bluuebunny/crossref_metadata_2025_split huggingface dataset:
Continuous mHealth Patch Monitoring for the Algorithm-Based Detection of Atrial Fibrillation: Feasibility and Diagnostic Accuracy Study
Authors: Santala Onni E , Lipponen Jukka A , Jäntti Helena , Rissanen Tuomas T , Tarvainen Mika P , Laitinen Tomi P , Laitinen Tiina M , Castrén Maaret , Väliaho Eemu-Samuli , Rantula Olli A , Naukkarinen Noora S , Hartikainen Juha E K , Halonen Jari , Martikainen Tero J 
Published: June 2022

Background
The detection of atrial fibrillation (AF) is a major clinical challenge as AF is often paroxysmal and asymptomatic. Novel mobile health (mHealth) technologies could provide a cost-effective and reliable solution for AF screening. However, many of these techniques have not been clinically validated.

Objective
The purpose of this study is to evaluate the feasibility and reliability of artificial intelligence (AI) arrhythmia analysis for AF detection with an mHealth patch device designed for personal well-being.

Methods
Patients (N=178) with an AF (n=79, 44%) or sinus rhythm (n=99, 56%) were recruited from the emergency care department. A single-lead, 24-hour, electrocardiogram-based heart rate variability (HRV) measurement was recorded with the mHealth patch device and analyzed with a novel AI arrhythmia analysis software. Simultaneously registered 3-lead electrocardiograms (Holter) served as the gold standard for the final rhythm diagnostics.

Results
Of the HRV data produced by the single-lead mHealth patch, 81.5% (3099/3802 hours) were interpretable, and the subject-based median for interpretable HRV data was 99% (25th percentile=77% and 75th percentile=100%). The AI arrhythmia detection algorithm detected AF correctly in all patients in the AF group and suggested the presence of AF in 5 patients in the control group, resulting in a subject-based AF detection accuracy of 97.2%, a sensitivity of 100%, and a specificity of 94.9%. The time-based AF detection accuracy, sensitivity, and specificity of the AI arrhythmia detection algorithm were 98.7%, 99.6%, and 98.0%, respectively.

Conclusions
The 24-hour HRV monitoring by the mHealth patch device enabled accurate automatic AF detection. Thus, the wearable mHealth patch device with AI arrhythmia analysis is a novel method for AF screening.

Trial Registration
ClinicalTrials.gov NCT03507335; https://clinicaltrials.gov/ct2/show/NCT03507335
Operationalizing Engagement With an Interpretation Bias Smartphone App Intervention: Case Series
Authors: Ramadurai Ramya , Beckham Erin , McHugh R Kathryn , Björgvinsson Thröstur , Beard Courtney 
Published: June 2022

Background
Engagement with mental health smartphone apps is an understudied but critical construct to understand in the pursuit of improved efficacy.

Objective
This study aimed to examine engagement as a multidimensional construct for a novel app called HabitWorks. HabitWorks delivers a personalized interpretation bias intervention and includes various strategies to enhance engagement such as human support, personalization, and self-monitoring.

Methods
We examined app use in a pilot study (n=31) and identified 5 patterns of behavioral engagement: consistently low, drop-off, adherent, high diary, and superuser.

Results
We present a series of cases (5/31, 16%) from this trial to illustrate the patterns of behavioral engagement and cognitive and affective engagement for each case. With rich participant-level data, we emphasize the diverse engagement patterns and the necessity of studying engagement as a heterogeneous and multifaceted construct.

Conclusions
Our thorough idiographic exploration of engagement with HabitWorks provides an example of how to operationalize engagement for other mental health apps.
Exploring COVID-19–Related Stressors: Topic Modeling Study
Authors: Leung Yue Tong , Khalvati Farzad 
Published: June 2022

