Telehealth Nursing Research: Adding to the Evidence-base for Healthcare

This paper reviews recent, nurse-led telehealth research with the goal of describing research findings that provide evidence for practice. Methods: Using an iterative search method, of eight electronic databases, 84 nurse-led research papers were separated into intervention research, systematic reviews and meta-analyses, and descriptive research. The main emphasis was on full text analysis of the intervention research. Results: Fifteen intervention research papers reported findings related to cardiovascular disease, diabetes mellitus, older age, young adults, early adolescents, children with special health care needs, people with a stoma, post-partum mothers and nurses. Also reviewed for useable evidence for practice were 10 systematic reviews, two meta-analyses and two papers that described reviews plus meta-analyses. Resuts: Fifty-five papers with descriptive designs are briefly described. Nurse-led intervention research is increasing knowledge about the use of telehealth technology and applications in care delivery. People with healthcare needs do better with individual attention and increased follow-up. People have a tolerance for technology used with them to advance their quality of life and healing but there is a point at which too much technology is overwhelming. Clinical research is a challenge due to the number of extraneous variables that are difficult to control and that can affect a person’s response to the research intervention. Conclusion: Continuation of nurse-led telehealth intervention research will help to ensure that technology used to support and advance care delivery will be evidence-based

Determinants of Artificial Intelligence Adoption in Disease Diagnosis for Improving Health Sector Services in Tanzania: A Case of Muhimbili National Hospitals

The study was conducted at Muhimbili national Hospitals to assess the use of Artificial Intelligence in Disease Diagnosis for Improving Health Sector Services in Tanzania. Specifically, the study was interested to assess factors affecting AI adoption in public hospital, examine health workers perception on AI adoption in public hospital and find out effectiveness of AI adoption in proper diagnostic of diseases for improving patient health in public hospitals. The study guided by Technology Acceptance Model. It employed quantitative research approach and survey research design. A sample size of 47 respondents was used where questionnaire were used in data collection. The study revealed that artificial intelligence was useful in diseases diagnosis as it provides accurate information pertaining to patient health; it is quicker in diseases diagnosis and quicker in predicting and diagnosis of patient health. The findings also posited that artificial intelligence is effective in monitoring heart attack and asthma in real time, AI is effective in managing health services, AI is also effective in improving diagnostic and patient. The study recommends the government to provide health workers with training regularly on how to use AI in diseases diagnosis

Affective Attitudes Toward Robots at Work : A Population-Wide Four-Wave Survey Study

Robotization of work is progressing fast globally, and the process has accelerated during the COVID-19 pandemic. Utilizing integrated threat theory as a theoretical framework, this study investigated affective attitudes toward introducing robots at work using a four timepoint data (n = 830) from a Finnish working population longitudinal study. We used hybrid multilevel linear regression modelling to study within and between participant effects over time. Participants were more positive toward introducing robots at work during the COVID-19 pandemic than before it. Increased cynicism toward individuals’ own work, robot-use self-efficacy, and prior user experiences with robots predicted positivity toward introducing robots at work over time. Workers with higher perceived professional efficacy were less and those with higher perceived technology-use productivity, robot-use self-efficacy, and prior user experiences with robots were more positive toward introducing robots at work. In addition, the affective attitudes of men, introverts, critical personalities, workers in science and technology fields, and high-income earners were more positive. Robotization of work life is influenced by workers’ psychological well-being factors and perceived as a welcomed change in the social distancing reality of the pandemic.publishedVersionPeer reviewe

General Attitudes Towards Robots Scale (GAToRS): A New Instrument for Social Surveys

Psychometric scales are useful tools in understanding people's attitudes towards different aspects of life. As societies develop and new technologies arise, new validated scales are needed. Robots and artificial intelligences of various kinds are about to occupy just about every niche in human society. Several tools to measure fears and anxieties about robots do exist, but there is a definite lack of tools to measure hopes and expectations for these new technologies. Here, we create and validate a novel multi-dimensional scale which measures people's attitudes towards robots, giving equal weight to positive and negative attitudes. Our scale differentiates (a) comfort and enjoyment around robots, (b) unease and anxiety around robots, (c) rational hopes about robots in general (at societal level) and (d) rational worries about robots in general (at societal level). The scale was developed by extracting items from previous scales, crowdsourcing new items, testing through 3 scale iterations by exploratory factor analysis (Ns 135, 801 and 609) and validated in its final form of the scale by confirmatory factor analysis (N: 477). We hope our scale will be a useful instrument for social scientists who wish to study human-technology relations with a validated scale in efficient and generalizable ways.Peer reviewe

Perceptions of Assistive Robots at Work: An Experimental Approach to Social Influence

