Athlete Perceptions of a Monitoring and Strength and Conditioning Program

Authors: Jacob P Reed(1), Mauro Palmero(2), Kimitake Sato(3), Cheng-Tu Hsieh(4), Michael Stone(3)

(1)Kinesiology, Allied Health, and Human Services
University of Northern Iowa
Cedar Falls, IA 50614

(2)Hospitality Management Department
University of Missouri Columbia
Columbia, MO 65211

(3)Center of Excellence for Sport Science and Coach Education
Department of Exercise and Sport Science
East Tennessee State University
Johnson City, TN 37614

(4)Departmet of Kinesiology
California State University, Chico
Chico, CA 95929

Corresponding Author:
Jacob P. Reed
University of Northern Iowa
203 Wellness and Recreation Center
Cedar Falls, IA 50614
Phone: (319)-271-8090

Athlete Perceptions of a Monitoring and Strength and Conditioning Program

Purpose: The purpose of this investigation was to assess athlete perceptions of a monitoring program.

Methods: Athletes currently participating in the monitoring program were invited to participate. Reliability for the questionnaire and principle components analysis (PCA) were completed in the spring of 2013. To analyze changes throughout the academic year, the questionnaire was administered six times throughout the fall 2013 and spring 2014 semesters.

Results: The questionnaire was considered reliable. PCA revealed a three-component model (KMO = .798, Bartlett’s Test of Sphericity = p < .001) with eigenvalues over one explaining 68.88% of total variance. Statistical differences between pre and later time points were noted for of overall performance, skill, strength, speed, power and understanding of the monitoring protocols. Conclusion: The questionnaire was shown reliable and can be considered for future use. The first component of the PCA revealed that perceptions of overall performance are influenced by perceptions of strength, skill, power, and agreement that testing data reflects performance. Second, aerobic and anaerobic endurance and speed are all highly correlated. Finally, athletes understanding of the program monitoring increased with the return of data. Overall, perceptions of the programs influence the questionnaire components were positive ranging from no different to much better.

Applications in Sport: The athlete monitoring program seems to be a beneficial model for enhancing athlete’s perceptions of certain aspects of performance.

Keywords: Questionnaire, Performance, Assessment, Higher Education

Sport coaches constantly strive for the enhancement of athletic performance. In order to obtain this, coaches must rely on their knowledge and experience. Coach knowledge typically consists of informal interaction with other coaches or a more formal two-three day class or coach education courses which are limited in scope (Gilbert & Trudel, 1999; Stone, Sands, & Stone, 2004). Additionally, these formal courses tend to assume that the coach has some degree of education in the area (Gilbert & Trudel, 1999). In the end, coach education relies heavily on practical experience and sometimes formal education, with the former encompassing the majority (Gilbert & Trudel, 1999; Nash & Sproule, 2009). While this information is valuable, it typically is built with the experience and leadership of their mentors, whose teachings might not be built on scientific evidence. However, recently some teams and coaches are turning toward other professionals in sport (i.e., sport scientists) for this education. Sport scientists are trained professionals usually with an advanced degree in higher education (Master’s or Doctorate). These individuals then provide the coach with scientifically supported information regarding the training of their athletes.

In the United States, many university sport science programs exist. However, these typically focus on pedagogy or exercise science rather than sport science (Stone et al., 2004). Exercise science focuses on exercise and the biological systems it influences. This information is typically derived from exercise science research that generally uses recreationally trained or untrained individuals (Stone et al., 2004). Sport science focuses on the enhancement of sport performance through peer-reviewed research, ideally, which has been conducted on an athletic or elite population. To the authors’ knowledge, the only sport science program in the United States meeting these criteria currently resides at East Tennessee State University (ETSU).

