Yoxas/statistical_literacy huggingface dataset:
Internet-based cognitive behavioral therapy has shown effectiveness in managing chronic tinnitus. Internet-based cognitive behavioral therapy is currently available in only a few languages (English, Swedish, Spanish, and German). The current study aimed to adapt, evaluate, and compare the readability and acceptability of the Turkish internet-based cognitive behavioral therapy materials compared to previous versions. Internet-based cognitive behavioral therapy materials were adapted from the preexisting American English to the Turkish population in a 4-step process: (1) cultural adaptations, (2) acceptability adaptation of materials to the Turkish-speaking population, and (3) literacy-level adjustments. Experts (n=11) and patients (n=11) rated the intervention materials and the ePlatform for acceptability, including usability, content, presentation, and suitability (4). Literacy-level adjustments generated acceptable and readability levels of the Turkish version of the internet-based cognitive behavioral therapy program. The average readability score was 76.15 ± 0.35. The Turkish internet-based cognitive behavioral therapy (Mdn: 7.00) was statistically lower compared to the Swedish (Mdn: 9.00) but higher when compared to the American English and Spanish (Mdn: 5.00) versions. There were no statistical differences between the British English and Turkish versions in readability scores. Acceptability in the internet-based cognitive behavioral therapy platform was rated favorably. The Turkish internet-based cognitive behavioral therapy was found to be user-friendly and easy to understand, with navigations that are straightforward, have clear information, and are supported by audiologists. The readability score of the Turkish internet-based cognitive behavioral therapy is within recommended limits to ensure comprehensibility. We suggest that an online cognitive behavioral therapy program is adaptable for other languages for countries with a limited number of clinicians focused on cognitive behavioral therapy and tinnitus.
Internet-based Cognitive Behaviour Therapy (iCBT) for depression have been implemented in routine care across Europe in varying ways, at various scales and with varying success. This study aimed to advance our understanding of organisational implementation climate from the perspectives of implementers and mental health service deliverers. Qualitative and quantitative methods were combined to study the concept of organisational implementation climate in mental health care settings. Based on concept mapping, a qualitative workshop with implementers was used to conceptualise organisational implementation climate for optimizing iCBT use in routine practice. Service deliverers involved in the provision of iCBT were invited to participate in an explorative cross-sectional survey assessing levels of satisfaction and usability of iCBT, and organisational implementation climate in implementing iCBT. The two methods were applied independently to study viewpoints of implementers as well as service deliverers. Corresponding to the explorative nature of the study, inductive reasoning was applied to identify patterns and develop a reasonable explanation of the observations made. Correlative associations between satisfaction, usability and implementation climate were explored. Sixteen implementers representing fourteen service delivery organisations across Europe participated in the workshop. The top-three characteristics of a supportive organisational implementation climate included: (1) clear roles and skills of implementers, (2) feasible implementation targets, and (3) a dedicated implementation team. The top-three tools for creating a supportive implementation climate included: (1) feedback on job performance, (2) progress monitoring in achieving implementation targets, and (3) guidelines for assessing the impact of iCBT. The survey (n=111) indicated that service providers generally regarded their organisational implementation climate as supportive in implementing iCBT services. Organisational implementation climate was weakly associated with perceived usability and moderately with satisfaction with iCBT services. Organisational implementation climate is a relevant factor to implementers and service deliverers in implementing iCBT in routine care. It is not only an inherent characteristic of the context in which implementation takes place, it can also be shaped to improve implementation of iCBT services. Future research should further theorise organisational implementation climate and empirically validate the measurement instruments such as used in this study.
Internet-based health education is increasingly vital in patient care. However, the readability of online information often exceeds the average reading level of the US population, limiting accessibility and comprehension. This study investigates the use of chatbot artificial intelligence to improve the readability of cancer-related patient-facing content. We used ChatGPT 4.0 to rewrite content about breast, colon, lung, prostate, and pancreas cancer across 34 websites associated with NCCN Member Institutions. Readability was analyzed using Fry Readability Score, Flesch-Kincaid Grade Level, Gunning Fog Index, and Simple Measure of Gobbledygook. The primary outcome was the mean readability score for the original and artificial intelligence (AI)-generated content. As secondary outcomes, we assessed the accuracy, similarity, and quality using F1 scores, cosine similarity scores, and section 2 of the DISCERN instrument, respectively. The mean readability level across the 34 websites was equivalent to a university freshman level (grade 13±1.5). However, after ChatGPT's intervention, the AI-generated outputs had a mean readability score equivalent to a high school freshman education level (grade 9±0.8). The overall F1 score for the rewritten content was 0.87, the precision score was 0.934, and the recall score was 0.814. Compared with their original counterparts, the AI-rewritten content had a cosine similarity score of 0.915 (95% CI, 0.908-0.922). The improved readability was attributed to simpler words and shorter sentences. The mean DISCERN score of the random sample of AI-generated content was equivalent to "good" (28.5±5), with no significant differences compared with their original counterparts. Our study demonstrates the potential of AI chatbots to improve the readability of patient-facing content while maintaining content quality. The decrease in requisite literacy after AI revision emphasizes the potential of this technology to reduce health care disparities caused by a mismatch between educational resources available to a patient and their health literacy.
