Nicolas Hoertel1,2,3, Léa Rotenberg4, Carlos Blanco5, Vincent Camus6, Caroline Dubertret7,8,9, Véronique Charlot8,9, Franck Schürhoff10,11,12,13, Pierre Vandel14,15,16,17, Frédéric Limosin4,7,18. 1. DMU Psychiatrie et Addictologie, Service de Psychiatrie et d'Addictologie de l'Adulte et du Sujet Âgé, Centre Ressource Régional de Psychiatrie du Sujet Agé (CRRPSA), Hôpital Corentin Celton, AP-HP.Centre, Université de Paris, Paris, France. nico.hoertel@yahoo.fr. 2. Inserm U1266, Institut de Psychiatrie et Neurosciences de Paris, Paris, France. nico.hoertel@yahoo.fr. 3. Faculté de Médecine Paris Descartes, Université de Paris, Paris, France. nico.hoertel@yahoo.fr. 4. DMU Psychiatrie et Addictologie, Service de Psychiatrie et d'Addictologie de l'Adulte et du Sujet Âgé, Centre Ressource Régional de Psychiatrie du Sujet Agé (CRRPSA), Hôpital Corentin Celton, AP-HP.Centre, Université de Paris, Paris, France. 5. Division of Epidemiology, Services, and Prevention Research, National Institute on Drug Abuse, Bethesda, MD, USA. 6. Université de Tours, CHRU de Tours, Tours, France. 7. Inserm U1266, Institut de Psychiatrie et Neurosciences de Paris, Paris, France. 8. Department of Psychiatry, AP-HP, Louis Mourier Hospital, Colombes, France. 9. Faculté de médecine Paris Diderot, Université de Paris, Paris, France. 10. AP-HP, DHU PePSY, Hôpitaux Universitaires Henri-Mondor, Pôle de Psychiatrie, 94000, Créteil, France. 11. Inserm, U955, Team 15, 94000, Créteil, France. 12. Fondation FondaMental, 94000, Créteil, France. 13. Faculté de médecine, UPEC, Université Paris-Est, 94000, Créteil, France. 14. Centre d'investigation Clinique-Innovation Technologique CIC-IT 1431, Inserm, CHRU Besançon, 25000, Besançon, France. 15. Neurosciences Intégratives et Cliniques EA 481, Université Franche-Comté, Université Bourgogne Franche-Comté, 25000, Besançon, France. 16. Service de Psychiatrie de l'adulte, CHRU Besançon, 25000, Besançon, France. 17. Centre Mémoire de Ressource et de Recherche de Franche-Comté, CHRU Besançon, 25000, Besançon, France. 18. Faculté de Médecine Paris Descartes, Université de Paris, Paris, France.
Abstract
BACKGROUND: Numerous factors are known to influence quality of life of adults with schizophrenia. However, little is known regarding the potential predictors of quality of life in the increasing population of older adults with schizophrenia. The main objective of the present study was to propose a comprehensive model of quality of life in this specific population. METHODS: Data were derived from the Cohort of individuals with Schizophrenia Aged 55 years or more (CSA) study, a large (N = 353) multicenter sample of older adults with schizophrenia or schizoaffective disorder recruited from French community mental-health teams. We used structural equation modeling to simultaneously examine the effects of six broad groups of clinical factors previously identified as potential predictors of quality of life in this population, including (1) severity of general psychopathology, (2) severity of depression, (3) severity of cognitive impairment, (4) psychotropic medications, (5) general medical conditions and (6) sociodemographic characteristics. RESULTS: General psychopathology symptoms, and in particular negative and depressive symptoms, cognitive impairment, reduced overall functioning and low education were significantly and independently associated with diminished quality of life (all p < 0.05). Greater number of medical conditions and greater number of antipsychotics were also independently and negatively associated with quality of life, although these associations did not reach statistical significance in sensitivity analyses, possibly due to limited statistical power. CONCLUSION: Several domains are implicated in quality of life among older adults with schizophrenia. Interventions targeting these factors may help improve importantly quality of life of this vulnerable population.
BACKGROUND: Numerous factors are known to influence quality of life of adults with schizophrenia. However, little is known regarding the potential predictors of quality of life in the increasing population of older adults with schizophrenia. The main objective of the present study was to propose a comprehensive model of quality of life in this specific population. METHODS: Data were derived from the Cohort of individuals with Schizophrenia Aged 55 years or more (CSA) study, a large (N = 353) multicenter sample of older adults with schizophrenia or schizoaffective disorder recruited from French community mental-health teams. We used structural equation modeling to simultaneously examine the effects of six broad groups of clinical factors previously identified as potential predictors of quality of life in this population, including (1) severity of general psychopathology, (2) severity of depression, (3) severity of cognitive impairment, (4) psychotropic medications, (5) general medical conditions and (6) sociodemographic characteristics. RESULTS: General psychopathology symptoms, and in particular negative and depressive symptoms, cognitive impairment, reduced overall functioning and low education were significantly and independently associated with diminished quality of life (all p < 0.05). Greater number of medical conditions and greater number of antipsychotics were also independently and negatively associated with quality of life, although these associations did not reach statistical significance in sensitivity analyses, possibly due to limited statistical power. CONCLUSION: Several domains are implicated in quality of life among older adults with schizophrenia. Interventions targeting these factors may help improve importantly quality of life of this vulnerable population.
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Authors: Nicolas Hoertel; Marina Sánchez-Rico; Erich Gulbins; Johannes Kornhuber; Alexander Carpinteiro; Miriam Abellán; Pedro de la Muela; Raphaël Vernet; Nathanaël Beeker; Antoine Neuraz; Aude Delcuze; Jesús M Alvarado; Céline Cougoule; Pierre Meneton; Frédéric Limosin Journal: Transl Psychiatry Date: 2022-03-03 Impact factor: 6.222