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. 2022 Jun 21;75:15. doi: 10.1186/s13620-022-00220-x

Table 1.

Listing of the studies found according to full text search, indicating the standardised and non-standardised questionnaires, the EPHPP ranking and a selection of main results

First author, year of publication and location EPHPP raking Used questionnaire Sample and study type Results
Bartram et al. 2009, UK [22 weak The hospital anxiety and depression scale (HADS), Three questions on suicidal ideation derived from the second National Survey of Psychiatric Morbidity, The Warwick-Edinburgh mental wellbeing scale (WEMWBS), The Health and Safety Executive management standards indicator tool (HSE MSIT), Subscales of the Survey Work-home Interaction Nijmegen (SWING), A series of 27 original items specifically focusing on potential sources of stress in the veterinary profession (a domain of 9 items referred to clinical work and was only completed by respondents to whom this domain was relevant, An open question inviting respondents to identify in free text up to three main sources of pleasure and/or satisfaction in practice A sample consisting of 1796 practicing veterinary surgeons (50% male, 50% female) in a cross-sectional study

HADS-A (total mean): 7.9 (± 4.1); non-case (0–7%): 48.8; possible case (8–10%): 25.3; probable case (≥ 11): 26.3%

HADS-D (total mean): 4.6 (± 3.4); anxiety subscale non-case (0–7%): 80.6; anxiety subscale possible case (8–10%): 13.6; anxiety subscale probable case (≥ 11): 5.8%

HADS-T (total mean): 12.6 (± 6.8)

Twelve-month prevalence of suicidal ideation: life was not worth living (23.0%; death wishes (15.0%); suicidal thoughts (21.3%); any suicidal ideation (29.4%)

WEMBS (mean score): 48.85 (± 9.06); The mean scores for veterinary surgeons working in university-based non-clinical university-based clinical roles vs. working in small animal practice after adjusting for age and gender (university-non-clinical: β = 3.50, 95% CI: 0.37–6.62, p = 0.029; university-clinical: β = 2.76, 95% CI: 0.48–5.03, p = 0.018)

HSE MSIT: Total mean (95% CI): demands 2.96 (± 0.70), control 3.47 (± 0.78), managerial support 3.14 (± 0.89), peer support 3.75 (± 0.73), relationships 4.01 (± 0.69), role 4.21 (± 0.63), change 3.22 (± 0.94)

WHI_N: total mean: 1.19 (± 0.57)

WHI_P: total mean: 0.97 (± 0.56)

Contributors to stress: Number of hours (42.9%), making professional mistakes (40.4%), client expectations: (38.0%), administrative and clerical tasks (27.9%)

Sources of satisfaction: good clinical outcomes (41.5%), relationships with colleagues (33.7%), intellectual challenge/learning (32.4%)

Best et al. 2020, Canada [39] weak HADS, MBI-Human Services Scale (MBI-HSS), Professional Quality of Life (version 5) (ProQOL), Connor-Davidson Resilience Scale (CD-RISC) A sample consisting of 412 veterinary (Nearly 70% of participants identified as female and 30.5% as male) in a cross-sectional study

HADS-A (total mean): 8.8 (± 4.3); non-case (0–7%): 38.7; possible case (8–10%): 28.7%; probable case (≥ 11): 32.6%

HADS-D (total mean): 5.2 (± 3.9); non-case (0–7%): 75.4%; possible case (8–10%): 15.6%; probable case (≥ 11): 9.0%

Comorbidity defined as both anxiety and depression subscales having scores ≥ 11: 7.1% (4.8–10.0 CI)

Approximately 1/3 of participants were classified as probable cases of anxiety based on a HADS-A score ≥ 11, and 9% of participants were classified as probable cases of depression based on a HADS-D score of ≥ 11. Furthermore. Approximately 7% were classified as having comorbid anxiety and depression. Female participants tended to have higher anxiety and depression scores and percentage probable caseness than males

MBI-HSS: 36.9% of participants in this survey could be classified as experiencing burnout (95% CI: 32.1% to 42.0%). Female participants (37.8%) tended to have a higher proportion experiencing burnout (95% CI: 31.8% to 44.0%) than male participants (32.7%, 95% CI: 24.2% to 42.2%)

ProQOL: Female participants tended to have higher scores in Burnout (44.8% vs. 38.9%) and Secondary Traumatic Stress (72.9% vs. 60.7%), and were more likely to be within the “high” category for these components of compassion fatigue. Compassion Satisfaction: male 36.3% vs. female 31.4%)

