Compassion satisfaction, burnout, and secondary traumatic stress among full-time veterinarians in the United States (2016–2018)

Frederic B. Ouedraogo Veterinary Economics, Divisions, AVMA, Schaumburg, IL 60173.

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Sandra L. Lefebvre Publications, Divisions, AVMA, Schaumburg, IL 60173.

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Charlotte R. Hansen Veterinary Economics, Divisions, AVMA, Schaumburg, IL 60173.

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B. Wade Brorsen Department of Agricultural Economics, Ferguson College of Agriculture, Oklahoma State University, Stillwater, OK 74076.

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Abstract

OBJECTIVE

To determine prevalences of low compassion satisfaction (CS), high burnout (BO), and high secondary traumatic stress (STS) scores among full-time US veterinarians and estimate effects of selected demographic, employment-related, and education-related factors on those scores.

SAMPLE

5,020 full-time veterinarians who participated in the 2016, 2017, and 2018 AVMA Census of Veterinarians surveys.

PROCEDURES

Data were obtained from census surveys regarding demographic, employment-related, and education-related factors, and scores assigned to items from a professional quality-of-life instrument designed to measure CS and compassion fatigue (ie, BO and STS) were compared between and among various demographic and employment groups.

RESULTS

Overall, 35.5% of veterinarians were classified as having low CS scores, 50.2% as having high BO scores, and 58.9% as having high STS scores. Controlling for other variables, high educational debt was associated with low CS, high BO, and high STS scores. Veterinarians who spent ≥ 75% of their time working with dogs or cats had higher BO and STS scores than did those who spent < 25% of their time. Veterinarians with more experience and higher annual incomes had higher CS scores and lower BO and STS scores. Women had higher BO and STS scores than did men, but no gender differences were observed in CS scores.

CONCLUSIONS AND CLINICAL RELEVANCE

Several variables were identified that may put veterinarians at higher risk than others for compassion fatigue and low CS. These findings may be useful in the development of resources and targeted initiatives to support and defend veterinarian well-being.

Abstract

OBJECTIVE

To determine prevalences of low compassion satisfaction (CS), high burnout (BO), and high secondary traumatic stress (STS) scores among full-time US veterinarians and estimate effects of selected demographic, employment-related, and education-related factors on those scores.

SAMPLE

5,020 full-time veterinarians who participated in the 2016, 2017, and 2018 AVMA Census of Veterinarians surveys.

PROCEDURES

Data were obtained from census surveys regarding demographic, employment-related, and education-related factors, and scores assigned to items from a professional quality-of-life instrument designed to measure CS and compassion fatigue (ie, BO and STS) were compared between and among various demographic and employment groups.

RESULTS

Overall, 35.5% of veterinarians were classified as having low CS scores, 50.2% as having high BO scores, and 58.9% as having high STS scores. Controlling for other variables, high educational debt was associated with low CS, high BO, and high STS scores. Veterinarians who spent ≥ 75% of their time working with dogs or cats had higher BO and STS scores than did those who spent < 25% of their time. Veterinarians with more experience and higher annual incomes had higher CS scores and lower BO and STS scores. Women had higher BO and STS scores than did men, but no gender differences were observed in CS scores.

CONCLUSIONS AND CLINICAL RELEVANCE

Several variables were identified that may put veterinarians at higher risk than others for compassion fatigue and low CS. These findings may be useful in the development of resources and targeted initiatives to support and defend veterinarian well-being.

Introduction

The National Alliance on Mental Illness estimates that 1 in 5 adults in the United States experiences mental illness and 1 in 25 experiences serious mental illness.1 In comparison, a 2014 survey2 of US veterinarians revealed that 1 in 11 veterinarians had scores consistent with serious psychological distress and 1 in 6 had experienced suicidal ideation since graduation from veterinary school. Other studies3,4,5,6,7,8 have shown that veterinarians are at higher risk than the general population for suicide, suicide attempts, and suicidal ideation, suggesting that perhaps elements of veterinary work in addition to other factors may threaten veterinarians’ mental health.

Although research concerning the psychological well-being of the veterinarian subset of health-care professionals has increased over the past 2 decades, much remains to be learned about the prevalence of various mental health outcomes in veterinarians, modifiable factors that may contribute to or detract from veterinarians’ well-being, and static factors that might render certain groups more at risk of adverse mental health outcomes than others.

Veterinarians, like other health-care providers, may experience both enhancements and challenges to their professional quality of life through their relationships with patients and, when relevant, their patients’ primary caregivers (eg, pet owners or parents). Stamm9 defined professional quality of life as comprised of 2 components: CS and compassion fatigue. Professional quality of life in this context is proposed to be influenced by the work environment, helped person's environment, and caregiver's environment. Compassion satisfaction, a measure of well-being, is defined as the pleasure that professional caregivers derive from being able to help their patients and represents the positive side of caregiving.9 Veterinarians, like other professional caregivers, may feel relief or a sense of success after an animal for which they have been caring recovers from its clinical condition, believing they can make a difference.10 Other factors that might affect CS include earnings, employee benefits, recognition of work well-done, personal and professional ethics and values, work environment and conditions, and work-life balance.9,10,11,12,13,14

The negative side of caregiving, compassion fatigue, is comprised of 2 components: BO and STS.9 Burnout in this context refers to “feelings of hopelessness and difficulties in dealing with work or in doing your job effectively,” which are typically gradual in onset.9 Professional caregivers with BO may experience exhaustion, frustration, anger, and depression.9 Other symptoms of BO include cynicism, declining productivity, and lack of focus.15

Secondary traumatic stress, on the other hand, is “a negative feeling driven by fear and work-related trauma” and can arise from prolonged exposure to others’ traumatic events,9 such as caring for and euthanizing suffering animals and providing emotional support and comfort to animal owners and their families. Symptoms of STS are similar to those of posttraumatic stress disorder and include difficulty concentrating, irritability, sleep disturbances, intrusive thoughts, and traumatic memories.16 Unlike BO, these symptoms are usually rapid in onset. Although BO and STS both involve negative effects, BO as defined does not address fear, whereas STS does.9

A 2017 study8 explored, among other measures of mental health, prevalences of CS, BO, and STS, as defined by Stamm,9 and gender differences in mean scores for these variables among Canadian veterinarians (n = 1,403). Findings of that study8 indicate overall high prevalences of high BO (41.7%) and STS (65.4%) scores, as classified on the basis of score cutpoints suggested by De La Rosa et al,17 with female veterinarians having significantly higher mean BO and STS scores and higher prevalences of BO and STS than male veterinarians. Another study18 examined distributions of CS, BO, and STS among Australian veterinarians and people in other animal-related jobs (n = 229), revealing that veterinarians had the highest prevalences of high scores for BO (34.8%) and STS (31.9%). Although no gender differences in BO were identified in that study,18 women were again more likely than men to have high scores for STS.

