Self-directed learning

BACKGROUND: Subjective cognitive concerns (SCCs) entail perceived difficulties in thinking or memory, often reported without substantial objective evidence of cognitive impairment. These concerns are prevalent among individuals with a history of brain injuries, neurological conditions, or chronic illnesses, contributing to both psychological distress and functional limitations. They are increasingly considered to be a risk factor for future objective decline. A considerable number of individuals reporting SCCs also exhibit mental health symptoms, such as a history of trauma, depression, or anxiety...

The purpose of this work is to analyze how new technologies can enhance clinical practice while also examining the physical traits of emotional expressiveness of face expression in a number of psychiatric illnesses. Hence, in this work, an automatic facial expression recognition system has been proposed that analyzes static, sequential, or video facial images from medical healthcare data to detect emotions in people's facial regions. The proposed method has been implemented in five steps. The first step is image preprocessing, where a facial region of interest has been segmented from the input image...

OBJECTIVE: As societies become more complex, disasters are increasing in frequency and magnitude. To respond to the psychological problems that may arise in such situations, it is necessary to develop the psychological first aid (PFA) training program that is more engaging for disaster relief workers and less limited in time and space. This study aimed to investigate the effectiveness of a web-based PFA simulation game for disaster relief workers to provide to fire disaster victims. METHODS: This was a non-randomized controlled experimental study with 30 participants in the experimental and control groups...

This study is the first to apply the theoretical principles of Malcolm Knowles' theory of andragogy to evaluate data collected from learners who participated in team science training workshops in a biomedical research setting. Briefly, andragogy includes six principles: the learner's self-concept, the role of experience, readiness to learn, orientation to learning, the learner's need to know, and intrinsic motivation. Using an embedded study design, the primary focus was on qualitative data, with quantitative data complementing the qualitative findings...

BACKGROUND: In medical imaging courses, due to the complexity of anatomical relationships, limited number of practical course hours and instructors, how to improve the teaching quality of practical skills and self-directed learning ability has always been a challenge for higher medical education. Artificial intelligence-assisted diagnostic (AISD) software based on volume data reconstruction (VDR) technique is gradually entering radiology. It converts two-dimensional images into three-dimensional images, and AI can assist in image diagnosis...

BACKGROUND AND PURPOSE: To investigate final-year student pharmacists' experiences of a new module for North American Pharmacist Licensure Examination® (NAPLEX®) preparation at one college of pharmacy in the United States. EDUCATIONAL ACTIVITY AND SETTING: All student pharmacists enrolled in a new Spring 2023 module for NAPLEX preparation (n = 118) were invited to complete an electronic questionnaire and participate in a semi-structured interview...

While colleges and universities grapple with delivering instruction face-to-face during the pandemic, there is still a lot to learn from remote teaching experiences. The present study aimed to predict self-reported learning during the first year of the pandemic. Building on previous scholarship on the topic, we focus on the moderating effects of self-efficacy, and the mediating effects of coping styles on the relationship between stress and self-reported learning experiences. We also included self-perceptions of class effort, the instructor, and changes in class, personal, professor, and health behaviors...

The gyrus, a pivotal cortical folding pattern, is essential for integrating brain structure-function. This study focuses on 2-Hinge and 3-Hinge folds, characterized by the gyral convergence from various directions. Existing voxel-level studies may not adequately capture the precise spatial relationships within cortical folding patterns, especially when relying solely on local cortical characteristics due to their variable shapes and homogeneous frequency-specific features. To overcome these challenges, we introduced a novel model that combines spatial distribution, morphological structure, and functional magnetic resonance imaging data...

Accurate and expeditious segmentation of stroke lesions can greatly assist physicians in making accurate medical diagnoses and administering timely treatments. However, there are two limitations to the current deep learning methods. On the one hand, the attention structure utilizes only local features, which misleads the subsequent segmentation; on the other hand, simple downsampling compromises task-relevant detailed semantic information. To address these challenges, we propose a novel feature refinement and protection network (FRPNet) for stroke lesion segmentation...

Self-supervised learning (SSL) has recently achieved impressive performance on various time series tasks. The most prominent advantage of SSL is that it reduces the dependence on labeled data. Based on the pre-training and fine-tuning strategy, even a small amount of labeled data can achieve high performance. Compared with many published self-supervised surveys on computer vision and natural language processing, a comprehensive survey for time series SSL is still missing. To fill this gap, we review current state-of-the-art SSL methods for time series data in this article...

