (Ahn, 2018).

Volunteer Retention

The concept of intention to volunteer has been a central focus in volunteer research, emerging as a pivotal predictor for the prospective retention of volunteers. This prominence is exemplified by the findings of Clary et al. (1998), who underscored the significance of the intention to volunteer as a crucial factor influencing both the recruitment and subsequent retention of volunteers. Volunteer retention refers to the actions, decisions, and patterns of engagement exhibited by individuals who choose to sustain their involvement in volunteer activities (Clary et al., 1998). It encompasses the dynamics that contribute to volunteers choosing to stay committed and engaged in their roles (Hustinx & Lammertyn, 2003). For instance, individuals who consistently participate in volunteer activities over time, take on additional responsibilities, attend scheduled training events, speak positively about their experiences, and invest their resources serve as a few examples of characteristics of volunteer retention (Hustinx & Lammertyn, 2003).

The Mediating Role of Overall Volunteer Satisfaction

Overall volunteer satisfaction refers to the comprehensive evaluation of volunteers’ contentment, fulfillment, and positive experiences across various aspects of their engagement with a volunteer program or organization (Clary et al., 1998). As volunteers are more likely to continue their engagement if they derive overall satisfaction from their work (Warner et al., 2011), overall satisfaction is immensely important as it predicts retention and decreased turnover rates (Galindo-Kuhn & Guzley, 2001). Satisfied volunteers are more likely to continue their service and even inspire and recruit others to volunteer (Coyne & Coyne, 2001). Moreover, overall satisfaction with a specific volunteer episode fosters positive perceptions of volunteering, highlighting its significance in driving retention (Coyne & Coyne, 2001). The concept of volunteer overall satisfaction has been extensively studied, and existing literature has consistently suggested that it is a predictor of the time spent volunteering, the longevity of volunteer service, and the intention to continue volunteering (Costa et al., 2006). Thus, it is theoretically assumed that volunteers’ perceptions of role satisfaction, personal achievement, and extrinsic rewards collectively influence their overall satisfaction, subsequently impacting volunteer retention. Therefore, the following hypotheses were proposed: 

H1. Role satisfaction has a positive effect on overall volunteer satisfaction. 

H2. Personal achievement has a positive effect on overall volunteer satisfaction. 

H3. Extrinsic rewards have a positive effect on overall volunteer satisfaction. 

H4. Overall volunteer satisfaction will positively impact volunteer retention.  

H5a. Overall volunteer satisfaction mediates the positive relationship between role satisfaction and actual retention.

H5b. Overall volunteer satisfaction mediates the positive relationship between personal achievement and actual retention.

H5c. Overall volunteer satisfaction mediates the positive relationship between extrinsic rewards and actual retention.

METHOD

Data Collection and Participants

Data were collected from volunteers who participated in the 2018 PyeongChang Winter Olympics, with the valuable contribution of secondary data made available by the PyeongChang Winter Olympics Organizing Committee. An online survey link was sent to actual event volunteers, and the survey link was available during the entire Olympic Games event, from February 7th to 25th in 2018. A total of 2,500 volunteers initially completed the online survey. During the data screening process, 344 incomplete questionnaires were eliminated, resulting in 2,156 usable questionnaires. An additional 29 questionnaires were removed since all items were recorded in the same number. A final sample of 2,127 questionnaires was used for analysis, with 734 males (34.5%) and 1,393 females (65.5%), the majority being single (86.1%) and holding a bachelor’s degree (77.2%), and the largest age group being 20 to 29 years (82.1%).

Instrument and Data Analysis

A total of 20 items were used to measure the four constructs: six items for role satisfaction, eight items for personal achievement, three items for extrinsic rewards, and three items for overall satisfaction. Each measure was found to be internally consistent since composite reliability values ranged from .77 to .85 in this study. All items were anchored on a 5-point Likert scale, ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). To identify the participants who were repeat volunteers to a mega event, the respondents were screened to report whether they had returned to the event and had previous experience volunteering at the mega sporting event. Volunteer retention was used as the binary dependent variable, with the number of volunteer retention variables dichotomized into 0 = non-retention volunteers and 1 = retention volunteers.