CD-RISC: The mean CD-RISC score (n = 368) was 70.4 (± 14.9). Approximately 74.5% of participants (95% CI: 69.7% to 78.8%) had scores lower than the scale’s comparative norm (the general population of the United States) of 80.7

Cevizci et al. 2014, Turkey [40] weak Swedish Demand-Control-Support Questionnaire (DCSQ), self-reported physical and mental health problems by veterinary surgeons A sample consisting of 223 veterinary (71,7% male, 28.3% female) in a cross-sectional study

DCSQ (mean values between vets in civil servant vs. vets in private sector employee): work load 9.65 (± 1.73) vs 9.26 (± 1.94)*, work control 10.73 (± 2.94) vs. 9.95 (± 2.51)*, skill use 7.12 (± 1.92) vs. 7.02 (± 1.68)*, decision latitude 3.61 (± 1.84) vs. 2.94 (± 1.42)**, social support 11.46 (± 3.58) vs. 11.12 (± 4.19)*. *p < 0.05, **p = 0.008

Reported mental health problems by veterinary surgeons: Unresponded (21.4%), stress (19.7%), short temper (15.4%), Depression (12.8%), Burnout (12.0%), Unhappiness/restlessness (10.3%), Chronic fatigue/insomnia (7.7%), Attention deficit (0.9%)

Crane et al. 2015, Australia [41] weak 21-item Depression, Anxiety, Stress Scale (DASS-21), Positive and Negative Affect Scale (PANAS), Brief Resilience Scale, Stressor events were identified via three focus groups held with 11 veterinarians (9-point scale), 24-item version of the Multidimensional Perfectionism Scale (FMPS-Reduced) A sample consisting of 540 veterinary (64.2% female) in a cross-sectional study

inability to pay (n = 530): stressor frequency 6.32 (± 2.03) and degree moral significance 59.84 (± 28.40); balancing client and patient welfare (n = 501): stressor frequency 5.23 (± 2.05) and moral significance 67.73 (± 25.18); carrying out wishes even if they´re not in the best interest of the animal patient (n = 455): stressor frequency 4.63 (± 1.91) and moral significance 74.19 (± 23.78); euthanasia for reasons you did not agree with (n = 441): stressor frequency 3.63 (± 1.60) and moral significance 80.04 (± 23.79); euthanasia (n = 429): stressor frequency 7.41 (± 1.54) and moral significance 60.08 (± 33.77); assisting with incompetent care (n = 353): stressor frequency 3.85 (± 2.03) and moral significance 80.46 (± 22.50); suspected patient/pet abuse (n = 131): stressor frequency 2.45 (± 1.43) and moral significance 84.23 (± 20.46)

The perfectionism was positively related to stress (r = 0.509, p < 0.01), anxiety (r = 0.473, p < 0.01), and negative affect (r = 0.444, p < 0.01) and negatively related to resilience (r =  − 0.474, p < 0.01)

Psychological resilience: perceived resilience (F(7, 490) = 23.60, p < 0.001)

Dawson und Thompson 2017, UK [42] weak NEO Five-Factor Inventory (NEO-FFI), MBI and Job Stress Survey (JSS) A sample consisting of 363 veterinary (139 males and 220 females, 4 did not specify sex) in a cross-sectional study

H1: Veterinarians' experiences of occupational stress will be explained more through personality factors than environmental factors: The personality can explain 7.3% (R2 = 0.073) of the variance in occupational stress. The final model indicates that personality has a significant effect on occupational stress (F[1, 309] = 24.411, p < 0.001). The beta coefficient confirms that personality significantly predicts occupational stress (β = 0.271, t[309] = 4.941, p < 0.001)

H2: The personality traits of neuroticism and conscientiousness will be more related to occupational stress than the traits of extraversion, openness, and agreeableness: Neuroticism can explain 7.3% (R2 = 0.073) of the variance in occupational stress. The final model indicates that neuroticism is a significant predictor of occupational stress (F[1, 309] = 24.411, p < 0.001). Likewise the beta coefficient confirms this (β = 0.271, t[309] = 4.941, p < 0.001). Environment can explain 2.2% of the variance in OS when neuroticism is removed (R2 = 0.022). The final model indicates that environment has a significant effect on occupational stress (F[1, 309] = 6.958, p = 0.009). The beta coefficient also shows that environment significantly predicts OS (β = 0.148, t[309] = 2.638, p = 0.009)