Housed in the department of Sports, Exercise, Recreation and Kinesiology (SERK) and Center of Excellence for Sport Science and Coach Education (CESSCE), this program seeks to develop sport scientists that have education in the enhancement of athletic performance as well as practical application of the methods. The graduate program is designed to offer both master’s and doctoral degrees (“PhD sport physiology & sport performance,” n.d.). What separates ETSU’s department of Sport, Exercise, Recreation, and Kinesiology (SERK) is that the students are provided the opportunity to learn and apply sport science in a real world environment by working within a National Collegiate Athletics Associate (NCAA) Division I athletics program.

Within the CESSCE is the Sport Performance Enhancement Consortium (SPEC). This group consists of experienced sports scientists serving as faculty at ETSU whose goals are to train future sports scientists by forming partnerships with Division I NCAA teams. Via the collaboration between sport scientists, coaches, sports medicine personnel, and SERK faculty, a sport performance enhancement group (SPEG) for each sports team is formed. The goal of each SPEG is to develop a plan to enhance their respective team’s performance. One of these ways is through periodic testing of each individual athlete’s biomotor abilities, fitness qualities, and other factors, termed ‘athlete monitoring’. These tests evaluate athlete’s physical abilities (i.e., strength, power, speed, agility, aerobic and anaerobic endurance) as well as each athlete’s perceptions of their overall well-being. By assessing these variables, the SPEG can obtain objective and subjective information as to how the training process is influencing the biomotor ability of the athlete.

Because of the unique nature of the SPEG, it is important to determine its perceived effectiveness. Wins and losses can serve to measure the effectiveness of a team’s physical preparation. However, it is also crucial to obtain athlete perceptions on individual and team enhancement. Ultimately, if the program is not viewed as a useful and practical source of performance feedback, it is difficult to justify its use. Therefore, the primary purpose of this investigation was to examine the reliability and factor structure of a questionnaire designed to assess athletes’ perceptions of an athlete monitoring program. The second purpose was to test their perceptions of the SPEC over an academic year.

After approval for exempt status from the university IRB committee, NCAA division I athletes were recruited to participate. The final pool included athletes from women’s basketball, men’s and women’s soccer, men’s and women’s tennis, and women’s volleyball, a total of 96 possible participants. Men’s tennis (n = 10) and Women’s Basketball (n = 11) was not available for reliability analysis, resulting in a pool of 75 athletes. Only those participating in the SPEC athlete monitoring program and over the age of 18 were invited to participate.

Table 1

The questionnaire was designed to assess the athlete perceptions of various aspects for the SPEC program. Although the SPEC program collects quantitative data on physiological performance, it is of the interest for those managing the SPEC program to account for these same variables in the eyes of athletes thereby gaining insight on the perceived value they place on the SPEC program. A modified version of the Elite Athlete Self-Description Questionnaire was used to determine athlete perceptions of the monitoring program (Marsh, Hey, Johnson, & Perry, 1997). The constructs of skill, aerobic, anaerobic, and performance were included for use within this questionnaire and worded to meet the question requirements. All questions were self-evident meaning that there is no deception in the wording and that the construct represented is stated within.

The survey implemented was designed to assess nine constructs that relate to the SPEC program. These constructs included overall performance, skill, anaerobic endurance, aerobic endurance, strength, speed, power, SPEC data reflection of performance, and data administration. The descriptive component asked if the participant was over the age of 18, sport participating, sex, and academic year (freshmen, sophomore, junior, senior). Eleven total items were included in the questionnaire. The questions asked the athletes’ perceptions on their overall performance, skill, endurance, repeated sprint ability, physical strength, speed, power, the SPEC data’s reflection of their performance, if they understand why they participate in SPEC testing and monitoring (two separate questions), and if their coach provided them with SPEC collected data throughout the season. The first seven questions used a 5 point Likert-like scale (much worse, worse, no different, better, and much better) to assess the respondents’ perception. The final four questions were also measured via a 5 point Likert-like scale, however, the wording was different: strongly disagree, disagree, neutral, agree, and strongly agree.

