The Impact of the Number of Student Athletes on Burnout and Work-Family Conflict of High School Athletic Trainers

Authors: Christianne M Eason, Alexandrya H Cairns, and Stephanie M. Singe

Department of Kinesiology, University of Connecticut, CT, USA

Corresponding Author:
Christianne M Eason, PhD, ATC
President of Sport Safety
Department of Kinesiology, University of Connecticut
2095 Hillside Road U-1110, Storrs, CT 06269
Cell: 617-548-8283
Twitter: CM_Eason
Fax: 860-486-1123
Website: ksi.uconn.edu
Email:  christianne.eason@uconn.edu

Christianne M. Eason is the President of Sport Safety at the Korey Stringer Institute which is housed in the Department of Kinesiology at the University of Connecticut. Her research interests include the work-life interface of athletic trainers, specifically organizational factors and sports safety advocacy.

Alexandrva H Cairns is a second year PhD student in the Department of Kinesiology at the University of Connecticut. Her research interests include work-life balance among athletic trainers, and more specifically perceptions of patient care and clinician well-being.

Stephanie M. Singe is an associate professor in the Department of Kinesiology. Her research focus is on work-life balance and other factors that influence the job satisfaction and quality of life of an athletic trainer. She is lead author of the position statement on Facilitating Work-Life Balance in Athletic Training Practice Settings.

The Impact of the Number of Student Athletes on Burnout and Work-Family Conflict of High School Athletic Trainers

ABSTRACT

Context: The relationship between clinician’s perceptions of patient care and burnout and work-family conflict (WFC) has not been examined as closely. In the high school setting, where athletic trainers often work as the only clinician and/or have a high volume of patients it is important to determine if experiences of burnout and WFC impacts perceptions of patient care.

Objective: Determine if any relationship exists between burnout and WFC and athletic trainer’s perceptions of patient care.

Design: Cross-sectional study

Setting: Online web-based survey

Patients or Other Participants: Athletic trainers were emailed through the Athletic Training Location and Services (ATLAS) database and invited to participate. Data from 573 (n = 373 (65.1%) women, n = 195 (34.2%) men, n = 1 (0.2%) transgender woman, n = 1 (0.02%) not listed, and n = 2 (0.3%) Prefer Not to Answer) were included in data analysis.

Main Outcome Measure(s): Data analyzed for this study included basic demographic information, the Copenhagen Burnout Inventory, a Work-Family Conflict Scale, and 5 questions specific to patient care (open-ended and ranking).

Results: Overall, participants reported low levels of burnout and WFC. The majority (55.7%) were satisfied with the time they had to deliver patient care and (65.7%) the care they were able to deliver. Stress was most often selected as a factor that negatively impacted patient care, while exercise was most commonly selected as the factor that positively impacted patient care. Participants who were satisfied with patient-care had lower strain-based conflict (U = 32441.0, p = .030) and participants who were satisfied with time for patient care had lower total WFC (U = 29174.5, p < .001).

Conclusions: Student athlete number and interactions do not appear to be a source of burnout or WFC among high school athletic trainers. Work-related factors and personal well-being and mental-health appear to impact clinicians’ perceptions of care delivered to patients.

Keywords: Self-Care, Patient Care, Work-Life Balance

INTRODUCTION

Work-family conflict (WFC) and burnout have been studied extensively in the athletic training literature, as it is often linked to job satisfaction and turnover (11, 15-17, 26, 30). In fact, WFC is often a cause of burnout among athletic trainers (26). A hallmark characteristic of burnout is physical and psychological fatigue/exhaustion experienced by a person due to increased perceived stress (21-22). Burnout has been associated with compassion fatigue, which is the emotional strain that can occur from working in roles that require a person to care for others, while those individuals are under strain. Both compassion fatigue and burnout result in emotional and physical exhaustion, as well as a reduction in interest in those activities that they once enjoyed (2). Burnout has been reported among healthcare professionals including physical and occupational therapists (19), physicians and nurses (20), and athletic trainers (26). While burnout is a state of emotional, mental, and sometimes physical exhaustion precipitated by prolonged or repeated stress, WFC is a stressor that is experienced when demands between work and family roles are incompatible. Work-family conflict has been reported by athletic trainers when they struggle finding the time, energy, and resources to balance their professional and personal lives (1, 4, 8, 15).

