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The Evolving Role of Technology and Analytics in Coaching: Transforming Practices and Enhancing the Impact on the Profession

Authors: Lawrence W. Judge1, Matt Moore2

1College of Health, Ball State University

2 College of Social Work, University of Kentucky 

 

 

Corresponding Author: 

Dr. Matt Moore

Associate Dean of Academic and Student Affairs

College of Social Work

University of Kentucky

601 Patterson Office Tower

Lexington, KY 40506

[email protected] 

ABSTRACT 

This commentary examines the evolving landscape of coaching, focusing on the transformative integration of artificial intelligence, advanced analytics, and real-time performance tracking. These technologies enhance athlete monitoring, optimize decision-making, and redefine coaching pedagogy. However, the rapid adoption of data-driven methodologies presents challenges, including resistance among experienced coaches and ethical considerations regarding athlete privacy. This commentary explores strategies for effectively integrating coaching tools into coaching while preserving the critical human elements of mentorship and decision-making. As the digital age reshapes sports, embracing innovative technologies is essential for meeting athletes’ complex, evolving needs and achieving performance goals. This integration ensures a balance between innovation and the enduring human elements of coaching, elevating the profession to unprecedented levels of effectiveness and impact.

Keywords: Leadership, Development, Strategy, Mentoring, Performance, Education

Introduction

In the evolution of coaching, technology has transitioned from rudimentary tools to sophisticated systems that have transformed the way athletes are trained and developed (Zhang et al., 2023). Early coaching methodologies heavily relied on basic instruments such as stopwatches, tape measures, and handwritten training logs to assess performance metrics and track progress (Sohail et al., 2022). These tools, while limited, served as the foundation for the integration of technology into coaching practices. Video analysis, introduced in its nascent stages, provided groundbreaking insights into athletes’ movements, enabling coaches to refine techniques with unprecedented precision (Cronin et al., 2019). Similarly, the advent of heart rate monitors and early biomechanical sensors marked the initial shift toward data-driven decision-making in athletic training (Goudsmit et al., 2022).

As technology evolved, so did its application in sports. The introduction of analytics into coaching practices in the 1970s marked a significant turning point (Passmore & Woodward, 2023). One notable example is the Oakland Athletics’ pioneering use of statistical analysis under General Manager Billy Beane, a methodology that revolutionized talent evaluation and team composition in professional baseball (Abisaid & Cassidy, 2017). Popularized as the “Moneyball” approach, this strategy demonstrated the potential of empirical data to transcend traditional methods and optimize performance, sparking a broader analytics revolution across various sports (Gin, 2018). Building on this foundation, modern coaching now incorporates advanced technologies such as wearable devices, artificial intelligence (AI), virtual and augmented reality, and machine learning algorithms to deliver real-time performance analytics, injury prevention insights, and skill acquisition strategies (Catapult, 2023; Müller et al., 2022; Wang et al., 2024).

Despite these advancements, the adoption of technology in coaching presents challenges, particularly among seasoned professionals accustomed to traditional practices (Judge et al., 2024). Resistance to change underscores the importance of balancing innovative tools with the human elements of coaching, including mentorship, trust, and the nuanced understanding of individual athletes’ needs (Passmore & Woodward, 2023). Effective integration of technology requires not only familiarity with innovative tools but also an appreciation of how these tools can complement established coaching principles, rather than supplant them. Additionally, data analytics plays a crucial role in helping athletes evaluate their performance by providing insights into key metrics, enabling personalized training strategies and enhancing decision-making to improve outcomes (Bennett & Szedlak, 2023).

This commentary explores the historical evolution, current applications, and future potential of technology in coaching, offering a comprehensive framework for understanding its transformative role in improving athlete performance and competitive outcomes. By examining how technology integrates with and enhances traditional coaching practices, the work aims to provide actionable insights for leveraging innovation while preserving the foundational principles that define the profession and the commitment to maximizing athlete potential. This dual focus ensures that coaches can navigate the rapidly advancing digital landscape without compromising the interpersonal connections essential to athlete development (Bishop et al., 2023).

Current Roles of Technology in Coaching

The integration of advanced technologies, particularly analytics and AI, has significantly transformed the landscape of sports coaching, enabling precise, evidence-based approaches to athlete development (Catapult, 2023; Zhang et al., 2023). These tools allow coaches to analyze extensive datasets, offering actionable insights for decision-making, personalized training design, and effective athlete monitoring (Baraniuk, 2015; Zhang et al., 2023). Historically, coaching was driven by intuition, anecdotal evidence, and experiential knowledge (Sohail et al., 2022). The advent of AI and advanced analytics has augmented these traditional methods, introducing unparalleled precision and efficiency into coaching practices (Judge et al., 2024). Furthermore, these advances in technology empower athletes to self-reflect on their performance by providing real-time, data-driven insights that foster deeper understanding and targeted improvements (Bennett & Szedlak, 2023).

Modern performance analytics tools provide granular assessments of key metrics, including speed, distance, exertion levels, and tactical patterns (Judge et al., 2021). These insights enable tailored interventions that optimize training regimens and improve competitive tactical strategies that engage coaches and athletes in a collaborative process (Talha & Sohail, 2023). Wearable technologies, such as GPS trackers and heart rate monitors, deliver real-time data on physiological responses and recovery profiles, enhancing injury prevention and facilitating optimal workload management (Catapult, 2023; Müller et al., 2022). Additionally, cloud-based platforms streamline communication between coaching teams and athletes by enabling seamless sharing of playbooks, video analyses, and tactical adjustments (Cronin et al., 2019).

Innovations in skill acquisition and cognitive training have further elevated coaching methodologies. Virtual reality (VR) and augmented reality (AR) create immersive simulations of competitive environments, fostering improved decision-making and technical precision under realistic conditions for both coaches and athletes (Müller et al., 2022). Technologies such as PlaySight© and TrackMan© provide sport-specific feedback on mechanics and strategy, offering coaches and athletes valuable data to refine performance (Bishop et al., 2023; Stanescu, 2018). Emerging innovations, including Catapult’s Vector S7/T7 wearable GPS-tracking systems, deliver detailed insights into athlete movement, speed, and workload, facilitating personalized training and injury prevention strategies (Catapult, 2023). Similarly, Omega’s AI-powered systems analyze historical and real-time performance data, generating comprehensive feedback to enhance race preparation with data related to split times, stride frequency, pacing, and race strategies (Wired, 2023).

These innovative technologies bridge the gap between practice and competition by enabling targeted skill development, data-driven decision-making, and tailored performance optimization (Catapult, 2023; Stanescu, 2018). Data metrics and AI in sport go beyond what a coach can see by providing in-depth, quantifiable insights into an athlete’s biomechanics, performance trends, and recovery patterns, enabling a more comprehensive understanding of strengths and areas for improvement that might otherwise be overlooked (Bishop et al., 2023).

Despite these advancements, it is critical to maintain a balance between technology and traditional coaching practices. Over-reliance on automated systems can undermine essential human elements such as emotional intelligence, trust, and mentorship, which are fundamental to effective coaching (Goudsmit et al., 2022). Coaches must critically assess and integrate tools that align with their methodologies and philosophies while preserving the interpersonal dynamics that underpin athlete development (Judge et al., 2024). By synthesizing advanced technologies with traditional coaching principles, practitioners can create comprehensive training environments that address the physical, cognitive, and emotional dimensions of athletic performance (Passmore & Woodward, 2023).

This section underscores the importance of blending coaching tools with evidence-based practices to maximize their impact while safeguarding the human-centric essence of coaching. Integrating wearable sensors, cognitive training platforms, and collaborative digital tools into coaching workflows ensures an integrated approach that meets the multifaceted demands of modern sports (Catapult, 2023). This integration is essential for meeting modern athletes’ expectations in highly competitive environments. Furthermore, the data-centric revolution is complemented by the potential for greater customization and enhanced feedback mechanisms, which together can pave the way for more effective coaching interventions and superior athletic performance (Zhang et al., 2023) (See Table 1).

Future Roles of Technology in Coaching

Advanced technologies form the backbone of evidence-based coaching strategies, facilitating a personalized approach tailored to each athlete’s physiological and psychological needs (Cronin et al., 2019; Rajasinghe et al., 2022). As such, the integration of experimental technologies not only enhances performance optimization but also reshapes the future role of the coach as a data-driven strategist and mentor. Athletes are also increasingly becoming consumers of data, using detailed performance metrics to engage in self-reflection, identify areas for improvement, and make informed decisions to enhance their training and competitive outcomes (Bishop et al., 2023). Among these innovations, technologies like TrackMan© stand out by offering real-time data on critical metrics, such as release angles, velocity, and distance in track and field events. Such precise measurements empower coaches to refine techniques with unprecedented accuracy (Judge et al., 2021). Similarly, in golf, TrackMan© enhances swing mechanics and ball trajectory analysis, enabling targeted adjustments that optimize performance outcomes (Bishop et al., 2023). Reflexion’s touchscreen lightboards and mixed reality headsets, enhance athletes’ focus, decision-making skills, and mental resilience by strengthening cognitive abilities critical for competitive performance (Reflexion, 2023). PlaySight© empowers tennis players and coaches by providing instant video feedback and detailed data points, such as stroke speed, ball placement, rally length, serve percentages, and location of unforced errors, allowing athletes to analyze their technique, adjust strategies, and track progress with precision (Stanescu, 2018). PlaySight and other advanced software systems save coaches and athletes valuable time by automating video analysis and providing instant feedback, allowing coaches and athletes to focus more on strategy and individualized development rather than manual data collection and review (Judge et al., 2021; Stanescu, 2018).

The National Basketball Association (NBA) initiated the Launchpad program, selecting companies to develop basketball technologies. For instance, SkillCorner utilizes computer vision and machine learning to generate player tracking data from existing video feeds, enabling detailed analysis of player movements and strategies. Similarly, Springbok Analytics employs AI-based technology to transform MRI data into 3D digital twins, quantifying an athlete’s musculature for precision health and performance optimization (NBA, 2023).

Moreover, the NBA has partnered with Sony’s Hawk-Eye Innovations to deploy 3D optical tracking technology, capturing real-time movements of players and the ball in three dimensions with sub-second latency. This system enhances officiating accuracy and provides detailed performance data (Hawk-Eye Innovations, 2023). These technological advancements serve as a bridge to previously elusive performance metrics, enabling granular analysis of biomechanical efficiency, tactical awareness, and psychosocial factors. Such insights not only inform but also revolutionize training regimens, allowing coaches to create hyper-personalized programs tailored to the physiological and psychological profiles of individual athletes (Catapult, 2023).

Beyond sport-specific tools, technology has made significant strides with AI in enhancing athletes’ mental performance. For example, AI-driven applications such asNeuroTrainer andMentalEdge provide personalized cognitive training programs to improve focus, decision-making, and mental resilience, while tracking vital internal metrics such as confidence and concentration (MentalEdge, 2023; NeuroTrainer, 2023). These platforms deliver tailored mental health and performance support, complementing physical preparation with robust psychological strategies (Talha & Sohail, 2023). Monitoring the physical and psychological attributes of athletes provides coaches with a holistic understanding of how best to prepare practice and training opportunities that simulate competitive settings (Passmore & Woodward, 2023).

Similarly, predictive modeling through AI enables coaches to anticipate performance trends and design hyper-personalized training regimens. Tools such as IBM Watson’s Sports Performance Analytics analyze vast datasets to identify patterns, forecast outcomes, and provide initiative-taking adjustments to maximize developmental trajectories (IBM, 2023). Platforms like Megalabs AI further demonstrate the potential of AI in sports training by using advanced algorithms to assess athlete performance and suggest data-driven interventions (Megalabs, 2023). By leveraging historical data and advanced algorithms to forecast future performance trends, injury risks, and game outcomes, coaches and athletes can strategically prepare for competition with greater precision and foresight (Megalabs, 2023).

Balancing Technology with Traditional Coaching Practices

As technology advances, maintaining a balance between its application and the humanistic core of effective coaching is paramount (Judge et al., 2024). While technological tools offer unprecedented data-driven insights into athlete performance, they remain insufficient substitutes for the interpersonal connections, mentorship, and empathy that underpin successful coaching relationships (Carson & Collins, 2016; Driska et al., 2017). These humanistic elements are indispensable in cultivating trust, resilience, and holistic growth in athletes, outcomes that technology alone cannot achieve. The integration of technology must enhance, not replace, the relational dynamics essential to coaching (Rajasinghe et al., 2022). Research underscores that the mentorship and emotional intelligence of coaches are critical in navigating the psychological and emotional challenges faced by athletes, fostering a foundation for long-term development and achievement (Carson & Collins, 2016). Thus, while technology can serve as a powerful adjunct in optimizing training and performance, it must be grounded in and guided by the human-centered principles of the coaching process (Driska et al., 2017). This balance not only ensures effective athlete development but also reinforces the irreplaceable role of coaches as mentors and leaders in the evolving landscape of sports.