Data Collection Procedure
Respondents answered the questionnaires on six separate occasions. The first two occurred during the spring semester at a time in which little to no variation in perceptions or performance occurred due to day to day stressors (such as an active rest period) for the purposes of reliability. After administration of the first questionnaire, the second was given immediately upon after returning the first and completed within 48 hours. Questionnaires three and four were given prior to (before the conference schedule) and after (within two weeks) their competitive seasons. Finally, the fifth and sixth questionnaires were given at the beginning and end of each teams’ offseason. After completing each questionnaire, they were asked to either contact the PI for pick up or return of the document to a specified location. For reliability, 36 paired responses were received out of a possible 75, a 48.00% rate of return. A total of 384 responses were anticipated throughout assessment across the academic year (four testing occasions) with 179 responses received, leaving a 46.65% response rate.

Statistical Analysis
For the purposes of reliability and principle components analysis (PCA), the questionnaire administered in the spring prior to fall competition was used. In order to determine the day to day variation, reliability was assessed via Chronbach’s Alpha. PCA with a Varimax rotated component matrix was run to determine the factor structure of the questionnaire. Performing this test allowed for grouping of the questionnaires and aided in the assessment of the SPEC monitoring program. When determining perceptual changes throughout the academic year, a Kruskal-Wallis test was used with post-hoc analysis consisting of the Mann-Whitney U test on each question. Statistical significance was set at p < 0.05, however, Bonferroni adjusted significance was needed resulting in a standard of p < 0.0125. All data was analyzed using SPSS statistical software (SPSS: An IBM Company, New York, NY). RESULTS
Reliability analysis and PCA were conducted on the responses of thirty-six participants. A Chronbach’s Alpha of 0.84 (p < 0.001, 95% CI 0.81 – 0.87) showed the questionnaire to be reliable. Results from the PCA revealed a three component model of eigenvalues exceeding one. The model explained 68.88% of the variance (30.56%, 23.29%, and 15.03%, respectively). A Kaiser-Meyer-Oklin value of 0.798 and Bartlett’s Test of Sphericity reached statistical significance (p < 0.001), indicated a strong correlation matrix. The rotation allowed for better interpretation of the three components which showed that each question only loaded substantially on a single component (Table 2). With the exception of one (test understanding, 0.577), all questions were above 0.600 and loaded on separate components. Table 2

One hundred seventy-nine instances were used in the analysis of changes through time (preseason = 36, postseason = 59, early offseason = 45, late offseason = 39). A statistically significant difference (p < 0.05) between time points was noted for all questions except aerobic endurance and data return through the Kruskal-Wallis test. Post-hoc tests revealed statistically significant differences between many of the preseason values and the later dates (Table 3). Measurements of effect size are noted in Table 4. Table 4

Table 3

Factor Loadings
A three-factor model was constructed from the PCA based on this reliable questionnaire (Chronbach’s Alpha = 0.84). The first and strongest factor consisted of the questions assessing overall performance, skill, strength, power, and performance reflection. The second included questions regarding aerobic and anaerobic endurance as well as speed. Finally, the third included understanding of monitoring and data return.

In the first factor, the above mentioned loading was not surprising. The SPEC program places high emphasis on developing strength and power. While this is evident in the training programs, it is also communicated to the athletes. They will often ask why they are performing certain exercises which the strength coaches then provide evidence based rationale to their programming. It has often been shown that as an individual increases strength, their jumping, sprinting, and potentially overall performance can increase (Israetel, 2013; Kraska et al., 2009). Based on the data from the current study, it appears that the athletes believe increasing strength and power, improves their perception of overall performance. This implication could potentially influence sporting success, as was suggested in a review of research on self-efficacy beliefs of athletes that showed individuals who have high self-efficacy tend to perform better (Feltz & Lirgg, 2001). Component two loaded with all the running questions. This result indicated that as the athletes perform any type of running, whether it be direct sprint training, intervals or long distance, their perceptions of running in general, followed suit. The practical implication of this is that by training speed, the SPEC personnel can also improve the athlete’s perceptions of endurance and vice versa. Finally, the third component revolved around the athletes’ understanding of monitoring in the SPEC program. In a logical result, it showed that when data is returned to athletes, their understanding of the monitoring program increases. This makes it clear that continuation of SPEC monitoring needs to go hand in hand with a rapid return of data.

