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- The interplay of personality traits and early life experiences in predicting delinquent behaviorsPublication . Bonfá-Araujo, Bruno; Baptista, Makilim Nunes; Pechorro, Pedro; Maroco, João; Franco, Víthor Rosa; Nunes, Cristina; Jonason, Peter K.This study explores the interplay between family bonds, attachment styles, emotional regulation, dark personality traits, and delinquent behaviors. We assessed 336 Brazilians (M = 24.61, SD = 8.30), using network analysis. Participants were assessed using the Proposed Specifiers for Conduct Disorder, Parental Bonding Instrument, Difficulties in Emotion Regulation Scale, The Brazilian Adult Attachment Scale, The Short Dark Tetrad, and the Self-Report Delinquency Scale. Our findings suggest that attachment and family bonds influence emotional regulation, affecting delinquent behaviors. Dark personality traits are strong predictors of delinquent behaviors. We highlight the importance of early life experiences and personality in understanding delinquent and antisocial behaviors.
- Development and psychometric validation of an app-integrated questionnaire to assess healthy habits in children (Ages 8–11): implications for pediatric nursing practicePublication . Merino-Godoy, María Ángeles; Yot-Domínguez, Carmen; Conde-Jiménez, Jesús; Costa, Emília IsabelIntroduction: Promoting healthy habits in childhood is fundamental for fostering long-term well-being. This study aimed to develop and psychometrically validate an app-integrated instrument to assess knowledge, habits, and attitudes related to health in children aged 8–11, within the context of the MHealth intervention Healthy Jeart. Methods: A quantitative, cross-sectional design was used. An initial item pool underwent expert content validation before being administered to a sample of 623 children from primary education centers in Andalusia, Spain. Construct validity was examined through exploratory and confirmatory factor analyses. Results: The analyses supported a coherent four-factor structure comprising 21 items: (1) Use of technologies, (2) diet and growth, (3) psychological well-being, and (4) physical activity and well-being. The instrument demonstrated satisfactory model fit and internal consistency, providing a multidimensional assessment of children’s health-related behaviors. The sample was recruited from primary schools in Andalusia (Spain), which may limit the generalizability of the findings to other regions and cultural contexts. Conclusions: The validated instrument offers a reliable and efficient means of evaluating healthy habits in children aged 8–11, particularly when embedded within digital interventions such as Healthy Jeart. It represents a valuable tool for educators and pediatric nursing professionals working in school settings, enabling early identification of gaps in health literacy and supporting targeted interventions that promote holistic child well-being.
- Coupling geometric morphometrics and machine learning for mandibular sex estimation in late pleistocene and late modern populationsPublication . Godinho, Ricardo Miguel; Crevecoeur, Isabelle; Garcia, Susana; Whiting, Rebecca; Aramendi, JuliaAccurate sex estimation is crucial for studying both modern and ancient human populations, yet methods are often limited to well-preserved skeletons. Here, we combine Geometric Morphometrics (GM) and Machine Learning (ML) to assess mandibular sexual dimorphism and classify sex across a wide chronological and geographic range to bracket the potential of this approach. Sixty-seven individuals from the modern, identified Luis Lopes collection (Portugal) and 18 Late Pleistocene individuals from Jebel Sahaba (Sudan) were surface scanned. Anatomical landmark coordinates were extracted and analyzed with GM, and ML models were trained on a subset of the modern sample to predict sex in both the remaining modern individuals and the Late Pleistocene specimens. GM revealed significant sexual dimorphism in all samples, and ML achieved high intrapopulation classification accuracy. However, predictions were less reliable when applied across the temporally and geographically distant Jebel Sahaba population, reflecting interpopulation differences in mandibular size and shape. These results demonstrate that while GM-ML approaches are powerful tools for sex estimation within populations, caution is required when extending models to other populations.