Messaging Platform Research Articles

Promotion of Influenza Vaccination in the Emergency Department

BackgroundInfluenza vaccine uptake is low among underserved populations whose primary health care access occurs in emergency departments. We sought to determine whether implementation of two interventions would increase 30-day influenza vaccine uptake in unvaccinated patients in the emergency department.MethodsThis three-group, prospective, cluster-randomized controlled trial compared two interventions with a control group in noncritically ill, adult patients in the emergency department who were not vaccinated for influenza in the current vaccine season. The unit of randomization was individual calendar days. Participants received either Intervention M (an influenza vaccine messaging platform consisting of a video, one-page flyer, and scripted message, followed by a vaccine acceptance question and provider notification if participants indicated vaccine acceptance), Intervention Q (no messaging but the vaccine acceptance question and provider notification), or control (usual care/no intervention). The primary outcome was receipt of an influenza vaccine at 30 days ascertained by electronic health record review and telephone follow-up, comparing the Intervention M group with the control group. Secondary outcomes included comparisons of 30-day vaccine uptake in Intervention Q versus control and Intervention M versus Intervention Q.ResultsBetween October 2022 and February 2023, a total of 767 trial participants were enrolled at six emergency departments in five U.S. cities. Median age was 46 years; 353 (46%) participants were female, 274 (36%) were African American, and 158 (21%) were Latinx; 126 (16%) lacked health insurance, and 244 (32%) lacked primary care. The Intervention M, Intervention Q, and control groups had 30-day vaccine uptakes of 41%, 32%, and 15%, respectively (P<0.0001 for Intervention M vs. control). Comparing Intervention M versus Intervention Q, the adjusted difference in 30-day vaccine uptake was 8.7 percentage points (95% confidence interval, −0.1 to 17.6 percentage points).ConclusionsImplementation of influenza vaccine messaging platforms (video clips, printed materials, and verbal scripts) improved 30-day vaccine uptake among unvaccinated patients in the emergency department. (Funded by the National Institute of Allergy and Infectious Diseases; ClinicalTrials.gov number, NCT05836818.)

An exploratory analysis of COVID bot vs human disinformation dissemination stemming from the Disinformation Dozen on Telegram

The COVID-19 pandemic of 2021 led to a worldwide health crisis that was accompanied by an infodemic. A group of 12 social media personalities, dubbed the “Disinformation Dozen”, were identified as key in spreading disinformation regarding the COVID-19 virus, treatments, and vaccines. This study focuses on the spread of disinformation propagated by this group on Telegram, a mobile messaging and social media platform. After segregating users into three groups—the Disinformation Dozen, bots, and humans, we perform an investigation with a dataset of Telegram messages from January to June 2023, comparatively analyzing temporal, topical, and network features. We observe that the Disinformation Dozen are highly involved in the initial dissemination of disinformation but are not the main drivers of the propagation of disinformation. Bot users are extremely active in conversation threads, while human users are active propagators of information, disseminating posts between Telegram channels through the forwarding mechanism.

Discord as a fandom platform: Locating a new playground

The VoIP and instant messaging platform Discord has seen immense user growth over the past few years, including among fans involved with transformative works. Analyzing Discord from a framework of polymedia and play provides new insights into what Discord affords these fans and how they navigate the platform as part of their fan practices. It shows how the platform has been adopted and adapted in ways that facilitate fan play and allow for play moods to be created, strengthened, or maintained. Discord provides a suitable playground for fans, because it allows fans to negotiate closed online spaces where they can play freely, without outside disruption. These spaces can be organized in ways that distinguish between play and nonplay and maintain fannish principles of warning and consent. In addition, Discord provides an extra dimension to the experience of taking part in fan fiction exchanges, creating a compelling, collective mood in servers that people can continually come back to. Positioning this within a broader network of platforms and affordances that fans navigate shows how Discord fulfills particular needs and niches, especially with regard to Not Safe For Work material. More generally, this study provides a framework for understanding the reciprocal and dynamic relationships between users, affordances, rules, and structures in contemporary platform society.

Leveraging Machine Learning to Develop Digital Engagement Phenotypes of Users in a Digital Diabetes Prevention Program: Evaluation Study.