Overall Performance
Change throughout the academic year was greatest for overall performance (Table 3). The initial perceptions were 4.28 ± 0.61 indicating a positive influence. However, as time progressed, the initial perceptions dropped below 4.0. This difference, while statistically significant, is not too concerning as the overall perception indicated the athletes perceived the SPEC program had a positive influence on their overall performance. The reason for this decline was possibly due to a decreased time spent with the SPEC personnel and/or a shift in conditioning emphasis during the competitive season. The SPEC personnel and athletes primarily interact in the weight-room and it is traditional that during a competitive season, time in the weight-room is decreased to allow for greater time spent on sport practice. Interestingly though, as time progressed into the offseason, their perceptions did not return to the preseason values. This is most likely due to the absolute difference between a 4 (better) and 5 (much better). Additionally, one of the primary limitations of the study is that individual perception changes could not be assessed over time. It is possible that the exclusion or removal of certain athletes, due to their choice to participate at each time point, could have influenced the outcome. Finally, it is entirely possible that the athletes believed that their teams’ strength and conditioning plan did not correspond with an improvement in overall performance. However, this could be a byproduct of a periodized plan, which is a cornerstone of the SPEC program. The strength and conditioning plan is designed to enhance performance over time, which the SPEC program has been successful at accomplishing (Kavanaugh, 2014; Painter et al., 2012; Sole et al., 2013). As would be expected, this includes higher volumes of strength training further away from competition and lower volumes in-season, allowing for more time spent practicing and sport participation. Anecdotally, some athletes appear to perceive higher training volumes to have an immediate and positive influence on their performance. Thus the lower perceptions at the end of the season make sense as the training volumes are lower than that in the offseason and preseason. While this may be the case, these perceptions do not match performance results obtained from this type of training system found in previous research (Kavanaugh, 2014; Painter et al., 2012; Sole et al., 2013). This hypothesis will serve as a primary explanation for all subsequent questions.

Perceptions of the strength and conditioning program and the influence it has on skill was low, but ranged from no influence to a positive influence. This was statistically different from pre and postseason to the end of the offseason. It is possible that this range indicates a lack of education from the part of the SPEC program on how the programming could influence skill. Specifically, the program is designed to influence the physical qualities of the athletes (strength, power, endurance, etc.). In doing so it is possible that the athlete’s skill may improve, especially if the specific skill is heavily influenced by strength characteristics. For the future, SPEC personnel should include information about the physical qualities necessary for success of the athlete and how the program can influence those factors. However, execution of skill is still heavily based on the athlete and coach.

Aerobic Endurance
Aerobic endurance perceptions were stable at no different to positive influence throughout the academic year. As with the other questions, a down trend is noticeable. However, like skill and overall performance, it is not surprising that this would trend downward towards the end of the offseason. Aerobic endurance should be its best during the season. Once the offseason begins, training typically reverts to a heavier influence on strength training. This would cause the athletes perceptions of time on aerobic endurance training to decrease.

Anaerobic Endurance
The perceived effects on anaerobic endurance was no different to positive across all time points. Preseason perceptions were statistically higher for anaerobic endurance than the postseason and late offseason. Again, the pre- and post- season changes could have occurred because of the decreased time spent with SPEC personnel. It is likely that if the athletes’ questions were worded to reflect the coaches’ influence instead of SPEC personnel, perceptions would increase. This is primarily because of the increased time spent with coaches in practice. Practice in itself is both anaerobic and aerobic in nature, typically consisting of drills or games followed by a rest period. As is stated before, the offseason is spent primarily on training in the weight room. Thus, these perceptions should decrease.

