接受使用人工智能和数字技术进行心理健康干预:UTAUT-AI-DMHI的开发和初步验证

IF 3.2 3区 心理学 Q1 PSYCHOLOGY, CLINICAL
Vera Békés, Beata Bőthe, Katie Aafjes-van Doorn
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引用次数: 0

摘要

数字卫生技术正越来越多地融入精神卫生保健。这意味着患者有不同的治疗选择,临床医生也需要考虑不同的方式来支持他们的患者。数字心理健康干预(DMHI)技术的采用将受到患者和临床医生对这些技术的态度的影响。技术接受和使用统一理论(UTAUT)是最常用的模型,用于检查专业环境中技术的接受程度,它确定了使用技术(如人工智能(AI))的行为意图的决定因素。我们的目的是开发和验证UTAUT-AI-DMHI测量,以评估各种类型的数字和基于ai的心理健康干预措施的接受程度。我们在三个干预措施中评估了UTAUT-AI-DMHI的心理测量特性:通过视频会议的远程治疗,AI聊天机器人和AI虚拟治疗师干预两个样本。样本1包括n = 528例患者,n = 155名临床医生和n = 432名参与者,属于两组;样本2用于证实结果,其中包括一个具有代表性的美国社区样本n = 536。我们的研究结果证明了UTAUT因子具有足够的结构效度和信度。与之前的UTAUT文献一致,验证性因子分析显示,最终的17个项目(加上一个评估行为意图的项目)量表由七个因素组成:易用性、社会影响力、便利性、人际关系、感知隐私风险、享乐动机和治疗质量预期。在三种DMHI格式中,所有因素都与对人工智能的一般态度和未来使用干预措施的意图呈正相关。这意味着UTAUT-AI-DMHI自我报告量表可用于评估对各种数字和基于ai的心理健康干预措施的接受程度。此外,UTAUT-AI-DMHI可以作为患者、临床医生和公众的自我报告量表进行管理,从而可以直接比较对不同干预形式的接受程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Acceptance of Using Artificial Intelligence and Digital Technology for Mental Health Interventions: The Development and Initial Validation of the UTAUT-AI-DMHI

Digital health technologies are being increasingly integrated into mental healthcare. This means that patients have different treatment options, and clinicians need to consider different ways of supporting their patients too. The adoption of Digital Mental Health Intervention (DMHI) technologies will be influenced by patients' and clinicians' attitudes towards these technologies. The Unified Theory of Acceptance and Use of Technology (UTAUT) is the most commonly used model to examine acceptance of technologies in professional settings, which identifies determinants of behavioural intention to use technologies, such as artificial intelligence (AI). We aimed to develop and validate the UTAUT-AI-DMHI measure to assess acceptance various types of digital and AI-based mental health interventions. We assessed the UTAUT-AI-DMHI's psychometric properties in three interventions: teletherapy via videoconferencing, AI chatbot and AI virtual therapist interventions in two samples. Sample 1 included n = 528 patients, n = 155 clinicians and n = 432 participants belonging to both groups; Sample 2 was used to corroborate the results and included a representative US community sample of n = 536. Our results demonstrated adequate construct validity and reliability of the UTAUT factors. In line with previous UTAUT literature, confirmatory factor analysis revealed that the final 17-item (plus one item assessing Behavioural Intention) scale consisted of seven factors: ease of use, social influence, convenience, human connection, perceived privacy risk, hedonic motivation and therapy quality expectations. All factors were positively associated with general attitudes towards AI and intention to use the intervention in the future in each of the three DMHI formats. This implies that the UTAUT-AI-DMHI self-report scale can be applied to assess acceptance of various kinds of digital and AI-based mental health interventions. Further, the UTAUT-AI-DMHI can be administered as a self-report scale for patients, clinicians and the general public and thus allows for a direct comparison of acceptance of different intervention formats.

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来源期刊
Clinical psychology & psychotherapy
Clinical psychology & psychotherapy PSYCHOLOGY, CLINICAL-
CiteScore
6.30
自引率
5.60%
发文量
106
期刊介绍: Clinical Psychology & Psychotherapy aims to keep clinical psychologists and psychotherapists up to date with new developments in their fields. The Journal will provide an integrative impetus both between theory and practice and between different orientations within clinical psychology and psychotherapy. Clinical Psychology & Psychotherapy will be a forum in which practitioners can present their wealth of expertise and innovations in order to make these available to a wider audience. Equally, the Journal will contain reports from researchers who want to address a larger clinical audience with clinically relevant issues and clinically valid research.
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