Athletic training & sports health care

Purpose: To investigate differences in lower extremity joint angles between a forward (FSD) and lateral (LSD) step-down task at different heights (4 and 6 inches). Methods:Eighteen healthy adults performed four variations of the step-down task while hip, knee, and ankle kinematics were measured.A two-way repeated measures analysis of variance was performed.Results: There was a significant interaction and main effect for step direction and height for knee external rotation and ankle dorsiflexion angle (P < .05).Participants exhibited greater hip adduction, knee flexion, knee adduction, and ankle dorsiflexion during performance of the FSD than the LSD at the 4-and 6-inch height.For each step direction, participants demonstrated greater hip flexion, hip adduction, knee flexion, knee adduction, and ankle dorsiflexion during performance of the task at the 6-inch height. Conclusions:The FSD requires greater movement of the lower extremity than the LSD and increasing step height increases the biomechanical demands of the lower extremity.

Purpose: To determine the relationship between diagnosed concussions and impulsivity and sensation seeking in collegiate student-athletes. Methods: A convenience sample of 1,244 collegiate studentathletes (56.5% males; age: 19.52 ± 1.33 years) from four colleges and/or universities. This cross-sectional study used a 10-minute survey that included demographics, previously diagnosed concussion history, the 15-item Barratt Impulsiveness Scale, and the 8-item Brief Sensation Seeking Scale. Results: Impulsivity and sensation seeking were statistically significant correlates of total diagnosed concussions using Spearman’s rho (rho for impulsivity = .08, P < .01; rho for sensation seeking = .08, P < .01). Impulsivity remained a statistically significant predictor (exp(b) = 1.35, 95% CI = 1.16 to 1.54) in a negative binomial regression model, suggesting that a 1-point difference in impulsivity implies a 35% increase in concussions when adjusting for covariates. High-risk concussion sport type was also a significant predictor (exp(b) 2.02, 95% CI = 1.37 to 2.67). However, sensation seeking (exp(b) = 1.14, 95% CI = 0.94 to 1.34) and sex (1 = male, exp(b) = 1.03, 95% CI = 0.60 to 1.46) were not statistically significant. Conclusions: There may be a potential association between impulsivity and concussions, but longitudinal research is needed to help clarify the cause-and-effect directionality between concussions and impulsivity. [Athletic Training & Sports Health Care. 2021;13(6):e402-e412.] Sport-related concussions are a high-profile public health concern that affects athletes at all levels.1 Concussions are heterogeneous injuries that can present with a variety of physical symptoms (eg, headache, dizziness, and nausea) and impairments (eg, balance, cognitive, ocular, and vestibular).2 Although most physical and cognitive symptoms resolve within 14 days for adults3 and 30 days for children,4 many athletes experience lingering post-concussive symptoms and impairments.3 Although research suggests that multiple concussions may be associated with the development of mood, behavior, and cognitive changes,5,6 more research is needed regarding which intrinsic variables may be a risk factor for sustaining a concussion and which variables may be a consequence of injury. A starting point for concussion prevention is to identify injury risk factors. This may lead to interventions that can be developed to provide at-risk athletes with additional concussion education and sport technique modifications. Risk factors for sustaining a concussion are having a history of previous concussions7,8 and female sex.9-12 Athletes who have previously sustained concussions are at a greater risk of sustaining a future concussive injury compared to athletes with no concussion history.7,8 Females have a higher injury rate of concussions in comparable sports9-12 and take longer to The Relationship Between Impulsivity, Sensation Seeking, and Concussion History in Collegiate Student-Athletes Erica Beidler, PhD, ATC; M. Brent Donnellan, PhD; Anthony Kontos, PhD; Matthew Pontifex, PhD; Sally Nogle, PhD, ATC; Tracey Covassin, PhD, ATC From the Department of Athletic Training, Duquesne University, Pittsburgh, Pennsylvania (EB); the Departments of Psychology (MBD), Kinesiology (MP, TC), and Intercollegiate Athletics (SN), Michigan State University, East Lansing, Michigan; and the Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (AK). Submitted: August 27, 2020; Accepted: February 17, 2021 Supported by Blue Cross Blue Shield of Michigan (EB). The content of this investigation is solely the responsibility of the authors and does not represent the views of the Blue Cross Blue Shield of Michigan. The study sponsor was not involved in the study design, collection, analysis, interpretation, writing of the report, or the decision to submit the report for publication. Disclosure: The authors have no financial or proprietary interest in the materials presented herein. Correspondence: Erica Beidler, PhD, ATC, Department of Athletic Training, Duquesne University, 600 Forbes Avenue, Pittsburgh, PA 15282. Email:

Approximately 15 million individuals suffer a stroke worldwide each year.However, an incidence of stroke in a collegiate athlete is extremely rare.The goal of this case review is to highlight the importance of immediate recognition and rapid response when dealing with an uncommon medical condition, such as stroke, in the collegiate population.[

Isolated fracture of the cuboid bone is rare; therefore, careful examination and appropriate imaging are necessary for prompt recognition and treatment to avoid long-term sequelae.The authors present an isolated cuboid fracture in a collegiate football player following a supination, hyperplantarflexion injury of the foot with recommendations for successful evaluation and treatment.[

Original Research freeConcussion Reporting Intentions Among Division I Football Players: Consideration of Individual-Level and Team-Level Predictors Monica R. Lininger, PhD, LAT, ATC, , , PhD, LAT, ATC Heidi A. Wayment, PhD, , , PhD Ann Hergatt Huffman, PhD, , and , PhD Debbie I. Craig, PhD, LAT, ATC, , PhD, LAT, ATC Monica R. Lininger, PhD, LAT, ATC , Heidi A. Wayment, PhD , Ann Hergatt Huffman, PhD , and Debbie I. Craig, PhD, LAT, ATC Published Online:August 22, 2019https://doi.org/10.3928/19425864-20190822-01AbstractPDF 262.3 KB ToolsAdd to favoritesDownload CitationsTrack CitationsCopy LTI LinkHTMLAbstractPDF ShareShare onFacebookTwitterLinkedInRedditEmail SectionsMoreAbstractPurpose:To investigate the individual- and team-level factors associated with concussion reporting intentions using a hierarchical linear model.Methods:In this multi-site cross-sectional study, 248 athletes from three different National Collegiate Athletic Association Division I football programs completed a post-season questionnaire that assessed individual-level predictors of concussion reporting intentions: self-efficacy, norms about concussion reporting, and negative reporting attitudes. A hierarchical linear model analysis was used to examine the clustered data.Results:Nineteen percent of the variability in concussion reporting intentions was attributable to football program membership, leaving 81% of the variability in concussion reporting intentions predicted by individual-level variables. When adjusting for age and controlling for team-level influences, reporting attitudes and self-efficacy of reporting were significant predictors of concussion reporting intentions.Conclusions:Controlling for team-level factors, concussion reporting intentions were most strongly and significantly predicted by negative reporting attitudes and self-efficacy, across all three football programs. Development of methods to improve athlete self-efficacy and attitudes about reporting concussion symptoms should continue.[Athletic Training & Sports Health Care. 2021;13(1):31–40.]IntroductionResearch on sport-related concussions has grown exponentially over the past several years in an effort to better understand the etiology,1,2 pathology,3,4 methods to improve diagnosis,5–7 and rehabilitation outcomes8–11 for these injured student-athletes. These investigations are needed due to the high prevalence of sport-related concussions in athletics.12,13 Yet, there continues to be less known about the exact factors, both interpersonal and intrapersonal, that encourage a student-athlete to disclose a possible sport-related concussion. It has been noted that at least half of sport-related concussions are not reported by student-athletes.2,14,15 Many theories have been presented as to why student-athletes may not report potential sport-related concussions. These include the student-athlete not thinking the injury was serious enough,16–18 not knowing that it was indeed an sport-related concussion,19–21 not wanting to be removed from participation,16,19–22 and being afraid of letting the team down.17–21 Due to the lack of symptom reporting, valiant efforts have been made to increase the knowledge of sport-related concussions.23–29One of the most used models in predicting concussion reporting behavior is the Theory of Planned Behavior.30 The Theory of Planned Behavior suggests that behaviors can be predicted from attitudes regarding the behavior, subjective norms, and perceived behavioral control.31,32 Another important predictor of behavior is the intention to perform that specific behavior.33 Concussion reporting intentions have been shown to be related to actual in-season concussion reporting behavior.34 Research has consistently shown that the Theory of Planned Behavior provides some explanatory power related to concussion reporting intentions.30,35 Kroshus et al30 found that the Theory of Planned Behavior model provided significant prediction abilities of concussion reporting intentions, but only 25% of the variance in behavior and intention was explained in this sample. Additionally, attitudes, subjective norms, and perceived behavioral control have been associated with intentions to report in high school student-athletes.35 Yet one limitation of concussion reporting intention research using the Theory of Planned Behavior model is that the key variables within the model are individual-level factors that do not take into consideration team-level factors. We argue that behavior is a function of both individual- and team-level factors. This means individual-level factors (eg, positive or negative reporting attitudes) might initially be present with specific members of a team, but these factors will spread to other team members, making these factors distinct to the team (team-level negative reporting attitudes). These team-specific positive or negative reporting attitudes will then affect other individuals within the team, influencing individuals' reporting attitudes within the team. Research on teams has consistently shown that groups have a unique influence on individual behavior.36–38 Although this team-level effect is not an objective artifact, nor observable, it acts as a contextual factor that can be measured by assessing how much team members share in agreement related to the variable.39To date, no research has been published that examines predictors of concussion reporting intentions in a model that allows assessment of the impact that individual- and team-level variables may have simultaneously. Therefore, the purpose of this study was to assess the factors that encourage concussion reporting intention, at both the individual and team levels. Specifically, we assessed the ability of individual- and team-level factors to predict concussion reporting intentions. To test our model, we assessed the four key variables in the Theory of Planned Behavior model (individual-level factors: negative reporting attitudes, social norms, self-efficacy, and concussion reporting intentions) and three team-level factors (team identification, safety climate, and player position) in a sample of collegiate football players. We hypothesized that the set of individual- and team-level factors, together, would be significantly associated with concussion reporting intentions.MethodsParticipantsTwo hundred forty-eight student-athletes (age: 19.8 ± 1.5 years) on National Collegiate Athletic Association (NCAA) Division I football rosters for the 2017 season were invited to participate in this study (Table 1). Nearly 46% of the players self-identified as white, 50% were freshmen or sophomores, and they were equally divided as offensive and defensive players. All research procedures and instruments were approved by the institutional review boards from all institutions.Table 1 Demographic Characteristics and Response Rates of Student–Athletes in SampleVariableFrequencyPercentageNumber of Eligible Members of the TeamResponse RateInstitution (n = 248) 15923.811053.6 210241.111092.7 38735.110087.0Race (n = 218) White10045.9 African American8036.7 Hispanic/Latino41.8 Native American/Alaskan Native00 Asian10.5 Other3315.1Year in school (n = 217) Freshman5625.8 Sophomore5224.0 Junior4822.1 Senior3817.5 Fifth year senior2310.6Position (n = 240) Offense12250.8 Defense11849.2InstrumentationStudent-athletes completed a paper/pencil questionnaire at the conclusion of the 2017 football season. The questionnaire included demographic questions such as age, race/ethnicity, year in college, and six previously validated constructs (Table 2). Four scales23,30 were used for concussion reporting measures and two scales40,41 were selected as team-level assessments, as will later be discussed in detail. We used similar questions in the Fall of 2016 for data collection with 100 football student-athletes from Division I institutions.42,43Table 2 Previously Validated Scales With Individual Items Including Measure of Internal Consistency Used in QuestionnaireScaleItemsRating ScaleCronbach's AlphaVariable/LevelConcussion Reporting Intentions23I intend to report. I plan to report. I will make an effort to report.1 (not very likely) to 7 (very likely)0.98OutcomeSelf-efficacy of Reporting30I am confident in my ability to. . . report symptoms of a concussion, even when I really want to keep playing, report symptoms of a concussion, even when I think my teammates want me to play, report symptoms of a concussion, even if I do not think the symptoms are all that bad, report specific symptoms, even if I am not sure that it is actually a concussion.1 (strongly disagree) to 5 (strongly agree)0.95Predictor; Individual-levelReporting Attitudes30If I report what I suspect might be a concussion, my teammates will… respect me, think I made the right decision, not support me, think less of me.1 (strongly disagree) to 5 (strongly agree)0.86Predictor; Individual-levelSocial Norms Scale23People I know think I should report. People who are important to me think I should report. It is expected of me to report. People who are important would approve of my reporting.1 (strongly disagree) to 5 (strongly agree)0.91Predictor; Individual-levelSafety Climate Scale41My coach. . . is committed to improving player safety, places a strong emphasis on player safety, ensures players have adequate player safety training, encourages players to become involved in player safety, praises players' safe behavior, shows support for football players who report possible concussions, openly discusses player safety with his team.1 (strongly disagree) to 5 (strongly agree)0.96Predictor; Team-levelTeam Identification Scale40I feel very connected with this team. Being a member of this team is very important to me. I am very happy that I belong to this team.1 (strongly disagree) to 5 (strongly agree)0.94Predictor; Team-levelIndividual-Level VariablesFor this study, we used the four most studied predictors of concussion reporting intentions: negative reporting attitudes, social norms, self-efficacy, and reporting intentions.30 Negative reporting attitudes assessed a student-athlete's perceptions and attitudes about the consequences of reporting a potential sport-related concussion. This scale comprised 10 items, eight (Table 2) of which were identical to those found in the Kroshus et al30 study on concussion reporting attitudes and behaviors in a sample of late adolescent ice hockey players. For the current study, only four items (Table 2) were included: "If I report what I suspect might be concussion, my teammates will. . . 