Burnout and WFC have similar causative factors such as demanding work environment, long hours, as well as high workloads (8). Athletic trainers working in the secondary school setting are at risk for experiencing of burnout and WFC for several reasons including long work hours (27), weekend work, high patient-load since often only one athletic trainer is employed by a school, and a sport-minded organizational model which can lead to role incongruence (8). Additionally, the secondary school continues to grow as an employment setting and is considered the largest for employing athletic trainers (25).

While the concept of burnout and WFC has been examined extensively among the athletic training population, gaps still remain in the understanding of these constructs and their potential impact. Capel was one of the first to identify high patient loads as a causative factor to burnout among athletic trainers (5), but very little research beyond the study has examined factors influencing delivery of patient care. Burnout and WFC are stressors that can reduce an athletic trainer’s overall job satisfaction (23, 26), and for the case of the athletic trainer, job satisfaction can be relational to the care provided to patients.

Due to the limited understanding of athletic trainers’ perceptions of the impact of burnout and WFC on their ability to provide optimum patient care, the researchers identified a need to explore the phenomenon further. Therefore, the purpose of this research was to identify the factors that secondary school athletic trainers perceive are influencing their ability to provide quality patient care related to their own mental health and well-being. Additionally, the research  examined whether any relationship exists between perceptions of delivery of care and the time available to deliver individual patient care as it relates to WFC and burnout. Following are the hypotheses for the research.

H1a: The number of student-athletes in a secondary school setting would be positively correlated and predictive of burnout.

H1b: The number of student athletes in a secondary school setting would be positively correlated and predictive of WFC.

H2a: Secondary school athletic trainers who self-reported they perceived that they were not able to provide optimal care or did not have enough time to provide optimal care to individual student athletes would report higher levels of burnout.

H2b: Secondary school athletic trainers who self-reported they were not able to provide optimal care or did not have enough time to provide optimal care to individual patients would report higher levels of WFC.

METHODS

Study Design

This study was part of a larger cross-section study that was exploring individual work-life interface factors that included burnout, WFC, and patient workload among secondary school athletic trainers. This study had Institutional review board approval prior to data collection. Participants were contacted via email and asked to participate in an online survey through the Qualtrics LLC Software Program (Provo, Utah). This manuscript focuses specifically on the impact of patient workload, burnout, and WFC variables.  

Procedures

All participants indicated his or her consent prior to initiating the online screening and questionnaire. Participants were required to complete two screening questions to determine if they met inclusion criteria before they could complete the questionnaire. If participants did not meet inclusion criteria, they were directed to a survey termination page and thanked for their willingness to participate. The first two questions evaluating the inclusion criteria confirmed the participant worked in a secondary school and that at least 50% of their job responsibilities required working clinically with patients. After the screening questions, participants were presented with 14 demographic questions, 12 self-care questions, and 5 patient care questions. The final section of the survey consisted of 3 validated scales including 1) Copenhagen Burnout Inventory (CBI) (21), 2. The Perceived Stress Scale (10), and 3. The Work-Family Conflict Scale (6).

Participants

Secondary school athletic trainers were recruited though the Athletic Training Locations and Services (ATLAS) database (18), 7,386 emails were sent in Spring 2021 and 831 participants began the survey resulting in a 11% response rate. After cleaning the data and removing responses that were incomplete, 573 responses remained and were used in analysis.

