Implementation of the National Collegiate Athletic Association Sickle Cell Trait Screening Policy: Methods and Staff and Athlete Perspectives

Abstract

Introduction

This paper describes methods for a national study evaluating the implementation of the National Collegiate Athletic Association’s (NCAA) policy on sickle cell trait (SCT) screening of athletes and describes attitudes toward the screening.

Methods

In Fall 2020, 343 Division I schools, 302 Division II schools, and 426 Division III schools were invited to participate in this national survey.

Results

Across 123 participating schools, a total of 168 sport medicine administrators (121 head athletic trainers and 47 team physicians), 268 athletic staff (128 staff athletic trainers and 140 coaches), and 1,424 athletes from basketball, football, soccer, lacrosse, track and field completed the survey. While the vast majority of respondents agreed/strongly agreed with the screening policy, there was varying support for how the policy was implemented including prioritizing SCT screening versus screening for other conditions (40–50% agreed/strongly agreed), focusing on sports with higher risk of overexertion versus universal screening (50–75% agreed/strongly agreed), and focusing on racial and ethnic groups where SCT is more prevalent (25–40% agreed/strongly agreed). Perspectives varied by NCAA division and race. Higher SCT knowledge scores were associated with believing that screening all athletes for SCT is important.

Conclusions

Discussion of these findings provides important context for assessing how genetic screening requirements are implemented within collegiate athletics and more broadly.

Key Points

• Respondents in this national study generally supported the NCAA SCT screening policy.

• Yet SCT screening perspectives varied by NCAA division, race, and SCT knowledge.

• Understanding the perspectives of the sport medicine administrators and athletic staff responsible for SCT screening and precautions and the athletes subject to screening provides important context for assessing how SCT screening and future screening programs are implemented.

Introduction

The National Collegiate Athletic Association (NCAA) Sickle Cell Trait (SCT) screening policy is a one-of-a-kind nationwide genetic screening initiative and one of the largest genetic screening requirement programs implemented by a private entity in the USA. As first written, the policy required all athletes beginning their initial season of eligibility or trying out for a team to confirm their SCT status by (a) showing proof of prior testing for the trait, (b) undergoing a sickle cell solubility test, or (c) signing a liability waiver to opt out of testing [1, 2]. The policy was implemented in Division I (DI) in 2010 and expanded to Division II (DII) in 2012 and Division III (DIII) in 2014. In the last couple of years, governing bodies comprised school representatives voted to remove the waiver option, so since August 1, 2022, all incoming NCAA athletes are required to be screened or provide proof of previous testing.

The implementation of the NCAA SCT policy has generated ongoing discourse and debate regarding the need for and implications of a mandatory screening program. Prominent sickle cell-related organizations such as the American Society of Hematology (ASH), the Sickle Cell Disease Association of America (SCDAA), and the Secretary of the US Department of Health and Human Services’ Advisory Committee on Heritable Disorders in Newborns and Children (SACHDNC) have opposed the policy, stating that current scientific evidence does not justify screening all college athletes; instead, they have advocated for universal precautions to protect all athletes from exertion-related illness [3–7]. Despite the controversy, the policy stands.

Several studies examining the relationship between SCT and varying intensities of physical exertion, altitude, and heat have shown that complications associated with the polymerization of deoxy-hemoglobin S under these conditions can lead to splenic infarction, gross hematuria, pulmonary embolism, exertional rhabdomyolysis, and hyphema, among other nontraumatic injuries [8–10]. One stated goal of the policy was to reduce or prevent these types of catastrophic events from arising by identifying athletes who have SCT and may experience increased risk during participation. Since the 2010 adoption of the NCAA SCT screening policy, NCAA athlete exertional sickling-related deaths declined from 10 in 2001–2010 to 2 in 2011–2020 (incidence rate ratio = 0.29, 95% CI: 0.03–1.35, p = 0.146) [11].

SCT screening has potential costs and risks, both anticipated (e.g., the economic costs of testing) and unanticipated (e.g., stigmatization and discrimination). Understanding how genetic screening policies are implemented is essential both for maximizing the potential benefits of screening and for identifying and mitigating the associated risks. It also provides insight into how the public understands race, genetics, and health risk as those subject to the NCAA’s policy may reflect broader societal beliefs about who faces this risk, as well as context-specific attitudes about who should be tested and how to respond to athletes who have tested positive.

Previous researchers conducted a preliminary study on the implementation of the NCAA SCT screening policy and the attitudes and experiences of athletic staff and athletes affected by the policy. The study revealed variation in implementation across schools on dimensions including who paid for testing, which screening tests were used, whether genetic counseling was provided, if the waiver was offered, and how to manage athletes with SCT [12, 13]. This variation in implementation can affect the likelihood of achieving both primary benefits (e.g., decreased mortality) and secondary benefits (e.g., change in knowledge about SCT and individual SCT status). Participants indicated schools provided little education for coaches, athletic trainers (ATs), and athletes on the rationale for implementing a universal screening policy. Athletic staff at most schools found it beneficial to know athletes’ SCT status but wanted clearer guidance and more specific instructions from the NCAA on effective implementation strategies [12].

Many of the questions about the necessity of universal screening stem from a common awareness about population differences in SCT prevalence. Specifically, SCT is more common among people with ancestors from certain parts of Africa, the Mediterranean basin, India, the Arabian Peninsula, the Caribbean, and South and Central America [14]. In the USA, the prevalence is highest among African Americans, with about 1 in 13 African American babies being born with SCT [15]. Screening for attributes that are more prevalent in one racialized group than others raises concerns that the risks of stigma, financial burden, or lost opportunity will be disproportionately borne by members of that group. Validating this concern, some participants in the study by Baker et al. [12] believed that black athletes were the only ones at risk for having SCT and supported targeted over universal screening of athletes. These findings suggest that having the misconception that only black athletes can have SCT may reduce support for universal screening, while also placing athletes of other racialized groups who unknowingly have SCT at risk since they might opt out of learning their SCT status. Thus, in order to ensure this policy is most effective, it is important to investigate how the policy is being implemented, factors that contribute to buy-in from the participants, and what steps can be taken to maximize benefits and minimize potential harms.