Descriptive analysis was calculated, and a confirmatory factor analysis (CFA) was performed using Mplus 8.8 to assess the psychometric properties of the measurement. Furthermore, structural equation modeling (SEM) was conducted to estimate the direct and indirect effects of the measured latent variables on the dichotomous dependent variable, volunteer retention. As this is a logistic regression in SEM, χ2 was unavailable (Arlinghaus et al., 2012). Instead, the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) were used as the only fit indicators to assess model fit for the logistic regression model in SEM, so these two fit indicators were generally utilized in such models (Arlinghaus et al., 2012). This model was designed to predict volunteers’ retention from 557 participants who returned to volunteer at a mega sporting event. However, an estimation of weighted least squares (WSLMV), which was available in Mplus 8.8, allowed researchers to estimate binomial regression models that provide traditional model fit indices, such as the comparative fit index (CFI ≥ 0.90), the root mean square error of approximation (RMSEA ≤ 0.08), the Tucker-Lewis index (TLI ≥ 0.90), and the standardized root mean squared residual (SRMR ≤ 0.08). Thus, the WSLMV estimation method was used for our model. A significant level of 0.05 was used to determine statistical significance.

RESULTS

Descriptive Statistics

In terms of descriptive statistics, the mean scores of all factors related to volunteering, including volunteer role satisfaction, personal achievement, and extrinsic rewards, were above the mid-point. Among the three factors, personal achievement was rated as the highest mean score (M = 3.59, SD = 1.63), followed by volunteer role satisfaction (M = 3.40, SD = 1.87) and extrinsic rewards (M = 3.05, SD = 1.45). In addition, the mean score of overall satisfaction was 3.40 (SD = 1.69). As shown in Table 1, the relationships between variables were all less than .85, thereby demonstrating the absence of multicollinearity (Kline, 2005).

Model Comparison

The original model in this study was partially mediated. Any covariance structural models had alternative models that are identical to the original model regarding goodness of fit to data (MacCallum et al., 1993). To deal with this potential issue, the existence of such equivalent models can be compared with the original model. Besides our original model, we identified a fully mediated model, which omitted paths from volunteers’ personal achievement, role satisfaction, and extrinsic rewards to volunteer retention. The model comparison was performed between the hypothesized structural model and a model using overall model fit (Morgan & Hunt, 1994). SEM was performed for both models (i.e., the partially mediated model vs the fully mediated model). Accordingly, the partially mediated model revealed an acceptable model fit (CFI = .909, RMSEA = .062, TLI = .893, SRMR = .043). Also, all the paths were significant at the level of .05. However, the fully mediated model showed superior model fit compared to the partially mediated model (CFI = .913, RMSEA = .060, TLI = .898, SRMR = .043). Hence, we decided to use the more parsimonious model that excludes the paths from volunteers’ personal achievement, role satisfaction, and extrinsic rewards to volunteer retention.

Measurement Validation

The psychometric properties of the measurement were assessed by performing CFA. The initial process revealed that one item in volunteer role satisfaction and one item in personal achievement were deleted due to low factor loadings (i.e., < .40; Hair et al., 2010). Afterward, the results of CFA demonstrated that the remaining items demonstrated high factor loadings, ranging from .653 to .907. Additionally, composite reliability (C.R.) coefficients ranged from .77 to .88, exceeding the suggested criteria of .70 (Hair et al., 2010). The values of average variance extracted (AVE) were mostly above the cut-off criteria (.50; Bagozzi & Yi, 1988), except for personal achievement (.48) and extrinsic rewards (.47). Fornell and Larcker (1981) mentioned that AVE values of 0.4 can be accepted when its values of C.R. were above the acceptable level of .70. Based on the results of AVE and C.R., convergent validity was established. Discriminant validity was confirmed by comparing the square roots of AVE values with construct correlations (Fornell & Larcker, 1981). All the square roots of AVE values were greater than the values of construct correlations, indicating the presence of discriminant validity. Finally, model fit indices indicated a good fit to the data (CFI = .963, RMSEA = .043, TLI = .953, SRMR = .035).

Logistic Model in SEM

The results of the logistic model in SEM indicated a good fit of the data to the model (CFI = .913, RMSEA = .060, TLI = .898, SRMR = .043). All the path coefficients for the hypotheses were positively significant, supporting H1 to H4 (see Table 3 and Figure 1). H1 was supported since the relationship between volunteer role satisfaction and overall satisfaction was positively significant (𝛽 = .29, p < .001). Also, significant positive relationships were identified between personal achievement and overall satisfaction (𝛽 = .31, p < .001) and extrinsic rewards and overall satisfaction (𝛽 = .52, p < .001), thus supporting H2 and H3. In addition, H4 was supported in that overall satisfaction positively impacted volunteer retention (𝛽 = .05, p < .05). Regarding the latent variable of overall satisfaction, a total of 90.7% of the variance in overall satisfaction was explained by volunteer role satisfaction, personal achievement, and extrinsic rewards.

