The average daily time spent reading by individuals in the United States in 2023 amounted to 0.26 hours, or 15.6 minutes. According to the study, adults over the age of 75 were the most avid readers, spending over 45 minutes reading each day. Meanwhile, those aged between 15 and 19 years read for less than nine minutes per day on average. Reading and COVID-19 Daily time reading increased among most consumers between 2019 and 2020, part of which could be linked to the unprecedented increases in media consumption during COVID-19 shutdowns. The mean annual expenditure on books per consumer unit also increased year over year, along with spending on digital book readers. Book reading habits A 2020 survey on preferred book formats found that 70 percent of U.S. adults favored print books over e-books or audiobooks. However, engagement with digital books is growing. Figures from an annual study on book consumption revealed that the share of adults who reported reading an audiobook in the last year almost doubled between 2011 and 2019, and e-book readership also grew overall during that period.

Editor’s Choice

• The Healthcare IT market size is expected to be worth around USD 1728 Bn by 2032
• According to a report by UNESCO, countries in South and South-West Asia have the highest number of illiterate adults in the world, estimated at 388 million.
• Approximately 36% of adult Americans possess only basic or below basic health literacy skills.
• Only 12% of Americans are considered proficient in their health literacy skills.
• Health literacy levels in China increased from 6.48% of the population in 2008 to 23.15% in 2020.
• A recent study analyzing global health literacy research from 1995 to 2020 identified the United States, Australia, and the United Kingdom as major contributors to the international collaboration network on health literacy.
• Mental health has been the most active research field in recent years in the context of health literacy.

In 2023, adults in the United States spent more time reading on weekends than weekdays, according to recent data. The average time spent reading in the U.S. amounted to **** hours (almost ** minutes) on weekends and holidays, while daily time spent reading on weekdays in 2023 dropped back to pre-pandemic levels at a ******* of an hour.

In 2023, the average adult literacy rates (15 years and older) in Latin America and the Caribbean amounted to 94.79 percent. Literacy rates in Latin America and the Caribbean have been slightly improving in all three age groups since 2014.

The average for 2021 based on 3 countries was 94.81 percent. The highest value was in Costa Rica: 98.04 percent and the lowest value was in Puerto Rico: 92.4 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

Graph and download economic data for Literacy Rate, Adult Total for Developing Countries in Latin America and Caribbean (SEADTLITRZSLAC) from 1974 to 2023 about Caribbean Economies, Latin America, literacy, adult, and rate.

The average for 2021 based on 12 countries was 98.27 percent. The highest value was in Costa Rica: 99.53 percent and the lowest value was in Puerto Rico: 92.4 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

In the past five decades, the global literacy rate among adults has grown from 67 percent in 1976 to 87.36 percent in 2023. In 1976, males had a literacy rate of 76 percent, compared to a rate of 58 percent among females. This difference of over 17 percent in 1976 has fallen to just seven percent in 2020. Although gaps in literacy rates have fallen across all regions in recent decades, significant disparities remain across much of South Asia and Africa, while the difference is below one percent in Europe and the Americas. Reasons for these differences are rooted in economic and cultural differences across the globe. In poorer societies, families with limited means are often more likely to invest in their sons' education, while their daughters take up a more domestic role. Varieties do exist on national levels, however, and female literacy levels can sometimes exceed the male rate even in impoverished nations, such as Lesotho (where the difference was over 17 percent in 2014); nonetheless, these are exceptions to the norm.

There is a gender gap in the global literacy rate. Although literacy rates have generally increased worldwide for both men and women, men are on average more literate than women. As of 2023, about 90.6 percent of men and a little less than 84.1 percent of women worldwide were literate. Adult literacy rate is defined as the percentage of people aged 15 years and above who can both read and write with understanding a short, simple statement about their everyday life. Youth literacy rate Not only does the literacy gender gap concern adults, it also exists among the world’s younger generations aged 15 to 24. Despite an overall increase in literacy, young men are still more literate than young women. In fact, the global youth literacy rate as gender parity index was 0.98 as of 2023, indicating that young women are not yet as literate as young men. Gender pay gap Gender gaps occur in many different spheres of global society. One such issue concerns salary gender gaps in professional life. Regarding the controlled gender pay gap, which measures the median salary for men and women with the same job and qualifications, women still earned less than men as of 2024. The difference was even bigger when measuring the median salary for all men and women. However, not everyone worries about gender pay gaps. According to a survey from 2021, 54 percent of the female respondents deemed the gender pay gap a real problem, compared to 45 percent of the male respondents.

Abstract

The PIRLS 2006 aimed to generate a database of student achievement data in addition to information on student, parent, teacher, and school background data for the 47 areas that participated in PIRLS 2006.

Geographic coverage

Nationally representative

Analysis unit

Units of analysis in the study are schools, students, parents and teachers.

Universe

PIRLS is a study of student achievement in reading comprehension in primary school, and is targeted at the grade level in which students are at the transition from learning to read to reading to learn, which is the fourth grade in most countries. The formal definition of the PIRLS target population makes use of UNESCO's International Standard Classification of Education (ISCED) in identifying the appropriate target grade:

"…all students enrolled in the grade that represents four years of schooling, counting from the first year of ISCED Level 1, providing the mean age at the time of testing is at least 9.5 years. For most countries, the target grade should be the fourth grade, or its national equivalent."

