European national disparities in the integration of data linkage (ie, being able to match patient data between databases) into routine public health activities were recently highlighted. In France, the claims database covers almost the whole population from birth to death, offering a great research potential for data linkage. As the use of a common unique identifier to directly link personal data is often limited, linkage with a set of indirect key identifiers has been developed, which is associated with the linkage quality challenge to minimize errors in linked data.
The aim of this systematic review is to analyze the type and quality of research publications on indirect data linkage on health product use and care trajectories in France.
A comprehensive search for all papers published in PubMed/Medline and Embase databases up to December 31, 2022, involving linked French database focusing on health products use or care trajectories was realized. Only studies based on the use of indirect identifiers were included (ie, without a unique personal identifier available to easily link the databases). A descriptive analysis of data linkage with quality indicators and adherence to the Bohensky framework for evaluating data linkage studies was also realized.
In total, 16 papers were selected. Data linkage was performed at the national level in 7 (43.8%) cases or at the local level in 9 (56.2%) studies. The number of patients included in the different databases and resulting from data linkage varied greatly, respectively, from 713 to 75,000 patients and from 210 to 31,000 linked patients. The diseases studied were mainly chronic diseases and infections. The objectives of the data linkage were multiple: to estimate the risk of adverse drug reactions (ADRs; n=6, 37.5%), to reconstruct the patient\'s care trajectory (n=5, 31.3%), to describe therapeutic uses (n=2, 12.5%), to evaluate the benefits of treatments (n=2, 12.5%), and to evaluate treatment adherence (n=1, 6.3%). Registries are the most frequently linked databases with French claims data. No studies have looked at linking with a hospital data warehouse, a clinical trial database, or patient self-reported databases. The linkage approach was deterministic in 7 (43.8%) studies, probabilistic in 4 (25.0%) studies, and not specified in 5 (31.3%) studies. The linkage rate was mainly from 80% to 90% (reported in 11/15, 73.3%, studies). Adherence to the Bohensky framework for evaluating data linkage studies showed that the description of the source databases for the linkage was always performed but that the completion rate and accuracy of the variables to be linked were not systematically described.
This review highlights the growing interest in health data linkage in France. Nevertheless, regulatory, technical, and human constraints remain major obstacles to their deployment. The volume, variety, and validity of the data represent a real challenge, and advanced expertise and skills in statistical analysis and artificial intelligence are required to treat these big data.

BACKGROUND: Artificial intelligence (AI) has emerged as a major driver of technological development in the 21st century, yet little attention has been paid to algorithmic biases toward older adults.
OBJECTIVE: This paper documents the search strategy and process for a scoping review exploring how age-related bias is encoded or amplified in AI systems as well as the corresponding legal and ethical implications.
METHODS: The scoping review follows a 6-stage methodology framework developed by Arksey and O\'Malley. The search strategy has been established in 6 databases. We will investigate the legal implications of ageism in AI by searching grey literature databases, targeted websites, and popular search engines and using an iterative search strategy. Studies meet the inclusion criteria if they are in English, peer-reviewed, available electronically in full text, and meet one of the following two additional criteria: (1) include \"bias\" related to AI in any application (eg, facial recognition) and (2) discuss bias related to the concept of old age or ageism. At least two reviewers will independently conduct the title, abstract, and full-text screening. Search results will be reported using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) reporting guideline. We will chart data on a structured form and conduct a thematic analysis to highlight the societal, legal, and ethical implications reported in the literature.
RESULTS: The database searches resulted in 7595 records when the searches were piloted in November 2021. The scoping review will be completed by December 2022.
CONCLUSIONS: The findings will provide interdisciplinary insights into the extent of age-related bias in AI systems. The results will contribute foundational knowledge that can encourage multisectoral cooperation to ensure that AI is developed and deployed in a manner consistent with ethical values and human rights legislation as it relates to an older and aging population. We will publish the review findings in peer-reviewed journals and disseminate the key results with stakeholders via workshops and webinars.
BACKGROUND: OSF Registries AMG5P; https://osf.io/amg5p.
UNASSIGNED: DERR1-10.2196/33211.

