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© 2005 American Public Health Association
DOI: 10.2105/AJPH.2004.050807
RESEARCH AND PRACTICE |
At the time of the study, Jingzhen Yang, Stephen W. Marshall, J. Michael Bowling, Carol W. Runyan, and Frederick O. Mueller were with the University of North Carolina Injury Prevention Research Center, Chapel Hill. Stephen W. Marshall is also with the Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill. Jingzhen Yang, J. Michael Bowling, Carol W. Runyan, and Megan A. Lewis were with the Department of Health Behavior and Health Education, School of Public Health, University of North Carolina at Chapel Hill. Frederick O. Mueller is also with Department of Exercise and Sport Science, University of North Carolina at Chapel Hill.
Correspondence: Requests for reprints should be sent to Jingzhen Yang, the Department of Community and Behavioral Health, College of Public Health, The University of Iowa, 200 Hawkins Drive, E236 GH, Iowa City, IA 52242 (e-mail: jingzhen-yang{at}uiowa.edu).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Objectives. We sought to describe the use of discretionary protective equipment among high school athletes and to examine social and behavioral determinants contributing to equipment usage.
Methods. We analyzed data from a 3-year (1996–1999), stratified, 2-stage cluster sample of athletes engaged in 12 organized sports in 100 North Carolina high schools (n=19728 athlete-seasons) (an athlete-season represents an individual student who participates in a particular sport in a particular season). We used generalized logistic regression to model the association of social and behavioral determinants and demographic variables with discretionary protective equipment use.
Results. About one third of high school athletes self-reported using lower extremity discretionary protective equipment. Girls, seniors, those who played limited-contact sports, and those who played multiple sports reported higher usage. Small school size, low player/coach ratio, high proportion of team usage, and history of previous lower extremity injury were important predictors of usage. Coaches’ experience, qualifications, and training, however, were not predictive of usage.
Conclusions. Intervention efforts to promote use of discretionary protective equipment need to target school-level factors and should consider both team requirements and the role of peers in setting and reinforcing norms.
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INTRODUCTION |
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Use of protective equipment has been recognized as a common injury prevention strategy.1–6 Because the number of high-school students participating in organized sports has increased each year, rising to approximately 7 million in 2003,7 sports injuries have become more widespread and pose an increasingly serious threat to the health and well-being of young people.8 In particular, although sports and recreational activities are widely promoted as parts of healthy lifestyles, the physical and psychological benefits gained from participating in sports may be diminished if participants are injured.9–12
Although an extensive body of literature addresses various types of protective equipment and its role in protecting specific body parts from injuries,5,6,13–21 the patterns and determinants of use of discretionary (non-mandatory) protective equipment by high school athletes are poorly understood. An understanding of the determinants of voluntary use of protective equipment is crucial to developing intervention programs and policies to increase protective equipment use and thereby prevent sports injury.
A social and behavioral science perspective suggests that behavior is influenced by the social context in which the individual lives. Social cognitive theory, in particular, defines human behavior as a triadic, dynamic, and reciprocal interaction of personal factors, behavior, and environmental influences.22,23 In this context, the decisions of high school athletes to use discretionary protective equipment are influenced not only by individual determinants but also by the physical and social environment.22,23
No existing conceptual model in the injury literature describes the determinants leading to use of discretionary protective equipment by high school athletes to prevent sports injury; therefore, we used social cognitive theory as a guide to understand the determinants of discretionary protective equipment use. We proposed the model shown in Figure 1
on the basis of injury prevention literature,14,17,21 health behavior models,22–24 and developmental theory.25 This model posits that injury risk and severity are influenced by the use of discretionary protective equipment, which, in turn, is determined by aspects of the physical and social environment, observational learning through team member’s modeling equipment use, and the athlete’s behavioral capability. This model is supported by research which shows that: (1) health-protective behaviors are associated with smaller school size. Students in smaller schools are more attached to schools, have closer relationships with teachers, and have more parental involvement. Consequently, they are more likely to engage in health promoting behaviors.26–29 (2) A coach’s experience, qualification, and training creates a social environment that encourages equipment use.30–32 In addition, athletes in a team with lower player/coach ratio would receive higher quality instructional and emotional support.33,34 (3) Modeling of equipment by team members leads to more use.35,36 (4) Skills and knowledge deficits are associated with injury experience.14,37 Support for the conceptual model shown in Figure 1 would suggest that to reduce injury risk and severity, changes in use of discretionary protective equipment by high school athletes, like the learning of other complex behaviors, would ultimately be best accomplished through modifying behavioral determinants at intrapersonal, interpersonal, and environmental levels.