ISCED Level 1 corresponds to primary education or the first stage of basic education, and should mark the beginning of "systematic apprenticeship of reading, writing, and mathematics" (UNESCO, 1999). By the fourth year of Level 1, students have had 4 years of formal instruction in reading, and are in the process of becoming independent readers. In IEA studies, the above definition corresponds to what is known as the international desired target population. Each participating country was expected to define its national desired population to correspond as closely as possible to this definition (i.e., its fourth grade of primary school). In order to measure trends, it was critical that countries that participated in PIRLS 2001, the previous cycle of PIRLS, choose the same target grade for PIRLS 2006 that was used in PIRLS 2001. Information about the target grade in each country is provided in Chapter 9 of the PIRLS 2006 Technical Report.

Although countries were expected to include all students in the target grade in their definition of the population, sometimes it was not possible to include all students who fell under the definition of the international desired target population. Consequently, occasionally a country's national desired target population excluded some section of the population, based on geographic or linguistic constraints. For example, Lithuania's national desired target population included only students in Lithuanian-speaking schools, representing approximately 93 percent of the international desired population of students in the country. PIRLS participants were expected to ensure that the national defined population included at least 95 percent of the national desired population of students. Exclusions (which had to be kept to a minimum) could occur at the school level, within the sampled schools, or both. Although countries were expected to do everything possible to maximize coverage of the national desired population, school-level exclusions sometimes were necessary. Keeping within the 95 percent limit, school-level exclusions could include schools that:

• were geographically remote,
• had very few students,
• had a curriculum or structure different from the mainstream education system, or
• were specifically for students with special needs.

The difference between these school-level exclusions and those at the previous level is that these schools were included as part of the sampling frame (i.e., the list of schools to be sampled). Th ey then were eliminated on an individual basis if it was not feasible to include them in the testing.

In many education systems, students with special educational needs are included in ordinary classes. Due to this fact, another level of exclusions is necessary to reach an eff ective target population-the population of students who ultimately will be tested. These are called within-school exclusions and pertain to students who are unable to be tested for a particular reason but are part of a regular classroom. There are three types of within-school exclusions.

• Intellectually disabled students
• Functionally disabled students
• Non-native language speakers

Students eligible for within-school exclusion were identified by staff at the schools and could still be administered the test if the school did not want the student to feel out of place during the assessment (though the data from these students were not included in any analyses). Again, it was important to ensure that this population was as close to the national desired target population as possible. If combined, school-level and within-school exclusions exceeded 5 percent of the national desired target population, results were annotated in the PIRLS 2006 International Report (Mullis, Martin, Kennedy, & Foy, 2007). Target population coverage and exclusion rates are displayed for each country in Chapter 9 of the PIRLS 2006 Technical Report. Descriptions of the countries' school-level and within-school exclusions can be found in Appendix B of the PIRLS 2006 Technical Report.

Kind of data

Sample survey data [ssd]

Sampling procedure

The basic sample design used in PIRLS 2006 is known as a two-stage stratified cluster design, with the first stage consisting of a sample of schools, and the second stage consisting of a sample of intact classrooms from the target grade in the sampled schools. While all participants adopted this basic two-stage design, four countries, with approval from the PIRLS sampling consultants, added an extra sampling stage. The Russian Federation and the United States introduced a preliminary sampling stage, (first sampling regions in the case of the Russian Federation and primary sampling units consisting of metropolitan areas and counties in the case of the United States). Morocco and Singapore also added a third sampling stage; in these cases, sub-sampling students within classrooms rather than selecting intact classes.

For countries participating in PIRLS 2006, school stratification was used to enhance the precision of the survey results. Many participants employed explicit stratification, where the complete school sampling frame was divided into smaller sampling frames according to some criterion, such as region, to ensurea predetermined number of schools sampled for each stratum. For example, Austria divided its sampling frame into nine regions to ensure proportional representation by region (see Appendix B for stratification information for each country). Stratification also could be done implicitly, a procedure by which schools in a sampling frame were sorted according to a set of stratification variables prior to sampling. For example, Austria employed implicit stratification by district and school size within each regional stratum. Regardless of the other stratification variables used, all countries used implicit stratification by a measure of size (MOS) of the school.

All countries used a systematic (random start, fixed interval) probability proportional-to-size (PPS) sampling approach to sample schools. Note that when this method is combined with an implicit stratification procedure, the allocation of schools in the sample is proportional to the size of the implicit strata. Within the sampled schools, classes were sampled using a systematic random method in all countries except Morocco and Singapore, where classes were sampled with probability proportional to size, and students within classes sampled with equal probability. The PIRLS 2006 sample designs were implemented in an acceptable manner by all participants.

Sampling deviation

8 National Research Coordinators (NRCs) encountered organizational constraints in their systems that necessitated deviations from the sample design. In each case, the Statistics Canada sampling expert was consulted to ensure that the altered design remained compatible with the PIRLS standards.

