Athletic Training and Sports Health Care

Original Research 

The Relationship Between Athletic Trainer Personality and Patient Trust

Shannon L. David, PhD, AT, PES; Kyle McCuskey, MS, AT; Mary Larson, PhD, MPH, RD; Brent Hill, PhD

Abstract

Purpose:

To determine the degree of influence an athletic trainer's personality has on patient trust.

Methods:

Eighteen athletic trainers from local universities and a random sample of their athletes were recruited for the study (N = 273). The Myers-Briggs Type Indicator personality assessment was administered to the athletic trainers online using skillsone.com and trust questionnaires were administered to the athletes. Athletic trainers were assigned 1 of 16 categories in the 4 personality dichotomies of introversion/extroversion, sensing/intuition, thinking/feeling, and judging/perceiving. A linear mixed model was used with a nominal significance level (P = .05) to evaluate the differences between the dichotomies within the personality types.

Results:

Significant differences in trust between two personality dichotomies (sensing/intuition [P = .009] and thinking/feeling [P = .015]) were detected.

Conclusions:

The personality dichotomies of sensing/intuition and thinking/feeling appear to contribute to trust between athletic trainers and athletes, although more research is needed to better understand the influence of personality on trust in the athletic trainer–patient relationship.

[Athletic Training & Sports Health Care. 2019;11(3):105–112.]

Abstract

Purpose:

To determine the degree of influence an athletic trainer's personality has on patient trust.

Methods:

Eighteen athletic trainers from local universities and a random sample of their athletes were recruited for the study (N = 273). The Myers-Briggs Type Indicator personality assessment was administered to the athletic trainers online using skillsone.com and trust questionnaires were administered to the athletes. Athletic trainers were assigned 1 of 16 categories in the 4 personality dichotomies of introversion/extroversion, sensing/intuition, thinking/feeling, and judging/perceiving. A linear mixed model was used with a nominal significance level (P = .05) to evaluate the differences between the dichotomies within the personality types.

Results:

Significant differences in trust between two personality dichotomies (sensing/intuition [P = .009] and thinking/feeling [P = .015]) were detected.

Conclusions:

The personality dichotomies of sensing/intuition and thinking/feeling appear to contribute to trust between athletic trainers and athletes, although more research is needed to better understand the influence of personality on trust in the athletic trainer–patient relationship.

[Athletic Training & Sports Health Care. 2019;11(3):105–112.]

In health care fields, studies have analyzed trust and its relationship to patient–clinician interactions and patient outcomes.1–3 Overall, patients who trust their physicians take a more active role in their health care.4 Additionally, trust has been directly related to patient satisfaction, adherence to medical intervention, and improved health status.2,3 More specifically, patients who trust their primary care provider are more likely to adhere to new lifestyle interventions,5,6 take prescribed medications appropriately,6–8 and use health care opportunities5,8–10 and preventative interventions.11,12 Because trust is an important factor in patient outcomes, it is critical to better understand the factors that influence trust.

Many factors are known to influence patient–provider trust, including competence, compassion, privacy and confidentiality, reliability and dependability, and communication.2,3,13,14 The relationship between patient and provider develops during the initial visit. The five physician characteristics most strongly correlated with patient trust after the first visit are being caring and comforting, demonstrating competency, being encouraging and answering questions, explaining procedures, and understanding the reasons for the visit.15 Athletic trainer characteristics that influence trust are approachability, personal connection, communication, understanding the patient, and knowledge of the patient's sport.16

Personality

The manner in which people interact with each other is a reflection of their personality. Those interactions could be the foundation of building trust in the patient–clinician relationship, because trust is established during the first interaction. Personal interactions show characteristics of trust (eg, communication and approachability), so it is not unreasonable to wonder if one may influence another. Hall et al.16 suggested that personality is one of the strongest predictors of trust. Because a personal connection is a component of trust, personality may influence how trust is developed.17,18 Studies have examined factors to connect health care professionals' personalities (specifically medical students) to specialty preference, but patient care and trust were not considered.19,20 Unfortunately, the connection between provider personality and patient care (specifically trust) has not been evaluated in other health care professions.

