Psychological problems associated with coping strategies: a web-based study in Peruvian population during the COVID-19 pandemic

Abstract

ABSTRACT:BACKGROUND: The Coronavirus disease has quickly spread to all corners across Latin-American countries. Its exponential capacity has overwhelmed even the most resilient health systems (1). The already significant impact of the Coronavirus (COVID-19) on the global scale is worsened by psychological responses that may aggravate the health crisis. OBJECTIVE: This study is aimed at collecting demographic information, prevalence of psychological morbidities and associated coping styles during the COVID-19 pandemic on Peruvian population. Methods: This cross-sectional study was conducted through online survey using snowball sampling techniques after the state of emergency was declared in Perú. The General Health Questionnaire (GHQ -28) identify somatic symptom, anxiety/ insomnia, social misfunctioning and depression prevalence and the Coping Strategy Questionnaire (COPE-28) maps strategies addressing recent stress. RESULTS: We collected data from 434 self-selected participants within 18-68 years old (ME =33.87), by analysing the socio-economic information in which the majority of the respondents were women (61.3%), aged between 18 and 28 (41.7%), from well-educated groups (>=85.0 %), Peruvian (94.2%), working citizen (57.4%) and single (71.20 %). Nearly 40.8% rated psychological problems, expressing fear of being infected by coronavirus (71.43%). Regression analysis shows that female gender is associated to higher somatic (p<0.001*, C.I: -2.75 to -.99) and anxiety/insomnia symptoms (p=0.00*, C.I: -2.98 to 0.84). Depression and social dysfunction are experienced at any age. Educational status is protective against developing psychological disorders (p<0.05). While active responses (Acceptance and Social support) are scarcely used by individuals with psychological problems; Passive strategies are commonly reported (Denial, Self-Distraction, Self-Blame, Disconnection, and Emotional discharge).CONCLUSION: These findings provide a better understanding of psychological disorders resulting from the current pandemic in Peruvian population. This evidence informs the need to strengthen mental health programs, especially in less privileged groups after the Covid-19 pandemic.

Psychometric properties and factor invariance for the General Health Questionnaire (GHQ-28): study in Peruvian population exposed to the COVID-19 pandemic

“…The confirmatory Factor Analysis and exploratory analysis allowed to assess the structure of the (GHQ-28) sub-scales in Peruvian population not psychiatric. In Table 2, the quantitative analysis is shown, we found that global averages varied for the subscales of anxiety/insomnia and social dysfunction, whose means are high and are between (M= 1.01; DE = 0.885) and (M= 1.21; DE = 0.942) for items (1, 5, 8, 9, 10, 11, 15, 16, 17, 18, 20, 21).…”

“…Each item is graded on a 4-point scale to identify the severity of symptoms between 0 and 3 (“Not at all”, “No more than usual”, “More than usual” and “Much more than usual”). This version contains 4 subscales: somatic symptoms, anxiety, insomnia, social dysfunction, and severe depression (1).…”

“…The aim of this study was to conduct a psychometric analysis of the Goldberg’s GHQ-28 (1) through a sample of Peruvian adults using confirmatory factor analysis.…”

“… Abstract Large-scale epidemics are known to significantly disrupt the mental health and perceived well-being of most populations. In spite of the wide range of screening tools, there are not many reliable and widespread tools for the identification of psychological symptoms in non-clinical populations during a health crisis.

Objective The aim of this study was to conduct a psychometric analysis of the Goldberg’s GHQ-28 (1) through a sample of Peruvian adults using confirmatory factor analysis.

Materials and methods 434 individuals have been examined, studying the goodness and structure of the Goldberg GHQ-28 questionnaire.

Result We found high reliability indicating optimal values (α by Cronbach = .829), also there are four correlated factors that show strict invariance among the 28 items. Confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) were used to examine the structure of the subscales.

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