Skip to main content
PMC home page
PLOS ONE logoLink to PLOS ONE
. 2021 Jun 24;16(6):e0253111. doi: 10.1371/journal.pone.0253111

A preliminary study on assessment of wellbeing among veterinary medical house officers

Munashe Chigerwe 1,*, Linda Barter 2, Julie E Dechant 2, Jonathan D Dear 1, Karen A Boudreaux 3
Editor: Jenny Wilkinson4
PMCID: PMC8224950  PMID: 34166405

Abstract

Mental wellness is an important topic among practicing veterinarians. Peer reviewed studies focusing on veterinary house officers’ wellbeing are lacking in veterinary medicine. The aim of this study was to assess wellbeing of house officers using validated surveys for anxiety, burnout, depression, and quality of life. A cross-sectional survey of 103 house officers (residents, interns, and fellows) was performed. Respondents were invited to voluntarily complete the online surveys. Anxiety, burnout, depression, and quality of life were assessed using the Generalized Anxiety Disorder (GAD-7), Maslach Burnout Inventory (MBI), Patient Health Questionnaire (PHQ-9), and Short Form-8 (SF-8), respectively. Descriptive statistics were calculated. For qualitative analysis, respondents were requested to rate their perception of the level of stress regarding various work-related stressors. The first survey was completed in 2017 with 60 respondents of which 51 (85%) identified as females and nine (15%) identified as males. The second survey was completed in 2018 with 43 respondents of which 35 (81.4%) identified as females and 8 (18.6%) identified as males. Respondents reported high levels of burnout characterized by high levels of emotional exhaustion and lack of personal accomplishment but reported mild levels of anxiety and depression. The mental component of their quality of life score was lower than the general US population, whereas the physical component score was consistent with the general US population. Respondents indicated moderate scores of stress for concerns regarding patient management, research, teaching, work-life balance, relationships, organizational skills, time management, finances, and the mental and emotional impact of the work environment. The high levels of burnout, and low mental quality of life in house officers require specific intervention programs to improve wellbeing.

Introduction

Wellbeing among veterinarians is established as an area of concern for the veterinary profession in the United States [1–4] and other countries [5–9]. Factors that might increase the risk for mental illness in veterinarians include personality traits such as the tendency to be overachievers driven by perfectionism or neuroticism, and preference to work with animals rather than people that might lead to social isolation [5, 10, 11]. Work-related stressors such as long working hours, high client expectations, compassion fatigue, limited personal finances, possibility of client complaints and litigation, potential conflicts with peers [11], and being recently qualified [3, 12] have been suggested as other risk factors for mental illness in veterinarians. In addition to exposure to these risk factors, veterinary medical house officers (interns, residents, and fellows) might experience additional stressors including expectations to teach veterinary medical students, time constraints for studying for specialty board examinations, learning advanced clinical skills in their respective specialties, constant performance evaluation by supervisors and students, and designing and performing clinical research. Thus, it is anticipated that veterinary medical house officers might be at a high risk for anxiety, burnout, depression, and decreased quality of life.

House officers program at the University of California Davis, Veterinary Medical Teaching Hospital

The House Officers Program officers at the University of California Davis Veterinary Medical Teaching Hospital offers a maximum of 48 training positions composed of 39 residency positions and 9 internships/fellowship, each year. The residency programs are 3–4 years in duration, whereas the internships/fellowships are 1-year long. The number of house officers hired each year varies with the specialty. Residency programs with a small animal focus include, behavior, cardiology, dentistry and oral surgery, dermatology, neurology/neurosurgery, oncology, ophthalmology, radiation oncology, emergency/critical care, internal medicine, surgery, and zoological companion animal medicine and surgery. Residency programs with a large animal emphasis include comparative theriogenology, dairy production medicine, equine surgery, livestock production and herd health, and internal medicine (livestock or equine emphasis). Support services residency programs include anatomic pathology, anesthesiology, clinical pathology, nutrition, and diagnostic imaging/radiology. Fellowships/internships programs include equine field services, equine integrative sports medicine, large animal ultrasound, marine mammal and pathology, and small animal emergency. The responsibilities of house officers include primary patient care including after hours emergencies, teaching veterinary students, and client communication. Additionally, residents are required to perform clinical research, and complete requirements for specialty boards examinations.

Current mental health and wellness support for house officers

The University of California Davis campus through the Academic and Staff Assistance Program (https://www.hr.ucdavis.edu/departments/asap) offers cost-free services to house officers including mental health services that include managing anxiety and depression, self-care management including effective stress management, emotional intelligence, exercise, and work-related issues including assertiveness skills, bullying in the workplace, communication skills, and conflict resolution.

Current study

Peer reviewed studies focusing on veterinary house officers’ wellbeing are lacking in veterinary medicine. Studies on wellbeing of house officers are essential for program improvement by increasing awareness about mental health and providing wellness support. The objective of this preliminary study was to assess wellbeing of house officers using validated survey instruments (self-reported questionnaires) for anxiety, burnout, depression, and quality of life.

Materials and methods

Sampling and data collection

Sampling in 2017 and 2018 consisted of a non-probability, convenience, volunteer sample of house officers at the University of California Davis Veterinary Medical Teaching Hospital (VMTH). Email invitations to complete four survey instruments were sent with a link to an online survey tool (Qualtrics, Seattle, WA) through the secured VMTH portal allowing only invited house officers with appropriate login credentials to access the survey instruments. The email described the purpose of the study which was reiterated at the beginning of each survey instrument as that of gathering information to help improve the wellbeing of house officers. Each survey instrument also contained an electronic consent to participate in the study, as well as, the collection of demographic data, namely, gender, age, marital status, and dependents (spouse/partner, children, parents, grandparents, or other). Respondents were informed that the data collected for all instruments were confidential, and the anonymity of respondents was protected by removing all identifiable information before analysis. Questions were not presented in a forced choice format such that house officers could skip questions. The study was approved by the University of California-Davis, Institutional Review Board, which governs research with human participants.

Survey instruments

The majority of internships, residency, and fellowship programs at the institution of study commence in August of each year. To increase the enrollment sample size, the survey was open for two cohorts of house officers, from August 2017–November 2017 and August 2018–November 2018. The validated survey instruments used to assess anxiety, burnout, depression, and quality of life were the following:

Anxiety

The Generalized Anxiety Disorder (GAD-7) [13] is a self-administered questionnaire used as a screening tool for generalized anxiety disorders. The instrument is a 7-item survey, copyrighted (Pfizer Inc, New York, NY) but its usage is free [14]. The GAD-7 consists of 7 questions where house officers indicated the frequency with which they experienced designated problems. Scores were calculated by assigning a value of 0, 1, 2, or 3, to the response categories of ’not at all’, ’several days’, ’more than half the days’, and ’nearly every day’, respectively. The total score for each respondent was the sum of the scores for the seven items questions with a range from 0 to 21. Scores of 5–9 were considered indicative of mild anxiety, 10–14 moderate anxiety, and 15 or greater was considered severe anxiety. The internal consistency of the original GAD-7 instrument was excellent (Cronbach α = 0.92) [13].

Burnout

Burnout is defined as a state of physical and mental exhaustion related to caregiving activities or work [15]. The Maslach Burnout Inventory (MBI) [16] was a 22-item survey, copyrighted (Mind Garden Inc, Menlo Park, CA) and used for this study through a contractual agreement to measure individual burnout levels through the subscales of emotional exhaustion, depersonalization, and personal accomplishment which are identified as the key aspects to burnout, thereby providing a context for why burnout could possibly have occurred [16]. The emotional exhaustion subscale assesses feelings of overextension and exhaustion from work with total scores of ≤ 18, 19–26 and ≥ 27 indicating low, average and high levels of burnout, respectively. The score for the emotional exhaustion subscale for each respondent was a sum of responses to nine of the 22 items. The depersonalization subscale measures an impersonal response to other individuals (peers, students, staff, faculty or clients). The score for the depersonalization subscale for each respondent was a sum of responses to five of the 22 items. Depersonalization scores of ≤ 5, 6–9 and ≥ 10 indicated low, average and high levels of burnout, respectively. Total personal accomplishment subscale measures the house officer’s feelings of competence and success. The score for the personal accomplishment subscale for each respondent was the sum of responses to eight of the 22 items. Personal accomplishment scores of ≥ 40, 39–34 and ≤ 33 indicated low, average, and high levels of burnout, respectively. The reliability of the original MBI as determined by Cronbach α were 0.89, 0.77, and 0.74 for the emotional exhaustion, depersonalization, and personal accomplishment subscales, respectively [16].

Depression

The Patient Health Questionnaire (PHQ-9) [17] is a 9-item survey, copyrighted (Pfizer Inc, New York, NY) and free for use as a self-administered version of the PRIME-MD (Primary Care Evaluation of Mental Disorders) diagnostic instrument for common mental disorders, specifically focusing on depression to asked respondents to score nine depressive symptom criteria. The presence of each criterion during the previous 2 weeks was scored as 0 (not at all), 1 (several days), 2 (more than half the days), and 3 (nearly every day) resulting in a severity measure ranging from 0 to 27. Total score for each respondent was the sum of the scores from the nine items. Total scores of 0–4, 5–9, 10–14, 15–19, and 20–27, indicated mild, moderate, moderately severe, and severe levels of depression, respectively. The PHQ-9 is used to monitor the severity of depression and response to treatment as it is not a screening tool for depression. The internal reliability of the original PHQ-9 was excellent (Cronbach α = 0.89).

Quality of life

Health related quality of life is a multi-dimensional construct that reflects a patient’s perception of the impact of a disease and treatment on physical, psychological, and social function as related to overall well-being [18]. The Optum Short Form-8 Health Survey (SF-8) is an 8-item self-reported Likert scale instrument that assesses health related quality of life. The SF-8 has been established for the health domain scales of general health perception (GH), physical functioning (PF), role limitations due to physical health problems (role physical, RP), bodily pain (BP), energy/fatigue (vitality, VT), social functioning (SF), role limitation due to emotional problems (role emotional, RE), and psychological distress and well-being (mental health, MH) [19]. Two summary measures were determined, namely the physical component summary (PCS) and the mental component summary (MCS). Responses were standardized into scores for the eight dimensions using a commercial software made available through contractual agreement (Optum Pro CoRE, Eden Prairie, MN). Score of 50 points represent a reference average adult American population. Thus, scores below 50 correspond to deviations from normality and indicated a poorer quality of life, whereas scores above 50 points represented a better quality of life than that of the average adult American population [19]. Reliability of the original PCS and MCS were 0.88 and 0.82, respectively [19].

Qualitative data collection on perception of level of stress

House officers were requested to rate their perception of the level of stress (score 1 = least stressful; score 5 = most stressful) regarding concerns about their patients, research, teaching, work-life balance, family-related issues, personal health, relationships, organizational skills, time management, financial situations, living environment, physical environment of the VMTH, and mental and emotional impact of the environment of the VMTH. Additionally, house officers could make free text comments at end of the survey.

