Artigo Acesso aberto Revisado por pares

Health-Related Quality of Life in Former Division II Collegiate Athletes Using the Disablement of the Physically Active Scale

2019; Volume: 13; Issue: 2 Linguagem: Inglês

10.3928/19425864-20191106-02

ISSN

1942-5872

Autores

Stuart A. Wright, Alison R. Snyder Valier,

Tópico(s)

Sports Performance and Training

Resumo

Original Research freeHealth-Related Quality of Life in Former Division II Collegiate Athletes Using the Disablement of the Physically Active Scale Stuart A. Wright, DAT, ATC, CSCS, ; , DAT, ATC, CSCS Alison R. Snyder Valier, PhD, ATC, FNATA, , PhD, ATC, FNATA Stuart A. Wright, DAT, ATC, CSCS and Alison R. Snyder Valier, PhD, ATC, FNATA Published Online:December 16, 2019https://doi.org/10.3928/19425864-20191106-02Cited by:2AbstractPDF 217.6 KB ToolsAdd to favoritesDownload CitationsTrack CitationsCopy LTI LinkHTMLAbstractPDF ShareShare onFacebookTwitterLinkedInRedditEmail SectionsMoreAbstractPurpose:To use the Disablement of the Physically Active Scale (DPA) to evaluate the impact of injuries experienced during collegiate athletics on the health-related quality of life (HRQOL) of former Division II collegiate athletes.Methods:A survey assessing the health of former collegiate athletes was sent to 1,147 former Division II athletes. The DPA was reported as DPA total score, physical summary component (DPA-PSC), and mental summary component (DPA-MSC). Comparisons were made between participants with and without injury and between severe and mild injury.Results:Most respondents (n = 85 of 106, 80.2%) reported experiencing injury during intercollegiate participation. The mean ± standard deviation age of respondents was 33.4 ± 10 years. The mean ± standard deviation scores were 16 ± 12.9 for DPA total, 12.3 ± 10.3 for DPA-PSC, and 3.7 ± 3.8 for DPA-MSC. Former athletes who had a college injury reported worse DPA total scores (17.0 ± 12.4) than those who did not (11.7 ± 14.3, P = .002). Those with severe injury (21.7 ± 14.0) had worse total DPA scores than those with mild injury (12.6 ± 12.1, P = .02). Scores on the DPA-PSC were better for those who did not have a college injury (8.1 ± 10.6) than those who did (13.3 ± 10.0, P = .008) and for those with mild injury (12.6 ± 12.1) than those with severe injury (21.7 ± 14.0, P = .02). No differences were found for DPA-MSC (both P > .11).Conclusions:Injuries experienced during college may have a lasting impact on HRQOL in former Division II collegiate athletes, as measured by the DPA. However, previous college injury may not affect mental well-being in the same manner as physical health components.[Athletic Training & Sports Health Care. 2021;13(2):85–92.]IntroductionMore than 490,000 student-athletes participated in National Collegiate Athletic Association (NCAA) sports in 2018.1 Although the benefits of being physically active are well known,2 there are associated risks, including an estimated 72,316 injuries sustained per academic year in NCAA sports.3 It is estimated that 14,599 of those injuries occur at the Division II level.3 One study estimated the injury rate at the Division II level to be 3.36 and 12.36 per 1,000 athlete-exposures for practices and games, respectively.3 More recent studies stated that the injury rate across Division II athletics ranged from 2.78 (baseball) to 7.3 (wrestling) injuries per 1,000 athlete-exposures.4–16When combined with injuries sustained, the rigors of high-level sports participation may impact the health-related quality of life (HRQOL) of collegiate athletes.17 Because of an increased emphasis on understanding the impact of injuries on the whole person and beyond the physical manifestation of the injury, HRQOL has been used to describe a person's physical, psychological, and social health.18 A common way to evaluate HRQOL is with patient-reported outcome measures (PROMs). These measures are surveys or instruments that patients complete about their health, and the responses are used to evaluate the impact of health conditions, such as injuries or illnesses, on their lives.The use of PROMs is postulated to help clinicians facilitate personalized care management by highlighting the needs of the individual.19 They have been used in several studies investigating the HRQOL of patients. A systematic review of studies measuring HRQOL in general injury populations concluded that large variation exists in the use of HRQOL instruments, study populations, and assessment points.20 In athletic populations, several studies have used generic measurements to evaluate health, such as the Short Form-36 (SF-36).20 However, generic instruments are criticized for having