Latest Articles
College Choice Factors for Division I Athletes at an Urban University
ABSTRACT
Purpose: Recently there has been much research attention focused on the college and university choice factors of potential student-athletes. Kankey and Quarterman (2007) developed a questionnaire, which was tested on Division I softball players, and advocated for more research utilizing different athlete populations to further analyze college and university choice factors among student athletes. As a result, the purpose of this research is to apply Kankey and Quarterman’s (2007) questionnaire to one athletic department with student athlete respondents from all sports funded by a Division I athletic department in order to ascertain: What factors are important to these Division I athletes when choosing to attend their present school? Methods: Division I student athletes were surveyed regarding the importance of certain factors influencing their decisions to attend this particular urban-serving institution. Online surveys were solicited through sport programs for volunteers. Student athletes took the online survey, which was used to develop an electronic database for analysis. Surveys with missing or skipped information were discarded leaving a sample of 101 respondents (n=101). Results: Statistical analyses indicate the most important choice factor to be the coaching staff. Other important—and highly rated factors—include personal relationships, financially based reasons, and academics/ career development. The least important factors included media related issues, technology outlets, and past coaches. Conclusion: Hossler and Gallagher’s (1987) student choice model is integrated with Symbolic Interactionism in order to understand results. It appears that a variety of factors are important to student athletes, which illustrates the multifaceted identities of student athletes. Applications in Sport: Collegiate sport practitioners and/or coaches working with constrained student development programming and/or recruiting budgets are better able to streamline these processes with a better understanding of student athlete choice factors. Knowing which factors to emphasize during the choice stage of choosing a college/university will better assist urban-serving universities during program development or recruiting.
INTRODUCTION
A sizable proportion of colleges and universities within the United States support athletic opportunities for their respective student bodies (Kankey& Quarterman, 2007). One common notion is those athletic programs supported by colleges/universities are integral to the overall college experience for potential and/or current students. Indeed, Coakley (2007) articulated the common perception that student athletes positively impact universities because sport programs increase student enrollment and revenue generating opportunities. Another potential expense to colleges or universities is the process of bringing those student athletes to campus, which can be a costly venture. Urban serving institutions of higher education tend to have constrained financial resources, which mirror the social inequities of urban public schools (Jordan, 2007). Athletic departments within these institution scan benefit greatly from understanding how to efficiently recruit potential student athletes. Finally, “conducting research regarding college or university choice factors, especially when organized within a social framework,helps both practitioners and academics in understanding the identities of student-athletes by illustrating what is important to them during the recruiting process” (Vermillion, 2010, p. 1). Indeed, previous research identified the need for examining how student athletes view their identities,academic careers, and the factors influencing them to attend specific institutions of higher education. (For example, see Letawsky, Schneider,Pedersen, & Palmer, 2003; Kankey & Quarterman, 2007; Vermillion,2010).
This research focuses exclusively on Division I student athletes in an urban-serving institution and attempts to extend Kankey and Quarterman’s(2007) findings regarding factors influencing the university choice of NCAA Division I softball players by utilizing their questionnaire for student athletes of all sports. As a result, the purpose of this project is to readily identify what college or university factors influence Division I student athletes to attend their present urban-serving schools. To accurately ground this project within the previous literature, a brief background discussion of factors influencing the college or university choice of the general student body, student athletes, and sport specific student athletes is summarized.Vermillion (2010) noted the usefulness of amalgamating social theory with other education theories in order to develop a holistic, interdisciplinary framework for discussing college choice factors with student athletes. As a result,Hossler and Gallaher’s (1987) model, and Symbolic Interactionism (Blumer,1969) are combined in order to explain or describe not only the data collected,but also the results and recommendations.
Background
There has been a relatively constant stream of college and university choice factors research for the last 50 years (for example, see Astin, 1965, Gorman,1976, Kealey & Rockel, 1987, Lourman & Garman, 1995, and Hu &Hossler, 2000). Summarizing this research, several key college or university choice factors—regarding the general student body—have been identified. These key factors include academic reputation of the institution,friendship influences, proximity to family, financial aid availability, the location of the institution, and program availability. Kankey and Quarterman(2007) noted the increase of research being conducted regarding college or university choice factors as related to student athletes. The emerging line of scholarly inquiry includes, but is not limited to, research regardingwomen’s athletics (Nicodemus, 1990), male athletes in general (Fielitz,2001), male, sport-specific athletes (Ulferts, 1992; Kraft & Dickerson,1996), freshmen male athletes (Fortier, 1986), and Division III male athletes and non-athletes (Giese, 1986). Common conclusions from the aforementioned studies and other research indicates the head coach, opportunity for participation, various academic factors and amount of available scholarships are important factors influencing student athletes. However, Letawsky,Schneider, Pedersen, and Palmer (2003) noted while athletic -based factors are important to student athletes’ decisions to attend colleges or universities, non-athletic factors also contribute to the decision to attend apresent college or university. To our knowledge, there has been little to no exploration of college choice factors of student athletes in one athletic department with respondent representation of all athletic programs.Additionally, there has been very little research done examining urban-serving institutions and their respective athletic departments. In order to adequately understand college choice factors and urban serving schools’ athletics, a theoretical framework is needed to guide not only research questions, but also interpretation of the descriptive statistical results.
Conceptual Framework
The original conceptual framework utilized by Kankey and Quarterman (2007)to organize and represent their data and findings was Hossler and Gallaher’s (1987) model. Hossler and Gallaher’s model has also been adapted to better understand this research. Specifically, it is a three-stagemodel that identifies and describes the college selection process of individuals and is composed of three stages: predisposition, search, and choice stages. The predisposition stage is the time when students decide if they want to continue into higher education by pursuing colleges or universities, while the search stage encompasses the individual’s evaluations of college or universities, which includes large amounts of interaction. Finally, the choice stage focuses on the submission of application to a targeted pool of colleges or universities.Regarding sport, Kankey and Quarterman (2007) focused primarily on the last stage within Hossler and Gallagher’s (1987) model, which is when the student athlete develops serious intentions about a select few colleges or universities. The student athlete engages in a cost-benefit analysis in order to determine the positives and negatives of each college or university and attempts to make a sound decision. For student athletes, this stage could encompass not only being recruited, but also critically examining the factors that are the most pertinent to their specific situation and taking official visits. Focusing on the “choice stage” is also salient for this project, which addresses college athletes attending an urban serving institution. Understanding why some student athletes choose to attend one college or university over another competitor is important for understanding student athletes’ educational, athletic, and social motivations to attend institutions of higher education.
Symbolic Interactionism
Vermillion (2010) noted Symbolic Interactionism (SI)—a sociological theory focusing on identity, social interaction, and symbolinterpretation—is easily applied to many areas within the institution of sport. Using a micro level of analysis, SI provides a description or explanation of the constructed reality of spectators, athletes, or coaches(Coakley, 2007). Additionally, Cunningham (2007) noted SI understands how people give meaning to their participation or consumption of daily activities.Recently, SI has been used by a variety of scholars to examine a wide variety of sport-based social dynamics, including student athlete choice factors. Some of this research includes, but is not limited to: understanding sport subcultures and the resulting socialization process of rugby players and rock climbers (Donnelly & Young, 1999); examining the role of athletics in gay or lesbian athletes’ lives (Anderson, 2005); explaining the disproportionate lack of women in sport organization leadership positions(Sartore & Cunningham, 2007); understanding how students interpret and consume indigenous sport imagery (Vermillion, Friedrich, & Holtz, 2010); or examining the college choice factors important for influencing community college softball players to attend their current school (Vermillion, 2010).
SI is composed of three basic assumptions. Hughes and Kroehler (2005)summarize Blumer (1969) and Fine (1993) and stated the following theory tenets:1) we interact with things in our social environment based upon shared meanings, 2) these meanings are not inherent, but rather, are social constructions, and 3) shared meanings are in a perpetual state of change and evolution. Interactions and communication within a specific social environment adheres to the aforementioned assumptions and helps to form an individual’s “constructed reality,” which is an individual’s interpretation of the social world and dynamics around them(Eitzen & Sage, 2009). When combined with Hossler and Gallagher’s(1987) choice model, we are better able to understand the social psychological processes interacting within the decision to attend or not attend a specific urban -serving institution.
Explaining or describing choice factors important to athletes in urban-serving institutions is important by highlighting the social psychological processes associated with the decision to attend a specific institution of higher education. SI’s focus on the “meaning”athletes give to their participation is useful for examining the power the“athlete role” has on not only the identity of the student athlete,but also the decisions that student athlete makes. Stryker (1980) addressed oneof SI’s limitations—lack of a focus on social structure (Ritzer,2000)—by combining SI with role theory. This adapted version of SI identifies the importance of social roles within the lives of individuals,which are forms of social structure. Student athletes, for example, have multiple roles that they “play” throughout the day, including being a student, university representative, son/daughter, sibling, friend, and athlete. Examining the social-psychological process of how impactful these roles are upon the individual in question provides practitioners insight into the programs, services, or infrastructures that should be emphasized during the costly process of student athlete recruitment. As previously noted urban-serving, institutions tend to suffer from constrained fiscal environments, which are similar to those constraints faced by urban public schools (Jordan, 2007). SI’s usefulness lies in the fact it understands individuals are decision-makers, and provides a structured, analytical way for highlighting how the decisions student athletes make impact not only their social environments (Hughes & Kroehler, 2005), but also the colleges oruniversities they attend (Vermillion, 2010).
Significance
This research project is significant in a number of ways. First, there is very little research done examining the choice factors of: 1) all sports (and resulting athletes) in one athletic department, and 2) athletes from an urban-serving institution. The purpose of this research is to address these gaps in the previous literature. Secondly, the research would also be useful to college or university athletic programs. Specifically, the research will help to streamline the recruiting process for many athletic departments—ofsimilar composition—by addressing the most important choice factors for student athletes in these types of schools. As a result, a better and more efficient allocation of recruiting funds may be developed in order to maximize shrinking recruiting budgets. Moreover, this research is particularly timely as athletic departments attempt to build relationships with other university,academic-based programs. If certain academic programs are identified as particularly salient to potential student athletes, then athletic department personnel can work with other academic administrators in order to: 1) bridge the increasing division and distance between academic programs/the campus community and athletic departments, and 2) demonstrate a commitment to a holistic student athlete experience, which includes the social, athletic, and professional/academic development of the student athlete.
Finally, urban-serving institutions, historically, are comprised of student populations that differ from institutions not classified as such. Urban-serving school districts have higher rates of poverty, racial/ethnic diversity, and equalized access to strong community and educational infrastructures (Howey,2008). As Jordan (2007) noted, urban-serving colleges or universities mirror many of the same inequality patterns found in urban, public school districts.As a result, more research is needed in order to understand collegiate athletics within an urban- embedded university context. It can be hypothesized that universities within urban settings—or designated as urban-serving institutions—have athletic departments that must recognize the relatively unique nature of these campus communities, which may manifest itself in unique athletic facilities, programs, and/or recruiting efforts and strategies.
Research Questions
The research question guiding this research was influenced by previous sport-based research centering on college or university choice factors for student athletes. Based upon Hossler and Gallagher’s (1987) model, are cognition of the uniqueness of urban-serving institutions of higher education, and utilized in conjunction with SI’s theoretical influence,the following research questions is posed: Which college and university choice factors are the most influential for having Division I athletes attend their present urban serving institution? That is, what factors are the most important to Division I student athletes when deciding to attend their present school?
METHODOLOGY
Participants
Respondents for the study were selected from the student athlete population of a large, state university located in the southern high plains of the United States. The university is designated as an urban-serving university and is embedded in an urban environment within a predominantly rural state. It is important to note the university is designated as a Division I (formerly known as Division I AAA) by the NCAA. This is the label given to Division I athletic departments that do not fund or field football teams. As a result, the potential survey population is slightly smaller as compared to FBS (FootballBowl Subdivision) or FCS (Football Championship Series) athletic departments,formerly known as Division I A and Division I AA respectively. Surveys we readministered as online surveys and once surveys were completed, responses were automatically entered into a spreadsheet, which was imported into SPSS 17.0 in order to develop an electronic database. Surveys with missing (skipped)questions or ambiguous answers were discarded and not included in the database.While not all student athletes responded fully, there was representation of all athletic programs administered by the athletic department at the time of data collection. After data collection a total of 101 usable surveys were included in the analysis (n=101).
In order to determine the demographics of the respondents, basic questions were asked to determine gender, academic status (freshman, sophomore, junior,and senior), country of origin, race or ethnicity and sport they participated in. The resulting sample included more females than males (65% vs. 35%) and was composed of freshmen (23.2%), sophomores (30.3%), juniors (29.3%), and seniors(17.2%). The majority of respondents listed white as their race/ ethnicity(64.6%) or African-American/Black (30.2%) and their country of origin as the United State (84.5%). Finally, table 1 illustrates the percent of respondents based upon sport.
