Najran University

Integrated Reporting (IR) aims to present a holistic view of value creation by combining financial and non-financial information, including sustainability and ESG indicators. However, during the COVID-19 pandemic, companies in Saudi Arabia faced challenges related to delays in disclosure, limited transparency in non-financial information, and difficulties in providing timely and integrated reports due to operational disruptions and remote reporting systems. This study examines the impact of digital transformation on integrated reporting quality, the influence of pre- vs. post-COVID conditions, and the moderating effect of COVID-19 on the relationship between digital transformation and IR quality. Using a quantitative longitudinal approach, panel data from firms listed on the Saudi Stock Exchange (Tadawul) were analyzed using Stata over the periods before and after the pandemic (2018–2019 vs. 2020–2021/2022). The results reveal that digital transformation significantly improves IR quality, IR quality differs significantly between the pre- and post-COVID periods, and COVID-19 strengthens the relationship between digital transformation and IR quality. These findings highlight the importance of advanced digital technologies to enhance transparency, speed, and reliability in corporate reporting.

Extreme rainfall events can trigger flash floods that pose serious risks to communities, infrastructure, and critical services, particularly in arid and rapidly urbanizing environments. In the Kingdom of Saudi Arabia, short hydrological response times, strong spatial variability of precipitation, complex topography, and limited observational data significantly challenge flood early warning capabilities, which affect emergency management at the national scale. Addressing these challenges requires integrated and scalable hydro-meteorological forecasting systems capable of operating across large spatial domains while resolving convective weather events and associated localized flood impacts in urban/suburban areas.This study presents a nationwide, operational flash flood early warning system developed for the Kingdom of Saudi Arabia. The system is designed to provide consistent coverage across the country while capturing fine-scale weather, hydrological and hydrodynamic processes relevant to flash flooding in arid environments. It operates over 137 hydrological domains, representing more than 6,000 outlets, delivering 2D flood simulations at a spatial resolution of 30 m nationwide, with enhanced resolution of up to 2.5 m in selected urban areas.The forecasting framework is structured as an end-to-end modeling chain that links atmospheric forcing, hydrological response, hydraulic flood propagation, and infrastructure impacts. High-resolution numerical weather predictions generated by the Weather Research and Forecasting (WRF) model are combined with real-time radar and rain gauge observations to produce hourly ensemble weather and precipitation forecasts and hindcasts. These meteorological inputs drive a distributed hydrological model (CREST), which simulates runoff generation across arid catchments using spatially explicit information on topography, land cover, soil properties, and drainage networks. A reservoir management module is fully integrated within the modeling chain, allowing the system to account for reservoir storage dynamics, controlled releases, and spillway operations, and to assess the influence of dam infrastructure on downstream flood evolution.Hydrological outputs are used as boundary conditions to a two-dimensional hydrodynamic model, which simulates floodplain dynamics, water depths, and inundation extents.All model components are coupled within a WebGIS-based operational platform that displays deterministic and ensemble weather and hydrologic forecasts, probabilistic flood warnings, and real-time nowcasting products. Flood hazard information is delivered through interactive maps, warning levels, and time series, to support decision- making by civil protection authorities and emergency managers at national and local scales.The functionality and operational performance of the system are demonstrated through its application on a recent extreme rainfall and flash flood events that affected the entire region of Saudi Arabia in the period of December 9-16, 2025. The system successfully captured the timing, spatial extent, and severity of flooding across multiple domains, providing useful lead times and high-resolution inundation maps. This case study highlights the robustness, scalability, and operational value of the framework, demonstrating its potential to enhance flood preparedness through early warning, and risk management across the Kingdom of Saudi Arabia under increasing hydro- meteorological extremes.

BackgroundAssessing or measuring adherence is the initial step toward comprehending it, or the lack thereof.ObjectiveThis study aims to translate and validate the Treatment Adherence Questionnaire TAQ among Yemeni dialysis patients with cardiorenal syndrome.MethodsThis cross-cultural adaptation study was conducted at two dialysis centers in Hadhramout Governorate, Yemen, between January 10 and February 15 of 2021. The English version of TAQ was translated into Arabic using the Beaton translation process. Psychometric tests of the TAQ were performed on 100 patients with cardiorenal syndrome. For face and content validity, the pre-final version of the TAQ Arabic was tested using a convenience sample of 10 patients. Individual interviews were used to investigate the meaning, comprehensibility, and acceptability. To evaluate the factor loadings, discriminant validity, and internal consistency of the TAQ Arabic version (the TAQ-Ar), one hundred patients were selected in the same manner and using the same inclusion criteria. Exploratory Factor Analysis (EFA) was utilized to ascertain the underlying factor structure of the Arabic version of the questionnaire, as its dimensionality had not been previously determined in this group. We employed principal component extraction with promax rotation to produce a clear and understandable factor solution. To assess reproducibility, 30 patients were chosen randomly from 100 to resubmit the questionnaire 2 weeks after the initial administration and under the same conditions.ResultsThe transcultural adaptation process revealed that all TAQ-Ar items and patient descriptions exhibited full semantic equivalence. During the psychometric validation phase, the scale-level Content Validity Index was 0.88, and cognitive interviews (n = 30) confirmed patient clarity. Exploratory factor analysis identified four variables, aligning with the structure suggested by the original instrument inventor. Based on Bandalos' standards, factors were kept if their eigenvalues were more than 1 and their factor loadings were higher than 0.30. The overall average factor loading was 0.683, which shows that the test was valid. Internal consistency was very good (Cronbach's alpha = 0.948), and test-retest repeatability showed significant stability (ICC = 0.776).ConclusionWe confirm that the TAQ-Ar is suitable for assessing treatment adherence in individuals with Arabic as their first language for cardiorenal syndrome disease.