Introduction: The Boston Naming Test (BNT), a 60-item test of confrontation naming, may be administered either from Item 1 or Item 30, depending on assumptions of performance. If the BNT is administered from Item 30, 29 automatic credits are given for preceding items, allowing identical norms for either administration. We aimed to compare effects of automatic credits.
Method: We compared effects of automatic credits in the Gothenburg Mild Cognitive Impairment Study, first between normal controls (n = 23) and patients (n = 259), and then between the same patients grouped by stage of impairment: subjective cognitive impairment (SCI, n = 75), mild cognitive impairment (MCI, n = 117), or mild dementia (n = 67).
Results: Automatic credits added to all groups. Both administrations from Item 1 and those from Item 30 discriminated between controls (n = 23) and all patients (n = 259), as well as between the above stages of impairment. However, neither administration discriminated between normal controls and SCI patients. When earned scores were compared, with scores counted from Item 30 plus 29 automatic credits, mild dementia patients on average received a 3.4-credit boost. This equals 82% of the standard deviation of Tallberg's Swedish norms [Brain and Language, 94(1), 19-31 (2005)] or 117% of our normal controls' standard deviation.
Conclusions: In our homogenous material, administration of BNT from Item 30 distinguished between stages of deterioration as well as administration from Item 1. In line with recent literature, we also find BNT results skewed. Thus, for clinical accuracy, we recommend use of cumulative percentages, careful consideration of education and demographic factors, and, most importantly, never to mix forms of administrations with and without automatic credits. While BNT automatic credits diminish accuracy on all levels, they inflate scores significantly for nonaphasic mild dementia patients.
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http://dx.doi.org/10.1080/13803395.2015.1119254 | DOI Listing |
Sci Robot
December 2024
Department of Physics, University of Konstanz, Universitaetsstrasse 10, Konstanz, 78464, Germany.
Swarm robots offer fascinating opportunities to perform complex tasks beyond the capabilities of individual machines. Just as a swarm of ants collectively moves large objects, similar functions can emerge within a group of robots through individual strategies based on local sensing. However, realizing collective functions with individually controlled microrobots is particularly challenging because of their micrometer size, large number of degrees of freedom, strong thermal noise relative to the propulsion speed, and complex physical coupling between neighboring microrobots.
View Article and Find Full Text PDFHeliyon
October 2024
School of Economics and Management, Tsinghua University, Beijing, 100084, China.
This paper aims to provide new avenues for innovation in credit governance in the digital economy to provide more reliable credit evaluation solutions for financial, commercial, and social interactions. This paper integrates the potential value of Internet of Things (IoT) technology in credit governance and proposes a credit governance method that utilizes IoT data and an improved Long Short-Term Memory model. The proposed model introduces an adaptive mechanism to monitor changes in data in real-time and automatically adjust network parameters to improve the model performance.
View Article and Find Full Text PDFBMC Public Health
November 2024
Department of Family Medicine and Community Health, University of Minnesota, 717 Delaware St. SE, Minneapolis, MN, 55445, USA.
Background: Economic stability is a core social determinant of health and a necessary condition for maintaining food security, housing stability, and both physical and mental health. Using a qualitative approach, we identified barriers, facilitators, and participant perceptions about utilizing these relief measures. This study aimed to understand experiences with COVID-19 economic relief measures among low-wage worker households with children during the COVID-19 pandemic.
View Article and Find Full Text PDFbioRxiv
January 2025
Department of Psychological and Brain Sciences, Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD.
Mesolimbic dopamine (DA) neurons are central to sequence learning and habit formation. Yet, the mechanisms by which cue-induced DA neural activity drives goal-directed or habitual sequence execution remain unknown. We designed two novel tasks to investigate how sequence initiation and termination cues influence DA-driven behavioral strategies and learning.
View Article and Find Full Text PDFEntropy (Basel)
October 2024
School of Finance, Central University of Finance and Economics, Beijing 102206, China.
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