Table 1
Percent of respondents by sport categories (n=101).
| Sport | Percent (%) | N |
| Baseball | 9.1 | 9 |
| Softball | 6.1 | 6 |
| Women’s Basketball | 10.1 | 10 |
| Men’s Basketball | 5.1 | 5 |
| Volleyball | 10.1 | 10 |
| Men’s track | 11.1 | 11 |
| Women’s track | 24.2 | 24 |
| Men’s golf | 4 | 4 |
| Women’s golf | 3 | 3 |
| Women’s tennis | 4 | 4 |
| Men’s tennis | 4 | 4 |
| Cross Country | 9.1 | 9 |
Measure
The data collection survey consisted of the aforementioned five demographic questions and college choice factors used by Kankey and Quarterman (2007). Permission was obtained by the primary researcher to use the Kankey and Quarterman factor list for additional research and was adapted to this research focusing on Division I student athletes. The possible answer choices regarding the importance of the college choice factors included “extremely important,” “very important,” “moderately important,” “slightly important,” and“unimportant,” which were numerically coded with “extremely important” rating a five (5) while “unimportant” was rated as one (1). As a result, the higher the rating, the more important the college choice factor was to the student athlete.
Procedure
Student athletes were asked by their coaches or athletic program administrators to complete the online survey. Additional follow-up contacts were made to specific programs to ensure that there was student athlete representation from all sponsored sports in the athletic department. Informed consent was done electronically with the disclaimer attached to the electronic version of the survey. Student athlete participation was not mandatory, but it was encouraged. All results are not simply confidential, but also anonymous because a detailed respondent record cannot be tracked or charted in the current electronic database. Surveys were taken by student athletes while coaches and staff were not present to avoid any influence or tainting of respondent self-reports. The gathered statistical information was shared with the athletic department in addition to being used for this research. Electronic survey information, which was saved in spreadsheet format, was imported into SPSS 17.0 for data analysis.
RESULTS
In keeping with Kankey and Quarterman (2007) a descriptive analysis is used to initially describe and identify the college choice factors associated with Division I athletes attending urban-serving institutions. Regarding the research question (what factors are the most important to Division I student athletes when deciding to attend their present school?), initial univariate responses indicate that 87% of the factors presented in this research were at or above the midpoint of the scale (M= 3.00). In addition, almost half of the factors (15 out of 32, or almost 47%) had means over 4.00 with over 70% of respondents rating these factors as ‘extremely’ or ‘very important’ to their choice to attend this urban-serving university. The seven most highly rated factors, which had mean scale scores at or above 4.25,included coaching staff (M=4.68, SD=0.66); amount of financial aid or scholarship offered (M=4.47, SD=078); support services offered to studentathletes (e.g. study hall, tutors, etc…)(M=4.44, SD= 0.74); availability of resources (money, equipment, etc…)(M=4.31, SD=0.75); opportunity to win conference or national championship (M=4.27, SD=0.83); availability of major (M= 4.25, SD=0.94); and social atmosphere of team (M=4.25, SD= 0.88). See table 2.
The means of only three factors were rated below the scale midpoint. These factors included amount of media coverage (M=2.96, SD=1.94); high school coach(M=2.87, SD= 1.44); and team’s website, Facebook, Twitter (M=2.66, SD=1.21). Only about 30% of the respondents rated these three factors as‘extremely’ or ‘very important’ in their decision to attend this particular urban-serving institution and participate in athletics.See table 2.
Table 2
Mean, Standard Deviation, and Percent (%) of Factor Choices Influencing Division I Student Athletes to attend their Urban-serving Institution(n=101).
| Factor | Mean | SD | % rated extremely or very important |
| Coaching staff | 4.68 | 0.66 | 94% |
| Amt of financial aid/scholarship offered | 4.47 | 0.78 | 86.2% |
| Support services offered to student athletes (e.g. study hall, tutors, etc…) | 4.44 | 0.74 | 89.1% |
| Availability of resources (e.g. money, equipment, etc…) | 4.31 | 0.75 | 85.1% |
| Opportunity to win conference or national championship | 4.27 | 0.83 | 83.2% |
| Availability of anticipated major | 4.25 | 0.94 | 84.2% |
| Social atmosphere of team | 4.25 | 0.88 | 81.2% |
| Athletic facilities | 4.21 | 0.83 | 83.2% |
| Career opportunities after graduation | 4.20 | 0.95 | 78.2% |
| Team’s competitive schedule | 4.20 | 0.80 | 84.2% |
| Meeting team’s members | 4.12 | 0.98 | 74.2% |
| Amt of playing time | 4.10 | 1.02 | 77.3% |
| Overall reputation of the college/university | 4.10 | 0.90 | 80.2% |
| Academic reputation of the college/university | 4.10 | 1.00 | 71.2% |
| Team’s overall win/loss record | 4.03 | 0.86 | 73.3% |
| Team’s tradition | 3.89 | 0.85 | 68.3% |
| Location of university | 3.86 | 1.04 | 66.4% |
| Opportunity to play immediately | 3.82 | 1.08 | 59.4% |
| Conference affiliation of team | 3.82 | 0.96 | 61.4% |
| Cost of college/university | 3.76 | 1.26 | 64.3% |
| My parents | 3.76 | 1.37 | 59.5% |
| Housing | 3.66 | 1.04 | 57.5% |
| Campus visit | 3.64 | 1.13 | 62.4% |
| Fan support of the team | 3.60 | 1.12 | 52.5% |
| Social life at the university | 3.54 | 1.13 | 51.5% |
| Campus life at college/university | 3.53 | 1.01 | 48.5% |
| My friends | 3.26 | 1.39 | 46.5% |
| Size of the college/university | 3.24 | 1.10 | 39.6% |
| Team sponsorships (e.g. Nike, Adidas, UnderArmor) | 3.24 | 1.39 | 42.5% |
| Amt of media coverage | 2.96 | 1.24 | 30.7% |
| High school coach | 2.87 | 1.44 | 37.6% |
| Team’s website, Facebook, Twitter | 2.26 | 1.21 | 34.7% |
DISCUSSION
The purpose of this research was to identify the college choice factors mostsalient to Division I athletes attending urban-serving institutions. Table 2highlights the factors that were most readily identified by these studentathletes as impactful and relates to Hossler and Gallagher’s (1987)choice stage. Using symbolic interactionism (SI)—a social psychologicaltheory examining how sports are related to peoples’ choices and identities—may be beneficial for understanding the most and leastimportant factors for student athletes (Vermillion, 2010). As reported bystudent athletes, there are many factors that go into the choice to attend this particular urban-serving institution. Personal or social relationships (e.g.coaching staff, social atmosphere of team), career goals (e.g. support services, availability of major, career opportunities after graduation),finances (e.g. amount of financial aid/scholarship offered), and program success (e.g. opportunity to win conference or national championship) wereself-reported as influencing their decisions. Conversely, media coverage,technology outlets (e.g. website, Facebook, and Twitter), and previous headcoach had little to no impact upon their ultimate decision to attend thisuniversity.
These categories of factors illustrate how multi-faceted student athletes are regarding both their personal and athletic identities. Specifically, SI notes sports are important to an individual’s identity; with this information both academics and collegiate sport practitioners are able tobetter understand motives of student athletes when choosing colleges/universities and athletic departments/programs. In keeping with much previous research (e.g. Kankey & Quarterman, 2007), the importance of relationships—especially with coaches—tops the list of college choice factors. Indeed, Seifried (2006) noted the importance—on manylevels—of coaches within the lives of student athletes. Although the importance of “coaches” is not unexpected, additional results reveal the highly variegated nature of student athletes’ perceptions of themselves.
Athletic-related reasons, such as opportunity to win a conference ornational championships or the availability of resources, are still factors influencing the student athletes in this sample. However, Letawsky et al.(2003) noted the importance of non-athletic factors in deciding on a college/university. Regarding this sample, non-athletic factors appear salient,as well. For example, financial reasons (e.g. financial aid/scholarships) andpreparation for a professional career after sports (e.g. availability of major,support services offered to student athletes, and career opportunities after graduation) all had mean scores above 4.00, with almost 80% of respondents listing these non-athletic factors as ‘extremely’ or ‘very important’ in relationship to their decision to attend their urban-serving university.
Interpreting these findings from an SI framework would focus on the lack of role homogeneity within the sample. That is, these student athletes appear to“see” themselves as having multiple roles, which relates to amultifaceted or holistic identity. As a result, this research is in alignment with Letawsky et al.’s (2003) conclusions that non-athletic factors are important to student athletes, while simultaneously acknowledging that winning and athletic success is important to student athletes. Both of these models,i.e. student athlete development and performance and success, can be promoted effectively during recruiting processes.
CONCLUSION
The purpose of this research was to identify the most important college choice factors regarding Division I student athletes attending urban-serving institutions. Utilizing the college choice factors identified by Kankey and Quarterman (2007) and their analysis as a guide, student athletes were surveyedin an attempt to better understand their motives for attending an urban-serving institution. The research contributes to not only academic scholarship, but also advocates for the integration of social theory into athletic department data management strategies and recruiting. Streamlining the recruiting processis important in a collegiate athletic climate that is fiscally constrained and extremely competitive, especially at the Division I, FBS, and FCS levels.Smaller, less visible sports and/or athletic departments must find ways to become more efficient with student athlete recruitment. Additionally,common sensical or popular notions of funneling money into newer athletic facilities and media or technological outlets do not appear productive for all levels of collegiate sport; they are not a panacea for recruiting barriers nordo they automatically translate into traditional definitions of success. While these highly popular endeavors are important to maintaining a visible athletic department profile, this research hypothesizes—based upon the aforementioned results—they should not be viewed as the most productive recruiting tools. This research has identified how multifaceted student athletes may very well be, and that a commitment to a holistic student development model may be an efficient recruiting tool for student athletes,especially within Division I, urban-serving universities.
Limitations & future research
As with any research, there are limitations that should be identified.Firstly, the university student athlete population that was surveyed did notinclude a football team, which not only decreased the number of potentialsurvey respondents, but also limits the generalizability of the results. Additionally, using a Division I athletic department also decreases thegeneralizability of the research. Future research should extend the college choice factor scales to include FBS and FCS schools. Focusing on urban-serving institutions is a productive endeavor, but more research needs to be doneinvolving the athletic departments in these types of colleges/universities.According the Coalition of Urban Serving Universities, there are almost 50 nationally recognized urban-serving schools (Great cities, great universities,n.d.), many of which fund athletic programs.
Another limitation involves extrapolating group level summaries (such asmeans of college choice factors) to the individualistic level. SI recognizes the importance of group dynamics upon the individual. However, recruiting and the decision to attend one particular university is a decision that ultimately comes down to a single person, as evidenced in Hossler and Gallagher’s(1987) model, which focuses on the individualistic decision. Student athlete recruitment is a dynamic social psychological process that appears to be acombination of many factors. Sole reliance upon the factors identified in this research would be a disservice to not only collegiate sport practitioners, butalso the recruited student athletes.
APPLICATIONS IN SPORT
Division I student athletes see themselves as more than solely athletes;they have many “roles” to play throughout a given day, week,semester, or season. These roles include, but are not limited to: the athleterole (wanting program success), the social role with others (coachrelationships and social atmosphere of the team), and the student role(focusing on academics and preparing for a professional career after sports).It is important for collegiate sport practitioners involved in recruiting torealize that funneling resources exclusively into media/technology outlets orfacilities does not appear to be efficient or productive recruiting tools. Instead, these practitioners during recruiting efforts should focus on:programs for student success, professional preparation opportunities,highlighting the social and personal relationships within their athletic department/program, and programmatic success. The aforementioned focal pointsillustrate not only holistic student athlete development but also present athletic departments an opportunity for increasing campus wide collaborative efforts.
Of particular importance to urban-serving universities and athleticadministrators, the factor “location of the university” had a meanof 3.86 (midpoint of scale, M=3.00) with over 66% of respondents indicating itwas ‘extremely’ or ‘very important’ to them. It could be interpreted—cautiously, of course—that the stigma of the urban environment education as a disadvantage is unfounded and that, to some studentsor majors, the urban-serving mission and context could be perceived as a unique advantage.
REFERENCES
Anderson, E. (2005). In the game: Gay athletes and the cult of masculinity. Albany, NY: State University of New York Press.
Astin, A. W. (1965). College preferences of very able student. Collegeand University, 40(3), 292-297.
Blumer, H. (1969). Symbolic interactionism: Perspective and method.Englewood Cliffs, NJ: Prentice Hall.
Coalition of urban serving universities. (n.d.). Great cities, great universities: Advancing a shared agenda for America’s cities and metroregions. Retrieved fromhttp://www.usucoalition.org/downloads/part1/about_USU.pdf.
Coakley, J. (2007). Sports in society: Issues and controversies.(9th ed.). Boston: McGraw-Hill Higher Education
Cunningham, G. B. (2007). Diversity in sport organizations. Scottsdale, AZ: Holcomb Hathaway Publishers.
