A comparative vignette study: Evaluating the potential role of a generative AI model in enhancing clinical decision-making in nursing.

AIM: This study explores the potential of a generative artificial intelligence tool (ChatGPT) as clinical support for nurses. Specifically, we aim to assess whether ChatGPT can demonstrate clinical decision-making equivalent to that of expert nurses and novice nursing students. This will be evaluated by comparing ChatGPT responses to clinical scenarios to those of nurses on different levels of experience. DESIGN: This is a cross-sectional study. METHODS: Emergency room registered nurses (i.e. experts; n = 30) and nursing students (i.e. novices; n = 38) were recruited during March-April 2023. Clinical decision-making was measured using three validated clinical scenarios involving an initial assessment and reevaluation. Clinical decision-making aspects assessed were the accuracy of initial assessments, the appropriateness of recommended tests and resource use and the capacity to reevaluate decisions. Performance was also compared by timing response generations and word counts. Expert nurses and novice students completed online questionnaires (via Qualtrics), while ChatGPT responses were obtained from OpenAI. RESULTS: Concerning aspects of clinical decision-making and compared to novices and experts: (1) ChatGPT exhibited indecisiveness in initial assessments; (2) ChatGPT tended to suggest unnecessary diagnostic tests; (3) When new information required re-evaluation, ChatGPT responses demonstrated inaccurate understanding and inappropriate modifications. In terms of performance, the mean number of words utilized in ChatGPT answers was 27-41 times greater than that utilized by both experts and novices; and responses were provided approximately 4 times faster than those of novices and twice faster than expert nurses. ChatGPT responses maintained logical structure and clarity. CONCLUSIONS: A generative AI tool demonstrated indecisiveness and a tendency towards over-triage compared to human clinicians. IMPACT: The study shows that it is important to approach the implementation of ChatGPT as a nurse's digital assistant with caution. More study is needed to optimize the model's training and algorithms to provide accurate healthcare support that aids clinical decision-making. REPORTING METHOD: This study adhered to relevant EQUATOR guidelines for reporting observational studies. PATIENT OR PUBLIC CONTRIBUTION: Patients were not directly involved in the conduct of this study.

Fostering childbirth education on upright positions and mobility during labor in nulliparous women.

BACKGROUND: Upright labor positions and movement during labor have a positive effect on childbirth, yet the predominant labor positions are still horizontal. Therefore, it is important to explore how it is possible to improve childbirth education, particularly its instructional design, to strengthen women's self-efficacy toward the use of upright positions and mobility during labor. The aim of the study was to evaluate the impact of an instructional approach based on a cognitive engagement ICAP (Interactive, Constructive, Active, Passive) framework on the development of knowledge, attitudes, and self-efficacy expectations toward upright positions and mobility during labor. METHODS: A prospective quasi-experimental study was conducted among nulliparous women from the ultra-orthodox Jewish community (n = 74). While the control group (n = 34) participated in routine childbirth education, the intervention group (n = 36) learned with childbirth education that included interactive and constructive cognitive engagement activities. Participants in both groups completed a set of questionnaires regarding knowledge, attitudes, and self-efficacy. RESULTS: The post-test analysis revealed that women in the intervention group compared to the control group gained significantly higher knowledge scores (p < 0.05), more positive attitudes (p < 0.001), and stronger self-efficacy expectations toward upright positions and mobility during labor (p < 0.01). CONCLUSIONS: The findings suggest that by fostering women's cognitive engagement levels during childbirth education toward the interactive and constructive modes of the ICAP framework, women's self-efficacy to move during labor and to use upright positions can be induced. These results can serve as a foundation to improve the overall effectiveness of childbirth instruction. TRIAL REGISTRATION: The study was registered retrospectively.

Differences in mental health and health-related quality of life between the Israeli and Italian population during a COVID-19 quarantine.