Coaches must adopt a strategic approach to technology, utilizing it to complement their expertise rather than overshadowing it. For instance, wearable devices provide critical performance metrics, but their true value lies in a coach’s ability to interpret these data points and translate them into actionable insights (Catapult, 2023; Goudsmit et al., 2022). This equilibrium ensures that the art of coaching, characterized by intuition, adaptability, and emotional intelligence, remains integral to athlete development. Over-reliance on technology risks diluting these people skills, potentially leading to standardized approaches that overlook individual athlete needs (Sperlich et al., 2023). Coaches must critically evaluate the relevance and utility of each technological tool to ensure it aligns with their objectives and enhances the natural flow of training sessions. Coaches must also help athletes make sense of the data in a way that supports their technical, tactical, mental, and physical growth (Judge et al., 2024).

Table 2 illustrates the critical balance between integrating new coaching technologies and preserving traditional practices, emphasizing the importance of maintaining personal connections, leveraging intuitive experience, and fostering holistic athlete development alongside the adoption of innovative tools.

The Role of Relationships in Coaching

At its core, coaching is built on trust, empathy, and mentorship. These human-centric attributes enable coaches to inspire athletes, navigate challenges, and provide a sense of purpose that transcends physical performance (Judge et al., 2024). Unlike technology, which focuses on quantifiable metrics, the human aspects of coaching address intrinsic motivation, emotional intelligence, and adaptive problem-solving (Rajasinghe et al., 2022). Studies have shown that a strong coach-athlete relationship significantly influences athlete satisfaction, engagement, and performance (Passmore & Woodward, 2023). Consequently, even as technology becomes increasingly integrated into coaching, preserving the integrity of these interpersonal dynamics is essential.

Integrating Human-Centered and Data-Driven Approaches

The most effective coaching strategies blend human intuition with technological precision. While data can provide valuable performance insights, its utility is contingent on the coach’s ability to interpret and apply it within the broader context of athlete development. For example, injury prevention algorithms may flag overreaching and or overtraining risks, but the coach’s awareness of an athlete’s mental state and external stressors can provide critical context for tailoring interventions (Goudsmit et al., 2022). By combining the quantitative power of technology with the qualitative insights derived from interpersonal relationships, coaches can address athletes’ holistic needs and support the growth and nurturing of the athlete-coach relationship (Passmore & Woodward, 2023).

Challenges in Balancing Innovation with Tradition and the Road Ahead

Despite its transformative potential, over-reliance on technology can undermine essential coaching principles. Automated systems and analytics platforms, while efficient, risk depersonalizing the coaching experience (Driska et al., 2017). Algorithms often lack the flexibility to accommodate the unique, context-dependent variables that human coaches intuitively recognize (Sperlich et al., 2023). Furthermore, the adoption of technology poses a learning curve for seasoned coaches accustomed to traditional methods, highlighting the need for ongoing education and training in technological applications (Passmore & Woodward, 2023). Addressing these challenges requires fostering a culture of collaboration between coaches, sports scientists, and data analysts, ensuring that technological integration enhances rather than detracts from the human aspects of coaching.

The future of coaching is set to be fundamentally transformed by advancements in technologies such as AI and advanced analytics, which offer unparalleled opportunities to revolutionize strategic planning, optimize athlete performance, and redefine the landscape of sports development. The successful integration of these tools requires maintaining the balance between leveraging technological innovation and preserving the coach’s pivotal role as a mentor, strategist, and leader. Coaches who master the art of blending traditional practices with support from innovative technology will not only thrive but also redefine the coaching profession by offering their athletes a multidimensional support system.

Concurrently, the sports industry is increasingly incorporating technology through the strategic employment of data scientists and analysts within collegiate and professional teams. Roles such as Performance Science Analysts and Data Scientists are becoming essential, as teams leverage these professionals to collect and analyze performance data. This analysis translates complex metrics into actionable insights, informing strategic decisions and personalized training interventions (Indeed, 2023).

The convergence of AI-driven cognitive training tools and the integration of data science technology into coaching methodologies signifies a change in thinking in the sports industry. By leveraging these advancements, coaches can cultivate athletes who are not only physically adept but also possess the cognitive agility required for high-level competition. This integrated approach to athlete development is redefining performance optimization in modern sports.

Applications in Sport

The integration of technology into coaching represents a transformative frontier, providing tools that enhance precision in performance analysis and training methodologies. Yet, the heart of coaching remains deeply rooted in its human elements—empathy, trust, adaptability, and connection. By combining technological advancements with time-honored practices, coaches can create a dynamic, holistic, and sustainable approach to athlete development. This balance not only elevates athletic performance but also ensures that coaching continues to be a profoundly human-centered profession.

The rise of the Sport Scientist as a key position within collegiate and professional teams exemplifies this evolution. Sport Scientists collect and analyze vast amounts of data, ranging from biomechanical efficiency to cognitive performance metrics, translating these insights into actionable strategies for coaches. Their role bridges the gap between data-driven innovation and the human-centric principles of coaching, creating a collaborative environment where technology enhances, rather than replaces, the core values of mentorship and personal connection.While advancements in technology offer unprecedented opportunities to optimize athlete performance, successful coaches understand that these tools are only as effective as the human insight guiding their use. The essence of coaching lies in forming meaningful relationships, delivering individualized motivational strategies, and fostering resilience, qualities that remain inherently human. By integrating traditional coaching expertise with advanced technological tools, coaches can unlock their athletes’ full potential, cultivating a harmonious environment where data and human-centered guidance coalesce to achieve excellence. The future of coaching lies in this symbiotic relationship, ensuring that innovation complements, rather than competes with, the enduring principles of mentorship and connection.

REFERENCES 

Abisaid, J. L. & Cassidy, W. P. (2017). Traditional baseball statistics still dominate news stories. Newspaper Research Journal, 38(2), 158-171.

Baraniuk, C. (2015). Rise of the AI sports coach. New Scientist, 227(3035), 22-23.

Bennett, B., & Szedlak, C. (2023). Aligning online and remote coaching with the digital age: Novel perspectives for an emerging field of research and practice. International Journal of Sports Science and Coaching, 19(2), 882-893.

Bishop, C., Smith, R., & Jones, T. (2023). Integrating emerging technologies in elite sports. International Journal of Sports Performance, 30(2), 345-362.

Bishop, C., Well, J., Ehlert, A., Turner, A., Coughlan, D., Sachs, N., & Murray, A. (2023). Trackman 4: Withing and between-session reliability and inter-relationships of launch monitor metrics during indoor testing in high-level golfers. Journal of Sports Sciences, 41(23), 2138-2143.

Carson, F., & Collins, D. (2016). The future for the science of coaching: Bright, but with a significant glint? Current Opinion in Psychology, 16, 103-108.

Catapult. (2023). Sports technology trends: Performance optimization with wearable systems. https://www.catapult.com/blog/trends-in-sports.

Cronin, C., Whitehead, A. E., Webster, S., & Huntley, T. (2019). Transforming, storing, and consuming athletic experiences: A coach’s narrative of using a video application. Sport, Education, & Society, 24(3), 311-323.

Driska, A. P., Gould, D., & Pierce, S. (2017). Learning to coach through experience: Conditions that influence reflection. Physical Education and Sport Pedagogy, 22(1), 18-34.

Gin, W. (2018). Big data and labor: What baseball can tell us about information and inequality. Journal of Information Technology & Politics, 15(1), 66-79.

Goudsmit, J., Otter, R., Stoter, I., van Holland, B., van der Zwaard, S., de Jong, J., & Vos, S. (2022). Co-operative design of a coach dashboard for training, monitoring, and feedback. Sensors, 22(23), 9073-9092.

Hawk-Eye Innovations. (2023). NBA and Sony’s Hawk-Eye Innovations launch strategic partnership powering next-generation tracking technology. Hawk-Eye Innovations. https://www.hawkeyeinnovations.com/news/4155239/nba-and-sonys-hawkeye-innovations-launch-strategic-partnership-powering-next-generation-tracking-technology.

IBM. (2023). IBM Sports and Entertainment Partnerships. https://www.ibm.com/sports.

Indeed. (2023). Sports data science jobs, employment. https://www.indeed.com/q-Sports-Data-Science-jobs.html.

Judge, L. W., Petersen, J., Huffman, O., & Razon, S. (2024). Addressing the adoption gap: Exploring resistance to evidence-based practices among NCAA coaches. Journal of Applied Sport Management, 16(1), 7-16.

Judge, L. W., Cheetham, P. J., Fox, B., Schoeff, M. A., Wang, H., Momper, M., & Dickin, D. C. (2021). Using sport science to improve coaching: A case study of Felisha Johnson’s Road to Rio. International Journal of Sports Science & Coaching, 16(3), 848-861.

Megalabs. (2023). AI in sports training: A game changer. https://megalabs.ai/ai-in-sports-training/.

MentalEdge. (2023). Elevate your game. https://mentaledgeapp.com/.

Müller, A., Lahkar, B. K., Dumas, R., Reveret, L., & Robert, T. (2022). Accuracy of a markerless motion capture system in estimating upper extremity kinematics during boxing. Frontiers in Sports and Active Living, 4, 939980. https://doi.org/10.3389/fspor.2022.939980

National Basketball Association (NBA). (2023). NBA Launchpad selects seven companies to research and develop basketball and fan-related technology. NBA.com. https://pr.nba.com/nba-launchpad-selects-seven-companies-to-research-and-develop-basketball-and-fan-related-technology/.

NeuroTrainer. (2023). VR brain training for students & athletes. https://neurotrainer.com/.

Passmore, J., & Woodward, W. (2023). Coaching education: Wake up to the new digital and AI coaching revolution! International Coaching Psychology Review, 18(1), 58-72.

Rajasinghe, D., Garvey, B., Smith, W. A., Burt, S., Barosa-Pereira, A., Clutterbuck, D., & Csigas, Z. (2022). On becoming a coach: Narratives of learning and development. Coaching Psychologist, 18(2), 4-19.

Reflexion. (2023). Advanced cognitive training & performance technology. https://reflexion.co/.

Sohail, M., Talha, M., & Ali, M. (2022). Information technology and its’ modernization, the Internet, and sport psychology. Journal of Sport Psychology, 31(2), 83-92.

Sperlich, B., Duking, P., Leppich, R., & Holmberg, H. (2023). Strengths, weaknesses, opportunities, and threats associated with the application of artificial intelligence in connection with sport research, coaching, and optimization of athletic performance: A brief SWOT analysis. Frontiers in Sport and Active Living, 5, 1-6.

Stanescu, R. (2018). The new on-court tennis software: Perspective in training process. Conference Proceedings of eLearning and Software for Education, 3, 341-345.

Talha, M., & Sohail, M. (2023). Digital coaching and mental skills development in sports: Harnessing the power of information technology. Journal of Sport Psychology, 32(3), 90-99.

Wang, T., Zhong, Y., & Wei, X. (2024). Early excellence and future performance advantage. PLoS ONE, 19(6), 1-14.

Wired. (2023). Omega’s AI will map how Olympic athletes win. https://www.wired.com/story/omegas-ai-will-map-how-olympic-athletes-win.

Zhang, Y., Duan, W., Villanueva, L. E., & Chen, S. (2023). Transforming sports training through the integration of internet technology and artificial intelligence. Soft Computing – A Fusion of Foundations, Methodologies, & Applications, 27(20), 15409-15423.

2025-06-09T14:04:33-05:00November 14th, 2025|Commentary, Research, Sport Education, Sport Training, Sports Coaching, Sports Studies|Comments Off on The Evolving Role of Technology and Analytics in Coaching: Transforming Practices and Enhancing the Impact on the Profession

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

Authors: Jason N. Hughes1, Colby B. Jubenville2, Mitchell T. Woltring3, and Helen J. Gray 

1Department of Business, Accounting and Sport Management, Elizabeth City State University, Elizabeth City, NC, USA 

2Department of Health and Human Performance, Middle Tennessee State University, Murfreesboro, TN, USA 

3Department of Health, Kinesiology, and Sport, University of South Alabama, Mobile, AL, USA 

4Associate Dean of Academic Affairs, North Carolina Agricultural and Technical State University, Greensboro, NC, USA 

Corresponding Author: 

Jason Hughes, Ph.D., M.S.,  

1704 Weeksville Rd.  

Elizabeth City, NC 27909 

[email protected] 

252-335-3488 

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. 

