Search Results (266)

As Saudi Arabia accelerates digital transformation under Vision 2030, the sustainable adoption of Health 4.0 technologies depends on equitable digital health literacy (DHL) and population-level readiness for eHealth engagement. Despite growing interest, empirical data on the behavioral, social, and contextual determinants of digital health adoption remain limited in Middle Eastern settings. This study investigates the readiness of Saudi adults for eHealth services, identifies key behavioral factors influencing digital tool adoption, and proposes an equity-centered, network-aware DHL framework to support inclusive and sustainable Health 4.0 implementation. A multi-phase, cross-sectional study was conducted among 430 Saudi adults using validated instruments including eHEALS, TRI 2.0, UTAUT, and EQ-5D. Quantitative analysis employed multiple linear regression (R² = 0.79), structural equation modeling (CFI = 0.96; RMSEA = 0.04), social network analysis (centrality scores), and network-based diffusion analysis (s = 0.17). Additionally, a three-round Delphi method (CI ≤ 0.25) ensured expert consensus on framework development. Significant predictors of digital health tool adoption included eHealth readiness (β = 0.18), perceived usability, and system trust. Social network metrics identified central actors who facilitated peer-driven behavioral diffusion, validated through NBDA modeling. Based on these findings, a comprehensive DHL Equity Framework was synthesized, integrating behavioral drivers, network diffusion pathways, and principles from the Triple Bottom Line (TBL) framework to mitigate structural disparities while addressing environmental, economic, and social dimensions of sustainable digital health access. The framework was also systematically mapped to relevant Sustainable Development Goals (SDGs), highlighting its alignment with global health and sustainability targets. This study presents a scalable and policy-relevant model to guide inclusive eHealth strategies in Saudi Arabia and similar developing contexts. The proposed framework advances national digital resilience, reduces inequities, and promotes sustainable Health 4.0 service delivery. Full article

In alignment with Saudi Arabia’s Vision 2030, the Kingdom aims to achieve one of its main environmental targets: reaching net zero emissions by 2060. This ambitious goal can be realized through Carbon Dioxide Removal (CDR) technologies, particularly Direct Air Capture (DAC), which is among the most promising solutions. DAC offers high potential for extracting Carbon Dioxide (CO₂) directly from the atmosphere and is considered sustainable, especially when powered by renewable energy rather than fossil fuels. However, the technology remains highly cost-intensive. This paper presents a techno-economic assessment of renewable energy configurations to determine the most cost-effective solutions for DAC deployment. The evaluation focuses on Net Present Cost (NPC) and Levelized Cost of Energy (LCOE) across several regions in Saudi Arabia, using the Hybrid Optimization of Multiple Energy Resources (HOMER) Pro software (version 3.18.4). Full article

In recent years, solar energy has emerged as a pillar of sustainable development. However, maintaining panel efficiency under extreme environmental conditions remains a persistent hurdle. This study introduces an automated defect detection pipeline that leverages deep learning and computer vision to identify five standard anomaly classes: Non-Defective, Dust, Defective, Physical Damage, and Snow on photovoltaic surfaces. To build a robust foundation, a heterogeneous dataset of 8973 images was sourced from public repositories and standardized into a uniform labeling scheme. This dataset was then expanded through an aggressive augmentation strategy, including flips, rotations, zooms, and noise injections. A YOLOv11-based model was trained and fine-tuned using both fixed and adaptive learning rate schedules, achieving a mAP@0.5 of 85% and accuracy, recall, and F1-score above 95% when evaluated across diverse lighting and dust scenarios. The optimized model is integrated into an interactive dashboard that processes live camera streams, issues real-time alerts upon defect detection, and supports proactive maintenance scheduling. Comparative evaluations highlight the superiority of this approach over manual inspections and earlier YOLO versions in both precision and inference speed, making it well suited for deployment on edge devices. Automating visual inspection not only reduces labor costs and operational downtime but also enhances the longevity of solar installations. By offering a scalable solution for continuous monitoring, this work contributes to improving the reliability and cost-effectiveness of large-scale solar energy systems. Full article

