Can AI Digital Personas for Well-Being Provide Social Support? A Mixed-Method Analysis of User Reviews

IF 4.3 Q1 PSYCHOLOGY, MULTIDISCIPLINARY

Human Behavior and Emerging Technologies Pub Date : 2024-08-31 DOI:10.1155/2024/6738001

Radek Heissler, Juraj Jonáš, Nicole Carre, Karin Mostovoy, Eduardo L. Bunge

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引用次数: 0

Abstract

Introduction: Digital personas (DPs) are animated human-like characters that incorporate the capabilities of conversational agents (CAs) and communicate with users via audio and voice.

Aim: This study is aimed at understanding how users perceive the DPs designed for mental well-being and perceived social support.

Methods: A total of 1485 available ratings and user reviews of the DPs from the Elysai app were analyzed using a deductive and inductive thematic analysis. Ordinal regressions were conducted to identify domains predicting users’ ratings.

Results: The average rating of the app was 4.23 out of 5. The thematic analysis identified 27.59% of comments on social support from the DP. Emotional and companionship support were the most frequently reported themes. The inductive thematic analysis identified positive themes, such as the helpfulness of DPs, anthropomorphic traits, negative experiences with DPs, and technical issues. Regression analysis showed that themes of emotional and companionship, social support, positive feedback, anthropomorphic traits, helpfulness, and recommendations significantly predicted positive ratings (odds ratio 1.51–2.86). Conversely, the themes of negative experience with DP and technical issues predicted lower ratings (odds ratio 0.05 and 0.32).

Discussion: Overall, DPs were perceived positively by most reviews analyzed. Users reported that DPs provided emotional and companionship support, were helpful, and had anthropomorphic traits, but also had negative experiences with DPs and technical issues. The types of themes reported in the reviews predicted the user ratings.

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人工智能数字幸福角色能否提供社会支持？对用户评论的混合方法分析

引言：数字角色（DPs）是一种动画类人角色，它结合了对话代理（CAs）的功能，并通过声音和语音与用户进行交流：目标：本研究旨在了解用户如何看待为心理健康和社会支持而设计的数字角色：方法：采用演绎和归纳主题分析法，对伊利赛应用程序中的DPs的1485条可用评分和用户评论进行了分析。结果：该应用程序的平均评分为 4.5 分：该应用程序的平均评分为 4.23 分（满分为 5 分）。主题分析确定了 27.59% 的民主党人对社会支持的评论。情感支持和陪伴支持是最常见的主题。归纳式主题分析确定了积极的主题，如民主党人的乐于助人、拟人化特征、与民主党人的负面经历以及技术问题。回归分析表明，情感和陪伴、社会支持、积极反馈、拟人化特征、乐于助人和推荐等主题可显著预测正面评价（几率比 1.51-2.86）。相反，与民主党相处的负面经历和技术问题则预示着较低的评分（几率比 0.05 和 0.32）：讨论：总体而言，大多数分析评论都对民主党持积极态度。用户认为虚拟伙伴提供了情感和陪伴支持、乐于助人并具有拟人化特征，但也有用户对虚拟伙伴和技术问题有负面体验。评论中报告的主题类型预测了用户的评分。

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

Human Behavior and Emerging Technologies Social Sciences-Social Sciences (all)

CiteScore

17.20

自引率

8.70%

发文量

期刊介绍： Human Behavior and Emerging Technologies is an interdisciplinary journal dedicated to publishing high-impact research that enhances understanding of the complex interactions between diverse human behavior and emerging digital technologies.