There are a variety of ways to measure personality. The Myers-Briggs Type Indicator (MBTI) personality assessment analyzes personality preferences by categorizing how an individual engages and interacts.21,22 The MBTI instrument assesses personality characteristics through a series of questions related to extroversion/ introversion, sensing/intuition, thinking/feeling, and perceiving/judging. These four dichotomous areas pertain to where an individual prefers to focus, (eg, the external world or the internal world), how an individual gathers information (eg, using the senses or just knows), how an individual makes decisions (from beginning with logic to beginning with the uniqueness of the situation), and how environments are structured (eg, a great deal of consistency or maintaining open and flexible). Although a variety of behaviors and personality characteristics have been considered to affect trust and the patient–provider relationship, the personality type of health care providers has not been researched using the MBTI. Therefore, the purpose of this study was to examine the relationship between an athletic trainer's personality and patient trust.

Methods

Participants

Multistage cluster sampling was used with two distinct levels: athletic trainers and athletes. Each athlete was nested in an athletic trainer, meaning an athlete was under the exclusive care of only one athletic trainer in the sample.

Athletic trainers were randomly selected and recruited from three universities in the midwestern United States representing all three National Collegiate Athletic Association divisions. A total of 18 athletic trainers volunteered for this study (9 from Division I, 4 from Division II, and 5 from Division III). There were 12 female and 6 male athletic trainers who collectively covered a total of 10 different sports (Table 1). The ages of the athletic trainers ranged from 22 to 52 years, with an average age of 30.6 ± 9.4 years. Nine of the athletic trainers had a master's degree or higher, and the other nine were working toward a master's degree in athletic training. All athletic trainers were certified and were working with a team.

Frequencies of Athletes by Primary Sport and Sex

Table 1:

Frequencies of Athletes by Primary Sport and Sex

Athletes were randomly selected from the team rosters of each athletic trainer and invited to participate in the study. A total of 273 athletes (117 women, 156 men) volunteered, collectively representing 10 different sports (Table 1). The athletes in this sample had an average of 2.4 ± 1.1 years of collegiate-level athletic experience, ranging from less than 1 to 5 years of competition. Ages ranged from 18 to 23 years, with a mean age of 20 ± 1.3 years. Athletes were excluded if they were younger than 18 years.

Each athlete was nested in one of the 18 athletic trainers. The number of athletes under the care of an athletic trainer ranged from 7 to 54 (mean: 15.2 ± 10 athletes per athletic trainer).

Instrumentation

The MBTI is a well-known measure of personality based on the four Jungian dichotomies extroversion/ introversion, sensing/intuition, thinking/feeling, and judging/perceiving. This study used Form M,22 the most recent version of the MBTI, which consisted of 14 demographic questions and 93 forced-choice questions to which a respondent chose between two words or two short scenarios. The MBTI classifies a respondent into one of two preference categories for each of the four personality dichotomies. The combination of a respondent's preferences on the four dichotomies gives the MBTI 16 possible personality types. Form M takes approximately 15 to 20 minutes to complete. The MBTI was administered online and scored by the test publisher (Consulting Psychologists Press). The MBTI was administered to all athletic trainers in the sample.

The Patient–Athletic Trainer Trust Instrument (PATI) measures the relative amount of trust a patient (athlete) has in his or her athletic trainer, and it has been validated in the athletic training setting.17 The PATI comprises eight demographic and health-related background questions and 26 Likert-type items to measure trust. The response options for these items range from “never/a few times” to “always” and are scored from 1 to 4, respectively. The PATI is a summative scale; thus, the overall trust score has a possible range of 26 (least amount of trust) to 104 (greatest amount of trust). The instrument takes approximately 10 to 15 minutes to complete. It was administered to all athletes in the sample in person by a member of the research team (KM) via a tablet.

Procedures

Athletic trainers' e-mail addresses were acquired through each university's respective web site. A recruitment e-mail was sent to the athletic trainers, and a follow-up e-mail was sent to those who agreed to participate. The follow-up e-mail included a consent form and instructions for taking the MBTI personality questionnaire online. Each athletic trainer received a $10 incentive following completion of the MBTI.

