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This qualitative study aims to explore the experiences of Taiwan’s community-based long-term care service stations.

Semi-structured interviews were conducted with eight managers selected from stations located in the counties with the highest proportion of elderly people.

The results are as follows: the main services offered by the stations include health promotion activities, congregate meal programs, respite care and making house calls; government subsidies constitute a major proportion of the service stations’ funds, followed by user payments and external donations; the adversities encountered include frequent policy revisions, the dwellers’ reluctance to participate in the activities, manpower shortages and subpar service quality; and the effects of the stations on the community include achieving aging in place, providing more options for life after retirement, mitigating caregivers’ burden, expanding the elderly’s social networks and strengthening their health literacy.

The results of this research can understand the benefits and difficulties of Tier C service centers in Taiwan. Also, the practical experiences provide some suggestions for policies and training. Future studies can focus on establishing systematized training programs and standardizing the service personnel’s competence.

The identification of network user relationship in Fancircle contributes to quantifying the violence index of user text, mining the internal correlation of network behaviors among users, which provides necessary data support for the construction of knowledge graph.

A correlation identification method based on sentiment analysis (CRDM-SA) is put forward by extracting user semantic information, as well as introducing violent sentiment membership. To be specific, the topic of the implementation of topology mapping in the community can be obtained based on self-built field of violent sentiment dictionary (VSD) by extracting user text information. Afterward, the violence index of the user text is calculated to quantify the fuzzy sentiment representation between the user and the topic. Finally, the multi-granularity violence association rules mining of user text is realized by constructing violence fuzzy concept lattice.

It is helpful to reveal the internal relationship of online violence under complex network environment. In that case, the sentiment dependence of users can be characterized from a granular perspective.

The membership degree of violent sentiment into user relationship recognition in Fancircle community is introduced, and a text sentiment association recognition method based on VSD is proposed. By calculating the value of violent sentiment in the user text, the annotation of violent sentiment in the topic dimension of the text is achieved, and the partial order relation between fuzzy concepts of violence under the effective confidence threshold is utilized to obtain the association relation.

This study aims to examine the effects of dialect connectedness between the chairman and the chief executive officer (CEO) (DCCC) on the tunneling activities of controlling shareholders.

This study uses abnormal related-party transactions (ARPT) as a proxy for tunneling activities and traces dialects of chairmen and CEOs based on the respective birthplace information. Baseline results are examined using a fixed-effects model. The results remain robust when using the instrumental variable approach, propensity score matching (PSM) technique, changing the measurement of tunneling and Heckman two-step selection model.

The results show that DCCC reduces tunneling activities. This negative association is more pronounced for non-state-owned enterprises and firms whose chairmen and CEOs work in the respective hometowns. DCCC restrains tunneling activities through mechanisms by establishing an informal supervisory effect on CEOs because the CEOs fear reputational damage and strengthening cooperation between chairmen and CEOs. Further analyses suggest that this negative association is more significant when chairmen and CEOs are non-controlling shareholders, but the association is weakened during the coronavirus disease 2019 (COVID-19) crisis.

As dialect is a carrier of culture, this study's results imply that cultural proximity can replace formal mechanisms to enhance corporate governance.

Nurses' turnover intention has become a major issue in developing countries with high power distance cultures. Therefore, the authors attempt to investigate how turnover intention among nurses' can be reduced through paternalistic leadership (PL). The authors further investigate the mediating role of job satisfaction between the associations of benevolent, moral and authoritarian dimensions of PL with turnover intention. Finally, the authors examined perceived organizational support (POS) as a conditional variable between job satisfaction and turnover intention.

The authors collected data from 374 nurses working in public and private hospitals of high power distance culture using a questionnaire-based survey on convenience basis.

Structural equation modeling confirms that benevolent and moral dimensions of PL positively affect nurses' job satisfaction which helps them reduce their turnover intention. While the authoritarian dimension of PL negatively affects job satisfaction to further enhance their turnover intention. In addition, the authors noted POS as a conditional variable to trigger the negative effect of job satisfaction on turnover intention.

The authors used a cross-sectional design to collect responses and ensured the absence of common method variance through Harman's Single factor test.

This study identified the mechanism (job satisfaction and POS) through which benevolent, moral and authoritative dimensions of PL predict turnover intention among nurses working in high power distance culture.

