Search Results (110)

Background: Human immunodeficiency virus and hypertension increasingly co-occur in South Africa. Despite publicly funded care, patients with multimorbidity face high out-of-pocket costs, yet limited evidence exists from the patient perspective. Purpose: To quantify the economic burden of comorbid HIV and hypertension, assess predictors of monthly out-of-pocket costs, and explore coping mechanisms. Methods: We conducted a cross-sectional analysis using patient-level data from the Mobile Phone Text Messages to Improve Hypertension Medication Adherence in Adults with HIV (MOPHADHIV trial) [Trial number: PACTR201811878799717], a randomized controlled trial evaluating short messages services adherence support for hypertension care in people with HIV. We calculated the monthly direct non-medical, indirect, and coping costs from a patient perspective, valuing indirect costs using both actual income and minimum wage assumptions. Generalized linear models with a gamma distribution and log link were used to identify cost determinants. Catastrophic expenditure thresholds (10–40% of monthly income) were assessed. Results: Among 683 participants, mean monthly total costs were ZAR 105.81 (USD 5.72) using actual income and ZAR 182.3 (USD 9.9) when valuing indirect costs by minimum wage. These time-related productivity losses constituted the largest share of overall expenses. Regression models revealed a strong income gradient: participants in the richest quintile incurred ZAR 131.9 (95% CI: 63.6–200.1) more per month than the poorest. However, this gradient diminished or reversed under standardized wage assumptions, suggesting a heavier proportional burden on middle-income groups. Other socio-demographic factors (gender, employment, education) not significantly associated with total costs, likely reflecting the broad reach of South Africa’s primary health system. Nearly half of the participants also reported resorting to coping mechanisms such as borrowing or asset sales. Conclusions: Comorbid HIV and hypertension impose substantial patient costs, predominantly indirect. Income disparities drive variation, raising equity concerns. Strengthening integrated human immunodeficiency virus—non-communicable diseases care and targeting financial support are key to advancing South Africa’s Universal Health Coverage reforms. Full article

The aim of this research is to identify policy and practice interventions that support a just transition towards resilient practices for resource-dependent communities. We focus on Thai Nguyen and Phu Tho, two provinces in the Northern Midlands and Mountains of Vietnam. The region is reliant on agriculture but is assessed as highly vulnerable to climate change. We surveyed 105 farming households. A Likert-type questionnaire asked respondents to self-assess their experiences of weather extremes and of changes they had made to their farming practices. Our results show that for both Thai Nguyen and Phu Tho, farmers see the effects of climate change on their crops. Respondents in Thai Nguyen were more likely to report technically driven adaptation and engagement with extension services. Respondents in Pho Tho were more likely to continue traditional practices. For both, use of traditional knowledge and practices was related to taking measures to adapt to climate change. Our main conclusion is that at least three actions could support a just transition to resilient livelihoods. First is incorporating natural science and traditional knowledge into decision-making for just transitions. Second is considering long-term implications of interventions that appear to support livelihoods in the short term. Third is tailoring messaging and engagement strategies to the requirements of the most vulnerable people. The main message of this study is that a just transition for resource-dependent communities will inevitably be context-specific. Even in centralized and authoritarian contexts, flexibility to adapt top-down policies to locals’ own experiences of changing climates is needed. Full article

Background: Colonoscopy is an important and essential diagnostic and screening tool for colorectal cancer and other pathologies in the colon. High-quality bowel preparation (BP) is a key quality measure of colonoscopy and is critical for maximizing its effectiveness, including enhancing adenoma detection rates. However, inadequate bowel preparation (IBP) remains a frequent challenge and is influenced by multiple factors. This review aims to summarize and evaluate educational and technological interventions implemented before colonoscopy to improve BP quality. Methods: The methodology comprised a structured narrative review of studies published in English, including randomized controlled trials, prospective studies, observational cohorts, and meta-analyses. Interventions were categorized by their delivery mode and impact on BP adequacy. Interventions included written materials, internet-based education modules, short message service (SMS) reminders, visual aids, instructional videos, verbal communication, telephone support, smartphone applications, and virtual reality (VR) platforms. Results: Most studies reported significant improvements in BP quality with enhanced patient education, particularly with the use of instructional videos and smartphone applications. Verbal communication and telephone support also demonstrated positive outcomes but were limited by resource availability. VR represents a promising emerging technology, though its implementation remains costly and complex. Conclusions: Enhanced educational interventions are proven methods to optimize BP quality. The selection of an appropriate modality should consider patient characteristics, technological accessibility, and institutional resources. Personalized strategies targeting high-risk populations can further reduce IBP rates and improve overall colonoscopy outcomes. Full article