Questionnaire

Demographic information at the beginning of the survey included age, gender, years as a certified athletic trainer, current workplace setting, and years in current workplace. Demographic information provided information on differences among groups and a comparison of student athlete work-load between workplace settings. The two scales used for this manuscript were the CBI (19 items), and the Work-Family Conflict Scale (18 items).

The CBI (21) is a previously validated psychological test that contains 19-items divided into three subscales; personal burnout, work-related burnout, and client-related burnout (21). While the Maslach Burnout scale is most often used in the athletic training literature (22), the CBI has been used to assess burnout among athletic training populations and was intentionally selected because of the client-related burnout subscale given the purpose of this study (13, 29). Respondents to the CBI are asked to provide their level of agreement on a 5-point Likert scale (0= Never/almost never or to a very low degree, 4= Always or to a very high degree) (21). Scoring of the CBI followed the scale instructions with scores <50 indicating low burnout, 50-74 indicating moderate burnout, 75-99 indicating high burnout, and 100 indicating severe burnout. This CBI has been shown to have good internal consistency (a= .86) among an athletic trainer population (21).

The second scale was the WFC scale, which is an 18-item scale designed to measure various facets of conflict, including time, strain and behavior-based conflict (6). The three sub-scales allowed patient workload to be isolated with each facet of conflict. The WFC scale has been previously validated and shown to have good internal consistency among an athletic trainer population (a= .89) (6). Respondents are asked to state their level of agreement using a 5-point Likert Scale (1= strongly disagree, 5=strongly agree), where higher total scores indicate higher levels of WFC. In addition to the three sub-scales mentioned above the scoring of the WFC scales also allows researchers to analyze the directionality of conflict whereby work interferes with family conflict (WIFC), and/or family interferes with work conflict (FIWC) (6).

Data Analysis

Data was collected using Qualtrics LLC Software Program (Provo, Utah), and downloaded into Excel (Microsoft Corporation, Redmond, WA). The data was filtered for incomplete responses and the responses that remained were further analyzed.

Mann Whitney U and Kruskal Wallace non-parametric analysis were used to identify any differences among groups. A Spearman correlation was performed to identify existing relationships between number of student athletes and results of the CBI and WFC scale and sub-scales. A linear regression was performed, where number of student athletes was the dependent variable and time-based conflict subscale was the independent variable. A Chi-Square Test of Independence was utilized to determine if there was an association between burnout and time for patient care, as well as burnout and satisfaction of patient care.

An a priori value for significance was set at P < .05 for all statistical tests. The Cronbach a was calculated for CBI and WFC conflict scale to determine reliability within the athletic training population.

RESULTS

Demographics and Burnout and Work-Family Conflict Scores

The majority of participants self-identified as women (n = 373, 65.1 % women, n = 195, 34% male, n = 1, 0.2% transgender women, n = 1, 0.2% not listed, n = 3, 0.3% prefer not to answer). The average age of participants was 36 (SD= 10) years (range 22 – 73) with most having 13 (SD= 10) years (range 0 – 44) of Board Certification as an athletic trainer. The average number of student athletes athletic trainers in this sample provided medical care to was 476 (SD= 302) with a range of 3 – 2000. The majority (55.7%) of participants were satisfied with how much time they had to provide care to individual patients in their job settings. Overall, the majority of participants (65.7%) were satisfied with the patient care they are able to provide . Additional demographic information can be found in Table 1.

