Context: The success of any academic program, including athletic training, depends upon attracting and keeping quality students. The nature of persistent students versus students who prematurely leave the athletic training major is not known. Understanding the profiles of athletic training students who persist or leave is important.Objective: To (1) explore the relationships among the following variables: anticipatory factors, academic integration, clinical integration, social integration, and motivation; (2) determine which of the aforementioned variables discriminate between senior athletic training students and major changers; and (3) identify which variable is the strongest predictor of persistence in athletic training education programs.Design: Descriptive study using a qualitative and quantitative mixed-methods approach.Setting: Thirteen athletic training education programs located in District 3 of the National Athletic Trainers' Association.Patients or Other Participants: Ninety-four senior-level athletic training students and 31 college students who changed majors from athletic training to another degree option.Data Collection: Data were collected with the Athletic Training Education Program Student Retention Questionnaire (ATEPSRQ).Analysis: Data from the ATEPSRQ were analyzed via Pearson correlations, multivariate analysis of variance, univariate analysis of variance, and a stepwise discriminant analysis. Openended questions were transcribed and analyzed using open, axial, and selective coding procedures. Member checks and peer debriefing techniques ensured trustworthiness of the study.Results: Pearson correlations identified moderate relationships among motivation and clinical integration (r 5 0.515, P , .01) and motivation and academic integration (r 5 0.509, P , .01). Univariate analyses of variance showed that academic integration (F 1,122 5 8.483, P , .004), clinical integration (F 1,119 5 30.214, P , .001), and motivation (F 1,121 5 68.887, P , .001) discriminated between seniors and major changers. Discriminant analysis indicated that motivation was the strongest predictor of persistence in athletic training education, accounting for 37.2% of the variance between groups. The theoretic model accurately classified 95.7% of the seniors and 53.8% of the major changers. A common theme emerging from the qualitative data was the presence of a strong peer-support group that surrounded many of the senior-level students.Conclusions: Understanding student retention in athletic training is important for our profession. Results from this study suggest 3 key factors associated with student persistence in athletic training education programs: (1) student motivation, (2) clinical and academic integration, and (3) the presence of a peer-support system. Educators and program directors must create comprehensive recruitment and retention strategies that address factors influencing students' decisions to stay in the athletic training profession.Key Words: socialization, persistence, career choice, retention, drop-ou...
Context: Previous researchers have indicated that athletic training education programs (ATEPs) appear to retain students who are motivated and well integrated into their education programs. However, no researchers have examined the factors leading to successful persistence to graduation of recent graduates from ATEPs.Objective: To determine the factors that led students enrolled in a postprofessional education program accredited by the National Athletic Trainers' Association (NATA) to persist to graduation from accredited undergraduate ATEPs.Design: Qualitative study. Setting: Postprofessional education program accredited by the NATA.Patients or Other Participants: Fourteen graduates (12 women, 2 men) of accredited undergraduate entry-level ATEPs who were enrolled in an NATA-accredited postprofessional education program volunteered to participate. Data Collection and Analysis:We conducted semistructured interviews and analyzed data through a grounded theory approach. We used open, axial, and selective coding procedures. To ensure trustworthiness, 2 independent coders analyzed the data. The researchers then negotiated over the coding categories until they reached 100% agreement. We also performed member checks and peer debriefing.Results: Four themes emerged from the data. Decisions to persist to graduation from ATEPs appeared to be influenced by students' positive interactions with faculty, clinical instructors, and peers. The environment of the ATEPs also affected their persistence. Participants thought they learned much in both the clinic and the classroom, and this learning motivated them to persist. Finally, participants could see themselves practicing athletic training as a career, and this greatly influenced their eventual persistence.Conclusions: Our study gives athletic training educators insight into the reasons students persist to graduation from ATEPs. Specifically, athletic training programs should strive to develop close-knit learning communities that stress positive interactions between students and instructors. Athletic training educators also must work to present the athletic training field as exciting and dynamic.