Recently, STDenseNet (SpatioTemporal Densely connected convolutional Network) showed remarkable performance in predicting network traffic by leveraging the inductive bias of convolution layers. However, it is known that such convolution layers can only barely capture long-term spatial and temporal dependencies. To solve this problem, we propose Attention-DenseNet (ADNet), which effectively incorporates an attention module into STDenseNet to learn representations for long-term spatio-temporal patterns. Specifically, we explored the optimal positions and the types of attention modules in combination with STDenseNet. Our key findings are as follows: i) attention modules are very effective when positioned between the last dense module and the final feature fusion module, meaning that the attention module plays a key role in aggregating low-level local features with long-term dependency. Hence, the final feature fusion module can easily exploit both global and local information; ii) the best attention module is different depending on the spatio-temporal characteristics of the dataset. To verify the effectiveness of the proposed ADNet, we performed experiments on the Telecom Italia dataset, a well-known benchmark dataset for network traffic prediction. The experimental results show that, compared to STDenseNet, our ADNet improved RMSE performance by 3.72%, 2.84%, and 5.87% in call service (Call), short message service (SMS), and Internet access (Internet) sub-datasets, respectively. Full article

Empowered by artificial intelligence and 5G technologies, intelligent messaging service instead of the existing short messaging service could provide an omni-channel service, thus achieving higher interconnection for mobile users. In this paper, we adopted mixed methods research and explored the psychological factors that affect adoption intention to adopt intelligent messaging services among mobile users based on self-determination theory. After semi-structured interviews, we constructed a partial least squares structural equation model from the perspectives of intrinsic and extrinsic motivations. In addition, openness and perceived complexity were also introduced as an extended dimension. Through an online survey, 548 valid questionnaires were obtained. The results show that intrinsic motivation has a greater effect on adoption intention. Specifically, attitude, perceived autonomy, perceived relatedness, and perceived system quality have significant positive impacts on the adoption intention of intelligent messaging, while perceived complexity has a negative direct impact on adoption intention. Although perceived competence and perceived media richness have no significant effects on adoption intention, an indirect effect on adoption intention through attitude was observed. Notably, perceived interactivity and openness have no effect on adoption intention. Through this study, we aim to provide guidance for developers to focus on mobile users’ psychological needs regarding upgraded interactive channels, which can accelerate the construction of an omni-channel media environment. Full article

We sought to characterize momentary changes in fatigue, sleepiness, and difficulty with concentration during short and long duration shifts worked by emergency medical services (EMS) and fire personnel across the United States. In addition, we tested for differences in pre-shift and on-shift sleep stratified by shift duration. We examined real-time mobile-phone text message queries during scheduled shifts from the EMS Sleep Health Study, a nationwide, cluster-randomized trial (ClinicalTrials.gov Identifier: NCT04218279). Linear mixed effects models were used and Bonferroni p-values reported for multiple comparisons. In total, 388 EMS clinicians from 35 EMS/fire agencies documented 4573 shifts and responded to 64.6% of 161,888 text message queries. Most shifts (85.5%) were 12 or 24 h in duration. Mean sleep hours pre-shift was 6.2 (SD1.9) and mean sleep hours on shift was 3.4 (SD2.9) and varied by shift duration (p < 0.0001). The highest level of fatigue, sleepiness, and difficulty with concentration during any shift occurred during 24 h shifts and corresponded to the early morning hours at 03:00 or 04:00 a.m. The real-time assessments of sleep hours and fatigue in this study revealed deficits in sleep health for EMS and fire personnel and critical time points for intervention during shifts when the risk to safety is high. Full article