Table 1: Participant Demographics

	Total N= 573	Percentage
Age, mean (SD), yrs (range)	36.31 (SD=10.35) (22-73)
Gender, No. (%) Women Men Transgender Women Not Listed Prefer Not to Answer	373 195 1 1 2	65.1% 34.0% .2% .2% .3%
Marital Status, No. (%) Married Single Cohabitating Divorced Engaged Separated Widowed	302 196 53 10 5 3 3	52.7% 34.2% 9.2% 1.7% .9% .5% .5%
Certified Athletic Trainer mean (SD), yrs (range)	12.88  (SD=9.84) (0-44)
Employment Setting, No. (%) Public Private Charter Both Public & Private Other	7 173 79 273 39	1.2% 30.2% 13.8% 47.6% 6.8%
Employment Status, No (%) Full Time Part Time Other	526 35 11	91.8% 6.1% 1.9%

Participants’ average WFC score was 40.36 (SD= 15.63). Work-interfering with family conflict scores were 23.54 (SD= 9.32) while Family-interfering with work conflict scores were 16.82 (SD= 7.36). Additional WFC data can be found in Table 2. While data revealed the majority of the sample was experiencing no/low overall burnout (73.5%), almost a quarter of participants (24.8%) indicated moderate burnout, and 1.7% of the sample indicated they were experiencing high burnout. Overall, the sample was experiencing low personal, work-related, and client-related burnout. Burnout scores and additional data can be found in Table 3.

Table 2: Participants’ Self-Reported Work-Family Conflict

Scale/Measure	Scale Range	N	Mean + SD	Minimum	Maximum
Work-Family conflict	18-90	573	40.36 ± 15.63	18	76
Time-Based Conflict	3-15	573	15.10 ± 5.82	3	15
Strain-Based Conflict	3-15	573	12.46 ± 5.91	4	13
Behavior-Based Conflict	3-15	573	12.80 ± 6.03	6	14
WIFC Subscale	9-45	573	23.54 ± 9.32	10	42
FIWC Subscale	9-45	573	16.82 ± 7.36	10	36

Table 3: Participants’ Self-Reported Copenhagen Burnout Inventory

Scale/Measure	Scale Range	N	Mean + SD	Minimum	Maximum
Copenhagen Burnout Inventory	0-100	540	40 ± 16.28	2	86
Personal Burnout	0-100	540	47 ± 18.36	0	100
Work-Related Burnout	0-100	540	45 ± 17.75	0	89
Client-Related Burnout	0-100	540	28 ± 18.36	0	96

Reliability Statistics

Reliability statistics reveal strong internal consistency for the CBI (a = .930) and the Work-Family Conflict scale (a = .906) within the sample.

Satisfaction with Patient Care Delivered

Stress (49.04%) was the number one selected item when participants were asked about factors that negatively impact their ability to provide quality patient care followed closely by time (44.5%) and work-life conflict (43.8%). Exercise (71.9%) was most commonly selected as a factor that positively impacts the ability to provide quality patient care followed by sleep (44.85%) and work-life balance (38.91%). Table 4 illustrates the rank order of factors negatively or positively impacting patient care and the total number as well as percentage of participants selecting each item.

Table 4: Perceived Factors that Influence the Delivery of Quality Patient Care

Factors that negatively impact the ability to provide quality patient care	No. (%)
Stress	281 (49.04%)
Time	255 (44.50%)
Work-Life Balance	251 (43.80%)
Sleep	126 (21.98%)
Children	83 (14.48%)
Personal Health Conditions	75 (13.08%)
Exercise	72 (12.56%)
Diet	69 (12.04%)
Spouse	58 (10.12%)
Travel	55 (9.59%)
Pursuing Advanced Education	46 (8.02%)
Caring for others (e.g., elderly family members, family with medical conditions, etc.)	45 (7.85%)
Factors that positively impact the ability to provide quality patient care	No. (%)
Exercise	412 (71.90%)
Sleep	257 (44.85%)
Work-Life Balance	223 (38.91%)
Diet	206(35.95%)
Spouse	200 (34.90%)
Pursuing Advanced Education	166 (28.97%)
Children	143 (24.95%)
Caring for others (e.g., elderly family members, family with medical conditions, etc.)	126 (21.98%)
Travel	120 (20.94%)
Time	114 (19.89%)
Personal Health Conditions	85 (14.83%)
Stress	17 (2.96%)

Participants who indicated they were satisfied with the level of patient care they provided to student athletes had statistically significantly lower strain-based conflict, U(N_satisfied=378, N_unsatisfied =193,) =32441.00, z= -2.169, p = .030) than those who responded they were not satisfied with the patient care they were able to deliver. There were no statistically significant differences in any of the other WFC or burnout items. These include time-based conflict, behavior-based conflict, work-interfering with family conflict, family-interfering with work conflict, WFC total score, personal burnout, work-related burnout, client-related burnout, and burnout total which is represented in Table 5.