'think less of me,' 'respect me,' 'think I made the right decision,' and 'not support me'." The construct of social norms about concussion reporting behavior23 measures the extent to which an athlete believes a variety of referents think about whether or not the student-athlete should report potential concussions. This measure comprised four items (Table 2). The third construct, self-efficacy of concussion reporting,30 measured the extent to which a student-athlete felt confident in his ability to report symptoms of a concussion under different conditions. This measure comprised five items (Table 2). The final construct, concussion reporting intentions, came from work by Register-Mihalik et al23 and consisted of three items (Table 2): "I intend to report," "I plan to report," and "I will make an effort to report."Team-Level VariablesTo assess team-level variability, two constructs (team identification and safety climate) were used. Fransen et al's40 measure of team identification was used to assess the extent to which a student-athlete's personal identity is tied to his team. The scale comprised three items (Table 2): "I feel very connected with this team," "Being a member of the team is very important to me," and "I am very happy that I belong to this team." Next, the safety climate scale was used to determine a student-athlete's attitudes and beliefs about his head coach's role in promoting player safety in football. This eight-item measure (Table 2) was adapted from Beus et al's41 measure of organizational safety climate strength that sought to assess these same attitudes and beliefs regarding a supervisor's responsibility in promoting employee safety. Our adaptation replaced instances of the word "supervisor" with "coach," "workgroup" with "team," and "employees" with "players." Sample items included: "My head coach is committed to improving player safety" and "My head coach encourage players to become involved in player safety." Beus et al's41 measure was conceptually adapted from Zohar and Luria's44 multi-level model and measures of safety climate.ProceduresWe recruited three NCAA Division I football programs (one Football Bowl Subdivision program and two Football Championship Subdivision programs) from three different NCAA conferences. Prior to data collection, a member from the research team explained the purpose of the study, answered all questions, and then obtained informed consent from each participant. Across the three institutions, 248 student-athletes completed the post-season hardcopy questionnaire (Program 1 [Football Championship Subdivision] = 59, Program 2 [Football Bowl Subdivision] = 102, and Program 3 [Football Championship Subdivision] = 87) that took, on average, 15 minutes to complete. Participants received a $10 gift card once the questionnaire was completed. This sample was part of a larger investigation examining the culture of concussion reporting behaviors (see Craig et al43 for more detail about methods and procedures).Statistical AnalysesFrequencies and percentages were calculated for categorical data, whereas means and standard deviations were obtained for continuous variables. Preliminary analyses were conducted in SPSS software (version 24.0; IBM SPSS, Inc) to evaluate the normalcy, missingness, and linearity of the data. If a violation in normality was seen, a natural log transformation was used. For both team identification and the safety climate scale, a median split was applied to create a high/low level of team identification or safety due to violations in normality. There was approximately 12% missingness for race and year in school, but all other missingness was minimal (2%) and the assumption of linearity was met. In addition to the validated scales,23,30,40,41 football position was constructed to help assess team-level influence. A binary variable of position (offensive or defensive player) was used in the statistical analysis.Pairwise comparisons were conducted among the study variables. Pearson's correlation coefficients were used to describe the relationship between two continuous variables (ie, reporting attitudes with norms of concussion reporting), whereas point-biserial coefficients described the relationships between a continuous variable and a nominal variable (ie, negative reporting attitudes with bowl game appearance), and phi coefficients were used for two nominal variables (ie, offensive/defensive player).We used the hierarchical linear model analysis to examine the clustered data (student-athletes nested within football programs) of concussion reporting intentions. The hierarchical linear model allows the data to be modelled to determine how concussion reporting intentions differed between student-athletes while accounting for the clustered nature of the data. That is, student-athletes' attitudes and perceptions (eg, level 1 study variables of concussion reporting intentions, negative reporting attitudes, norms of concussion reporting, and self-efficacy of reporting) are "nested" within the team (eg, level 2 study variables of safety climate, team identification, and position [offense = 1, defense = 0]). The first model (Model 1: Unconditional Model) estimates variation attributable to athletes, individually. The second model (Model 2: Conditional Model) estimates variation attributable to team-level differences. Furthermore, the final model (Model 3: Adjusted Conditional Model) was adjusted for age and parent's median income as a marker of socioeconomic status. Also, to improve interpretation of the findings, the continuous predictors were grand mean centered, therefore showing the average response across groups. Hierarchical Linear Model software (version 7; Scientific Software International, Inc)45 was used for the multi-level modeling with alpha set to 0.05.ResultsSkewness and kurtosis estimates were in the range of normal (±2) along with non-significant Kolmogorov–Smirnov findings (P > .05), except for norms of concussion reporting (skewness: −1.32, kurtosis: 3.95, Kolmogorov– Smirnov: P < .0001), team identification, and the safety climate scale as seen in Table 3. A natural log was applied, transforming the data to a more normal distribution (skewness: 0.20, kurtosis: −0.76, Kolmogorov–Smirnov: P > .05). There were 14 statistically significant relationships between variables, nine positive and five inverse relationships (Table 4). Safety climate, age, and self-efficacy of reporting had the most number of significant relationships with other variables.Table 3 Descriptive Statistics and Normality Estimates of Concussion Reporting Behavior and Football Program VariablesVariableMeanStandard DeviationSkewnessKurtosisSER3.890.94−0.750.27NCR4.350.64−1.323.95Log(NCR)0.190.160.20−0.76RA3.860.79−0.450.45CRI5.391.57−0.990.43TI4.480.87−2.799.33SCS4.250.85−1.835.53SER = self-efficacy of reporting; NCR = norms of concussion reporting; Log(NCR) = natural log transformation of norms of concussion reporting; RA = reporting attitudes; CRI = concussion reporting intentions; TI = team identification; SCS = Safety Climate ScaleTable 4 Pearson's Pairwise Correlations of Individual- and Team-Level Variables Used in Statistical AnalysesAgeSESPositionTeam IDSCSSERLog(NCR)RACRIAge (y)–−0.001−0.130.19b−0.20b−0.18b0.08−0.12−0.15aSES–0.10−0.030.030.05−0.04−0.03−0.05Position–−0.04−0.050.080.10−0.060.08Team ID–−0.05−0.14a−0.22b−0.02−0.07SCS–0.35b−0.020.39b0.17bSER–−0.020.28b0.51bLog(NCR)–−0.07−0.07RA–0.24bCRI–SES = socioeconomic status measured through parents' median income; Position = offensive or defensive player; Team ID = team identification; SCS = Safety Climate Scale; SER = self-efficacy of reporting; Log(NCR) = natural log transformation of norms of concussion reporting; RA = reporting attitudes; CRI = concussion reporting intentionsaP < .05.bP < .001.Equation 1 shows the Model 3: Adjusted Conditional Model:where CRIij is the concussion reporting intentions for athlete j, γ00 is the level 1 intercept, γ01 adjusting for age, γ02 adjusting for socioeconomic status, γ03 is the effect of being either a defensive or offensive player, γ04 effect of team identification, γ05 