Various factors other than gender, including but not limited to personal factors (eg, perfectionism,19 empathy,10 or resilience20), job-related factors (eg, on-call status or workload14,15,21), and environmental factors (eg, workplace culture14,21), may influence CS, BO, and STS among veterinarians. For example, US death record data from 1979 through 2015 indicate that 79% (313/398) of veterinarians who died by suicide during this period were in clinical positions and that 75% (226/300) of veterinarians in clinical positions who died by suicide worked with companion animals.5 It follows that working with companion animals and their owners may put veterinarians at risk of severe mental distress or compassion fatigue, which some consider “the cost of caring.”10 On the other hand, a greater number of years since graduation was associated with fewer signs of distress, anxiety, and depression in Australian veterinarians (n = 2,125),22 suggesting experience might help to protect against BO and STS. Work-life balance and being paid fairly were among the variables associated with the highest levels of job satisfaction in a 2019 survey23 of randomly selected working US veterinarians (n = 2,874), and these variables may also be associated with CS. In contrast, high student debt was most strongly associated with serious psychological distress23 and therefore might influence CS, BO, and STS.

The purpose of the study reported here was to determine the prevalence of low CS, high BO, and high STS scores among full-time veterinarians participating in the AVMA Census of Veterinarians in 2016, 2017, and 2018 and estimate the effects of selected demographic, employment-related, and education-related factors on these scores. Our hypotheses were that female gender, recent (since 2010) graduation from veterinary school, and higher educational debt would be associated with lower CS and higher BO and STS scores, whereas higher total annual income and spending less time working with cats and dogs would be associated with higher CS and lower BO and STS scores, controlling for other variables.

Materials and Methods

Data source

Each year during the study period (2016 to 2018), an electronic survey—the AVMA Census of Veterinarians—was conducted by the Survey Research Laboratory of the University of Illinois at Chicago. This survey was distributed via email to veterinarians randomly selected from the AVMA membership list. It was designed to gather demographic, employment, and educational information and other data that might be associated with these variables. To assess the well-being of veterinarians, the survey also included items from the most recent version of the ProQOL (ie, the ProQOL5). This instrument was designed and validated to gauge how caring for others affects the quality of life of professional caregivers9 and has been used for this purpose in both human18 and veterinary medicine.8,19

Data used for the present study were obtained from surveys conducted in 2016 (distributed on May 4 and closed on July 6, 2016), 2017 (distributed on January 30 and closed on April 17, 2017), and 2018 (distributed on February 22 and closed on May 7, 2018). Respective response rates were 11.8% (2,545 responses), 17.4% (2,780 responses), and 18.9% (3,027 responses). Only surveys with complete responses in the ProQOL5 portion were included in the present study. Only veterinarians who reported working full-time (survey options: full-time or part-time) and graduated at least 2 years prior to the survey were included in the analysis. Part-time veterinarians were excluded to avoid the influence of other activities outside veterinary work, such as leisure or volunteer engagements, that might influence their well-being. New graduates were excluded to avoid the potential influence (bias) on the results of veterinarians who were still learning and adapting to their new roles.

ProQOL5

The ProQOL5 consisted of 30 statements about positive and negative experiences in relation to an individual caregiver's work environment and conditions and asked the individual to select the number on a 5-point Likert scale that reflected the frequency of each experience (1 = never, 2 = rarely, 3 = sometimes, 4 = often, and 5 = very often) in the past 30 days.8 Ten statements pertained to CS; the remainder pertained to the 2 components of compassion fatigue: BO (10 statements) and STS (10 statements). None of these statements were modified to be specific to veterinarians or to their relationships with clients and patients. With scores for the 10 statements pertaining to each component summed as suggested by Stamm,9 the minimum and maximum possible scores for each component were 10 and 50, respectively.

Statistical analysis

Survey data used for the present study consisted of gender (male [referent group] or female), year of graduation from veterinary school (used as a proxy for experience level; categorized as 2010 to 2 years prior to the survey [2014, 2015, or 2016; referent group], 2005 to 2009, 2000 to 2004, 1995 to 1999, 1990 to 1994, 1985 to 1989, 1980 to 1984, 1975 to 1979, and 1970 to 1974), type of veterinary employment, and percentage of time spent working with cats and dogs in the previous calendar year (categorized as < 25%, 25% to 74.9%, and ≥ 75% [referent group]). Also included were data regarding educational debt at graduation (categorized as < $25,000 [referent group], $25,000 to $99,999, $100,000 to $199,999, and ≥ $200,000), total annual income in the previous calendar year (categorized as $40,000 to $74,999 [referent group], $75,000 to $99,999, $100,000 to $124,999, $125,000 to $149,999, $150,000 to $174,999, $175,000 to $199,999, $200,000 to $224,999, $225,000 to $274,999, and $275,000 to $500,000), number of young children in the household in various age categories (< 2 years, 2 to 3 years, and 4 to 5 years), and zip code of the primary workplace (categorized by zip code regions). Age categories for children were chosen because initial modeling attempts revealed that when the data were grouped differently, categories above the toddler category (ie, 1.1 to 3 years) were not significant. Statistical softwarea was used for all analyses.

To gauge the representativeness of the respondents with respect to the general population of veterinarians in the United States, distributions of respondents by gender, year of graduation from veterinary school, type of veterinary employment, and workplace zip code region were compared with distributions for the US veterinarian population in 2018, as determined from the AVMA membership database, which included both AVMA members and nonmembers.