Digital diabetes prevention programs (dDPPs) are effective "digital prescriptions" but have high attrition rates and program noncompletion. To address this, we developed a personalized automatic messaging system (PAMS) that leverages SMS text messaging and data integration into clinical workflows to increase dDPP engagement via enhanced patient-provider communication. Preliminary data showed positive results. However, further investigation is needed to determine how to optimize the tailoring of support technology such as PAMS based on a user's preferences to boost their dDPP engagement. This study evaluates leveraging machine learning (ML) to develop digital engagement phenotypes of dDPP users and assess ML's accuracy in predicting engagement with dDPP activities. This research will be used in a PAMS optimization process to improve PAMS personalization by incorporating engagement prediction and digital phenotyping. This study aims (1) to prove the feasibility of using dDPP user-collected data to build an ML model that predicts engagement and contributes to identifying digital engagement phenotypes, (2) to describe methods for developing ML models with dDPP data sets and present preliminary results, and (3) to present preliminary data on user profiling based on ML model outputs. Using the gradient-boosted forest model, we predicted engagement in 4 dDPP individual activities (physical activity, lessons, social activity, and weigh-ins) and general activity (engagement in any activity) based on previous short- and long-term activity in the app. The area under the receiver operating characteristic curve, the area under the precision-recall curve, and the Brier score metrics determined the performance of the model. Shapley values reflected the feature importance of the models and determined what variables informed user profiling through latent profile analysis. We developed 2 models using weekly and daily DPP data sets (328,821 and 704,242 records, respectively), which yielded predictive accuracies above 90%. Although both models were highly accurate, the daily model better fitted our research plan because it predicted daily changes in individual activities, which was crucial for creating the "digital phenotypes." To better understand the variables contributing to the model predictor, we calculated the Shapley values for both models to identify the features with the highest contribution to model fit; engagement with any activity in the dDPP in the last 7 days had the most predictive power. We profiled users with latent profile analysis after 2 weeks of engagement (Bayesian information criterion=-3222.46) with the dDPP and identified 6 profiles of users, including those with high engagement, minimal engagement, and attrition. Preliminary results demonstrate that applying ML methods with predicting power is an acceptable mechanism to tailor and optimize messaging interventions to support patient engagement and adherence to digital prescriptions. The results enable future optimization of our existing messaging platform and expansion of this methodology to other clinical domains. ClinicalTrials.gov NCT04773834; https://www.clinicaltrials.gov/ct2/show/NCT04773834. RR2-10.2196/26750.

Cyberbullying and cyberstalking: Parents' role to protect their children

Cyberbullying has been a severe problem that emerged since the beginning of the 21st century, particularly among children and young people. Being the target of cyberbullying can result in feelings of depression, hopelessness, a loss of self-esteem, and isolation. These emotions are all antecedents of acts of self-harm, particularly for victims but also for bullies. Studies on cyberbullying have produced somewhat contradictory results, and the methods developed to counteract these phenomena have been consistent with these results. Cybercrime's reach has grown, as has its ability to inflict monetary and nonmonetary harm, including direct changes to the physical world. On the other hand, cybercrime has been extensively combating for decades, in contrast to cyberbullying. People's lives are becoming increasingly intertwined with the Internet, bringing many fresh educational and amusement opportunities. In addition, it offers a platform for forms of online harassment, such as cyberbullying and cyberstalking, both of which may have devastating impacts on the lives of young people. Cyberstalking can intentionally harm another person through digital technologies such as social media, email, text messaging, or other online platforms by cyberbullying; regularly following or harassing another person via these same technologies. Keeping in mind that cyberbullying and cyberstalking can happen at any time to anyone is the responsibility of every parent. They should openly discuss the risks of technology with their own children and provide them with strategies and tips for staying safe online to avoid cyberbullying and stalking. When protecting their children from the potentially serious legal consequences of cyberbullying, parents should provide as much information as possible about the relevant laws. In addition, parents should ensure that they are familiar with the websites and platforms that are used by one’s children and should be involved in their children's lives so that any unexpected changes in behavior or mood can be noticed early on and addressed. Finally, parents need to provide their children with aid and direction whenever required and to demonstrate that they are reachable and ready to listen if their children are victims of cyberbullying or cyberstalking.

