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Enregistrement W4401463560 · doi:10.1089/aut.2023.0192

Neurodivergence and the Rabbit Hole of Extremism: Uncovering Lived Experience

2024· article· en· W4401463560 sur OpenAlexaffabout
Sachindri Wijekoon, John Elder Robison, Christie Welch, Alexander Westphal, Rachel Loftin, Barbara Perry, Victoria Rombos, Christian Picciolini, Catherine Bosy, Lili Senman, Patrick Jachyra, Simon Baron‐Cohen, Melanie Penner

Notice bibliographique

RevueAutism in Adulthood · 2024
Typearticle
Langueen
DomaineNeuroscience
ThématiqueAutism Spectrum Disorder Research
Établissements canadiensOntario Tech UniversityUniversity of TorontoHolland Bloorview Kids Rehabilitation HospitalWestern University
Organismes subventionnairesnon disponible
Mots-clésIdeologyHatredPsychologySocial psychologyPsychological interventionDevelopmental psychologyPolitical sciencePsychiatry

Résumé

récupéré en direct d'OpenAlex

Background: There have been sporadic and disturbing media accounts of autistic people engaging with extreme ideologies, with comparatively little systematic exploration of this suggested association. Existing research has failed to consider the contextual factors that could influence these rare occurrences of engagement with extreme ideologies. This study explores how autistic individuals involved in extreme ideologies describe personal and contextual factors affecting their participation. Methods: Twelve individuals from Canada and the United States who were either diagnosed or self-identified as autistic and have engaged with extreme ideologies participated in semistructured interviews. The research approach and analysis of the data were informed by interpretative phenomenological analysis. Our interdisciplinary team met regularly to collectively examine initial assumptions and interpretations, while maintaining a central focus on the perspectives of the participants. Results: We identified the following three key themes: (1) early wounds, (2) missed formative opportunities, and (3) finding a fit for neurodivergence. Traumatic experiences, disenfranchisement, learned hatred from an insular upbringing, and systemic failings in health and social service systems contributed to participants’ decisions to engage with extreme ideologies. Hate groups, in turn, filled the voids by providing acceptance, purpose, structure, sense of community, and by accommodating participants’ neurodivergent needs. Conclusion: Autism alone did not explain participants’ engagement with extreme ideologies. Trauma and disenfranchisement related to being neurodivergent were common factors that made hate groups more appealing. Proactive interventions to prevent engagement in extreme ideologies must champion inclusive environments that recognize autistic individuals’ skills and address underlying factors that contribute to their disenfranchisement. Community Brief What was the purpose of this study? The media has reported on high-profile cases of autistic people with extreme beliefs who acted in violent ways. There is a lack of research on this topic and researchers have not directly spoken with autistic people who have been involved with these extreme beliefs. Our goal was to understand why some autistic people engaged with hateful beliefs, asking them about both autism and their life circumstances. What did the researchers do? We interviewed 12 people who identified as autistic to understand why they became involved in extreme beliefs. We conducted the interviews by phone or using Zoom Health. We read the interview text, identified important statements, and then identified the ideas linking these statements. What were the results of the study? Most of the people in our study were young to middle-aged men with White/European background from Canada and the United States. Only a few had a formal autism diagnosis. Participants faced many challenges, including being neglected by parents, experiencing trauma, and not feeling like they belong. Many of them were not given opportunities to freely express themselves or have positive interactions with people from different backgrounds. Everyone lacked the opportunity to build a positive view of themselves and the world around them. Participants described some autistic and neurodivergent traits, such as having a focused interest in one topic, having difficulty understanding and connecting with others, preferring clear rules and a set routine, and having difficulty controlling emotions, were not accepted elsewhere but were accepted in groups with extreme beliefs. What do these findings add to what was known? Hate groups provided autistic people a supportive environment where their strengths were highlighted, their individuality was celebrated, and their challenges were accommodated. This level of support contrasted with what autistic people had previously experienced in society. What are potential weaknesses? One limitation of our study was that we included people who identify as autistic, but we did not verify their diagnosis through formal testing. Our sample is a small group of autistic people who had engaged with hateful beliefs; our findings do not apply to all autistic people and should not be interpreted that all autistic people are more likely to have extreme or hateful beliefs. How will these findings help autistic adults now or in the future? Engagement with extreme groups or beliefs is only one possible negative outcome from the lack of inclusion and acceptance of autistic people, but is an important one. We should create supportive environments that welcome and appreciate autistic peoples’ skills and interests to allow them to feel valued and connected to their community. Families, teachers, and professionals should prioritize accurate and timely diagnosis and provide supports that are tailored to their needs. These steps can help autistic people build meaningful relationships and prevent them from turning to extremist groups to meet their needs.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,313
Score d'incertitude au seuil0,480

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,035
Tête enseignante GPT0,302
Écart entre enseignants0,267 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2024
Routes d'admission2
Résumé présentoui

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