|Sunday, June 21|
Evaluating the Fitness for the Elderly In the communities:Optimizing the LSES-ILE tool
* Yuliang Yan, Harbin Institute of Technology, China
Dake Wei, Harbin Institute of Technology, China
Background: Ageing of population is developing rapidly in China. More than half of Chinese elderly are "empty nesters" living independently in the mixed-age communities. Living environment affects the quality of their lives directly.Our team has established the LSES-ILE tool based on the investigation of the living needs of the elderly in the community which includes 4 domains, 119 controls and 197 excellent options.It’s a process with repeated practice and optimization to develop an evaluation criteria from a tool. The LSES-ILE tool has never been applied in different communities in China, thus the effect hasn’t been verified, needing to be optimized. Objectives: Verify and optimize the the LSES-ILE tool with application in multi-type communities around China.Evaluate the internal consistency, test-retest reliability and construct validity of LSES-ILE tool.Optimiz the items basing on practical application, reliability and validity test.Provide data support for the establishment of urban community living environment evaluation criterion. Novelty: Establish the evaluation tool which is currently missing in China to evaluate the fitness for elderly in community.It's a binary scale, which matches the needs of the elderly with environmental factors.Evaluate the fitness for the elderly in multi-type communities among China. Methods: 1.Sample selection According to a catalogue based on the current situation of Chinese communities, 26 community samples in different regions and types were selected. 2.Practical application Through observation and field measurement, LSES-ILE tool was used to evaluate sample communities to collect community sample score (CSS). In these communities, 103 elderly over 60 years old were recruited to conduct questionnaire interviews on their community living experience to collect auxiliary analysis data: quality of their lives (QoL), community satisfaction degree (CSD), community participation (CP) After two weeks, some communities were evaluated twice to get the second score of community sample (CSS 2). 3.Data analysis SPSS is used to analyze the data. Cronbach's α was used to test the internal consistency, KAPPA was used to test the test-retest reliability, and the construct validity was evaluated by the significance test of the correlation between CSS and QOL, CSD and CP. 4.Optimiz the items Adjust the secondary indicators according to the analysis results, delete the unqualified items. Expected outcomes/deliverables: The LSES-ILE tool can be used in many types of communities in China though some problems still existing in the old town and the city villages, such as fuzzy items and inconsistent with the actual situation.It's proved that the LSES-ILE tool has reliability. However, in community supporting facilities, urban function support and community-based service network, the reliability is obviously lowerthus it is necessary to supplement the content of these domains.It can be verified that CSS is related to QOL, CSD and CP, so the LSES-ILE tool has construct validity.It provides a research basis for the establishment of urban community living environment evaluation criterion which deleted 35 items.
Computational Models for Measuring Visual Environment Quality of the Elderlys Bedroom in Long-Term Care Home
* Xi Li, Harbin Institute of Technology, China
Dake Wei, Harbin Institute of Technology, China
Background: In the long-term care home, the bedroom is a private space to fullfill the most basic life needs of the elderly, whose spatial quality has a significant impact on the elderly’s quality of life. The majority of the elderly in the long-term nursing home have different degrees of physical, sensory and cognitive damage, and need the bedroom to provide targeted environmental support. In the past, the evidence-based qualitative research was often used, which could not provide direct design basis due to the lack of quantitative indicators. The post-evaluation study focuses on overall experience, lacking the in-depth study of visual environment. However, it is very important for the elderly with cognitive impairment to understand the spatial environment through visual maximization. The quantitative evaluation model for the quality of visible environment in the elderly's bedroom remains to be studied. Objects: This paper puts forward a computational model for measuring visual environment quality of the elder’s bedroom in long-term care home, through analyzing the architectural plane and functional partition from visual aspects. The computational data provide guidance and basis for optimization of the bedroom, so as to improve the quality of life for the elderly. MethodsBased on the literature review, this paper analysis the elderly's life needs and environmental support strategies. It establishes five evaluation parameters of visual environmental quality: permeability, accessibility, privacy, visibility and lighting quality. Then, using the method of spatial quality mapping model and mathematical model, the analysis steps and formula model are given from the perspective of spatial perception and visual experience. Finally, by computing demonstration, the feasibility of the model in analysing architectural plane and functional partition is verified. Results: The computational model is composed of three steps. The first step is to separate the perceptual space and path