Single image super-resolution (SISR) aims to reconstruct a high-resolution image from its low-resolution observation. Recent deep learning-based SISR models show high performance at the expense of increased computational costs, limiting their use in resource-constrained environments. As a promising solution for computationally efficient network design, network quantization has been extensively studied. However, existing quantization methods developed for SISR have yet to effectively exploit image self-similarity, which is a new direction for exploration in this study...

PURPOSE: The standard of care for prostate cancer (PCa) diagnosis is the histopathological analysis of tissue samples obtained via transrectal ultrasound (TRUS) guided biopsy. Models built with deep neural networks (DNNs) hold the potential for direct PCa detection from TRUS, which allows targeted biopsy and subsequently enhances outcomes. Yet, there are ongoing challenges with training robust models, stemming from issues such as noisy labels, out-of-distribution (OOD) data, and limited labeled data...

Although researchers actively study women's experiences in STEM fields, few do so from women's perspective. We thematically analyzed life narrative semi-structured interview data (46-item open-ended instrument, 90-120 Min) from eight STEM pioneering Saudi Arabian women careerists (mathematics, medicine, and biology) (convenience sample summer 2023). The objective was to glean their insights to discern self-reported influences (internal and external), struggles, and challenges in launching and advancing their careers...

BACKGROUND: UK policy for complex and long-term health conditions including dementia has recommended that specialist nursing intervention is offered across the trajectory of the condition, but there is a lack of agreement regarding the skills and competencies that specialist nurses are expected to possess. Admiral Nurses are the largest UK group of specialist dementia nurses. OBJECTIVE: To explore how Admiral Nurses met and were supported to meet competencies as defined in the Admiral Nurse Competency Framework, and to develop and maintain skills as dementia specialists...

With the rapid development of artificial intelligence and data science, Dynamic Bayesian Network (DBN), as an effective probabilistic graphical model, has been widely used in many engineering fields. And swarm intelligence algorithm is an optimization algorithm based on natural selection with the characteristics of distributed, self-organization and robustness. By applying the high-performance swarm intelligence algorithm to DBN structure learning, we can fully utilize the algorithm's global search capability to effectively process time-based data, improve the efficiency of network generation and the accuracy of network structure...

BACKGROUND: Systematic ways to teach health advocacy, an educational outcome for pharmacy graduates, is lacking. We developed a workshop to facilitate understanding and application of a novel structured framework for health advocacy and explored how pharmacy students enacted opportunities for health advocacy during subsequent outpatient experiential training. EDUCATIONAL ACTIVITY AND SETTING: A two-hour workshop was introduced for year 2 students in 2019. Its content was organized around a health advocacy framework...

AIM: This study was conducted to evaluate the effect of the flipped learning model on nursing students' asepsis knowledge and learning skills. BACKGROUND: The flipped learning model enables students to pursue their learning with online support whenever and wherever they want. Students have the responsibility for their learning activities. The flipped learning model is an effective method to improve nursing students' knowledge and skills related to the principles of asepsis with online innovative approaches...

BACKGROUND: Large language models (LLMs) hold potential for mental health applications. However, their opaque alignment processes may embed biases that shape problematic perspectives. Evaluating the values embedded within LLMs that guide their decision-making have ethical importance. Schwartz's theory of basic values (STBV) provides a framework for quantifying cultural value orientations and has shown utility for examining values in mental health contexts, including cultural, diagnostic, and therapist-client dynamics...

Background: The timely initiation of extracorporeal membrane oxygenation (ECMO) is crucial for providing life support. However, delays can occur when perfusionists are not readily available. The Jena Method aims to address this issue by offering a wet-primed ECMO system that can be rapidly established without the perfusionist's presence. Methods: The goal was to ensure prompt ECMO initiation while maintaining patient safety. The method focuses on meeting hygienic standards, safe primed storage of the circuit, staff training, and providing clear step-by-step instructions for the ECMO unit...

ConspectusThe COVID-19 pandemic further demonstrated the need for usable, reliable, and cost-effective point-of-care diagnostics that can be broadly deployed, ideally for self-testing at home. Antigen tests using more-detectable reporter labels (usually at the cost of reader complexity) achieve better diagnostic sensitivity, supporting the value of higher-analytical-sensitivity reporter technologies in lateral flow.We developed a new approach to simple, inexpensive lateral flow assays (LFAs) of great sensitivity, based on the glow stick peroxyoxalate chemistry widely used in emergency settings and in children's toys...