effect of safety culture, γ10 is self-efficacy for each athlete, γ20 is the effect of reporting attitudes for each athlete, γ30 is the effect of norms for concussion reporting for each athlete, and u0j and rij are the error terms associated for each athlete measured in the study.Using a two-level hierarchical linear model with student-athlete (N = 248) nested within team, 19% of the variability (τ00 / (τ00 + σ2; 0.31 / (0.31 + 1.32) in concussion reporting intentions was attributable to team-level differences, leaving 81% of the variability in the study variables attributable to individual-level differences. These results from Model 1: Unconditional Model only included self-efficacy of reporting, reporting attitudes, and norms about concussion reporting as the predictors of concussion reporting intentions. Moving to Model 2: Conditional Model, which now includes predictors at the team level (eg, offensive/defensive player, team identification, and safety climate scale), 17% of the variability is between schools. In this model, self-efficacy, reporting attitudes, and norms for concussion reporting were all significant predictors of intentions as seen in Table 5. However, when adjusting for age in Model 3: Adjusted Conditional Model, norms about concussions was no longer significant. Self-efficacy and negative reporting attitudes remained significant predictors in the adjusted conditional model. Model 3: Adjusted Conditional Model can be referenced in Equation 1.Table 5 Results of Multilevel Modeling for Concussion Reporting BehaviorsModel 1: Unconditional ModelFixed EffectParameterCoefficientSEdftInterceptB005.800.1420741.51bSelf-efficacyB100.730.122055.89bReporting AttitudesB200.280.122052.38aNorms of Concussion ReportingB30−1.050.62205−1.68Random EffectParameterVariance ComponentSDdfχ2Individual difference of initial valuer0j0.310.56207251.58aModel 2: Conditional ModelFixed EffectParameterCoefficientSEdftInterceptB005.940.2420424.36aPositionB010.240.172041.42Team IdentificationB02−0.130.17204−0.75Safety ClimateB03−0.310.19204−1.66Self-efficacyB100.740.122056.02bReporting AttitudesB200.360.122052.88aNorms of Concussion ReportingB30−1.230.61205−2.00aRandom EffectParameterVariance ComponentSDdfχ2Interceptr0j0.310.56204247.87aLevel 1 effecteij1.321.15Model 3: Adjusted Conditional ModelFixed EffectParameterCoefficientSEdftInterceptB005.930.2520224.14aAgeB01−0.070.06202−1.25SESB020.00050.0004202−1.36PositionB030.260.172021.56Team IdentificationB04−0.100.17202−0.55Safety ClimateB05−0.370.19202−1.91Self-efficacyB100.740.122056.15bReporting AttitudesB200.360.122052.96aNorms of Concussion ReportingB30−1.210.62205−1.94Random EffectParameterVariance ComponentSDdfχ2Interceptr0j0.310.56202245.39aLevel 1 effecteij1.311.14SE = standard error; df = degrees of freedom; SD = standard deviation; SES = socioeconomic statusaP < .05.bP < .001.DiscussionThis study investigated both the individual- and team-level variables that were associated with concussion reporting intentions. We hypothesized that the set of individual- and team-level factors, together, would be significantly associated with concussion reporting intentions. We used a hierarchical linear model approach, a statistical procedure that has not been used in the literature on predictors of concussion reporting intentions, to assess both individual- and team-level factors. Compared to the traditional methods, such as the general linear model that requires an assumption of independence, the hierarchical linear model accounts for the naturally occurring clusters (student-athletes within team) in which the observations are not independent. Student-athletes from the same team are more likely to be similar than those from other schools. Our findings showed that across three Division 1 football programs (N = 248 student-athletes), 19% of the systematic variation in players' concussion reporting intentions could be attributed to team-level variables. Furthermore, when controlling for these team-level variables, and the influence of age and socioeconomic status, 81% of the variability in measured variables was due to individual-level differences. In other words, more than three-quarters of the variability in concussion reporting intentions comes from within the person as opposed to factors related to the team as a whole. Our results strengthen prior research showing the use of the Theory of Planned Behavior model as predictors of concussion reporting intentions. Additionally, to our knowledge, this is the first concussion reporting intentions study to assess the role that group level constructs have in the Theory of Planned Behavior model.Taken together, our results suggest that the decision to report a possible sport-related concussion may be more likely influenced by negative reporting attitudes and self-efficacy, supporting earlier studies that have also shown that these two variables are important for concussion prevention efforts.22,34 For example, players are told that they should report symptoms during a game or immediately after a game. However, we are learning that players are more likely to report other orthopedic injuries when compared to a sport-related concussion.46 It is also reported that the sooner players report symptoms, the sooner they may recover and return to play.14 Although the empirical evidence is growing, the athletes themselves are not readily aware of it. Perhaps if players have practical and focused training about how and when to report symptoms, it would be easier for them to report. Methods to increase self-efficacy are well known,47,48 and include the cultivation of mastery experiences, role models, verbal persuasion, and motivational arousal. It should be noted that in our sample, norms of concussion reporting were not significantly associated with concussion reporting intentions, when adjusting for age and socioeconomic status, which contradicts previous work in NCAA Division I ice hockey student-athletes, where the reporting norm variable was focused on safety (not general reporting norms).49In applying the findings of our study, clinicians and administrators may want to address encouraging individual athletes, coaches, and others associated with the team to shift away from viewing concussion reporting as a negative act and toward this being supported by all as a positive act. This simple shift in framing takes into consideration the individual athlete's potentially negative reporting attitudes and lack of self-efficacy, which accounts for 81% of the variability in our study. Only when these individual-level changes occur can a similar shift in team-level variables occur. How to best influence these specific individual variables toward positive changes has yet to be empirically studied using the hierarchical linear model. Previous research investigating why individual athletes choose to hide or not disclose a possible concussion demonstrates that not wanting to let their coach or teammates down is a primary cause of non-disclosure.16 Thus, changing the perception that the act of reporting a potential concussion is a negative act could alter concussion reporting intentions across many individuals on the team. We suggest that this singular effort to change individual-level reporting attitudes may influence the desired positive change in concussion reporting intentions.Limitations and Future ResearchAlthough this work is novel, it has limitations. The major limitation is that regardless of our ability to find variables that are correlated with concussion reporting intentions, we have no indication of whether intentions are truly related to actual reporting behavior. Another limitation is the lack of a comparison school for the Football Bowl Subdivision institution. Our current analysis used players from two Football Championship Subdivision and one Football Bowl Subdivision institution. The hierarchical linear model analysis would be improved if we had additional players from another Football Bowl Subdivision school. The culture at Football Bowl Subdivision schools may differ from that at a Football Championship Subdivision school. Another limitation impacting generalizability is the use of only three football