To test H5, a post-hoc mediation analysis using 5,000 bootstrap samples was conducted to examine if overall satisfaction mediated the relationship between three factors (i.e., role satisfaction, personal achievement, and extrinsic rewards) and volunteer retention. Table 4 shows the results of the indirect effects. The mediation effect of extrinsic rewards on volunteer retention via overall satisfaction was significant at the level of .05, and the confidence interval did not include zero. Besides the mediating effects of extrinsic rewards, no other significant mediators were identified. Thus, H5a and H5b were not supported, but H5c was supported.

DISCUSSION

The current study investigated the impact of three underlying factors of volunteering (i.e., role satisfaction, personal achievement, and extrinsic rewards) and overall satisfaction as the drivers that promote volunteer retention in a mega sporting event. The findings demonstrated that all three factors positively influenced overall satisfaction, with extrinsic rewards playing a significant role in predicting volunteer retention.

Volunteer retention remains a significant challenge for human resource management in sports organizations. This study confirmed a positive relationship between overall satisfaction and volunteer retention (H4). Various factors, including volunteer roles, personal achievement, and extrinsic rewards, were found to influence overall satisfaction. Additionally, satisfaction with the volunteering experience positively affected both retention and recruitment efforts. Enhancing overall satisfaction improves volunteer performance and retention while fostering continued engagement and commitment in future mega sporting events through positive experiences.

The current study predicted a fully mediating effect of extrinsic rewards on volunteers’ future intentions through overall satisfaction (H5c). Previous research demonstrated intrinsic rewards as the primary motivator for volunteers, stemming from positive emotional states developed by satisfactory performance and a sense of worthiness (Wymer & Starnes, 2001). However, this study suggests the significance of extrinsic rewards in securing existing volunteers and maintaining professional relationships with them. Although volunteers provide their services without monetary compensation, the expectation of tangible rewards, complimentary services, or products (e.g., apparel, equipment, and souvenirs) is prevalent.

CONCLUSION AND FUTURE RESEARCH

This study provides compelling evidence on the importance of volunteer satisfaction in driving retention at mega sporting events, particularly highlighting the pivotal role of extrinsic rewards. Among the factors (i.e., role satisfaction, personal achievement, and extrinsic rewards), tangible incentives such as apparel, transportation, and discounts emerged as the most influential in enhancing volunteers’ overall satisfaction and future participation intentions. The findings also confirm that while intrinsic motivations are meaningful, it is the concrete, rewarding experiences that most effectively translate satisfaction into long-term commitment. These insights offer valuable guidance for event organizers and volunteer managers in designing volunteer programs that strategically balance motivational drivers. By prioritizing volunteer needs, recognizing contributions, and offering supportive and rewarding environments, sports organizations can cultivate a reliable and engaged volunteer base. Future research should expand on these findings by exploring variations across event types, cultural contexts, and demographic profiles to refine retention strategies and support the sustainability of volunteer engagement in sport.

APPLICATIONS IN SPORT

The current study suggests a practical insight into volunteering that sports organizations, volunteer managers, and event organizers can develop volunteer programs by incorporating a balanced mixture of intrinsic and extrinsic motivations. Sports organizations could focus on identifying various methods to improve overall satisfaction to ensure the retention of existing volunteers for upcoming events. Volunteer managers can continue offering high-quality onboarding services to improve overall satisfaction before, during, and after sports events. The onboarding process helps volunteers familiarize themselves with the organization’s mission and vision, and volunteers can also be informed about the training, support, and resources to fulfill their role more successfully (Gunn, 2023). For instance, before events, sports organizations could implement well-organized recruitment online systems, training sessions for designated roles, and detailed information about volunteer schedules (Angosto et al., 2021). During events, volunteer managers could actively listen to volunteers’ feedback and address any concerns to provide a better work environment. After events, sports organizations can express gratitude through appreciation emails to all volunteers and conduct satisfaction surveys to further enhance their retention behavior. Volunteer feedback helps figure out how to make the volunteer program better including its improvement, understanding of volunteer experiences, and communication with volunteers (Wang, 2023).

