Can Media Literacy Intervention Improve Fake News Credibility Assessment? A Meta-Analysis.

Fake news impacts individuals' behavior and decision-making while also disrupting political processes, perceptions of medical advice, and societal trends. Improving individuals' ability to accurately assess fake news can reduce its harmful effects. However, previous research on media literacy interventions designed for improving fake news credibility assessments has yielded inconsistent results. We systematically collected 33 independent studies and performed a meta-analysis to examine the effects of media literacy interventions on assessing fake news credibility (n = 36,256). The results showed that media literacy interventions significantly improved fake news credibility assessments (Hedges' g = 0.53, 95% confidence interval [0.29-0.78], p < 0.001). Gaming interventions were the most effective intervention form. Conversely, the intervention channel, outcome measurement, and subject characteristics (age, gender, and country development level) did not influence the intervention effects.

Association between Cholecystectomy and the Incidence of Pancreaticobiliary Cancer after Endoscopic Choledocholithiasis Management.

(1) Background: Previous studies have raised concerns about a potential increase in pancreaticobiliary cancer risk after cholecystectomy, but few studies have focused on patients who undergo cholecystectomy after receiving endoscopic retrograde cholangiopancreatography (ERCP) for choledocholithiasis. This study aims to clarify cancer risks in these patients, who usually require cholecystectomy, to reduce recurrent biliary events. (2) Methods: We conducted a nationwide cohort study linked to the National Health Insurance Research Database, the Cancer Registry Database, and the Death Registry Records to evaluate the risk of pancreaticobiliary cancers. All patients who underwent first-time therapeutic ERCP for choledocholithiasis from 2011 to 2017 in Taiwan were included. We collected the data of 13,413 patients who received cholecystectomy after endoscopic retrograde cholangiopancreatography and used propensity score matching to obtain the data of 13,330 patients in both the cholecystectomy and non-cholecystectomy groups with similar age, gender, and known pancreaticobiliary cancer risk factors. Pancreaticobiliary cancer incidences were further compared. (3) Results: In the cholecystectomy group, 60 patients had cholangiocarcinoma, 61 patients had pancreatic cancer, and 15 patients had ampullary cancer. In the non-cholecystectomy group, 168 cases had cholangiocarcinoma, 101 patients had pancreatic cancer, and 49 patients had ampullary cancer. The incidence rates of cholangiocarcinoma, pancreatic cancer, and ampullary cancer were 1.19, 1.21, and 0.3 per 1000 person-years in the cholecystectomy group, all significantly lower than 3.52 (p < 0.0001), 2.11 (p = 0.0007), and 1.02 (p < 0.0001) per 1000 person-years, respectively, in the non-cholecystectomy group. (4) Conclusions: In patients receiving ERCP for choledocholithiasis, cholecystectomy is associated with a significantly lower risk of developing pancreaticobiliary cancer.

Mapping land-use and land-cover changes through the integration of satellite and airborne remote sensing data.

An integrated, remotely sensed approach to assess land-use and land-cover change (LULCC) dynamics plays an important role in environmental monitoring, management, and policy development. In this study, we utilized the advantage of land-cover seasonality, canopy height, and spectral characteristics to develop a phenology-based classification model (PCM) for mapping the annual LULCC in our study areas. Monthly analysis of normalized difference vegetation index (NDVI) and near-infrared (NIR) values derived from SPOT images enabled the detection of temporal characteristics of each land type, serving as crucial indices for land type classification. The integration of normalized difference built-up index (NDBI) derived from Landsat images and airborne LiDAR canopy height into the PCM resulted in an overall performance of 0.85, slightly surpassing that of random forest analysis or principal component analysis. The development of PCM can reduce the time and effort required for manual classification and capture annual LULCC changes among five major land types: forests, built-up land, inland water, agriculture land, and grassland/shrubs. The gross change LULCC analysis for the Taoyuan Tableland demonstrated fluctuations in land types over the study period (2013 to 2022). A negative correlation (r = - 0.79) in area changes between grassland/shrubs and agricultural land and a positive correlation (r = 0.47) between irrigation ponds and agricultural land were found. Event-based LULCC analysis for Taipei City demonstrated a balance between urbanization and urban greening, with the number of urbanization events becoming comparable to urban greening events when the spatial extent of LULCC events exceeds 1000 m2. Besides, small-scale urban greening events are frequently discovered and distributed throughout the metropolitan area of Taipei City, emphasizing the localized nature of urban greening events.