Snapchat's disappearing messages: Balancing entertainment and privacy in digital communication

Modern instant messaging platforms often default to permanent data retention, raising concerns about data privacy and users' ability to manage their digital artifacts. In contrast, emerging applications like Snapchat introduce ephemeral communication, where messages automatically vanish after being viewed. This paper investigates the motivations and experiences of users utilizing Snapchat's disappearing message feature. The study employs semi-structured interviews with young adults aged 18-24, who are active Snapchat users. Findings reveal that Snapchat's primary appeal lies in entertainment, creative expression, and maintaining casual relationships. While the disappearing feature contributes to privacy perceptions, users' trust in the feature's privacy protection is not absolute. The paper highlights the challenge of conducting task-oriented or deep conversations due to the ephemerality, emphasizing Snapchat's utility for informal and lighthearted interactions. Ultimately, the study underscores the importance of aligning user experiences with application design, providing insights for practitioners seeking to enhance user-centered product development in the evolving landscape of digital communication.

Single Device-Based Deep Learning Approach for Geographical Position Spoofing Detection on an Instant Messaging Platform

Single Device-Based Deep Learning Approach for Geographical Position Spoofing Detection on an Instant Messaging Platform

Regulations and Legal Implications of Contracts through Instant Messaging Platforms in Saudi Arabia

Regulations and Legal Implications of Contracts through Instant Messaging Platforms in Saudi Arabia

Development of an Approach for Image Forgery Detection Using Machine Learning Algorithms

Digital picture fraud detection is an increasing societal necessity due to the importance of verified images. The detection of picture copying, splicing, retouching, and re-sampling forgeries is included. In the absence of digital signatures or watermarks, passive picture authentication may serve as an alternative to active authentication. Passive techniques, every so often recognized as blind techniques, could take place without preceding knowledge of the picture or its reference. Identifying counterfeiting picture or tampering was a research field for long a period of time, triggered via the Internet, online platforms, social messaging platforms, and extensive digital image usage. The rate of failure could be a key factor for examining the alteration of picture or forgery, among other existing methods. The research applies almost six common algorithms related to machine learning in order to extract features from Lightweight, Spatial Exploitation, and Residual deep learning models on benchmark datasets MICC-F220, Columbia, and CoMoFoD. The models of incorporated deep learning could consist of AlexNet, GoogleNet, VGG16, VGG19, SqueezeNet, MobileNetV2, ShuffleNet, ResNet-18, ResNet-50, and ResNet-101 for spatial exploitation. Fine-tuning is applied to the top three deep learning models, optimizing hyperparameters centered on indicators of performance for every single benchmark dataset. Tweaked SqueezeNet, MobileNetV2, and ShuffleNet deep learning models with SGDM Optimizer and SVM classifier yielded the best results for MICC-F220 dataset. Fine-tuned VGG19, MobileNetV2, and ResNet-50 deep learning models with SGDM Optimizer and SVM v classifier yielded the best results for Columbia dataset. In CoMoFoD dataset, fine-tuned AlexNet, MobileNetV2, and ShuffleNet deep learning models with SGDM Optimizer and SVM classifier yielded the best results. The proposed approach, utilizing machine learning algorithms and deep learning features, enhanced forgery detection and reduced false positives. Results were validated on benchmark image forgery datasets and compared to current methods.