The integration of robotics into Structural Health Monitoring (SHM) is rapidly reshaping how infrastructure is assessed and maintained. This review critically examines the current landscape of robotic technologies applied in SHM, with a specific focus on their implementation within the Saudi Arabian construction sector. It explores recent advancements in robotic platforms, such as unmanned aerial vehicles (UAVs), wall-climbing robots, and AI-driven inspection systems, and assesses their roles in damage detection, vibration monitoring, and real-time diagnostics. In addition to outlining technological capabilities, this paper identifies major adoption challenges related to system readiness, regulatory gaps, workforce limitations, and environmental constraints. Drawing on comparative experiences in the healthcare, energy, and legal domains, this review extracts cross-sectoral insights that offer practical guidance for accelerating robotic integration in SHM. This paper concludes by outlining research gaps and actionable recommendations to support scholars, policymakers, and industry professionals in advancing robotics-based monitoring in complex infrastructure environments. Full article

Background/Objectives: Hypertension is a growing public health concern in Saudi Arabia, driven by rapid socioeconomic changes. This study investigated the interplay between habitual, behavioral, and dietary risk factors associated with hypertension among Saudi adults. Methods: A cross-sectional survey was conducted among 3312 Saudi adults using multistage stratified random sampling. The data were collected via validated questionnaires assessing sociodemographic, anthropometric indicators, lifestyle behaviors, dietary patterns, and medical history. Hypertension status was determined through self-reported diagnosis. Bivariate analyses and multiple logistic regression identified independent predictors (p < 0.05). Results: Hypertension prevalence was 13% (mean age: 34 ± 15 years; 50% male). The strongest predictors were age (OR = 1.08/year; 95% CI: 1.07–1.10; p < 0.001), increased body mass index (OR = 1.03; 95% CI: 1.01–1.06; p = 0.011), smoking (OR = 1.55; 95% CI: 1.04–2.29; p = 0.030), and family history of hypertension (OR = 7.71; 95% CI: 5.61–10.75; p < 0.001). Participants with diabetes mellitus had 89% higher odds of hypertension (OR = 1.89; 95% CI: 1.42–2.51; p < 0.001), and those with dyslipidemia had more than double the odds (OR = 2.45; 95% CI: 1.38–4.22; p = 0.002). Protective factors included higher income (≥15,000 SAR; OR = 0.54; 95% CI: 0.36–0.81; p = 0.003) and regular whole grain consumption (OR = 0.60; 95% CI: 0.46–0.77; p < 0.001). Conclusions: Hypertension risk in Saudi adults is shaped by age, obesity, smoking, comorbid metabolic conditions (diabetes and dyslipidemia), and genetic pre-disposition. In contrast, higher income and whole grain intake may offer protection. These findings underscore the need for comprehensive prevention strategies that address both lifestyle and cardiometabolic comorbidities, in alignment with Saudi Vision 2030 health priorities. Full article

There is a growing global emphasis on reducing environmental pollution through innovative clean energy technologies, with photovoltaic systems gaining prominence as a sustainable solution. This study presents an integrated approach, combining advanced architectural modeling and dynamic energy simulation to evaluate the utilization of rooftop photovoltaic panels on a high-density higher educational building in Saudi Arabia. Utilizing detailed modeling involving Autodesk Revit and energy simulation through DesignBuilder to Level of Detail 3, the research provides unprecedented accuracy, validated against actual energy consumption data with a remarkable 92.28% precision. Notably, approximately 60% of the rooftop area is identified as suitable for photovoltaic installation, demonstrating a significant capacity to generate 1,028,494.50 kWh annually, covering 61.7% of the building’s energy needs. Financial analysis reveals robust economic benefits, including annual savings of USD 74,938.84, a payback period of under 7 years, and lifetime savings exceeding USD 1.87 million over 25 years. Seasonal variations and surplus energy during winter months are also detailed, highlighting the system’s resilience. Importantly, this study aligns with Saudi Arabia’s “Vision 2030” by showcasing the feasibility and strategic importance of rooftop photovoltaic solutions in urban educational settings within hot-climate regions, offering a pioneering contribution to sustainable urban energy planning. Full article

