Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 3 appraisals
African journal of reproductive health
Artificial intelligence-enabled digital reproductive health education: corpus-based strategies for strengthening Spanish health communication capacity
This study examines how corpus-grounded artificial intelligence (AI) can strengthen Spanish reproductive health communication capacity within China's digital health ecosystem. A mixed-methods design was employed, combining corpus linguistics, AI-assisted message generation, expert-informed evaluation, and quantitative user assessment. A domain-specific Spanish reproductive health corpus was constructed from 3,052 documents, including clinical guidelines, patient education materials, and FAQs/user queries, yielding 1,065,110 tokens for linguistic analysis and AI grounding. Corpus-derived readability benchmarks, lexical simplification rules, and discourse patterns were integrated into an AI content generation pipeline to produce reproductive health messages, which were then compared with non-corpus-grounded AI outputs. The user evaluation phase was conducted among 240 Spanish-speaking or Spanish-proficient adults in selected Chinese metropolitan cities. Data were collected through a structured questionnaire measuring Corpus-Grounded AI Generation, Spanish Communication Quality, and Health Communication Capacity, and were analyzed using reliability testing, correlation analysis, and structural equation modeling. The findings showed that corpus-grounded AI significantly improved Spanish communication quality, while communication quality had the strongest effect on users' comprehension, confidence, and help-seeking intention. Mediation analysis further demonstrated that Spanish communication quality significantly mediated the relationship between corpus-grounded AI generation and health communication capacity. The study concludes that linguistically informed AI design can enhance the clarity, accessibility, and effectiveness of reproductive health education and offers a practical framework for multilingual digital health communication in sensitive healthcare contexts. Cette étude visait à examiner le rôle de l'IA guidée par la linguistique de corpus dans l'amélioration de la qualité de la communication en espagnol sur la santé reproductive au sein de l'écosystème numérique chinois. En utilisant une approche à méthodes mixtes, la recherche a combiné l'analyse de corpus de textes espagnols sur la santé reproductive, la génération de contenu basée sur l'IA et l'évaluation par les utilisateurs. Un corpus espagnol spécifique au domaine de la santé reproductive a été construit et intégré dans un pipeline de génération d'IA ancré dans le corpus pour optimiser la lisibilité, l'exactitude et la sensibilité culturelle. La qualité de la communication et la capacité de communication en santé ont été mesurées à l'aide d'une analyse de fiabilité, de tests de corrélation et de modélisation par équations structurelles. Les résultats ont révélé que l'IA ancrée dans le corpus améliore significativement la qualité de la communication en espagnol, ce qui améliore à son tour la compréhension des utilisateurs, l'auto-efficacité et les intentions de recherche d'aide. La qualité de la communication est apparue comme un mécanisme médiateur clé entre la conception de l'IA et les résultats en matière de communication santé. Sur le plan théorique, l'étude établit une base pour intégrer la linguistique de corpus dans les systèmes d'éducation à la santé pilotés par l'IA, tandis que sur le plan pratique, elle propose un cadre évolutif pour les plateformes multilingues d'éducation à la santé reproductive. Ces résultats ont des implications importantes pour les politiques mondiales de santé numérique, la gouvernance de l'IA et les stratégies de communication en santé reproductive.
30 May 2026
Read appraisal →Studies in health technology and informatics
Accessibility of Digital Health and Welfare Services Among Immigrants in Finland
Digital health and welfare services support the delivery of the services. However, the health benefits are mixed at the population level, and further research is needed to better understand the driving factors of healthcare inequalities, particularly among vulnerable subgroups, e.g., immigrants. This qualitative study aimed to understand equality in service accessibility among immigrants, especially from the informational, experiential, and institutional perspectives. Five focus group interviews were conducted for immigrants. Data was analysed with deductive content analysis. Barriers for informational accessibility included linguistic challenges and inadequate digital literacy (DL); for experiential accessibility, usability challenges and disrespectful phone services; for institutional accessibility, challenges with electronic authentication identification for personalized digital services. Facilitators for the use of digital health and welfare services included linguistic improvements of services and support for DL. Further research, including interventions with participatory design and linguistic and digital support, is needed to improve accessibility of digital services for immigrants.
24 May 2026
Read appraisal →Global health action
Lifestyle interventions to prevent gestational and type 2 diabetes among migrant women from low- and middle-income countries: a systematic review.
Migrant women from low- and middle-income countries (LMICs) living in high-income settings experience disproportionately high risk of gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM). This review aimed to identify and synthesise culturally adapted lifestyle interventions for preventing or managing GDM and T2DM among migrant women from LMICs, focusing on intervention components, cultural adaptation strategies, and behavioural and metabolic outcomes. Five databases (PubMed, Embase, Scopus, CINAHL, Cochrane Central) were searched using Preferred Reporting Items for Systematic reviews and Meta-Analysis 2020 guidelines. Eligible studies included experimental designs involving lifestyle interventions delivered to migrant women from LMICs in high-income countries, reporting outcomes related to GDM or T2DM targeting behaviour change. Data were synthesised narratively; study quality was appraised using RoB2 for RCTs and a structured narrative approach for non-randomised designs. Certainty of evidence was evaluated using GRADE. Eight studies met the inclusion criteria. Sample sizes ranged from 28 to 641 participants. Intervention duration varied from 6 weeks to 12 months. Most interventions incorporated atleast one culturally tailored component, such as bilingual delivery, culturally adapted dietary education, or community-based engagement. Improvements were reported across dietary behaviours, physical activity, glycaemic measures, or diabetes-related knowledge; however, effect sizes were modest and inconsistent. Interventions combining dietary modification, physical activity, and culturally adapted delivery demonstrated greater improvements than exercise-only or digital-only programmes. Overall certainty of evidence ranged from low to moderate. Culturally adapted, multi-component lifestyle interventions show promise for improving behavioural and metabolic outcomes among migrant women from LMICs; however, the evidence base remains limited. Main findings: Culturally adapted, multi-component lifestyle interventions show modest but inconsistent improvements in behavioural and metabolic outcomes among migrant women from low- and middle-income countries with overall low-to-moderate certainty of evidence.Added knowledge: This review highlights cultural adaptation as a key feature of intervention effectiveness and identifies important evidence gaps, including limited high-quality studies and challenges in comparing heterogeneous interventions.Global health impact for policy and action: Policies should prioritise scalable, culturally responsive interventions – such as bilingual and community-based approaches – to reduce diabetes disparities and improve maternal health outcomes in migrant populations.
19 Apr 2026
Read appraisal →