Data analysis

Descriptive statistics for response rate, gender, marital status, age, and whether they had dependents were calculated. Normality check of the data was performed by the Shapiro-Wilk test. When data were normally distributed, mean ± standard deviation (SD) was reported, whereas median and interquartile range (IQR) was reported for not normally distributed data. Reliability (internal consistency) of each survey instrument was determined by calculating Cronbach’s alpha (α). For the purposes of this study Cronbach’s α for the subscales (emotional exhaustion, depersonalization and personal accomplishment) for burnout were used for analysis as they provide context for why burnout has occurred. The Cronbach α’s for the mental component summary and physical component summary were used for analysis because they may guide specific intervention to improve the mental or physical components of quality of life. Scale Cronbach’s α was used for analysis for the Generalized Anxiety Disorder and Patient Health Questionnaire instruments because both instruments do not have subscales. Cronbach’s α of ≥ 0.7 was considered to indicate acceptable reliability [20]. The scores for each instrument from 2017 were compared to that from 2018 using a Wilcoxon rank sum test. Multivariate analysis of variance (MANOVA) was performed for the combined data from 2017 and 2018 cohorts to determine the association between the scores for each instrument and selected explanatory variables. Based on previous studies that reported effect of different variables that affect levels of psychological stress in practicing veterinarians [3, 9], gender, marital status, and age were considered variables of interest. To ensure that MANOVA was appropriate for variables that were not normally distributed, distribution of the residuals and homogeneity of variances were assessed. To further confirm appropriateness of the MANOVA, analysis was performed using ranks for data points of variables that were not normally distributed. Correlation between the scores for each survey instrument were determined by calculation of Pearson’s correlation coefficient (r). Commercial software (JMP Pro Version 15, SAS Institute Inc., Cary, NC) was used for analysis and P < 0.05 was considered significant. Perceptions on the level of stress for various work-related stressors were reported as median (range) scores. Content analysis was performed on free text comments.

Results

Respondents

The descriptive statistics including response rate, gender, age, marital status and dependents for the respondents is summarized in Table 1.

Table 1. Descriptive statistics of University of California Davis house officers in 2017 and 2018.

2017 2018
Response rate 34.3% (60/175) 36% (43/119)
Gender
Female 85% (51/60) 81.4% (35/43)
Male 15% (9/60) 18.6% (8/43)
*Age
26–30 59.3% (35/59) 55.8% (24/43)
31–35 35.6% (21/59) 34.9% (15/43)
36–40 5.1% (3/59) 9.3% (4/43)
Marital status
Single 73.3% (44/60) 72.1% (31/43)
Married 26.7% (16/60) 23.3% (10/43)
Engaged 0 4.6% (2/43)
Dependents 6 2
Open in a new tab

*One respondent did not indicate their age in 2017.

In our study, standardized reliability as indicated by Cronbach’s α for MBI (burnout), GAD-7 (anxiety), PHQ-9 (depression) and SF-8 (quality of life) instruments were 0.78, 0.93, 0.90, and 0.87, respectively, and were considered acceptable. Cronbach’s α for the MBI subscales, that is, emotional exhaustion, depersonalization, and personal accomplishment were 0.59, 0.60, and 0.88, respectively. Cronbach’s α for SF-8 subscales of mental component summary and physical component summary were 0.87 and 0.85, respectively, in our study.

Anxiety (GAD-7), burnout (MBI), and depression (PHQ-9)

Median (IQR) GAD-7 scores for anxiety were 5 (8.3), 5.5 (9), and 5 (9) in 2017, 2018, and combined data for the two years, respectively, indicating mild levels of anxiety. There was no difference (P = 0.922) in the GAD-7 anxiety scores in 2017 and 2018. Median (IQR) scores for comparisons between 2017 and 2018 for MBI are summarized in Table 2. The MBI scores revealed high levels of burnout in both 2017 and 2018. The scores for emotional exhaustion (P = 0.636), depersonalization (P = 0.853), and personal accomplishment (P = 0.434) were not different between 2017 and 2018. Median (IQR) for PHQ-9 scores were 7 (8.5), 7.5 (10.5) and 7 (9.8) for 2017, 2018, and combined data for the two years, respectively, indicating mild levels of depression.

Table 2. Comparison of scores (median and interquartile range) of burnout with Maslach Burnout Inventory (MBI) for University of California Davis house officers in 2017 and 2018.

Year 2017 Year 2018 Combined 2017 and 2018 P-value
Emotional exhaustion (EE) 29.5 (3–50) 27 (7–51) 27 (19.5) 0.636
Depersonalization (DP) 7 (0–26) 6.5 (0–23) 7 (9) 0.853
Personal accomplishment (PA) 32 (13–44) 33 (19–47) 32 (10) 0.434
Number of respondents 60 43 103
Open in a new tab

EE scores of ≤ 18, 19–26 and ≥ 27 indicate low, average, and high levels of burnout, respectively.

DP scores of ≤ 5, 6–9 and ≥ 10 indicate low, average, and high levels of burnout, respectively.

PA scores of ≥ 40, 39–34 and ≤ 33 indicate low, average, and high levels of burnout, respectively.

Row score comparisons with P < 0.05 between 2017 and 2018 are different.

Gender (model P = 0.0412) was a significant predictor of emotional exhaustion scores for the MBI, with higher scores reported in males compared to females (33.8 vs 26.9; P = 0.035). Gender was a significant predictor of PHQ-9 scores, with higher scores reported in males compared females (11.5 vs 7.8; P = 0.027). Gender was also a predictor of GAD-7 scores with higher scores reported in males compared to females (10.1 vs 6.9; P = 0.040).

Marital status (model P <0.0001) was significant predictor of emotional exhaustion (32.4 vs 26.5; P <0.033) and depersonalization (11.2 vs 7.5; P = 0.011) scores of the MBI (burnout) with higher scores reported in married compared to single respondents for both subscales. Marital status was also a predictor of personal accomplishment subscale of MBI with higher scores reported in single compared to married respondents (32.8 vs 28.6; P = 0.010). Marital status was also a predictor of mental component summary subscale of the quality of life (Short Form-8) with higher scores reported in single compared to married respondents (42.5 vs 31.2; P<0.0001). Furthermore, marital status was a predictor of depression (PHQ-9) and anxiety scores (GAD-7) with higher scores reported for married compared to single respondents for PHQ-9 (12.0 vs 7.2; P = 0.0006) and GAD-7 (12.5 vs 5.8; P<0.0001).

Emotional exhaustion subscale of the MBI scores were positively correlated with PHQ-9 (r = 0.59) and GAD-7 scores (r = 0.50) but negatively correlated (r = -0.52) with mental component summary scale (MCS) scores of the SF-8 (quality of life). Depersonalization subscale of the MBI scores were positively correlated with PHQ-9 (r = 0.47) and GAD-7 scores (r = 0.54) but negatively correlated with MCS (r = -0.51). Personal accomplishment subscale of the MBI scores was negatively correlated with PHQ-9 (r = -0.49) and GAD-7 scores (r = -0.44) but positively correlated with MCS (r = 0.40). The MCS scores were negatively correlated with PHQ-9 (r = -0.72) and GAD-7 scores (r = -0.67). The GAD-7 and the PHQ-9 scores were positively correlated (r = 0.76). Age was not a significant predictor of scores for any of the survey questionnaires (P = 0.405).

Quality of life

Quality of life scores for 2017 and 2018 are summarized in Table 3. All mean scores for the 8 dimensions were below 50, except RP and BP dimensions in 2017. Scores for RE, MH, VT, GH, RP, PF, and BP were not different (P >0.05) between 2017 and 2018 (Table 3). The SF dimension was lower (P = 0.046) in 2018 (41.4 ± 8.3) compared to 2017 (45.0 ± 9.6), but both scores were below 50. The MCS was below 50 for 2017 and 2018, whereas the PCS was above 50 for 2017 and 2018. The MCS and PCS score were not different (P >0.05) between 2017 and 2018 (Table 3).

Table 3. Comparison of quality of life dimensions scores (mean ± standard deviation) with Short Form-8 (SF-8) scores among University of California Davis house officers in 2017 (n = 60) and 2018 (n = 43).

Year 2017 Year 2018 Combined 2017 and 2018 P-value
Role emotional (RE) 44.6 ± 7.8 42.4 ± 7.9 43.7 ± 7.9 0.162
Mental health (MH) 42.4 ± 10.3 40.2 ± 10.2 41.5 ± 10.3 0.297
Social functioning (SF) 45.0 ± 9.6 41.4 ± 8.3 43.5 ± 9.2 0.046
Vitality (VT) 46.0 ± 8.7 45.4 ± 6.9 45.8 ± 8.0 0.736
General health perception (GH) 45.2 ± 7.0 43.6 ± 8.0 44.5 ± 7.4 0.276
Role physical (RP) 50.1 ± 5.3 48.9 ± 5.3 49.6 ± 5.3 0.262
Physical functioning (PF) 48.7 ± 7.6 49.1 ± 5.8 48.9 ± 6.8 0.751
Bodily pain (BP) 51.3 ± 7.4 49.9 ± 6.6 50.7 ± 7.1 0.341
Mental component summary (MCS) 41.1 ± 12.5 37.9 ± 12.1 39.8 ± 12.4 0.196
Physical component summary (PCS) 51.2 ± 6.3 50.4 ± 6.9 50.9 ± 6.5 0.550
Open in a new tab

Scores below 50 points corresponded to deviations from normality and indicate a poorer quality of life, whereas scores above 50 points represented a better quality of life than that of the average adult American population [19]. Row score comparisons with P < 0.05 between 2017 and 2018 are different.

Quantitative and qualitative data collection on perception of level of stress

Summary of perception of level of stress among house officers are summarized in Table 4. For both years, respondents indicated similar moderate scores of stress for concerns regarding patient management, research, teaching, work-life balance, relationships, organizational skills, time management, finances, and the mental and emotional impact of the work environment of the VMTH.

Table 4. Median (range) scores for perception of stress regarding various aspects of training among house officers in 2017 (n = 60) and 2018 (n = 43).

Question 2017 2018
Concerns about patient management 4 (1–5) 4 (1–5)
Concerns about my research 3 (1–5) 3 (1–5)
Concerns about my teaching 3 (1–5) 3 (1–5)
Work/life balance 3 (1–5) 3 (1–5)
Family-related issues 2 (1–5) 2 (1–5)
Personal health 2 (1–5) 3 (1–5)
Relationships 3 (1–5) 3 (1–5)
Organizational skills 3 (1–5) 3 (1–5)
Time management 3 (1–5) 4 (1–5)
Financial situation 3 (1–5) 3 (1–5)
Living environment 2 (1–4) 2 (1–5)
Physical environment of the VMTH 2 (1–5) 2 (1–5)
Mental and emotional impact of the environment of the VMTH 3 (1–5) 3
Open in a new tab

The stem of the question was framed as: ‘From least stressful to most stressful, please rate the following with regards to your life as an employee of the VMTH:’

Scores range from 1 (least stressful) to 5 (most stressful).

