Exploring healthcare professionals' perceptions of artificial intelligence: Piloting the Shinners Artificial Intelligence Perception tool

Radiology Residents' Perceptions of Artificial Intelligence: Nationwide Cross-Sectional Survey Study

BACKGROUND

Artificial intelligence (AI) is transforming various fields, with health care, especially diagnostic specialties such as radiology, being a key but controversial battleground. However, there is limited research systematically examining the response of "human intelligence" to AI.

OBJECTIVE

This study aims to comprehend radiologists' perceptions regarding AI, including their views on its potential to replace them, its usefulness, and their willingness to accept it. We examine the influence of various factors, encompassing demographic characteristics, working status, psychosocial aspects, personal experience, and contextual factors.

METHODS

Between December 1, 2020, and April 30, 2021, a cross-sectional survey was completed by 3666 radiology residents in China. We used multivariable logistic regression models to examine factors and associations, reporting odds ratios (ORs) and 95% CIs.

RESULTS

In summary, radiology residents generally hold a positive attitude toward AI, with 29.90% (1096/3666) agreeing that AI may reduce the demand for radiologists, 72.80% (2669/3666) believing AI improves disease diagnosis, and 78.18% (2866/3666) feeling that radiologists should embrace AI. Several associated factors, including age, gender, education, region, eye strain, working hours, time spent on medical images, resilience, burnout, AI experience, and perceptions of residency support and stress, significantly influence AI attitudes. For instance, burnout symptoms were associated with greater concerns about AI replacement (OR 1.89; P<.001), less favorable views on AI usefulness (OR 0.77; P=.005), and reduced willingness to use AI (OR 0.71; P<.001). Moreover, after adjusting for all other factors, perceived AI replacement (OR 0.81; P<.001) and AI usefulness (OR 5.97; P<.001) were shown to significantly impact the intention to use AI.

CONCLUSIONS

This study profiles radiology residents who are accepting of AI. Our comprehensive findings provide insights for a multidimensional approach to help physicians adapt to AI. Targeted policies, such as digital health care initiatives and medical education, can be developed accordingly.

Graphical User Interface Development for a Hospital-Based Predictive Risk Tool: Protocol for a Co-Design Study

BACKGROUND

This co-design research method details the iterative process developed to identify health professional recommendations for the graphical user interface (GUI) of an artificial intelligence (AI)-enabled risk prediction tool. Driving the decision to include a co-design process is the belief that choices regarding the aesthetic and functionality of an intervention are best made by its intended users and that engaging these users in its design will promote the tool's adoption and use.

OBJECTIVE

The aim of this research is to identify health professional design and uptake recommendations for the GUI of an AI-enabled predictive risk tool.

METHODS

We will hold 3 research phases, each consisting of 2 workshops with health professionals, between mid-2023 and mid-2024. A total of 6 health professionals will be sought per workshop, resulting in a total enrollment of 36 health professionals at the conclusion of the research. A total of 7 workshop activities have been scheduled across the 3 workshops; these include context of use, notifiers, format, AI survey-Likert, prototype, AI survey-written, and testing. The first 6 of these activities will be repeated in each workshop to enable the iterative development and refinement of GUI. The last activity (testing) will be performed in the final workshop to examine health professionals' thoughts on the final GUI iteration. Qualitative and quantitative results data will be produced from tasks in each research activity. Qualitative data will be examined through inductive thematic analysis or deductive thematic analysis in accordance with the Nonadoption, Abandonment, and Challenges to the Scale-up, Spread, and Sustainability (NASSS) framework; visual data will be examined in accordance with "framework of interactivity;" and quantitative data will be examined using descriptive statistics.

RESULTS

Project registration with the Australia and New Zealand Clinical Trial Registry has been requested (#384098). Finalized design recommendations are expected in early to mid-2024, with a results manuscript to be submitted in mid-2024. This research method has human research ethics approval from the South Australian Department of Health and Wellbeing (#2022/HRE00131) as well as from the Human Research Ethics Committee of the University of South Australia (application ID#204143).

