Ngoc Tran

Parametric cognitive models are increasingly popular tools for analyzing data obtained from psychological experiments. One of the main goals of such models is to formalize psychological theories using parameters that represent distinct psychological processes. We argue that systematic quantitative reviews of parameter estimates can make an important contribution to robust and cumulative cognitive modeling. Parameter reviews can benefit model development and model assessment by providing valuable information about the expected parameter space, and can facilitate the more efficient design of experiments. Importantly, parameter reviews provide crucial—if not indispensable—information for the specification of informative prior distributions in Bayesian cognitive modeling. From the Bayesian perspective, prior distributions are an integral part of a model, reflecting cumulative theoretical knowledge about plausible values of the model's parameters (Lee,2018). In this paper we illustrate how systematic parameter reviews can be implemented to generate informed prior distributions for the Diffusion Decision Model (DDM; Ratcliff and McKoon,2008), the most widely used model of speeded decision making. We surveyed the published literature on empirical applications of the DDM, extracted the reported parameter estimates, and synthesized this information in the form of prior distributions. Our parameter review establishes a comprehensive reference resource for plausible DDM parameter values in various experimental paradigms that can guide future applications of the model. Based on the challenges we faced during the parameter review, we formulate a set of general and DDM-specific suggestions aiming to increase reproducibility and the information gained from the review process.

In this paper, we explore the effect of musical expertise on whistled word perception by naive listeners. In whistled words of nontonal languages, vowels are transposed to relatively stable pitches, while consonants are translated into pitch movements or interruptions. Previous behavioral studies have demonstrated that naive listeners can categorize isolated consonants, vowels, and words well over chance. Here, we take an interest in the effect of musical experience on words while focusing on specific phonemes within the context of the word. We consider the role of phoneme position and type and compare the way in which these whistled consonants and vowels contribute to word recognition. Musical experience shows a significant and increasing advantage according to the musical level achieved, which, when further specified according to vowels and consonants, shows stronger advantages for vowels over consonants for all participants with musical experience, and advantages for high‐level musicians over nonmusicians for both consonants and vowels. By specifying high‐level musician skill according to one's musical instrument expertise (piano, violin, flute, or singing), and comparing these instrument groups to expert users of whistled speech, we observe instrument‐specific profiles in the answer patterns. The differentiation of such profiles underlines a resounding advantage for expert whistlers, as well as the role of instrument specificity when considering skills transferred from music to speech. These profiles also highlight differences in phoneme correspondence rates due to the context of the word, especially impacting “acute” consonants (/s/ and /t/), and highlighting the robustness of /i/ and /o/.

AimHealthcare workers have directly provided care for COVID-19 patients, and have faced many additional sources leading to poor mental health. The study aimed to investigate the mental health problems and related factors among healthcare staff in Vietnam.MethodsA descriptive cross-sectional mixed methods study, combining quantitative and qualitative research methods, was performed among 400 healthcare workers working at the National Hospital for Tropical Diseases and Ninh Binh General Hospital from the first day of treatment for COVID-19 patients to May 01, 2020.ResultsThe results showed that 8.0% of participants had stress, 17.5% of participants had anxiety, and 14.8% of participants had depression. Approximately 50% of participants reported that they had at least one of these symptoms. The findings illustrated that stress, anxiety, and depression were associated with the position in a hospital, health status during the COVID-19 pandemic, family members/relatives infected with COVID-19, physical and mental support from friends, family, and community, department, years of working, and the average work hours per day of healthcare workers exposed to COVID-19.ConclusionDuring the COVID-19 pandemic, healthcare workers who worked in the hospital providing treatment and care for COVID-19 patients dealt with mental health problems such as stress, anxiety, and depression. It is necessary to promote mental health among healthcare workers, to contribute to the fight against the COVID-19 outbreak in Vietnam.