Page 94 - JCBP-2-4

Journal of Clinical and
Basic Psychosomatics Psychopathology of COVID-19 patients

• H1: Depression has a significant impact on the quality Table 1. Employment distribution of participants
of life of patients who contracted COVID-19.
• H2: Executive and cognitive functions of patients who Employment type Measurement %
contracted COVID-19 affect their quality of life Private sector 22 37.9
• H3: Demographic characteristics of research Public Sector 8 13.8
participants influence the quality of life of patients Self-employed 7 12.1
whose physical health has been affected by the Unemployed 7 12.1
COVID-19 pandemic. Pensioner 2 3.4

2. Methods Student 3 5.2
2.1. Participants
comprehensive results. Demographic characteristics
Data for the current research were collected from a post- collected included gender, age, marital status, educational
COVID-19 clinic at the Regular Outpatient Clinics of level, employment status, and region of residence. The
Sotiria Thoracic Diseases Hospital in Athens, Greece, where questionnaires used in this study were: (i) Patient Health
follow-up was provided to patients who had either been Questionnaire (PHQ-9), (ii) Health Survey Questionnaire
mildly ill or hospitalized with COVID-19. All participants Short Form (HSQ SF-36), (iii) Montreal Cognitive
(n = 49) in the present study were fully informed about the Assessment (MoCA), and one demographic questionnaire.
voluntary nature of the research. They were provided with
a consent form, which emphasized their right to withdraw 2.4. Statistical analysis
from the study at any time without consequence. The The research objectives were examined through one-way
survey took place from July 1 to July 30, 2023. Participants ANOVA and two multiple regression analyses to determine
were adult males and females, fluent in Greek (except for and interpret correlations accurately. Statistical reliability
one Georgian woman), and all were at least 20 years old. was established with a robust internal consistency,
The sample consisted of 20 male participants (40.82%) and demonstrated by a Cronbach’s alpha coefficient of 0.803.
29 female participants (59.18%). Participants were divided Statistical significance was set at P < 0.05. All statistical
into three age categories: 20 – 40 years (men: n = 4; women: analyses were performed using SPSS Statistical Package for
n = 7), 41 – 60 years (men: n = 13; women: n = 19), and Windows (version 28.0). 14
61 years and older (men: n = 3; women: n = 3). Regarding
employment status, 22 participants (37.9%) worked in the 3. Results
private sector, 8 (13.8%) in the public sector, 7 (12.1%) 3.1. First multiple regression analysis
were self-employed, 7 (12.1%) were unemployed, 2 (3.4%)
were retired, and 3 (5.2%) were students (Table 1). The first multiple regression analysis examined the
relationship between quality of life (HSQ SF-36) as the
2.2. Study design and settings dependent variable and depression (PHQ-9) and cognitive
This quantitative research examined categorical, nominal, and executive functions (MoCA) as the independent
and numerical variables in the study of participants. variables. Before interpreting the results, the assumptions
We used one-way analysis of variance (ANOVA) to underlying the regression model were assessed.
critically examine the relationship between independent In the Pearson correlation coefficient analysis,
variables and the dependent variable, to interpret and multicollinearity was assessed to ensure that the correlation
analyze correlations in detail. The independent variables coefficients between the independent variables were not
included demographics, depression, and cognitive and >0.8. The correlation between MoCA and PHQ-9 was
executive functions, while the dependent variable was −0.077, which falls within acceptable limits. In addition,
quality of life. Thus, cognitive and executive functions, the correlation between MoCA and SF-36 was marginally
demographics, and depression were the predictor significant, with a P = 0.057, close to the 0.05 threshold. In
variables, while quality of life served as the criterion contrast, the correlation between PHQ-9 and HSQ SF-36
variable. was stronger, with a significant P = 0.001 (Table 2).

2.3. Questionnaires 3.2. Second multiple regression analysis
Psychometric tests and closed-ended questions were The second multiple regression analysis explored the
used to test the hypotheses, allowing us to obtain both relationship between quality of life (HSQ SF-36) (dependent
quantitative and qualitative information, leading to more variable) and demographics (independent variable). As

Volume 2 Issue 4 (2024) 3 doi: 10.36922/jcbp.3879