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Auteur María TUBÍO-FUNGUEIRIÑO
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Documents disponibles écrits par cet auteur (3)
Faire une suggestion Affiner la rechercheCorrigendum to “Predicting autistic traits, anxiety and depression symptoms using camouflaging autistic traits questionnaire (CAT-Q-ES): A machine learning study” [Research in Autism 128 (2025) 202712] / Sabela CONDE-PUMPIDO-ZUBIZARRETA in Research in Autism, 133 (May 2026)
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[article]
Titre : Corrigendum to “Predicting autistic traits, anxiety and depression symptoms using camouflaging autistic traits questionnaire (CAT-Q-ES): A machine learning study” [Research in Autism 128 (2025) 202712] Type de document : texte imprimé Auteurs : Sabela CONDE-PUMPIDO-ZUBIZARRETA, Auteur ; María TUBÍO-FUNGUEIRIÑO, Auteur ; Marta POZO-RODRÍGUEZ, Auteur ; Ángel CARRACEDO, Auteur ; Eva CERNADAS, Auteur ; Manuel FERNÁNDEZ-DELGADO, Auteur ; Montse FERNÁNDEZ-PRIETO, Auteur Article en page(s) : p.202910 Langues : Anglais (eng) Index. décimale : PER Périodiques En ligne : https://doi.org/10.1016/j.reia.2026.202910 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=585
in Research in Autism > 133 (May 2026) . - p.202910[article] Corrigendum to “Predicting autistic traits, anxiety and depression symptoms using camouflaging autistic traits questionnaire (CAT-Q-ES): A machine learning study” [Research in Autism 128 (2025) 202712] [texte imprimé] / Sabela CONDE-PUMPIDO-ZUBIZARRETA, Auteur ; María TUBÍO-FUNGUEIRIÑO, Auteur ; Marta POZO-RODRÍGUEZ, Auteur ; Ángel CARRACEDO, Auteur ; Eva CERNADAS, Auteur ; Manuel FERNÁNDEZ-DELGADO, Auteur ; Montse FERNÁNDEZ-PRIETO, Auteur . - p.202910.
Langues : Anglais (eng)
in Research in Autism > 133 (May 2026) . - p.202910
Index. décimale : PER Périodiques En ligne : https://doi.org/10.1016/j.reia.2026.202910 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=585 Predicting autistic traits, anxiety and depression symptoms using camouflaging autistic traits questionnaire (CAT-Q-ES): A machine learning study / Sabela CONDE-PUMPIDO ZUBIZARRETA in Research in Autism, 128 (October 2025)
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[article]
Titre : Predicting autistic traits, anxiety and depression symptoms using camouflaging autistic traits questionnaire (CAT-Q-ES): A machine learning study Type de document : texte imprimé Auteurs : Sabela CONDE-PUMPIDO ZUBIZARRETA, Auteur ; María TUBÍO-FUNGUEIRIÑO, Auteur ; Marta POZO-RODRÍGUEZ, Auteur ; Ángel CARRACEDO, Auteur ; Eva CERNADAS, Auteur ; Manuel FERNÁNDEZ-DELGADO, Auteur ; Montse FERNÁNDEZ-PRIETO, Auteur Article en page(s) : p.202712 Langues : Anglais (eng) Mots-clés : ASD Autism CAT-Q-ES Camouflaging Supervised machine learning Mental health Gender Index. décimale : PER Périodiques Résumé : Research has linked camouflaging with compensating and hiding autistic traits during social interactions. Furthermore, these strategies have been linked to increased anxiety and depression symptoms and to greater reliance on camouflaging behaviors among individuals with more autistic traits, even in non-autistic populations. This study evaluated the viability of a machine learning algorithm to predict autistic traits and symptoms of depression and anxiety using camouflaging behaviors. The sample included 601 participants: 102 autistic adults (72 women, 18 men, and 12 non-binary individuals) and 499 non-autistic adults (399 women, 92 men, and eight non-binary individuals). The study predicted autistic traits measured with the Broader Autism Phenotype Questionnaire (BAPQ) subscales - Aloofness, Pragmatics, and Rigidity - as well as the total score of depressive (Patient Health Questionnaire - PHQ-9) and anxious symptoms (General Anxiety Disorder - GAD-7) using the individual items from the Camouflaging Autistic Traits Questionnaire Spanish version (CAT-Q-ES) as predictors. We developed fifty supervised learning models, including support vector machines, neural networks, linear regressors, decision trees, random forests, and Gaussian processes, among others. Correlation coefficients between true and predicted scores were strong for Aloofness (R=.85), Pragmatics (R=.82), and Rigidity (R=.74), being only moderate for Depression (R=.60) and Anxiety (R=.54). Autism diagnosis or gender identity did not improve the prediction’s accuracy. These results show the viability of machine learning algorithms to predict autistic traits (Aloofness, Pragmatics and Rigidity) and anxiety-depression symptoms, using the CAT-Q-ES. This suggests potential for developing a tool that may improve autistic traits and emotional problems screening in individuals whose diagnosis is unclear or not yet established, regardless of gender identity. En ligne : https://doi.org/10.1016/j.reia.2025.202712 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=570
in Research in Autism > 128 (October 2025) . - p.202712[article] Predicting autistic traits, anxiety and depression symptoms using camouflaging autistic traits questionnaire (CAT-Q-ES): A machine learning study [texte imprimé] / Sabela CONDE-PUMPIDO ZUBIZARRETA, Auteur ; María TUBÍO-FUNGUEIRIÑO, Auteur ; Marta POZO-RODRÍGUEZ, Auteur ; Ángel CARRACEDO, Auteur ; Eva CERNADAS, Auteur ; Manuel FERNÁNDEZ-DELGADO, Auteur ; Montse FERNÁNDEZ-PRIETO, Auteur . - p.202712.
