UNASSIGNED: Childhood mental health issues concern a large amount of children worldwide and represent a major public health challenge. The lack of knowledge among parents and caregivers in this area hinders effective management. Empowering families enhances their ability to address their children\'s difficulties, boosts health literacy, and promotes positive changes. However, seeking reliable mental health information remains challenging due to fear, stigma, and mistrust of the sources of information.
UNASSIGNED: This study evaluates the acceptance of a website, CléPsy, designed to provide reliable information and practical tools for families concerned about child mental health and parenting.
UNASSIGNED: This study examines user characteristics and assesses ease of use, usefulness, trustworthiness, and attitude toward using the website. Platform users were given access to a self-administered questionnaire by means of mailing lists, social networks, and posters between May and July 2022.
UNASSIGNED: Findings indicate that the wide majority of the 317 responders agreed or somewhat agreed that the website made discussions about mental health easier with professionals (n=264, 83.3%) or with their relatives (n=260, 82.1%). According to the ANOVA, there was a significant effect between educational level and perceived trust (F6=3.03; P=.007) and between frequency of use and perceived usefulness (F2=4.85; P=.008).
UNASSIGNED: The study underlines the importance of user experience and design in web-based health information dissemination and emphasizes the need for accessible and evidence-based information. Although the study has limitations, it provides preliminary support for the acceptability and usefulness of the website. Future efforts should focus on inclusive co-construction with users and addressing the information needs of families from diverse cultural and educational backgrounds.

BACKGROUND: In an increasingly digital age, students rely heavily on web resources to access health information. However, evaluating the reliability and relevance of such information is crucial for informed decision-making. This study examines the importance of students\' health information literacy skills (HILS) as mediators, particularly their ability to utilize web resources and successfully evaluate health information.
OBJECTIVE: This research investigates the mediating role of students\' HILS in the relationship between their utilization of web resources and their proficiency in evaluating health information.
METHODS: An online survey was distributed to current students at a public university in Bangladesh as part of the data collection process for this study. Using Google Forms, the authors created a structured questionnaire. The survey was distributed through Messenger groups, Facebook pages and email invitations to reach the target audience effectively. The researchers thoroughly analysed the gathered data using structural equation modelling (SEM) techniques and SmartPLS-4 software to look for correlations between the variables.
RESULTS: The study revealed that among the 122 participants, a significant number (N = 47) accessed internet health information on an occasional basis, whereas 30 individuals reported using it infrequently. The data revealed that 58 individuals, accounting for 47.5% of the sample, possessed the necessary abilities to access and assess online health information. Additionally, 57 participants, representing 46.7% of the sample, demonstrated proficiency in conducting online health information searches. The measurement model demonstrated good convergent validity, as evidenced by composite reliability (CR) scores and Cronbach\'s ⍺ values over 0.700 and an average extracted variance (AVE) of 0.500. The structural model demonstrated R2 values exceeding 0.1, thus validating its dependable forecasting capability. Notable effects were seen, with f2 values of 0.335 and 0.317 for the challenges in accessing and evaluating health information (CAEHI) to health information evaluation (HIE) and CAEHI to HILS relationships, respectively. The mediation analysis found that HILS act as a mediator between types of web resources (TWRs) and HIE, with TWR having an indirect impact on HIE through HILS.
CONCLUSIONS: The result supports all hypotheses. Therefore, it is evident that students\' HILS mediate the relationship between utilization of web resources and their proficiency in evaluating health information.
CONCLUSIONS: This study\'s findings could significantly impact instructional practices meant to raise students\' health information literacy. This initiative seeks to enable students to make informed decisions about their health by providing them with the necessary tools to analyse and evaluate health-related information.
UNASSIGNED: Research on health information literacy can assist patients and the general public by instructing them on how to assess trustworthy online health resources. Students gave insightful feedback that assisted in shaping the study and guaranteeing its relevancy. If they better comprehend health information literacy, patients and the general public can use web-based resources and critically evaluate health information more accurately.