The aims of the national study described here were to (1) assess implementation, risks, and secondary benefits of the NCAA SCT screening policy and determine contributors to and implications of variation and (2) provide guidance on the current NCAA SCT policy and practice and inform other similar public health policies and practices. The study directly addresses research gaps in secondary prevention strategies noted at a national summit on SCT [16] and provides an unprecedented source of empirical data as well as strategies for addressing issues associated with new frontiers in public health genetics. This paper details the methods of the study and describes attitudes among sport medicine administrators (head athletic trainers [HATs] and team physicians [TPs]), athletic staff (staff ATs and coaches), and athletes about the NCAA’s policy to screen athletes for SCT.

Methods

This national study used a mixed-methods research approach, which included online surveys and semi-structured telephone interviews with a subset of HATs, TPs, staff ATs, coaches, and athletes at NCAA colleges and universities. This paper reports the procedures for administering the online survey and compares survey responses across participant groups. The Duke University Institutional Review Board approved the study protocol (IRB #2019-0613).

Instruments

A previous study on NCAA schools’ SCT screening practices [12, 13] guided the initial version of survey questions, as well as study procedure and interview guidelines. Separate surveys were created for the three groups: sport medicine administrators (HAT/TP), athletic staff (staff AT/coach), and athletes. Survey measures assessed respondent characteristics in addition to information in the following four domains: (1) SCT knowledge; (2) perspectives on and experiences with the screening policy; (3) college/university implementation and positive test management practices; and (4) attitudes and beliefs about the relationship between genetics and race. While many survey items in domains 1, 2, and 4 were consistent across the three surveys, domains were tailored for each group in accordance with their roles. The survey items included adaptations of questions from previous research [12, 17–19], as well as items that were unique to this context. For instance, since data collection took place during the first 2 years of the COVID-19 pandemic, additional questions were added regarding participation in college sports during COVID-19. Response formats included both fixed-choice and open-ended items to test the study hypotheses.

Survey questions were designed by a multidisciplinary research team with expertise in survey design, program evaluation, race and genetics, sickle cell disease and trait, qualitative research, epidemiology, and sport injury. The research team held multiple rounds of team meetings and group discussions to revise each survey and customize survey questions for each group. A diverse group of current and former NCAA athletes from one institution participated in survey piloting to identify and adjust challenging items. An advisory committee that included experts in genetics, sickle cell disease and trait, public health screening, and NCAA organizational practices and policies provided additional guidance on survey drafts and potential recruitment procedures. Expert feedback, current literature, and research team discussions informed multiple rounds of survey revisions and refinements.

Sampling

The initial sampling frame consisted of 343 DI schools, 302 DII schools, and 426 DIII schools who were members of the NCAA at the time the sample was drawn (Sept 2020). The NCAA provided a list including contact information for the HAT at each school. A two-stage probability sample design was implemented to make the data collection process more manageable for schools, reduce overall costs, and decrease participant burden. To be eligible to participate in the study, as defined by stage 1 of the sample design, the school needed to actively participate in one or more of the following sports programs during the previous academic year: men’s and women’s basketball, football, men’s and women’s soccer, men’s and women’s lacrosse, or men’s and women’s track and field. These five sports programs had particular relevance to our project and were among the NCAA championship sports with the largest numbers of athletes. Since we were not able to oversample athletes with SCT, we chose basketball, football, and track and field to maximize potential inclusion of athletes with SCT, given that SCT-related deaths had occurred in these sports. Lacrosse was chosen because it was the fastest-growing sport in the NCAA [20], while soccer offered a broad range of ethnic diversity among athletes [21].

Stage 2 of the sampling design included randomly selecting up to two sports at each eligible school. Since schools that only participated in 1 of the 5 sports the previous season were allowed to be in the study, at some schools only one sport was included. At this stage, the HAT at each school served as a liaison between the research team and the TPs, coaches, staff ATs, and athletes within the randomly selected sports. HATs also provided the frame counts and demographic composition of athletic staff and athletes for both men’s and women’s teams within those selected sports to allow for nonresponse adjustments and weights. There was no further sampling after randomly choosing the sports – all TPs, staff ATs, coaches, and athletes within selected sports were eligible to participate.

Recruitment

HATs at each school in the stage 1 sampling frame were mailed letters and sent emails inviting their respective school to participate in the study. To determine eligibility, the HATs completed a brief online screening tool that obtained informed consent and delineated which of the five sports were available at their school (stage 1). HATs at eligible schools then provided information in the online screening tool about the size and demographic composition of the coaching staff, staff ATs, and athletes for up to two randomly selected sports (stage 2). Size and demographic composition were reported separately for men’s and women’s teams.

Data collection started when the country was besieged by the COVID-19 pandemic; thus, two waves of data collection were necessary to obtain adequate sample sizes. The first wave of data collection occurred during the 2020–2021 academic year. The initial solicitation started in late Fall 2020 and included three follow-up reminders. COVID-19 potentially impacted data collection in three powerful ways: (i) some sport teams were either dissolving or not actively participating that season; (ii) email proved unreliable and many HATs were not going into the office to retrieve mail; and (iii) program cuts had a wide variety of consequences on staffing levels. Each of these made it challenging for HATs to learn about the study and may have reduced survey distribution and participation.

For the purposes of this study, if the selected sport teams had active rosters for the 2020–21 season, they were eligible to participate in the study. Even if team play was sidelined by COVID-19, all of the athletes on the rosters would have undergone SCT screening prior to the start of the season. With HATs infrequently going into their offices, unreliable email addresses, spam filters, and unstable staffing, study research staff spent considerable time calling nonresponders for contact information updates. Consequently, the number of positively responding schools to wave 1 (n = 210/1,071) was low, so we implemented a second wave of data collection during the 2021–2022 academic year in the Fall of 2021 (see Table 1). We obtained an updated list of HATs from the NCAA (n = 949), but the fielding process was similar to wave 1 without paper letters, and again we spent considerable time calling schools pursuing updated contact information for the purpose of direct recruitment into the study.

Table 1.

Study recruitment schedule

Solicitations	Wave 1 20/21 academic year		Wave 2 21/22 academic year
	dates	sample size	dates	sample size
Total number of schools	​	1,084	​	​
Schools excludeda	​	13	​	​
Initial invitation	October 27, 2020	1,071	September 14, 2021	949
Second invitation	January 12, 2021	1,001	Calls and emails on rolling basis	–
Third invitation	January 27, 2021	989		–
Fourth invitation	February 24, 2021	960		–
Updated contact information	February 24, 2021–May 24, 2021	68	September 30, 2021–January 12, 2022	70
Summer requests and last attempt	June 3, 2021	816	​	​
HATs, consented, no surveys	​	​	February 23, 2022	44

^aSchools excluded were not in the USA, were in Puerto Rico, or had closed or left NCAA.

Survey Rollout

We asked the HAT to complete a survey and to invite all eligible TPs, staff ATs, coaches, and athletes from the two randomly selected sports at their institution to complete surveys, as well. HATs did so by distributing the survey links via team management applications and email listservs. We also asked HATs to send two reminder emails with embedded survey links to all nonresponders at 2- and 4-week intervals. We chose to have HATs serve as survey distribution liaisons because of their knowledge of SCT implementation policy within their schools and due to the lack of a publicly available list of athletic staff and athlete email addresses. We attempted to field the surveys during periods in which the chosen sports were not in playoffs.

All participants were initially incentivized with HATs receiving USD 100 for their assistance with recruitment and survey administration. In wave 2, the HAT incentive was increased to USD 300. TPs, staff ATs, coaches, and athletes were all offered USD 10 in wave 1 and USD 20 in wave 2 for completing the survey. At the end of the survey, all respondents were invited to participate in the semi-structured interviews.

Study Participation

Of the initial list of 1,084 schools provided by the NCAA, 13 schools were excluded because they were not in the USA, were in Puerto Rico, had closed, or had left the NCAA. Out of 1,071 eligible schools, 280 schools completed the initial screening tool (26.1%) and 177 schools consented to participate in the study (16.5% of all schools, 63.2% of 280 schools that completed the screener) (Table 2). Out of the 177 consenting schools, 120 schools had at least 1 survey from a HAT or TP (11.2% of all schools, 67.8% of consenting schools). Among those schools, 80 schools generated 273 AT and coaching staff surveys, and 72 schools yielded 1,588 athlete surveys.

Table 2.

Study participation flowchart

​	Participants, n	Schools, n	Proportion of schools by total number eligible schools, n = 1,071
All NCAA schools 2020/2021	​	1,084	​
Schools excludeda	​	13	​
Schools contacted	​	1,071	​
HAT initial screeners	280	280	26.1%
HATs consented	177	177	16.5%
HAT-TP surveys	162	120	11.2%
Coach-staff AT surveys	273	80	7.4%
Athlete surveys	1,588	72	6.7%

^aSchools excluded were not in the USA, were in Puerto Rico, or had closed or left NCAA.

Sampling Weights and Adjustments

Separate sets of weights were developed for each dataset we collected in this study. The HATs and TPs formed the first dataset and were weighted to represent all schools participating in at least one of the five chosen sports in this study. The second dataset consisted of athletic staff (i.e., coaches and staff ATs) who work with the chosen sports. The third dataset included athletes participating in the selected sports.

HAT/TP Weights

We calculated final weights for the HATs/TPs by using the following formula: (base weight * [1/probability of choosing a sport] * nonresponse adjustment), where base weight was divided by the number of participating schools in each of the corresponding nonresponse adjustment cells. If both HAT and TP responded for the same school, the base weight was divided by 2, so that the total base weight did not exceed the frame count (n = 1,071). Adjustments to the random selection of sports was simply the number of selected sports divided by the number of active sports at the participating school. Nonresponse adjustments were determined by dividing the sample count into the frame count, which was based on region (North, Midwest, South) and division type (DI-FBS, DI-FCS, DII, DIII). We collapsed cell counts of less than 5 (see online suppl. Table 1; for all online suppl. material, see https://doi.org/10.1159/000550672).

Staff AT/Coach Weights

The formula for weighting the staff AT/coach dataset was the same as the HAT/TP dataset: (base weight * [1/probability of choosing a sport] * nonresponse adjustment). The only difference was that nonresponse adjustments were based on population counts, which came from the staff AT/coach size provided by the HAT for the randomly selected sports. There were 27 adjustment cells by division (DI, DII, and DIII), sport (5 men’s and 4 women’s sports), and gender (man, woman). Counts with fewer than 5 were collapsed resulting in 23 final adjustment cells due to small sample sizes in men’s DI-DIII and women’s DI lacrosse and soccer (see online suppl. Table 2).

Athlete Weights

The formula for weighting the athlete dataset was the same as the staff AT/coach dataset: (base weight * [1/probability of choosing a sport] * nonresponse adjustment). Unlike the staff AT/coach weights, nonresponse adjustments were based on population counts or size of the athlete population provided by the Equity in Athletics Data Analysis Cutting Tool counts [22]. There were 27 adjustment cells by division (DI, DII, DIII), sport (5 men’s and 4 women’s sports), and gender (man, woman). Counts with fewer than 5 were collapsed resulting in 25 final adjustment cells due to small sample sizes in DI lacrosse and soccer in both men’s and women’s programs (see online suppl. Table 3).