Background:Research evaluating the effect of comprehensive coach education and practice contact restriction in youth football injury rates is sparse. In 2012, USA Football released their Heads Up Football coaching education program (HUF), and Pop Warner Football (PW) instituted guidelines to restrict contact during practice.Purpose:To compare injury rates among youth football players aged 5 to 15 years by whether their leagues implemented HUF and/or were PW-affiliated.Study Design:Cohort study; Level of evidence, 2.Methods:Athletic trainers (ATs) evaluated and tracked injuries at each practice and game during the 2014 youth football season. Players were drawn from 10 leagues across 4 states. The non–Heads Up Football (NHUF) group consisted of 704 players (none of whom were PW-affiliated) from 29 teams within 4 leagues. The HUF+PW group consisted of 741 players from 27 teams within 2 leagues. The HUF-only group consisted of 663 players from 44 teams within 4 leagues. Injury rates and injury rate ratios (IRRs) were reported with 95% CIs.Results:A total of 370 injuries were reported during 71,262 athlete-exposures (AEs) (rate, 5.19/1000 AEs). Compared with the NHUF group (7.32/1000 AEs), the practice injury rates were lower for the HUF+PW group (0.97/1000 AEs; IRR, 0.13; 95% CI, 0.08-0.21) and the HUF-only group (2.73/1000 AEs; IRR, 0.37; 95% CI, 0.26-0.53). Compared with the NHUF group (13.42/1000 AEs), the game injury rate was lower for the HUF+PW group (3.42/1000 AEs; IRR, 0.25; 95% CI, 0.15-0.44) but not for the HUF-only group (13.76/1000 AEs; IRR, 1.02; 95% CI, 0.73-1.43). Also, the HUF+PW game injury rate was lower than that of HUF-only (IRR, 0.20; 95% CI, 0.12-0.36). Higher injury rates were typically found in those aged 11 to 15 years compared with those aged 5 to 10 years. However, stronger effects related to HUF implementation and PW affiliation were seen among 11- to 15-year-olds. When restricted to concussions only, the sole difference was found between the practice concussion rates among 11- to 15-year-olds in the HUF+PW (0.14/1000 AEs) and NHUF groups (0.79/1000 AEs) (IRR, 0.18; 95% CI, 0.04-0.85).Conclusion:These findings support comprehensive coach education and practice contact restrictions as effective methods of injury mitigation. Future research should continue evaluating similar programming within other levels of competition and sports.
Context: Limited evidence exists on the role clinical education can play in the development of athletic training student commitment for the profession.Objective: Investigating the role clinical education experiences play on the development of passion for athletic training.Design: Exploratory qualitative study.Setting: Athletic training education programs.Patients or Other Participants: Seventeen students (8 males, 9 females) volunteered. Students represented both junior (13) and senior (4) levels, were engaged in 23 6 5 hours per week of clinical education, and were 20 6 2 years old.Main Outcome Measure(s): One-on-one, in-person interviews following a semistructured format. Multiple analyst triangulation and member checks were included as steps to establish data credibility.Results: A positive clinical education experience as described by this cohort of students was inclusive of strong mentorship, realism, professional commitment of the preceptor, and clinical skill integration. In combination, these attributes appear to help students develop their professional commitment for athletic training. Preceptors who provided mentorship by modeling appropriate professional behaviors, providing a realistic perspective to their role, and showing enthusiasm allowed the students in this study to gain an accurate understanding of the profession. Opportunities to develop clinical skills with feedback for improvement demonstrated the preceptors' commitment to the profession and the student and was valued as contributing to the overall experience.Conclusions: The development of the athletic training student's commitment to the profession is directly related to a positive clinical education experience facilitated by a preceptor who is also passionate about the job. Preceptors are encouraged to provide the athletic training student with a realistic impression of the clinical setting in which they are gaining experiences in order for them to fully understand their future role and responsibilities. Maintaining an optimistic but pragmatic attitude is also valued by the athletic training student.
Background:American youth football leagues are typically structured using either age-only (AO) or age-and-weight (AW) playing standard conditions. These playing standard conditions group players by age in the former condition and by a combination of age and weight in the latter condition. However, no study has systematically compared injury risk between these 2 playing standards.Purpose:To compare injury rates between youth tackle football players in the AO and AW playing standard conditions.Study Design:Cohort study; Level of evidence, 2.Methods:Athletic trainers evaluated and recorded injuries at each practice and game during the 2012 and 2013 football seasons. Players (age, 5-14 years) were drawn from 13 recreational leagues across 6 states. The sample included 4092 athlete-seasons (AW, 2065; AO, 2027) from 210 teams (AW, 106; O, 104). Injury rate ratios (RRs) with 95% CIs were used to compare the playing standard conditions. Multivariate Poisson regression was used to estimate RRs adjusted for residual effects of age and clustering by team and league. There were 4 endpoints of interest: (1) any injury, (2) non–time loss (NTL) injuries only, (3) time loss (TL) injuries only, and (4) concussions only.Results:Over 2 seasons, the cohort accumulated 1475 injuries and 142,536 athlete-exposures (AEs). The most common injuries were contusions (34.4%), ligament sprains (16.3%), concussions (9.6%), and muscle strains (7.8%). The overall injury rate for both playing standard conditions combined was 10.3 per 1000 AEs (95% CI, 9.8-10.9). The TL injury, NTL injury, and concussion rates in both playing standard conditions combined were 3.1, 7.2, and 1.0 per 1000 AEs, respectively. In multivariate Poisson regression models controlling for age, team, and league, no differences were found between playing standard conditions in the overall injury rate (RRoverall, 1.1; 95% CI, 0.4-2.6). Rates for the other 3 endpoints were also similar (RRNTL, 1.1 [95% CI, 0.4-3.0]; RRTL, 0.9 [95% CI, 0.4-1.9]; RRconcussion, 0.6 [95% CI, 0.3-1.4]).Conclusion:For the injury endpoints examined in this study, the injury rates were similar in the AO and AW playing standards. Future research should examine other policies, rules, and behavioral factors that may affect injury risk within youth football.
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