VMTH—Veterinary Medical Teaching Hospital.

Content analysis from free text comments from respondents indicated that financial instability, lack of collegiality among supervising faculty, lack of appropriate feedback from supervising faculty, worry about employment opportunities after graduation from programs, difficult client interactions, lack of mentoring by faculty supervisors, low quality of mental health, and coping with high academic demands of training were significant sources of stress.

Discussion

The findings in this study suggest that veterinary house officers consistently experienced high levels of burnout as indicated by personal accomplishment and emotional exhaustion scores. Findings further suggest that burnout might be related to stressors such as lack of time management and organizational skills, lack of research and teaching skills, financial instability, lack of balancing work and non-work activities, and undesirable working environment in sections of the VMTH. While there are no comparable studies in veterinary medicine, causes of burnout in medical residents include sleep deprivation, high workload, unsatisfactory salaries, [21] and taking many responsibilities at work [22, 23]. The consequences of burnout in medical residents that are applicable to veterinary house officers include increased risk for medical errors, adverse effects on patient safety, depression [15], and suicidal ideation [24]. Burnout results from an individual being overstretched in their work place. Therefore, if the source of burnout is removed or reduced, the stress experienced by an individual is reduced whereas depression affects one’s holistic life (work and outside work). Burnout can predispose to depression and in our study, the levels of burnout require attention.

High levels of burnout in medical residents were associated with high levels of anxiety during medical school [25]. In contrast, participants in our study reported mild levels of anxiety, which is desirable, despite high levels of anxiety reported in North American veterinary students [26, 27]. While participants in our study reported mild levels of depression, surveys in the United States indicated that veterinarians experience high levels of depression and suicidal ideation compared to the US general population [1–4]. These differences in anxiety and depression levels suggest that the structure of a large house officer training program might create a support network of like-minded peers that may alleviate some of the stressors experienced by veterinary students and practicing veterinarians, consistent with previous studies [3]. Furthermore, house officers may be protected from the daily stressors of veterinary practice because they are in a supervised training programs that allow for protected time for non-clinical activities. However, these aspects of house officer training do not necessarily result in durable coping strategies or resilience and might not be transferrable to post-training working environment. Therefore, it is important to note that house officers will join the veterinary workforce after graduating and will be exposed to the stressors associated with high levels of depression among veterinarians, which may result in deterioration of their mental health and wellbeing.

Assessment of quality of life allows identification of the most compromised dimensions of well-being and therefore, the ability to intervene by providing resources for house officers. Quality of life assessments allow comparison of the house officers in our study to a reference United States adult population, and therefore are interpreted as deviations from normality. Participants in our study reported lower quality of mental health as indicated by low scores for role emotional (RE), mental health (MH), social functioning (SF), vitality (VT), general health perception (GH) and the mental component summary (MCS). This result might be related to the work-related stressors indicated by the results of the qualitative analysis. In contrast, house officers in our study had physical component summary scores >50 consistent with their relatively young age (26–35 years). This is because young adults are likely to experience better physical health compared to older individuals, and previous studies have reported that physical component summary scores decrease with advanced normal aging [28].

In our study male respondents had higher scores for emotional exhaustion, PHQ-9 (depression) and GAD-7 scores (anxiety) compared to female respondents. This result contrasts with previous studies that reported higher risk for psychological distress for female veterinarians compared to males [3, 7, 9]. However, it should be noted that female respondents were overrepresented (83.5%) in our study, and therefore our study results should be interpreted with caution. Married respondents reported higher scores for all subscales of burnout, GAD-7, and PHQ-9, but lower scores for the mental component summary subscale for SF-8 (quality of life) suggesting higher psychological distress compared to unmarried respondents. A possible reason for this finding might be increased additional stress associated with managing a family among married respondents. Previous studies indicated that negative at-home interference such as communication with clients after office hours potentially predisposes to strained spousal relationships for married respondents compared to unmarried respondents [29, 30]. In contrast, other studies have reported a protective psychological of effect of marriage [31]. It should be noted that in our study unmarried respondents were overrepresented (75%) and therefore our results should be interpreted with caution. Age was not a significant predictor of survey questionnaire scores in our study, consistent with previous studies that indicated that poor mental health outcomes in young veterinarians is a combination of other personal and career attributes [5]. Correlations and direction of the correlations (negative or positive) among scores of the various instruments when gender or marital status were expected.

The results of our study are a basis for improvements and intervention of training programs to reduce burnout and improve wellbeing among house officers. While burnout might be inevitable among house officer training programs, awareness about burnout is crucial to short-term and long-term improvements of these training programs. Awareness regarding burnout can be disseminated during program orientation or during performance evaluation of house officers. A significant proportion of veterinarians have been reported to have negative attitudes towards treatment and social support for mental illness [32] and might not seek help when required. Therefore, awareness of burnout for house officers should include availability of resources, and recommendations for house officers to consider accessing the resources. Specific examples of resources include a veterinary practice house officer ombudsman/woman, and on-campus counselling services. The VMTH at our institution appointed a faculty member (Director of House Officer Affairs and Education) to collaborate with a Graduation Clinical Education Committee to resolve concerns regarding house officers. Furthermore, house officers might require representation of their training related concerns at the VMTH level through 2–4 elected (depending on the size of the program) chief house officers.

The personal accomplishment subscale of burnout assessed feelings of competence and successful achievement in a house officer’s work. Personal accomplishment and depersonalization determine emotional exhaustion [33]. Consequently, focusing on early signs of emotional exhaustion is not recommended because when the signs of emotional exhaustion appear, the burnout process is already underway [33]. The high scores of emotional exhaustion, low scores of personal accomplishment, lack of collegiality among faculty, and lack of appropriate feedback from faculty reported by house officers indicate the need for improvement in interactions between house officers and faculty to create a safe learning environment. To increase the sense of personal accomplishment and counteract burnout, specific training programs have been recommended for employees in various fields [34]. These training programs include role-playing to provide success experiences (enactive mastery), models of performances (vicarious experiences), coaching and encouragement (verbal persuasion) [34]. Specifically, veterinarians supervising house officers should behave as role models when communicating with other veterinarians or clients, provide constructive feedback, and effectively mentor house officers on research and teaching skills. House officers have variable teaching experience, and respondents in our study identified teaching students as an important stressor. Therefore, basic interactive courses with application exercises (either in online or in-person format) on how students learn should be incorporated in the training to improve house officers’ teaching skills and confidence.

Further long-term approaches to reduce burnout for house officers include incorporation of mindfulness-based stress reduction (MBSR) intervention programs during training [35]. Mindfulness-based stress reduction intervention programs are structured programs that employ mindful meditation to alleviate suffering associated with physical, psychosomatic, and psychiatric disorders [35]. The programs are non-religious and non-esoteric and help individuals develop enhanced awareness of mental experiences [35]. Consequently, this improves an individual’s self-care and well-being, including during periods of high stress [36].

Limitations of our study include the small sample size, from a single institution and therefore the results have limited external validity and cannot be generalized to house officers other than those enrolled in the study. Participation in the study was voluntary and may introduce response bias as house officers with an interest in the topic might have self-selected to complete the surveys. The surveys consisted of self-reported data to which social desirability bias may be present as participants may respond to items in what they feel are socially acceptable selections. Results from self-reported data are also dependent on the participants introspective ability, honesty, and ability to interpret the question which leads to further limitations of our study. With a volunteer sample, sampling bias may also be present as personal motivations for completing the instruments was unknown. Due to the small sample size, our study did not assess influence of the training stage (for instance, Year 1 compared to Year 2 of training) on wellbeing of house officers. Overrepresentation of females in our house officers study population is consistent with a relative higher proportion of practicing female veterinarians [3]. Future studies should consider cross-sectional studies evaluating wellbeing of house officers in different programs across North America. In medical residencies, burnout was significantly higher in surgical/urgency than in other clinical specialties [37]. Urology, neurology, emergency medicine, and general surgery were also associated with higher risks of burnout relative to training in internal medicine [25]. Therefore, further studies should also evaluate influence of training stage and specialty on wellbeing of house officers. Our study only focused on factors associated with psychological stress but not aspects of house officers’ training that improve mental health and wellness. Future studies should focus on surveys such as measure of subjective happiness [38] that evaluate factors that positively enhance mental health and wellness among house officers during training.

Conclusion

Veterinary house officers experience high levels of burnout characterized by high levels of emotional exhaustion and lack of personal accomplishment, and mild levels of anxiety and depression. The mental component of quality of life of house officers is lower than the general US population, whereas the physical component of their quality of life is consistent with the general US population. Patient management, research, teaching, work-life balance, relationships, organizational skills, time management, finances, and the mental and emotional impact of the work environment were qualitatively identified as important stressors affecting wellbeing.

Acknowledgments

The authors thank Dr. Kate Hopper, Jan Harlan, and Nicole Adams for their assistance in data collection. The authors thank all house officers who completed the surveys.

Data Availability

Data cannot be shared publicly because the data represents individual house officers' responses from a single institution (University of California Davis School of Veterinary Medicine). The data presented in our study potentially contain sensitive identifying personal information such as mental health data which have psychological risks to the respondents. The minimal aggregated data set from the research are available from University of California Institutional Review Board Committee (contact via email provided below) for researchers who meet the criteria for access to confidential data. We have provided contacts (non-authors of this paper) to which data requests may be sent to obtain aggregated data. The contact is the institutional representative for the ethics committee: University of California Davis: Office of Research IRB Administration 1850 Research Park Drive Davis, CA 95618-6153 Phone: (530) 754-7679 Fax: (530) 754-7894 Email: ORExecutiveMgtAsst@ad3.ucdavis.edu.

Funding Statement

The authors received no specific funding for this work.

