INTRODUCTION
The outbreak of COVID-19 in January 2020 has rapidly transformed into a pandemic after the World Health Organization’s classification. The public health emergency has motivated the implementation of social distancing measures and prohibition of non-essential services1, followed by universities that suspended in-person activities aiming at reducing students’ mobility and, consequently. restricting disease transmission2. In medical schools, the migration to e-learning platforms was almost immediate and an alternative to adapt medical education from the traditional format to virtual scenarios3),(4.
Although technology may represent an alternative to continuing knowledge5, the lack of solid evidence that it may be as effective as in-person teaching methodology for medical students brought concerns with regard to their personal and professional development6)-(8, and this challenge still needs clarification during the ongoing pandemic, as a second wave strikes Europe and North America. Therefore, medical students, more specifically those attending the last years of undergraduate medical school, suffer more anxiety, because they are at a crucial moment to obtain which cannot be obtained in a similar fashion through digital platforms.
However, the same clinical scenario is the most at-risk place for acquiring COVID-19 and several strategies should be proposed in the attempt to overcome prejudices due to the lack of clinical training in this group of students. The virtual discussion of real clinical-case scenarios and elective disciplines that improve the training in critical situations (telemedicine10), as well as volunteer activities, have been fundamental as a response to many health sectors11. Volunteering may be seen as an altruistic attitude, or an opportunity to learn from the situation, but in the presence of a pandemic, there might be other reasons12),(13 and medical courses should be aware of them. Given that, we sought to identify the factors associated with choosing a volunteering activity among medical students attending the last years of medical school during the COVID-19 pandemic.
METHODS
Study design and population
A cross-sectional study was performed with students attending the fourth, fifth and sixth years (MS4, MS5 and MS6) at the School of Medical Sciences, University of Campinas (UNICAMP), Brazil. In Brazil, the undergraduate medical school takes six years, during which the MS4 students do rotations in clinical areas and begin to perform medical consultations (medical history plus physical examination) under supervision and the MS5-MS6 learn by practicing on their own but have the consultation revised by an attending physician14.
The study was approved by the Institutional Review Board of our institution (CAAE: 31785520.1.0000.5404, approved on May 29th, 2020) and the free and informed consent was obtained from all students before they were admitted into the study.
Data collection
A self-administered, anonymous, electronic survey was developed and administered using the web-based survey platform Google Forms (Alphabet Co., Mountain View, California). The survey instrument and instructions were provided in the Brazilian Portuguese language and links to the survey were distributed to the medical students via email individually; 350 invitations were sent on a weekly basis and the survey was conducted from May 31st to July 14th, 2020.
Volunteer activities
Volunteer activities are defined as non-paid, freely offered activities performed by medical students, with no direct benefits to them and aimed at helping the population. They were considered outside the formal medical curriculum and divided into the following activities:
Telemedicine: after preparatory classes and under pedagogical guidance, medical students answer the population’s questions presential or by telephone and provide counseling on hygiene measures, disease prevention and symptoms that require face-to-face care in health facilities.
Health Expeditionary: non-profit, non-governmental organization that provides medical care by screening suspected cases of COVID-19, where medical students seek to identify signs and symptoms of the disease; it is carried out through clinical presentations, making the decision to monitor a suspect case in the health facility or home.
Shifts: medical students could perform night calls with one resident from 6 pm to midnight, at the Obstetrics and Gynecology discipline at the university Women’s hospital, in a space next to the admission room, but with no contact with other scenarios, providing care to women with gynecological and obstetrical complaints, attendind a few number os cases. This option was considered later, because several MS reported they would like to continue to help the residents and physicians.
External Activities: another volunteer activity not related to the university´s health service, such as the loan of electronic equipment (computers/laptops and tablets) and prepaid phones for internet access so that students could follow remote classes and keep up with their activities.
Survey instrument
The participants filled out a 21-item questionnaire specifically developed for our study, which was pilot-tested after a modified Delphi panel that consisted of physicians and tutors specialized in medical education and learning methods. It contains: sociodemographic, baseline information (age, gender, year of study, family income), multiple-choice, open-ended questions about internet access and education technology use (use of medias, time spent on social media and academic activities), questions about the students’ capability to face an emergency related to a global health situation as volunteers and the developed activities; theoretical and practical learning methods, strengths and limitations of the medical school curriculum for undergraduate students. We also asked questions about teaching methods before and during the pandemic situation.
Statistical analysis
Continuous variables were expressed by mean and standard deviation or median/range, while categorical variables were described as percentages. The unpaired t-student test was performed for continuous variables and the chi-square test for binomial variables. The bivariate analysis was expressed as odds ratio with lower and upper limits within a 95% confidence interval. The multivariate analysis was calculated by logistic regression including all independent variables, whose p-values were < 0.10 in the final model. The significance level was set at 5%. A statistical package was used for further analysis (Intercooled Stata 13.0, StataCorp, College Station, TX, US).
RESULTS
Of 350 invitations, 125 (35.8%) responded and were included in the analysis. Response rates varied: 24.8% from the MS4, 37.6% from MS5 and 37.6% from the MS6. No incomplete responses were found. Table 1 shows the sociodemographic characteristics and the questionnaire responses by volunteers and non-volunteers. Among the participants, 79 were females (63.2%) and 46 (36.8%) males. All participants had access to the Internet and 102 (81.6%) used a notebook, 10 (8%) used a desktop computer and 13 (10.4%) used smartphones and tablets. Sixty-five (52%) students were volunteers and the distribution of the activities were (more than one type of activity could be chosen): 56 worked with telemedicine, 16 worked with the Expeditionary Health team, 8 worked by taking medical night calls and 7 performed external activities. Among the volunteers, most of them were MS-5/6 (66.15%); however, less than half of this medical class were volunteers - among the MS-4s, 70.97% were volunteers.
Variables | Volunteer | Control | p-value* |
---|---|---|---|
N (%) | N (%) | ||
Age (years) | 0.73 | ||
20-23 | 29 (44.6) | 24 (40) | |
24-27 | 28 (43.1) | 30 (50) | |
28+ | 8 (12.3) | 6 (10) | |
Gender | 0.73 | ||
Male | 23 (35.4) | 23 (38.3) | |
Female | 42 (64.6) | 37 (61.7) | |
Internship Year | 0.01 | ||
MS4 | 22 (33.8) | 9 (15.0) | |
MS5-MS6 | 43 (66.2) | 51 (85.0) | |
Family Income (multiple of 2020 minimal wage) | 0.03 | ||
0-1 | 0 (0) | 3 (5.1) | |
1.1-5.0 | 16 (25.0) | 12 (20.3) | |
5.1-10 | 28 (43.7) | 15 (25.4) | |
>10 | 20 (31.3) | 29 (49.2) | |
External Activity | 0.00 | ||
Yes | 7 (10.8) | 0 (0) | |
No | 58 (89.2) | 60 (100) | |
Telemedicine | 0.00 | ||
Yes | 56 (86.2) | 0 (0) | |
No | 9 (13.8) | 60 (100) | |
Expeditionary Health team | 0.00 | ||
Yes | 16 (24.6) | 0 (0) | |
No | 49 (75.4) | 60 (100) | |
Night calls | 0.00 | ||
Yes | 8 (12.3) | 0 (0) | |
No | 57 (87.7) | 60 (100) | |
Theoretical and practical preparation | 0.02 | ||
Insufficient | 9 (13.8) | 7 (11.7) | |
Somewhat insufficient | 35 (55.4) | 47 (78.3) | |
Somewhat Sufficient | 19 (29.2) | 6 (10.0) | |
Sufficient | 1 (1.6) | 0 (0) | |
Exclusive e-learning for professional qualification | 0.30 | ||
Stayed the same | 6 (9.2) | 12 (20.0) | |
Somewhat worse | 36 (55.4) | 31 (51.7) | |
Much worse | 14 (21.5) | 7 (11.7) | |
Somewhat better | 8 (12.3) | 8 (13.3) | |
Much better | 1 (1.6) | 2 (3.3) | |
Ability in a pandemic situation | 0.10 | ||
Not at all | 33 (50.8) | 39 (65.0) | |
Very Little | 12 (18.4) | 13 (21.7) | |
Somewhat | 18 (27.7) | 8 (13.3) | |
To a great extent | 2 (3.1) | 0 (0) | |
Time spent on social media platforms | 0.10 | ||
< 120 min | 17 (26.1) | 7 (11.7) | |
120-360 min | 33 (50.8) | 39 (65) | |
> 360min | 15 (23.1) | 14 (23.3) | |
E-learning before pandemic | 0.18 | ||
Slightly Important | 1 (1.6) | 5 (8.3) | |
Moderately Important | 27 (41.5) | 29 (48.3) | |
Important | 32 (49.2) | 21 (35.0) | |
Very important | 5 (7.7) | 5 (8.4) |
*Chi-square test for binomial variables and T-student for continuous variables.
