Objectives: To describe the communication behaviors of patients and physicians and patient par-ticipation in communication about treatment decision-making during consultation visits for local-ized prostate cancer (LPC...Objectives: To describe the communication behaviors of patients and physicians and patient par-ticipation in communication about treatment decision-making during consultation visits for local-ized prostate cancer (LPCa). Methods: This is a secondary analysis of data from 52 men enrolled in the usual care control group of a randomized trial that focused on decision-making for newly diagnosed men with LPCa. We analyzed the patient-physician communication using the transcribed audio-recordings of real-time treatment consultations and a researcher-developed coding tool, including codes for communication behaviors (information giving, seeking, and clarifying/ verifying) and contents of clinical consultations (health histories, survival/mortality, treatment options, treatment impact, and treatment preferences). After qualitative content analysis, we categorized patient participation in communication about treatment-related clinical content, including “none” (content not discussed);“low” (patient listening only);“moderate” (patient providing information or asking questions);and “high” (patient providing information and asking questions). Results: Physicians mainly provided information during treatment decision consultations and patients frequently were not active participants in communication. The participation of patients with low and moderate cancer risk typically was: 1) “moderate and high” in discussing health histories;2) “low” in discussing survival/mortality;3) “low and moderate” in discussing treatment options;4) “none and low” in discussing treatment impacts;and 5) “low” in discussing treatment preferences. Conclusions: Findings suggest opportunities for increasing patient participation in communication about treatment decision-making for LPCa during clinical consultations.展开更多
This paper contains research on strategic decision-making in a local government. In a profit-oriented organization, the option that maximizes profits tends involve reaching an agreement between stakeholders. However, ...This paper contains research on strategic decision-making in a local government. In a profit-oriented organization, the option that maximizes profits tends involve reaching an agreement between stakeholders. However, there is tendency for stakeholders to differ in their beliefs as to what is desirable particularly in a non-profit organization. In a local government, it is especially difficult for the interests of a stakeholder group to be completely in agreement. This research considers the use of the analytical hierarchy process （Saaty, 1971） as a solution for one of the difficulties of decision-making in a local government. This research is a case study to explore the strategy of a local Japanese healthcare management organization. The conclusion was drawn to decide which strategic option should be taken by using the analytical hierarchy process. Also, it was found what to work on a countermeasure that prevents the negative effects that are generated by selecting the strategic option.展开更多
Based on the cross-sectional data about the municipal Party committee secretaries sacked since the 18th CPC National Congress, this paper adopts a regression model to examine and assess the impact of local top Party l...Based on the cross-sectional data about the municipal Party committee secretaries sacked since the 18th CPC National Congress, this paper adopts a regression model to examine and assess the impact of local top Party leaders' corruption. The study discovers that local heads' integrity directly affects local political ecology they are in; that regions in the charge of corruptive heads suffer a higher degree of corruption; and that the tenure of corruptive local heads relates much to the degree of local corruption(i.e. the longer their tenure is, the more baneful influence they exert on the clean governance of local leaders and cadres). Consequently, it is imperative to establish and consolidate a power structure and a corresponding operating mechanism which enable effective mutual constraint and balance among decisionmaking power, executive power and supervision power. Only by doing so can China alleviate the negative impact of local heads' corruption, effectively restrict and supervise local heads' exercise of power, and maintain a well balance between "power delegation" and "power supervision".展开更多
Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examini...Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.展开更多
文摘Objectives: To describe the communication behaviors of patients and physicians and patient par-ticipation in communication about treatment decision-making during consultation visits for local-ized prostate cancer (LPCa). Methods: This is a secondary analysis of data from 52 men enrolled in the usual care control group of a randomized trial that focused on decision-making for newly diagnosed men with LPCa. We analyzed the patient-physician communication using the transcribed audio-recordings of real-time treatment consultations and a researcher-developed coding tool, including codes for communication behaviors (information giving, seeking, and clarifying/ verifying) and contents of clinical consultations (health histories, survival/mortality, treatment options, treatment impact, and treatment preferences). After qualitative content analysis, we categorized patient participation in communication about treatment-related clinical content, including “none” (content not discussed);“low” (patient listening only);“moderate” (patient providing information or asking questions);and “high” (patient providing information and asking questions). Results: Physicians mainly provided information during treatment decision consultations and patients frequently were not active participants in communication. The participation of patients with low and moderate cancer risk typically was: 1) “moderate and high” in discussing health histories;2) “low” in discussing survival/mortality;3) “low and moderate” in discussing treatment options;4) “none and low” in discussing treatment impacts;and 5) “low” in discussing treatment preferences. Conclusions: Findings suggest opportunities for increasing patient participation in communication about treatment decision-making for LPCa during clinical consultations.
文摘This paper contains research on strategic decision-making in a local government. In a profit-oriented organization, the option that maximizes profits tends involve reaching an agreement between stakeholders. However, there is tendency for stakeholders to differ in their beliefs as to what is desirable particularly in a non-profit organization. In a local government, it is especially difficult for the interests of a stakeholder group to be completely in agreement. This research considers the use of the analytical hierarchy process （Saaty, 1971） as a solution for one of the difficulties of decision-making in a local government. This research is a case study to explore the strategy of a local Japanese healthcare management organization. The conclusion was drawn to decide which strategic option should be taken by using the analytical hierarchy process. Also, it was found what to work on a countermeasure that prevents the negative effects that are generated by selecting the strategic option.
文摘Based on the cross-sectional data about the municipal Party committee secretaries sacked since the 18th CPC National Congress, this paper adopts a regression model to examine and assess the impact of local top Party leaders' corruption. The study discovers that local heads' integrity directly affects local political ecology they are in; that regions in the charge of corruptive heads suffer a higher degree of corruption; and that the tenure of corruptive local heads relates much to the degree of local corruption(i.e. the longer their tenure is, the more baneful influence they exert on the clean governance of local leaders and cadres). Consequently, it is imperative to establish and consolidate a power structure and a corresponding operating mechanism which enable effective mutual constraint and balance among decisionmaking power, executive power and supervision power. Only by doing so can China alleviate the negative impact of local heads' corruption, effectively restrict and supervise local heads' exercise of power, and maintain a well balance between "power delegation" and "power supervision".
文摘Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.
