Athletic Training Employment in US Secondary Schools by Geographic Setting and School Size

Data-Collection Procedure

All public and private secondary schools in the United States containing at least one grade 9 through 12 were included in this study, and school demographic information and AT employment status were obtained from the ATLAS database. Initially, schools were contacted via a phone call or email and asked if they offer a school-sanctioned interscholastic athletics program. Schools not offering interscholastic athletics program were removed from the database, while schools with an interscholastic athletics program were asked if they received full-time or part-time (or both) AT services and the number of ATs providing these services. Simultaneously, we distributed an online survey¹⁹ to secondary school ATs throughout the country to obtain more detailed and accurate information about the AT services provided in secondary schools. This data-acquisition process and the methods were described by Huggins et al.¹⁵ For the dataset used in this study (exported from the ATLAS database in October 2017), all schools were included independent of ATLAS survey completion status. Three main types of schools are in the database: schools with surveys completed within the previous 2 years, schools with verified AT services but no updated survey, and schools without reported AT services. In addition to biannual recruitment for the survey, the ATLAS Project takes steps to improve the accuracy and verify the employment data of those schools that have AT services with no survey and those with no AT services. These steps include annual repeat calling or email correspondence with the schools, cross-referencing of information from high school athletics association websites and directories and personal correspondence with the leadership or office, verification of employment with the state athletic training association leadership or state medical licensing board, and email or phone contact with other ATs in the area who have updated the survey recently and can help verify the level of AT services. Schools that could not be verified are listed as unknown in the database until verification is completed.

Open-access data provided by the US Department of Education and the National Center for Education Statistics (NCES) regarding geographic locale and student enrollment²⁰ were merged by zip code with the ATLAS database for each school with athletics. We exported the geographic locale and student enrollment data from the NCES database from August 2017 through October 2017. The NCES locale classifications categorize US territories into 4 types: city, suburban, town, or rural. Each locale type contains 3 subtypes, and each locale subtype has a corresponding 2-digit locale code (Table 1). We used NCES locales for this study because these were the only accessible geographic indicators that allowed us to assess the physical location of schools in relation to urbanized areas, which we expected to be an important factor for the recruitment and retention of ATs. The US Census Bureau defines urbanized areas and urban clusters as territory that is densely developed and encompasses residential, commercial, and nonresidential urban land uses and defines principal cities as places with a large population of residents and workers located within a metropolitan and micropolitan statistical area (a geographic entity associated with at least 1 population core of 10 000 or more, plus adjacent territory that has a high degree of social and economic integration with the core as measured by commuting ties).²¹ Given the definitions, the city locale focuses on large, densely populated areas, while the suburban locale is just outside the territory with a city locale.²¹ The town and rural locales are defined by the distance in relation to urbanized area or urban cluster, and towns are commonly located near urbanized areas, often with easy access to the larger population core.²¹ We did not use the subtypes for our analyses because the population and distance thresholds for the subtype classification could have complicated the presentation of the results.

Table 1 Geographic Locale Classifications and Criteria²⁰

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We examined the quartiles of those included in the dataset to classify levels of student enrollment. Quartiles were selected after we determined that the classification would capture the characteristic changes in AT employment, referring to the results of the benchmark study by Pryor et al.¹⁴ School enrollments of small (first quartile; ≤293 students), medium (second quartile; >293 and ≤638 students), moderate (third quartile; >638 and ≤1319 students), and large (fourth quartile; >1319 students) were classified and coded. Because the student enrollment of private schools was unavailable in the NCES website at the time of export, this classification applies only to public schools in this study.

Data Analysis

The dataset exported from the ATLAS database contained 20 078 (15 992 public and 4086 private) secondary schools. Schools for which AT employment status was unknown (57 public and 35 private) were removed from the analyses. Of the remaining 19 986 schools, 68 public schools were removed because they were missing a valid NCES locale code, and 85 more public schools were removed for failing to report the number of students enrolled. Descriptive statistics were computed for all demographic variables. We used Mann-Whitney tests to examine the differences in the distribution of schools by geographic locale between public and private schools. Chi-square tests showed the relationships between AT employment status and geographic locale and between AT employment status and school size classification. To examine the odds of having AT access or a full-time AT among the categories, odds ratios (ORs) with 95% CIs were also computed, with statistical significance defined as the 95% CI not including 1.00. To investigate common and less common employment models (full-time AT, part-time AT, or no AT) among locale categories, χ² tests with residual analysis were used, and statistical significance was defined as adjusted residuals of 2.0 and –2.0. Additionally, the Somers D was calculated between locale and school size classification of public schools to examine the strength and direction of association between the variables. We chose the Somers D over a correlational analysis because it is thought to assess the association of 2 ordinal variables (eg, locale and school size classification) more accurately. To assess the ability of locale and school size variables to predict the AT employment status of public schools, binary logistic regression was performed. All data analyses were performed using IBM SPSS (version 22.0; IBM SPSS Inc).

