著者

UBARA Ayaka SUMI Yukiyoshi ITO Kazuki MATSUDA Arichika MATSUO Masahiro MIYAMOTO Towa KADOTANI Hiroshi 乳原 彩香 角 幸頼 伊藤 一樹 松田 有史 松尾 雅博 宮本 都和 角谷 寛

出版者

MDPI AG

雑誌

International Journal of Environmental Research and Public Health

巻号頁・発行日

vol.17, no.23, pp.8971, 2020-12-02

被引用文献数

11

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We aimed to analyze (a) the changes in depression, sleepiness, insomnia, and sleep habits in relation to the degree of self-isolation and (b) the effects of changes in sleep habits and social interactions on depression, insomnia, and sleepiness during the coronavirus disease 2019 (COVID-19) pandemic. We enrolled 164 patients who visited the sleep outpatient clinic in Shiga University of Medical Science Hospital. We compared the sleep habits, depression (Patient Health Questionnaire-9: PHQ-9), insomnia (Athens Insomnia Scale: AIS), and sleepiness (Epworth Sleepiness Scale: ESS) of patients during the period from April to July 2019 vs. May 2020 (a period of self-isolation due to COVID-19). A Wilcoxon signed-rank test indicated no significant differences in PHQ-9, ESS, and AIS scores between 2019 and 2020 within both the strong self-isolation group and no/little self-isolation group. With respect to sleep habits, earlier bedtime (p = 0.006) and increased sleep duration (p = 0.014) were found in the strong self-isolation group. The former (p = 0.009) was also found in the no/little self-isolation group, but we found significant differences in sleep duration between the no/little self-isolation group and the strong self-isolation group (p = 0.047). Therefore, self-isolation due to COVID-19 had relatively small one-year effects on depression, sleepiness, and insomnia in a clinical population.

著者

Prilandita Niken McLellan Benjamin Tezuka Tetsuo

出版者

MDPI AG

雑誌

Challenges (ISSN:20781547)

巻号頁・発行日

vol.7, no.1, 2016-04-14

被引用文献数

3

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Autonomous decision-making in this study is defined as the process where decision-makers have the freedom and ability to find problems, select goals, and make decisions for achieving the selected problems/goals by themselves. Autonomous behavior is considered significant for achieving decision implementation, especially in the context of energy and environmental management, where multiple stakeholders are involved and each stakeholder holds valuable local information for making decisions. This paper aims to build a structured process in modeling the autonomous decision-making. A practical decision-making process in waste-to-energy conversion activities in a community in Bandung, Indonesia, is selected as a case study. The decision-making process here is considered as a discrete event system, which is then represented as a Petri-net model. First, the decision-making process in the case study is decomposed into discrete events or decision-making stages, and the stakeholders' properties in each stage are extracted from the case study. Second, several stakeholder properties that indicate autonomous behavior are identified as autonomous properties. Third, presented is a method to develop the decision-making process as a Petri-net model. The model is utilized for identifying the critical points for verifying the performance of the derived Petri-net.

著者

Prilandita Niken McLellan Benjamin Tezuka Tetsuo

出版者

MDPI AG

雑誌

Sustainability (Switzerland) (ISSN:20711050)

巻号頁・発行日

vol.9, no.1, 2017-01-09

被引用文献数

4

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This paper develops an evaluation method for assessing autonomous decision-making performance and demonstrates it using a case study. Focusing on community decision-making practice in energy-environmental innovation projects, a decision-making model is developed using Petri-net. This empirical model is then expanded to be able to accommodate autonomous properties and more pathways to reach various decision-making outcomes. The autonomous decision-making performance evaluation is employed by simulating the impact of various levels of autonomous conditions using the expanded model stochastically. Those results are further divided into six categories, based on the conditions (autonomous, semi-autonomous, and non-autonomous) and decision outcomes (fully successful, moderately successful, and failed). For each category, the specific stakeholders' properties are analysed and explained. The categorised conditions are useful for estimating the outcomes of the particular community decision-making practice based on the stakeholders' properties. The model can be modified in order to pre-evaluate other energy and environmental related decision-making.