Yoxas/statistical_literacy huggingface dataset:
A developed IPE (Interprofessional Education)-communication course was first implemented at Universitas Pelita Harapan/UPH via online learning due to the COVID-19 pandemic. This study aimed to analyze the effectiveness of a newly developed IPE-online communication course offered to medical (MS) and nursing (NS) students. This study was a quantitative study using a pre-post design without control. The IPAS (Interprofessional Attitude Scale) assessed students' attitudes toward IPE. Satisfaction with the program was also measured following its completion. The questionnaire was administered via Survey Monkey to 535 respondents (MS = 250; NS = 285). Univariate and bivariate statistical analyses were employed. Before and after the IPE program, 161 MS and 146 NS completed the IPAS questionnaire (n = 307). The attitude of MS and NS were not improved significantly (p-value >0.05). Moreover, several subscales of attitudes decreased significantly, including "Diversity and Ethics" with a low-size effect for medical students and "Teamwork, Roles, and Responsibilities" and "Patient-Centeredness" with a low-size effect for nursing students. Both students (n = 307) were also satisfied with the IPE course (Mean MS: 4.28 and NS: 4.34). This study suggests that online IPE communication course may not be effective in fostering student attitudes. The IPE communication course should be accomplished through in-person class instead of online learning. Further IPE course evaluations are required to improve the acceptability, applicability, and effectiveness of IPE in health education.
A diabetic foot ulcer is a preventable complication of diabetes, which could lead to lower extremity amputation and increased mortality and morbidity. Self-care behaviors play a key role in the prevention of diabetic foot ulcers. This study aimed to estimate the total score of diabetic foot self-care behaviors. We searched databases such as Web of Science, Medline (PubMed), and Scopus using various keywords, including diabetic foot, diabetic feet, diabetic problem, diabetic foot ulcer, and self-care, for relevant articles with no time limit. The heterogeneity of the studies was assessed using Cochran's Q test and I2 statistic. Data were analyzed using STATA software version 12 using the meta-analysis method and a random effects model. In total, eight studies were analyzed with a sample size of 2,493. The pooled score of diabetes foot self-care was 62.84% and this score was higher in the studies conducted on two groups of patients with type I and type II diabetes compared to those performed only on patients with type II diabetes. The results also indicated correlation between the self-care score and year of publication (P < 0.001), and the self-care scores significantly declined during 2015-2021 (P < 0.001). Overall, the diabetic foot self-care score was moderate, which highlights the need to provide self-care education to diabetic patients.
A digital divide exists for people from rural and regional areas where they are less likely and confident to engage in digital health technologies. The aim of this study was to evaluate the digital health literacy and engagement of people from rural and regional communities, with a focus on identifying barriers and facilitators to using technology. Forty adults living in rural/regional areas completed a survey consisting of the eHealth Literacy Scale (eHEALS) with additional items surveying participants' experience with a range of digital health technologies. All participants had used at least one digital health technology. Most (80%) participants had an eHEALS score of 26 or above indicating confidence in online health information. Commonly reported barriers to digital health technology use centred on product complexity and reliability, awareness of resources, lack of trust, and cost. Effective digital health technology use is becoming increasingly important, there may be a need to prioritise and support people with lower levels of digital health literacy. We present opportunities to support community members in using and accessing digital health technology.
A digitally literate nursing workforce can support the delivery of safe, effective care and improve patient outcomes. However, digital literacy among nurses is variable. Electronic patient records (EPRs), which require the digital documentation of all patient encounters, can be used to generate data that will inform strategies to improve patient care and patient safety. Nurse leaders at Imperial College Healthcare NHS Trust acknowledged that although ward nurses were providing excellent patient care, there were gaps in their digital documentation of that care. To address the issue, the trust implemented a model of education informed by data analytics and aimed at developing nurses' digital skills and increasing their engagement with digital workflows. This article describes how applications extracting data from the EPR system are used to identify nurses' digital literacy training needs and how a team of digital clinical practice educators delivers targeted educational strategies to meet those needs.