CONCLUSIONS

Understanding whether an intervention is needed in a particular situation is just the start; designing an intervention so that it is used within that situation is paramount. This co-design process engages end users to create a GUI that includes the aesthetic and functional details they need in a manner that aligns with their existing work practices. Indeed, interventions that fail to do this may be disliked, and at worst, they may be dangerous.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/47717.

Mobile nutrition and health management platform for perioperative recovery: an interdisciplinary research achievement using WeChat Applet

Background

In recent years, the number of people using mobile applications to promote health and welfare has exponentially increased. However, there are fewer applications in the field of ERAS. How to promote the rapid rehabilitation of patients with malignant tumor surgery during perioperative period and the mastery of its long-term nutritional state is a problem to be solved.

Objective

The purpose of this study is to design and develop a mobile application, and use Internet technology to better manage nutritional health to achieve rapid recovery of patients with malignant tumor surgery.

Methods

This study is divided into three stages: (1) Design: use participating design to make the MHEALTH APP adapt to the clinical practice of nutritional health management; (2) Development: the WeChat Applet of Nutrition and Health Assessment (WANHA) developed using the Internet technology development, and web management programs. (3) Procedure test: patients and medical staff evaluate WANHA's quality (UMARS), availability (SUS), and satisfaction, and conduct semi-structured interviews.

Results

In this study, 192 patients with malignant tumor surgery, 20 medical staff used WANHA. Patients with nutritional risks are supported by supporting treatment. The results show that patients who have not been treated during the perioperative period, the incidence of postoperative complications (22.4%) and the average hospitalization time after surgery decreased significantly. The incidence of nutritional risks is nearly more than the preoperative level. 45 patients and 20 medical staff participated in the survey of WANHA's SUS, UMARS, and satisfaction. In the interview, most patients and medical personnel believe that the procedure can improve the current medical services and nutritional health knowledge levels, promote the communication of medical staff and patients, and strengthen the nutritional health management of patients with malignant tumors under the concept of ERAS.

Conclusion

WeChat Applet of Nutrition and Health Assessment is a MHEALTH APP that enhances the nutrition and health management of patients with perioperative period. It can play a huge role in improving medical services, increasing patient satisfaction, and ERAS.

Experience of using a smartphone WeChat applet for dental anxiety assessment and preoperative evaluation: A nationwide multicenter study

Introduction

Dental anxiety is a multivariate phenomenon that regularly occurs during a dental procedure. Although it may lead to patients' safety concerns and adverse events in routine treatment, it is often ignored. The purpose of this research is to develop a novel WeChat Applet for dental anxiety (WADA) with the following features and aims: (1) to help patients with dental anxiety management; (2) provide patient with a physical status self-evaluation; and(3) provide a platform for online assessment and tele-consultancy by dentists. We aimed to test and verify whether such an applet could play a beneficial role before and after a dental procedure and facilitate management of high-risk patients during the COVID-19 pandemic.

Materials and methods

During the 12-month survey period (August 2020 to July 2021), a total of 180 patients aged 3–74 years from eight different cities (n = 180 at the end of treatment, n = 25 for the System Usability Scale (SUS) and follow-up interview) and 20 medical staff from eight different cities (n =20 for follow-up interview) were evaluated by WADA. At the end of the survey period, the results of the interviews were analyzed thematically.

Results

WADA assessment results from 180 patients and follow-up interview results from 45 participants were analyzed. In this study with a male to female ratio of 2:3, 75% were found to be suffering from dental anxiety, 86% were found with postoperative complications, and 11 cases were found to have contraindications to surgery. The total SUS score for WADA is 72.25 above the mean score, proving that WADA is a relevant and useful tool before and after dental treatment. Based on the results of the interviews, the following themes were identified: patient satisfaction; dentists' effectiveness; multi-center data integration; and increase its frequency of usage.

Conclusions

The WADA was developed for dental procedures and is effective for reducing treatment risks, improving patients' satisfaction and dentists' convenience, especially in terms of facilitating management of high-risk patient during the COVID-19 pandemic.