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In this study, we describe the use of discretionary protective equipment among high school athletes and examine how social and behavioral determinants, consistent with social cognitive theory, influence equipment use by high school athletes. In particular, we examined how school size; coach experience, qualifications, and training; player/coach ratio; teammate usage of protective equipment; and a history of prior injury affect use by athletes of lower-extremity discretionary protective equipment (e.g., kneepads, shin guards, knee braces, and ankle braces).
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METHODS |
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Data and Study Design
We used data from the North Carolina High School Athletic Injury Study, a 3-year prospective cohort study conducted from 1996 through 1999. The study design included a stratified 2-stage cluster sample of 100 North Carolina public high school athletes. At the first stage, each of the 324 member schools of the North Carolina High School Athletic Association was first assigned to 1 of 50 strata according to school size and geographic region. Two schools were then randomly selected from each stratum. At the second stage, 6 team sports in each study school were selected. We used systematic sampling to ensure that the sample spanned all seasons and included teams from both genders. Finally, all athletes on each selected team were included in the sample as study athletes. The study followed each selected team for 3 years. A detailed description of the study design and methods has been published elsewhere.38
A total of 100 high schools and 12 sports, 6 male sports and 6 female sports, were included in the analysis. The study sports were boys’ and girls’ soccer, boys’ and girls’ track, boys’ and girls’ basketball, boys’ baseball, boys’ wrestling, boys’ football, girls’ softball, girls’ volleyball, and girls’ cheerleading. The unit of analysis in this study was an athlete-season, which was defined as an individual student who participated in a particular sport in a particular season. Thus, an individual student who participated in several sports during each year might have been surveyed several times in each year.
Variables and Measures
Use of lower extremity discretionary protective equipment (LEDPE ), the outcome variable, was defined as any self-reported usual use of lower extremity protective equipment not mandated by sports rules.39 We did not include mandatory use of protective equipment in this study because such usage does not reflect an athlete’s personal choice. For example, the rules mandate the use of kneepads in football and shin guards in soccer; therefore, using such protective equipment in these sports was not classified as use of LEDPE in this study.
Use of LEDPE was assessed at preseason by asking athletes to respond to the question, "What protective equipment do you usually use?" The athletes participating in a specific sport were asked to select the protective equipment they used from a checklist. Because rules vary across sports, the same piece of protective equipment might be required in one sport but optional in another. For each sport, we determined whether use of a given piece of protective equipment was discretionary or mandatory on the basis of the rules. We limited discretionary protective equipment to only lower extremities because they are the most commonly injured body sites among high school athletes.40–42 We combined 3 years of data in the analysis because there were no significant differences in LEDPE usage over time (year 1, 33.8%; year 2, 34.4%; and year 3, 34.6%, P = .6). The four types of LEDPE regularly used by high school athletes and included in this study were: kneepads, shin guards, knee braces, and ankle braces. Use of LEDPE was coded dichotomously.
School size, a predictor variable, constituted our measure of the school’s physical environment.26 We measured school size as the number of students enrolled at the beginning of each school year27 and categorized it into "small" (fewer than 960 students enrolled), "medium" (960 to 1310 students enrolled), and "large" (more than 1310 students enrolled).
Head coach experience, qualifications, and training (EQT), a composite score predictor variable, was used to measure an aspect of the school’s social environment and to assess the influence of coaches on LEDPE use. We created head coach EQT by summing 5 binary head coach characteristic variables: (1) coached the particular sport more than 1 year at a high school level or higher; (2) played the sport more than 1 year at a high school level or higher; (3) had a graduate level of education; (4) was currently certified in a safety-related area; and (5) had taken a coaching class. The composite score was used because none of these individual measures was more predictive of protective equipment usage than the composite score.32 We then categorized the composite score variable into three levels ("low," "medium," and "high") on the basis of its distribution.