About the time spent on social media during a day, 24 (19.2%) students accessed them for less than 120 minutes, 72 (57.6%) spent between 120 and 360 minutes and 29 (23.2%) more than 360 minutes. On the other hand, 80 (64.5%) spent less than 120 minutes using the e-learning platforms.
Compared to MS5-MS6 students, MS-4s participation as volunteers was significantly lower (χ2=5.94; p=0.01), as well as MS with higher family income (χ2=8.96; p=0.03) and students that considered themselves more satisfied with previous theoretical and practical preparation (χ2=9.28; p=0.02) (Table 1).
When students were asked about their capability during theoretical and practical preparation for a public health emergency, 98 (78.4%) considered themselves as not sufficient and 97 (77.6%) did not feel capable to attending or dealing with an emergency in a global health situation, such as COVID-19.
Before the pandemic, 50.4% of the respondents considered important the teaching technologies (eg. e-learning). However, during the pandemic, the exclusive use of e-learning for theoretical activities and clinical case discussions were considered not sufficient for 70.4% of students about their professional qualification.
Univariate and multivariate analysis to the associated factors with volunteering were described in Table 2. After logistic regression, it was found that MS-5/6s were less associated with volunteering (OR, 0.21; 95% CI, 0.06-0.66), family income with 5.1-10 minimal wages more associated with volunteering (OR, 2.32; 95% CI, 0.94-6.42). Exposure to social media platforms between 120-360 minutes in social media platforms (OR, 0.1; 95%CI, 0.02-0.42) and over 360 minutes (OR=0.16[0.03-0.76]) reduced the risk for volunteering. Interestingly, MS that considered themselves able to face a pandemic situation (OR 4.91; 95%CI, 1.49-16.2) and that presented e-learning modules before pandemic (OR=16.46[1.35-200.32]) were risk factors for being volunteers (Table 2).
Variables | Crude Odds Ratio (95%CI) | p-value | Adjusted Odds Ratio (95%CI) | p-value |
---|---|---|---|---|
Medical school year | ||||
4th | 2.44 (1.12-5.3) | .01 | ------------------ | |
5th/6th | 0.34 (0.14-0.82) | .02 | 0.21 (0.06-0.66) | .00 |
Family Income (multiple of 2020 minimal wage) | ||||
<1 | ||||
1.1-5 | 1.93 (0.75-4.95) | .17 | 2.45 (0.74-8.07) | .14 |
5.1-10 | 2.7 (1.16- 6.31) | .02 | 2.32 (0.94-6.42) | .10 |
>10 | 0.69 (0.39-1.21) | .20 | ||
Time spent on social media platforms (dummy variable) | ||||
< 120 min | 1.1 (0.71-1.71) | .65 | 1.17 (0.06-20.1) | .91 |
120-360min | 0.45 (0.14-1.44) | .18 | 0.1 (0.02-0.42) | .00 |
> 360min | 1.28 (0.54-3.02) | .57 | 0.16 (0.03-0.76) | .02 |
Ability in a pandemic situation | ||||
Not at all | 0.84 (0.53-1.34) | .48 | ---------------- | |
Extraordinarily little | 1.09 (0.43-2.71) | .85 | 0.79 (0.25-2.49) | .69 |
Somewhat | 2.65 (1.02-6.89) | .04 | 4.91 (1.49-16.2) | .00 |
To a great extent | ||||
E-learning before pandemic | ||||
Slightly Important | 0.20 (0.02-1.71) | .14 | ----------------- | |
Moderately Important | 4.65 (0.51- 42.43) | .17 | 6.86 (0.58-81.21) | .13 |
Important | 7.61 (0.83-69.9) | .07 | 16.46 (1.35-200.32) | .03 |
Especially important | 4.99 (0.41-59.65) | .20 | 2.15 (0.12-36.24) | .59 |
DISCUSSION
This study has identified factors associated with volunteer activities among medical students attending the last years of undergraduate school during the COVID-19 pandemic. Students attending the 4th year of the medical course, students with family income between 5-10 minimum wages, and students who felt more confident and capable to face the pandemic were more prone to be volunteers. Students that more often used social media networks showed a low probability of being volunteers.
An interruption of the educational process of the medical curriculum was expected to happen during the COVID-19 pandemic11, as we were not prepared to deal with a situation like that from a public health standpoint and the resources provided to students by the institutions were tested during this unprecedented period. During this survey, an attempt was made to identify medical students willing to be volunteers during a healthcare emergency situation, and we found that few students felt prepared regarding their abilities and previous experiences13, and many thought that the lack of full medical training would compromise their assistance to patients, even under supervision14),(15. It was possible to observe during this pandemic, the unraveling of the scenarios in a virtual environment and how damage to the medical education could be minimized- that is, the fact that the e-learning structure was not completely prepared for what was coming16.