These country specific deviations from sample design are detailed in Appendix B of the PIRLS 2006 Technical Report (page 231) attached as Related Material.

Mode of data collection

Face-to-face [f2f]

Research instrument

• PIRLS Background Questionnaires By gathering information about children’s experiences together with reading achievement on the PIRLS test, it is possible to identify the factors or combinations of factors that relate to high reading literacy. An important part of the PIRLS design is a set of questionnaires targeting factors related to reading literacy. PIRLS administered four questionnaires: to the tested students, to their parents, to their reading teachers, and to their school principals.

• Student Questionnaire Each student taking the PIRLS reading assessment completes the student questionnaire. The questionnaire asks about aspects of students’ home and school experiences - including instructional experiences and reading for homework, self-perceptions and attitudes towards reading, out-of-school reading habits, computer use, home literacy resources, and basic demographic information.

• Learning to Read (Home) Survey The learning to read survey is completed by the parents or primary caregivers of each student taking the PIRLS reading assessment. It addresses child-parent literacy interactions, home literacy resources, parents’ reading habits and attitudes, homeschool connections, and basic demographic and socioeconomic indicators.

• Teacher Questionnaire The reading teacher of each fourth-grade class sampled for PIRLS completes a questionnaire designed to gather information about classroom contexts for developing reading literacy. This questionnaire

In 2023, the share of women aged 15 or older who could read and write in Latin America and the Caribbean amounted to 94.79 percent, around 0.33 percentage point lower than the literacy rate among adult men. This region's adult literacy rate averaged at 94.8 percent in 2023.

Abstract

PIRLS provides internationally comparative data on how well children read by assessing students’ reading achievement at the end of grade four. PIRLS 2016 is the fourth cycle of the study and collects considerable background information on how education systems provide educational opportunities to their students, as well as the factors that influence how students use this opportunity. In 2016 PIRLS was extended to include ePIRLS – an innovative assessment of online reading.

The results of PIRLS 2016 demonstrate a number of positive developments in reading literacy worldwide. For the first time in the history of the study, as many as 96 percent of fourth graders from over 60 education systems achieved above the PIRLS low international benchmark.

Geographic coverage

Nationally representative samples of approximately 4,000 students from 150 to 200 schools participated in PIRLS 2016. About 319,000 students, 310,000 parents, 16,000 teachers, and 12,000 schools participated in total.

Analysis unit

The unit of analysis describes:

• Schools

• Students

• Parents

• Teachers

Universe

All students enrolled in the grade that represents four years of schooling counting from the first year of ISCED Level 1, providing the mean age at the time of testing is at least 9.5 years.

All students enrolled in the target grade, regardless of their age, belong to the international target population and should be eligible to participate in PIRLS. Because students are sampled in two stages, first by randomly selecting a school and then randomly selecting a class from within the school, it is necessary to identify all schools in which eligible students are enrolled. Essentially, eligible schools for PIRLS are those that have any students enrolled in the target grade, regardless of type of school.

Kind of data

Sample survey data [ssd]

Sampling procedure

PIRLS is designed to provide valid and reliable measurement of trends in student achievement in countries around the world, while keeping to a minimum the burden on schools, teachers, and students. The PIRLS program employs rigorous school and classroom sampling techniques so that achievement in the student population as a whole may be estimated accurately by assessing just a sample of students from a sample of schools. PIRLS assesses reading achievement at fourth grade. The PIRLS 2016 cycle also included PIRLS Literacy-a new, less difficult reading literacy assessment, and ePIRLS-an extension of PIRLS with a focus on online informational reading.

PIRLS employs a two-stage random sample design, with a sample of schools drawn as a first stage and one or more intact classes of students selected from each of the sampled schools as a second stage. Intact classes of students are sampled rather than individuals from across the grade level or of a certain age because PIRLS pays particular attention to students’ curricular and instructional experiences, and these typically are organized on a classroom basis. Sampling intact classes also has the operational advantage of less disruption to the school’s day-to-day business than individual student sampling.

SAMPLE SIZE

For most countries, the PIRLS precision requirements are met with a school sample of 150 schools and a student sample of 4,000 students for each target grade. Depending on the average class size in the country, one class from each sampled school may be sufficient to achieve the desired student sample size. For example, if the average class size in a country were 27 students, a single class from each of 150 schools would provide a sample of 4,050 students (assuming full participation by schools and students). Some countries choose to sample more than one class per school, either to increase the size of the student sample or to provide a better estimate of school level effects.

For countries choosing to participate in both PIRLS and PIRLS Literacy, the required student sample size is doubled-i.e., around 8,000 sampled students. Countries could choose to select more schools or more classes within sampled schools to achieve the required sample size. Because ePIRLS is designed to be administered to students also taking PIRLS, the PIRLS sample size requirement remains the same for countries choosing also to participate in ePIRLS.