References

  • 1.Skipper GE, Williams JB. Failure to acknowledge high suicide risk among veterinarians. J Vet Med Educ. 2012;39:79–82. doi: 10.3138/jvme.0311.034R [DOI] [PubMed] [Google Scholar]
  • 2.Nett RJ, Witte TK, Holzbauer SM, Elchos BL, Campagnolo ER, Musgrave KJ, et al. Notes from the field: prevalence of risk factors for suicide among veterinarians—United States, 2014. MMWR Morb Mortal Wkly Rep. 2015;64:131–132. [PMC free article] [PubMed] [Google Scholar]
  • 3.Nett RJ, Witte TK, Holzbauer SM, Elchos BL, Campagnolo ER, Musgrave KJ, et al. Risk factors for suicide, attitudes toward mental illness, and practice–related stressors among U.S. veterinarians. J Am Vet Med Assoc. 2015;247:945–955. doi: 10.2460/javma.247.8.945 [DOI] [PubMed] [Google Scholar]
  • 4.Fowler HN, Holzbauer SM, Smith KE, Scheftel JM. Survey of occupational hazards in Minnesota veterinary practices in 2012. J Am Vet Med Assoc. 2016;248:207–218. doi: 10.2460/javma.248.2.207 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Bartram DJ, Baldwin DS. Veterinary surgeons and suicide: a structured review of possible influences on increased risk. Vet Rec. 2010;166:388–397. doi: 10.1136/vr.b4794 [DOI] [PubMed] [Google Scholar]
  • 6.Platt B, Hawton K, Simkin S, Mellanby RJ. Systematic review of the prevalence of suicide in veterinary surgeons. Occup Med. 2010;60:436–446. doi: 10.1093/occmed/kqq044 [DOI] [PubMed] [Google Scholar]
  • 7.Hatch PH, Winefield HR, Christie BA, Lievaart JJ. Workplace stress, mental health, and burnout of veterinarians in Australia. Aust Vet J. 2011;89:460–468. doi: 10.1111/j.1751-0813.2011.00833.x [DOI] [PubMed] [Google Scholar]
  • 8.Platt B, Hawton K, Simkin S, Mellanby RJ. Suicidal behaviour and psychosocial problems in veterinary surgeons: a systematic review. Soc Psychiatry Psychiatr Epidemiol. 2012;47:223–240. doi: 10.1007/s00127-010-0328-6 [DOI] [PubMed] [Google Scholar]
  • 9.Shirangi A, Fritschi L, Holman CD, Morrison D. Mental health in female veterinarians: effects of working hours and having children. Aust Vet J. 2013;91:123–130. doi: 10.1111/avj.12037 [DOI] [PubMed] [Google Scholar]
  • 10.Bartram DJ, Baldwin DS. Veterinary surgeons and suicide: Influences, opportunities and research directions. Vet Rec. 2008;162:36–40. doi: 10.1136/vr.162.2.36 [DOI] [PubMed] [Google Scholar]
  • 11.Stoewen DL. Suicide in veterinary medicine: Let’s talk about it. Can Vet J. 2015;56:89–92. [PMC free article] [PubMed] [Google Scholar]
  • 12.Dawson BF, Thompson NJ. The effect of personality on occupational stress in veterinary surgeons. J Vet Med Educ. 2017;44:72–83. doi: 10.3138/jvme.0116-020R [DOI] [PubMed] [Google Scholar]
  • 13.Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder—The GAD-7. Arch Intern Med. 2006;166:1092–1097. doi: 10.1001/archinte.166.10.1092 [DOI] [PubMed] [Google Scholar]
  • 14.Williams N. The GAD-7 questionnaire. Occup Med. 2014; 64:224. [DOI] [PubMed] [Google Scholar]
  • 15.Ishak WW, Lederer S, Mandili C, Nikravesh R, Seligman L, Vasa M, et al. Burnout during residency training: A literature review. J Grad Med Educ. 2009;1:236–242. doi: 10.4300/JGME-D-09-00054.1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Maslach C, Jackson SE: Maslach Burnout Inventory-Human Services Survey (MBI-HSS). In: Maslach C, Jackson SE, Leiter P, editors. Maslach Burnout Inventory Manual. Mountain View: Consulting Psychologists Press; 1996. pp. 1–48. [Google Scholar]
  • 17.Kroenke K, Spitzer RL, Williams JBW. The PHQ-9: Validity of a Brief Depression Severity Measure. J Gen Intern Med. 2001;16:606–613. doi: 10.1046/j.1525-1497.2001.016009606.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Guyatt GH, Feeny DH, Patrick DL. Measuring health-related quality of life. Ann Intern Med. 1993;118: 622–629. doi: 10.7326/0003-4819-118-8-199304150-00009 [DOI] [PubMed] [Google Scholar]
  • 19.Ware JE Jr, Kosinski M, Turner-Bowker DM, et al. How to score and interpret single-item health measures: A manual for users of the SF-8 TM Health Survey, Lincoln, RI: Quality Metric Incorporated; 2001. [Google Scholar]
  • 20.Bland J, Altman D. Statistics notes: Cronbach’s alpha. BMJ. 1997; 314:275. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Lockley SW, Cronin JW, Evans EE, Cade BE, Lee CJ, Landrigan CP, et al. Effect of reducing interns’ weekly work hours on sleep and attentional failures. N Engl J Med. 2004;351:1829–1837. doi: 10.1056/NEJMoa041404 [DOI] [PubMed] [Google Scholar]
  • 22.Geurts S, Rutte C, Peeters M. Antecedents and consequences of work-home interference among medical residents. Soc Sci Med. 1999;48:1135–1148. doi: 10.1016/s0277-9536(98)00425-0 [DOI] [PubMed] [Google Scholar]
  • 23.Thomas NK. Resident Burnout. JAMA. 2004;292:2880. doi: 10.1001/jama.292.23.2880 [DOI] [PubMed] [Google Scholar]
  • 24.Dyrbye LN, Shanafelt T. A narrative review on burnout experienced by medical students and residents. Med Educ. 2016;50:132–149. doi: 10.1111/medu.12927 [DOI] [PubMed] [Google Scholar]
  • 25.Dyrbye LN, Burke SE, Hardeman RR, Herrin J, Wittlin NM, Yeazel M, et al. Association of clinical specialty with symptoms of burnout and career choice regret among us resident physicians. JAMA. 2018;320:1114–1130. doi: 10.1001/jama.2018.12615 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Siqueira Drake AA, Hafen M Jr, Rush BR, Reisbig AM. Predictors of anxiety and depression in veterinary medicine students: a four-year cohort examination. J Vet Med Educ. 2012; 39:322–330. doi: 10.3138/jvme.0112-006R [DOI] [PubMed] [Google Scholar]
  • 27.Nahar VK, Davis RE, Dunn C, Layman B, Johnson EC, Dascanio JJ, et al. The prevalence and demographic correlates of stress, anxiety, and depression among veterinary students in the Southeastern United States. Res Vet Sci. 2019;125:370–373. doi: 10.1016/j.rvsc.2019.07.007 [DOI] [PubMed] [Google Scholar]
  • 28.Kaarlola A, Tallgren M, Pettilä V. Long-term survival, quality of life, and quality-adjusted life-years among critically ill elderly patients. Crit Care Med. 2006;34: 2120–2126. doi: 10.1097/01.CCM.0000227656.31911.2E [DOI] [PubMed] [Google Scholar]
  • 29.Hansez I, Schins F, Rollin F. Occupational stress, work-home interference and burnout among Belgian veterinary practitioners. Ir Vet J 2008;61:233–241. doi: 10.1186/2046-0481-61-4-233 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Perret JL, Best CO, Coe JB, Greer AL, Khosa DK, Jones-Bitton A. Association of demographic, career, and lifestyle factors with resilience and association of resilience with mental health outcomes in veterinarians in Canada. J Am Vet Med Assoc. 2020; 15;257:1057–1068. doi: 10.2460/javma.2020.257.10.1057 [DOI] [PubMed] [Google Scholar]
  • 31.Rendall MS, Weden MM, Favreault MM, Waldron H. The protective effect of marriage for survival: a review and update. Demography 2011;48:481–506. doi: 10.1007/s13524-011-0032-5 [DOI] [PubMed] [Google Scholar]
  • 32.Kassem AM, Witte TK, Nett RJ, Carter KK. Characteristics associated with negative attitudes toward mental illness among US veterinarians. J Am Vet Med Assoc. 2019; 254: 979–985. doi: 10.2460/javma.254.8.979 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.van Dierendonck D, Schaufeli WB, Buunk BP. Toward a process model burnout: results from a secondary analysis. Eur J Work and Organ Psychol. 2001;10:41–52. [Google Scholar]
  • 34.Bandura A. Self Efficacy: The Exercise of Control. New York: W.H Freeman; 1997. [Google Scholar]
  • 35.Grossman P, Niemann L, Schmidt S, Walach H. Mindfulness-based stress reduction and health benefits: A meta-analysis. J Psychosom Res. 2004; 57: 35–43. doi: 10.1016/S0022-3999(03)00573-7 [DOI] [PubMed] [Google Scholar]
  • 36.Hassed C, de Lisle S, Sullivan G, Pier C. Enhancing the health of medical students: outcomes of an integrated mindfulness and lifestyle program. Adv Health Sci Educ Theory Pract. 2009;14: 387–398. doi: 10.1007/s10459-008-9125-3 [DOI] [PubMed] [Google Scholar]
  • 37.Rodrigues H, Cobucci R, Oliveira A, Cabral JV, Medeiros L, Gurgel K, et al. Burnout syndrome among medical residents: A systematic review and meta-analysis. PLOS ONE. 2018. 13(11). doi: 10.1371/journal.pone.0206840 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Lyubomirsky S, Lepper HS. A measure of subjective happiness: preliminary reliability and construct validation. Social Indicators Research 1999; 46: 137–155. [Google Scholar]

Decision Letter 0

Serge Brand

28 Oct 2020

PONE-D-20-17459

A preliminary study on assessment of wellbeing among veterinary medical house officers

PLOS ONE

Dear Dr. Chigerwe,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Dec 12 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Serge Brand

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please include additional information regarding the survey or questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed a questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information.

3. In your Methods section, please provide additional information about the participant recruitment method and the demographic details of your participants. Please ensure you have provided sufficient details to replicate the analyses such as: a) the recruitment date range (month and year), b) a description of any inclusion/exclusion criteria that were applied to participant recruitment, c) a table of relevant demographic details, d) a statement as to whether your sample can be considered representative of a larger population, e) a description of how participants were recruited, and f) descriptions of where participants were recruited and where the research took place.

4.We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

Additional Editor Comments (if provided):

Dear Authors,

As you'll see, three Reviewers and experts in the field commented on your manuscript. While they identified some merits, they also raised major concerns. Herewith, I do invite you to try to cope with the Reviewers' concerns. When re-submitting a revision, please ensure to use the track change mode. Note that asking for a revision does not imply an acceptance.

Sincerely,

Serge Brand

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for the opportunity to review the article. This topic has become more warranted given more attention is paying for the wellbeing of people who in veterinary and animal welfare profession. I have got a few queries and comments for the authors to consider and address:

1. The authors sampled two cohorts of participants in 2017 and 2018. I would like the authors to provide a bit more information (aside from what was written on p. 4, line 92 to 94) on why they recruited in these two different period. Was it because they mainly just want to increase the sample size for analysis?

2. Aside from the authors reporting the Cronbach Alphas for the measures from their own study in the results section, I suggest they also report the measures' initial Cronbach Alphas from the original studies in the Instrument sections.

