Time to Incorporate Artificial Intelligence into High-Fidelity Patient Simulators for Nursing Education: A Secondary Analysis of a Pilot Study

2021 ◽  
pp. 227-236
Author(s):  
Angelo Dante ◽  
Carmen La Cerra ◽  
Luca Bertocchi ◽  
Vittorio Masotta ◽  
Alessia Marcotullio ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Nursing Education ◽  
Pilot Study ◽  
Secondary Analysis ◽  
High Fidelity ◽  
Patient Simulators

71. Are video interviews a good alternative to in person interviews in assessing international applicants' skills?

2007 ◽  
Vol 30 (4) ◽  
pp. 67
Author(s):  
M. Alameddine ◽  
K. Imrie ◽  
S. Akers ◽  
S. Verma
Keyword(s):  
Nursing Education ◽  
Pilot Study ◽  
Psychological Treatment ◽  
Cost Savings ◽  
Good Alternative ◽  
Average Score ◽  
Global Rating ◽  
Problem Solving Skills ◽  
Global Satisfaction ◽  
Personal Connection

We developed and administered two questionnaires to assess the interview experience of both interviewers and applicants during postgraduate medical selection interviews. Using a 5 point likert scale, the questionnaires assessed three areas (1) ability to show/assess communication, interpersonal and problem solving skills; (2) ability to know the other side well and (3) level of comfort with the interview. Interviewers and applicants were asked to provide a global rating for the interview. The questionnaires were administered to both candidates and applicants from 6 departments in 18 in-person and 12 video interviews. 30 applicant and 87 interviewer survey forms were collected and analyzed. T-tests were used to compare the means of the two groups and significance levels were analyzed. Both interviewers and applicants had a higher average global satisfaction for video interviews compared to in person interviews. No difference was indicated in the ability of interviewers to assess the applicants’ skills between the two types of interviews. For both interviewers and applicants, video interviews, compared to in person interview, had a lower average score for connecting personally & establishing rapport and for satisfaction with administrative arrangements. Video interviewed applicants had a 50% probability of getting accepted in a program compared to 22% of in person interviewed candidates. We conclude that video interviews appear to be a valuable alternative to in-person interviews, with some sacrifice in personal connection and rapport. Video interviews result in significant time and cost savings for international applicants and have potential implications for the CaRMS process as well. Sackett KM, Campbell-Heider N, Blyth JB. The evolution and evaluation of videoconferencing technology for graduate nursing education. Comput Inform Nurs. 2004 (Mar-Apr); 22(2):101-6. Shepherd L, Goldstein D, Whitford H, Thewes B, Brummell V, Hicks M. The utility of videoconferencing to provide innovative delivery of psychological treatment for rural cancer patients: results of a pilot study. J Pain Symptom Manage 2006 (Nov); 32(5):453-61. Arena J, Dennis N, Devineni T, Maclean R, Meador K. A pilot study of feasibility and efficacy of telemedicine-delivered psychophysiological treatment for vascular headache. Telemed J E Health 2004 (Winter); 10(4):449-54.

The Perceptions of Nurse Educators regarding the use of High Fidelity Simulation in Nursing Education

2018 ◽  
Vol 20 (1) ◽  
Author(s):  
Viola Janse van Vuuren ◽  
Eunice Seekoe ◽  
Daniel Ter Goon
Keyword(s):  
Nursing Education ◽  
South African ◽  
Clinical Training ◽  
Nurse Educators ◽  
Teaching Staff ◽  
High Fidelity ◽  
High Fidelity Simulation ◽  
Simulation Based ◽  
Nursing College ◽  
Faculty Shortages

Although nurse educators are aware of the advantages of simulation-based training, some still feel uncomfortable to use technology or lack the motivation to learn how to use the technology. The aging population of nurse educators causes frustration and anxiety. They struggle with how to include these tools particularly in the light of faculty shortages. Nursing education programmes are increasingly adopting simulation in both undergraduate and graduate curricula. The aim of this study was to determine the perceptions of nurse educators regarding the use of high fidelity simulation (HFS) in nursing education at a South African private nursing college. A national survey of nurse educators and clinical training specialists was completed with 118 participants; however, only 79 completed the survey. The findings indicate that everyone is at the same level as far as technology readiness is concerned, however, it does not play a significant role in the use of HFS. These findings support the educators’ need for training to adequately prepare them to use simulation equipment. There is a need for further research to determine what other factors play a role in the use of HFS; and if the benefits of HFS are superior to other teaching strategies warranting the time and financial commitment. The findings of this study can be used as guidelines for other institutions to prepare their teaching staff in the use of HFS.

Endoscopic prediction of submucosal invasion in Barrett’s cancer with the use of Artificial Intelligence: A pilot Study

Endoscopy ◽  
2020 ◽  
Author(s):  
Alanna Ebigbo ◽  
Robert Mendel ◽  
Tobias Rückert ◽  
Laurin Schuster ◽  
Andreas Probst ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Pilot Study ◽  
White Light ◽  
Submucosal Invasion ◽  
Learning System ◽  
Endoscopic Images ◽  
Barrett’S Cancer ◽  
Significant Difference ◽  
Sensitivity Specificity

