Predictors of Wellness Behaviors in U.S. Army Physicians

Predictors of Wellness Behaviors in U.S. Army Physicians Abstract Introduction In 2013, the U.S. Army Surgeon General implemented the Performance Triad (P3), an educational initiative to improve health-related behaviors of soldiers throughout the U.S. Army. The components of P3 are Sleep, Activity, and Nutrition with tenet behaviors for each component. This study reports the results of the 2015 U.S. Army Medical Corps survey regarding physician knowledge and adherence to the tenet behaviors of P3. Methods In 2015, an anonymous survey was sent to all active duty U.S. Army physicians to assess demographic information, work hours, and knowledge of and adherence to P3. The survey assessed the tenets of P3 with questions about the following topics: obtaining 8 h of sleep per day; performing at least 2 d of resistance training and 1 day of agility training per week; re-fueling 30–60 min after exercise; incorporating at least 150 min of moderate and 75 min of vigorous aerobic exercise per week; going caffeine free 6 h before bedtime; eating at least 8 servings of fruits and vegetables per day; and getting 15,000 steps per day. For each question, there were four response options which ranged from “Always” to “Never.” A positive response to the questionnaire was defined as answering frequently or always. The responses were analyzed by comparison of several physician categories utilizing descriptive statistics and multivariable analysis. Results Surveys were completed by 1,003 of approximately 4,500 U.S. Army physicians. 79.1% of the respondents were male. Staff physicians made up 834 (83.6%) of the respondents compared with 164 (16.4%) physicians in training. Overall 25% of respondents were adherent to the sleep tenet, 45% to the exercise tenet, and 38% to the nutrition tenet. Reported work hours were significantly higher in physicians in training compared with staff physicians (p < 0.001). About 28.4% of staff reported a positive response to obtaining at least 8 h of sleep per night, compared with 12.7% of residents/fellows. In multivariable analyses, better sleep was associated with being a staff physician [odds ratio 2.4 (95% confidence interval 1.40–4.13)], working fewer hours per week [1.75 (1.37–2.25)], and belief in supervisor adherence to P3 [2.04 (1.59–2.56)]. Increased exercise was associated with male gender [2.09 (1.45–3.02)], being a staff physician [1.63 (1.09–2.43)], and belief in supervisor adherence to P3 [1.43 (1.18–1.75)]. Positive response to the nutrition tenet was associated with belief in supervisor adherence to P3 [1.23 (1.01–1.49)]. Conclusion Overall, U.S. Army physicians are most adherent to the exercise tenet and least adherent to the sleep tenet of P3; this is consistent with the military culture. Work hours seem to affect wellness behaviors. Specifically, physicians who work fewer hours are more likely to report obtaining 8 h of sleep per day and exercise on a regular basis. Importantly, belief in supervisor adherence to P3 was associated with better adherence to P3, suggesting that physician leadership has a positive effect on wellness behaviors. This suggests a role for similar wellness programs in civilian healthcare institutions. Future research should also include changes in health system policies to motivate physician wellness behaviors. INTRODUCTION Physician wellness is strongly linked to compassionate and appropriate care for patients. However, many physicians experience burnout, which degrades physician wellness and has a negative impact on patient care.1,2 Physician burnout has been defined as a triad of emotional exhaustion, depersonalization, and low sense of personal accomplishment.1 Physicians experience higher rates of burnout than the general population beginning in medical school and rates increase among residents and mid-career physicians. A 2011 survey of U.S. physicians noted 45% of respondents reported burnout, and burnout was more common among physicians compared with other professions.3 This trend continues to increase, as noted by a follow on survey in 2014 showing the burnout response rate had increased to 54%.4 These findings are significant for several reasons. Personally, it may contribute to mental health problems, such as depression and anxiety. Although extreme, physician burnout can eventually lead to suicidal ideations. Within the past few years, reports of physician suicides rates are over 400 annually.5 Professionally, it has been well documented that physician burnout impacts quality of medical care provided.6–8 There are many publications regarding physician burnout, with few that address solutions to address burnout. More recent publications are now addressing physician wellness as a means to combat burnout.9–12 Previous studies have demonstrated factors such as maintenance of work-life balance, social and family support, adequate rest, and regular physical activity are correlated with career satisfaction, improved sense of well-being, increased empathy, and decreased burnout.9–12 Physicians who engage in health promoting behaviors are also more likely to promote these behaviors to their patients and are also perceived as more credible and motivating proponents of these interventions to their patients.13–15 There are few studies that assess personal wellness habits of physicians in the USA, although several medical resident surveys have been performed.16,17 One study assessed exercise habits of resident and attending physicians.18 These limited studies suggest many physicians do not engage in health promoting behaviors. Many barriers to engaging in healthy behavior exist among physicians, including time pressures and a culture of altruistic and self-sacrificing behavior that encourages physicians to neglect self-care. Many health systems have implemented programs to encourage physician wellness and combat burnout through education programs and changes to the work environment with variable success.9,19–21 In 2013, the U.S. Army Surgeon General implemented the Performance Triad (P3), a multimodal educational initiative to encourage U.S. Army soldier engagement in wellness behaviors including obtaining adequate sleep, regular physical activity, and proper nutrition.22 Evaluations of the sleep and nutrition components of the P3 note U.S. Army soldiers with better nutrition and sleep habits performed better on the Army Physical Fitness Test.23,24 These wellness surveys of U.S. Army soldiers also showed better sleep and nutrition were associated with higher fitness scores in emotional, social, family and spiritual categories. However, adherence to the P3 amongst U.S. Army physicians is unknown. This study explored physician engagement in the P3 program and attempted to identify factors that enhanced or hindered physician engagement. METHODS Survey In 2015, the U.S. Army Medical Corps sent an anonymous survey to all active duty Army physicians. Surveys were completed by 1,009 U.S. Army physicians, with a response rate of 22.4%. The survey assessed their military duties, deployment history, work satisfaction in the Military Healthcare System, and knowledge of and adherence to the P3. Demographic information collected included age, gender, hours worked per week (including hours of home call), provider medical specialty, and medical training status (i.e., staff versus resident or fellow). Performance Triad Assessment Personal involvement in P3 activities was assessed through four questions: “Do you get 8 h of quality sleep per 24-h period?”, “Do you include at least 2 d or more resistance training per week and 1 day agility training?”, “Do you incorporate at least 150 min of moderate and 75 min of vigorous intensity aerobic exercise per week?”, and “Do you eat at least 8 servings of fruits and vegetables per day?”. Responses to these questions were assessed using a 4-point Likert scale ranging from “Always, Frequently, Occasionally, Never”. The subject responses to the exercise and resistance training questions were correlated (correlation coefficient 0.667, p < 0.001) so these two items were combined into a single exercise item with a range of 1 (always engages in both exercise types) to 4 (never engages in either exercise type) (Cronbach’s α = 0.800). The three P3 measures were significantly correlated with each other: exercise/sleep (0.128, p < 0.001), exercise/diet (0.309, p < 0.001), and diet/sleep (0.178, p < 0.001). However, the level of correlation between the measures was not high and combining these measure together did not yield a reliable scale (Cronbach’s α = 0.436). Therefore, provider adherence to each of these activities was measured independently. A provider’s opinion of the importance of promotion of the P3 activities as a medical professional was measured with a single question, “What is your opinion of the Performance Triad as a core mission and emphasis of the Army Medical Department?”, with a 5-point Likert response scale ranging from “Very Positive” to “Very Negative”. The survey also measured a provider’s impression of his or her supervisor’s involvement in P3 activities with a single question, “Do you believe your first and second line supervisor adhere to all the recommendations of the performance triad?”, with a 4-point Likert response scale ranging from “Always” to “Never”. Statistical Analysis Simple descriptive statistics was used to describe the demographics of the sample population, provider involvement in P3 activities, provider belief in the importance of P3 promotion as a medical provider, and perception of supervisor involvement in P3 activities. The bivariable relationship of personal involvement in P3 activities with the demographic variables, provider opinions of P3 promotion, and perception of supervisor’s personal involvement in P3 activities was assessed using the univariate general linear model procedure in SPSS. Variables that had a significant (p < 0.05) relationship with the outcome variable in bivariable analysis were entered into a multivariable Univariate General Linear Model to assess the independent association between these factors and the outcome measures. The univariate general linear model procedure calculated an F-statistic for each predictor variable. This statistic assessed the change in model fit between the model with and without the predictor variable. If p < 0.05 for the F-statistic then you can conclude the predictor variable has a significant relationship with the dependent variable. Statistical analyses were conducted with SPSS software (version 22; IBM Corporation, Armonk, NY, USA). This study was reviewed and approved by the Institutional Review Board of the San Antonio Military Medical Center. RESULTS The majority of the survey respondents were male (79.1%). Staff physicians made up 834 (84%) of the respondents compared with 164 (16%) physicians in training. Over 80% of the respondents were between the ages of 31- and 50-yr-old. Non-surgical specialties represented 77% of the respondents. Almost 90% of the respondents worked between 41 and 80 h per week. Only 41% of physicians had a positive opinion of promoting exercise, sleep, diet as a core mission of the Army Medical Department (Table I). Overall, 50.6% of physicians reported frequently or always engaging in aerobic exercise, 44.3% of physicians reported frequently or always engaging in resistance/agility exercise, 25.6% reported frequently or always getting 8 h a of sleep a night, and 39.1% reported frequently or always eating 8 servings of fruits and vegetables a day. Only 34.6% of physicians thought their supervisors were frequently or always engaging in P3 activities (Table II). In bivariable analyses, higher personal engagement in exercise was associated with male gender, being a staff physician rather than a resident or fellow, having a higher opinion of P3 promotion as a core mission of the Army Medical Department, and perceiving higher engagement in P3 activities by supervisors. Physicians were more likely to report getting 8 h of sleep a night if they were not in a graduate medical education program, not a surgeon, worked fewer hours a week, had a higher opinion of P3 promotion, and perceived their supervisors were engaging in P3 activities. Only a positive opinion of P3 promotion and perceiving supervisor engagement in P3 activities was associated with higher fruit and vegetable consumption (Table III). In multivariable analyses, male physicians, staff physicians, and physicians who perceive that their supervisors engage in P3 activities were more likely to engage in regular exercise. Reporting a higher frequency of obtaining 8 h of sleep a night was associated with being a staff physician, working in a non-surgical specialty, working fewer hours a week, and believing that your supervisors engaged in the p3 activities. More frequent fruit and vegetable consumption was associated with having a more positive opinion of P3 promotion as a physician and perception of supervisor engagement in P3 activities (Table IV, Fig. 1). Table I. US Army Physician Survey Respondents (n = 1,009) Gender n % Male 793 79.1 Female 210 20.9 Age group  21–30 93 9.3  31–40 475 47.5  41–50 327 32.7  51–60 94 9.4  60+ 11 1.1 Training status  Staff 834 83.6  Residents/fellows 164 16.4 Specialty type  Non-surgical 770 76.8  Surgical 233 23.2 Hours worked per week (including home call)  20–40 26 2.6  41–60 469 46.8  61–80 419 41.8  81+ 88 8.8 What is your opinion of the performance triad as a core mission and emphasis of the army medical department?  Very positive 90 9.3  Positive 308 31.8  Neutral 380 39.2  Negative 124 12.8  Very negative 68 7.0 Gender n % Male 793 79.1 Female 210 20.9 Age group  21–30 93 9.3  31–40 475 47.5  41–50 327 32.7  51–60 94 9.4  60+ 11 1.1 Training status  Staff 834 83.6  Residents/fellows 164 16.4 Specialty type  Non-surgical 770 76.8  Surgical 233 23.2 Hours worked per week (including home call)  20–40 26 2.6  41–60 469 46.8  61–80 419 41.8  81+ 88 8.8 What is your opinion of the performance triad as a core mission and emphasis of the army medical department?  Very positive 90 9.3  Positive 308 31.8  Neutral 380 39.2  Negative 124 12.8  Very negative 68 7.0 Table I. US Army Physician Survey Respondents (n = 1,009) Gender n % Male 793 79.1 Female 210 20.9 Age group  21–30 93 9.3  31–40 475 47.5  41–50 327 32.7  51–60 94 9.4  60+ 11 1.1 Training status  Staff 834 83.6  Residents/fellows 164 16.4 Specialty type  Non-surgical 770 76.8  Surgical 233 23.2 Hours worked per week (including home call)  20–40 26 2.6  41–60 469 46.8  61–80 419 41.8  81+ 88 8.8 What is your opinion of the performance triad as a core mission and emphasis of the army medical department?  Very positive 90 9.3  Positive 308 31.8  Neutral 380 39.2  Negative 124 12.8  Very negative 68 7.0 Gender n % Male 793 79.1 Female 210 20.9 Age group  21–30 93 9.3  31–40 475 47.5  41–50 327 32.7  51–60 94 9.4  60+ 11 1.1 Training status  Staff 834 83.6  Residents/fellows 164 16.4 Specialty type  Non-surgical 770 76.8  Surgical 233 23.2 Hours worked per week (including home call)  20–40 26 2.6  41–60 469 46.8  61–80 419 41.8  81+ 88 8.8 What is your opinion of the performance triad as a core mission and emphasis of the army medical department?  Very positive 90 9.3  Positive 308 31.8  Neutral 380 39.2  Negative 124 12.8  Very negative 68 7.0 Table II. Self-Reported Frequency of Triad Behaviors and Perceived Supervisor Behavior Among U.S. Army Physicians Reported Frequency Do you incorporate at least 150 min of moderate and 75 min of vigorous intensity aerobic exercise per week? Do you include at least 2 d or more resistance training per week and 1 d agility training? Combined Aerobic and Resistance Exercise Variable Do you get 8 h of quality sleep per 24-h period? Do you eat at least 8 servings of fruits and vegetables per day? Do you believe your supervisors adhere to all of the Performance Triad recommendations? n % n % n % n % n % n % Always 219 22.4 181 18.5 139 14.3 22 2.2 76 7.8 41 4.3 69 7.1 Frequently 276 28.2 252 25.8 192 19.7 230 23.4 305 31.3 289 30.3 140 14.4 Occasionally 350 35.8 345 35.3 234 24.0 513 52.2 442 45.3 482 50.5 106 10.9 Never 134 13.7 200 20.4 95 9.7 217 22.1 152 15.6 142 14.9 Reported Frequency Do you incorporate at least 150 min of moderate and 75 min of vigorous intensity aerobic exercise per week? Do you include at least 2 d or more resistance training per week and 1 d agility training? Combined Aerobic and Resistance Exercise Variable Do you get 8 h of quality sleep per 24-h period? Do you eat at least 8 servings of fruits and vegetables per day? Do you believe your supervisors adhere to all of the Performance Triad recommendations? n % n % n % n % n % n % Always 219 22.4 181 18.5 139 14.3 22 2.2 76 7.8 41 4.3 69 7.1 Frequently 276 28.2 252 25.8 192 19.7 230 23.4 305 31.3 289 30.3 140 14.4 Occasionally 350 35.8 345 35.3 234 24.0 513 52.2 442 45.3 482 50.5 106 10.9 Never 134 13.7 200 20.4 95 9.7 217 22.1 152 15.6 142 14.9 Table II. Self-Reported Frequency of Triad Behaviors and Perceived Supervisor Behavior Among U.S. Army Physicians Reported Frequency Do you incorporate at least 150 min of moderate and 75 min of vigorous intensity aerobic exercise per week? Do you include at least 2 d or more resistance training per week and 1 d agility training? Combined Aerobic and Resistance Exercise Variable Do you get 8 h of quality sleep per 24-h period? Do you eat at least 8 servings of fruits and vegetables per day? Do you believe your supervisors adhere to all of the Performance Triad recommendations? n % n % n % n % n % n % Always 219 22.4 181 18.5 139 14.3 22 2.2 76 7.8 41 4.3 69 7.1 Frequently 276 28.2 252 25.8 192 19.7 230 23.4 305 31.3 289 30.3 140 14.4 Occasionally 350 35.8 345 35.3 234 24.0 513 52.2 442 45.3 482 50.5 106 10.9 Never 134 13.7 200 20.4 95 9.7 217 22.1 152 15.6 142 14.9 Reported Frequency Do you incorporate at least 150 min of moderate and 75 min of vigorous intensity aerobic exercise per week? Do you include at least 2 d or more resistance training per week and 1 d agility training? Combined Aerobic and Resistance Exercise Variable Do you get 8 h of quality sleep per 24-h period? Do you eat at least 8 servings of fruits and vegetables per day? Do you believe your supervisors adhere to all of the Performance Triad recommendations? n % n % n % n % n % n % Always 219 22.4 181 18.5 139 14.3 22 2.2 76 7.8 41 4.3 69 7.1 Frequently 276 28.2 252 25.8 192 19.7 230 23.4 305 31.3 289 30.3 140 14.4 Occasionally 350 35.8 345 35.3 234 24.0 513 52.2 442 45.3 482 50.5 106 10.9 Never 134 13.7 200 20.4 95 9.7 217 22.1 152 15.6 142 14.9 Table III. Bivariable Analysis – Association Between Demographic Factors and Triad Behaviors Among U.S. Army Physicians Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Mean score (95% CI) Mean score (95% CI) Mean score (95% CI) Gender  Male 2.43 (2.37–2.50) p < 0.001 2.95 (2.89–3.00) p = 0.553 2.67 (2.61–2.73) p = 0.332  Female 2.72 (2.59–2.84) 2.91 (2.81–3.01) 2.74 (2.62–2.85) Age group  21–30 2.59 (2.40–2.78) p = 0.525 3.08 (2.93–3.23) p = 0.238 2.85 (2.68–3.03) p = 0.205  31–40 2.52 (2.44–2.61) 2.90 (2.83–2.97) 2.68 (2.61–2.76)  41–50 2.45 (2.35–2.55) 2.94 (2.86–3.03) 2.68 (2.59–2.77)  51–60 2.43 (2.24–2.62) 3.01 (2.86–3.16) 2.55 (2.39–2.72)  60+ 2.32 (1.78–2.86) 2.91 (2.47–3.35) 2.64 (2.15–3.13) Training status  Staff 2.47 (2.40–2.53) p = 0.044 2.91 (2.86–2.96) p = 0.006 2.68 (2.62–2.73) p = 0.191  Residents 2.63 (2.48–2.77) 3.09 (2.97–3.20) 2.77 (2.64–2.90) Specialty type  Non-surgical 2.49 (2.42–2.56) p = 0.809 2.90 (2.85–2.96) p = 0.003 2.66 (2.60–2.72) p = 0.154  Surgical 2.51 (2.39–2.63) 3.07 (2.98–3.17) 2.75 (2.64–2.86) Hours worked per week (including home call)  20–40 2.38 (2.02–2.74) p = 0.309 2.40 (2.12–2.68) p < 0.001 2.40 (2.16–2.81) p = 0.384  41–60 2.44 (2.35–2.52) 2.81 (2.74–2.87) 2.67 (2.59–2.74)  61–80 2.55 (2.46–2.64) 3.07 (3.00–3.14) 2.70 (2.62–2.77)  81+ 2.52 (2.33–2.72) 3.21 (3.06–3.37) 2.61 (2.61–2.96) Personal opinion of the performance triad  Very positive 2.30 (2.11–2.49) p < 0.001 2.73 (2.58–2.89) p = 0.022 2.43 (2.26–2.60) p < 0.001  Positive 2.42 (2.32–2.52) 2.89 (2.81–2.97) 2.65 (2.56–2.74)  Neutral 2.47 (2.38–2.56) 2.95 (2.87–3.02) 2.69 (2.60–2.77)  Negative 2.69 (2.53–2.85) 3.12 (2.99–3.25) 2.74 (2.59–2.88)  Very negative 2.73 (2.51–2.94) 3.15 (2.97–3.32) 3.02 (2.82–3.21) Frequency of supervisor adherence to triad recommendations  Always 2.37 (2.09–2.64) p < 0.001 2.50 (2.28–2.72) p < 0.001 2.43 (2.17–2.68) p < 0.001  Frequently 2.31 (2.20–2.41) 2.73 (2.65–2.82) 2.59 (2.50–2.69)  Occasionally 2.49 (2.41–2.57) 3.01 (2.95–3.08) 2.67 (2.60–2.74)  Never 2.90 (2.75–3.04) 3.30 (3.18–3.41) 2.99 (2.85–3.12) Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Mean score (95% CI) Mean score (95% CI) Mean score (95% CI) Gender  Male 2.43 (2.37–2.50) p < 0.001 2.95 (2.89–3.00) p = 0.553 2.67 (2.61–2.73) p = 0.332  Female 2.72 (2.59–2.84) 2.91 (2.81–3.01) 2.74 (2.62–2.85) Age group  21–30 2.59 (2.40–2.78) p = 0.525 3.08 (2.93–3.23) p = 0.238 2.85 (2.68–3.03) p = 0.205  31–40 2.52 (2.44–2.61) 2.90 (2.83–2.97) 2.68 (2.61–2.76)  41–50 2.45 (2.35–2.55) 2.94 (2.86–3.03) 2.68 (2.59–2.77)  51–60 2.43 (2.24–2.62) 3.01 (2.86–3.16) 2.55 (2.39–2.72)  60+ 2.32 (1.78–2.86) 2.91 (2.47–3.35) 2.64 (2.15–3.13) Training status  Staff 2.47 (2.40–2.53) p = 0.044 2.91 (2.86–2.96) p = 0.006 2.68 (2.62–2.73) p = 0.191  Residents 2.63 (2.48–2.77) 3.09 (2.97–3.20) 2.77 (2.64–2.90) Specialty type  Non-surgical 2.49 (2.42–2.56) p = 0.809 2.90 (2.85–2.96) p = 0.003 2.66 (2.60–2.72) p = 0.154  Surgical 2.51 (2.39–2.63) 3.07 (2.98–3.17) 2.75 (2.64–2.86) Hours worked per week (including home call)  20–40 2.38 (2.02–2.74) p = 0.309 2.40 (2.12–2.68) p < 0.001 2.40 (2.16–2.81) p = 0.384  41–60 2.44 (2.35–2.52) 2.81 (2.74–2.87) 2.67 (2.59–2.74)  61–80 2.55 (2.46–2.64) 3.07 (3.00–3.14) 2.70 (2.62–2.77)  81+ 2.52 (2.33–2.72) 3.21 (3.06–3.37) 2.61 (2.61–2.96) Personal opinion of the performance triad  Very positive 2.30 (2.11–2.49) p < 0.001 2.73 (2.58–2.89) p = 0.022 2.43 (2.26–2.60) p < 0.001  Positive 2.42 (2.32–2.52) 2.89 (2.81–2.97) 2.65 (2.56–2.74)  Neutral 2.47 (2.38–2.56) 2.95 (2.87–3.02) 2.69 (2.60–2.77)  Negative 2.69 (2.53–2.85) 3.12 (2.99–3.25) 2.74 (2.59–2.88)  Very negative 2.73 (2.51–2.94) 3.15 (2.97–3.32) 3.02 (2.82–3.21) Frequency of supervisor adherence to triad recommendations  Always 2.37 (2.09–2.64) p < 0.001 2.50 (2.28–2.72) p < 0.001 2.43 (2.17–2.68) p < 0.001  Frequently 2.31 (2.20–2.41) 2.73 (2.65–2.82) 2.59 (2.50–2.69)  Occasionally 2.49 (2.41–2.57) 3.01 (2.95–3.08) 2.67 (2.60–2.74)  Never 2.90 (2.75–3.04) 3.30 (3.18–3.41) 2.99 (2.85–3.12) Significant relationships (p < 0.05) based on the based on the GLM F-test statistic for goodness of fit are marked in bold print. Table III. Bivariable Analysis – Association Between Demographic Factors and Triad Behaviors Among U.S. Army Physicians Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Mean score (95% CI) Mean score (95% CI) Mean score (95% CI) Gender  Male 2.43 (2.37–2.50) p < 0.001 2.95 (2.89–3.00) p = 0.553 2.67 (2.61–2.73) p = 0.332  Female 2.72 (2.59–2.84) 2.91 (2.81–3.01) 2.74 (2.62–2.85) Age group  21–30 2.59 (2.40–2.78) p = 0.525 3.08 (2.93–3.23) p = 0.238 2.85 (2.68–3.03) p = 0.205  31–40 2.52 (2.44–2.61) 2.90 (2.83–2.97) 2.68 (2.61–2.76)  41–50 2.45 (2.35–2.55) 2.94 (2.86–3.03) 2.68 (2.59–2.77)  51–60 2.43 (2.24–2.62) 3.01 (2.86–3.16) 2.55 (2.39–2.72)  60+ 2.32 (1.78–2.86) 2.91 (2.47–3.35) 2.64 (2.15–3.13) Training status  Staff 2.47 (2.40–2.53) p = 0.044 2.91 (2.86–2.96) p = 0.006 2.68 (2.62–2.73) p = 0.191  Residents 2.63 (2.48–2.77) 3.09 (2.97–3.20) 2.77 (2.64–2.90) Specialty type  Non-surgical 2.49 (2.42–2.56) p = 0.809 2.90 (2.85–2.96) p = 0.003 2.66 (2.60–2.72) p = 0.154  Surgical 2.51 (2.39–2.63) 3.07 (2.98–3.17) 2.75 (2.64–2.86) Hours worked per week (including home call)  20–40 2.38 (2.02–2.74) p = 0.309 2.40 (2.12–2.68) p < 0.001 2.40 (2.16–2.81) p = 0.384  41–60 2.44 (2.35–2.52) 2.81 (2.74–2.87) 2.67 (2.59–2.74)  61–80 2.55 (2.46–2.64) 3.07 (3.00–3.14) 2.70 (2.62–2.77)  81+ 2.52 (2.33–2.72) 3.21 (3.06–3.37) 2.61 (2.61–2.96) Personal opinion of the performance triad  Very positive 2.30 (2.11–2.49) p < 0.001 2.73 (2.58–2.89) p = 0.022 2.43 (2.26–2.60) p < 0.001  Positive 2.42 (2.32–2.52) 2.89 (2.81–2.97) 2.65 (2.56–2.74)  Neutral 2.47 (2.38–2.56) 2.95 (2.87–3.02) 2.69 (2.60–2.77)  Negative 2.69 (2.53–2.85) 3.12 (2.99–3.25) 2.74 (2.59–2.88)  Very negative 2.73 (2.51–2.94) 3.15 (2.97–3.32) 3.02 (2.82–3.21) Frequency of supervisor adherence to triad recommendations  Always 2.37 (2.09–2.64) p < 0.001 2.50 (2.28–2.72) p < 0.001 2.43 (2.17–2.68) p < 0.001  Frequently 2.31 (2.20–2.41) 2.73 (2.65–2.82) 2.59 (2.50–2.69)  Occasionally 2.49 (2.41–2.57) 3.01 (2.95–3.08) 2.67 (2.60–2.74)  Never 2.90 (2.75–3.04) 3.30 (3.18–3.41) 2.99 (2.85–3.12) Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Mean score (95% CI) Mean score (95% CI) Mean score (95% CI) Gender  Male 2.43 (2.37–2.50) p < 0.001 2.95 (2.89–3.00) p = 0.553 2.67 (2.61–2.73) p = 0.332  Female 2.72 (2.59–2.84) 2.91 (2.81–3.01) 2.74 (2.62–2.85) Age group  21–30 2.59 (2.40–2.78) p = 0.525 3.08 (2.93–3.23) p = 0.238 2.85 (2.68–3.03) p = 0.205  31–40 2.52 (2.44–2.61) 2.90 (2.83–2.97) 2.68 (2.61–2.76)  41–50 2.45 (2.35–2.55) 2.94 (2.86–3.03) 2.68 (2.59–2.77)  51–60 2.43 (2.24–2.62) 3.01 (2.86–3.16) 2.55 (2.39–2.72)  60+ 2.32 (1.78–2.86) 2.91 (2.47–3.35) 2.64 (2.15–3.13) Training status  Staff 2.47 (2.40–2.53) p = 0.044 2.91 (2.86–2.96) p = 0.006 2.68 (2.62–2.73) p = 0.191  Residents 2.63 (2.48–2.77) 3.09 (2.97–3.20) 2.77 (2.64–2.90) Specialty type  Non-surgical 2.49 (2.42–2.56) p = 0.809 2.90 (2.85–2.96) p = 0.003 2.66 (2.60–2.72) p = 0.154  Surgical 2.51 (2.39–2.63) 3.07 (2.98–3.17) 2.75 (2.64–2.86) Hours worked per week (including home call)  20–40 2.38 (2.02–2.74) p = 0.309 2.40 (2.12–2.68) p < 0.001 2.40 (2.16–2.81) p = 0.384  41–60 2.44 (2.35–2.52) 2.81 (2.74–2.87) 2.67 (2.59–2.74)  61–80 2.55 (2.46–2.64) 3.07 (3.00–3.14) 2.70 (2.62–2.77)  81+ 2.52 (2.33–2.72) 3.21 (3.06–3.37) 2.61 (2.61–2.96) Personal opinion of the performance triad  Very positive 2.30 (2.11–2.49) p < 0.001 2.73 (2.58–2.89) p = 0.022 2.43 (2.26–2.60) p < 0.001  Positive 2.42 (2.32–2.52) 2.89 (2.81–2.97) 2.65 (2.56–2.74)  Neutral 2.47 (2.38–2.56) 2.95 (2.87–3.02) 2.69 (2.60–2.77)  Negative 2.69 (2.53–2.85) 3.12 (2.99–3.25) 2.74 (2.59–2.88)  Very negative 2.73 (2.51–2.94) 3.15 (2.97–3.32) 3.02 (2.82–3.21) Frequency of supervisor adherence to triad recommendations  Always 2.37 (2.09–2.64) p < 0.001 2.50 (2.28–2.72) p < 0.001 2.43 (2.17–2.68) p < 0.001  Frequently 2.31 (2.20–2.41) 2.73 (2.65–2.82) 2.59 (2.50–2.69)  Occasionally 2.49 (2.41–2.57) 3.01 (2.95–3.08) 2.67 (2.60–2.74)  Never 2.90 (2.75–3.04) 3.30 (3.18–3.41) 2.99 (2.85–3.12) Significant relationships (p < 0.05) based on the based on the GLM F-test statistic for goodness of fit are marked in bold print. Table IV. Multivariable Analysis – Demographic Factors and Triad Behavior Among U.S. Army Physicians Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Gender Male 2.56 (2.45–2.67) p = 0.001 Female 2.81 (2.65–2.97) Training status  Staff 2.58 (2.48–2.68) p = 0.008 2.81 (2.71–2.92) p = 0.018  Residents 2.79 (2.62–2.96) 2.96 (2.81–3.11) Speciality type  Non-surgical 2.81 (2.70–2.93) p = 0.006  Surgical 2.96 (2.83–3.10) Hours worked per week (including home call)  20–40 2.40 (2.11–2.69) p < 0.001  41–60 2.87 (2.76–2.97)  61–80 3.08 (2.97–3.18)  81+ 3.21 (3.04–3.37) Personal opinion of the performance triad  Very positive 2.55 (2.35–2.76) p = 0.205 2.78 (2.60–2.95) p = 0.457 2.47 (2.29–2.64) p = 0.044  Positive 2.64 (2.50–2.78) 2.88 (2.75–3.01) 2.67 (2.56–2.78)  Neutral 2.63 (2.50–2.76) 2.87 (2.75–3.00) 2.67 (2.56–2.77)  Negative 2.81 (2.62–3.00) 2.95 (2.78–3.11) 2.68 (2.51–2.84)  Very negative 2.79 (2.55–3.03) 2.96 (2.76–3.15) 2.89 (2.68–3.10) Frequency of supervisor adherence to triad recommendations  Always 2.59 (2.30–2.88) p < 0.001 2.48 (2.24–2.72) p < 0.001 2.47 (2.21–2.73) p = 0.001  Frequently 2.49 (2.35–2.63) 2.76 (2.63–2.88) 2.62 (2.51–2.73)  Occasionally 2.66 (2.54–2.78) 3.03 (2.92–3.14) 2.67 (2.59–2.76)  Never 3.00 (2.83–3.17) 3.28 (3.13–3.43) 2.93 (2.80–3.07) Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Gender Male 2.56 (2.45–2.67) p = 0.001 Female 2.81 (2.65–2.97) Training status  Staff 2.58 (2.48–2.68) p = 0.008 2.81 (2.71–2.92) p = 0.018  Residents 2.79 (2.62–2.96) 2.96 (2.81–3.11) Speciality type  Non-surgical 2.81 (2.70–2.93) p = 0.006  Surgical 2.96 (2.83–3.10) Hours worked per week (including home call)  20–40 2.40 (2.11–2.69) p < 0.001  41–60 2.87 (2.76–2.97)  61–80 3.08 (2.97–3.18)  81+ 3.21 (3.04–3.37) Personal opinion of the performance triad  Very positive 2.55 (2.35–2.76) p = 0.205 2.78 (2.60–2.95) p = 0.457 2.47 (2.29–2.64) p = 0.044  Positive 2.64 (2.50–2.78) 2.88 (2.75–3.01) 2.67 (2.56–2.78)  Neutral 2.63 (2.50–2.76) 2.87 (2.75–3.00) 2.67 (2.56–2.77)  Negative 2.81 (2.62–3.00) 2.95 (2.78–3.11) 2.68 (2.51–2.84)  Very negative 2.79 (2.55–3.03) 2.96 (2.76–3.15) 2.89 (2.68–3.10) Frequency of supervisor adherence to triad recommendations  Always 2.59 (2.30–2.88) p < 0.001 2.48 (2.24–2.72) p < 0.001 2.47 (2.21–2.73) p = 0.001  Frequently 2.49 (2.35–2.63) 2.76 (2.63–2.88) 2.62 (2.51–2.73)  Occasionally 2.66 (2.54–2.78) 3.03 (2.92–3.14) 2.67 (2.59–2.76)  Never 3.00 (2.83–3.17) 3.28 (3.13–3.43) 2.93 (2.80–3.07) Numbers in bold reflect an independent relationship with the outcome variable at the p < 0.05 level of significance based on the based on the GLM F-test statistic for goodness of fit. Only variables that were significant (p < 0.05) in bivariable analyses were included in each multivariable model. Table IV. Multivariable Analysis – Demographic Factors and Triad Behavior Among U.S. Army Physicians Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Gender Male 2.56 (2.45–2.67) p = 0.001 Female 2.81 (2.65–2.97) Training status  Staff 2.58 (2.48–2.68) p = 0.008 2.81 (2.71–2.92) p = 0.018  Residents 2.79 (2.62–2.96) 2.96 (2.81–3.11) Speciality type  Non-surgical 2.81 (2.70–2.93) p = 0.006  Surgical 2.96 (2.83–3.10) Hours worked per week (including home call)  20–40 2.40 (2.11–2.69) p < 0.001  41–60 2.87 (2.76–2.97)  61–80 3.08 (2.97–3.18)  81+ 3.21 (3.04–3.37) Personal opinion of the performance triad  Very positive 2.55 (2.35–2.76) p = 0.205 2.78 (2.60–2.95) p = 0.457 2.47 (2.29–2.64) p = 0.044  Positive 2.64 (2.50–2.78) 2.88 (2.75–3.01) 2.67 (2.56–2.78)  Neutral 2.63 (2.50–2.76) 2.87 (2.75–3.00) 2.67 (2.56–2.77)  Negative 2.81 (2.62–3.00) 2.95 (2.78–3.11) 2.68 (2.51–2.84)  Very negative 2.79 (2.55–3.03) 2.96 (2.76–3.15) 2.89 (2.68–3.10) Frequency of supervisor adherence to triad recommendations  Always 2.59 (2.30–2.88) p < 0.001 2.48 (2.24–2.72) p < 0.001 2.47 (2.21–2.73) p = 0.001  Frequently 2.49 (2.35–2.63) 2.76 (2.63–2.88) 2.62 (2.51–2.73)  Occasionally 2.66 (2.54–2.78) 3.03 (2.92–3.14) 2.67 (2.59–2.76)  Never 3.00 (2.83–3.17) 3.28 (3.13–3.43) 2.93 (2.80–3.07) Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Gender Male 2.56 (2.45–2.67) p = 0.001 Female 2.81 (2.65–2.97) Training status  Staff 2.58 (2.48–2.68) p = 0.008 2.81 (2.71–2.92) p = 0.018  Residents 2.79 (2.62–2.96) 2.96 (2.81–3.11) Speciality type  Non-surgical 2.81 (2.70–2.93) p = 0.006  Surgical 2.96 (2.83–3.10) Hours worked per week (including home call)  20–40 2.40 (2.11–2.69) p < 0.001  41–60 2.87 (2.76–2.97)  61–80 3.08 (2.97–3.18)  81+ 3.21 (3.04–3.37) Personal opinion of the performance triad  Very positive 2.55 (2.35–2.76) p = 0.205 2.78 (2.60–2.95) p = 0.457 2.47 (2.29–2.64) p = 0.044  Positive 2.64 (2.50–2.78) 2.88 (2.75–3.01) 2.67 (2.56–2.78)  Neutral 2.63 (2.50–2.76) 2.87 (2.75–3.00) 2.67 (2.56–2.77)  Negative 2.81 (2.62–3.00) 2.95 (2.78–3.11) 2.68 (2.51–2.84)  Very negative 2.79 (2.55–3.03) 2.96 (2.76–3.15) 2.89 (2.68–3.10) Frequency of supervisor adherence to triad recommendations  Always 2.59 (2.30–2.88) p < 0.001 2.48 (2.24–2.72) p < 0.001 2.47 (2.21–2.73) p = 0.001  Frequently 2.49 (2.35–2.63) 2.76 (2.63–2.88) 2.62 (2.51–2.73)  Occasionally 2.66 (2.54–2.78) 3.03 (2.92–3.14) 2.67 (2.59–2.76)  Never 3.00 (2.83–3.17) 3.28 (3.13–3.43) 2.93 (2.80–3.07) Numbers in bold reflect an independent relationship with the outcome variable at the p < 0.05 level of significance based on the based on the GLM F-test statistic for goodness of fit. Only variables that were significant (p < 0.05) in bivariable analyses were included in each multivariable model. Figure 1. View largeDownload slide Perceived supervisor behavior and self-reported triad behavior of U.S. Army physicians. Figure 1. View largeDownload slide Perceived supervisor behavior and self-reported triad behavior of U.S. Army physicians. DISCUSSION The results of this study suggest leadership, specifically the immediate level supervisor, has a strong association with healthy sleep, exercise, and nutrition behaviors of physicians. Belief in an immediate supervisor’s adherence with the P3 was consistently associated with an individual’s adherence with all three components of the P3. Organizational initiatives, similar to the P3, that involve executive level leadership have been able to impact physician burnout.7 Creating a culture that promotes physician wellness at the highest level is vital for any wellness initiative to succeed. However, lower level leadership is vital in cultivating this culture by serving as a role model and emphasizing the importance of positive wellness behaviors. One example from the Northwestern Family Medicine Residency noted the positive benefit of “green balance”, where the leadership of the inpatient physician team ensured at least 10 min of outside fresh air after rounds to rebalance the team.18 Simple directives such as this, from an immediate supervisor, can have an exponential impact on the wellness of the physician team. Exercise was the component of the P3 that showed the highest adherence in our