from the perspective of architectural geometric. The second step is to subdivide perceptual space using spatial quality mapping model. The third step is parameter calculation using mathematical models. Novilty: Based on life needs of the elderlythe parameters and processes of the computational model reflect environmental support for them. Aiming at the in-depth study of visual environmentvisual distance, visual angle, visual field and light are considered comprehensively. Importance: The computational method used in the model may bring development to measuring the visual environment. The model can be used to provide basis for the optimization of spatial design, which is conducive to the improvement of living space and the well-being of the elderly's life. Supported by the natural research fund of Heilongjiang Province, China, this paper is the core content of the project, “Study on Basic Nursing Space Design Parameters for the Disabled Elderly in Severe Cold Area Based on Behavior Experiment”. Key Words: Computational models, Visual environment, Elderly’s bedroom, Long-term care home, Spatial qualities rankings
Where to Locate Patients with High Risk for Fall: Nurses Subjective Perspectives and Space Syntax Objective Analysis
* Mahshad Kazem Zadeh, University of Florida, United States
Purpose: This study investigates the best and worst patient rooms in medical/surgical nursing units of hospital for assigning patients with high risk for fall. Examining physical environmental factors associated with fall rates, this study compares subjective assessments of nursing staff with objective indicators derived from space syntax attributes. Fifty units in VA hospitals with a 5-year record: twenty-five units with low-fall rates and twenty-five with high-fall rates form the sample for this study. Background: Patient fall can lead to preventable patient harm, increased length of stay, and high healthcare costs (Wu, Keeler, Rubenstein, Maglione, & Shekelle, 2010). Studied extensively in the last several years, contributors to patient falls in healthcare facilities cover a complex array of internal and external risk factors. Research on the physical environment of the healthcare setting as a contributor to falls is growing (Pati et al., 2019), yet these studies (1) typically examine a few environmental factors measured either by subjective or objective assessments, and (2) generally have small sample sizes using convenience sampling. There is a body of literature investigating nurses perceptions of factors contributing to falls (Ayton et al., 2017; Chaudhury, Mahmood, & Valente, 2006; DeChance, 2016; Garrett, 2010; Grealish et al., 2019; Mahmood, Chaudhury, & Valente, 2011; Rush et al., 2009; Shever, Titler, Mackin, & Kueny, 2011; Tzeng & Yin, 2008); however, the focus of these studies generally pertains to programmatic, organizational and cultural factors of the healthcare setting. To strengthen the knowledge field, more systematic methods and sampling techniques are needed, along with multi-methodological approaches that include both objective and subjective assessments, especially from the lenses of nursing staff who work in those immediate settings where falls occur. The theory of Space Syntax, which was first introduced by Hillier (1976), focuses on highlighting the underlying social logic of spaces by developing strategies to explain their configurations and their effects on various social and cultural attributes (Hillier, Leaman, Stansall, & Bedford, 1976). According to Choi (2017), who utilized Space Syntax theory and methods in relation with patient falls, visibility and accessibility in inpatient unit layouts of hospitals can be optimized to understand ways to decrease the rate of this adverse event (Choi, 2011). Methods: We will use fall data from the VA Inpatient Evaluation Center (IPEC) and patient data from additional data sources to identify 25 medical/surgical nursing units with higher- than expected (i.e. showing highest deviation from rates predicted by an appropriately fitted regression model, using studentized mixed model residuals) and 25 medical/surgical nursing units with lower- than expected fall rates. Once these units are identified, we assess quantified spatial characteristics of these units by measuring visibility and accessibility integration through using Space Syntax theory and methods. To gauge subjective assessments, we interviewed and surveyed nurses from these units about physical characteristics of rooms most conducive and least conducive to fall-risk patients. A comparison of the results of these two approaches was made, as pertaining to low-fall and high-fall units. Results: While the results of the study are currently on-going, the presentation at the conference will include the findings from the Space Syntax and nursing survey research; along with preliminary data comparing the two, in light of low-fall and high-fall hospital units. Implications: The methodology and results of this study will demonstrate the value of a multifaceted approach to examining physical environmental contributors to patient falls in hospital settings. In conjunction with other studies of this knowledge field, informed guidelines for designers, facility managers, policy makers, and healthcare stakeholders can be created for not only architectural and interior design and modifications, but also for assigning patients with high risk of fall to patient rooms. Applying the results of this study in practice will enhance patient safety in hospitals, which is the true goal of evidence-based design.