Sports organizations may seek to augment volunteer recruitment and satisfaction by implementing strategies to elevate individual volunteer achievements. In promoting volunteer programs for sports events or organizations, hiring managers can accentuate potential achievements, such as leadership, communication skills, language acquisition, and networking. For example, volunteering can provide opportunities to practice essential skills used in the workplace or community, incorporating teamwork, communication, problem-solving, and task management (Segal & Robinson, 2013). Our findings also imply that sports organizations can provide a better quality of products or services to enhance overall satisfaction for volunteers, such as uniforms, shoes, and equipment. Additionally, sports event organizations can utilize volunteer-specific gear or clothing brands and products as extrinsic rewards to boost engagement and morale among volunteers in general sport settings (Volunteer Hub, n.d.). In essence, leveraging our findings and practical implications holds the potential to significantly enhance volunteer retention at mega sporting events through strategic and targeted interventions.

REFERENCES

George Minoso2025-05-21T12:33:38-05:00

Career Decision-Making Self-Efficacy at Super Bowl LIII 

George Minoso2025-05-21T12:33:38-05:00September 19th, 2025|General, Sports Management|

Career Decision-Making Self-Efficacy at Super Bowl LIII 

Abstract

The present study surveyed sport management students who volunteered at Super Bowl LIII to examine the effects of mega-event volunteering on career decision-making self-efficacy (CDSE). Results suggest that volunteering at mega-events such as the Super Bowl, increased CDSE and that upper-class students and females self-reported greater CDSE than under-class students and males, respectively. Thus, program directors and sport management staff at major sport organizations should consider collaborating to enhance student involvement in order to more effectively prepare the next generation of sport management professionals.

Keywords: mega-event volunteering; career decision-making self-efficacy; professional development; Super Bowl

Introduction

While mega-event volunteers have many different motives, Ledford, Mitchell, and Scheadler (2018) noted that sport management students were mostly motivated to volunteer at Super Bowl LII for professional development (PD). It is important to explore, then, if mega-event volunteering satisfies this motivation. Thus, the purpose of the study was to examine the effects of mega-event volunteering on career decision-making self-efficacy (CDSE) and will likely be useful for sport management internship supervisors and program directors.

Greater CDSE, the belief in one’s capabilities to make career-related decisions (Hackett & Betz, 1981), improves grades, persistence, and perceived career options (Lent, Brown, & Larkin, 1986) and self-esteem, goal-setting, problem-solving, planning, and self-appraisal (Gianakos, 2001). These skills strengthen CDSE and may be fostered by internship and volunteer experiences. Internships/volunteer experiences boost critical thinking skills and commitment to one’s chosen career path (Assante, Huffman, & Harp, 2010), expand social networks (Tse, 2010), improve problem-solving skills (Busby & Gibson, 2010), and enhance autonomy (McManus & Feinstein, 2014). Similarly, Lee and Chao (2013) and Wang, Chiang, and Lee (2014) discovered that internships provide a more thorough understanding of sport management careers, making it easier for them to adjust to related careers post-graduation.

Badura’s Self-Efficacy Theory (1977, 1986, 1997) explained that CDSE can be increased by focusing on performance accomplishments, which are identified via previous successes and then can be generalized to other related current and future scenarios to make one more comfortable with the current task, thus enhancing CDSE.

Due to the popularity and short-lived nature of mega-event volunteering, sport management students may have more positive attitudes and experience more enjoyment when they volunteer at mega-events when compared to their lesser-known internships. Therefore, mega-events may also foster performance accomplishments. Specifically, mega-events have a unique opportunity to provide students with an example of a performance accomplishment, especially since such events are popular in mainstream media. This may satisfy the motivation to use a mega-event for PD. In addition, it is likely that, as one nears graduation, one is more likely to contemplate future careers and become more motivated to seek out PD opportunities. Therefore, the following hypotheses were formulated:

H1: Volunteering at Super Bowl LIII will increase CDSE in sport management students.

H2: Upper-class students (i.e., juniors and seniors) will self-report greater CDSE than under-class students (i.e., freshmen and sophomores).

H3: Students that volunteer more hours will self-report greater CDSE.

