Authors: Jason N. Hughes1,Colby B. Jubenville2,Mitchell T. Woltring3, and Helen J. Gray4
1Department of Business, Accounting and Sport Management, Elizabeth City State University
2Department of Health and Human Performance, Middle Tennessee State University
3Department of Health, Kinesiology, and Sport, University of South Alabama
4Department of Experience Industry Management, California Polytechnic State University
Jason Hughes, Ph.D., M.S.
1704 Weeksville Rd.
Elizabeth City, NC 27909
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 interest includes 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 Department Head and Professor of Experience Industry Management at California Polytechnic State University. Her research interests include sport management, youth sport, and pedagogy in sport, leisure, and tourism.
Division-1 athletes’ perceptions of sport specialization as a predictor of perfectionism
Sport specialization is a trend amongst athletes today who are looking to gain an advantage over the competition. However, little research has examined the psychosocial consequences of this trend. One psychological construct that has not been sufficiently investigated regarding its relationship with sports specialization is perfectionism. Perfectionism is a multidimensional personality trait with two higher orders: perfectionistic strivings, and concerns; both of which are associated with adaptive and maladaptive outcomes in sport. Perfectionistic concerns have shown consistent negative associations with processes and outcomes. Perfectionistic strivings results have been inconsistent. The purpose of this study was to examine the previously unexplored relationship between specializing in sport and perfectionism concerns and strivings. Two multiple-hierarchical analyses were performed on a sample of 393 Division-1 NCAA student-athletes (M age = 20.21, SD 1.36) to investigate the level of sport specialization as a predictor of perfectionistic concerns and perfectionistic strivings. Findings indicated that student-athletes who are highly specialized were more likely to predict perfectionistic concerns, whereas moderate and low sport specializers did not have a relationship with perfectionistic concerns. Perfectionistic strivings had no significant relationship with sport specialization.
Key words: perfectionism, perfectionistic concerns, perfectionistic strivings, sport specialization, athletes, athletic development
The traditional view of early sport participation was that it was a child-driven, recreational activity that one participated in for enjoyment. This is no longer the case, as youth sport participation is now parent-driven, highly structured, and consists of deliberate practice with the specific purpose of developing sport-specific skills (6, 22). This emphasis on skill development is ultimately aimed at achieving the highest levels of athletic success in high school and college sport (28) and developed in response to the continuing polarization of successful athletes and the benefits they enjoy (39, 42). As a result, there is a belief amongst coaches, parents, and athletes that specialization is necessary to achieve athletic success. However, many in the field of sports medicine and related fields have raised concerns regarding sport specialization and the potential for increased risk of injury and psychological consequences.
The most accepted definition of sport specialization is “intense, year-round training in a single sport with the exclusion of other sports” (p. 252) (22). Historically, the perception was that to develop a well-rounded athlete needed to engage in sport diversification which is defined as an “athlete sampling multiple sports” (p. 13) (42). Over the past two decades, an increasing number of youth athletes are choosing to specialize in playing one sport at a younger age garnering an influx of attention and raising concerns about the potential ramifications of specializing in a sport. (3, 11, 21, 42).
The decision to specialize in one sport at a young age is made with the hopes of achieving future success in the form of financial assistance such as athletic scholarships and professional contracts, usually at the urging of parents. National Public Radio (2015) indicated that 26% of parents whose children participated in sport had personal dreams of their son or daughter becoming a professional athlete. This increases to 39% for families whose socioeconomic income was less than $50,000 (24). Unfortunately, professional success is unlikely, as roughly one in 168 high school baseball players will get drafted by a Major League Baseball team, and just one in 2,451 men’s high school basketball players will get drafted by a National Basketball Association team (24). Furthermore, data suggests that the success of obtaining financial assistance in the form of a college scholarship is unfavorable. One study highlighted this difficulty for athletes suggesting that just above 2% of high school athletes received college scholarships, while full scholarships were even lower, at 1.2% for girls and 1.1% for boys (28). Even for those receiving an athletic scholarship to play collegiately, the National Collegiate Athletic Association (NCAA) reports that only 0.9% – 9.7% of their athletes will reach the professional ranks depending on their respective sports. The two most popular NCAA sports – college football and college basketball – see only 1.6% and 1.2% of athletes advancing to play professionally (30). Despite the overwhelming data that most athletes will not reach the higher echelons of sport, athletes are still choosing to specialize in a sport with the hopes of achieving collegiate and professional success.
