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Universal Visual Quality Finding Low...
~
Hallsaxton, Morna Jayne Corinne.
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Universal Visual Quality Finding Low-Stress Perceptions Across Interior Built and Exterior Nature Environments.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Universal Visual Quality Finding Low-Stress Perceptions Across Interior Built and Exterior Nature Environments./
作者:
Hallsaxton, Morna Jayne Corinne.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2024,
面頁冊數:
190 p.
附註:
Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
Contained By:
Dissertations Abstracts International85-11B.
標題:
Environmental health. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31145529
ISBN:
9798382346731
Universal Visual Quality Finding Low-Stress Perceptions Across Interior Built and Exterior Nature Environments.
Hallsaxton, Morna Jayne Corinne.
Universal Visual Quality Finding Low-Stress Perceptions Across Interior Built and Exterior Nature Environments.
- Ann Arbor : ProQuest Dissertations & Theses, 2024 - 190 p.
Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
Thesis (Ph.D.)--Michigan State University, 2024.
As humans spend more time inside built environments, as evidenced by recent COVID 19 pandemic mandates, attention to how the built environment affects human health with stress is increasing (Nunez-Gonzalez, et al., 2020). Recent literature investigating the built environment found improved occupant health with greenbuilding rating systems (GRS) certified buildings. However, statistical research and literature about the built environment attributes shown to improve mental health by decreasing stress through interaction with nature environments remains limited. This study investigates the relationships of the built environment attributes (some stated in WELL Mind Concept criteria) with Attention Restorative Theory (ART) (Kaplan & Kaplan, 1989) engagement components for the effects of environmental stress on human mental health. Three questions are addressed: 1) Are there significant spatial attributes surrounding built environments, nature environments, or a combination of both, that can be consistently recognized to lower human stress within the built environment? 2) What spatial attributes are identified from a predictive model suggesting a ranking of significant low-stress attributes? 3) Are the participants' feelings of low stress shown in differential word antonyms associated with their visual perceptions of low-stress photographs? A significant predictive model (p<0.05) is originated with independent variables investigating photographs of MountainScape, ForestScape, WaterScape, Agricultural, RuralScape, Urban and Industrial, Ceiling Heights, Inside Views of Nature, Outside Views of Nature from inside, Inside Nature Engagement, and Outside Nature Engagement. Random surveys using Q-Sort Visual Quality Assessment method are created asking participants to rank ten variable photographs for perception of least stress (#1) to most stress (#10) on a scale of one to ten. The Semantic Differential method survey questions ask participants to rank their feelings with word antonyms from viewing specific variable photographs. Disclosure of data analysis reveals MountainScape, ForestScape and Outside Nature Engagement attributes as the most low-stress attributes. New knowledge is provided for low-stress mental health criteria necessary for architects and designers to implement with built environments, building policies and procedures, and educating others.
ISBN: 9798382346731Subjects--Topical Terms:
543032
Environmental health.
Subjects--Index Terms:
Architectural design
Universal Visual Quality Finding Low-Stress Perceptions Across Interior Built and Exterior Nature Environments.
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As humans spend more time inside built environments, as evidenced by recent COVID 19 pandemic mandates, attention to how the built environment affects human health with stress is increasing (Nunez-Gonzalez, et al., 2020). Recent literature investigating the built environment found improved occupant health with greenbuilding rating systems (GRS) certified buildings. However, statistical research and literature about the built environment attributes shown to improve mental health by decreasing stress through interaction with nature environments remains limited. This study investigates the relationships of the built environment attributes (some stated in WELL Mind Concept criteria) with Attention Restorative Theory (ART) (Kaplan & Kaplan, 1989) engagement components for the effects of environmental stress on human mental health. Three questions are addressed: 1) Are there significant spatial attributes surrounding built environments, nature environments, or a combination of both, that can be consistently recognized to lower human stress within the built environment? 2) What spatial attributes are identified from a predictive model suggesting a ranking of significant low-stress attributes? 3) Are the participants' feelings of low stress shown in differential word antonyms associated with their visual perceptions of low-stress photographs? A significant predictive model (p<0.05) is originated with independent variables investigating photographs of MountainScape, ForestScape, WaterScape, Agricultural, RuralScape, Urban and Industrial, Ceiling Heights, Inside Views of Nature, Outside Views of Nature from inside, Inside Nature Engagement, and Outside Nature Engagement. Random surveys using Q-Sort Visual Quality Assessment method are created asking participants to rank ten variable photographs for perception of least stress (#1) to most stress (#10) on a scale of one to ten. The Semantic Differential method survey questions ask participants to rank their feelings with word antonyms from viewing specific variable photographs. Disclosure of data analysis reveals MountainScape, ForestScape and Outside Nature Engagement attributes as the most low-stress attributes. New knowledge is provided for low-stress mental health criteria necessary for architects and designers to implement with built environments, building policies and procedures, and educating others.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31145529
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