Yoxas/statistical_literacy huggingface dataset:
Since the middle of the 20th century, perceptions of risk have been critical to understanding engagement in volitional behavior change. However, theoretical and empirical risk perception research seldom considers the possibility that risk perceptions do not simply exist: They must be formed. Thus, some people may not have formulated a perception of risk for a hazard at the time a researcher asks them, or they may not be confident in the extent to which their perception matches reality. We describe a decade-long research program that investigates the possibility that some people may genuinely not know their risk of even well-publicized hazards. We demonstrate that indications of not knowing (i.e., "don't know" responses) are prevalent in the U.S. population, are systematically more likely to occur among marginalized sociodemographic groups, and are associated with less engagement in protective health behaviors. "Don't know" responses are likely indications of genuinely limited knowledge and therefore may indicate populations in need of targeted intervention. This body of research suggests that not allowing participants to indicate their uncertainty may threaten the validity and generalizability of behavior-change research. We provide concrete recommendations for scientists to allow participants to express uncertainty and to analyze the resulting data.
Since the publication of the Core Competencies for Public Health in Canada in 2008, the public health and communication landscape has changed dramatically. Digital media and infodemics have shifted how practitioners must communicate and respond to health information. The age of the current competency framework, which is relied on for workforce development, alongside emerging public health challenges, have prompted calls for modernized competency statements. This study aims to (i) measure self-reported communication competence in the public health workforce, (ii) measure agreement with new communication competency statements, (iii) identify variation in agreement between sub-groups of professionals, and (iv) explore current and needed communication training. Using a mixed-methods online survey, a sample of 378 participants in various Canadian public health roles and regions were asked to rate their current communication competence and agreement with a modernized, evidence-based draft communication competency framework. The survey was distributed in both official languages through partner organizations and social media. Descriptive statistics were performed to assess agreement and variation was analyzed in relation to public health roles and experience. While most participants self-reported communication competence, specific areas were rated lower. All 21 proposed competency statements received high agreement with some variation observed between expertise and experience levels. Demand for communication training is high. Strong agreement with statements indicates support for a modernized communication competency framework among sampled professionals. Research to gather more evidence surrounding the communication demands of the public health workforce and observed variation in strong agreement for the proposed statements is underway.
Since the release of ChatGPT, numerous positive applications for this artificial intelligence (AI) tool in higher education have emerged. Faculty can reduce workload by implementing the use of AI. While course evaluations are a common tool used across higher education, the process of identifying useful information from multiple open-ended comments is often time consuming. The purpose of this study was to explore the use of ChatGPT in analyzing course evaluation comments, including the time required to generate themes and the level of agreement between instructor-identified and AI-identified themes. Course instructors independently analyzed open-ended student course evaluation comments. Five prompts were provided to guide the coding process. Instructors were asked to note the time required to complete the analysis, the general process they used, and how they felt during their analysis. Student comments were also analyzed through two independent Open-AI ChatGPT user accounts. Thematic analysis was used to analyze the themes generated by instructors and ChatGPT. Percent agreement between the instructor and ChatGPT themes were calculated for each prompt, along with an overall agreement statistic between the instructor and two ChatGPT themes. There was high agreement between the instructor and ChatGPT results. The highest agreement was for course-related topics (range 0.71-0.82) and lowest agreement was for weaknesses of the course (range 0.53-0.81). For all prompts except themes related to student experience, the two ChatGPT accounts demonstrated higher agreement with one another than with the instructors. On average, instructors took 27.50 ± 15.00 min to analyze their data (range 20-50). The ChatGPT users took 10.50 ± 1.00 min (range 10-12) and 12.50 ± 2.89 min (range 10-15) to analyze the data. In relation to reviewing and analyzing their own open-ended course evaluations, instructors reported feeling anxiety prior to the process, satisfaction during the process, and frustration related to findings. This study offers valuable insights into the potential of ChatGPT as a tool for analyzing open-ended student course evaluation comments in health professions education. However, it is crucial to ensure ChatGPT is used as a tool to assist with the analysis and to avoid relying solely on its outputs for conclusions.
Since the release of the third version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III), biological psychiatry has been systematically applying its classification reasoning to social phenomena of many natures. From this perspective, the discourse of trauma gained relevance and events of devastating magnitude began to receive neurobehavioral interpretations until finally being recognized less for their cultural and subjective effects than for the physiological changes they cause. By a narrative review, this study aims to analyze the transition of traumatic rationality from the 19th century, when trauma was associated with the cognitive concept of memory, to the 20th century, when this phenomenon was finally attached to neuroscientific research on stress. The plurality of conceptual models and deterministic paradigms can contribute to the fact that trauma research produces multifactorial coping protocols more appropriate to the human experience of post-traumatic suffering.