While much of the research on sports specialization is not favorable for the continuance of its practice, some researchers have posited arguments that sports specialization is necessary for the development of elite athletes. One study found that current-elite and ex-elite soccer players ranked higher in deliberate practice and focused more of their time on soccer, as compared to those who were not considered elite athletes who played multiple sports (13). Another study of elite-soccer players expressed that motivation to get better was their primary reason for sport specialization, which increased their overall dedication to the sport as compared to non-elite soccer players (41). Despite some evidence of sport specialization could be necessary for the development of elite athletes, many researchers caution against practicing sport specialization due to concerns around physical and psychological well-being. Researchers have suggested that sport specialization should only be recommended in select sports such as women’s gymnastics, diving, women’s basketball, figure skating, and dance. Sport specialization in these sports is seen as necessary and is encouraged as athletes reach their peak age of performance before their full body maturation (22).
Physical injuries are the most recognized negative consequence of sport specialization, but the negative emotional and psychological consequences are often overlooked and lack epidemiological data (35). One psychological construct that needs further investigating regarding sport specialization is perfectionism. Perfectionism is defined as having “a commitment to exceedingly high standards combined with a tendency to critically appraise performance accomplishments” (14, 19). Perfectionism can be viewed as a multidimensional dispositional personality construct that captures the extent to which individuals both strive for flawlessness in achievement and worry about failing to meet these high standards (12). Contemporary researchers believe perfectionism overlaps a wide domain of ranges and these domains fall in line with two higher order dimensions: perfectionistic concerns and perfectionistic strivings (36). 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 (26). Additionally, perfectionistic concerns are associated with burnout, rumination, fear of failure, amotivation, and performance-avoidance (20). Perfectionistic strivings are associated with self-oriented striving, where one places high goals on oneself intrinsically, and the setting of very high personal performance standards (18).
To date, insufficient research has been found which investigated the effect perfectionism have upon athletes who engage in sport specialization. Thus, this study sets out to investigate this relationship. For this study, two research questions are being assessed. Research question one asked, “what is the relationship between sport specialization and perfectionistic concerns?” The second research question asked,” what is the relationship between sport specialization and perfectionistic strivings?” Each research question assessed 3 hypotheses. For the first research question, it was hypothesized that H1) high sport specialization would be positively associated to perfectionistic concerns, H2) moderate sport specialization would be positively associated to perfectionistic concerns, and H3) that low sport specialization would be negatively associated with perfectionistic concerns. For the second research question, it was hypothesized that H4) that high sport specialization would be negatively associated with perfectionistic strivings, H5) that moderate sport specialization would be negatively associated with perfectionistic strivings, H6) that low sport specialization would be positively associated with perfectionistic strivings. Two multiple-hierarchical regression analyses were conducted, one for each research question.
Additionally, this study wanted to investigate any mediator variables that might that influence the results. Gender was included as a mediator variable as there has been evidence that there are disparities between males and females when it comes to perfectionism. Females tend to rate themselves as being more perfectionistic than males (34). Age was also included because developmental research has shown a negative correlation between perfectionism and an increase in age (25). One study found a negative correlation between perfectionism and an increase in age between current college students and alumnae (25). Previous studies have indicated that the type of sport an athlete plays, individual-sport or team-sport, can be a mediator between psychological constructs in athletes (31). The type of sport was also included as a mediator variable. Previous studies have indicated that the type of sport an athlete plays, individual-sport or team-sport, can be a mediator between psychological constructs in athletes (31). It was found that athletes in individual sports scored higher on depressive symptoms than athletes who participated in team-sports. Additionally, the same study also found that athletes in team-sports had a positive relationship with perfectionism (31).