The primary investigator then visited each participating athletic trainer's athletic training facility to recruit athletes in person. The PATI was administered to each participating athlete in person on his or her consent, so all of the participants were provided the opportunity to ask questions regarding the instrument and the study. Participants completed the instrument in a private room to ensure confidentiality. This study protocol was approved by the institutional review boards of all institutions involved.

Data Analysis

Not all Myers-Briggs personality types were observed in this sample of athletic trainers. Thus, these analyses focused primarily on the dichotomies rather than the types. Analyzing data in terms of the dichotomies is endorsed by the MBTI manual.21,22

There were four separate analyses with one corresponding to each MBTI dichotomy, which were conducted using linear mixed-effects models to accommodate random effects and nesting. Athletes are nested in athletic trainers, and athletic trainers are nested in one of two general personality classes for each dichotomy. Random effects are needed for these results to properly generalize the greater population of athletic trainers. Further, linear mixed-effects models can incorporate heteroskedasticity, which appeared to be a limitation of the data collected for this study. Models were estimated using restricted maximum likelihood with Kenward-Roger adjustment for degrees of freedom (recommended for linear mixed-effects models with unbalanced groups).23 The Šidák procedure was applied when post-hoc analysis was warranted. A nominal significance level of α = .05 was set prior to analysis.

Results

Descriptive Statistics for the MBTI and PATI

There were 8 of 16 possible Myers-Briggs personality types observed in this sample of athletic trainers, but only three of these types were observed for both sexes (Table 2). Although there were 8 personality types not represented, both preference categories from each dichotomy were represented (Table 3).

Frequencies of Athletic Trainers and Nested Athletes by Myers-Briggs Personality Type and Sexa

Table 2:

Frequencies of Athletic Trainers and Nested Athletes by Myers-Briggs Personality Type and Sex

Frequencies of Athletic Trainers (and Nested Athletes) by Dichotomy Preferences and Sexa

Table 3:

Frequencies of Athletic Trainers (and Nested Athletes) by Dichotomy Preferences and Sex

Tables 23 show the number of athletic trainers classified under various categories and the number of athletes nested (eg, treated) in athletic trainers in each category. The tables do not indicate the personality type, dichotomy preferences, or sex of the athletes themselves, but only those characteristics of the respective athletic trainers to whom the athletes are assigned.

Because athletes were nested in athletic trainers, there were multiple PATI trust scores per athletic trainer, so a composite (average) trust score was computed for each athletic trainer. These composite trust scores ranged from 80.9 to 102.9 with an unweighted mean (with respect to athletic trainers) of 98.0 ± 5.2 for the entire sample. The weighted mean was 98.2. A histogram of the composite trust scores is shown in Figure 1.

Histogram of the composite trust scores for the athletic trainers (ATs).

Figure 1.

Histogram of the composite trust scores for the athletic trainers (ATs).

Linear Mixed-Effects Models for the Personality Dichotomies

The following results are from the analyses of the four separate personality dichotomies. Various potential covariates including age of the athletes, pain severity, number of injuries, years of participation in collegiate athletics, and age, sex, and educational level of the athletic trainers were initially used in the models; however, all except sex of the athletic trainer were non-significant in all four models and therefore removed from the analysis. Further, sex of the athletic trainer is a theoretically relevant covariate for trust because psychological and behavioral research acknowledges a general relationship between sex and trustworthiness.18,19,21,22 More germane to the patient–athletic trainer context, the sex of a health care provider has been shown to have an impact on related areas such as a patient's levels of satisfaction with that provider, but not necessarily trust.20 Hence, each dichotomy was crossed with the sex of the athletic trainer to produce four possible combinations (2 × 2 table).

The dichotomy and sex are fixed effects, as is their interaction. The fixed effects were dummy coded, so the results are interpretable as an analysis of variance. As described previously, there are two levels of nesting: each athletic trainer is nested in one of four dichotomy/sex combinations, and each athlete is in turn nested in an athletic trainer. Athletic trainers are treated as a random effect.