ceiling effects in athletic populations.17 Recently, the Disablement of the Physically Active (DPA)21 scale was introduced as a PROM that evaluates the quality of life in active populations such as athletes.The DPA is a generic PROM consisting of 16 questions scored on a 5-point Likert scale.21,22 Although the DPA is a generic instrument, Houston et al17 used it to evaluate HRQOL in athletes and found that the ceiling effect that is often present with traditional generic measures was not present for the physical summary component in an athletic population. The psychometric properties of the DPA have been reviewed as separate summary components23 and as a complete instrument,22 and they have good internal consistency and test–retest reliability.22,23QOL has been studied in different groups of collegiate athletes: healthy, currently injured, and previously injured athletes.17,24–27 Research suggests that collegiate athletes without a history of injury report better HRQOL than injured athletes.24 Athletes with current injury who are actively engaged in athletics have more HRQOL deficits than those who are injured but can still participate in their respective sport.17 Further, HRQOL as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) scale (range: 0 to 100 points) is worse in former collegiate athletes than non-athletes in the domains of physical function (mean difference [MD] = 17.51 points), depression (MD = 7.31), sleep disturbance (MD = 5.88), and pain interference (MD = 10.17).26 The same study found recreationally active patients and the general U.S. population have better HRQOL than former Division I collegiate athletes.26 When compared with contact and limited contact athletes, research suggests collision athletes may sacrifice their future HRQOL.27 Taken together, the current literature illustrates that collegiate athletics and injury both affect HRQOL, but due to a paucity of research, it is less clear how injury may affect the health of former collegiate athletes in the long term.The current literature on HRQOL is expanding, even though variability in the measures used still limits the clinical use of the data.26,27 Therefore, the long-term impact of the injuries sustained by athletic populations should be investigated. Further, HRQOL differences should also be investigated, such as between different types of injury, within larger populations, across regional and disease-specific measures, and across the lifespan28 of athletes, paying particular attention to HRQOL once an athlete's career has ended. There are still gaps in our understanding of the impact of injury on the lives of athletes. As such, we need to collect better quality and quantity of data, which may assist clinicians to pursue treatment and rehabilitation plans that promote positive patient outcomes. Therefore, the purpose of the current study was to evaluate the impact of injuries experienced during collegiate athletics on the HRQOL of former Division II collegiate athletes.MethodsDesignThe current study used a survey study design to investigate the current health of former collegiate athletes. Data were collected for sex, age, and level of sport participation. For comparative analysis, the independent variables were injury history (ie, yes, no) and injury severity (ie, mild, severe). The dependent variables were the total DPA and physical (DPA-PSC) and mental (DPA-MSC) summary component scores.ParticipantsParticipants were recruited through convenience sampling of former NCAA Division II athletes from a small private college. A former Division II athlete was defined as a person who competed in one of the following NCAA Division II sanctioned sports for one or more competitive seasons: lacrosse (n = 24), soccer (n = 21), baseball (n = 20), softball (n = 7), basketball (n = 6), swimming (n = 6), cross country (n = 5), field hockey (n = 5), volleyball (n = 5), tennis (n = 4), golf (n = 3), football (n = 2), track and field (n = 2), or wrestling (n = 2). Graduating from the institution was not a requirement for inclusion.ProceduresA demographic survey was developed by the authors, and further edited over the course of 1 month to determine those questions most pertinent to the clinical question. On completion of the survey, former NCAA Division II athletes were asked to participate in the current study through email invitation. The institutional administration provided the email list of the student athletes. The invitation briefly described the study. Reminder emails to complete the survey were sent out 2 and 4 weeks after the initial invitation. Responses were limited to one survey per email address to ensure