programs. The findings of this study can also not be generalized to other levels of athletics, other sports, or female student-athletes. Future research can improve upon the current work by including that comparison institution and extending the research in a longitudinal study to see if factors differ across seasons. Building on this study, researchers should investigate the efficacy of interventions designed to improve negative concussion-related attitudes and self-efficacy. If these predictors are directly associated with concussion reporting intentions, interventions aimed at modifying an athlete's perception of performing a behavior along with his or her confidence to perform the behavior are vital to changing concussion reporting behavior.Implications for Clinical PracticeThe results from this study suggest that by using a hierarchical linear model statistical analysis that controls for both individual- and team-level sources of variation, concussion reporting intentions are most significantly affected by individual student-athlete's negative reporting attitudes and self-efficacy. Because student-athletes' reporting attitudes are less negative, and self-efficacy increases, so does their concussion reporting intentions. Instead of focusing interventions on additional education, this study postulates that future educational and behavioral interventions should focus on how best to improve negative concussion reporting attitudes and perceptions of self-efficacy to be able to report in specific competitive situations. Our measure of negative attitudes toward reporting reflected athletes' fears that they would not be respected by their teammates for reporting.Our results imply that intervention efforts must more clearly aim to influence the root of why negative attitudes toward reporting persist. Although concussion education has been mandated at various sport levels by sports oversight committees and in many state legislative efforts, what is included in the educational sessions is less prescribed.20,50 This study supports that efforts beyond simple concussion knowledge (ie, relaying signs and symptoms of sport-related concussions) that go further to address changing negative reporting attitudes and improving self-efficacy would have a greater impact on concussion reporting intentions. Current research evidence suggests addressing negative reporting attitudes through discussion of perceived social norms may benefit concussion reporting intentions.30,35,51 Finally, interventions that are not presented within traditional "concussion education sessions," but rather as team or small group discussions where athletes have the ability to express their concerns, may have a greater impact on decreasing negative attitudes at both the individual and team levels. This approach has yet to be empirically studied to our knowledge.1.Meier T, Bellgowan P, Mayer . A Longitudinal assessment of local and global functional connectivity following sports-relate

Literature Review freePractical Implementation Strategies for Heat Acclimatization and Acclimation Programming to Optimize Performance Yasuki Sekiguchi, PhD, CSCS, ; , PhD, CSCS Courteney L. Benjamin, PhD, CSCS, ; , PhD, CSCS Gabrielle E. W. Giersch, PhD, ; , PhD Luke N. Belval, PhD, ATC, CSCS, ; , PhD, ATC, CSCS Rebecca L. Stearns, PhD, ATC, ; , PhD, ATC Douglas J. Casa, PhD, ATC, , PhD, ATC Yasuki Sekiguchi, PhD, CSCS , Courteney L. Benjamin, PhD, CSCS , Gabrielle E. W. Giersch, PhD , Luke N. Belval, PhD, ATC, CSCS , Rebecca L. Stearns, PhD, ATC , and Douglas J. Casa, PhD, ATC Published Online:February 18, 2021https://doi.org/10.3928/19425864-20201002-01AbstractPDF 758.7 KB ToolsAdd to favoritesDownload CitationsTrack CitationsCopy LTI LinkHTMLAbstractPDF ShareShare onFacebookTwitterLinkedInRedditEmail SectionsMoreAbstractRepeated exercise heat exposures enhance exercise performance through a complex series of adaptations that are referred to as heat acclimatization (HAz), which occurs in an artificial environment, and heat acclimation (HA), which occurs in a natural environment. Special considerations are needed to induce adaptations and verify HAz and HA status. To ensure the effectiveness of each session, sufficient duration of exercise-induced hyperthermia is required. To this end, environmental conditions and exercise frequency, intensity, time, type, volume, and progression can be adjusted to achieve optimal adaptations. Furthermore, adaptations are typically lost within 1 week to 1 month following the cessation of exercise heat exposure and maintenance of adaptations is an important factor. Additionally, selecting the appropriate testing procedure is critical to ensure an athlete's HAz and HA status. The purpose of the current study was to provide various HAz and HA frameworks based on different sports so clinicians can implement HAz and HA to optimize performance. [Athletic Training & Sports Health Care. 2021;13(4):e238–e246.]IntroductionGiven the increased participation of athletes in outdoor sports, the known decrement in performance when exercising in hot environmental conditions, and the high incidences of exertional heat illness in sports (232 exertional illnesses were reported in 5 years in National Collegiate Athletic Association athletes), it is important to fully understand the physiological, psychological, and performance responses of athletes to physical activity in the heat.1–4 A better understanding of athletes' responses in the heat allows for the development of mitigation strategies to enhance exercise performance and safety. The most effective strategies for enhancing performance and safety in the heat are heat acclimatization (HAz) and heat acclimation (HA).Greater physiological strain, such as an increased heart rate and internal body temperature, is placed on the body when an athlete exercises in a hot environment compared to a temperate environment.5 HAz and HA are systematic and repeated heat exposures to induce a set of adaptations, which are important to reduce the incidence of heat illness for athletes who exercise in the heat but can also be an effective agent to reduce thermoregulatory and cardiovascular strain to enhance an athlete's performance in hot and cold environments.5–7 HAz describes heat-related adaptations that are performed in a natural environment (eg, high ambient temperature during normal training outside), whereas HA refers to adaptations elicited from an artificial hot environment (eg, environmental chamber).8 This study aims to provide a framework, rationale, and example scenarios to assist sport coaches, strength and conditioning coaches, and athletic trainers in developing appropriate HAz and HA protocols.Performance EnhancementWhat Are the Benefits of HAz and HA? One of the most rapid adaptations observed following HAz and HA is increased plasma volume leading to increased stroke volume and decreased heat rate, which typically occurs within 3 to 6 days of exercise heat exposure.8,9 The range of plasma volume expansion can be 3% to 27%, which corresponds to decreases in heart rate by 15% to 25%.7,10,11 These adaptations are a result of the expansion of total body water via increases in aldosterone and arginine vasopressin secretion and total plasma protein.8,11 These adaptations also contribute to a better maintenance of cardiac output and blood pressure during exercise.7 An increase in cardiac output likely explains the approximately 5% improvement in VO2max following HA, which leads to performing exercise at a lower relative intensity when absolute workload is matched.8 Additionally, perceived exertion and thermal sensation improve in the relatively early stages of exercise heat exposure during the HAz and HA processes.5,11Arguably the most important adaptation to HAz and HA is the decrease in internal body temperature at a similar exercise intensity in similar environmental conditions. Resting and exercising rectal temperature decrease approximately 0.18 and 0.34 ºC, respectively, within 5 to 8 days of exercise heat exposure.5,8,11 This allows for an increased effort at a relative exercise intensity that can lead to more effective training or enhanced performance.Another