PURPOSE: Severe restrictions related to COVID-19 were implemented almost simultaneously in Italy and Israel in early March 2020, although the epidemic situation in both countries was significantly different. Therefore, the purpose of this study was to examine how and to what extent the severe restrictions affected the mental health and health-related quality of life of non-infected people, in a comparison between Israel and Italy. METHODS: A cross-sectional study was conducted during the first week of May 2020 among 510 Israeli and 505 Italian participants. Anxiety and depression levels were measured using the Patient Health Questionnaire-4 (PHQ-4), and the short form-8 health survey (SF-8) questionnaire measured health-related quality of life. Linear hierarchic regression forced steps analysis was performed to measure the unique contribution of each variable to predicting health-related quality of life. RESULTS: After adjusting for socioeconomic variables, the results showed a significantly higher anxiety level and lower health-related quality of life in the Italian participants. The anxiety and depression variables predicted lower health-related quality of life. Physical activity was found to be a protective factor. CONCLUSION: The results suggest that early monitoring of anxiety and depression in situations such as quarantine may detect the risk for decline in health-related quality of life. Establishment of professional interventions is needed in order to prevent the negative health consequences of the pandemic-related policy.

Glycemic control in adolescents with type 1 diabetes: Are computerized simulations effective learning tools?

OBJECTIVE: Type 1 diabetes mellitus (T1DM) in adolescent patients is often characterized by poor glycemic control. This study aimed at exploring the contribution of learning with computerized simulations to support: (a) mechanistic understanding of the biochemical processes related to diabetes; (b) diabetes self-management knowledge; and (c) glycemic control. We hypothesized that learning with such simulations might support adolescents in gaining a better understanding of the biochemical processes related to glucose regulation, and consequently improve their glycemic control. METHODS: A prospective case-control study was conducted in 12- to 18-year-old adolescents with T1DM (n = 85) who were routinely treated at an outpatient diabetes clinic. While the control group (n = 45) received the routine face-to-face follow-up, the intervention group (n = 40) learned in addition with computerized simulations that were embedded in pedagogically supportive activities. Participants in both groups completed a set of questionnaires regarding sociodemographic characteristics, diabetes mechanistic reasoning and diabetes self-management. Clinical data and serum glycated hemoglobin (HbA1c) levels were gathered from medical records. All the data was collected at recruitment and 3 months later. RESULTS: Analysis revealed improvement HbA1c levels in the intervention group (8.7% ± 1.7%) vs the controls (9.6% ± 1.6%) after 3 months (P < .05). Regression analysis showed that levels of diabetes mechanistic understanding and diabetes self-management knowledge, in addition to sociodemographic parameters, accounted for 31% of the HbA1c variance (P < .001). CONCLUSION: These results suggest that learning with computerized simulations about biochemical processes can improve adolescents' adherence to medical recommendations and result in improved glycemic control. Implementing scientific learning into the hospital educational setting is discussed.

Knowledge and information credibility evaluation strategies regarding COVID-19: A cross-sectional study.

BACKGROUND: The novel coronavirus disease (COVID-19) pandemic has not only caused significant challenges for health systems worldwide, but also fueled a surge in misinformation. Nurses as frontline health care providers should be equipped with the most accurate information on COVID-19. PURPOSE: This study examines nurses' knowledge and strategies of information credibility sourcing. METHOD: A cross-sectional survey among nurses and laypersons with no health care background. The questionnaire dealt with knowledge and ability assess credibility of COVID-19 information. FINDINGS: Nurses' knowledge of COVID-19 preventative behaviors was significantly higher than that of laypersons; however, there was no difference in science-based knowledge of COVID-19. In contrast to laypersons, nurses in this study were better able to discern the credibility of health-related information about COVID-19 than laypersons. Yet they rarely used scientific criteria in evaluating conflicting information. DISCUSSION: Given the importance of assessing the credibility of information, both information literacy skills and science-based knowledge about COVID-19 should be offered.

Adherence to diabetes care: Knowledge of biochemical processes has a high impact on glycaemic control among adolescents with type 1 diabetes.