duplicates were not submitted. Only responses from respondents who completed the DPA were included in the analyses. The median completion time for the surveys was 6.5 minutes.InstrumentationA web-based survey was developed for the current study using the Qualtrics survey software platform (Qualtrics Lab, Inc). The survey consisted of a demographic questionnaire and the DPA scale. A multistaged validation process was used to validate the survey and included item generation, expert review, instrument revision, and mechanical review.Demographic Questionnaire. The demographic questionnaire had questions about age, years played, and years since graduation, and injuries sustained during collegiate participation. Respondents who reported an injury were asked to reflect on the "most significant" injury during that time. Requested information related to the injury included body region, diagnosis, injury severity, and time loss. DPA. The DPA scale is a generic PROM consisting of 16 questions scored on a 5-point Likert scale.21,22 A score of 1 indicates no problem, whereas a score of 5 indicates a severe problem.21 Each item and domain on the DPA is weighted equally, and 16 points are removed from the final total score so the score range is from 0 to 64 points, where higher scores suggest lower function and well-being.22,29 The final subscale scores range from 0 to 48 points for the physical summary (12 questions), and 0 to 16 for the mental summary (4 questions).23 When patients complete the DPA, their answers for each statement should represent their level of disablement in the previous 24 hours.22The psychometric properties of the DPA have been reviewed as a total score22 and as separate summary components.23 The DPA total score has adequate internal consistency with a Cronbach alpha value of 0.91.22 The DPA-PSC (alpha = 0.94) and DPA-MSC (alpha = 0.88) health components have also demonstrated adequate internal consistency.23 Test–retest reliability of the DPA is also strong (intraclass correlation coefficient = 0.94).22 The minimal clinically important difference is estimated to be 6 DPA points for chronic conditions and 9 DPA points for acute conditions.22AnalysesDescriptive statistics including frequencies, percentages, and means ± standard deviations (SD) were reported for all variables, and for those who did and did not have an injury because of collegiate athletics. The mean ± SD DPA total score, DPA-PSC, and DPAMSC were calculated for all respondents, for those with injury history (ie, did or did not have a college injury), and for injury severity (ie, mild or severe). Injury severity was differentiated subjectively by each participant. Kolmogorov–Smirnov tests were conducted preliminarily and suggested the data violated assumptions of normality (P = .002). Therefore, Mann–Whitney tests were used for group comparisons. Significance was set a priori at a P value of less than .05. Participants who did not fully complete the DPA were omitted from analyses (n = 17). Analyses were conducted using SPSS version 24 software (IBM Corporation).Ethical ConsiderationsThe study was approved by the local institutional review boards of the private college and the investigating university. An invitation was sent to the email list of former collegiate athletes that briefly described the study, and consent was given when participants clicked on the link to complete the survey. Data were collected on a secure server and were anonymous.ResultsResponsesOf 1,146 emails initially sent to former collegiate athletes of a Division II NCAA institution, 59 were undeliverable (5.1%) and 1,087 (94.9%) were delivered. Of those delivered, 129 surveys were initiated (11.9%, 129 of 1,087) and 123 were submitted (95.3%, 123 of 129). Of the 123, 17 were omitted from analyses because the respondents did not complete the full survey. The final completion rate was 86.2% (106 of 123), although the overall response rate of the emails delivered was 9.75% (106 of 1,087).Survey ResponsesMore men (62.3%, 66 of 106) than women (37.7%, 40 of 106) completed the survey. The mean ± SD age was 33.4 ± 10.0 years (range = 22 to 61 years).Of injuries experienced during collegiate athletics, the knee was most frequently reported as injured (19.8%, 21 of 106), followed by the ankle (10.4%, 11 of 106), shoulder (10.4%, 11 of 106), and lower back (6.6%, 7 of 106) (Table 1). The most frequently reported diagnosis was anterior cruciate ligament (ACL) sprains/tears (11.3%, 12 of 106), followed by non-ACL sprains/tears (9.4%, 10 of 106), fractures (9.4%, 10 of 106), muscle strains (7.5%, 8 of 106), torn cartilage (6.6%, 7 of 106), concussions (5.7%, 6 of 106), and other (12%, 11.3 of 106) (Table 2).Table 1 Injury Distribution of Former NCAA Division II Athletes by Body Region (N = 106)Body RegionNo.