This scoping review explores and summarizes the existing literature on the use of chatbots to support and promote health in Africa.
The primary aim was to learn where, and under what circumstances, chatbots have been used effectively for health in Africa; how chatbots have been developed to the best effect; and how they have been evaluated by looking at literature published between 2017 and 2022. A secondary aim was to identify potential lessons and best practices for others chatbots. The review also aimed to highlight directions for future research on the use of chatbots for health in Africa.
Using the 2005 Arksey and O\'Malley framework, we used a Boolean search to broadly search literature published between January 2017 and July 2022. Literature between June 2021 and July 2022 was identified using Google Scholar, EBSCO information services-which includes the African HealthLine, PubMed, MEDLINE, PsycInfo, Cochrane, Embase, Scopus, and Web of Science databases-and other internet sources (including gray literature). The inclusion criteria were literature about health chatbots in Africa published in journals, conference papers, opinion, or white papers.
In all, 212 records were screened, and 12 articles met the inclusion criteria. Results were analyzed according to the themes they covered. The themes identified included the purpose of the chatbot as either providing an educational or information-sharing service or providing a counselling service. Accessibility as a result of either technical restrictions or language restrictions was also noted. Other themes that were identified included the need for the consideration of trust, privacy and ethics, and evaluation.
The findings demonstrate that current data are insufficient to show whether chatbots are effectively supporting health in the region. However, the review does reveal insights into popular chatbots and the need to make them accessible through language considerations, platform choice, and user trust, as well as the importance of robust evaluation frameworks to assess their impact. The review also provides recommendations on the direction of future research.

BACKGROUND: The use of mobile health (mHealth) apps is increasing rapidly worldwide. More and more institutions and organizations develop regulations and guidelines to enable an evidence-based and safe use. In Germany, mHealth apps fulfilling predefined criteria (Digitale Gesundheitsanwendungen [DiGA]) can be prescribed and are reimbursable by the German statutory health insurance scheme. Due to the increasing distribution of DiGA, problems and barriers should receive special attention.
OBJECTIVE: This study aims to identify the relevant problems and barriers related to the use of mHealth apps fulfilling the criteria of DiGA.
METHODS: This scoping review will follow published methodological frameworks and the PRISMA-Scr (Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews) criteria. Electronic databases (MEDLINE, EMBASE, PsycINFO, and JMIR), reference lists of relevant articles, and grey literature sources will be searched. Two reviewers will assess the eligibility of the articles by a two-stage (title and abstract as well as full text) screening process. Only problems and barriers related to mHealth apps fulfilling the criteria of DiGA are included for this research. The identified studies will be categorized and analyzed with MAXQDA.
RESULTS: This scoping review gives an overview of the available evidence and identifies research gaps regarding problems and barriers related to DiGA. The results are planned to be submitted to an indexed, peer-reviewed journal in the first quarter of 2022.
CONCLUSIONS: This is the first review to identify the problems and barriers related to the use of mHealth apps fulfilling the German definition of DiGA. Nevertheless, the findings can be applied to other contexts and health care systems as well.
UNASSIGNED: DERR1-10.2196/32702.

BACKGROUND: Understanding consumers\' health information needs across all stages of the pregnancy trajectory is crucial to the development of mechanisms that allow them to retrieve high-quality, customized, and layperson-friendly health information.
OBJECTIVE: The objective of this study was to identify research gaps in pregnancy-related consumer information needs and available information from different sources.
METHODS: We conducted a systematic review of CINAHL, Cochrane, PubMed, and Web of Science for relevant articles that were published from 2009 to 2019. The quality of the included articles was assessed using the Critical Appraisal Skills Program. A descriptive data analysis was performed on these articles. Based on the review result, we developed the Pregnancy Information Needs Ontology (PINO) and made it publicly available in GitHub and BioPortal.
RESULTS: A total of 33 articles from 9 countries met the inclusion criteria for this review, of which the majority were published no earlier than 2016. Most studies were either descriptive (9/33, 27%), interviews (7/33, 21%), or surveys/questionnaires (7/33, 21%); 20 articles mentioned consumers\' pregnancy-related information needs. Half (9/18, 50%) of the human-subject studies were conducted in the United States. More than a third (13/33, 39%) of all studies focused on during-pregnancy stage; only one study (1/33, 3%) was about all stages of pregnancy. The most frequent consumer information needs were related to labor delivery (9/20, 45%), medication in pregnancy (6/20, 30%), newborn care (5/20, 25%), and lab tests (6/20, 30%). The most frequently available source of information was the internet (15/24, 63%). PINO consists of 267 classes, 555 axioms, and 271 subclass relationships.
CONCLUSIONS: Only a few articles assessed the barriers to access to pregnancy-related information and the quality of each source of information; further work is needed. Future work is also needed to address the gaps between the information needed and the information available.