Internet-based interventions are recognised as a practical approach to address mental health issues. The acceptance and utilisation of such interventions are closely linked to user attitudes and preferences. This study aims to examine the predictors of university students' attitudes towards internet-based interventions. Additionally, it seeks to elucidate students' preferences regarding crucial features of these interventions, such as the format, delivery mode, content type, and structural components, to understand better what makes these interventions appealing and practical for university students. A total of 273 university students (comprising 68 % females and 32 % males) participated in the study. The data collection instruments employed were the Personal Information Form, Internet-Based Intervention Preference Survey, E-therapy Attitude Measure (ETAM), Digital Literacy Scale, Patient Health Questionnaire-9, and the Generalized Anxiety Disorder-7 (GAD-7). The data were analysed utilising descriptive statistics, Pearson correlation analysis, and multiple linear regression analysis. The multiple regression analysis revealed digital literacy as a predictive factor for attitudes towards internet-based interventions. Demographic variables, such as age and gender, and psychological variables, such as depression and anxiety levels, were found not to be associated with attitudes towards these interventions. While students are actively seeking mental health information online, a significant majority remain unaware of internet-based interventions. They show a preference for interventions offering greater human interaction, including face-to-face guidance and video content featuring people. Participants favour completing one or two sessions of the intervention weekly. Desired features of internet-based interventions include self-assessment scales, relatable characters, voice relaxation exercises, practical daily life activity tasks, and weekly reminders throughout the process. In conclusion, initiatives aimed at enhancing digital literacy levels could foster more positive attitudes towards internet-based interventions among students. Developers creating Internet-Based Interventions (IBI) for university students should consider these preferences.
Interpretability in machine learning has become increasingly important as machine learning is being used in more and more applications, including those with high-stakes consequences such as healthcare where Interpretability has been regarded as a key to the successful adoption of machine learning models. However, using confounding/irrelevant information in making predictions by deep learning models, even the interpretable ones, poses critical challenges to their clinical acceptance. That has recently drawn researchers' attention to issues beyond the mere interpretation of deep learning models. In this paper, we first investigate application of an inherently interpretable prototype-based architecture, known as ProtoPNet, for breast cancer classification in digital pathology and highlight its shortcomings in this application. Then, we propose a new method that uses more medically relevant information and makes more accurate and interpretable predictions. Our method leverages the clustering concept and implicitly increases the number of classes in the training dataset. The proposed method learns more relevant prototypes without any pixel-level annotated data. To have a more holistic assessment, in addition to classification accuracy, we define a new metric for assessing the degree of interpretability based on the comments of a group of skilled pathologists. Experimental results on the BreakHis dataset show that the proposed method effectively improves the classification accuracy and interpretability by respectively 8% and 18% . Therefore, the proposed method can be seen as a step toward implementing interpretable deep learning models for the detection of breast cancer using histopathology images.
Interpretation of the electrocardiogram (ECG) is fundamental in the practice and teaching of emergency medicine. Previous studies have shown that providers of all levels have expressed interest in additional education with ECGs. Asynchronous learning has been shown to be beneficial for improving residents' ability to recognize findings of acute myocardial ischemia. The goal of the study was to know whether a new format based on free, online content would improve residents' ability to interpret ECGs. In this 1-year educational pilot study at a single urban teaching hospital, resident physicians participated in a longitudinal curriculum based on free, online content, which was delivered to them electronically on a weekly basis. The study was conducted during the 2016-2017 academic year. Prior to and after the study period, their subjective attitudes toward ECG interpretation, and their objective ability to interpret them successfully, were assessed. Of 42 residents, 25 (59.5%) completed the pre- and post-ECG testing. During the study period, trainees demonstrated improvement in both their subjective attitude toward ECG interpretation and their objective ability to interpret various abnormalities. Despite some important limitations, we believe this study represents an essential step in the development of training methods for the modern emergency medicine trainee.
Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question answering models apparently can learn to use function words as part of answering questions about complex visual scenes. In this paper, we study what these models learn about function words, in the hope of better understanding how the meanings of these words can be learned by both models and children. We show that recurrent models trained on visually grounded language learn gradient semantics for function words requiring spatial and numerical reasoning. Furthermore, we find that these models can learn the meanings of logical connectives and and or without any prior knowledge of logical reasoning as well as early evidence that they are sensitive to alternative expressions when interpreting language. Finally, we show that word learning difficulty is dependent on the frequency of models' input. Our findings offer proof-of-concept evidence that it is possible to learn the nuanced interpretations of function words in a visually grounded context by using non-symbolic general statistical learning algorithms, without any prior knowledge of linguistic meaning.
Interpreting single-cell chromatin accessibility data is crucial for understanding intercellular heterogeneity regulation. Despite the progress in computational methods for analyzing this data, there is still a lack of a comprehensive analytical framework and a user-friendly online analysis tool. To fill this gap, we developed a pre-trained deep learning-based framework, single-cell auto-correlation transformers (scAuto), to overcome the challenge. Following DNABERT's methodology of pre-training and fine-tuning, scAuto learns a general understanding of DNA sequence's grammar by being pre-trained on unlabeled human genome via self-supervision; it is then transferred to the single-cell chromatin accessibility analysis task of scATAC-seq data for supervised fine-tuning. We extensively validated scAuto on the Buenrostro2018 dataset, demonstrating its superior performance on chromatin accessibility prediction, single-cell clustering, and data denoising. Based on scAuto, we further developed an interactive web server for single-cell chromatin accessibility data analysis. It integrates tutorial-style interfaces for those with limited programming skills. The platform is accessible at http://zhanglab.icaup.cn. To our knowledge, this work is expected to help analyze single-cell chromatin accessibility data and facilitate the development of precision medicine.
Interpretive pedagogy with simulation encourages students to consider multiple perspectives contextually leading students to think deeper in a shared learning environment. Clinical sites were lacking in a senior nursing leadership and management course and necessitated the adaptation of traditional clinical teaching methodologies. Low-fidelity simulation was used as an active learning strategy to fulfill clinical hours. Comparing student groups' pretest mean scores were not significant (p = .610; 95% confidence interval [CI] [-0.95, 0.12]). Comparatively, the student groups' posttest scores ranging between 87% and 90%, respectively, were also not statistical significance (p = .136, 95% CI [-0.95, 0.12]). Students were positive about their experience. They appreciated the opportunity to practice what they learned in the classroom in a safe environment. As a result, simulation in a senior nursing leadership course can be successfully used as an alternative to traditional clinical experiences and fulfill clinical hour requirements.
Interprofessional collaborative practice is essential for meeting patients' needs and improving their health outcomes; thus, the effectiveness of interprofessional education (IPE) should be clearly identified. There is insufficient evidence in the literature to determine the outcomes of IPE compared to traditional single-profession education (SPE). This study aimed to compare the outcomes of IPE and SPE during a simulation training course. The study design was a mixed-methods, incorporated cross-over design and a qualitative survey. A total of 54 students including 18 medical students and 36 nursing students were recruited from March to April 2019. The 4-week simulation course was designed based on Kolb's experimental learning theory and Bandura's social learning theory. Participants were evenly divided into group 1 (received IPE-learning followed by SPE-learning), and group 2 (received SPE-learning followed by IPE-learning). Students' medical task performance, team behavior performance, teamwork attitude, and patient safety attitude were collected at pretest, mid-test, and posttest. Descriptive statistics and repeated measures analysis of variance were used. End-of-study qualitative feedback was collected, and content analysis was performed. Both groups demonstrated moderate-to-large within-group improvements for multiple learning outcomes at mid-test. Group 1 students' medical task performance (F = 97.25; P < 0.001) and team behavior performance (F = 31.17; P < 0.001) improved significantly. Group 2 students' medical task performance (F = 77.77; P < 0.001), team behavior performance (F = 40.14; P < 0.001), and patient safety attitude (F = 6.82; P < 0.01) improved significantly. Outcome differences between groups were nonsignificant. Qualitative themes identified included: personal factor, professional factor, interprofessional relationship, and learning. The IPE program provided students with exposure to other professions and revealed differences in expertise and responsibilities. IPE-simulation and SPE-simulation were effective interventions that enabled medical and nursing students to develop critical medical management and team behavior performance. IPE-simulation provided more opportunities for improving competencies in interprofessional collaborative practice. In circumstances with limited teaching resources, SPE-simulation can be an acceptable alternative to IPE-simulation.