PIRLS STRATIFIED TWO-STAGE CLUSTER SAMPLE DESIGN

The basic international sample design for PIRLS is a stratified two-stage cluster sample design, as follows:

• First Sampling Stage. For the first sampling stage, schools are sampled with probabilities proportional to their size (PPS) from the list of all schools in the population that contain eligible students. The schools in this list (or sampling frame) may be stratified (sorted) according to important demographic variables. Schools for the field test and data collection are sampled simultaneously using a systematic random sampling approach. Two replacement schools are also pre-assigned to each sampled school during the sample selection process, and these replacement schools are held in reserve in case the originally sampled school refuses to participate. Replacement schools are used solely to compensate for sample size losses in the event that the originally sampled school does not participate. School sampling is conducted for each country by Statistics Canada with assistance from IEA Hamburg, using the sampling frame provided by the country’s National Research Coordinator.

• Second Sampling Stage. The second sampling stage consists of the selection of one (or more) intact class from the target grade of each participating school. Class sampling in each country is conducted by the National Research Coordinator using the Within-School Sampling Software (WinW3S) developed by IEA Hamburg and Statistics Canada. Having secured a sampled school’s agreement to participate in the assessment, the National Research Coordinator requests information about the number of classes and teachers in the school and enters it in the WinW3S database.

Classes smaller than a specified minimum size are grouped into pseudo-classes prior to sampling. The software selects classes with equal probabilities within schools. All students in each sampled class participate in the assessment. Sampled classes that refuse to participate may not be replaced.

For countries participating in both PIRLS and PIRLS Literacy, students within a sampled class are randomly assigned either a PIRLS or PIRLS Literacy booklet through a booklet rotation system. This is done to ensure that PIRLS and PIRLS Literacy are administered to probabilistically equivalent samples. In countries taking part in ePIRLS, all students assessed in PIRLS are expected to participate in ePIRLS.

STRATIFICATION

Stratification consists of arranging the schools in the target population into groups, or strata, that share common characteristics such as geographic region or school type. Examples of stratification variables used in PIRLS include region of the country (e.g., states or provinces); school type or source of funding (e.g., public or private); language of instruction; level of urbanization (e.g., urban or rural area); socioeconomic indicators; and school performance on national examinations.

In PIRLS, stratification is used to:

• Improve the efficiency of the sample design, thereby making survey estimates more reliable

• Apply different sample designs, such as disproportionate sample allocations, to specific groups of schools (e.g., those in certain states or provinces)

• Ensure proportional representation of specific groups of schools in the sample School stratification can take two forms: explicit and implicit. In explicit stratification, a separate school list or sampling frame is constructed for each stratum and a sample of schools is drawn from that stratum. In PIRLS, the major reason for considering explicit stratification is disproportionate allocation of the school sample across strata. For example, in order to produce equally reliable estimates for each geographic region in a country, explicit stratification by region may be used to ensure the same number of schools in the sample for each region, regardless of the relative population size of the regions.

Implicit stratification consists of sorting the schools by one or more stratification variables within each explicit stratum, or within the entire sampling frame if explicit stratification is not used. The combined use of implicit strata and systematic sampling is a very simple and effective way of ensuring a proportional sample allocation of students across all implicit strata. Implicit stratification also can lead to improved reliability of achievement estimates when the implicit stratification variables are correlated with student achievement.

National Research Coordinators consult with Statistics Canada and IEA Hamburg to identify the stratification variables to be included in their sampling plans. The school sampling frame is sorted by the stratification variables prior to sampling schools so that adjacent schools are as similar as possible. Regardless of any other explicit or implicit variables that may be used, the school size is always included as an implicit stratification variable.

SCHOOL SAMPLING FRAME

One of the National Research Coordinator’s most important sampling tasks is the construction of a school sampling frame for the target population. The sampling frame is a list of all schools in the country that have students enrolled in the target grade and is the list from which the school sample is drawn. A well-constructed sampling frame provides complete coverage of the national target population without being contaminated by incorrect or duplicate entries or entries that refer to elements that are not

