ABSTRACT
Previous studies have revealed various factors related to nurses' resilience and predictors of resilience. However, there are no studies analysing the association of three variables-mental well-being, coping strategies, and stress-with resilience. This study aims to assess the impact of mental well-being, levels of stress, and coping strategies on resilience using path analysis. This study used a cross-sectional approach that involved 763 nurses from 16 major hospitals in the eastern and northern regions of Saudi Arabia during the COVID-19 pandemic. The data gathering was conducted from August to November 2022. The staff nurses possessed positive mental wellness (3.75 ± 1.08), moderate stress levels (3.06 ± 1.21), adequate coping skills (3.33 ± 1.23), and a low level of resilience (2.90 ± 1.040). Age had a small effect on resilience (ß = 0.040; p < 0.001) but work experience (ß = -0.019; p > 0.139) and marital status (ß = 0.019; p > 0.072) were not significant. Conversely, mental well-being (ß = 0.043; p < 0.001) and stress (ß = -0.089; p < 0.001) had a small effect on resilience, but coping strategies (ß = 0.561; p < 0.001) had a large effect on resilience. Therefore, coping strategies must be reinforced at all times to assist nurses and other healthcare professionals in identifying contributing elements that maintain these workers' resilience in the face of unforeseen and protracted pandemics and other life events.
ABSTRACT
Telenursing is one type of telehealth service delivery proposed to resolve the predicted gap between healthcare workforce demand and supply globally. The aim of this article is to explore the 'Nurse Chatbot' for chronic care on the benefits of increasing patient/client access to healthcare information and maximizing the potential of artificial intelligence/AI to bridge the 'demand-supply gap' of human healthcare providers. Moreover,closing this gap through the establishment of a 'Nurse Chatbot' will be innovative, favorably scalable and customizable within a decentralized health network, and potentially sustainable in the new digital economy. Following are the assumptions : 1) "caring" communicated textually is highly 'transactive' in chronic disease selfmanagement support/CDSMS for goal agreements between agents and for overcoming the system noise in the form of cross-entropy, perplexity, and information wastage ; 2) 'Nurse Chatbot' is the interlocutor in nursing care and the nursing agency by superpositioning and entanglement ; and 3) possible effects of chatbot-user transactions are information flows, management of health, and patient satisfaction. This article also looks into 'Nurse Chatbot' development for CDSMS, simulation of its diffusion capacity egocentrically, technology acceptance model/TAM to inquire the engagement of users, and possible approaches to ethical and safety issues. J. Med. Invest. 66 : 24-30, February, 2019.
