Socio economic status (SES) was calculated by assigning values to the responses which were based on the parents’ monthly income, level of education and the occupation. A maximum value that could be obtained was twenty two. Scores obtained were converted to percentages in order to identify two levels of SES. (< 50- low, 50 or above-high)

Each correct answer for the statements in section A was given a score of one and each incorrect answer was given a zero. The sum was calculated to obtain a knowledge score.

For each question in section C regarding the practices, a favorable practice for prevention of the spread was given a score of one while an unfavorable practice was given a zero. The sum was calculated per student and a practice score was obtained.

An ordinal Likert scale of five points was used to assess the agreement to each attitude statement (Strongly Agree, Agree, Neutral, Disagree, and Strongly Disagree). Each statement (1 to 5) in section B was analyzed separately to highlight their significance. A score for general fear regarding COVID- 19 (fear score- general) was calculated using the statements 6 to 8 of section B (Table 1). In statements 7 and 8, a maximum score of five was assigned to those who strongly disagreed to the statements. A positive attitude score for clinical students was calculated by summing up the scores for attitude statements 1 to 4 in section D. A separate fear score (fear score clinical) for the category of clinical students was also calculated using the statements 5 and 6 in section D of Table 1.In statement 6, highest score was assigned to those who strongly disagreed to the statement and for statement 5 it was the opposite.

Students had a high knowledge score of 89.6%. Female students, students below 25 years, pre-clinical students and students with high SES had more knowledge compared to male students, students above 25 years, clinical students and students with low SES. But within categories, no significances were found for knowledge (p>0.05). More than 93% were knowledgeable regarding the modes of transmission, incubation period, risk categories, symptoms and methods of preventing the spread. However, they lacked knowledge regarding the testing required (44%), effects of vaccine (19%) and the current modes of treatment (18%).

Students had a good practice score of 84.4%. Clinical students had favorable practices to prevent spread than pre-clinical students (p=0.026). However, only 56.3% of the students avoided sharing other collogues’ phones, desks, pens, tools and equipment; 28.2% avoided using their smart devices during clinical/ practical time for study purposes, 55% avoided buying cooked meals from the restaurants and 57% avoided sharing meals with the colleagues.

The students demonstrated a low fear score of 31%. Despite the low fear score, majority of 79.3% of the students were feeling more threatened with exposure to COVID -19. Moreover they had specific fears as indicated by the fact that only 7% had no objection to work with a colleague who has had COVID -19 and recovered; and only 3.2% had no objection to undergo necessary testing if there is a suspected exposure. Table 2 summarizes the average values for knowledge, practice and fear scores obtained from the values of the common questions to all the respondents.

Table 2

	N	Mean	Std. Deviation	Minimum	Maximum	Median
Knowledge	246	89.6498	11.68799	30.77	100.00	92.31
Practice	246	84.4399	9.83128	61.11	100.00	83.33
Fear Score	246	31.45	6.044	16	52	32.00

Mean for knowledge, practice and fear was higher among female students compared to male students but the difference was not statistically significant. Fear score was significantly higher in students who were above 25 years of age. (p=0.006) Scores for knowledge were higher in pre-clinical students whereas fear score was higher among the clinical students. However, the difference was not statistically significant. The mean score for practices was significantly higher among clinical students than the pre-clinical students. (p=0.026) Fear score was highest among Sri Lanka Moor students followed by Sinhalese and Tamils students, the difference being statistically significant. (p=0.01) There was no observed significance in any of the scores between the low and high socio-economic status. (Table 3)

The responses of the students to the statements 1-5 in section B were compared between the gender, age, race, socio economic status and the undergraduate category. Students who were in low SES were willing to undergo infection control training than the students who were in high SES. The difference of agreement was statistically significant. (p=0.02) The pre-clinical students did not have any objection to get quarantined while other colleagues continue the study program as opposed to the students in clinical years. (p=0.036) (Table 4)

The average fear score of the students in clinical years (fear score clinical) was 61.2% which were high compared to general fear experienced by all the student categories. (Table 5) Specifically, 55% of the clinical students agreed that they feel stressful while treating patients who have had COVID-19 infection and recovered. In addition, only 18% of the students agreed that they’ll treat patients coming from a high-risk area. Despite having a positive attitude score of 80.5 in the two groups of clinical students, only 68% were aware of which authority to contact if he/she came across a patient suspected to have Covid-19 infection.

Further, there was no statistically significant difference in either the fear score or positive attitude score between the two groups of clinical students studying in their third and fourth years. (p<0.05)

However, when the fear and positive attitude score were compared between the genders, female students had more fear compared to male students. (p=0.018) (Table 5)

Significant negative correlations were present between the fear score and practice score as well as the knowledge score and fear score, (p<0.05) indicating that the fear declines while increasing the knowledge and practice increases with the deduction of the fear. However, correlations between fear- knowledge and fear- practice were weak.

There was a significant positive correlation between the practice and the SES scores. But the positive relationship was weak. (p =0.021, r=0.108) There was a significant higher score for fear in students with less socio-economic status, but the correlation being weak and negative. (p=0.001, r=-0.153). Table 6 summarizes the correlations and significances.