To determine the prevalence of low CS, high BO, and high STS scores, summed scores for the 3 components of the ProQOL5 were classified as low, moderate, or high as follows: CS, low if ≤ 33, moderate if 34 to 41, and high if ≥ 42; BO, low if ≤ 19, moderate if 20 to 26, and high if ≥ 27; and STS, low if ≤ 13, moderate if 14 to 20, and high if ≥ 21.17 These categories were based on cutpoints representing the 25th and 75th percentiles of total scores for 5,612 professional caregivers representing a variety of demographics17 and were not intended for diagnostic purposes. Because Stamm9 noted that the ProQOL5 is more sensitive when continuous scores (vs cutpoint scores) are used, actual CS, BO, and STS scores were also used in data analyses.

Ordinary least squares regression was used to determine whether mean values for total CS, BO, and STS scores (dependent variables) differed among respondent groups, adjusting for covariates. Gender, total annual income category, educational debt category, year of graduation category, time spent working with cats and dogs category, number of children by age category, and time-related changes over the 3-year survey period (ie, a time trend variable) were all included in the model as independent variables. The t test was used to conduct pairwise comparisons when the variable had 2 categories. For categories with 3 or more groups or levels, the Bonferroni pairwise comparison and Tukey honestly significant difference tests were conducted.

Results

Respondents

Overall, 8,352 veterinarians responded to the AVMA Annual Census of Veterinarians survey during the 3-year study period. After removal of respondents with incomplete responses to the ProQOL5 portion of the surveys, 1,460, 1,665, and 1,895 respondents remained to represent 2016, 2017, and 2018, respectively. In total, 5,020 (60.1%) respondents were included in the study. Because individuals who received each year's survey were randomly selected and participants were anonymous, it is possible that an individual may have participated in > 1 year's survey and, thus, been represented more than once in the respondent total.

General characteristics

Characteristics of the included veterinarians were summarized (Table 1). Women (n = 3,641) outnumbered men (1,369) in all 3 survey years, with the percentage of women ranging from 69.5% of veterinarians in 2016 to 74.9% in 2018. Ten (0.2%) veterinarians did not indicate their gender. The most commonly represented workplace zip code regions were regions 9 (zip codes 90000 to 99999) and 2 (20000 to 29999). A total of 663 veterinarians had children < 2 years old, 535 had children 2 to 3 years old, and 353 had children 4 to 5 years old.

Table 1

Characteristics of full-time US veterinarians who provided complete survey responses to the ProQOL portion of the 2016, 2017, and 2018 AVMA Census of Veterinarians.

Survey respondents (%)
Characteristic 2016 (n = 1,460) 2017 (n = 1,665) 2018 (n = 1,895) US veterinarian population in 2018* (%)
Gender
 Female 69.5 72.5 74.9 61.7
 Male 30.3 27.3 24.9 38.2
 No response 0.2 0.2 0.2 0.1
Year of graduation from veterinary school
 2010–2 years before survey 46.1 46.5 62.8 22.6
 2005–2009 16.1 17.7 2.4 13.9
 2000–2004 11.2 11.1 14.1 12.8
 1995–1999 4.0 5.2 2.7 11.6
 1990–1994 11.4 9.1 12.5 10.6
 1985–1989 4.0 3.7 2.8 10.9
 1980–1984 3.3 4.3 1.6 9.6
 1975–1979 2.3 1.8 0.8 6.3
 1970–1974 1.6 0.6 0.2 1.7
Type of veterinary employment
 Food animal exclusive practice 1.2 1.9 1.3 1.4
 Food animal predominant practice 1.2 1.6 1.9 3.4
 Mixed-animal practice 5.8 6.5 6.6 4.5
 Companion animal predominant practice 11.5 13.0 10.5 6.9
 Companion animal exclusive practice 56.9 58.4 61.0 53.0
 Equine practice 4.4 2.8 3.8 4.5
 Public sector 4.8 3.9 3.5 4.1
 Industry or commercial organization 8.0 6.1 5.8 3.9
 College or university 3.4 3.3 2.4 7.5
 Not-for-profit organization 2.7 2.4 3.3 1.1
Percentage of time spent with cats and dogs
 < 25 29.1 31.9 32.6
 25–74.9 4.7 5.2 5.7
 ≥ 75 66.2 62.9 61.7
Educational debt at graduation ($)
 < 25,000 23.6 21.8 20.4
 25,000–99,999 28.1 28.1 26.4
 100,000–199,999 30.9 30.4 27.0
 ≥ 200,000 17.4 19.8 26.1
Total annual income ($)
 40,000–74,999 24.9 23.5 21.7
 75,000–99,999 30.6 30.6 33.1
 100,000–124,999 18.5 18.3 19.3
 125,000–149,999 9.0 8.8 9.0
 150,000–174,999 4.5 6.2 6.3
 175,000–199,999 3.3 2.8 3.0
 200,000–224,999 3.4 2.6 2.4
 225,000–249,999 1.5 1.5 0.9
 250,000–274,999 0.6 1.4 1.1
 275,000–500,000 3.7 4.4 3.3
Workplace zip code region
 0 (00000–09999) 7.5 8.2 8.9 7.9
 1 (10000–19999) 8.6 8.5 8.3 8.8
 2 (20000–29999) 12.5 12.1 12.2 10.9
 3 (30000–39999) 12.4 11.4 10.6 13.7
 4 (40000–49999) 10.4 11.5 9.1 9.7
 5 (50000–59999) 7.9 9.2 8.4 7.8
 6 (60000–69999) 9.8 9.3 7.6 7.8
 7 (70000–79999) 9.9 9.1 11.5 10.4
 8 (80000–89999) 7.5 8.9 9.4 8.1
 9 (90000–99999) 13.5 11.8 13.9 15.0

Data obtained from the AVMA membership database, which consisted of AVMA members and nonmembers.

The public sector included federal, state, and local government.