Donnelly, P. & Young, K. (1999). Rock climbers and rugby players: Identity construction and confirmation. In J. Coakley & P. Donnelly (Eds.)Inside sports (pp. 67-76). London and New York: Routledge.
Eitzen, S. D. & Sage, G. H. (2009). Sociology of North Americansport. (8th ed.). Boulder, CO: Paradigm Publishers.
Fielitz, L. R. (2001). Factors influencing the student-athletes’decision to attend the United States military academy (Doctoral dissertation,The Pennsylvania State University, State College, PA). Dissertation Abstracts International, 62, 144.
Fine, G. A. (1993). The sad demise, mysterious disappearance, and glorious triumph of symbolic interactionism. Annual Review of Sociology, 19,61-87.
Fortier, R. S. (1986). Freshman football players’ perception offactors influencing their choice of college (Doctoral dissertation, TheUniversity of North Dakota, Grand Fords, ND). Dissertation Abstracts International 48, 111.
Giese, R. F. (1986). A comparison of college choice factors and influential sources of information between division three male athletes and male nonathletes (Doctoral Dissertation, Kent State University, Kent, OH).Dissertation Abstracts International, 47, 169.
Gorman, W. P. (1976). An evaluation of student-attracting methods anduniversity features by attending students. College and University, 51,220-225.
Hossler, D. R. & Gallagher, K. S. (1987). Studying student collegechoice. A three-phase model and implication for policymakers. College and University, 62(3), 207-222.
Howey, K. R. (2008).Toward identifying attributes of urban teachereducation. Retrieved from The University of Cincinnati, The Center forUrban Education (CUE) website:http://www.usucoalition.org/downloads/part4/UrbanTeacher_Preparation_11-14-08.pdf.
Hu, S., & Hossler, D. (2000). Willingness to pay and preference forprivate institutions. Research in Higher Education, 41, 685-701.
Hughes, M. & Kroehler, C. J. (2005). Sociology: The core. (7thed.). Boston: McGraw-Hill Higher Education.
Jordan, S. (2007, July 17). Stop starving our urban public universities.Inside Higher Ed Retrievedhttp://www.insidehighered.com/views/2007/07/17/jordan.
Kankey, K. & Quarterman, J. (2007). Factors influencing the university choice of NCAA division I softball players. The SMART Journal, III(II), 35-49.
Kealy, M., & Rockel, M. L. (19870. Student perceptions of college quality: The influence of college recruitment policies. Journal of HigherEducation, 58(6), 683-703.
Kraft, R. & Dickerson, K. (1996). Influencing the footballprospect’s choice of college: Football-related factors outweigh academicand facility considerations. Coach & Athletic Director, 65,72-74.
Letawsky, N. R., Schneider, R. G., Pedersen, P. M., Palmer, C. J. (2003.)Factors influencing the college selection process of student-athletes: Aretheir factors similar to non-athletes? College Student Journal, 37, 4,604-610.
Lourman, L. D. & Garman, G. (1995). College selectivity and earning.Journal of Labor Economics, 13, 289-308.
Nicodemus, K. A. (1990). Predicting the college choice of the female student-athlete: An application of the linear additive expectancy-value model(Fishbein Model) (Doctoral dissertation, The University of Nebraska, Lincoln,NE). Dissertation Abstracts International, 51, 144.
Ritzer, G. (2000). Sociological theory. (5th ed.). NY:McGraw-Hill.
Sartore, M. L. & Cunningham, G. B. (2007). Explaining theunder-representation of women in leadership positions of sport organizations: Asymbolic interactionist perspective. Quest, 59, 244-266.
Seifried, C. (2006). Examining punishment and discipline: Defending the useof punishment by coaches. Quest, 60, 370-386.
Stryker, S. (1980). Symbolic interactionism: A social structuralversion. Menlo Park, CA: Benjamin/Cummings.
Ulferts, L. (1992). Factors influencing recruitment of collegiate basketballplayers in institutions of higher education in the upper Midwest (Doctoraldissertation, University of North Dakota, Grand Forks, ND). Dissertation Abstracts International, 54(03), 770.
Vermillion, M. (2010). College choice factors influencing community collegesoftball players. Journal of Coaching Education, 3 (1), 1-20.
Vermillion, M., Friedrich, C. & Holtz, L. (2009). Collegestudents’ perceptions of Native American imagery in sport.International Journal of Sport Management, 11,1, 111-140.
Sports Confidence and Critical Incident Intensity After a Brief Application of Emotional Freedom Techniques: A Pilot Study
ABSTRACT
Purpose: To determine whether a single session of EmotionalFreedom Techniques (EFT) could reduce the emotional impact of traumatic memories related to sports performance and lead to increased confidence levels in athletes.
Background: A relationship has been noted in other studies between sports performance and psychological factors such as confidence and anxiety levels. Critical incidents, which are experienced as traumaticmemories, are associated with increased levels of psychological distress acrossa variety of symptom domains. Brief EFT sessions have been demonstrated toimprove sports performance and reduce anxiety.
Methods: Female college athletes (N = 10) withtraumatic memories were assessed on three self-reports and one objectivemeasure (pulse rate). Subjective measures were the State Sport ConfidenceInventory, Subjective Units of Distress (SUD), and the Critical Sport IncidentRecall (CSIR) questionnaire, which measured both emotional and physical formsof distress. Subjects received a single 20-min EFT session. Baseline valueswere obtained, as well as pre-, post-, and 60-day follow-ups.
Results: Significant post-intervention improvements werefound in SUD, for both emotional and physical components of CSIR, and forperformance confidence levels (p = .001). The change in pulse rate wasmarginally significant (p = .087). All participant gains weremaintained on follow-up.
Conclusions: EFT may increase sport confidence levels byreducing the emotional and physical distress associated with the recall ofcritical incidents.
Applications in Sport: A brief application of EFT employedimmediately prior to competition may increase confidence and mediate anxiety
INTRODUCTION
Research investigating the linkage between psychological factors and sportsperformance reveals complicated relationships among anxiety, stress,self-confidence, and achievement. Although researchers have observedsignificantly higher levels of confidence alongside lower levels of cognitiveand somatic anxiety in elite versus non-elite athletes (1,2), or even withinthe same athlete in practice versus competition (3), predicting performancebased on variations in those measures has proven more difficult.
Findings on the relationship between self-confidence and performance havebeen more consistent, with reports of high self-confidence predicting highperformance among a variety of athletes. These include young female gymnasts(4,5), high school long-distance runners (6), singles tennis players (7), andbaseball players (8). Research into the predictive power of anxiety onperformance has yielded less stable results, however. Jones et al. for example(4), found no significant differences between the somatic anxiety ratings givenby high- and low-performing gymnasts; and Sanchez, Boschker, and Llewellyn (9)actually found an inverse relationship: that higher levels of pre-competitionsomatic anxiety in elite male climbers were related to higher performanceduring competition. Whether somatic anxiety improves or harmsathleticperformance may depend on athletes’ perceptions of theiranxiety, that is, whether they regard it as something more likely to befacilitative or debilitative of performance (4,10). Anxiety is also mediated bywhether the athlete is competing in a team or individual sport (11), theperceived level of support provided by a coach (12), and whether the setting isat the athletes’ home venue (13).
This summary of findings suggests that athletes seeking mental conditioningin an effort to improve their performance in sport should look to methods withthe potential to maximize their self-confidence while diminishing the effectsof anxiety (or reorienting the athlete to perceive this anxiety, particularlysomatic anxiety, as facilitative toward performance). Interventions designed totarget these psychological factors have ranged from relaxation-based techniquesto cognitive-behavioral therapy (CBT), and reviews have found them efficacious(14,15). It is worth noting, however, that many of the therapeuticinterventions under examination involved numerous treatment sessions. Twostudies on CBT to improve vertical jump height and free throw percentage inbasketball players prescribed anywhere from 6 to 12 hours oftreatment(16,17)—which while useful as part of an athlete’s long-termtraining regimen is hardly an expedient method for use in high-pressure,competitive situations. The ideal therapy for these situations would be brief,economical, reliable, and easy to administer or self-administer.
These characteristics have led to increased use by athletes of EmotionalFreedom Techniques (EFT). Developed by Craig (18), and referred to elsewhere as“acupressure assisted psychotherapy” (19), thispsychophysiological intervention pairs exposure to a traumatic memory with acognitive element involving self-acceptance. To these established methods itadds a somatic element, in the form of stimulating 12 specific points on thebody. These locations are regarded in traditional Chinese medicine as theendpoints of acupuncture meridians. The EFT client provides a self-assessmentof the degree of emotional distress before and after stimulating these pointswith the fingertips, and repeats the process until the distress is reduced. Theprotocol can be performed in less than a minute.
Published studies have found evidence for the efficacy of EFT in thelong-term reduction of psychological distress (20,21). EFT has been tested fora range of psychological conditions including phobias (22-24), posttraumaticstress disorder (PTSD) (25-28), test anxiety (29,30), and physical symptoms(31,32). EFT remains effective when delivered as an online intervention (31)and when adapted to a group format (33).
To investigate the physiological mechanisms of action of EFT, Church, Yount& Brooks (34) undertook a randomized controlled trial measuring thecortisol levels of 83 participants before and after an hour-long intervention.Cortisol was selected as a target since it is a multi-systemic endocrinehormone, regulating many of the body’s stress-response systems. Pre- andpost cortisol levels were measured for three groups: the first group receivedEFT coaching; the second group received a supportive interview by a therapist,while the third group rested. The study found that psychological symptoms suchas anxiety and depression were significantly improved after EFT when comparedto the other two groups, and that cortisol declined significantly (p <.03). Anxiety in the EFT group declined by 58% (p <.05). Theimprovement in psychological symptoms was significantly associated with thedecline in cortisol, indicating a simultaneous psychological and physiologicaleffect for EFT.
The potential for use of EFT in sports psychology became apparent due topress reports over the last decade began to note its increasing popularityamong baseball, soccer, and basketball players, and among golfers (35-37),though evidence for its effects on performance were largely anecdotal untilChurch (38) undertook a randomized controlled trial to study its impact on freethrow performance and jump height in elite (i.e., Division 1 college)basketball players. Church compared a 15-min EFT intervention with a placebotreatment delivered to performance-matched men’s and women’sbasketball teams. He found that following a 15-min EFT intervention,players’ free throw percentages improved significantly. In a subsequentcritique and re-analysis of Church, Baker (39) argued that Church understatedthe effectof EFT due to the ceiling effect: players with perfect scores couldnot improve more whether they were in the control or experimental groups. Byre-analyzing results for the lowest-scoring athletes, Baker found thatlow-performing players improved disproportionately. A second randomizedcontrolled trial measured EFTs efficacy at improving soccer free kickperformance when compared to a placebo, and also found significant improvement(40).
The present study sets aside the question of performance outcome to look atthe impact of EFT on athletes’ levels of confidence and distress. Itseeks to elucidate the psychological mechanisms underlying the positiveassociation between EFT and improved athletic performance by examiningEFT’s potential for increasing confidence and reducing anxiety. Weexpected that these outcomes would be evidenced in changes in bothpsychological measures, via self-reported levels of confidence and distress,and physiological measures, via recordings of participants’ pulserates.
Method
Participants
Participants were members of a women’s university volleyball team.Permission was obtained from the university’s ethics committee toconduct the study, and all participants signed informed consent forms. Elevenpotential participants were initially assessed for inclusion in the study. Theonly exclusionary criterion was a score of less than 3 on a Likert scale(ranging from 0 = minimal distress to 10 = maximum distress)that assessed participants’ distress when asked to recall either anemotionally troubling memory in which their “team did not win” ortheir “worst experience with a coach.”
One potential participant was excluded based on this criterion. The dataanalysis is therefore based on the recordings for the remaining 10 women.Participants ranged in age from 18 to 21, with a mean age of 19. All hadobtained academic scholarships based on their sports abilities, and 8 hadobtained Most Valued Player status. They had played volleyball prior to thestudy for periods ranging from 6 to 11 years, with a mean value of 9 years, andreported playing between 0 and 6 other sports, with a mean value of 2 othersports.
Design and Intervention
Participants completed the Subjective Units of Distress (SUD) scale, theState Sport Confidence Inventory (SSCI), and the Critical Sport Incident RecallSurvey (CSIR). Assessments were performed at the following intervals: 30 dayspre-intervention, 15 days pre-intervention, immediately pre-, immediatelypost-, and 60 days post-intervention. Participants’ pulse rates werealso measured at these same intervals. Measures are described in detail below.Participants were competing with other teams throughout the assessmentperiod.
