The ‘Negotiator’: Assessing artificial intelligence (AI) interview preparation for graduate radiographers

IF 1.3 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Journal of Medical Imaging and Radiation Sciences Pub Date : 2025-05-17 DOI:10.1016/j.jmir.2025.101982

M. Chau , E. Arruzza , C.L. Singh

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引用次数: 0

Abstract

Introduction

The Negotiator is an AI-powered interview preparation tool utilizing OpenAI's ChatGPT to assist graduate radiographers in preparing for professional job interviews. The study aimed to assess the tool’s relevance, clarity, alignment with competency standards, and overall ability to enhance interview readiness for candidates with distinct educational and professional backgrounds.

Methods

Three academic evaluators independently assessed two AI-generated interview scenarios tailored to (1) a Bachelor’s graduate with foundational radiography knowledge and clinical placement experience, and (2) a graduate-entry Master’s student transitioning into radiography from another career. Evaluators rated six criteria—relevance, clarity, alignment with competency standards, practicality, engagement, and overall effectiveness—using a Likert scale. Quantitative analysis included Friedman tests and intraclass correlation coefficients (ICC) to assess inter-rater reliability, while manifest content analysis of qualitative feedback identified strengths and limitations of the tool.

Results

The Friedman test revealed no significant differences in ratings for Scenario 1 (p=0.232), but Scenario 2 showed significant differences (p=0.047). ICC analysis indicated low inter-rater reliability across both scenarios (Scenario 1: ICC=0.182, Scenario 2: ICC=0.242). Thematic analysis highlighted the tool’s strengths in providing relevant prompts, structured responses, and interview readiness while identifying limitations in aligning with competency standards and addressing specific clinical scenarios.

Conclusion

The Negotiator demonstrates potential as a supplementary tool for radiography interview preparation by enhancing clarity and confidence. However, refinements are needed to improve alignment with professional standards and contextual specificity. Future research should explore personalization, broader applications, and its impact on real-world interview outcomes.

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“谈判者”：评估毕业放射技师的人工智能（AI）面试准备

谈判者是一个人工智能驱动的面试准备工具，利用OpenAI的ChatGPT来帮助毕业生放射技师准备专业的工作面试。该研究旨在评估该工具的相关性、清晰度、与能力标准的一致性，以及为具有不同教育和专业背景的候选人增强面试准备的整体能力。方法：三名学术评估人员独立评估了两种人工智能生成的面试场景，分别针对(1)具有基础放射学知识和临床实习经验的本科毕业生，以及(2)从其他职业过渡到放射学的研究生入学。评估人员使用李克特量表对六个标准进行评估——相关性、清晰度、与能力标准的一致性、实用性、参与度和整体有效性。定量分析包括弗里德曼测试和类内相关系数（ICC）来评估评级者之间的可靠性，而定性反馈的显式内容分析确定了该工具的优势和局限性。结果Friedman检验显示情景1的评分无显著差异（p=0.232），但情景2的评分有显著差异（p=0.047）。ICC分析表明，两种情况下的评级间信度都很低（场景1:ICC=0.182，场景2:ICC=0.242）。专题分析强调了该工具在提供相关提示、结构化回答和面试准备方面的优势，同时确定了与能力标准保持一致和解决特定临床场景的局限性。结论谈判者通过提高清晰度和信心，展示了作为x线摄影面试准备的补充工具的潜力。然而，需要改进以改进与专业标准和上下文特异性的一致性。未来的研究应该探索个性化，更广泛的应用，以及它对现实世界面试结果的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Medical Imaging and Radiation Sciences RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-

CiteScore

2.30

自引率

11.10%

发文量

231

审稿时长

53 days

期刊介绍： Journal of Medical Imaging and Radiation Sciences is the official peer-reviewed journal of the Canadian Association of Medical Radiation Technologists. This journal is published four times a year and is circulated to approximately 11,000 medical radiation technologists, libraries and radiology departments throughout Canada, the United States and overseas. The Journal publishes articles on recent research, new technology and techniques, professional practices, technologists viewpoints as well as relevant book reviews.