Yoxas/statistical_literacy huggingface dataset:
Egypt faces a significant public health burden due to chronic liver diseases (CLD) and peptic ulcer disease. CLD, primarily caused by Hepatitis C virus (HCV) infection, affects over 2.9% of the population nationwide, with regional variations. Steatotic liver disease is rapidly emerging as a significant contributor to CLD, especially in urban areas. Acid-related disorders are another widespread condition that can significantly impact the quality of life. These factors and others significantly influence the indications and findings of gastrointestinal endoscopic procedures performed in Egypt. We aimed to evaluate the clinico-demographic data, indications, and endoscopic findings in Egyptian patients undergoing gastrointestinal endoscopic procedures in various regions of Egypt. This study employed a retrospective multicenter cross-sectional design. Data was collected from patients referred for gastrointestinal endoscopy across 15 tertiary gastrointestinal endoscopy units in various governorates throughout Egypt. 5910 patients aged 38-63 were enrolled in the study; 75% underwent esophagogastroduodenoscopy (EGD), while 25% underwent a colonoscopy. In all studied patients, the most frequent indications for EGD were dyspepsia (19.5%), followed by hematemesis (19.06%), and melena (17.07%). The final EGD diagnoses for the recruited patients were portal hypertension-related sequelae (60.3%), followed by acid-related diseases (55%), while 10.44% of patients had a normally apparent endoscopy. Male gender, old age, and the presence of chronic liver diseases were more common in patients from upper than lower Egypt governorates. Hematochezia (38.11%) was the most reported indication for colonoscopy, followed by anemia of unknown origin (25.11%). IBD and hemorrhoids (22.34% and 21.86%, respectively) were the most prevalent diagnoses among studied patients, while normal colonoscopy findings were encountered in 18.21% of them. This is the largest study describing the situation of endoscopic procedures in Egypt. our study highlights the significant impact of regional variations in disease burden on the utilization and outcomes of GI endoscopy in Egypt. The high prevalence of chronic liver disease is reflected in the EGD findings, while the colonoscopy results suggest a potential need for increased awareness of colorectal diseases.
Egypt is a country of nearly 100 million citizens, and there are less than 1000 registered psychiatrists. The mental health care system is under resourced and nearly inaccessible for the majority of the population. In addition, youth under the age of 25 years represent 50% of Egyptian citizens; however, there are no specific services addressing their unique needs. How can the needs of the largest population in the Middle East be effectively addressed? Is a web-based framework an option for Egyptian psychiatrists to serve the population? The aims of this study were to better understand the opinions of psychiatrists on the current state of mental health care services in Egypt and their current knowledge on electronic mental health (EMH); assess the attitudes of Egyptian psychiatrists toward web-based interventions and telemedicine for mental health; and identify perceived advantages and barriers of EMH development in Egypt. A cross-sectional survey was conducted online among 640 Egyptian psychiatrists. It included a total of 36 items within a set of 16 questions asking about EMH literacy, integrating EMH into the mental health care system, and the perceived priorities and barriers of EMH. The sampling was supported by Tanta University, a large academic institution close to Cairo. Statistical analysis was performed using SPSS 25 (IBM Corp). Descriptive statistics, the chi-square test, the independent sample t test, and analysis of variance were applied. A total of 188 participants responded (response rate of 29.4%), of which 54.2% (102/188) were female and 54.3% (102/188) were between 30 and 45 years old. Less than half of the participants thought that the current health care system was efficient for adults (69/155, 44.4%), and even less thought it was efficient for youth (44/155, 28.3%). Almost all participants agreed that EMH would be beneficial for patient care (147/155, 94.8%) and that integrating EMH into the current health care system would be a good idea (118/155, 76.2%). The highest rated utility of web-based solutions was documentation, followed by psychoeducation and communication with professionals. The main advantages were to improve access to care in rural areas of the country and its convenience. There is scarcity of mental health resources in Egypt. Egyptian psychiatrists are interested in EMH and believe web-based platforms can become part of the solution for the Egyptian mental health care system.