survey of U.S. Army physicians. Participation in regular exercise has been shown to be associated with improved quality of life and decreased burnout in resident physicians.25 A unique aspect of military medicine is the requirement for frequent physical fitness assessments that applies to all members of the armed services. The U.S. Army Physical Fitness Test is required biannually. Failure of this test can lead to consequences such as disqualification from a medical training program, and disqualification from rank promotion. This incentive may contribute to exercise being the most adhered to component of the P3 for the U.S. Army physician. The results of our survey show better adherence to exercise for U.S. Army physicians compared with a report from a civilian physician survey.18 The previously mentioned incentives for passing the U.S. Army Physical Fitness Test, may contribute to this improved exercise adherence in U.S. Army physicians. The typical candidate for a position as an U.S. Army physician may have a higher emphasis on personal fitness that attracts him or her to military service. Sleep was the P3 component that showed the least adherence. Sleep deprivation has long been associated with the physician lifestyle. In the past, being able to function while sleep deprived was considered a positive trait amongst physicians. It was commonly felt that long work hours was part of the professional ethos of physicians to provide care for the patient, even at the expense of inadequate personal sleep.26 However, it is well known that sleep deprivation is a known cause for medical errors.27–31 Physician resident work hour restrictions were instituted primarily to address the sleep deprivation that was induced by the traditional residency work hours and call schedules.32 Despite the implementation of the resident work hour restrictions, among our sample of physicians only a minority of residents (and staff physicians) regularly achieve 8 h of sleep per day. The lack of regular sleep was especially prominent among surgical specialists both during and after completion of training. Our study did show less hours worked per week was associated with better adherence to getting 8 h of sleep per night. However, the question used in our survey may not be the most appropriate measure of adequate sleep. The National Sleep Foundation reports the average sleep requirement for adults is 7–9 h per night.33 Therefore, using a cutoff of 8 h may overestimate inadequate sleep. Sleep deprivation is not unique to the military physician, as evidenced by a study of licensed California physicians which reported 34% of respondents slept less than 6 h per day.34 Nutrition is often neglected by physicians during a busy workday. It is not uncommon for physicians to skip meals as catching up on work intrudes on planned meal times. The quality of diet may also be a casualty of the physician’s work environment. Hospital cafeteria food has been shown to have excessive caloric content.35 Oftentimes, lower quality but quickly available food is the choice when time is limited. In civilian institutions, catered meals are sometimes available, but are not typically of the best nutritional quality. Poor nutrition has been reported to affect physician’s physical, emotional and cognitive functioning.36 One study showed improving physician nutrition is associated with improved cognitive testing results.37 Therefore, proper nutrition is an important component in physician wellness and can impact patient care.38 Survey responses indicated Army physicians have less than ideal adherence to the nutrition component of the P3. Physician adherence to wellness behaviors may have an impact on clinical practice. Several studies have shown that physicians who practiced healthy exercise and nutrition habits were more likely to promote and counsel patients on wellness behaviors.13–15 Instilling wellness behaviors in physicians who are in residency training may have long lasting benefit in their own clinical practice. Practicing wellness behaviors should not be limited to physicians in training, as physicians at any stage of their career may benefit. There are several weaknesses in our study. Only 22% of the active duty Army physicians responded to the survey. The majority of these respondents were staff physicians, which may skew the results. Staff physicians are more likely to have flexibility in work hours, less work hours, and less in house call compared with resident physicians. Therefore, staff physicians may have more opportunity to adhere to healthy wellness behaviors. Another weakness of this study was our measures of physician wellness behaviors. The questions we used in this study were selected to measure components of P3 and were not validated measures of diet, sleep, or exercise. It is unclear how well these questions measure actual provider diet, sleep, and exercise. Future studies building on our results should use more robust and validated measures of these activities, such as dietary logs or actigraphy, to measure actual wellness behavior and physician fitness. Sleep, exercise and nutrition are all vital components of physical wellness behaviors. Although other areas of focus (e.g., social, spiritual, and emotional) are required for a comprehensive wellness program, improvements in the physical wellness behaviors have been shown to improve physician burnout. Initiatives similar to P3 should be considered integral parts of a comprehensive wellness program for physicians. CONCLUSION Overall, U.S. Army physicians are most adherent to the exercise tenet and least adherent to the sleep tenet of P3; consistent with the military culture. Work hours seem to affect wellness behaviors. Specifically, physicians who work fewer hours are more likely to report obtaining 8 h of sleep per day and exercising on a regular basis. Importantly, belief in supervisor adherence to P3 was associated with better adherence to P3, suggesting physician leadership has a positive effect on wellness behaviors. Specific programs to improve military physician adherence to the tenants of P3 should be considered. Future research should also include systemic changes in health system policies to motivate physician wellness behaviors, and correlating physician wellness with lifestyle counseling with patients. Prior Presentation The content of this manuscript has been presented orally at the BAMC research day at Brooke Army Medical Center on April 27, 2017. It was also presented in poster form at the 2017 ACGME annual education conference in Orlando, FL, USA on March 10, 2017, and the 31st Annual Meeting of the Associated Professional Sleep Societies conference in Boston, MA, USA on June 5, 2017. References 1 Maslach C , Jackson SE , Leiter MP : Maslach burnout inventory manual. 3rd ed. Consulting Psychologists; 1996 . 2 Rafferty JP , Lemkau JP , Purdy RR , et al. : Validity of the Maslach Burnout Inventory for family practice physicians . J Clin Psychol 1986 ; 42 : 488 – 92 . Google Scholar CrossRef Search ADS PubMed 3 Shanafelt TD , Boone S , Tan L , et al. : Burnout and satisfaction with work-life balance among US physicians relative to the general US population . Arch Intern Med 2012 ; 172 ( 18 ): 1377 – 85 . Google Scholar CrossRef Search ADS PubMed 4 Shanafelt TD , Hasan O , Dyrbye LN , et al. : Changes in burnout and satisfaction with work-life balance in physicians and the general US working population between 2011 and 2014 . Mayo Clin Proc 2015 ; 90 ( 12 ): 1600 – 13 . doi:10.1016/j.mayocp.2015.08.023 ; Erratum in: Mayo Clin Proc 2016 Feb;91(2):276. Google Scholar CrossRef Search ADS PubMed 5 Genovese JM , Berek JS : Can arts and communication programs improve physician wellness and mitigate physician suicide? J Clin Onc 2016 ; 34 ( 15 ): 1820 – 2 . Google Scholar CrossRef Search ADS 6 Ariely D , Lanier WL : Disturbing trends in physician burnout and satisfaction with work-life balance: dealing with malady among the nation’s healers . Mayo Clin Proc 2015 ; 90 ( 12 ): 1593 – 6 . Google Scholar CrossRef Search ADS PubMed 7 Shanafelt TD , Noseworthy JH : Executive leadership and physician well-being: nine organizational strategies to promote engagement and reduce burnout . Mayo Clin Proc 2017 ; 92 ( 1 ): 129 – 46 . Google Scholar CrossRef Search ADS PubMed 8 Dewa CS , Loong D , Bonato S , et al. : How does burnout affect physician productivity? A systematic literature review . BMC Health Serv Res 2014 ; 14 : 325 . Google Scholar CrossRef Search ADS PubMed 9 Eckleberry-Hunt J , Van Dyke A , Lick D , et al. : Changing the conversation from burnout to wellness: physician well-being in residency training programs . J Grad Med Educ 2009 ; 1 ( 2 ): 225 – 30 . Google Scholar CrossRef Search ADS PubMed 10 McClafferty H , Brown OW : Physician health and wellness . Pediatrics 2014 ; 134 ( 4 ): 830 – 5 . Google Scholar CrossRef Search ADS PubMed 11 West CP : Physician well-being: expanding the triple aim . J Gen Intern Med 2016 ; 31 ( 5 ): 458 – 9 . Google Scholar CrossRef Search ADS PubMed 12 Taub S , Morin K , Goldrich MS , et al. : Council on ethical and judicial affairs of the American Medical Association. Physician health and wellness . Occup Med. 2006 ; 56 ( 2 ): 77 – 82 . Google Scholar CrossRef Search ADS 13 Livaudais JC , Kaplan CP , Haas JS , et al. : Lifestyle behavior counseling for women patients among a sample of California physicians . J Womens Health (Larchmt) 2005 ; 14 ( 6 ): 485 – 95 . Google Scholar CrossRef Search ADS PubMed 14 Abramson S , Stein J , Schaufele M , et al. : Personal exercise habits and counseling practices of primary care physicians: a national survey . Clin J Sport Med 2000 ; 10 ( 1 ): 40 – 8 . Google Scholar CrossRef Search ADS PubMed 15 Howe M , Leidel A , Krishnan SM , et al. : Patient-related diet and exercise counseling: do providers’ own lifestyle habits matter? Prev Cardiol 2010 Fall; 13 ( 4 ): 180 – 5 . Google Scholar CrossRef Search ADS PubMed 16 Daneshvar F , Weinreich M , Daneshvar D , et al. : Cardiorespiratory fitness in internal medicine residents: are future physicians becoming deconditioned? J Grad Med Educ 2017 ; 9 ( 1 ): 97 – 101 . Google Scholar CrossRef Search ADS PubMed 17 Leventer-Roberts M , Zonfrillo MR , Yu S , et al. : Overweight physicians during residency: a cross-sectional and longitudinal study . J Grad Med Educ 2013 ; 5 ( 3 ): 405 – 11 . Google Scholar CrossRef Search ADS PubMed 18 Williams AS , Williams CD , Cronk NJ , et al. : Understanding the exercise habits of residents and attending physicians: a mixed methodology study . Fam Med 2015 ; 47 ( 2 ): 118 – 23 . Google Scholar PubMed 19 Lefebvre DC : Perspective: Resident physician wellness: a new hope . Acad Med 2012 ; 87 ( 5 ): 598 – 602 . Google Scholar CrossRef Search ADS PubMed 20 Drolet BC , Rodgers S : A comprehensive medical student wellness program – design and implementation at Vanderbilt School of Medicine . Acad Med 2010 ; 85 ( 1 ): 103 – 10 . Google Scholar CrossRef Search ADS PubMed 21 Place S , Talen M : Creating a culture of wellness: conversations, curriculum, concrete resources, and control . Int J Psychiatry Med 2013 ; 45 ( 4 ): 333 – 44 . Google Scholar CrossRef Search ADS PubMed 22 Caravalho J : Improving soldier health and performance by moving army medicine toward a system for health . J Strength Cond Res 2015 ; 29 ( Suppl 11 ): S4 – 9 . Google Scholar CrossRef Search ADS PubMed 23 Purvis DL , Lentino CV , Jackson TK , et al. : Nutrition as a component of the performance triad: how healthy eating behaviors contribute to soldier performance and military readiness. AMEDD J Oct-Dec 2013 ; 66 – 78 . http://www.cs.amedd.army.mil/amedd_journal.aspx; accessed November 1, 2016. 