3.1 Study design and selection criteria
For this study, we recruited 375 participants voluntarily from Lima (Peru) between 18 and 80 years old for an online electronic survey. The volunteers included medical students from the faculty of Medicine of the Peruvian University "Cayetano Heredia" (UPCH) and health personnel from Lima's health centers. The participants were recruited between 20th July and 21st September 2020 and allocated into five groups: general population (GP; n = 125), medical students in preclinical studies (MS-pre; n = 59), medical students in clinical studies (MS-cli; n = 66), COVID-19 first-line health personnel (HP-COVID; n = 59) and health personnel not involved with COVID-19 patients (HP; n = 66). A complete description is shown in Table 1.
Participants younger than 18 years old, with insufficient knowledge of Spanish and medical difficulties that could restrict the participation (i.e., learning difficulties or blindness) in the online survey were not included in this study.
Each participant was fully informed of the study and gave their consent to participate. This study was approved by the ethics committee from the Faculty of Medicine of the Peruvian University Cayetano Heredia and carried out following the Helsinki Declaration and the APA's ethical standards.
3.2 Data collection
3.2.1 Online Survey
For the data collection, an online electronic survey was carried out. Due to the restrictive policies for avoiding COVID-19 contagions, all instruments and questions were digitalized and programmed in a survey internet-free program (Google Forms). The questions included: informed consent, general information (i.e., age, gender, district, confession/faith, and occupation), previous medical diagnosis and medication intake, and the COVID-19 peri-traumatic distress index (CPDI) for the COVID-19 pandemic, GAD-7, and PHQ-9 instruments.
Finally, additional questions were as follows: “in the last 14 days, did you have a cough, difficulty breathing, sore throat, and fever?” (COVID_1), “do you have positive results for any COVID-19 test?” (COVID_2), “have you been hospitalized (or are you hospitalized at the moment) due to COVID-19?” (COVID_3), “do you have relatives with positive results for any COVID-19 test?” (COVID_4), “do you have relatives who were hospitalized due to COVID-19?” (COVID_5) and “do you have relatives who have passed away due to COVID-19?” (COVID_6).
3.2.2 COVID-19 Peritraumatic distress index (CPDI)
The COVID-19 peritraumatic distress index (CPDI) was first applied in China 20 and recently validated in other countries 21,22. This instrument was designed for a population evaluation of changes related to mood, behavior, cognitive skills, circadian rhythm, and other somatic symptoms due to the COVID-19 pandemic.
This instrument consists of 24 items, with a four-factor design: negative mood, cognition, behavioral change, somatization, and hyperarousal/exhaustion. Each item was evaluated by using Likert elements (from 0 to 4: never, occasionally, sometimes, often, and most of the time). The sum of each value per question results in the raw score. The displayed score is obtained by adding 4 to the raw score and used to calculate the CPDI severity degrees. For this reason, this instrument defines different categories for peritraumatic stress due to the COVID-19 pandemic: normal (0 to 28 display points), mild (29 to 52 display points, and severe (53 to 100 display points).
3.2.3 Depressive and anxiety symptoms
The Peruvian version of the PHQ-9 23 was used to assess the severity of depressive symptoms. The PHQ-9 delivers values in the range between 0 and 27. The highest value indicates a higher depression score. This instrument was validated in Peru with a representative sample (n = 30446) and showed significant internal consistency (Cronbach's α = 0.87). This inventory defines different categories for depression scores: minimal (1 to 4 points), mild (5 to 9 points), moderate (10 to 14 points), and severe (15 to 27 points).
For anxiety symptoms, the Peruvian version of the GAD-7 24 was used to assess the severity of anxiety symptoms. The GAD-7 delivers values in the range between 0 and 21 points. The highest value indicates a higher anxiety score. This instrument was also validated in Peru with a representative sample (n = 2978), showing significant internal consistency (Cronbach's α = 0.89). This inventory also defines different categories for anxiety scores: minimal (0 to 4 points), mild (5 to 10 points), moderate (11 to 15 points, and severe (16 to 21 points).
3.2.4 Statistical Analysis
Statistical analyses were performed using SPSS version 26.0 (Statistical Package for the Social Sciences, International Business Machines Corporation, New York, United States of America) and jamovi 22.214.171.124 25.
Descriptive data were managed with count data and percentages. To improve readability, the information is presented in tables. Quantitative variables approximately fitting a normal distribution are specified in the text as the mean ± standard deviation (M ± SD), and those with a non-normal distribution are expressed as the median (Me) with percentile 75 (Q3) and percentile 25 (Q1) and the interquartile range (Q3 – Q1; IQR). Categorical variables were specified with count data and percentages. Data were rounded to the next decimal to obtain results with two decimals. Values smaller than 0.001 were shown as < 0.001 and values greater than one million were expressed in scientific notation.
Multinomial logistic regression was computed for comparing the five groups, considering the group status (GP, MS-pre, MS-cli, HP or HP-COVID) as a dependent variable. Regarding predictor variables, the following were used as predictor variables and added in four different blocks, as follows:
- Block 1: CPDI scores, GAD-7 scores, PHQ-9 scores.
- Block 2: age, gender, CPDI scores, GAD-7 scores, PHQ-9 scores.
- Block 3: COVID_1, COVID_2, COVID_3, COVID_4, COVID_5, COVID_6, age, gender, CPDI scores, GAD-7 scores, PHQ-9 scores.
- Block 4: domicile, confession/faith, medication intake, previous medical disease, COVID_1, COVID_2, COVID_3, COVID_4, COVID_5, COVID_6, age, gender, CPDI scores, GAD-7 scores, PHQ-9 scores.
The “block” that better explained the data was chosen by using the Akaike information criterion (AIC).
The results of this statistical modeling are presented in Table 4. The odds ratio was flagged as “significant” if the two-tailed p-value was smaller than 0.05. The 95-percent confidence intervals were calculated for this model.