The impact of environmental stimuli on the psychological and behavioral compliance of international construction employees.

Introduction: This study explores the overlooked psychological and behavioral dynamics of employees in compliance management, applying the Stimulus-Organism-Response (SOR) framework to assess environmental stimuli's impact on employees in international construction projects. Methods: A scenario-based survey involving 270 international construction employees was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA), focusing on the relationship between environmental stimuli and compliance intentions. Results: Findings categorize environmental influences on compliance into internal and external organizational dimensions, highlighting the significant impact of internal factors on compliance intentions. Key determinants identified for high compliance intention include individual traits and organizational climate, while project pressures, rules and regulations, and cultural differences show variable influence. Conclusion: This study enhances the understanding of the psychological factors driving non-compliant behaviors and introduces a binary micro-ecological approach to compliance management, effectively integrating individual and project organizational elements. In contrast to traditional corporate governance approaches, this strategy emphasizes the role of project organizational micro-ecology in the management of international construction projects. The strategy aims to improve compliance management among international contractors by influencing the psychological and behavioral compliance of frontline employees.

Efficient multiple change point detection for high-dimensional generalized linear models.

Change point detection for high-dimensional data is an important yet challenging problem for many applications. In this paper, we consider multiple change point detection in the context of high-dimensional generalized linear models, allowing the covariate dimension p to grow exponentially with the sample size n. The model considered is general and flexible in the sense that it covers various specific models as special cases. It can automatically account for the underlying data generation mechanism without specifying any prior knowledge about the number of change points. Based on dynamic programming and binary segmentation techniques, two algorithms are proposed to detect multiple change points, allowing the number of change points to grow with n. To further improve the computational efficiency, a more efficient algorithm designed for the case of a single change point is proposed. We present theoretical properties of our proposed algorithms, including estimation consistency for the number and locations of change points as well as consistency and asymptotic distributions for the underlying regression coefficients. Finally, extensive simulation studies and application to the Alzheimer's Disease Neuroimaging Initiative data further demonstrate the competitive performance of our proposed methods.

Qualitative study of the psychological experience of COVID-19 patients during hospitalization.

BACKGROUND: Coronavirus disease 2019 (COVID-19) continues to spread across the globe, but patient experiences are rarely documented. OBJECTIVE: To explore the psychology of COVID-19 patients during hospitalization. METHODS: A phenomenological and robust sampling approach was employed. Sixteen patients admitted to the First Affiliated Hospital of Henan University of Science and Technology with COVID-19 from 20th January to 1st March 2020 were selected. Data were collected through semi-structured interviews, phone calls, or face-to-face interviews using quarantine measures. Data were analyzed using the Colaizzi method. RESULTS: The psychological experience of COVID-19 patients during hospitalization could be summarized into five themes. Firstly, attitudes toward the disease included fear, denial, and stigma during the early stages, which gradually developed into acceptance in the later stages. Secondly, the major source of stress included the viral nature of the disease, quarantine measures, and concerns regarding the health of family members. Thirdly, reactions of body and mind included disease stage-dependent emotional responses, excessive attention to symptoms, rumination, and changes in diet, sleep, and behavior. Fourthly, supportive factors included psychological adjustments, medical care, and family and social support. Finally, the disease resulted in psychological growth and patients viewed problems with gratitude through the cherishing of life, family, bravery, and tenacity. CONCLUSION: COVID-19 patients gradually changed their attitude toward the disease and displayed emotional responses dependent on the stage of the disease. Negative emotions dominated during the early stages but gradually gave way to mixed positive and negative emotions. Active guidance of psychological growth may therefore promote physical and mental recovery in COVID-19 patients.