Validating a novel measure for assessing patient openness and concerns about using artificial intelligence in healthcare

IF 2.6 Q2 HEALTH POLICY & SERVICES

Learning Health Systems Pub Date : 2024-06-13 DOI:10.1002/lrh2.10429

Bryan A. Sisk, Alison L. Antes, Sunny C. Lin, Paige Nong, James M. DuBois

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Abstract

Objectives

Patient engagement is critical for the effective development and use of artificial intelligence (AI)-enabled tools in learning health systems (LHSs). We adapted a previously validated measure from pediatrics to assess adults' openness and concerns about the use of AI in their healthcare.

Study Design

Cross-sectional survey.

Methods

We adapted the 33-item “Attitudes toward Artificial Intelligence in Healthcare for Parents” measure for administration to adults in the general US population (AAIH-A), recruiting participants through Amazon's Mechanical Turk (MTurk) crowdsourcing platform. AAIH-A assesses openness to AI-driven technologies and includes 7 subscales assessing participants' openness and concerns about these technologies. The openness scale includes examples of AI-driven tools for diagnosis, prediction, treatment selection, and medical guidance. Concern subscales assessed privacy, social justice, quality, human element of care, cost, shared decision-making, and convenience. We co-administered previously validated measures hypothesized to correlate with openness. We conducted a confirmatory factor analysis and assessed reliability and construct validity. We performed exploratory multivariable regression models to identify predictors of openness.

Results

A total of 379 participants completed the survey. Confirmatory factor analysis confirmed the seven dimensions of the concerns, and the scales had internal consistency reliability, and correlated as hypothesized with existing measures of trust and faith in technology. Multivariable models indicated that trust in technology and concerns about quality and convenience were significantly associated with openness.

Conclusions

The AAIH-A is a brief measure that can be used to assess adults' perspectives about AI-driven technologies in healthcare and LHSs. The use of AAIH-A can inform future development and implementation of AI-enabled tools for patient care in the LHS context that engage patients as key stakeholders.

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验证用于评估患者对在医疗保健中使用人工智能的开放性和担忧程度的新型测量方法

患者的参与对于在学习型医疗系统（LHS）中有效开发和使用人工智能（AI）工具至关重要。我们通过亚马逊的Mechanical Turk (MTurk)众包平台招募参与者，改编了33个项目的 "家长对医疗保健领域人工智能的态度 "测量方法，用于美国普通人群中的成年人（AAIH-A）。AAIH-A 评估对人工智能驱动技术的开放程度，包括 7 个分量表，评估参与者对这些技术的开放程度和担忧。开放性量表包括人工智能驱动的诊断、预测、治疗选择和医疗指导工具的实例。担忧子量表评估隐私、社会公正、质量、护理的人文因素、成本、共同决策和便利性。我们共同采用了之前验证过的假设与开放性相关的测量方法。我们进行了确认性因子分析，并评估了可靠性和构建有效性。我们建立了探索性多变量回归模型，以确定开放性的预测因素。共有 379 名参与者完成了调查。确认性因子分析证实了关注的七个维度，量表具有内部一致性可靠性，并与现有的技术信任和信心测量方法相关。多变量模型表明，对技术的信任以及对质量和便利性的担忧与开放性有显著关联。AAIH-A 是一种简短的测量方法，可用于评估成年人对医疗保健和长者健康服务中人工智能驱动技术的看法。AAIH-A的使用可为未来在长者健康服务背景下开发和实施用于患者护理的人工智能工具提供参考，让患者成为关键的利益相关者。

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