REFERENCES 

  1. Baker, J., Côté, J., & Abernethy, B. (2003). Sport-specific practice and the development of expert decision-making in team ball sports. Journal of Applied Sport Psychology, 15(1), 12-25.  
  1. Barynina I., & Vaitsekhovskii, S. (1992). The aftermath of early sports specialization for highly qualified swimmers. Fitness & Sports Review International, 27(4), 132-133. 
  1. Bell, D., Post, E., Trigsted, S., Hetzel, S., McGuine, T., & Brooks, M. (2016). Prevalence of sport specialization in high school athletics: A 1-year observational study. The American Journal of Sports Medicine, 44(6), 1469-1474. 
  1. Bell, D. R., Post, E. G., Trigsted, S. M., Schaefer, D. A., McGuine, T. A., Watson, A. M., & Brooks, M. A. (2018). Sport Specialization Characteristics Between Rural and Suburban High School Athletes. Orthopaedic Jjournal of Sports Medicine, 6(1). 
  1. Buhrow, C., Digman, J., Waldron, J., Gienau, D., Thomas, S., & Sigler, D. (2017) The relationship between sport specialization and mental toughness in college athletes. International Journal of Exercise and Science. 10(1), 44-52.  
  1. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Ed.). Lawrence Earlbaum Associates. 
  1. Côté, J. & Hay, J. (2002), Children’s involvement in sport: A developmental perspective.  In J. In J.M. Côté & D.M. Stevens (Eds.), Psychological Foundations of Sport. (pp. 484-502), Allyn & Bacon. 
  1. Côté, J. (1999). The influence of the family in the development of talent in sport. The Sport Psychologist, 13(4), 395–417. 
  1. Coté, J., & Fraser-Thomas, J. (2007). Youth involvement in sport. In P. R. E. Crocker (Ed.), Introduction to sport psychology: A Canadian Perspective (pp. 270-298). Pearson 
  1. Cox, B., Enns, W., & Clara, I. (2002). The multidimensional structure of perfectionism in clinically distressed and college student samples. Psychological Assessment, 14(3), 365-373.  
  1. Emery, C. (2003). Risk factors for injury in child and adolescent sport. Clinical Journal of Sport Medicine, 13(4), 256-268.  
  1. Fleisig, G., Andrews, J., & Cutter, G. (2011). Risk of serious injury for young baseball pitchers: a 10-year prospective study. American Journal of Sports Medicine, 39(2), 253-257.  
  1. Flett, G., & Hewitt, P. (Eds.). (2002). Perfectionism: Theory, research, and treatment. American Psychological Association (pp. 5-31).  
  1. Ford, P., & Williams, M. (2012). The developmental activities engaged in by elite youth soccer players who progressed to professional status compared to those who did not. Psychology of Sport and Exercise, 13(3), 349-352.  
  1. Frost, R., Marten, P., Lahart, C., & Rosenblate, R. (1990). The dimensions of perfectionism. Cognitive Therapy and Research, 15(5), 449-468.  
  1. Gould, D., Tuffey, S., Udry, E., & Loehr, J. (1996). Burnout in competitive junior tennis players: A quantitative psychological assessment. The Sport Psychologist, 10(4), 322-340.  
  1. Gotwals, J., & Dunn, J. (2009). A multi-method multi-analytic approach to establishing internal construct validity evidence: The Sport Multidimensional Perfectionism Scale 2. Measurement in Physical Education and Exercise Science, 13(2), 71-92.  
  1. Gotwals, J., Stoeber, J., Dunn, J., & Stoll, O. (2012). Are perfectionistic strivings in sport adaptive? A systematic review of confirmatory, contradictory, and mixed evidence. Canadian Psychology/Psychologie Canadienne, 53(4), 263-279.  
  1. Güllich, A., Macnamara, B. N., & Hambrick, D. Z. (2022). What Makes a Champion? Early Multidisciplinary Practice, Not Early Specialization, Predicts World-Class Performance. Perspectives on Psychological Science, 17(1), 6–29.  
  1. Hewitt, P., & Flett, G. (1991). Perfectionism in the self and social contexts: Conceptualization, assessment, and association with psychopathology. Journal of Personality and Social Psychology, 60(3), 456-470.  
  1. Hill, A., & Mallison, S., & Jowett, G. (2018). Multidimensional perfectionism in sport: A meta-analytic review. Sport, Exercise, and Performance Psychology, 7(3), 235-270. 
  1. Jayanthi, N., Pinkham, C., Dugas, L., Patrick, B., & LaBella C. (2013). Sports specialization in young athletes: Evidence-based recommendations. Sports Health, 5(3), 251-257.  
  1. Jayanthi, N., LaBella, C., Fischer, D., Pasulka, J., & Dugas, L. (2015). Sports-specialized intensive training and the risk of injury in young athletes: A clinical case-control study. American Journal of Sports Medicine, 43(4), 794-801.  
  1. Kelto, A. (2015, September 4). How likely is it, really, that your athletic kid will turn pro? http://www.npr.org/sections/health-shots/2015/09/04/432795481/howlikely-is-it-really-that-your-athletic-kid-will-turn-pro 
  1. Lizmore, M., Dunn, Jo, Dunn, Ja., & Hill, A. (2019). Perfectionism and performance following failure in a competitive task. Psychology of Sport & Exercise, 45, 101582.  
  1. Malina, R. M. (2009). Organized youth sports: Background, trends, benefits and risks. Youth Sports: Participation, Trainability and Readiness, 2–27. 
  1. Malina R. (2010). Early sport specialization: Roots, effectiveness, risks. Current Sports Medicine Reports, 9(6), 364-371. 
  1. Malina, R., Bouchard, C., & Bar-Or, O. (2004). Growth, maturation, and physical activity (2nd ed.). Human Kinetics. 
  1. National Collegiate Athletic Association (n.d.). Retrieved February 2, 2025, from https://www.ncaa.org/sports/2015/3/6/estimated-probability-of-competing-in-professional-athletics.aspx  
  1. Post, E. G., Trigsted, S. M., Riekena, J. W., Hetzel, S., McGuine, T. A., Brooks, M. A., & Bell, D. R. (2017). The Association of Sport Specialization and Training Volume With Injury History in Youth Athletes. The American journal of sports medicine, 45(6), 1405–1412.  
  1. Rose S., Emery, C., & Meeuwisse, W. (2009). Sociodemographic predictors of sport injury in adolescents. Medicine and Science in Sports Exercise, 40(3), 444-450.  
  1. Sabato, T., Walch, T., & Caine, D. (2016). The elite young athlete: Strategies to ensure physical and emotional health. Journal of Sports Medicine, 7, 99–113.  
  1. Stoeber, J. (2011). The dual nature of perfectionism in sports: Relationships with emotion, motivation, and performance. International Review of Sport and Exercise Psychology, 4(2), 128-145. 
  1. Stoeber, J. (2014). Perfectionism. In R. C. Eklund & G. Tenenbaum (Eds.), Encyclopedia of sport and exercise psychology, Vol. 2, 527-530. SAGE Publications, Inc. 
  1. Wall, M., & Côté, J. (2007). Developmental activities that lead to dropout and investment in sport. Physical Educational Sport Pedagogy, 12(1), 77-87. 
  1. Weiss, M.R., & Petlichkoff, L.M. (1989). Childrenʼs motivation for participation in and withdrawal from sport: Identifying the missing links. Pediatric Exercise Science, 1, 195-211. 
  1. Wiersma L. (2000). Risks and benefits of youth sport specialization: Perspectives and recommendations. Pediatric Exercise Science, 12(1), 13-22.  

2025-05-22T15:03:47-05:00October 31st, 2025|Research, Sport Education, Sport Training, Sports Coaching, Sports Exercise Science|Comments Off on A Comparison of Perfectionism and Time of Sport Specialization of Division-1 Athletes 

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

Author: Jimmy Smith1

1Department of Kinesiology and Sport Management, Gonzaga University, Spokane, WA, USA

 

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.

Corresponding Author: 

Jimmy Smith, Ph.D.

Gonzaga University

502 E. Boone Ave

Spokane, WA 99258

[email protected]

509-313-3483

Jimmy Smith, Ph. D., is an Associate Professor of Sport Management at Gonzaga University in Spokane, WA. His research interests include organizational behavior.

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.