The Galileo Open Service Navigation Message Authentication (OSNMA) service has been transmitting stably in recent years and is expected to be declared operational in the next months. While the protocol is very flexible, most of the parameters, such as key and tag sizes and cryptographic functions, have been already fixed in view of the operational declaration. However, some degree of flexibility remains in the tag and cross-authentication sequence. The cross-authentication sequence defines the satellites “cross-authenticated” by an authenticating Galileo satellite and is one of the main properties of the OSNMA protocol. It facilitates the authentication of nearby Galileo satellites for higher redundancy against losses, authenticating data from satellites not connected to the ground and therefore not transmitting OSNMA, and authenticating GPS or other data in the future. It has a significant impact on OSNMA performance: if the sequence is too long, many cross-authenticated satellites will not be seen by the users, limiting the optimal use of the OSNMA bandwidth, and with a major impact on TBA (Time Between Authentications) and Time To First Authenticated Fix (TTFAF). If the sequence is too short, several non-connected but visible satellites may remain unauthenticated, also degrading performance. This paper presents an analysis with real SIS data from different cross-authentication sequences transmitted by Galileo in recent months, involving different tag distribution and a number of cross-authenticated satellites including open-sky static, dynamic, and urban environments. This work shows the degradation with sub-optimal cross-authentication sequences and identifies current bottlenecks, proposing some recommendations for future sequences. Full article

Background and aim: The use of mHealth, especially short-message text (SMS), has proven to be an effective intervention in promoting behavioral health outcomes in populations across different contexts and settings. While MomConnect, an mHealth technological device designed to enhance maternal and child health services in South Africa, offers various health-related contents aimed at improving maternal outcomes for pregnant and postpartum women, it currently lacks information on prenatal physical activity. However, physical activity and exercise during pregnancy is safe and beneficial for both the mother and the baby. This article outlines the protocol for designing and developing a prenatal physical activity and exercise text messaging content for the MomConnect device. To achieve this, the protocol aims to elucidate the preferences of prenatal physical activity and exercise text messages and ascertain the preferred amount of SMS messaging to inform the design of an intervention for the incorporation of prenatal physical activity and exercise text messages into the MomConnect device in South Africa. Methods: We will apply a user-centred design approach conducted in three phases. First, a scoping literature review and interviews with pregnant women will be conducted to inform the formative stage for developing a desirable prototype SMS. Secondly, healthcare providers and pregnant women will be interviewed to collate data on the preferred SMS. Lastly, a cross-sectional survey will be conducted to determine the preferred quantity of SMS messaging to be incorporated in the MomConnect device. Expected outcomes: A preferred or desirable prenatal physical activity and exercise SMS text message will inform the design of SMS text messages to be incorporated into the content of the MomConnect device to promote prenatal physical activity and exercise participation among women in the Eastern Cape Province. This study will develop a tailored mHealth intervention to improve prenatal physical activity participation and health behaviors among pregnant women in South Africa. Full article

Based on spatiotemporal sensing techniques, the cross-regional traveling welcome short messaging service (TW-SMS) has been adopted in China and has become popular, typically being used when travelers pass through or arrive in cities. In this service, governmental institutions in combination with telecom operators send welcome messages with the local characteristics. As a typical location-based service for mobile users, the TW-SMS includes reminders or alerts related to COVID-19 prevention and control. In this paper, we investigate the perceptions and behavior of mobile users regarding this special TW-SMS through mixed-methods research. An online survey was conducted among mobile users who engaged in intercity travel. After analyzing samples of TW-SMS data collected during the COVID-19 pandemic, we found that the respondents exhibited a relatively positive overall attitudes and recognized the necessity and helpfulness of the TW-SMS with its trusted content. For content analysis, we found that more than 70% of the messages transmitted by the TW-SMS were released by official departments (e.g., the COVID-19 Prevention and Control Office). Reminders about traveling registration and nucleic acid testing were assigned the highest importance, as they offer convenience in communicating the most up-to-date prevention and control information to mobile users during intercity travel. Through this study, we provide insights into epidemic prevention and control experiences during public health emergencies in cities. Full article