important adaptation is the increased retention of electrolytes from the sweat glands.7 Sodium and chloride concentrations in sweat decrease within 5 to 10 days of exercise heat exposure, which leads to better conservation of electrolytes9 and helps to increase total body water.8 Furthermore, the initiation of sweating and the increase of skin blood flow at milder environmental conditions start earlier with exercise heat exposure so that heat dissipation through these mechanisms begins at the lower internal temperature.5,8 Additionally, sweat rate increases within 8 to 14 days of exercising heat exposure.9 This results in an evaporative heat loss of up to 11%.12Metabolic changes are also observed following exercising heat exposure. Blood and muscle lactate accumulation are reduced during submaximal exercise due to a decrease in oxygen uptake and glycogen utilization at a given exercise intensity.5,8 This reduction has been shown to increase power output.7,13 This can be beneficial for sports in which glycogen depletion can cause fatigue, such as marathon or ultra-endurance running.14Beneficial adaptations that occur with repeated exercise heat exposures include plasma volume expansion, higher sweat rate, lowered internal temperature, decreased heart rate, improved maintenance of cardiac output, reduced oxygen demand, less reliance on glycolysis, improved perceived exertion and thermal comfort, and greater power output at lactate thresholds.5,7,8Figure 1 shows the percent change in plasma volume, heart rate, internal temperature, sweat rate, and exercise capacity throughout HA. All of the factors mentioned previously contribute to increased exercise performance following heat acclimatization, especially in sports that require strong aerobic or anaerobic capacity such as running, cycling, soccer, and American football. A lower internal temperature has been found to be an advantage in intermittent sprints performance,15 which is related to team intermittent sports (soccer, lacrosse, rugby, American football, etc). Exercise heat training may lead to an improvement in exercise performance, not only in the heat but also in temperate and cool conditions.13 Thus, exercising heat exposure has advantages to exercise in both hot and cool environments.Figure 1. The percent change in plasma volume, heat rate, internal temperature, sweat rate, and exercise capacity throughout induction in heat acclimation. Created using data from Periard JD, Racinais S, Sawka MN. Adaptations and Mechanisms of Human Heat Acclimation: Applications for Competitive Athletes and Sports. Scand J Med Sci Sports. 2015;25(Suppl 1):20-38. doi:10.1111/sms.12408Heat Acclimatization and Special ConsiderationsHow Do I Know if Someone Is Heat Acclimated?In light of the adaptations that occur, the three following variables can be used to assess heat acclimatization in a field setting: (1) lower rectal temperature or ingestible thermistor at the same environmental conditions and exercise intensities; (2) lower heart rate at the same environmental conditions and exercise intensities; and (3) increased sweat rate at the same environmental conditions and exercise intensities during a repeated test protocol.5,7 For additional evidence supporting HAz and HA, lower rating of perceived exertion (Borg Scale), thermal sensation, and lower environmental symptoms questionnaire scores can also be evaluated during the testing protocol.5,16 This could be a useful, safe, and effective framework that may provide sports scientists, athletic trainers, strength and conditioning specialists, and sport coaches with a tool to evaluate an athlete's acclimatization and acclimation status.How Can I Ensure My Athletes Maintain HAz and HA Benefits?Adaptations achieved by HAz and HA are typically lost within 1 week to 1 month following the cessation of exercise heat exposure.17 Maintenance of HAz and HA is arguably the most important factor in this process because, similar to maintenance of fitness throughout a competitive season, the physiological benefits obtained during this process are crucial to optimize performance. When HAz or HA is accomplished, maintaining the benefits and adaptations allows for enhancing performance in hot and cold environments, along with maintaining safety for athletes exercising in the heat.13,18 Maintenance of HAz and HA is commonly achieved via one to two heat exposures per week following the appropriate acclimatization or acclimation protocol.19 The timing of maintenance is also critical because the benefits of HAz and HA decay rapidly. Because HA is intense training, having athletes complete HA a few weeks before the competition and avoid large amounts of training in the heat right before competition by maintaining HA adaptations is helpful to achieve peak performance. One study demonstrated that 35% of acclimation benefits (heart rate and internal temperature) were lost after 2 weeks without heat exposure.20 Another study showed that approximately 100% of heart rate and 50% of internal temperature losses occurred after 3 weeks without heat exposure.21 Therefore, ensuring appropriate heat exposures following HAz and HA protocol is crucial for the athlete's performance.17,22What Factors Should I Consider for HAz and HA Sessions?Internal Body Temperature. To ensure that each HAz and HA session is effective, internal body temperature should be monitored throughout the exercise session, with each session eliciting sufficient hyperthermia over an adequate duration of time to elicit desired physiological and psychological adaptations.7 Although a minimum temperature of 38.5 ºC and duration of at least 60 minutes has been recommended for this response, HAz and HA should be based on individual responses to exercise in the heat because several variations of protocols have been successful.7,18 Rectal thermometer and ingestible thermometer are the two most common methods of collecting internal body temperature during exercise. Tympanic, aural, oral, skin, temporal, and axillary temperature are not valid assessments of this measurement and should not be used to assess internal temperature.23 All of the following variables can be adjusted based on this internal temperature criterion. Optimal internal temperature is critical to achieve performance benefits. Similar to other aspects of training, optimal adaptations require the application of an appropriate load.7 Similar to aerobic or strength training, HAz and HA can be thought of as a supercompensation response. Adaptations obtained by HA have been shown to be maximum 3 days following HA induction.24 Too little load, in this case rise in internal temperature, will result in suboptimal adaptations. Meanwhile, too much load can put an individual at risk for exertional heat illnesses.25Environmental Conditions. When using the natural environment to achieve HAz and HA, environmental conditions should be appropriately monitored with valid measures of ambient temperature and relative humidity, or with a wet-bulb globe temperature device that incorporates ambient temperature, humidity, and radiant heat load.7 When using an artificial setting (heat laboratory, indoor facility, etc) environmental conditions can be altered, based on the desired exercise intensity, to achieve sufficient hyperthermia. The primary environmental conditions that can be altered are ambient temperature and relative humidity, unless in a facility that can allow for precise radiant heat exposure. Coaches should consider the environmental conditions of the target competition to guide selection of the environmental conditions and optimize the benefits of HAz and HA.7Exercise Frequency, Intensity, Time, Type, Volume, Progression Model for HAz and HAFrequency. The frequency of the HAz and HA protocol should be based on the needs analysis of the team or individual. Daily heat exposure is the fastest way to obtain adaptations, although two sessions in 1 day does not appear to enhance this process.26 When daily heat exposure is not feasible, intermittent heat exposures can also be conducive for achieving adapatations.27Intensity. The intensity of the sessions can be based on several variables (eg, VO2max, heart rate, and