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BACKGROUND: This paper considers remote working in patient public involvement and engagement (PPIE) in health and social care research. With the advent of the Covid-19 pandemic and associated lock-down measures in the UK (from March 2020), PPIE activities switched to using remote methods (e.g., online meetings), to undertake involvement. Our study sought to understand the barriers to and facilitators for remote working in PPIE by exploring public contributors' and PPIE professionals' (people employed by organisations to facilitate and organise PPIE), experiences of working remotely, using online and digital technologies. A particular focus of our project was to consider how the 'digital divide' might negatively impact on diversity and inclusion in PPIE in health and social care research. METHODS: We used a mixed method approach: online surveys with public contributors involved in health and social care research, online surveys with public involvement professionals, and qualitative interviews with public contributors. We co-produced the study with public contributors from its inception, design, subsequent data analysis and writing outputs, to embed public involvement throughout the study. RESULTS: We had 244 respondents to the public contributor survey and 65 for the public involvement professionals (PIPs) survey and conducted 22 qualitative interviews. Our results suggest public contributors adapted well to working remotely and they were very positive about the experience. For many, their PPIE activities increased in amount and variety, and they had learnt new skills. There were both benefits and drawbacks to working remotely. Due to ongoing Covid restrictions during the research project, we were unable to include people who did not have access to digital tools and our findings have to be interpreted in this light. CONCLUSION: Participants generally favoured a mixture of face-to-face and remote working. We suggest the following good practice recommendations for remote working in PPIE: the importance of a good moderator and/or chair to ensure everyone can participate fully; account for individual needs of public contributors when planning meetings; provide a small expenses payment alongside public contributor fees to cover phone/electricity or WiFi charges; and continue the individual support that was often offered to public contributors during the pandemic.
This paper looks at remote working in patient public involvement and engagement (PPIE) in health and social care research. When the Covid-19 pandemic began and the UK went into lock-down in March 2020, PPIE activities began to use remote working methods, such as Zoom or Teams online meetings. We co-developed a study to understand the experiences of both public contributors and PPIE professionals, those who are employed to organise PPIE, of working remotely. We were particularly interested in how remote working might affect diversity and inclusion in PPIE in health and social care research. We ran online surveys for public contributors and public involvement professionals and conducted semi-structured interviews with public contributors. We co-produced the study with public contributors to embed public involvement throughout the study. We had 244 respondents to the public contributor survey, 65 for the public involvement professionals survey and conducted 22 qualitative interviews. Due to ongoing Covid restrictions during the research project we could not include people who did not have access to digital tools, and this is a limitation of our project. We found that public contributors generally liked working remotely and, for many, their PPIE activities increased. There were both benefits and drawbacks to working remotely. From our findings, we have made a number of suggestions for how to run remote meetings in PPIE and what to prioritise based on the areas public contributors thought were important (such as one-to-one support).
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OBJECTIVE: Artificial intelligence (AI) will have a significant impact on healthcare over the coming decade. At the same time, health inequity remains one of the biggest challenges. Primary care is both a driver and a mitigator of health inequities and with AI gaining traction in primary care, there is a need for a holistic understanding of how AI affect health inequities, through the act of providing care and through potential system effects. This paper presents a systematic scoping review of the ways AI implementation in primary care may impact health inequity. DESIGN: Following a systematic scoping review approach, we searched for literature related to AI, health inequity, and implementation challenges of AI in primary care. In addition, articles from primary exploratory searches were added, and through reference screening.The results were thematically summarised and used to produce both a narrative and conceptual model for the mechanisms by which social determinants of health and AI in primary care could interact to either improve or worsen health inequities.Two public advisors were involved in the review process. ELIGIBILITY CRITERIA: Peer-reviewed publications and grey literature in English and Scandinavian languages. INFORMATION SOURCES: PubMed, SCOPUS and JSTOR. RESULTS: A total of 1529 publications were identified, of which 86 met the inclusion criteria. The findings were summarised under six different domains, covering both positive and negative effects: (1) access, (2) trust, (3) dehumanisation, (4) agency for self-care, (5) algorithmic bias and (6) external effects. The five first domains cover aspects of the interface between the patient and the primary care system, while the last domain covers care system-wide and societal effects of AI in primary care. A graphical model has been produced to illustrate this. Community involvement throughout the whole process of designing and implementing of AI in primary care was a common suggestion to mitigate the potential negative effects of AI. CONCLUSION: AI has the potential to affect health inequities through a multitude of ways, both directly in the patient consultation and through transformative system effects. This review summarises these effects from a system tive and provides a base for future research into responsible implementation.
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Artificial Intelligence , Health Inequities , Humans , Gray Literature , PubMed , Primary Health CareABSTRACT
INTRODUCTION: Big data research has grown considerably over the last two decades. This presents new ethical challenges around consent, data storage and anonymisation. Big data research projects require public support to succeed and it has been argued that one way to achieve this is through public involvement and engagement. To better understand the role public involvement and engagement can play in big data research, we will review the current literature. This protocol describes the planned review methods. METHODS AND ANALYSIS: Our review will be conducted in two stages. In the first stage, we will conduct a scoping review using Arksey and O'Malley methodology to comprehensively map current evidence on public involvement and engagement in big data research. Databases (CINAHL, Health Research Premium Collection, PubMed, Scopus, Web of Science) and grey literature will be searched for eligible papers. We provide a narrative description of the results based on a thematic analysis. In the second stage, out of papers found in the scoping review which discuss involvement and engagement strategies, we will conduct a systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, exploring the delivery and effectiveness of these strategies. We will conduct a qualitative synthesis. Relevant results from the quantitative studies will be extracted and placed under qualitative themes. Individual studies will be appraised through Mixed Methods Appraisal Tool (MMAT), we will then assess the overall confidence in each finding through Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual). Results will be reported in a thematic and narrative way. ETHICS AND DISSEMINATION: This protocol sets out how the review will be conducted to ensure rigour and transparency. Public advisors were involved in its development. Ethics approval is not required. Review findings will be presented at conferences and published in peer-reviewed journals.