Background and aims: The accurate differentiation between T1a and T1b Barrett’s cancer has both therapeutic and prognostic implications but is challenging even for experienced physicians. We trained an Artificial Intelligence (AI) system on the basis of deep artificial neural networks (deep learning) to differentiate between T1a and T1b Barrett’s cancer white-light images. Methods: Endoscopic images from three tertiary care centres in Germany were collected retrospectively. A deep learning system was trained and tested using the principles of cross-validation. A total of 230 white-light endoscopic images (108 T1a and 122 T1b) was evaluated with the AI-system. For comparison, the images were also classified by experts specialized in endoscopic diagnosis and treatment of Barrett’s cancer. Results: The sensitivity, specificity, F1 and accuracy of the AI-system in the differentiation between T1a and T1b cancer lesions was 0.77, 0.64, 0.73 and 0.71, respectively. There was no statistically significant difference between the performance of the AI-system and that of human experts with sensitivity, specificity, F1 and accuracy of 0.63, 0.78, 0.67 and 0.70 respectively. Conclusion: This pilot study demonstrates the first multicenter application of an AI-based system in the prediction of submucosal invasion in endoscopic images of Barrett’s cancer. AI scored equal to international experts in the field, but more work is necessary to improve the system and apply it to video sequences and in a real-life setting. Nevertheless, the correct prediction of submucosal invasion in Barret´s cancer remains challenging for both experts and AI.

Do paramedic students have situational awareness during high-fidelity simulation? A mixed-methods pilot study

2021 ◽  
Vol 56 ◽  
pp. 100983
Author(s):  
Justin Hunter ◽  
Michael Porter ◽  
Andy Phillips ◽  
Melissa Evans-Brave ◽  
Brett Williams
Keyword(s):  
Mixed Methods ◽  
Pilot Study ◽  
Situational Awareness ◽  
High Fidelity ◽  
High Fidelity Simulation

Automated Large Artery Occlusion Detection in Stroke: A Single-Center Validation Study of an Artificial Intelligence Algorithm

2021 ◽  
pp. 1-6
Author(s):  
Gabriel Rodrigues ◽  
Clara M. Barreira ◽  
Mehdi Bouslama ◽  
Diogo C. Haussen ◽  
Alhamza Al-Bayati ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Secondary Analysis ◽  
Large Artery ◽  
Single Center ◽  
Characteristic Analysis ◽  
Cohen’S Kappa ◽  
Accurate Identification ◽  
Vessel Occlusion ◽  
Test Characteristic ◽  
Cohen's Kappa

<b><i>Introduction:</i></b> Expediting notification of lesions in acute ischemic stroke (AIS) is critical. Limited availability of experts to assess such lesions and delays in large vessel occlusion (LVO) recognition can negatively affect outcomes. Artificial intelligence (AI) may aid LVO recognition and treatment. This study aims to evaluate the performance of an AI-based algorithm for LVO detection in AIS. <b><i>Methods:</i></b> Retrospective analysis of a database of AIS patients admitted in a single center between 2014 and 2019. Vascular neurologists graded computed tomography angiographies (CTAs) for presence and site of LVO. Studies were analyzed by the Viz-LVO Algorithm® version 1.4 – neural network programmed to detect occlusions from the internal carotid artery terminus (ICA-T) to the Sylvian fissure. Comparisons between human versus AI-based readings were done by test characteristic analysis and Cohen’s kappa. Primary analysis included ICA-T and/or middle cerebral artery (MCA)-M1 LVOs versus non-LVOs/more distal occlusions. Secondary analysis included MCA-M2 occlusions. <b><i>Results:</i></b> 610 CTAs were analyzed. The AI algorithm rejected 2.5% of the CTAs due to poor quality, which were excluded from the analysis. Viz-LVO identified ICA-T and MCA-M1 LVOs with a sensitivity of 87.6%, specificity of 88.5%, and accuracy of 87.9% (AUC 0.88, 95% CI: 0.85–0.92, <i>p</i> &#x3c; 0.001). Cohen’s kappa was 0.74. In the secondary analysis, the algorithm yielded a sensitivity of 80.3%, specificity of 88.5%, and accuracy of 82.7%. The mean run time of the algorithm was 2.78 ± 0.5 min. <b><i>Conclusion:</i></b> Automated AI reading allows for fast and accurate identification of LVO strokes with timely notification to emergency teams, enabling quick decision-making for reperfusion therapies or transfer to specialized centers if needed.

Identifying an Effect of Simulation Role Assignment on Critical Thinking Development in Baccalaureate Nursing Students

2016 ◽  
Vol 60 (1) ◽  
pp. 1818-1822 ◽  
Author(s):  
Dustin T. Weiler ◽  
Jason J. Saleem
Keyword(s):  
Critical Thinking ◽  
Nursing Students ◽  
Scenario Analysis ◽  
Baccalaureate Nursing ◽  
Baccalaureate Nursing Students ◽  
High Fidelity ◽  
Role Assignment ◽  
Assessment Scores ◽  
Patient Simulators ◽  
The Relationship

With an increase in the number of nursing students and the limited number of open clinical positions, high-fidelity patient simulators (HFPS) have become the new norm. Multiple studies have evaluated HFPS effectiveness and several suggest that HFPS does has an effect on critical thinking. This study intends to provide data to support that suggestion. In addition, this study was designed to identify a possible correlation between role assignment and improvements in critical thinking after completion of a HFPS scenario. Analysis revealed that role assignment, for most of the roles, did have a statistically significant effect on the post-simulation critical thinking assessment scores. The relationship between role assignments and HFPS scenario outcomes (such as critical thinking), as well as the nature of the correlation, may help scenario developers better understand how critical thinking improvement can be affected by the involvement of the participant based on the roles assigned to them.

Human Patient Simulators in Nursing Education: An Overview

2001 ◽  
Vol 32 (2) ◽  
pp. 194-204 ◽  
Author(s):  
Wendy M. Nehring ◽  
Wayne E. Ellis ◽  
Felissa R. Lashley
Keyword(s):  
Nursing Education ◽  
Human Patient ◽  
Human Patient Simulators ◽  
Patient Simulators
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