BackgroundThe COVID-19 pandemic has affected the lives of people globally for over 2 years. Changes in lifestyles due to the pandemic may cause psychosocial stressors for individuals and could lead to mental health problems. To provide high-quality mental health support, health care organizations need to identify COVID-19–specific stressors and monitor the trends in the prevalence of those stressors.ObjectiveThis study aims to apply natural language processing (NLP) techniques to social media data to identify the psychosocial stressors during the COVID-19 pandemic and to analyze the trend in the prevalence of these stressors at different stages of the pandemic.MethodsWe obtained a data set of 9266 Reddit posts from the subreddit \rCOVID19_support, from February 14, 2020, to July 19, 2021. We used the latent Dirichlet allocation (LDA) topic model to identify the topics that were mentioned on the subreddit and analyzed the trends in the prevalence of the topics. Lexicons were created for each of the topics and were used to identify the topics of each post. The prevalences of topics identified by the LDA and lexicon approaches were compared.ResultsThe LDA model identified 6 topics from the data set: (1) “fear of coronavirus,” (2) “problems related to social relationships,” (3) “mental health symptoms,” (4) “family problems,” (5) “educational and occupational problems,” and (6) “uncertainty on the development of pandemic.” According to the results, there was a significant decline in the number of posts about the “fear of coronavirus” after vaccine distribution started. This suggests that the distribution of vaccines may have reduced the perceived risks of coronavirus. The prevalence of discussions on the uncertainty about the pandemic did not decline with the increase in the vaccinated population. In April 2021, when the Delta variant became prevalent in the United States, there was a significant increase in the number of posts about the uncertainty of pandemic development but no obvious effects on the topic of fear of the coronavirus.ConclusionsWe created a dashboard to visualize the trend in the prevalence of topics about COVID-19–related stressors being discussed on a social media platform (Reddit). Our results provide insights into the prevalence of pandemic-related stressors during different stages of the COVID-19 pandemic. The NLP techniques leveraged in this study could also be applied to analyze event-specific stressors in the future.
Developing the Message Assessment Scale for Tobacco Prevention Campaigns: Cross-sectional Validation Study
Authors: Rath Jessica M , Perks Siobhan N , Williams Kenneshia N , Budnik Tracy , Geraci John , Vallone Donna M , Hair Elizabeth C 
Published: June 2022

Background
Mass media campaigns are effective for influencing a broad range of health behaviors. Prior to launching a campaign, developers often conduct ad testing to help identify the strengths and weaknesses of the message executions among the campaign’s target audience. This process allows for changes to be made to ads, making them more relevant to or better received by the target audience before they are finalized. To assess the effectiveness of an ad’s message and execution, campaign ads are often rated using a single item or multiple items on a scale, and scores are calculated. Endorsement of a 6-item perceived message effectiveness (PME) scale, defined as the practice of using a target audience’s evaluative ratings to inform message selection, is one approach commonly used to select messages for antitobacco campaigns; however, the 6-item PME scale often does not produce enough specificity to make important decisions on ad optimization. In addition, the PME scale is typically used with adult populations for smoking cessation messages.

Objective
This study includes the development of the Message Assessment Scale, a new tobacco prevention message testing scale for youth and young adults.

Methods
Data were derived from numerous cross-sectional surveys designed to test the relevance and potential efficacy of antitobacco truth campaign ads. Participants aged 15-24 years (N=6108) responded to a set of 12 core attitudinal items, including relevance (both personal and cultural) as well as comprehension of the ad’s main message.

Results
Analyses were completed in two phases. In phase I, mean scores were calculated for each of the 12 attitudinal items by ad type, with higher scores indicating more endorsement of the item. Next, all items were submitted to exploratory factor analysis. A four-factor model fit was revealed and verified with confirmatory factor analysis, resulting in the following constructs: personally relevant, culturally relevant, the strength of messaging, and negative attributes. In phase II, ads were categorized by performance (high/medium/low), and constructs identified in phase I were correlated with key campaign outcomes (ie, main fact agreement and likelihood to vape). Phase II confirmed that the four constructs identified in phase I were all significantly correlated with main fact agreement and vape intentions.

Conclusions
Findings from this study advance the field by establishing an expanded set of validated items to comprehensively assess the potential effectiveness of advertising executions. This set of items expands the portfolio of ad testing measures for ads focused on tobacco use prevention. Findings can inform how best to optimize ad executions and message delivery for health behavior campaigns, particularly those focused on tobacco use prevention among youth and young adult populations.
Published Research on COVID-19 in the Eastern Mediterranean Region: Bibliometric Analysis
Authors: Saad Randa K , Abu Khudair Sara , El Rabbat Maha , Omar Mayeh , Al Nsour Mohannad , Khader Yousef , Rawaf Salman 
Published: June 2022

Background
The challenges presented by the COVID-19 pandemic have led to unprecedented global research activity. The Eastern Mediterranean Region (EMR) continues to contribute to COVID-19 research driven by the unique challenges of the region, including the protracted conflicts, already stressed health systems, and serious health and social inequalities.

Objective
This study aims to provide an overview of the publication activities and trends in COVID-19 research in the EMR from the onset of the disease to early 2022 using bibliometric methods.

Methods
A literature search using Scopus was conducted from December 1, 2019, to January 31, 2022, using keywords relevant to COVID-19 and the World Health Organization (WHO) EMR country list. Data were exported and analyzed using Microsoft Excel and the Citation Overview function on Scopus. The quality of journals was determined using SCImago Journal Rank and CiteScore. VOSviewer software was used to visualize the relationships between authors, countries, and key terms used in the retrieved documents.

Results
A total of 6880 documents were retrieved, of which 1805 (26.24%) were from the Kingdom of Saudi Arabia (KSA) and 1782 (25.90%) from Iran, followed by Pakistan, Egypt, and Jordan. Most published documents were affiliated with EMR universities, primarily the Tehran University of Medical Sciences in Iran and King Saud University in KSA (396/6880, 5.76%, and 370/6880, 5.4%, respectively), while only 407 (5.92%) of 6880 documents were associated with universities outside the EMR. For most of the identified publications (5020/6880, 72.97%), no funding source was reported, while King Saud University contributed the largest share (282/1860, 15.16%) of funded publications. Retrieved documents were cited 53,516 times, with an average of 7.78 (SD 34.30). Iran was the EMR country with the most links to other countries (77 links and total link strength of 1279). The 5 authors with the most publications were from KSA, Qatar, and Jordan. There were 290 high-frequency keywords that occurred ≥10 times and were linked in 7 different clusters. The cluster with the most linked keywords was related to epidemiology and mortality. Recent topics included vaccines, vaccination, machine learning, and online learning.

Conclusions
This is the first study to show trends in and project future developments of COVID-19 research activity in the EMR. Authors and institutions who led research on COVID-19 in the region were from Iran and KSA. There were multiple regional collaborative efforts; however, international collaboration was limited. Recently, interest has been shifting toward topics related to vaccination, machine learning, and online learning. Understanding the current state of research is instrumental to future research production, and our study will inform regional research initiatives on emerging concepts, as well as opportunities for collaboration and funding.
KAJIAN KUAT TEKAN DAN GESER INTERFACE PADA BETON SCC DENGAN PEMANFAATAN FLY ASH SEBAGAI SUBSTITUSI SEMEN
Authors: Kurniadi Edi , Kurniawan Agus 
Published: June 2022

Teknologi bidang konstruksi terus berkembang. Beton Self Compacting Concrete (SCC) merupakan beton dengan kinerja tinggi yang mempunyai kemampuan mengalir dengan sendirinya, durabilitas baik, dan mempunyai kekuatan tinggi. Penggunaan beton SCC dapat menghemat tenaga kerja dan penggunaan alat pemadatan, namun jumlah semen yang digunakan lebih banyak daripada beton normal. Pada konsep bangunan hijau (green building) yang ramah lingkungan mensyaratkan bahwa pembangunan dalam bidang konstruksi menggunakan material-material yang ramah lingkungan. Penggunaan semen walaupun dalam beton digunakan sekitar 7%-15%, ternyata untuk menghasilkan semen digunakan energi yang cukup besar dan kurang ramah lingkungan. Penggunaan fly-ash merupakan cara untuk penerapan green building. Penelitian ini memanfaatkan fly ash sebagai bahan substitusi semen, substitusi ini akan mengurangi penggunaan semen yang akan mengakibatkan penurunan performa dari kekuatan beton SCC. Pada penelitian ini mengkaji kuat tekan dan geser interface pada beton Self Compacting Concrete (SCC) dengan pemanfaatan penggunaan fly ash yang akan di substitusikan dengan semen. Substitusi fly-ash tersebut sebesar 0%, 5%, 10%, 15%, 20%, 25%, 30% dan dengan menggunakan chemical admixture type F (sika viscocrete 1003). Pengujian kuat tekan dilakukan dengan menggunakan benda uji berupa silinder beton ukuran diameter 150 mm dan tinggi 300 mm sesuai standar SNI sedang untuk pengujian kuat geser menggunakan benda uji kubus beton dengan ukuran 150 mm × 150 mm × 150 mm mengacu pada metode bi-surface shear test. Hasil workability beton SCC meliputi pengujian filling ability menggunakan slump flow test didapatkan nilai yang lebih besar dari persyaratan minimum 55 cm, pengujian passing-ability menggunakan L-Box test didapatkan nilai rasio h2/h1 yang lebih besar dari persyaratan minimum 0,8 dan viskositas/segregasi menggunakan V-funnel didapatkan nilai waktu kurang dari persyaratan maksimum 12 detik, dari ketiga pengujian tersebut maka beton tersebut termasuk dalam kriteria sebagai beton SCC. Kuat tekan beton SCC pada umur 7 hari 14 hari dan 28 hari menunjukkan dengan substitusi fly-ash sampai 20% ada peningkatan kuat tekan beton sampai 21 persen selanjutnya pada substitusi fly-ash 30% terjadi penurunan kuat tekan.
DETEKSI KADAR SATURASI OKSIGEN DARAH (SpO2) DAN DETAK JANTUNG SECARA NON-INVASIF DENGAN SENSOR CHIP MAX30100
Authors: Kemalasari  , Rochmad Mochammad 
Published: June 2022