REFERENCES 

  1. American Camp Association (2011). Camp emerging issues survey. Retrieved from http://www.acacamps.org/sites/defauIt/files/images/research/improve/EI%20all%20results%20(wozip)11.pdf
  2. American Camp Association (2019). Camp participation and enrollment trends. Retrieved from https://www.acacamps.org/pressroom/aca-facts-trends
  3. American Camp Association (2020). Camp industry statistics and trends. Retrieved from https://www.acacamps.org/resource-library/research/aca-camps-business
  4. American Camp Association (2023). Breakthrough study from American Camping Association outlines the benefits of camp experience. Retrieved from https://www.acacamps.org/news/press-release/breakthrough-study-outlines-benefits-camp-experience
  5. American Camp Association (2024a). National economic impact study of the camp industry. Retrieved from https://www.acacamps.org/resources/national-economic-impact-study-camp-industry
  6. American Camp Association (2024b). Find a camp. Retrieved from https://find.acacamps.org/
  7. American Psychological Association. (2017). Ethical principles of psychologists and code of conduct. American Psychological Association. Retrieved from https://www.apa.org/ethics/code/
  8. Amonett, K. (2021). Preventing burnout: Caring for your staff’s mental health while camp is in session. Retrieved from https://www.acacamps.org/article/camping-magazine/preventing-burnout-caring-your-staffs-mental-health-while-camp-session
  9. And, K. A., & Kouthouris, C. (2005). Personal incentives for participation in summer children’s camps: Investigating their relationships with satisfaction and loyalty. Managing Leisure10(1), 39-53.
  10. Arkin, M. (2024). Development and validation of a self-report measurement scale of summer camp counselor burnout. (Doctoral dissertation, University of Massachusetts Boston).
  11. Babbie, E. (2021). The practice of social research (15th ed.). Cengage Learning.
  12. Bailey, A., Kang, H., & Kuiper, K. (2012). Personal, environmental, and social predictors of camp staff burnout. Journal of Outdoor Recreation, Education, and Leadership4(3), 157-171.
  13. Bean, C. N., Kendellen, K., & Forneris, T. (2016). Examining needs support and positive developmental experiences through youth’s leisure participation in a residential summer camp. Leisure/Loisir40(3), 271-295.
  14. Beiner, A. (2024). Counselor retention at Jewish summer camp (Doctoral dissertation, Northeastern University).
  15. Braun, S., Wesche, J. S., Frey, D., Weisweiler, S., & Peus, C. (2012). Effectiveness of mission statements in organizations: A review. Journal of Management & Organization18(4), 430-444.
  16. Brennan, D., & Wendt, L. (2021). Increasing quality and patient outcomes with staff engagement and shared governance. Online Journal of Issues in Nursing26(1), 1-10.
  17. Brymer, E., Crabtree, J., & King, R. (2021). Exploring perceptions of how nature recreation benefits mental well-being: A qualitative inquiry. Annals of Leisure Research24(3), 394–413.
  18. Bultena, G. L., & Klessig, L. L. (1969). Satisfaction in camping: A conceptualization and guide to social research. Journal of Leisure Research1(4), 348–354.
  19. Campbell, D. T., & Stanley, J. C. (2015). Experimental and quasi-experimental designs for research. Ravenio Books.
  20. Carpio de los Pinos, C., Soto, A. G., Martín Conty, J. L., & Serrano, R. C. (2020). Summer camp: Enhancing empathy through positive behavior and social and emotional learning. Journal of Experiential Education43(4), 398-415.
  21. Claman, M. (2021). Evaluating your camp staff orientation during orientation. American Camp Association. Retrieved from https://www.acacamps.org/blog/evaluating-your-camp-staff-orientation-during-orientation.
  22. Corder, G. W., & Foreman, D. I. (2014). Nonparametric statistics: A step-by-step approach. John Wiley & Sons.
  23. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed method approaches (5th ed.). Sage Publications.
  24. Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: The tailored design method (4th ed.). John Wiley & Sons.
  25. Edwards, M. B., Henderson, K. A., & Campbell, K. (2013). Facilitating healthy, well, and wise camp staff. Retrieved from https://www.acacamps.org/article/camping-magazine/facilitating-healthy-well-wise-camp-staff
  26. Garst, B. A., Gagnon, R. J., & Whittington, A. (2016). A closer look at the camp experience: Examining relationships between life skills, elements of positive youth development, and antecedents of change among camp alumni. Journal of Outdoor Recreation, Education, and Leadership8(2), 180–199.
  27. Garst, B. A., Skrocki, A., Owens, M. H., Gaslin, T., Schultz, B. E., Hashikawa, A. N., … & DeHudy, A. A. (2024). Evaluating the mental, emotional, and social health status of youth and staff in a national summer camp cohort. Children’s Health Care, 1-21.
  28. Garst, B. A., & Whittington, A. (2020). Defining moments of summer camp experiences: An exploratory study with youth in early adolescence. Journal of Outdoor Recreation, Education, and Leadership12(3), 306-321.
  29. Garst, B. A., Williams, D. R., & Roggenbuck, J. W. (2009). Exploring early 21st-century developed forest camping experiences and meanings. Leisure Sciences, 32(1), 90-107.
  30. Gaslin, T., Dubin, A., Sorenson, J., Rosen, N., Garst, B., & Schultz, B. (2023). The unexpected positive outcomes for summer camps in the time of COVID-19. Journal of Park and Recreation Administration41(1), 107-119.
  31. Glass, J. (2023). Creating a positive organizational culture: Keys to employee satisfaction. Business Studies Journal, 15(6), 1-2.
  32. Halsall, T., Kendellen, K., Bean, C., & Forneris, T. (2016). Facilitating positive youth development through residential camp: Exploring perceived characteristics of effective camp counselors and strategies for youth engagement. Journal of Park and Recreation Administration34(4), 20-35.
  33. Hawke, A., & Page, E. (2022). Summer camp: Staffing and supply hurdles, but no shortage of fun. Retrieved from https://www.csmonitor.com/The-Culture/2022/0713/Summer-camp-Staffing-and-supply-hurdles-but-no-shortage-of-fun
  34. Henderson, K. A., Whitaker, L. S., Bialeschki, M. D., Scanlin, M. M., & Thurber, C. (2007). Summer camp experiences: Parental perceptions of youth development outcomes. Journal of Family Issues28(8), 987-1007.
  35. Holt, N. L., Neely, K. C., Slater, L. G., Camiré, M., Côté, J., Fraser-Thomas, J., … & Tamminen, K. A. (2017). A grounded theory of positive youth development through sport based on results from a qualitative meta-study. International review of sport and exercise psychology10(1), 1-49.
  36. Honig, D., & Diver, R. (2022). Mission-driven bureaucrats: Why support intrinsic motivation in developmental leadership? Retrieved from https://dlprog.org/opinions/mission-driven-bureaucrats-why-support-intrinsic-motivation-in-developmental-leadership/
  37. Joshi, A., Kale, S., Chandel, S., & Pal, D. K. (2015). Likert scale: Explored and explained. British Journal of Applied Science & Technology, 7(4), 396-403.
  38. Kelley, B. C. (1994). A model of stress and burnout in collegiate coaches: Effects of gender and time of season. Research Quarterly for Exercise & Sport, 65(1), 48-58.
  39. Larson, M. G. (2006). Descriptive statistics and graphical displays. Circulation114(1), 76–81.
  40. Lencioni, P. (2012). The advantage: Why organizational health trumps everything else in business. Jossey-Bass.
  41. Lubans, D. R., Plotnikoff, R. C., & Lubans, N. J. (2012). A systematic review of the impact of physical activity programs on social and emotional well-being in at‐risk youth. Child and Adolescent Mental Health17(1), 2-13.
  42. Lussier, R. N., & Achua, C. F. (2022). Leadership: Theory, application, & skill development. Sage Publications.
  43. Lynch, M. L., Trauntvein, N. E., Barcelona, R. J., & Moorhead, C. A. (2023).Retaining camp’s most valuable resource: A study on the fulfillment of counselor autonomy, competence, and relatedness and their impact on willingness to return. Journal of Park and Recreation Administration, 41(4),37-54.
  44. Mazzetti, G., & Schaufeli, W. B. (2022). The impact of engaging leadership on employee engagement and team effectiveness: A longitudinal, multi-level study on the mediating role of personal and team resources. Plos one17(6), 1-25.
  45. McCole, D., Jacobs, J., Lindley, B., & McAvoy, L. (2012). The relationship between seasonal employee retention and sense of community: The case of summer camp employment. Journal of Park and Recreation Administration30(2), 85–101.
  46. Pastore, D. (1994). Job satisfaction and female college coaches. Physical Educator, 50(4), 216–221.
  47. Pathak, A. (2024). The role of leadership in promoting employee wellness. The HR Director. Retrieved from https://www.thehrdirector.com/features/employee-engagement/role-leadership-promoting-employee-wellness/
  48. Povilaitis, V. (2015). Positive youth development at a residential summer sport camp. University of Toronto (Canada).
  49. Ramsing, R. (2007). Organized camping: A historical perspective. Child and Adolescent Psychiatric Clinics of North America16(4), 751–754.
  50. Reeves, S., Kuper, A., & Hodges, B. D. (2008). Qualitative research methodologies: Ethnography. BMJ337, 512–514.
  51. Robson, C., & McCartan, K. (2016). Real world research (4th ed.). John Wiley & Sons.
  52. Russell, R., Guerry, A. D., Balvanera, P., Gould, R. K., Basurto, X., Chan, K. M., … & Tam, J. (2013). Humans and nature: How knowing and experiencing nature affects well-being. Annual Review of Environment and Resources38(1), 473–502.
  53. Saldivar, J. M. N. (2024). Mission-driven leadership: An emergent theory. Ignatian International Journal for Multidisciplinary Research2(9), 328-342.
  54. Sibthorp, J., Browne, L., & Bialeschki, M. D. (2010). Measuring positive youth development at summer camp: Problem solving and camp connectedness. Research in Outdoor Education10(1), 1-12.
  55. Sieber, J. E. (Ed.). (2012). The ethics of social research: Surveys and experiments. Springer Science & Business Media.
  56. Tian, H., Iqbal, S., Akhtar, S., Qalati, S. A., Anwar, F., & Khan, M. A. S. (2020). The impact of transformational leadership on employee retention: mediation and moderation through organizational citizenship behavior and communication. Frontiers in Psychology11, 1-11.
  57. Vella, S., Oades, L., & Crowe, T. (2011). The role of the coach in facilitating positive youth development: Moving from theory to practice. Journal of Applied Sport Psychology23(1), 33–48.
  58. Wahl-Alexander, Z., Richards, K. A., & Washburn, N. (2017). Changes in perceived burnout among camp staff across the summer camp season. Journal of Park & Recreation Administration35(2), 74–85.
  59. Warner, R. P., Godwin, M., & Hodge, C. J. (2021). Seasonal summer camp staff experiences: A scoping review. Journal of Outdoor Recreation, Education, and Leadership13(1), 40–63.
  60. Whitacre, J., & Farmer, J. (2013). How come the best job I ever had was when I worked at a summer camp? Understanding retention among camp counselors. Journal of Youth Development8(2), 29–40.
  61. Wicks, C., Barton, J., Orbell, S., & Andrews, L. (2022). Psychological benefits of outdoor physical activity in natural versus urban environments: A systematic review and meta‐analysis of experimental studies. Applied Psychology: Health and Well-Being14(3), 1037–1061.
  62. Yin, R. K. (2018). Case study research and applications. Sage Publications.
  63. Zigmond, L. (2018). A reason to stay: Staff retention at Jewish overnight summer camps. Journal of Jewish Education84(4), 389–412.

2025-09-25T15:13:42-05:00October 24th, 2025|Research, Sport Education, Sports Coaching, Sports Facilities, Sports Health & Fitness|Comments Off on Managerial practices and coach satisfaction: A summer camp recreation and athletics case study 

The Impact of Head Coach and Student Athlete Decision Making in the Transfer Portal Era of College Sports

Authors:

Howard Bartee, Jr., Ed.D.1

Author affiliations:

1School of Public and Allied Health, Division of Kinesiology and Physical Education, Prairie View A & M University, Prairie View, TX, USA

Corresponding Author:

Howard Bartee, Jr., Ed.D.

Prairie View A & M University

700 University Drive

Prairie View, TX 77446

[email protected]

770-314-4415

Howard Bartee, Jr., Ed.D. is an Assistant Professor of Health and Kinesiology-Sport Management at Prairie View A & M University in Prairie View, TX.  His research interests include sports management and communication, sports analytics, and organizational behavior within the context of health and kinesiology. With nearly twenty-five years in higher education, Dr. Bartee has served in administrative capacities and previously taught sports management and sports administration courses at Houston Christian University in Houston, TX and Belhaven University in Jackson, MS. Dr. Bartee has further spearheaded initiatives related to sports career services, student advisement, and program and curriculum development. 

ABSTRACT

In collegiate sports, the reputation of the head coach is important in urban and suburban America as the transfer portal era of college sports continues to evolve. Many young athletes are going through the decision-making process as they prepare to compete on the collegiate level. Athletes have overcome their circumstances to open doors to the field of college sports, but with the impact of coaching changes, coaching reputations, and the growth of the transfer portal in recent years, college sports has entered an era of mobility on the coach and player levels, during the post-Covid pandemic society in our global sports world.

Key Words: High School Sports, College Sports, HBCU Sports, Coaching, Transfer Portal

INTRODUCTION

College sports has evolved tremendously from the days of four-year scholarship opportunity commitments to now the transfer portal era of today’s sports paradigm.  The transfer portal era refers to the ability of players to sign with one school this year and then transfer to another school the next year if another opportunity arises.  Many forces are now influencing the expansion of college sports and which, in effect, draw attention to the reasons why the impact of who the head coach is and the student athlete decision making process, are now having an impact on where today’s student athlete is deciding to go on signing day. 

From a practical viewpoint, while the college or university name plays a role in the decision-making process, when considering the student athlete decision, when considering the movement in player recruitment evolving over the past five years, the reputation of the coach along with the transfer portal and name, image, and likeness (NIL) opportunities are now playing a larger role in where students are attending across America.  When considering the hiring of coaches like Deion “Coach Prime” Sanders at Jackson State University in 2021 and then his movement to the University of Colorado in 2023 and the growth of transfer portal in recent years, coaching changes and coaching reputations have evolved to a level where a ‘free agent” market, like professional sports includes, is now part of the everyday operations of college sports. 

Thus, using sociohistorical and current perspectives and demographical information, the following questions guide this exploration:  

  1. What is the impact of the head coach in the pre-Covid transfer portal era (prior to 2020) and post-Covid transfer portal era (2020 to the present) on the NCAA Division I (FBS), NCAA Division I (FCS), NCAA Division II, and NCAA Division III levels of college sports? 
  2. What is the impact of the student athlete decision making process in the pre-Covid transfer portal era (prior to 2020) and post-Covid transfer portal era (2020 to the present) on the NCAA Division I (FBS), NCAA Division I (FCS), NCAA Division II, and NCAA Division III levels of college sports? 

These questions provide the context for understanding how the impact of the head coach has evolved from the pre-Covid transfer era in 2020 to the present post-Covid era on the NCAA Division I (FBS), NCAA Division I (FCS), NCAA Division II, and NCAA Division III levels. These questions show how on each of these levels and even to the recruitment of graduating high school student athletes is much different in 2025 as compared to years past. Using the implications of contextual matters, these questions offer a wider understanding of the contextual impact of the head coach along with their reputation and the universities ability to compete in the transfer portal era of college sports with the appropriate academic and athletic resources, today and tomorrow in the changing landscape. 

A View of the Impact of the Head Coach in the Transfer Portal Era of College Sports

Context matters when viewing the impact of the head coach and the student athlete decision making in the transfer portal era of college football, particularly given how the post-Covid transfer portal era is significantly different than the pre-Covid transfer portal era has evolved for student athletes selecting their colleges and universities.  The competition that has become apparent is that many athletes are now choosing not only where they attend based upon the reputation of coach, as past studies show, but also now where they can build upon their name, image and likeness (NIL) as well as where they can have the abilities to play the sport they love.  With the convergence of these concepts, entrance into the college ranks has been a detailed process from middle school to high school as many parents and student athletes embrace the process of going from youth sports to collegiate sports through the traditional way of the college choice process as outlined in past studies, like (1), (4), (5), and (7).  

According to (2), the primary college choice model is the (3) model, which focuses on the “predisposition phase, the search process and the choice stage” (pp. 207-221). In this model, (3) explain the logical steps that a student would encounter in the decision-making process, including the following: (1) the predisposition phase focuses on whether or not the student would like to continue formal education; (2) the search process focuses on the consideration and selection of characteristics of higher education and (3) the choice stage focuses on developing choice criteria and selecting an institution to attend.