A1: To establish the key facets within neuroticism and conscientiousness that most contribute to stress: 6.5% of the variance in occupational stress can be attributed to the personality component depression and another 2.4% to anger and hostility, two of the five facets of neuroticism. The final model shows that both depression and anger hostility have a significant effect on OS (F[2, 308] = 15.027, p < 0.001). Beta coefficients confirm that depression and anger hostility are significant predictors of OS, with depression presenting the strongest correlation (β = .183, t[308] = 3.054, p = 0.002) followed by anger hostility (β = 0.171, t[308] = 2.853, p = 0.005)

A2: To explore demographic factors (such as years qualified and type of practice) as potential mediators and/or moderators of any relationships found: Years qualified (YO) and anger hostility were significant predictors of occupational stress (F[6, 302] = 7.531, p < 0.001). Beta coefficients confirm that years qualified is a significant mediator in the relationship between depression and occupational stress (β [YQ] =  − 0.200, t[302] =  − 3.684, p < 0.001; β [anger hostility] = 0.156, t[302] = 2.582, p = 0.010). Type of practice presented no significant effects on facets within neuroticism and conscientiousness

YQ moderated the EE and DP relationships with respect to OS, resulting in weaker correlations (final model [YQ, EE]: F[2, 306] = 64.713, p < 0.001). The beta coefficients confirm these correlations (β [YQ] =  − 0.154, t[306] =  − 3.178, p = 0.002; β [EE] = 0.501, t[306] = 10.331, p < 0.001; final model [YQ, DP]: F[2, 306] = 41.339, p < 0.001) and the corresponding beta coefficients demonstrate this correlation between YQ and DP (β [YQ] =  − 0.140, t[306] =  − 2.700, p = 0.007; β [DP] = 0.410, t[306] = 7.901, p < 0.001). However, results show that there was a moderated relationship between PA and OS in relation to YQ, resulting in a stronger correlation (final model [YQ, PA]: F[2, 306] = 10.980, p < 0.001). The beta coefficients confirm this moderated relationship, revealing an increase in the strength of the correlation (β [YQ] =  − 0.230, t[306] =  − 4.173, p < 0.001; β [PA] =  − 0.122, t[306] =  − 2.206, p = 0.028)

Dow et al. 2019, Australia [38] weak Kessler Psychological Distress Scale (K10), Compassion Fatigue Short Scale (CFSS), and items designed by the researchers specifically for the study (personal grief when the life of a client's animal ends and their physical and mental wellbeing) A sample consisting of 103 veterinary (63,1% female) in a cross-sectional study

Mental/physical health was affected by euthanasia (40.2% (strongly agree + agree))

CFSS: There was a statistically significant association between total score on the CFSS and hours worked when adjusting for age (global p-value < 0.0001). The most significant comparison was veterinarians who worked 10–20 h had a mean CFSS score 43 units less than veterinarians who worked 20–30 h (estimate =  − 43, 95% CI: − 62, − 23, comparison p-value < 0.0001). The most significant comparison was veterinarians aged 18–34 had a mean CFSS score 32 units more than veterinarians aged > 64 (estimate = 32, 95% CI: 19, 44, comparison p-value < 0.0001)

K10: There was a statistically significant association between psychological distress and age when marital status and animal type were considered (global p-value = 0.0029). The most significant comparison was that veterinarians aged 18–34 years had a mean K10 score 8 units higher than veterinarians aged > 64 years (estimate = 8, 95% CI: 4, 13, comparative p-value = 0.0005)

There was a statistically significant association between psychological distress and marital status when age and animal type were considered (global p-value = 0.0314). Married and partnered veterinarians had a mean K10 score 3 units lower than non-married or partnered veterinarians (estimate = -3, 95% CI: -5, -0.3)

There was a statistically significant association between psychological distress and animal type when age and marital status were considered (global p-value = 0.0218). Veterinarians dealing with companion animals, horses, and mixed animals had a mean K10 score 10 units higher than veterinarians dealing with other animals or involved in research (estimate = 10, 95% CI: 1, 18)

Fritschi et al. 2009, Australia [37] weak General Health Questionnaire (GHQ), Warr's work-related affect scales, self-reported questions A sample consisting of 2125 veterinary (1217 male, 908 female) in a cross-sectional study

psychological health associated with demographic and practice factors:

GHQ score > 2: Gender (p < 0,001): female 37.6%, male 29.7%; Practice type (p < 0,4): mixed 34.8%, small 33.1%, non-animal 32.1%, large 29.6%

Mean Anxiety/Contentment score: Gender (p < 0,001): male 4.04%, female 3.72%; Practice type (p < 0,001): non-animal 4.11%, large 4.04%, mixed 3.92%, small 3.83%