The level of oxygen saturation in the blood (SpO2) and heart rate is one of an importent variables to determine the health of the body. The purpose of this research is to design and implement a non-invasive tool to measure the level of SpO2 and heart rate, so that the measurement of them becomes easier. To measure the level of SpO2 and heart rate is used the MAX30100 chip sensor, which consists of infrared led, red led and photo diode, and that are integrated with arduino uno and PC. By attach the left index fingertip on the MAX30100 chip sensor, then the sensor will transmit infrared and red lights through the fingertips and the blood molecules will absorption the lights, while the photodioda will detect the absorption of light by the physical properties of the blood molecules, so the level of SpO2 and heart rate per minute can be detected. Data connection between the MAX30100 chip sensor and Arduino nano is connected by I2C (Inter Integrated Circuit) which has a serial data path (SDL) and a serial clock path (SCL), and RS232 is used for connection to a PC. On the PC, the level of the SpO2, the value of heart rate and its signal will be displayed on the GUI so the results of measurement can be monitored and used to analyze body health. The test of tool was carried out on 20 people with range of age are 18 to 50 years by comparing the results of the tool that designed with an Elitech pulse oximeter tool, where the value of an average error of SpO2 is 0.84 % and heart rate is 1.6 %.
Transmigración de canino inferior. Reporte de un caso clínico
Authors: Pérez-Flores Antonieta , Castillo Pino Gabriela , Fierro Monti Claudia 
Published: June 2022

La retención dentaria es el retraso en la erupción dental. Con la ex- cepción de los terceros molares y caninos superiores, la retención dental es rara, al igual que la migración intraósea de los dientes retenidos. Se define transmigración como una anomalía atípica en la que un diente migra cruzando la línea media. Por lo general, el diagnóstico de esta patología se realiza por hallazgo radiográfico y conlleva múltiples tratamientos como extracción o posicionamiento ortodóncico. La transmigración dental generalmente es asintomá- tica, aunque puede relacionarse con complicaciones graves como la reabsorción radicular de dientes adyacentes, daño a estructuras anatómicas, malposición dental, desviación de la línea media y agenesia. El diagnóstico precoz con radiografías de rutina es fun- damental en su detección. El presente caso describe la evolución de un paciente entre los ocho y 12 años con un canino mandibular transmigrado y adicionalmente se hace una revisión de la literatura enfocada en los tratamientos a seguir.
In-vitro antibacterial activity of Fosfomycin and Nitrofurantoin against Pseudomonas aeruginosa and Acinetobacter baumannii against clinical isolates collected from Indian tertiary care hospitals
Authors: Chavan Rajesh , Naphade Bhushan , Waykar Bhalchandra 
Published: June 2022