Regions can be interpreted as follows: 0 = Connecticut, Massachusetts, Maine, New Hampshire, New Jersey, Rhode Island, and Vermont; 1 = Delaware, New York, and Pennsylvania; 2 = District of Columbia, Maryland, North Carolina, South Carolina, Virginia, and West Virginia; 3 = Alabama, Florida, Georgia, Mississippi, and Tennessee; 4 = Indiana, Kentucky, Michigan, and Ohio; 5 = Iowa, Minnesota, Montana, North Dakota, South Dakota, and Wisconsin; 6 = Illinois, Kansas, Missouri, and Nebraska; 7 = Arkansas, Louisiana, Oklahoma, and Texas; 8 = Arizona, Colorado, Idaho, New Mexico, Nevada, Utah, and Wyoming; and 9 = Alaska, American Samoa, California, Hawaii, Oregon, and Washington.

— = Not available.

Percentages for type of employment for the US veterinarian population in 2018 do not sum to 100% owing to other responses allowed in that assessment that were not assessed in the present study.

With respect to the year of graduation from veterinary school, recent graduates (2010 to 2014, 2010 to 2015, or 2010 to 2016, depending on the survey year) were the most common group for all 3 years, and the percentage of that group ranged from 46.1% of all respondents in 2016 to 62.8% in 2018 (Table 1). Most veterinarians (56.9% in 2016 to 61.0% in 2018) were exclusively in companion animal practice. Most veterinarians (from 66.2% in 2016 to 61.7% in 2018) spent 75% to 100% of their time working with cats, dogs, or both. For all 3 years, the most common category of educational debt at graduation was $100,000 to $199,000. More than half of veterinarians in each year had a total annual income < $100,000.

No substantial deviation was evident in distributions of respondent characteristics for all 3 years from those for the US veterinarian population in 2018 (as determined from the AVMA membership database, which included both AVMA members and nonmembers), except that recent graduates, although still being the most common group, comprised only 22.6% of the US veterinarian population (Table 1). Industry veterinarians were slightly overrepresented in the study relative to the US veterinarian population, whereas veterinarians in colleges and universities were slightly underrepresented.

CS, BO, and STS

Prevalences of low, moderate, and high CS, BO, and STS scores among survey respondents were summarized (Table 2). The prevalence of a low CS score (ie, a score ≤ 33) increased from 32.4% in 2016 to 38.1% in 2018, whereas the prevalences of high BO (ie, a score ≥ 27) and STS (ie, a score ≥ 21) scores fluctuated across the years. Overall, mean ± SD (range) total scores for the CS, BO, and STS items in the survey for all 3 years were 36.1 ± 6.8 (10 to 50), 26.7 ± 6.3 (10 to 46), and 22.6 ± 6.6 (10 to 48).

Table 2

Number (%) of the veterinarians of Table 1 with low, moderate, and high CS, BO, and STS scores.

Variable 2016 (n = 1,460) 2017 (n = 1,665) 2018 (n = 1,895) Overall (n = 5,020)
CS
Low 473 (32.4) 588 (35.3) 722 (38.1) 1,783 (35.5)
Moderate 648 (44.3) 727 (43.7) 781 (41.2) 2,156 (42.9)
High 339 (23.2) 350 (21.0) 392 (20.7) 1,081 (21.5)
BO
Low 178 (12.3) 295 (17.7) 198 (10.5) 671 (13.4)
Moderate 567 (38.8) 619 (37.2) 645 (34.0) 1,831 (36.5)
High 715 (49.0) 751 (45.1) 1,052 (55.5) 2,518 (50.2)
STS
Low 69 (4.7) 127 (7.6) 126 (6.6) 322 (6.4)
Moderate 472 (32.3) 636 (38.2) 634 (33.5) 1,742 (34.7)
High 919 (62.9) 902 (54.2) 1135 (59.9) 2,956 (58.9)

Total CS, BO, and STS scores were classified as low, moderate, or high as follows: CS, low if ≤ 33, moderate if 34 to 41, and high if ≥ 42; BO, low if ≤ 19, moderate if 20 to 26, and high if ≥ 27; and STS, low if ≤ 13, moderate if 14 to 20, and high if ≥ 21.12 Low CS scores and high BO and STS scores were considered undesirable.

Impact of time—Results of multivariable ANOVA indicated that year of survey had a significant impact on mean scores, but this effect was relatively small. From 2016 to 2018, the mean CS score decreased by 0.28 points (P = 0.02), mean BO score increased by 0.33 points (P = 0.002), and mean STS score decreased by 0.44 points (P < 0.001).

Impact of experience—Mean CS scores increased and mean BO and STS scores decreased as the number of years since graduation from veterinary college increased (Table 3). The greatest difference between mean scores for veterinarians who graduated in 2010 or later and mean scores for those who graduated earlier was observed for veterinarians who graduated between 1970 and 1974 versus veterinarians who graduated in 2010 or later (mean difference, 5.42, −4.69, and −2.37 points for CS, BO, and STS scores, respectively).

Table 3

Summary data* for total CS, BO, and STS scores for the veterinarians of Table 1, without controlling for other factors.