Player/coach ratio, another measure that reflected the school’s social environment, was computed as the number of athletes in a team divided by the total number of coaches (head coach and assistant coaches) for that team. We defined a team as a group of athletes who represented the same school and participated in the same sport in the same year. We coded the variable into three categories: "low" (ratio 
10), "medium" (10 < ratio 16), and "high" (ratio > 16) on the basis of the distribution.
Team use of LEDPE, a predictor variable that reflected the construct of "observational learning," was calculated as the number of teammates (other than the athlete) who reported using LEDPE, divided by the total number of athletes on the team, and then multiplied by 10. The proportion of team members’ use was then coded as a categorical variable; 0% use was considered "not used," 1%–25% was "low," 26%–50% was "medium," and 51% or higher was "high."
History of prior lower extremity injury, a proxy of "behavioral capability," was assessed at preseason by asking athletes whether they had sustained any injury before the start of the sports season. In the case of athletes who remained in the study more than 1 year who sustained injuries during 1 sport season but indicated "no prior injury" at the beginning of a subsequent season, we updated the injury history variable to reflect known prior injuries. Only athletes with a history of lower extremity injury were classified as having a history of prior injury. The variable was coded dichotomously.
We included 4 variable demographic characteristics of athletes in the multivariable model. They were gender (male vs female), grade (9th, 10th, 11th, or 12th), whether an athlete had played multiple sports in the past (yes vs no), and the type of sport in which an athlete was currently participating. The sports were categorized as "full-contact sports" (e.g., football, wrestling), "limited-contact sports" (e.g., basketball, soccer, baseball, softball), or "noncontact sports" (e.g., track, volleyball, cheerleading) on the basis of the amount of allowed body contact among players.39
Statistical Analysis
We used descriptive statistics to describe number and proportion of any LEDPE use, including use of braces, pads, and shin guards. We used 
2 tests to determine the differences in LEDPE usage among the subgroups.43
We used generalized logistic regression to model LEDPE use with the independent variables of interest,44 including social and behavioral predictor variables (e.g., school size, coaches’ EQT, player/coach ratio, team use of LEDPE, and a history of prior lower extremity injury) and the demographic variables of the athletes (e.g., gender, grade, type of sport, and whether athletes had played multiple sports in the past). We calculated unadjusted and adjusted odds ratios for LEDPE use; no LEDPE use was the referent. Odds ratios greater than 1 indicate an increased usage.44
We used SAS-callable SUDAAN 8.0 computer software (Research Triangle Institute, Research Triangle Park, NC) to perform all statistical analyses. Because some athletes stayed in the study for more than 1 year and some participated in more than 1 sport per season, their use of LEDPE across or within seasons was correlated. We used SUDAAN to account for within-subject correlation.45 We weighted data to account for complexity of sampling and nonresponse.
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RESULTS |
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Demographic Characteristics
A total of 13513 individual students were included in the analysis, which constituted 19728 athlete-seasons. Of 13513 students, 7916 (61.3%) were male and 5597 (38.7%) were female. Nearly two thirds (62.9%) of the students described themselves as White, and approximately three fourths (74.0%) of athletes participated in multiple sports. A total of 418 (70.2%) male coaches and 191 (29.8%) female coaches participated in the study, with ages ranging from 20 to 65 years. Twenty-two percent of the coaches reported having a graduate level of education. The average player/coach ratio was 16.
Prevalence of LEDPE Use
Table 1 presents the patterns of LEDPE use according to the demographic characteristics of the athletes. Approximately one third of the athletes (32.5%, 95%CI=29.8, 35.2) reported use of LEDPE. Athletes who were female, were in their senior year, played limited-contact sports, or played multiple sports in the past were more likely to report using LEDPE. Athletes playing boys’ baseball, girls’ softball, and girls’ volleyball reported highest usage; athletes in both boys’ and girls’ track, boys’ soccer, and girls’ cheerleading reported lowest usage. Athletes with a history of lower extremity injury reported higher proportion of LEDPE usage than those without history of lower extremity injury at 54.4% versus 23.8%, respectively.
