A Gamified Assessment Tool for Antisocial Personality Traits (Antisocial Personality Traits Evidence-Centered Design Gamified): Randomized Controlled Trial
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,003 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».