The intervention, delivered by a certified EFT practitioner, consisted of a20-min EFT session with each athlete individually. Under thepractitioner’s direction, each participant paired her description of thetraumatic memory (i.e., of her team not winning or of her worst experience witha coach) with a statement of acceptance: for example, “Even thoughI’m angry that my coach embarrassed me by yelling at me in front of theentire team, I fully and completely accept myself.” The practitioner orparticipant then activated the somatic component of the intervention by tappingon the prescribed acupoints (for a thorough description of the EFT tappingsequence and acupoints, see Church & Brooks (41)). After the 20-min sessionwas complete, the participant provided another SUD score.
Measures
Subjective Units of Distress. SUD uses an11-point Likert scale ranging from 0 (minimal distress) to 10(maximum distress) to assess the emotional impact of criticalincidents (42). Increased SUD has been found to be associated with heightenedarousal of the sympathetic nervous system (43). SUD also correlates with heartrate, respiratory rate, and galvanic skin response (44). When interventionslower SUD, physiological signs of stress are also reversed (45).
State Sport Confidence Inventory. The SSCI is a validatedinstrument that asks the question “How confident are you right now aboutcompeting in the upcoming contests?” across 13 categories (46). For eachcategory, athletes report their confidence level on a scale from 1 (lowconfidence) to 8 (high confidence). The SSCI is designed to measure confidencelevels at a defined point in time, such as prior to a future series of athleticevents, and relative to “the most self-confident athlete” theparticipant knows.
Critical Sport Incident Recall Survey. The CSIR wasdeveloped for this study by the second author (47), as a means of assessingPTSD symptoms in athletes, after a literature search determined a lack ofsuitable validated assessments. It measures emotional distress (ECSIR) andphysical distress (PCSIR) associated with the recall of a critical incident. Ithas 16 questions, scored by participants on a scale from 0 (verycomfortable) to 4 (very distressed).
Pulse rate. Participants’ pulse rates were measuredwith the Instapulse 107 (Bio Sign Instruments, Champlain, NY). The Instapulseis a portable handheld device that measures electrocardiogram rhythm anddisplays a four-heartbeat average. We selected the Instapulse as one of theleast invasive methods of obtaining pulse rate values. Athletes held the devicefor 30 seconds while at rest, and the mean of the values obtained was used inthe study.
Statistical Analysis
We conducted paired t tests to compare the first and secondpretests. One participant was missing the second pretest; therefore, wecalculated a mean substitution (mean of the first and third pretest) for thisparticipant. All t tests were nonsignificant; therefore an average ofthe two pretests was calculated and used in subsequent analyses (see Table 1).A general linear models repeated measures analysis of variance was conducted onall dependent variables across four time points: average of the first twopretests, pretest immediately preceding the intervention, posttest, andfollow-up. We then conducted post hoc paired t tests on all significant models.Because of the number of possible comparisons (6), we applied the Bonferronicorrection, setting the alpha level to p < .008 for thepairedt tests.
Table 1. Paired t-test results for first and second pretests.
|
Measure |
First pretest: |
Second pretest: |
t(9) |
p |
|
SUDS |
6.10 (2.4) |
6.00 (1.9) |
0.25 |
.811 |
|
ECSIR |
34.45 (8.0) |
27.20 (5.8) |
-1.0 |
.343 |
|
PCSIR |
27.20 (5.8) |
25.35 (6.3) |
1.26 |
.240 |
|
SSCI |
74.10 (21.6) |
73.0 (19.8) |
0.62 |
.550 |
|
Pulse |
90.50 (13.4) |
102.55 (15.4) |
-2.05 |
.071 |
Note. SUDS = Subjective Units of Distress; ECSIR = emotional distress as measured on the Critical Sport Incident Recall (CSIR) survey; PCSIR = physical distress as measured on the CSIR; SSCI = State Sport Confidence Inventory.
Results
The main effect for time was significant for SUDS, ECSIR, PCSIR, and SSCI(p = .001). Time was marginally significant in the model for pulserate (p = .087). In the post hoc analyses, the pretest average wassignificantly higher than the posttest for SUDS, ECSIR, and PCSIR, suggestingan improvement in these variables. Similarly, the pretest average was lowerthan the posttest for SSCI, indicating an increase in sports confidence. Thepretest average was also significantly different than the follow-up for all ofthe variables, including pulse rate, indicating maintenance of the improvementsobserved at the posttest. Similarly, the pretest immediately prior to theintervention was significantly different than the posttest and the follow-upfor all variables, with the exception of the pulse rate, indicatingan immediateimprovement on these variables following the EFT intervention. There was nodifference between the posttest and the follow-up for any of the dependentvariables. Change data are displayed in Table 2.
Table 2. Change over time.
|
Measure |
Pretest average: |
Immediate pretest: |
Posttest: |
Follow-up: |
F(3, 7) |
p |
|
SUDS |
6.05 (2.1)a |
5.10 (2.4)c |
0.70 (1.6)b,d |
2.30 (1.7)b,d |
28.73 |
.001 |
|
ECSIR |
34.28 (8.0)a |
27.40 (7.0)c |
20.0 (8.8)b,d |
19.80 (7.1)b,d |
11.85 |
.001 |
|
PCSIR |
26.28 (5.6)a |
24.10 (7.2)c |
16.70 (7.4)b,d |
18.70 (7.1)b,d |
11.55 |
.001 |
|
SSCI |
73.55 (20.5)a |
74.60 (20.3)c |
90.70 (15.8)b,d |
87.50 (21.5)b,d |
10.38 |
.001 |
|
Pulse |
96.53 (11.0)e |
91.70 (21.5) |
84.90 (13.8) |
81.30 (9.0)e |
2.43 |
.087 |
Note. Changes between scores denoted “a” and scores denoted “b” yielded reductions that were statistically significant at the p < .003 level; changes between scores denoted “c” and those denoted “d” yielded reductions that were statistically significant at the p < .006 level.
a > b p < .003; c > d p < .006; e > f p = .002.
These findings indicate an immediate positive effect of EFT on the SUDSrating, emotional and physical competition experience ratings (ECSIR, PCSIR),and sports confidence level (SSCI). However, there was no immediate effect onpulse rate. In addition, all significant changes were maintained at thefollow-up, indicating maintenance of the effects observed immediately followingthe intervention. A decrease in the pulse rate was found at the follow-up.However, given that the decrease in pulse rate was nonsignificant immediatelyfollowing the intervention, it is unclear whether the observed difference atthe follow-up can be attributed to the intervention.
Discussion
The present study extends research by Church (38) and Llewellyn (40) to showfurther evidence of the potential of EFT for use by athletes. WhereasChurch’s randomized controlled trial found significant improvement inbasketball free throw performance, and Llewellyn found significant improvementsin soccer free kicks, these were both outcome studies that did not attempt toinvestigate the psychological or physiological mechanisms of action of EFT. Thecurrent pilot study examines a number of plausible psychological mechanisms,and suggests that EFT can maximize athletes’ confidence while reducingthe distress they experience when recalling sport-related trauma. Furthermore,EFT’s effects on confidence and distress were long-lasting, remainingsignificant even 60 days after application of the brief, 20-minintervention. Alarge effect size in a small population receiving a brief intervention isconsistent with a robust treatment effect.
A limitation of the present study is its small sample size, though the useof t tests was designed to mitigate against individual variance. Replication isnecessary in larger populations, with different sports and age groups, and withactive control groups, before these results can be generalized. EFT’slow cost, ease of use, and quick application, argue strongly for its furtherstudy.
We found only a marginally significant effect of EFT on athletes’pulse rates in this study, and therefore, although psychological measuressupported the efficacy of EFT, our single physiological measure provided onlylimited support for our hypothesis. In their study of the effects of EFT onphobias, as measured by behavioral, self-report, and physiological measures,Wells et al. (22) similarly found only marginally significant changes inparticipants’ pulse rates. They noted, however, that this was notuncommon in the arena of behavioral interventions, which “tend to yieldchanges on physiological measures with less regularity than they do onbehavioral and self-report measures” (48, 49).
A similar disparity between the size of physiological and psychologicalmeasures was found in the cortisol study (34). While both cortisol andpsychological distress decreased significantly, a significant effect was notedin psychological measures after testing only 30 subjects. Almost three timesthat number were required to demonstrate significance on the physiologicalmeasure of cortisol. A replication of the present study with a larger N mightsimilarly produce confirmatory data.
Additionally, pulse rate may be too imprecise a measure, since it istypified by rapid fluctuations. Church et al argue that salivary cortisol testsare a more sensitive physiological measure of stress, since cortisol levelsadjust slowly relative to most other hormones and neurotransmitters. Thecircadian cycle of cortisol is stable month after month, and ultradianfluctuations are small. Salivary cortisol assays can elucidate the hormonaleffects of EFT, and by extension its genetic effects as well, since the genesthat code for cortisol must of necessity be expressed in order for cortisollevels to rise. For this reason, a review of the experimental evidence for EFTstates that: “Exposure [and] acupoint treatments modulate, with unusualspeed and power, gene expression for specific as well as systemictherapeuticgains,” (50). Not only does EFT therefore offer sportspsychology a technique that is ripe for exploration; sports psychology offersenergy psychology a fertile field for the further elucidation of itsmechanisms.
Conclusion & Applications in Sport
Because of the complexity of relationships between psychological factors,such as confidence and anxiety, and athletic performance, the challenge forsports psychology is to find interventions that simultaneously improveathletes’ confidence levels, reduce the stress of sport-related trauma,demonstrate efficacy in game-appropriate time frames, and yield measurableimprovements in performance. Although a range of techniques has been assessed,few have demonstrated the results apparent in the preliminary research withEFT. This pilot study found significant improvements in confidence, reductionsin the intensity of sport-related traumatic memories, and reductions inself-reported stress. Further research is required to determine whether theseresults can be replicated in a randomized controlled trial against anactivetreatment group, whether physiological measures correlate reliably withpsychological improvement, and whether EFT demonstrates similar effects whentested with larger sample sizes.
REFERENCES
1. Kim, K. J., Chung, J. W., Park, S., & Shin, J. T. (2009).Psychophysiological stress response during competition between elite andnon-elite Korean junior golfers. International Journal of Sports Medicine,30, 503–508.
2. Robazza, C., & Bortoli, L. (2003). Intensity, idiosyncratic contentand functional impact of performance-related emotions in athletes. Journalof Sports Sciences, 21, 171–189.
3. McKay, J. M., Selig, S. E., Carlson, J. S., & Morris, T. (1997).Psychophysiological stress in elite golfers during practice and competition.Australian Journal of Science and Medicine in Sport, 29,55–61.
4. Jones, G., Swain, A., & Hardy, L. (1993). Intensity and directiondimensions of competitive state anxiety and relationships with performance.Journal of Sports Sciences, 11, 525–532.
5. Tsopani, D., Dallas, G., & Skordilis, E. K. (2011). Competitive stateanxiety and performance in young female rhythmic gymnasts. Perceptual andMotor Skills, 112, 549–560.
6. Martin, J. J., & Gill, D. L. (1991). The relationships amongcompetitive orientation, sport-confidence, self-efficacy, anxiety andperformance. Journal of Sport and Exercise Psychology, 13,149–159.
7. Filaire, E., Alix, D., Ferrand, C., & Verger, M. (2009).Psychophysiological stress in tennis players during the first single match of atournament. Psychoneuroendocrinology, 34, 150–157.
8. Kimbrough, S., DeBolt, L., & Balkin, R. S. (2007). Use of theAthletic Coping Skills Inventory for prediction of performance in collegiatebaseball. The Sport Journal, 10(1).
9. Sanchez, X., Boschker, M. S., & Llewellyn, D. J. (2010).Pre-performance psychological states and performance in an elite climbingcompetition. Scandinavian Journal of Medicine & Science in Sports,20, 356–363.
10. Raglin, J. (1992). Anxiety and sports performance. Exercise andSport Sciences Reviews, 20, 243.
11. Hanton, S., Jones, G., & Mullen, R. (2000). Intensity and directionof competitive state anxiety as interpreted by rugby players and rifleshooters. Perceptual and Motor Skills, 90, 513–521.
12. Ryska, T. A., & Yin, Z. (1999). Testing the buffering hypothesis:Perceptions of coach support and pre-competitive anxiety among male and femalehigh school athletes. Current Psychology, 18(4), 381-392.
13. Jamieson, J. P. (2010). The home field advantage in athletics: Ameta-analysis. Journal of Applied Social Psychology, 40(7),1819–1848.
14. Meyers, A. W., Whelan, J. P., & Murphy, S. M. (1996). Cognitivebehavioral strategies in athletic performance enhancement. Progress inBehavior Modification, 21, 171–189.
15. Weinberg, R. S., & Comar, W. (1994). The effectiveness ofpsychological intervention in competitive sport. Sports Medicine, 18,406–418.
16. Hamilton, S. A., & Fremouw, W. J. (1985).Cognitive–behavioral training for college basketball free-throwperformance. Cognitive Therapy Research, 9, 479–483.