When looking at the (3) of college choice in more detail along with (2) study on the college choice process of male and female collegiate student athletes going to the next level, it has three primary components including: (a) creating a simpler yet more conceptual model as compared to previous models; (b) isolating and containing the college choice process within a manageable three-stage framework (predisposition, search, and choice) as described above; and (c) emphasizing stages that focuse more on the student rather than the institution.  As a result, we see how student athletes are navigating to colleges and universities, that include those hired during the Coach Prime Era from 2020 to the present, those with previous college coaching experience or those coached with former NFL players.

As Table 4 shows, from the sampling of coaching hires, it was found that out of 25 coaching hires, 10 or 40% had NFL Playing Experience, had college coaching experience 13 or 52%, and had NFL Coaching Experience, 2 or 8%, excluding Coach Prime, thus the Coach Prime Effect on college coaching hires is part of the impact of today’s post Covid transfer portal era along with higher coaching salaries heading into the 2025 season, according to (10) in Table 5.

A View of the Impact of the Student Athlete Decision Making Process in the Transfer Portal Era of College Sports

In 2025, context matters, too, with regards to the head coach and student athlete decision making in the transfer portal era of college sports, specifically in football.  During the past five years, following Covid in 2020, the transfer portal has become a major component of the college football paradigm.  With the ability of players to become immediately eligible to play in most cases when they transfer, player movement has evolved to resemble the free agency model of professional football.  Through a sampling of schools throughout the country, there has been an uptick in players entering the transfer portal from 2020 to 2024 that have impacted to the collegiate sports industry.  Table 6 summarizes how this period has reshaped the sports paradigm. 

As Table 6 shows from NBC Sports and On3.com, “there has been an increase from years 2020 to 2021 and then from 2022 to 2023. The 65% increase in 2020-2021, along with the 19% increase from 2022-2023, shows that the impact of the transfer portal is growing throughout the field of college football and in the student athlete decision making process” (9), (10), (11), (12), (13) and (14). The largest increase has been from the 2020 to the 2025 years as there has been a 418% increase in the number of transfer portal entrants as shown in Table 6 above from 786 entrants in 2020 to 4060 entrants currently in June 2025.

Table 7 shows the impact of when a high-profile coach leaves one college and moves to another college that student athlete’s decision making resulted in approximately 60 student athletes entering the transfer portal.  This occurred when Deion “Coach Prime” Sanders took a head coach job at the University of Colorado and completed his work as head coach at Jackson State University.  Coach Prime’s exit resulted in him achieving a Power 5 position in the Big 12 Conference.  The resulting impact has also seen the hiring of other former athletes, like former Tennessee State University head coach Eddie George, recently moving to Bowling Green State University after having a measure of success with an Ohio Valley Conference Championship and postseason playoff appearance at Tennessee State University. 

Though many well-known sports figures are arriving at colleges and universities, like Michael Vick at Norfolk State University (football), Desean Jackson at Delaware State University (football), Reggie Barlow at Tennessee State University(football), and Bill Belichick at the University of North Carolina (football), the student athlete decision making process of offers, commitments and signings continue to be a valuable part of the recruiting process as the world of college athletics in 2025 evolves into a stronger business model of NIL collectives, new administrative roles like Athletic Department General Managers, and a more active transfer portal era during the post-Covid era, thus requiring a broader contextual perspective.

Additionally, Coach Prime and the Colorado Buffaloes recently continued in their turnaround from a one win season in 2022, prior to his arrival, as they qualified for the Alamo Bowl with a nine win season in Year Two of the Coach Prime Era along with having a Heisman Trophy Winner, while Coach T.C. Taylor, the coach that replaced Coach Prime at Jackson State, just recently led them to a SWAC Championship and Celebration Bowl HBCU National Championship twelve-win, two loss season, though both schools were recently impacted by the transfer portal between 2022 and 2024, according to (6). Also, the Ohio State University football team won the first-ever 12 team playoff National Championship over the University of Notre Dame, with a fourteen-win, two loss season. 

Shared Implications of Coaching, Student Athlete Decision Making and the Transfer Portal Era of an Evolving College Sports Model in 2025 and Beyond

In closing, since the first collegiate football game in November of 1869 between Rutgers University and the College of New Jersey (now Princeton University) until the most recent national championship between the Ohio State University and the University of Notre Dame in January 2025, the college sports model has been consistently focused on maintaining the balance between student and athlete.  For many years, this balance was focused on a model of players going to school for an education through scholarship achievement and athletic competition.  Though this still remains the primary focus, the transfer portal is now playing a stronger role on the student athlete decision making process as athletes have the flexibility to opt-out of their scholarships and transfer to other schools on a year to year basis, if they so choose.  Moving forward, with a major $2.8 billion settlement coming in July of 2025, a shift in the model on all levels will see more fluidity as the impact of the head coach and who that person is, along with how valued a student athlete feels will become factors that influence where players play and whether or not they choose to enter the transfer portal and then go elsewhere.  For example, according to (8), “more than 4,600 Division I athletes have entered their names in the NCAA transfer portal in the month of April 2025, in part because schools have been preparing for the expected roster limits in the $2.8 billion settlement”.  Moreover, as new student athletes enter the college sports arena from high school, having knowledge of the NIL process, will factor into the how student athletes make college choices and it will also have an impact on how colleges and universities structure their athletic departments and, in many instances, run them like professional organizations as the transfer portal era continues. 

REFERENCES

  1. Adler, P., & Adler, P. (1991). Backboards and blackboards: College athletes and role engulfment. New York: Columbia University Press.
  2. Bartee, Jr. H. (2011).  The next level: Six erspectives on the college choice process of student athletes.  United States: CreateSpace.  ISBN-13:  978-1456377762
  3. Hossler, D. & Gallagher, K. (1987). Studying college choice: A three-phase model and the implication for policy makers. College and University, 62, 207-21.
  4. Hossler, D., Schmitt, J. and Vesper, N. (1999).  Going to college: How social, economic, and educational factors influence the decisions students make.  Baltimore, MD: John Hopkins Press.
  5. Letawsky, N. (2003). Factors influencing the college selection process of student athletes: are their factors similar to non-athletes. College Student Journal, 37(4), 604-610.
  6. Keith, J. T. (2023).  Jackson state football transfer tracker: Who’s leaving via portal. Retrieved on April 10, 2025 from https://www.clarionledger.com/story/sports/college/jackson-state/2023/12/04/jackson-state-football-transfer-portal-tracker-tc-taylor/71799007007/
  7. Mathes, S. & Gurney, G. (1985). Factors in student athletes’ choices of colleges. Journal of College Student Personnel, 26, (4), 327-333.
  8. Murphy, D. (2025, April 23).  Judge delays house settlement approval over roster limits. Retrieved on April 24, 2025 from https://www.espn.com/college-sports/story/_/id/44823761/judge-delays-house-settlement-approval-roster-limits.
  9. NBC Sports Staff (2024, February 12).  College football transfer portal tracker.  Retrieved on April 22, 2025 from https://www.nbcsports.com/college-football/news/college-          football transfer-portal-tracker.
  10. On3. (2025). 2025 College football transfer portal. On3.com. Retrieved on June 23, 2025 from https://www.on3.com/transfer-portal/wire/football/
  11. On3. (2024). 2024 College football transfer portal. On3.com. Retrieved on June 23, 2025 from https://www.on3.com/transfer-portal/wire/football/2024/
  12. On3. (2023). 2023 College football transfer portal. On3.com. Retrieved on June 23, 2025 from https://www.on3.com/transfer-portal/wire/football/2023/
  13. On3. (2022). 2022 College football transfer portal. On3.com. Retrieved on June 23, 2025 from https://www.on3.com/transfer-portal/wire/football/2022/
  14. On3. (2021). 2021 College football transfer portal. On3.com. Retrieved on June 23, 2025 from https://www.on3.com/transfer-portal/wire/football/2021/
  15. Talty, J. (2025, March 28).  College football’s highest-paid coaches in 2025: Colorado’s Deion Sanders enters top 10 with amended contract. Retrieved on April 24, 2025 from  https://www.cbssports.com/college-football/news/college-footballs-highest-paid-coaches-in-2025-colorados-deion-sanders-enters-top-10-with-amended-contract/

2025-06-24T08:57:53-05:00July 11th, 2025|Contemporary Sports Issues, General, Research, Sports Studies|Comments Off on The Impact of Head Coach and Student Athlete Decision Making in the Transfer Portal Era of College Sports

Efficacy of 12-Week Handgrip Strength Training Program Amongst Older Adults: A Pilot Study 

Author’s: Abbey Keller1, David Cason1, Shannon Hardy2, Madison Norris2, Angila Berni1, Michel Heijnen1, Alexander McDaniel1, Lindsey Schroeder1, Tiago Barriera3, Wayland Tseh1

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

2 Carolina Bay at Autumn Hall, 630 Carolina Bay Drive., Wilmington, North Carolina, United States of America

3 School of Education, Syracuse University, Syracuse, New York, United States of America 

Corresponding Author: 

Lindsey H. Schroeder, Ed.D., LAT, ATC, CES

University of North Carolina Wilmington
School of Health & Applied Human Sciences

601 South College Road
Wilmington, NC 28403-5956
O: (910) 962-7188

F: (910) 962-7073

ABSTRACT 

Handgrip strength is indicative of overall health and longevity. The significance of a strong grip increases with age as it relates to lower mortality rates and improved functional capacity.

PURPOSE: To evaluate the effectiveness of a 12-week handgrip strength training program amongst older adults. METHODS: A total of 12 participants (mean age = 82.7 ± 4.8 years; height = 160.7 ± 7.4 cm; body mass = 64.2 ± 13.9 kg; 2 males; 10 females) completed the 12-week exercise intervention. The participants engaged in a twice-weekly, 45-minute suspension training regimen that incorporated a range of exercises targeting upper body strength and stability. Handgrip strength was assessed via a handgrip dynamometer at baseline and post-intervention. A paired samples t-test was employed to assess differences between pre-and post-intervention grip strength. A Bonferroni correction was applied to mitigate the risk of Type I error due to multiple comparisons, setting the adjusted alpha level at p = 0.025. Effect sizes were calculated using Cohen’s d to assess the practical significance of the findings. RESULTS: The analysis revealed a statistically significant improvement in right-handgrip strength, with values increasing from 21.5 ± 1.3 kg in Week 1 to 23.0 ± 1.4 kg in Week 12 (p = 0.006). No significant improvement was observed in left-handgrip strength (20.2 ± 1.2 kg to 21.1 ± 1.5 kg; p = 0.12). The right handgrip strength demonstrated a large effect (d = 0.99), whereas the left handgrip strength exhibited a moderate effect (d = 0.48). CONCLUSION: Findings from this study suggest that the 12-week suspension training and handgrip strength exercise regimen was both statistically and practically effective in increasing HGS in older adults. PRACTICAL APPLICATIONS: Allied healthcare professionals should educate older adults on the importance of HGS and incorporate targeted exercises into their regimens to mitigate age-related functional decline and promote better outcomes.

KEYWORDS: Suspension Training, Longevity, Handgrip Strength

INTRODUCTION 

By the year 2050, the global population of older adults is projected to reach 2.1 billion (10). As this demographic shift occurs, various risks associated with aging, including falls, cognitive decline, and impaired longevity and quality of life, become increasingly concerning (8, 14, 45). A crucial yet frequently underappreciated factor contributing to falls and other age-related risks is diminished handgrip strength (HGS), which impairs an individual’s capacity to stabilize themselves and prevent injuries (16, 19). Research suggests that HGS is representative of overall body strength (1). Handgrip strength is defined as the maximum amount of force the hand generates when gripping an object. Thresholds for HGS required to perform functional tasks in older adults are estimated at greater than 18.5 kg for females and 28.5 kg for males (2). Beyond serving as a measure of physical strength, HGS is also a strong predictor of longevity and overall quality of life, making it especially relevant in the context of aging (1). Comprehending the relationship between HGS and other fitness components is essential for devising effective strategies to preserve functional independence and enhance quality of life, particularly as the global population experiences unprecedented aging trends.

According to the Centers for Disease Control and Prevention (CDC), falls represent the leading cause of mortality among individuals aged 65 years and older. Annually, approximately 36 million older adults experience falls, with 32,000 cases resulting in fatal outcomes (4). Falls impact the quality of life by jeopardizing health, mobility, and independence. Although multiple factors influence fall risk, prioritizing interventions to improve HGS may offer a practical and impactful approach to reducing the incidence of falls among older adults (24).