24 Lentino CV , Purvis DL , Murphy KJ , et al. : Sleep as a component of the performance triad: the importance of sleep in a military population . AMEDD J . Oct-Dec 2013 ; 98 – 108 . http://www.cs.amedd.army.mil/amedd_journal.aspx; accessed November 1, 2016. 25 Weight CJ , Sellon JL , Lessard-Anderson CR , et al. : Physical activity, quality of life, and burnout among physician trainees: the effect of a team-based, incentivized exercise program . Mayo Clin Proc 2013 ; 88 ( 12 ): 1435 – 42 . Google Scholar CrossRef Search ADS PubMed 26 Ginsberg S : Duty hours as viewed through a professionalism lens . BMC Med Educ 2014 ; 14 ( Suppl 1 ): S15 . Google Scholar CrossRef Search ADS PubMed 27 Mansukhani MP , Kolla BP , Surani S , et al. : Sleep deprivation in resident physicians, work hour limitations, and related outcomes: a systematic review of the literature . Postgrad Med 2012 ; 124 ( 4 ): 241 – 9 . Google Scholar CrossRef Search ADS PubMed 28 Majekodunmi A , Landrigan CP : The effect of physician sleep deprivation on patient safety in perinatal-neonatal medicine . Am J Perinatol 2012 ; 29 ( 1 ): 43 – 8 . Google Scholar CrossRef Search ADS PubMed 29 Olson EJ , Drage LA , Auger RR : Sleep deprivation, physician performance, and patient safety . Chest 2009 ; 136 ( 5 ): 1389 – 96 . Google Scholar CrossRef Search ADS PubMed 30 Mountain SA , Quon BS , Dodek P , et al. : The impact of housestaff fatigue on occupational and patient safety . Lung 2007 ; 185 ( 4 ): 203 – 9 . Google Scholar CrossRef Search ADS PubMed 31 Parshuram CS : The impact of fatigue on patient safety . Pediatr Clin North Am 2006 ; 53 ( 6 ): 1135 – 53 . Google Scholar CrossRef Search ADS PubMed 32 Veasey S , Rosen R , Barzansky B , et al. : Sleep loss and fatigue in residency training: a reappraisal . JAMA. 2002 ; 288 ( 9 ): 1116 – 24 . Google Scholar CrossRef Search ADS PubMed 33 Hirshkowitz M , Whiton K , Albert SM , et al. : National Sleep Foundation’s sleep time duration recommendations: methodology and results summary . Sleep Health 2015 ; 1 ( 1 ): 40 – 3 . Google Scholar CrossRef Search ADS PubMed 34 Bazargan M , Makar M , Bazargan-Hejazi S , et al. : Preventive, lifestyle, and personal health behaviors among physicians . Acad Psychiatry 2009 ; 33 ( 4 ): 289 – 95 . Google Scholar CrossRef Search ADS PubMed 35 Lesser LI , Cohen DA , Brook RH : Changing eating habits for the medical profession . JAMA 2012 ; 308 ( 10 ): 983 – 4 . Google Scholar CrossRef Search ADS PubMed 36 Lemaire JB , Wallace JE , Dinsmore K , et al. : Food for thought: an exploratory study of how physicians experience poor workplace nutrition . Nutr J 2011 ; 10 ( 1 ): 18 . Google Scholar CrossRef Search ADS PubMed 37 Lemaire JB , Wallace JE , Dinsmore K , et al. : Physician nutrition and cognition during work hours: effect of a nutrition based intervention . BMC Health Serv Res 2010 ; 10 : 241 . Google Scholar CrossRef Search ADS PubMed 38 Hamidi MS , Boggild MK , Cheung AM : Running on empty: a review of nutrition and physicians’ well-being . Postgrad Med J 2016 ; 92 ( 1090 ): 478 – 81 . Google Scholar CrossRef Search ADS PubMed Author notes The views expressed herein are those of the authors and do not reflect the official policy or position of Brooke Army Medical Center, the U.S. Army Medical Department, the U.S. Army Office of the Surgeon General, the Departments of the Army, Navy, Air Force, the Department of Defense, or the U.S. Government. © Association of Military Surgeons of the United States 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 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Abstract

Abstract Introduction In 2013, the U.S. Army Surgeon General implemented the Performance Triad (P3), an educational initiative to improve health-related behaviors of soldiers throughout the U.S. Army. The components of P3 are Sleep, Activity, and Nutrition with tenet behaviors for each component. This study reports the results of the 2015 U.S. Army Medical Corps survey regarding physician knowledge and adherence to the tenet behaviors of P3. Methods In 2015, an anonymous survey was sent to all active duty U.S. Army physicians to assess demographic information, work hours, and knowledge of and adherence to P3. The survey assessed the tenets of P3 with questions about the following topics: obtaining 8 h of sleep per day; performing at least 2 d of resistance training and 1 day of agility training per week; re-fueling 30–60 min after exercise; incorporating at least 150 min of moderate and 75 min of vigorous aerobic exercise per week; going caffeine free 6 h before bedtime; eating at least 8 servings of fruits and vegetables per day; and getting 15,000 steps per day. For each question, there were four response options which ranged from “Always” to “Never.” A positive response to the questionnaire was defined as answering frequently or always. The responses were analyzed by comparison of several physician categories utilizing descriptive statistics and multivariable analysis. Results Surveys were completed by 1,003 of approximately 4,500 U.S. Army physicians. 79.1% of the respondents were male. Staff physicians made up 834 (83.6%) of the respondents compared with 164 (16.4%) physicians in training. Overall 25% of respondents were adherent to the sleep tenet, 45% to the exercise tenet, and 38% to the nutrition tenet. Reported work hours were significantly higher in physicians in training compared with staff physicians (p < 0.001). About 28.4% of staff reported a positive response to obtaining at least 8 h of sleep per night, compared with 12.7% of residents/fellows. In multivariable analyses, better sleep was associated with being a staff physician [odds ratio 2.4 (95% confidence interval 1.40–4.13)], working fewer hours per week [1.75 (1.37–2.25)], and belief in supervisor adherence to P3 [2.04 (1.59–2.56)]. Increased exercise was associated with male gender [2.09 (1.45–3.02)], being a staff physician [1.63 (1.09–2.43)], and belief in supervisor adherence to P3 [1.43 (1.18–1.75)]. Positive response to the nutrition tenet was associated with belief in supervisor adherence to P3 [1.23 (1.01–1.49)]. Conclusion Overall, U.S. Army physicians are most adherent to the exercise tenet and least adherent to the sleep tenet of P3; this is consistent with the military culture. Work hours seem to affect wellness behaviors. Specifically, physicians who work fewer hours are more likely to report obtaining 8 h of sleep per day and exercise on a regular basis. Importantly, belief in supervisor adherence to P3 was associated with better adherence to P3, suggesting that physician leadership has a positive effect on wellness behaviors. This suggests a role for similar wellness programs in civilian healthcare institutions. Future research should also include changes in health system policies to motivate physician wellness behaviors. INTRODUCTION Physician wellness is strongly linked to compassionate and appropriate care for patients. However, many physicians experience burnout, which degrades physician wellness and has a negative impact on patient care.1,2 Physician burnout has been defined as a triad of emotional exhaustion, depersonalization, and low sense of personal accomplishment.1 Physicians experience higher rates of burnout than the general population beginning in medical school and rates increase among residents and mid-career physicians. A 2011 survey of U.S. physicians noted 45% of respondents reported burnout, and burnout was more common among physicians compared with other professions.3 This trend continues to increase, as noted by a follow on survey in 2014 showing the burnout response rate had increased to 54%.4 These findings are significant for several reasons. Personally, it may contribute to mental health problems, such as depression and anxiety. Although extreme, physician burnout can eventually lead to suicidal ideations. Within the past few years, reports of physician suicides rates are over 400 annually.5 Professionally, it has been well documented that physician burnout impacts quality of medical care provided.6–8 There are many publications regarding physician burnout, with few that address solutions to address burnout. More recent publications are now addressing physician wellness as a means to combat burnout.9–12 Previous studies have demonstrated factors such as maintenance of work-life balance, social and family support, adequate rest, and regular physical activity are correlated with career satisfaction, improved sense of well-being, increased empathy, and decreased burnout.9–12 Physicians who engage in health promoting behaviors are also more likely to promote these behaviors to their patients and are also perceived as more credible and motivating proponents of these interventions to their patients.13–15 There are few studies that assess personal wellness habits of physicians in the USA, although several medical resident surveys have been performed.16,17 One study assessed exercise habits of resident and attending physicians.18 These limited studies suggest many physicians do not engage in health promoting behaviors. Many barriers to engaging in healthy behavior exist among physicians, including time pressures and a culture of altruistic and self-sacrificing behavior that encourages physicians to neglect self-care. Many health systems have implemented programs to encourage physician wellness and combat burnout through education programs and changes to the work environment with variable success.9,19–21 In 2013, the U.S. Army Surgeon General implemented the Performance Triad (P3), a multimodal educational initiative to encourage U.S. Army soldier engagement in wellness behaviors including obtaining adequate sleep, regular physical activity, and proper nutrition.22 Evaluations of the sleep and nutrition components of the P3 note U.S. Army soldiers with better nutrition and sleep habits performed better on the Army Physical Fitness Test.23,24 These wellness surveys of U.S. Army soldiers also showed better sleep and nutrition were associated with higher fitness scores in emotional, social, family and spiritual categories. However, adherence to the P3 amongst U.S. Army physicians is unknown. This study explored physician engagement in the P3 program and attempted to identify factors that enhanced or hindered physician engagement. METHODS Survey In 2015, the U.S. Army Medical Corps sent an anonymous survey to all active duty Army physicians. Surveys were completed by 1,009 U.S. Army physicians, with a response rate of 22.4%. The survey assessed their military duties, deployment history, work satisfaction in the Military Healthcare System, and knowledge of and adherence to the P3. Demographic information collected included age, gender, hours worked per week (including hours of home call), provider medical specialty, and medical training status (i.e., staff versus resident or fellow). Performance Triad Assessment Personal involvement in P3 activities was assessed through four questions: “Do you get 8 h of quality sleep per 24-h period?”, “Do you include at least 2 d or more resistance training per week and 1 day agility training?”, “Do you incorporate at least 150 min of moderate and 75 min of vigorous intensity aerobic exercise per week?”, and “Do you eat at least 8 servings of fruits and vegetables per day?”