Athletes perceive the strength and conditioning influence on strength to be positive. This is not surprising as developing strength is a primary goal of the training program. Strength is a large component of many tasks associated with sport, such as speed, jumping, hitting, etc (Kraska et al., 2009). By emphasizing strength characteristics the athletes can be better prepared to perform the tasks necessary to their sport, as well as developing a larger work capacity in practice and competition (Aagaard & Andersen, 2010). For the pre- and post-season comparisons, a statistical difference is expected, yet not ideal. The in-season training plan developed by the SPEC personnel revolves around maintenance and fatigue management. It is the ultimate goal to program the absolute minimum training stimulus necessary for strength maintenance while optimizing power. These results indicate that, for the next competitive season, the plan may need to be modified to make up for the perceived decrease in influence on strength. What is interesting is the decrease in strength perception values from pre to late offseason. The late offseason is when the training program perceived influence on strength should be the highest. This might indicate that the SPEC programming is not meeting the athlete’s expectations. However, the difference between preseason (4.56 ± 0.73) and late offseason (4.26 ± 0.82) is small and shows that the athletes’ perception of the strength and conditioning program’s influence on strength is still positive. Finally, these results coincide with the results of the factor analysis. As athletes perceive an increase in their strength, perceived overall performance increases as well. Therefore, it would be a good idea for the SPEC personnel to continue placing heavy influence on strength characteristics throughout the academic year.

In general, athletes perceive the SPEC program to have no influence to a positive influence on speed. The trends throughout the year are slightly different than the other questions. While speed decreased from preseason to late offseason, like many of the others, the athlete’s perceptions also decreased from early offseason to late offseason. Even though one of the main goals of the training program is to improve strength (and thus speed) in the offseason, it seems that the athletes had greater expectations out of the program in terms of improving speed. Although this result does not mean that the SPEC program needs to drastically change their programming, it indicates that the athletes believe a greater emphasis on speed would be beneficial. This could include changing or adding specific programming or simply education on the relationship of strength and speed. It is known that the limiting factors in sprint times are vertical forces and strength (McBride et al., 2009; Wisløff, Castagna, Helgerud, Jones, & Hoff, 2004). While the SPEC personnel know this factor and the athletes are told of strength’s influence on speed, it would be beneficial to reiterate these factors throughout the year. This can be done through education or testing speed at various points.

Perceptions of power were maintained at positive from pre- to early offseason. In the competitive season power is a primary focus of weight training as it is a rate of performing work and can benefit from the lower training volumes that occur. The quicker the athlete can perform work, the more likely they are to perform better. Observing no statistical change in this variable from pre- to postseason is positive. However, a statistical difference is noted from pre to late offseason as with most other variables. In the offseason, exercises focusing directly on power are not necessarily the emphasis of training. While strength is an underlying component of power and thus increasing strength should increase power, this may not be evident to the athletes. Therefore, like speed, it may be beneficial to further educate the athletes on the reasons why certain exercises are performed throughout the year.

Understanding of Monitoring
Overall, the athletes are in agreement that they understand the SPEC testing and monitoring protocols and that their coaches provided them with information regarding their results in the testing and monitoring. Statistical differences were noted for understanding of monitoring from pre to postseason. From a practical standpoint, these differences indicate a slightly decreased understanding. It is possible that the differences from pre to postseason are because the SPEC personnel did not explain the monitoring or that the outcome of the season, whether it be positive or negative, influenced their understanding. For example, if the season did not go as planned they might start to question why some of the monitoring occurs. It is up to the SPEC personnel to reassure the athlete of the rationale behind the monitoring.
The limitations within this study are that only one institution was assessed and a limited population of athletes was surveyed. These limitations can be partially justified by the fact that the SPEC program is unique to ETSU.