Langues : Anglais (eng)
in Research in Autism > 128 (October 2025) . - p.202712
Mots-clés : ASD Autism CAT-Q-ES Camouflaging Supervised machine learning Mental health Gender Index. décimale : PER Périodiques Résumé : Research has linked camouflaging with compensating and hiding autistic traits during social interactions. Furthermore, these strategies have been linked to increased anxiety and depression symptoms and to greater reliance on camouflaging behaviors among individuals with more autistic traits, even in non-autistic populations. This study evaluated the viability of a machine learning algorithm to predict autistic traits and symptoms of depression and anxiety using camouflaging behaviors. The sample included 601 participants: 102 autistic adults (72 women, 18 men, and 12 non-binary individuals) and 499 non-autistic adults (399 women, 92 men, and eight non-binary individuals). The study predicted autistic traits measured with the Broader Autism Phenotype Questionnaire (BAPQ) subscales - Aloofness, Pragmatics, and Rigidity - as well as the total score of depressive (Patient Health Questionnaire - PHQ-9) and anxious symptoms (General Anxiety Disorder - GAD-7) using the individual items from the Camouflaging Autistic Traits Questionnaire Spanish version (CAT-Q-ES) as predictors. We developed fifty supervised learning models, including support vector machines, neural networks, linear regressors, decision trees, random forests, and Gaussian processes, among others. Correlation coefficients between true and predicted scores were strong for Aloofness (R=.85), Pragmatics (R=.82), and Rigidity (R=.74), being only moderate for Depression (R=.60) and Anxiety (R=.54). Autism diagnosis or gender identity did not improve the prediction’s accuracy. These results show the viability of machine learning algorithms to predict autistic traits (Aloofness, Pragmatics and Rigidity) and anxiety-depression symptoms, using the CAT-Q-ES. This suggests potential for developing a tool that may improve autistic traits and emotional problems screening in individuals whose diagnosis is unclear or not yet established, regardless of gender identity. En ligne : https://doi.org/10.1016/j.reia.2025.202712 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=570 Social Camouflaging in Females with Autism Spectrum Disorder: A Systematic Review / María TUBÍO-FUNGUEIRIÑO in Journal of Autism and Developmental Disorders, 51-7 (July 2021)
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[article]
Titre : Social Camouflaging in Females with Autism Spectrum Disorder: A Systematic Review Type de document : texte imprimé Auteurs : María TUBÍO-FUNGUEIRIÑO, Auteur ; Sara CRUZ, Auteur ; Adriana SAMPAIO, Auteur ; Ángel CARRACEDO, Auteur ; Montse FERNÁNDEZ-PRIETO, Auteur Article en page(s) : p.2190-2199 Langues : Anglais (eng) Mots-clés : Adaptation, Psychological Autism Spectrum Disorder/psychology Female Humans Male Sex Factors Social Adjustment Autism Camouflage Females Systematic review Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a neurodevelopmental disorder with increasing prevalence, and a male-to-female ratio of 4:1. Research has been suggesting that discrepancy in prevalence may be due to the fact that females camouflage their symptoms. In this study, we aimed to systematically review evidence on the camouflage effect in females with ASD. Following the PRISMA guidelines, we reviewed empirical research published from January 2009 to September 2019 on PubMed, Web of Science, PsychInfo and Scopus databases. Thirteen empirical articles were included in this review. Overall, evidence supports that camouflaging seems to be an adaptive mechanism for females with ASD, despite the negative implications of these behaviours in their daily life. En ligne : http://dx.doi.org/10.1007/s10803-020-04695-x Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=452
in Journal of Autism and Developmental Disorders > 51-7 (July 2021) . - p.2190-2199[article] Social Camouflaging in Females with Autism Spectrum Disorder: A Systematic Review [texte imprimé] / María TUBÍO-FUNGUEIRIÑO, Auteur ; Sara CRUZ, Auteur ; Adriana SAMPAIO, Auteur ; Ángel CARRACEDO, Auteur ; Montse FERNÁNDEZ-PRIETO, Auteur . - p.2190-2199.
Langues : Anglais (eng)
in Journal of Autism and Developmental Disorders > 51-7 (July 2021) . - p.2190-2199
Mots-clés : Adaptation, Psychological Autism Spectrum Disorder/psychology Female Humans Male Sex Factors Social Adjustment Autism Camouflage Females Systematic review Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a neurodevelopmental disorder with increasing prevalence, and a male-to-female ratio of 4:1. Research has been suggesting that discrepancy in prevalence may be due to the fact that females camouflage their symptoms. In this study, we aimed to systematically review evidence on the camouflage effect in females with ASD. Following the PRISMA guidelines, we reviewed empirical research published from January 2009 to September 2019 on PubMed, Web of Science, PsychInfo and Scopus databases. Thirteen empirical articles were included in this review. Overall, evidence supports that camouflaging seems to be an adaptive mechanism for females with ASD, despite the negative implications of these behaviours in their daily life. En ligne : http://dx.doi.org/10.1007/s10803-020-04695-x Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=452
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