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Direct linkRey-Guerra, Catalina; Zachrisson, Henrik D.; Dearing, Eric; Berry, Daniel; Kuger, Susanne; Burchinal, Margaret R.; Naerde, Ane; van Huizen, Thomas; Côté, Sylvana M. – Child Development, 2023
Whether high quantities of center-based care cause behavior problems is a controversial question. Studies using covariate adjustment for selection factors have detected relations between center care and behavior problems, but studies with stronger internal validity less often find such evidence. We examined whether within-child changes in hours in…
Descriptors: Child Care Centers, Child Behavior, Behavior Problems, Time
Dagan, Or; Schuengel, Carlo; Verhage, Marije L.; van IJzendoorn, Marinus H.; Sagi-Schwartz, Abraham; Madigan, Sheri; Duschinsky, Robbie; Roisman, Glenn I.; Bernard, Kristin; Bakermans-Kranenburg, Marian; Bureau, Jean-François; Volling, Brenda L.; Wong, Maria S.; Colonnesi, Cristina; Brown, Geoffrey L.; Eiden, Rina D.; Fearon, R. M. Pasco; Oosterman, Mirjam; Aviezer, Ora; Cummings, E Mark – New Directions for Child and Adolescent Development, 2021
An unsettled question in attachment theory and research is the extent to which children's attachment patterns with mothers and fathers "jointly" predict developmental outcomes. In this study, we used individual participant data (IPD) meta-analysis to assess whether early attachment networks with mothers and fathers are associated with…
Descriptors: Attachment Behavior, Parent Child Relationship, Mothers, Fathers
Talbott, Elizabeth; Zurheide, Jaime L.; Karabatsos, George; Kumm, Skip – Behavioral Disorders, 2021
Valid and reliable teacher ratings serve as the foundation for screening and assessment of youth with behavioral disorders and twin studies offer an opportunity to study those ratings. We conducted a meta-analysis of 15 empirical investigations of aggressive and rule-breaking behavior using teacher ratings in the context of a twin research design.…
Descriptors: Student Behavior, Twins, Teacher Attitudes, Predictor Variables
Soni, Alisha; Bakhru, Kanupriya Misra – International Journal of Learning and Change, 2023
Social entrepreneurship is a planned behaviour and rapidly gaining its importance in society. This complex process can be understood by studying intention which is the single best predictor of subsequent behaviour. It helps in understanding the reasons behind the actions undertaken and the manner in which potential entrepreneurs decide and act to…
Descriptors: Entrepreneurship, Behavior Theories, Intention, Predictor Variables
Sánchez-Fernández, Magdalena; Borda-Mas, Mercedes – Education and Information Technologies, 2023
University students are a high-risk population with problematic online behaviours that include generalized problematic Internet/smartphone use and specific problematic Internet uses (for example, social media or gaming). The study of their predictive factors is needed in order to develop preventative strategies. This systematic review aims to…
Descriptors: College Students, Student Behavior, Telecommunications, Handheld Devices
Anjie Cao; Molly Lewis; Sho Tsuji; Christina Bergmann; Alejandrina Cristia; Michael C. Frank – Developmental Science, 2025
Developmental psychology focuses on how psychological constructs change with age. In cognitive development research, however, the specifics of this emergence is often underspecified. Researchers often provisionally assume linear growth by including chronological age as a predictor in regression models. In this work, we aim to evaluate this…
Descriptors: Language Acquisition, Infant Behavior, Age Differences, Developmental Stages
Yuntian Xie; Ying Li; Taowen Yu; Yuxuan Liu – Education and Information Technologies, 2025
This study aimed to develop and validate the Metacognitions about Generative AI Use Scale (MGAUS) to assess college students' metacognitive beliefs about generative AI and to explore these metacognitions as predictors of generative AI addiction risk. A total of 1229 college students from China participated in the study, providing data through an…
Descriptors: Foreign Countries, College Students, Metacognition, Student Attitudes