護士有離職意向，在擁有高權力距離文化的發展中國家，已成為一個重大的問題。因此，我們擬探討如何可以透過採用家長式領導、把護士離職的意欲減低，繼而研究工作滿足感，在離職意向與家長式領導中仁慈、道德和獨裁這三個層面的關係中所起的中介作用。最後，我們就組織支持感，作為是工作滿足感與離職意向之間的一個條件變數，進行了研究。

本研究透過採用在便利的基礎上進行的問卷調查，從374名在高權力距離文化的公營和私營醫院內工作的護士取得數據，進行分析。

結構方程模型證實了家長式領導中的仁慈和道德這兩個層面，會對可減低護士離職意欲的工作滿足感，產生積極的影響。家長式領導中的獨裁層面、則會對護士的工作滿足程度產生負面的影響，繼而增強其離職意欲。而且，我們確認了組織支持感是一個會增強工作滿足感與離職意向之間負相聯的條件變數。

我們以橫斷面的設計法來收集回應，並透過採用哈曼 (Harman) 的單因素檢定法，來確保共同方法變異不會存在。

本研究確定了一個 (工作滿足感與組織支持感) 機制，透過這機制，家長式領導中的仁慈、道德和獨裁這三個層面可預測於高權力距離文化工作的護士的離職意向。

Global climate change speeds up ice melting and increases flooding incidents. China launched a sponge city policy as a holistic nature-based solution combined with urban planning and development to address flooding due to climate change. Using Weibo analytics, this paper aims to study public perceptions of sponge city.

This study collected 53,586 sponge city contents from Sina Weibo via Python. Various artificial intelligence tools, such as CX Data Science of Simply Sentiment, KH Coder and Tableau, were applied in the study.

76.8% of public opinion on sponge city were positive, confirming its positive contribution to flooding management and city branding. 17 out of 31 pilot sponge cities recorded the largest number of sponge cities related posts. Other cities with more Weibo posts suffered from rainwater and flooding hazards, such as Xi'an and Zhengzhou.

To the best of the authors’ knowledge, this study is the first to explore the public perception of sponge city in Sina Weibo.

This paper seeks to investigate the differences in the teachers’ professional development (TPD) by mentorship in workplace. The authors examined the role of mentorship in the PD of teachers and conducted a meta-analysis of pertinent empirical data.

Using data from over 2,900 individuals, 66 experiments and 12 countries, the authors presented a meta-analysis of the association between workplace mentorship and TPD.

The authors concluded that mentoring activities could boost the TPD to some extent. It contributes positively to the discipline of science and language, kindergarten, individual mentoring and curriculum research. In addition, the periodicity should not exceed 1 year.

The results of the meta-analysis are restricted to short-term mentorship activities, and the sample size is modest. Building upon the findings from the literature review and meta-analysis, the authors delineated a research agenda for prospective investigations. This includes an imperative for further exploration into the nexus between mentoring and the PD of educators.

Based on the available literature and meta-analysis findings, the authors developed a framework for the “Experts in the classroom” TPD pattern.

This is the first meta-analysis evaluating the association between mentorship and TPD.

Attributes conveying cultural significance play a key role in heritage management, as well as in differentiating interventions in built heritage. However, seldom the relation between interventions and attributes, either tangible or intangible, has been researched systematically. How do both tangible and intangible attributes and interventions relate? What attributes make interventions on built heritage differ?

This paper conducts a systematic content analysis of forty-one international doctrinal documents—mainly adopted by the Council of Europe, UNESCO and ICOMOS, between 1877 and 2021. The main aim is to reveal and compare the selected eight intervention concepts, namely—restoration (C1), preservation (C2), conservation (C3), adaptation (C4), rehabilitation (C5), relocation (C6), reconstruction (C7) and renewal (C8)—and their definitions, in relation to attributes, both tangible and intangible. The intensity of the relationship between intervention concepts and attributes is determined based on the frequency of the mentioned attributes per intervention.

There were three key findings. First, although the attention to intangible attributes has increased in the last decades, the relationship between interventions and tangible attributes remains stronger. The highest frequency of referencing the tangible attributes was identified in “relocation” and “preservation,” while the lowest was in “rehabilitation.” Second, certain attributes play contradictory roles, e.g. “material,” “use” and “process,” which creates inconsistent definitions between documents. Third, as attributes often include one another in building layers, they trigger the intervention concepts in hierarchical patterns.