The increasing use of unmanned aerial vehicles (UAVs) in the commercial and recreational sectors has led to a heightened demand for effective recovery solutions after a crash, particularly for lightweight drones. This paper presents the development of a long-range and low-cost emergency radio beacon designed specifically for small UAVs. Unlike traditional emergency locator transmitters (ELTs), our proposed beacon addresses the unique needs of UAVs by reducing size, weight, and cost, while maximizing range and power efficiency. The device utilizes a global system for mobile (GSM)-based communication module to transmit location data via short message service (SMS), eliminating the need for specialized receivers and expanding the operational range even in obstacle-rich environments. Additionally, a built-in global navigation satellite system (GNSS) receiver provides precise coordinates, activated only upon impact detection through an accelerometer, thereby saving power during normal operations. Experimental tests confirm the extended range, high precision, and compatibility of the prototype with common mobile networks. Cost-effective and easy to use, this beacon improves UAV recovery efforts by providing reliable localization data to users in real time, thus safeguarding the UAV investment. Full article

Short Message Service (SMS) still continues its existence despite the emergence of different messaging services. It plays a part in our lives as a communication service. Companies use SMS for advertisement purposes due to the fact that e-mail filtering systems have rooted, short message systems are being undersold by the operators, and spam detection and blocking systems used for short messages are ineffective. Individuals falling victim to SMS spam messages sent by malevolent persons incur pecuniary and non-pecuniary losses. The aim of this study is to present a hybrid model proposal with the intention of detecting SMS spam messages. This detection model uses a gated recurrent unit (GRU) and convolutional neural network (CNN) as two deep learning methods. However, the fact that both algorithms require high memory capacities is a limitation. The design for this model was laid out by using two different datasets containing combined text messages written in the Turkish and English languages. The datasets used in the study are TurkishSMSCollection and the SMS Spam dataset from the UCI database. The testing process was performed on the dataset through benchmarking as well as other machine learning algorithms. It was revealed in the study that the hybrid CNN + GRU approach attained an accuracy of 99.07% by demonstrating a better performance compared to the other algorithms. Full article

This study investigated vegetable farmers’ willingness-to-pay (WTP) for private agricultural advisory services in northwestern Ethiopia. Understanding farmers’ preferences is a crucial step for modernizing agricultural advisory services and transforming smallholder agri-food systems into a sustainable path. Discrete choice experiment data from 393 farm households were analyzed using a random parameter logit model (RPL). The results revealed that vegetable farmers are willing to pay for practice-oriented private advisory services. The result also showed the existence of heterogeneity in farmers’ preference for features of vegetable advisory services. Household heads’ educational status and age influenced preferences for advisory service features. The result is substantiated by the fact that merely 25.5% of the sample households acquired formal education. Farmers in general preferred extension services with frequent expert visits and practical engagement on-farm as opposed to digitized options that rely on short message service (SMS) and voice-based guidance. Additionally, farmers are willing to pay an ETB 120.89 and ETB 203.94 monthly fee for an extension service that emphasizes fruity and root and tuber vegetables, respectively, as opposed to leafy vegetables. The findings imply initiatives that push for commercializing agricultural advisory services should strive to achieve a balance between the practical application and digitization of extension services accounting for the heterogeneous preferences of smallholder farmers. Full article