The integration of artificial intelligence (AI) into environmental, social, and governance (ESG) disclosure represents a critical frontier for corporate transparency in emerging markets. This study investigates the relationship between AI adoption in ESG reporting, disclosure quality, and financial performance among 180 Saudi-listed companies (2021–2024) within Vision 2030’s transformative context. Using the System Generalized Method of Moments (GMM) estimation with panel unit root and cointegration testing to ensure stationarity assumptions and addressing endogeneity through bounding analysis, the study finds that AI adoption intensity significantly enhances ESG disclosure quality (β = 0.289, p < 0.001), with coefficient significance assessed through t-tests using firm-clustered robust standard errors. Enhanced disclosure quality translates into meaningful financial performance improvements: 0.094 percentage points in return on assets (ROA), 0.156 in return on equity (ROE), and 0.0073 units in Tobin’s Q. Mediation analysis reveals that 73% of AI’s total effect operates through improved ESG quality rather than direct operational benefits. The findings demonstrate parametric bounds robust to macroeconomic confounders, suggesting AI-enhanced transparency creates substantial shareholder value through strengthened stakeholder relationships and reduced information asymmetries. Full article

As cyber threats such as phishing and ransomware continue to escalate, healthcare systems are facing significant challenges in protecting sensitive data and ensuring operational continuity. This study explores how email communication practices influence cybersecurity in Saudi Arabia’s healthcare sector, particularly within the framework of rapid digitalisation under Vision 2030. The research employs a qualitative approach, with semi-structured interviews conducted with 40 healthcare professionals across various hospitals. A phenomenological analysis of the data revealed several key vulnerabilities, including inconsistent cybersecurity training, a reliance on informal messaging apps, and limited awareness of phishing tactics. The inconsistent cybersecurity training across regions emerged as a major weakness affecting overall resilience. These findings, grounded in rich qualitative data, offer a significant standalone contribution to understanding cybersecurity in healthcare settings. The findings highlight the need for mandatory training and awareness programmes and policy reforms to enhance cyber resilience within healthcare settings. Full article

Background: Hearing impairment is a significant public health issue globally, yet national data for Saudi Arabia remain sparse. Methods: Using data from the 2017 Disability Survey, we analysed 12 hearing-related indicators across 13 administrative regions. Descriptive statistics, logistic regression, cluster analysis, and residual mapping were applied to identify socio-demographic disparities and service gaps. Findings: Among 20,408,362 Saudi nationals, about 1,445,723 (7.1%) reported at least one functional difficulty. Of these, 289,355 individuals (1.4%) had hearing impairment, either alone or with other difficulties—229,541 (1.1%) had hearing impairment combined with other disabilities, while 59,814 (0.3%) had only hearing impairment. Females and males were equally affected. Notably, educational attainment and marital status significantly influenced device uptake; less-educated and divorced individuals were particularly underserved. Regionally, southern provinces (Al-Baha, Jazan, and Najran) demonstrated the highest unmet need due to geographic barriers, limited audiological resources, and socioeconomic constraints, reflecting compounded risks from consanguinity and rural isolation. Cluster analyses identified provinces requiring urgent attention, recommending mobile audiology units, tele-audiology services, and means-tested vouchers to enhance coverage. Conclusions: Despite Saudi Arabia’s existing public audiology services and a National Newborn Hearing Screening programme achieving 96% coverage, substantial gaps remain in follow-up care and specialist distribution, underscoring the necessity for systematic workforce tracking and enhanced rural incentives. International evidence from India and Brazil underscores the feasibility and cost-effectiveness (approximately USD 5200/QALY) of these recommended interventions. Implementing targeted provincial strategies, integrating audiological screening into routine healthcare visits, and aligning resource allocation with the WHO and Vision 2030 benchmarks will significantly mitigate hearing impairment’s health, social, and economic impacts, enhancing the quality of life and societal inclusion for affected individuals. Full article