. Responses to these questions were assessed using a 4-point Likert scale ranging from “Always, Frequently, Occasionally, Never”. The subject responses to the exercise and resistance training questions were correlated (correlation coefficient 0.667, p < 0.001) so these two items were combined into a single exercise item with a range of 1 (always engages in both exercise types) to 4 (never engages in either exercise type) (Cronbach’s α = 0.800). The three P3 measures were significantly correlated with each other: exercise/sleep (0.128, p < 0.001), exercise/diet (0.309, p < 0.001), and diet/sleep (0.178, p < 0.001). However, the level of correlation between the measures was not high and combining these measure together did not yield a reliable scale (Cronbach’s α = 0.436). Therefore, provider adherence to each of these activities was measured independently. A provider’s opinion of the importance of promotion of the P3 activities as a medical professional was measured with a single question, “What is your opinion of the Performance Triad as a core mission and emphasis of the Army Medical Department?”, with a 5-point Likert response scale ranging from “Very Positive” to “Very Negative”. The survey also measured a provider’s impression of his or her supervisor’s involvement in P3 activities with a single question, “Do you believe your first and second line supervisor adhere to all the recommendations of the performance triad?”, with a 4-point Likert response scale ranging from “Always” to “Never”. Statistical Analysis Simple descriptive statistics was used to describe the demographics of the sample population, provider involvement in P3 activities, provider belief in the importance of P3 promotion as a medical provider, and perception of supervisor involvement in P3 activities. The bivariable relationship of personal involvement in P3 activities with the demographic variables, provider opinions of P3 promotion, and perception of supervisor’s personal involvement in P3 activities was assessed using the univariate general linear model procedure in SPSS. Variables that had a significant (p < 0.05) relationship with the outcome variable in bivariable analysis were entered into a multivariable Univariate General Linear Model to assess the independent association between these factors and the outcome measures. The univariate general linear model procedure calculated an F-statistic for each predictor variable. This statistic assessed the change in model fit between the model with and without the predictor variable. If p < 0.05 for the F-statistic then you can conclude the predictor variable has a significant relationship with the dependent variable. Statistical analyses were conducted with SPSS software (version 22; IBM Corporation, Armonk, NY, USA). This study was reviewed and approved by the Institutional Review Board of the San Antonio Military Medical Center. RESULTS The majority of the survey respondents were male (79.1%). Staff physicians made up 834 (84%) of the respondents compared with 164 (16%) physicians in training. Over 80% of the respondents were between the ages of 31- and 50-yr-old. Non-surgical specialties represented 77% of the respondents. Almost 90% of the respondents worked between 41 and 80 h per week. Only 41% of physicians had a positive opinion of promoting exercise, sleep, diet as a core mission of the Army Medical Department (Table I). Overall, 50.6% of physicians reported frequently or always engaging in aerobic exercise, 44.3% of physicians reported frequently or always engaging in resistance/agility exercise, 25.6% reported frequently or always getting 8 h a of sleep a night, and 39.1% reported frequently or always eating 8 servings of fruits and vegetables a day. Only 34.6% of physicians thought their supervisors were frequently or always engaging in P3 activities (Table II). In bivariable analyses, higher personal engagement in exercise was associated with male gender, being a staff physician rather than a resident or fellow, having a higher opinion of P3 promotion as a core mission of the Army Medical Department, and perceiving higher engagement in P3 activities by supervisors. Physicians were more likely to report getting 8 h of sleep a night if they were not in a graduate medical education program, not a surgeon, worked fewer hours a week, had a higher opinion of P3 promotion, and perceived their supervisors were engaging in P3 activities. Only a positive opinion of P3 promotion and perceiving supervisor engagement in P3 activities was associated with higher fruit and vegetable consumption (Table III). In multivariable analyses, male physicians, staff physicians, and physicians who perceive that their supervisors engage in P3 activities were more likely to engage in regular exercise. Reporting a higher frequency of obtaining 8 h of sleep a night was associated with being a staff physician, working in a non-surgical specialty, working fewer hours a week, and believing that your supervisors engaged in the p3 activities. More frequent fruit and vegetable consumption was associated with having a more positive opinion of P3 promotion as a physician and perception of supervisor engagement in P3 activities (Table IV, Fig. 1). Table I. US Army Physician Survey Respondents (n = 1,009) Gender n % Male 793 79.1 Female 210 20.9 Age group  21–30 93 9.3  31–40 475 47.5  41–50 327 32.7  51–60 94 9.4  60+ 11 1.1 Training status  Staff 834 83.6  Residents/fellows 164 16.4 Specialty type  Non-surgical 770 76.8  Surgical 233 23.2 Hours worked per week (including home call)  20–40 26 2.6  41–60 469 46.8  61–80 419 41.8  81+ 88 8.8 What is your opinion of the performance triad as a core mission and emphasis of the army medical department?  Very positive 90 9.3  Positive 308 31.8  Neutral 380 39.2  Negative 124 12.8  Very negative 68 7.0 Gender n % Male 793 79.1 Female 210 20.9 Age group  21–30 93 9.3  31–40 475 47.5  41–50 327 32.7  51–60 94 9.4  60+ 11 1.1 Training status  Staff 834 83.6  Residents/fellows 164 16.4 Specialty type  Non-surgical 770 76.8  Surgical 233 23.2 Hours worked per week (including home call)  20–40 26 2.6  41–60 469 46.8  61–80 419 41.8  81+ 88 8.8 What is your opinion of the performance triad as a core mission and emphasis of the army medical department?  Very positive 90 9.3  Positive 308 31.8  Neutral 380 39.2  Negative 124 12.8  Very negative 68 7.0 Table I. US Army Physician Survey Respondents (n = 1,009) Gender n % Male 793 79.1 Female 210 20.9 Age group  21–30 93 9.3  31–40 475 47.5  41–50 327 32.7  51–60 94 9.4  60+ 11 1.1 Training status  Staff 834 83.6  Residents/fellows 164 16.4 Specialty type  Non-surgical 770 76.8  Surgical 233 23.2 Hours worked per week (including home call)  20–40 26 2.6  41–60 469 46.8  61–80 419 41.8  81+ 88 8.8 What is your opinion of the performance triad as a core mission and emphasis of the army medical department?  Very positive 90 9.3  Positive 308 31.8  Neutral 380 39.2  Negative 124 12.8  Very negative 68 7.0 Gender n % Male 793 79.1 Female 210 20.9 Age group  21–30 93 9.3  31–40 475 47.5  41–50 327 32.7  51–60 94 9.4  60+ 11 1.1 Training status  Staff 834 83.6  Residents/fellows 164 16.4 Specialty type  Non-surgical 770 76.8  Surgical 233 23.2 Hours worked per week (including home call)  20–40 26 2.6  41–60 469 46.8  61–80 419 41.8  81+ 88 8.8 What is your opinion of the performance triad as a core mission and emphasis of the army medical department?  Very positive 90 9.3  Positive 308 31.8  Neutral 380 39.2  Negative 124 12.8  Very negative 68 7.0 Table II. Self-Reported Frequency of Triad Behaviors and Perceived Supervisor Behavior Among U.S. Army Physicians Reported Frequency Do you incorporate at least 150 min of moderate and 75 min of vigorous intensity aerobic exercise per week? Do you include at least 2 d or more resistance training per week and 1 d agility training? Combined Aerobic and Resistance Exercise Variable Do you get 8 h of quality sleep per 24-h period? Do you eat at least 8 servings of fruits and vegetables per day? Do you believe your supervisors adhere to all of the Performance Triad recommendations? n % n % n % n % n % n % Always 219 22.4 181 18.5 139 14.3 22 2.2 76 7.8 41 4.3 69 7.1 Frequently 276 28.2 252 25.8 192 19.7 230 23.4 305 31.3 289 30.3 140 14.4 Occasionally 350 35.8 345 35.3 234 24.0 513 52.2 442 45.3 482 50.5 106 10.9 Never 134 13.7 200 20.4 95 9.7 217 22.1 152 15.6 142 14.9 Reported Frequency Do you incorporate at least 150 min of moderate and 75 min of vigorous intensity aerobic exercise per week? Do you include at least 2 d or more resistance training per week and 1 d agility training? Combined Aerobic and Resistance Exercise Variable Do you get 8 h of quality sleep per 24-h period? Do you eat at least 8 servings of fruits and vegetables per day? Do you believe your supervisors adhere to all of the Performance Triad recommendations? n % n % n % n % n % n % Always 219 22.4 181 18.5 139 14.3 22 2.2 76 7.8 41 4.3 69 7.1 Frequently 276 28.2 252 25.8 192 19.7 230 23.4 305 31.3 289 30.3 140 14.4 Occasionally 350 35.8 345 35.3 234 24.0 513 52.2 442 45.3 482 50.5 106 10.9 Never 134 13.7 200 20.4 95 9.7 217 22.1 152 15.6 142 14.9 Table II. Self-Reported Frequency of Triad Behaviors and Perceived Supervisor Behavior Among U.S. Army Physicians Reported Frequency Do you incorporate at least 150 min of moderate and 75 min of vigorous intensity aerobic exercise per week? Do you include at least 2 d or more resistance training per week and 1 d agility training? Combined Aerobic and Resistance Exercise Variable Do you get 8 h of quality sleep per 24-h period? Do you eat at least 8 servings of fruits and vegetables per day? Do you believe your supervisors adhere to all of the Performance Triad recommendations? n % n % n % n % n % n % Always 219 22.4 181 18.5 139 14.3 22 2.2 76 7.8 41 4.3 69 7.1 Frequently 276 28.2 252 25.8 192 19.7 230 23.4 305 31.3 289 30.3 140 14.4 Occasionally 350 35.8 345 35.3 234 24.0 513 52.2 442 45.3 482 50.5 106 10.9 Never 134 13.7 200 20.4 95 9.7 217 22.1 152 15.6 142 14.9 Reported Frequency Do you incorporate at least 150 min of moderate and 75 min of vigorous intensity aerobic exercise per week? Do you include at least 2 d or more resistance training per week and 1 d agility training? Combined Aerobic and Resistance Exercise Variable Do you get 8 h of quality sleep per 24-h period? Do you eat at least 8 servings of fruits and vegetables per day? Do you believe your supervisors adhere to all of the Performance Triad recommendations? n % n % n % n % n % n % Always 219 22.4 181 18.5 139 14.3 22 2.2 76 7.8 41 4.3 69 7.1 Frequently 276 28.2 252 25.8 192 19.7 230 23.4 305 31.3 289 30.3 140 14.4 Occasionally 350 35.8 345 35.3 234 24.0 513 52.2 442 45.3 482 50.5 106 10.9 Never 134 13.7 200 20.4 95 9.7 217 22.1 152 15.6 142 14.9 Table III. Bivariable Analysis – Association Between Demographic Factors and Triad