Eilts, Jule; Koglin, Ute – Emotional & Behavioural Difficulties, 2022
Bullying and victimisation are extremely damaging behaviours that are present in schools all over the world. However, there is little research on the involvement of students with emotional and behavioural disabilities in the bullying dynamic and their risk and protective factors. Following the PRISMA guidelines, the search terms were entered in…
Descriptors: Journal Articles, Developmental Disabilities, Bullying, Victims
Schwinger, Malte; Trautner, Maike; Pütz, Nadine; Fabianek, Salome; Lemmer, Gunnar; Lauermann, Fani; Wirthwein, Linda – Journal of Educational Psychology, 2022
Self-handicapping is a maladaptive strategy that students employ to protect their self-image when they fear or anticipate academic failure. Instead of increasing their effort, students may harm their chances of success by procrastinating, strategically withdrawing effort, or engaging in destructive behaviors like drug abuse, so that potential…
Descriptors: Student Behavior, Self Destructive Behavior, Time Management, Withdrawal (Psychology)
Brianna M. Anderson; Autumn Kozluk; Marie-Chanel M. Morgan; Melissa A. MacDonald; Jonathan E. Friedel; Alison D. Cox – Journal of Behavioral Education, 2024
Previous research evaluating behavior skills training and performance feedback has largely examined factors influencing interventionist performance outcomes. However, to our knowledge, researchers have yet to compile existing literature to specifically explore characteristics associated with improved learner outcomes in the context of…
Descriptors: Intervention, Training, Outcomes of Education, Meta Analysis
Rasha Noureddine; David Boote; Laurie O. Campbell – Education and Information Technologies, 2025
A meta-analytic study was conducted of the "Unified Theory of Acceptance and Use of Technology" to understand higher education instructors use of technology in teaching and learning. Through broad searches of the years 2003-2023, 117 records were identified for initial review. After reviewing the studies and removing those studies that…
Descriptors: College Faculty, Teacher Attitudes, Technological Literacy, Computer Literacy
Sulat, Jaelan Sumo; Prabandari, Yayi Suryo; Sanusi, Rossi; Hapsari, Elsi Dwi; Santoso, Budiono – Health Education, 2018
Purpose: The health belief model (HBM) is the behavioral change theory most widely used in health behavior studies. Several studies have identified the limitations of this model, one of which concerns the validity in predicting behavioral changes. The purpose of this paper, scoping review, is to map the validity of HBM variables in predicting…
Descriptors: Health Behavior, Behavior Change, Predictor Variables, Correlation
Kulkarni, Tara; Sullivan, Amanda L.; Kim, Jiwon – Educational Psychology Review, 2021
Children's low academic skills are associated with a variety of behavior problems and maladaptive outcomes throughout childhood and adulthood. Given the prevalence of behavioral disorders is approximately 19% of all US children, understanding of the mechanisms through which academic achievement and externalizing behavior problems interact can…
Descriptors: Low Achievement, Behavior Problems, Academic Achievement, Correlation
Thornberg, Robert – European Journal of Developmental Psychology, 2023
Moral disengagement (MD) refers to social-cognitive distortions that allow individuals to sidestep the self-regulatory processes that normally prevent immoral conduct. MD has been linked to bullying in childhood and adolescence, but most studies have used a cross-sectional design. Less is known about the longitudinal link. Therefore, the aim of…
Descriptors: Bullying, Moral Values, Self Management, Antisocial Behavior
Hui Shi; Nuodi Zhang; Secil Caskurlu; Hunhui Na – Journal of Computer Assisted Learning, 2025
Background: The growth of online education has provided flexibility and access to a wide range of courses. However, the self-paced and often isolated nature of these courses has been associated with increased dropout and failure rates. Researchers employed machine learning approaches to identify at-risk students, but multiple issues have not been…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, At Risk Students
