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Objectives: Climate change (CC) is of major importance for physicians as they are directly confronted with changing disease patterns, work in a greenhouse gas intensive sector and can be potential advocates for healthy people on a healthy planet. Methods: We assessed third to fifth year medical students’ needs to support the integration of CC topics into medical curricula. A questionnaire with 54 single choice-based items was newly designed with the following sections: role perception, knowledge test, learning needs, preference of educational strategies and demographic characteristics. It was administered online to students at Heidelberg medical faculty. Data sets were used for descriptive statistics and regression modelling. Results: 72.4% of students (N=170, 56.2% female, 76% aged 20-24 years) (strongly) agreed that physicians carry a responsibility to address CC in their work setting while only 4.7% (strongly) agreed that their current medical training had given them enough skills to do so. Knowledge was high in the area of CC, health impacts of CC, vulnerabilities and adaptation (70.1% correct answers). Knowledge gaps were greatest for health co-benefits and climate-friendly healthcare (55.5% and 16.7% of correct answers, respectively). 79.4% wanted to see CC and health included in the medical curriculum with a preference for integration into existing mandatory courses. A multilinear regression model with factors age, gender, semester, aspired work setting, political leaning, role perception and knowledge explained 45.9% of variance for learning needs. Conclusion: The presented results encourage the integration of CC and health topics including health co-benefits and climate-friendly healthcare, as well as respective professional role development into existing mandatory courses of the medical curriculum.

Grammatical knowledge has often been investigated in wug tests, in which participants inflect pseudo-words. It was argued that in inflecting these pseudo-words, speakers apply their knowledge of word formation. However, it remains unclear what exactly this knowledge is and how it is learned. According to one theory, the knowledge is best characterised as abstractions that specify how units are combined. Another theory maintains that it is best characterised by memory-based analogy. In both cases the knowledge is learned by association based on positive evidence alone. In this paper, we model the classification of pseudo-words to Maltese plurals using a shallow neural network trained with an error-driven learning algorithm. We demonstrate that the classifications mirror those of Maltese speakers in a wug test. Our results indicate that speakers rely on gradient knowledge of a relation between the phonetics of whole words and plural classes, which is learned in an error-driven way. [ABSTRACT FROM AUTHOR]

Word-based models of morphology propose that complex words are stored without reference to morphemes. One of the questions that arises is whether information about word forms alone is enough to determine a noun's number from its form. We take up this question by modelling the classification and production of the Maltese noun plural system, using models that do not assume morphemic representations. We use the Tilburg Memory-Based Learner, a computational implementation of exemplar theory and the Naive Discriminative Learner, an implementation of Word and Paradigm, for classification. Both models classify Maltese nouns well. In their current implementations, TiMBL and NDL cannot concatenate sequences of phones that result in word forms. We used two neural networks architectures (LSTM and GRU) to model the production of plurals. We conclude that the Maltese noun plural system can be modelled on the basis of whole words without morphemes, supporting word-based models of morphology. [ABSTRACT FROM AUTHOR]

We investigate the storage and processing of sound and broken plural forms in the Maltese lexicon by means of a cross-modal priming study. The results show no significant differences in reaction time between sound and broken plurals, but indicate a different priming effect for sound than for broken plurals. We argue that the different priming effect is a result of the phonological overlap between sound singulars and their corresponding plurals forms, while broken singulars and their plurals do not share the same phonological structure. Our results support a single-mechanism model of morphological processing in which both frequency of pattern and morphophonological similarity interact. [ABSTRACT FROM AUTHOR]

In Semitic languages, the consonantal root is central to morphology, linking form and meaning. While psycholinguistic studies highlight its importance in language processing, the role of meaning in early lexical access and its representation remain unclear. This study investigates when meaning becomes accessible during the processing of Maltese verb forms, using a computational model based on the Discriminative Lexicon framework. Our model effectively comprehends and produces Maltese verbs, while also predicting response times in a masked auditory priming experiment. Results show that meaning is accessible early in lexical access and becomes more prominent after the target word is fully processed. This suggests that semantic information plays a critical role from the initial stages of lexical access, refining our understanding of real-time language comprehension. Our findings contribute to theories of lexical access and offer valuable insights for designing priming studies in psycholinguistics. Additionally, this study demonstrates the potential of computational models in investigating the relationship between form and meaning in language processing., (© 2024 The Author(s). Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)