Mia Björk, Annika Eklund, Maria Skyvell Nilsson and Viola Nyman
The aim of this study was to identify and describe the collaborative and professional boundary challenges at a hospital ward from a bottom-up perspective.
Abstract
Purpose
The aim of this study was to identify and describe the collaborative and professional boundary challenges at a hospital ward from a bottom-up perspective.
Design/methodology/approach
The study was conducted as a bottom-up improvement project at a hospital ward in western Sweden. An insider action research (IAR) approach was used during the project. The theoretical framework for this project was based on the Cultural-Historical Activity Theory (CHAT). Data were collected between 2019 and 2021.
Findings
The findings showed that unclear professional boundaries and limited resources challenged and hindered interprofessional collaboration. The project group had to reorganize its daily work to adjust to the different disciplines’ legal responsibilities in relation to the patients’ recovery process. To safely discharge patients, the professionals needed to talk about each other’s professional responsibilities, professional boundaries and ethical codes.
Originality/value
The IAR project revealed that revising the daily team-round routine improved the status of assistant nurses and encouraged physicians to consider input from all professions during the patients’ recovery process. However, the new approach faced resistance from clinic leadership, who believed it could prolong patients’ stays in the ward. The findings underscore the challenges of modifying hierarchical structures and social orders within hospital settings.
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Keywords
Xiaohang (Flora) Feng, Shunyuan Zhang and Kannan Srinivasan
The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured…
Abstract
The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility – if only the model outputs are interpretable enough to earn the trust of consumers and buy-in from companies. To build a foundation for understanding the importance of model interpretation in image analytics, the first section of this article reviews the existing work along three dimensions: the data type (image data vs. video data), model structure (feature-level vs. pixel-level), and primary application (to increase company profits vs. to maximize consumer utility). The second section discusses how the “black box” of pixel-level models leads to legal and ethical problems, but interpretability can be improved with eXplainable Artificial Intelligence (XAI) methods. We classify and review XAI methods based on transparency, the scope of interpretability (global vs. local), and model specificity (model-specific vs. model-agnostic); in marketing research, transparent, local, and model-agnostic methods are most common. The third section proposes three promising future research directions related to model interpretability: the economic value of augmented reality in 3D product tracking and visualization, field experiments to compare human judgments with the outputs of machine vision systems, and XAI methods to test strategies for mitigating algorithmic bias.
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Rose Onyeali, Benjamin A. Howell, D. Keith McInnes, Amanda Emerson and Monica E. Williams
Older adults who are or have been incarcerated constitute a growing population in the USA. The complex health needs of this group are often inadequately addressed during…
Abstract
Purpose
Older adults who are or have been incarcerated constitute a growing population in the USA. The complex health needs of this group are often inadequately addressed during incarceration and equally so when transitioning back to the community. The purpose of this paper is to discuss the literature on challenges older adults (age 50 and over) face in maintaining health and accessing social services to support health after an incarceration and to outline recommendations to address the most urgent of these needs.
Design/methodology/approach
This study conducted a narrative literature review to identify the complex health conditions and health services needs of incarcerated older adults in the USA and outline three primary barriers they face in accessing health care and social services during reentry.
Findings
Challenges to healthy reentry of older adults include continuity of health care; housing availability; and access to health insurance, disability and other support. The authors recommend policy changes to improve uniformity of care, development of support networks and increased funding to ensure that older adults reentering communities have access to resources necessary to safeguard their health and safety.
Originality/value
This review presents a broad perspective of the current literature on barriers to healthy reentry for older adults in the USA and offers valuable system, program and policy recommendations to address those barriers.