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Phubbing is a behaviour that can be defined as the act of ignoring interlocutors in a social interaction while using a mobile phone (Chotpitayasunondh & Douglas, 2016). This paper provides a thorough examination of the existing literature, specifically addressing the antecedents and outcomes of phubbing behavior. The current study seeks to provide a comprehensive understanding of the literature review in relation to phubbing behaviour, specifically in the workplace. A thorough examination was carried out on 63 articles from the SSCI database, encompassing the years 2013 to 2024. The results of the comprehensive literature review suggest that there are two different dimensions of a phubbing behavior along with the two categories i.e., antecedents and outcomes. This paper, which draws on a review of research spanning a decade, adds to our knowledge of phubbing behavior in the workplace and stresses the need to address this issue for the sake of interpersonal relationship along with organizational effectiveness and employee performance. [ABSTRACT FROM AUTHOR]

The present study investigates the impact of autocratic and despotic leadership styles on employees' deviant behavior, with the moderating effect of perceived organizational justice. In the realm of research, there exists significant concern regarding the influence of despotic and autocratic leadership styles on employees' deviant behavior, particularly within serviceoriented industries such as banking and educational institutions. Therefore, this study helps to understand how these leadership styles may affect deviant behavior among employees. This study used a quantitative survey-based research methodology, Data was collected from 356 employees of different banks and universities in Rawalpindi, Islamabad, and Lahore. The findings show a positive and significant effects of autocratic and despotic leadership styles on employees' deviant behavior. Results also indicate that the relationship between autocratic leadership and employees' deviant behavior is moderated by perceived organizational justice. Future researchers should explore different industries, use multisource data, and different mediators in the relationship between negative leadership styles and deviant behavior for a diversified sample size. [ABSTRACT FROM AUTHOR]

Background: Electronic standard order sets automate the ordering of specific treatment, testing, and investigative protocols by physicians. These tools may help reduce unwarranted clinical variation and improve health care efficiency. Despite their routine implementation within electronic medical records (EMRs), little is understood about how they are used and what factors influence their adoption in practice., Objective: This study aims to (1) describe the patterns of use of standard order sets implemented in a widely used EMR (PowerPlans and Cerner Millennium) within a multihospital digital health care system; (2) explore the experiences and perceptions of implementers and users regarding the factors contributing to the use of these standard order sets; and (3) map these findings to the Capability, Opportunity, and Motivation Behavior (COM-B) model of behavior change to assist those planning to develop, improve, implement, and iterate the use of standard order sets in hospital settings., Methods: Quantitative data on standard order set usage were captured from 5 hospitals over 5-month intervals for 3 years (2019, 2020, and 2021). Qualitative data, comprising unstructured and semistructured interviews (n=15), were collected and analyzed using a reflexive thematic approach. Interview themes were then mapped to a theory-informed model of behavior change (COM-B) to identify determinants of standard order set usage in routine clinical practice. The COM-B model is an evidence-based, multicomponent framework that posits that human actions result from multiple contextual influences, which can be categorized across 3 dimensions: capability, opportunity, and motivation, all of which intersect., Results: The total count of standard order set usage across the health system during the 2019 observation period was 267,253, increasing to 293,950 in 2020 and 335,066 in 2021. There was a notable shift toward using specialty order sets that received upgrades during the study period. Four emergent themes related to order set use were derived from clinician interviews: (1) Knowledge and Skills; (2) Perceptions; (3) Technical Dependencies; and (4) Unintended Consequences, all of which were mapped to the COM-B model. Findings indicate a user preference for customized order sets that respond to local context and user experience., Conclusions: The study findings suggest that ongoing investment in the development and functionality of specialty order sets has the potential to enhance usage as these sets continue to be customized in response to local context and user experience. Sustained and continuous uptake of appropriate Computerized Provider Order Entry use may require implementation strategies that address the capability, opportunity, and motivational influencers of behavior., (©Sundresan Naicker, Amina Tariq, Raelene Donovan, Honor Magon, Nicole White, Joshua Simmons, Steven M McPhail. Originally published in JMIR Formative Research (https://formative.jmir.org), 08.11.2024.)

Background: Computerized clinical decision support systems (CDSSs) enhance patient care through real-time, evidence-based guidance for health care professionals. Despite this, the effective implementation of these systems for health services presents multifaceted challenges, leading to inappropriate use and abandonment over the course of time. Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework, this qualitative study examined CDSS adoption in a metropolitan health service, identifying determinants across implementation stages to optimize CDSS integration into health care practice., Objective: This study aims to identify the theory-informed (NASSS) determinants, which included multiple CDSS interventions across a 2-year period, both at the health-service level and at the individual hospital setting, that either facilitate or hinder the application of CDSSs within a metropolitan health service. In addition, this study aimed to map these determinants onto specific stages of the implementation process, thereby developing a system-level understanding of CDSS application across implementation stages., Methods: Participants involved in various stages of the implementation process were recruited (N=30). Participants took part in interviews and focus groups. We used a hybrid inductive-deductive qualitative content analysis and a framework mapping approach to categorize findings into barriers, enablers, or neutral determinants aligned to NASSS framework domains. These determinants were also mapped to implementation stages using the Active Implementation Framework stages approach., Results: Participants comprised clinical adopters (14/30, 47%), organizational champions (5/30, 16%), and those with roles in organizational clinical informatics (5/30, 16%). Most determinants were mapped to the organization level, technology, and adopter subdomains. However, the study findings also demonstrated a relative lack of long-term implementation planning. Consequently, determinants were not uniformly distributed across the stages of implementation, with 61.1% (77/126) identified in the exploration stage, 30.9% (39/126) in the full implementation stage, and 4.7% (6/126) in the installation stages. Stakeholders engaged in more preimplementation and full-scale implementation activities, with fewer cycles of monitoring and iteration activities identified., Conclusions: These findings addressed a substantial knowledge gap in the literature using systems thinking principles to identify the interdependent dynamics of CDSS implementation. A lack of sustained implementation strategies (ie, training and longer-term, adopter-level championing) weakened the sociotechnical network between developers and adopters, leading to communication barriers. More rigorous implementation planning, encompassing all 4 implementation stages, may, in a way, help in addressing the barriers identified and enhancing enablers., (©Manasha Fernando, Bridget Abell, Steven M McPhail, Zephanie Tyack, Amina Tariq, Sundresan Naicker. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 17.10.2024.)

Clinical decision support systems (CDSS) can enhance the safety and quality of patient care, but their benefits are often hampered by low acceptance and use by clinicians in practice. Existing research has explored clinicians' experiences with CDSS in a static nature, with limited consideration of how user needs may change over time. This review aimed to identify the methods used to capture clinicians' acceptance and use of CDSS in hospital settings at different time points following implementation and highlight gaps to inform future work. Seventy-six studies met inclusion criteria. Qualitative methods were rarely used during the early implementation phases, particularly in the first 2 months following implementation. Further work is needed to understand clinicians' experiences immediately following implementation of CDSS and how these insights can be used to support use over time.