Predictors of fear control related to COVID-19 among older population: an investigation on COVID-19 risk perception and health related quality of life during the pandemic

Abstract

Background The aim of this study was to examine the role of demographic characteristics, general health and health related quality of life on the fear control. Also, the aim of study was to explore how older people percept the COVID-19 pandemic by using the component of the expanded parallel process model (EPPM), and how the possible perception may contribute to probable behavior responses to prevention and control of COVID-19. Methods The present study is a cross-sectional study that was conducted in Tabriz, a city in north of Iran from February to April 2021, the period that correspond with the fourth wave of COVID-19. To collect information, the Covid-19 risk perception questionnaire (based on EPPM model including efficacy, defensive responses, and perceived threat) and health related quality of life (HQOL) Short Form-36 questionnaire were used. Discriminate value was calculated to estimate fear control and danger control. Univariate and multivariable logistic regression were calculated to examine the effect of demographic characteristics, general health and health-related quality of life on the fear control. Results The mean age of the 350 participants was 67.9 (6.4) years. A total of 83.1% of participants were engaged in danger control processes and 16.9% in fear control processes. According to the multivariable results, significant predictors for fear control were: gender 1.57 (95% CI 1.05–2.34, 0.025), education 7.38 (1.42–38.35, p = 0.017), economic status 1.31 (0.4–0.63, p = 0.029), and significant protective factors for fear control were: body pain 0.97 (0.94–0.99, p = 0.041), general health 0.96 (0.93–0.98, p = 0.032), physical health 0.94 (0.90–0.98) and total quality of life 0.024 (0.89–0.98). Conclusions Strong associations of fear control were found with being female, being illiterate, and having a good economic status and also body pain, general health, physical health and total HQOL were significantly associated with danger control. Since, most of elderly populations have adequately higher perceptions of efficacy to counteract their threat perceptions to continue motivating these older people to engage in COVID-19 self-protective behaviors, it is necessary to emphasis on the susceptibility of target population and the severity of the COVID-19 threats.

Investigating the Global Fear associated with COVID-19 using Subjectivity Analysis and Deep Learning

“…To summarize, there have been multiple works conducted in this field thus far where the investigation of fear and response related to COVID-19 was performed However, the prior works in this field have multiple limitations. First, prior works in this field have focused on investigating the fear and response towards COVID-19 by taking into account survey responses primarily from one country such as China [49,52], United States [55,64], India [59,65], Bangladesh [56,68], Iran [57], Hong Kong [60], Saudi Arabia [61], Ethiopia [62], Austria [63], Italy [66], Cameroon [67], Turkey [70,73], Pakistan [71], Korea [72], Spain [74], Germany [75]. Even though a prior work in this field by Eder et al [50] focused on the analysis of responses in a survey where the respondents were from four countries -Austria, Spain, Poland, and the Czech Republic, a study in this field is yet to be conducted where the respondents were from a considerable number of countries.…”

“…Even though a prior work in this field by Eder et al [50] focused on the analysis of responses in a survey where the respondents were from four countries -Austria, Spain, Poland, and the Czech Republic, a study in this field is yet to be conducted where the respondents were from a considerable number of countries. Second, most of the studies in this field [55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71] have focused only on the data analysis or content analysis of survey responses and did not apply any approaches such as subjectivity analysis to understand the degrees of personal opinions and facts represented in the survey responses. Third, even though there have been multiple studies where machine learning algorithms were used [49][50][51][52][53][54], none of those works focused on the development of a machine learning or deep learning model that could detect if a person was receiving mental health-related help based on their responses to surveys in the context of fear of COVID-19.…”

Investigation of the Global Fear Associated with COVID-19 Using Subjectivity Analysis and Deep Learning

“…The study conducted by Avazzadeh et al [57] aimed to investigate fear control among individuals aged 60 and above in the context of COVID-19. The findings revealed that 83.1% engaged in danger control processes, while 16.9% were in fear control processes.…”

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“…Understanding the epidemic risk perception of people in a timely manner can provide a basis for the formulation of prevention and control measures, and can also provide evidence for how to regulate the risk perception of people. At present, there are barely any relevant studies on the impact of self-leadership on quality of life (19) and only a few studies on the impact of epidemic risk perception on quality of life (20). Hence, this study aims to explore the influence of self-leadership and epidemic risk perception on quality of life based on two surveys of Chinese mainland citizens in early 2021 and late 2022 (when the epidemic control and prevention measures were fully implemented) to examine the effect of individual active behavior on improving quality of life in public health emergencies.…”

“…The coronavirus disease 2019 (COVID- 19) is an infectious disease that mainly damages the respiratory system and has significant physical, psychological, and social implications for people (1). Since the first case of COVID-19 was reported in Wuhan, China in December 2019 (2), more than 762 million confirmed cases and 6.8 million deaths worldwide have been reported by the World Health Organization (WHO) as of April 8, 2023 (3).…”