ABSTRACT
Introduction Research on the effects of COVID-19 has shown that a favorable attitude toward the COVID-19 vaccine would help reduce the pandemic's sequelae and avoid lethal variants. Objective A theoretical model was tested through the strategy of path analysis and structural equation modeling, seeking to evaluate the direct effect of neuroticism and the indirect effects of risk-avoidance and rule-following behaviors, mediated by attitudes toward science. Methods A total of 459 adults, mostly women (61%), mean age 28.51 (SD = 10.36), living in Lima (Peru), participated. The scales of neuroticism, risk avoidance behavior (RAB), norm following (NF), attitudes toward science, and attitudes toward vaccination were administered. Results The path analysis explained 36% of the variance in vaccine attitude, whereas the latent structural regression model achieved a 54% explanation;according to this model attitude toward science (β=.70, p < .01) and neuroticism (β=-.16, p < .01) are significant predictors of vaccine attitude. Likewise, risk avoidance behavior and rule-following have indirect effects on attitudes toward vaccination. Conclusion Low neuroticism and a positive attitude toward the science that mediates the effects of RAB and NF directly condition the possibility of vaccination against COVID-19 in the adult population.
ABSTRACT
Introduction: Research on the effects of COVID-19 has shown that a favorable attitude toward the COVID-19 vaccine would help reduce the pandemic's sequelae and avoid lethal variants. Objective: A theoretical model was tested through the strategy of path analysis and structural equation modeling, seeking to evaluate the direct effect of neuroticism and the indirect effects of risk-avoidance and rule-following behaviors, mediated by attitudes toward science. Methods: A total of 459 adults, mostly women (61%), mean age 28.51 (SD = 10.36), living in Lima (Peru), participated. The scales of neuroticism, risk avoidance behavior (RAB), norm following (NF), attitudes toward science, and attitudes toward vaccination were administered. Results: The path analysis explained 36% of the variance in vaccine attitude, whereas the latent structural regression model achieved a 54% explanation; according to this model attitude toward science (ß=.70, p < .01) and neuroticism (ß=-.16, p < .01) are significant predictors of vaccine attitude. Likewise, risk avoidance behavior and rule-following have indirect effects on attitudes toward vaccination. Conclusion: Low neuroticism and a positive attitude toward the science that mediates the effects of RAB and NF directly condition the possibility of vaccination against COVID-19 in the adult population.
ABSTRACT
Our aim was to determine the influence of the variables Death Anxiety, Loneliness, and Depression on suicidal ideation in Peruvian adults during the COVID-19 pandemic. The sample consisted of 1342 subjects from Lima-Callao and regions of Peru, selected with non-probabilistic purposive sampling. A predictive, non-experimental design with the cross-sectional measurement using previously validated questionnaires was conducted. The differential effect of the variables Death Anxiety, Loneliness, and Depression on suicidal ideation was found. The two models obtained through structural equation modeling highlight a significant predictive relationship of Depression directly on suicidal ideation, while Loneliness is the second factor that best predicts suicidal ideation's indirect relationships. Likewise, being single and unemployed were found to be significantly associated (p < 0.05) and to have a differential effect on Death Anxiety, Loneliness and Depression. The same trend was evidenced by people aged less than 30, with no schooling, not practicing sports and sleeping less than 4 h;however, neither having had COVID-19 nor place of residence was found to influence suicidal ideation. As a conclusion, depressive symptomatology is the best predictor of suicidal ideation. Likewise, loneliness indirectly influences suicidal ideation.
ABSTRACT
Physicians that pursue postgraduate studies must simultaneously manage activities related to their academic training and their duties as specialized in a hospital. The aim of this study was to determine the challenges that affect the professional development and growth of 142 first-year medical residents from a private university in Peru, during the COVID-19 pandemic. The residents responded to an online questionnaire with eight open-ended questions soliciting the identification of two difficulties or challenges per question. Descriptive analysis of the challenges that were detected was carried out and two binomial logistic regression models were tested to evaluate the effect of academic and personal factors on professional development. A structural regression model with three predicting factors (Academic training, Mentorship and use of ICT, and Health conditions) was also tested to predict professional development. Over 80% of the residents expressed having problems with their professional performance, activities, and attention span during the residency. The adjusted logistic regression model explained 42% of the effect of factors that make the emergence of challenges for medical residents more probable in the performance of professional activities. Likewise, the structural regression model indicated a good fit, where all three factors significantly explained medical residents' professional performance;however, the Mentorship and use of ICTs factor was the best predictor of professional performance during the residency program.