Table 5: Mann Whitney U Results
Survey Question: Please indicate if you are satisfied or unsatisfied with the level of care you are able to provide to your student athletes.

Scale Item	Satisfied (N)	Unsatisfied (N)	U value	z value	p value
WFC Total	378	193	32902.5	-1.918	.055
Strain-based conflict	378	193	32441.0	-2.169	.030*
Time-based conflict	378	193	33759.0	-1.461	.144
Behavior- based conflict	378	193	34127.5	-1.264	.206
WIFC	378	193	33295.0	-1.881	.060
FIWC	378	193	33295.0	-1.709	.087
CBI Total	378	192	35152.0	-.612	.541
Personal burnout	378	192	34661.5	-.877	.380
Work-related burnout	378	192	34594.0	-.913	.361
Client- related burnout	378	192	36231.5	-.030	.976

Participants who indicated they were satisfied with the amount of time they are able to provide care to individual patients had statistically significantly (p < .001) lower total WFC, time-based conflict, behavior-based conflict, work-interfering with family conflict, and family-interfering with work conflict. There were no statistically significant differences in burnout total, personal burnout, work-related burnout, or client-related burnout. All of which is represented in Table 6.

Table 6: Mann Whitney U Results
Survey Question: Please indicate if you are satisfied or unsatisfied with the time allotted to provide quality patient care.

Scale Item	Satisfied (N)	Unsatisfied (N)	U value	z value	p value
WFC Total	319	254	29174.5	-5.761	<.001*
Strain-based conflict	319	254	32514.0	-4.072	<.001*
Time-based conflict	319	254	29120.5	-5.800	<.001*
Behavior- based conflict	319	254	32216.0	-4.229	<.001*
WIFC	319	254	27503.0	-6.613	<.001*
FIWC	319	254	33101.0	-3.770	<.001*
CBI Total	319	253	40140.0	-.109	.913
Personal burnout	319	253	39691.0	-.338	.735
Work-related burnout	319	253	39239.5	-.569	.570
Client- related burnout	319	253	38623.0	.884	.377

Chi-Square test of independence examining the relationship between burnout and clinician satisfaction with patient care did not reveal a significant relationship, C² (2, N = 540) = 4.46, p = .108. Additionally, there was no statistically significant relationship between burnout and time for patient care, C² (4, N = 539) = 4.08, p = .982.

Student Athlete Number Impact on Work-Family Conflict and Burnout

Results of the Spearman correlation indicated that there was a significant negative weak association between the number of student-athletes that participants indicated they provide medical care for and time-based conflict (r(569) = -.094, p = .024). There was no statistically significant correlations between number of athletes and any of the other WFC or burnout variables; strain-based conflict (r(569) = -.074, p = .079), behavior-based conflict (r(569) = -.039, p = .351), work-interfering with family conflict (r(569) = -.068, p = .104), family-interfering with work conflict (r(569) = -.065, p = .124), WFC (r(569) = -.070, p = .096), personal burnout (r(569) = .016, p = .701), work-related burnout (r(569) = .041, p = .329), client-related burnout (r(569) = .062, p = .138), and burnout (r(569) = .048, p = .250).

A significant regression equation was found (F(1, 567) = 5.094, p = .024), with an R² of .009 where number of athletes was used to predict time-based conflict. Participants predicted time-based conflict score is equal to 15.99 (SD=.455).

DISCUSSION

While burnout and WFC have been examined extensively among an athletic trainer population, little is known regarding the relationship between these constructs and perceptions of patient care delivery. Given the number of athletic trainers employed in the high school setting and the unique aspect of this employment setting, the researchers sought to gain a better understanding of the factors that clinicians perceive impact their ability to provide quality health care to their patients. The results did not support the hypotheses that the number of student athletes would be positively correlated to burnout or WFC. Additionally, self-reports of providing optimal patient care or time to provide optimal care to individual patients had no relationship to burnout. Those who were satisfied with the patient care they could deliver had lower strain-based conflict and those who were satisfied with the time they had available to provide care had lower total WFC scores and scored lower on all of the WFC subscales.

First, it is important to note that the overall sample was experiencing low levels of burnout and overall scores on Work-Family Conflict scale were on the lower end. While burnout has been studied extensively in the athletic training profession due to attrition rates and other outcomes, high school athletic trainers reported lower overall levels of burnout than other healthcare professionals during the Covid-19 pandemic. A recent study examining burnout among physicians in major trauma centers found 56.3% of the sample was experiencing moderate burnout and 36.7% reported high burnout scores (3). Another study found that the mean CBI score for burnout among emergency room nurses’ was 51.3 and 45.7 for emergency room doctors (9). The study herein found that high school athletic trainers’ mean CBI score for burnout was 40.0. Without directly comparing the professions it would be difficult to definitively explain differences in observed burnout scores. These findings do suggest that burnout is not an isolated athletic trainer experience. While the overall sample experienced low levels of burnout, more than a quarter of high school athletic trainers indicated moderate or high levels of burnout.

Though this study did not explore specific causative factors of burnout, it did find that work-related factors were contributing more to experiences of burnout among high school athletic trainers than patient interactions given the CBI scores on these subscales. Despite a mean of 476 student athletes, number of student athletes was not predictive of burnout scores and the hypothesis was not supported. Additionally, there was no association between burnout and clinicians’ perceptions of the time they have for patient care, or the quality of patient care they can deliver. Number of student athletes was shown to be predictive of time-based conflict, but the explained variance was so small that it is practically negligible. In the high school employment setting, many athletic trainers are employed through an outreach arrangement which sets the number of hours contracted employees work which may also influence the medical care able to be provided to student-athletes. It is possible that outsourcing rehabilitative services to a clinic, for example, creates a situation where the high school athletic trainer focuses on diagnosis and acute management of those injuries. While the study did ask participants to identify their employment setting and status, they were asked to identify their employment model. Future studies could compare stress, burnout, and WLC on high school athletic trainers hired through different employment models.

The overall CBI scale assesses burnout as a measure of fatigue and exhaustion with the patient-related subscale assessing the degree of physical and psychological fatigue that an individual perceives is derived from their work with patients (21). The personal burnout subscale simply measures how tired or exhausted an individual is and the work-related subscale assesses the level of physical and physiological fatigue and exhaustion that an individual believes stems from their work (21). Results of the research herein show that levels of personal and work-related burnout are similar and patient-related burnout scores are much lower. Lower levels of patient-related burnout compared to work-related burnout have been observed in other healthcare professionals (3). These findings indicate that participants of the study herein attribute their level of physical and physiological fatigue to work-related factors and not patient interactions or non-work factors such as family demands. An area that warrants further investigation is coping strategies as well as organizational/workplace policies that can offer support to the athletic trainer to prevent burnout. Understanding management of work and personal stress can provide useful information to continue to reduce burnout and conflict for the athletic trainer.