Mean Depression/Enthusiasm score: Gender (p < 0,001): male 4.46%, female 4.31%; Practice type (p < 0,007): non-animal 4.58%, large 4.47%, mixed 4.41%, small 4.34%

GHQ Wald coefficient (95% CI): Gender: female 1.13 (0.89, 1.44), male 1.0; Practice type: non-animal 1.40 (0.77, 2.56), mixed 1.12 (0.87, 1.43), large 1.06, (0.78, 1.45), small 1.0; Working hours (per hour): 1.01 (1.00, 1.02)

Anxiety/Contentment Beta (95% CI), adjusted R2 0.479: Gender: male (Baseline), female − 0.12 (− 0.198, − 0.06); Practice type: non-animal 0.09 (− 0.07, 0.24), mixed 0.04 (− 0.02, 0.11), large 0.01 (− 0.07, 0.09), small (Baseline); working hours − 0.01 (− 0.01, − 0.00)

Depression/Enthusiasm Beta (95% CI), adjusted R2 0.566: Gender: female 0.01 (− 0.05, 0.07), male (Baseline); Practice type: non-animal 0.10 (− 0.04, 0.23), large − 0.03 (− 0.10, 0.04), mixed 0.01 (− 0.05, 0.06), small (Baseline); working hours − 0.00 (− 0.01, − 0.00)

Hansez et al. 2008, Belgium [21] weak Positive and Negative Occupational Stress Inventory (PNOSI), SWING, subscale of emotional exhaustion A sample consisting of 216 veterinary (75,5% male, 24,5% female) in a cross-sectional study

job engagement: mean 54.06 (± 8.89); Level low 3.7%, Level medium 71.3%, Level high 24.2%; Type of activity: small animals 56.55 (± 8.95), mixed 53.41 (± 8.91), bovine 52.09 (± 8.49)

job strain: mean 52.19 (± 8.15); Level low 5.6%, Level medium 79.2%, Level high 14.8%; Type of activity: mixed 54.24 (± 6.97), bovine 53.14 (± 8.20) small animals 50.64 (± 8.17)

burnout: mean 22.22 (± 9.47); level low 31%,

Level medium 51.9%, Level high 14.4%; Type of activity: bovine 24.14 (± 10), mixed 22.79 (± 9.09), small animals 20.93 (± 9.20)

Harling et al. 2007, Germany [43] weak Frequency-quantity index, CAGE-Test, Demoralization Scale, Psychosocial Stress Scale A sample consisting of 1131 veterinary (male 47,5%, female 52,5%) in a cross-sectional study

Psychosocial stress: burdened (19.1%), mean: 1.4

more hours, more stress (r = 0.443, p < 0.001); stress for self-employed more than for employed veterinarians (r = -0.2, p < 0.001)

mean demoralization scale: 1.2; employed more demoralized than self-employed (r = 0.119; p < 0.001); young vets more demoralized than older vets (r = -0.124; p < 0,001) severe psychosocial stress often associated with demoralization (r = 0.442; p < 0.001)

Hatch et al. 2011, Austria [44] weak K10, DASS, CBI A sample consisting of 1947 veterinary (51.4% male, 48.6% female) in a cross-sectional study

K10 scores:

all respondents (n = 1944): low (35.2%), moderate (42%), high (14%), very high (5%)

DASS-depression scores:

all respondents (n = 1942): normal (74.5%), mild (7.9%), moderate (10%), severe (3.8%), extremely severe (3.9%)

DASS-anxiety scores:

all respondents (n = 1942): normal (83.3%), mild (4.6%), moderate (7.8%), severe (2.2%), extremely severe (2.1%)

DASS- stress:

all respondents (n = 1942): normal (68.2%), mild (11.5%), moderate (10.5%), severe (6.8%), extremely severe (2.4%)

Burnout CBI: reference data: personal (22.2%, n = 1945), work (19.7%, n = 1946), client (16.6%, n = 1933)

all respondents: personal (37%), work (35.6%), client (24.8%)

Logistic Regression

more likely highest categories (DASS depression): capital cities, rural cities/town

high/very high K10 scores (> 22): Female (OR = 1.6, 95%CI:1.2–2.0) and veterinarians < 10 years

high/very high personal burnout scores: Female (OR = 2.3, 95%CI: 1.9–2.9), capital city (OR = 2.55, 95%CI: 1.1–6.1), rural city/town (OR = 1.4, 95%CI: 1.0–1.9)

Lower work and client burnout scores (OR < 1): all types of practice/ work other than companion animal practice