Since the start of the COVID-19 pandemic, new guidelines for dental practice were published. This research aims to examine the knowledge of dental students and their attitudes towards current guidelines. The study involved 76 fourth-year dental medicine students from three public universities in Croatia. A survey questionnaire was developed based on in-depth interviews and a pilot pretesting. The online questionnaire consisting of 36 questions was published using Google Forms. The survey data were analysed using Microsoft Excel and presented with descriptive statistics. Survey data showed the dental students' knowledge of the guidelines for dental practices is at an insufficient level (average score of 67% correct answers). Students who have come across the guidelines outside the faculty environment through assistantships have demonstrated lesser knowledge (65%) of the guidelines than the ones who do not (68%). A similar trend is observed with dental students who grew up in a family of doctors of dental medicine (61%) and ones who did not (68%). Students also independently assessed their knowledge of the guidelines as moderate (3.15 out of 5), while evaluating the application of current guidelines as very important (4.38 out of 5). Awareness of dental students should be improved by adapting the curriculum of dental studies and increasing the availability of information on current guidelines. Dental students need to be motivated to independently inform themselves about the current guidelines for dental practices, thus improving their clinical work.
Since the traditional mental health system showed significant limitations in the early identification, diagnosis and treatment of the current new youth psychopathological trajectories, by substantially failing in targeting the needs of the current young generation, there is the demand to redesign and digitally adapt youth mental health care and systems. Indeed, the level of digital literacy and the level of digital competency and knowledge in the field of digital psychiatry is still under-investigated among mental health professionals, particularly in youth mental health. Therefore, we aimed at: (a) carrying out a post-hoc analysis of an international multi-centre study, to investigate the opinions of mental health professionals regarding the feasibility, efficacy and clinical experience in delivering digital mental health interventions (DMHIs) in youths; (b) providing a comprehensive overview on the integrated digitally-based youth mental health care models and innovations. Mental health professionals declared the lack of a formal training in digital psychiatry, particularly in youth mental health. Subjects who received a formal theoretical/practical training on DMHIs displayed a statistical trend towards a positive feasibility of digital psychiatry in youth mental health (p = 0.053) and a perceived increased efficacy of digital psychiatry in youths (p = 0.051). Respondents with higher Digital Psychiatry Opinion (DPO) scores reported a positive perceived feasibility of DMHIs in youths (p < 0.041) and are more prone to deliver DMHIs to young people (p < 0.001). Respondents with higher knowledge scores (KS) declared that DMHIs are more effective in youth mental health (p < 0.001). Overall, the digitalisation indeed allowed young people to keep in touch with a mental health professional, facilitating a more dynamic and fluid mental health care access and monitoring, generally preferred and considered more feasible by post-Millennial youngsters. Accordingly, our findings demonstrated that mental health professionals are more prone to offer DMHIs in youth mental health, particularly whether previously trained and knowledgeable on the topic.
Since their development, integrated plastic and reconstructive surgery (PRS) residency training programs have established diverse methods of incorporating general surgery training into graduate medical education. Programs have questioned the necessary duration and timing of such training. The aim of this study is to assess the landscape of general surgery exposure in integrated PRS residency programs. Thirty-six integrated PRS residency programs were included based on the availability of postgraduate year (PGY)-level rotation data. Rotations were measured in units of weeks with descriptive titles maintained as advertised by the program. Individual general surgery rotations were also categorized as being either PRS-aligned, American Board of Plastic Surgery (ABPS) Required Clinical (RC) or ABPS Strongly Suggested (SS). Statistical analyses were carried out on the relative proportions of each subcategory in the 2 parent groups. All 36 programs evaluated required general surgery rotations in years PGY- 1 to -2. By PGY-3, 69% of programs required general surgery, and by PGY-6, 25%, and these were limited to 4- to 6-week rotations in burn, breast, or trauma. Looking across all 6 years, with 312 weeks of training total, the minimum number of weeks spent in general surgery rotations was 32, and the maximum number was 119, with an average of 61 weeks (±21).Programs were subcategorized into 2 groups based on whether they spent more (n = 16) or less (n = 20) than the net average number of weeks in ABPS RC + SS rotations. No significant difference was found in the relative proportion of PRS-aligned general surgery across groups. Programs with <60 weeks of general surgery had a relatively greater proportion of ABPS RC and SS rotations. These data demonstrate that there exists significant variability in overall duration of general surgery training across integrated PRS training programs. When controlling overall general surgery exposure for variables of interest like PRS-aligned exposure or compatibility with ABPS requirements, we found no discernable educational model or patterns to explain the observed range in exposure. These results warrant reexamination of an ideal general surgery track within the integrated plastic surgery training model that optimizes training for the PRS resident.
