Social Network Analysis of Intensive Care Unit Health Care Professionals Measured by Wearable Sociometric Badges: Longitudinal Observational Study

Wearable Systems for Unveiling Collective Intelligence in Clinical Settings

Nowadays, there is an ever-growing interest in assessing the collective intelligence (CI) of a team in a wide range of scenarios, thanks to its potential in enhancing teamwork and group performance. Recently, special attention has been devoted on the clinical setting, where breakdowns in teamwork, leadership, and communication can lead to adverse events, compromising patient safety. So far, researchers have mostly relied on surveys to study human behavior and group dynamics; however, this method is ineffective. In contrast, a promising solution to monitor behavioral and individual features that are reflective of CI is represented by wearable technologies. To date, the field of CI assessment still appears unstructured; therefore, the aim of this narrative review is to provide a detailed overview of the main group and individual parameters that can be monitored to evaluate CI in clinical settings, together with the wearables either already used to assess them or that have the potential to be applied in this scenario. The working principles, advantages, and disadvantages of each device are introduced in order to try to bring order in this field and provide a guide for future CI investigations in medical contexts.

Exploring the organisational structure of networks for exercise oncology provision: a social network analysis of OnkoAktiv

BACKGROUND

Structured exercise programs provide considerable health benefits for cancer patients. Therefore, various OnkoAktiv (OA) networks were established in Germany with the aim to connect cancer patients with certified exercise programs. However, knowledge about the integration of exercise networks into cancer care systems and conditions of interorganisational collaboration is lacking. The aim of this work was to analyse the OA networks to guide further network development and implementation work.

METHODS

We used methods of social network analysis within a cross-sectional study design. Network characteristics were analysed such as node and tie attributes, cohesion and centrality. We classified all networks into their level of organisational form in integrated care.

RESULTS

We analysed 11 OA networks with 26 actors and 216 ties on average. The smallest network counted 12 actors/56 ties, the largest 52/530. 76% of all actors operated within the medical/exercise sector, serving 19 different medical professions. In smaller "linkage" networks, several individual professionals were linked "from service to service", whereas the more integrated networks revealed a core-periphery-structure.

DISCUSSION

Collaborative networks enable the involvement of professional actors from different operational fields. This study provides an in-depth understanding of underlying organisational structures that provides information for further development of exercise oncology provision.

TRIAL REGISTRATION

Not applicable, as no health care intervention was performed.

Network approaches and interventions in healthcare settings: A systematic scoping review

INTRODUCTION

The growing interest in networks of interactions is sustained by the conviction that they can be leveraged to improve the quality and efficiency of healthcare delivery systems. Evidence in support of this conviction, however, is mostly based on descriptive studies. Systematic evaluation of the outcomes of network interventions in healthcare settings is still wanting. Despite the proliferation of studies based on Social Network Analysis (SNA) tools and techniques, we still know little about how intervention programs aimed at altering existing patterns of social interaction among healthcare providers affect the quality of service delivery. We update and extend prior reviews by providing a comprehensive assessment of available evidence.

METHODS AND FINDINGS

We searched eight databases to identify papers using SNA in healthcare settings published between 1st January 2010 and 1st May 2022. We followed Chambers et al.'s (2012) approach, using a Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. We distinguished between studies relying on SNA as part of an intervention program, and studies using SNA for descriptive purposes only. We further distinguished studies recommending a possible SNA-based intervention. We restricted our focus on SNA performed on networks among healthcare professionals (e.g., doctors, nurses, etc.) in any healthcare setting (e.g., hospitals, primary care, etc.). Our final review included 102 papers. The majority of the papers used SNA for descriptive purposes only. Only four studies adopted SNA as an intervention tool, and measured outcome variables.

CONCLUSIONS

We found little evidence for SNA-based intervention programs in healthcare settings. We discuss the reasons and challenges, and identify the main component elements of a network intervention plan. Future research should seek to evaluate the long-term role of SNA in changing practices, policies and behaviors, and provide evidence of how these changes affect patients and the quality of service delivery.

Healthcare Monitoring Using Low-Cost Sensors to Supplement and Replace Human Sensation: Does It Have Potential to Increase Independent Living and Prevent Disease?