Methods

The sample in the current study consisted of 28 student volunteers (M = 21; F = 7) from a small liberal arts college in southwestern Ohio and included freshmen (n = 8), sophomores (n = 9), juniors (n = 4), and seniors (n = 7). However, only 24 students (M = 19; F = 5) completed the post-assessment in addition to the pre-assessment and included freshmen (n = 5), sophomores (n = 8), juniors (n = 4), and seniors (n = 7). The students involved in this study volunteered at the National Football League (NFL) Experience located at the Georgia World Congress Center, which provided patrons NFL-themed games and activities. This is a regular experience for students at this institution and many students choose to participate in multiple experiences during their time as students. For this specific event, students volunteered at interactive games such as youth clinics, a current NFL player or retiree autograph station, punt/pass/kick event, hail-mary event, the 40-year dash, field goal kick event, and Lombardi trophy photograph station. Some students worked as line security, other students worked the interactive games, while other students checked in fans to participate in the interactive games. Moreover, students worked Super Bowl LIII game day as wayfinders by greeting fans at parties and provided information and directions to patrons.

Student volunteers completed a questionnaire prior to reporting to shifts at the NFL Experience. One of the researchers administered and collected questionnaires at the NFL Experience volunteer meeting, minimizing the chance of a low return rate. Participants also completed identical post-event surveys to assess the changes in CDSE.

Participants completed the Career Decision Self-Efficacy Scale-Short Form (CDSES-SF; Buyukgoze-Kavas, 2014). The CDSES-SF consists of 18 items (e.g., “how much confidence do you have that you could determine the steps you need to take to successfully complete your chosen major?”) measured on a 5-point Likert-type scale (1 = No Confidence at All; 5 = Complete Confidence). It is worth noting, though, that the original CDSES-SF consists of 25 items, but was shortened to 18-items due to the irrelevancy of seven items to the present study. For example, the participants were all sport management majors and, thus, did not need to be questioned on the ability to select a major.

In addition to the CDSE, participants also reported how much they have volunteered (in hours) in the last 12 months. Options included 0, 1-10, 11-20, 21-30, 31-40, and 50 or more hours. The question did not however, investigate the types of events at which the volunteer hours were spent.

Results

The internal consistency reliability (Cronbach’s alpha) of the questionnaire was α = 0.907, well above the 0.70 commonly accepted threshold for reliability (Nunnally, 1978). The data were summarized and analyzed using independent sample t-tests. Post-hoc analysis was also used to analyze differences amongst the classes.

H1, which predicted that CDSE would be higher in post-assessments (M = 3.99 SD = 0.68) than in pre-assessments (M = 3.86; SD = 1.06), was supported, t = 2.14, p < 0.05. In other words, CDSE increased after volunteering at Super Bowl LIII.

H2 predicted upper-class students (M = 4.34; SD = 0.47) would have higher CDSE than under-class students (M = 3.75; SD = 1.23). H2 was also supported, t = -7.054, p < 0.001. Post hoc Tukey analysis showed significant variations within each of the classes and not just between upper- and under-class students.

While the mean CDSE for freshman (M = 3.82, SD = 1.14) was not significantly different from sophomores (M = 3.73, SD = 0.28), t = 1.75 p = 0.33, it was significantly lower than the mean CDSE for juniors (M = 4.06, SD = 0.74), t = -3.37, p = 0.01 and for seniors (M = 4.25, SD = 0.78), t = -4.62, p < .001.

In addition, the mean CDSE for sophomores was statistically different from juniors t = -6.91, p < 0.001 and seniors, t = -8.50, p < 0.001. And finally, juniors and seniors had statistically different CDSEs, t = -1.274, p < 0.05. Taken together, these results suggest that class rank impacts CDSE.

The final hypothesis, H3, predicted that the number of hours volunteered would have a positive impact on CDSE. To run a t-test, we compared participants who completed at least 30 volunteer hours in the last 12 months (M = 3.98, SD = 0.09) with participants who completed less than 30 volunteer hours in the last 12 months (M = 3.82, SD = 0.035). Students that had volunteered at least 30 hours reported greater CDSE than those volunteering less than 30 hours, t = -2.38, p < 0.01. Therefore, H3 was supported.

Also, further analysis revealed gender as a significant factor contributing to CDSE. Females (M = 4.20) had greater CDSE when compared to males (M = 3.85), t = 5.51, p < 0.001.

