98%
921
2 minutes
20
Previous studies have shown that values are developed during young adulthood. This study investigated whether and when developmental trajectories of values depend on gender, language region, cognitive competence, expected education duration, and ambition. Longitudinal data of 2620 adolescents in Switzerland were collected at eight waves of measurement over 10 years. Latent growth model analysis revealed that work values mainly increase between ages 16 and 20, whereas family values primarily increase after age 20. This pattern fits the major life and career roles sequence: Becoming established in one's career comes first, and focusing on family building follows later. The initial levels and development of values were essentially affected by gender, but other individual factors such as cognitive competence, expected education duration, and ambition also showed some effect, particularly on family values. These new insights into the development of values improve the understanding of the career decisions and career behavior of adolescents.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.adolescence.2015.03.013 | DOI Listing |
J Med Internet Res
September 2025
School of Advertising, Marketing and Public Relations, Faculty of Business and Law, Queensland University of Technology, Brisbane, Australia.
Background: Labor shortages in health care pose significant challenges to sustaining high-quality care for people with intellectual disabilities. Social robots show promise in supporting both people with intellectual disabilities and their health care professionals; yet, few are fully developed and embedded in productive care environments. Implementation of such technologies is inherently complex, requiring careful examination of facilitators and barriers influencing sustained use.
View Article and Find Full Text PDFPLoS Comput Biol
September 2025
Faculty of Science, Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands.
Predictive coding (PC) proposes that our brains work as an inference machine, generating an internal model of the world and minimizing predictions errors (i.e., differences between external sensory evidence and internal prediction signals).
View Article and Find Full Text PDFPLoS Med
September 2025
Perinatal Epidemiology Group, Department of Obstetrics, Gynaecology, and Newborn Health, University of Melbourne, Melbourne, Victoria, Australia.
Background: Hypertensive disorders of pregnancy may be associated with an increased risk of adverse neurodevelopmental outcomes for the child, though no recent comprehensive meta-analyses exist. The aim of this study was to conduct a systematic review and meta-analysis examining the association between hypertensive disorders of pregnancy and child neurodevelopmental disabilities, intelligence, and educational outcomes.
Methods And Findings: A search was conducted of MEDLINE, CINAHL, Web of Science, and PsycINFO databases from inception until 18 September 2024.
PLoS One
September 2025
Seidenberg School of Computer Science and Information Systems, Pace University, New York, New York, United States of America.
While there has been extensive research on techniques for explainable artificial intelligence (XAI) to enhance AI recommendations, the metacognitive processes in interacting with AI explanations remain underexplored. This study examines how AI explanations impact human decision-making by leveraging cognitive mechanisms that evaluate the accuracy of AI recommendations. We conducted a large-scale experiment (N = 4,302) on Amazon Mechanical Turk (AMT), where participants classified radiology reports as normal or abnormal.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Engineering and School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Citizen science engages volunteers to contribute data to scientific projects, often through visual annotation tasks. Hearing based activities are rare and less well understood. Having high quality annotations of performed music structures is essential for reliable algorithmic analysis of recorded music with applications ranging from music information retrieval to music therapy.
View Article and Find Full Text PDF