Linda Clare1,2, Laura D Gamble3, Anthony Martyr1, Serena Sabatini1, Sharon M Nelis1, Catherine Quinn4,5, Claire Pentecost1, Christina Victor6, Roy W Jones7, Ian R Jones8, Martin Knapp9, Rachael Litherland10, Robin G Morris11, Jennifer M Rusted12, Jeanette M Thom13, Rachel Collins1, Catherine Henderson9, Fiona E Matthews3. 1. Centre for Research in Ageing and Cognitive Health, University of Exeter Medical School, Exeter, UK. 2. NIHR Applied Research Collaboration South-West Peninsula, Exeter, UK. 3. Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK. 4. Centre for Applied Dementia Studies, Bradford University, Bradford, UK. 5. Wolfson Centre for Applied Health Research, Bradford, UK. 6. College of Health, Medicine and Life Sciences, Brunel University London, London, UK. 7. Research Institute for the Care of Older People (RICE), Bath, UK. 8. Wales Institute for Social and Economic Research, Data and Methods, Cardiff University, Cardiff, UK. 9. Care Policy and Evaluation Centre, London School of Economics and Political Science, London, UK. 10. Innovations in Dementia CIC, Exeter, UK. 11. Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. 12. School of Psychology, University of Sussex, Brighton, UK. 13. School of Health Sciences, University of New South Wales, Sydney, Australia.
Abstract
OBJECTIVES: We aimed to examine change over time in self-rated quality of life (QoL) in people with mild-to-moderate dementia and identify subgroups with distinct QoL trajectories. METHODS: We used data from people with mild-to-moderate dementia followed up at 12 and 24 months in the Improving the experience of Dementia and Enhancing Active Life (IDEAL) cohort study (baseline n = 1,537). A latent growth model approach examined mean change over time in QoL, assessed with the QoL-AD scale, and investigated associations of baseline demographic, cognitive, and psychological covariates with the intercept and slope of QoL. We employed growth mixture modeling to identify multiple growth trajectories. RESULTS: Overall mean QoL scores were stable and no associations with change over time were observed. Four classes of QoL trajectories were identified: 2 with higher baseline QoL scores, labeled Stable (74.9%) and Declining (7.6%), and 2 with lower baseline QoL scores, labeled Stable Lower (13.7%) and Improving (3.8%). The Declining class had higher baseline levels of depression and loneliness, and lower levels of self-esteem and optimism, than the Stable class. The Stable Lower class was characterized by disadvantage related to social structure, poor physical health, functional disability, and low psychological well-being. The Improving class was similar to the Stable Lower class but had lower cognitive test scores. DISCUSSION: Understanding individual trajectories can contribute to personalized care planning. Efforts to prevent decline in perceived QoL should primarily target psychological well-being. Efforts to improve QoL for those with poorer QoL should additionally address functional impairment, isolation, and disadvantage related to social structure.
OBJECTIVES: We aimed to examine change over time in self-rated quality of life (QoL) in people with mild-to-moderate dementia and identify subgroups with distinct QoL trajectories. METHODS: We used data from people with mild-to-moderate dementia followed up at 12 and 24 months in the Improving the experience of Dementia and Enhancing Active Life (IDEAL) cohort study (baseline n = 1,537). A latent growth model approach examined mean change over time in QoL, assessed with the QoL-AD scale, and investigated associations of baseline demographic, cognitive, and psychological covariates with the intercept and slope of QoL. We employed growth mixture modeling to identify multiple growth trajectories. RESULTS: Overall mean QoL scores were stable and no associations with change over time were observed. Four classes of QoL trajectories were identified: 2 with higher baseline QoL scores, labeled Stable (74.9%) and Declining (7.6%), and 2 with lower baseline QoL scores, labeled Stable Lower (13.7%) and Improving (3.8%). The Declining class had higher baseline levels of depression and loneliness, and lower levels of self-esteem and optimism, than the Stable class. The Stable Lower class was characterized by disadvantage related to social structure, poor physical health, functional disability, and low psychological well-being. The Improving class was similar to the Stable Lower class but had lower cognitive test scores. DISCUSSION: Understanding individual trajectories can contribute to personalized care planning. Efforts to prevent decline in perceived QoL should primarily target psychological well-being. Efforts to improve QoL for those with poorer QoL should additionally address functional impairment, isolation, and disadvantage related to social structure.
Authors: Kristiina Hongisto; Saku Väätäinen; Janne Martikainen; Ilona Hallikainen; Tarja Välimäki; Sirpa Hartikainen; Jaana Suhonen; Anne M Koivisto Journal: Am J Geriatr Psychiatry Date: 2015-07-17 Impact factor: 4.105
Authors: Marcia C Dourado; Maria F de Sousa; Raquel L Santos; José P Simões; Marcela L Nogueira; Tatiana T Belfort; Bianca Torres; Rachel Dias; Jerson Laks Journal: Braz J Psychiatry Date: 2016-01-08 Impact factor: 2.697