A disease severity classification system is widely used to predict the survival of patients admitted to the intensive care unit with different diagnoses. In the present study, conventional severity classification systems were compared with artificial intelligence predictive models (Artificial Neural Network and Decision Tree) in terms of the prediction of the survival rate of the patients admitted to the intensive care unit. This retrospective cohort study was performed on the data of the patients admitted to the ICU of Ghaemshahr's Razi Teaching Care Center from March 20th, 2017, to September 22nd, 2019. The required data for calculating conventional severity classification models (SOFA, SAPS II, APACHE II, and APACHE IV) were collected from the patients' medical records. Subsequently, the score of each model was calculated. Artificial intelligence predictive models (Artificial Neural Network and Decision Tree) were developed in the next step. Lastly, the performance of each model in predicting the survival of the patients admitted to the intensive care unit was evaluated using the criteria of sensitivity, specificity, accuracy, F-measure, and area under the ROC curve. Also, each model was validated externally. The R program, version 4.1, was used to create the artificial intelligence models, and SPSS Statistics Software, version 21, was utilized to perform statistical analysis. The area under the ROC curve of SOFA, SAPS II, APACHE II, APACHE IV, multilayer perceptron artificial neural network, and CART decision tree were 76.0, 77.1, 80.3, 78.5, 84.1, and 80.0, respectively. The results showed that although the APACHE II model had better results than other conventional models in predicting the survival rate of the patients admitted to the intensive care unit, the other conventional models provided acceptable results too. Moreover, the findings showed that the artificial neural network model had the best performance among all the studied models, indicating the discrimination power of this model in predicting patient survival compared to the other models.
A false "equity versus excellence" debate over mathematics curricula has long disrupted education in the United States.
A fully automated and accurate assay of rare cell phenotypes in densely-packed fluorescently-labeled liquid biopsy images remains elusive. Methods: Employing a hybrid artificial intelligence (AI) paradigm that combines traditional rule-based morphological manipulations with modern statistical machine learning, we deployed a next generation software, ALICE (Automated Liquid Biopsy Cell Enumerator) to identify and enumerate minute amounts of tumor cell phenotypes bestrewed in massive populations of leukocytes. As a code designed for futurity, ALICE is armed with internet of things (IOT) connectivity to promote pedagogy and continuing education and also, an advanced cybersecurity system to safeguard against digital attacks from malicious data tampering. Results: By combining robust principal component analysis, random forest classifier and cubic support vector machine, ALICE was able to detect synthetic, anomalous and tampered input images with an average recall and precision of 0.840 and 0.752, respectively. In terms of phenotyping enumeration, ALICE was able to enumerate various circulating tumor cell (CTC) phenotypes with a reliability ranging from 0.725 (substantial agreement) to 0.961 (almost perfect) as compared to human analysts. Further, two subpopulations of circulating hybrid cells (CHCs) were serendipitously discovered and labeled as CHC-1 (DAPI+/CD45+/E-cadherin+/vimentin-) and CHC-2 (DAPI+ /CD45+/E-cadherin+/vimentin+) in the peripheral blood of pancreatic cancer patients. CHC-1 was found to correlate with nodal staging and was able to classify lymph node metastasis with a sensitivity of 0.615 (95% CI: 0.374-0.898) and specificity of 1.000 (95% CI: 1.000-1.000). Conclusion: This study presented a machine-learning-augmented rule-based hybrid AI algorithm with enhanced cybersecurity and connectivity for the automatic and flexibly-adapting enumeration of cellular liquid biopsies. ALICE has the potential to be used in a clinical setting for an accurate and reliable enumeration of CTC phenotypes.
A fundamental decision that an organism must make is how to allocate resources to offspring, with respect to both size and number. The two major theoretical approaches to this problem, optimal offspring size and optimistic brood size models, make different predictions that may be reconciled by including how offspring fitness is related to size. We extended the reasoning of Trivers and Willard (1973) to derive a general model of how parents should allocate additional resources with respect to the number of males and females produced, and among individuals of each sex, based on the fitness payoffs of each. We then predicted how harvester ant colonies should invest additional resources and tested three hypotheses derived from our model, using data from 3 years of food supplementation bracketed by 6 years without food addition. All major results were predicted by our model: food supplementation increased the number of reproductives produced. Male, but not female, size increased with food addition; the greatest increases in male size occurred in colonies that made small females. We discuss how use of a fitness landscape improves quantitative predictions about allocation decisions. When parents can invest differentially in offspring of different types, the best strategy will depend on parental state as well as the effect of investment on offspring fitness.
