ABSTRACT
Background: The world health organization has indicated that the problem of COVID-19 and confinement generated strong psychological impacts on the world population. Much of the research has focused on studying mental health in different population groups, leaving aside a positive mental health perspective. Objective(s): The present research intended to establish positive mental health profiles in confined women due to COVID-19 during 2020. Method(s): The factors of personal satisfaction, prosocial attitude, self-control, autonomy, problem-solving, self-actualization, and interpersonal relationships were assessed through the application of Lluch's positive mental health scale, in a sample of 202 confined women in the Department of Sucre, Colombia, selected by non-probabilistic convenience sampling. In addition, cluster analysis models were applied to identify psychological profiles of positive mental health and characterize sociodemographic variables, the selected model was evaluated and validated using the statistical technique of discriminant analysis using Minitab 18 software. Results and Discussion: A positive mental health differentiation in women is shown from which four psychological profiles of positive mental health could be identified, with scores of 14.10 in profile 1, 11.41 in profile 2, 9.15 in profile 3, and 7.56 in profile 4. The positive mental health factors used showed an ability to discriminate in 92.6% of the cases in the profiles. Conclusion(s): The identified profiles are significant and important to characterize psychometric profiles of positive mental health of confined women, which are important results for their diagnosis and the development of public policies for their treatment.Copyright © 2023 Bentham Science Publishers.
ABSTRACT
Objective: This work aims to provide a valid procedure to characterize and classify positive mental health profiles of subjects in prolonged confinement by COVID-19. M ethod: Methodologically, the factors prosocial attitude, self-control, personal satisfaction, autonomy, problem-solving and self-actualization, and interpersonal relationships were adopted in 285 individuals aged 18 to 75 years;the literature related to positive mental health, the application of Artificial Neural Networks and Cluster Analysis were reviewed, which allowed structuring a systematic analysis procedure to characterize and classify positive mental health profiles. Results: A procedure was achieved that integrates a cluster analysis that identified behavioral patterns and characterized groups of positive mental health and an artificial neural network that classifies positive mental health profiles into two groups distinguishing stages of the well-being of individuals and the normalized importance of the factors analyzed was established. Conclusion: From the results, it can be concluded that the proposed procedure that integrates cluster analysis and artificial neural networks can be used as a characterization and classification tool in studies where there are multiple variables, which complements traditional studies, providing robustness in the analysis. © 2022 Academia Nacional de Medicina. All rights reserved.
ABSTRACT
Introduction: The current situation given by the COVID-19 has not only affected the economy and health of many countries, but has also caused a number of problems in the mental health of the general population. Therefore, the commitment and research among professionals in the social sciences and psychology is necessary. Objective: To structure a method of analysis to evaluate and typify psychometric profiles of positive mental health in the Colombian population in a situation of confinement by COVID-19. Material and Methods: We reviewed the literature related to positive mental health and the multivariate technique of cluster analysis. We took a sample of 270 men and women between the ages of 18 and 75, to whom we applied the Positive Mental Health Scale proposed by Lluch related to the factors of personal satisfaction, prosocial attitude, self-control, autonomy, problem solving and self-updating, and interpersonal relationship skills. We applied the multivariate technique of cluster analysis to establish the psychometric profiles of positive mental health. Results: Four profiles that typify positive mental health in confinement were shown, with profile 1 being rated with an average of 2.05 and profile 2 with 2.69 being in a medium rating, while profile 3 with an average of 3.13 and profile 4 with an average of 3.32 being in a high rating of positive mental health. Conclusions: The proposed method of analysis is significant to evaluate and typify psychometric profiles of positive mental health in confinement by COVID-19. © 2021 Universidad de Ciencias Medicas de La Hab. All rights reserved.