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Psychological resilience is a dynamic process that enables individuals to cope with stressors and sustain balance throughout life. Previous studies have supported the relationship between psychological resilience and social support. However, variations in cultural contexts and populations may limit the generalizability of their findings to the Saudi Arabian population. This study utilized a latent profile analysis (LPA) to identify the latent profiles of psychological resilience and assess their association with sociodemographic characteristics and social support. A cross-sectional design was used on a sample of 385 adults in outpatient clinics at a general hospital in Riyadh, Saudi Arabia. Participants were recruited using a convenience sampling strategy. The questionnaire included sociodemographic data, the Connor-Davidson Resilience Scale (CD-RISC), and the MOS Social Support Survey (MOS-SSS). LPA was conducted to identify different profiles of psychological resilience. Furthermore, univariate analysis included the Chi-Square Test and Analysis of Variance (ANOVA) were conducted to examine the differences among profiles. Multinomial regression analysis was used to identify factors affecting psychological resilience profiles. Three resilience profiles were identified as the best-fitting model including low (11.68%), moderate (37.92%), and high (50.38%). The findings indicated that education, age, and the presence of psychiatric illness were associated with psychological resilience. Affectionate support, as well as emotional and informational support, were associated with psychological resilience. Healthcare practitioners may need to pay attention to individuals with lower education, younger age, mental illness, and lack of social support. They may also consider designing targeted interventional strategies to strengthen psychological resilience, specifically for vulnerable individuals, and enhance their ability to manage and cope with health-related stressors, thereby enhancing their well-being. Using a person-centered approach contributes to the existing knowledge by identifying different resilience profiles and assessing their associations with social support and sociodemographic variables.
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Alhazmi et al. (2026) studied this question.
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