In this study, we examined human reactions to other people’s experiences of using assistive robots at work. An online vignette experiment was conducted among respondents from the United States (N = 1059). In the experiment, participants read a written scenario in which another person had started using assistive robots to help with a daily work-related task. The experiment manipulated the closeness of the messenger (familiar versus unfamiliar colleague) and message orientation (positive versus negative). Finding out positive user experiences of a familiar or unfamiliar colleague increased positive attitude toward assistive robots, perceived robot usefulness, and perceived robot use self-efficacy. Furthermore, those who reported higher perceived robot suitability to one’s occupational field and openness to experiences reported more positive attitude toward assistive robots, higher perceived robot usefulness, and perceived robot use self-efficacy. The results suggest that finding out other people’s positive user experiences has a positive effect on perceptions of using assistive robots to help with a daily work-related task. Perceptions of assistive robots at work are also associated with individual and contextual factors such as openness to experiences and perceived robot suitability to one’s occupational field. This is one of the first studies to experimentally investigate the role of social influence in the perceptions of assistive robots at work.Peer reviewe

Use of Live and Robotic Assistance Animals for Psychological and Cognitive Health in Military Populations

This literature review addresses the use of live and robotic animal-assisted therapy for psychological and cognitive health in military populations. More specifically, this literature review aims to address the benefits and limitations of the use of live animal-assisted therapy, complementary and alternative techniques (i.e., Combat and Emotional Stress Control Dogs and social robots) for military personnel, and possible attitudinal barriers regarding active duty and veteran soldiers, while utilizing literature conducted with the civilian population to augment. A systematic review of peer-reviewed quantitative and qualitative publications and book chapters was utilized to accomplish this. Results of the literature review indicated that animal-assisted therapy and the use of complementary and alternative techniques has been found to not only improve psychological and cognitive health of military personnel but can also positively impact the individual’s interpersonal functioning and quality of life. General limitations of the literature review included limited empirical studies, a reliance on qualitative information, small sample sizes, lack of standardization, and lack of detailed demographic information. General clinical implications included the lengthy process to obtain an animal, the cost, adverse effects on the individual, stress to the animal, and proper utilization of the intervention. Recommendations for future research include the completion of more empirical studies for animal-assisted therapy and complementary and alternative techniques with military personnel with a focus on the specific impact the intervention has, exploring the theory regarding the mechanisms of how animal-assisted therapy works, and the creation of a succinct policy for the use of animal-assisted therapy on military instillations

Integrated Green Lean Six Sigma-Industry 4.0 approach to combat COVID-19: from literature review to framework development

Purpose: The Coronavirus (COVID-19) pandemic has led to a surge in demand for healthcare facilities, medicines, vaccines, and other healthcare items. Integrating Green Lean Six Sigma (GLSS) and Industry 4.0 (I4.0) has the potential to meet the modern demand of healthcare units and also leads to improving the quality of inpatient care with better safety, hygiene, and real-time diagnoses. A systematic review has been conducted to determine the tools/techniques, challenges, application areas, and potential benefits for the adoption of an integrated GLSS-I4.0 approach within healthcare facilities from the perspective of COVID management. Further, a conceptual framework of integrated GLSS- I4.0 has been proposed for better COVID management. Methodology: To conduct literature, authors used Preferred reporting items for systematic reviews and meta-analysis (PRISMA) and covers relevant articles from the arrival of COVID-19. Based on the systematic understanding of the different facets of the integrated GLSS- I 4.0 approach and through insights of experts (academicians, and healthcare personnel), a conceptual framework is proposed to combat COVID-19 for better detection, prevention, and cure. Findings: The systematic review presented here provides different avenues to comprehend the different facets of the integrated GLSS-I4.0 approach in different areas of COVID healthcare management. In this study, the proposed framework reveals that IOT (Internet of Things), Big Data, and Artificial Intelligence (AI) are the major constituents of I4.0 technologies that lead to better COVID management. Moreover, integration of I4.0 with GLSS aids during different stages of the COVID management right from diagnosis, manufacture of items, inpatient and outpatient care of the affected person. Implications: This study provides a significant knowledge database to the practitioners by understanding different tools and techniques of integrated approach for better COVID management. Moreover, the proposed framework aids to grab day-to-day information from the affected people and ensures reduced hospital stay with better space utilization and the creation of a healthy environment around the patient. This inclusive implementation of the proposed framework will enhance knowledge-based in medical areas and provides different novel prospects to combat other medical urgencies

Facilitating Caring Behaviors in Technology-Dependent Nursing Practice Through the use of Simulation Training and Confluent Education Strategies

This paper explores the meaning and benefits of nurse caring, describes the impact that technology has on modern nursing practice, and outlines recommendations for the integration of caring and technology to achieve the highest quality nursing care. Supported by Swanson’s (1991) Theory of Caring and Locsin’s (2005) Theory of Technological Competency as Caring in Nursing, instructional strategies that could be employed by a nurse educator to foster and enhance caring behaviors concurrently with technical training are presented. These include the use of simulation, with an emphasis on reflection during debriefing, and confluent education strategies. The goal of these strategies is to assist practicing nurses to identify their own caring behaviors, to recognize opportunities to enhance their caring practice, and to find meaning in the use of technology as an expression of caring for their patients