3. I am a bit confusing with the "Qualitative data collection on perception of level of stress". It looks to me (based on the results) that a scale was used to detect the perception but then there was a free text comments for participants to write qualitative comments in relation to stress. When I read the results, it looks like the authors just reported numbers that matched categories, rather than really engaging with the qualitative data to illustrate the content. This raised the question to me whether the identification of themes provided was mainly based on content analysis. I think the authors need to provide a bit more discussion and distinction. My original thought was that aside from identifying themes from the free texts, there will be some captions be used to further illustrate those themes but that does not seem to be the case. I would probably reframe it as using the score to identify perception of level of stress. Free text enables participants to provide more in-depth descriptions and those descriptions were sorted by content analysis. The way it is being described here would have made other readers to assume some qualitative comments be illustrated to further support the descriptive data.

Reviewer #2: 1. Thank you for the opportunity to review this submission.

2. The paper reports on a small-scale cross-sectional survey of well-being among veterinary medical house officers at a training organization in the USA. It would be helpful to have more context, e.g. the responsibilities, support and duration of a veterinary house officer’s role, as not all training programs use this structure.

3. Data and data analysis

4. Data were collected by a cross-sectional study with 103 respondents, who completed online surveys on anxiety, burnout, depression and quality of life, using validated published scales. The data were collected in 2017 (N=60, 85% female, 34% response rate) and 2018 (43 respondents, 81% female, 36% response rate).

5. Some points to clarify:

6. On p. 16 we learn that it’s a 2-year training program so it is important to clarify whether participants in each year were different cohorts or the same people surveyed twice (a repeated measures design).

7. Participants were asked to rate, not rank, their perceptions of stress associated with the listed stressors, and this is quantitative, not qualitative, data.

8. The open-ended questions do provide qualitative data; there is no information on how this was analyzed (e.g. thematic analysis).

9. ‘Selected independent variables’ are mentioned on p. 7 but it’s not clear how they were selected or what they or the dependent/criterion variables were. There is no hypothesis-testing.

10. P. 7 states that demographic variables were included; p. 9 states that they were omitted. Without these analyses, there is no information on which groups, if any, were more affected.

11. Cronbach’s alpha is given for the scales overall but is also required for each sub-scale, as the analyses were based on these.

12. There is insufficient information on how the quality of life scores were derived. The burnout measures need number of items and response options.

13. The statistical analyses compare scores between the 2017 and 2018 groups. However, there is no testing of sample vs. population distributions.

14. Findings are over-stated. For example, conclusions are made about overall high levels of burnout when scores are on, or within a point of, a threshold and there is wide variation in the data.

15. The list of stressors with ‘relatively higher scores’ includes nearly all of them (10 of 13), and 8/13 score 3 on the 5 point scale. As scores are rounded to whole numbers this suggests most were at the scale midpoint, not ‘high’ scores.

16. Overall, the data do not give strong evidence of problems throughout the cohort. More interestingly perhaps, variation in the data suggests that some individuals may be experiencing difficulties, so targeted solutions matched to individual needs may be required.

17. Conclusions

18. The paper focuses on problems and argues for interventions but the evidence is thin. There is little said about the null findings for several variables or that, where others exceeded cut-offs, it was never by much. There are considerable problems – logical and statistical – with saying that a score of 49.1 is fine but 50.1 is problematic, for instance.

19. As the PHQ is described, it’s not possible to be ‘not at all’ depressed; at best people have to be ‘mildly’ depressed. Depression is a serious diagnosable mental health condition, so telling participants that they are ‘mildly depressed’ based on these scores could cause problems in itself.

20. Claims that participants ‘consistently experienced high levels of burnout’ do not match the data, from which burnout does not appear to be extreme or widespread.

21. The authors suggest that ‘burnout was associated with stressors such as…’ but no tests of association (e.g. correlation) are presented.

22. Conclusions about possible intervening variables - coping and resilience, and wider implications e.g. transfer to working environments, are not part of the study.

23. Although there is little evidence of problems, the wider literature is used to argue that there are in fact problems which need to be solved. Scale ranges suggest that some participants may be experiencing problems but this does not show which interventions are required or by whom. Targeted approaches focused on needs would seem preferable. The suggested solutions are not based on the study findings.

24. Clarity

25. It’s well written and readable, except that the use of acronyms in the results section means constantly referring back to what each one means. There’s also a constant need to refer back to information on score thresholds to work out what mean scores indicate.

26. Summary

27. Overall, then, this is a small-scale study in one training institution which does not allow conclusions to be drawn about a profession, or even veterinary training, as a whole. The findings are over-stated and focus too much on the negative, and the suggested interventions are unrelated to the study findings. While professional well-being in veterinarians is interesting and important, the conclusions should be carefully aligned with the findings.

Reviewer #3: Comments for the Authors:

Thank you for the opportunity to review your manuscript. Wellbeing of veterinarians is an important scientific topic and deserves to be investigated.

After reading your manuscript one is confused what the purpose was of carrying out the study in two consecutive school-years? What made you think that veterinarians’ wellbeing may be changed in one year? What happened in that period that might approve this study design? Another question is how many people from the 2017 and 2018 samples are actually the same persons? We don’t know anything about that after reading your description of the results? Further, as the samples from 2017 and 2018 are not dependent nor independent but mixed, there is no statistical test that might compare the respondents wellbeing in 2017 and 2018. In conclusion, you have chosen a wrong method to fulfill the purpose of the study. Therefore, unfortunately I have to recommend the editor to reject your paper.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 Jun 24;16(6):e0253111. doi: 10.1371/journal.pone.0253111.r002

Author response to Decision Letter 0

15 Mar 2021

Reviewer #1:

Thank you for the opportunity to review the article. This topic has become more warranted given more attention is paying for the wellbeing of people who in veterinary and animal welfare profession. I have got a few queries and comments for the authors to consider and address:

AU: Thank you for taking time to review our manuscript. Below is point-by-point response to your comments. To make it easier for you, we highlighted responses to your comments in green.

1. The sampled two cohorts of participants in 2017 and 2018. I would like the authors to provide a bit more information (aside from what was written on p. 4, line 92 to 94) on why they recruited in these two different period. Was it because they mainly just want to increase the sample size for analysis?

AU: Yes, that is correct that we wanted to increase the sample size. This was because data analysis of one of the instruments (Quality of life scores which requires standardization of responses using a special software) for the 2017 cohort was completed in 2018. Therefore, to increase the sample size we enrolled the second group of house officers in 2018.

In response to your comment, we added a comment indicating that another reason for enrolling 2 cohorts was to increase sample size. Please see Materials and Methods under “Survey instruments”.

2. Aside from the authors reporting the Cronbach Alphas for the measures from their own study in the results section, I suggest they also report the measures' initial Cronbach Alphas from the original studies in the Instrument sections.

AU: We included the Cronbach’s alphas for each instrument. Please see Materials and Methods under “Survey instruments”.

3. I am a bit confusing with the "Qualitative data collection on perception of level of stress". It looks to me (based on the results) that a scale was used to detect the perception but then there was a free text comments for participants to write qualitative comments in relation to stress. When I read the results, it looks like the authors just reported numbers that matched categories, rather than really engaging with the qualitative data to illustrate the content. This raised the question to me whether the identification of themes provided was mainly based on content analysis. I think the authors need to provide a bit more discussion and distinction. My original thought was that aside from identifying themes from the free texts, there will be some captions be used to further illustrate those themes but that does not seem to be the case. I would probably reframe it as using the score to identify perception of level of stress. Free text enables participants to provide more in-depth descriptions and those descriptions were sorted by content analysis. The way it is being described here would have made other readers to assume some qualitative comments be illustrated to further support the descriptive data.

AU: Thank you for your comment. Thematic analysis was not performed in this case. And as you indicate, analysis of the free text is simply content analysis. We phrased to indicate that content analysis instead of thematic analysis was performed. Please see Data Analysis and Results (qualitative data collection of perception of levels of stress).

Reviewer #2: 1. Thank you for the opportunity to review this submission.

AU: Thank you for taking time to review our manuscript. We responded point-by-point to your comments. To make it easier for you to find responses specific to your comments, we highlighted the responses in yellow.

2. The paper reports on a small-scale cross-sectional survey of well-being among veterinary medical house officers at a training organization in the USA. It would be helpful to have more context, e.g. the responsibilities, support and duration of a veterinary house officer’s role, as not all training programs use this structure.

AU: Thank you. We added more context regarding the house officers program including responsibilities, duration, and support opportunities. Please see the Introduction.

3. Data and data analysis

4. Data were collected by a cross-sectional study with 103 respondents, who completed online surveys on anxiety, burnout, depression and quality of life, using validated published scales. The data were collected in 2017 (N=60, 85% female, 34% response rate) and 2018 (43 respondents, 81% female, 36% response rate).

5. Some points to clarify:

6. On p. 16 we learn that it’s a 2-year training program so it is important to clarify whether participants in each year were different cohorts or the same people surveyed twice (a repeated measures design).

AU: We clarified this in the following ways:

1. We included the description of the House Officers Program, including the length of the residency programs and fellowships/internships (Please see the Introduction). Whereas the fellows/interns respondents were different in 2017 and 2018 because they are 1 year-programs, some of residents (unless they were in their final year of the residency program) potentially responded to the surveys in both 2017 and 2018. We did not track the residents who might have responded to the survey in 2017 and 2018 to maintain anonymity of the respondents.

2. We also included both 2017 and 2018 in our study to increase our sample size. We indicated this in the Materials and Methods, under the subsection “Survey instruments”. The changes are highlighted in green as Reviewer #1 raised similar concerns.

7. Participants were asked to rate, not rank, their perceptions of stress associated with the listed stressors, and this is quantitative, not qualitative, data.

AU: Replaced the word “rank” with “rate” the Abstract and Materials and Methods.

8. The open-ended questions do provide qualitative data; there is no information on how this was analyzed (e.g. thematic analysis).

AU: Thank you. Content analysis rather than thematic analysis was performed. We corrected this in the Materials and Methods (Data analysis) and Results section. The changes are highlighted in green as Reviewer #1 raised similar concerns.

9. ‘Selected independent variables’ are mentioned on p. 7 but it’s not clear how they were selected or what they or the dependent/criterion variables were. There is no hypothesis-testing.

AU: We included the reasons why the chosen independent variables were considered and included relevant references. Please see Data Analysis section.

As indicated in our first submission, age was distributed across the various strata considered in our study, but respondents who identified as female and unmarried respondents were overrepresented in our population. We included the data of the multivariate analysis. We discussed the significant variables predicting survey scores, namely gender and marital status. We also discussed age as a variable as it was not a significant predictor of survey scores. We also indicated in the discussion that this should be interpreted with caution due to female and unmarried respondents being overrepresented. Please see results section and discussion. We also included appropriate references in the discussion.

10. P. 7 states that demographic variables were included; p. 9 states that they were omitted. Without these analyses, there is no information on which groups, if any, were more affected.

AU: Please see clarification and comments above.

11. Cronbach’s alpha is given for the scales overall but is also required for each sub-scale, as the analyses were based on these.