BACKGROUND: As a newly emerged concept and a product of the twenty-first century, health information governance is expanding at a rapid rate. The necessity of information governance in the healthcare industry is evident, given the significance of health information and the current need to manage it. The objective of the present scoping review is to identify the dimensions and components of health information governance to discover how these factors impact the enhancement of healthcare systems and services.
METHODS: PubMed, Scopus, Web of Science, ProQuest and the Google Scholar search engine were searched from inception to June 2024. Methodological study quality was assessed using CASP checklists for selected documents. Endnote 20 was utilized to select and review articles and manage references, and MAXQDA 2020 was used for content analysis.
RESULTS: A total of 37 documents, including 18 review, 9 qualitative and 10 mixed-method studies, were identified by literature search. Based on the findings, six core categories (including health information governance goals, advantages and applications, principles, components or elements, roles and responsibilities and processes) and 48 subcategories were identified to form a unified general framework comprising all extracted dimensions and components.
CONCLUSIONS: Based on the findings of this scoping review, health information governance should be regarded as a necessity in the health systems of various countries to improve and achieve their goals, particularly in developing and underdeveloped countries. Moreover, in light of the undesirable effects of the coronavirus disease 2019 (COVID-19) pandemic in various countries, the development and implementation of health information governance models at organizational, national and international levels are among the pressing concerns. Researchers can use the present findings as a comprehensive model for developing health information governance models. A possible limitation of this study is our limited access to some databases.

BACKGROUND: Foreign body (FB) inhalation, ingestion, and insertion account for 11% of emergency admissions for ear, nose, and throat conditions. Children are disproportionately affected, and urgent intervention may be needed to maintain airway patency and prevent blood vessel occlusion. High-quality, readable online information could help reduce poor outcomes from FBs.
OBJECTIVE: We aim to evaluate the quality and readability of available online health information relating to FBs.
METHODS: In total, 6 search phrases were queried using the Google search engine. For each search term, the first 30 results were captured. Websites in the English language and displaying health information were included. The provider and country of origin were recorded. The modified 36-item Ensuring Quality Information for Patients tool was used to assess information quality. Readability was assessed using a combination of tools: Flesch Reading Ease score, Flesch-Kincaid Grade Level, Gunning-Fog Index, and Simple Measure of Gobbledygook.
RESULTS: After the removal of duplicates, 73 websites were assessed, with the majority originating from the United States (n=46, 63%). Overall, the quality of the content was of moderate quality, with a median Ensuring Quality Information for Patients score of 21 (IQR 18-25, maximum 29) out of a maximum possible score of 36. Precautionary measures were not mentioned on 41% (n=30) of websites and 30% (n=22) did not identify disk batteries as a risky FB. Red flags necessitating urgent care were identified on 95% (n=69) of websites, with 89% (n=65) advising patients to seek medical attention and 38% (n=28) advising on safe FB removal. Readability scores (Flesch Reading Ease score=12.4, Flesch-Kincaid Grade Level=6.2, Gunning-Fog Index=6.5, and Simple Measure of Gobbledygook=5.9 years) showed most websites (56%) were below the recommended sixth-grade level.
CONCLUSIONS: The current quality and readability of information regarding FBs is inadequate. More than half of the websites were above the recommended sixth-grade reading level, and important information regarding high-risk FBs such as disk batteries and magnets was frequently excluded. Strategies should be developed to improve access to high-quality information that informs patients and parents about risks and when to seek medical help. Strategies to promote high-quality websites in search results also have the potential to improve outcomes.

OBJECTIVE: Alcohol use disorder (AUD) is characterized by low levels of engagement with effective treatments. Enhancing awareness of AUD treatments and how to navigate the treatment system is crucial. Many individuals use online sources (e.g. search engines) for answers to health-related questions; web-based results include a mix of high- and low-quality information. Artificial intelligence may improve access to quality health information by providing concise, high-quality responses to complex health-related questions. This study evaluated the quality of ChatGPT-4 responses to AUD-related queries.
METHODS: A comprehensive list of 64 AUD-related questions was developed through a combination of Google Trends analysis and expert consultation. ChatGPT-4 was prompted with each question, followed by a request to provide 3-5 peer-reviewed scientific citations supporting each response. Responses were evaluated for whether they were evidence-based, provided a referral and provided supporting documentation.
RESULTS: ChatGPT-4 responded to all AUD-related queries, with 92.2% (59/64) of responses being fully evidence-based. Although only 12.5% (8/64) of responses included referrals to external resources, all responses (100%; 5/5) to location-specific (\'near me\') queries directed individuals to appropriate resources like the NIAAA Treatment Navigator. Most (85.9%; 55/64) responses to the follow-up question provided supporting documentation.
CONCLUSIONS: ChatGPT-4 responds to alcohol use disorder-related questions with evidence-based information and supporting documentation. ChatGPT-4 could be promoted as a reasonable resource for those looking online for alcohol use disorder-related information.

BACKGROUND: OpenAI\'s ChatGPT is a source of advanced online health information (OHI) that may be integrated into individuals\' health information-seeking routines. However, concerns have been raised about its factual accuracy and impact on health outcomes. To forecast implications for medical practice and public health, more information is needed on who uses the tool, how often, and for what.
OBJECTIVE: This study aims to characterize the reasons for and types of ChatGPT OHI use and describe the users most likely to engage with the platform.
METHODS: In this cross-sectional survey, patients received invitations to participate via the ResearchMatch platform, a nonprofit affiliate of the National Institutes of Health. A web-based survey measured demographic characteristics, use of ChatGPT and other sources of OHI, experience characterization, and resultant health behaviors. Descriptive statistics were used to summarize the data. Both 2-tailed t tests and Pearson chi-square tests were used to compare users of ChatGPT OHI to nonusers.
RESULTS: Of 2406 respondents, 21.5% (n=517) respondents reported using ChatGPT for OHI. ChatGPT users were younger than nonusers (32.8 vs 39.1 years, P<.001) with lower advanced degree attainment (BA or higher; 49.9% vs 67%, P<.001) and greater use of transient health care (ED and urgent care; P<.001). ChatGPT users were more avid consumers of general non-ChatGPT OHI (percentage of weekly or greater OHI seeking frequency in past 6 months, 28.2% vs 22.8%, P<.001). Around 39.3% (n=206) respondents endorsed using the platform for OHI 2-3 times weekly or more, and most sought the tool to determine if a consultation was required (47.4%, n=245) or to explore alternative treatment (46.2%, n=239). Use characterization was favorable as many believed ChatGPT to be just as or more useful than other OHIs (87.7%, n=429) and their doctor (81%, n=407). About one-third of respondents requested a referral (35.6%, n=184) or changed medications (31%, n=160) based on the information received from ChatGPT. As many users reported skepticism regarding the ChatGPT output (67.9%, n=336), most turned to their physicians (67.5%, n=349).
CONCLUSIONS: This study underscores the significant role of AI-generated OHI in shaping health-seeking behaviors and the potential evolution of patient-provider interactions. Given the proclivity of these users to enact health behavior changes based on AI-generated content, there is an opportunity for physicians to guide ChatGPT OHI users on an informed and examined use of the technology.

BACKGROUND: Although uncertainties exist regarding implementation, artificial intelligence-driven generative language models (GLMs) have enormous potential in medicine. Deployment of GLMs could improve patient comprehension of clinical texts and improve low health literacy.
OBJECTIVE: The goal of this study is to evaluate the potential of ChatGPT-3.5 and GPT-4 to tailor the complexity of medical information to patient-specific input education level, which is crucial if it is to serve as a tool in addressing low health literacy.
METHODS: Input templates related to 2 prevalent chronic diseases-type II diabetes and hypertension-were designed. Each clinical vignette was adjusted for hypothetical patient education levels to evaluate output personalization. To assess the success of a GLM (GPT-3.5 and GPT-4) in tailoring output writing, the readability of pre- and posttransformation outputs were quantified using the Flesch reading ease score (FKRE) and the Flesch-Kincaid grade level (FKGL).
RESULTS: Responses (n=80) were generated using GPT-3.5 and GPT-4 across 2 clinical vignettes. For GPT-3.5, FKRE means were 57.75 (SD 4.75), 51.28 (SD 5.14), 32.28 (SD 4.52), and 28.31 (SD 5.22) for 6th grade, 8th grade, high school, and bachelor\'s, respectively; FKGL mean scores were 9.08 (SD 0.90), 10.27 (SD 1.06), 13.4 (SD 0.80), and 13.74 (SD 1.18). GPT-3.5 only aligned with the prespecified education levels at the bachelor\'s degree. Conversely, GPT-4\'s FKRE mean scores were 74.54 (SD 2.6), 71.25 (SD 4.96), 47.61 (SD 6.13), and 13.71 (SD 5.77), with FKGL mean scores of 6.3 (SD 0.73), 6.7 (SD 1.11), 11.09 (SD 1.26), and 17.03 (SD 1.11) for the same respective education levels. GPT-4 met the target readability for all groups except the 6th-grade FKRE average. Both GLMs produced outputs with statistically significant differences (P<.001; 8th grade P<.001; high school P<.001; bachelors P=.003; FKGL: 6th grade P=.001; 8th grade P<.001; high school P<.001; bachelors P<.001) between mean FKRE and FKGL across input education levels.
CONCLUSIONS: GLMs can change the structure and readability of medical text outputs according to input-specified education. However, GLMs categorize input education designation into 3 broad tiers of output readability: easy (6th and 8th grade), medium (high school), and difficult (bachelor\'s degree). This is the first result to suggest that there are broader boundaries in the success of GLMs in output text simplification. Future research must establish how GLMs can reliably personalize medical texts to prespecified education levels to enable a broader impact on health care literacy.