Continuous monitoring of health status has the potential to enhance the quality of life and life expectancy of people suffering from chronic illness and of the elderly. However, such systems can only come into widespread use if the cost of manufacturing is low. Advancements in material science and engineering technology have led to a significant decrease in the expense of developing healthcare monitoring devices. This review aims to investigate the progress of the use of low-cost sensors in healthcare monitoring and discusses the challenges faced when accomplishing continuous and real-time monitoring tasks. The major findings include (1) only a small number of publications (N = 50) have addressed the issue of healthcare monitoring applications using low-cost sensors over the past two decades; (2) the top three algorithms used to process sensor data include SA (Statistical Analysis, 30%), SVM (Support Vector Machine, 18%), and KNN (K-Nearest Neighbour, 12%); and (3) wireless communication techniques (Zigbee, Bluetooth, Wi-Fi, and RF) serve as the major data transmission tools (77%) followed by cable connection (13%) and SD card data storage (10%). Due to the small fraction (N = 50) of low-cost sensor-based studies among thousands of published articles about healthcare monitoring, this review not only summarises the progress of related research but calls for researchers to devote more effort to the consideration of cost reduction as well as the size of these components.

Social support and professional networks of nurses and nursing technicians in coping with Covid-19: A sectional study in two Brazilian cities

Among healthcare workers, nurses are at exceptionally considerable risk for contracting COVID-19. Regardless of professionals' level of education, Brazilian nursing is one of the healthcare occupations shouldering the highest levels of responsibility and workload. Social support networks to health and nursing can be a strategy to reduce workload and stress and may contribute to implementing the activities and protecting workers' health. This study aimed to map and analyze social support networks at workplaces as informed by frontline nursing professionals working in healthcare units in the Brazilian cities of Rio de Janeiro and Fortaleza, capitals of the States of Rio de Janeiro and Ceará, respectively. This observational and cross-sectional study used an online data collection instrument based on social network analysis methodology. We recruited 163 participants in two reference services for health professionals suspected or with COVID-19 symptoms. The research question was: "Which category or categories of health professionals have supported you or other colleagues the most in the event of diagnosis or suspicion of COVID-19 among nursing categories? Data were organized by nursing category and city and analyzed through social network analysis using Ucinet©, generating graphs and centrality metrics. Results point to the central relevance of nursing categories in the workplace social support in the pandemic, followed by other health professional categories.

Universal association between depressive symptoms and social-network structures in the workplace

An unhealthy communication structure at a workplace can adversely affect the mental health of employees. However, little is known about the relationship between communication structures in the workplace and the mental health of employees. Here, we evaluated the face-to-face interaction network among employees (N = 449) in a variety of real-world working environments by using wearable devices and investigated the relationship between social network characteristics and depressive symptoms. We found that the cohesive interaction structure surrounding each individual was negatively correlated with depressive symptoms: a universal relationship regardless of occupation type. This correlation was evident at the group scale and was strongly related to active interactions with abundant body movement. Our findings provide a quantitative and collective perspective on taking a systematic approach to workplace depression, and they suggest that the mental health of employees needs to be addressed systematically, not only individually.

Team Building Through Team Video Games: Randomized Controlled Trial

Background

Organizations of all types require the use of teams. Poor team member engagement costs billions of US dollars annually.

Objective

This study aimed to explain how team building can be accomplished with team video gaming based on a team cohesion model enhanced by team flow theory.

Methods

In this controlled experiment, teams were randomly assigned to a team video gaming treatment or a control treatment. Team productivity was measured during both pretreatment and posttreatment team tasks. After the pretest, teams who were involved in the team video gaming treatment competed against other teams by playing the Halo or Rock Band video game for 45 minutes. After the pretest, teams in the control treatment worked alone for 45 minutes. Then, all teams completed the posttest team activity. This same experimental protocol was conducted on 2 different team tasks.

Results

For both tasks, teams in the team video gaming treatment increased their productivity significantly more (F₁=8.760, P=.004) on the posttest task than teams in the control treatment. Our flow-based theoretical model explained team performance improvement more than twice as well (R²=40.6%) than prior related research (R²=18.5%).

Conclusions

The focused immersion caused by team video gaming increased team performance while the enjoyment component of flow decreased team performance on the posttest. Both flow and team cohesion contributed to team performance, with flow contributing more than cohesion. Team video gaming did not increase team cohesion, so team video gaming effects are independent of cohesion. Team video gaming is a valid practical method for developing and improving newly formed teams.

Sociometric wearable devices for studying human behavior in corporate and healthcare workplaces

Wearable sensor technology enables objective data collection of direct human interactions. The authors review sociometric wearable devices (SWD) and their application in healthcare. Human interactions captured by wearable sensors have been shown to correlate with social constructs such as teamwork and productivity in the office. Application of SWD in the field of healthcare requires special considerations: validation studies have shown technological disadvantages in acute medical settings. Application of SWD in healthcare should be considered based on the strengths and weaknesses of the methodology. SWD can also play an important role in investigation of human interaction and epidemic spread. When study designs and methodologies are carefully considered, incorporation of SWD in healthcare research has promising potential for new insights.