%Knee2119.8Ankle1110.4Shoulder1110.4Lower back76.6Head54.7Face43.8Hip43.8Lower leg43.8Elbow32.8Wrist32.8Foot21.9Other21.9Toes21.9Upper back21.9Upper leg21.9Fingers10.9Sternum10.9Missing2119.8NCAA = National Collegiate Athletic AssociationTable 2 Injury Distribution of Former NCAA Division II Athletes by Diagnosis (N = 106)DiagnosisNo.%Ligament sprain/tear: ACL1211.3Other1211.3Fracture109.4Ligament sprain/tear: non-ACL109.4Muscle strain87.5Torn cartilage76.6Concussion65.7Tendinitis or tendinopathy54.7Stress fracture43.8Puncture wound or laceration32.8Contusion21.9Joint dislocation21.9Joint subluxation21.9Tendon tear or rupture21.9Missing2119.8NCAA = National Collegiate Athletic Association; ACL = anterior cruciate ligamentMost respondents reported an injury (80.2%, 85 of 106) during participation in collegiate athletics (Table 3). The mean ± SD score on the DPA for all responses was 16.0 ± 12.9 points. The mean ± SD DPA-PSC score was 12.3 ± 10.3 points, and the mean ± SD DPA-MSC score was 3.7 ± 3.8 points (Table 3).Table 3 Scores on the DPA Scale for Former NCAA Division II Athletes by Injury History for Those With and Without a Collegiate InjuryaDPATotal (N = 106)Collegiate Injury (n = 85, 80.2%)No Collegiate Injury (n = 21, 19.8%)Total score16.0 ± 12.917.0 ± 12.411.7 ± 14.3bPhysical summary score12.3 ± 10.313.3 ± 10.08.1 ± 10.6bMental summary score3.7 ± 3.83.7 ± 3.73.5 ± 4.4DPA = Disablement of the Physically Active; NCAA = National Collegiate Athletic AssociationaData are reported as mean ± standard deviation.bSignificant difference (P < .05).ComparisonsAthletes who experienced an injury during collegiate athletics reported worse HRQOL than those who did not experience an injury on the DPA (17.0 ± 12.4 vs 11.7 ± 14.3 points, P = .002) and the DPA-PSC (13.3 ± 10.0 vs 8.1 ± 10.6 points, P = .008) (Table 3). No differences were found between groups for the DPAMSC (P = .57). Athletes who experienced a mild injury reported better HRQOL than those with a severe injury on the DPA (12.6 ± 12.1 vs 21.7 ± 14.0 points, P = .02) and the DPA-PSC (10.1 ± 9.9 vs 17.4 ± 10.7 points, P = .02) (Table 4). No differences were found for injury severity on the DPA-MSC (P = .11).Table 4 Scores on the DPA Scale for Former NCAA Division II Athletes by Injury SeverityaDPATotal (N = 45)Mild Injury (n = 26)Severe Injury (n = 19)Total score17.0 ± 12.412.7 ± 12.121.68 ± 14.0bPhysical summary score13.4 ± 10.010.2 ± 10.017.4 ± 10.7bMental summary score3.7 ± 3.72.5 ± 3.34.3 ± 4.3DPA = Disablement of the Physically Active; NCAA = National Collegiate Athletic AssociationaData are reported as mean ± standard deviation.bSignificant difference (P < .05).DiscussionOur findings suggested those who had an injury reported worse HRQOL, as measured by the DPA, than those who did not, especially in relation to physical health. The severity of the injury also affected QOL: former athletes with severe injuries had worse HRQOL than those with mild injuries. Again, injury severity was mostly related to physical health. Our results also suggested that mental health, as measured by the DPA, was not affected.Former athletes who suffered injury reported worse HRQOL on the DPA, but the extent of the impact of those injuries on current functioning in daily life is unknown. Although HRQOL is generally reported to be worse in those with injury, our DPA total score of 17 ± 12.4 points suggested that respondents may not be affected by their injuries to a great extent. A score of 17 of 64 reflects the top 25% in the score range (lower scores reflect better health on the DPA). Therefore, although statistically significant differences exist, participants may still function well on a daily basis. More research is needed to better understand DPA scale scores and score ranges as they relate to health status and ability to function in daily and sport type activities.In addition, it is worth noting that the DPA (11.7 ± 14.3 vs 12.7 ± 12.1) and DPA-PSC (8.1 ± 10.6 vs 10.2 ± 10.0) scores for the uninjured and mild injury groups, respectively, appear similar. Although this comparison was not statistically assessed, the similar scores warrant future exploration to further explore the impact that injury has on short- and longer-term health status.In the current study, total DPA and DPA-PSC scores indicated reduced HRQOL in athletes who experienced an injury in college. This result contradicted the recent work of Houston et al,17 who used the DPA tool and detected no HRQOL differences between collegiate