CS BO STS
Variable Mean (range) P value Mean (range) P value Mean (range) P value
Gender
 Female (n = 3,086) 35.8 (10–50) 0.57 27.4 (10–46) < 0.001 23.3 (10–48) < 0.001
 Male (n = 1,157) 37.1 (11–50) 24.7 (10–45) 20.3 (10–46)
Year of graduation from veterinary school
 2010–2 years before survey (n = 2,637) 35.3 (10–50) 27.7 (10–46) 23.7 (10–48)
 2005–2009 (n = 576) 35.2 (11–50) 0.01 27.3 (13–46) 0.04 22.8 (10–43) 0.38
 2000–2004 (n = 615) 36.2 (17–50) 0.54 26.4 (13–46) 0.35 21.8 (10–45) 0.02
 1995–1999 (n = 198) 36.9 (18–50) 0.15 26.3 (11–42) 0.72 22.1 (12–41) 0.56
 1990–1994 (n = 555) 38.2 (19–50) < 0.001 24.8 (10–42) < 0.001 20.6 (10–41) < 0.001
 1985–1989 (n = 173) 38.2 (19–50) 0.001 23.9 (12–41) < 0.001 19.8 (10–38) < 0.001
 1980–1984 (n = 150) 39.9 (17–50) < 0.001 22.4 (10–41) < 0.001 19.0 (10–37) < 0.001
 1975–1979 (n = 80) 39.3 (23–50) 0.004 21.7 (10–36) < 0.001 18.9 (11–35) 0.01
 1970–1974 (n = 36) 42.3 (33–50) < 0.001 20.4 (10–36) < 0.001 19.1 (10–31) 0.03
Educational debt at graduation ($)
 < 25,000 (n = 1,090) 37.7 (11–50) 24.7 (10–46) 20.9 (10–45)
 25,000–99,999 (n = 1,373) 36.5 (10–50) 0.011 26.1 (10–46) 0.003 21.7 (10–46) 0.10
 100,000–199,999 (n = 1,464) 35.4 (17–50) 0.002 27.4 (12–46) < 0.001 23.3 (10–46) < 0.001
 ≥ 200,000 (n = 1,074) 35.1 (13–50) 0.006 28.4 (10–46) < 0.001 24.5 (10–48) < 0.001
Percentage of time working with cats and dogs
 < 25 (n = 1,574) 36.1 (14–50) 0.25 26.2 (10–46) 0.048 21.6 (10–46) < 0.001
 25–74.9 (n = 263) 36.6 (13–50) 0.06 26.7 (12–45) 0.22 22.8 (11–44) 0.14
 ≥ 75 (n = 3,183) 36.1 (10–50) 26.9 (10–46) 23.1 (10–48)
Total annual income ($)
 40,000–74,999 (n = 1,166) 35.4 (12–50) 27.5 (12–46) 23.9 (10–47)
 75,000–99,999 (n = 1,583) 35.2 (14–50) 0.27 27.4 (10–46) 0.70 23.3 (10–47) 0.10
 100,000–124,999 (n = 941) 36.1 (10–50) 0.12 26.8 (10–45) 0.57 22.4 (10–48) 0.008
 125,000–149,999 (n = 447) 36.8 (17–50) 0.04 26.3 (10–46) 0.64 21.8 (10–46) 0.02
 150,000–174,999 (n = 290) 37.7 (18–50) < 0.001 25.1 (10–42) 0.004 20.9 (10–44) < 0.001
 175,000–199,999 (n = 150) 38.1 (21–50) 0.004 24.6 (12–46) 0.03 21.2 (11–45) 0.16
 200,000–224,999 (n = 137) 38.7 (24–50) 0.002 24.2 (13–38) 0.06 20.1 (10–33) 0.01
 225,000–249,999 (n = 64) 39.4 (26–50) 0.003 23.7 (12–36) 0.04 19.7 (10–35) 0.01
 250,000–274,999 (n = 52) 39.4 (28–50) 0.008 23.0 (10–40) 0.01 18.7 (11–30) 0.003
 275,000–500,000 (n = 190) 39.2 (20–50) < 0.001 23.2 (10–41) 0.001 19.6 (11–38) 0.002

Mean and median values were identical or nearly identical for all variables. Range is reported to show the breadth of responses.

— = Not applicable (referent group).

Number of respondents may not total 5,020 owing to unanswered questions for some veterinarians.

Impact of educational debt—Mean CS scores decreased with increasing educational debt at graduation, whereas mean BO and STS scores increased. Pairwise tests revealed that, compared with mean CS scores for veterinarians with an educational debt < $25,000 (the referent group), mean CS scores for veterinarians with educational debt from $25,000 to $99,999, from $100,000 to $199,999, or ≥ $200,000 were significantly lower (Figure 1; Table 3). On the other hand, compared with mean scores for veterinarians in the referent group, mean BO scores for veterinarians in each of the 3 other debt categories were significantly higher, as were mean STS scores for veterinarians with educational debt from $100,000 to $199,999 (approx 1 point higher) or ≥ $200,000 (approx 2 points higher).

Figure 1
Figure 1

Mean scores for CS, BO, and STS minus mean scores for the referent group (ie, respondents with educational debt at graduation < $25,000) for full-time US veterinarians who provided complete survey responses (n = 5,020) to the ProQOL portion of the 2016, 2017, and 2018 AVMA Census of Veterinarians and had educational debt at graduation between $25,000 and $99,999 (white bars), between $100,000 and $199,999 (gray bars), and ≥ $200,000 (black bars), after controlling for other variables. *Value was significantly (P < 0.05) different from 0.

Citation: Journal of the American Veterinary Medical Association 258, 11; 10.2460/javma.258.11.1259

Impact of working with cats and dogs—Veterinarians who spent < 25% of their time working with dogs and cats had a significantly lower mean BO score and significantly lower mean STS score than did the referent group (Figure 2; Table 3). No other associations with this variable were identified.

Figure 2
Figure 2

Mean scores for CS, BO, and STS minus mean scores for the referent group (ie, respondents who spent ≥ 75% of their time) for respondents in Figure 1 who spent < 25% of their time working with cats, dogs, or both (black bars) or 25% to 74.9% of their time working with cats, dogs, or both (white bars), after controlling for other variables. See Figure 1 for remainder of key.

Citation: Journal of the American Veterinary Medical Association 258, 11; 10.2460/javma.258.11.1259

Impact of income—Overall, mean CS scores increased as total annual income increased. Pairwise tests revealed no significant difference in mean CS scores between veterinarians with annual incomes between $40,000 and $74,999 (the referent group) and those who earned between $75,000 and $99,999 or between $100,000 and $124,999. However, significant differences from the referent group were observed for all income categories ≥ $125,000, with differences peaking at approximately 2.6 points for veterinarians earning between $224,000 and $249,000 or between $250,000 and $274,999 (Figure 3; Table 3).

Figure 3
Figure 3

Mean CS scores minus mean score for the referent group (ie, respondents with total annual income < $75,000) for respondents in Figure 1 grouped on the basis of total annual income, after controlling for other variables. See Figure 1 for remainder of key.

Citation: Journal of the American Veterinary Medical Association 258, 11; 10.2460/javma.258.11.1259

On the other hand, mean BO and STS scores decreased with increasing income category (Figures 4 and 5; Table 3). Significantly lower BO scores were identified for veterinarians in higher income categories, beginning at $150,000, with mean differences from referent group values ranging from −1.17 to −2.21 points. For STS, mean differences from referent group values ranged from −0.75 points for veterinarians earning between $100,00 and $124,999 to −2.66 points for veterinarians earning between $250,000 and $274,999.