Further sporting this finding that burnout is stemming from work-related factors and not non-work factors are the WIFC and FIWC subscale scores. As previously mentioned, WFC can be predictive of burnout (26). The mean of the WIFC subscale was 23.54 compared to 16.82 on the FIWC. This indicates that participants perceive that work interferes more with their family roles than vice-versa. Work-life balance is most simply defined as the time and energy for both work and personal roles and when the time or energy spent in one role inhibits the time and energy for another roles, WFC results (7). Overall, those who indicated that they were satisfied with the time they had available for patient care had lower overall levels of WFC, time-based conflict, strain-based conflict, behavior-based conflict, WIFC, and FIWC. There are many factors that could explain why our sample were satisfied with their time for patient care, and also had lower levels of burnout and WFC, including having effective support networks and utilizing self-care practices to reduce stress (12, 14, 24, 28).

While the majority of participants indicated they were satisfied with the care they were able to deliver to their patients and the time they had for patient care, nearly half of the athletic trainers in this sample indicated they were not satisfied with the time they had for patient care, and more than a quarter were not satisfied with the care they were able to deliver to patients. It is important to recognize that many high school athletic trainers do not feel they are able to provide optimal care to their patients. Knowing this assumption, it becomes even more important to examine specific factors that may influence the ability to deliver patient care. Participants indicated that exercise, sleep, and work-life balance positively impacted their ability to provide patient care while stress, time, and work-life conflict negatively impacted their ability to deliver quality patient care.

The factors high school athletic trainers identified as positively impacting their ability to provide optimal patient care have all been shown to reduce stress, which was the number one selected factor for negatively influencing optimal patient care delivery. Previous research has shown that participation in sporting activities (exercise) and spending time with friends/family are common methods to cope with the stress experienced during the Covid-19 pandemic (9). The results suggest possible strategies to help athletic trainers in secondary schools to mitigate experiences of stress, which has direct links to experiences of burnout (26).  

LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH

The goal of this study was to examine any potential relationship between clinicians’ perceptions of patient care and work-life conflict and burnout, but it is important to note that perceptions of care are not an accurate representation of delivery of care. Future studies should explore clinician burnout and work-life conflict and patient outcomes or patient perceptions of care received from clinicians who report high levels of work-life conflict or burnout. While the questionnaire asked participants to indicate the number of student athletes at their school that they were responsible for providing care to, participants were not explicitly asked to identify how many treatments or patients they provide care to. The number of student athletes may not be representative of the patient workload and could have impacted the lack of group differences observed in the sample. The nature of a cross-sectional study means that participant responses indicate one moment in time and future studies should further explore the potential relationship between these constructs longitudinally. Future researchers should also explore the potential relationships between these constructs in other athletic training employment settings.

CONCLUSIONS

The number of student athletes nor interactions with patients seem to be a significant source of clinician burnout or WFC. Rather, work-related factors appeared to contribute to experiences of physical and psychological fatigue. While the majority of participants indicated they were satisfied with the amount of time they had available to provide care to their patients, nearly half of high school athletic trainers indicated they were not. Factors associated with personal well-being and mental health, such as stress, exercise, and sleep seem to impact clinicians’ perceptions of the quality of care they are able to deliver to their patients. Recognizing the relationship between clinician work-life interface outcomes and patient care is essential to move towards building strategies to help prioritize clinician well-being. While one’s own well-being should always be a priority, the altruistic nature of many athletic trainers often creates situations in which they will put the needs of others ahead of their own. Clinicians and administrators alike may pay more attention to concepts like WFC and burnout if there is a better understanding of the potential impact on patients.

APPLICATION IN SPORT

A majority of athletic trainers are employed in sport settings, and so the findings have implications on the care they provide to athletes within these sport organizations.  So,  recognizing factors that lead to clinician burnout may help create strategies to help mitigate the associated negative consequences. Reducing clinician burnout will have direct impact on patient care and outcomes. While number of student athletes did have a weak correlation to time-based strain, it is important to recognize that number of student athletes does not appear to be directly related to WFC and burnout. Addressing organizational and workplace issues and promoting self-care strategies may help athletic trainers continue to deliver optimal care to their patients in the secondary school setting.

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