eHealth literacy (EHL) refers to a variety of capabilities that enable individuals to obtain health information from electronic resources and apply it to solve health problems. With the digitization of health care and the wide availability of health apps, a more diverse range of eHealth skills is required to properly use such health facilities. Existing EHL measurements focus mainly on the skill of obtaining health information (Web 1.0), whereas skills for web-based interactions (Web 2.0) and self-managing health data and applying information (Web 3.0) have not been well measured. This study aims to develop an EHL scale (eHLS) termed eHLS-Web3.0 comprising a comprehensive spectrum of Web 1.0, 2.0, and 3.0 skills to measure EHL, and evaluate its validity and reliability along with the measurement invariance among college students. In study 1, 421 Chinese college students (mean age 20.5, SD 1.4 years; 51.8% female) and 8 health experts (mean age 38.3, SD 5.9 years; 87.5% female) were involved to develop the eHLS-Web3.0. The scale development included three steps: item pool generation, content validation, and exploratory factor analysis. In study 2, 741 college students (mean age 21.3, SD 1.4 years; 52.2% female) were recruited from 4 Chinese cities to validate the newly developed eHLS-Web3.0. The construct validity, convergent validity, concurrent validity, internal consistency reliability, test-retest reliability, and measurement invariance across genders, majors, and regions were examined by a series of statistical analyses, including confirmatory factor analysis (CFA) and multigroup CFAs using SPSS and Mplus software packages. Based on the item pool of 374 statements collected during the conceptual development, 24 items (4-10 items per subscale) were generated and adjusted after cognitive testing and content validity examination. Through exploratory factor analysis, a 3-factor eHLS-Web3.0 was finally developed, and it included acquisition (8 items), verification (6 items), and application (10 items). In study 2, CFAs supported the construct validity of the 24-item 3D eHLS-Web3.0 (χ2244=903.076, χ2244=3.701, comparative fit index=0.924, Tucker-Lewis index=0.914, root mean square error of approximation [RMSEA]=0.06, and standardized root mean residual [SRMR]=0.051). The average variance extracted (AVE) value of 0.58 and high correlation between eHLS-Web3.0 subscales and the eHealth Literacy Scale (r=0.725-0.880, P<.001) indicated the convergent validity and concurrent validity of the eHLS-Web3.0. The results also indicated satisfactory internal consistency reliability (α=.976, ρ=0.934-0.956) and test-retest reliability (r=0.858, P<.001) of the scale. Multigroup CFA demonstrated the 24-item eHLS-Web3.0 to be invariant at all configural, metric, strength, and structural levels across genders (female and male), majors (sport-related, medical, and general), and regions (Yinchuan, Kunming, Xiamen, and Beijing). The 24-item 3D eHLS-Web3.0 proved to be a reliable and valid measurement tool for EHL in the Web 3.0 context among Chinese college students.
eHealth literacy has many benefits for patients and community members, including the direct impact on improving the quality of patient education and reducing direct and indirect healthcare costs. Benefiting from eHealth literacy in patients with cardiovascular diseases can effectively provide healthcare services and manage these patients. This study aimed to evaluate eHealth literacy level and its factors affecting patients with cardiovascular diseases in a Heart Center Hospital. This cross-sectional study was conducted in 2022. A valid and reliable questionnaire has been used for data gathering. From 147 distributed questionnaires among patients with cardiovascular diseases at Madani Heart Center Hospital in Khorramabad city, finally, 86 questionnaires have been collected completely. Data analyses were done using IBM Statistical Package for the Social Sciences (SPSS) software version 22 descriptive and analytical tests such as one-way ANOVA, independent sample t-test, and Spearman correlation coefficient based on the study objectives. The study showed that heart patients' eHealth literacy status is moderate (3.38 out of 5). The awareness of the availability of resources on the Internet had the highest score (3.79). The importance of using the Internet to obtain health information (r = 0.62, P < 0.001) and the ability to use the Internet (r = 0.62, P < 0.001) had the most significant relationship with eHealth literacy among patients with cardiovascular diseases. It is suggested that by increasing the level of Internet skills, expanding the use of the Internet for health-related services, using the Internet to make accurate health decisions among patients, extending the use of the Internet to access health resources, and reducing the patient's level of concern about their health status to improve the level of eHealth literacy of cardiovascular patients.
eHealth literacy is important as it influences health-promoting behaviors and health. The ability to use eHealth resources is essential to maintaining health, especially during COVID-19 when both physical and psychological health were affected. This study aimed to assess the prevalence of eHealth literacy and its association with psychological distress and perceived health status among older adults in Blekinge, Sweden. Furthermore, this study aimed to assess if perceived health status influences the association between eHealth literacy and psychological distress. This cross-sectional study (October 2021-December 2021) included 678 older adults' as participants of the Swedish National Study on Aging and Care, Blekinge (SNAC-B). These participants were sent questionnaires about their use of Information and Communications Technology (ICT) during the COVID-19 pandemic. In this study, we conducted the statistical analysis using the Kruskal-Wallis one-way analysis of variance, Kendall's tau-b rank correlation, and multiple linear regression. We found that 68.4% of the participants had moderate to high levels of eHealth literacy in the population. Being female, age [Formula: see text] years, and having a higher education are associated with high eHealth literacy ([Formula: see text]). eHealth literacy is significantly correlated ([Formula: see text]=0.12, p-value=0.002) and associated with perceived health status ([Formula: see text]=0.39, p-value=0.008). It is also significantly correlated ([Formula: see text]=-0.12, p-value=0.001) and associated with psychological distress ([Formula: see text]=-0.14, p-value=0.002). The interaction of eHealth literacy and good perceived health status reduced psychological distress ([Formula: see text]=-0.30, p-value=0.002). In our cross-sectional study, we found that the point prevalence of eHealth literacy among older adults living in Blekinge, Sweden is moderate to high, which is a positive finding. However, there are still differences among older adults based on factors such as being female, younger than 75 years, highly educated, in good health, and without psychological distress. The results indicated that psychological distress could be mitigated during the pandemic by increasing eHealth literacy and maintaining good health status.
eHealth resources and interventions promise to promote favorable behavior change, self-efficacy, and knowledge acquisition, thereby improving health literacy. However, individuals with limited eHealth literacy may find it difficult to identify, understand, and benefit from eHealth use. It is necessary to identify the self-assessed eHealth literacy of those who use eHealth resources to classify their eHealth literacy levels and to determine the demographic characteristics associated with higher and lower eHealth literacy skills. This study aimed to identify notable factors closely associated with limited eHealth literacy among Chinese male populations to provide some implications for clinical practice, health education, medical research, and public health policy making. We hypothesized that participants' eHealth literacy status was associated with various demographic characteristics. Therefore, we elicited the following information in the questionnaire: age and education, self-assessed disease knowledge, 3 well-developed health literacy assessment tools (ie, the All Aspects of Health Literacy Scale, eHealth Literacy Scale, and General Health Numeracy Test), and the 6 Internal items on health beliefs and self-confidence in the Multidimensional Health Locus of Control Scales. Using randomized sampling, we recruited survey participants from Qilu Hospital of Shandong University, China. After validating the data collected through a web-based questionnaire survey via wenjuanxing, we coded all valid data according to predefined coding schemes of Likert scales with different point (score) ranges. We then calculated the total scores of the subsections of the scales or the entire scale. Finally, we used logistic regression modeling to associate the scores of the eHealth Literacy Scale with the scores of the All Aspects of Health Literacy Scale, the General Health Numeracy Test-6, and age and education to ascertain factors considerably associated with limited eHealth literacy among Chinese male populations. All data from the 543 returned questionnaires were valid according to the validation criteria. By interpreting these descriptive statistics, we found that 4 factors were significantly correlated with participants' limited eHealth literacy: older age, lower education attainment, lower levels of all aspects of health literacy (functional, communicative, and critical), and weaker beliefs and self-confidence in internal drivers and strengths to stay healthy. By applying logistic regression modeling, we ascertained 4 factors that were significantly correlated with limited eHealth literacy among Chinese male populations. These relevant factors identified can inform stakeholders engaging in clinical practice, health education, medical research, and health policy making.
Elder abuse is a single or repeated act, or lack of appropriate action, which causes harm to an older person. This systematic review and meta-analysis aimed to assess the prevalence of elder abuse in Sub Saharan Africa. This systematic review and meta-analysis involved a comprehensive search of electronic databases, including PubMed, Scopus, Web of Science, African Journals Online and Google Scholar. Cochrane I2 statistics and Eggers test with funnel plot were done to check heterogeneity and publication bias, respectively. Five studies with 2123 elderly people aged 60 and above were included in this review. The pooled prevalence of elder abuse was (46.73 % (45.08-48.38)) with a substantial level of heterogeneity (I2 =99.7 %; p < 0.001). To overcome the effect of high level heterogeneity subgroup analysis was deployed. Accordingly, the subgroup analysis by publication year revealed that the prevalence of elder abuse was highest among studies conducted after 2018 (64.034 (95 % CI: 12.66, 115.4). Similarly, sub-group analysis by country revealed that the prevalence of elder abuse was highest in Ethiopia (63.2(21.276, 105.124).The subgroup analysis by the sampling technique revealed that elder abuse was highest among studies conducted using systematic random sampling technique (84.57 (95 % CI: 79.22, 89.92). Subgroup analysis by type of abuse revealed that physical abuse was highest (29.27 (-7.854, 66.394)) CONCLUSION: The pooled prevalence of elder abuse was high and, physical abuse was the commonest type of abuse. As a result, there should be awareness creation about the caring of elders to minimize abuse.
Elea-Maria Abisamra is an honors undergraduate student and research fellow at Virginia Tech. She is majoring in Cognitive and Behavioral Neuroscience and has passions for STEM, writing, and entrepreneurship. In June 2022, Elea acted on her dream and founded Kids Can Write, becoming a CEO of a global nonprofit organization helping turn kids into published authors while teaching them STEM in an innovative and unique way. This is her story.
Electrical burns are devastating injuries and can cause deep burns with significant morbidity and delayed sequelae. Epidemiological data regarding the etiology, socioeconomic differences and geographic variation are necessary to assess the disease burden and plan an effective preventive strategy. These severe injuries often lead to amputations and thus hamper quality of life in the long term. To identify the population at maximum risk of sustaining electrical burns. We also studied the impact of electrical burns on these patients in terms of quality of life as well as return to work. The study was conducted at a tertiary referral teaching hospital over a period of eighteen months. All patients with a history of sustaining electrical burns and satisfying the inclusion criteria were included in the study. All relevant epidemiological parameters and treatment details were recorded. The patients were subsequently followed up at 3 mo, 6 mo and 9 mo. The standardized Brief Version of the Burn Speciﬁc Health Scale (BSHS-B) was adopted to assess quality of life. Statistical analysis was conducted using IBM SPSS statistics (version 22.0). A P value of < 0.05 was considered statistically significant. A total of 103 patients were included in the study. The mean age of the patients was 31.83 years (range 18-75 years). A significant majority (91.3%) of patients were male. The mean total body surface area (TBSA) in these patients was 21.1%. In most of the patients (67%), the injury was occupation-related. High voltage injuries were implicated in 72.8% of patients. Among the 75 high voltage burn patients, 31 (41%) required amputation. The mean number of surgeries the patients underwent in hospital was 2.03 (range 1 to 4). The quality of life parameters amongst the patients sustaining high voltage electrical burns were poorer when compared to low voltage injuries at all follow-up intervals across nine domains. In eight of these domains, the difference was statistically significant. Similarly, the scores among the amputees were poorer when compared to non-amputees. The difference was statistically significant in six domains. Electrical burns remain a problem in the developing world. Most injuries are occupation-related. The quality of life in patients with high voltage burns and amputees remains poor. Work resumption was almost impossible for amputees. These patients could not regain pre-injury status. Steps should be taken to create awareness and to implement an effective preventive strategy to safeguard against electrical injuries.
Electrocardiogram (ECG) is a convenient, economic, and non-invasive detecting tool in myocardial ischemia (MI). Its clinical appearance is mainly exhibited by ST-T complex change. MI events are usually instantaneous and asymptomatic in some cases, which cannot be forecasted to have a precautionary measure in time by doctors. The automatic detection of MI by computer and a cued warning of danger in real time play an important role in diagnosing heart disease. With the help of the medical staff, some quantitative approbatory indicators, such as ST-segment deviation, the amplitude of T-wave peak and the rate of ST and heart rate (HR), were combined to judge MI using fuzzy reasoning. After MIT-BIH database and the long-term ST database (LTST) verification, sensitivity and positive predictive values reached 75% and 78% respectively, and specificity and negative predictive values were 85% and 87% respectively. In addition, the proposed method was close to human way of thinking and understanding, and easy to apply in clinical detection and engineering fields.
Electrocardiogram (ECG) is widely considered the primary test for evaluating cardiovascular diseases. However, the use of artificial intelligence (AI) to advance these medical practices and learn new clinical insights from ECGs remains largely unexplored. We hypothesize that AI models with a specific design can provide fine-grained interpretation of ECGs to advance cardiovascular diagnosis, stratify mortality risks, and identify new clinically useful information. Utilizing a data set of 2 322 513 ECGs collected from 1 558 772 patients with 7 years follow-up, we developed a deep-learning model with state-of-the-art granularity for the interpretable diagnosis of cardiac abnormalities, gender identification, and hypertension screening solely from ECGs, which are then used to stratify the risk of mortality. The model achieved the area under the receiver operating characteristic curve (AUC) scores of 0.998 (95% confidence interval (CI), 0.995-0.999), 0.964 (95% CI, 0.963-0.965), and 0.839 (95% CI, 0.837-0.841) for the three diagnostic tasks separately. Using ECG-predicted results, we find high risks of mortality for subjects with sinus tachycardia (adjusted hazard ratio (HR) of 2.24, 1.96-2.57), and atrial fibrillation (adjusted HR of 2.22, 1.99-2.48). We further use salient morphologies produced by the deep-learning model to identify key ECG leads that achieved similar performance for the three diagnoses, and we find that the V1 ECG lead is important for hypertension screening and mortality risk stratification of hypertensive cohorts, with an AUC of 0.816 (0.814-0.818) and a univariate HR of 1.70 (1.61-1.79) for the two tasks separately. Using ECGs alone, our developed model showed cardiologist-level accuracy in interpretable cardiac diagnosis and the advancement in mortality risk stratification. In addition, it demonstrated the potential to facilitate clinical knowledge discovery for gender and hypertension detection which are not readily available.
Electrocardiograms (ECGs) are a cornerstone in cardiac care. Traditional statistical metrics like sensitivity and specificity are commonly used for diagnostic evaluations but are limited when applied in clinical settings due to their inability to incorporate pre-test likelihoods or individual patient context. Traditional diagnostic metrics do not provide a complete picture in clinical scenarios. Bayesian reasoning allows for a more nuanced approach, integrating pre-test probabilities and individual patient context to produce more accurate post-test probabilities. This was demonstrated through Bayesian analysis of four clinical cases. Bayesian reasoning enhances diagnostic accuracy and personalizes patient care by integrating prior probabilities into diagnostic decision-making. This shift toward Bayesian reasoning is crucial for improving patient outcomes in the era of evidence-based medicine.