Grounded in a strength-based (asset) model, this study explores the racial disparities in students’ learning and well-being during the pandemic. Linking the U.S. national/state databases of education and health, it examines whole-child outcomes and related factors—remote learning and protective community. It reveals race/ethnicity-stratified, state-level variations of learning and well-being losses in the midst of school accountability turnover. This data file includes aggregate state-level data derived from the NAEP and NSCH datasets, including all 50 U.S. states' pre-pandemic and post-pandemic measures of whole-child development outcomes (academic proficiency, socioemotional wellness, and physical health) as well as environmental conditions (remote learning and protective community) among school-age children. Methods To address the research questions, this study examines repeated cross-sectional datasets with nation/state-representative samples of school-age children. For academic achievement measures, the National Assessment of Educational Progress (NAEP) 2019 and 2022 datasets are used to assess nationally representative samples of 4th-grade and 8th-grade students’ achievement in reading and math (http://www.nces.ed.gov/nationsreportcard). In 2019, the NAEP samples included: 150,600 fourth graders from 8,300 schools and 143,100 eighth graders from 6,950 schools. In 2022, the NAEP samples included: (1) for reading, 108,200 fourth graders from 5,780 schools and 111,300 eighth graders from 5,190 schools; (2) for math, 116,200 fourth graders from 5,780 schools and 111,000 eighth graders from 5,190 schools. Data are weighted to be representative of the US population of students in grades 4 and 8, each for the entire nation and every state. Results are reported as average scores on a 0 to 500 scale and as percentages of students performing at or above the NAEP achievement levels: NAEP Basic, NAEP Proficient, and NAEP Advanced. In this study, we focus on changes in the percentages of students at or above the NAEP Basic level, which is the minimum competency level expected for all students across the nation. As a supplement to the NAEP assessment data, this study uses the NAEP School Dashboard (see https://ies.ed.gov/schoolsurvey/mss-dashboard/), which surveyed approximately 3,500 schools each month at grades 4 and 8 each during the pandemic period of January through May 2021: 46 states/jurisdictions participated, and 4,100 of 6,100 sampled schools responded. This study uses state-level information on the percentages of students who received in-person vs. remote/hybrid instructional modes. The school-reported remote learning enrollment rate is highly correlated with the NAEP survey student-reported remote learning experience (during 2021) across grades and subjects (r = .82 for grade 4 reading, r = .81 for grade 4 math, r = .79 for grade 8 reading, r = .83 for grade 8 math). These strong positive correlations provide supporting evidence for the cross-validation of remote learning measures at the state level. For socioemotional wellness and physical health measures, the National Survey of Children’s Health (NSCH) data are used. The 2018/19 surveys involved about 356,052 households screened for age-eligible children, and 59,963 child-level questionnaires were completed. The 2020/21 surveys involved about 199,840 households screened for age-eligible children, and 93,669 child-level questionnaires were completed. Our analysis focuses on school-age children (ages 6-17) in the data. In addition, the NSCH data are also used to assess the quality of protective and nurturing environment for child development across family, school, and neighborhood settings (see Appendix).

Reading Software for Children Market Outlook

The global market size for reading software for children is projected to grow from USD 2.5 billion in 2023 to USD 6.2 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 10.4% during the forecast period. This robust growth can be attributed to several factors such as the increasing integration of technology in education and the growing emphasis on early childhood literacy. As parents and educators seek innovative ways to enhance children's reading skills, the demand for interactive and engaging reading software is expected to soar.

One of the primary growth drivers for this market is the rising awareness of the importance of early childhood education. Studies have shown that early exposure to reading can significantly boost a childÂ’s cognitive development and academic performance. Consequently, parents are investing more in educational tools that can provide a strong foundation for their childrenÂ’s learning journey. With the advent of user-friendly and interactive reading software, children can now explore the world of books in a more engaging manner, thereby fostering a love for reading from an early age.

Technological advancements have also played a crucial role in propelling the market forward. The proliferation of smartphones and tablets has made it easier for developers to create versatile and accessible reading software. These advancements have paved the way for features such as voice recognition, interactive storylines, and personalized learning paths, making reading a more dynamic and enjoyable experience for children. Additionally, the incorporation of artificial intelligence and machine learning algorithms has enabled these platforms to offer customized content that adapts to the individual learning pace of each child.

The growing collaboration between educational institutions and software developers is another significant factor driving market growth. Schools and educational organizations are increasingly partnering with tech companies to integrate reading software into their curriculum. This collaboration not only enhances the learning experience for students but also provides valuable data insights that can be used to further refine and improve the software. By leveraging these educational technologies, institutions can better track student progress, identify areas of improvement, and offer targeted interventions where necessary.

In recent years, the popularity of Children Picture Book has surged, particularly as a complementary tool to digital reading software. These books, with their vibrant illustrations and engaging narratives, play a crucial role in developing a child's imagination and storytelling skills. They serve as an excellent bridge between traditional reading and interactive digital platforms, offering a tactile experience that digital formats sometimes lack. As parents and educators continue to value the importance of diverse reading experiences, the integration of Children Picture Book into educational curriculums is becoming more prevalent. This trend not only supports literacy development but also encourages a lifelong love for reading by combining the best of both worlds—print and digital.

Regionally, North America is expected to dominate the market, primarily due to the high adoption rate of digital learning tools in the United States and Canada. The presence of a well-established educational infrastructure, coupled with substantial investments in educational technology, has created a conducive environment for the growth of reading software. Additionally, the Asia Pacific region is anticipated to witness significant growth, driven by increasing awareness about the importance of early childhood education and rising disposable incomes. Governments in countries like China and India are also investing heavily in educational reforms, further bolstering market growth in the region.