A Survey on Blockchain Technology in Communication Protocols

Offering decentralized and secure solutions to age-old problems. In the realm of communication protocols,where Blockchain technology has emerged as a disruptive force across various industries, trust, security, and transparency are paramount, blockchain holds immense promise. This paper delves into the integration of blockchain technology into communication protocols, exploring its potential impact, challenges, and future directions. The paper begins by elucidating the fundamental concepts of blockchain technology, emphasizing its decentralized nature,cryptographic security, and immutable ledger. It then delineates the significance of communication protocols in facilitating data exchange, highlighting the need for robust mechanisms to ensure confidentiality, integrity, and authenticity. Subsequently, the paper examines how blockchain technology can augment existing communication protocols by introducing decentralized consensus mechanisms, enhancing data integrity through cryptographic hashing,and fortifying security through encryption techniques. It elucidates how blockchain-enabled communication protocols can mitigate single points of failure, resist tampering, and provide transparent audit trails, thereby fostering trust in communication networks. Furthermore, the paper discusses various applications of blockchain technology in communication protocols, ranging from secure messaging platforms and decentralized social networks to verifiable data transmission and digital identity management. It explores the potential of blockchain to revolutionize peer-to-peer communication, enabling direct interaction without intermediaries while preserving privacy and security. Moreover, the paper addresses the challenges and limitations associated with integrating blockchain into communication protocols,including scalability concerns, latency issues, and regulatory hurdles. It underscores the need for ongoing research and development to overcome these obstacles and realize the full potential of blockchain technology in communication networks. Finally, the paper concludes by envisioning future trends and advancements in blockchain-enabled communication protocols, such as the integration of artificial intelligence for dynamic routing and optimization, the emergence of interoperable blockchain standards for seamless intefgration across diverse networks, and the proliferation of decentralized autonomous communication systems. In summary, this paper provides a comprehensive overview of the integration of blockchain technology into communication protocols, highlighting its transformative potential, challenges,and future prospects. It underscores the importance of continued innovation and collaboration to harness the full benefits of blockchain in shaping the future of communication networks.

Five-Stage Framework of Technology Domestication in the Workplace: An Organisational Case Study of Implementing a Mobile Management Software

With the rise of remote working due to the Coronavirus disease 2019 (COVID-19) pandemic, organisations today increasingly adopt mobile collaborative technologies such as instant messaging platforms, enterprise social media, and project management software to facilitate a variety of work and communication practices. While previous studies on workplace digital transformation have surfaced the wide-ranging implications of digital technologies for organisational functioning, the complicated process of integrating new technologies into an organisation’s workflow, especially in Small and Medium Enterprise (SME) settings, is hitherto understudied. Given the pressing need of digitalisation and the myriad challenges faced by SMEs, it is imperative to uncover the complexity of collective decision-making, interaction, and negotiation during the process of implementing digital technologies in the workplace environment of SMEs. As an effort to shed light on this missing link, we conducted an in-depth ethnographic case study on the dynamic process of implementing a self-developed mobile management software in a construction SME in Singapore. Drawing on technology domestication theory, a five-stage workplace technology domestication framework was developed in which various stakeholders, including the company’s CEO, office staff, shop floor workers, and the developer team, engaged in ongoing and multifaceted negotiations revolving around the application of the new technology and the changes it heralded. During the domestication process, the functionality and meanings of the software as well as employee acceptance and user experiences were continuously reconfigured by a constellation of technological, individual, organisational, and sociocultural conditions. This study uncovers the iterative and participatory nature of technology design and implementation in the workplace, thereby opening up a promising approach for SMEs to maximise benefits from digital transformation with limited resources available.

A Survey on Blockchain Technology in Communication Protocols

Offering decentralized and secure solutions to age-old problems. In the realm of communication protocols, where Blockchain technology has emerged as a disruptive force across various industries, trust, security, and transparency are paramount, blockchain holds immense promise. This paper delves into the integration of blockchain technology into communication protocols, exploring its potential impact, challenges, and future directions. The paper begins by elucidating the fundamental concepts of blockchain technology, emphasizing its decentralized nature, cryptographic security, and immutable ledger. It then delineates the significance of communication protocols in facilitating data exchange, highlighting the need for robust mechanisms to ensure confidentiality, integrity, and authenticity. Subsequently, the paper examines how blockchain technology can augment existing communication protocols by introducing decentralized consensus mechanisms, enhancing data integrity through cryptographic hashing, and fortifying security through encryption techniques. It elucidates how blockchain-enabled communication protocols can mitigate single points of failure, resist tampering, and provide transparent audit trails, thereby fostering trust in communication networks. Furthermore, the paper discusses various applications of blockchain technology in communication protocols, ranging from secure messaging platforms and decentralized social networks to verifiable data transmission and digital identity management. It explores the potential of blockchain to revolutionize peer-to-peer communication, enabling direct interaction without intermediaries while preserving privacy and security. Moreover, the paper addresses the challenges and limitations associated with integrating blockchain into communication protocols, including scalability concerns, latency issues, and regulatory hurdles. It underscores the need for ongoing research and development to overcome these obstacles and realize the full potential of blockchain technology in communication networks. Finally, the paper concludes by envisioning future trends and advancements in blockchain-enabled communication protocols, such as the integration of artificial intelligence for dynamic routing and optimization, the emergence of interoperable blockchain standards for seamless intefgration across diverse networks, and the proliferation of decentralized autonomous communication systems. In summary, this paper provides a comprehensive overview of the integration of blockchain technology into communication protocols, highlighting its transformative potential, challenges, and future prospects. It underscores the importance of continued innovation and collaboration to harness the full benefits of blockchain in shaping the future of communication networks.