Statistical Analysis

All analyses were performed in Statistical Analysis Software (SAS V9.4 2016). Participant demographics based on unweighted frequencies were summarized with percentages for categorical variables and means with range and standard deviations for continuous variables. In addition, analyses of dependent variables regarding attitudes toward the SCT screening policy took the sample design into account and were computed using the survey procedures in Statistical Analysis Software (SAS V9.4 2016). Unless otherwise specified, we provided weighted sample means and proportions with 95 percent confidence intervals. Multivariable logistic regression models were computed for each dependent variable (binary agree vs. disagree) adjusted for gender (woman vs. man), race (non-white vs. white for HAT/TP and staff AT/coach; black versus white, other versus white for athletes), division (DII and DIII vs. DI), and SCT knowledge score (continuous variable ranging from 0 to 10). For athletic staff, models also included a variable for role (staff AT vs. coach). Note that models for HAT/TP were not adjusted by role (HAT vs. TP) as this was accounted for by the statistical weights described above.

Results

A total of 168 administrators (121 [72.0%] HATs and 47 [28.0%] TPs) completed the survey representing 123 schools. Forty-four schools had responses from both the HAT and the TP with the remaining 78 schools having responses from either the HAT or TP. A total of 268 athletic staff (128 [47.8%] staff AT and 140 [52.2%] coaches) and 1,424 athletes completed the survey. Demographics for the three survey groups are presented in Table 3. Across all three groups, respondents were predominantly white, of non-Hispanic/Latino ethnicity, and from DIII institutions followed by DI and DII. HAT/TPs and staff AT/coaches were more likely to be men (66.1% and 54.1%), whereas athletes were more likely to be women (59.1%). Respondents represented and/or supported a variety of sports.

Table 3.

Respondent demographics by survey respondent group: HAT/TP, staff AT/coach, and athlete (unweighted)

	Sports medicine administrative staff (HAT/TP)		Athletic staff (staff AT/coach)		Athlete
	N	%	N	%	N	%
Total	168	100.0	268	100.0	1,424	100.0
Role
HAT	121	72.0	–		–	–
TP	47	28.0	–		–	–
Staff AT	–	–	128	47.8	–	–
Coach	–	–	140	52.2	–	–
Athlete	–	–	–	–	1,424	100.0
Gender
Woman	57	33.9	122	45.5	842	59.1
Man	111	66.1	145	54.1	578	40.6
Unknown/other	–	–	1	0.4	4	0.3
Birthplace
USA	167	99.4	253	94.4	1,281	90.2
Outside USA	1	0.6	15	5.6	139	9.8
Race (more than one can apply)
American Indian or Alaskan Native	1	0.6	4	1.5	12	0.8
Asian	0	0	5	1.9	41	2.9
Black or African American	6	3.6	34	12.7	308	21.6
Native Hawaiian or Other Pacific Islander	0	0	2	0.7	19	1.3
White	155	92.3	223	83.2	1,085	76.2
Other	8	4.8	7	2.6	36	2.5
Hispanic/Latino ethnicity
Yes	7	4.2	15	5.6	109	7.7
No	160	95.2	252	94.0	1,315	92.4
Missing	1	0.6	1	0.4
NCAA Division
I	54	32.1	83	31.0	374	26.3
II	46	27.4	75	28.0	368	25.8
III	68	40.5	110	41.0	682	47.9
Sport you support or represent (more than one can apply)
Men’s basketball	110	65.5	53	19.0	54	3.8
Women’s basketball	101	60.1	62	23.0	145	10.2
Football	79	47.0	48	17.0	183	12.9
Men’s lacrosse	52	31.0	27	10.0	56	3.9
Women’s lacrosse	61	36.3	41	15.0	129	9.1
Men’s soccer	81	48.2	42	15.0	120	8.4
Women’s soccer	97	57.7	64	23.0	324	22.8
Men’s track and field	84	50.0	67	25.0	196	13.8
Women’s track and field	97	57.7	68	25.0	277	19.5
Other	71	42.3
NCAA SCT Screening Policy
Not knowledgeable	3	1.1	40	14.9	608	42.7
Somewhat knowledgeable	46	27.4	117	43.7	659	46.3
Knowledgeable	75	44.6	86	32.1	129	9.1
Very knowledgeable	45	26.8	23	8.6	28	2.0

	Sports medicine administrative staff (HAT/TP)		Athletic staff (staff AT/coach)		Athlete
	mean (sd)	range	mean (sd)	range	mean (sd)	range
Age, years	43.0 (10.0)	25–72	34.5 (11.1)	22–75	19.8 (1.4)	18–24
Years in current position	13.0 (9.5)	1–49	9.5 (9.1)	1–44	–	–
Years in current position at institution	9.0 (8.7)	0–48	5.1 (7.1)	0–41	–	–
SCT Knowledge Scale	9.0 (0.9)	6–10	8.0 (1.3)	2–10	7.0 (1.3)	1–10

On average, HAT/TPs were older than staff AT/coaches (43.0 vs. 34.5 years old) and had more years of experience (9.5 vs. 1.3 years in current position). Sixty percent of HAT/TP and staff AT/coaches had attained a masters’ degree. The majority of staff AT/coaches were employed by the athletics departments (85.8%) whereas HAT/TPs were employed by athletics departments (60.7%), clinics/hospitals (noncollege/university-affiliated [19.6%] or college/university-affiliated [14.9%]), or other entities (4.8%). On average, athletes were 19.8 (range 18–24) years old and were in their first year of eligibility (36.1%), second year (25.1%), third year (21.4%), fourth year (12.4%), or other (5.0%).

Overall, 71.4% of HAT/TPs self-reported they were knowledgeable/very knowledgeable about the NCAA SCT screening policy compared to 40.7% of staff AT/coaches and 11.1% of athletes (Table 3). The SCT knowledge scale scores supported the three groups’ self-reported knowledge with average scores of 9.01 (HAT/TP), 7.99 (staff AT/coach), and 6.97 (athlete) out of 10 possible points.

