A Quantitative Analysis of Mandatory Wellness Assessments for 1st and 3rd Year Medical Students at the University of Ottawa

doi:10.21203/rs.3.rs-3970771/v1

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A Quantitative Analysis of Mandatory Wellness Assessments for 1st and 3rd Year Medical Students at the University of Ottawa

https://doi.org/10.21203/rs.3.rs-3970771/v1

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Background

An alarming prevalence of burnout among medical students has been reported in many countries, including Canada. To design resilience and wellness programs, it is important to explore individual risk factors. This article presents an example of a Wellness Assessment Program for medical students at the University of Ottawa. The overall goal was to identify risk factors for poorer mental health outcomes among medical students at the University of Ottawa.

Methods

We conducted a quantitative study to determine risk factors for mental health, among MD-A (1st year only), MD-B (1st year only), MD-C (1st and 3rd year) and MD-D (1st and 3rd year).

Results

Risk factors that significantly impacted the mental health of 1st and 3rd year medical students at the University of Ottawa were physical health, sleep/fatigue, social support, education and career, stress, and drug and/or alcohol use. Students who were originally from Ottawa had more social support and less stress and drug and/or alcohol use (p < 0.001;p = 0.009). Being in the Francophone cohort had a positive effect on physical health, but a negative effect on psychological/emotional health (p = 0.039;p = 0.004). There was a statistically significant difference (p = 0.021) between the psychological/emotional health of 1st year students (M = 0.7895) and 3rd year students (M = 0.8923) when co-variates (risk factors) were not considered.

Conclusion

In the current context of the limited effectiveness of measures to address the negative impacts of medical education on student well-being, this study showed that efficient use of the wellness program data can identify risk factors that have a significant impact on wellness.

medical student

wellness program

mental health

training

undergraduate

It is well known that medical schools are considered stressful environments, as the academic expectations are extreme (1). However, it is only recently that the epidemic of burnout related to medical training has been studied (1). Medical students are facing several stressors that place them at high risk for burnout and poor mental health (2, 3). Several studies have shown the negative impacts of medical education on student well-being in several countries, including Canada (1, 4, 5). It is therefore not surprising that the prevalence of psychological distress among medical students is significantly higher than in the general population (6, 7). When compared to individuals with professional degrees or Doctoral degrees in other fields, physicians experience higher rates of emotional exhaustion and burnout and report more dissatisfaction with work-life balance (8). The more years a physician has been in practice, the more positive the perception of well-being, whereas physicians with fewer years (< 5 years) of practice reported greater burnout and lower resilience (9). Females had higher odds of having low resilience and they reported more burnout, depression and suicidal ideation when compared to men (9).

The alarming condition of medical students’ well-being has prompted several institutional organizations, including medical schools, to develop and implement various wellness programs for burnout prevention and resiliency (10, 11). However, the targeted risk factors and overall quality of these programs are inconsistent, and there is limited evidence about their effectiveness (11). Despite the increasing number of evidence on the worrying state of medical students' well-being, few systematic studies have addressed different risk factors reported to date (11). Understanding the factors that contribute to medical student distress and how to address them requires identifying risk factors for poor mental health (11). The overall goal of this study is to identify risk factors for mental health among undergraduate medical students at the University of Ottawa. Specific objectives are: 1) define the variation of these risk factors according to demographic variables; 2) determine if there is a change in the mental health of students during the 1st and 3rd year of their undergraduate program.

Study design and setting

Students from 4 different cohorts were invited to complete the Wellness Assessment Questionnaire. For the purpose of anonymizing the participating years, cohorts were identified with numbers: MD-A(1st year only), MD-B(1st year only), MD-C (1st and 3rd year) and MD-D (1st and 3rd year).

We used a quantitative approach to analyze the Wellness Assessment questionnaire results among 1st and 3rd year students. The responses were converted to numerical values and analyzed statistically.

Description of the University of Ottawa's Wellness Assessment Program

The health and well-being of students are a priority for the Faculty of Medicine at the University of Ottawa. The Wellness Assessment Program aims to promote and ensure the health and well-being of students while fostering academic success. It offers a full range of services to undergraduate students, such as personal wellness, psychological health, financial and career planning, including support for the residency application process (12). The Wellness Assessment Questionnaire is part of the program, and it is based on the Medical Students Well-Being Index, the Perceived Wellness Survey and the Burns Depression Inventory (11, 13, 14). The questionnaire has the following headings: demographic information, mental health and risk factors such as physical health, sleep, social support, financial stress, education and career, stress and drug use and/or alcohol. Open-ended questions are also asked about any concerns the student may have, as well as a list of suggestions for the medical program.