Behaviors Among U.S. Army Physicians Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Mean score (95% CI) Mean score (95% CI) Mean score (95% CI) Gender  Male 2.43 (2.37–2.50) p < 0.001 2.95 (2.89–3.00) p = 0.553 2.67 (2.61–2.73) p = 0.332  Female 2.72 (2.59–2.84) 2.91 (2.81–3.01) 2.74 (2.62–2.85) Age group  21–30 2.59 (2.40–2.78) p = 0.525 3.08 (2.93–3.23) p = 0.238 2.85 (2.68–3.03) p = 0.205  31–40 2.52 (2.44–2.61) 2.90 (2.83–2.97) 2.68 (2.61–2.76)  41–50 2.45 (2.35–2.55) 2.94 (2.86–3.03) 2.68 (2.59–2.77)  51–60 2.43 (2.24–2.62) 3.01 (2.86–3.16) 2.55 (2.39–2.72)  60+ 2.32 (1.78–2.86) 2.91 (2.47–3.35) 2.64 (2.15–3.13) Training status  Staff 2.47 (2.40–2.53) p = 0.044 2.91 (2.86–2.96) p = 0.006 2.68 (2.62–2.73) p = 0.191  Residents 2.63 (2.48–2.77) 3.09 (2.97–3.20) 2.77 (2.64–2.90) Specialty type  Non-surgical 2.49 (2.42–2.56) p = 0.809 2.90 (2.85–2.96) p = 0.003 2.66 (2.60–2.72) p = 0.154  Surgical 2.51 (2.39–2.63) 3.07 (2.98–3.17) 2.75 (2.64–2.86) Hours worked per week (including home call)  20–40 2.38 (2.02–2.74) p = 0.309 2.40 (2.12–2.68) p < 0.001 2.40 (2.16–2.81) p = 0.384  41–60 2.44 (2.35–2.52) 2.81 (2.74–2.87) 2.67 (2.59–2.74)  61–80 2.55 (2.46–2.64) 3.07 (3.00–3.14) 2.70 (2.62–2.77)  81+ 2.52 (2.33–2.72) 3.21 (3.06–3.37) 2.61 (2.61–2.96) Personal opinion of the performance triad  Very positive 2.30 (2.11–2.49) p < 0.001 2.73 (2.58–2.89) p = 0.022 2.43 (2.26–2.60) p < 0.001  Positive 2.42 (2.32–2.52) 2.89 (2.81–2.97) 2.65 (2.56–2.74)  Neutral 2.47 (2.38–2.56) 2.95 (2.87–3.02) 2.69 (2.60–2.77)  Negative 2.69 (2.53–2.85) 3.12 (2.99–3.25) 2.74 (2.59–2.88)  Very negative 2.73 (2.51–2.94) 3.15 (2.97–3.32) 3.02 (2.82–3.21) Frequency of supervisor adherence to triad recommendations  Always 2.37 (2.09–2.64) p < 0.001 2.50 (2.28–2.72) p < 0.001 2.43 (2.17–2.68) p < 0.001  Frequently 2.31 (2.20–2.41) 2.73 (2.65–2.82) 2.59 (2.50–2.69)  Occasionally 2.49 (2.41–2.57) 3.01 (2.95–3.08) 2.67 (2.60–2.74)  Never 2.90 (2.75–3.04) 3.30 (3.18–3.41) 2.99 (2.85–3.12) Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Mean score (95% CI) Mean score (95% CI) Mean score (95% CI) Gender  Male 2.43 (2.37–2.50) p < 0.001 2.95 (2.89–3.00) p = 0.553 2.67 (2.61–2.73) p = 0.332  Female 2.72 (2.59–2.84) 2.91 (2.81–3.01) 2.74 (2.62–2.85) Age group  21–30 2.59 (2.40–2.78) p = 0.525 3.08 (2.93–3.23) p = 0.238 2.85 (2.68–3.03) p = 0.205  31–40 2.52 (2.44–2.61) 2.90 (2.83–2.97) 2.68 (2.61–2.76)  41–50 2.45 (2.35–2.55) 2.94 (2.86–3.03) 2.68 (2.59–2.77)  51–60 2.43 (2.24–2.62) 3.01 (2.86–3.16) 2.55 (2.39–2.72)  60+ 2.32 (1.78–2.86) 2.91 (2.47–3.35) 2.64 (2.15–3.13) Training status  Staff 2.47 (2.40–2.53) p = 0.044 2.91 (2.86–2.96) p = 0.006 2.68 (2.62–2.73) p = 0.191  Residents 2.63 (2.48–2.77) 3.09 (2.97–3.20) 2.77 (2.64–2.90) Specialty type  Non-surgical 2.49 (2.42–2.56) p = 0.809 2.90 (2.85–2.96) p = 0.003 2.66 (2.60–2.72) p = 0.154  Surgical 2.51 (2.39–2.63) 3.07 (2.98–3.17) 2.75 (2.64–2.86) Hours worked per week (including home call)  20–40 2.38 (2.02–2.74) p = 0.309 2.40 (2.12–2.68) p < 0.001 2.40 (2.16–2.81) p = 0.384  41–60 2.44 (2.35–2.52) 2.81 (2.74–2.87) 2.67 (2.59–2.74)  61–80 2.55 (2.46–2.64) 3.07 (3.00–3.14) 2.70 (2.62–2.77)  81+ 2.52 (2.33–2.72) 3.21 (3.06–3.37) 2.61 (2.61–2.96) Personal opinion of the performance triad  Very positive 2.30 (2.11–2.49) p < 0.001 2.73 (2.58–2.89) p = 0.022 2.43 (2.26–2.60) p < 0.001  Positive 2.42 (2.32–2.52) 2.89 (2.81–2.97) 2.65 (2.56–2.74)  Neutral 2.47 (2.38–2.56) 2.95 (2.87–3.02) 2.69 (2.60–2.77)  Negative 2.69 (2.53–2.85) 3.12 (2.99–3.25) 2.74 (2.59–2.88)  Very negative 2.73 (2.51–2.94) 3.15 (2.97–3.32) 3.02 (2.82–3.21) Frequency of supervisor adherence to triad recommendations  Always 2.37 (2.09–2.64) p < 0.001 2.50 (2.28–2.72) p < 0.001 2.43 (2.17–2.68) p < 0.001  Frequently 2.31 (2.20–2.41) 2.73 (2.65–2.82) 2.59 (2.50–2.69)  Occasionally 2.49 (2.41–2.57) 3.01 (2.95–3.08) 2.67 (2.60–2.74)  Never 2.90 (2.75–3.04) 3.30 (3.18–3.41) 2.99 (2.85–3.12) Significant relationships (p < 0.05) based on the based on the GLM F-test statistic for goodness of fit are marked in bold print. Table III. Bivariable Analysis – Association Between Demographic Factors and Triad Behaviors Among U.S. Army Physicians Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Mean score (95% CI) Mean score (95% CI) Mean score (95% CI) Gender  Male 2.43 (2.37–2.50) p < 0.001 2.95 (2.89–3.00) p = 0.553 2.67 (2.61–2.73) p = 0.332  Female 2.72 (2.59–2.84) 2.91 (2.81–3.01) 2.74 (2.62–2.85) Age group  21–30 2.59 (2.40–2.78) p = 0.525 3.08 (2.93–3.23) p = 0.238 2.85 (2.68–3.03) p = 0.205  31–40 2.52 (2.44–2.61) 2.90 (2.83–2.97) 2.68 (2.61–2.76)  41–50 2.45 (2.35–2.55) 2.94 (2.86–3.03) 2.68 (2.59–2.77)  51–60 2.43 (2.24–2.62) 3.01 (2.86–3.16) 2.55 (2.39–2.72)  60+ 2.32 (1.78–2.86) 2.91 (2.47–3.35) 2.64 (2.15–3.13) Training status  Staff 2.47 (2.40–2.53) p = 0.044 2.91 (2.86–2.96) p = 0.006 2.68 (2.62–2.73) p = 0.191  Residents 2.63 (2.48–2.77) 3.09 (2.97–3.20) 2.77 (2.64–2.90) Specialty type  Non-surgical 2.49 (2.42–2.56) p = 0.809 2.90 (2.85–2.96) p = 0.003 2.66 (2.60–2.72) p = 0.154  Surgical 2.51 (2.39–2.63) 3.07 (2.98–3.17) 2.75 (2.64–2.86) Hours worked per week (including home call)  20–40 2.38 (2.02–2.74) p = 0.309 2.40 (2.12–2.68) p < 0.001 2.40 (2.16–2.81) p = 0.384  41–60 2.44 (2.35–2.52) 2.81 (2.74–2.87) 2.67 (2.59–2.74)  61–80 2.55 (2.46–2.64) 3.07 (3.00–3.14) 2.70 (2.62–2.77)  81+ 2.52 (2.33–2.72) 3.21 (3.06–3.37) 2.61 (2.61–2.96) Personal opinion of the performance triad  Very positive 2.30 (2.11–2.49) p < 0.001 2.73 (2.58–2.89) p = 0.022 2.43 (2.26–2.60) p < 0.001  Positive 2.42 (2.32–2.52) 2.89 (2.81–2.97) 2.65 (2.56–2.74)  Neutral 2.47 (2.38–2.56) 2.95 (2.87–3.02) 2.69 (2.60–2.77)  Negative 2.69 (2.53–2.85) 3.12 (2.99–3.25) 2.74 (2.59–2.88)  Very negative 2.73 (2.51–2.94) 3.15 (2.97–3.32) 3.02 (2.82–3.21) Frequency of supervisor adherence to triad recommendations  Always 2.37 (2.09–2.64) p < 0.001 2.50 (2.28–2.72) p < 0.001 2.43 (2.17–2.68) p < 0.001  Frequently 2.31 (2.20–2.41) 2.73 (2.65–2.82) 2.59 (2.50–2.69)  Occasionally 2.49 (2.41–2.57) 3.01 (2.95–3.08) 2.67 (2.60–2.74)  Never 2.90 (2.75–3.04) 3.30 (3.18–3.41) 2.99 (2.85–3.12) Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Mean score (95% CI) Mean score (95% CI) Mean score (95% CI) Gender  Male 2.43 (2.37–2.50) p < 0.001 2.95 (2.89–3.00) p = 0.553 2.67 (2.61–2.73) p = 0.332  Female 2.72 (2.59–2.84) 2.91 (2.81–3.01) 2.74 (2.62–2.85) Age group  21–30 2.59 (2.40–2.78) p = 0.525 3.08 (2.93–3.23) p = 0.238 2.85 (2.68–3.03) p = 0.205  31–40 2.52 (2.44–2.61) 2.90 (2.83–2.97) 2.68 (2.61–2.76)  41–50 2.45 (2.35–2.55) 2.94 (2.86–3.03) 2.68 (2.59–2.77)  51–60 2.43 (2.24–2.62) 3.01 (2.86–3.16) 2.55 (2.39–2.72)  60+ 2.32 (1.78–2.86) 2.91 (2.47–3.35) 2.64 (2.15–3.13) Training status  Staff 2.47 (2.40–2.53) p = 0.044 2.91 (2.86–2.96) p = 0.006 2.68 (2.62–2.73) p = 0.191  Residents 2.63 (2.48–2.77) 3.09 (2.97–3.20) 2.77 (2.64–2.90) Specialty type  Non-surgical 2.49 (2.42–2.56) p = 0.809 2.90 (2.85–2.96) p = 0.003 2.66 (2.60–2.72) p = 0.154  Surgical 2.51 (2.39–2.63) 3.07 (2.98–3.17) 2.75 (2.64–2.86) Hours worked per week (including home call)  20–40 2.38 (2.02–2.74) p = 0.309 2.40 (2.12–2.68) p < 0.001 2.40 (2.16–2.81) p = 0.384  41–60 2.44 (2.35–2.52) 2.81 (2.74–2.87) 2.67 (2.59–2.74)  61–80 2.55 (2.46–2.64) 3.07 (3.00–3.14) 2.70 (2.62–2.77)  81+ 2.52 (2.33–2.72) 3.21 (3.06–3.37) 2.61 (2.61–2.96) Personal opinion of the performance triad  Very positive 2.30 (2.11–2.49) p < 0.001 2.73 (2.58–2.89) p = 0.022 2.43 (2.26–2.60) p < 0.001  Positive 2.42 (2.32–2.52) 2.89 (2.81–2.97) 2.65 (2.56–2.74)  Neutral 2.47 (2.38–2.56) 2.95 (2.87–3.02) 2.69 (2.60–2.77)  Negative 2.69 (2.53–2.85) 3.12 (2.99–3.25) 2.74 (2.59–2.88)  Very negative 2.73 (2.51–2.94) 3.15 (2.97–3.32) 3.02 (2.82–3.21) Frequency of supervisor adherence to triad recommendations  Always 2.37 (2.09–2.64) p < 0.001 2.50 (2.28–2.72) p < 0.001 2.43 (2.17–2.68) p < 0.001  Frequently 2.31 (2.20–2.41) 2.73 (2.65–2.82) 2.59 (2.50–2.69)  Occasionally 2.49 (2.41–2.57) 3.01 (2.95–3.08) 2.67 (2.60–2.74)  Never 2.90 (2.75–3.04) 3.30 (3.18–3.41) 2.99 (2.85–3.12) Significant relationships (p < 0.05) based on the based on the GLM F-test statistic for goodness of fit are marked in bold print. Table IV. Multivariable Analysis – Demographic Factors and Triad Behavior Among U.S. Army Physicians Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Gender Male 2.56 (2.45–2.67) p = 0.001 Female 2.81 (2.65–2.97) Training status  Staff 2.58 (2.48–2.68) p = 0.008 2.81 (2.71–2.92) p = 0.018  Residents 2.79 (2.62–2.96) 2.96 (2.81–3.11) Speciality type  Non-surgical 2.81 (2.70–2.93) p = 0.006  Surgical 2.96 (2.83–3.10) Hours worked per week (including home call)  20–40 2.40 (2.11–2.69) p < 0.001  41–60 2.87 (2.76–2.97)  61–80 3.08 (2.97–3.18)  81+ 3.21 (3.04–3.37) Personal opinion of the performance triad  Very positive 2.55 (2.35–2.76) p = 0.205 2.78 (2.60–2.95) p = 0.457 2.47 (2.29–2.64) p = 0.044  Positive 2.64 (2.50–2.78) 2.88 (2.75–3.01) 2.67 (2.56–2.78)  Neutral 2.63 (2.50–2.76) 2.87 (2.75–3.00) 2.67 (2.56–2.77)  Negative 2.81 (2.62–3.00) 2.95 (2.78–3.11) 2.68 (2.51–2.84)  Very negative 2.79 (2.55–3.03) 2.96 (2.76–3.15) 2.89 (2.68–3.10) Frequency of supervisor adherence to triad recommendations  Always 2.59 (2.30–2.88) p < 0.001 2.48 (2.24–2.72) p < 0.001 2.47 (2.21–2.73) p = 0.001  Frequently 2.49 (2.35–2.63) 2.76 (2.63–2.88) 2.62 (2.51–2.73)  Occasionally 2.66 (2.54–2.78) 3.03 (2.92–3.14) 2.67 (2.59–2.76)  Never 3.00 (2.83–3.17) 3.28 (3.13–3.43) 2.93 (2.80–3.07) Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Gender Male 2.56 (2.45–2.67) p = 0.001 Female 2.81 (2.65–2.97) Training status  Staff 2.58 (2.48–2.68) p = 0.008 2.81 (2.71–2.92) p = 0.018  Residents 2.79 (2.62–2.96) 2.96 (2.81–3.11) Speciality type  Non-surgical 2.81 (2.70–2.93) p = 0.006  Surgical 2.96 (2.83–3.10) Hours worked per week (including home call)  20–40 2.40 (2.11–2.69) p < 0.001  41–60 2.87 (2.76–2.97)  61–80 3.08 (2.97–3.18)  81+ 3.21 (3.04–3.37) Personal opinion of the performance triad  Very positive 2.55 (2.35–2.76) p = 0.205 2.78 (2.60–2.95) p = 0.457 2.47 (2.29–2.64) p = 0.044  Positive 2.64 (2.50–2.78) 2.88 (2.75–3.01) 2.67 (2.56–2.78)  Neutral 2.63 (2.50–2.76) 2.87 (2.75–3.00) 2.67 (2.56–2.77)  Negative 2.81 (2.62–3.00) 2.95 (2.78–3.11) 2.68 (2.51–2.84)  Very negative 2.79 (2.55–3.03) 2.96 (2.76–3.15) 2.89 (2.68–3.10) Frequency of supervisor adherence to triad recommendations  Always 2.59 (2.30–2.88) p < 0.001 2.48 (2.24–2.72) p < 0.001 2.47 (2.21–2.73) p = 0.001  Frequently 2.49 (2.35–2.63) 2.76 (2.63–2.88) 2.62 (2.51–2.73)  Occasionally 2.66 (2.54–2.78) 3.03 (2.92–3.14) 2.67 (2.59–2.76)  Never 3.00 (2.83–3.17) 3.28 (3.13–3.43) 2.93 (2.80–3.07) Numbers in bold reflect an independent relationship with the outcome variable at the p < 0.05 level of significance based on the based on the GLM F-test statistic for goodness of fit. Only variables that were significant (p < 0.05) in bivariable analyses were included in each multivariable model. Table IV. Multivariable Analysis – Demographic Factors and Triad Behavior Among U.S. Army Physicians Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Gender Male 2.56 (2.45–2.67) p = 0.001 Female 2.81 (2.65–2.97) Training status  Staff 2.58 (2.48–2.68) p = 0.008 2.81 (2.71–2.92) p = 0.018  Residents 2.79 (2.62–2.96) 2.96 (2.81–3.11) Speciality