Knowledge, Attitude, and Perception of Public Towards Participation in COVID-19 Clinical Trials: A Cross-Sectional Study
Author: Amira Mandour
Biostatistician | Clinical Trials & Statistical Modeling
Expert
2021-12-24
Research Question:
What factors are associated with public knowledge, perception, and
willingness to participate in clinical trials for COVID-19
treatments?
This cross-sectional analysis explores how demographic and behavioral
variables influence knowledge levels, perceptions, and attitudes towards
participation in COVID-19 clinical research, using a simulated dataset
modeled after real-world survey data.
Statistical Methods Used:
KAP Scoring System: Each correct answer in the knowledge, attitude, and perception sections was awarded 2 points. Section scores were converted into percentage scores. Based on Bloom’s cutoff criteria, each KAP domain was categorized into: High (>80%), Moderate (60%–79%), and Low (<60%).
Instrument Reliability:
The internal consistency of the survey questions was evaluated using Cronbach’s alpha.
Descriptive Statistics:
Numerical variables were reported as mean ± standard deviation (SD) or median and range, depending on the distribution.Categorical variables were summarized using frequencies and percentages.
Correlation Analysis:
Spearman rank correlation coefficients were used to assess the relationships between knowledge, attitude, and perception scores.
Regression Analysis:
Logistic regression models were used to assess the association between sociodemographic characteristics (e.g., age, education level, gender) and the level of knowledge, attitude, and perception.
Tools Used:
All analyses were performed using R, with the following packages:
tidyverse & dplyr ( for data cleaning and
manipulation).
psych (for reliability analysis and scoring).
ggplot2 (for data visualization).
finalfit (for descriptive statistics and regression
modeling).
gtsummary (for clean, professional-quality summary and
model tables).
corrplot (for correlation visualization).
ggpubr (for publication-ready plots and grouped
comparisons).
Key Findings:
Basic Characteristics of the Study Participants:
| Characteristic | N = 501 |
|---|---|
| Age | 30 (25, 35) |
| Sex | |
| Female | 27 (54%) |
| Male | 23 (46%) |
| Marital Status | |
| Married | 27 (54%) |
| Single | 23 (46%) |
| Educational Level | |
| Bachelor | 30 (60%) |
| Postgraduate Studies | 14 (28%) |
| Student | 6 (12%) |
| Job | |
| Healthcare Professional | 30 (60%) |
| Housewife | 2 (4.0%) |
| Jobless | 3 (6.0%) |
| Not Healthcare Professional | 6 (12%) |
| Student | 9 (18%) |
| Health Condition | |
| Chronic Condition (e.g., Hypertension, Diabetes, etc.) | 1 (2.0%) |
| COVID19activestatus | 1 (2.0%) |
| Nothing | 42 (84%) |
| Recovered from COVID-19 | 6 (12%) |
| Do you have a friend or a family member diagnosed with COVID 19? | |
| No | 15 (30%) |
| Yes | 35 (70%) |
| How many clinical trials have you been taken part in your life time? | |
| 0 | 50 (100%) |
| Have you been participated in a clinical trial for a new medication or a vaccine for COVID 19? | |
| No | 47 (94%) |
| Yes | 3 (6.0%) |
| 1 Median (IQR); n (%) | |
Table 1 shows that among all participants, 54% were female and 46% were male. The majority were married (54%), while 46% were single. Most respondents held a bachelor’s degree (60%), and 28% were enrolled in postgraduate studies. Regarding occupation, 60% were healthcare professionals, whereas 40% came from non-healthcare backgrounds. Additionally, 70% reported having a friend or family member diagnosed with COVID-19.
