The implementation of people-centred care requires strategies that respond to local conditions and contexts, with the participation of local stakeholders in collaborative approaches such as co-design. Within this framework, the authors performed a literature review to identify the most implemented practices in health and social care services for co-designing digital solutions. The literature review was conducted following five steps: (i) Definition of the Keywords and their relations; (ii) Definition of the selection criteria; (iii) Search in PubMed; (iv) Selection of papers; and (v) Analysis of the selected papers. 20 papers addressed to co-design health digital solutions with stakeholders were analysed in terms of the activities implemented and participants involved. Previous studies using co-design methods for the deployment of health digital solutions employed a wide range of activities, most of them combining activities and/or mixed target groups. Co-design is the key to deliver people-centred care as it allows to involve stakeholders in the development of health digital solutions. Implementing one or more of the co-design methods identified in this literature review should be considered to better address the needs and specific projects and target groups.

Introduction: Engagement and co-production in healthcare research and innovation are crucial for delivering person-centred interventions in underserved communities, but the knowledge of effective strategies to target this population is still vague, limiting the provision of person-centred care. Our research aimed to identify essential knowledge to foster engagement and co-production. Materials and Methods: A meta-synthesis research design was used to compile existing qualitative research papers on health communication, engagement, and empowerment in vulnerable groups in high-income countries (HICs) from 2008 to 2018. A total of 23 papers were selected and analysed. Results: ‘Design and recruitment’ and ‘engagement and co-production’ thematic areas are presented considering the factors related to researcher–communities attunement and the strategical plans for conducting research. The insights are discussed in light of the literature. Long-term alliances, sustainable structures, and strengthened bonds are critical factors for producing real long-term change, empowering persons and communities, and paving the way to person-centred care. Conclusions: The enhancement of the recruitment, involvement, and empowerment of traditionally disengaged communities and individuals depends on the awareness and analysis of social determinants, power differentials and specific tactics, and the capacity of researchers and individuals to apply all these principles in real-world practice.

Context: Despite growing interest in using AI to improve public policies and services, its application in evaluation lacks systematised evidence and scientific publications on the implications of these technologies in evaluation practice. Objective: To map, through available literature, the current and emerging state of AI application in public policy evaluation. Methods: We conducted the study through an exploratory literature review, or scoping review, following the methodological framework of Levac et al. (2010). The synthesis was carried out with a thematic analysis of 27 studies and analytical-theoretical literature. Results: AI is increasingly being applied in various phases of the evaluation cycle, primarily as a support tool (“human-in-the-loop”), especially in the operationalisation, report preparation and results dissemination phases. Use cases include the analysis of large volumes of administrative and textual data through Machine Learning (ML) and Natural Language Processing (NLP), the performance of simulations and counterfactual analyses, the potential for real-time monitoring, and the use of Large Language Models (LLMs) for synthesis or visualisation tasks, among others. Conclusions and implications: Current evidence points toward the predominance of human-machine collaboration models (human-in-the-loop), indicating that realising the benefits of AI in this field does not involve total automation, but rather strategic, critically reflective and contextually adapted implementation.

Dear Dr. Garwe: Your article analyzes a very interesting - and nowadays, necessary - topic while integrating your findings within a relevant and evidence-based framework: distributed cognition theory. Please, find below my suggestions for improving...