Overall, it seems that the SPEC programming are accepted and viewed as positive. The deviations in perceptions over time could be due to the nature of SPEC programming, or by not meeting the expectations of the athletes. Based on the results of the SPEC programming, the program is accomplishing its performance goals (Kavanaugh, 2014; Painter et al., 2012; Sole et al., 2013). Further examination of this population in the future could support or refute these claims.

Sports science is experiencing a renaissance in the United States. Employers are experiencing an increasing demand for sports scientists trained in higher education. Due to the limited options in the United States, these individuals often look overseas for their employees. The SPEC program at ETSU can serve as a successful demonstration of incorporating sports science into higher education in the United States.

There are no financial or non-financial conflicts of interests associated with this investigation. Additionally, no funding was received before, during, and after the completion of this research.

1.Aagaard, P., & Andersen, J. L. (2010). Effects of strength training on endurance capacity in top-level endurance athletes. Scandinavian Journal of Medicine & Science in Sports, 20(s2), 39–47.
2. Feltz, D. L., & Lirgg, C. D. (2001). Self-efficacy beliefs of athletes, teams, and coaches. Handbook of Sport Psychology, 2(2001), 340–361.
3. Gilbert, W., & Trudel, P. (1999). Framing the construction of coaching knowledge in experiential learning theory. Sociology of Sport Online, 2(1).
4. Israetel, M. A. (2013). The interrelationships of fitness characteristics in division 1 athletes (Doctoral Dissertation). East Tennessee State University, Johnson City, TN.
5. Kavanaugh, A. A. (2014). Longitudinal changes in strength and explosive performance characteristics in NCAA division I women’s volleyball athletes (Doctoral Dissertation). East Tennessee State University, Johnson City, TN.
6. Kraska, J. M., Ramsey, M. W., Haff, G. G., Fethke, N., Sands, W. A., Stone, M. E., & Stone, M. H. (2009). Relationship between strength characteristics and unweighted and weighted vertical jump height. International Journal of Sport Physiology and Performance, 4(4), 461–473.
7. Marsh, H. W., Hey, J., Johnson, S., & Perry, C. (1997). Elite athlete self-description questionnaire: Hierarchical confirmatory factor analysis of responses by two distinct groups of elite athletes. International Journal of Sport Psychology, 28(3), 237–258.
8. McBride, J. M., Blow, D., Kirby, T. J., Haines, T. L., Dayne, A. M., & Triplett, N. T. (2009). Relationship between maximal squat strength and five, ten, and forty-yard sprint times. The Journal of Strength & Conditioning Research, 23(6), 1633–1636.
9. Nash, C. S., & Sproule, J. (2009). Career development of expert coaches. International Journal of Sports Science & Coaching, 4(1), 121–138.
10. Painter, K., Haff, G., Ramsey, M., McBride, J., Triplett, T., Sands, W., … Stone, M. (2012). Strength gains: Block versus daily undulating periodization weight training among track and field athletes. International Journal of Sport Physiology and Performance, 7(2), 161–169.
11. PhD sport physiology & sport performance. (n.d.). Retrieved February 8, 2017, from
12. Sole, C. J., Kavanaugh, A. A., Reed, J. P., Israetel, M. A., Devine, L. E., Ramsey, M. W., … Stone, M. H. (2013). The sport performance enhancement group: A five-year analysis of interdisciplinary athlete development. In Conference Papers from the 8th Annual Coaches and Sport Science College December 13-14, 2013 (p. 28). Johnson City, TN.
13. Stone, M. H., Sands, W. A., & Stone, M. E. (2004). The downfall of sports science in the United States. Strength & Conditioning Journal, 26(2), 72–75.
14. Wisløff, U., Castagna, C., Helgerud, J., Jones, R., & Hoff, J. (2004). Strong correlation of maximal squat strength with sprint performance and vertical jump height in elite soccer players. British Journal of Sports Medicine, 38(3), 285–288.

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