A total of 393 student-athletes (146 males, 249 females) from Division-1 NCAA institutions participated in this study. Participants ranged in ages of 18-25 years (M = 20.21, SD = 1.36), and competed in 15 overall sports, with the largest numbers coming from swimming (N = 73), soccer (N = 38), and track and field (N = 32). Table 1 and Table 3 provide a full participant breakdown in terms of demographics included in each analysis. Upon approval from the primary researcher’s institutional review board, respondents were recruited to participate in an online survey delivered through Surveymonkey.com. Inclusion criteria for the study were that participants must compete in intercollegiate athletics at a Division-1 NCAA institution at the time of data collection. To reduce the homogeneity of the population, athletes were recruited from different Division-1 schools and different conferences. Athletes were recruited from Massachusetts, Virginia, South Carolina, California, Alabama, Florida, Arkansas, Connecticut, Michigan, Tennessee, and Ohio. Athletes were recruited from every Division-1 conference.
A priori power analysis was conducted before the onset of the study using G*power 3.1.92. The program allows the researcher to specify the type of analysis that will be run as well as the known value needed to compute the power of the desired analysis. Power, by definition, is the ability to find a statistically significant difference when the null hypothesis is false. The power analysis was set to achieve a 95% power level, while the alpha level was set at 0.05 to control for Type I error. Moreover, a small Cohen’s effect size f2 of 0.05 was selected to statistically detect small yet important effect sizes based on the guidelines (.02 small, .15 medium, .35 large) (7). Therefore, with five predictor variables (sport specialization, age, gender, years played, and sport) it was calculated that a sample size of 402 would be needed. The current study had 393 participants which is within proximity of the target goal. For this reason, power was sufficient to be able to detect significant associations if they existed.
In the cases retained for the final analysis (N = 393), 69 participants had more than 1 missing response on the seven-item Likert-scale that measured perfectionism. Out of the 393 participants in the study, 45 of them were missing one item and were included in the final analysis while others were missing more than one item and were excluded. To calculate the missing data for those were who included, expectation maximization algorithm was used. Expectation maximization imputation is available in SPSS software and was used for the analysis.
Expectation Maximization is an iterative procedure in which it uses other variables to impute a value (expectation) that is most likely (maximization). It will re-impute values until it reaches the most likely value.
Expectation Maximization imputations are suggested to be better than mean imputations, especially for regression, because it preserves the relationship with other variables. This approach was deemed appropriate as the missing data for the individual responses were very small (approximately 3%).
Participants completed a demographic questionnaire, a self-perceived sport specialization questionnaire, and a questionnaire of subscales of perfectionistic concerns and perfectionistic strivings.
Multiple measures were utilized to measure perfectionistic striving and perfectionistic concerns, following previous suggestions from Stoeber (36, 37). Hewitt and Flett’s Multidimensional Perfectionism Scale (H-MPS) (19) and Gotwals and Dunn’s Sport Multidimensional Perfectionism Scale (Sport-MPS-2) (17) provided the basis for the present study. As such, components from two perfectionism inventories were combined to reflect a 7-point Likert-Scale. The combined measures reported strong reliability (α =.892), which matched previous reliabilities (17, 19).
Perfectionistic concerns: To accurately access perfectionistic concerns, three subscales were used in the study. Two subscales from the Sport-MPS-2 (17) were used. The eight-item “concerns over mistakes” subscale included questions such as “If I fail in competition, I feel like a failure are a person”. To measure the participants’ feelings of discrepancy between one’s expectations and performance, the six-item “doubts about actions” subscale was used and included questions such as “I usually feel unsure about the adequacy of my pre-competition practices”. Part of Hewitt and Flett’s H-MPS (19) was used to assess the fear of negative social evaluations and comprised of 15 items from the “socially prescribed” perfectionism subscale. This scale included questions such as “People expect nothing less than perfectionism from me”.
Perfectionistic Strivings: Perfectionistic strivings deal with the aspects that are self-oriented striving and the setting of high personal performance standards. To measure perfectionistic strivings, two subscales were used utilized from the Sport Multidimensional Perfectionism Scale (Sport-MPS-2) and the Hewitt & Flett Multidimensional Perfectionism Scale (H-MPS) (19) also. To measure self-oriented perfectionism, the five-item self-oriented perfectionism subscale (e.g., “One of my goals is to be perfect in everything I do”) from the H-HMPS was used. To measure the high professional performance standards, the seven-item personal standards subscale (e.g., “I hate being less than the best at things in my sport.”) from the S-MPS-2 was used. Evidence has been provided to support the internal consistency (H-MPS, α ≥ .79; SMPS, α ≥ .74) of the subscales (8, 17).
