Project LIFEisGAME: characters preferences and characters' empirical validation

Characters Results (%) Image Type Photorealistic (animal, child, adult) Animal (54.4%) 2D Simple Cartoon (animal, child, adult) Animal (61.8%) 3D Complex Cartoon (animal, child and adult) Animal (61.5%) Format 3D Complex Cartoon vs. Photorealistic (children) Photorealistic (36.6%) 3D Complex Cartoon vs. Photorealistic (adults) 3D Complex (52.9%) 3D Complex Cartoon vs. Photorealistic (animals) Photorealistic (45.8%) Familiarity Known Vs. Unknown (male children) Known (48.3%) Known Vs. Unknown (female children) Known (48.0%) Known Vs. Unknown (adults) Known (39.9%) Known Vs. Unknown (animals) Known (69.1%) Project Project LIFEisGAME LIFEisGAME: : Characters Characters Preferences Preferences and and Characters Characters´ ´Empirical Empirical Validation Validation People with Autism Spectrum Disorders (ASD) are less likely to attend to faces and are impaired in face discrimination tasks. Technology plays an active part in helping these individuals to understand emotions and recognize facial expressions, trying to ameliorate their social interactions (Baron-Cohen et al., 2004; Kuusikko et al., 2009). During LIFEisGAME prototype’s development, empirical tests were conducted using Ekman´s six basic emotions applied to children without ASD due the difficulty of these children to identify emotions. The studies aimed to: Study 1: To identify appealing characteristics of characters, verify preferred type of character and get a hierarchy of preferences. Study 2: To validate the facial expressions of happiness, sadness, anger, disgust , surprise, fear and neutral (no emotion) of the LIFEisGAME character “Monkey”. Study 3: To validate children and adults models of Radboud Database (Langner et al., 2010) for the Portuguese Population. People with Autism Spectrum Disorders (ASD) are less likely to attend to faces and are impaired in face discrimination tasks. Technology plays an active part in helping these individuals to understand emotions and recognize facial expressions, trying to ameliorate their social interactions (Baron-Cohen et al., 2004; Kuusikko et al., 2009). During LIFEisGAME prototype’s development, empirical tests were conducted using Ekman´s six basic emotions applied to children without ASD due the difficulty of these children to identify emotions. The studies aimed to: Study 1: To identify appealing characteristics of characters, verify preferred type of character and get a hierarchy of preferences. Study 2: To validate the facial expressions of happiness, sadness, anger, disgust , surprise, fear and neutral (no emotion) of the LIFEisGAME character “Monkey”. Study 3: To validate children and adults models of Radboud Database (Langner et al., 2010) for the Portuguese Population. 1. 1. Aims Aims 2. 2. Method Method 4. 4. Conclusions Conclusions 5. 5. References References Study 1:children prefer type animal characters (e.g. dogs) and almost always photorealistic. Mass-media impacts onto children 'preferences because in all categories the “known characters” by movies or cartoon series (e.g. ratatouille) are always chosen above all others. Results also show that the most selected characters are female and have “babyface” characteristics (round face, big eyes, small nose), this is true even for animals. These findings are consistent with the studies of Langner et al. (2010) that argue that important aspects of face processing are symmetry, distinction between female and male and “babyface” traits. We also think is important to have in our game photorealistic characters because children with ASD need more verbal and contextual clues to recognize emotions (Kuusikko et al., 2009). Study 2: we achieved validation of the character “Monkey”, all facial expressions were recognised by the majority of children. It is important to validate characters used in the game as these will work as best models for players. Study 3: validation of human faces used in the game is crucial to avoid misreadings. Children recognize best the pictures of other children, suggesting that in the game we must include pictures of children and adult to allow generalization. Additionally, having a validated database for the Portuguese population increases characters 'scientific richness and can be a useful resource for other studies. 