Developing and Testing a Model of the Assisted Living Environment

Datos Bibliográficos

ID6152850
AutoresSarah Holme (0000-0001-7094-7927, University of Maryland, Baltimore, autor de correspondencia), Barbara Resnick (0000-0002-2839-5783, University of Maryland, Baltimore), Elizabeth Galik (0000-0002-7337-8018, University of Maryland, Baltimore), Nancy Kusmaul (0000-0003-2278-8495, University of Maryland, Baltimore County)
Año2020
Volumen35
Número1
Páginas62-76
Fecha de publicación2020-07-21
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaJournal of Aging and Environment (JOURNAL)
Identificadores de la revistaISSN: 2689-2618 • E-ISSN: 2689-2626
EditorialTaylor & Francis (PUBLISHER • GB)
DOI10.1080/26892618.2020.1793439
PMID34423332
OpenAlexW3043983655
IdiomaEN
Referencias citadas36

The assisted living (AL) environment plays an important role in supporting residents' satisfaction and helping them to age in place. The AL environment is multidimensional and has many interrelated components including staffing (e.g. direct care workers, nursing, activity staff), services provided (e.g. medical, mental health, pharmacy), amenities offered at the setting (e.g. beauty salon, library, exercise facilities), and the physical environment. Evidence suggests that aspects of the AL environment can enhance or detract from the physical function, well-being, social engagement, and behavioral outcomes among residents. The purpose of this study was to develop and test a multidimensional AL environment measurement model that includes indicators of staffing, services, amenities, and the physical environment. Baseline data was used from a study testing the Dissemination and Implementation of Function Focused Care in AL. A total of 54 AL facilities across three states were included in the sample. Settings ranged in size from 31 to 164 beds with an average size of 82.2 (SD=26.2) beds and the majority were for profit facilities (n=41, 74.5%). Structural equation modeling was used to test the proposed model. Results showed that the model fit the data (χ2/df=1.861, p<.05; CFI=.858, RMSEA=.126). Having a comprehensive AL environment measurement model will advance future research that explores the impact of the environment on resident outcomes. Findings from this study will inform interventions and programs designed to modify AL environments to optimize residents' satisfaction with AL

Built environment · Psychological intervention · Staffing · Structural equation modeling · Test (biology · Applied Psychology · Computer Science · Engineering · Geriatric Care and Nursing Homes · Health disparities and outcomes · Medicine · Migration, Aging, and Tourism Studies · Nursing · Psychology · Gerontology