To the researchers’ knowledge, only one scale had been used to classify athletes to different levels of sport specialization. Following previously established protocols (3, 23); 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. Developing the three questions from prior research on sport specialization, the questions included items such as “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?” A categorical classification system was used to assess the sport specialization questions (yes = 1, no = 0), with a score of 3 considered high specialization, a score of 2 considered moderate specialization, and a score of 0 or 1 considered low specialization.
Participants were asked additional information to disclose regarding their experiences in sports along with their age and their gender. With the collection of the additional data, five predictor variables were included in the analysis; gender, age, the number of years played, and the specific sport being played. Research regarding gender and perfectionism has shown some disparities between males and females (34). Age was included because some research has shown a discrepancy between perfectionism and age (25). The type of sport was also included as a mediator variable. Previous studies have indicated that the type of sport an athlete plays, individual-sport or team-sport, can be a mediator between psychological constructs in athletes (31).
Descriptive statistics of all the participants and mediator variables for perfectionistic concerns can be found in Table 1. The descriptive statistics for the participants and mediator variables for perfectionistic strivings can be found in Table 2.
Descriptive Statistics of Perfectionistic Concerns, Sport Specialization, Gender, Years Played, and Individual Sport
|Low Sport Specialization||0.05||0.21||18|
|Moderate Sport Specialization||0.42||0.82||83|
|High Sport Specialization||2.23||1.31||292|
|Track & Field||0.99||3.60||6|
Descriptive Statistics of Perfectionistic Strivings, Sport Specialization, Gender, Years Played, and Individual Sport
|Low Sport Specialization||0.05||0.21||19|
|Moderate Sport Specialization||0.42||0.82||83|
|High Sport Specialization||2.23||1.32||291|
|Track & Field||0.99||3.60||32|
Multiple hierarchical regression analyses were used to determine the extent to which sport specialization can predict perfectionistic concerns and perfectionistic strivings. This method was used to minimize within-group error attributable to individual differences (38). Unlike designs that test two different groups of participants or use a matched-pair sampling criterion, within-subject design guarantees that participants in each treatment are identical on a number of characteristics. In the cases retained for the final analysis (N = 393), 69 participants had more than 1 missing response on the seven-item Likert-scale that measured perfectionism. Out of the 393 participants in the study, 45 of them were missing one item and were included in the final analysis while others were missing more than one item and were excluded. To calculate the missing data for those were who included, the expectation maximization imputation included with SPSS was used for the analysis.
To effectively understand the influences that sport specialization might have regarding perfectionism for Division-1 NCAA athletes, the current study utilized multiple-hierarchal regression analyses to determine the extent to which sport specialization can predict perfectionistic concerns and strivings. There are suggested advantages to using a within-subject analysis. The most cited benefit is the minimization of within-group error attributable to individual differences (38). Unlike designs that test two different groups of participants or use a matched-pair sampling criterion, within-subject design guarantees that participants in each treatment are identical on several characteristics.
Results for Perfectionistic Concerns
Multiple linear hierarchal regression results for perfectionistic concerns are presented in Table 2. H1 predicted that perceptions of athletes with higher levels of sport specialization would be positively predict perfectionistic concerns than athletes with higher levels of sport specialization. H1 was supported. High sport specializers were found to be a significant predictor of perfectionistic concerns. Additionally, H3 was supported as low sport specializers who practice sport diversification negatively predicted perfectionistic concerns. H2 was not supported as moderate sport specializers were not a significant predictor of perfectionistic concerns. Overall, the model explained 2% of the variance. Additional findings of the analysis were two predictor variables, gender and the years played, which negatively predicted perfectionistic concerns in the model. The results indicated that the longer an individual played a sport the less likely they were to have perfectionistic concerns. Moreover, the results indicated that males were less likely to have perfectionistic concerns. Further findings in the analysis indicated that athletes who played football, baseball, and golf were more likely to predict displaying perfectionistic concerns.
