Anxiety, Depression and Substance Use in Undergraduate Health Science Students During the Covid-19 Pandemic.
Anxiety, Depression and Substance Use in Undergraduate Health Science Students During the Covid-19 Pandemic.
A study will be conducted with a quantitative approach with correlational scope, observational analytical study, prospective cross-sectional. The objective is to compare the levels of anxious symptomatology, depressive symptomatology and substance use in university students who were exposed to SARS-CoV-2 with those who were not.
Sampling:
A non-experimental sampling by volunteer subjects is performed, since the subjects will come to the study by a call on social networks.
Scenario:
The evaluation will be carried out in the application called Survey Monkey and will be distributed through social networks.
Methodological guidelines for reporting the study:
The guide to improve the quality of methodological reporting of cross-sectional online studies called CHERRIE will be used.
Sample size:
The infinite population formula for qualitative variables will be used, since we will be working with ordinal variables. In addition to the fact that the total number of observation units is unknown or when the population is greater than 100,000.
The sample size for 100,000 persons should be 384 persons per country, so that 95% of the time the data to be measured is within the ±5% interval with respect to the data observed in the evaluation.
Data analysis
Descriptive statistics were used to analyze the central tendency frequencies of the participants' characteristics. Non-parametric analyses will be applied, because the data do not meet the criteria of normality in the analysis of their distribution, the type of variable and the number of participants; therefore, Spearman correlations will be used to contrast ordinal data. On the other hand, odds ratio analysis will be used to determine the likelihood of a health condition or disease occurring in one population group versus the risk of it occurring in another.
Data analysis for instrument validation
Feasibility: This section will record the time participants took to complete the scale, the difficulties patients encountered in answering questions, and the number of missing values (patients who did not respond) for each question. Items will be analyzed by calculating the frequency of each response category within each item, as well as the blank response rate for each item. Floor and ceiling effects were also analyzed, both for each item and for the overall questionnaire.
Reliability: reliability was assessed by calculating Cronbach's alpha to determine internal consistency.
Validity:
(a) Construct: structural validity (or construct validity) was assessed by exploratory factor analysis using the common factor model, principal component extraction method and Oblimin rotation (if rotation was possible). The K1 rule (eigenvalues greater than one) and Cattell's screen test were used to decide the number of factors contained in the solution. A confirmatory factor analysis was also performed to corroborate the original structure, assuming the existence of a single factor where all items loaded. The maximum likelihood estimation method was used using R studio software.
b) Discriminant validity: discriminant validity will be calculated by dividing the sample into quartiles based on the total score of GAD-7 and the PHQ-9 and the upper quartile will be compared with the lower quartile, both for the mean scores of individual items and for the overall score. For other clinical criteria, validity will be assessed by calculating the related mean difference between the mean overall GAD-7 score of the diagnostic groups assigned by the clinical investigator, Student's t-test, Mann-Whitney U-test for independent groups or one-way ANOVAs were used, depending on the number of groups compared.
c) Criterion validity: the diagnostic performance curves (ROC curves) were analyzed and the sensitivity and specificity rates were calculated, as well as the positive and negative predictive values of the questionnaire, when comparing the resulting diagnostic classification with the reference clinical diagnosis.
d) Convergent validity: the degree of agreement between the GAD-7 and PHQ-9 scales and the Hospital Anxiety and Depression Scale (HADS, anxiety and depression domain) was calculated.
Inclusion Criteria:
Exclusion Criteria: