The effect of COVID-19 pandemic on diabetes care indices in Southern Iran: an interrupted time series analysis.

BACKGROUND: Type 2 diabetes mellitus (T2DM) requires a continues bulk of cares. It is very probable COVID-19 pandemic is affected its healthcare coverage. METHODS: The interrupted time series analysis is used to model the trend of diabetes healthcare indices, such as the health worker visits, physician visits, body mass index (MBI), fasting blood sugar (FBS), and hemoglobin A1c (HbA1c), before and after the start of COVID-19 pandemic. The reference of data was the totals of all T2DM patients living in Fars Province, Southern Iran, areas covered by Shiraz University of Medical Science (SUMS), from 2019 to 2020. RESULTS: A significant decrease for visits by the health workers, and physicians was observed by starting COVID-19 pandemic (ß2 = -0.808, P < 0.001, ß2 = -0.560, P < 0.001); Nevertheless, the coverage of these services statistically increased by next months (ß3 = 0.112, P < 0.001, ß3 = 0.053, P < 0.001). A same pattern was observed for the number of BMI, FBS and HbA1c assessments, and number of refer to hospital emergency wards (ß3 = 0.105, P < 0.001; ß3 = 0.076, P < 0.001; ß3 = 0.022, P < 0.001; ß3 = 0.106, P < 0.001). The proportion of T2DM patients with HbA1C < 7%, and controlled hypertension during study period was statistically unchanged. CONCLUSIONS: When the COVID-19 pandemic was announced, T2DM healthcare coverage drastically decreased, but it quickly began to rebound. The health monitoring system could not have any noticeable effects on diabetes outcomes.

Ecological validity of executive function tests in predicting driving performance.

Almost all of our everyday activities depend on executive function (EF) skills. In line with the increasing attention to the ecological validation of neuropsychological assessment and intervention methods, this study aimed to explore the ecological validity of a relevant set of widely used EF tests, mostly from well-known paradigms of EF assessment, in predicting driving ability. Ninety-six healthy novice drivers (Mage = 26.2 years, SD = 8.4; 48 female) completed four stages of our data collection including psychological, EF, and driving assessments. For the psychological assessment, validated measures of sensation-seeking, risk-taking, personality traits, ADHD symptoms, depression, anxiety, and stress were administered. For the EF assessment, selected tests from the Delis-Kaplan Executive Function System (D-KEFS: Trail Making, Design Fluency, and Tower) and the Behavioral Assessment of the Dysexecutive Syndrome (BADS: Key Search, Zoo Map, and Modified Six Elements) along with a computerized Stroop test were administered. For the driving assessment, we used a simulated driving test comprising of 14 key dimensions of driving skills. Several correlations and multiple regression analyses were conducted. Significant correlations were found between all the EF measures and driving performance. Moreover, the EF measures predicted the driving ability over and above the effects of previous driving experience and the psychological variables. These results provide supporting evidence for the ecological validity of the EF tests in predicting driving performance. The incorporation of assessment and intervention targeting multiple domains of EF into driving rehabilitation and education programs could be a focus of future research.