athletes with and without a history of injury. However, that study included active student athletes, rather than former collegiate athletes, which could account for the differences.17 Other studies supported our results. Huffman et al30 found that minor injuries resulted in athletes reporting a negative impact on HRQOL, but they used the SF-36 rather than the DPA. A recent systematic review24 indicated athletes without a history of injury reported better HRQOL on generic instruments than those with a history of injury. The concept of injury impacting HRQOL is further supported by Simon and Docherty,26 who used the PROMIS tool and found that Division I athletes reported worse HRQOL than recreational athletes and the general U.S. population. The authors concluded that injuries experienced because of the rigors of sport may be a significant contributor to reduced HRQOL later in life.26Although our results suggested previous college injury affected physical health, no differences were found for mental health. These findings supported Houston et al,17 who also reported no differences on the DPA-MSC between athletes with and without a history of injury.17 Therefore, although this study suggests injury experienced during collegiate athletics may have little impact on mental health, more research is needed to verify this claim.Results suggested that HRQOL was negatively affected by the severity of the injury; former collegiate athletes with a self-reported severe injury expressed worse HRQOL than those with a mild injury. This finding supported McAllister et al,25 who examined injury severity in currently injured athletes using the SF-36 and found that severity was a primary factor for worse health. However, the reported impact of injury severity on HRQOL is inconsistent. Houston et al17 reported that injury severity did not affect HRQOL even though severity of injury experienced during intercollegiate athletics is thought to contribute to differing HRQOL between athletic and general populations.26 One reason for the variance could be the varied injury severity definitions. The current study used a self-reported method, whereas Houston et al used a time loss definition of mild (less than 8 days' absence from sport) and severe (greater than 21 days' absence from participation).17 McAllister et al25 defined a mild injury as one that had minimal to no impact on participation, whereas serious injury was defined as an injury that had a significant impact on participation. Additional research examining the impact of injury severity on current and long-term HRQOL is needed, as well as consideration for creating standardized definitions related to injury severity.Multiple studies have investigated HRQOL in athletic populations.17,24–27,30,31 Although Houston et al24 conducted a systematic review, synthesis of the literature is challenging because reporting methods and outcome measures used across studies vary. Common tools used to evaluate quality of life in athletes are the SF-36, SF-12, Pediatric Outcomes Data Collection Instrument, PROMIS, Fear-Avoidance Beliefs Questionnaire, and the DPA. The DPA is the only one of these generic measures designed for athletic populations and is not subject to ceiling effects in this high-functioning population,21,22 but this instrument is not included in the most recent synthesis of patient-outcome literature in athletes.24The current study had several limitations. Because we retrospectively collected self-reported injury information, our results have the potential for recall bias. However, this method of self-report is commonly used in the medical literature.32–34 In addition, missing data were present for injury distribution for body part (19.8%, 21 of 106) and diagnosis (19.8%, 21 of 106), which should be considered when interpreting results. Another limitation was the cross-sectional design, which limited our ability to infer causal relationships. Further, the convenience sampling method used to recruit participants and the small sample size limited our ability to compare subgroups. Finally, there is a larger range of participants, which limits the ability to consider the long-term impact of injury on former collegiate athletes. In addition, further events may have occurred between the time of initial college injury and the time in which the participant completed the survey in this study and events during that time could have affected the HRQOL of each individual. Future studies should be conducted on a larger scale to address these issues and expand the generalizability of findings.Despite these limitations, the current study contributes to the existing