AU: We provided the scales Cronbach’s alpha for all survey instruments in the Materials and Methods, including the subscales for the Maslach Burnout Inventory and Short-Form 8 (Quality of life). We also provided Cronbach’s alpha for the Maslach Burnout Inventory, which has 3 subscales, and Short-Form -8 scale which has 2 subscales, in the results. Please see results. The other survey instruments, namely Generalized Anxiety Disorder, and Patient Health Questionnaire -9 (Depression) only have items without subscales.

12. There is insufficient information on how the quality of life scores were derived. The burnout measures need number of items and response options.

AU: Both the Quality of Life (SF-8) and Maslach Burnout Inventory survey instruments are copyrighted. Legally we cannot provide the items. We had access to the instruments through a paid contract. The GAD-7 and PHQ-9 are currently available for use in research and can be accessed online. As indicated in our first submission, we provided as much information as we can without violating any copyrights. We included the number of items for SF-8 and Maslach Burnout Inventory.

13. The statistical analyses compare scores between the 2017 and 2018 groups. However, there is no testing of sample vs. population distributions.

AU: We included information of testing distribution in the Data analysis section.

14. Findings are over-stated. For example, conclusions are made about overall high levels of burnout when scores are on, or within a point of, a threshold and there is wide variation in the data.

AU: Our interpretation of high burnout was based on higher mean scores of emotional exhaustion and low personal accomplishment scores. As noted in our discussion, other studies indicate that poor perception of personal accomplishment by individual precedes signs of emotional exhaustion. Thus, by the time emotional exhaustion is identified, burnout might be already underway. The respondents in our study had very low scores of perception of their personal accomplishment (<=33).

In response to you comment, we revised our results and discussion to make sure our results and their interpretation are not overstated or overreaching. Please see Results and Discussion.

15. The list of stressors with ‘relatively higher scores’ includes nearly all of them (10 of 13), and 8/13 score 3 on the 5 point scale. As scores are rounded to whole numbers this suggests most were at the scale midpoint, not ‘high’ scores.

AU: Thank you for the comment. We replaced the phrase “relatively higher scores” with “moderate”. Please see Abstract and Results (qualitative data collection on perception of level of stress).

16. Overall, the data do not give strong evidence of problems throughout the cohort. More interestingly perhaps, variation in the data suggests that some individuals may be experiencing difficulties, so targeted solutions matched to individual needs may be required.

AU: As indicated in our introduction, house officers are veterinarians who are potentially under stress during training and our aim was to investigate if their mental wellness is optimal given that veterinary students and other practicing veterinarians have been reported to have elevated psychological stress compared the general population. You are correct, our data does not give strong evidence that that our cohort had higher levels of psychological stress compared to other practicing veterinarians (which was surprising but desirable). We indicated in our discussion proposed ways to offer resources, in this case a faculty member to resolve personal/service concerns. As indicated, one of the major drawback is that our study is preliminary study and has limited external validity, but it might serve as a basis for our/other house officers programs.

17. Conclusions

18. The paper focuses on problems and argues for interventions but the evidence is thin. There is little said about the null findings for several variables or that, where others exceeded cut-offs, it was never by much. There are considerable problems – logical and statistical – with saying that a score of 49.1 is fine but 50.1 is problematic, for instance.

AU: Thank you for that comment and your point is well taken. Please see our comment as to why we had focused on “problems” in response to comment #16.

Other research recommends focusing on the aspects that improve wellness. In response to your comment, we indicated in the discussion about considering studies that focus on positive aspects, such as measure of happiness. Please see Discussion and relevant references.

19. As the PHQ is described, it’s not possible to be ‘not at all’ depressed; at best people have to be ‘mildly’ depressed. Depression is a serious diagnosable mental health condition, so telling participants that they are ‘mildly depressed’ based on these scores could cause problems in itself.

AU: You point is well taken. As indicated in the materials and methods, the PHQ-9 is not a screening tool for depression, but it is validated and used to monitor severity if depression or response to treatment and thus the results in our study should be interpreted as such. The description and use of PHQ-9 were made explicit in our first submission.

20. Claims that participants ‘consistently experienced high levels of burnout’ do not match the data, from which burnout does not appear to be extreme or widespread.

AU: Please see our response for item #14 for the response on why we considered our cohort to have high levels of burnout (high emotional exhaustion scores and low scores of personal accomplishment scores). We hope this clarifies the reviewer’s concerns regarding our conclusions on burnout.

21. The authors suggest that ‘burnout was associated with stressors such as…’ but no tests of association (e.g. correlation) are presented.

AU: Thank you for the comment. We replaced the word “correlation” with the phrase “might be related to..”

22. Conclusions about possible intervening variables - coping and resilience, and wider implications e.g. transfer to working environments, are not part of the study.

AU: We deleted the information regarding wider implications, coping, and resilience. Thank you.

23. Although there is little evidence of problems, the wider literature is used to argue that there are in fact problems which need to be solved. Scale ranges suggest that some participants may be experiencing problems but this does not show which interventions are required or by whom. Targeted approaches focused on needs would seem preferable. The suggested solutions are not based on the study findings.

AU: Please see our responses to your comments in #16 and #18 above.

24. Clarity

25. It’s well written and readable, except that the use of acronyms in the results section means constantly referring back to what each one means. There’s also a constant need to refer back to information on score thresholds to work out what mean scores indicate.

AU: We responded to the scoring of the content analysis and changed the phrase “relatively higher scores” with “moderate”. Please see responses to comment #15 above.

We revised the manuscript and minimized acronyms to reduce distraction to the reader.

26. Summary

27. Overall, then, this is a small-scale study in one training institution which does not allow conclusions to be drawn about a profession, or even veterinary training, as a whole. The findings are over-stated and focus too much on the negative, and the suggested interventions are unrelated to the study findings. While professional well-being in veterinarians is interesting and important, the conclusions should be carefully aligned with the findings.

AU: Thank you for the comments. Below is the summarized response for the above comment:

1. We revised the manuscript to ensure our conclusions are not overreaching or overstated.

2. As pointed out in the introduction, this is a preliminary study and might serve as a basis for future studies.

3. We also acknowledged why our study focused on the psychological stress based on previous studies in veterinary students and practicing veterinarians. We also acknowledged that further studies should also focus on aspects of resident training that improve mental health and wellness.

4. We also included results of multivariate analysis as you recommended and discussed the results.

Reviewer #3: Comments for the Authors:

Thank you for the opportunity to review your manuscript. Wellbeing of veterinarians is an important scientific topic and deserves to be investigated.

After reading your manuscript one is confused what the purpose was of carrying out the study in two consecutive school-years? What made you think that veterinarians’ wellbeing may be changed in one year? What happened in that period that might approve this study design? Another question is how many people from the 2017 and 2018 samples are actually the same persons? We don’t know anything about that after reading your description of the results? Further, as the samples from 2017 and 2018 are not dependent nor independent but mixed, there is no statistical test that might compare the respondents wellbeing in 2017 and 2018. In conclusion, you have chosen a wrong method to fulfill the purpose of the study. Therefore, unfortunately I have to recommend the editor to reject your paper.

AU: Thank you for taking time to review our manuscript. Please see our responses to your comments:

1. We included the reason for including 2 cohorts from 2017 and 2018. We included the cohorts to increase our sample size for the cross-sectional study. We indicated this in the Materials and Methods.

2. We included the description of the House Officers Program, including the length of the residency programs and fellowships/internships (Please see the Introduction). Whereas the fellows/interns respondents were different in 2017 and 2018 because they are 1 year-programs, some of residents (unless they were in their final year of the residency program) potentially responded to the surveys in both 2017 and 2018. We did not track the residents who might have responded to the survey in 2017 and 2018 to maintain anonymity of the respondents. Anonymity was important because the responses are considered personal medical information.

3. We also included multivariate analysis determining variables associated with the survey scores as suggested and discussed the results.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (21.7KB, docx)

Decision Letter 1

Jenny Wilkinson

19 Apr 2021

PONE-D-20-17459R1

A preliminary study on assessment of wellbeing among veterinary medical house officers

PLOS ONE

Dear Dr. Chigerwe,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jun 03 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Jenny Wilkinson, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

Thank you for your revisions and responses to reviewers; one of the original reviewers have [provide some further comments. I invite you to consider these comments and provide responses, and if necessary, revisions to the manuscript. These comments particular focus on clarity of your work and on ensuring that findings are not overstated.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for addressing the comments. I think the manuscript is in good shape to be recommended for publication.

Reviewer #2: 1. The focus is on veterinary house officers and the potential stressors they face, which is interesting. It would be helpful to contextualise it with information on other health professionals, but this information doesn't appear until the Discussion. It would be better in the introduction to set the scene for the study. There is good information on the training programme and support available. It would be interesting to know the extent to which house officers use the supports.

2. Some clarification is needed in the method section.

3. Internal consistencies are needed for each scale/subscale based on the data for this study – put this in the Method not the Results. Where reliabilities for the entire measure and for subscales are given, clarify which was used in the analysis and why. For all scales, state how many items were in each subscale, what the scale anchors were, and whether scores were calculated as the sum or mean of items.

4. Expand the data analysis section. Which variables met parametric assumptions, which didn’t? Which analysis were carried out using which methods? In some cases medians are given, suggesting non-parametric data, but MANOVA was used. Consistency and clarity in the analysis are required.

5. The MBI section states that it ‘gives a context for why burnout could have possibly occurred’ but this is not part of the study – the MBI does not measure the causes of burnout e.g. work demands.

6. For burnout, avoid calling all subscales ‘burnout’. For instance, p.6: “The emotional exhaustion subscale assesses … indicating low, average and high levels of burnout, respectively” should read “… indicating low, average and high levels of emotional exhaustion, respectively.” Same for depersonalisation and personal accomplishment. This also applies to the Results section e.g. footnote to Table 1.

7. As noted in my earlier review I am concerned that at best a person must be ‘mildly depressed’ on the PHQ-9. How were ethical requirements for avoiding harm managed when giving participants feedback?

8. For the SF-8, how many items were there for the physical and mental scales? What were the scale reliabilities and ranges? How were scores ‘standardised’?

9. The rating scales for stressors are quantitative not qualitative as numerical scores are given. The free text answers are, of course, qualitative, but not analysed here.

10. Page 3 states that there were 48 training positions in each year. Two years of data were collected, and p. 9 states that there were 175 potential participants in one year and 119 in the next year. This does not fit the description of the programme.

11. The demographic information should be summarised in a Table.

12. Comparing the two years was not the focus of the study. It would be simpler to state, near the start of the results, that there were no meaningful differences between the two cohorts and to carry out all analyses on the combined datasets.

13. Where medians and ranges are given, include the IQR. Alternatively, use mean and SD if suitable.

14. The findings and Discussion over-state the level of distress identified.

15. Anxiety: the medians show ‘mild’ anxiety (p. 6).

16. Burnout. While emotional exhaustion was high, depersonalisation was average, and feelings of personal accomplishment were on the boundary between low and average. This suggests fatigue/weariness rather than problematic levels of the much more severe syndrome of burnout.