In 2016, Szulc and colleagues examined 890 men aged 50 and older, assessing appendicular skeletal muscle mass (ASM), physical function, and HGS (42). Over a 5-year follow-up period, 813 participants aged 60 and above were monitored, of whom 144 experienced multiple falls. Findings from this research investigation revealed that those who sustained Grade 2 or Grade 3 vertebral fractures and multiple fractures had reduced HGS, decreased physical function, and an increased risk of multiple falls (42).

The number of global dementia cases is expected to almost triple from 57.4 million cases in 2019 to 152.8 million in 2050 (17). That said, aging significantly elevates the risk of cognitive decline, potentially leading to a loss of independence and other adverse outcomes. Although many factors are involved in preventing and treating cognitive decline and related illnesses, HGS may play a key role in determining who is at risk for these diseases. Physical impairments, such as diminished HGS, can interact with other factors to amplify the risk of age-related cognitive decline (7, 18). Consequently, investigating the relationship between HGS and cognitive function is essential for addressing the challenges of an aging global population.

In 2022, Orchard et al. evaluated both gait speed and HGS as predictors of cognitive decline and dementia (36). The participants were community-dwelling older adults who were cognitively intact at the onset of the study. Researchers assessed each participant’s 3-meter walk time and measured their HGS. A 4.7-year median follow-up was used to gather data on the prevalence of cognitive decline and dementia among participants. Slower walking gait and low HGS were independently related to an increased incident risk of dementia and cognitive decline. When these variables were combined, slow walking gait and low HGS were associated with a 79% increase in the risk of dementia development and a 43% increased risk of cognitive decline (36).

Precursory research has revealed that a culmination of exercise methods, including resistance training, Vitality Acupunch training program, multi-modal training, and suspension training (ST), can impact the HGS of older adults (2, 3, 10, 21, 23, 25, 26, 44). Among these, ST programs, such as total resistance exercise (TRX), stand out as accessible and adaptable methods. Due to the nature of ST, users possess the unique opportunity to train in several different facets of fitness at differing scalable resistances in a single bout of exercise (27). The suspension training system enables individuals to perform strength exercises adapted to their unique capabilities, offering progressive resistance to facilitate individualized strength development (15, 27).

In 2018, Campa, Silva, and Toselli conducted a study to determine the effects of a 12-week ST intervention on the phase angle and HGS of female older adults. Thirty older women were randomly assigned to either a control or training group. Participants in the control group continued their usual activities throughout the study, while those in the training group underwent a 12-week ST program. Both groups were assessed on various fitness parameters, including HGS. At the conclusion of the study, researchers found that ST promoted improvements in HGS in older women (3).

In 2022, Pierle and associates conducted a study to examine the efficacy of a 6-week ST program on a sample of 11 older individuals (37). The fitness parameters of interest were functional reach, overall balance, body fat, body mass, and HGS. While this study demonstrated improvements in functional reach and overall balance, body fat, body mass, and HGS showed no significant changes. These findings suggest that ST may be an effective exercise modality for enhancing certain aspects of fitness in older adults. However, further investigation is crucial to understand its impact on HGS better and determine whether ST can optimize strength outcomes in this population (37).

Against this backdrop, given the dearth of research examining the effects of ST protocols on HGS and the relationship between HGS and fall prevention, further investigation is imperative to elucidate the potential benefits of ST, especially amongst the older adult population. Therefore, the primary purpose of this study is to fill this critical gap by evaluating the efficacy of a 12-week ST and HGS exercise program in enhancing handgrip strength in this population. The apriori hypothesis posits that significant improvements in HGS will be observed between pre- and post-assessment measurements, underscoring the potential of ST and HGS as a targeted intervention to improve strength and reduce fall risk among older adults.

METHODS 

Participants

Prior to participating in this study, participants were screened using inclusionary and exclusionary criteria. The inclusion requirements included participants who currently exercise, are older than 55 years of age, and are independent of assistive walking devices (e.g., walker, rollator, wheelchair, etc.). The exclusionary criteria included participants not having a medical release form on record, being overwhelmed by the exercise routine, specifically, mild increases in heart rate and blood pressure during exercise, or possessing a pacemaker or other internally implanted device. All participants, therefore, were required to have a medical release to participate. This study was approved by the university’s institutional review board and adhered to the practice of ethical research standards.

All participants were recruited from a local retirement community and were required to report to the Wellness Center onsite for 24 sessions over 12 weeks. Flyers were posted, and those interested were instructed to sign up for an appointment with the principal investigator (PI) to complete the protocol requirements. Participants were encouraged to contact the PI or co-PI by phone or email if any question(s) arose or if any of the requirements remained unclear.

Upon arrival for the pre-assessment session, participants read/signed/dated an informed consent form approved by the University’s Institutional Review Board (IRB) for human subject use (IRB#: H24-0565). Ten females and 2 males (Age = 82.7 ± 4.8 years; Height = 160.7 ± 7.4 cm; Body Mass = 64.2 ± 13.9 kg), completed the 12-week exercise intervention.

Protocol

Once the informed consent was obtained, pre-assessment data was collected. All participants were instructed to remove footwear, socks, and stockings before stepping onto the scale. Height (cm) and body mass (kg) were assessed via Seca 217 Mobile Stadiometer (Model Number 2171821009, USA). The participant’s height and body mass results were displayed and recorded via a data collection sheet. Grip strength was assessed via the Smedley Creative Health Products III Analog Grip Strength Dynamometer (T.K.K. 5001, Japan). Participants were instructed to maintain the standard bipedal position during the entire test with the arm in complete extension and to avoid touching any part of the body with the handgrip dynamometer except the hand being measured. Participants comfortably grasped the handgrip dynamometer and were encouraged to exert maximal grip.

Three trials, with brief pauses, were allowed for each hand alternately. The sum of the highest left and right values was recorded on the data collection sheet. The PI was the lead exercise instructor of the 12-week exercise intervention. The PI took attendance, organized, and provided corrective feedback/instructions during each exercise session. A team of fitness instructors at the retirement community and a research assistant also led these classes by providing feedback to participants and keeping each session organized. The exercise intervention required participants to attend two sessions per week for 12 weeks, with each class being 45 minutes. Attendance was recorded at the start of each class to keep track of the adherence rate. Every session consisted of seven strength training exercises in a circuit style (Table 1), followed by a grip strength series consisting of four exercises (Table 2).

Strength training exercises were advanced every 4 weeks, specifically, progressing from 30-second intervals (first micro-cycle) to 35 seconds (second micro-cycle) to 40 seconds (final micro-cycle). The Farmer’s Carry exercise specifically intensified each micro-cycle, starting with holding one dumbbell each set, then holding one dumbbell each set vertically upright by the head of the weight, and finally holding the head of a dumbbell in each hand. The grip strength series progressed throughout the 12-week intervention, starting with one set of each exercise for 15 seconds per hand in the first 4 weeks and followed by 8 weeks of performing each exercise for two sets of 15 seconds. Each session started with a 5-minute warm-up, followed by 35 minutes of exercise, and concluded with a 5-minute cooldown. The 12-week exercise training intervention took place as a group fitness class in the fitness center of a local retirement community, giving participants the advantage of working with partners for each exercise, increasing accountability and motivation. The TRX suspension training (ST) allowed users to exercise in a customizable and scalable capacity that fits their personal specifications, comfort, and intensity levels (27). Additionally, the PI used a timed-circuit style class versus measuring each exercise based on repetition, allowing participants to perform at their own intensified pace.

Statistical Analysis

A paired samples t-test was employed to assess differences between pre-and post-intervention grip strength. To mitigate the risk of Type I error due to multiple comparisons, a Bonferroni correction was applied, setting the adjusted alpha level at p = 0.025. Effect sizes were calculated using Cohen’s d to assess the practical significance of the findings. 

RESULTS 

The primary objective of this study was to evaluate the efficacy of a 12-week exercise intervention on handgrip strength (HGS) in a population of community-dwelling older adults. Sixteen participants were initially recruited; however, four withdrew during the study, resulting in a final sample size of 12 participants (Age = 82.7 ± 4.8 years; Height = 160.7 ± 7.4 cm; Body Mass = 64.2 ± 13.9 kg; 2 males and ten females). Attendance was monitored at each session, yielding an average adherence rate of 83%. The adherence rate remained consistent throughout this study.

A paired-sample t-test was conducted to assess differences between pre- and post-intervention measurements. A Bonferroni correction was applied to mitigate the risk of Type I errors due to multiple comparisons, resulting in an adjusted alpha level of p = 0.025. Effect sizes were quantified using Cohen’s d, with thresholds of 0.2, 0.5, and >0.8 representing small, medium, and large effects, respectively.

The analysis revealed a statistically significant improvement in right-hand grip strength, which increased from 21.5 ± 1.3 kg at baseline (Week 1) to 23.0 ± 1.4 kg post-intervention (Week 12, p = 0.006). In contrast, no statistical improvement was observed for left-hand grip strength (20.2 ± 1.2 kg to 21.1 ± 1.5 kg, p = 0.12). The effect size for right-hand grip strength was large (d = 0.99), whereas the left-hand grip strength demonstrated a moderate effect (d = 0.48). Detailed results are presented in Table 3.

DISCUSSION 

Limited research exists with respect to investigating sustained strength training (ST) programs and handgrip strength (HGS) in older adults (12, 23). Therefore, the primary purpose of this study was to determine the efficacy of a 12-week ST and HGS exercise program in a community-dwelling older adult population. The researchers hypothesized a statistically significant improvement in HGS between pre- and post-assessment data. At the conclusion of the 12-week ST and HGS exercise program, right-HGS improved significantly and demonstrated a large effect size, while the left hand showed a moderate but non-significant change. These findings suggest that a 12-week suspension training exercise program may enhance grip strength and potentially improve functional independence and reduce fall risk in older adults. However, additional research is needed to fully understand these effects and any differences between dominant and non-dominant hands.

 In 2018, a research study was conducted by Campa and colleagues in which the participants were divided into two groups: 1) 12-week ST exercise group and 2) control group that maintained their usual daily activity (3). Both groups of participants underwent pre-and post-tests, evaluating several fitness components, including HGS. Findings from the current research study and the study by Campa et al. (3) revealed both shared and contrasting results in how structured exercise interventions affect HGS in older adults. More precisely, both studies reported statistically significant HGS improvements following their 12-week interventions. The current research study observed an increase in right-hand grip strength from 21.5 ± 1.3 kg to 23.0 ± 1.4 kg, equating to an approximate 7.0% improvement. Similarly, Campa et al. (3) reported an increase in dominant-hand HGS from 38.2 ± 9.7 kg to 40.1 ± 9.0 kg, reflecting a significant 4.97% improvement. Both findings confirm the efficacy of a 12-week exercise program in promoting upper-body strength among older adults. Notably, both studies targeted older adults, with the current study involving a mixed-gender cohort (mean age 82.7 years) and Campa et al. (3) focusing on men with a mean age of 67.4 years. Despite this approximate 15-year age difference, the consistency in outcomes underscores the adaptability of exercise interventions across different subsets of older adults. Both research studies spanned 12 weeks, suggesting that this time frame is sufficient to elicit measurable improvements in muscular strength. Given these similarities, improvements in HGS in both studies align with broader health and functional benefits. Because HGS is a well-established predictor of overall physical health (29, 35), these findings highlight the role of resistance-based interventions in enhancing the quality of life and functional independence among older adults.

While both studies displayed shared findings, it was noted that the baseline mean HGS of the current study was strikingly lower (21.5 ± 1.3 kg) compared to Campa et al.’s (3) sample group (38.2 ± 9.7 kg). This discrepancy may be due to the age difference of about 15 years, which more than likely contributed to variations in baseline physical fitness and adaptive capacity. Older adults often experience diminished neuromuscular responsiveness and muscle plasticity (7, 32).

To summarize, the current research study and Campa et al.’s (3) study demonstrate significant improvements in HGS following 12-week exercise programs, reinforcing the utility of structured ST in mitigating age-related strength decline. Both studies provide compelling evidence that targeted interventions can yield functional strength gains in older populations regardless of modality. However, the differences in participant demographics highlight the influence of baseline fitness levels and age on HGS outcomes.