However, facing COVID-19 can have a positive impact promoted by medical students17. In Switzerland, students supervised by medical tutors in a critical-care scenario have demonstrated that the medical students felt motivated to work and learn, and the experience was considered feasible and safe (18. In Brazil and United States19, medical students were submitted to a compulsory interruption of their clinical rotations and did not have a central role when facing this crisis, if one remembers that these countries had the largest death tolls worldwide20. This can be a controversial discussion, and there are pros and cons to both opinions on exposing a medical student to a pandemic situation.
The MS-4 have their first exposure to patient care14, and faced the interruption of outpatient and inpatient clinical rotations22),(23. Volunteering can be a positive stimulus as the student can consider the unpredictability of the scenario, without knowing when they are coming back to the “normal” routine. This experience can motivate them to have contact with clinical experiences24; however, they showed less interest in volunteering than MS-5 and MS-6, and it is possible that the latter group considered the longer duration of the pandemic and having to undergo a transition to become physicians with less practical training. In addition, the unpredictability of the end of the medical course due to the pandemic21, as previous studies have shown that medical students may feel psychologically stress before the residency selection process25. Many countries, such as United Kingdom and United States, are changing the residency process to a virtual format and the new scenario can add stress to the process26.
During the COVID-19 pandemic, the use of social media has disseminated a great amount of information, and this certainly contributed to misinformation and fake news27. This trend may have impacted on the interest to be a volunteer; we have found that spending longer periods on social media decreased the interest to be a volunteer, and this can be explained by the fact that wrong information can generate high levels of stress and fear/uncertainty27),(28. Social media exposure (SME) may cause misinformation and this can affect the mental health of users29 and compromise their willingness to participate in other activities during a crisis. Humanitarian crises may have consequences on the mental health of survivors29 and usually, the most affected population live in low‐ and middle‐income countries (LMICs)30),(31, such as Brazil.
Many health determinants, such as family income, may impact on the risk and outcomes caused by SARS-CoV-232. For individuals with a low socioeconomic level, social distancing may be more difficult, due to overcrowded housing and difficulty to maintain jobs with the home-office modality during the pandemic33. Such evidence may be related to difficulties that low-income students had to struggle with; many could not face the challenge of staying in the city where they were attending their medical school as the economic crisis was affecting many families; it is known that economic consequences secondary to restrictive measures have caused a global increase in unemployment rates34.
Students that felt prepared to face a global health emergency were more prone to be volunteers, and literature has shown that attitudes and previous knowledge may influence the student’s decision to volunteer35. A Canadian study analyzed factors and attitudes of medical students who chose to volunteer during the influenza pandemic and reported that a previous volunteering experience was a strong predictor of being available to collaborate in that circumstance36. Other variables, such as age and gender36 may also be related to volunteering; however, our study did not identify these associations.
Our study has some limitations, which include the non-response bias inherent to its survey design and the sample that may be biased by self-selection, as the sample size was not calculated. If responders were more interested in being a volunteer than those that did not respond, then our results would be overly optimistic about the factors associated to participation in volunteer activities. Secondly, the impact of a higher risk of severe illness caused by Covid-19 infection was not directly measured among the responders. Another one is that all the students who answered the survey came from a single university located in the same country, which does not allow us to generalize our results.
The strengths of our study include the fact that it was conducted in a country that represents the third place regarding the number of cases and the second in death rates caused by COVID-19 and that has faced the collapse of the public health system in many cities around its national territory. Our response rate was satisfactory and compatible with other surveys.
COVID-19 pandemic has led our society to reshape itself and medical schools have undergone modifications aiming to face this pandemic. Medical students were questioned about their role during this pandemic period. It was concluded that half of our sample participated in volunteer activities during the COVID-19 pandemic and a previous, confident attitude towards a public health emergency increased the odds of working as a volunteer.
CONCLUSION
COVID-19 pandemic has led our society to reshape itself and medical schools have undergone modifications aiming to face this pandemic. Medical students were questioned about their role during this pandemic period. It was concluded that half of our sample participated in volunteer activities during the COVID-19 pandemic and a previous, confident attitude towards a public health emergency increased the odds of working as a volunteer. It is possible that the volunteer activities performed by medical students, with a high-quality training, during this pandemic might change the public health system care, especially in low-and-middle income countries, facilitating access to the service and care of patients with lower clinical complexity.