Analysis shows that in Step I, the entry of Low Sport Specialization, Moderate Sport Specialization, and High Sport Specialization was a significant predictor of perfectionistic concerns, R2 = .02, F (3, 390) = 3.927, p < .05. After Step II, the addition of age was not a not a significant predictor of perfectionistic concerns R2 = .023, ΔR2 = .003, F (1, 390) = 1.182, p > 05. After Step III, the addition of the number of years playing their primary sport was also not a significant predictor of perfectionistic concerns, R2 =. 024, ΔR2 = .002, F (1, 389) = .738, p > .05. In Step IV, the addition of gender was not a significant predictor to the overall model, R2 = .032, ΔR2 = .008, F (1, 388) = 3.059, p > .05. The addition of individual sport in Step V was a significant and the biggest predictor in model with R2 = .093, ΔR2 = .061, F (14, 374) = 1.786, p < .05. The overall model was able to explain 9% of variance in predicting perfectionistic concerns (see Table 3).
The normality assumption was checked by using the corresponding histogram and p-p plot for standardize residuals. The histogram was reasonably identical to the normal distribution curve suggesting the residuals follow a normal distribution and that there is not a violation of the normality assumption. The normality assumption was validated further by checking the p-p plot that showed the residuals approximated a superimposed straight line. The linearity and homoscedasticity of the predictor variables were not compromised as the points appear to scatter randomly and evenly about the line that originates from the mean of the residuals. As a result, depicted a rectangle, therefore, the linearity and homoscedasticity of the regression were indicated (32). Homoscedasticity in the regression means that the variance is the same in the sample and that standard errors are not biased in the test (32).
Results for Perfectionistic Strivings
A multiple linear hierarchal regression was calculated to predict perfectionistic strivings based on sport specialization classification of low specialization, moderate specialization, and high specialization. Predictor variables of age, years played, gender, and the type of sport were also included in the models. The hypotheses regarding research question II were as follows, H4 predicted that perceptions of athletes with higher levels of sport specialization would be negatively associated with perfectionistic strivings than athletes with higher levels of sport specialization. H5 predicted that perceptions of athletes with moderate levels of sport specialization would be negatively associated with perfectionistic strivings. H6 predicted that sport athletes with low sport specialization would be positively associated with perfectionistic strivings. Regarding research question II, it was found that three types of sport specialization; low, moderate, and high were not significant predictors of perfectionistic strivings. Secondary findings of the analysis did however show that the gender of male and age were significant predictors of perfectionistic strivings. Being a male was a predictor of having higher levels of perfectionistic strivings (B = 1.798, β = 1.80), however this only accounts for about 3% variance (ΔR2 =.032) in the model. In addition, it was found that as participants in the study increased in age (B = -.1.05, β = -.149) they would more than likely have less perfectionistic strivings. However, this only accounts for about 1% variance (ΔR2 = .014) (see Table 4).
The results of the F test for ΔR2 were not statically significant at .05 for all levels of sport specialization. F (2, 390) = .532, p > .05. Analysis shows that in Step I, the entry of Moderate Sport Specialization and High Sport Specialization was not significant, R2 = .003, F (2-390) = .532; p >.05 (p = .567). After Step II, the addition of age did improve the predictive ability of the model with R2 = .018, ΔR2 = .015, F (1, 389) = 5.709, p < .05, but the overall predictive model with the addition of age was not significant at p > .05 (p = .074). After Step III, the addition of how many years playing their primary sport did not improve the predictive ability of the equation with R2 = .02, F (1, 388) = 1.124, p > .05 and the overall contribution to the model was not significant, p >.05. The addition of gender in Step IV did significantly improve the predictive ability of the model. While the gender of female was not significant, the gender of male was found to be significant in the predictive ability of the model R2 = .053, F (1, 387) = 13.160, p < .05). In Step V of the model, the inclusion of individual sports did not increase the predictive ability of the model, R2 = .097, F (13, 374) = 1.411, p > .05 (see Table 4).