Key Factors Influencing Public Attitudes Toward Charities' Involvement in Emergency Management: A Study Based on Online Public Opinion in China.

Charities play a pivotal role in engaging the public in emergency management efforts. They serve to complement governmental restrictions by leveraging social resources to aid in emergency management. The involvement of charities in emergency management is likely to shape public attitudes, thereby influencing their effectiveness in this sphere. Therefore, understanding the factors that influence public attitudes toward charities in emergency management is crucial. This study sought to identify these key factors and offer recommendations for charities to enhance their participation in emergency management. The data for this study were collected from messages and comments on two prominent instant messaging platforms, WeChat Public and Sina Weibo. Content Analysis was employed to categorize the data, and the Apriori algorithm was utilized to uncover association rules and key factors. Based on the key factors, it is recommended that charities focus on collaborating with celebrities and enterprises, prioritize establishing and upholding a positive reputation, and enhance their expertise in emergency management practices.

Older Veteran Experiences of using Technology during a Multicomponent Telerehabilitation Program: A Convergent Mixed Methods Study.

Less than half of U.S. veterans meet physical activity guidelines. Even though changing physical activity can be challenging, prior studies have demonstrated that it is possible. Older adults are using technology to aid in such behavior change. However, research that explores the mechanisms of how technology can aid in behavior change is lacking, especially among older veterans. Thus, the purpose of this secondary, convergent mixed methods study was to explore how older veterans engaged with technologies that were used during a multicomponent telerehabilitation program. The study included veterans aged ≥60 years with ≥3 chronic medical conditions and physical function limitation. Quantitative data were collected during the primary randomized controlled trial, and qualitative data were collected via individual interviews following completion of the telerehabilitation program. Data were merged and then analyzed by high vs. low technology engagement groups. Key similarities and differences between groups were identified in five domains: satisfaction with the virtual environment, coping self-efficacy, perceptions of Annie (automated text messaging platform), experiences using the activity monitor, and self-management skills. Findings can help inform the successful integration of similar technologies into physical rehabilitation programs. Further study is warranted to understand additional factors and mechanisms that influence technology engagement in telerehabilitation.

Development of a Culturally Appropriate Text Messaging Platform for Improving Breast Cancer Screening Uptake Among Ghanaian Women in Metropolitan Areas.

Objective: Early detection through screening could improve breast cancer (BC) outcomes in sub-Saharan Africa (SSA). We explored women's preferences for BC-related mobile health text messaging, described the development of a mobile-health text messaging platform, and examined the enablers and barriers to BC screening. Methods: A concurrent mixed-method study of women aged 40-59 years was conducted. Four essential actions were carried out: (i) a baseline survey of 130 women, (ii) five focus group discussions (FGDs), (iii) a stakeholder meeting with BC research and clinical treatment specialists, and (iv) text message pretesting. The survey and FGD findings were used to create a culturally appropriate SMS platform for BC screening. Results: Thirty-five text messages were developed and evaluated with the following communication goals in mind: 15 addressed BC awareness, six emphasized the importance of early detection, five alleviated anxieties as a barrier to BC screening, seven encouraged women to prioritize their health, and three indicated screening locations and costs. The majority (92.6%) of survey respondents who had heard of mammography (54/130) said screening was necessary. Fear of the screening procedure, receiving a positive diagnosis, and other testing-related worries (40.7%) were identified as potential barriers to BC screening, along with low income (18.5%), a lack of BC-related indicators (9.3%), insufficient breast awareness education (9.3%), and time restrictions (7.4%). The presence of BC-related symptoms (27.8%), breast awareness education (24.1%), and doctor's advice (16.7%) were all potential facilitators of BC screening uptake. The majority of FGD participants favored brief texts, with 42.3% preferring one text message per day. Conclusion: Several factors limit women from accessing BC screening services; nevertheless, specific barriers such as a lack of BC education, time constraints, and disease fears can be successfully targeted through SMS messaging interventions to encourage women to use BC screening programs.