The results from a study by Gaedtke and Morat (16) also revealed results like those of the current study. Eleven older adults (Mean Age = 66.0 ± 4.0 yrs) participated in a 12-week TRX-OldAge training program, composed of seven exercises progressing through multiple stages of difficulty. The intervention method utilized TRX equipment, shared by Gaedtke and Morat (16) and the current study. Both studies also had similar sample sizes and durations, spanning 12 weeks. The results displayed within Gaedtke and Morat’s (16) research study share thematic similarities with the current research in demonstrating improvements in HGS. Both studies emphasize the potential of targeted programs to enhance functional strength, which is critical for maintaining independence and reducing the risk of falls in aging populations. Specifically, the current research reported a 7.0% increase in right-hand grip strength, showcasing the tangible benefits of a 12-week intervention. Similarly, participants in Gaedtke and Morat’s (16) study subjectively reported strength gains as the most notable improvement following the TRX-OldAge program. However, Gaedtke and Morat (16) did not provide quantifiable pre- and post-assessment metrics for HGS, which limits direct comparisons. While participant feedback highlights strength improvements, the lack of quantifiable data undermines the ability to assess the efficacy of the intervention, specifically on grip strength. This limitation in Gaedtke and Morat’s (16) study underscores the importance of incorporating quantifiable assessments in future investigations to validate self-reported outcomes and to draw more substantial comparisons with similar studies. Regardless, given the vast similarities between the two research studies, it is evident that a TRX-related exercise regime conducted for 12 weeks does enhance muscular strength in older individuals.

In a study conducted by Skelton et al. (41), a 12-week progressive ST intervention was implemented to assess its effects on the strength, power, and functionality of women aged 75 and older (41). The intervention included three exercise sessions per week, with two sessions conducted at home and one in a group setting. The additional day of exercise, as well as the inclusion of home exercise sessions, differs from the current study, which took place twice a week in a group fitness class setting. While the exercises did not mimic the functional tests entirely, each session was tailored to work the specific muscles relevant for functional tasks. Exercises were performed in three sets of four to eight repetitions, using rice bags and elastic bands for resistance. An assortment of pre- and post-assessments were conducted, including a HGS test, resembling the current study.

Despite these methodological differences, Skelton and colleagues (41) demonstrated increases in HGS, which aligns with the improvements observed in the current research study. In Skelton et al.’s (41) 12-week progressive resistance training program, participants experienced a significant 4% increase in HGS, from a pre-training mean of 21.6 ± 3.4 kg to a post-training mean of 22.3 ± 3.9 kg. This outcome parallels findings from the current research study, whereby a significant 7% improvement in HGS was observed. This supports the notion that 12 weeks of functional resistance training may improve HGS amongst a sample of older individuals.

A potential explanation for the greater improvement in HGS observed in the current study may be the focused, grip-specific training regimen utilized. Skelton et al.’s (41) training program, while progressive and resistance-based, did not include exercises that mimicked or directly engaged the musculature required for grip strength improvement. Instead, the program targeted broader functional movements, such as knee extensors, elbow flexors, and other large muscle groups. This specificity likely contributed to the larger improvement in grip-related performance observed in the current study.

Because the current study partially mimicked and addressed some of the limitations of Pierle and colleagues (37), detailed comparative results will be described. Pierle et al. (37) evaluated the efficacy of a 6-week ST intervention on multiple fitness components of older adults (37). This intervention consisted of 1-2 sets of 8 ST exercises performed twice a week. At the conclusion of this study, participants showed improvements in several fitness and functional areas. In contrast to the current study, Pierle et al. (37) did not observe improvements in HGS.

In the current study, participants demonstrated a statistically significant improvement in right-HGS following a 12-week intervention. Pre-assessment HGS for the right hand was 21.5 ± 1.3 kg, which increased to 23.0 ± 1.4 kg, reflecting a 7.0% improvement and a large effect size (d = 0.99). Conversely, left-hand HGS exhibited a smaller, non-significant increase from 20.2 ± 1.2 kg to 21.1 ± 1.5 kg (4.5% improvement, d = 0.48). Comparatively, Pierle et al. (37) observed no statistically significant changes in HGS, with pre-assessment values averaging 22.4 ± 1.9 kg and post-assessment values averaging 22.8 ± 1.8 kg. The effect size (d = 0.03) was minimal, indicating negligible gains in grip strength.

The differences in duration and intervention may explain this disparity in findings. For instance, the intervention in Pierle et al.’s (37) study lasted for 6 weeks, with two sessions per week, totaling 12 training sessions. This short duration may have limited the time available for participants to experience significant neuromuscular adaptations, such as improved motor unit recruitment and muscle hypertrophy, which are crucial for strength gains (6, 33). In contrast, the current study required participants to exercise for 12 weeks, providing twice the intervention time, therefore allowing for a more progressive overload and adaptation. The longer program likely facilitated more robust changes in muscle strength, particularly in the dominant hand. Previous research documents that strength improvements, particularly in older adults, rely on consistent and prolonged exposure to resistance-based stimuli to elicit meaningful neuromuscular adaptations (9, 20).

Another potential reason for the difference in findings is the modality and specificity of exercises. Pierle and colleagues’ study (37) focused on general ST, which emphasized functional movements, overall balance, core stability, and flexibility but did not prioritize grip-intensive exercises. In contrast, the current study employed targeted resistance and isometric exercises specifically designed to enhance HGS, ensuring a more direct focus on grip-related adaptations. Previous research has shown that exercise modality plays a critical role in the specificity of adaptations (15, 21). The lack of direct HGS training in Pierle et al.’s (37) protocol likely limited the magnitude of HGS improvements compared to the current research study.

The current study displayed a statistically significant improvement in right-HGS. While no statistically significant improvement was observed in left-HGS. While said findings were unanticipated, previous research investigations have displayed similar asymmetrical findings (22, 30, 43). In 2008, Thomas & Sahlberg recruited 41 college-aged males and females to complete an 8-week resistance training protocol with the aim of enhancing HGS. Data revealed by Thomas and Sahlberg (2008) align closely with the current investigation in demonstrating significant improvements in right-hand HGS, while no significant changes were observed in the left-hand HGS. In Thomas and Sahlberg’s (43) study, participants in the training group exhibited a statistically significant increase in right-hand HGS (32.9 ± 8.6 kg to 35.5 ± 7.6 kg) over an 8-week general resistance training intervention. However, the left-hand HGS showed no significant changes (30.7 ± 8.4 kg and 30.2 ± 6.0 kg). Similarly, the current research reported a statistically significant improvement in right-hand HGS (21.5 ± 1.3 kg to 23.0 ± 1.4 kg) but observed no significant change in left-hand HGS, which increased only marginally from 20.2 ± 1.2 kg to 21.1 ± 1.5 kg.

The consistency between these studies highlights the tendency for dominant-hand HGS to exhibit greater responsiveness to resistance training interventions. Both studies emphasize the role of hand dominance in determining training outcomes, with dominant hands showing significant strength gains due to frequent daily use and greater neuromuscular efficiency (5, 39). Conversely, the non-dominant hand may require more targeted stimuli to achieve comparable improvements, as evidenced by the lack of significant HGS gains in the left hand in both studies (13, 40). These findings emphasize the importance of tailoring training programs to address asymmetries and maximize bilateral strength development.

In 2019, Labott and colleagues conducted a comprehensive meta-analytical review to evaluate the effects of various exercise interventions on HGS in older adults. The review analyzed 24 research articles involving 3,018 participants with a mean age of 73.3 years (22), focusing on interventions ranging from resistance training to multimodal programs. While the findings revealed small but statistically significant improvements in HGS overall, the results emphasized a common trend across studies to the extent that greater responsiveness in right-hand HGS compared to the left-hand HGS. These authors concluded that task-specific and multimodal training interventions often yielded measurable gains in dominant hand strength, as this hand benefits from more frequent use and neuromuscular efficiency in daily activities. In contrast, left-hand HGS frequently displayed minimal or no significant change, reflecting the need for targeted stimuli to elicit comparable adaptations in the non-dominant hand. The review highlights this asymmetry as a recurring observation in HGS research, reinforcing the importance of tailored interventions to address disparities between dominant and non-dominant hand strength (5,22).

Although no statistically significant improvement was observed in left-hand HGS among participants in the current study, the practical implications of the findings should not be overlooked. A mean increase of 1.1 kg (4%) represents a meaningful real-world difference, particularly within aging populations. For older adults, even modest improvements in HGS can translate into enhanced functional capacity, better mobility, fall mitigation, greater independence in activities of daily living, and improved overall quality of life (11, 22, 28, 31, 38, 46). Moreover, from an applied perspective, a 4% increase in left-hand HGS may provide critical support in scenarios requiring quick reflexive actions, such as maintaining balance or catching oneself during a fall (28, 34). This seemingly minor improvement could make a significant difference in preventing injury and maintaining mobility, highlighting the value of targeted interventions to enhance HGS, even in cases where statistical significance is not achieved.

There were several limitations to this study that may have impacted the results. The small sample size (n = 12) and the low male participation in this study may have stifled the results from reaching their full expression. Future studies would benefit from a larger and more gender-balanced sample to enhance the generalizability of findings. Additionally, an increased sample size would allow for a control group to be utilized, bolstering the findings of future studies. Adherence to the 12-week intervention proved difficult as it slowly declined by 17% throughout the study, as many participants had busy schedules and prior commitments that interfered with consistent session attendance. Future studies may consider methods to improve adherence, such as scheduling flexibility or at-home modifications. Longer intervention durations may yield more robust findings, as 12 weeks might not have allowed the intervention to reach its full potential. Confounding variables, such as diet, sleep, and baseline activity levels, were not accounted for and may have influenced the results. Tracking these variables in future studies could provide additional insights into their potential impact.

As individuals age, their priorities often shift toward improving quality of life, extending longevity, and maintaining functional independence. Because HGS directly impacts these aspects of healthy aging, its maintenance, or better yet, improvement, should remain a priority in interventions targeting older adults. The intention of this study was to discover the efficacy of a 12-week ST exercise intervention on the HGS of older adults and underscore its importance for healthy aging. The current study revealed a statistically significant improvement in right-HGS, whereas no significant improvement was observed in left-HGS. Future research should evaluate asymmetrical HGS, as this was not an anticipated finding. Additionally, further research should investigate ST in older adult populations, addressing the limited existing evidence on its efficacy in this demographic.

CONCLUSION 

Findings from this study suggest that the 12-week ST and HGS exercise regime was statistically and practically effective in increasing overall HGS in older adults. These findings may serve as valuable guidance for fitness instructors, physical therapists, and other allied healthcare professionals working with older adults. Integrating ST exercises and HGS-specific exercises results in improved HGS, an essential component of maintaining functional independence as individuals age. Utilizing the TRX system for this intervention provided unique advantages, as the exercises were simple to perform and customizable to each participant.

PRACTICAL APPLICATIONS

Implementing an exercise program focusing on HGS has broader implications, as HGS correlates with improved quality of life, longevity, and reduced risk of falls. Allied healthcare professionals working with older adult populations should educate their patients on the importance of HGS and adopt intentional HGS-focused exercises into their regimens. In doing so, they can help mitigate age-related functional decline and promote better outcomes for aging individuals.

ACKNOWLEDGMENTS

The author would like to personally thank the health and wellness team at Carolina Bay at Autumn Hall: Shannon Hardy and Madison Norris.

The author would also like to thank the Center for the Support of Undergraduate Research and Fellowships for their generous contributions.