Background/Objectives: Saudi Arabia implemented the Saudi Medical Appointments and Referrals Centre (SMARC) e-referral system to coordinate patient transfers and enhance healthcare access across the country. This nationwide system was established to improve coordination between healthcare facilities and provide timely access to specialized services. SMARC operates as a centralized coordination hub connecting secondary and tertiary care facilities across all specialties nationwide. This study evaluates SMARC’s evolution since 2020–2021 and efficiency improvements through 2023–2024 after major expansion efforts. Methods: This retrospective analysis examined 755,145 e-referrals across all 13 administrative regions of Saudi Arabia during 2023–2024. The study analyzed data extracted from the SMARC database covering two consecutive years. Outcomes assessed included acceptance rates, referral destinations (internal within the same region vs. external to other regions), and factors associated with system performance. Results: The total volume of e-referrals through SMARC increased substantially by 19.34% to 755,145 in 2023–2024. Acceptance rates for referrals improved markedly from 74.13% to 90.19% over this period. The proportion of internal referrals increased from 80.13% of total referrals to 87.52%. In contrast, external referrals to other regions declined from 19.87% to 12.48% of the total. Critical care referrals (ICU, CCU, NICU, PICU) decreased from 12.39% to 9.91%. Referrals for life-saving emergency conditions showed a noticeable decrease from 6.65% to 2.18%. Referrals to hospital outpatient departments (OPD) also showed an increase from 48.07% to 66.66% of total referrals. Conclusions: SMARC demonstrated considerable improvements in key metrics including referral acceptance rates and growth in regional self-sufficiency. This progress is associated with the Kingdom’s goals for advancing its healthcare system under Vision 2030 initiatives. The system has enabled more effective care coordination and access to specialized services across regions. These achievements were observed during a period of significant healthcare infrastructure expansion documented during this period, including growth in specialized centers, increased ICU bed capacity following governmental regulation after the COVID-19 pandemic, and expansion of trained medical subspecialists. Full article

Franchising operates as a proven business model that drives substantial growth for small and medium-sized enterprises (SMEs) worldwide. The franchise ecosystem in Saudi Arabia lacks sufficient research, despite established frameworks for success in markets such as the United States, the United Kingdom, and Australia. This research investigates the elements that lead to franchise success in Saudi Arabia through a combination of qualitative and quantitative data. This research evaluates franchise performance through metrics such as Average Revenue Per Unit (ARPU), Return on Investment (ROI), Franchise Success Rate, Time to Break Even, and Market Growth Rate, comparing Saudi Arabia with the U.S., the U.K., and India to identify essential success determinants. The research reveals that franchise success depends on regulatory frameworks, cultural alignment, economic diversification, and supply chain efficiency. The U.S. and U.K. enjoy established legal protections, whereas Saudi Arabia faces regulatory complexities and resource limitations. The research proposes three strategic recommendations: government incentives, locally adapted business models, and carefully selected locations to boost franchise success. The analysis provides essential information to policymakers, franchisors, and entrepreneurs seeking to expand their businesses in Saudi Arabia. The implementation of Vision 2030 growth barrier solutions and market opportunities will enable Saudi Arabia to build up its franchising sector and enhance market performance. This research adds new knowledge to the franchising literature in emerging markets and its impact on sustainable business growth. Full article

Background: Visual impairment (VI) continues to be a significant global public health concern, especially in underserved rural communities. Objectives: This study aims to assess the prevalence of VI and refractive errors, as well as to identify the causes and risk factors associated with VI in Duhknah, a rural area in Qassim Province, Saudi Arabia. Methods: This cross-sectional study, conducted in May 2024, included 929 participants aged 6–90 years from Duhknah, a rural area in Qassim Province, Saudi Arabia. Refractive errors (REs) were measured using a non-cycloplegic autorefractometer. Anterior and posterior eye examinations were performed using slit lamp biomicroscopy, direct ophthalmoscopy, and 90 D fundus biomicroscopy. VI was classified based on the International Classification of Diseases 11th revision (ICD-11), 2018. Results: The findings revealed that 671 (72.2%) participants had never undergone an eye examination. The overall prevalence of presenting VI was 370 (39.8%), comprising 21.6% with mild VI, 11.0% moderate, 4.1% severe, and 3.1% classified as blind. The prevalence of hyperopia, myopia, and astigmatism was 20.6%, 36.9%, and 13.2%, respectively. Uncorrected REs were the most common cause of VI (81.4%), followed by amblyopia (13.5%) and cataracts (3.2%). Regression analysis showed that women had 1.58 times higher odds of VI (p = 0.001). Participants with eye examinations for one year or more had 3.64 times higher odds (p < 0.001). Additionally, the risk of VI was significantly lower among older participants (ages 18–90) compared to younger ones (ages 6–17), (p < 0.001). Conclusions: This study found most participants had never had an eye exam, and VI was highly prevalent in the rural community. These findings underscore the need to strengthen primary eye care in rural Saudi Arabia. Regular vision screening, particularly for children, and better access to refractive services could significantly reduce VI and support the goals of Saudi Vision 2030. Full article