A Novel Approach for Arabic SMS Spam Detection Using Hybrid Deep Learning Techniques

Spam detection in SMS communication is a crucial task for maintaining the quality of messaging services and protecting users from unwanted and potentially harmful messages. Arabic SMS spam detection poses unique challenges due to the rich morphology and complex structure of the Arabic language, which can significantly impact the performance of traditional text classification methods. To address these challenges, this paper presents a novel approach for Arabic SMS spam detection using a hybrid deep learning model that combines Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (Bi-LSTM) networks. The proposed model leverages the strengths of CNNs in capturing local features and patterns in the text and the capability of Bi-LSTM networks to understand long-term dependencies and contextual information. This hybrid architecture is designed to effectively handle the complexities of the Arabic language and improve the accuracy of spam detection. The model was evaluated on a dataset of Arabic SMS messages, consisting of both ham (non-spam) and spam messages. The dataset underwent preprocessing steps, including text cleaning, tokenization, and padding, to prepare it for training the deep learning model. The hybrid model was trained using the Adam optimizer and evaluated using accuracy, precision, recall, and F1 score metrics. Early stopping was implemented to prevent overfitting during the training process. The results demonstrate that the hybrid model achieved high performance, with an accuracy of 0.9699, precision of 0.9739, recall of 0.9675, and an F1 score of 0.9707. These metrics indicate the model's effectiveness in accurately detecting spam in Arabic SMS messages. Additionally, the paper provides visualizations of the confusion matrix, ROC curve, and training-validation loss graph to illustrate the model's performance. The implications of this research are significant for the field of Arabic text classification and spam detection. The proposed hybrid model offers a robust solution for accurately classifying Arabic SMS messages, which can be integrated into messaging platforms to enhance spam detection capabilities and improve user experience. Future work could explore data augmentation techniques, transfer learning, and advanced hybrid architectures to further enhance the model's performance and applicability.

An Analysis of Students’ Experience in Using English Learning Application “myON” in Helping Students’ English Learning Process

&lt;p class="Abstrak"&gt;Generally, teaching and learning activities mostly rely on books, instructional materials provided by teachers, and written or verbal exercises. These learning approaches are monotonous. Given the progress of technology and the internet, it is necessary for educators to utilize technology-driven online learning platforms, such as myON applications. This will be achieved by employing qualitative research methodologies to investigate the students' experiences and perspectives on the utilization of the “myON” application for English learning. A Google Form questionnaire is utilized and distributed using the messaging platform Whatsapp. Data analysis include the utilization of narrative methodologies to effectively and accurately summarize and depict the outcomes of questionnaires, which are derived from the experiences of students. The study centered on students in the IX-B Grade of Al-Fityan High School in Medan Selayang, Sumatera Utara. Its objective was to examine the level of student engagement and enthusiasm in utilizing online learning tools, while also seeking to enhance accuracy through feedback obtained from questionnaires. The app received positive feedback from students in class IX B, who expressed satisfaction with its simple design and its positive influence on their English proficiency. While the majority experienced significant improvements in their writing, reading, listening, and grammatical skills, a few individuals indicated dissatisfaction, citing intricate explanations, high costs, and a perception of monotonous. Hence, it is imperative for the "myON" application to underscore the significance of this tool in the process of English language acquisition by showcasing improved functionalities and enhanced communication capabilities that correspond with user preferences.&lt;/p&gt;

Trends in maternal oral health services at primary healthcare centers in Saudi Arabia: a cross-sectional study