AIM: To evaluate the impact of patients' understanding of biochemical processes involved in glucose regulation (causal-biochemical knowledge) and of diabetes self-management knowledge on adherence to treatment recommendations among adolescents with type 1 diabetes mellitus. DESIGN: A cross-sectional study. METHODS: Adolescents with type 1 diabetes mellitus, aged 12-18 years and able to read and write in Hebrew or in Arabic were eligible. Participants were recruited between August 2016 - January 2018 during routine visits to the Paediatric Diabetes Clinic; informed consent was obtained as customary. Patients completed sociodemographic, clinical and type 1 diabetes mellitus self-management and biochemical knowledge questionnaires. Adherence to treatment was assessed by patients' serum HbA1c levels, collected from medical records. RESULTS: Ninety-seven patients participated in the study. Mean HbA1c levels were 9.2% (1.9%) and only 24 (24.7%) patients met the recommended HbA1c ≤ 7.5%. Lower HbA1c levels were strongly associated with higher family income, older age at diagnosis and with better type 1 diabetes mellitus self-management and causal-biochemical knowledge. A regression model showed that causal-biochemical knowledge contributed to the variance in HbA1c levels. Furthermore, causal-biochemical knowledge, but not self-management knowledge, was found to mediate the negative relationship between low family income and high HbA1c levels. CONCLUSIONS: Causal-biochemical knowledge is a valuable component for the adherence to diabetes care and glycaemic control. IMPACT: Our study suggests that causal knowledge is a valuable component that should be included in nursing and healthcare educational programmes for adolescents with type 1 diabetes mellitus.

Playing the Role of a Nurse in a Virtual Reality Simulation: A Safe Environment for Emotion Management.

BACKGROUND: Nurses' successful emotional coping with unpleasant emotions triggered by intense clinical situations is associated with better-quality patient care. Nursing students experience significant challenges with managing their emotions in clinical practice. PURPOSE: To evaluate a virtual reality (VR)-based simulation as a platform for emotional management training. METHODS: A pretest-posttest research design was used to study sophomore nursing students (n = 75) while learning with a VR simulation. RESULTS: Playing the role of a nurse in a VR hospital triggered an emotional dissonance to uncover students' management strategies, specifically deep cognitive acting and surface acting strategies. Surface acting emphasizes emotions that are displayed but not genuinely experienced and was negatively associated with posttest knowledge scores (r =-0.34, P < .05). CONCLUSION: Learning with VR can provide a safe environment both for acquiring knowledge and for revealing students' emotional management, which, in turn, can be leveraged by educators to redirect the emotion work required in the nursing profession.

The Role of Science-Based Knowledge on the SARS-CoV-2 Virus in Reducing COVID-19-Induced Anxiety among Nurses.

The COVID-19 infection has generated not only a risk of morbidity and mortality but also resulted in an enormous psychological impact on healthcare providers and the general public. This study aimed to evaluate the prevalence of anxiety and identify the role of protective factors. A two-part cross-sectional study was conducted, by means of an online questionnaire. Part 1 investigated 562 registered nurses, nursing students, and the general public. Participants were assessed for anxiety symptoms with the State-Trait-Anxiety Inventory. A one-way ANCOVA analysis revealed that nurses had the highest level of anxiety compared to the general public and students, with 26% of them reporting severe anxiety. To identify how anxiety can be mitigated, the Part 2 study was focused on registered nurses from Part 1. Multiple regression revealed that a higher level of science-based knowledge of COVID-19 and professional experience were associated with a lower level of anxiety among nurses. The findings suggest that nurses are a vulnerable population prone to anxiety symptoms resulting from the COVID-19 pandemic. Having a deeper science-based understanding of COVID-19 may protect nurses from anxiety. This study underlines the importance of deep evidence-based knowledge for health providers, which may be generalized to a possible future emergency disaster.

Interactions between emotional and cognitive engagement with science on YouTube.

This study aimed to map and characterize public engagement with science on YouTube. A two-part study was conducted. First, we collected and quantitatively analyzed trending videos on YouTube to evaluate the magnitude of public interaction with science content. Then, we assessed actual, rather than self-reports of, media interactions with science-related YouTube trending videos. We tested associations between behavioral engagement of viewing, liking, disliking or commenting, and emotional and cognitive engagement. Our findings affirm that science content attracts high public interest and that emotional and cognitive engagement with science on social media are distinct, but interrelated. We show that regardless of the valence of emotional engagement, emotion is linked to greater behavioral engagement of posting comments and to greater cognitive engagement of argumentative deliberation. Therefore, our findings suggest that social media interactions, which tend to evoke emotional responses, are a promising means of advancing person-to-person engagement with science.