Secondary School Demographics

The distribution of schools by geographic locale is reported in Table 2. The Mann-Whitney tests revealed that the distributions of the 2 samples from public and private schools were different (P < .001). Most public schools (43.3%; n = 6864) were located in rural areas, and most private schools (36.1%; n = 1404) were located in city areas.

Table 2 School Demographics by Geographic Locale, % (n)

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Athletic Training Employment by Locale Classification

A total of 19 918 public and private schools with AT employment status and locale code (city [n = 4701]; suburban [n = 5379]; town [n = 2789]; and rural [n = 7679]) were included in the analyses. More suburban schools received AT services (80.1%; n = 4306), compared with schools in cities, towns, or rural locales. Employment of ATs and geographic locale were associated (x²₃ = 1104.6, P < .01), and the ORs indicated that schools within city, suburban, and town locales had increased odds of AT services compared with schools in rural locales (OR = 2.17 [95% CI = 2.00, 2.36], 3.55 [95% CI = 3.28, 3.85], and 1.93 [95% CI = 1.76, 2.12]), respectively. Similarly, more suburban schools had full-time AT services (47.9%; n = 2579) than city, town, or rural locales. The ORs revealed that schools in city, suburban, and town locales had increased odds of a full-time AT compared with schools in rural locales, (OR = 2.51 [95% CI = 2.31, 2.73], 3.87 [95% CI = 3.58, 4.18], and 1.95 [95% CI = 1.77, 2.15]), respectively. A χ² test with residual analysis for employment model (full-time AT, part-time AT, or no AT) and locale was significant (x²₃ = 1586.6, P < .001), and the adjusted residuals for full-time employed, part-time employed, and no AT employed were 7.6, –0.2, and –7.3 for city, 28.4, –3.0, and –25.2 for suburban, –0.9, 3.8, and –2.9 for town and –31.6, 0.2, and 31.1 for rural, respectively. The complete list of AT employment by locale is depicted in Table 3. Regarding the number of ATs employed, having 1 full-time or part-time AT employed was the most common observation in the secondary school setting (Table 3).

Table 3 Athletic Trainer (AT) Employment Status for Public and Private Schools by Geographic Locale, % (No.)

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The AT employment status for public and private schools in each geographic locale by state can be found in Table 4. In the city locale, while 100% of secondary schools in Wyoming and Montana received AT services, Michigan (48.6%), New Hampshire (40.0%), and Illinois (35.8%) schools were below 50%. In the suburban locale, 100% of schools in Hawaii, Nebraska, South Dakota, and Vermont had access to AT services. No schools in the suburban area in Alaska had access to AT services. For schools located in towns, only New Jersey had 100% of schools with access to AT services, while Massachusetts had the lowest access to AT services (33.3%). The AT services provided to rural schools were highest in New Jersey (93.3%) and lowest in Alaska (2.5%). In Alaska, only 3 rural schools of 119 had access to AT services.

Table 4 Athletic Training Employment Status by Geographic Locale in US Secondary Schools

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Athletic Training Employment by School Size Classifications