literature because a better understanding of the impact of injury on athletes' HRQOL is important for future intervention strategies. Given our results, it is likely that most collegiate athletes will experience an injury and those injuries will contribute to significantly worse HRQOL, primarily in the physical dimension after their collegiate athletic experience is over. Prevention strategies should be optimized to reduce the number of injuries sustained. Such strategies would be especially useful for this specific patient demographic that lacks access to the same care after their participation in collegiate sports. In the current study, ACL sprains were the most commonly reported injury, and research suggests that patients with an ACL injury have a high likelihood of developing osteoarthritis,35 which has the potential to impact HRQOL. Although injury prevention strategies to reduce the incidence of ACL injuries have been successful,36 more research is needed to investigate the implementation of such programs in collegiate environments, especially given the potential impact of these significant injuries.Inconsistencies and variance currently exist in the literature about the true impact of collegiate athletics on HRQOL.17,24–27,30,31 Therefore, more data are needed to answer questions about patient outcomes related to intercollegiate athletics. Based on study results, researchers have recommended the use of more disease-specific or regional measures,17,24,26,37 prospective studies,17,27,37 better group comparisons,37 and larger scale studies in more diverse populations.31,37 Many of these suggestions can be achieved through electronic methods of distribution. The methods in the current study were similar to those of Simon and Docherty,26 and they may fill gaps in the literature when future studies incorporate appropriate electronic survey software, larger sample sizes, and regional and disease-specific measures. Thus, future research should focus on addressing these factors through the refinement of study methods until practice-based networks can provide prospective data on patients.Implications for Clinical PracticeResults of the current study indicated that the physical HRQOL of former NCAA Division II collegiate athletes was worse in those who experienced an injury during intercollegiate athletics than in those who did not. The idea that injury in college can have a lasting impact on physical HRQOL is troubling. Therefore, there is a need for clinicians to maximize strategies that limit injury in intercollegiate athletics and promote positive health outcomes. Health care decisions should include education regarding the impact on HRQOL.1.Irick E. NCAA sports sponsorship and participation rates report: 1981-82-2014-15. Published October 2018. Accessed November 13, 2018. https://ncaaorg.s3.amazonaws.com/research/sportpart/Oct2018RES_2017-18SportsSponsorshipParticipationRatesRe-port.pdf Google Scholar2.Warburton DE, Nicol CW, Bredin SS. Health benefits of physical activity: the evidence. CMAJ. 2006; 174(6):801–809. doi:10.1503/cmaj.051351 Crossref, Google Scholar3.Hootman JM, Dick R, Agel J. Epidemiology of collegiate injuries for 15 sports: summary and recommendations for injury prevention initiatives. J Athl Train. 2007; 42(2):311–319. Google Scholar4.Clifton DR, Hertel J, Onate JAet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school girls' basketball (2005–2006 through 2013–2014) and National Collegiate Athletic Association women's basketball (2004–2005 through 2013–2014). J Athl Train. 2018; 53(11):1037–1048. doi:10.4085/1062-6050-150-17 Crossref, Google Scholar5.Clifton DR, Onate JA, Hertel Jet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school boys' basketball (2005–2006 through 2013–2014) and National Collegiate Athletic Association men's basketball (2004–2005 through 2013–2014). J Athl Train. 2018; 53(11):1025–1036. doi:10.4085/1062-6050-148-17 Crossref, Google Scholar6.DiStefano LJ, Dann CL, Chang CJet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school girls' soccer (2005–2006 through 2013–2014) and National Collegiate Athletic Association women's soccer (2004–2005 through 2013–2014). J Athl Train. 2018; 53(9):880–892. doi:10.4085/1062-6050-156-17 Crossref, Google Scholar7.Kerr ZY, Gregory AJ, Wosmek Jet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school girls' volleyball (2005–2006 through 2013–2014) and National Collegiate Athletic Association women's volleyball (2004–2005 through 2013–2014). J Athl Train. 