Figure 4
Figure 4

Mean BO scores minus mean score for the referent group (ie, respondents with total annual income < $75,000) for respondents in Figure 1 grouped on the basis of total annual income, after controlling for other variables. See Figure 1 for remainder of key.

Citation: Journal of the American Veterinary Medical Association 258, 11; 10.2460/javma.258.11.1259

Figure 5
Figure 5

Mean STS scores minus mean score for the referent group (ie, respondents with total annual income < $75,000) for respondents in Figure 1 grouped on the basis of total annual income, after controlling for other variables. See Figure 1 for remainder of key.

Citation: Journal of the American Veterinary Medical Association 258, 11; 10.2460/javma.258.11.1259

Impact of gender—No significant difference in mean CS score was identified between men and women (Figure 6; Table 3). However, mean BO and STS scores were significantly higher for women than for men (mean difference in scores, 1.27 and 1.72, respectively).

Figure 6
Figure 6

Mean CS, BO, and STS scores for men (white bars; n = 1,157) and women (black bars; 3,086) in Figure 1, after controlling for other factors. *Significantly (P < 0.05) different from the value for men.

Citation: Journal of the American Veterinary Medical Association 258, 11; 10.2460/javma.258.11.1259

Impact of number of children—As the number of children in each of the various age categories (< 2 years, 2 to 3 years, and 4 to 5 years) increased by 1, mean CS score increased by 0.59, 0.87, and 0.96 points (P ≤ 0.01), respectively. On the other hand, mean BO score decreased by 1.10, 0.81, and 1.24 points (P ≤ 0.002), respectively, and mean STS score decreased by 1.05 (P < 0.001), 0.32 (P = 0.23), and 0.76 (P = 0.03) points, respectively, with every additional child in each of the age categories.

Discussion

The present study yielded several important findings regarding CS, BO, and STS among full-time US veterinarians, as measured with the ProQOL5. As hypothesized, recent graduation from veterinary school (ie, from 2010 to 2014, 2010 to 2015, and 2010 to 2016 for the 2016, 2017, and 2018 surveys, respectively) and higher educational debt were independently associated with lower CS scores and higher BO and STS scores, whereas higher total annual income was associated with higher CS and lower BO and STS scores. Spending a low (< 25%) versus high (≥ 75%) percentage of time working with cats and dogs was associated with lower BO and STS scores, but not CS scores, and being female versus male was associated with higher BO and STS scores but not CS scores.

Overall prevalences of low CS and high BO and STS scores for all 3 survey years were 35.5%, 50.2%, and 58.9%, respectively. These values were higher than prevalences of low CS and high BO scores but lower than the prevalence of high STS scores reported for Canadian veterinarians (28.1%, 41.7%, and 65.4%, respectively).8 The importance of these differences is unclear, particularly given that the statements in the Canadian survey were modified to be more specific to veterinarians and such changes may have been interpreted differently by respondents. In addition, the distribution of veterinarians by year of graduation was not reported for the Canadian survey, and that distribution may have differed from the distribution in the present study. Other factors that should be considered include differences between countries in employment laws (eg, maximum work hours and paid vacation or sick leave), work conditions, healthcare access, salaries, and veterinary school tuition and fees.

To put these findings for US and Canadian veterinarians into perspective, prevalences of low CS and high BO and STS scores among pediatric health-care providers (n = 274) at a US children's hospital (who might be considered similar to veterinarians in the need to rely on patients’ caretakers for information necessary for decision-making and other aspects) were 25%, 31%, and 27%, respectively.24 Similarly, in a study25 of US pediatric nurses (n = 239), prevalences of low CS, high BO, and high STS scores were 28%, 29%, and 27%, respectively. Direct comparisons of our findings with those for other professional caregiver groups are precluded because of different or unclear cutpoints used to define low CS, high BO, and high STS; use of different versions of the ProQOL instrument; or lack of reporting of these data. Although the high prevalences of these variables among veterinarians may appear disconcerting, Stamm9 emphasized that the ProQOL5 is not intended to be used for diagnostic purposes but, rather, for screening purposes, and our results should be interpreted with this in mind.

Mean scores for CS, BO, and STS over all 3 years for veterinarians in the present study were 36.1, 26.7, and 22.6, respectively, which fell within normative ranges representing moderate CS (34 to 41), moderate to high BO (20 to 26 and 27 to 50, respectively), and high STS (21 to 50) scores12 and differed slightly from mean scores reported for Canadian veterinarians (37.5, 25.2, and 23.5, respectively).8 Such score patterns are consistent with previous observations that, for professional caregivers in general, CS scores are generally higher than BO scores and BO scores are generally higher than STS scores.9 Compared with normative means for other types of professional caregivers (37.7, 16.7, and 22.8, respectively17), these data for US and Canadian veterinarians suggest that, on average, the well-being of veterinarians may be slightly lower. Nevertheless, although the observed similarities in demographic, educational, and employment characteristics between survey respondents and the US veterinarian population in 2018 suggested our findings were generalizable to the general population of US veterinarians, recent graduates were overrepresented in the present study by a factor of 2 to 3 times their representation in the US veterinarian population. The impact of this overrepresentation on overall prevalence and mean values was likely relevant, and our results must be considered with this in mind. Because year of graduation was controlled for in the multivariable model, the overrepresentation of recent graduates was also controlled for in the comparisons of mean scores and was, therefore, less relevant.