REFERENCES 

  1. Attia, P. (2022, July 30). Avoiding Injury Part II: Grip Strength. Peter Attia MD. https://peterattiamd.com/avoiding-injury-part-ii-grip-strength/
  2. Bohannon, R.W. (2019). Grip strength: an indispensable biomarker for older adults. Clinical Interventions in Aging, 14, 1681–1691. https://doi.org/10.2147/CIA.S194543
  3. Campa, F., Silva, A., & Toselli, S. (2018). Changes in phase angle and handgrip strength induced by suspension training in older women. International Journal of Sports Medicine, 39(06), 442–449. https://doi.org/10.1055/a-0574-3166
  4. Centers for Disease Control and Prevention. (2022, June 9). Keep on your feet-preventing older adult falls. Centers for Disease Control and Prevention. https://www.cdc.gov/falls/about/?CDC_AAref_Val=https://www.cdc.gov/injury/features/older-adult-falls/index  
  5. Chapman, J. A., & Henneberg, M. (1999). Switching the handedness of adults: Results of 10 weeks training of the non-dominant hand. Perspectives in Human Biology, 4(1), 211–217. https://www.researchgate.net/publication/233726410
  6. Christie, A., & Kamen, G. (2010). Short-term training adaptations in maximal motor unit firing rates and afterhyperpolarization duration. Muscle & Nerve, 41(5), 651–660. https://doi.org/10.1002/mus.21539
  7. Clark, D.J., & Fielding, R.A. (2012). Neuromuscular contributions to age-related weakness. Journals of Gerontology: Series A, 67(1), 41–47. https://doi.org/10.1093/gerona/glr041
  8. Clark, S., Parisi, J., Kuo, J., & Carlson, M. C. (2016). Physical Activity Is Associated With Reduced Risk of Executive Function Impairment in Older Women. Journal of aging and health28(4), 726–739. https://doi.org/10.1177/0898264315609908
  9. Conlon, J.A., Newton, R.U., Tufano, J.J., Peñailillo, L.E., & Banyard, H.G. (2017). The efficacy of periodised resistance training on neuromuscular adaptation in older adults. European Journal of Applied Physiology, 117(1), 137–149. https://doi.org/10.1007/s00421-017-3605-1
  10. Cunningham, C., O’ Sullivan, R., Caserotti, P., & Tully, M.A. (2020). Consequences of physical inactivity in older adults: a systematic review of reviews and meta-analyses. Scandinavian Journal of Medicine & Science in Sports, 30(5), 816–827. https://doi.org/10.1111/sms.13616
  11. Damush, T.M., & Damush, J.G. Jr. (1999). The effects of strength training on strength and health-related quality of life in older adult women. The Gerontologist, 39(6), 705–710. https://doi.org/10.1093/geront/39.6.705
  12. Domingues, L.B., Schneider, V.M., & Abreu, R.F. (2024). Effects of a 4-week detraining period after 12 weeks of combined training using different weekly frequencies on health-related physical fitness in older adults. International Journal of Environmental Research and Public Health, 21(11), 1433. https://doi.org/10.3390/ijerph21111433
  13. Dunn, A.M. (2017). Non-dominant arm training improves functional performance and modifies spontaneous arm selection. Penn State University Libraries Theses and Dissertations. Retrieved from https://etda.libraries.psu.edu/catalog/13597amd460
  14. Fritz, N. E., McCarthy, C. J., & Adamo, D. E. (2017). Handgrip strength as a means of monitoring progression of cognitive decline – A scoping review. Ageing research reviews35, 112–123. https://doi.org/10.1016/j.arr.2017.01.004
  15. Fyfe, J.J., & Loenneke, J.P. (2018). Interpreting adaptation to concurrent compared with single-mode exercise training: Some methodological considerations. Sports Medicine, 48(2), 289–297. https://doi.org/10.1007/s40279-017-0812-1
  16. Gaedtke, A. & Morat, T. (2015). TRX suspension training: a new functional training approach for older adults – development, training control and feasibility.” International Journal of Exercise Science, 8(3), 224–233.
  17. GBD 2019 Dementia Forecasting Collaborators (2022). Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019. The Lancet. Public health7(2), e105–e125. https://doi.org/10.1016/S2468-2667(21)00249-8
  18. Gudlaugsson, J., Gudnason, V., Aspelund, T., Siggerirsdottir, K., Olafsdottir, A.S., Jonsson, P.V., Arngrimsson, S.A., Harris, T.B., & Johannnsson, E. (2012). Effects of a 6-month multimodal training intervention on retention of functional fitness in older adults: a randomized-controlled cross-over design. International Journal of Behavioral Nutrition and Physical Activity, 9(107). https://doi.org/10.1186/1479-5868-9-107
  19. Haider, S., Luger, E., Kapan, A., Titze, S., Lackinger, C., Schindler, K.E., & Dorner, T.E. (2016). Associations between daily physical activity, handgrip strength, muscle mass, physical performance and quality of life in prefrail and frail community-dwelling older adults. Quality of Life Research, 25(12). https://doi.org/10.1007/s11136-016-1349-8
  20. Häkkinen, K., Alen, M., Kallinen, M., Newton, R.U., & Kraemer, W.J. (2000). Neuromuscular adaptation during prolonged strength training, detraining, and re-strength-training in middle-aged and elderly people. European Journal of Applied Physiology, 83(1), 51–62. https://doi.org/10.1007/s004210000248
  21. Isner-Horobeti, M.E., Dufour, S.P., Vautravers, P., & Geny, B. (2013). Eccentric exercise training: Modalities, applications, and perspectives. Sports Medicine, 43(6), 483–512. https://doi.org/10.1007/s40279-013-0052-y
  22. Labott, B.K., Bucht, H., Morat, M., Morat, T., & Donath, L. (2019). Effects of exercise training on handgrip strength in older adults: A meta-analytical review. Gerontology, 65(6), 686–696. https://doi.org/10.1159/000501203
  23. Leitão, L., Campos, Y., Louro, H., & Figueira, A.C.C., Figueiredo, T., Pereira, A., Conceicao, A., Marinho, D.A., & Neiva, H.P. (2024). Detraining and retraining effects from a multicomponent training program on the functional capacity and health profile of physically active prehypertensive older adults. Healthcare, 12(2), 271. https://doi.org/10.3390/healthcare12020271
  24. Liu, H., Hou, Y., Li, H., & Lin, J. (2022). Influencing factors of weak grip strength and fall: A study based on the China Health and Retirement Longitudinal Study (CHARLS). BMC Public Health, 22(1), 2337. https://doi.org/10.1186/s12889-022-14753-x
  25. López-Bueno, R., Andersen, L. L., Koyanagi, A., Núñez-Cortés, R., Calatayud, J., Casaña, J., & Del Pozo Cruz, B. (2022). Thresholds of handgrip strength for all-cause, cancer, and cardiovascular mortality: A systematic review with dose-response meta-analysis. Aging Research Reviews, 82, 101778. https://doi.org/10.1016/j.arr.2022.101778
  26. Mayer, F., Scharhag-Rosenberger, F., Carlsohn, A., Cassel, M., Muller, S., & Scharhag, J. (2011) The intensity and effects of strength training in the elderly. Deutsches Ärzteblatt International, 108(21), 359-364. https://doi.org/10.3238/arztebl.2011.0359
  27. McDaniel, A. T., Heijnen, M. J. H., Kawczynski, B., Haugen, K. H., Caldwell, S., Campe, M. M., Conley, E. C., & Tseh, W. (2023). Efficacy of Army Combat Fitness Test 12-Week Virtual Exercise Program. Military medicine, 188(7-8), e2035–e2040. https://doi.org/10.1093/milmed/usac364
  28. McGrath, R., Clark, B. C., Cesari, M., & Johnson, C. (2021). Handgrip strength asymmetry is associated with future falls in older Americans. Aging Clinical and Experimental Research, 33(9), 2461-2469. https://doi.org/10.1007/s40520-020-01757-z
  29. McGrath, R. P., Kraemer, W. J., Snih, S. A., & Peterson, M. D. (2018). Handgrip strength and health in aging adults. Sports Medicine, 48(5), 1059–1062. https://doi.org/10.1007/s40279-018-0952-y
  30. McGrath, R., Lang, J., Clark, B.C., Cawthon, P.M., Black, K., Kieser, J., Fraser, B.J., & Tomkinson, G.R. (2023). Prevalence and trends of handgrip strength asymmetry in the United States. Advances in Geriatric Medicine and Research, 5(2), e230006. https://doi.org/10.20900/agmr20230006
  31. McGrath, R., Vincent, B.M., Hackney, K.J., Robinson-Lane, S.G., Downer, B., & Clark, B.C. (2020). The longitudinal associations of handgrip strength and cognitive function in aging Americans. Journal of the American Medical Directors Association, 21(6), 634-639.e1. https://doi.org/10.1016/j.jamda.2019.08.032
  32. McNeil, C.J., & Rice, C.L. (2018). Neuromuscular adaptations to healthy aging. Applied Physiology, Nutrition, and Metabolism, 43(4), 307–317. https://doi.org/10.1139/apnm-2018-0327
  33. Moritani, T. (1993). Neuromuscular adaptations during the acquisition of muscle strength, power, and motor tasks. Journal of Biomechanics, 26(1), 95–107. https://doi.org/10.1016/0021-9290(93)90082-P
  34. Neri, S.G.R., Lima, R.M., Ribeiro, H.S., & Vainshelboim, B. (2021). Poor handgrip strength determined clinically is associated with falls in older women. Journal of Frailty, Sarcopenia and Falls, 6(2), 43-49. https://doi.org/10.22540/JFSF-06-043
  35. Norman, K., Stobäus, N., Gonzalez, M.C., Schulzke, J.D., & Pirlich, M. (2011). Hand grip strength: Outcome predictor and marker of nutritional status. Clinical Nutrition, 30(2), 135–142. https://doi.org/10.1016/j.clnu.2010.09.010
  36. Orchard, S.G., Polekhina, G., Ryan, J., Shah, R.C., Storey, E., Chong, T.T., Lockery, J.E., Ward, S.A., Wolfe, R., Nelson, M.R., Reid, C.M., Murray, A.M., Espinoza, S.E., Newman, A.B., McNeil, J.J., Collyer, T.A., Callisaya, M.L., Woods, R.L., & ASPREE Investigator group. (2022). Combination of gait speed and grip strength to predict cognitive decline and dementia. Alzheimer’s & Dementia, 14(1), e12353. https://doi.org/10.1002/dad2.12353
  37. Pierle, C., McDaniel, A.T., Schroeder, L.H., Heijnen, M.J.H., & Tseh, W. Efficacy of a 6-Week suspension training exercise program on fitness components in older adults. International Journal of Exercise Science, 15(3), 1168–78, https://doi.org/10.70252/GPEB7735
  38. Santanasto, A.J., Glynn, N.W., Lovato, L.C., Blair, S.N., Fielding, R.A., Gill, T.M., Guralnik, J.M., Fang-Chi, H., King, A.C., Strotmeye, E.S., Manini, T.M., Marsh, A.P., McDermott, M.M., Goodpaster, B.H., Pahor, M., Newman, A.B., & LIFE Study Group. (2017). Effect of physical activity versus health education on physical function, grip strength and mobility. Journal of the American Geriatrics Society, 65(7), 1427–1433. https://doi.org/10.1111/jgs.14804
  39. Sarikaya, P.M., Incel, N.A., Yilmaz, A., & Cimen, O.B. (2017). Effect of hand dominance on functional status and recovery of hand in stroke patients. Science, 6(3), 39-45. https://doi.org/10.11648/j.sjcm.20170603.12
  40. Shiba, J., & Lizarraga, J. (2020). The effects of laterality card training on non-dominant hand grip strength compared to traditional hand grip strengthening exercises. ProQuest Dissertations. Retrieved from https://search.proquest.com/openview/d14677df9d3c3a2d1f3227defc22bc9f/1
  41. Skelton, D.A., Young, A., Greig, C.A., & Malbut, K.E. (1995) Effects of resistance training on strength, power, and selected functional abilities of women aged 75 and older. Journal of the American Geriatrics Society, 43(10), 1081–1087. https://doi.org/10.1111/j.1532-5415.1995.tb07004.x
  42. Szulc, P., Feyt, C., & Chapurlat, R. (2016). High risk of fall, poor physical function, and low grip strength in men with fracture-the STRAMBO study. Journal of Cachexia, Sarcopenia and Muscle, 7(3), 299–311. https://doi.org/10.1002/jcsm.12066
  43. Thomas, E.M., & Sahlberg, M. (2008). The effect of resistance training on handgrip strength in young adults. Isokinetics and Exercise Science, 16(3), 159–165. https://doi.org/10.3233/IES-2008-0307
  44. Tung, H., Chen, K., Chou, C., Belcastro, F., Hsu, H., & Kuo, C. (2023). Acupunch exercise improved muscle mass, hand grip strength, and sleep quality of institutional older adults with probable sarcopenia. Journal of Applied Gerontology, 42(5), 888–97. https://doi.org/10.1177/07334648221141413
  45. Watermeyer, T., Massa, F., Goerdten, J., Stirland, L., Johansson, B., & Muniz-Terrera, G. (2021). Cognitive dispersion predicts grip strength trajectories in men but not women in a sample of the oldest old without dementia. Innovation in Aging, 5(3), igab025. https://doi.org/10.1093/geroni/igab025
  46. Winger, M.E., Caserotti, P., Cauley, J.A., Boudreau, R.M., Piva, S.R., Cawthon, P.M., Orwoll, E.S., Ensrud, K.E., Kado, D.M., Strotmeyer, E.S., & Osteoporotic Fractures in Men (MrOS) Research Group (2023). Lower leg power and grip strength are associated with increased fall injury risk in older men: the osteoporotic fractures in men study. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 78(3), 479–485. https://doi.org/10.1093/gerona/glac122

2025-05-23T11:26:33-05:00June 13th, 2025|Research, Sport Education, Sport Training, Sports Coaching, Sports Exercise Science, Sports Health & Fitness, Sports Medicine|Comments Off on Efficacy of 12-Week Handgrip Strength Training Program Amongst Older Adults: A Pilot Study 
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