Smishing attacks, a sophisticated form of cybersecurity threats conducted via Short Message Service (SMS), have escalated in complexity with the widespread adoption of mobile devices, making it increasingly challenging for individuals to distinguish between legitimate and malicious messages. Traditional phishing detection methods, such as feature-based, rule-based, heuristic, and blacklist approaches, have struggled to keep pace with the rapidly evolving tactics employed by attackers. To enhance cybersecurity and address these challenges, this paper proposes a hybrid deep learning approach that combines Bidirectional Gated Recurrent Units (Bi-GRUs) and Convolutional Neural Networks (CNNs), referred to as CNN-Bi-GRU, for the accurate identification and classification of smishing attacks. The SMS Phishing Collection dataset was used, with a preparatory procedure involving the transformation of unstructured text data into numerical representations and the training of Word2Vec on preprocessed text. Experimental results demonstrate that the proposed CNN-Bi-GRU model outperforms existing approaches, achieving an overall highest accuracy of 99.82% in detecting SMS phishing messages. This study provides an empirical analysis of the effectiveness of hybrid deep learning techniques for SMS phishing detection, offering a more precise and efficient solution to enhance cybersecurity in mobile communications. Full article

Background/Objectives: The optimal dietary approach for managing glycemic and metabolic control in type 2 diabetes (T2D) is still uncertain, though it should be tailored for clinical settings. Therefore, we sought to assess the impact of a multicomponent nutritional strategy on glycemic control in T2D patients within a public health system. Methods: NUGLIC was an open-label, parallel-group, superiority, multicenter randomized controlled trial. Participants aged 30 and older with poorly controlled T2D were randomly assigned to either (1) a personalized dietary prescription (control group, n = 185) or (2) a strategy involving targeted nutritional advising, mindfulness techniques, and short message services (NUGLIC [intervention] group, n = 186). The primary outcomes were glycated hemoglobin (HbA1c, %) measured after 24 weeks and glycemic control, defined as having an HbA1c > 7% at baseline and achieving ≤7% after follow-up, or having HbA1c ≤ 7% at baseline and reducing the use of glucose-lowering medications post-follow-up. The secondary outcomes included cardiometabolic features, self-care practices, diet quality, and quality of life. Results: A total of 371 participants were included in an intention-to-treat analysis for the primary outcomes. At six months, both groups exhibited a reduction in HbA1c levels compared to the baseline (NUGLIC group: −0.6% [95% confidence interval (CI) −0.9; −0.3], p < 0.001; control group: −0.5% [95% CI −0.7; −0.3], p < 0.001). However, no significant differences were observed between the groups in terms of HbA1c after follow-up (intervention group: 8.1%; control group: 8.3%; difference: −0.2% [95% CI −0.5; 0.1], p = 0.30) or glycemic control (NUGLIC group: 19.9%; control group: 18.9%; odds ratio 0.96 [95% CI 0.56; 1.67], p = 0.89). While the control group showed an improvement in overall diet quality, no significant differences emerged between the groups by the end of this study (p = 0.13). There were also no significant differences in other secondary outcomes nor in the use of glucose-lowering medications and adverse events after follow-up. Conclusions: The multicomponent nutritional strategy did not demonstrate superiority over personalized dietary prescriptions in achieving glycemic control for participants with poorly managed T2D. In this sense, both nutritional interventions could be used in clinical practice to improve HbA1c levels, considering the profile and preferences of individuals. Full article

Underreporting is the main limitation of spontaneous reporting systems. This cohort-event monitoring study aims to examine the potential of short message service (SMS)-based surveillance compared to traditional surveillance systems. Using VigiVax software, parents of vaccinated children aged two years or younger, in the period March 2021–May 2022, received a single SMS inquiry about adverse events following immunization (AEFI). Responses were collected, validated by health operators and integrated with the information on electronic immunization registries. AEFI reports were automatically submitted to the Italian Pharmacovigilance system. Among 254,160 SMS messages sent, corresponding to 451,656 administered doses (AD), 71,643 responses were collected (28.2% response rate), and 21,231 of them (8.3%) reported AEFI. After a seriousness assessment based on clinical criteria, 50 reports (0.24%) were classified as serious. Among these, a causality assessment identified 31 reports at least potentially related to the vaccination (RR: 6.86/100,000 AD). Febrile seizures following MMRV (measles, mumps, rubella, varicella) vaccination accounted for 11 of these 31 cases, with an incidence of 32 per 100,000 AD. No fatal outcomes were reported. Our findings support the highly favorable risk profile of pediatric vaccinations and the possibility to improve spontaneous reporting through the integration of digital technologies. Full article