Since traditional teaching could not help to develop competences, flipped classroom has caught the sight of researchers. Despite the uptake of flipped classroom in other disciplines, there is a dearth of evidence available about the use in nursing curricula. In addition, there is no consensus on how to best implement a flipped classroom. This study aimed to (1) develop a flipped classroom underpinned by constructivism theory and (2) to verify its effectiveness. This study adopted a quasi-experimental design. This study was conducted in 2018 spring semester at a University in East China with 6th semester undergraduate nursing students in four parallel classes in Community Nursing Course. A flipped classroom characterized by situational and collaborative learning was developed and carried out with two classes (intervention group, n = 98). In-class lectures was applied for the other two classes (control group, n = 90). Course examination score, experience (course experience questionnaire, CEQ), and students' appraisal were used to verify the effectiveness of flipped classroom. Compared to control group, the examination score was higher for intervention group. As for the four domains of CEQ, good teaching domain rating was lower, learning burden domain rating was higher for the intervention group. There was no statistical difference in classroom quality and harvest domains. More students in intervention group chose the course helped them in developing "critical thinking" and "self-cognition and evaluation" abilities. Satisfaction rating of groups was not statistically different. Flipped classroom was efficient in improving students' academic performance and promoting development of higher-level thinking abilities; however, it failed in improving students' satisfaction and course experience. These findings suggest that active learning strategies such as situational and collaborative learning of group problem solving and discussion should be integrated into nursing curriculum and refinement to flipped classroom are needed to create students' buy-in.
Single nucleotide polymorphisms (SNPs) may influence pain susceptibility and impact treatment response in pain-related temporomandibular disorders (TMDp). Explore the role of COMT (rs4646310, rs6269, rs4818, rs4680) and OPRM1 (rs1799971) genotypes in regulating treatment response. Sixty TMDp patients (55 females and 5 males), diagnosed with the Diagnostic Criteria for TMD (DC/TMD), underwent standardised treatment (information and education, home physical therapy, occlusal splint) for 6 months. Treatment outcomes included: pain intensity, pain-free mouth opening, jaw functional limitation, depression, and anxiety. Genotyping for COMT and OPRM1 SNPs was performed using DNA from buccal mucosa swabs and TaqMan assays. Statistical analysis was carried out to compare the changes in treatment outcomes and the influence of genotypes on treatment response. Significantly less pain reduction was observed in minor allele carriers of rs4646310, and rs4680 compared to dominant homozygous (p < .025). Minor allele carriers of rs1799971 and rs4646310 demonstrated worsening in pain-free mouth opening while dominant homozygous exhibited improvement (p < .025). Significantly less anxiety reduction was observed in minor allele carriers of rs4646310 compared to dominant homozygous (p = .003). Of the all variables assessed in the regression model, carrying a minor allele of rs1799971 predicted a poorer treatment response considering pain-free mouth opening while carrying a minor allele of rs4646310 predicted less pain and less anxiety reduction. Our findings indicate that certain SNP variants of the COMT and OPRM1 genes were associated with poorer treatment response and may therefore play a significant role in the classification of TMDp patients. Also, assessment of patient genotype could potentially aid in predicting treatment response.
Single-best response types of MCQs are commonly used tools in medical assessment. However, these are not particularly apt for the assessment of higher-order thinking skills (HOTS) among students. Assessment of HOTS and clinical reasoning skills requires unexplored tools like extended matching questions (EMQs) and SCTs. The aim is to assess HOTS and clinical reasoning skills during formative assessment among medical students post a simulation-based education (SBE) using EMQ and SCT on the topic of shock and collect student perceptions regarding new assessment tools. The research is an observational descriptive study. Fifty-two first-year medical students were asked to take a formative assessment consisting of 20 MCQs, 6 EMQs, and 2 SCT post a SBE during July 2022 on the topic of shock. MCQs were categorized into themes of aetiology, pathophysiology, and management of shock. These categorized MCQs were compared and analyzed with EMQs and SCTs prepared on the same themes. The data analysis by a one-way analysis of variance (ANOVA) was conducted to compare the difference in per cent mean scores of MCQ with EMQ and MCQ with SCT. The overall mean scores and also under the theme of aetiology and management, the student's score in MCQ were higher than EMQ and SCT and the difference was statistically significant with the P value (≤0.001). Students scored better in familiar assessment tools like MCQ, but majority of the students were of the opinion that EMQ tested the delivered content better and SCT tested the clinical application better.