Product Type Analysis

The reading software for children market can be segmented by product type into phonics-based software, whole language-based software, interactive storybooks, and others. Phonics-based software focuses on teaching children to read by correlating sounds with letters or groups of letters. This type of software is particularly effective in helping young learners develop decoding skills, which are essential for reading fluency. The demand for phonics-based software is expected to grow significantly as educators and parents recognize its effe

Transparency Matters: A Review of Readability in Clinical Trial Informed Consent FormsBackground: Clinical research trials rely on informed consent forms (ICFs) to explain all aspects of the study to potential participants. Despite efforts to ensure the readability of ICFs, concerns about their complexity and participant understanding persist. There is a noted gap between Institutional Review Board (IRB) standards and the actual readability levels of ICFs, which often exceed the recommended 8th-grade reading level. This study evaluates the readability of over five thousand ICFs from ClinicalTrials.gov in the United States to assess their literacy levels.Methods: We analyzed 5,239 U.S.-based ICFs from ClinicalTrials.gov using readability metrics such as the Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning Fog Index, and the percentage of difficult words. We examined trends in readability levels across studies initiated from 2005 to 2024.Results: Most ICFs exceeded the recommended 8th-grade reading level, with an average Flesch-Kincaid Grade Level of 10.99. While 91% of the ICFs were written above the 8th-grade level, there was an observable improvement in readability, with fewer studies exceeding a 10th-grade reading level in recent years.Conclusions: The study reveals a discrepancy between the recommended readability levels and actual ICFs, highlighting a need for simplification. Despite a trend toward improvement at higher grade levels, ongoing efforts are necessary to ensure ICFs are comprehensible to participants of varied educational backgrounds, reinforcing the ethical integrity of the consent process.

During a survey held in early 2021, it was found that 83 percent of adults aged between 18 and 29 years old had read a book in any format in the previous year, up by two percent from the share who said the same in 2019. The survey results showed that adults within this age category were more likely than older respondents to have read a book within the last twelve months.

Book readers in the U.S.

While it is mostly believed that book reading is a vanishing pastime, particularly among Millennials, surveys among consumers in the U.S. have shown the opposite. The share of book readers in the U.S. has varied from 72 percent to 79 percent between 2011 and 2016.

In regards to age of book readers in the country, a 2016 survey shows about 80 percent of respondents between the ages of 18 to 29 had read at least one book in the previous 12 months, the highest share amongst all age groups. About 73 percent of the respondents aged between 30 to 49 years old said they read at least one book in the last 12 months. The share among respondents between 50 and 64 years old stood at 70 percent, whereas 67 percent of respondents aged 65 plus stated reading book during the time measured. In terms of education level, book readers in the U.S. are more likely to have a college degree, or at least some college education – 86 percent and 81 percent respectively. Women in the U.S. read slightly more than men; 68 percent of male respondents started reading at least one book in the previous 12 months, against 77 percent of female respondents that said the same.

Despite the rise of digital platforms and the rising popularity of e-reading devices such as Kindle, Kobo and others, printed books still remain the most popular book format in the U.S., as 65 percent of Americans stated preference for printed books in 2016. E-books were consumed by 28 percent of respondents in 2016, whereas audio books were listened by 14 percent of the respondents. Millennials accounted for the largest share of printed book readers in the U.S. – 72 percent as of 2016.

Abstract

Though the National Bureau of Statistics generates youth and adult literacy data regularly on annual basis, the survey was conducted with a wider scope to complement the existing data on literacy in Nigeria. The main purpose of the survey was to determine the magnitude, levels and distribution of adult literacy and obtain comprehensive data and information with a view identifying issues of concern, which need to be addressed in the promotion of adult literacy in Nigeria. Underlying this is the fact that literacy is fundamental to information dissemination, socio-economic development and poverty alleviation among others. It was the first attempt to carry out a stand alone survey on Literacy Survey Nigeria.

The objectives of the 2009 National Literacy Survey were to: - Determine the magnitude, level and distribution of mass literacy (persons aged 15 year and above) - Obtain comprehensive data and information on mass literacy from literacy providers and stakeholders in both private and public sectors - Identify issues of concern which need to be addressed in the promotion of mass literacy in the country - Determine the number of persons aged 6 – 14 that are out of school - Ascertain number of persons mainstreaming from non-formal to formal education or vice versa

Geographic coverage

The survey will cover all the 36 states and Federal Capital Territory (FCT). Both urban and rural areas will be canvassed

Analysis unit

Household level

Kind of data

Sample survey data [ssd]

Sampling procedure

2.1 Sample Design 2.1.1 Introduction of NISH Design 1993/99

The Multiple Indicator Cluster Survey (MICS) 1999 was run as a module of the National Integrated Survey of Households (NISH) design. NISH is the Nigerian version of the United Nations National Household Survey Capability Programme and is a multi-subject household based survey system. It is an ongoing programme of household based surveys enquiring into various aspects of households, including housing, health, education and employment. The programme started in 1981 after a pilot study in 1980. The design utilizes a probability sample drawn using a random sampling method at the national and sub-national levels.

The main features of the NISH design are:

Multi-Phase Sampling: In each state 800 EAs were selected with equal probability as first phase samples. A second phase sample of 200 EAs was selected with probability proportional to size.

Multi-Stage Sampling Design: A two-stage design was used. Enumeration Areas were used as the first stage sampling units and Housing Units (HUs) as the second stage sampling units.

Replicated Rotatable Design: Two hundred EAs were selected in each state in 10 independent replicates of 20 EAs per replicate. A rotation was imposed which ensured 6 replicates to be studied each survey year but in subsequent year a replicate is dropped for a new one, that is, a rotation of 1/6 was applied. This means in a survey year, 120 EAs will be covered in each state. In the Federal Capital Territory (Abuja), 60 EAs are covered.