Kassem et al. 2019, USA [45] weak Kessler psychological distress scale A sample consisting of 9522 veterinary (30.8% male, 69.2% female) in a cross-sectional study

negative attitude toward treatment effectiveness: male vs. female OR = 1.79, solo vs. nonsolo OR = 1.60, with vs. without psychological distress OR = 2.11, suicide ideation vs non OR = 1.83

Negative attitude toward social support: males vs females OR = 0.72, solo vs nonsolo OR = 1.23, not belong vs belong veterinary association OR = 1.29, psychological distress vs none OR = 1.55; suicidal ideation vs none OR = 1.55, age 40–59 vs 20–39 = OR = 1.18. small animal practice associated with neg. attitude toward treatment

Mair et al. 2021, UK [46] weak WEMWBS (pre and during covid pandemic) A sample consisting of 451 veterinary (38.4% males, 61.0% females, 0.6% n.r.) in a cross-sectional study

WEMWBS mean: current survey (during pandemic): 47.17; 2019 survey (pre pandemic): 48.08

cheerful: none of time (0–2%), rarely (2–17%), some of the time (17–60%), often (60–93%), all of the time (93–100%)

interested in new things: none of time (0–8%), rarely (8–27%), some of the time (27–57%), often (57–88%), all of the time (88–100%)

feeling loved: none of time (0–3%), rarely (3–11%), some of the time (11–48%), often (48–72%), all of the time (72–100%)

able to make up my mind about things: none of time (0–1%), rarely (1–9%), some of the time (9–48%), often (48–79%), all of the time (79–100%)

confident: none of time (0–2%), rarely (2–21%), some of the time (21–55%), often (55–88%), all of the time (88–100%)

close to others: none of time (0–3%), rarely (3–27%), some of the time (27–60%), often (60–90%), all of the time (90–100%)

feeling good about myself: none of time (0–5%), rarely (5–19%), some of the time (19–63%), often (63–91%), all of the time (91–100%)

thinking clearly: none of time (0–1%), rarely (1–6%), some of the time (6–35%), often (35–82%), all of the time (82–100%)

spare energy: none of time (0–7%), rarely (7–46%), some of the time (46–72%), often (72–93%), all of the time (93–100%)

dealing with problems well: none of time (0–1%), rarely (1–7%), some of the time (7–45%), often (45–87%), all of the time (87–100%)

interested in others: none of time (0–2%), rarely (2–9%), some of the time (9–46%), often (46–86%), all of the time (86–100%)

relaxed: none of time (0–10%), rarely (10–41%), some of the time (41–77%), often (77–95%), all of the time (95–100%)

being useful: none of time (0–4%), rarely (4–11%), some of the time (11–36%), often (36–69%), all of the time (69–100%)

optimistic about future: none of time (0–4%), rarely (4–21%), some of the time (21–62%), often (62–91%), all of the time (91–100%)

Mastenbroek et al. 2014, Netherlands [20] weak Interviews and questionnaire: The Questionnaire Experience and Evaluation of Work (QEEW), Proactive Personality Scale, Groningen Reflection Ability Scale, nine-item version of the Utrecht Work Engagement Scale (UWES), exhaustion dutch version of MBI A sample consisting of 860 veterinary (27% males, 73% females) in a cross-sectional study correlations: workload: work-self conflict 0.463**, physical demands: work-self conflict 0.364**, feedback from work: decision latitude 0.327**, support form colleagues: feedback from work 0.394**, exhaustion: workload .376**, exhaustion: physical demands 0.338**, exhaustion: work-self conflict: 0.557**, exhaustion: decision latitude -0.416**, exhaustion: self-efficacy -0.313** (only over 0.300 and not all)
Nett et al. 2015, USA (Puerto Rico) [47] weak Kessler-6 psychological distress scale, history of depression and mental health treatment, attitudes toward mental illness and mental health treatment, stressors related to veterinary practice, and satisfaction related to practicing veterinary medicine A sample consisting of 11.627 veterinary (male 31%) in a cross-sectional study

9% respondents with current serious psychological distress. Since leaving veterinary school, 31% respondents experienced depressive episodes, 17% experienced suicidal ideation, and 1% attempted suicide. Currently, 19% respondents were receiving treatment for a mental health condition. 32% respondents somewhat or strongly agreed that people are sympathetic toward persons with mental illness

Reported psychological distress (score ≥ 13): female > male in all categories, previous depressive episodes (31%) > suicidal ideation (17%) > attempted suicide (1%). Among those who had attempted suicide, the median number of attempts was 1.0. Currently receiving treatment: n = 2228 (19%)