UNASSIGNED: The Global Specialist Digital Health Workforce Census is the largest workforce survey of the specialist roles that support the development, use, management, and governance of health data, health information, health knowledge, and health technology.
UNASSIGNED: This paper aims to present an analysis of the roles and functions reported by respondents in the 2023 census.
UNASSIGNED: The 2023 census was deployed using Qualtrics and was open from July 1 to August 13, 2023. A broad definition was provided to guide respondents about who is in the specialist digital health workforce. Anyone who self-identifies as being part of this workforce could undertake the survey. The data was analyzed using descriptive statistical analysis and thematic analysis of the functions respondents reported in their roles.
UNASSIGNED: A total of 1103 respondents completed the census, with data reported about their demographic information and their roles. The majority of respondents lived in Australia (n=870, 78.9%) or New Zealand (n=130, 11.8%), with most (n=620, 56.3%) aged 35-54 years and identifying as female (n=720, 65.3%). The top four occupational specialties were health informatics (n=179, 20.2%), health information management (n=175, 19.8%), health information technology (n=128, 14.4%), and health librarianship (n=104, 11.7%). Nearly all (n=797, 90%) participants identified as a manager or professional. Less than half (430/1019, 42.2%) had a formal qualification in a specialist digital health area, and only one-quarter (244/938, 26%) held a credential in a digital health area. While two-thirds (502/763, 65.7%) reported undertaking professional development in the last year, most were self-directed activities, such as seeking information or consuming online content. Work undertaken by specialist digital health workers could be classified as either leadership, functional, occupational, or technological.
UNASSIGNED: Future specialist digital health workforce capability frameworks should include the aspects of leadership, function, occupation, and technology. This largely unqualified workforce is undertaking little formal professional development to upskill them to continue to support the safe delivery and management of health and care through the use of digital data and technology.

Telecommunications offers an alternative or supplement to community-based interventions as a means of extending healthcare services and improving health outcomes in remote settings but can fail to reach target communities and achieve the desired impact if barriers to access are not overcome. We conducted seven focus group discussions and 26 interviews with community health workers, community leaders, and female members of the public who declared that they had or had not previously accessed free audio health messages provided via a mobile platform in two rural communities of Mali, Koulikoro and Bougouni. A content analysis showed that participants accessed and trusted health information from a range of sources, including radio, telephone and television, as well as town criers, local relays and community health centres. Barriers to access faced by women included economic factors, lack of network or electricity, and social factors such as illiteracy, cultural restrictions and being unaware of mobile communication. Through analysis and interpretation of the participants\' responses, we have made recommendations for future campaigns for the dissemination of health-related information for women in remote settings.

BACKGROUND: The rise in popularity of chatbots, particularly ChatGPT by OpenAI among the general public and its utility in the healthcare field is a topic of present controversy. The current study aimed at assessing the reliability and accuracy of ChatGPT\'s responses to inquiries posed by parents, specifically focusing on a range of pediatric ophthalmological and strabismus conditions.
METHODS: Patient queries were collected via a thematic analysis and posed to ChatGPT 3.5 version across 3 unique instances each. The questions were divided into 12 domains totalling 817 unique questions. All responses were scored on the response quality by two experienced pediatric ophthalmologists in a Likert-scale format. All questions were evaluated for readability using the Flesch-Kincaid Grade Level (FKGL) and character counts.
RESULTS: A total of 638 (78.09%) questions were scored to be perfectly correct, 156 (19.09%) were scored correct but incomplete and only 23 (2.81%) were scored to be partially incorrect. None of the responses were scored to be completely incorrect. Average FKGL score was 14.49 [95% CI 14.4004-14.5854] and the average character count was 1825.33 [95%CI 1791.95-1858.7] with p = 0.831 and 0.697 respectively. The minimum and maximum FKGL scores were 10.6 and 18.34 respectively. FKGL predicted character count, R²=.012, F(1,815) = 10.26, p = .001.
CONCLUSIONS: ChatGPT provided accurate and reliable information for a majority of the questions. The readability of the questions was much above the typically required standards for adults, which is concerning. Despite these limitations, it is evident that this technology will play a significant role in the healthcare industry.