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Objective: The present study aimed to predict corona disease anxiety among medical staff in Tehran based on five-factor theory of personality. Method: In the present descriptive and correlational study, the statistical population included all medical staff in Tehran in 2020, among which 210 physicians, nurse, and other medical staffs were selected based on snowball sampling method. The instruments included Neo-Five Factor Inventory (NEO-FFI), Corona Disease Anxiety Scale (CDAS). Data were analyzed using Pearson’s correlation and Multiple Regression Analysis. Findings: Regression analysis indicated significantly Beta coefficients for openness personality traits (-0.238) and conscientiousness personality traits (-0.249). a statistically significant correlation is observed between openness (39%), neuroticism (-39%), extraversion (37%), conscientiousness (34%), and agreeableness (25%) with coronavirus anxiety at the 99% confidence level. Further, the correlation between each of the dimensions and the mental component of coronavirus anxiety is more compared to that of physical one. Conclusion: Based on the results of multiple regression analysis, the micro-components of openness and conscientiousness could predict the level of total coronavirus anxiety. Considering standard coefficients, conscientiousness plays a more important role in predicting the level of total coronavirus anxiety in medical staffs, which decreases by increasing openness and conscientiousness. Medical staff who are higher in openness and conscientiousness personality traits are lower in corona disease anxiety.

Purpose: The purpose of this study was to prioritize the factors affecting consumer-buying behavior in online social media marketing.Method: The analysis and validation of indicators were conducted using the mixed method of structural equation modeling and partial least squares. Additionally, the IPMA matrix was utilized to determine the importance and type of performance of each factor. The research data were influenced by consumer information, predominantly consisting of women with a master's degree aged between 36 and 50 years. The study employed a non-probability sampling method common for online surveys, and 466 individuals were examined using Cohen's effect size formula.Findings: The research findings indicated that consumer engagement was the most important factor, and ease of use exhibited the highest level of performance in the overall social media model. Furthermore, consumer engagement was identified as the most important factor, while electronic word-of-mouth (EWOM) demonstrated the highest performance level on Instagram. Conversely, EWOM was deemed the most important factor, with consumer engagement displaying the highest performance level on Telegram. These results can be utilized by marketers to influence consumer purchasing behavior and craft online marketing strategies accordingly.Conclusion: Companies utilizing online social media platforms are advised to enhance consumer engagement and performance by implementing short-term techniques and effective strategies, such as incorporating online chat functionalities in the user environment. Instagram, being the most widely used social media platform and an online shopping hub for consumers, showcased acceptable performance in terms of consumer engagement. Hence, companies need to take measures to elevate performance levels to match their importance. In the case of Telegram, EWOM emerged as the most crucial factor among others, with a commendable performance rating. Businesses can bolster their Customer Relationship Management (CRM) units and enhance WOM initiatives to the fullest extent possible.

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