The remarkable increase in resistance to currently available antibiotics to Gram-negative pathogens particularly multidrug resistant (MDR) Pseudomonas aeruginosa and Acinetobacter baumannii, This has resulted in increasing use of older under evaluated antibiotics such as fosfomycin, nitrofurantoin, and Trimethoprime-Sulfamethoxazole for the treatment of infections caused by MDR pathogens. However, limited in-vitro pharmacodynamic data for fosfomycin and nitrofurantoin against Pseudomonas Spp., and Acinetobacter Spp., is available in literature. The current study demonstrates in-vitro activities of fosfomycin and nitrofurantoin against Pseudomonas and Acinetobacter pathogens (425 Pseudomonas Spp., and 352 Acinetobacter Spp., Total: 777 Strains), isolated from Indian tertiary care hospitals. The minimum inhibitory concentration (MIC50/90) of fosfomycin and nitrofurantoin along with comparator antibiotics were determined using Clinical and Laboratory Standards Institute recommended agar dilution method. Fosfomycin demonstrated excellent in-vitro activity against Pseudomonas while in nitrofurantoin demonstrated poor activity against Pseudomonas Spp.,. Fosfomycin and nitrofurantoin did not show promising activities against Acinetobacter Spp.,. By applying E. coli breakpoints, the susceptibility rates of fosfomycin for Pseudomonas Spp., and Acinetobacter Spp., were 72.4%, and 14.8%, respectively. By applying respective breakpoints, the susceptibility rates of comparator drugs, including imipenem and meropenem, were lower than fosfomycin. Susceptibility rate of nitrofurantoin for Pseudomonas Spp., and Acinetobacter Spp., was <1.2% suggesting its poor activity. The susceptibility rate of fosfomycin was > 70% for Pseudomonas isolates, including strains expressing carbapenemases is encouraging finding and supports its potential use. Nitrofurantoin did not show activity against both the Spp., with susceptibility rates <1.2%.
Keywords: Fosfomycin, Nitrofurantoin Gram-negative, Multi Drug Resistant, A. baumannii and P. aeruginosa.
Factors Affecting Covid-19 Infection in Clinical Students at the Indonesian Christian University in 2022
Authors: Sanggul Andriyani Risma , Vidi Posdo Simarmata Vidi Posdo Simarmata 
Published: June 2022

COVID-19 or Coronavirus Disease is an acute respiratory disease caused by a new RNA virus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This virus is rapidly spreading around the world. There are several risk factors for COVID-19 infection. This study aims to determine the factors that influence the incidence of COVID-19 in UKI Medical Faculty clinical students in 2022. The research design was a cross-sectional analytic using primary data by google form questionnaire involving 164 samples of clinical students FK UKI analyzed by univariate and bivariate. The results of this research were five people (3.1%) infected with COVID-29 2 times, 95 people (57.9%) clinical students FK UKI who had been exposed to COVID-19. There was a relationship between the use of masks (p=0.008), washing hands (p=0.000), keeping a distance (p=0.014), avoiding crowds (p=0.005), mobility limitations (p=0.002), and contact with COVID-19 patients (p=0.010). However, there was no relationship between gender (p=0.393), smoking (p=0.581), complete vaccination (p=0.136), and comorbid disease (p=0.641) on the incidence of COVID-19 in clinical students FK UKI in 2022. The conclusion is that the implementation of the 5M protocol (Using masks, washing hands, Keeping a distance, Avoiding crowds, and Mobility limitations) and contact with COVID-19 patients proved to affect the incidence of COVID-19 in FK UKI clinic students in 2022.
Keywords: Gender, wearing a mask, washing hands, keeping a distance, avoiding restrictions, limiting mobility, contact with patients, vaccination, smoking, comorbidities, COVID-19.
A review on potential medicinal herbs as health promoters
Authors: Badnale Anil B , Sarukh Vikram S. , Nikam Yogesh P. , Supekar Amol V. , Khandagale Sandip. S 
Published: June 2022

Nature has been a source of medicinal agents for thousands of years and a moving number of modern drugs have been isolated from natural sources they have plays an important role in the treatment and management of different diseases. The practice of herbal medicine has existed since prehistoric times as the primary source of medicine. In recent technology has very much advanced, herbal medicines still show and are finding exceptional acceptance in both the developing and the developed countries due to their natural origin and lesser side effects. Traditional herbal remedies as alternative medicine play a significant role. Ginger has an Antiviral effect, Antioxidant effect & Anti-inflammatory effect given. Garlic is an ayurvedic medicinal herb that has been widely used as a medication and as a taste enhancer of the food. In traditional remedies, coriander was used for the relief of gastrointestinal conditions. Turmeric shows different biological activities such as Anti-inflammatory, Anti-viral, Anti-oxidant, anti-cancer, Anti-bacterial, Antiarthritis, Anti-diabetic, Fennel shows carminative and stimulant activities as well as spasmolytic activity due to its volatile and non-volatile compounds. Cardamom is used as a home remedy it helps cure various ailments like indigestion, nausea, headache, etc. Clove is a flavouring agent, antibacterial, stimulant, carminative, fragrant, and antiseptic. It's also used as an antiemetic and an anodyne. Dentists use clove oil to sterilize root canals and as an oral anesthetic. Cinnamon is used in coughs and colds, In brief, the information on medicinal herbs will be helpful to create more interest in this medicinal species by defining novel pharmacological and clinical applications and it may be helpful in developing new drug formulations in the future.
Keywords: Medicinal herbs, health, Ginger, Garlic, Coriander, Turmeric, Clove, Cinnamon, Fennel, Cardamom