Designing for online computer-based clinical simulations: Evaluation of instructional approaches.

BACKGROUND: Online computer-based simulations are becoming more widespread in nursing education. Therefore, an understanding of when and how to implement the variety of instructional strategies related to these simulations is fundamental. OBJECTIVES: This study compares the effectiveness of online computer-based simulations designed using two alternative instructional approaches-Productive Failure and Simple-to-Complex sequencing-on learning of clinical reasoning skills. PARTICIPANTS: Participants in this study were undergraduate nursing students (n = 103, mean age = 23.4 ±â€¯2.1) enrolled at a university in Israel. METHODS: Participants completed two online simulations designed using Productive Failure approach (emergency medicine, mental health) and two online simulations using Simple-to-Complex approach (cardiovascular health, pediatrics). Pre- and post-test clinical reasoning evaluations were administered prior to and immediately following each simulation. RESULTS: Clinical reasoning learning gains were significantly higher for online simulations designed with the Simple-to-Complex approach than simulations designed with Productive Failure approach (F (3, 288) = 9.656, P < 0.001). Students devoted significantly more time (F (1, 102) = 260.15, P < 0.001) and more attempts (F (1, 102) = 167.39, P < 0.001) in learning with Simple-to-Complex simulations than they did with Productive Failure simulations. The amount of time that students were engaged in learning with simulations was significantly associated with learning gains scores. CONCLUSIONS: This study proposes that well-designed online simulations can improve nursing students' clinical reasoning. The Simple-to-Complex approach was found to be more efficient than Productive Failure for online learning. Learning with Simple-to-Complex approach was behaviorally more engaging and students' achievements were higher, which implies that instructional process facilitates learning, and therefore have to be taken in consideration by nurse educators. Integration of computerized educational modalities within nursing education is discussed.

Nursing students learning the pharmacology of diabetes mellitus with complexity-based computerized models: A quasi-experimental study.

BACKGROUND: Pharmacology is a crucial component of medications administration in nursing, yet nursing students generally find it difficult and self-rate their pharmacology skills as low. OBJECTIVES: To evaluate nursing students learning pharmacology with the Pharmacology Inter-Leaved Learning-Cells environment, a novel approach to modeling biochemical interactions using a multiscale, computer-based model with a complexity perspective based on a small set of entities and simple rules. This environment represents molecules, organelles and cells to enhance the understanding of cellular processes, and combines these cells at a higher scale to obtain whole-body interactions. PARTICIPANTS: Sophomore nursing students who learned the pharmacology of diabetes mellitus with the Pharmacology Inter-Leaved Learning-Cells environment (experimental group; n=94) or via a lecture-based curriculum (comparison group; n=54). METHODS: A quasi-experimental pre- and post-test design was conducted. The Pharmacology-Diabetes-Mellitus questionnaire and the course's final exam were used to evaluate students' knowledge of the pharmacology of diabetes mellitus. RESULTS: Conceptual learning was significantly higher for the experimental than for the comparison group for the course final exam scores (unpaired t=-3.8, p<0.001) and for the Pharmacology-Diabetes-Mellitus questionnaire (U=942, p<0.001). The largest effect size for the Pharmacology-Diabetes-Mellitus questionnaire was for the medication action subscale. Analysis of complex-systems component reasoning revealed a significant difference for micro-macro transitions between the levels (F(1, 82)=6.9, p<0.05). CONCLUSIONS: Learning with complexity-based computerized models is highly effective and enhances the understanding of moving between micro and macro levels of the biochemical phenomena, this is then related to better understanding of medication actions. Moreover, the Pharmacology Inter-Leaved Learning-Cells approach provides a more general reasoning scheme for biochemical processes, which enhances pharmacology learning beyond the specific topic learned. The present study implies that deeper understanding of pharmacology will support nursing students' clinical decisions and empower their proficiency in medications administration.