Master Sample: The EAs and HUs selected constitute the Master Sample and subsets were taken for various surveys depending on the nature of the survey and the sample size desired. In any one-year, the 120 EAs are randomly allocated to the 12 months of the year for the survey. The General Household Survey (GHS) is the core module of NISH. Thus, every month 10 EAs are covered for the GHS. For other supplemental modules of NISH, subsets of the master sample are used. The MICS 1999 was run as a module of NISH.

2.1.2 Sample Size

The global MICS design anticipated a sample of 300-500 households per district (domain). This was based on the assumption of a cluster design with design effect of about 2, an average household size of 6, children below the age of 5 years constituting 15 percent of the population and a diarrhoea prevalence of 25 percent. Such a sample would give estimates with an error margin of about 0.1 at the district level. Such a sample would usually come from about 10 clusters of 40 to 50 households per cluster.

In Nigeria, the parameters are similar to the scenario described above. Average household size varied from 3.0 to 5.6 among the states, with a national average of about 5.5. Similarly, children below 5 years constituted between 15-16 percent of total population. Diarrhoea prevalence had been estimated at about 15 percent. These figures have led to sample sizes of between 450 and 660 for each state.

It was decided that a uniform sample of 600 households per state be chosen for the survey. Although non-response, estimated at about 5 percent from previous surveys reduced the sample further, most states had 550 or more households. The MICS sample was drawn from the National Master Sample for the 1998/99 NISH programme implemented by the Federal Office of Statistics (FOS).

The sample was drawn from 30 EAs in each state with a sub-sample of 20 households selected per EA. The design was more efficient than the global MICS design which anticipated a cluster sub-sample size of 40-50 households per cluster. Usually, when the sub-sample size was reduced by half and the number of clusters doubled, a reduction of at least 20 percent in the design effect was achieved. This was derived from DEFF = 1 + (m-1) rho where m is sub-sample size and rho is intra-class correlation. Therefore, the design effect for the Nigerian MICS was about 1.6 instead of 2. This means that for the same size of 600 households, the error margin was reduced by about 10 percent, but where the sample was less than 600 the expected error margin would be achieved.

It should be noted that sampling was based on the former 30 states plus a Federal Capital Territory administrative structure [there are now 36 states and a Federal Capital Territory].

2.1.3 Selection of Households

The global design anticipated either the segmenting of clusters into small areas of approximate 40-45 households and randomly selecting one so that all households within such area was covered or using the random walk procedure in the cluster to select the 40-45 households. Neither of the two procedures was employed. For the segmentation method, it was not difficult to see that the clustering effect could be increased, since, in general, the smaller the cluster the greater the design effect. With such a system, DEFF would be higher than 2, even if minimally. The random walk method, on the other hand, could be affected by enumerator bias, which would be difficult to control and not easily measurable.

For NISH surveys, the listing of all housing units in the selected EAs was first carried out to provide a frame for the sub-sampling. Systematic random sampling was thereafter used to select the sample of housing units. The GHS used a sub-sample of 10 housing units but since the MICS required 20 households, another supplementary sample of 10 housing units was selected and added to the GHS sample. All households in the sample housing units were interviewed, as previous surveys have shown that a housing unit generally contained one household.

Sampling deviation

There were no deviation from sample design

Mode of data collection

Face-to-face [f2f]

Research instrument

The study used various instruments to collect the data. Apart from the main questionnaire that was developed for the survey and targeted the households and individuals, there were other instruments for the conduct of the assessment tests. The main questionnaire was structured in English Language but the interviewers were trained to translate and conduct the interview in local languages.

The questionnaire contains nine parts (A - I). Part A: Identification information Part B: Socio demographic background (all members) Part C: Educational attainment
Part D: Educational attainment
Part E: Literacy in english
Part F: Literacy in any other language Part G: Literacy in english Part H: Literacy in any other language Part I: Knowledge and accessibility of literacy programme

Cleaning operations

The 2009 National Literacy Survey data was processed in 4 stages namely, manual editing and coding, data entry, data cleaning and tabulation.

• Manual Processing - Completed questionnaires started arriving at the NBS headquarters two weeks after training from the states. Manual processing started with the development of editing/coding guidelines which were used to train the officers on manual editing. Development of data entry programme; data entry and editing and tabulation. Census and Surveys Processing System (CSPro) software were used for data entry, Statistical Package for Social Sciences (SPSS) and Census and Surveys Processing System (CSPro) for editing and a combination of SPSS, Statistical Analysis Software (SAS) and EXCEL for table generation.

The guidelines include errors that could be found in the completed questionnaires and how they could be corrected. These likely errors include omissions, inconsistencies, unreasonable entries, impossible entries, double entries, transcription errors and others found in the questionnaires. 10 officers were selected as editors, while 20 data entry staff were used in addition to 3 programers.

• Data Entry - The data entry was done manually, using the following steps: 1) Questionnaire reception 2) Office editing and coding 3) Data entry 4) Structure and completeness checking 5) Verification entry 6) Comparison of verification data 7) Back up of raw data 8) Secondary editing 9) Edited data back up After all clusters are processed, all data is concatenated together and then the following steps are completed for all data

In early 2021, a survey found that 59 percent of adults in the United States with high school education or less had read or listened to a book in the last year. By contrast, almost 90 percent of adults who had graduated college or pursued further education after college had engaged with a print, e-book, or audiobook in the 12 months leading to the survey.

The statistic depicts the literacy rate in Mexico from 2008 to 2020. The literacy rate measures the percentage of people ages 15 and above who can read and write. In 2020, Mexico's literacy rate was around 95.25 percent. The source does not provide data for 2019.Education in MexicoThe literacy rate is commonly defined as the share of people in a country who are older than 15 years and are able to read and write. In Mexico, a state with more than 115 million inhabitants, the literacy rate is above 90 percent, making it significantly higher than the global average. More than 70 percent of Mexico’s population is older than 15 years, a figure than has been quite consistent over the last ten years. Mexico’s compulsory education comprises grades 1 to 9, with an optional secondary education up to grade 12. Literacy is considered basic education. The lowest literacy rates can be found in African countries, the highest in Europe. Additionally, the literacy rate is one of the factors that determines a country’s ranking on the Human Development Index of the United Nations, which ranks the overall well-being of a country’s population. Apart from literacy, it also includes factors such as per-capita income, health and life expectancy and others. Mexico is currently not among the countries with the highest Human Development Index value.

These data were collected as part of the evaluation of the Healthy School Program (HSP), a program that provides support to elementary, middle, and high schools in the United States as they work to create healthy school environments that promote physical activity and healthy eating for students and staff. HSP was created in 2006 by the Alliance for a Healthier Generation with funding from the Robert Wood Johnson Foundation. The HSP evaluation addressed both process and impact outcomes: Is the HSP technical assistance and training model effective in increasing the implementation of policies and programs that promote and provide access to healthier foods and more physical activity before, during and after school? Are there distinctive or common school-level characteristics that hasten or hinder school-level implementation of policies and programs that promote and provide access to healthy foods and physical activity in the school setting in HSP schools? Does participation in HSP contribute to an increase in healthy eating behaviors and physical activity participation among students? Does participation in HSP contribute to a decrease in body mass index (BMI) among students? The evaluation used a mixed-method design incorporating both quantitative and qualitative components. The quantitative component of the evaluation was a longitudinal design that measured student changes in eating and physical activity behaviors and BMI and schools' implementation of policies and practices promoted by HSP. For the qualitative component the evaluation team conducted site visits in a sample of HSP schools. Nine data files constitute this data collection: HSP Participation and Inventory Data File, 2006-2011 (originally called the Inventory Data File) Pilot Student Survey Data File Pilot Student Height and Weight Measurements Data File Survey of Students in Boston and Miami-Dade Public Schools Data File HSP Participation and Inventory Data File, 2006-2014 Arizona, Prince George's County and Nevada Healthy Schools Youth Survey Data File Arizona and Prince George's County Youth Height and Weight Measurements Data File Arizona Academic Achievement Data File Prince George's County School Wellness Coordinator Survey Data File Dataset 1 contains data on school characteristics, HSP engagement indicators, baseline and follow-up responses to the Healthy Schools Inventory, and indices derived from the Inventory for all HSP schools as of August 2011. The Inventory collected information about each school's adherence to the Healthy Schools Program Framework, a set of best practice guidelines that promote physical activity and healthy eating among students and staff. Datasets 2, 4 and 6 contain data from baseline and follow-up administrations of the Healthy Schools Youth Survey questionnaire in three samples of HSP schools: students in grades 5-12 in the initial pilot cohort of HSP schools; students in grades 5, 8 and 10 in the 2007-2008 cohort of HSP schools in Boston, Massachusetts and Miami-Dade County, Florida; and students in grades 5, 8 and 10 or 11 in HSP schools in Arizona, Nevada and Prince George's County, Maryland. Topics covered by the Healthy Schools Youth Survey questionnaire include eating and physical activity habits, attitudes about healthy eating and physical activity, health knowledge, and school food environments. Datasets 3 and 7 contain baseline and follow-up height and weight measurements and derived BMIs, the former for students in grades 4-12 in schools sampled by the Pilot Student Survey and the latter for students in grades 5, 8, and 10 in Arizona and grades 1-12 in Prince George's County in schools sampled by the Arizona, Prince George's County and Nevada Healthy Schools Youth Survey. Dataset 5 is an update to Dataset 1. Like Dataset 1 it contains data on HSP participation and engagement and school characteristics. Dataset 5 covers 8,500 schools that participated in HSP through fall 2014. It includes 4,028 of the 4,542 schools in Dataset 1. Dataset 8 contains average math, reading and language scores for grades in HSP and comparable non-HSP schools in Arizona. Every record in the data file represents a grade (one or more of the grades 2-9) within a school (150 schools) for a given school year (up to seven years 2007-2008 to 2013-2014). Dataset 9 contains data from a survey of HSP scho