SCT Screening Policy Perspectives

Figure 1 provides unadjusted weighted results for SCT screening policy perspectives for all three respondent groups. The vast majority of respondents from the three groups agreed/strongly agreed with the NCAA SCT screening policy, specifically that “athletes must be screened or present a previous test result to establish SCT status” (84.6% HAT/TP, 93.2% staff AT/coach, and 87.3% athlete). Despite this high level of support for establishing athlete SCT status, 41% of HAT/TP, 49.8% of staff AT/coaches, and 51.1% of athletes agreed/strongly agreed that “screening for other conditions, such as arrhythmia, is more important.”

Fig. 1.

Perspectives on SCT screening policy stratified by survey respondent group: head athletic trainer/team physician (HAT/TP) (n = 165), staff athletic trainer/coach (AT/coach) (n = 268), and athlete (n = 1,424^a) (weighted percent [%] and 95% confidence intervals [CI], vertical bars represent 95% CI). ^aMissing values for athletes: (1) n = 57; (2) n = 60.

Half or more of respondents from the three groups agreed/strongly agreed “SCT screening should focus on athletes whose sports place them at greater risk for over-exertion” with the highest agreement among athletes (51.3% HAT/TP, 58.4% staff AT/coach, and 74.7% athletes). A quarter or more agreed/strongly agreed that “SCT screening should focus on athletes from racial/ethnic groups in which SCT is more common” (25.6% HAT/TP, 31.6% staff AT/coach, and 41.8% athletes). Half of athletes (49.9%) agreed/strongly agreed that “the NCAA policy that athletes with SCT should use precautions when exercising is not realistic” compared to 17.8% of HAT/TPs and 36.2% of staff AT/coaches.

Results from multivariable logistic regression models across all three respondent groups are presented in Table 4 for each dependent variable (binary agree versus disagree) adjusted for gender, race, NCAA division, and SCT knowledge score. Notable differences were observed by NCAA Division and SCT knowledge scores. Among staff AT/coaches, those in Division III were more likely to agree/strongly agree that “the NCAA policy that athletes with SCT should use precautions when exercising is not realistic” (OR = 2.61; 95% CI: 1.28–5.32) and “screening for other conditions, such as arrhythmia, is more important” (OR = 1.99; 95% CI: 1.02–3.89) compared to those in Division I. Among athletes, higher SCT knowledge was associated with lower odds of agreement that “screening for other conditions, such as arrhythmia, is more important” (OR = 0.88; 95% CI: 0.79–0.98), “the NCAA policy that athletes with SCT should use precautions when exercising is not realistic” (OR = 0.82; 95% CI: 0.74–0.91), and “SCT screening should focus on athletes from racial/ethnic groups in which SCT is more common” (OR = 0.89; 95% CI: 0.80–1.00).

Table 4.

Factors associated with perspectives on SCT screening policy by survey respondent group: HAT/TP (n = 165), staff AT/coach (n = 268), and athlete (n = 1,424) (weighted odds ratios and 95% CI)