The normality assumption was again checked by using a histogram and the corresponding p-p plot for standardize residuals. The histogram was reasonably identical to the normal distribution curve suggesting the residuals followed a normal distribution and that there is not a violation of the normality assumption. The p-p plot again showed the residuals approximated a superimposed straight line. The linearity and homoscedasticity of the predictor variables were not comprised as the points appeared to scatter randomly and evenly from the line that originated from the mean of the residuals. As a result, depicted a rectangle, therefore, the linearity and homoscedasticity of the regression were indicated.
The objective of this study was to examine the perception of Division-1 NCAA student-athletes regarding how sport specialization could predict their degree of perfectionism. Secondary objectives were to see what the mediator roles of age, gender, years playing the sport, and the type of sport affect the relationship between perfectionism and sport specialization. The present findings provide further explanation of the risks that are associated with sport specialization. Based on the results of the present study, the findings suggest that there are potential maladaptive consequences regarding perfectionism and specialization.
It was hypothesized that 1) high sport specialization would be positively related to perfectionistic concerns, 2) moderate sport specialization would be positively related to perfectionistic concerns, and 3) low sport specialization would be negatively associated with perfectionistic concerns. The results of the analysis provide support for two of the three hypotheses. The results supported the first hypothesis and third hypotheses. Specifically, those athletes who are highly specialized were more likely to display maladaptive perfectionism. Conversely, athletes who participate in sport diversification were less likely to display maladaptive form of perfectionism. These results are in line with previous research that indicates research that indicates that sport specialization is a maladaptive behavior to engage in with numerous risks with few positive outcomes.
The finding that high sport specialization is significant predictor of perfectionistic concerns is perhaps the most significant finding of the analysis. Based on the results of the current study, negative psychological consequences from maladaptive perfectionism should be included as a potential consequence of sport specialization regarding perfectionistic concerns. This is worrisome as prior research has established that perfectionistic concerns are associated with an array of negative consequences. It has been well established that sport specialization carries many physical consequences and adding the potential for maladaptive perfections further confounds the argument that sport specialization is needed to develop elite athletes. Sport specialization might be more harmful than previously thought.
The maladaptive outcomes of perfectionism are well documented. Regarding sports, the on-field consequences of perfectionistic concerns include burnout, rumination, fear of failure, amotivation, and performance-avoidance (20). Off the field, research has shown potentially dire consequences of perfectionism concerns include suicide, a decline in physical health, fatigue, and early mortality (19, 9, 15, 29). Parents, coaches, and athletes should be aware of the potential consequences that are associated with sport specialization. This study further highlights that sports specialization is potentially a maladaptive behavior with very few positive outcomes and an array of established negative consequences far outweigh the positives. Given the findings that high sport specialization is significantly related to perfectionistic concerns, the current environment of increased sport specialization is particularly concerning.
This study provides a basis for future research regarding sport specialization and perfection. Future research on the effects of sport specialization could look to focus on several areas such as age differences, gender differences, sport differences, team vs. individual sports, and a more longitudinal approach. The present study focused on a very specific age range of collegiate athletes. This study found gender to be a predictor of perfectionistic concerns and perfectionistic strivings. Males were less likely to have perfectionistic concerns as compared to their female counterparts while engaging in more perfectionistic strivings. This dynamic should be explored more purposefully. The type of sport and the team/individual aspects of sports may also have significant impacts on perfectionistic concerns. Lastly, a longitudinal study is needed as the results of this study indicated that the effects of sport specialization on perfectionistic concerns dissipated the longer an athlete played their respective sport.
While the present study contributes to the overall knowledge regarding athletes’ perceptions regarding sport specialization and perfectionism, this study is not without limitations. The population sample included only Division-1 NCAA athletes, which increased the homogeneity of the sample and decreased the variability in the responses in specific ways. Since the athletes in the study were from a Division-1 NCAA school, they could be considered “elite” athletes who have reached some of the highest levels of success an athlete can reach. Given their success, these athletes could be more impervious to the effects of sport specialization and perfectionism as compared to athletes who are younger and have not yet reached their level of success. At the conduction of the study, there was only one scale in the literature being used to classify athletes as being low, medium, or high specializers. Furthermore, a low number of participants in certain sports relative to others should be noted.