A future shortage of physicians, especially in general practice, will result in an increasing workload for health care providers as a whole. Therefore, it is important to optimize patient-encounter processes to increase time efficiency related to visits. Utilizing digital tools to record patients' medical histories prior to a consultation offers great potential to achieve this goal. The collected information can be stored into the practice's electronic medical record, allowing for the general practitioner to review structured information of the patients' complaints and related medical history beforehand, thereby saving time during the encounter. However, the low usability of new digital developments in this setting often hinders implementation. The aim of this study was to evaluate the usability of an app designed for medical history taking in general practice to capture the patients' perspective. Between November 2021 and January 2022, we recruited 406 patients with acute complaints in one out-of-hour urgent care and seven general practice clinics. These study participants used the app during their waiting time and subsequently assessed its usability by completing the System Usability Scale (SUS), a robust and well-established 10-question survey measuring the perceived usability of products and technologies. Additionally, we collected general participant information, including age, sex, media usage, health literacy, and native language. Descriptive and inferential statistics were applied to identify patient characteristics associated with low or high SUS scores. We analyzed data from 397 patients (56.7% female, 43.3% male). The mean total SUS score was 77.8 points; 54.4% (216/397) of participants had SUS scores of 80 points or higher, indicating high usability of the app. In a multiple linear regression predicting SUS score, male sex and higher age (65 years or older) were significantly negatively associated with the SUS score. Conversely, a higher health literacy score and German as the native language were significantly positively associated with the SUS score. Usability testing based on the SUS anticipates successful implementation of the app. However, not all patients will easily adapt to utilizing the app, as exemplified by the participants of older age in this study who reported lower perceived usability. Further research should examine these groups of people, identify the exact problems in operating such an app, and provide targeted solutions. German Clinical Trials Register World Health Organization Trial Registration Data Set DRKS00026659; https://trialsearch.who.int/Trial2.aspx?TrialID=DRKS00026659.
A glass ceiling effect exists for women in male-dominated professions. Recent studies also show a glass-cliff effect where senior women can more easily fall from positions of leadership. Transplantation remains a male-dominated specialty. This study investigated gender and the perception of adverse clinical incidents in transplantation. Prospective randomised web-based survey involving five clinical scenarios presenting two versions of episodes with errors or mistakes, with either a male or female as a randomly named protagonist (Set1 and Set2). To address unconscious bias, the study was described as examining actions following clinical adverse incidents in transplantation. Each scenario was followed by 2 closed questions: (1) clinical performance rating and (2) selection of action required. Reasoning was invited (open-text comments). Responses were analyzed using quantitative and qualitative methods. One hundred ninety-one invitees responded; 134 completed questionnaires. There were no statistically significant differences (P > 0.05) in responses between sets for performance ratings or recommended actions. However, for "first solo laparoscopic surgery" scenario, there was some indication that "No Action" was more likely if surgeon was male (P = 0.056). Male responses rated female performance as significantly worse (P = 0.035) for the laboratory-based scenario. One hundred two participants provided open-text comments. Thematic analysis identified 7 themes. Acceptable levels of risk theme demonstrated engendered leadership beliefs, that is, when clinical judgment proved incorrect, males described as forceful but females as needing support. In cases where things went wrong, respondents were more likely to comment females should not have decided to proceed. While gender may no longer be an overt issue in perceived performance of senior staff in transplantation, respondents' use of language and their choice of words display elements of unconscious (covert) engendered views.
