UNASSIGNED: Adults within 3 years of stroke who had spent >2 nights in hospital for stroke and were able to consent were included (Melbourne, Australia). Using a factorial design, we immersed participants in 16 different virtual hospital patient rooms in both daytime and nighttime conditions, systematically varying design attributes: patient room occupancy, social connectivity, room size (spaciousness), noise (nighttime), greenery outlook (daytime). While immersed, participants rated their affect (Pick-A-Mood Scale) and preference. Mixed-effect regression analyses were used to explore participant responses to design variables in both daytime and nighttime conditions. Feasibility and safety were monitored throughout. Australian New Zealand Clinical Trials Registry, Trial ID: ACTRN12620000375954.
UNASSIGNED: Forty-four adults (median age, 67 [interquartile range, 57.3-73.8] years, 61.4% male, and a third with stroke in the prior 3-6 months) completed the study in 2019-2020. We recorded and analyzed 701 observations of affective responses (Pick-A-Mood Scale) in the daytime (686 at night) and 698 observations of preference responses in the daytime (685 nighttime) while continuously immersed in the virtual reality scenarios. Although single rooms were most preferred overall (daytime and nighttime), the relationship between affective responses differed in response to different combinations of nighttime noise, social connectivity, and greenery outlook (daytime). The virtual reality scenario intervention was feasible and safe for stroke participants.
UNASSIGNED: Immediate affective responses can be influenced by exposure to physical design variables other than room occupancy alone. Virtual reality testing of how the physical environment influences patient responses and, ultimately, outcomes could inform how we design new interventions for people recovering after stroke.
UNASSIGNED: URL: https://anzctr.org.au; Unique identifier: ACTRN12620000375954.
■中风后3年内因中风住院>2晚并能够同意的成年人包括在内(墨尔本,澳大利亚)。使用阶乘设计,我们让参与者在白天和晚上的16个不同的虚拟医院病房里,系统变化的设计属性:病房占用,社会连通性,房间大小(宽敞),噪音(夜间),绿化前景(白天)。当浸入水中时,参与者对他们的影响(Pick-A-Mood量表)和偏好进行评分。混合效应回归分析用于探索参与者在白天和夜间条件下对设计变量的反应。全程监测可行性和安全性。澳大利亚新西兰临床试验注册中心,试用ID:ACTRN12620000375954。
■44名成年人(平均年龄,67[四分位间距,57.3-73.8]年,61.4%男性,三分之一在前3-6个月出现中风)在2019-2020年完成了研究。我们记录并分析了白天(夜间686个)的701个情感反应观察(Pick-A-MoodScale)和白天(685个夜间)的698个偏好反应观察,同时持续沉浸在虚拟现实场景中。虽然单人间是最优选的整体(白天和夜间),情感反应之间的关系在响应夜间噪声的不同组合时不同,社会连通性,和绿化前景(白天)。虚拟现实情景干预对于卒中参与者是可行且安全的。
■直接的情感反应会受到暴露于物理设计变量而不是单独的房间占用的影响。虚拟现实测试物理环境如何影响患者的反应,最终,结果可以告知我们如何为卒中后康复患者设计新的干预措施.
■URL:https://anzctr.org.au;唯一标识符:ACTRN12620000375954。