17. Kearns, D. W., & Crossman, J. (1992). Effects of a cognitiveintervention package on the free-throw performance of varsity basketballplayers during practice and competition. Perceptual and Motor Skills,75(3, Pt. 2), 1243–1253.
18. Craig, D. (2008). The EFT manual. Santa Rosa, CA: Energy PsychologyPress.
19. Lane, James R. (2009). The neurochemistry of counterconditioning:Acupressure desensitization in psychotherapy. Energy Psychology: Theory,Research, and Treatment, 1(1), 31–44.
20. Rowe, J. E. (2005). The effects of EFT on long-term psychologicalsymptoms. Counseling and Clinical Psychology, 2, 104–111.
21. Palmer-Hoffman, J., & Brooks, A. J. (2011). Psychological symptomchange after group application of Emotional Freedom Techniques (EFT).Energy Psychology: Theory, Research, and Treatment, 3(1), 33-38.
22. Wells, S., Polglase, K., Andrews, H. B., Carrington, P., & Baker, A.H. (2003). Evaluation of a meridian-based intervention, Emotional FreedomTechniques (EFT), for reducing specific phobias of small animals. Journalof Clinical Psychology, 59, 943–966.
23. Salas, M., Rowe, J., & Brooks, A. J. (2011). The immediate effect ofa brief energy psychology intervention (EFT) on specific phobias: A randomizedcontrolled trial. Explore: The Journal of Science and Healing, 7(3),255-160.
24. Baker, A. H. & Siegel, L. (2010). Emotional Freedom Techniques (EFT)reduces intense fears ; A partial réplication and extension of Wells etal. (2003), Energy Psychology : Theory, Research, and Treatment 2(2),13-30.
25. Karatzias, T., Power, K. Brown, K., McGoldrick, T., Begum, M., Young,J., Loughran, P., Chouliara, Z., & Adams, S. (2011). A controlledcomparison of the effectiveness and efficiency of two psychological therapiesfor post-traumatic stress disorder: EMDR vs. EFT. Journal of Nervous andMental Disease, 199(6), 372–378.
26. Church, D., Piña, O., Reategui, C., & Brooks, A. J. (2012).Single session reduction of the intensity of traumatic memories in abusedadolescents: A randomized controlled trial. Traumatology, in press.
27. Church, D. (2009b). The treatment of combat trauma in veterans using EFT(Emotional Freedom Techniques): A pilot study. Traumatology, 15(4).
28. Church, D., Geronilla, L., & Dinter, I. (2009a). Psychologicalsymptom change in veterans after six sessions of EFT (Emotional FreedomTechniques): An observational study. International Journal of Healing andCaring, 9(1).
29. Benor, D. J., Ledger, K., Touissant, L., Hett, G., & Zaccaro, D.(2009). Pilot study of Emotional Freedom Techniques, Wholistic Hybrid DerivedFrom Eye Movement Desensitization and Reprocessing and Emotional FreedomTechnique, and Cognitive Behavioral Therapy for treatment of test anxiety inuniversity students. Explore, 5, 338–340.
30. Sezgin, N., & Özcan, B. (2009). The effect of ProgressiveMuscular Relaxation and Emotional Freedom Techniques on test anxiety in highschool students: A randomized controlled trial. Energy Psychology: Theory,Research, and Treatment, 1(1), 23-30.
31. Brattberg, G. (2008). Self-administered EFT (Emotional FreedomTechniques) in individuals with fibromyalgia: A randomized trial.Integrative Medicine: A Clinician’s Journal, 7,30–35.
32. Patricia M. Hodge, P. M., & Jurgens, C. Y. (2011). Psychological andphysiological symptoms of psoriasis after group EFT treatment: A pilot study.Energy Psychology: Theory, Research, & Treatment, 3(2), 13-24.
33. Church, D., & Brooks, A. J. (2010). The effect of brief EmotionalFreedom Techniques self-intervention on anxiety, depression, pain, and cravingsin health care workers. Integrative Medicine: A Clinician’s Journal,9, 40–43.
34. Church, D., Yount, G., & Brooks, A. (2012). The effect of EmotionalFreedom Techniques (EFT) on stress biochemistry: A randomized controlled trial.Journal of Nervous and Mental Disease, in press.
35. Achenbach, J. (2006, March 25). Golfers “tap” intopsychology. Golfweek, 25, 60.
36. Bachman, R. (2007, June 18). In Corvallis, suddenly there came atapping. The Oregonian.
37. Rowe, J. (2009). EFT and golf. Bangor, ME: Booklocker.
38. Church, D. (2009b). The effect of EFT (Emotional Freedom Techniques) onathletic performance: A randomized controlled blind trial. Open SportsSciences, 2, 94–99.
39. Baker, A. H. (2010). A re-examination of Church’s (2009) studyinto the effects of Emotional Freedom Techniques (EFT) on basketball free-throwperformance. Energy Psychology: Theory, Research, & Treatment,2(2), 39–44.
40. Llewellyn-Edwards, T., & Llewellyn-Edwards, M. (2012). The effect ofEmotional Freedom Techniques (EFT) on soccer performance. Fidelity: Journalfor the National Council of Psychotherapy, (in press).
41. Church, D., & Brooks, A. J. (2010). Application of Emotional FreedomTechniques. Integrative Medicine: A Clinician’s Journal, 10,46–48.
42. Wolpe, J. (1973). The practice of therapy (2nd ed.). New York, NY:Pergamon Press.
43. Thyer, B. A., Papsdorf, J. D., Davis, R., & Vallecorsa, S. (1984).Autonomic correlates of the Subjective Anxiety Scale. Journal of BehaviorTherapy and Experimental Psychiatry, 15, 3–7.
44. Scheeringa, M. S., Zeanah, C. H., Myers, L., & Putnam, F. (2004).Heart period and variability findings in preschool children with posttraumaticstress symptoms. Biological Psychiatry, 55, 685–691.
45. Wilson, D., Silver, S. M, Covi, W., & Foster, S. (1996). Eyemovement desensitization and reprocessing: Effectiveness and autonomiccorrelates. Journal of Behavior Therapy and Experimental Psychiatry,27, 219–229.
46. Vealey, R. S. (1986). Conceptualization of sport-confidence andcompetitive orientation: Preliminary investigation and instrument development.Journal of Sport Psychology, 8, 221–246.
47. Downs, D. (2005). The Critical Sport Incident Recall Survey.Ursuline College, Pepper Pike, OH.
48. Ost, L.-G. (1991). One-session therapist-directed exposure vs.self-exposure in the treatment of spider phobia. Behavior Therapy, 22,407–422.
49. Turpin, G. (1989). Handbook of clinical psychophysiology. NewYork, NY: Wiley.
50. Feinstein, D., & Church, D. (2010). Modulating gene expressionthrough psychotherapy: The contribution of noninvasive somatic interventions.Review of General Psychology, 14, 283–295. doi:10.1037/a0021252
The Kinematics of the Return of Serve in Tennis: The Role of Anticipatory Information
Abstract
Visual anticipatory information from early periods of ball flight is thought necessary to intercept the ball in many sports. This study analyzed the temporal characteristics of returning a tennis serve by manipulating the amount of visual information available to the receiver. The movements of tennis players receiving ‘serves’ were measured on court. Participants received serves when playing against a ball machine or an actual server during full vision conditions and also during partial vision occlusion (i.e., early ball flight, second third, last third of ball projection). We measured the moment of the receiver’s movement initiation; the back swing duration; and the forward swing duration. There were no consistent differences in these movement characteristics between the ball machine and the server up to the projection speed of 125 km.hr-1. There were differences in the duration of the forward swing during the partial vision conditions. Initiation of the forward swing occurred earlier and the swing duration was increased when the first third of ball flight was occluded. Important anticipatory information about when to initiate the forward swing is present during the first third of ball flight. When receiving moderately fast serves up to 125 km.hr-1, the receiver does not appear to use information from the server’s action to modify the timing of their response.
Physical Self-Perception Profile of Female College Students: Kinesiology Majors vs. Non-Kinesiology Majors
ABSTRACT
The purpose of this study was to compare college student’s Physical Self-Perception Profile (PSPP) (18) scores in female kinesiology majors and non-kinesiology majors. Participants included 68 female kinesiology majors and 88 female non-majors in a mid-sized university. The mean age for the kinesiology majors was 20.8 years with a standard deviation of 2.31 and non-kinesiology majors was 19.7 years with a standard deviation of 3.16. MANOVA results indicated a significant difference between kinesiology majors and non-kinesiology major’s self-perceptions. Results show that kinesiology majors had significant higher self-perceptions of their sports competence, physical condition, physical self-worth, and physical strength. Researchers believe that identifying groups of people with low self-perceptions of theirphysical abilities and implementing strategies to improve these self-perceptions to increase physical activity levels may help in decreasing weight related health issues. This study will aid coaches, teachers, parents, athletic trainers, and health and fitness instructors in assessing individuals who struggle with low self-esteem in relation to their physical abilities and movements. Professionals will be encouraged to provide physical ability support and implement effective strategies to improve self-perceptions in order to increase physical activity levels.
The Mentoring Role of High School Girls’ Basketball Coaches in the Collegiate Recruiting Process
ABSTRACT
This study was designed to determine Louisiana high school girls’ basketball coaches’ perceptions of their roles as mentors; the impact coaches have on choices female athletes make regarding attendance in post-secondary education; the type of information possessed by the coaches to assist in these decisions; and whether the coaches perceived additional training related to collegiate recruiting was needed for coaches. Coaches reported a strong belief in their roles as mentors, have a disparity of beliefs regarding what students will face during the recruiting process and believe additional training would benefits themselves, their peers, and their athletes. It was further concluded a deficiency exists in the level of knowledge possessed by the coaches regarding recruiting rules and eligibility requirements
INTRODUCTION
The opportunities for high school girls’ basketball players to obtain college scholarships are plentiful and competitive. Eleven thousand college scholarships are available across the United States for young female athletes. As specialized teachers, coaches of student-athletes have a tremendous chance to influence and to change the lives of the individual under their charge (Nasir & Hand, 2008). According to the National Collegiate Athletic Association (NCAA), of the females who attend college, roughly 50,000 initially attend as or become student-athletes (2009b). For the student-athlete who attempts to use athleticism as a mechanism to garner assistance for college, the pressure to perform at high levels is a daily fact of life (Lawrence, Harrison, & Stone, 2009).
Lough (2001) examined the coaches’ role as mentors at the college level and how that interaction often drives a career choice by a graduating college student. The role mentors played in the study was significant. Issues such as developing relationships, understanding communication anomalies, and providing visible and connected examples of role models were key components driving college athletes to make significant career choices (Lough, 2001). However, no study could be found that addressed the objectives of this study, namely, the mentoring role of high school girls’ basketball coaches in the collegiate recruiting process.
PURPOSE AND OBJECTIVES
This study examined Louisiana girls’ high school basketball coaches’ perceptions of the mentoring relationship between aspiring basketball players and arguably the person with the most potential to assist the athlete during her collegiate recruiting process: Her high school coach. The objectives were to describe: (1) the coaches’ personal and demographic characteristics; (2) the coaches’ estimates of the collegiate athletic opportunities afforded to their female basketball players; (3) the coaches’ knowledge of academic standards and recruiting requirements for entry into collegiate athletics into the two primary organizations for collegiate basketball, the NCAA and National Association of Intercollegiate Athletics (NAIA); (4) the coaches’ perceptions of their role as mentor fortheir female high school athletes; (5) the coaches’ perceptions regarding the collegiate environment that student-athletes may encounter; and (6) the coaches’ perception regarding whether additional training is needed to strengthen the coaches’ knowledge of collegiate recruiting rules.
THEORETICAL/CONCEPTUAL FRAMEWORK
Kram’s mentor role theory (1985) provided the framework for this study. Kram indicated that mentoring involved a relationship that enriches individual progress and growth. She indicated that mentoring is comprised of either psychosocial or career components. The psychosocial functions build competence, effectiveness, and identity in the professional roles of mentors and mentees in areas such as role modeling, acceptance, confirmation, friendship, and counseling (Kram, 1985). Kram delineated four sub-areas within the career/professional aspect of the relationship: Exposure and visibility; sponsorship; protection; and coaching. Kram maintained that the relationship increased in benefit to the mentee as the mentor provided more of these functions. Mentoring is not a rigid relationship – mentors may be partially orcompletely meeting the mentor’s needs (Ragins & Cotton, 1999). Mentoring may have a delayed rather than immediate impact and the benefits may be realized over an extended period of time (Kram).
Ragins and Kram (2007) addressed the necessity of more research into the area of the “rising star” effect in a mentor-mentee relationship. In this study, we examined the recruitable athlete who is, in fact, the “rising star” the high school coach mentors on a periodic basis. With the evolved framework of Ragins and Kram (2007) firmly in mind, we examined the perception that the mentor (coach) has in terms of what he or she should be providing to the mentee.