type  Non-surgical 2.81 (2.70–2.93) p = 0.006  Surgical 2.96 (2.83–3.10) Hours worked per week (including home call)  20–40 2.40 (2.11–2.69) p < 0.001  41–60 2.87 (2.76–2.97)  61–80 3.08 (2.97–3.18)  81+ 3.21 (3.04–3.37) Personal opinion of the performance triad  Very positive 2.55 (2.35–2.76) p = 0.205 2.78 (2.60–2.95) p = 0.457 2.47 (2.29–2.64) p = 0.044  Positive 2.64 (2.50–2.78) 2.88 (2.75–3.01) 2.67 (2.56–2.78)  Neutral 2.63 (2.50–2.76) 2.87 (2.75–3.00) 2.67 (2.56–2.77)  Negative 2.81 (2.62–3.00) 2.95 (2.78–3.11) 2.68 (2.51–2.84)  Very negative 2.79 (2.55–3.03) 2.96 (2.76–3.15) 2.89 (2.68–3.10) Frequency of supervisor adherence to triad recommendations  Always 2.59 (2.30–2.88) p < 0.001 2.48 (2.24–2.72) p < 0.001 2.47 (2.21–2.73) p = 0.001  Frequently 2.49 (2.35–2.63) 2.76 (2.63–2.88) 2.62 (2.51–2.73)  Occasionally 2.66 (2.54–2.78) 3.03 (2.92–3.14) 2.67 (2.59–2.76)  Never 3.00 (2.83–3.17) 3.28 (3.13–3.43) 2.93 (2.80–3.07) Regular Aerobic and Resistance Exercise 1 (Always) – 4 (Never) Adequate Sleep 1 (Always) – 4 (Never) Fruits and Vegetable Consumption 1 (Always) – 4 (Never) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Estimated marginal mean (95% CI) Gender Male 2.56 (2.45–2.67) p = 0.001 Female 2.81 (2.65–2.97) Training status  Staff 2.58 (2.48–2.68) p = 0.008 2.81 (2.71–2.92) p = 0.018  Residents 2.79 (2.62–2.96) 2.96 (2.81–3.11) Speciality type  Non-surgical 2.81 (2.70–2.93) p = 0.006  Surgical 2.96 (2.83–3.10) Hours worked per week (including home call)  20–40 2.40 (2.11–2.69) p < 0.001  41–60 2.87 (2.76–2.97)  61–80 3.08 (2.97–3.18)  81+ 3.21 (3.04–3.37) Personal opinion of the performance triad  Very positive 2.55 (2.35–2.76) p = 0.205 2.78 (2.60–2.95) p = 0.457 2.47 (2.29–2.64) p = 0.044  Positive 2.64 (2.50–2.78) 2.88 (2.75–3.01) 2.67 (2.56–2.78)  Neutral 2.63 (2.50–2.76) 2.87 (2.75–3.00) 2.67 (2.56–2.77)  Negative 2.81 (2.62–3.00) 2.95 (2.78–3.11) 2.68 (2.51–2.84)  Very negative 2.79 (2.55–3.03) 2.96 (2.76–3.15) 2.89 (2.68–3.10) Frequency of supervisor adherence to triad recommendations  Always 2.59 (2.30–2.88) p < 0.001 2.48 (2.24–2.72) p < 0.001 2.47 (2.21–2.73) p = 0.001  Frequently 2.49 (2.35–2.63) 2.76 (2.63–2.88) 2.62 (2.51–2.73)  Occasionally 2.66 (2.54–2.78) 3.03 (2.92–3.14) 2.67 (2.59–2.76)  Never 3.00 (2.83–3.17) 3.28 (3.13–3.43) 2.93 (2.80–3.07) Numbers in bold reflect an independent relationship with the outcome variable at the p < 0.05 level of significance based on the based on the GLM F-test statistic for goodness of fit. Only variables that were significant (p < 0.05) in bivariable analyses were included in each multivariable model. Figure 1. View largeDownload slide Perceived supervisor behavior and self-reported triad behavior of U.S. Army physicians. Figure 1. View largeDownload slide Perceived supervisor behavior and self-reported triad behavior of U.S. Army physicians. DISCUSSION The results of this study suggest leadership, specifically the immediate level supervisor, has a strong association with healthy sleep, exercise, and nutrition behaviors of physicians. Belief in an immediate supervisor’s adherence with the P3 was consistently associated with an individual’s adherence with all three components of the P3. Organizational initiatives, similar to the P3, that involve executive level leadership have been able to impact physician burnout.7 Creating a culture that promotes physician wellness at the highest level is vital for any wellness initiative to succeed. However, lower level leadership is vital in cultivating this culture by serving as a role model and emphasizing the importance of positive wellness behaviors. One example from the Northwestern Family Medicine Residency noted the positive benefit of “green balance”, where the leadership of the inpatient physician team ensured at least 10 min of outside fresh air after rounds to rebalance the team.18 Simple directives such as this, from an immediate supervisor, can have an exponential impact on the wellness of the physician team. Exercise was the component of the P3 that showed the highest adherence in our survey of U.S. Army physicians. Participation in regular exercise has been shown to be associated with improved quality of life and decreased burnout in resident physicians.25 A unique aspect of military medicine is the requirement for frequent physical fitness assessments that applies to all members of the armed services. The U.S. Army Physical Fitness Test is required biannually. Failure of this test can lead to consequences such as disqualification from a medical training program, and disqualification from rank promotion. This incentive may contribute to exercise being the most adhered to component of the P3 for the U.S. Army physician. The results of our survey show better adherence to exercise for U.S. Army physicians compared with a report from a civilian physician survey.18 The previously mentioned incentives for passing the U.S. Army Physical Fitness Test, may contribute to this improved exercise adherence in U.S. Army physicians. The typical candidate for a position as an U.S. Army physician may have a higher emphasis on personal fitness that attracts him or her to military service. Sleep was the P3 component that showed the least adherence. Sleep deprivation has long been associated with the physician lifestyle. In the past, being able to function while sleep deprived was considered a positive trait amongst physicians. It was commonly felt that long work hours was part of the professional ethos of physicians to provide care for the patient, even at the expense of inadequate personal sleep.26 However, it is well known that sleep deprivation is a known cause for medical errors.27–31 Physician resident work hour restrictions were instituted primarily to address the sleep deprivation that was induced by the traditional residency work hours and call schedules.32 Despite the implementation of the resident work hour restrictions, among our sample of physicians only a minority of residents (and staff physicians) regularly achieve 8 h of sleep per day. The lack of regular sleep was especially prominent among surgical specialists both during and after completion of training. Our study did show less hours worked per week was associated with better adherence to getting 8 h of sleep per night. However, the question used in our survey may not be the most appropriate measure of adequate sleep. The National Sleep Foundation reports the average sleep requirement for adults is 7–9 h per night.33 Therefore, using a cutoff of 8 h may overestimate inadequate sleep. Sleep deprivation is not unique to the military physician, as evidenced by a study of licensed California physicians which reported 34% of respondents slept less than 6 h per day.34 Nutrition is often neglected by physicians during a busy workday. It is not uncommon for physicians to skip meals as catching up on work intrudes on planned meal times. The quality of diet may also be a casualty of the physician’s work environment. Hospital cafeteria food has been shown to have excessive caloric content.35 Oftentimes, lower quality but quickly available food is the choice when time is limited. In civilian institutions, catered meals are sometimes available, but are not typically of the best nutritional quality. Poor nutrition has been reported to affect physician’s physical, emotional and cognitive functioning.36 One study showed improving physician nutrition is associated with improved cognitive testing results.37 Therefore, proper nutrition is an important component in physician wellness and can impact patient care.38 Survey responses indicated Army physicians have less than ideal adherence to the nutrition component of the P3. Physician adherence to wellness behaviors may have an impact on clinical practice. Several studies have shown that physicians who practiced healthy exercise and nutrition habits were more likely to promote and counsel patients on wellness behaviors.13–15 Instilling wellness behaviors in physicians who are in residency training may have long lasting benefit in their own clinical practice. Practicing wellness behaviors should not be limited to physicians in training, as physicians at any stage of their career may benefit. There are several weaknesses in our study. Only 22% of the active duty Army physicians responded to the survey. The majority of these respondents were staff physicians, which may skew the results. Staff physicians are more likely to have flexibility in work hours, less work hours, and less in house call compared with resident physicians. Therefore, staff physicians may have more opportunity to adhere to healthy wellness behaviors. Another weakness of this study was our measures of physician wellness behaviors. The questions we used in this study were selected to measure components of P3 and were not validated measures of diet, sleep, or exercise. It is unclear how well these questions measure actual provider diet, sleep, and exercise. Future studies building on our results should use more robust and validated measures of these activities, such as dietary logs or actigraphy, to measure actual wellness behavior and physician fitness. Sleep, exercise and nutrition are all vital components of physical wellness behaviors. Although other areas of focus (e.g., social, spiritual, and emotional) are required for a comprehensive wellness program, improvements in the physical wellness behaviors have been shown to improve physician burnout. Initiatives similar to P3 should be considered integral parts of a comprehensive wellness program for physicians. CONCLUSION Overall, U.S. Army physicians are most adherent to the exercise tenet and least adherent to the sleep tenet of P3; consistent with the military culture. Work hours seem to affect wellness behaviors. Specifically, physicians who work fewer hours are more likely to report obtaining 8 h of sleep per day and exercising on a regular basis. Importantly, belief in supervisor adherence to P3 was associated with better adherence to P3, suggesting physician leadership has a positive effect on wellness behaviors. Specific programs to improve military physician adherence to the tenants of P3 should be considered. Future research should also include systemic changes in health system policies to motivate physician wellness behaviors, and correlating physician wellness with lifestyle counseling with patients. Prior Presentation The content of this manuscript has been presented orally at the BAMC research day at Brooke Army Medical Center on April 27, 2017. It was also presented in poster form at the 2017 ACGME annual education conference in Orlando, FL, USA on March 10, 2017, and the 31st Annual Meeting of the Associated Professional Sleep Societies conference in Boston, MA, USA on June 5, 2017. References 1 Maslach C , Jackson SE , Leiter MP : Maslach burnout inventory manual. 3rd ed. Consulting Psychologists; 1996 . 2 Rafferty JP , Lemkau JP , Purdy RR , et al. : Validity of the Maslach Burnout Inventory for family practice physicians . J Clin Psychol 1986 ; 42 : 488 – 92 . 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This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Military MedicineOxford University Press

Published: Apr 18, 2018

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