3. 3. Results Results - Baron-Cohen, S., Golan, O., Wheelwrights, S. & Hill, J. (2004). Mindreading: The interactive guide to emotions. London: Jessica Kingsley. - Kuusikko, S., Haapsamo, H., Jansson-Verkasalo, E., Hurtig, T., Mattila, M.L, & Moilanen, I. (2009). Emotion recognition in children and adolescents with Autism Spectrum Disorders. Journal of Autism and Developmental Disorders, 39 (6), 938-45. - Langner, O., Dotsch, R., Bijlstra, G., Wigboldus, D.H., Hawk, S.T., & Van Knippenberg, A. (2010). Presentation and validation of the Radboud Faces Database. Cognition and Emotion, 24 (8), 1377-1388. Copyright © Shutterstock 1 Laboratório de Reabilitação Psicossocial (FPCEUP / ESTSP), Portugal 2Faculdade de Psicologia e de Ciências da Educação da Universidade do Porto (FPCEUP), Portugal 3 Escola Superior de Tecnologia da Saúde do Porto – Instituto Politécnico do Porto (ESTSP), Portugal 4 Faculdade de Ciências da Universidade do Porto (FCUP), Portugal 5Porto Interactive Center (PIC), Portugal 6 Instituto de Telecomunicações (IT), Portugal [email protected] [email protected] [email protected] Cristina Queirós1,2 Samanta Alves1,2, António Marques1,3 , Mónica Oliveira1,2 & Verónica Orvalho4, 5, 6 Facial Expressions Result s (%) Image Best Recognized Happiness 99% Neutral 91% Sadness 85% Anger 83% Disgust 80% Surprise 78% Fear 68% Worst Recognised Facial Expressions Results (%) BestModel Children (male/female) Results (%) BestModel Adults (male/female) Happiness 99.7% 100% Sadness 92.6% 90.6% Anger 86.5% 91.2% Disgust 89.9% 83.1% Surprise 94.5% 96.8% Fear 87.6% 83.7% *Note: Red frame for the best models of female and male child and adult Copyright © LIFEisGAME Copyright © Radbound Database Study 1 – Characters´ Preferences Participants: Random sample of 383 children -(Porto and V.N.Gaia EB 1 schools); ages between 7-13 (M=10.1, SD=1.65); 50% male; 50% female; 2ºyear -13%, 3º year-16%, 4ºyear-8%, 5ºyear29% and 6ºyear-33% . Instruments: Sociodemographic questionnaire; characters´questionnaire. Stimuli: 36 Power Point (PPT) slides with images of different characters according to format (photorealistic, 2D simple cartoon, 3D complex cartoon), type (adult, child or animal) and familiarity (known or unknown) Procedure: Inter-judge stimuli selection. Data collected in 2011, during school time, school and parental consent; selfadministered (confidential and anonymous) characters´ preference questionnaire . Data Analysis: SPSS-17 for descriptive analysis and Chisquare test . Study 2 – “Monkey” Facial Expressions Validation Participants : Random sample of 102 children -(Porto, EB 1 Cabanas´ school); ages between 6 -10 (M=8,57, SD=0,939); 40% male; 60% female; 2ºyear - 21%, 3º year-24%, 4ºyear55%. Instruments: Sociodemographic questionnaire and facial expressions questionnaire Stímuli: 12 PPT slides of character “Monkey” facial expressions (6 basic emotions) Procedure: PPT random presentation of 6 basic emotions (twice per emotion). Data collected in 2012, during school time, after school and parental consent. Self-administered (confidential and anonymous) Monkey´s facial expressions questionnaire. Data Analysis: SPSS-17 for descriptive and frequency analysis. Study 3Portuguese Validation of Radboud Database Participants: Random sample of 410 children -(Porto and V.N.Gaia EB 1 and EB 2/3 schools); ages between 6-14 (M=10.21, SD=1.698); 50% male; 50% female; 2ºyear -13%, 3º year-16%, 4ºyear-7%, 5ºyear32% and 6ºyear-32% . Instruments: Sociodemographic questionnaire and facial expressions questionnaire Stimuli: 12 photos of children and 12 adults from Radbound Database presented in a PPT format expressing the 6 basic emotions. Procedure: Inter-judge stimuli selection of best 2 models (children-male and female; adult-male and female). Data collected in 2012/2013, during school time, after school and parental consent. Self-administered (confidential and anonymous) facial expressions questionnaire. Data Analysis: SPSS-17 for descriptive and frequency analysis.