{"title":"A Gamified Assessment Tool for Antisocial Personality Traits (Antisocial Personality Traits Evidence-Centered Design Gamified): Randomized Controlled Trial.","authors":"Yaobin Tang, Yongze Xu, Qunli Zhou, Ran Bian","doi":"10.2196/70453","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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).</p><p><strong>Objective: </strong>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).</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p><p><strong>Trial registration: </strong>Open Science Framework (OSF) Registries tvg6x; https://osf.io/tvg6x.</p>","PeriodicalId":14795,"journal":{"name":"JMIR Serious Games","volume":"13 ","pages":"e70453"},"PeriodicalIF":4.1000,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12417903/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Serious Games","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2196/70453","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
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.
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.