We had hypothesized that the more experience that veterinarians had (inferred from the year of graduation from veterinary school), the less susceptible they would be to BO and STS. In other words, we presumed that recent graduates would have higher BO and lower CS scores owing to the challenges associated with starting a new career, such as servicing educational debt, coping with a new professional environment, and learning to balance professional and family life. These notions were supported by our findings. Indeed, of all variables evaluated in the study, year of graduation category corresponded with the greatest observed differences in mean scores, whereby veterinarians who graduated between 1970 and 1974 had, on average, a CS score approximately 5 points higher and a BO score approximately 5 points lower than did veterinarians who graduated in 2010 or later, even though new graduates (ie, those who graduated < 2 years prior to the survey) were excluded from the study. Our findings aligned with those reported for a survey22 of Australian veterinarians, wherein the longer respondents had been in their current job and the longer since graduation from veterinary school, the less likely they were to have responses indicative of distress, anxiety, or depression. Similar results have been reported for female veterinarians in Australia, whereby recent graduates reported higher levels of stress and anxiety than did their more experienced counterparts.26

One may presume that the more years of experience a veterinarian has, the more resilient they become. Indeed, resilience, considered to involve “the capacity of an individual to harness personal and contextual resources to navigate through challenges,” has been suggested to be an under-researched yet potentially important influencer of professional engagement, satisfaction, and well-being beyond traditionally researched outcomes such as stress and other mental health measures.20 However, in a recent study,27 age was not associated with resilience in Canadian veterinarians after controlling for other factors. In all, it seems likely that other aspects yet to be evaluated, such as cohort effects, that come with years of experience (or years since graduation) explain the influence of experience on CS, BO, and STS. We also recognize that veterinarians who left the veterinary profession because of BO, STS, or low CS would likely not have been included in the Census of Veterinarians surveys, potentially biasing results toward a more optimistic picture for more experienced veterinarians. This possibility warrants further investigation.

Also as hypothesized, higher educational debt at graduation had an adverse impact on all evaluated measures of well-being, with an almost 2-point increase in mean BO and STS scores observed for veterinarians owing ≥ $200,000 relative to those owing < $25,000. Educational debt is reported to be one of the most important issues for veterinarians, threatening both financial and mental health.28 Despite the advantages of a veterinary education, graduating with high debt could impact employment decisions,29,30 such as choosing a job on the basis of salary or opportunities for extra paid hours rather than alignment with one's aspirations, personal needs, or beliefs. Servicing educational debt could be challenging for recent graduates, particularly veterinarians receiving low starting salaries. In 2018, 26.1% of respondents reported an annual income < $75,000, and financial challenges have been shown to be associated with low well-being in other surveys.23 High debt and low income may even jeopardize the health of the veterinary profession given that 21.3% (611/2,874) of respondents in a 2019 survey reported high debt as a reason they would not recommend the veterinary profession and 19.1% (550/2,874) reported low pay as a reason.23

One of the premises explored in the study reported here was that the greater the percentage of time a veterinarian spent caring for companion animals such as dogs or cats and, by extension, engaging with their owners, the greater the opportunity would be for exposure to situations that might adversely impact their well-being, such as challenging interpersonal situations, ethical and moral dilemmas, euthanasia, unexpected outcomes, and fear of complaints or mistakes.3,4,31,32 The human-animal bond may lead owners to have high expectations concerning what can and should be done for their pets, which could put pressure on animal healthcare providers. Indeed, the present study showed that veterinarians who spent < 25% of their time working with cats and dogs had lower mean BO and STS scores, compared with scores for veterinarians who spent ≥ 75% of their time working with dogs and cats. These findings were supported by those of a 2014 survey,2 which showed that veterinarians in small animal practice (64.2% [7,460/11,627] of all respondents) were significantly more likely to have had a depressive episode, received treatment for depression, and experienced suicidal ideation since graduation from veterinary school than were all respondents combined.

The observed associations between total annual income and CS, BO, and STS scores in the present study were not surprising given our other findings. The referent group in the analysis ($40,000 to $74,999), which comprised 23.2% (1,166/5,020) of all respondents, likely included high proportions of recent graduates, interns, and residents. Whereas a previous survey23 showed that work-life balance and being paid fairly were associated with job satisfaction among US veterinarians, lack of a work-life balance was also associated with BO, as measured with the Mayo Clinic Physician Burnout and Wellbeing Scale. Interestingly, only when income was ≥ $125,000 (CS), ≥ $150,000 (BO), or ≥ $100,000 (STS) in our study were differences from the referent group observed in mean CS, BO, and STS scores. This income advantage reached a maximum at an annual income of $225,000 to $250,000 and not at an annual income of $275,000 to $500,000 (the highest-evaluated category), suggesting a point at which income no longer had as strong an influence on these measures of well-being.

As in other studies8,18 involving veterinarians, well-being in the present study was associated with gender, whereby women had higher compassion fatigue (ie, higher mean BO and STS scores) than did men, but a similar degree of CS. Gender differences among veterinarians specifically have been observed for other indicators of mental health or illness as well. For example, death record data from 1979 through 2015 indicated that female veterinarians in the United States were at greater risk of dying by suicide (population mortality ratio, 3.5) than were male veterinarians (2.1).5 This finding is supported by the higher prevalence of serious psychological distress found in 2019 for female (8.1%) versus male (3.9%) veterinarians.23 In general, women are also almost twice as likely as men to have an anxiety disorder,33 and female veterinarians are more likely to suffer from stress than male veterinarians.26,34 Because gender options in the surveys were limited to male and female, a deeper exploration of the effects of gender identity or expression on CS, BO, and STS could not be performed but would be important to pursue to inform and provide resources supportive of well-being for all veterinarians.

Interestingly, as the number of children respondents noted having in each of the various age categories (< 2 years, 2 to 3 years, and 4 to 5 years) increased by 1, the mean CS score also increased and the mean BO and STS scores decreased, suggesting that having young children does not compromise well-being in veterinarians and that having a life outside of work may relieve rather than magnify stress. These results were supported by findings for female veterinarians (n = 1,017) in an Australian survey,26 which indicated that women with ≥ 2 children had less anxiety and depression than did those with no children. Although not explored in the present study, this seemingly protective effect of parenthood may be attributable to less time spent at work, given that other research has shown that both male and female veterinarians with children work significantly fewer hours per week than do those without children.35 Although all included veterinarians indicated they were employed full-time, the number of hours worked per week was not examined in our study. The possibility that less time at work, even among full-time workers, translates to greater well-being is important and warrants further research.

Use of the ProQOL5 could be considered a limitation of the present study because the questions were designed for people who care for people and not for people who care for animals and their owners and who might experience CS, STS, and BO differently. To the authors’ knowledge, no similar, validated instrument exists specific to animal caregivers, but such an instrument would be useful for further defining the factors that contribute to adverse mental health outcomes among veterinarians.