Kram (1985) delineated four stages of the mentee-mentor relationship: Invitation, cultivation, separation, and redefinition. Kram’s theory relates to a 3-8 year relationship between adult professionals. Though our study relates to the relationship between an adult and mid to late teenagers (15-18 year old), the framework is similar. The Kram framework is applicable to the evolving relationship between the coach and his or her athlete who is being recruited to play at the collegiate level.
RELATED LITERATURE
The high school girls’ basketball coach is the focus of this research. The coach stands at the cross roads between the student-athlete and the college and a potentially life altering decision for a young athlete. The coach’s knowledge and perception of their role are critical for the student-athlete.
Coach Behavior and Immediacy
The coach’s influence on the athlete and the interaction between the coach and the athlete is the undergirding aspect in need of exploration. Turman’s (2008) study of the phenomenon of whether the coach’s verbal immediacy had an effect on both the individual and on the team identified a definitive link and a predictor of the satisfaction of the athlete both with the program (team) and with the coach. Turman (2003) also examined the amount of time players spent with and in close physical proximity to a coach. Though the focus of the study was on verbal and non-verbal immediacies, the extrapolation to the coach’s influence is unmistaken.
Donohue, Miller, Crammer, Cross, and Covassin (2007) highlighted the importance of the influence of the coach on the athlete. While the study had a four-pronged approach for measurement (i.e., looking at relationships with teammates, families, peers, and coaches), the primary outcome in relation to this study was the apparent dissatisfaction that a significant number of student-athletes have with their relationships with their coaches. Data indicated a wide area of strengths and weaknesses in the various relationships, but poor relationships with and among coaches are problematic.
Jowett (2005) chronicled a multi-faceted relationship between the coach and the athlete with the broad issue of behavior and interpersonal interactions at the core. Three schools of thought are provided in terms of the level of and depth of the relationship as they relate to the behavior of the coach: Effective versus ineffective relationships; successful versus unsuccessful relationships; and helping relationships. While athletics by its nature is “win oriented,” Jowett (2005) described a level of success that goes to developing a relationship that is both helpful to the coach and to the student.
What Is at Stake?
In addition to the intrinsic reward of earning an athletic scholarship, a great deal of costs and future earnings are also at stake for the student-athlete and within the power of influence by the coach. According to the U.S. government, the average per year cost in an average four-year college is approximately $10,000 per year. Private and some high prestige public institutions cost much more. In the near term, what is at stake is worth an average of $40,000 per student-athlete who earns a full scholarship (U.S. Department of State, 2009).
In the long term, the average lifetime earnings for a college graduate are $1.3 million more than the earnings of an average high school graduate. So, in addition to the near term cost of paying for an education, the college graduate has a better opportunity to earn higher life-time earnings than someone who does not attend college (University of Wisconsin-River Falls, 2009).
College Coaches: What Are They Seeking?
Possibly one of the most critical pieces of information a high school coach can know and be prepared to pass on to student-athletes is what a college coach is looking for when they are recruiting athletes. These traits include motivation/competitiveness, “coachability” (referring to an athlete’s propensity to receive and use instruction in a positive manner), the development potential of the athlete, the influence of the coach, influence of one’s teammates, and miscellaneous contextual influences as identified by Giacobbi et al. (2002) as key elements college coaches and recruiters are seeking in their scholarship athletes.
While these traits may seem like “common sense,” their existence and prevalence need to be communicated to the potential recruit by someone. The question arises as to “how” the future college athlete would know these things intrinsically? The rational assumption is someone would have to impart this knowledge and the ensuing rational step is that the high school coach is the most likely candidate to impart this information to the athlete (Lawrence et al., 2009).
Academic Preparation: Necessity of Preparation and Role of the Coach
A truly critical reality a coach should prepare students for is the rigor of academics at the collegiate level. Though the role of the coach is to prepare a student-athlete for competition at the high school level, this paper has established the fact the massive volume of time spent with the student-athlete affords the coach an unparalleled opportunity to provide both guidance and wisdom in terms of telling the student-athlete what life will be like once she leaves the friendly and comfortable confines of the high school environment.
The literature described in the next few paragraphs provides some startling data and anecdotal but believable stories of experiences of two high school students, Nate Miles and, Bryce Brown, upon reaching the collegiate level. A glaring missing piece in the equation is the role or lack of role high school coaches had in these students’ lives as they prepared to make critical decisions and in the terminal phase of high school as the student-athletes prepared for entry into college.
Thamel (2011) reported on the case of Nate Miles, a prized male recruit who lived an odyssey of an existence as a high school student. The young man who was the focus of the story reportedly moved five times during high school, mostly at the urging of “agent” type personnel who tried to convince the young man he had a great future as a collegiate and professional basketball player. Though Mr. Miles was a great player, the “whole person” concept of a solid student, solid person did not exist, and his path was shortened and blunted because of probable outside influences. The non-existence of a high school coach and mentor to guide the young man through these complicated waters is a gaping hole in the article and the story about a lost opportunity.
Evans and Thamel (2009) also reported on a case of a high profile high school football recruit who had his college career choices altered or denied because of his association with someone who was reportedly acting as his agent. Bryce Brown, a highly prized football player from Kansas had doors closed for him on more than one occasion when his association with a recruiting service raised questions regarding his eligibility. Upon his graduation from high school, Brown appeared to be en route to the University of Miami to play running back for the Miami Hurricanes. This association never materialized because of Brown’s association with a recruiting service. Though not related to basketball per se, the question immediately arises as to if this unfortunate route could have been diverted had Brown been influenced or led bya strong mentor and coach in his high school.
While the specifics of the cases are interesting, the implied lack of information provided to Mr. Brown and Mr. Miles are an indictment of an entire culture that develops around athletes. At the very crux and beginning of this process could be the influences of the high school coaches who guided these young people and helped prepare them for this eventuality.
A contrarian view was provided by Aries, McCarthy, Salovey, and Banaji in their 2009 study of over 1,100 non-athletes and over 400 athletes at two northeastern U.S. colleges. A review of athletes entering these colleges indicated while many entered college with lower academic credentials than their purely academic counterparts, the athletes performed at the norm across the time span of a college career, meaning they more or less achieved the grades and success the over 1,100 non-athlete peers achieved, as measured by entry expectations. In brief, data gathered indicated athletes performed at a level during college that was commensurate with their entry ACT/SAT scores and high school grade point averages. The point reverts back to the information the student-athlete has when she enters college: A coach or some other mentorshould be prepared to provide the student-athlete with this type of information and to make the student-athlete aware of the expectation for academic performance at the collegiate level. The article did not raise the question or influence of the coach or mentor who could have prepared the students for the eventualities of the college experience.
In a study similar to Adler and Adler’s earlier (1985) study, Horton (2009) drew some interesting conclusions based on a national qualitative study of 17 junior college athletes. The application to this study is compelling. Horton highlighted a perception at the junior college level that coaches and administrators were important both in academics and athletics. He emphasized the need for strong involvement from the academic side to support the athletic side and summarized the perceptions of students regarding the importance of academics and the faculty apparatus for the junior college student. Many of the issues faced and related in earlier literature citations were related by the students in Horton’s (2009) study, undergirding the assumption that preparation is the key for success in the post high schoollearning environment.
Harrison et al. (2009) described the perceptions of 88 male and female athletes on what would happen to them academically at the collegiate level. The study predicted and data affirmed that females at the collegiate level performed more poorly after their academic and athletic identities were linked by personnel on the campus. The inferred interpretation is these students were probably unaware of the pressures from academia that would become realities at the college level above and beyond which they found at the high school level. Oftentimes, students can be put on pedestals as high school athletes and given a pass or not have to worry about performing at the high school level (Stevens, 2006).
Though negative inputs and things to be “aware” of have made up the review of literature to this point, it should be noted that the inputs provided by a coach can not only help a student-athlete avoid bad things, but it can help a student-athlete understand some things that will work to her advantage during the recruiting process. Harrison et al. (2009) conducted an investigation of issues related to the recruiting of high profile athletes which produced some remarkable results. Though the survey was primarily aimed at high profile, African American male athletes, data was collected that related to and is relevant to the recruiting of female athletes.
Harrison et al.’s (2009) study codified a perception that many have suspected or observed casually through the years, primarily that prized recruits are given ‘red carpet’ or preferential treatment in the recruiting process, especially when the athlete shows up on campus for an official or unofficial visit. While this may be true, the knowledge of this reality could be easily used to the advantage of the student-athlete who desires entry into a more high profile or exclusive college. Phillips (2009) also addressed this subject and found preferential treatment for student-athletes in Alabama.
The Recruitment Process: Potential for Confusion
Lopez (1998) described the complexities and intensities of the recruitment process in a 1998 feature entitled Full Court Press. The experiences of a small number of highly recruited athletes are explained and chronicled. The details of the complexities of being recruited incessantly were described in the article as almost a warning to the parents, students, and coaches who will be on the receiving end of the process. The article described massive volumes of letters, phone calls, and the presence of coaches and scouting directors at events during the summer after a junior year and during the athlete’s senior year.
Along these same lines, Klungseth (2005) crafted an article which summarized the five most important recruiting rules a high school coach should know. Though broad in nature and covering overall NCAA rules, it does provide important details for basketball coaches. The article provides a concise overview of information high school coaches should be appraised of with regards to propriety and legality (in terms of the NCAA) during the recruiting process. The five items, while seemingly “common sense”, have acute and subtle meanings and definitions within the parameters of the NCAA guidelines. The rules and their applicability are the types of things that coaches should be fully apprised of if the day arrives when they have a recruitable athlete at their high school. Specifically, the rules/areas of concern listedare (1) limits on phone calls and contacts; (2) representatives of athletic interests; (3) offers and inducements; (4) official visits; and (5) national letters of intent. Within each of the five areas, more specific, sport specific rules are outlined and delineated. Though the information is simple on the face, the overlapping nature of issues such as school year guidelines (i.e., what happens during a junior year versus a senior year) are spelled out, sport specific rules are delineated, and references to NCAA publications are also provided.
The information relayed in the article is critical, but the question the article raises is how broadly is this information disseminated? How many high school coaches across the nation and across the state are aware of these specifics? Do coaches know the ramifications of recruiting guideline violations? Are coaches prepared to guide students through this complicated process?
Necessity for Enhanced Training, Certification or Mentorship
A key component of the study is to determine whether additional training is necessary for coaches. Review of the literature found no direct recommendations or studies tied to this train of thought. However, some studies have been conducted which broadly address the need for training and certification.
Maetozo (1971) published a series of essays addressing the need for certification of high school and junior high school coaches. He addressed the issue from the perspective of the need for standards in hiring and employing coaches. Several conclusions were drawn regarding the necessity of bringing in qualified individuals to lead athletes, with the primary conclusion being that states should consider establishment of certification programs to ensure qualified and competent individuals are hired as coaches. Outlines were provided as recommendations for states to use in implementation and statements were made that “several states” had initiated the programs, but the states were not delineated. It should be noted that the college recruiting process was not mentioned whatsoever in this article. Also, no evidencewas available in reviewing literature that any national or cohesive state certification programs had been adopted.
Bloom, Durand-Bush, Schinke, and Salmela (1998) addressed the issue of mentoring across a wide girth of sports in the country. As with the Maetozo study, a broad brush was used in the approach, but general applicability can be drawn. The key issue of coaches mentoring athletes was addressed and at length, with conclusions drawn regarding the necessity and benefit for the athlete. Of note, however, was that the authors highlighted a possible need for formalized mentoring programs.
Deficiencies/Limitations in Literature
There appears to be a significant gap in both the research conducted and the scholarly articles published in the areas of demographics of college athletes. Deficiencies were also noted in the areas of characterizations and analyses of coaches. Searches were conducted to characterize and codify the experience levels of coaches across the nation, and little was found. We sought to analyze the level of involvement and mentoring done by coaches with experience levels of coaches being held as independent variable, but little was uncovered in the review of literature. Additionally, we sought to uncover data on knowledge of coaches regarding recruiting rules and entry requirements for college-bound athletes, but little was found.
METHOD
The target and accessible population for this study was defined as all head coaches of girls’ basketball teams in Louisiana whose schools are members of the High School Athletic Association (HSAA). A random sample was drawn of head coaches of girls’ basketball teams in the state whose host/sponsor schools were members of the association in the Fall during the 2010-2011 academic school year. The minimum returned sample size (n = 119) was determined based on Cochran’s Sample Size Formula (Snedecor & Cochran, 1988). Since a return rate as low as 40% was anticipated, the sample size for the study was set at 224. No instrument which met the needs of the study could be located in the research literature; therefore, an instrument was developed by the research team that addressed the objectives of the study.Embedded within the instrument was an information inventory which measured coach perceptions and knowledge bases.