The wellness check is a mandatory assessment of the student wellness conducted in year 1 and year 3 of their undergraduate training. The Wellness Check Program was established in 2010–2011 but has not been validated (12). Students complete an online 15-minute Wellness Assessment Questionnaire on Survey Monkey prior to their appointment followed by an individual virtual 30-minute meeting with a counsellor. During and following these sessions, students are oriented to the different resources provided in relation to the pillars of Student Affairs Office services. As of the 2017–2018 academic year, the Wellness Check Program became a mandatory program for 1st year students, and since then all students must complete the questionnaire.

Students in year 3 of clerkship are also invited to participate in the Wellness Check Program on a voluntary basis. An email is sent to all students at the end of April of each year to complete the survey online, accompanied by an invitation to follow up with an in-person visit with a counsellor to address any concerns or to build on strengths. Counsellors communicate with students if they identify specific concerns or red flags upon reviews of the completed surveys as well. As of the academic year 2017–2018, the 3rd year wellness check became mandatory as well.

Data analysis

We analyzed the responses to questions with Likert scales and converted to numbers to perform a statistical analysis addressing different questions.

A multiple linear regression analysis was performed to identify independent predictors of psychological/emotional health. Independent sample t-test was used to compare various risk factors of mental health between gender, study cohort (francophone vs. anglophone) and residence. Linear mixed model repeated measures were performed to determine if time (1st year to 3rd year) has an effect on the psychological/emotional health of the students. A second linear mixed model with covariates was also performed to determine if time still has an effect on psychological/emotional health.

Data were converted from the Likert scale to a numerical scale (Strongly Disagree = -2, Disagree = -1, Neutral = 0, Agree = 1, Strongly Agree = 2).

The data for some questions were also reversed so that a high score in each category was considered "healthy" and a low score was therefore considered "unhealthy". For example, for question 13: In general, I have good eating habits, a Strongly Disagree has a low score (-2) while a Strongly Agree response has a high score (2). Therefore, the healthier the student is physically, the higher the score and vice versa.

On the other hand, question 38: I rarely engage in exercise and/or physical activities was reversed. Therefore, a student who answered Strongly Disagree had a score of 2 (they are in better physical health) and a student who answered Strongly Agree had a score of -2 (they are in poor physical health). Due to the different number of questions by categories in the 1st - and 3rd year questionnaire, we had to use the average of the responses to the questions in each category for each student.

SPSS 22.0 for Windows was used to perform statistical analyses. Results are expressed as means ± standard deviation and standardized beta coefficient with a 95% confidence interval. A p-value ≤ 0.05 was considered statistically significant.

What are the risk factors for mental health in medical students?

These analyses were done on three groups: 1st year students only, 3rd year students only, and all responses combined (1st year responses from MD-A, MD-B, MD-C, and MD-D, and 3rd year responses from MD-C and MD-D). At the time of conducting this study, only two cohorts had completed both year 1 and year 3 assessments.

A multiple linear regression was calculated to determine predictors of the psychological/emotional health score. The model was a significant predictor explaining 56% (R square = 0.556; p < 0.001), 73% (R square = 0.726; p < 0.001) and 59% (R square = 0.594; p < 0.001) for 1st year, 3rd year and both years, respectively. Significant predictors are presented in Table 1.

Table 1

Mental health risk factors for 1st, 3rd and all responses (1st and 3rd year)
	B	Standard Error	95% Confidence Interval		Standardized coefficient Beta	p value
	B	Standard Error	Lower Limit	Upper limit	Standardized coefficient Beta	p value
Year 1
Sleep/fatigue	0.18	0.03	0.125	0.237	0.24	< 0.001
Social support	0.30	0.04	0.226	0.375	0.28	< 0.001
Education and Career	0.19	0.05	0.098	0.285	0.14	< 0.001
Stress and drug and/or alcohol use	0.31	0.05	0.219	0.394	0.24	< 0.001
Year 3
Physical health	0.13	0.04	0.056	0.197	0.13	< 0.001
Sleep/fatigue	0.20	0.03	0.138	0.267	0.27	< 0.001
Finance	-0.06	0.02	-0.108	-0.014	-0.09	0.011
Education and Career	0.33	0.05	0.233	0.431	0.30	< 0.001
Stress and drug and/or alcohol use	0.36	0.05	0.252	0.465	0.30	< 0.001
Year 1 & 3
Physical health	0.05	0.03	0.005	0.102	0.06	0.030
Sleep/fatigue	0.21	0.02	0.162	0.249	0.27	< 0.001
Social support	0.17	0.03	0.116	0.228	0.17	< 0.001
Education and Career	0.30	0.03	0.229	0.363	0.24	< 0.001
Stress and drug and/or alcohol use	0.30	0.04	0.226	0.363	0.24	< 0.001

B = Unstandardized Coefficient. Regression method. Variables entered in the model for each group year: Are you new to Ottawa; MD program stream (French or English); Gender; Physical health; Sleep/fatigue; Social support; Finance; Education and career; Stress and drug and/or alcohol use.