A total of 15 850 public schools (private schools removed as mentioned in the Methods section) with known AT employment status and student enrollment numbers were included in the analyses. Large schools had a higher percentage with AT services (92.1%; n = 3646) than moderate (84.2%; n = 3335), medium (62.6%; n = 2480), or small (38.6%; n = 1530) schools. A complete list of AT employment status by school size classification is in Table 5 and the Figure. The relationship between AT employment and student enrollment class was significant (x²₃ = 3220.3, P < .01), and the OR showed that large, moderate, and medium schools had increased odds of AT services over small schools, (OR = 18.49 [95% CI = 16.20, 21.08], 8.45 [95% CI = 7.60, 9.40], and 2.66 [95% CI = 2.43, 2.92]), respectively. When we examined full-time AT services and school size, although 59.8% (n = 2369) of large schools reported having 1 or more full-time AT, only 6.9% (n = 275) of small schools had 1 or more full-time AT. Similarly, large, moderate, and medium schools had increased odds of full-time AT services compared with small schools (OR = 19.98 [95% CI = 17.40, 22.94], 12.45 [95% CI = 10.85, 14.28], and 4.15 [95% CI = 3.60, 4.79]), respectively. A detailed report of odds ratios is given in Table 6. All of the odds calculated were significant.

Table 5 Athletic Trainer (AT) Employment Status in Public Schools by Student Enrollment Class, % (No.)^a

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Table 6 Odds Ratios (95% CIs) by Geographic Locale and Student Enrollment Class^a

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Regression Analysis

The Somers D was used to assess the strength and direction of the relationship between locale and school size classification for public schools. The values were 0.52 when locale was the dependent variable and 0.55 when school size was the dependent variable, which indicates moderate agreement between the variables, meaning that larger schools were more likely to be located in urbanized areas. The logistic model produced by a stepwise approach is shown in Table 7. With this model, the percentage of correct predictions was 75.0%.

Table 7 Logistic Regression Models for Predicting Athletic Trainer Employment Status in Public Schools

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Athletic Training Employment Status and Geographic Locale

The purpose of our study was to describe and examine AT services by geographic locale and student enrollment. The percentage of schools with AT services was highest in the suburbs and lowest in rural locations. The same trend was observed for the full-time employment of ATs. As demonstrated by the increased odds, AT employment differed noticeably between rural locales (53.1%) and other locales (68.5% [town], 71.0% [city], and 80.0% [suburban]). These findings shed light on the idea that a secondary school with athletics located in a rural area was a limiting factor for AT employment, although the extent of the effect of locale status was much smaller than that of school size in public schools as we explain later. Based on our findings, the athletic training profession might opt to promote and enhance employment in rural areas, considering that 43.3% (n = 6864) of US public schools were located in rural territories. Although most private schools (36.1%, n = 1404) were located in city areas, when public and private schools were combined, more than one-third of secondary schools were in rural areas (n = 7757; 38.7%).

To enhance employment in these rural areas, strategies to overcome barriers to employment may need to be developed. One of the most common challenges for rural health care providers is too few continuing education (CE) opportunities.^22,23 Ramos et al²² found that rural school nurses were less likely to have received recent CE on such health topics as asthma; anaphylaxis; healthy weight; and lesbian, gay, bisexual, and transgender health, which are relevant to schoolchildren. Other investigators²⁴ have also identified cultural difficulties in providing health care within a remote area, such as isolation, difficulty building community relationships, and increased rate of burnout. To overcome these challenges and concerns, increasing online CE opportunities,^22,24 building a network of consultants within the community,²⁴ and learning effective self-care practices²⁴ have been suggested for clinicians in rural areas. Telehealth and telemedicine integration and hiring incentives are also worth considering by employers and school districts.

Regarding employment type, full-time employment was observed more frequently in city and suburban locales than expected and less frequently in the rural locale. Full-time employment occurred most often in the suburban locale, where approximately half of schools (47.9%) had ATs in a full-time capacity; in contrast, only 19.2% of rural schools had a full-time AT. Part-time employment was more common in towns and less common in suburbs than expected. This was likely because the major employment types were part time in the town locale (part time [53.8%] versus full time [46.2%]) and full time in the suburban locale (part time [40.1%] versus full time [59.9%]). Although part-time employment was most frequent in schools with AT access in the rural locale (part time [63.8%] versus full time [36.2%]), the residual analysis did not demonstrate statistical significance because the percentage of schools with only a part-time AT to the total number of schools in the rural locale fell in the expected range (33.8%). In the rural locale, approximately half (46.9%) of schools did not have access to an AT. To date, we believe we are the first to successfully quantify the precise number and percentage of schools with AT services by geographic locale.