Perret et al. 2020, Canada [48] weak Davidson Resilience Scale, Perceived Stress Scale, HADS, MBI, ProQOL A sample consisting of 1.130 veterinary (male 21.6%, female 78.4%) in a cross-sectional study

Subjective general health (excellent vs. reference person, poor; β = 18.28 [95% CI, 11.89 to 24.67]; t = 5.61; p < 0.001); Satisfaction with support from friends (very satisfied vs. reference person, not at all satisfied; β = 8. 87 [95% CI, 1.81 to 15.92]; t = 2.47; p = 0.014); Satisfaction with relationship or partner support (very satisfied vs reference person, not at all satisfied; β = 6.21 [95% CI, 0.60 to 11.82]; t = 2.17; p < 0.030) had strong positive associations with resilience; 2 children (2 vs reference, none; β = 2.74 [95% CI, 0.58 to 4.90]; t = 2.49; p = 0.013); 3 children (3 vs reference, none; β = 3.09 [95% CI, 0.23 to 5.95]; t = 2. 12; p = 0.034) or having a scheduled call (vs no call; β = 1.91 [95% CI, 0.13 to 3.70]; t = 2.11; p = 0.035) was also positively associated with resilience; self-reported presence of current mental illness had the strongest negative association with resilience (vs no current illness; β = -5.03 [95% CI, -7.37 to -2.69]; t = -4.23; p < 0.001); being married was negatively associated with resilience (married vs referent, single; β = -5.85 [95% CI, -10.88 to -0.81]; t = -2.28; p = 0.023) or practicing small animal medicine (small animal only vs referent, mixed; β = -2.53 [95% CI, -4.97 to -0.089]; t = -2.03; p = 0.042)

association between mental health outcome scores (as dependent variable) and the CD-RISC scores: CD-RISC: mean 69.9 (range 20–99); PSS: mean 17.0 (range 0–7); HADS: mean 13.2 (range 0–39); MBI: emotional exhaustion: mean 26.1 (range 0–54), Depersonalization: mean 8.9 (range 0–8); Personal accomplishment: mean 36.6 (range 10–48); ProQOL: Burnout: mean 25.2 (range 10–45), secondary traumatic stress: mean 23.6 (range 10–46), Compassion satisfaction: mean 37.8 (range 14–50)

Shirangi et al. 2013 [49] weak Affective Well-Being Scale, PANAS, GHQ and CGHQ A sample consisting of 1017 female veterinary in a cross-sectional study

GHQ: > 2: 37%; CGHQ: > 4: 63%

Mean score on the Anxiety-Contentment Axis: 3.72 (± 0.8); Mean score on the Depression-Enthusiasm Axis: 4.31 (± 0.82)

PANAS: PA mean score 33.5 (± 6.25); NA mean score: 18.7 (± 6.12)

Reijula et al. 2003, Finland [36] weak MBI, self-reported health, self-reported diseases A sample consisting of 785 veterinary (male 225, female 550) in a cross-sectional study

severe burnout (age groups/year): 25–34: men (2.1) vs women (0.0); 35–44: men (2.0) vs women (0.0), 45–54: men (0.0) vs women (3.2), 55.65: men (0.0) vs women (3.1), total: women (1.8) vs men (1.7)

self-reported health: men:

55–65 years: rather good (46.8%) > average (40.4%) > good (10.6%) > poor (2.1%)

45–54 years: rather good (47.6%) > average (32.1%) > good (14.3%) > rather poor (6%)

35–44 years: rather good (38.6%) > average (29.8%) > good (28.1%) > rather poor (3.5%)

25–34 years: rather good (40.0%) > average (30.0%) > good (26.7%) > rather poor (3.3%)

women:

55–65 years: average (53.3%) > rather good (26.7%) > good (13.3%) > rather poor (6.7%)

45–54 years: rather good (36.9%) > average (31.0%) > good (22.6%) > rather poor (7.1%) > poor (2.4%)

35–44 years: rather good (39.6%) > good (31.0%) > average (25.4%) > rather poor (2.5%) > poor (1.5%)

25–34 years: rather good (40.8%) > good (36.1%) > average (21.0%) > rather poor (2.1%)

self-reported diseases:

mental disorder: women (8%), men (7%)

Rivera et al. 2021, USA [50] weak PHQ-8 A sample consisting of 101 veterinary (40.6% male, 59.4% female) in a longitudinal cohort study (2001, 2004, 2007, and 2011)