17. PHQ-9 ‘mild’ depression - as mentioned above it’s not possible to be better than ‘mildly depressed’. This scale is, by its nature (clinical assessment) designed to show distress. Median scores were around 7 showing, at worst, ’moderate’ levels of depression.

18. No weight can be placed on the gender comparisons as there were so few males; married participants were also under-represented.

19. The analysis is unclear. What is meant by ‘when gender [or marital status] was considered as the independent variable, … scores were positively correlated with… ‘? This suggests regression with demographics as control variables (not independent variables) but then the reference to correlation doesn’t fit, and the data analysis section mentions MANOVA – again, not correlation.

20. The paragraph on p. 12 about the QoL measure is nearly incompressible. As this scale was analysed in terms of two scales – physical and mental – that should be the level of analysis rather than the ‘dimensions’ which are the separate items.

21. While some scores on the QoL measure were ‘below 50’ they were not far below. A rigid cut-off of 50 provides no information on the variance or standard errors associated with this cut-off. The data show, instead, that the participant group is close to ‘normal’, as would be expected of a hard-working and busy professional group.

22. The stress data show that participants endorsed most items, which is to be expected as the items were chosen because they are known sources of stress to working professionals. There’s nothing to say these were problematic stressors for participants.

23. The discussion over-states the levels of distress in this group. Participants appear, by and large, to be doing rather well, although busy and probably at times feeling overwhelmed – that would be normal in a demanding professional programme. Some individuals may be experiencing genuine distress, and may need help and support, but as regards the group, or house officers in general, the data don’t show that they’re overly distressed or unwell. In addition, the study can’t say what’s causing any fatigue/emotional exhaustion – its’ a cross-sectional study and there’s no demonstrated link between the stressor items and the mental health hones. Nothing can’t show causation, the information on work demands is unlinked to the wellbeing data, and some demographic subgroups are too small. The study does not tell us what helps and what doesn’t hep this sample of house officers to manage their wellbeing. Nothing can be said about training as a solution, or that ‘burnout is inevitable’ (p. 18). Much more caution is needed in interpreting the findings.

Reviewer #3: Thank you again for the opportunity to review the article. You have corrected everything that was required.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 Jun 24;16(6):e0253111. doi: 10.1371/journal.pone.0253111.r004

Author response to Decision Letter 1

25 May 2021

Dr. Wilkinson

Academic Editor

Thank you for reviewing our manuscript. Below are our responses to the reviewers’ comments.

Academic Editor Comments

Thank you for your revisions and responses to reviewers; one of the original reviewers have provide some further comments. I invite you to consider these comments and provide responses, and if necessary, revisions to the manuscript. These comments particular focus on clarity of your work and on ensuring that findings are not overstated.

AU: We addressed the reviewer’s concerns regarding clarity and conclusions from our study.

Reviewer #1: Thank you for addressing the comments. I think the manuscript is in good shape to be recommended for publication.

AU: Thank you.

Reviewer #2: 1. The focus is on veterinary house officers and the potential stressors they face, which is interesting. It would be helpful to contextualise it with information on other health professionals, but this information doesn't appear until the Discussion. It would be better in the introduction to set the scene for the study. There is good information on the training programme and support available. It would be interesting to know the extent to which house officers use the supports.

AU: Thank you for your thorough review of our manuscript. Below are our responses to your comments and suggestions. To make it easier for you to identify specific responses to your comments, we highlighted the changes in yellow in the body of the manuscript.

We focused on veterinary medicine in the introduction because several studies are available for practicing veterinarians and there are also perceived differences in risk factors for mental health issues among various health professionals (for instance, veterinarians versus physicians).

2. Some clarification is needed in the method section.

3. Internal consistencies are needed for each scale/subscale based on the data for this study – put this in the Method not the Results. Where reliabilities for the entire measure and for subscales are given, clarify which was used in the analysis and why. For all scales, state how many items were in each subscale, what the scale anchors were, and whether scores were calculated as the sum or mean of items.

AU: We clarified your comments and suggestions as follows:

a. The internal consistency Cronbach alphas we provided in the materials and methods for each instrument (Maslach, GAD-7, PHQ-9 and SF-8) were the original alphas for validation of the instruments (as you requested in the first review). Whereas, the Cronbach’s alphas for the scales/subscales indicated in the results are Cronbach’s alphas from our study. We think it is desirable to indicate the Cronbach’s alphas from our study in the results section so that the reader can relate these to the original alphas reported when the instruments were developed (materials and methods). We had provided these values, but in response to your comment, we clarified the source of the Cronbach’s alphas in the materials and methods (original) and results (from our study).

b. We indicated whether scale or subscales Cronbach’s alphas were used in our analysis, and reasons for the choice, namely:

Maslach Burnout Inventory (MBI)– we used the 3 subscales emotional exhaustion, depersonalization, and personal accomplishment. The subscales better describe the context of why burnout might have occurred.

Generalized Anxiety Disorders (GAD-7) and Patient Health Questionnaire (PHQ-9): The instruments have no subscales therefore whole scale alphas were used.

Quality of Life: Subscales mental component summary (MCS) and physical mental summary (PCS) are more relevant than the whole scale because they might guide specific interventions

to improve the mental or physical component of quality of life.

Please see “data analysis” section for the changes.

c. We had indicated the number of items in each instrument in our previous version of the manuscript. Please see materials and methods.

d. We had indicated the scale anchors for GAD-7 in our previous manuscript version. We included the anchors for scores 1 (several days) and 2 (more than half the days) for PHQ-9. The anchors for MBI and SF-8 (quality of life) depends on the item, thus, it will be easier for the reader to look at the instrument for specific anchors. As indicated in our previous version of the manuscript, we cannot provide the specific items for the MBI and SF-8 because they are copyrighted. Please see materials and methods for the changes.

e. We clarified how the scores were calculated for each instrument. Please note for the MBI we only indicated the number of items used to obtain the scores for the subscales. As indicated in our previous version of the manuscript, a software standardizes the responses against the referent United States population for the SF-8. Please see materials and methods for the changes.

4. Expand the data analysis section. Which variables met parametric assumptions, which didn’t? Which analysis were carried out using which methods? In some cases medians are given, suggesting non-parametric data, but MANOVA was used. Consistency and clarity in the analysis are required.

AU: All variables with mean reported followed a normal distribution whereas those with medians reported were not normally distributed.

You are correct that a MANOVA (assumes normal distribution) was used and yet some of the data points for some variables were not normally distributed. Because there isn’t a straightforward way in the software we used to run a non-parametric MANOVA, we did the following during the initial data analysis to make sure that running a MANOVA was appropriate:

a. We checked for assumptions for using MANOVA to be met by checking whether the residuals were normally distributed and homogeneity of variances was present. MANOVA is fairly robust for underlying distributions and is not sensitive to violations of multivariate normality when the data does not contain outliers.

b. To ensure the above in (a), we also ran a MANOVA on ranks and re-analyzed the data and arrived at the same conclusions.

We included the clarification summary of relevant information in the data analysis section.

5. The MBI section states that it ‘gives a context for why burnout could have possibly occurred’ but this is not part of the study – the MBI does not measure the causes of burnout e.g. work demands.

AU: The “context on why burnout could have possibly occurred” refers to the subscales (emotional exhaustion, depersonalization, personal accomplishment) and not the causes of burnout. Each of the subscales will have different specific reasons for the score magnitude and these have to be investigated. Our statement did not intent to refer to the causes of burnout. We hope this clarifies the reviewer’s comment.

6. For burnout, avoid calling all subscales ‘burnout’. For instance, p.6: “The emotional exhaustion subscale assesses … indicating low, average and high levels of burnout, respectively” should read “… indicating low, average and high levels of emotional exhaustion, respectively.” Same for depersonalisation and personal accomplishment. This also applies to the Results section e.g. footnote to Table 1.

AU: We respectfully disagree with the reviewer regarding this comment and interpretation. High emotional exhaustion scores alone, or high levels of depersonalization alone or low scores of personal accomplishment alone are interpreted as indicating burnout. Additionally, a combination of scores for the subscales outside the ranges is also interpreted as indicating burnout. Thus for instance, one cannot conclude a group of individuals who have high emotional exhaustion scores, but within reference depersonalization and personal accomplishment scores are not experiencing burnout. Our argument is based on how the scores are interpreted in the Maslach Burnout Inventory Manual. We did not change the interpretation in the manuscript. We hope the reviewer is comfortable with this comment.

7. As noted in my earlier review I am concerned that at best a person must be ‘mildly depressed’ on the PHQ-9. How were ethical requirements for avoiding harm managed when giving participants feedback?

AU: Thank you for the important comment. All identifiers for the respondents were removed and anonymity of respondents was protected before analysis and access by the investigators. The data was reported as median or means for the whole group of house officers. In the event of a house officer requesting individual scores, there were plans to recommend them to discuss the results with Academic and Staff Assistance Program or personal therapist. In our study, none of the house officers requested individual results. It is also important to note that the PHQ-9 is not a screening tool for depression but it is used to monitor severity of depression and response to treatment as noted in the Materials and Methods. Additionally, during administration of instruments, the purpose of each instrument was described. All questions were not delivered in a forced format, and respondents could skip questions.

8. For the SF-8, how many items were there for the physical and mental scales? What were the scale reliabilities and ranges? How were scores ‘standardised’?

AU: a. Some items assess both physical and mental components whereas some assess mental component only and others assess the physical component only.

For instance the item:

a. “Overall, how would you rate your health during the past 4 weeks?” assesses both mental and physical components.

Compared to the following items:

a. During the past 4 weeks, how much did physical health problems limit usual physical activities (such as walking or climbing stairs)?” assess the physical component.

b. During the past 4 weeks, how much have you been bothered by emotional problems (such as feeling anxious, depressed or irritable)?” assesses the mental component summary.

We had indicated the scale reliabilities for the mental and physical component summaries. Please also see our response above to why we chose to report the reliability for the mental and physical component summaries. Please see materials and methods under data analysis.

As indicated in the materials and methods, responses for each item for each individual respondent are standardized using a software (Optum Pro CoRE). Standardizing refers to converting the responses to scores for the eight dimensions and comparing them to a referent United States population. Please see materials and methods under ‘Quality of life” section.

9. The rating scales for stressors are quantitative not qualitative as numerical scores are given. The free text answers are, of course, qualitative, but not analyzed here.

AU: Content analysis (free text) were analyzed as stated in the previous version of the manuscript. Please see under “data analysis” and results section under “quantitative and qualitative data collection on perception of level of stress”

We added the word “qualitative” on the subheading “quantitative and qualitative data collection on perception of level of stress” to clarify your comment.

10. Page 3 states that there were 48 training positions in each year. Two years of data were collected, and p. 9 states that there were 175 potential participants in one year and 119 in the next year. This does not fit the description of the programme.