These analyses are all based on linear mixed-effects models, so the degrees of freedom reported in the following analyses are not whole numbers because the Kenward-Roger adjustment method is used. Also, each analysis has a table of estimated marginal means (otherwise known as predicted or least-squares means) rather than a conventional contingency table of means. Such estimates are based on a given model, so the overall mean and the marginal means at both levels of the athletic trainer's sex (the fixed factor used in all four models) differ slightly from model to model.

The sensing/intuition dichotomy and sex of the athletic trainer are the two fixed effects in this model. These two factors were not completely crossed because there were no female athletic trainers in the intuition preference category observed in this sample. However, the two main effects can still be tested with such a design if interaction is provisionally assumed to be nonexistent for the fixed factors.26 Consequently, all results from this model, and interpretations thereof, are contingent on the condition that there is no interaction; thus, the results related to the sensing/intuition dichotomy are tentative.

The effect of the sensing/intuition dichotomy on trust was significant (b = −10.107, t [24.4] = −2.834, P = .009), but the effect of sex of the athletic trainer was not (b = 3.031, t [11.6] = 1.603, P = .136). No post-hoc analysis is needed for the significant main effect because there is no interaction and the sensing/intuition dichotomy has only two levels. The sensing preference group had a greater predicted mean trust score than the intuition preference group by a margin of more than 10 points. The estimated marginal means are shown in Table 4. Because there is no interaction term in this model, a marginal mean could be estimated for the empty cell (female athletic trainers with a preference for intuition).

Estimated Mean Trust Scores for Dichotomy Preference by Sex of the Athletic Trainer

Table 4:

Estimated Mean Trust Scores for Dichotomy Preference by Sex of the Athletic Trainer

Thinking/Feeling Dichotomy. The thinking/feeling dichotomy, sex of the athletic trainer, and the interaction of these factors were fixed effects. These two factors were completely crossed. The interaction of the thinking/ feeling dichotomy and sex of the athletic trainer was significant (b = 11.341, t [20.5] = 2.667, P = .015). Neither of the main effects produced a significant difference (thinking/feeling dichotomy: b = 1.258, t [14.7] = 0.582, P = .570; sex of the athletic trainer: b = 3.564, t [11.6] = 1.630, P = .130). The estimated marginal means are shown in Table 4.

The significant interaction warranted a post-hoc analysis of the simple main effects. The analysis revealed that the thinking preference group had a greater mean trust score than the feeling preference group by a margin of 10 points for male athletic trainers (P = .023); however, there was no significant difference between the thinking and feeling preference groups for female athletic trainers (t [−0.582], P = .815).

Extroversion/Introversion Dichotomy. The two levels of the extroversion/introversion dichotomy were crossed with the two levels of sex of the athletic trainers. Both factors and their interactions were treated as fixed effects. The analysis revealed no significant effects on trust for the extroversion/introversion dichotomy (b = −1.719, t [13.3] = 0.539, P = .599), sex of the athletic trainer (b = 1.622, t [14.8] = 0.495, P = .628), or the interaction of those factors (b = 5.365, t [11.7] = 0.819, P = .429). The estimated marginal means of the trust scores are shown in Table 4.

Judging/Perceiving Dichotomy. The two levels of the judging/perceiving dichotomy were crossed with the two levels of sex of the athletic trainers. Both factors and their interaction were treated as fixed effects. The analysis revealed no significant effects on trust for the dichotomy (b = 2.997, t [14.3] = 0.806, P = .433), sex of the athletic trainer (b = 1.428, t [12.3] = 0.252, P = .805), or the interaction of those factors (b = 0.124, t [12.9] = 0.018, P = .986). The estimated marginal means of the trust scores are shown in Table 4.