the internal body temperature).17 If internal temperature is measured during these sessions, the intensity can be adjusted throughout the sessions to obtain adaptations. If internal temperature is not measured, the session intensity should be above 50% VO2max.9 Although laboratory-grade VO2max values may not be achievable in a practical setting, there are several validated tests that can be used to estimate an athlete's VO2max, including the Yo-Yo Intermittent Recovery Level 2 test, 1.5-mile run, and 12-minute run test.28,29 Additionally, sports training can be used to induce HAz.30Time: Circadian Rhythm. Based on the nature of circadian rhythm, attainability of HAz and HA is more conducive to exercise in the afternoon.31 This can decrease the overall training intensity and volume on the athlete when considering time to reach the hyperthermia and training time.Time: Before Competition. To ensure maximum benefits, coaches should consider completing HAz or HA at least 2 weeks prior to the competition of interest and begin implementation of the maintenance protocol to reduce training stress and peak for the target competition.24 If HAz or HA is desired for a longer period, such as throughout an entire season, the maintenance protocol discussed above should be implemented to prevent decay.Environmental Variation Throughout Competitive Season. Coaches should also consider the environmental conditions of each sport and how that affects an athlete's HAz and HA status. For example, fall sport athletes (eg, football, soccer, and cross-country) typically train in warm environmental conditions throughout the summer and during pre-season to prepare for their competitive season, and therefore, start the season heat acclimatized and may benefit from a maintenance protocol.32–34 Spring athletes (eg, track and field and field hockey), who typically begin their season in cooler environmental conditions and are not heat acclimatized, would benefit from HA training to prepare for warmer competitions later in the season.Type. HAz and HA can use sport-specific exercise modalities to achieve the adaptations as long as athletes are monitored appropriately to ensure the safety of the athlete's exercise in the heat.35 Alternatively, exercise modalities that reduce the training stress of the athlete can also be used to achieve adaptations (biking, incline walking, etc). Alternative methods, such as sauna and wearing extra clothing, can be used to induce adaptations; however, exercise is needed to achieve optimal adaptations.35,36 When alternative methods are used, coaches and athletes should strongly consider combining those alternative methods with exercise to achieve maximum performance enhancement.35When an environmental chamber is not available, a small enclosed room can be used to induce or maintain HA. To create this room, select a room that is large enough to add exercise equipment but small enough to sufficiently heat with space heaters. Use a wet-bulb globe temperature monitor to determine the environmental conditions in the room throughout all exercise sessions, because temperature and humidity can rise substantially with exercise to maintain appropriate environmental conditions. Internal body temperature should also be continuously monitored in this setting to ensure safety.25 Additionally, extreme fatigue and exhaustion during exercise should be avoided to reduce the risk of heat illnesses, such as exertional heat stroke and exertional heat exhaustion, and to perform sessions safely.25Volume. As with any additional training stress, coaches should consider the total physical and mental demands placed on the athlete.35 If HAz or HA is desired for improved sport performance, other training volume, intensity, or duration may need to be modified to ensure the athlete does not overtrain or develop maladaptations.35 It is important to note that HAz can be achieved in the scope of the athlete's normal training, as long as sufficient hyperthermia is met during those sessions.Progression. Intensity, time, environmental conditions, and volume should be increased gradually over the course of the protocol.5 To achieve the adaptations, intensity and environmental conditions are the two primary modifiable variables.Fluid Intake. Coaches should ensure that athletes are consuming adequate fluid to maintain euhydration to minimize fluid loss and reduce the risk of heat illness during exercise.37 Fluid intake can be prescribed based on losses (before to after body mass measures) and sweat rate (Table A, available in the online version of this article).38Table A Heat Acclimation Testing Data SheetAthlete Name__________________ Testing# Date____________________Pre BM______________(kg) Post BM______________(kg) Fluid intake_________(kg)Pre Fluid Bolus Mass_____________(kg) Post Fluid Bolus Mass_____________(kg)TimeInternal TemperatureHRRPEThermalAmbient TemperatureHumidityNote0510152025303540455055END:Time __________________Internal Temperature __________________ HR __________________RPE __________________ Thermal __________________Temperature __________________ Humidity __________________Safety. Gradual implementation of heat exposures is important to maintain the safety of all players.39 Special considerations are needed for at-risk populations, such as those taking medications that could affect thermoregulation and fluid balance and individuals with a past history of heat illness or sickle cell trait. These individuals may need careful monitoring of internal temperature.HAz and HA ScenarioThe following tables provide examples of how the methods described in this study can be used in real-world scenarios. Testing procedure, HAz, HA, and maintenance examples are described for different sports with different goals in mind. Data sheets that can be used for testing, training, rating perceived exertion, thermal sensation, and thirst scale are provided in Tables B–F, available in the online version of this article, respectively. Although these are examples, strength and conditioning can use these scenarios to create HAz and HA protocols for their athletes.Table B Heat Acclimation Training Data SheetName__________________ Trial # Date____________________Pre BM______________(kg) Post BM______________(kg) Fluid intake_________(kg)Pre Fluid Bolus Mass_____________(kg) Post Fluid Bolus Mass______(kg)TimeSpeed/ResistanceInternal TemperatureHRAmbient TemperatureHumidityNote/Table C Rating of Perceived Exertion Scale67Very, Very Light89Very Light1011Fairly Light1213Somewhat Hard1415Hard1617Very Hard1819Very, Very Hard20Reprinted with permission from Borg G. Psychophysical scaling with applications in physical work and the perception of exertion. Scand J Work Environ Health. 1990;16(suppl 1):55–58. doi:10.5271/sjweh.1815Table D Thermal Sensation Scale0.0Unbearable Cold0.51.0Very Cold1.52.0Cold2.53.0Cool3.54.0Comfortable4.55.0Warm5.56.0Hot6.57.0Very Hot7.58.0Unbearably HotReprinted with permission from Young AJ, Sawka MN, Epstein Y, Decristofano B, Pandolf KB. Cooling different body surfaces during upper and lower body exercise. J Appl Physiol (1985). 1987;63(3):1218–1223. doi:10.1152/jappl.1987.63.3.1218Table E Thirst Scale1Not Thirsty At ALL23A Little Thirsty45Moderately Thirsty67Very Thirsty89Very, Very ThirstyCreated using data from Engell DB, Maller O, Sawka MN, Francesconi RN, Drolet L, Young AJ. Thirst and fluid intake following graded hypohydration levels in humans. Physiol Behav. 1987;40(2):229–236. doi:10.1016/0031-9384(87)90212-5Table F Sweat Rate Calculation Instructions1.Before the exercise, ensure the athlete is hydrated (light colored urine). Being dehydrated may affect normal sweat rate.2.Take nude body mass before the start exercise.3.Perform exercise.4.If water is consumed, weigh the water before and after the exercise to determine the amount of fluid intake. A.Pre water weight: _______kgB.Post water weight: _______kgC.A – B: ___________kg fluid consumed5.After the exercise take another body weight and calculate the difference between pre and post exercise. D.Pre-exercise nude body mass: _______kgE.Post-exercise nude body mass: _______kgF.D – E: ___________kg body mass loss6.Pre and post body weight, fluid intake, and exercise duration are used to calculate sweat rate (L·hour−1) with the following equation.