Mental health problem: No (84.2%. n = 85), Yes (15.8%, n = 16), p = 0.026

Suicidal ideation: Not at all (91.8%, n = 67), several days or more (8.2%, n = 6), p = 0.282

Lack of social support: No (not bothered) (63.4%, n = 64), Yes (bothered) (36.6%, n = 37), p = 0.023

Schwerdtfeger et al. 2020b [13] weak PHQ-9, SBQ-9 A sample consisting of 3.118 veterinary (20.5% male, 79.5% female) in a cross-sectional study

PHQ-9: 27.78% were screened positive for depression (17.45% displayed moderate symptoms of depression, 10.33% indicated moderately severe to severe symptoms of depression). Compared with the general population: OR = 0.349; 95% CI 0.309 to 0.940

PHQ-9 (item 9): 19.2% having suicidal ideation in the past two weeks (15.91% reporting to have had such feelings on several days during the last two weeks, 2.31% on nearly half of the days and 0.96% nearly every day during the last two weeks). Compared with the general population: OR = 0,497; 95% CI 0,445 to 0,554

SBQ-9: 32.11% were classified as having an increased suicide risk (compared with the general population: OR = 0,150; 95% CI 0,123 to 0,183). 38.3% have never thought about, planned or attempted suicide. 24.2% report that they have planned to kill themselves at least once. 2.7% stated that they have attempted to kill themselves at least once in the past

Schwerdtfeger et al. 2020a, Germany [51] weak COPSOQ, PHQ-9, SBQ-R A sample consisting of 3179 veterinary (22.2% male, 78.8% female) in a cross-sectional study

stress makes it difficult to meet personal/family obligations = female: agree (32%), disagree (21%), partly (19%), fully agree (18%), totally disagree (9%)

male: agree (29%), disagree (25%), partly (17%), totally disagree (15%), fully agree (14%)

frequency feeling emotionally exhausted = female: often (36%), sometimes (33%), rarely (21%), always (5%), never (4%)

male: rarely (33%), sometimes (29%), often (25%), never (11%), always (3%)

current suicidal thoughts (19.2%, n = 598), increased suicide risk (32.1%, n = 1001), clinically relevant depression symptoms (27.8%, n = 886)

Witte et al. 2020, England & USA [52] weak Kessler 6 psychological distress scale and self-formulated question (revalence of serious psychological distress, a history of depressive episodes, a history of suicidal ideation, and a history of attempted suicide and negative mental health outcomes and work- and school-related emotional outcomes for respondents) A sample consisting of 440 veterinary (Cis female: 62.0%, Cis male: 30.7%, Transgender (male to female): 0.5%, Transgender (female to male): 1.6%, Do not identify as male or female: 4.5%, Prefer not to answer: 0.7% in a cross-sectional study

Highest correlation between the scores for emotional exhaustion and job satisfaction (-0.66)

Prevalence of serious psychological distress (Kessler 6 score ≥ 13) in different to the prevalences of the veterinarians in general (Nett et al. 2015 [47]): Transgender and nonbinary individuals (41%, p < 0.01), Nonheterosexual cis women 16%, p = 0.005), Transgender and nonbinary individuals (50%, p = 0.001)

Prevalence of depressive episodes in different to the prevalences of the veterinarians in general (Nett et al. 2015 [47]): Nonheterosexual cis women (45%, p = 0.003)

Study without valid survey instruments
Batchelor und McKeegan 2012, UK [12] weak Ethical dilemmas: the frequency with which they faced ethical dilemmas in an average week (0, 1 to 2, 3 to 5, 6 to 10,  > 10) & three common scenarios: (1) convenience euthanasia of a healthy animal, (2) financial limitations of the client restricting the treatment options and (3) the client wishing to continue treatment despite compromised animal welfare/quality of life (scale 0–10, 0 not at all stressful, 10 extremely stressful) A sample consisting of 58 practicing veterinary surgeons (15 male, 43 female) in a cross-sectional study

The median stress ratings (0, 1 to 2, 3 to 5, 6 to 10, > 10): healthy animal euthanasia (female 8, male 7), financial limitations (7 female, 7 male) and client wishing to continue treatment (9 female, 8 male)

Most commonly encountered dilemma: financial limitations (55%), healthy animal euthanasia (7%), client wishing to continue treatment (14%), other (5%), none give (19%)

Epp und Waldner 2012, Canada [32] weak Not standardized, Scale 1–5, 1 no stress, 3 moderate, 5 severe stress A sample consisting of 823 veterinary (44.7% male, 54.8% female, without 4) in a cross-sectional study (75.9% practice, 11.1% academia, 5.2% industry, 7.8% government)