DATA COLLECTION
A multiple-phase approach was employed to collect data. The sample for the study was randomly selected from a master list of coaches in the state obtained from the state HSAA. The list consisted of coaches’ names, schools, physical mail addresses and electronic mail (email) addresses for each coach. We then proceeded with the pre-determined contact procedures. Two data collections letters with instruments were sent to the sample. For both mailed data collections, notification emails were transmitted to the sample by the research team as recommended by Kent and Turner (2003). Also in each instance, we sought and received the assistance of highly respected coaches who sent an e-mail message to all coaches in the research sample in which they endorsed the concept and encouraged participation in the project. In addition,in the second mailing, we included a single, dollar bill as an incentive and to incite additional attention to our survey packet on the part of potential respondents.
Personalized follow up phone calls to a random sample of non respondents were conducted to determine if the mail respondents were representative of the population as recommended by Gall, Gall, and Borg (2003). Twenty six (n=26) coaches in the random sample of 50 non-respondents returned the questionnaire. Independent samples t-tests were used to compare the means for key variables for the responses received during the telephone follow-up to those received by mail as recommended by Gall, Gall, and Borg (2003). No significant differences existed in the responses. Since no significant differences existed between the mail and telephone follow-up responses, it was concluded that the responses appeared to accurately represent the population of head girls’ high school basketball coaches in the state. The mail responses werecombined with the responses received as a result of the telephone follow-up for further analyses. The final response rate was 128 (57.14%) out of the 224 coaches in the random sample and this number exceeded the minimum of 119 responses required for the study.
RESULTS AND DISCUSSION
In data related to the first research objective, we discovered the population of coaches in the surveyed state was generally white, male, educated, and experienced. Over half (56%) of the head coaches in the state were male, 72% were Caucasian, the average head coach had 8.5 years of experience as a head coach, 15.2 years as a coach and 14.9 years as a classroom teacher. Slightly over two-thirds of the coaches (64%) reported having a bachelor’s degree as their highest level of education.
In the second objective, coaches in the state reported an average of 8.0 students during their career that had been recruited to play college basketball. We clarified the meaning of “being recruited” as a student-athlete receiving a letter, email, phone call or other direct interest by a NCAA or NAIA college or university. Further, the coaches reported 4.4 of their players having signed national letters of intent to play college basketball. Most of the coaches (76%) had at least one player who had been recruited during their career. However, only 25% of coaches reported having 10 or more players who had been recruited during the coaches’ career and 11% reported having 10 or more players who had signed national letters of intent to play at the collegiate level.
Of note was the relative scarcity of coaches having athletes who had been recruited. On the surface, one athlete per year who is recruited and each coach averages one every other year that signs a letter of intent or gains a scholarship, which seems like a fairly frequent occurrence. However, given the volume of students a teacher has in a classroom environment throughout the year or on a single or multiple sports teams, a single athlete every year or one every other year seems like a fairly rare occurrence.
In the third objective, the study also sought to describe the level of knowledge possessed by coaches regarding academic standards and requirements for entry into collegiate athletics in the two, primary playing organizations for collegiate basketball, the NCAA and NAIA (see Table 1). This was accomplished by administering a 10 question Information Inventory of basic entry and recruiting rules for athletes ascending into the two types of institutions. The mean score on the 10 question inventory was 5.52 (SD=1.88), suggesting the population of coaches in the state has some knowledge of entry and recruiting rules in the NCAA and NAIA, but gaps exist across the domain of institution types and playing levels. All items possessed strong item discrimination power according to the standards proposed by Bott (1996).
Over half of the coaches correctly answered questions related to the NCAA Division I entry and requirements. Responses indicated very strong understanding of ACT and grade point average requirements (81.3%) and a strong understanding of core curriculum requirements (64.8%). They also demonstrated a solid, consistent knowledge of recruiting and contact requirements and limitations (62.5% & 69.5%). The fact that all four questions directly related to Division I requirements had a majority of coaches answer correctly seems to indicate knowledge is more widely disseminated or there is more interest in those requirements than in other playing institutions.
Coaches were less familiar with Division II, Division III and NAIA requirements. For the three questions related to Division II, the participants correctly answered over 60% of the time for only one of the three questions and that instance was an overlapping question that was also applicable to Division I (types of communication that may not be used). In questions strictly dedicated to Division II, coaches answered correctly 32.8% of the time when asked about entry requirements (number of core courses required) and 56.3% of the time when asked about grade and ACT requirements. This deficiency was a stark drop off from the higher number of correct answers for questions related for Division I schools. Similar, if not more striking contrasts were drawn in certain areas related to Division III and NAIA requirements. Questionsrelated to Division III and NAIA recruiting rules registered responses as low as 21.9% and 30%.
The fourth objective sought to describe the coaches’ perceptions regarding their role in guiding and mentoring recruitable athletes under their tutelage (see Table 2). A four point, Likert-type scale was used to measure the coach’s perception of his role as a mentor to recruitable athletes. The Cronbach’s alpha for the scale was .88, which indicates the scale possessed extensive reliability (Robinson et al., 1991). Coaches gave their highest ratings to three questions: “I should be able to explain what it takes to become a recruitable athlete” (M = 3.74); “I should be a mentor to my recruitable players” (M = 3.71); and “I should assist my recruitable athletes in being prepared for the rigors of the college academic as well as athletic environment” (M = 3.56).Although the coaches still agreed with this item, the lowest rated item was “I should help recruitable athletes make wise life decisions such as choosing the correct college” (M = 3.713.22). Data related to this objective are found in Table 2.
The sixth objective was to measure perceptions with regard to whether new or additional training was considered necessary in terms of preparing or enhancing the coach’s knowledge base in recruiting related activities. As with the fifth objective, a Likert-type scale was used to measure the coach’s perception of whether new or enhanced training or certification would be beneficial to the coaches in general, to new coaches specifically, to the individual coach or to students in the coach’s school. The Cronbach’s alpha for the scale was .88, which indicates the scale possessed exemplary reliability (Robinson et al., 1991).
The coaches measured consistently in favor of enhanced training or certification in this section of the instrument. The coaches agreed with all five items in this scale. The lowest rated item was, “Additional certification or training requirements for high school coaches are necessary to ensure entry level coaches have the knowledge they need about the college recruiting process prior to entering a coaching position” (M = 2.86). All remaining questions registered above a 3.0 on the Likert-type scales. The intent of these questions was to assess what coaches believed regarding the necessity for training. The scale mean was M = 3.07 (SD =.57) which indicated that the coaches agreed that additional training was needed. Data from this objective are in Table 3.
CONCLUSIONS
The conclusions for this study apply only to high school girls’ basketball coaches in Louisiana.
Conclusions for Objective One: Coaches’ Characteristics
It is concluded the gender and ethnicity of the typical girls’ basketball coaches in the studied state are male and white, respectively. This conclusion is based on the finding that approximately 70% of girls’ basketball coaches are Caucasian and 56% are males. This conclusion is in contrast to the population in the State, where Caucasians (not including Hispanic origin) in the state was reported as 61% and African American as 32% in 2010, (United States Government, 2010). It is concluded coaches have the same level of education as their non-coaching, teacher counterparts. This conclusion is based on data gathered during the study and is consistent with State’s public statistics which indicate 35.9 percent of public school teachers in have a master’s degree or higher. Thirty-six percent of coachesin this survey reported having a degree above the bachelors level (MS, MS+30 or doctoral level).
It is concluded that female high school basketball players in the state are led by an experienced cadre of coaches. With an average of 15 years in the classroom, 15 years as a coach and nearly 9 years as a head coach, it is apparent that the state’s girls’ basketball players are coached by experienced personnel.
Conclusion for Objective Two: Athletes Who Were Recruited, Signed, or Accepted Scholarships
It is concluded that coaches routinely encounter recruitable athletes, but do not encounter an overwhelming number of athletes who are recruited or signed to become college basketball players. On average, a head coach has just under one student-athlete per year who receives recruiting interest from an NCAA or NAIA school, making this occurrence not rare, but also not a predominant action in the life of a coach. The figure of one student-athlete per year was derived by comparing the average number of players recruited (M = 8.59) to the characterization in Objective One in which it was revealed the average head coach in the state has been in his or her position for approximately nine years. This conclusion is in contrast to the analysis reported by the National High School Center (2009) which indicated that one in six schoolswill experience a scholarship type student-athlete on an annual basis. There is a deficiency of data concerning the average number of athletes that coaches have contact with who are recruited, sign letters of intent, or garner scholarships.
Conclusion for Objective Three: Knowledge of NCAA & NAIA Recruiting Rules.
It is concluded coaches have limited knowledge of recruiting rules and entry requirements among the four types of playing levels for recruitable athletes. This conclusion is based on the finding that the coaches test score was 52% (out of a possible 100%) on an Information Inventory which asked questions about NCAA Division I, II, III (NCAA, 2009a) and NAIA (NAIA, 2010) entry requirements and recruiting rules. This conclusion conflicts with the framework proposed by Kram (1985) which pre-supposes the mentor will possess a superior knowledge of key areas of importance to a mentee. The conclusion also is in contrast to the rules Klungseth (2005) cited as important for coaches.
Conclusion for Objective Four: Coach’s Role
It is concluded coaches believe they have a role across a range of responsibilities in terms of mentoring their recruitable athletes. This conclusion is supported by Jowett (2005) and Donohue et al. (2007) who found that the relationship between the athlete and the coach during the recruiting process is critical. On the Likert-type scale used in this portion of the research study, the respondents registered their highest collective score, 3.72 out of 4.0, strongly agreeing their roles as mentors were real, important and wide ranging. Of concern: It is illuminating to compare the acknowledgment for an across the board need and benefit for new training with the relatively poor results achieved by the coaches in the Information Inventory. It is also encouraging to compare this eagerness for training with the resolute agreementamong coaches regarding their roles as mentors.
Conclusion for Objective Five: Expectations Regarding Collegiate Environment
It is concluded coaches believe treatment for athletes at the collegiate level will be composed of both mildly negative treatment and mildly positive preferential treatment. This conclusion is based on the finding that coaches believe athletes will face both negative stigmas (2.61 on 4.0 Likert-type scale) and encounter positive preferential treatment (2.52 on 4.0 Likert-type scale) while in college, simply because they are athletes. The coaches indicated an understanding that the environment an athlete will face will have inequities and athletes could face both positive and negative treatments. This finding is consistent with and illustrative of the cases of Nat Miles (Thamel, 2011) and Bryce Brown (Evans and Thamel), both athletes whose lives took unfortunate turns because they were probably not well informed of collegiateexpectations. While coaches were consistent in their views on this topic; there were no strong positive or negative feelings on the topic.
Conclusion for Objective Six: Necessity for Additional Training for the State’s High School Basketball Coaches
It is concluded coaches believe additional training for themselves and their peers is necessary and this training would benefit both coaches and athletes. This conclusion was based on the concurrence provided by the coaches (3.07 on 4.0 Likert-type scale) in the research indicating the need for additional training for themselves, their peers and the benefit training would provide their schools and athletes. The coaches indicated a belief that additional training or certification would be beneficial for themselves, their peers and recruitable athletes. In the strongest level of concurrence within this objective (3.27 out of 4.0) the coaches indicated a belief that all coaches would benefit by additional training and certification, indicating a consistency across the population that this was necessary. The weakest level ofconcurrence (2.86 out of 4.0) was related to the question of whether or not training was needed for entry-level coaches. This conclusion was consistent with Maetozo’s (1971) and Bloom et al.’s (1998), recommendations and discussions of the need for training and certification.
RECOMMENDATIONS AND APPLICATIONS IN SPORTS
Coaches were the primary focus of this research, and data in this report should be illuminating to them. The information should also be applicable to athletic directors and to HSAAs that administer state-wide programs. It is apparent that HSAAs should examine the necessity for an enhanced training or certification program for girls’ high school basketball coaches. Several key facts established in the study merged to drive this recommendation. First of all, coaches registered solid concurrence that: (A) They believe their roles as mentors are important; and (B) They believe additional training would be beneficial to themselves, their peers and their students. These two facts, standing alone, indicate both recognition of the critical role of the coach and a self-reflection regarding a necessity for self and communityimprovement.
Secondly, results from the Information Inventory indicate a deficiency in the knowledge base of recruiting rules and requirements. No evidence or literature was found which provided an indication coaches have any formal training on the recruiting rules and entry requirements for athletes who play basketball in the NCAA or NAIA. The researchers recommend additional training or certification could be in order for the population of coaches and that this training could result in benefits for girls’ basketball players.
Even though coaches expressed the need for additional training or certification, a concern exists regarding the apparently low number of athletes who signed national letters of intent or garnered scholarships. On average, a coach has one athlete each year that is the subject of recruiting attention and has one who receives a scholarship or signs a national letter of intent every other year. With figures this low, the question to be posed is whether additional training is truly merited to enhance or potentially help such a small number of athletes. Though the coaches believe additional training would be beneficial, a cost-benefit analysis would have to be made to determine the utility of such a new program or mandate.