A growing body of conceptual evidence over the last decade has increased our understanding of parents' experiences of having an infant with complex congenital heart disease. These concepts include parents' feelings of uncertainty, fear, excitement, and mastery. However, little is known about parents' experiences, confidence, and knowledge acquisition during transition from hospital to home with their infant after the first stage of complex cardiac surgery. A theoretical framework to assess, plan and implement child and family centered care would assist children's cardiac nurses responsible for parental education, discharge planning and coordination. To explore parents' experiences of the transition from hospital to home with their infant, following the first stage of cardiac surgery. A prospective mixed methods longitudinal design. Semi-structured interviews were undertaken, including administration of the Maternal Confidence Questionnaire at four timepoints: before discharge following stage one cardiac surgery (T0), 2 weeks' post discharge (T1), 8 weeks' post discharge (T2) and after stage two surgery (T3). Qualitative data were thematically analyzed. Descriptive statistics were used to characterize the sample and non-parametric repeated measures analysis of variance was used to analyze changes over time in maternal confidence scores. Sixteen parents of 12 infants participated. Four "patterns of transition experience" emerged, the fourth "Mastery", is discussed in this paper. Mastery can be contextualized in terms of the parents' journeys of knowledge construction, gaining confidence and reflection. Learning was dynamic and transformational, but successful learning and acquisition of knowledge was also dependent upon the parents' ability to absorb, integrate and adjust at any given time. Confidence at T0 was significantly lower than at T1 (p = .011), T2 (p = .018) and T3 (p = .012). There were no significant differences between scores at T1, T2 and T3. Liminality, as a concept, described the between and betwixt time that parents experienced as they were preparing for discharge from hospital; excitement to be going home balanced with the fear of being alone and confidence in looking after their fragile infant. Parents of infants with complex congenital heart disease obtain knowledge, confidence, and mastery dependent upon their transition experience and their personal journey through pre-liminal, liminal, and post-liminal phases of discharge from hospital to home. A conceptual framework "Parenting through Transitions - hospital to home" emerged that could assist in structuring assessment of parents' knowledge and support needs within a coordinated discharge process. Identifying individualized support would promote adaptation and adjustment during transition from the pre to post liminal phase, following their infant's first stage of complex cardiac surgery.
A growing body of research documents the relevance of parental education as a marker of family socio-economic status for children's later-life health outcomes. A strand of this literature evaluates how the early-life environment shapes mortality outcomes during infancy and childhood. However, the evidence on mortality during the life course and old age is limited. This paper contributes to the literature by analysing the association between paternal education and children's old-age mortality. We use data from Social Security Administration death records over the years 1988-2005 linked to the United States 1940 Census. Applying a family(cousin)- fixed-effects model to account for shared environment, childhood exposures, and common endowments that may confound the long-term links, we find that having a father with a college or high-school education, compared with elementary/no education, is associated with a 4.6- or 2.6-month-higher age at death, respectively, for the child, conditional on them surviving to age 47.
A growing body of research has examined parents' practices to support their young children's number learning at home, i.e., the home numeracy environment. Many of these studies focus on formal and informal domains of numeracy activities, which are inconsistently defined and related to children's math learning. In this study, we explore dimensions of the home numeracy environment and examine their relations with children's math skills among a sample of four-year-old children and their parents over the course of one year. Parents reported on the frequency of 21 numeracy activities when children were four and five. Exploratory and confirmatory factor analyses revealed a two-factors solution: number-related play activities and use of educational materials with numbers. Frequency of play with numbers was positively related to children's ability to solve applied math problems at age five, controlling for prior number skills, child age, and socioeconomic status. In contrast, neither measure of the home numeracy environment predicted symbolic number knowledge or non-symbolic number sense when controlling for covariates. These findings underscore the need to differentiate between factors of the home numeracy environment and to develop clear theoretical definitions of these factors.
A growing body of research suggests that growth in early literacy skills, including letter sound fluency, is predictive of later reading outcomes. In turn, educators and school psychologists use measures of letter sound fluency to monitor student response to early reading instruction. Limited research has evaluated whether decision-making frameworks that educators apply to early reading time series data to make instructional decisions (e.g., to continue or change the intervention) yield accurate recommendations. Further, it is unclear how long data need to be collected and which type of decision rule (e.g., data point, trend line) will produce the most accurate recommendations. We conducted a series of simulations to investigate the impact of data collection duration (4 to 16 weeks) and decision-rule type (data point, trend line, and median) on the accuracy of data-based decisions using early literacy data. Results suggest that the median and trend-line rules produced recommendations that were sufficiently accurate in identifying students that were not making adequate progress (sensitivity) after about 12 weeks when data were collected once a week. However, the median and trend-line rules did not produce recommendations that were sufficiently accurate to continue an intervention (specificity) across all progress monitoring durations. The opposite pattern was observed for the data-point rule. Outcomes suggest that recommendations developed from other progress monitoring measures (e.g., oral reading fluency) should not be extrapolated to other measures without empirical investigation. More research is needed to identify appropriate decision rules to evaluate early literacy progress monitoring data. (PsycINFO Database Record (c) 2019 APA, all rights reserved).