Discussion

The purpose of the present study was to explore how volunteering at Super Bowl LIII affects CDSE. Ledford et al. (2018) found that sport management students were primarily motivated to volunteer at Super Bowl LIII because of the unique opportunity for PD. The present study provides initial evidence that students who volunteer at a mega-event satisfy their motivation to volunteer at the mega-event.

First, the present study revealed that CDSE increased after volunteering at Super Bowl LIII. Perhaps, as could be argued with Self-Efficacy Theory (Bandura, 1986), experience at a mega-event provides students with a perceived performance accomplishment. More specifically, volunteering at a mega-event may inflate one’s beliefs in one’s own skills and knowledge because they have now participated at one of the most elite stages in sport. In other words, students might think that if they have what it takes to participate at a mega-event, then they can be successful in the field of sport management.

Similarly, upper-class students may have more experience in sport management considering they have been in the program longer, and thus, completed more sport management-related coursework and internship hours. Therefore, because upper-class students likely have more sport management experiences, they likely have more successful sport management experiences, providing them with a longer history of performance accomplishments to boost CDSE. For the same reason, those who commit to more hours of volunteering may have greater CDSE because they may have more experiences, which would explain why students with a greater number of hours spent volunteering had higher CDSE than students who volunteered less.

It is also noteworthy to recognize that the present study did find gender differences in CDSE—female volunteers self-reported greater levels of CDSE than their male counterparts. This is really interesting considering the sport industry is dominated by men (e.g., Burton & Leberman, 2017). It may be easy for women to feel undervalued in sport (e.g., Burton, Grappendort, & Henderson, 2011; Kanter, 1977), which would likely decrease one’s CDSE; however, the women in this study experienced greater CDSE. Perhaps, women in this study experienced heightened empowerment because they not only gained a perceived performance accomplishment, but also because they did so when they were a minority. In other words, breaking through more barriers allowed women to experience peak CDSE.

Limitations & Suggestions

Although the present study provides insights into best practices for sport management programs, it does not come without its limitations. First, we must acknowledge the small sample size. Unfortunately, only few students volunteer at mega-events such as Super Bowl LIII, making it difficult to expand this study to more participants. Previous mega-event experience was not factored into the study. Students at this institution have multiple opportunities to volunteer at mega-events and many choose to volunteer at several. The results from this sample could have been impacted if participants had previously volunteered at a mega-event. Moreover, the present study deleted seven items from the CDSE-SF prior to data collection. Although the items may not have been relevant to the current sample, inclusion of these items might have altered results. Nonetheless, the internal consistency reliability of the CDSE-SF was above the common threshold (Nunnally, 1978) and was similar to the internal consistency reliability reported by Buyukgoze-Kavas (2014; α = .92). The present study also did not include a control group. Therefore, the increases in CDSE could have been due to the natural growth and continued education of the participants. Nevertheless, the results provide preliminary evidence towards the effectiveness of volunteering at mega-events. Future studies, therefore, should compare the experimental group with a control group. Finally, more research needs to be conducted to explore and explain the gender differences for CDSE.

Practical Applications

It is important to study CDSE as an outcome of volunteering at a mega-event to analyze the effectiveness of the mega-event at providing a PD opportunity. The present study offers support in favor of promoting student engagement at mega-events by providing prefatory evidence that volunteering at a mega-event boosts CDSE.

In turn, CDSE is important to focus on because, as Gianakos (2001) indicated, it strengthens self-esteem, goal-setting, problem-solving, planning, and self-appraisal, which are all necessary skills that facilitate goal accomplishment. Moreover, internship and volunteer experiences bolster critical thinking skills (Assante et al., 2010), problem-solving skills (Busby & Gibson, 2010), autonomy (McManus & Feinstein, 2014), and knowledge of and preparation for sport management careers (Lee & Chao, 2013; Wang et al., 2014). In addition, according to Koo, Diacin, Khojasteh, and Dixon (2016), since the need for PD is seemingly being met, these participants may be more likely to challenge themselves to achieve greater educational and career goals.

Sport management professionals, therefore, should develop more opportunities for sport management students to gain experience at mega-events. Program directors should facilitate networking between students and professionals who work for major sport organizations. Also, program directors and sport management staff at major sport organizations (e.g., NFL) should develop a greater focus on collaborative projects aimed towards the inclusion of students. Finally, because the present study suggests that mega-event volunteering is especially helpful for women, collaborative efforts should also emphasize the inclusion of women and other minorities.