Knowledge Levels Concerning Current COVID-19 Clinical Trials:
| Characteristic | N = 501 |
|---|---|
| 1. Have you heard about any COVID-19 clinical trials in your country of residence? | |
| Yes | 32 (64%) |
| No | 18 (36%) |
| 2. If you heard about the COVID-19 clinical trial in your country of residence, how did you hear about it? | |
| 1 (2.0%) | |
| Friends/Relative | 5 (10%) |
| I didn't hear | 15 (30%) |
| Newspaper | 1 (2.0%) |
| Search Engine | 2 (4.0%) |
| Social Media | 21 (42%) |
| TV | 3 (6.0%) |
| Your Healthcare provider | 2 (4.0%) |
| 3. In diseases like COVID-19, do you think your physician can give you a new drug under investigation without your approval? | |
| Yes | 3 (6.0%) |
| No | 47 (94%) |
| 4. Have you heard about an Institutional Review Board in your country of residence? | |
| Yes | 31 (62%) |
| No | 19 (38%) |
| 5. Suppose that you have been enrolled in a COVID-19 clinical trial, do you think your confidential information will be published? | |
| Yes | 7 (14%) |
| No | 43 (86%) |
| Knowledge Scores | |
| Less than 60% (Poor Knowledge) | 17 (34%) |
| <80% and >60% (Moderate Knowledge) | 13 (26%) |
| More than 80% (Excellent Knowledge) | 20 (40%) |
| 1 n (%) | |
Table 2. In terms of knowledge about COVID-19 clinical trials, 40% of the participants demonstrated a high level of knowledge, while 34% and 26% had low and moderate knowledge levels, respectively. Social media was reported as the primary source of information by 42% of participants.(Table 2)
Public Attitudes Toward Participation in COVID-19 Clinical Trials:
| Characteristic | N = 501 |
|---|---|
| 1. If you have been invited to participate in the COVID-19 clinical trial, what happened? | |
| I declined to takepart in the trial. | 2 (4.0%) |
| I haven’t been approached before. | 48 (96%) |
| 2. Are you interested in learning more about taking part in COVID-19 clinical trials? | |
| Yes | 24 (48%) |
| No or not sure | 26 (52%) |
| 3. Would you like to participate in a clinical trial for a new MEDICATION for COVID-19? | |
| Yes | 9 (18%) |
| No or not sure | 41 (82%) |
| 4. Would you like to participate in a clinical trial for a new VACCINE for COVID-19? | |
| Yes | 13 (26%) |
| No or not sure | 37 (74%) |
| 5. Do you agree with having a family member participate in COVID-19 clinical trials? | |
| Yes | 10 (20%) |
| No or not sure | 40 (80%) |
| 6. Would you be prepared to participate in a COVID-19 clinical trial where treatment can be active or placebo? | |
| Yes | 8 (16%) |
| No or not sure | 42 (84%) |
| 7. Would you be prepared to participate in a COVID-19 clinical trial where treatment will be assigned at random? | |
| Yes | 7 (14%) |
| No or not sure | 43 (86%) |
| 8. Suppose that you have been enrolled in a random choice study if the treatment you were receiving did not suit you for any reason, you could always leave the study, and your doctor would then give you whatever other treatment might be appropriate for you. Would that encourage you to take part? | |
| Yes | 19 (38%) |
| No or not sure | 31 (62%) |
| Attitude Score | |
| Less than 60% (Poor Attitude) | 42 (84%) |
| <80% and >60% (Moderate Attitude) | 2 (4.0%) |
| More than 80% (Excellent Attitude) | 6 (12%) |
| 1 n (%) | |
Table 3.Regarding attitudes toward participation in COVID-19 clinical trials, the vast majority of respondents (96%) reported that they had never been approached to participate. Most expressed unwillingness to take part in a trial for a potential new medication (82%) or a vaccine candidate (74%) for COVID-19. Overall, 84% of participants demonstrated a poor attitude score (Table 3).
Perception towards participation in COVID-19 clinical trials:
| Characteristic | N = 501 |
|---|---|
| 1. From your point of view, clinical research is an essential step in developing a new treatment vaccine for COVID-19 | |
| Yes | 48 (96%) |
| No or not sure | 2 (4.0%) |
| 2. From your point of view, hospitals that participate in COVID-19 clinical trials provide better healthcare. | |
| Yes | 34 (68%) |
| No or not sure | 16 (32%) |
| 3. From your point of view, clinical research information provided by pharmaceutical companies can be trusted. | |