2% reported no job-related stress, 5% reported severe stress, whereas the majority (53%) reported moderate stress. No significance of median stress scores among veterinarians working in practice, industry, government, or academia (p = 0.74). For each group, the median reported stress score was 3 on a scale of 5. Stress was higher among those who had graduated in the past 2 decades compared with those who graduated before 1990 (p = 0.005), among women compared with men (p < 0.001), and among those who worked more than 40 h per week (p = 0.001). The types of stress reported by respondents differed by work environment; workload and client-related problems were most common among veterinarians working in a practice

Workload-related (Yes), p = 0,001: practice (79%), academia (64%), industry (70%), government (63%)

Client-related (Yes), p < 0,001: practice (62%), academia (30%), industry (26%), government (27%)

Hagen et al. 2020 [53], UK weak Questionnaire with closed and open questions within three sections: ‘current employment’, ‘about you’ and ‘you as an employer’ A sample consisting of 2472 veterinary (22,9% male, 76,8% female) in a cross-sectional study reasons to stay in a position (n = 701): team 56.7%, location 48.3%, family 34.4%; reasons to leave a position (n = 536): work-life balance 41.2%, management 39.6%, salary 33.8%; Assumptions by employers about leaving (not only veterinarians): family 32.6%, asked them to leave 24.1%, location 22.2%, work-life balance 22%, other 22%; most disliked aspects about profession (n = 2365): dealing with people 50.4%, work-life balance 26.6%, physical/mental stress 19.6%; what they would change (n = 2169): working hours 29.6%, more team support 16.9%, management 14.7%
Heath 2008, Australia [31] weak Not standardized (Respondents were asked to indicate whether they strongly agreed (SA: score = 1) agreed (A: 2), were neutral (N: 3), disagreed (D: 4) or strongly disagreed (SD: 5) with each statement) A sample consisting of 350 veterinary (25% males, 75% females) in a cross-sectional study

I felt significant and regular stress: 29 (SA), 41 (A), 14 (N), 14 (D), 2 (SD)

stress: significant and regular stress: 75% female, 57% male (p < 0.01); main factors (p < 0.001): help and support from boss, work-life-balance, adequacy of compensation; stress—boss as role model for behaviour (p < 0.05); stress—type/size of the practice; hours worked (no significance); hours worked—(troublesome) work-life-balance (p < 0.001)

Kogan et al. 2018, USA [33] weak Not standardized (involvement with near misses (NM) and adverse events (AE)) A sample consisting of 606 veterinary (22.6% male, 77.4% female) in a cross-sectional study

66.4% with near misses (NM), 29.5% with adverse events (AE) in the past 12 month. NM: 68.0% with short-term (≤ 1 week after the incident) negative impact; 36.4% with long-term (> 1 week after the incident) negative impact on personal life

For AE: 84.1% short-term and 56.2% long-term. NM: 37.6% less confidence in their ability as a doctor, 31.5% felt their confidence in their abilities had suffered, 29.5% ag less satisfied with their job, 26.5% felt burned out. AE: 44.3%) less confident in their ability as a doctor, 44.3% felt their confidence in their abilities had suffered, 42.4 less satisfied with their job, 37.7% felt burned out, 36.9% decrease in overall happiness, 35.1% felt that their professional reputation had been negatively impacted, 33.7% had problems sleeping, and 33.5% felt persistently guilty. – > 70.3% stress level outside of work had not impacted the number of NMs or AEs. 4.0% high stress outside of work had markedly increased the frequency of these incidents, 24.0% slightly increased the frequency of these incidents

Morello et al. 2019, USA [34] weak Not standardized (reciprocal effects of career, family and gender on elements of their professional life (diploma, income, inequality etc.) A sample consisting of 836 veterinary (59% males, 41% females) in a cross-sectional study income: private practice > academia***, small animal > large animal***, males > females***; practice ownership: males > females***, working time: private practice owner > other**, comments about their gender related to performance: females > males***. passion for the job the most importance factor, also finicial compensation and locaton. Emergency duties were the least influential factor. Women were more likely to report negative underemployment (i.e. the desire to work fewer hours) than men
Moses et al. 2018, North America (USA—Canada) [35] weak Not standardized (ethical conflict and moral distress) A sample consisting of 889 veterinary in a cross-sectional study Moral distress levels and coping methods: not being able to do the right thing: severe stress (73%), moderate—severe stress (78%), not being able to provide care they thought was appropriate: moderate—severe distress (69%), distressed or anxious about work: often (43%) > some-times (34%)