2018; 53(10):926–937. doi:10.4085/1062-6050-162-17 Crossref, Google Scholar8.Kerr ZY, Putukian M, Chang CJet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school boys' soccer (2005–2006 through 2013–2014) and National Collegiate Athletic Association men's soccer (2004–2005 through 2013–2014). J Athl Train. 2018; 53(9):893–905. doi:10.4085/1062-6050-166-17 Crossref, Google Scholar9.Kerr ZY, Wilkerson GB, Caswell SVet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in United States high school football (2005–2006 through 2013–2014) and National Collegiate Athletic Association football (2004–2005 through 2013–2014). J Athl Train. 2018; 53(8):738–751. doi:10.4085/1062-6050-144-17 Crossref, Google Scholar10.Kroshus E, Utter AC, Pierpoint LAet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school boys' wrestling (2005–2006 through 2013–2014) and National Collegiate Athletic Association men's wrestling (2004–2005 through 2013–2014). J Athl Train. 2018; 53(12):1143–1155. doi:10.4085/1062-6050-154-17 Crossref, Google Scholar11.Lynall RC, Gardner EC, Paolucci Jet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school girls' field hockey (2008–2009 through 2013–2014) and National Collegiate Athletic Association women's field hockey (2004–2005 through 2013–2014). J Athl Train. 2018; 53(10):938–949. doi:10.4085/1062-6050-173-17 Crossref, Google Scholar12.Lynall RC, Mihalik JP, Pierpoint LAet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school boys' ice hockey (2008–2009 through 2013–2014) and National Collegiate Athletic Association men's and women's ice hockey (2004–2005 through 2013–2014). J Athl Train. 2018; 53(12):1129–1142. doi:10.4085/1062-6050-176-17 Crossref, Google Scholar13.Pierpoint LA, Caswell SV, Walker Net al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school girls' lacrosse (2008–2009 through 2013–2014) and National Collegiate Athletic Association women's lacrosse (2004–2005 through 2013–2014). J Athl Train. 2019; 54(1):42–54. doi:10.4085/1062-6050-201-17 Crossref, Google Scholar14.Pierpoint LA, Lincoln AE, Walker Net al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school boys' lacrosse (2008–2009 through 2013–2014) and National Collegiate Athletic Association men's lacrosse (2004–2005 through 2013–2014). J Athl Train. 2019; 54(1):30–41. doi:10.4085/1062-6050-200-17 Crossref, Google Scholar15.Wasserman EB, Register-Mihalik JK, Sauers ELet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school girls' softball (2005–2006 through 2013–2014) and National Collegiate Athletic Association women's softball (2004–2005 through 2013–2014). J Athl Train. 2019; 54(2):212–225. doi:10.4085/1062-6050-206-17 Crossref, Google Scholar16.Wasserman EB, Sauers EL, Register-Mihalik JKet al.. The first decade of web-based sports injury surveillance: descriptive epidemiology of injuries in US high school boys' baseball (2005–2006 through 2013–2014) and National Collegiate Athletic Association men's baseball (2004–2005 through 2013–2014). J Athl Train. 2019; 54(2):198–211. doi:10.4085/1062-6050-239-17 Crossref, Google Scholar17.Houston MN, Hoch JM, Van Lunen BL, Hoch MC. The impact of injury on health-related quality of life in college athletes. J Sport Rehabil. 2017; 26(5):365–375. doi:10.1123/jsr.2016-0011 Crossref, Google Scholar18.Fayers PM, Machin D. Quality of Life: The Assessment, Analysis and Interpretation of Patient-Reported Outcomes, 2nd ed. John Wiley & Sons; 2007. Crossref, Google Scholar19.McCarty CW, Hankemeier DA, Walter JM, Newton EJ, Van Lunen BL. Use of evidence-based practice among athletic training educators, clinicians, and students, part 2: attitudes, beliefs, accessibility, and barriers. J Athl Train. 2013; 48(3):405–415. doi:10.4085/1062-6050-48.2.19 Crossref, Google Scholar20.Polinder S, Haagsma JA, Belt Eet al.. A systematic review of studies measuring health-related quality of life of general injury populations. BMC Public Health. 2010; 10(1):783. doi:10.1186/1471-2458-10-783 Crossref, Google Scholar21.Vela LI, Denegar C. Transient disablement in the physically active with musculoskeletal injuries, part I: a descriptive model. J Athl Train. 2010; 45(6):615–629. doi:10.4085/1062-6050-45.6.615 Crossref, Google Scholar22.Vela LI, Denegar CR. The Disablement in the Physically Active Scale, part II: the psychometric properties of an outcomes scale for musculoskeletal injuries. J Athl Train. 2010; 45(6):630–641. doi:10.4085/1062-6050-45.6.630 Crossref, Google Scholar23.Houston MN, Hoch JM, Van Lunen BL, Hoch MC. The development of summary components for the Disablement in the Physically Active scale in collegiate athletes. Qual Life Res. 2015; 24(11):2657–2662. doi:10.1007/s11136-015-1007-6 Crossref, Google Scholar24.Houston MN, Hoch MC, Hoch JM. Health-related quality of life in athletes: a systematic review with meta-analysis. J Athl Train. 