Another limitation of this study is the cross-sectional and the retrospective method in which it has been conducted. All obtained data followed from a self-report survey conducted at a single point in time, leading to a limitation in generalization. A longitudinal study would possibly produce different results. In addition, purposive-homogeneous sampling was used for this study. This type of non-probability sampling involves the sample being drawn from a distinct subpopulation. There are many advantages of purposive sampling such as ease of eliminating those who are not suitable, the convenience of identifying appropriate subjects, and perhaps most importantly – the results are expected to be more representative of the population. However, despite these advantages, purposive-homogeneous sampling is not without criticisms and limitations. Purposive-homogeneous sampling can be vulnerable to the selection bias of the researcher. The researchers would like to point out that the aim of this study is not to be generalized to the population but instead focuses primarily on athletes.
Findings from the current study add to the literature but also provide areas to be further studied. Athletes are deciding to specialize in a 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 specializations, both physically and psychologically, before having athletes become specialized. The results of the present study indicate that as specialization increases, susceptibility to maladaptive perfectionism also increases. Athletes should fully be aware of the pitfalls of specializing in a sport before engaging in sport specialization.
Additionally, three sports, golf, baseball, and football were found to be significant predictors of perfectionistic concerns. Future research needs to focus on whether athletes who participate in individual-sport compared to team-sport lead to an increase in perfectionistic concerns. Furthermore, the number of years an athlete played their sport was found to be a significant predictor of perfectionistic concerns. The results of our study suggest that the longer an athlete plays their sport, the less likely they are to have perfectionistic concerns. There might be a few explanations for this occurrence, all of which need to be further investigated. Studies have shown that experience might serve as a buffer against psychological consequences. For example, a study found that senior high school wrestlers scored higher on mental toughness as compared to freshman wrestlers (10). This suggested that maturity and competing increased mental toughness scores, which might explain why the college athletes in this study are more resilient to the effects of perfectionistic concerns. The athletes in this study were Division-1 NCAA athletes who have reached the highest pillars of success which occurs with more experience and playing time than those who do not reach these levels making them more resilient. Another explanation might be that the effects of perfectionism in sport might be contemporary and confined to the time in which an athlete is engaging in sport specialization or diversification. In one study it was found that there was no relationship between the age of specialization and mental toughness in college athletes (5). As in that study, many athletes in this sample are elite athletes who have demonstrated expertise in their field, in congruence with sport diversification and not early specialization. However, since they are now specialized since being at the Division-1 level, they are now experiencing the consequences of specializing with respect to perfectionistic concerns.
APPLICATIONS IN SPORT
Given the vast concerns of researchers regarding the maladaptive outcomes of sport specialization, both physical and psychological, at what point do we question the ethical consequences of sport specialization? If only 2% of athletes ever research elite status, what are the costs of exposing young athletes to the risks of sport specialization when so few reach elite status? Coaches, parents, and other sport practitioners need to discuss setting realistic expectations with their athletes. There are many proven benefits to taking part in sports such as sport participation has been shown to increase an active lifestyle over a lifespan and can help protect mental health in young athletes (32). However, this only occurs if their experience is enjoyable and developmentally appropriate (4). The maladaptive outcomes of sport specialization, both physical and psychological, seem counterproductive to the goal of sport participation as the risks of engaging in sport specialization far outweigh the rewards.
Generally, research shows that athletes who engaged in diversification were more likely to have sporting success. A survey of 376 Division-1 intercollegiate athletes, found that except for swimming, 83% of the college athletes indicated that they had taken part in other sports and that their first sporting experience was in a different sport than their current sport (29). Diversification provides opportunities to develop more skills that will be necessary for athletic success. Among high-level athletes, the greater number of athletic events they engaged in during their developing years (ages 0-12), the less specialized sport training was necessary to learn the high-level skills in their sport (1). It is the opinion of experts that early diversification followed by specialization in later adolescence leads to more enjoyment, fewer injuries, and longer participation (2, 16, 40) which ultimately will be more conducive to overall sport success (22).
This study was designed to be exploratory and 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. Coaches, athletes, and parents need to be aware of all the potential risks and rewards regarding sport specialization.
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