In the current study, we investigated how long the effects of one single collaboration session continue to influence individual memory. Participants learned categorized word lists and prose passages individually, and then they were instructed to recall learned materials either collaboratively or individually. Following initial recall, participants completed an individual recall test after a delay of 5 min, 48 h, or 1 week. On the initial recall test, we found that collaboration reduced recall of correct items on both word lists and prose passages (collaborative inhibition), and that collaboration reduced false recall on both word lists and prose passages (error correction). However, on the subsequent individual memory test after a delay, the pattern of post collaborative effects differed across veridical and false recall. For both word lists and prose passages, post collaborative benefits on correct recall lasted 1 week. However, there were no lasting effects of error correction on subsequent false recall. These results suggest that the time course of post collaborative benefits can be long lasting, but they are selective to veridical recall. The results are explained by theories of reexposure and error correction.
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http://dx.doi.org/10.3758/s13421-024-01609-5 | DOI Listing |
Behav Res Methods
December 2024
ETSI de Telecomunicación, Universidad Politécnica de Madrid, Avenida Complutense, 30, 28040, Madrid, Spain.
This study investigates the potential of large language models (LLMs) to estimate the familiarity of words and multi-word expressions (MWEs). We validated LLM estimates for isolated words using existing human familiarity ratings and found strong correlations. LLM familiarity estimates performed even better in predicting lexical decision and naming performance in megastudies than the best available word frequency measures.
View Article and Find Full Text PDFJ Am Med Inform Assoc
December 2024
Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, United States.
Objective: To detect and classify features of stigmatizing and biased language in intensive care electronic health records (EHRs) using natural language processing techniques.
Materials And Methods: We first created a lexicon and regular expression lists from literature-driven stem words for linguistic features of stigmatizing patient labels, doubt markers, and scare quotes within EHRs. The lexicon was further extended using Word2Vec and GPT 3.
Neuropsychol Rev
December 2024
Laboratory of Neuropsychology of Memory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Via Ardeatina 306, 00179, Rome, Italy.
To date, few studies have focused on the benefits of dopaminergic treatment on episodic memory functions in patients affected by Parkinson's disease (PD). We conducted a meta-analysis to determine the effects of pharmacological therapy with dopamine in alleviating episodic memory deficits in Parkinson's patients. A secondary aim was to evaluate the role of dopamine in episodic memory circuits and thus in different memory systems.
View Article and Find Full Text PDFDiagnostics (Basel)
November 2024
Department of Medical Rehabilitation Sciences, College of Applied Medical Sciences, King Khalid University, Abha 61481, Saudi Arabia.
Background/objectives: The present study investigates the reasons for better recognition of disyllabic words in Malayalam among individuals with hearing loss. This research was conducted in three experiments. Experiment 1 measured the psychometric properties (slope, intercept, and maximum scores) of disyllabic wordlists.
View Article and Find Full Text PDFJ Grad Med Educ
December 2024
is Professor of Surgery and Director of Planetary Health Faculty of Medicine, University of Ottawa, and Clinical Investigator, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
As future health care leaders who work and train in diverse clinical settings, resident physicians are uniquely positioned to advance sustainable health care systems. However, residents are insufficiently educated about health care sustainability and given limited opportunities to engage in planetary health. This article introduces and reports on the early outcomes of the Trainee-Led Research and Audit for Sustainability in Healthcare Canada (TRASH-CAN), a resident-driven initiative launched in 2023 with the aim of reducing Canadian health care's environmental impact.
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