| Yes | 25 (50%) |
| No or not sure | 25 (50%) |
| 4. If you decide not to participate in a COVID-19 clinical trial, you will expect that your doctor will not give you good care. | |
| Yes | 8 (16%) |
| No or not sure | 42 (84%) |
| 5. From your point of view, human participants in the COVID-19 clinical trial will be treated like experimental animals. | |
| Yes | 13 (26%) |
| No or not sure | 37 (74%) |
| 6. From your point of view, volunteers in COVID-19 clinical trials will get adequate compensation for their participation. | |
| Yes | 29 (58%) |
| No or not sure | 21 (42%) |
| 7. From your point of view, volunteers in the COVID-19 clinical trials will get adequate information about the trial they participate in. | |
| Yes | 37 (74%) |
| No or not sure | 13 (26%) |
| Perception Score | |
| Less than 60% (Poor Perception) | 16 (32%) |
| <80% and >60% (Moderate Perception) | 13 (26%) |
| More than 80% (Excellent Perception) | 21 (42%) |
| 1 n (%) | |
Table 1. Concerning perceptions of participation in COVID-19 clinical trials, the majority of respondents (96%) believed that clinical research is essential for the development of a new COVID-19 vaccine. However, half of the participants (50%) expressed distrust toward clinical research information provided by pharmaceutical companies. Additionally, 84% responded negatively to the expectation that their doctor would not provide them with good care if they didn’t participate in the clinical trial. In terms of perception scores, 42% participants demonstrated a high perception score, while 26% and 32% participants had moderate and low scores, respectively.(Table 4)
Levels of Knowledge, Attitude, and Perception among participants:| Domain | Score Level | Frequency (%) |
|---|---|---|
| Knowledge Score | Low | 17 (34.0) |
| Moderate | 13 (26.0) | |
| High | 20 (40.0) | |
| Attitude Score | Low | 42 (84.0) |
| Moderate | 2 (4.0) | |
| High | 6 (12.0) | |
| Perception Score | Low | 16 (32.0) |
| Moderate | 13 (26.0) | |
| High | 21 (42.0) |
Correlation Analysis:
| Variables | rs..95..CI. | p.value |
|---|---|---|
| Knowledge–Attitude | 0.115 (-0.169 to 0.381) | 0.853 |
| Knowledge–Perception | 0.086 (-0.197 to 0.356) | 0.853 |
| Attitude–Perception | 0.254 (-0.026 to 0.497) | 0.225 |
| Note: All values are based on Spearman rank correlations with 95% confidence intervals. |
Figure 2. Correlation matrix between Knowledge, Attitude, and Perception.
The correlation analysis reveals that Knowledge and Attitude exhibit a weak positive relationship (r = 0.115), indicating a slight tendency for individuals with higher knowledge scores to have more favorable attitudes. Similarly, Attitude and Perception show a weak to moderate positive correlation (r = 0.254), suggesting that individuals with more favorable attitudes tend to have more positive perceptions. These findings imply that while there are positive associations among the variables, the relationships are relatively weak, indicating that other factors may also influence these constructs.(Table 6)
Logistic Regression of Sociodemographic Predictors of KAP Scores:
Domain | Variable | Categories | Poor (<60% of right answers) | Excellent (>80% right answers) | OR Univariable | OR Multivariable |
|---|---|---|---|---|---|---|
Knowledge | Age | Mean (SD) | 29.9 (9.1) | 31.6 (7.7) | 1.03 (0.95-1.12, p=0.515) | 1.06 (0.81-1.59, p=0.691) |
Sex | Female | 10 (52.6) | 9 (47.4) | - | - | |
Male | 7 (38.9) | 11 (61.1) | 1.75 (0.48-6.67, p=0.403) | 2.26 (0.06-78.77, p=0.619) | ||
Marital Status | Married | 10 (50.0) | 10 (50.0) | - | - | |
Single | 7 (41.2) | 10 (58.8) | 1.43 (0.39-5.41, p=0.592) | 3.78 (0.21-236.62, p=0.434) | ||
Education.level | Bachelor | 11 (47.8) | 12 (52.2) | - | - | |
Postgraduate Studies | 4 (36.4) | 7 (63.6) | 1.60 (0.37-7.57, p=0.530) | 0.32 (0.00-9.27, p=0.518) | ||
Student | 2 (66.7) | 1 (33.3) | 0.46 (0.02-5.45, p=0.547) | 0.93 (0.01-142.89, p=0.974) | ||
Job | Healthcare Professional | 4 (18.2) | 18 (81.8) | - | - | |