Do risk factors and mental health vary by gender, cohort (Francophone vs. Anglophone) and whether the student is coming from Ottawa or out-of-town?

Table 2

Difference between gender on well-being.
	Average for female(N = 519)	Average for male (N = 386)	p value
Physical health	0.87 ± 0.65	0.99 ± 0.63	0.007
Sleep/fatigue	0.11 ± 0.83	0.38 ± 0.81	< 0.001
Social support	0.87 ± 0.61	0.93 ± 0.62	0.133
Finance	0.47 ± 0.86	0.62 ± 0.88	0.009
Education and Carreer	0.52 ± 0.48	0.66 ± 0.55	< 0.001
Stress and drug and/or alcohol use	0.84 ± 0.51	0.99 ± 0.52	< 0.001
Psychological/emotional health	0.72 ± 0.62	0.92 ± 0.63	< 0.001
N = number

Data are presented as mean ± standard deviation.

Table 3

Difference between cohorts on well-being.
	Average for the Francophone cohort (N = 296)	Average for the Anglophone cohort (N = 609)	p value
Physical health	0.99 ± 0.63	0.89 ± 0.65	0.039
Sleep/fatigue	0.17 ± 0.85	0.25 ± 0.82	0.186
Social support	0.91 ± 0.62	0.89 ± 0.61	0.570
Finance	0.47 ± 0.90	0.56 ± 0.85	0.160
Education and Career	0.55 ± 0.50	0.59 ± 0.52	0.297
Stress and drug and/or alcohol use	0.88 ± 0.50	0.91 ± 0.52	0.428
Psychological/emotional health	0.72 ± 0.65	0.85 ± 0.62	0.004
N = number

Data are presented as mean ± standard deviation.

Table 4

Difference related to students’ residence on well-being.
	Average for students coming from Ottawa (N = 486)	Average for students coming out-of-town (N = 419)	p value
Physical health	0.91 ± 0.64	0.94 ± 0.65	0.552
Sleep/fatigue	0.23 ± 0.83	0.23 ± 0.83	0.992
Social support	0.97 ± 0.60	0.81 ± 0.62	< 0.001
Finance	0.57 ± 0.85	0.48 ± 0.89	0.135
Education and Career	0.58 ± 0.50	0.58 ± 0.52	0.885
Stress and drug and/or alcohol use	0.95 ± 0.53	0.86 ± 0.5	0.009
Psychological/emotional health	0.81 ± 0.64	0.79 ± 0.63	0.638
N = number

Data are presented as mean ± standard deviation.

Is mental health better in the 1st or 3rd year of medical school?

The linear mixed model repeated measures analysis conducted for this question showed a statistically significant difference (p = 0.021) between 1st year students (0.79 ± 0.63) and 3rd year students (0.89 ± 0.59) on psychological/emotional health.

Summary of the main results of the study

The results from Table 1 show that the higher the standardized coefficient, the more impact it has on mental health. For every 1 unit increase of the risk factor, there is an impact (increase in this case) on the mental health value corresponding to the standardized coefficient. Table 2 shows a significant difference between genders in physical health, sleep/fatigue, finance, education and career, stress and drug and/or alcohol use and psychological/emotional health. Compared to males, females have a poorer outcome in terms of physical health, sleep/fatigue, finances, education and career stress and drug/alcohol use, and psychological/emotional health.

Table 3 shows a significant difference between the language cohort on physical health and psychological/emotional health. Results showed that being in one cohort or the other partially explains the higher (and therefore healthier) scores in these categories. Therefore, being in the Francophone cohort showed a higher positive effect on physical health and a lower psychological/emotional health compared to Anglophones.

Table 4 shows a significant difference between students’ origin on social support and stress and drug and/or alcohol. Coming from Ottawa partially explains the higher (and therefore healthier) scores for these risk factors. This means that students who come from Ottawa have more social support and less stress and drug and/or alcohol use when compared to students coming from out of town.

Finally, the mental health of the 1st year students is poorer when compared to the 3rd year students. However, when considering the co-variates (physical health, sleep/fatigue, social support, finances, education and career, and stress and substance use), the difference is no longer significant.