​	HAT/TP		Staff AT/coach		Athlete
	beta (SE)	OR (95% CI)	beta (SE)	OR (95% CI)	beta (SE)	OR (95% CI)
The NCAA policy that athletes must be screened is appropriate
Woman	0.01 (0.24)	1.03 (0.40, 2.64)	−0.07 (0.27)	0.87 (0.29–2.55)	0.09 (0.10)	1.20 (0.83–1.74)
Non-white race	0.30 (0.41)	1.81 (0.37, 9.01)	1.09 (0.52)*	8.91 (1.14–69.50)	​	​
			p = 0.04
Black race (athlete only)	​	​	​	​	−0.11 (0.12)	0.80 (0.49–1.31)
Other race (athlete only)	​	​	​	​	0.19 (0.20)	1.46 (0.67–3.18)
AT (staff AT/coach only)	​	​	0.92 (0.36)*	6.33 (1.56–25.63)	​	​
			p = 0.01
DII	−0.08 (0.30)	0.75 (0.27, 2.10)	−0.49 (0.33)	0.32 (0.08–1.31)	−0.002 (0.18)	0.84 (0.45–1.56)
DIII	−0.12 (0.31)	0.73 (0.25, 2.09)	−0.17 (0.32)	0.44 (0.11–1.76)	−0.18 (0.13)	0.70 (0.45–1.11)
SCT knowledge score	−0.07 (0.28)	0.93 (0.54, 1.63)	0.01 (0.20)	1.01 (0.69–1.50)	−0.03 (0.08)	0.97 (0.83–1.13)
R2 (f test)	0.005 (0.18, p = 0.97)		0.07 (3.33, p = 0.003)		0.005 (1.26, p = 0.27)
The NCAA policy that athletes with SCT should use precautions when exercising is not realistic for most athletes who test positive for SCT
Female	−0.07 (0.23)	0.87 (0.36, 2.13)	0.001 (0.16)	1.00 (0.53–1.90)	−0.09 (0.07)	0.83 (0.64–1.08)
Non-white race	−0.41 (0.41)	0.44 (0.09, 2.28)	0.10 (0.18)	1.23 (0.60–2.55)	​	​
Black race (athlete only)	​	​	​	​	0.26 (0.09)**	1.67 (1.18–2.36)
					p = 0.004
Other race (athlete only)	​	​	​	​	0.33 (0.14)*	1.95 (1.12–3.37)
					p = 0.02
AT (staff AT/coach only)	​	​	−0.81 (0.18)***	0.20 (0.10–0.40)	​	​
			p < 0.0001
DII	−0.12 (0.37)	1.03 (0.28, 3.80)	0.07 (0.22)	1.79 (0.82–3.94)	−0.12 (0.12)	0.79 (0.52–1.18)
DIII	0.27 (0.28)	1.51 (0.55, 4.17)	0.44 (0.20)*	2.61 (1.28–5.32)	−0.00 (0.09)	0.88 (0.65–1.20)
			p = 0.03
SCT knowledge score	−0.26 (0.27)	0.77 (0.45, 1.31)	0.10 (0.11)	1.11 (0.89–1.39)	−0.20 (0.05)**	0.82 (0.74–0.91)
					p = 0.0004
R2 (f test)	0.02 (0.64, p = 0.67)		0.14 (7.47, p < 0.0001)		0.04 (10.87, p < 0.0001)
SCT screening should focus on athletes from racial/ethnic groups in which SCT is more common [1]
Female	−0.08 (0.21)	0.84 (0.37, 1.93)	0.04 (0.15)	1.09 (0.60–2.00)	−0.08 (0.07)	0.86 (0.65–1.13)
Non-white race	−0.17 (0.34)	0.72 (0.19, 2.78)	−0.09 (0.19)	0.83 (0.39–1.78)	​	​
Black race (athlete only)	​	​	​	​	0.07 (0.09)	1.15 (0.80–1.65)
Other race (athlete only)	​	​	​	​	−0.03 (0.15)	0.94 (0.52–1.71)
AT (staff AT/coach only)	​	​	−0.34 (0.18)t	0.51 (0.25–1.02)	​	​
			p = 0.06
DII	−0.19 (0.31)	0.86 (0.30, 2.52)	−0.28 (0.23)	0.80 (0.36–1.75)	0.02 (0.13)	0.93 (0.61–1.41)
DIII	0.23 (0.25)	1.30 (0.54, 3.17)	0.32 (0.20)	1.43 (0.72–2.82)	−0.11 (0.10)	0.82 (0.59–1.12)
SCT knowledge score	−0.22 (0.24)	0.80 (0.50, 1.27)	−0.20 (0.12)	0.82 (0.64–1.05)	−0.12 (0.06)*	0.89 (0.80–1.00)
					p = 0.04
R2 (f test)	0.01 (0.48, p = 0.79)		0.06 (2.75, p = 0.01)		0.01 (3.07, p = 0.005)
SCT screening should focus on athletes who sports place them at greater risk for overexertion [1]
Female	0.003 (0.17)	1.01 (0.52, 1.96)	−0.01 (0.15)	0.98 (0.55–1.76)	−0.08 (0.08)	0.86 (0.64–1.16)
Non-white race	0.30 (0.30)	1.81 (0.56, 5.88)	−0.20 (0.19)	0.67 (0.32–1.41)	​	​
Black race (athlete only)	​	​	​	​	−0.17 (0.10)t	0.71 (0.48–1.04)
					p = 0.08
Other race (athlete only)	​	​	​	​	−0.11 (0.16)	0.81 (0.43–1.52)
AT (staff AT/coach only)	​	​	0.04 (0.16)	1.08 (0.57–2.07)	​	​
DII	−0.09 (0.26)	1.09 (0.44, 2.70)	−0.36 (0.20)t	0.64 (0.32–1.26)	0.26 (0.15)t	1.32 (0.82–2.14)
			p = 0.07		p = 0.07
DIII	0.26 (0.22)	1.54 (0.69, 3.43)	0.27 (0.19)	1.20 (0.62–2.30)	−0.24 (0.11)*	0.80 (0.56–1.14)
					p = 0.02
SCT knowledge score	−0.06 (0.19)	1.06 (0.73, 1.55)	−0.16 (0.12)	0.85 (0.67–1.08)	−0.05 (0.07)	0.95 (0.83–1.08)
R2 (f test)	0.01 (0.54, p = 0.75)		0.03 (1.27, p = 0.27)		0.01 (2.70, p = 0.013)
Screening athletes for other sports-related conditions is more important than SCT [2]
Female	−0.53 (0.18)**	0.34 (0.17, 0.71)	−0.20 (0.15)	0.67 (0.38–1.19)	−0.04 (0.07)	0.93 (0.71–1.21)
	p = 0.004
Non-white race	−0.89 (0.35)*	0.17 (0.04, 0.67)	−0.20 (0.21)	0.67 (0.30–1.52)	​	​
	p = 0.01
Black race (athlete only)	​	​	​	​	−0.15 (0.09)	0.75 (0.53–1.06)
Other race (athlete only)	​	​	​	​	−0.05 (0.15)	0.91 (0.51–1.63)
AT (staff AT/coach only)	​	​	−0.05 (0.17)	0.91 (0.47–1.74)	​	​
DII	0.19 (0.26)	1.91 (0.78, 4.68)	−0.26 (0.21)	0.95 (0.46–1.99)	0.04 (0.12)	1.04 (0.69–1.58)
DIII	0.26 (0.24)	2.05 (0.89, 4.71)	0.48 (0.19)*	1.99 (1.02–3.89)	−0.04 (0.09)	0.96 (0.70–1.31)
			p = 0.01
SCT knowledge score	0.12 (0.20)	1.13 (0.75, 1.68)	−0.002 (0.12)	1.00 (0.79–1.26)	−0.13 (0.06)*	0.88 (0.79–0.98)
					p = 0.02
R2 (f test)	0.09 (3.39, p = 0.005)		0.05 (2.26, p = 0.035)		0.01 (2.56, p = 0.018)

Referents for variables: gender (man), race (non-white for HAT/TP and staff AT/coach; white for athletes), for staff AT/coach only (coach), and division (DI). Missing values for athletes: (1) n = 57; (2) n = 60.

^t>0.05 to <0.10, *<0.05, **<0.001, ***<0.0001.