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Of the four types of LEDPE studied, kneepads were used most often (17.9%), followed by ankle braces (11.2%), knee braces (7.6%), and shin guards (0.1%) (Table 2
). Female athletes were more likely to report using kneepads, ankle braces, and shin guards, but male athletes reported more knee brace use. Athletes who were in the 11th or 12th grade reported brace use more often than athletes in the 9th and 10th grades did. Athletes who participated in full or limited-contact sports were more likely to report using knee braces, ankle braces, and kneepads than athletes who participated in noncontact sports.
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Determinants of LEDPE Use
We used generalized logistic regression to examine the determinants of athletes’ use of LEDPE. The unadjusted and adjusted odds ratios for use versus no use of LEDPE are presented in Table 3
. The results showed that athletes from small schools had a 29% increase in the odds of LEDPE usage compared with those in large schools. Athletes who had a history of previous lower extremity injury had 4.4 times greater odds of LEDPE usage than those without previous lower extremity injuries. Athletes who played on teams with lower player/coach ratio or greater proportions of teammates who used LEDPE were more likely to use LEDPE themselves. However, there was no association between use of LEDPE and coach EQT.
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We conducted further analysis by examining influence of teammates on LEDPE use. Teammate usage was rescaled to be centered about its school mean by computing the average teammate use within a school and the difference between a team and its school mean.46 The findings suggested that the influence of teammate LEDPE usage is a function of both the school and the team. Athletes who are in a school with average teammate usage greater than 50% had a 4.2 times greater odds (95% CI = 3.3, 5.4) of LEDPE usage than those in a school with an average teammate use of less than 50%. Athletes on teams in which the proportion of teammate use was greater than the school average had 6.5 times greater (95% CI = 5.2, 8.1) odds of LEDPE usage than those on teams with team-mates who use less than the school average.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Our study expands upon previous research on protective equipment use to prevent sports injury in two ways. First, it describes the prevalence of use of discretionary protective equipment by North Carolina high school athletes. Second, the study advances our understanding of the social and behavioral determinants of discretionary protective equipment use by including interpersonal and environmental factors, in addition to individual level determinants, in the analysis of usage behaviors. Our findings have implications for future research and intervention strategies.
Despite the importance of protective equipment use in preventing youth sport injuries,3,4,14 relatively few studies have used social and behavioral theories to inform the examination of the determinants of such use. Most previous studies of protective equipment usage have been limited to individual level determinants (i.e., gender, grade, injury history, sports position played, attitudes and beliefs).14,37,47–51 The environmental and interpersonal determinants that may have a direct or indirect impact on decisions by athletes to use protective equipment have been largely ignored. Furthermore, previous research has mainly focused on elite athletes rather than high school athletes.2–6,48 However, youth sports participants constitute the majority of the injury burden attributable to sports.52
LEDPE Use in Limited-Contact Sports
Although full-contact sports have the highest level of body contact and require athletes to wear more protective equipment,53 our findings showed that the use of LEDPE was higher in limited-contact sports than in full-contact sports. This result may be largely an artifact of reduced potential for LEDPE use in full contact sports that require players to wear more protective equipment. For example, kneepad use by football players is required,39 so we did not include kneepad use as discretionary protective equipment for this sport.
Our finding that more than 80% of boys’ baseball and girls’ softball players reported using discretionary protective equipment suggests that there is a strong perceived need for such use, and mandatory equipment rules should be also re-evaluated.
Determinants of LEDPE Use
Consistent with the existing literature,26,28,29,54,55 our findings suggest that small school size was associated with a higher proportion of discretionary protective equipment use, even after adjusting for other variables. A key explanation for such a pattern is that when school size is smaller, students are closer to each other and parents are more involved in the school, increasing the likelihood of a positive effect of the social environment.26,56 The sports examined in our study are all team sports in which players rely on each other. Cooperative interdependence in smaller schools may also create an environment that fosters a health-protective environment for athletes. Although school size may not be easily changeable, future intervention efforts regarding protective equipment use should examine different strategies for schools of different sizes.