Having 1 AT (either full time or part time) was the most common observation in secondary schools across all locales. This finding was consistent with a previous study²⁵ that indicated the median ratios of student-athletes to AT were 300:1 in public schools and 200:1 in private schools. Pryor et al¹⁴ also examined AT employment in the secondary school setting and identified the need to hire multiple ATs because 1 AT may not be able to cover more than 200 student-athletes. Whereas hiring multiple full-time ATs might be unrealistic for many schools at the present time due to budgetary constraints, these findings justify the need for improved strategies and employment models for ATs in secondary schools to improve on-site medical services.

Athletic Training Employment Status and Public School Size

Large public schools received AT services more often overall and more often in a full-time capacity than moderate-, medium-, and small-sized schools. These results suggested that public schools with increased student enrollments were at increased odds of having AT services and offering employment in a full-time capacity, which is consistent with the findings of Pryor et al.¹⁴ Considering that only 38.6% of small public schools received AT services and only 6.9% were in a full-time AT capacity, low student enrollment is a barrier to AT employment in public schools. We also showed that full-time employment largely differed from small schools (6.9%) to large schools (59.8%) in comparison with part-time employment (31.7% in small schools and 32.2% in large schools). Given that the increase in overall AT employment paralleled the increase in full-time AT employment, overall AT employment status was highly contingent on full-time AT employment status in secondary schools. The strategies for small schools to obtain access to AT services were discussed by Pike et al.¹² Although Wham et al¹³ determined that hiring a full-time AT was best, sharing AT services among smaller schools may be a more viable option for schools that do not currently have access.¹² Another option is to form a cooperative athletic program with multiple neighboring small schools.¹² The health and safety of student-athletes should be the first priority in the athletic program. Thus, a small student enrollment does not justify failing to hire an AT.

Effect of School Size on Athletic Training Employment Status in Public Schools

Moderate strength of agreement in direction was present between locale and school size in public schools, which meant larger public schools were located in more urbanized areas. The binary logistic regression revealed that the locale and school size variables were significant in independently predicting AT employment status. However, the extent of the effect of school size on AT employment status was much larger than that of locale as the ORs indicated (2.883 versus 0.927) in the logistic regression model (Table 7). According to the model, the odds of access to AT services increased by 2.883 times when school size went up by 1 category, and it is safe to state that in public schools, school size is a more critical predictor of AT employment status than locale, although locale explains AT employment to a small extent.

Limitations

One limitation of our research was that we did not include the regulatory status (eg, certification, registration, or licensure) of the ATs in our database. This may leave the definition of AT and medical care provided by ATs unclear, especially in a state where minimal regulation is required (eg, California). To determine a more accurate extent of AT status and medical coverage by an AT, future authors should clarify the regulatory status of the ATs.

We were only able to confirm geographic settings (locale) and school size as variables for examining AT employment status; therefore, we are limited in our understanding of the role of other factors that may contribute to the provision of AT service by schools. Pike et al,¹² who examined barriers to AT employment in secondary schools, found that budgetary constraints, lack of awareness of the role of ATs, small school size, and rural location limited AT employment. Of those factors, budgetary constraints were identified most frequently during the interview process.¹² Thus, although we did not examine budget availability, it may be another important factor in AT employment status in secondary schools.

We made every effort annually to ensure the accuracy of the employment, enrollment and locale data, but we are unable to guarantee with 100% certainty that these data were from the same year in all cases for each school. Further, our data were limited in that NCES typically is 1 year behind the current calendar year in determining school enrollment and locale. Although NCES school enrollment sizes and locale do not typically change from year to year, employment status may have changed during that 1-year period. Considering all factors, these data are the most accurate that the ATLAS project was able to obtain and the most up-to-date data available from the NCES and the US Department of Education.

Future Directions

We successfully quantified and described factors pertaining to AT employment in secondary schools. However, to better understand the challenges and barriers for schools in hiring AT services, we must take other factors into account. Budgetary constraints were previously found to be an important factor limiting AT employment,¹² so ongoing efforts to understand the relationship between budgetary availability and AT employment should be explored. Examining socioeconomic status may reveal how the budget affects AT employment. At the time of the data export for our study, socioeconomic status from the American Census Survey (median family and household income) was not available or included in the database. Certainly, NCES free and reduced-price lunch information was available. Nonetheless, we elected to not include this information because it was beyond the scope of our description of services by locale and school size. In our future work, we aim to bring these factors and possible confounders together and assess the effect of each with a regression-based approach.