This paper explores and discusses the results of a novel comparative analysis between different intervention concepts and definitions, with a particular focus on the attributes. The results can support further research and practice, clarifying the identified differences and similarities.

The present study aims to test the impact of workplace incivility and violence on doctors' turnover intentions. Besides, the present study also tested the mediating role of employees' burnout.

The population of the present study was doctors working in 20 public sector hospitals. Where 250 doctors working in emergency departments participated, the sample size was calculated through Krejcie and Morgan's table. The data analysis was conducted through SPSS and Smart-PLS.

Results of the present study supported all the relationships except the relationship between workplace violence and turnover intentions. More specifically, relationship between workplace incivility and turnover intentions was confirmed, and mediation effect of doctors' burnout was also confirmed.

This present study is novel in a way that this study framed the study model using conservative resource theory and social cognitive theory covering both employees cognitive and external factors. Further, the nexus “workplace incivility → workplace violence → job burnout → turnover intentions” was tested for the first time, hence making a valuable addition to the body of literature. Further this study is a contribution to healthcare literature in context of incivility, violence, burnout, and turnover. Burnout is first time explored as moderator with workplace incivility which is another contribution.

In the context of constructing an integrated national strategic system, collaborative innovation among enterprises is the current social focus. Therefore, in order to find the interest relationship between multiple game subjects, to explore the influencing factors of collaborative innovation of civil-military integration enterprises. This paper constructs a collaborative innovation mechanism for military–civilian integration involving four game subjects (military enterprises, private enterprises, local governments, and science and technology intermediaries). It aims to solve and reveal the evolutionary game relationship among the four parties.

To explore the mechanism of military–civilian collaborative innovation involving four players, this study employs game theory and constructs an evolutionary game model for collaborative innovation with the participation of military enterprises, civilian enterprises, local governments, and technology intermediaries. The model reveals the evolutionary game patterns among these four entities, analyzes the impact of various parameters on the evolutionary process of the game system, and numerical simulation is used to show these changes more specifically.

The research findings demonstrate that active government subsidies promote cooperation throughout the system. Moreover, increasing the input-output ratio of research and development (R&D), the rate of technological spillovers, and the R&D investment of civilian enterprises all facilitate the tendency toward cooperation within the system. However, when the government chooses to actively provide subsidies, increasing R&D investment in military enterprises may hinder the tendency toward cooperation. Furthermore, central transfer payments, government punishment from the central government, and an increase in the information conversion rate of technology intermediaries may suppress the rate of cooperation within the system.

Most of the previous studies on the collaborative innovation of military–civilian integration have been tripartite game models between military enterprises, private enterprises, and local governments. In contrast, this study adds science and technology intermediaries on this basis, reveals the evolution mechanism of collaborative innovation of civil-military integration enterprises from the perspective of four-party participation, and analyzes the factors influencing the cooperation of the whole system. The conclusion of this study not only enriches the collaborative innovation evolution mechanism of military–civilian integration enterprises from the perspective of multiple agents but also provides practical guidance for the innovation-driven development of military–civilian integration enterprises.

Social media texts as a data source in depression research have emerged as a significant convergence between Information Management and Public Health in recent years. This paper aims to sort out the depression-related study conducted on the text on social media, with particular attention to the research theme and methods.

The authors finally selected research articles published in Web of Science, Wiley, ACM Digital Library, EBSCO, IEEE Xplore and JMIR databases, covering 57 articles.

(1) According to the coding results, Depression Prediction and Linguistic Characteristics and Information Behavior are the two most popular themes. The theme of Patient Needs has progressed over the past few years. Still, there is a lesser focus on Stigma and Antidepressants. (2) Researchers prefer quantitative methods such as machine learning and statistical analysis to qualitative ones. (4) According to the analysis of the data collection platforms, more researchers used comprehensive social media sites like Reddit and Facebook than depression-specific communities like Sunforum and Alonelylife.

The authors recommend employing machine learning and statistical analysis to explore factors related to Stigmatization and Antidepressants thoroughly. Additionally, conducting mixed-methods studies incorporating data from diverse sources would be valuable. Such approaches would provide insights beneficial to policymakers and pharmaceutical companies seeking a comprehensive understanding of depression.

This article signifies a pioneering effort in systematically gathering and examining the themes and methodologies within the intersection of health-related texts on social media and depression.