2016; 51(6):442–453. doi:10.4085/1062-6050-51.7.03 Crossref, Google Scholar25.McAllister DR, Motamedi AR, Hame SL, Shapiro MS, Dorey FJ. Quality of life assessment in elite collegiate athletes. Am J Sports Med. 2001; 29(6):806–810. doi:10.1177/03635465010290062201 Crossref, Google Scholar26.Simon JE, Docherty CL. Current health-related quality of life is lower in former Division I collegiate athletes than in non-collegiate athletes. Am J Sports Med. 2014; 42(2):423–429. doi:10.1177/0363546513510393 Crossref, Google Scholar27.Simon JE, Docherty CL. Current health-related quality of life in former national collegiate athletic association Division I collision athletes compared with contact and limited-contact athletes. J Athl Train. 2016; 51(3):205–212. doi:10.4085/1062-6050-51.4.05 Crossref, Google Scholar28.Parsons JT, Snyder AR. Health-related quality of life as a primary clinical outcome in sport rehabilitation. J Sport Rehabil. 2011; 20(1):17–36. doi:10.1123/jsr.20.1.17 Crossref, Google Scholar29.Houston MN, Hoch JM, Van Lunen BL, Hoch MC. The development of summary components for the Disablement in the Physically Active scale in collegiate athletes. Qual Life Res. 2015; 24(11):2657–2662. doi:10.1007/s11136-015-1007-6 Crossref, Google Scholar30.Huffman GR, Park J, Roser-Jones C, Sennett BJ, Yagnik G, Webner D. Normative SF-36 values in competing NCAA intercollegiate athletes differ from values in the general population. J Bone Joint Surg Am. 2008; 90(3):471–476. doi:10.2106/JBJS.G.00325 Crossref, Google Scholar31.Sorenson SC, Romano R, Scholefield RMet al.. Holistic life-span health outcomes among elite intercollegiate student-athletes. J Athl Train. 2014; 49(5):684–695. doi:10.4085/1062-6050-49.3.18 Crossref, Google Scholar32.Bourgeois FT, Porter SC, Valim C, Jackson T, Cook EF, Mandl KD. The value of patient self-report for disease surveillance. J Am Med Inform Assoc. 2007; 14(6):765–771. doi:10.1197/jamia.M2134 Crossref, Google Scholar33.Honkanen K, Honkanen R, Heikkinen L, Kröger H, Saarikoski S. Validity of self-reports of fractures in perimenopausal women. Am J Epidemiol. 1999; 150(5):511–516. doi:10.1093/oxfordjournals.aje.a010040 Crossref, Google Scholar34.Klasser GD, de Leeuw R, Albuquerque RJ. Self-report health questionnaire: a necessary and reliable tool in dentistry. Gen Dent. 2005; 53(5):348–354. Google Scholar35.Poulsen E, Concalves GH, Roos EM, Thorlund J, Juhl CB. Quantifying the risk of developing knee osteoarthritis following knee injury: a systematic review and meta-analysis. Osteoarthritis Cartilage. 2017; 25:S363. doi:10.1016/j.joca.2017.02.621 Crossref, Google Scholar36.Mandelbaum BR, Silvers HJ, Watanabe DSet al.. Effectiveness of a neuromuscular and proprioceptive training program in preventing anterior cruciate ligament injuries in female athletes: 2-year follow-up. Am J Sports Med. 2005; 33(7):1003–1010. doi:10.1177/0363546504272261 Crossref, Google Scholar37.Valovich McLeod TC, Bay RC, Parsons JT, Sauers EL, Snyder AR. Recent injury and health-related quality of life in adolescent athletes. J Athl Train. 2009; 44(6):603–610. doi:10.4085/1062-6050-44.6.603 Crossref, Google Scholar Previous article Next article FiguresReferencesRelatedDetailsCited by DiSanti J, Marshall A, Valier A and McLeod T (2022) High School Athletes' Health-Related Quality of Life Across Recovery After Sport-Related Concussion or Acute Ankle Injury: A Report From the Athletic Training Practice-Based Research Network, Orthopaedic Journal of Sports Medicine, 10.1177/23259671211068034, 10:2, (232596712110680), Online publication date: 1-Feb-2022. Cross S, Gill D, Brown P and Reifsteck E (2021) Prior Injury, Health-Related Quality of Life, Disablement, and Physical Activity in Former Women's Soccer Players, Journal of Athletic Training, 10.4085/1062-6050-0731.20, Online publication date: 29-Jun-2021. Request Permissions InformationCopyright 2021, SLACK IncorporatedThe authors would like to sincerely thank Deborah Goggin, MA, scientific writer, A.T Still University, for her assistance in reviewing the manuscript.Correspondence: Stuart A. Wright, DAT, ATC, CSCS, El Paso Locomotive FC, 1 Ball Park Plaza, El Paso, TX 79901. Email: [email protected]eduFrom El Paso Locomotive FC, El Paso, Texas (SAW); and the Athletic Training Program, Department of Interdisciplinary Sciences, Arizona School of Health Sciences, Department of Research Support, and School of Osteopathic Medicine in Arizona, A.T. Still University, Mesa, Arizona (ARSV).The authors have no financial or proprietary interest in the materials presented herein.

Referência(s)