Les participants surestiment à quel point ils sont utiles dans un scénario de jeu à deux joueurs envers un compère artificiel qui divulgue un diagnostic d’autisme

Titre original en anglais : Participants Over-Estimate How Helpful They Are in a Two-Player Game Scenario Toward an Artificial Confederate That Discloses a Diagnosis of Autism

Cette publication est incluse dans le projet « Contributions académiques de personnes autistes sur l’autisme ». un auteur·ice de cette publication est identifié·e comme autiste dans le projet.

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Heasman, B. & Gillespie, A. (2019). Participants Over-Estimate How Helpful They Are in a Two-Player Game Scenario Toward an Artificial Confederate That Discloses a Diagnosis of Autism. Frontiers in Psychology, 10, 1349-1349. https://doi.org/10.3389/fpsyg.2019.01349

Date de publication: 11/06/2019 Ajout dans AutiHub: 30/08/2026 Type: Article Langue de l’article: Anglais
Source éditeur (DOI) Texte intégral Source OpenAlex

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Auteurs

Auteur·ices des publications
2
Auteur·ices de la publication identifié·es comme autistes
1 / 2 (50,0 %)
  1. Brett Heasman *
  2. Alex Gillespie

Résumé

Les recherches sur la manière dont les personnes autistes sont perçues par les personnes neurotypiques indiquent que la divulgation d’un diagnostic entraîne un biais discriminatoire positif ; cependant, les récits autobiographiques de personnes autistes indiquent que la divulgation diagnostique aboutit souvent à des comportements discriminatoires négatifs. Nous présentons une étude exploratoire visant à comparer les comportements d’aide auto-déclarés des personnes avec leurs comportements d’aide réels envers un collaborateur supposé autiste. Nous avons amené 255 participants à croire qu’ils interagissaient en ligne avec une personne réelle pour jouer à Dyad3D, un jeu de navigation dans un labyrinthe où les joueurs doivent travailler ensemble pour ouvrir des portes et terminer les niveaux. Cependant, les participants jouaient en réalité avec un compère artificiel (AC) programmé pour se comporter de la même manière dans toutes les interactions. Cette conception nous a permis de manipuler le statut diagnostique de l’AC que les participants recevaient avant la collaboration selon trois conditions : aucune divulgation, divulgation de dyslexie et divulgation d’autisme. Nous utilisons cette méthode pour explorer deux questions de recherche : (1) Dyad3D est-il viable pour créer une interaction simulée susceptible de tromper les participants en leur faisant croire qu’ils collaboraient en ligne avec un autre joueur humain ? et (2) quels sont les effets de la divulgation d’un diagnostic d’autisme sur la perception sociale et la collaboration ? Associées à un questionnaire post-jeu, nous avons comparé les différences entre les conditions diagnostiques et les différences entre les comportements auto-déclarés et les comportements réels dans le jeu. Nos résultats montrent que Dyad3D s’est révélé être une méthode efficace et viable pour créer une interaction crédible (taux de réussite de la tromperie >96 %). De plus, la divulgation diagnostique de l’autisme conduit à percevoir l’AC comme plus intelligent et plus utile, mais les participants se percevaient également comme plus utiles envers l’AC qu’ils ne l’étaient réellement. Nous évaluons les forces et les limites de la méthode actuelle et formulons des recommandations pour les recherches futures. Le code source de Dyad3D est librement disponible (CC-BY-NC 4.0), afin que l’étude soit reproductible et ouverte à de futures adaptations.

Research on how autistic people are perceived by neurotypical people indicates that disclosing a diagnosis leads to a positive discriminatory bias; however, autobiographical autistic accounts indicate that diagnostic disclosure often results in negative discriminatory behavior. We report on an exploratory study to compare people's self-reported helping behavior with their actual helping behavior toward an assumed autistic collaborator. We led 255 participants to believe that they were interacting online with a real person to play Dyad3D, a maze navigation game where players must work together to open doors, and complete the levels. However, participants were actually playing with an artificial confederate (AC) that is programmed to behave the same way across all interactions. This design enabled us to manipulate the diagnostic status of the AC that participants received prior to collaboration across three conditions: no disclosure, dyslexia-disclosure, and autism-disclosure. We use this method to explore two research questions: (1) is Dyad3D viable in creating a simulated interaction that could deceive participants into believing they were collaborating with another human player online? and (2) what are the effects of disclosing an autism diagnosis on social perception and collaboration? Combined with a post-game questionnaire, we compared differences between diagnostic conditions and differences between self-reported behavior and actual behavior in the game. Our findings show that Dyad3D proved to be an efficient and viable method for creating a believable interaction (deception success rate >96%). Moreover, diagnostic disclosure of autism results in the AC being perceived as more intelligent and useful, but participants also perceived themselves to be more helpful toward the AC than they actually were. We evaluate the strengths and limitations of the current method and provide recommendations for future research. The source code for Dyad3D is freely available (CC-BY-NC 4.0) so that the study is reproducible and open to future adaptation.

Bibliographie citée par cette référence

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Vue d’ensemble de la bibliographie citée

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Références citées
68
Avec un DOI
58
Sans DOI, à partir du texte brut de la bibliographie
10
8 / 68 (11,8 %) références citées comprennent au moins une personne identifiée comme autiste.
Références avec données à compléter
8 / 68 (11,8 %)
Références avec noms d’auteurices détectés
68 / 68 (100,0 %)
Sans nom d’auteurice détecté
0
Sans titre structuré
8
Sans identifiant stable
10
Références avec noms bruts d’auteurices restant à vérifier
0
Références avec problème de récupération des métadonnées externes
0
Ces indicateurs portent sur les références citées affichées sur cette page, après fusion des doublons techniques. Une référence sans DOI peut quand même soutenir les statistiques d’auteurices lorsqu’un titre et des noms d’auteurices sont disponibles.
Noms d’auteurices détectés dans la bibliographie citée
172
À partir du DOI ou de métadonnées externes
172
À partir du texte brut validé de la bibliographie
0
Noms bruts déjà validés
0
Noms bruts restant à vérifier
0
57 / 172 (33,1 %) noms sont associés à un·e auteurice déjà présent·e dans AutiHub. 115 / 172 (66,9 %) noms ne sont pas encore associés.
Noms associés à une personne identifiée comme autiste
9 / 172 (5,2 %)
Calculé sur l’ensemble des noms d’auteurices détectés dans la bibliographie citée. Parmi les noms associés à un·e auteurice déjà présent·e dans AutiHub : 9 / 57 (15,8 %). Personnes distinctes identifiées comme autistes : 5 / 146 (3,4 %).
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