(F + C) × 60 / exercise duration (min)Note: Every 2.2 pounds a person loses equates to 1 liter of fluid loss (sweat loss). For example, if someone loses 5 pounds in 1 hour their sweat rate is 5/2.2 = 2.27 liters·hour−1. Similarly any liter of fluid consumed = 33.8 fluid oz. Please note that urinating during this test will skew results. Ideally if an individual needs to urinate the urine should be weighed and added back into the post weight value in order to avoid urine losses being mistakenly calculated as sweat losses.Created using data from Adams JD, Sekiguchi Y, Suh H-G, et al. Dehydration impairs cycling performance, independently of thirst: a blinded study. Med Sci Sports Exerc. 2018;50(8):1697–1703. doi:10.1249/MSS.0000000000001597Scenario 1A team of distance runners has been training in cold weather for the previous 2 months. They will be competing in extremely warm weather or cool weather in 4 weeks. HA can improve exercise performance in not only in the warm weather, but also in the cold conditions. The following methods can be used to ensure they are going to peak for their race. Table 1 indicates the method of assessing responses to the heat prior to HA, primary factors that will be considered for this test, examples of the exercise frequency, intensity, time, type, volume, and progression model, and the outcome variables that will be assessed. Athletes run until their internal body temperature reaches 39.0 °C and their performance will be based the amount of time it takes them to reach that temperature (more time indicates greater adaptation). The internal body temperature is monitored by rectal or ingestible thermometer. Table 2 shows an example of the induction program. Athletes perform 75 to 90 minutes of running or biking and maintain the internal body temperature above 38.5 °C for 60 minutes. They perform this induction session 10 total times. Table 3 indicates the method to maintain adaptations with approximately two times of heat training per week, with the same training method as induction.Table 1 Heat Testing Procedures for Cross-Country AthletesaPrimary factors Internal body temperatureMeasured with ingestible thermistor or rectal thermometer Environmental conditions≥ 35.0 ºC, ≥ 50% relative humidityFITT-VP (secondary factors) FrequencyBefore and after induction plan IntensityEstimate for athlete to reach in 30 to 45 minutes, approximately 70% to 80% of heart rate reserve TimeTime for internal temperature to reach 39.0 or 102.2 ºC TypeRunning VolumeConsider balance between training and heat acclimation ProgressionNot applicableAthlete responsesHeart rate, chest strap Internal body temperatureRectal thermometry, ingestible thermometer Fluid intakeWeigh water bottle before and after exercise Sweat rateSee Table A Perceptual measuresRating of perceived exertion, thermal sensation scaleFITT-VP = frequency, intensity, time, type, volume, and progressionaGoal: Time for internal body temperature to reach 39.0 ºC before and after the procedures. Internal body temperature should be monitored and used as the stopping criterion for the test. The testing information will be used to determine if the heat training protocol elicited the desired physiological responses.Table 2 Heat Exposures for Cross-Country AthletesaPrimary factors Internal body temperatureBetween 38.5 and 39.75 ºC Environmental conditionsCan be adjusted for internal temperatureFITT-VP (secondary factors) Frequency10 sessions, sessions should be no more than 3 days apart IntensityMaintain internal body temperature between 38.5 and 39.75 ºC TimeWarm up for 15 to 30 minutes until internal temperature reaches 38.5 ºC. Train for 60 minutes of internal body temperature is above 38.5 ºC TypeRunning or biking VolumeConsider balance between training and heat acclimation ProgressionProgressive increase in intensity and environmental conditionsAthlete responsesHeart rate, chest strap Internal body temperatureRectal thermometry, ingestible thermometerFITT-VP = frequency, intensity, time, type, volume, and progressionaGoal: Induction of heat acclimation. Athletes should aim for internal temperatures between 38.5 and 39.75 °C to fully elucidate the heat acclimation adaptations. Modifiable factors for this training include: frequency, intensity, time, type, volume, and progression. Type of exercise was chosen based on muscle mass used during exercise that increases the metabolic heat produced; however, other exercises with large muscle groups used continuously could certainly be used. Throughout a heat acclimation induction protocol, intensity and environmental conditions should be gradually increased with each session to maintain safety and not overwhelm the thermoregulatory system too quickly.Table 3 Maintenance of Adaptations for Cross-Country AthletesaPrimary factors Internal body temperatureBetween 38.5 and 39.75 ºC Environmental conditionsSame as the last induction sessionFITT-VP (Secondary factors) Frequency≥ 2 times per week IntensityMaintain internal body temperature between 38.5 and 39.5 ºC TimeWarm up for 15 to 30 minutes until the internal temperature reaches 38.5 ºCTrain for 60 minutes until the internal body temperature is above 38.5 ºC TypeRunning or biking VolumeConsider balance between training and heat acclimation ProgressionNot applicableAthlete responsesHeart rate, chest strap Heart rateChest strap Internal temperatureRectal thermometry, ingestible thermometerFITT-VP = frequency, intensity, time, type, volume, and progressionaGoal: Keep all benefits gained from induction. Athletes should aim for internal temperatures between 38.5 and 39.75 °C to fully maintain adaptations. Modifiable factors for maintenance include: frequency, intensity, time, type, volume, and progression. Type of exercise was chosen based on muscle mass used during exercise that increases the metabolic heat produced, but other exercises with large muscle groups used continuously could certainly be used.Scenario 2A soccer team has been training in cold weather for the previous 2 months. They will be competing in extremely warm weather in 4 to 5 weeks. The following methods can be used to ensure they are going to peak for the game. Table 4 indicates the method to assess baseline responses. This testing includes 60 minutes of steady state exercise to examine the changes in internal body temperature, sweat rate, and heart rate before and after HAz or HA. Table 5 demonstrates the example of HAz or HA. The goal is to maintain the internal body temperature above 38.5 °C for 60 minutes with running, biking, or soccer. Athletes perform HAz or HA training a total 10 to 14 times. Table 6 indicates the method to maintain adaptations, which consist of approximately two times of heat training per week, with the same training method as induction. It is important to consider the balance between soccer training and HAz or HA training.Table 4 Testing Protocol for Team Sport AthletesaPrimary factors Internal body temperatureBetween 38.5 and 39.75 ºC Environmental conditions35.0 ºC, 50% relative humidityFITT-VP (secondary factors) FrequencyBefore and after induction plan IntensitySteady state exercise, approximately 70% to 80% of heat rate reserve Time60 minutes TypeRunning, biking VolumeConsider balance between training and heat acclimation ProgressionNot applicableAthlete responses Heart rateChest strap Internal body temperatureRectal thermometry, ingestible thermometer Fluid intakeWeigh water bottle before and after exercise Sweat rateSee Table A Perceptual measuresRating of perceived exertion, thermal sensation scaleFITT-VP = frequency, intensity, time, type, volume, and progressionaGoal: Internal body temperature and sweat rate increase and heart rate decreases from before to after induction. Rating of perceived exertion and thermal sensation scale can be used as supplementary evidence of heat acclimation and heat acclimatization. In the presence of increased sweat rate, decreased heart rate, and decreased rectal temperature, decreased rating of perceived exertion and thermal sensation scale add to the likelihood of attainment of heat acc