10.1016/s0967-0653(97)84657-1

Vollständiger Abstract

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BACKGROUND: Demoralization negatively affects the quality of life, especially in people with mental disorders. OBJECTIVE: This study aims to assess demoralization in a cohort of community-dwelling older adults, to identify groups of individuals who share similar characteristics in terms of mental health conditions and the severity of demoralization domains, and to investigate the different characteristics across these groups. METHODS: Participants were enrolled in 3 centers as part of the cross-sectional MentDis_ICF65+ study and were assessed using the Demoralization Scale and the Composite International Diagnostic Interview at baseline. A cluster analysis was conducted using the partitioning around medoids algorithm with Gower's distance to classify individuals based on demoralization severity and the diagnosis of mental health disorders, allocating individuals to a distinct number of patterns by examining their similarities across these variables. RESULTS: Among the final sample of 1369 participants, 3 clusters were identified: the "low psychopathology" cluster, with very few mental health diagnoses; the "affective" cluster, characterized by affective disorders (100% of participants); and the "anxiety" cluster, characterized by anxiety disorders (100% of participants). Men were prevalent in the "low psychopathology" cluster (n=635, 59.1%; P<.001), while women were more prevalent in the "affective" cluster (n=133, 72.3%; P<.001) and the "anxiety" cluster (n=79, 71.8%; P<.001). The "affective" cluster had the highest mean scores for disheartenment (17.1, SD 6.7; P<.001), dysphoria (12.1, SD 3.5; P<.001), and loss of meaning (11.8, SD 4.9; P<.001) but the lowest for sense of failure (17.4, SD 3.2; P<.001). CONCLUSIONS: The identification of different clusters of demoralization and mental health disorders in community-dwelling older adults, as well as sex-based differences, highlights the need for tailored mental health interventions in this vulnerable population.

Abstract: PubMed · Datensatz