AU: The 48 refers to the maximum positions available each year. To clarify, the number of positions available differs each year due the following reasons:

a. A program may hire more than one house officer per year whereas some programs may hire a house officer every other year or hire different number each year (for instance 2 house officers in one year and 1 house officer the following year). Thus in a year where all programs are hiring their maximum number of allocated positions approximately 175 participants can be reached; mean of 43 (175/4) house officers per year -1st, 2nd, 3rd and 4th years in 2017. As indicated the in 2018 only 119 participants were available indicating that some of the house officers graduated and other programs did not hire any house officers or hired less house officers.

b. Fellowships and internships are 1 yearlong whereas residency programs are 3-4 years.

To clarify we added the word “maximum” before “48” and also added that the number of house officers hired varies depending on the specialty. Please see introduction under information on the residency program.

11. The demographic information should be summarised in a Table.

AU: Thank you. We summarized the demographic information in a table (Table 1). We changed the identification of the other tables accordingly. We deleted the sentences with the information on demographic information in the body of the manuscript.

12. Comparing the two years was not the focus of the study. It would be simpler to state, near the start of the results, that there were no meaningful differences between the two cohorts and to carry out all analyses on the combined datasets.

AU: While we agree with your comment, we wanted also to demonstrate that the despite the cohorts being dissimilar, the scores were not significantly different. One of the reviewers had also indicated to leave the data as indicated for 2017 and 2018.

In response to your comment, we included calculation of combined scores for GAD-7 and PHQ-9, and a column for the combined years form MBI (Table 2) and SF-8 (Table 3). We hope this is acceptable to the reviewer.

13. Where medians and ranges are given, include the IQR. Alternatively, use mean and SD if suitable.

AU: Strictly speaking the range is the difference between the minimum and maximum data points and we had provided both the minimum and the maximum data points in the previous version of the manuscript. We do not think it is necessary to provide both the range and IQR as measures of dispersion for the median. In response to your comment, we included IQR as the measure of dispersion for the median because the range is biased and prone to extremely small and large measurements. Please see results.

We had provided mean and standard deviation for the measurements that were normally distributed in our previous manuscript.

14. The findings and Discussion over-state the level of distress identified.

AU: As we indicated in our previous version, we emphasized the limitations of our study in our discussion mainly focusing on the limited external validity, and overrepresentation of various demographics (biased towards unmarried and or female respondents). Please see also our respondents to your comments regarding interpretation of the survey instruments. We re-read our discussion to make sure our conclusions do not overreach beyond our study results and interpretations.

15. Anxiety: the medians show ‘mild’ anxiety (p. 6).

AU: That is correct that our results interpretation of scores of 5-9 are indicative of mild anxiety (Page 6). Median score (for both years) from our study was 5, and that is how we interpreted the results.

16. Burnout. While emotional exhaustion was high, depersonalisation was average, and feelings of personal accomplishment were on the boundary between low and average. This suggests fatigue/weariness rather than problematic levels of the much more severe syndrome of burnout.

AU: The scores for personal accomplishment (PA) were 32 (2017), 33 (2018) and 32 (combined). The interpretation for PA scores as indicated in Table 2 are: ≥ 40, 39–34 and ≤ 33 indicate low, average, and high levels of burnout, respectively. The scores are ≤ 33 indicate high levels of burnout. Please see also our responses to #6 regarding interpretation of the Maslach Burnout Inventory. We hope this clarifies the reviewer’s comments.

17. PHQ-9 ‘mild’ depression - as mentioned above it’s not possible to be better than ‘mildly depressed’. This scale is, by its nature (clinical assessment) designed to show distress. Median scores were around 7 showing, at worst, ’moderate’ levels of depression.

AU: As mentioned in the materials and methods, the PHQ-9 is not used for screening for depression but it is used to monitor depression or response to treatment. Therefore using the adverb “mildly” implies diagnosis of depression from a screening test/clinical examination. Although this may sound technical, it’s an important differentiation and hence we maintained using the adjective “mild” as recommended by the survey instrument.

18. No weight can be placed on the gender comparisons as there were so few males; married participants were also under-represented.

AU: We agree with the reviewer and we had indicated that the results need to be interpreted with caution in the previous version of the manuscript. We retained the comments regarding interpretation of the results regarding gender.

19. The analysis is unclear. What is meant by ‘when gender [or marital status] was considered as the independent variable, … scores were positively correlated with… ‘? This suggests regression with demographics as control variables (not independent variables) but then the reference to correlation doesn’t fit, and the data analysis section mentions MANOVA – again, not correlation.

AU:

a. To clarify we used the term “explanatory” variable rather than “independent” variable based on your comment.

b. “When gender (or marital status) was considered as the independent variables” refers to when either is considered the explanatory variable for the scores. Because of the over-representation of females and unmarried respondents we chose to assess each significant explanatory variable (gender or marital status) one at a time and evaluate its effect on the scores of the 4 instruments. In response to your comment, we simplified, the analysis and re-ran the MANOVA with both gender and marital status in the model. The correlation coefficients were similar and the conclusions remained the same. Please see results.

c. It is important to note that each respondent has scores on 4 instruments (GAD-7, PHQ-9, MBI, and SF-8). However, those scores from each respondent on each instrument are not independent, i.e they are correlated. In addition to analyzing variance (similar to ANOVA) between the scores as a function of the explanatory variables (gender and marital status and age in our case) MANOVA also allows investigation of the correlations (strength and direction of the correlation) among the scores from the various instruments while maintaining a single type 1 error (no adjustment for multiple comparisons). The correlations are important information in that they give an idea of the relationship between the scores from the different instruments. For instance, in our study, emotional exhaustion scores were positively correlated with PHQ-9 scores (r=0.59). We hope this clarifies to the reviewer the reason for inclusion of correlations.

20. The paragraph on p. 12 about the QoL measure is nearly incompressible. As this scale was analysed in terms of two scales – physical and mental – that should be the level of analysis rather than the ‘dimensions’ which are the separate items.

AU: We understand the reviewer’s comment especially given that we are not able to publish the items, which would make it clear. While the physical and mental component summary are what we used to make interpretations, the scores are derived from the 8 dimensions. We think it is important to include the scores for each dimension as they might help the approaches to interventions when necessary i.e does the intervention need to focus specifically on certain dimensions to improve mental or physical health? For instance, the following item assess the “Social Functioning” dimension: “During the past 4 weeks, how much did your physical health or emotional problems limit your usual social activities with family or friends?” Social functioning is dimension that is affected by either physical, mental or both mental and physical health. Thus, if the score for this dimension is poor, it might be recommended to improve both mental and physical components of quality of life. In contrast the following item assesses physical functioning dimension: “During the past 4 weeks, how much did physical health problems limit your usual physical activities (walking, climbing stairs)?” Intervention for this dimension might be focused on physical component of quality of life.

We hope this context is acceptable to the reviewer.

21. While some scores on the QoL measure were ‘below 50’ they were not far below. A rigid cut-off of 50 provides no information on the variance or standard errors associated with this cut-off. The data show, instead, that the participant group is close to ‘normal’, as would be expected of a hard-working and busy professional group.

AU: Thank you for the comment. As indicated above the scores from the responses are converted to scores that are compared to a referent American population. In the original validation of the quality of life instrument, the reported standard deviation was 10.

22. The stress data show that participants endorsed most items, which is to be expected as the items were chosen because they are known sources of stress to working professionals. There’s nothing to say these were problematic stressors for participants.

AU: We agree with the reviewer’s comments. We only made comments on those items that might be associated with burnout. Furthermore, these items might be only be relevant to our study (for instance physical environment of the teaching hospital) or specific specialty (for instance patient management is irrelevant for an anatomic pathology residency program.

23. The discussion over-states the levels of distress in this group. Participants appear, by and large, to be doing rather well, although busy and probably at times feeling overwhelmed – that would be normal in a demanding professional programme. Some individuals may be experiencing genuine distress, and may need help and support, but as regards the group, or house officers in general, the data don’t show that they’re overly distressed or unwell. In addition, the study can’t say what’s causing any fatigue/emotional exhaustion – its’ a cross-sectional study and there’s no demonstrated link between the stressor items and the mental health hones. Nothing can’t show causation, the information on work demands is unlinked to the wellbeing data, and some demographic subgroups are too small. The study does not tell us what helps and what doesn’t hep this sample of house officers to manage their wellbeing. Nothing can be said about training as a solution, or that ‘burnout is inevitable’ (p. 18). Much more caution is needed in interpreting the findings.

AU: Our results focused on burnout for which have evidence of its presence (high emotional exhaustion and low personal accomplish scores). We made a comment that the scores on anxiety and depression were low and we are in fact happy about it (and we gave reasons why are results are different from other practicing veterinarians). Burnout results from an individual being overstretched in their work place and if the source of burnout is removed or reduced, the stress experienced by an individual is reduced whereas depression affects one’s holistic life (work and outside work). Burnout can predispose to depression and in our study, it is a concern that need to be addressed.

We did not investigate causality but rather associations between explanatory variables and the scores and we were cautious with our interpretations as indicated. The recommendations we indicate in our study are based on other studies in veterinary/medical fields and further studies are required to make such comments. As you point out this is a cross-sectional study, therefore only associations are appropriate.

We re-read the discussion to make sure our conclusions are not overreaching.

Reviewer #3: Thank you again for the opportunity to review the article. You have corrected everything that was required.

AU: Thank you.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (26.2KB, docx)

Decision Letter 2

Jenny Wilkinson

31 May 2021

A preliminary study on assessment of wellbeing among veterinary medical house officers

PONE-D-20-17459R2

Dear Dr. Chigerwe,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Jenny Wilkinson, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Thank you for your detailed responses and manuscript revisions; these have satisfactorily addressed reviewer comments.

Reviewers' comments:

Acceptance letter

Jenny Wilkinson

16 Jun 2021

PONE-D-20-17459R2

A preliminary study on assessment of wellbeing among veterinary medical house officers

Dear Dr. Chigerwe:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr Jenny Wilkinson

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (21.7KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (26.2KB, docx)

    Data Availability Statement

    Data cannot be shared publicly because the data represents individual house officers' responses from a single institution (University of California Davis School of Veterinary Medicine). The data presented in our study potentially contain sensitive identifying personal information such as mental health data which have psychological risks to the respondents. The minimal aggregated data set from the research are available from University of California Institutional Review Board Committee (contact via email provided below) for researchers who meet the criteria for access to confidential data. We have provided contacts (non-authors of this paper) to which data requests may be sent to obtain aggregated data. The contact is the institutional representative for the ethics committee: University of California Davis: Office of Research IRB Administration 1850 Research Park Drive Davis, CA 95618-6153 Phone: (530) 754-7679 Fax: (530) 754-7894 Email: ORExecutiveMgtAsst@ad3.ucdavis.edu.

    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES