Hasil untuk "Computer applications to medicine. Medical informatics"

Jinnan Hu, Donald Freed, Hanying Feng et al.

BackgroundIntegrating short- and long-read sequencing technologies has become a promising approach for achieving accurate and comprehensive genomic analysis. Although short-read sequencing (Illumina, etc.) offers high base accuracy and cost efficiency, it struggles with structural variant (SV) detection and complex genomic regions. In contrast, long-read sequencing (PacBio HiFi) excels in resolving large SVs and repetitive sequences but is limited by throughput, higher insertion or deletion (indel) error rates, and sequencing costs. Hybrid approaches may combine these technologies and leverage their complementary strengths and different sources of error to provide higher accuracy, more comprehensive results, and higher throughput by lowering the coverage requirement for the long reads.MethodsThis study benchmarks the DNAscope Hybrid (DS-Hybrid) pipeline, a novel integrated alignment and variant calling framework that combines short- and long-read data sequenced from the same sample. The DNAscope Hybrid pipeline is a bioinformatics pipeline that runs on generic x86 CPUs. We evaluate its performance across multiple human genome reference datasets (HG002–HG004) using the draft Q100 and Genome in a Bottle v4.2.1 benchmarks. The pipeline’s ability to detect small variants [single-nucleotide polymorphisms (SNPs)/indels)], SVs, and copy-number variations (CNVs) is assessed using data from the Illumina and PacBio sequencing systems at varying read depths (5×–30×). Benchmark results are compared to those of DeepVariant.ResultsThe DNAscope Hybrid pipeline significantly improves SNP and indel calling accuracy, particularly in complex genomic regions. At lower long-read depths (e.g., 5×–10×), the hybrid approach outperforms stand-alone short- or long-read pipelines at full sequencing depths (30×–35×), reducing variant calling errors by at least 50%. Additionally, the DNAscope Hybrid outperforms leading open-source tools for SV and CNV detection and enhances variant discovery in challenging genomic regions. The pipeline also demonstrates clinical utility by identifying variants in disease-associated genes. Moreover, DNAscope Hybrid is highly efficient, achieving less than 90 min runtimes at single standard instance.ConclusionThe DNAscope Hybrid pipeline is a computationally efficient, highly accurate variant calling framework that leverages the advantages of both short- and long-read sequencing. By improving variant detection in challenging genomic regions and offering a robust solution for clinical and large-scale genomic applications, it holds significant promise for genetic disease diagnostics, population-scale studies, and personalized medicine.

Jing Jin, Yun Wang, Sixiang Liang et al.

Objective: Repetitive transcranial magnetic stimulation (rTMS) has been shown to alleviate depressive and anxiety symptoms in patients with major depressive disorder (MDD), typically by targeting the dorsolateral (DLPFC) or dorsomedial prefrontal cortex (DMPFC). Based on a pre-registered randomized controlled trial, this study presents an exploratory neuroimaging analysis investigating the impact of rTMS targeting the DLPFC versus the DMPFC on functional connectivity with the default mode network (DMN) and frontal-parietal network (FPN) in patients with MDD. Methods: Sixty-four MDD patients were randomly assigned to DLPFC-rTMS (n = 36) or DMPFC-rTMS (n = 28) groups for a 21-day intervention. Symptoms were evaluated with Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA). Changes in individualized functional connectivity (inFC) between individualized targets and DMN/FPN were assessed and correlated with symptom improvements. As a control analysis, FC was evaluated based on the group-based seeds of DLPFC or DMPFC. Additionally, symptom-specific circuit map comparisons were conducted. Results: Both groups showed symptom improvements and changes in inFC with the DMN and FPN, but the specific connectivity profiles differ. In the DMN, the DLPFC-rTMS group showed decreased negative connectivity between left DLPFC and precuneus (t = -2.39, p = 0.022), while the DMPFC-rTMS group showed increased positive inFC between DMPFC and precuneus (t = -2.78, p = 0.01, FDR adjusted p = 0.034) and PCC (t = -3.15, p = 0.004, FDR adjusted p = 0.028). In the FPN, the DLPFC group showed decreased negative inFC with medial superior frontal gyrus (t = -2.35, p = 0.024) and decreased positive inFC with inferior parietal lobule (t = 2.3, p = 0.028). The DMPFC group showed increased positive connectivity with inferior frontal gyrus (t = -3.65, p = 0.001, FDR adjusted p = 0.019) and su pplementary motor area (t = -2.24, p = 0.033), and decreased negative connectivity with middle cingulate cortex (t = 2.27, p = 0.032). Canonical correlation analysis revealed a strong association between inFC changes and depression symptom improvement in the DMPFC-rTMS group (r = 0.57). Group seed-based FC changes were limited to the FPN and correlated with depressive improvement in the DLPFC-rTMS group (r = 0.52). Symptom-specific circuit maps linked to depression and anxiety were consistent across targets. Conclusion: Both DLPFC and DMPFC rTMS alleviate depressive and anxiety symptoms, displaying similar overall circuit patterns but distinct connectivity changes specific to their targets.

Eray Yilmaz, Keegan D’Mello, Amrit Kirpalani

Elizabeth K. Farkouh, Loren L. Toussaint, Brian A. Lynch

Introduction/Objectives: Social determinants of health (SDOH) have the potential to differentially impact child developmental outcomes. This study examined whether scores on the Environmental Screening Questionnaire (ESQ), a newly developed SDOH screening tool, were associated with scores on the Brigance and Ages & Stages Questionnaires-Social-Emotional (ASQ:SE-2) child development assessments. Methods: Brigance, ASQ:SE-2, and ESQ scores from children enrolled in a Head Start Program in Northeast Iowa were collected during the 2021 to 2022 and 2022 to 2023 school years. Associations between scores in each ESQ domain and Brigance and ASQ:SE-2 scores were assessed. Results: Education-Employment and Community concerns on the ESQ were associated with reduced Brigance scores ( r  = −.21, P  < .001; r  = −.17, P  = .001). Concerns related to Housing, Child and Family Health, and Community were associated with more concerning ASQ:SE-2 scores ( r  = .14, P  = .005; r  = .18, P  < .001; r  = 0.27, P  < .001). In multivariable models controlling for sex and ethnicity, Education-Employment concerns were significant predictors of lower Brigance scores, while Child and Family Health and Community concerns were significant predictors of ASQ:SE-2 scores. Conclusions: ESQ scores in certain SDOH domains correlate significantly with child developmental outcomes. The ESQ domains of Child and Family Health and Community appear to be particularly important for appropriate child socio-emotional development. Interventions should focus on addressing critical SDOH domains to promote child resilience and counteract the non-medical factors that can interfere with child developmental outcomes.

Jiao Li, Xiaojuan Jing, Qin Zhang et al.

Abstract Background Subepithelial lesions (SELs) present significant diagnostic challenges in gastrointestinal endoscopy, particularly in differentiating malignant types, such as gastrointestinal stromal tumors (GISTs) and neuroendocrine tumors, from benign types like leiomyomas. Misdiagnosis can lead to unnecessary interventions or delayed treatment. To address this challenge, we developed ECMAI-WME, a parallel fusion deep learning model integrating white light endoscopy (WLE) and microprobe endoscopic ultrasonography (EUS), to improve SEL classification and lesion characterization. Methods A total of 523 SELs from four hospitals were used to develop serial and parallel fusion AI models. The Parallel Model, demonstrating superior performance, was designated as ECMAI-WME. The model was tested on an external validation cohort (n = 88) and a multicenter test cohort (n = 274). Diagnostic performance, lesion characterization, and clinical decision-making support were comprehensively evaluated and compared with endoscopists’ performance. Results The ECMAI-WME model significantly outperformed endoscopists in diagnostic accuracy (96.35% vs. 63.87–86.13%, p < 0.001) and treatment decision-making accuracy (96.35% vs. 78.47–86.13%, p < 0.001). It achieved 98.72% accuracy in internal validation, 94.32% in external validation, and 96.35% in multicenter testing. For distinguishing gastric GISTs from leiomyomas, the model reached 91.49% sensitivity, 100% specificity, and 96.38% accuracy. Lesion characteristics were identified with a mean accuracy of 94.81% (range: 90.51–99.27%). The model maintained robust performance despite class imbalance, confirmed by five complementary analyses. Subgroup analyses showed consistent accuracy across lesion size, location, or type (p > 0.05), demonstrating strong generalizability. Conclusions The ECMAI-WME model demonstrates excellent diagnostic performance and robustness in the multiclass SEL classification and characterization, supporting its potential for real-time deployment to enhance diagnostic consistency and guide clinical decision-making.

Chika Yinka-Banjo, Mary Akinyemi, Olasupo Ajayi et al.

Gender equity, particularly in healthcare, has been gaining increasing attention in recent years. The goal is to ensure that everyone has equal access to quality healthcare services irrespective of age, gender, or socio-economic status. However, most countries in sub-Saharan Africa struggle to meet this goal, due to several challenges, including poverty, poor infrastructure, and gender-bias. Using Nigeria as a case-study, it is common knowledge that gender inequality and discrimination is predominant in the northern region of the country. This work sought to gather data to assess the level of healthcare accessibility from a gender-based perspective in northern Nigeria. Data were sourced anonymously from residents in about 500 locations across the northern region of Nigeria, using WhatsApp-based questionnaires, in two phases and two languages - English and Hausa. About 4700 participants took part in the survey and each had to answer 43 questions, split into demographic, socio-economic, wellness check, and diversity, equity, and inclusion (DEI) in health care services obtained.

Michael Barnett, Dongang Wang, Heidi Beadnall et al.

Abstract Modern management of MS targets No Evidence of Disease Activity (NEDA): no clinical relapses, no magnetic resonance imaging (MRI) disease activity and no disability worsening. While MRI is the principal tool available to neurologists for monitoring clinically silent MS disease activity and, where appropriate, escalating treatment, standard radiology reports are qualitative and may be insensitive to the development of new or enlarging lesions. Existing quantitative neuroimaging tools lack adequate clinical validation. In 397 multi-center MRI scan pairs acquired in routine practice, we demonstrate superior case-level sensitivity of a clinically integrated AI-based tool over standard radiology reports (93.3% vs 58.3%), relative to a consensus ground truth, with minimal loss of specificity. We also demonstrate equivalence of the AI-tool with a core clinical trial imaging lab for lesion activity and quantitative brain volumetric measures, including percentage brain volume loss (PBVC), an accepted biomarker of neurodegeneration in MS (mean PBVC −0.32% vs −0.36%, respectively), whereas even severe atrophy (>0.8% loss) was not appreciated in radiology reports. Finally, the AI-tool additionally embeds a clinically meaningful, experiential comparator that returns a relevant MS patient centile for lesion burden, revealing, in our cohort, inconsistencies in qualitative descriptors used in radiology reports. AI-based image quantitation enhances the accuracy of, and value-adds to, qualitative radiology reporting. Scaled deployment of these tools will open a path to precision management for patients with MS.

M. Daniela Vélez, Johanna Pedroza-Díaz, Gloria A. Santa-González

Functional foods, beyond basic nutrition, offer health benefits to consumers thanks to the presence of bioactive compounds such as some phytochemicals [1,2]. Today, these foods are of particular interest in biomedical research due to their chemopreventive potential, as they have been shown to induce various biological effects on tumor cells, including the ability to inhibit cell proliferation, induce apoptosis, arrest cell cycle progression, and increase reactive oxygen species [3,4]. Multiple studies have confirmed the relationship between diet and the onset and progression of colorectal cancer (CRC), a malignant neoplasm that arises in the lining of the colon and/or rectum. Therefore, finding foods that can intervene in the carcinogenesis process is an important avenue of research [5,6].Chlorogenic acid (CGA) is one of the most abundant phenolic compounds in coffee and is also found in fruits and vegetables. Scientific evidence suggests that CGA has chemopreventive potential on CRC cells [7–9]. For example, in previous studies conducted by our research group, green and roasted coffee extracts were characterized, and this compound was identified as the most abundant [7]. In addition, it was found to significantly decrease cell viability, reduce migration capacity, cause DNA fragmentation, and induce the production of reactive oxygen species in colorectal adenocarcinoma cells cultured in monolayer and treated with different doses of CGA. Furthermore, the mechanism underlying this biological activity has been related to CGA's ability to modulate the Wnt- /β-catenin pathway, which is implicated in the development and progression of CRC [7,10,11].This paper presents data on the cytotoxic response of CGA treatments on HT-29 cells cultured in a 3D model. To this end, morphological changes in cell spheroids, propidium iodide and DiOC6 uptake, quantification of reactive oxygen species (ROS) production, phosphatidylserine exposure, and cell cycle progression were evaluated by flow cytometry.

Dakota Aaron McCarty, Hyun Woo Kim

Point of interest (POI) data refers to information about the location and type of amenities, services, and attractions within a geographic area. This data is used in urban studies research to better understand the dynamics of a city, assess community needs, and identify opportunities for economic growth and development. POI data is beneficial because it provides a detailed picture of the resources available in a given area, which can inform policy decisions and improve the quality of life for residents. This paper presents a large-scale, standardized POI dataset from OpenStreetMap (OSM) for the European continent. The dataset's standardization and gridding make it more efficient for advanced modeling, reducing 7,218,304 data points to 988,575 without significant resolution loss, suitable for a broader range of models with lower computational demands. The resulting dataset can be used to conduct advanced analyses, examine POI spatial distributions, conduct comparative regional studies, and research to help enhance the understanding of the distribution of economic activity and attractions, and subsequently help in the understanding of the economic health, growth potential, and cultural opportunities of an area. The paper describes the materials and methods used in generating the dataset, including OSM data retrieval, processing, standardization, hexagonal grid generation, and point count aggregations. The dataset can be used independently or integrated with other relevant datasets for more comprehensive spatial distribution studies in future research.

Iman Kassam, Hwayeon Danielle Shin, Keri Durocher et al.

Background OpenNotes is the concept of patients having access to their health records and clinical notes in a digital form. In psychiatric settings, clinicians often feel uncomfortable with this concept, and require support during implementation. Objective This study utilizes an implementation science lens to explore clinicians’ perceptions about using OpenNotes in Canadian psychiatric care contexts. The findings are intended to inform the co-design of implementation strategies to support the implementation of OpenNotes in Canadian contexts. Method This qualitative descriptive study employed semi-structured interviews which were completed among health professionals of varying disciplines working in direct care psychiatric roles. Data analysis consisted of a qualitative directed content analysis using themes outlined from an international Delphi study of mental health clinicians and experts. Ethical approval was obtained from the Centre for Addiction and Mental Health and the University of Toronto. Results In total, 23 clinicians from psychiatric settings participated in the interviews. Many of the themes outlined within the Delphi study were voiced. Benefits included enhancements to patient recall, and empowerment, improvements to care quality, strengthened relational effects and effects on professional autonomy and efficiencies. Despite the anticipated benefits of OpenNotes, identified challenges pertained to clarity surrounding exemption policies, training on patient facing notes, managing disagreements, and educating patients on reading clinical notes. Conclusion Many benefits and challenges were identified for adopting OpenNotes in Canadian psychiatric settings. Future work should focus on applying implementation frameworks to develop interventions that address the identified challenges.

Janice R Turek, Vikas Bansal, Aysun Tekin et al.

BackgroundThe rapid emergence of the COVID-19 pandemic globally collapsed health care organizations worldwide. Incomplete knowledge of best practices, progression of disease, and its impact could result in fallible care. Data on symptoms and advancement of the SARS-CoV-2 virus leading to critical care admission have not been captured or communicated well between international organizations experiencing the same impact from the virus. This led to the expedited need for establishing international communication and data collection on the critical care patients admitted with COVID-19. ObjectiveDeveloping a global registry to collect patient data in the critical care setting was imperative with the goal of analyzing and ameliorating outcomes. MethodsA prospective, observational global registry database was put together to record extensive deidentified clinical information for patients hospitalized with COVID-19. ResultsProject management was crucial for prompt implementation of the registry for synchronization, improving efficiency, increasing innovation, and fostering global collaboration for valuable data collection. The Society of Critical Care Medicine Discovery VIRUS (Viral Infection and Respiratory Illness Universal Study): COVID-19 Registry would compile data for crucial longitudinal outcomes for disease, treatment, and research. The agile project management approach expedited establishing the registry in 15 days and submission of institutional review board agreement for 250 participating sites. There has been enrollment of sites every month with a total of 306 sites from 28 countries and 64,114 patients enrolled (as of June 7, 2021). ConclusionsThis protocol addresses project management lessons in a time of crises which can be a precept for rapid project management for a large-scale health care data registry. We aim to discuss the approach and methodology for establishing the registry, the challenges faced, and the factors contributing to successful outcomes. Trial RegistrationClinicalTrials.gov NCT04323787; https://clinicaltrials.gov/ct2/show/NCT04323787

Evelyn Abrahante Terrell, Andy Bopp, Kristen Neville et al.

The American Occupational Therapy Association, the American Physical Therapy Association, the American Speech-Language-Hearing Association and the American Telemedicine Association are collaborating to advance telehealth and ensure sustainability of virtual care services beyond the COVID-19 pandemic. These professional associations represent the interests of more than 888,000 rehabilitation services professionals. This paper summarizes the current state of telehealth policy principles and priorities for rehabilitation services. The report outlines key considerations when advocating with policymakers to avoid the “Telehealth Cliff” for audiology and therapy services and to facilitate the continued advancement of telehealth innovation and transformation by rehabilitation services professionals.

Martin Kuna, Roman Křivánek, Ondřej Chvojka et al.

The archaeological site of Březnice (Czechia) represents one of the large settlements of the Late Bronze Age (Ha A2/B1, 14C: 1124–976 BC) in Bohemia. The site became known mainly for a high number of so-called ‘trenches’, oblong pit features (breadth around 1 m, length 4–7 m), remarkable not only for their specific shape but also for their contents (unusual amounts of pottery, daub, loom weights and other finds, often with traces of a strong fire).In 2018–20, a research project focusing on the study of the site was realized. Magnetometer survey became an integral part of the project since it represented a way to obtain an overall image of the site. A 5-channel fluxgate gradiometer from Sensys (Germany) was used; the vertical gradient of the Z component of the Earth magnetic field was measured. In total, the survey covered an area of over 17 hectares and included over 1.8 million measurements. Profiles were orientated from east to west and data taken bidirectionally (alternate lines in opposite directions), in a 0.5 × 0.2 m grid.The site is extraordinary due to the fact that all archaeological features discovered so far belong to a single archaeological period (Late Bronze Age). This makes the acquired data set exceptional. It can be further used by archaeologists and geophysicists, both to create alternative models of the dynamics of prehistoric settlements and to better understand the nature and interpretive possibilities of the magnetometer data in archaeology as such.

Gaspar, Andréa G Martins, Lapão, Luís Velez

BackgroundThe population is aging on a global scale, triggering vulnerability for chronic multimorbidity, balance disorders, and falls. Falls with injuries are the main cause of accidental death in the elderly population, representing a relevant public health problem. Balance disorder is a major risk factor for falling and represents one of the most frequent reasons for health care demand. The use of information and communication technologies to support distance healthcare (eHealth) represents an opportunity to improve the access and quality of health care services for the elderly. In recent years, several studies have addressed the potential of eHealth devices to assess the balance and risk of falling of elderly people. Remote rehabilitation has also been explored. However, the clinical applicability of these digital solutions for elderly people with balance disorders remains to be studied. ObjectiveThe aim of this review was to guide the clinical applicability of eHealth devices in providing the screening, assessment, and treatment of elderly people with balance disorders, but without neurological disease. MethodsA systematic review was performed in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement. Data were obtained through searching the PubMed, Google Scholar, Embase, and SciELO databases. Only randomized controlled trials (RCTs) or quasiexperimental studies (QESs) published between January 2015 and December 2019 were included. The quality of the evidence to respond to the research question was assessed using Joanna Briggs Institute (JBI) Critical Appraisal for RCTs and the JBI Critical Appraisal Checklist for QESs. RCTs were assessed using the Cochrane risk of bias tool. We provide a narrative synthesis of the main outcomes from the included studies. ResultsAmong 1030 unduplicated articles retrieved, 21 articles were included in this review. Twelve studies explored different technology devices to obtain data about balance and risk of falling. Nine studies focused on different types of balance exercise training. A wide range of clinical tests, functional scales, classifications of faller participants, sensor-based tasks, intervention protocols, and follow-up times were used. Only one study described the clinical conditions of the participants. Instrumental tests of the inner ear were neither used as the gold-standard test nor performed in pre and postrehabilitation assessments. ConclusionseHealth has potential for providing additional health care to elderly people with balance disorder and risk of falling. In the included literature, the heterogeneity of populations under study, methodologies, eHealth devices, and time of follow-up did not allow for clear comparison to guide proper clinical applicability. This suggests that more rigorous studies are needed.

Bridget R. Scanlon, Robert C. Reedy, Pei Xu et al.

The data in this report are associated with https://doi.org/10.1016/j.scitotenv.2020.137085 [4] and include data on water volumes and water quality related to the major unconventional oil and gas plays in the U.S. The data include volumes of water co-produced with oil and gas production, county-level estimates of annual water use volumes by various sectors, including hydraulic fracturing water use, and the quality of produced water. The data on volumes of produced water and hydraulic fracturing water volumes were obtained from the IHS Enerdeq and FracFocus databases. Water use in other sectors was obtained from the U.S. Geological Survey water use database. Data on produced water quality were obtained from the USGS produced waters database.

Fiza Singh, I-Wei Shu, Sheng-Hsiou Hsu et al.

Schizophrenia is a debilitating mental disorder that is associated with cognitive deficits. Impairments in cognition occur early in the course of illness and are associated with poor functional outcome, but have been difficult to treat with conventional treatments. Recent studies have implicated abnormal neural network dynamics and impaired connectivity in frontal brain regions as possible causes of cognitive deficits. For example, high-frequency, dorsal-lateral prefrontal oscillatory activity in the gamma range (30–50 Hz) is associated with impaired working memory in individuals with schizophrenia. In light of these findings, it may be possible to use EEG neurofeedback (EEG-NFB) to train individuals with schizophrenia to enhance frontal gamma activity to improve working memory and cognition. In a single-group, proof-of-concept study, 31 individuals with schizophrenia received 12 weeks of twice weekly EEG-NFB to enhance frontal gamma band response. EEG-NFB was well-tolerated, associated with increased gamma training threshold, and significant increases in frontal gamma power during an n-back working memory task. Additionally, EEG-NFB was associated with significant improvements in n-back performance and working memory, speed of processing, and reasoning and problem solving on neuropsychological tests. Change in gamma power was associated with change in cognition. Significant improvements in psychiatric symptoms were also found. These encouraging findings suggest EEG-NFB targeting frontal gamma activity may provide a novel effective approach to cognitive remediation in schizophrenia, although placebo-controlled trials are needed to assess the effects of non-treatment related factors.

Hesse, Bradford William

Internet-augmented medicine has a strong role to play in ensuring that all populations benefit equally from discoveries in the medical sciences. Yet, data from the Centers for Disease Control and Prevention collected from 1999 to 2014 suggested that during the first phase of internet diffusion, progress against mortality has stalled, and in some cases, receded in rural areas that are traditionally underserved by medical and broadband resources. This problem of failing to extend the benefits of extant medical knowledge equitably to all populations regardless of geography can be framed as the “last mile problem in health care.” In theory, the internet should help solve the last mile problem by making the best knowledge in the world available to everyone worldwide at a low cost and no delay. In practice, the antiquated supply chains of industrial age medicine have been slow to yield to the accelerative forces of evolving internet capacity. This failure is exacerbated by the expanding digital divide, preventing residents of isolated, geographically distant communities from taking full advantage of the digital health revolution. The result, according to the Federal Communications Commission’s (FCC’s) Connect2Health Task Force, is the unanticipated emergence of “double burden counties,” ie, counties for which the mortality burden is high while broadband access is low. The good news is that a convergence of trends in internet-enabled health care is putting medicine within striking distance of solving the last mile problem both in the United States and globally. Specific trends to monitor over the next 25 years include (1) using community-driven approaches to bridge the digital divide, (2) addressing structural disconnects in care through P4 Medicine, (3) meeting patients at “point-of-need,” (4) ensuring that no one is left behind through population management, and (5) self-correcting cybernetically through the learning health care system.

Olujide A. Adekeye, Emmanuel O. Amoo, Sussan O. Adeusi et al.

Alcohol is the most widely used substance of abuse among youths in Nigeria. Underage drinking poses a serious public health problem in most colleges and despite the health and safety risk, consumption of alcohol is rising. Having recourse to the public health objective on alcohol by the World Health organization, which is to reduce the health burden caused by the harmful use of alcohol, thereby saving live and reducing injuries, this data article explored the nature of alcohol use among college students, binge drinking and the consequences of alcohol consumption. Secondary school students are in a transition developmentally and this comes with its debilitating effects such as risky alcohol use which affects their health and educational attainment [1,2]. This data article consists of data obtained from 809 (ages 14–20 years) participants from selected schools in Ota, near Lagos State, Nigeria. For data collection, the youth questionnaire on underage drinking was employed. This data article presents information on participants' alcohol demographics. Analyses of the data can provide insights into heavy episodic drinking (HED), ever drinkers, prevalence of alcohol consumption, strategies to reducing alcohol use, reasons for underage drinking and effects of alcohol consumption. The data will be useful for public health interventions. Keywords: Alcohol, College, Underage drinking, Youths, Nigeria

Waleed Al-Rahmi, Ahmed Aldraiweesh, Noraffandy Yahaya et al.

The data presented in this article are based on provides a systematic and organized review of 219 studies regarding using of Massive Open Online Courses (MOOCs) in higher education from 2012 to 2017. Consequently, the extant, peer-reviewed literature relating to MOOCs was methodically assessed, as a means of formulating a classification for MOOC-focused scholarly literature. The publication journal, country of origin, researchers, release data, theoretical approach, models, methodology and study participants were all factors used to assess and categorise the MOOC. These data contribute to materials required by readers who are interested in different aspects related to the literature of using Massive Open Online Courses (MOOCs) in higher education. Intention to use, interaction, engagement, motivations and satisfaction were five dynamics assessed in relation to the improvement of MOOCs. Students’ academic performance can be influenced by MOOC which has the advantage of facilitating the learning process through offering materials and enabling the share of information. Keywords: Massive Open Online Courses (MOOCs), Higher education, Systematic literature review

T. Sahama, A. Stranieri, Priyantha Hewagamage et al.