Single-case experimental designs (SCEDs) have grown in popularity in the fields such as education, psychology, medicine, and rehabilitation. Although SCEDs are valid experimental designs for determining evidence-based practices, they encounter some challenges in analyses of data. One of these challenges, missing data, is likely to be occurred frequently in SCEDs research due to repeated measurements over time. Since missing data is a critical factor that can weaken the validity and generalizability of a study, it is important to determine the characteristics of missing data in SCEDs, which are especially conducted with a small number of participants. In this regard, this study aimed to describe missing data features in SCEDs studies in detail. To accomplish this goal, 465 published SCEDs studies within the recent 5 years in six journals were included in the investigation. The overall results showed that the prevalence of missing data among SCEDs articles in at least one phase, as at least one data point, was approximately 30%. In addition, the results indicated that the missing data rates were above 10% within most studies where missing data occurred. Although missing data is so common in SCEDs research, only a handful of studies (5%) have handled missing data; however, their methods are traditional. In analyzing SCEDs data, several methods are proposed considering missing data ratios in the literature. Therefore, missing data rates determined in this study results can shed light on the analyses of SCEDs data with proper methods by improving the validity and generalizability of study results.
Single-cell RNA sequencing (scRNA-Seq) is a recent technology that allows for the measurement of the expression of all genes in each individual cell contained in a sample. Information at the single-cell level has been shown to be extremely useful in many areas. However, performing single-cell experiments is expensive. Although cellular deconvolution cannot provide the same comprehensive information as single-cell experiments, it can extract cell-type information from bulk RNA data, and therefore it allows researchers to conduct studies at cell-type resolution from existing bulk datasets. For these reasons, a great effort has been made to develop such methods for cellular deconvolution. The large number of methods available, the requirement of coding skills, inadequate documentation, and lack of performance assessment all make it extremely difficult for life scientists to choose a suitable method for their experiment. This paper aims to fill this gap by providing a comprehensive review of 53 deconvolution methods regarding their methodology, applications, performance, and outstanding challenges. More importantly, the article presents a benchmarking of all these 53 methods using 283 cell types from 30 tissues of 63 individuals. We also provide an R package named DeconBenchmark that allows readers to execute and benchmark the reviewed methods (https://github.com/tinnlab/DeconBenchmark).
Single-cell transcriptomics profiling has increasingly been used to evaluate cross-group differences in cell population and cell-type gene expression. This often leads to large datasets with complex experimental designs that need advanced comparative analysis. Concurrently, bioinformatics software and analytic approaches also become more diverse and constantly undergo improvement. Thus, there is an increased need for automated and standardized data processing and analysis pipelines, which should be efficient and flexible too. To address these, we develop the s ingle- c ell D ifferential A nalysis and P rocessing P ipeline (scDAPP), a R-based workflow for comparative analysis of single cell (or nucleus) transcriptomic data between two or more groups and at the levels of single cells or "pseudobulking" samples. The pipeline automates many steps of pre-processing using data-learnt parameters, uses previously benchmarked software, and generates comprehensive intermediate data and final results that are valuable for both beginners and experts of scRNA-seq analysis. Moreover, the analytic reports, augmented by extensive data visualization, increase the transparency of computational analysis and parameter choices, while facilitate users to go seamlessly from raw data to biological interpretation. scDAPP is freely available for non-commercial usage as an R package under the MIT license. Source code, documentation and sample data are available at the GitHub ( https://github.com/bioinfoDZ/scDAPP ).
Single-molecule surface-enhanced Raman spectroscopy (SM-SERS) has the potential to detect single molecules in a non-invasive, label-free manner with high-throughput. SM-SERS can detect chemical information of single molecules without statistical averaging and has wide application in chemical analysis, nanoelectronics, biochemical sensing, etc. Recently, a series of unprecedented advances have been realized in science and application by SM-SERS, which has attracted the interest of various fields. In this review, we first elucidate the key concepts of SM-SERS, including enhancement factor (EF), spectral fluctuation, and experimental evidence of single-molecule events. Next, we systematically discuss advanced implementations of SM-SERS, including substrates with ultra-high EF and reproducibility, strategies to improve the probability of molecules being localized in hotspots, and nonmetallic and hybrid substrates. Then, several examples for the application of SM-SERS are proposed, including catalysis, nanoelectronics, and sensing. Finally, we summarize the challenges and future of SM-SERS. We hope this literature review will inspire the interest of researchers in more fields.