Italy IT: Literacy Rate: Youth: % of People Age 15-24 data was reported at 99.860 % in 2011. This records an increase from the previous number of 99.812 % for 2001. Italy IT: Literacy Rate: Youth: % of People Age 15-24 data is updated yearly, averaging 99.812 % from Dec 1981 (Median) to 2011, with 3 observations. The data reached an all-time high of 99.860 % in 2011 and a record low of 99.643 % in 1981. Italy IT: Literacy Rate: Youth: % of People Age 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Italy – Table IT.World Bank.WDI: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Italy IT: Literacy Rate: Adult: % of People Aged 15 and Above data was reported at 98.848 % in 2011. This records an increase from the previous number of 98.417 % for 2001. Italy IT: Literacy Rate: Adult: % of People Aged 15 and Above data is updated yearly, averaging 98.417 % from Dec 1981 (Median) to 2011, with 3 observations. The data reached an all-time high of 98.848 % in 2011 and a record low of 96.461 % in 1981. Italy IT: Literacy Rate: Adult: % of People Aged 15 and Above data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Italy – Table IT.World Bank: Education Statistics. Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Yearly (annual) dataset of the Italy Adult Literacy Rate, including historical data, latest releases, and long-term trends from 1981-12-31 to 2019-12-31. Available for free download in CSV format.

Italy IT: Literacy Rate: Youth Female: % of Females Aged 15-24 data was reported at 99.869 % in 2011. This records an increase from the previous number of 99.820 % for 2001. Italy IT: Literacy Rate: Youth Female: % of Females Aged 15-24 data is updated yearly, averaging 99.820 % from Dec 1981 (Median) to 2011, with 3 observations. The data reached an all-time high of 99.869 % in 2011 and a record low of 99.587 % in 1981. Italy IT: Literacy Rate: Youth Female: % of Females Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Italy – Table IT.World Bank: Education Statistics. Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Italy IT: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24 data was reported at 1.000 Ratio in 2011. This records an increase from the previous number of 1.000 Ratio for 2001. Italy IT: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24 data is updated yearly, averaging 1.000 Ratio from Dec 1981 (Median) to 2011, with 3 observations. The data reached an all-time high of 1.000 Ratio in 2011 and a record low of 0.999 Ratio in 1981. Italy IT: Gender Parity Index (GPI): Literacy Rate: Youth Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Italy – Table IT.World Bank: Education Statistics. Gender parity index for youth literacy rate is the ratio of females to males ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Dataset for Zoccolotti, P.; De Luca, M.; Marinelli, C.V. Interpreting Developmental Surface Dyslexia within a Comorbidity Perspective. Brain Sci. 2021, 11, 1568. https:// doi.org/10.3390/brainsci11121568

Figure 2. Reading times (in s/word) in the reading of a list of 30 high-frequency words. Data (redrawn from [Pontillo, M.; De Luca, M.; Ellis, A.W.; Marinelli, C.V.; Spinelli, D.; Zoccolotti, P. Failure to learn a new format in developmental dyslexia. Sci. Rep. 2014, 4, 4869.]) refer to a cross-sectional study on a group of 1st to 8th grade typically developing children. Power functions indicate performance at the 10th, 30th, 50th, 70th, and 90th percentiles (curves from top to bottom). Vertical red bars mark the difference between the 90th and the 50th percentile foreach grade; note that the difference becomes quantitatively smaller at progressively higher grades (as indicated by shorter red bars). Horizontal blue bars link the performance corresponding to the 90th percentile with the corresponding performance at the level of the 50th percentile; this indicates the distance (in years) between the two levels of performance. Note that the distance (in years) increases at progressively higher grades (as indicated by longer blue bars).

Sector: 04. Provide quality, equitable and inclusive education and promote learning opportunities for all Algorithm: Percentage of upper secondary school class III students not achieving a sufficient level of literacy - Females Territorial comparisons: South Tyrol, Italy

The study aimed to explore whether the 1-in-X bias is also present in relation to immigration growth rates. We tested this research question on a representative sample of adult residents in Trento, Italy, between March and April 2019. Participants were presented with data comparing the foreign immigrant-to-resident population ratio in Italy for 2001 (1 in 40) and 2011 (1 in 15), using two distinct formats—1-in-X and percentages. They were then asked to express the perceived increase. Baseline measures of several individual-level factors, including cultural worldviews, perceptions of immigration, numeracy, science literacy, and economic literacy, were also collected to explore the potential role of individual differences in influencing the effect of the 1-in-X format on the perceived increase in immigrants. The results confirmed the existence of the 1-in-X bias, demonstrating that the immigration growth rate in the 1-in-X format was perceived as higher than in the percentage format, even after controlling for the effects of the idiosyncratic variables. The results of this study provide insight into how different numerical formats can influence public perceptions of immigration growth rates, offering suggestions to policymakers, communicators, and stakeholders about how the presentation of information can shape public opinion.

Dataset from Trajectories of Health-Related Quality of Life, Health Literacy, and Self-Efficacy in Curatively-Treated Patients with Esophageal Cancer: A Longitudinal Single-Center Study in Italy Arianna Magon, RN, MSN, PhD, Rosario Caruso, PhD, Andrea Sironi, MD, Sabrina Mirabella, RN, MSN, Federica Dellafiore, PhD, RN, Cristina Arrigoni, RN, MSc, Luigi Bonavina, MD, FACS https://doi.org/10.1177/23743735211060769

Abstract

This prospective longitudinal study aimed to describe the trajectories of HRQoL, health literacy, and self-efficacy in patients with esophageal cancer, which have been thus far poorly described. Data were collected at baseline (preoperative phase) and in the postoperative period (two weeks, and one, two, and three months after esophagectomy). The study hypothesis was that health literacy and self-efficacy might predict better health status and quality of life over time. Forty-five patients were enrolled between 2018 and 2019. HRQoL, health literacy, and self-efficacy were assessed using validated scales. The ability to analyze information to exert greater control over life events critically (critical health literacy) (η²p = 0.660) and the individual's confidence in dealing with challenging tasks (self-efficacy) (η²p = 0.501) strongly predicted the scores of general health status over time. Overall, the functional status improved at 3 months after surgery, and this trend paralleled the decline of cancer-specific and surgery-related symptoms. In conclusion, researchers and clinicians should pay greater attention to optimizing baseline health literacy and self-efficacy levels. Future educational and motivational interventions should be further tested and possibly integrated into the prehabilitation programs.