BackgroundDuring pregnancy, many complex physiological changes and increased levels of pregnancy hormones are associated with adverse oral health and increased prevalence of periodontal disease. Our study aimed to assess the oral health needs of pregnant women and describe the patterns of dental services provided to them before, during, and after pregnancy. Assessing the oral health needs of pregnant women and understanding the patterns of dental services provided to them are important to facilitate efficient utilization of oral health services to promote better health outcomes for the mother and baby.MethodsOur study utilized a cross-sectional design to examine the prevalence of dental problems and use of dental services among a sample of postpartum women who visited primary healthcare centers (PHCs) in Jeddah for antenatal care, between 2018 and 2019. A link to a questionnaire adapted from the Pregnancy Risk Assessment Monitoring System (PRAMS) was sent to participants via the WhatsApp messaging platform. A total of 1350 postpartum women responded to the online survey. We estimated the prevalence of dental problems among women before and during pregnancy and assessed the association between their dental problems and their respective demographic characteristics. We calculated the prevalence of each dental service received before, during, and after pregnancy and examined the trends in dental services over these three periods. All bivariate associations were tested using Pearson’s chi-squared test.ResultsWe found that significantly fewer women visited a dental clinic during pregnancy (31.0%) compared to pre-pregnancy (38.2%) and post-pregnancy (47.3%). The prevalence of toothache, dental caries, gum disease, and dental extraction need before pregnancy was 45.9%, 57.0%, 27.3%, and 40.0%, respectively. These percentages remained the same during pregnancy, except for the need for dental extraction, which significantly decreased to 35.3%. Check-up dental visits increased significantly to 70.6% during pregnancy compared to pre-pregnancy (51.7%) and post-pregnancy (59.9%).ConclusionIncreasing women’s awareness of the importance and safety of oral healthcare during pregnancy, training dental students and primary healthcare dentists in the practice guidelines for the dental management of pregnant women, and developing and monitoring key performance indicators for maternal oral healthcare are the starting steps for improving the oral health and well-being of women and their children.

Physician experiences with teleconsultations amidst conflict in Sudan

The current conflict in Sudan severely hinders the accessibility of health services across the country. To address this, several initiatives were proposed including offering services using teleconsultations. This study aimed to assess Sudanese doctors' teleconsultation experience, perception, and concerns during the recent conflict. This cross-sectional survey focused on Sudanese medical officers, residents, specialists, and consultants living inside or outside the country having a practice license from the Sudan Medical Council and conducting teleconsultations with Sudanese patients during the conflict period. The questionnaire was distributed to personal and professional contacts and via social media platforms in the English language among doctors who provided teleconsultation during the conflict. Data analysis was performed using the Statistical Package for Social Sciences software version 26. The study enrolled 2463 clinicians from 17 different specialties, and females represented more than half the sample (56.8%). Internal medicine was the most frequent specialty (36.1%) and the majority (68.7%) of clinicians had less than 5 years of work experience. Voice call was the most frequent platform (50.1%) used for teleconsultation during the conflict and had the highest convenience score (p < 0.01), whereas messaging platforms had the lowest score. Most clinicians (73.3%) agreed that teleconsultations created a trusted patient-physician relationship and provided good-quality care (61.8%). However, 85.1% highlighted the importance of physical touch in medical practice. Clinicians were concerned that incomplete information (81.4%), missed diagnosis (76.8%), medicolegal problems (71.0%), and prescription errors (68.4%) could arise with teleconsultations. Most respondents (70.7%) emphasized the importance of continuing to offer teleconsultation even after the war abated. In conclusion, physicians who participated in the current study agreed that teleconsultation provided quality care even in this dire crisis in Sudan. Based on our study findings, we recommend upscaling telemedicine interventions including teleconsultations at the national level. This would require unified coordination efforts of a wide mix of stakeholders to address concerns identified in the current study.

Chatbot research: Unveiling evolutionary trends and collaborative pathways through bibliometric analysis

As technology continues to grow and rapidly transform, marketing techniques have adapted to meet the evolving desires and requirements of customers. The recent advancements in artificial intelligence (AI) and machine learning, coupled with the widespread popularity of the internet and messaging platforms, have led businesses to shift their focus toward chatbots. This study aims to contribute to the field of chatbot research by conducting a bibliometric analysis of chatbot papers available in the Scopus and Web of Science (WoS) databases. A comprehensive analysis of 360 articles was performed utilizing the Bibliometrix software package. The keywords "Chatbot" and "Artificial Intelligence" emerged as the most frequently employed terms in the majority of publications. Collaboration between the United States and China was found to be the most extensive in the field. However, limited studies have been conducted on marketing-related aspects of chatbots, such as anthropomorphism, customer satisfaction, and trust. This study reviews Scopus and WoS titles and abstracts to provide an in-depth view of chatbot research and recommends new areas of research.