The anti-COVID-19 vaccination campaign in the United States provided a significant contribution to the control of the virus spread. Despite the recommendations by public health institutions, vaccine skepticism and hesitancy contributed to low vaccine uptake, thus possibly disrupting the management of preventable diseases associated with the COVID-19 infection. The process that led individuals to accept COVID-19 vaccines required the ability to gather, synthesize, and weigh-up information within a novel, dynamically changing, complex, and ambiguous context. To deal with such complexity, we hypothesized that both the ability of reflection and flexible adaptation played a fundamental role. Based on previous research on cognitive predictors of vaccine refusal, we decided to investigate the combined role of two constructs, namely, problem-solving skills and socio-cognitive polarization (SCP), on vaccine acceptance and uptake. Two-hundred-seventy-seven US participants completed an online survey aimed to measure problem-solving ability, through a rebus puzzles task, and SCP, through a composite measure of absolutist thinking, political conservatism, and xenophobia. Mediation analyses indicated that SCP mediated the association between problem-solving ability and vaccine acceptance, so lower problem-solving abilities associated with higher polarization predicted vaccine rejection. Thus, our findings suggested that low problem-solving skills may represent a risk factor for COVID-19 vaccine refusal, with cognitive and social rigidity playing a crucial role in undermining the anti-COVID-19 vaccine uptake.
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http://dx.doi.org/10.3390/ijerph20031721 | DOI Listing |
Biomed Tech (Berl)
January 2025
College of Ocean, Jiangsu University of Science and Technology, Zhenjiang, China.
Objectives: In recent years, significant progress has been made in the research of gesture recognition using surface electromyography (sEMG) signals based on machine learning and deep learning techniques. The main motivation for sEMG gesture recognition research is to provide more natural, convenient, and personalized human-computer interaction, which makes research in this field have considerable application prospects in rehabilitation technology. However, the existing gesture recognition algorithms still need to be further improved in terms of global feature capture, model computational complexity, and generalizability.
View Article and Find Full Text PDFInnov Aging
December 2024
Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System, Durham, North Carolina, USA.
Background And Objectives: As the population ages there is an increasing need for caregiver training programs, but little is known about how to deliver implementation support for diverse sites in large-scale implementation efforts. External group-based implementation facilitation may be one promising approach. This study's objective is to detail the development and delivery of a pragmatic implementation facilitation approach to support the national rollout of caregiver training, Caregivers FIRST, at over 140 Veterans Health Administration (VHA) sites.
View Article and Find Full Text PDFFront Psychol
January 2025
Department of Early Childhood Education, University of Stavanger, Stavanger, Norway.
This study investigates the role of teacher mediation in facilitating children's communication during problem-solving, play-based coding activities with Kubo, a screen-free coding toy, in Early Childhood Education and Care (ECEC) settings. Following an initial observation involving nine kindergarten teachers and 36 children, a workshop was held to identify elements that teachers considered relevant for facilitating children's use of verbal and non-verbal communication. Key mediation elements, such as multimodal communication, planning, time, humor, and reflective questioning, were identified during the workshop and applied in a subsequent observation with the same participants.
View Article and Find Full Text PDFPeerJ
January 2025
Anesthesiology and Reanimation, Central Clinical Hospital, Baku, Azerbaijan.
Background: Patients who are informed about the causes, pathophysiology, treatment and prevention of a disease are better able to participate in treatment procedures in the event of illness. Artificial intelligence (AI), which has gained popularity in recent years, is defined as the study of algorithms that provide machines with the ability to reason and perform cognitive functions, including object and word recognition, problem solving and decision making. This study aimed to examine the readability, reliability and quality of responses to frequently asked keywords about low back pain (LBP) given by three different AI-based chatbots (ChatGPT, Perplexity and Gemini), which are popular applications in online information presentation today.
View Article and Find Full Text PDFAlzheimers Res Ther
January 2025
Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Sankt Augustin, Germany.
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting millions worldwide, leading to cognitive and functional decline. Early detection and intervention are crucial for enhancing the quality of life of patients and their families. Remote Monitoring Technologies (RMTs) offer a promising solution for early detection by tracking changes in behavioral and cognitive functions, such as memory, language, and problem-solving skills.
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