Our study used a Wellness Assessment Questionnaire, which is part of the University of Ottawa Wellness Check Program, to determine risk factors for mental health among medical students. It is acknowledged that poor mental health of medical students is a ‘’disease condition that is endemic to medical schools’’ (15). A systematic overview of risk factors for suicidal ideation and suicide attempts among medical students indicated that poor mental health outcomes such as burnout and depression are the strongest risks. Female gender was significantly associated with an increased risk of suicidal ideation, compared with males (15). Additionally, strong evidence on the wellness of medical students shows that their well-being is deteriorating throughout training, and it is becoming a growing problem (16, 17). In 2016, Canadian medical students reported burnout and suicidal ideation rates of 37% and 6%, respectively (18). An increase in the prevalence of mood disorders, anxiety disorders, suicidal ideation, and psychological distress in Canadian medical students compared to age-matched controls from the general population was observed in 2019 (18). It is well documented that physicians who demonstrate a high level of resilience report better well-being that promotes fulfillment in their work environment (19). It is then favorable to support the development of resilience wellness programs in medical training, to equip and prepare students for the challenges of the clinical environment (16, 20). However, the lack of enthusiasm for resilient programs in medical education remains. The culture that "doctors are invincible" persists (p.6–7) (18). A first systematic review conducted on the effectiveness of resilient programs in medical education indicates an improvement in resilience and well-being across several studies, however, no standardized resilient program has been evaluated (21).

In the current context of limited effectiveness of resources (wellness programs, access to tertiary care services) implemented to address the negative impacts of medical education on student well-being (15), this study shows that thoughtful use of the wellness program can identify risk factors that have a significant impact on medical students’ mental health. Wellness programs could also tailor effective interventions to address these risk factors for poor mental health (22). In addition to thoughtful use of wellness programs, it is also required to have a comprehensive approach to address the systemic and structural factors in which students live and learn (23). Most wellness and resilience programs implemented to date tend to focus on teaching self-care to students when the main problem often comes from the work environment (24). Further studies are needed to explore the influence of the work environment on poor mental health among medical students to evaluate the outcomes of wellness and resilience programs targeting risk factors identified by medical students. This study data was gathered in pre-covid context, further studies could consider the impact of COVID-19 on the program.

The lack of homogeneity in responses across student cohorts may have affected the results of the study. There was significant variability in responses regarding risk factors on mental health, as the percentage of impact of risk factors on psychological and emotional health was unequally distributed among students. Also, there were more responses from first-year students considered. Furthermore, given that there is no data on the psychometric properties of the instrument currently used, it is difficult to determine whether the differences arise from real differences among students or from artifacts due to the instrument (e.g. problem loyalty). In addition, this questionnaire is a mixture of statements from several English instruments which makes it less reliable for administration to French-speaking students, the translated version does not give rise to a back-translation or validation. This absence of using a reliable and valid tool for assessing the psychological health of medical students supports further research in this area.

The alarming condition of medical students’ well-being prompted medical schools to develop and implement various wellness programs for burnout prevention and resilient trainees. However, resilience training and wellness programs are unlikely to make a difference if they are not used efficiently. This study shows that wellness programs may be relevant to identifying risk factors related to poor mental health among medical students and implementing interventions that are more effective.

ETHICAL APPROVAL AND CONSENT TO PARTICIPATE

This research received an ethics exemption from the Ottawa Health Science Network Research Ethics Board as it was determined in the category of quality improvement. Informed consent to participate has been also waived by the Ethics committee ( see exemption letter)

CONSENT TO PUBLICATION

Not applicable

DATA AVAILABILITY STATEMENT

All data generated or analysed during this study are included in this published article. They are available from the corresponding author on reasonable request.

CONFLICT OF INTERESTS

There is no conflict of interest to declare.

FUNDING SOURCES

This project was funded by the AMUHM (Association médicale universitaire Hôpital Montfort) and the Department of Family Medicine New Innovator Award (University of Ottawa).

ACKNOWLEDGEMENT

All authors revised it critically for important intellectual content, gave final approval of the version to be published and agreed to be accountable for all aspects of the work. Kay-Anne Haykal and Ines Zombre share senior authorship.

AUTHOR CONTRIBUTION

Kay-Anne Haykal was the PI of this project, she designed the study, and contributed to data acquisition.
Ines Zombre drafted the manuscript with the support of Dr Haykal, Miryam Duquet
Miryam Duquet coordinated the manuscript and contributed to different drafts
Selena Laprade contributed to data analysis and reviewed the final draft of the manuscript
Joseph Abdulnour contributed to data analysis and reviewed the different drafts of the manuscript

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No competing interests reported.

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You are reading this latest preprint version

A Quantitative Analysis of Mandatory Wellness Assessments for 1st and 3rd Year Medical Students at the University of Ottawa

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

BACKGROUND

METHODS

Study design and setting

Description of the University of Ottawa's Wellness Assessment Program

Data analysis

RESULTS

What are the risk factors for mental health in medical students?

Is mental health better in the 1st or 3rd year of medical school?

Summary of the main results of the study

DISCUSSION

CONCLUSION

Declarations

References

Additional Declarations

Status:

Version 1