Discussion

This study examined the relationship between athletic trainer personality, measured by the MBTI, and patient trust. Eight of 16 possible personality types were identified among the athletic trainers sampled. These results are to be expected because personality type is a classification rather than a continuous, manipulated variable. Further analyses reviewed the dichotomies of the personality types because a full comparison of the levels of trust across the complete set of personality types was not possible. Additionally, the data became increasingly sparse with many empty cells when the eight available personality types were crossed with other important categorical covariates (ie, sex of the athletic trainer; Table 2). However, the four separate personality dichotomies are particularly useful for statistical analyses, and the dichotomies are often better for facilitating the interpretation and discussion of the results.18,19

Of the four dichotomous measures, there were significantly higher trust scores among athletes working with female athletic trainers who preferred sensing than male athletic trainers who preferred intuition. All but two of the athletic trainers had the sensing preference in their type. The sensing/intuition dichotomy corresponds to preferences for how information is gathered to make decisions.18,19 When an individual prefers sensing, he or she typically gathers data through seeing, touching, and hearing and commonly uses this information to make decisions based on how the information fits into what he or she knows. In contrast, an individual who prefers intuition prefers ideas and examines the situation by thinking about what is unknown to generate solutions. This individual has a strong connection to a “gut feeling” about what is going on and makes decisions by anticipating what is not obvious. An athletic trainer who prefers gathering data through his or her senses seems to be logical given that there has been a strong push in recent years for the use of evidence–based practice or using objective data to support treatment plans. By using their senses, athletic trainers are gathering as much data as possible and using their clinical judgment to procure a treatment approach, which is consistent with current educational practices.26,27 Patients' higher trust scores seemed to reflect the use of tangible assessment strategies, such as palpation during a physical examination.

The data revealed an even distribution between the personality preferences of thinking and feeling. Individuals who prefer thinking tend to make decisions based on cognitive processes after considering their emotions. On the other hand, individuals who prefer feeling will consider cognitive ideas but base decisions more on emotions.18,19 In addition, individuals with a thinking preference may be more interested in the technical aspects of athletic training (eg, positive special test), whereas those with a feeling preference may be more interested in the interpersonal aspects of athletic training (eg, understanding the patient's role on his or her team). A statistically significant difference was found in trust scores between male athletic trainers who preferred thinking compared to male athletic trainers who preferred feeling. Interestingly, gender differences between men and women related to thinking and feeling are often socially expected. Related to this social expectation, Seegmiller and Epperson28 conducted a study to distinguish thinking and feeling preferences between males and females using the MBTI and found statistically significant results indicating a male preference for thinking over feeling in comparison to females. In addition, Stillwell et al.29 found that a majority of female medical students had a feeling preference compared to their male counterparts, who mostly had a thinking preference.

In contrast to these studies, we did not see a preference of feeling over thinking among the female athletic trainers. Although gender roles and stereotypes are complex concepts, one possible explanation for the difference in the trust scores in this study could be the social stereotypes related to personality preferences based on gender, indicating the desirability among patients for male athletic trainers who possess a thinking personality preference.28 In a separate study, the authors suggested that it is more the ability of clinicians to make quick decisions or use their deductive reasoning skills than a gender difference.30 This would align with athletic training because in emergency situations patients need athletic trainers to make quick and potentially lifesaving decisions.

Extroversion and introversion personality preferences are described as an individual's preference to focus on the “outer world” or the “inner world.”18 More simply, participants tend to fall into the extroversion category when they excel with multiple stimuli at once and introversion participants prefer to focus on more specific tasks. Previous studies examining personality traits in health care professionals found that medical students with a preference for introversion were more likely to choose primary care,29 and attending physicians who scored higher in extroversion had substantially higher teaching evaluations.30 However, neither study evaluated how personality traits affected patient trust. Specifically related to athletic training, an extrovert athletic trainer may prefer the opportunity to work with a wide variety of patients, whereas an introvert athletic trainer may prefer to work one on one over a longer period of time. Understanding the intricacies of both the athletic trainer and the patient could help facilitate a smoother personal connection. For example, an extrovert athletic trainer may establish a personal connection more quickly, whereas an introvert athletic trainer may take longer, but the connection is likely to be deeper. Both of these skills sets are important when working with patients. Because both extrovert and introvert athletic trainers have strengths when establishing trust, it is not surprising that the current study did not see a difference between the groups.

Finally, the dichotomy of perceiving and judging corresponds to an individual's preference for a flexible and spontaneous (perceiving) or a structured and planned (judging) work environment. These preferences pertain to being flexible with the needs of the patient and providing structure at the same time. The even distribution of perceiving and judging personality preferences and lack of statistical significance reflects the necessity in athletic training to prepare (judging) for the unexpected (perceiving).18 For example, an athletic trainer must be prepared for emergent situations (judging); at the same time, he or she must exercise spontaneity to manage a situation as it arises (perceiving). Additionally, when rehabilitating an injured athlete, creating goals can maintain the athlete's motivation and promote a positive environment (judging). However, the athletic trainer's ability to adjust goals and approach work in a more flexible manner is also important (perceiving). Having a balance between these skills will benefit the athletic trainer. Moreover, pairing an athletic trainer who has a preference for perceiving with an athletic trainer who has a preference for judging could provide a good, balanced patient environment. For example, an athletic trainer who has a preference for perceiving will not be startled by the spontaneity of an emergent situation, whereas the athletic trainer who has a preference for judging has considered and thought out contingencies and has all of the necessary equipment on hand.

Limitations

As with all studies, limitations are inevitable. The smaller sample size of athletic trainers necessitated a nested design and makes generalization more difficult. Additionally, we did not set parameters on the personality preference of the patients selected under each athletic trainer. It is unclear how other variables (eg, patient age, gender, personality type, or length of time spent with the specific athletic trainer) would affect the outcome of the current study. Future studies should consider these variables with a larger sample size.

Implications for Clinical Practice

The athletic trainer's personality appears to positively affect the trust that athletes have in their athletic trainer, specifically for female athletic trainers who prefer the sensing personality type and male athletic trainers who prefer the thinking personality type. There is a dearth of studies examining the relationship between personality traits, as measured by the MBTI, and trust; therefore, additional research is needed to evaluate personality and trust in a larger, more diverse sample of athletic trainers and patients. Other characteristics such as communication style, demeanor, confidence, and competence should be investigated with regard to the promotion of trust in the patient–provider relationship.

References

  1. Lee YY, Lin JL. How much does trust really matter: a study of the longitudinal effects of trust and decision-making preferences on diabetic patient outcomes. Patient Educ Couns. 2011;85:406–412. doi:10.1016/j.pec.2010.12.005 [CrossRef]
  2. Safran DG, Kosinski M, Tarlov AR, et al. The primary care assessment survey: tests of data quality and measurement performance. Med Care. 1998;36:728–739. doi:10.1097/00005650-199805000-00012 [CrossRef]
  3. Pearson SD, Raeke LH. Patients' trust in physicians: many theories, few measures, and little data. J Gen Intern Med. 2000;15:509–513. doi:10.1046/j.1525-1497.2000.11002.x [CrossRef]
  4. Kraetschmer N, Sharpe N, Urowitz S, Deber RB. How does trust affect patient preferences for participation in decision-making?Health Expect. 2004;7:317–326. doi:10.1111/j.1369-7625.2004.00296.x [CrossRef]
  5. Bonds DE, Camacho F, Bell RA, Duren-Winfield VT, Anderson RT, Goff DC. The association of patient trust and self-care among patients with diabetes mellitus. BMC Fam Pract. 2004;5:26. doi:10.1186/1471-2296-5-26 [CrossRef]
  6. Jones DE, Carson KA, Bleich SN, Cooper LA. Patient trust in physicians and adoption of lifestyle behaviors to control high blood pressure. Patient Educ Couns. 2012;89:57–62. doi:10.1016/j.pec.2012.06.003 [CrossRef]
  7. Elder K, Ramamonjiarivelo Z, Wiltshire J, et al. Trust, medication adherence, and hypertension control in Southern African American men. Am J Public Health. 2012;102:2242–2245. doi:10.2105/AJPH.2012.300777 [CrossRef]
  8. Blackstock OJ, Addison DN, Brennan JS, Alao OA. Trust in primary care providers and antiretroviral adherence in an urban HIV clinic. J Health Care Poor Underserved. 2012;23:88–98. doi:10.1353/hpu.2012.0006 [CrossRef]
  9. Mancuso JM. The impact of health literacy and patient trust on glycemic control. West J Nurs Res. 2009;31:1086–1087. doi:10.1177/0193945909342548 [CrossRef]
  10. Whetten K, Leserman J, Whetten R, et al. Exploring lack of trust in care providers and the government as a barrier to health service use. Am J Public Health. 2006;96:716–721. doi:10.2105/AJPH.2005.063255 [CrossRef]
  11. Musa D, Schulz R, Harris R, Silverman M, Thomas SB. Trust in the health care system and the use of preventive health services by older black and white adults. Am J Public Health. 2009;99:1293–1299. doi:10.2105/AJPH.2007.123927 [CrossRef]
  12. O'Malley AS, Sheppard VB, Schwartz M, Mandelblatt J. The role of trust in use of preventive services among low-income African-American women. Prev Med. 2004;38:777–785. doi:10.1016/j.ypmed.2004.01.018 [CrossRef]
  13. Murray B, McCrone S. An integrative review of promoting trust in the patient-primary care provider relationship. J Adv Nurs. 2015;71:3–23. doi:10.1111/jan.12502 [CrossRef]
  14. Rolfe A, Cash-Gibson L, Car J, Sheikh A, McKinstry B. Interventions for improving patients' trust in doctors and groups of doctors. Cochrane Database Syst Rev. 2014;3:CD004134.
  15. Thom DHStanford Trust Study Physicians. Physician behaviors that predict patient trust. J Fam Pract. 2001;50:323–328.
  16. Hall MA, Zheng B, Dugan E, et al. Measuring patients' trust in their primary care providers. Med Care Res Rev. 2002;59:293–318. doi:10.1177/1077558702059003004 [CrossRef]
  17. David SL. Development and validation of the patient–AT trust instrument [dissertation]. Athens: Ohio University; 2013.
  18. Buchan NR, Croson RTA, Solnick S. Trust and gender: an examination of behavior and beliefs in the investment game. Journal of Economic Behavior and Organization. 2008;68:466–476. doi:10.1016/j.jebo.2007.10.006 [CrossRef]
  19. Rau HADsseldorf Institute for Competition Economics (DICE). Trust and trustworthiness: a survey of gender differences. In: McGeown Sarah, ed. Psychology of Gender Differences. New York: Nova Science Publishers; 2012:131–143.
  20. Derose KP, Hays RD, McCaffrey DF, Baker DW. Does physician gender affect satisfaction of men and women visiting the emergency department?J Gen Intern Med. 2001;16:218–226. doi:10.1046/j.1525-1497.2001.016004218.x [CrossRef]
  21. The Myers Briggs Foundation. MBTI Basics. http://www.myers-briggs.org/my-mbti-personality-type/mbti-basics/home.htm?bhcp=1.
  22. Myers IB, McCaulley MH, Quenk NL, Hammer AL. MBTI Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator, 3rd ed. Palo Alto, CA: Consulting Psychologists Press; 1998.
  23. StataCorp. Stata Multilevel Mixed-Effects Reference Manual. College Station, TX: Stata Press.
  24. Kutner MH, Nachtsheim CJ, Neter J, Li W. Applied Linear Statistical Models, 5th ed. New York: McGraw-Hill; 2005.
  25. Scharlemann JPW, Eckel CC, Kacelnik A, Wilson RK. The value of a smile: game theory with a human face. Journal of Economic Psychology. 2001;22:617–640. doi:10.1016/S0167-4870(01)00059-9 [CrossRef]
  26. Steves R, Hootman JM. Evidence based medicine: what is it and how does it apply to athletic training?J Athl Train. 2004;39:83–87.
  27. Commission on Accreditation of Athletic Training Education. Standards for the accreditation of professional athletic training programs. Author. https://caate.net/wp-content/uploads/2015/12/2012-Professional-Standards.pdf.
  28. Seegmiller RA, Epperson DL. Distinguishing thinking-feeling preferences through the content analysis of natural language. J Pers Assess. 1987;51:42–52. doi:10.1207/s15327752jpa5101_4 [CrossRef]
  29. Stilwell NA, Wallick MM, Thal SE, Burleson JA. Meyers-Briggs type and medical specialty choice: a new look at an old question. Teach Learn Med. 2000;12:14–20. doi:10.1207/S15328015TLM1201_3 [CrossRef]
  30. Scheepers RA, Lombarts KM, van Aken MA, Heineman MJ, Arah OA. Personality traits affect teaching performance of attending physicians: results of a multi-center observational study. PLoS ONE. 2014;9:e98107. doi:10.1371/journal.pone.0098107 [CrossRef]

Frequencies of Athletes by Primary Sport and Sex

Sport Sex of Athletic Trainer Number of Female Athletes Number of Male Athletes Total Athletes
Football Male 0 83 83
Track and field Female 19 19 38
Basketball Female 12 15 27
Soccer Female 25 1 26
Wrestling Male 0 26 26
Softball Female 16 0 16
Swimming Female 16 0 16
Ice hockey Male 15 0 15
Volleyball Female 14 0 14
Baseball Male 0 12 12
Total number of athletes 117 156 273

Frequencies of Athletic Trainers and Nested Athletes by Myers-Briggs Personality Type and Sexa

Personality Type Sex Total

Female Male
Extroversion, sensing, thinking, judging 4 (50) 1 (15) 5 (65)
Extroversion, sensing, thinking, perceiving 1 (11) 2 (26) 3 (37)
Extroversion, sensing, feeling, judging 2 (27) 2 (27)
Extroversion, intuition, feeling, perceiving 2 (32) 2 (32)
Introversion, sensing, thinking, judging 1 (10) 1 (10)
Introversion, sensing, thinking, perceiving 1 (12) 1 (54) 2 (66)
Introversion, sensing, feeling, judging 2 (24) 2 (24)
Introversion, sensing, feeling, perceiving 1 (12) 1 (12)
Total 12 (146) 6 (127) 18 (273)

Frequencies of Athletic Trainers (and Nested Athletes) by Dichotomy Preferences and Sexa

Personality Dichotomy Preferences Sex Total

Female Male
Extroversion/introversion Extroversion 7 (88) 5 (73) 12 (161)
Introversion 5 (58) 1 (54) 6 (112)
Sensing/intuition Sensing 12 (146) 4 (95) 16 (241)
Intuition 2 (32) 2 (32)
Thinking/feeling Thinking 7 (83) 4 (95) 11 (178)
Feeling 5 (63) 2 (32) 7 (95)
Judging/perceiving Judging 9 (111) 1 (15) 10 (126)
Perceiving 3 (35) 5 (112) 8 (147)
Total 12 (146) 6 (127) 18 (273)

Estimated Mean Trust Scores for Dichotomy Preference by Sex of the Athletic Trainer

Dichotomy Preference Female Male Total
Extroversion/introversion
  Extroversion 98.7 97.1 98.0
  Introversion 97.0 100.8 98.8
  Total 98.0 98.6 98.3
Sensing/intuition
  Sensing 98.0 101.1 99.4
  Intuition 87.9 91.0 89.3
  Total 96.8 99.9 98.3
Thinking/feeling
  Thinking 97.5 101.1 99.2
  Feeling 98.8 91.0 95.1
  Total 97.9 97.5 98.3
Judging/perceiving
  Judging 98.8 100.2 99.4
  Perceiving 95.8 97.3 96.5
  Total 97.2 98.7 97.9
Authors

From the Department of Health, Nutrition, and Exercise Science (SLD), the Department of Public Health (ML), and the School of Education (BH), North Dakota State University, Fargo, North Dakota; and OSR Physical Therapy, Minnetonka, Minnesota (KM).

The authors have no financial or proprietary interest in the materials presented herein.

Correspondence: Shannon L. David, PhD, AT, PES, Department of Health, Nutrition, and Exercise Science, North Dakota State University, P.O. Box 6050, Department 2620, Fargo, ND 58108-6050. E-mail: Shannon.david@ndsu.edu

Received: August 07, 2017
Accepted: February 16, 2018
Posted Online: November 27, 2018

10.3928/19425864-20181128-01

Sign up to receive

Journal E-contents