Interprofessional collaborative team-based approaches to care in health service delivery has been identified as important to health care reform around the world. Many academic institutions have integrated interprofessional education (IPE) into curricula for pre-licensure students in healthcare disciplines, but few provide formal initiatives for interprofessional practice (IPP). It is recognized that experiential learning (EL) can play a significant role supporting IPP education initiatives; however, little is known of how EL is used within education for IPP in healthcare settings. We conducted a scoping review to map peer-reviewed literature describing IPP education initiatives involving EL for pre-licensure students in healthcare disciplines. A literature search was executed in MEDLINE, CINAHL, EMBASE, ERIC, PsycINFO, Scopus, and Social Services Abstracts. After deduplication, two independent reviewers screened titles and abstracts of 5664 records and then 252 full-text articles that yielded 100 articles for data extraction. Data was extracted using an Excel template, and results synthesized for presentation in narrative and tabular formats. The 100 included articles represented 12 countries and IPP education initiatives were described in three main typologies of literature - primary research, program descriptions, and program evaluations. Forty-three articles used a theory, framework, or model for design of their initiatives with only eight specific to EL. A variety of teaching and learning strategies were employed, such as small interprofessional groups of students, team huddles, direct provision of care, and reflective activities, but few initiatives utilized a full EL cycle. A range of perspectives and outcomes were evaluated such as student learning outcomes, including competencies associated with IPP, impacts and perceptions of the IPP initiatives, and others such as client satisfaction. Few educational frameworks specific to EL have been used to inform EL teaching and learning strategies to consolidate IPE learning and prepare students for IPP in healthcare settings. Further development and evaluation of existing EL frameworks and models would be beneficial in supporting robust IPP educational initiatives for students in healthcare disciplines. Intentional, thoughtful, and comprehensive use of EL informed by theory can contribute important advances in IPP educational approaches and the preparation of a future health care workforce.
Interprofessional education (IPE) is an integrative approach that enables collaboration of students of two or more different health professions in aim to acquire skills and competencies related not only to their field of study but also to ensure the standard of care based on collaborative practice. IPE has not yet been explored in relation to collaboration between dietetics-nutrition and pharmacy students, while there is evidence that in many cases nutrition is complementary to pharmacotherapy in the treatment process. The aim of this scoping review was to gather, describe and discuss all relevant literature regarding joint interprofessional training of pharmacy and dietetics-nutrition undergraduates. We performed a literature search for studies where IPE between dietetics-nutrition and pharmacy students was described. 2204 articles on this topic were identified. After eligibility assessment, 8 articles were included in the review. Eight studies were included in the review. Two of these described IPE activities between dietetics and pharmacy students only. The included studies varied in setting, methodology and outcome measures and covered a wide range of topics relevant to clinical practice, such as management of inflammatory bowel diseases, care of the older adults or counselling skills. The most common teaching method was the use of case studies. Some of the included studies did not identify specific learning objectives. The most common way of gathering feedback from participants was through questionnaires and interviews. IPE of pharmacy and dietetics-nutrition students is feasible and may be beneficial in many aspects related to learning. However, there is no well-established model or standard that would facilitate the implementation of such activities in individual educational institutions.
Interprofessional education (IPE) is prioritized as a critical component in preparing pre-licensure health professional students for effective teamwork and collaboration in the workplace to facilitate patient-centered care. Knowledge in anatomy is fundamental for healthcare professionals, making interprofessional anatomy education an attractive intervention for IPE and anatomy learning. Since 2009, the Education Program in Anatomy at McMaster University has offered an intensive 10-week IPE Anatomy Dissection elective to seven health professional programs annually. From 2011, students were invited to complete the Readiness for Interprofessional Scale (RIPLS) and Interprofessional Education Perception Scale (IEPS) before and after the elective. A total of 264 students from 2011 to 2020 completed RIPLS and IEPS. There were significant differences before and after the elective in students' total RIPLS scores and three of the four subscales: teamwork and collaboration, positive professional identity, and roles and responsibilities. Similarly, there were statistical differences in the total IEPS scores and two of three subscales: competency and autonomy and perceived actual cooperation. Statistically significant differences in RIPLS and IEPS total scores across several disciplines were also observed. This study demonstrates the elective's impact in improving students' IPE perceptions and attitudes, likely from the extended learning and exposure opportunity with other disciplines.