It is recommended the knowledge base of all coaches throughout the state be assessed, with possible expansion to coaches across the south or the country. Though this study was focused on girls’ basketball coaches, the entire population of coaches in the state may benefit from additional training or certification. The snap shot of coaches in one sport indicates a possible deficiency in knowledge but a willingness to learn and recognition that more training could be valuable. The existence of this limitation in one sport in a Southern state could be a clarion reminder that many student-athletes are not getting the information or, more importantly, the mentoring they need to ascend to a higher level of education and thus a better life.
ACKNOWLEDGMENTS
None
REFERENCES
1.Adler, P., & Adler, P. (1985). From idealism to pragmatic detachment: The academic performance of college athletes. Sociology of Education, 58(4), 241-250
2.Aries, E., McCarthy, D., Salovey, P., & Banaji, M. (2004). A comparison of athletes and non-athletes at highly selective colleges: Academic performance and personal development. Research in Higher Education, 45(6), 577-602.
3.Bloom, G., Durand-Bush, N., Schinke, R., & Salmela, J. (1998), The importance of mentoring in the development of coaches and athletes. International Journal of Sports Psychology, 29, 267-281.
4.Bott, P. A. (1996). Testing and assessment in occupational and technical education. Boston, MA: Allyn and Bacon, Inc.
5.Donohue, B., Miller, A., Crammer, L., Cross, C., & Covassin, T. (2007). A standardized method of assessing sport specific problems in the relationships of athletes with their coaches, teammates, family, and peers. Journal of Sport Behavior, 30(4), 375-397.
6.Evans, T., & T, P. (2009, February 27). NCAA investigates role of recruit’s adviser. New York Times. Retrieved from http://www.nytimes.com/2009/02/27/sports/ncaafootball/27recruit.html
7.Gall, M., Gall, J., & Borg, W. (2003). Educational research: An introduction (7th ed.). Boston: Allyn & Bacon
8.Giacobbi Jr., P., Whitney, J., Roper, E., & Butryn, T. (2002). College coaches’ views about the development of successful athletes: A descriptive exploratory investigation. Journal of Sport Behavior, 25(2), 164-181.
9.Harrison, C., Stone, J., Shapiro, J., Yee, S., Boyd, J., & Rullan, V. (2009). The role of gender identities and stereotype salience with the academic performance of male and female college athletes. Journal of Sport & Social Issues, 33(1), 78-96.
10.Horton Jr., D. (2009). Class and cleats: Community college student-athletes and academic success. New Directions for Community Colleges, (147), 15-27.
11.Jowett, S. (2005). The coach-athlete partnership. The Psychologist, 18(7), 412-415. Available: http://www.thepsychologist.org.uk/archive/archive_home.cfm?volumeID=18&editionID=125&ArticleID=895
12.Kent. A, & Turner, B. (2002). Increasing response rate among coaches: The role of pre-notification methods. Journal of Sports Management, 16(1), 230-238.
13.Klungseth S. (2005, April). The five NCAA recruiting rules that high school coaches should know. Coach & Athletic Director, 74(9), 75-81. Retrieved from http://findarticles.com/p/articles/mi_m0FIH/is_9_74/ai_n17209237/
14.Kram, K. E. (1985). Mentoring at work. Boston: Scott, Foresman and Company.
15.Lawrence, S., Harrison, C., & Stone, J. (2009). A day in the life of a male college athlete: A public perception and qualitative campus investigation. Journal of Sport Management, 23(5), 591-614.
16.Lopez S. (1998, January 19). Full-court press. Sports Illustrated, 88(2), 84. Retrieved from http://sportsillustrated.cnn.com/vault/article/magazine/MAG1142801/index.htm
17.Lough, N. (2001). Mentoring connections between coaches and female athletes. Journal of Physical Education, Recreation & Dance, 72(5), 30-33.
18.Maetozo, M.G, American Association for Health. (1971). Certification of high school coaches.
19.Nasir, N., & Hand, V. (2008). From the court to the classroom: Opportunities for engagement, learning, and identity in basketball and classroom mathematics. Journal of the Learning Sciences, 17(2), 143-179.
20.National Association of Intercollegiate Athletics. (2010). DI women’s basketball. Kansas City, MO: Author. Retrieved from: http://naia.cstv.com/sports/w-baskbl/naia-w-baskbl-body.html
21.National Collegiate Athletic Association. (2009a). 2009-2010 guide for the college bound student-athlete. Indianapolis, IN: Author. Retrieved from http://www.ncaapublications.com/productdownloads/CB10.pdf
22.National Collegiate Athletic Association. (2009b). In estimated probability of competing in athletics beyond the high school interscholastic level. Indianapolis, IN: Author. Retrieved from http://www.ncaa.org/wps/ncaa?key=/ncaa/ncaa/academics+and+athletes/education+and+research/probability+of+competing/methodology+-+prob+of+competing
23.National Collegiate Athletic Association. (2010). Women’s basketball administration. Indianapolis, IN: Author. Retrieved from http://www.ncaa.org/wps/portal/ncaahome?WCM_GLOBAL_CONTEXT=/ncaa/ncaa/sports+and+championship/basketball/womens
24.National High School Center. (2009). High schools in the United States. Washington, DC. Retrieved from http://www.betterhighschools.org/pubs/documents/QuickStatsFactSheet_HSintheUS_03-13-09.pdf
25.Phillips, M. (2009). Un-equal protection: Preferential admissions treatment for student-athletes. Alabama Law Review, 60(3), 751-782.
26.Ragins, B. R., & Cotton, J. L. (1999). Mentor functions and outcomes: A comparison of men and women in formal and informal mentoring relationships. Journal of Applied Psychology, 84(4), 529–550.
27.Ragins, B. R., & Kram, K. E. (2007). The handbook of mentoring at work: Theory, research, and practice. Thousand Oaks, CA: Sage Publications.
28.Robinson, J. P., Shaver, P. R., & Wrightsman, L. S. (1991). Criteria for scale selection and evaluation. In J. P. Robinson, P. R. Shaver, & L. S. Wrightsman (Eds.). Measures of personality and social psychological attitudes (pp. 1-16). New York: Academic Press.
29.Snedecor, G., & Cochran, W. G. (1989). Statistical methods (8th ed.). New York: Wiley
30.Stevens, B. (2006). High school sports: Spirit or spite? Kansas Association of Health, Physical Education, Recreation, and Dance Journal, 78(2), 41-42. Retrieved from http://www.kahperd.org/journal/falljournal06.pdf
31.Thamel, P. As UCONN plays on, once-prized recruit can only watch, (April 1, 2011), Retrieved from: http://www.nytimes.com/2011/04/02/sports/ncaabasketball/02uconn.html?_r=1&ref=sports
32.Turman, P. (2003). Athletic coaching from an instructional communication perspective: the influence of coach experience on high school wrestlers’ preferences and perceptions of coaching behaviors across a season. Communication Education, 52(2), 73-86.
33.Turman, P. (2008). Coaches’ immediacy behaviors as predictors of athletes’ perceptions of satisfaction and team cohesion. Western Journal of Communication, 72(2), 162-179. doi:10.1080/10570310802038424
34.U.S. Census Bureau. (2010). State and county, quick facts, Washington, DC; Retrieved from http://quickfacts.census.gov/gfd/states/22000.html
35.U.S. Department of State. (2009). The cost of college in the United States. Washington, DC: Author. Retrieved from: http://www.america.gov/st/educ-english/2008/April/20080519002020SrenoD0.56625.html
36.University of Wisconsin-River Falls. (2009). Learn more, earn more. River Falls, WI: Author. Retrieved from: http://www.uwrf.edu/admissions
Table 1. Correct Responses to the Head Girls’ Basketball Coaches Information Inventory
| Test item | Correct responses | |
| n | % | |
| In order for an athlete to be ruled eligible for NCAA Division I athletics immediately after high school, the athlete must achieve the following: Answer Choices: A: An ACT score of 18 B: Graduate w/a GPA of 3.5 on 4.0 scale C: Have combination GPA & ACT on “Sliding Scale” D: Have a GPA of at least 3.0 and in top 45% of graduating class |
104 |
81.3 |
| Which of the following institution types does not offer athletic scholarships? a Answer Choices: A: NAIA B: NCAA Division III C: NCAA Division II D: NCAA Division I |
91 |
71.1 |
| The type of communication that may not be used by an NCAA coach to communicate with a recruitable athlete is: Answer Choices: A: Texting B: Email C: Land line phone calls D: Cell phone calls |
89 |
69.5 |
| How many core courses does the NCAA require an athlete to complete prior to entering any Division I college or university? Answer Choices: A: 12 B: 14 C: 15 D: 16 |
83 |
64.8 |
| According to NCAA recruiting calendar, the first time a Division I NCAA women’s basketball coach may place a telephone call to a recruitable athlete is: Answer Choices: A: At the end of athlete’s junior year B: At the end of athlete’s sophomore year C: At the end of the athlete’s senior year D: Never |
80 |
62.5 |
| In order for an athlete to be ruled eligible at a NAIA institution, the athlete must achieve the following. Answer Choices: A: A minimum ACT score of 21 B: A minimum GPA of 2.5 on a 4.0 scale C: Meet 2 of 3 minimum standards in 3 broad categories D: Have minimum GPA of 2.0 and minimum ACT sum score of 68 |
78 |
60.9 |
| In order for an athlete to be ruled eligible for NCAA Division II athletics immediately after high school, the athlete must achieve the following: Answer Choices: A: A minimum ACT score of 18 B: GPA of at least 3.5 on 4.0 scale C: Have combination of minimum GPA and class ranking D: Have minimum GPA and a minimum sum score of 68 |
72 |
56.3 |
| How many core courses does the NCAA require an athlete to complete prior to entering any Division II college or university? Answer Choices: A: 12 B: 14 C: 15 D: 16 |
42 |
32.8 |
| Which statement below describes contact rules for NCAA Division III coaches in terms of making direct contact with recruitable high school athletes? Answer Choices: A: There are no restrictions B: Contact may be initiated prior to the end of the sophomore year C: Contact may only be initiated by prospective student D: Contact in prohibited |
39 |
30.5 |
| A recruitable high school athlete may sign a Letter of Intent to play for an NAIA institution: Answer Choices: A: At any time B: After the student’s junior year C: Only during the student’s senior year D: Only after the student’s senior year |
28 |
21.9 |
Note. For the Information Inventory: M=5.52, SD=1.88, N=127. Correct answer choices are bolded and underlined.
aOf the 36 coaches who answered this question incorrectly, 34 identified the NAIA as being the type of institution which does not offer athletic scholarships, which was incorrect.
Table 2. Coaches’ Perceptions of Their Role as the Head Girls’ Basketball Coach for Recruitable Athletes
| Statement’s about coaches’ role |
N |
M |
SD |
Interpretation |
| I should be able to explain to an athlete what is required to become a recruitable athlete |
128 |
3.74 |
.49 |
Strongly agree |
| I should be a mentor to my recruitable players. |
128 |
3.71 |
.55 |
Strongly agree |
| I should assist my recruitable athletes in being prepared for the rigors of the college academic as well as athletic environment? |
128 |
3.56 |
.54 |
Strongly agree |
| I should assist my recruitable athletes in preparing for the pressures of collegiate athletics? |
128 |
3.49 |
.60 |
Agree |
| I should assist my recruitable athletes in marketing themselves (e.g., send out letters of endorsement, make video highlights, etc.). |
128 |
3.42 |
.64 |
Agree |
| I should help recruitable athletes make wise life decisions such as choosing the correct college |
128 |
3.22 |
.76 |
Agree |
|
Coach’s Role Scale: |
128 |
3.52 |
.42 |
Strongly agree |
Note. Scale ranged from 1 = “Strongly Disagree” to 4 = “Strongly Agree. Alpha = .79.
Table 3. Need for Additional Training on Collegiate Athletic Recruitment Rules
| Coaches believed |
N |
M |
SD |
Interpretation |
| Additional training for high school coaches is necessary to ensure coaches stay up-to-date on current college recruiting rules/regulations/trends. | 128 |
3.27 |
.70 |
Agree |
| I would benefit from an additional training program for coaches that would keep you up to date on college recruiting rules/regulations/trends. | 128 |
3.10 |
.64 |
Agree |
| Athletes in my school would benefit from a training program that would keep coaches up to date on college recruiting rules/regulations/trends. | 128 |
3.08 |
.68 |
Agree |
| My school would benefit from an additional training program to keep coaches up to date on college recruiting rules/regulations/trends. | 128 |
3.05 |
.62 |
Agree |
| Additional certification or training requirements for high school coaches are necessary to ensure entry level coaches have the knowledge they need about the college recruiting process prior to entering a coaching position. | 128 |
2.86 |
.76 |
Agree |
|
Necessity for Additional Training scale: |
128 |
3.07 |
.57 |
Agree |
Note. Scale ranged from 1 = “Strongly Disagree” to 4 = “Strongly Agree. Alpha = .88.