Housewife | 2 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Jobless | 3 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Not Healthcare Professional | 6 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Student | 2 (50.0) | 2 (50.0) | 0.22 (0.02-2.29, p=0.188) | 0.24 (0.00-82.47, p=0.610) | ||
Health.condition | Chronic Condition (e.g., Hypertension, Diabetes, etc.) | 1 (100.0) | 0 (0.0) | - | - | |
COVID19activestatus | 0 (0.0) | 1 (100.0) | 0.00 (NA) | 0.00 (NA) | ||
Nothing | 15 (46.9) | 17 (53.1) | 0.00 (NA) | 0.00 (NA) | ||
Recovered from COVID-19 | 1 (33.3) | 2 (66.7) | 0.00 (NA) | 0.00 (NA) | ||
Attitude | Age | Mean (SD) | 31.1 (9.2) | 30.0 (3.2) | 0.99 (0.88-1.09, p=0.774) | 0.72 (0.43-0.96, p=0.082) |
Sex | Female | 24 (96.0) | 1 (4.0) | - | - | |
Male | 18 (78.3) | 5 (21.7) | 6.67 (0.96-133.74, p=0.096) | 15.24 (0.65-1282.32, p=0.147) | ||
Marital Status | Married | 23 (85.2) | 4 (14.8) | - | - | |
Single | 19 (90.5) | 2 (9.5) | 0.61 (0.08-3.46, p=0.585) | 0.39 (0.01-6.26, p=0.536) | ||
Education.level | Bachelor | 27 (90.0) | 3 (10.0) | - | - | |
Postgraduate Studies | 11 (78.6) | 3 (21.4) | 2.45 (0.40-15.16, p=0.314) | 0.21 (0.00-4.42, p=0.346) | ||
Student | 4 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Job | Healthcare Professional | 24 (80.0) | 6 (20.0) | - | - | |
Housewife | 2 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Jobless | 3 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Not Healthcare Professional | 6 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Student | 7 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Health.condition | Chronic Condition (e.g., Hypertension, Diabetes, etc.) | 1 (100.0) | 0 (0.0) | - | - | |
COVID19activestatus | 1 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Nothing | 36 (87.8) | 5 (12.2) | 0.00 (NA) | 0.00 (NA) | ||
Recovered from COVID-19 | 4 (80.0) | 1 (20.0) | 0.00 (NA) | 0.00 (NA) | ||
Perception | Age | Mean (SD) | 28.7 (8.8) | 33.5 (8.6) | 1.07 (0.99-1.17, p=0.109) | 1.10 (0.90-1.40, p=0.384) |
Sex | Female | 8 (44.4) | 10 (55.6) | - | - | |
Male | 8 (42.1) | 11 (57.9) | 1.10 (0.30-4.10, p=0.886) | 0.22 (0.01-2.44, p=0.264) | ||
Marital Status | Married | 9 (37.5) | 15 (62.5) | - | - | |
Single | 7 (53.8) | 6 (46.2) | 0.51 (0.13-2.01, p=0.341) | 0.88 (0.07-11.15, p=0.919) | ||
Education.level | Bachelor | 9 (45.0) | 11 (55.0) | - | - | |
Postgraduate Studies | 5 (38.5) | 8 (61.5) | 1.31 (0.32-5.68, p=0.711) | 0.98 (0.08-12.39, p=0.987) | ||
Student | 2 (50.0) | 2 (50.0) | 0.82 (0.08-7.96, p=0.855) | 3.66 (0.06-332.18, p=0.526) | ||
Job | Healthcare Professional | 7 (31.8) | 15 (68.2) | - | - | |
Housewife | 1 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Jobless | 2 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Not Healthcare Professional | 3 (50.0) | 3 (50.0) | 0.47 (0.07-3.08, p=0.416) | 0.36 (0.02-6.38, p=0.485) | ||
Student | 3 (50.0) | 3 (50.0) | 0.47 (0.07-3.08, p=0.416) | 0.38 (0.00-66.61, p=0.714) | ||
Health.condition | Chronic Condition (e.g., Hypertension, Diabetes, etc.) | 0 (0.0) | 1 (100.0) | - | - | |
COVID19activestatus | 1 (100.0) | 0 (0.0) | 0.00 (NA) | 0.00 (NA) | ||
Nothing | 12 (38.7) | 19 (61.3) | 0.00 (NA) | 0.00 (NA) | ||
Recovered from COVID-19 | 3 (75.0) | 1 (25.0) | 0.00 (NA) | 0.00 (NA) |
Table 7 presents the results of univariate and multivariable logistic regression analyses evaluating the associations between sociodemographic factors and KAP scores (categorized as excellent vs. poor). As expected with simulated data used for confidentiality, none of the associations reached statistical significance (p > 0.05). These results are not intended to reflect real-world relationships, but rather to demonstrate the methodological approach, data handling, and reporting style typical in such analyses.
The table illustrates the application of binary logistic regression, calculation of odds ratios (ORs) with confidence intervals, and the structuring of regression outputs for publication. Key features include appropriate variable transformation, adjustment for potential confounders in multivariable models, and polished presentation using flextable in R Markdown.