Guided by social cognitive theory, observational learning or peer influence has been widely applied in the field of health behavior and health education.22,35,50 Consistent with previous research linking peer influence to other protective behaviors,35,49 we found that athletes who played on a team with a higher proportion of players who used LEDPE were more likely to use protective equipment themselves. Perceived peer influence in this age group is more important than attitudes in determining many behavior choices,35,36 although decisions to wear or not to wear protective equipment may also be influenced by concerns about perceived appearance.22 The elevated odds of a player’s usage observed in this study may be spurious, because some teams may provide equipment to every player, or equipment may be required by some coaches. Because this type of information was unavailable for analysis, we cannot determine the extent to which this may have influenced athlete behavior.
Two studies of rugby noted that previous injury was 1 of 2 main reasons for protective equipment use among rugby players.14,37 We also found that athletes with a previous injury had 4.4 times greater odds of using lower extremity discretionary protective equipment. Athletes who have experienced previous injury may be more aware of the advantages of using protective equipment and thus more motivated to use it. Preventing sports injury is important for all athletes. However, because a history of prior injury is also one of the strongest predictors of reinjury,57,58 special effort needs to be made to encourage use by those athletes with a history of prior injury.
Previous studies have shown that through their unique position of trust and authority, coaches can influence the personal behavior of an athlete.33,34 Findings from this study, however, indicated no association between coach EQT with athletes’ increased use of LEDPE, although a low player/coach ratio was associated with enhanced use of LEDPE. We had no measures of coach attitudes toward injury prevention, their perceptions about the importance of using protective equipment, or how they emphasized injury prevention in their coaching. These are factors that may be more proximal sources of influence than coach EQT. Future studies should more closely examine the influence of coaches, including how their attitudes and beliefs about injury risks, and their encouragement of protective equipment use, might affect their players.
Although these data allowed for a careful examination of several determinants of athletes’ use of LEDPE, the information on use of protective equipment was on the basis of self-reported data and may be subject to social desirability bias. Moreover, information on the availability of the discretionary protective equipment, and whether it was provided by the schools, coaches, or athletic trainers, was not collected in this study. Thus, the results on the estimation of team member influence on use of discretionary protective equipment could have been overestimated. Finally, because of limited data on individual expectations or the social context (e.g., peer norms, performance expectations when using protective equipment), our assessment of individual level factors or peer influence on LEDPE usage may be underestimated.
Conclusions
Social cognitive theory has been successfully used to develop preventive interventions for adolescents.59 The findings of present research suggest that it may also be a useful basis for developing interventions to reduce sports injury among high school athletes.
Our findings on small school size, low player/coach ratio, high usage by team-mates, and a history of prior injury associated with higher usage among high school athletes suggest that intervention efforts to promote use of discretionary protective equipment need to target school-level factors and involve peer influence.
Further study that explores why team factors (e.g., coaches and teammates) affect decisions by athletes to use LEDPE, and what role schools could play to promote the usage, is a logical next step. In addition, those who are responsible for assessing sports rules should consider, in their future deliberations about which equipment to mandate in baseball and softball, that as many as 80% of athletes in boys’ baseball and girls’ softball already use discretionary protective equipment.
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Acknowledgments |
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This study was supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant R01-AR42297) and the National Center for Injury Prevention and Control (grant R49-CCR402444) to the University of North Carolina Injury Prevention Research Center. We express our appreciation to Dr. Nancy Weaver, Dr. William D. Kalsbeek, John Sideris, Brian Sutton, and the advisory board of the North Carolina High School Athletic Injury Study, particularly Richard Knox and William E. Prentice, Jr. We acknowledge the invaluable contribution of the high school athletic trainers and athletic directors who participated in this project.
Human Participants Protection
The committee on research involving human subjects of the School of Public Health, the University of North Carolina at Chapel Hill approved this study.
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Footnotes |
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Peer Reviewed
Contributors
J. Yang originated the study, conducted the analyses, and led the writing of the article. J M. Bowling and S. W. Marshall collaborated on conceiving the analyses, interpreting the results, and writing the article. M. A. Lewis and C. W. Runyan collaborated on developing the conceptual model, interpreting the results, and writing the article. F.O. Mueller collaborated on interpreting the results and writing the article.
Accepted for publication March 3, 2005.
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