Text-to-speech and related read-aloud tools are being widely implemented in an attempt to assist students’ reading comprehension skills. Read-aloud software, including text-to-speech, is used to translate written text into spoken text, enabling one to listen to written text while reading along. It is not clear how effective text-to-speech is at improving reading comprehension. This study addresses this gap in the research by conducting a meta-analysis on the effects of text-to-speech technology and related read-aloud tools on reading comprehension for students with reading difficulties. Random effects models yielded an average weighted effect size of ( d ¯ = .35, with a 95% confidence interval of .14 to .56, p < .01). Moderator effects of study design were found to explain some of the variance. Taken together, this suggests that text-to-speech technologies may assist students with reading comprehension. However, more studies are needed to further explore the moderating variables of text-to-speech and read-aloud tools’ effectiveness for improving reading comprehension. Implications and recommendations for future research are discussed.

Background: The transmission of health information from in-person communication to web-based sources has changed over time. Patients can find, understand, and use their health information without meeting a health care provider and are able to participate more in their health care management. In recent years, the internet has emerged as the primary source of health information, although clinical providers remain the most credible source. The ease of access, anonymity, and busy schedules may be motivating factors to seek health information on the web. Social media has surfaced as a popular source of health information, as it can provide news in real time. The increase in the breadth and depth of health information available on the web has also led to a plethora of misinformation, and individuals are often unable to discern facts from fiction. Competencies in health literacy (HL) can help individuals better understand health information and enhance patient decision-making, as adequate HL is a precursor to positive health information–seeking behaviors (HISBs). Several factors such as age, sex, and socioeconomic status are known to moderate the association between HL and HISBs. Objective: In this study, we aimed to examine the relationship between HL and HISBs in individuals living in a southern state in the United States by considering different demographic factors. Methods: Participants aged ≥18 years were recruited using Qualtrics Research Services and stratified to match the statewide demographic characteristics of race and age. Demographics and source and frequency of health information were collected. The Health Literacy Questionnaire was used to collect self-reported HL experiences. SPSS (version 27; IBM Corp) was used for the analysis. Results: A total of 520 participants met the criteria and completed the survey (mean age 36.3, SD 12.79 years). The internet was cited as the most used source of health information (mean 2.41, SD 0.93). Females are more likely to seek health information from physicians than males (r=0.121; P=.006). Older individuals are less likely to seek health information from the internet (r=−0.108; P=.02), social media (r=−0.225; P<.001), and friends (r=−0.090; P=.045) than younger individuals. Cluster analysis demonstrated that individuals with higher levels of HISBs were more likely to seek information from multiple sources than those with lower levels of HISBs (mean range 3.05-4.09, SD range 0.57-0.66; P<.001). Conclusions: Age and sex are significantly associated with HISB. Older adults may benefit from web-based resources to monitor their health conditions. Higher levels of HL are significantly associated with greater HISB. Targeted strategies to improve HISB among individuals with lower levels of HL may improve their access, understanding, and use of health information.

This study rank ordered the contributive importance of several predictors of listening comprehension for third, seventh, and tenth graders. Principal components analyses revealed that a three-factor solution with fluency, reasoning, and working memory components provided the best fit across grade levels. Dominance analyses indicated that fluency and reasoning were the strongest predictors of third-grade listening comprehension. Reasoning emerged as the strongest predictor of seventh- and tenth-grade listening comprehension. These findings suggest a shift in the contributive importance of predictors to listening comprehension across development (i.e., grade levels). The implications of our findings for educators and researchers are discussed.

Comprehension monitoring is a meta-cognitive skill that is defined as the ability to self-evaluate one’s comprehension of text. Although it is known that struggling adult readers are poor at monitoring their comprehension, additional research is needed to understand the mechanisms underlying comprehension monitoring and their role in reading comprehension in this population. This study used a comprehension monitoring task with struggling adult readers, which included online eye movements (reread and regression path durations) and an offline verbal protocol (oral explanations of key information). We examined whether eye movements predicted accuracy on the passages’ reading comprehension questions, a norm-referenced reading assessment, and an offline verbal protocol after controlling for age and traditional component skills (i.e., decoding, oral language, working memory). Regression path duration uniquely predicted accuracy on the questions; however, decoding and oral vocabulary were the most salient predictors of the norm-referenced reading comprehension measure. Regression path duration also predicted the offline verbal protocol, such that those who exhibited longer regression path duration were also better at explaining key information. These results contribute to the literature regarding struggling adults’ reading component skills, eye movement behaviors involved in processing connected text, and future considerations in assessing comprehension monitoring.