Although the large sample size in the present study facilitated detection of significant differences, some of those differences may have lacked psychological relevance. For example, veterinarians with an educational debt ≥ $200,000 had significantly lower CS scores than did those with a debt < $25,000, but the observed mean difference was < 1 point on a scale from 10 to 50. To the authors’ knowledge, no information is available to suggest how large a difference needs to be for it to be considered psychologically meaningful. Even so, the overall findings highlighted several demographic and employment factors that adversely impacted CS, BO, and STS scores and, therefore, deserve attention and intervention, where possible. Groups identified as at higher risk than others included women, recent graduates, veterinarians in companion animal practice, and veterinarians with high educational debt or low annual incomes. The broad range of CS, BO, and STS scores within each demographic and employment category suggested that veterinarians of all demographic and employment categories, and not just selected groups, would benefit from resources and initiatives to promote well-being.

Many ideas have been proposed to help mitigate BO and STS and enhance professional well-being among veterinarians and other professional caregivers. For example, West et al36 summarized the causes of BO among physicians (ie, excessive workloads, work inefficiency and lack of support, lack of work-home integration, loss of control and autonomy, and loss of meaning from work) and also described organization- and individual-level solutions, ranging from duty-hour limits and informed specialty choices (individual level) to promotion of professional communities and shared core values (organization level) and stress management and resiliency training (individual level, but could be offered at the organization level). Similar suggestions have been made in the veterinary literature, such as providing recent veterinary school graduates with opportunities for professional development and continuing education, support from superiors, and latitude in decision-making (eg, by allowing flexible work schedules) to help reduce exhaustion.37 Some authors suggest that attempts to encourage or improve well-being among veterinarians should begin with entry to veterinary school by inclusion of a well-being curriculum designed to build resilience.27 Others propose that veterinary teams acknowledge that veterinary medicine is a stressful profession and mental health challenges are common and that individual veterinarians create a stress management plan, prioritize work-life balance, engage a financial planner, and limit time on social media.23 Given the adverse impacts of higher educational debt and lower income on CS, BO, and STS scores in the present study, we strongly suggest that the veterinary profession and employers continue exploring, advocating for, and implementing ways to alleviate financial burdens on veterinarians. Additional research is warranted to further explore modifiable factors that could be addressed at the profession, organization, and individual level to defend or improve the well-being of veterinarians.

Although the results of the present study may be used to target well-being resources and initiatives toward specific veterinarian groups with potential mental health concerns, we would encourage all veterinarians to prioritize their well-being and seek help when that well-being is threatened. Several resources have been developed to support well-being and work-life balance among veterinarians. The AVMA has launched an online toolkit to enhance the professional well-being of veterinarians and help them cope with work-related stressors (www.avma.org/resources-tools/wellbeing). Other useful resources are available elsewhere for veterinarians and their teams (eg, www.merck-animal-health-usa.com/offload-downloads/mahhealthy-strategies-infographic and catalystvetpc.com/veterinary-team-wellbeing-resources/), veterinary technicians (eg, www.navta.net/page/WellbeingResources), and the general public (eg, www.who.int/news-room/feature-stories/mental-well-being-resources-for-the-public and screening.mhanational.org/). Information is also available to help individuals from the preveterinary stage to more established stages to increase their financial literacy and reduce and manage their educational debt (eg, www.avma.org/resources-tools/personal-finance/personal-financial-planning-resources, vinfoundation.org/resources/student-debt-center, vmae.org/veterinary-debt-initiative, and avma.org/membership/SAVMA/financing-your-veterinary-medical-education).

Acknowledgments

The Census of Veterinarians surveys were funded by the AVMA.

Drs. Ouedraogo and Lefebvre and Charlotte Hansen are employees of the AVMA. The authors declare that there were no conflicts of interest.

Opinions expressed are not necessarily those of the AVMA.

Footnotes

a.

SAS, version 9.4, SAS Institute, Cary, NC.

Abbreviations

BO

Burnout

CS

Compassion satisfaction

ProQOL

Professional Quality of Life Scale

STS

Secondary traumatic stress

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  • Figure 1

    Mean scores for CS, BO, and STS minus mean scores for the referent group (ie, respondents with educational debt at graduation < $25,000) for full-time US veterinarians who provided complete survey responses (n = 5,020) to the ProQOL portion of the 2016, 2017, and 2018 AVMA Census of Veterinarians and had educational debt at graduation between $25,000 and $99,999 (white bars), between $100,000 and $199,999 (gray bars), and ≥ $200,000 (black bars), after controlling for other variables. *Value was significantly (P < 0.05) different from 0.

  • Figure 2

    Mean scores for CS, BO, and STS minus mean scores for the referent group (ie, respondents who spent ≥ 75% of their time) for respondents in Figure 1 who spent < 25% of their time working with cats, dogs, or both (black bars) or 25% to 74.9% of their time working with cats, dogs, or both (white bars), after controlling for other variables. See Figure 1 for remainder of key.

  • Figure 3

    Mean CS scores minus mean score for the referent group (ie, respondents with total annual income < $75,000) for respondents in Figure 1 grouped on the basis of total annual income, after controlling for other variables. See Figure 1 for remainder of key.

  • Figure 4

    Mean BO scores minus mean score for the referent group (ie, respondents with total annual income < $75,000) for respondents in Figure 1 grouped on the basis of total annual income, after controlling for other variables. See Figure 1 for remainder of key.

  • Figure 5

    Mean STS scores minus mean score for the referent group (ie, respondents with total annual income < $75,000) for respondents in Figure 1 grouped on the basis of total annual income, after controlling for other variables. See Figure 1 for remainder of key.

  • Figure 6

    Mean CS, BO, and STS scores for men (white bars; n = 1,157) and women (black bars; 3,086) in Figure 1, after controlling for other factors. *Significantly (P < 0.05) different from the value for men.

  • 1.

    National Alliance on Mental Health. Mental health by the numbers. Available at: www.nami.org/mhstats. Accessed Sep 2, 2020.

  • 2.

    Nett R, Witte TK, Holzbauer SM, et al. Risk factors for suicide, attitudes toward mental illness, and practice-related stressors among US veterinarians. J Am Vet Med Assoc 2015;247:945955.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Bartram DJ, Baldwin DS. Veterinary surgeons and suicide: a structured review of possible influences on increased risk. Vet Rec 2008;166:388397.

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