Improving construction site safety remains a critical challenge in Saudi Arabia’s rapidly growing construction sector, where high accident rates and diverse labor forces demand evidence-based managerial interventions. This study investigated the influence of Managers’ Safety Perceptions and Practices (MSP) on Workers’ Safety Behaviors (WSB) in the Saudi construction industry, emphasizing the mediating roles of Workers’ Safety Awareness (WSA), Safety Competency (WSC), and Safety Actions (SA). The conceptual framework integrates these three mediators to explain how managerial attitudes and practices translate into frontline safety outcomes. A quantitative, cross-sectional design was adopted using a structured questionnaire distributed among construction workers, supervisors, and project managers. A total of 352 from 384 valid responses were collected, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4. The findings revealed that MSP does not directly influence WSB but has significant indirect effects through WSA, WSC, and SA. Among these, WSC emerged as the most powerful mediator, followed by WSA and SA, indicating that competency is the most critical driver of safe worker behavior. These results provide robust empirical support for a multidimensional mediation model, highlighting the need for managers to enhance safety behaviors not merely through supervision but through fostering awareness and competency, providing technical training, and implementing proactive safety measures. Theoretically, this study contributes a novel and integrative framework to the occupational safety literature, particularly within underexplored Middle Eastern construction contexts. Practically, it offers actionable insights for safety managers, industry practitioners, and policymakers seeking to improve construction safety performance in alignment with Saudi Vision 2030. Full article

Background: Social and financial services are essential for the inclusion and well-being of people with disabilities (PWDs), who often rely on family caregivers to access these systems. In Saudi Arabia, where disability inclusion is a strategic goal under Vision 2030, understanding caregiver experiences is crucial to identifying service gaps and improving accessibility. Objectives: This study aimed to explore caregivers’ perspectives on awareness, perceived barriers, and accessibility of social and financial services for PWDs in Saudi Arabia. The analysis is grounded in Andersen’s Behavioural Model of Health Service Use and the WHO’s International Classification of Functioning, Disability and Health (ICF) framework. Methods: A cross-sectional survey was conducted with 3353 caregivers of PWDs attending specialised day schools. The survey collected data on demographic characteristics, service awareness, utilisation, and perceived obstacles. Exploratory Factor Analysis (EFA) identified latent constructs, and Structural Equation Modelling (SEM) was used to test relationships between awareness, barriers, and accessibility. Results: Findings reveal that over 70% of caregivers lacked awareness of available services, and only about 3% had accessed them. Key challenges included technological barriers, complex procedures, and non-functional or unclear service provider platforms. Both User Barriers and Service Barriers were negatively associated with Awareness and Accessibility. Awareness, in turn, significantly predicted perceived Accessibility. Caregiver demographics, such as age, education, gender, and geographic location, also influenced awareness and service use. Conclusions: There is a pressing need for targeted awareness campaigns, accessible digital service platforms, and simplified service processes tailored to diverse caregiver profiles. Inclusive communication, decentralised outreach, and policy reforms are necessary to enhance service access and promote the societal inclusion of PWDs in alignment with Saudi Arabia’s Vision 2030. Full article

Saudi Vision 2030 seeks to improve social sustainability in the Kingdom through comprehensive economic and social reforms. This study investigates whether these reforms are associated with changes in subjective well-being (SWB), commonly understood as individuals’ experienced quality of life. Using Gallup World Poll data from 2013 to 2023 on Cantril ladder scores and affect balance in Saudi Arabia, we find increases in SWB following the implementation of Vision 2030 reforms, particularly for the affective component of SWB. While positive changes in SWB are observed across the entire population, the gains in affective well-being are especially pronounced among women. Blinder–Oaxaca decompositions show that improvements are associated with enhanced community basics, followed by greater income sufficiency, improved perceptions of social life, and an increased sense of personal freedom. Full article