Middle Eastern Journal of Disability Studies

Abstract
Background & Objectives: The coronavirus caused a new disease worldwide called COVID–19. Because this disease led to the death of many people, it was accompanied by anxiety and panic, especially in older people. Psychological wellbeing in older adults is influenced by socioeconomic conditions; social network membership; and social, recreational, physical, and mental activities. Paying attention to older people's interactions and communication patterns with family members is very important. According to the World Health Organization, quality of life is related to a person's understanding of life, values, goals, standards, and interests. The quality of life, psychological health and communication of all humans faced a fundamental challenge. For this reason, World Health authorities recommended prevention by following health protocols as the only way to deal with this disease. Therefore, this study aimed to determine the causal model of Corona anxiety in elderly educators based on psychological wellbeing and communication patterns with the mediation of quality of life.
Methods: The research method was analytical using structural equation modeling. The statistical population of the present study comprised all cultural seniors, whose number was reported to be 1460 in the academic year of 2021–2022, according to the information of the General Department of Education of Lorestan Province, Iran. Sampling was done by the available method. According to the number of research variables, the statistical sample of the research was 260 older people (148 men, 112 women) selected from the statistical population. The inclusion criteria were retired and elderly teachers in 2020–2021. The exclusion criterion was the incomplete answers to all the questionnaire questions. Data were collected through the Psychological Wellbeing Scale (Ryff, 1989), the World Health Organization Quality of Life Brief Version (WHOQOL–BREF) (WHO, 1996), the Family Communication Patterns Scale (Ritchie & Fitzpatrick, 1990) and the Corona Disease Anxiety Scale (Alipour et al., 2020). Data analysis was done using the descriptive (mean, standard deviation, lowest and highest score) and inferential statistics (the Pearson correlation coefficient, structural equation modeling) in SPSS and AMOS version 25 software. The significance level for all tests was considered 0.05.
Results: In examining the coefficients of the direct path between different paths, the results showed that between communication patterns and quality of life (Beta=0.379, p<0.001), between psychological wellbeing and quality of life (Beta=0.641, p=0.033), between the quality of life and corona anxiety (Beta=–0.157, p=0.010) and between psychological wellbeing and corona anxiety (Beta=–0.058, p=0.031) there was a significant direct relationship. There is no significant direct relationship between communication patterns and corona anxiety (Beta=–0.025, p=0.077). In examining the coefficients of the total effect, the results showed that the total impact of psychological wellbeing and corona anxiety (Beta= –0.159, p<0.001) and the total effect of communication patterns and corona anxiety (Beta=–0.084, p=0.023) were significant.
The indirect effect of psychological wellbeing on corona anxiety with the mediating role of quality of life (B=–0.504, p=0.032) and the indirect impact of communication patterns on corona anxiety with the mediating role of quality of life (B=–0.124, p=0.040) were significant. The goodness of fit indices also supports the good fit of the model with the collected data (CMIN/df=2.325, GFI=0.946, NFI=0.967, CFI=0.916, RFI=0.921, IFI=0.908, PNFI=0.761, RMSEA=0.093).
Conclusion: According to research findings, psychological wellbeing and communication patterns affect corona anxiety. In the meantime, the quality of life has a mediating and influential role.