This paper examines how innovative skills and knowledge are transmitted and acquired among adolescents in two hunter-gatherer communities, the Aka of southern Central African Republic and the Chabu of southwestern Ethiopia. Modes of transmission and processes of social learning are addressed. Innovation as well as social learning have been hypothesized to be key features of human cumulative culture, enhancing the fitness and survival of individuals in diverse environments. The innovation literature indicates adult males are more innovative than children and female adults and therefore predicts that adolescents will seek out adult males. Further, the mode of transmission should be oblique (i.e., learning from adults other than parents). Thus, learning of innovations should be oblique or horizontal rather than vertical, with adolescents paying particular attention to "successful" innovative individuals (prestige bias). The social learning literature indicates that complex skills or knowledge is likely to be learned through teaching, and therefore that teaching will be an important process in the transmission of innovations. In-depth and semi-structured interviews, informal observations, and systematic free-listing were used to evaluate these hypotheses. The study found that (1) cultural context patterned whether or not adolescents sought out adult male or female innovators; (2) oblique modes of transmission were mentioned with greater frequency than horizontal or vertical modes; (3) knowledge and skill bias was notable and explicitly linked by the adolescents to reproductive effort; and (4) teaching was biased toward same-sex individuals and was an important but not an exclusive means of transmitting complex skills and social knowledge.
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http://dx.doi.org/10.1007/s12110-021-09391-y | DOI Listing |
J Adolesc Health
January 2025
The National Alliance to Advance Adolescent Health/Got Transition, Washington, D.C.
Purpose: There is a paucity of evidence examining clinician experiences with structured health-care transition (HCT) programs. Among HCT Learning Collaborative participants, this study describes clinician experiences with implementation of a structured HCT process: Got Transition's 6 Core Elements.
Methods: Representative members from 6 health systems designed a survey to collect clinician feedback regarding HCT and demographic and practice information.
BMC Public Health
January 2025
Statistics, Brigham Young University, Provo, 84602, Utah, USA.
Background: Bullying, encompassing physical, psychological, social, or educational harm, affects approximately 1 in 20 United States teens aged 12-18. The prevalence and impact of bullying, including online bullying, necessitate a deeper understanding of risk and protective factors to enhance prevention efforts. This study investigated the key risk and protective factors most highly associated with adolescent bullying victimization.
View Article and Find Full Text PDFSci Rep
January 2025
College of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, 321004, China.
Athlete engagement is influenced by several factors, including cohesion, passion and mental toughness. Machine learning methods are frequently employed to construct predictive models as a result of their high efficiency. In order to comprehend the effects of cohesion, passion and mental toughness on athlete engagement, this study utilizes the relevant methods of machine learning to construct a prediction model, so as to find the intrinsic connection between them.
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January 2025
Department of Psychology, Faculty of Behavioural and Social Sciences, University of Groningen, Grote Kruisstraat 2/1, 9712TS, Groningen, The Netherlands.
Recruits are exposed to high levels of psychological and physical stress during the special forces selection period, resulting in dropout rates of up to 80%. To identify who likely drops out, we assessed a group of 249 recruits, every week of the selection program, on their self-efficacy, motivation, experienced psychological and physical stress, and recovery. Using linear regression as well as state-of-the-art machine learning techniques, we aimed to build a model that could meaningfully predict dropout while remaining interpretable.
View Article and Find Full Text PDFTransl Psychiatry
January 2025
Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Background: Alcohol use disorder (AUD) is associated with deficits in social cognition and behavior, but why these deficits are acquired is unknown. We hypothesized that a reduced association between actions and outcomes for others, i.e.
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