A Gamified Assessment Tool for Antisocial Personality Traits (Antisocial Personality Traits Evidence-Centered Design Gamified): Randomized Controlled Trial.

IF 4.1 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
JMIR Serious Games Pub Date : 2025-08-25 DOI:10.2196/70453
Yaobin Tang, Yongze Xu, Qunli Zhou, Ran Bian
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引用次数: 0

Abstract

Background: The traditional self-report instruments (eg, scales) used to measure antisocial personality traits are characterized by social desirability bias and fail to capture multidimensional behaviors (eg, manipulation and deception).

Objective: This study aimed to develop and validate an evidence-based design for a gamified assessment tool (Antisocial Personality Traits Evidence-Centered Design Gamified assessment tool; ASP-ECD-G) to measure 7 antisocial personality traits (manipulative, callous, deceptive, hostile, risk taking, impulsive, and irresponsible) as defined in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5).

Methods: This research featured a 3-phase evidence-centered design framework. Ontology development (study 1): semistructured interviews were conducted with 9 workplace professionals to translate the DSM-5 criteria into 24 observable workplace behaviors, which were integrated into a text-based game featuring 10 subscenarios, 34 interactive questions, and logic rooted in logical jumps to simulate real-world decision-making. Model construction (study 2): 6 machine learning models were trained by reference to a set of Personality Inventory for DSM-5 Short Form scores (n=286). The gated recurrent unit model, which uses 1-hot encoding to address nominal response data, was evaluated in terms of the root mean square error (RMSE), mean absolute error, criterion correlation (r), and test-retest reliability. Retest reliability was assessed using intraclass correlation coefficients based on 10 participants (1-month interval). Empirical validation (study 3): a 2×2 mixed design (n=148) was used to compare the gamified assessment with questionnaires under conditions involving incentives (ie, situations in which "rational results" led to increased payments).

Results: For model performance, the gated recurrent unit outperformed the alternatives, as indicated by the highest criterion correlation (r=0.850) and the lowest test RMSE (0.273); in particular, it excelled in moderate score ranges (1.5-3, RMSE≤0.377) and in resisting extreme value distortions (3.5-4, RMSE 0.854). Retest reliability was moderate to strong (intraclass correlation coefficients=0.776, P=.02). For validation findings, the gamified assessment was associated with higher levels of immersion (mean 7.628 vs 7.216; F147=14.259, P<.001) and interest (mean 7.095 vs 6.155; F147=47.940, P<.001), although it also elicited stronger negative emotions (mean 4.365 vs 2.473; F147=151.109, P<.001). Incentives reduced questionnaire scores (incentivized: 2.066 vs control: 2.201; F1=5.740, P=.02) but had no effect on gamified scores (P=.71), confirming resistance to manipulation.

Conclusions: By integrating evidence-centered design with gamified workplace simulations, ASP-ECD-G can provide more objective and ecologically valid measurements of antisocial personality traits, thereby supporting both research and organizational practice.

Trial registration: Open Science Framework (OSF) Registries tvg6x; https://osf.io/tvg6x.

反社会人格特征游戏化评估工具(反社会人格特征证据中心设计游戏化):随机对照试验
背景:用于测量反社会人格特征的传统自我报告工具(如量表)存在社会可取性偏差,无法捕捉多维行为(如操纵和欺骗)。目的:本研究旨在开发并验证基于证据的游戏化评估工具(反社会人格特征以证据为中心的设计游戏化评估工具;ASP-ECD-G)的设计,以测量《精神疾病诊断与统计手册》第五版(DSM-5)中定义的7种反社会人格特征(操纵、冷酷、欺骗、敌对、冒险、冲动和不负责任)。方法:本研究采用以证据为中心的3阶段设计框架。本体开发(研究1):对9名职场专业人士进行半结构化访谈,将DSM-5标准转化为24种可观察的职场行为,并将其整合到一个基于文本的游戏中,该游戏包含10个子场景、34个互动问题和基于逻辑跳跃的逻辑,以模拟现实世界的决策。模型构建(研究2):参考DSM-5短表得分人格量表(n=286)训练6个机器学习模型。门控循环单元模型使用1-hot编码来处理标称响应数据,根据均方根误差(RMSE)、平均绝对误差、标准相关性(r)和重测信度进行评估。采用基于10名参与者(间隔1个月)的类内相关系数评估重测信度。实证验证(研究3):使用2×2混合设计(n=148)将游戏化评估与涉及激励条件(即“理性结果”导致支付增加的情况)的问卷进行比较。结果:对于模型性能,门控循环单元优于备选方案,最高标准相关性(r=0.850)和最低测试RMSE(0.273)表明;特别是在中等得分范围(1.5-3,RMSE≤0.377)和抵抗极端值扭曲(3.5-4,RMSE 0.854)方面表现突出。重测信度为中强(类内相关系数=0.776,P= 0.02)。对于验证结果,游戏化评估与更高水平的沉浸感相关(平均7.628 vs 7.216; F147=14.259)。结论:通过将以证据为中心的设计与游戏化工作场所模拟相结合,ASP-ECD-G可以提供更客观和生态有效的反社会人格特征测量,从而支持研究和组织实践。试验注册:开放科学框架(OSF)注册中心tvg6x;https://osf.io/tvg6x。
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
JMIR Serious Games
JMIR Serious Games Medicine-Rehabilitation
CiteScore
7.30
自引率
10.00%
发文量
91
审稿时长
12 weeks
期刊介绍: JMIR Serious Games (JSG, ISSN 2291-9279) is a sister journal of the Journal of Medical Internet Research (JMIR), one of the most cited journals in health informatics (Impact Factor 2016: 5.175). JSG has a projected impact factor (2016) of 3.32. JSG is a multidisciplinary journal devoted to computer/web/mobile applications that incorporate elements of gaming to solve serious problems such as health education/promotion, teaching and education, or social change.The journal also considers commentary and research in the fields of video games violence and video games addiction.
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