In this study, we investigated explicit and implicit endorsement of prescriptive age stereotypes. To achieve that, we captured endorsement of a wide range of prescriptive expectations targeting both younger and older people. Younger and older adults participated in the study. We assessed implicit endorsement of prescriptive age stereotypes with the Propositional Evaluation Paradigm and used a direct measure to assess explicit endorsement. In general, we found strong support for age-specificity in both explicit and implicit endorsement of prescriptive age stereotypes: Sentences (...) ascribing expectations for young/old to the respective age group were endorsed much more strongly than sentences in which expectations for young/old were ascribed to the other age group. Age group differences in the endorsement of prescriptive age stereotypes were found. Compared to younger participants, older participants showed stronger endorsement for prescriptive beliefs targeting both younger and older targets. Explicit and implicit endorsement of prescriptive age stereotypes did not correlate with one another, thus revealing they might assess independent belief systems with different predictive potential. (shrink)

BackgroundBilateral cerebral palsy is the most common type of CP in children and is often accompanied by different degrees of communication impairment. Several studies have attempted to identify children at high risk for communication impairment. However, most prediction factors are qualitative and subjective and may be influenced by rater bias. Individualized objective diagnostic and/or prediction methods are still lacking, and an effective method is urgently needed to guide clinical diagnosis and treatment. The aim of this study is to develop and (...) validate an objective, individual-based model for the prediction of communication impairment in children with BCP by the time they enter school.MethodsA multicenter prospective cohort study will be conducted in four Chinese hospitals. A total of 178 children with BCP will undergo advanced brain magnetic resonance imaging at baseline. At school entry, communication performance will be assessed by a communication function classification system. Three-quarters of children with BCP will be allocated as a training cohort, whereas the remaining children will be allocated as a test cohort. Multivariate lesion- and connectome-based approaches, which have shown good predictive ability of language performance in stroke patients, will be applied to extract features from MR images for each child with BCP. Multiple machine learning models using extracted features to predict communication impairment for each child with BCP will be constructed using data from the training cohort and externally validated using data from the test cohort. Prediction accuracy across models in the test cohort will be statistically compared.DiscussionThe findings of the study may lead to the development of several translational tools that can individually predict communication impairment in children newly diagnosed with BCP to ensure that these children receive early, targeted therapeutic intervention before they begin school.Trial registrationThe study has been registered with the Chinese Clinical Trial Registry. (shrink)