Notable differences by gender and race were also observed. Among HATs/TPs, respondents identifying as women and non-white were less likely to agree that “screening for other conditions, such as arrhythmia, is more important” (women: OR = 0.34; 95% CI: 0.17, 0.71 and non-white: OR = 0.17; 95% CI: 0.04, 0.67). Among staff AT/coaches, respondents identifying as non-white were more likely to agree with the NCAA policy that “athletes must be screened or present a previous test result to establish SCT status” (OR = 8.91; 95% CI: 1.14, 69.50). Among athletes, respondents identifying as black or other race were more likely to agree “the NCAA policy that athletes with SCT should use precautions when exercising is not realistic” (black: OR = 1.67; 95% CI: 1.18, 2.36 or other race: OR = 1.95; 95% CI: 1.12, 2.37).

Discussion

The sampling strategy employed in this study was both novel and innovative and might be useful to others with large nationwide groups of respondents and those working with incomplete frame or population counts. Fortunately, the NCAA provided the listings of over 1,000 schools and contact information of current HATs. Once enrolled in the study, HATs provided the population counts for coaches, staff ATs, and athletes within the randomly selected sports. These counts provided the denominator for nonresponse adjustments for coaches and staff ATs but also allowed us to make population inferences beyond the participating schools by multiplying the selection probability for the corresponding school with the nonresponse adjustment at the school level. Therefore, the findings produced from this study, to the extent that the sample was random and unbiased, apply to all DI, DII and DIII schools participating in football, basketball, lacrosse, soccer, and track and field. Without the coach and staff AT counts provided by the HAT, the link to inferential statistics for that group would have been broken because we would not have the denominator for those programs by those participants (i.e., coaches/staff ATs).

To varying degrees, all three respondent groups in this study were knowledgeable about the SCT screening policy and most agreed/strongly agreed with the policy. SCT knowledge results in the current study 10 years after implementation were consistent with a previous survey of NCAA DI institutions in North Carolina 3 years after the screening policy was implemented which found 75% of athletes, 74% of coaches, and all ATs were knowledgeable about the policy [12]. Overall, support for the screening policy was higher in the current study (85% HAT/TP, 93% AT/coach, 87% athlete) compared to the earlier study (87% AT, 78% coach, 62% athletes) [12], suggesting that support for the policy may have improved during this period, at least among AT, coaches, and athletes. The prior study did not include TPs and did not delineate HAT roles.

Among ATs, coaches, and athletes, support for targeted screening based on sport and/or athlete race/ethnicity was substantially higher in the current study than in the earlier study. Half or more of respondents in this study (51.3% HAT/TP, 58.4% staff AT/coach, and 74.7% athletes) supported targeted screening based on sport compared to 2.8% coach, 0% AT, and 6.6% of athletes in the previous study [12]. Similarly, 25% or more of respondents in the current study (25.6% HAT/TP, 31.6% staff AT/coach, and 41.8% athletes) supported targeted screening based on athlete race/ethnicity compared to 5.6% coach, 3.3% AT, and 16.3% athletes in the previous study [12]. Changes in support for a policy that targets screening based on sport and/or athlete race/ethnicity may be due to having experienced the work involved in screening all athletes versus athletes in certain sports or groups when the prevalence of an athlete having SCT may be perceived as or in actuality relatively low. This may also reflect attitudes and knowledge about the risks to the health of athletes with SCT from sport, environmental conditions, or other factors. It is important to note when comparing findings of the current study to Baker et al. [12], survey respondents in Baker et al. were from 1 Southeastern state and provided a neutral option for all questions and 25% of athletes and 10–20% of ATs and coaches were neutral on targeted screening.

Variation in perspectives by NCAA division was expected a priori based on previous research [13, 23] and known differences in policy by division. According to bylaws at the time this study was conducted (2021/22), all schools were required to either establish SCT status through direct testing or a previous test result or allow athletes to submit a waiver of testing [24]. However, DIII bylaws went a step further and included language regarding educating athletes when they chose the waiver option [25]. As noted, effective August 2022, the waiver option was eliminated and all divisions are currently required to establish SCT status. In addition, previous research on SCT screening practices indicated that screening varied by division, with higher rates of screening for DI versus DII and DIII [23, 26]. Moreover, resources were identified as a major barrier to screening [23] and previous research on sports medicine staffing identified differences in resources by division where DI schools had 2 times the number of staff ATs, 3 times the total number of ATs, and 2 times the number of on-site physicians compared to DII and DIII schools [27]. Variation by division was also evident in our study. Staff ATs and coaches at DIII schools were more likely than those at DI schools to view screening for other conditions as more important than SCT. Moreover, ATs and coaches at DIII schools were more likely than ATs and coaches at DI schools to see it as unrealistic to expect athletes with SCT to use precautions when exercising. This may reflect different staff priorities, experiences, and practices surrounding SCT screening for DIII compared to other divisions. Given lower rates of screening and resources by division, future research is needed to understand how these perspectives impact implementation of the policy at each division.

Differences in perspectives were also observed in this study among athletes by race and SCT knowledge. Higher SCT knowledge scores among athletes were independently associated with recognizing the importance of SCT screening for all athletes regardless of race/ethnicity and for SCT screening compared to other conditions. However, compared to white athletes, athletes identifying as black or other race were more likely to agree that it is not realistic for most athletes with SCT to use precautions when exercising. This is in contrast to athletes with higher SCT knowledge scores who were less likely to agree that using precautions was not realistic. These findings suggest that health education for athletes may be important in increasing and maintaining support for screening programs as well as evidence-based practices that ensure the safety of athletes who have the screened conditions [28, 29].

Perspectives also differed by race among sports medicine administrative and athletic staff. HAT/TPs and staff AT/coaches who identified as non-white strongly supported screening athletes for SCT (OR = 1.81 and 8.91, respectively) and were less likely to think screening for other conditions was more important (OR = 0.17 and 0.67, respectively) compared to those who identified as white. Sports medicine administrative staff play a critical role in determining which screenings are required at their institution and how screening is implemented and along with athletic staff the actions taken after screening for athletes who screen positive. These differences among sport medicine administrators and athletic staff by race suggest further study to understand these differences in perspective and how they may impact screening selection, implementation, and any actions taken. The NCAA SCT screening policy requires all member institutions to verify athlete SCT status, and then it is up to each member institution and their staff to determine how the policy is implemented including type and location of screening, precautions, education, genetic counseling, etc.

This study had several limitations. First, study recruitment was greatly impacted by the COVID-19 pandemic. Although the research team continued recruiting throughout the pandemic, the final response rates for the three respondent groups were lower than projected, largely due to changes and adjustments of the sport seasons and activities due to the pandemic. For example, many universities and colleges dropped some sports seasons or postponed them to later in the year. These changes and unprecedented challenges significantly increased the workload of HATs, who served as our entrée into the school. Specifically, even in a regular sports season, HATs are busy supervising the athletic training staff, coordinating schedules and activities, and managing athlete healthcare. The pandemic brought additional responsibilities, such as COVID testing, reporting, and contact-tracing; establishing and enforcing rules for athletes for avoiding infection; altered sports schedules; reduced access to treatment areas; and, at many schools, reduced athletic training staff due to a drop in athletic department revenues. As we relied on HATs to send athletic staff and athletes links to the survey Websites and periodic reminders to complete the survey, those additional responsibilities left HATs with little time or energy for completing surveys or distributing surveys to their staff and athletes. Another issue that may have reduced the sample size was that several HATs communicated their inability to distribute this survey to athletes at their schools without the study’s receiving approval via an athletics-based internal review at their school. Of the HATs (n = 65) who provided reasons for not participating in the study, the majority noted lack of time (n = 46) primarily due to the additional tasks due to COVID-19 or being short staffed; administration restrictions on research participation (n = 6); not relevant (n = 6) because their school does not administer tests or low SCT prevalence; other ongoing research with staff or students (n = 2); and other (n = 5). Consequently, the smaller sample size impacted our weighting strategies and analyses. For instance, we were unable to weight fully by region and not at all by sport. Analyses could not support full race stratification, stratification by staff role (e.g., HAT vs. TP), nor could we adjust models by sport.

Despite these limitations, this study is important for several reasons. First, to our knowledge, it is the largest and most comprehensive evaluation of the NCAA SCT screening policy. Second, it provides an unprecedented window into the complexities of the processes, benefits, and challenges of implementing the policy filling a critical knowledge gap identified at a recent national summit on SCT [16]. Third, it facilitated innovation in the exploration and execution of strategies for conducting such a study during a challenging data collection period (i.e., the pandemic) and in the collection of data about the impacts of COVID19 on college sports. Assuming that the study results are representative, this study allows for the development of evidence-based approaches for addressing issues regarding the NCAA SCT screening policy and enhancing its implementation. In addition, it can serve as a data-driven guide for similar public health endeavors.

Conclusion

This research was not designed to make a determination on the merits of the current policy, but rather sought to provide athletics policymakers, administrators, staff, and others concerned about college athletes’ health with information about context and implementation that can help them understand and make decisions about screening design, implementation, and ancillary programming such as education. Respondents in this national study generally supported the NCAA SCT screening policy. Yet SCT screening perspectives varied by NCAA division, race, and SCT knowledge. Future work from this national study will seek to explain these differences in perspectives and how they may impact successful implementation of this screening mandate. Understanding the perspectives of the sport medicine administrators and athletic staff responsible for SCT screening and precautions and the athletes subject to screening provides important context for assessing how SCT screening and future screening programs for otherwise healthy individuals are implemented within college sports and nationally.

Acknowledgments

We thank the head athletic trainers, team physicians, staff athletic trainers, coaches, and athletes who participated in this study. We thank the National Collegiate Athletic Association (NCAA) for providing school contact information and their support of this study. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. Results of the present study do not constitute endorsement by ACSM or the NCAA.

Statement of Ethics

This study protocol was reviewed and approved by the Duke University Institutional Review Board (Approval No. IRB #2019-0613). All participants provided written informed consent to participate in this study.

Conflict of Interest Statement

Author K.K. is director of the National Center for Catastrophic Sport Injury Research, which is funded to conduct national surveillance in part through a contract with the National Collegiate Athletic Association. Authors C.R. and M.M. report 2012 funding from a grant from the National Collegiate Athletic Association. For the remaining authors, no conflicting interests were declared.

Funding Sources

This study was funded by the National Human Genome Research Institute (Grant #R01HG010364) at the National Institutes of Health. The funder had no role in the design, data collection, data analysis, and reporting of this study.

Author Contributions

All authors of this paper have contributed to all four of the ICMJE authorship criteria: (1) Substantial contributions to the conception or design of the work, or the acquisition, analysis, or interpretation of data for the work; (2) drafting the work or reviewing it critically for important intellectual content; (3) final approval of the version to be published; and (4) agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Kucera, Agans, Schmid, and McDonald contributed to design, acquisition, analysis, and interpretation; drafting and review; final approval; and accountability of work. Robbins contributed to acquisition and interpretation; drafting and review; final approval; and accountability of work. Yang contributed to acquisition, analysis, and interpretation; drafting and review; final approval; and accountability of work. Haagen contributed to design and interpretation; drafting and review; final approval; and accountability of work. Silberberg and Royal contributed to conception, design and interpretation; drafting and review; final approval; and accountability of work. Marean contributed to acquisition; drafting and review; final approval; and accountability of work.

Funding Statement

This study was funded by the National Human Genome Research Institute (Grant #R01HG010364) at the National Institutes of Health. The funder had no role in the design, data collection, data analysis, and reporting of this study.

Data Availability Statement

All data generated or analyzed during this study are included in this article are included in this article and its online supplementary material files. Further inquiries can be directed to the corresponding author.