Empathic healthcare improves patient satisfaction with care, anxiety and pain, while reducing practitioner burnout. Artificial intelligence (AI) is continuously advancing and changing the context of empathy in healthcare. While AI may improve diagnostic accuracy or help streamline processes to reduce workload, there is a concern about how AI will impact human patient–practitioner relationships. However, patient and practitioner experiences of AI in healthcare are underexplored. We therefore aimed to synthesise the findings of qualitative studies which explore patient and practitioner experiences of empathy in AI-supported encounters in healthcare.

We will include any qualitative study in which patient or practitioner experiences of empathy with AI-assisted healthcare are explored. Secondary studies, quantitative studies and those exploring other stakeholders’ experiences will be excluded. The search will include records from database inception in any language. The search strategy is based on the Population, Phenomenon of Interest, Context framework, built around the keywords: artificial intelligence, empathy, healthcare professionals and patients. The following databases will be searched: MEDLINE, Scopus, APA PsycINFO and CINAHL. Additionally, grey literature searches in BASE and OpenAIRE. Forward and backward citation chasing will also be conducted. Records will be screened by two independent reviewers, data extraction will be conducted by one reviewer and checked by another. The risk of bias assessment will be conducted in duplicate using the Joanna Briggs Institute appraisal tool for qualitative studies. The results will be synthesised using thematic synthesis. The number of records identified from the search and the exclusions to reach the total number of included records will be presented in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. The included studies will be listed, along with summaries of relevant study characteristics and risk of bias assessments. Confidence in the evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation - Confidence in the Evidence from Reviews of Qualitative research framework.

The systematic review will include only previously anonymised data from primary studies. For this reason, ethical approval is not required for this study. Dissemination of the findings of the final systematic review will occur through publishing in a peer-reviewed journal.

CRD420261301427.

Remote consultations (video, telephone, text) have become integral to the delivery of primary care and are promoted by government initiatives. While many find these more convenient, they may also discriminate against those with lower digital literacy and present a barrier to empathy by removing some non-verbal communication. The aim of this realist review is to understand how therapeutic empathy can be effectively expressed during remote consultations in general practice across different situations and for different people.

This realist review will follow the methodological framework proposed by Pawson and colleagues, which includes the following five steps: (1) identify existing theories to develop an initial programme theory; (2) systematically search bibliographic databases to identify relevant literature; (3) select, extract and organise data; (4) synthesise evidence to develop context-mechanism-outcome configurations; (5) refine and finalise programme theory. This iterative process will be guided by a Content Expert Group consisting of patients, carers, clinical staff working in general practice and representatives from national stakeholder groups. The final programme theory will inform the development of evidence-based recommendations to help clinical staff working in general practice express empathy during remote consultations.

This review does not require ethics approval. Findings will be disseminated through peer-reviewed journals, national and international conferences and through relevant professional associations and primary care networks in the UK.

CRD420261306014.

Deficiencies in non-technical skills—including communication and leadership—are well-established causes of clinical errors in healthcare. Healthcare students and professionals increasingly use high-fidelity and virtual reality (VR) simulation to replicate clinical practice, through immersive and realistic scenarios in a risk-free teaching setting. However, there is no up-to-date, high-quality synthesis of the effects of high-fidelity and VR simulation on non-technical skills for healthcare students and professionals. A systematic review and meta-analysis of this literature is required to enhance the current knowledge.

This protocol has been reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) 2015 statement. We will include randomised trials and other controlled studies that report differences in non-technical skills between high-fidelity and VR simulation. We will search MEDLINE, Scopus, EMBASE, ERIC and CINAHL, from database inception. We will also search reference lists and contact experts to identify additional studies. Two independent reviewers will screen titles and abstracts, review full texts, and extract data. Discrepancies will be resolved through discussion, with a third reviewer if necessary. For randomised trials, we will use the Cochrane Risk-of-Bias 2.0 (RoB2) tool to evaluate the risk of bias in the included studies. For non-randomised studies, we will use the Risk Of Bias In Non-randomized Studies (ROBINS-1) assessment tool. If appropriate, meta-analysis will be performed. We will analyse continuous outcomes using weighted mean differences (with 95% CIs) or standardised mean differences (with 95% CIs) if different measurement scales are used. We will use subgroup and sensitivity analyses to explore heterogeneity. The overall certainty of evidence will be assessed using the GRADE (Grading of Recommendations, Assessment, Development and Evaluations) tool.

Ethical approval is not applicable for this study because no primary data have been collected. This review will be disseminated through peer-reviewed publication and presented at conferences to inform ongoing educational practises.

CRD420251136479.

Previous reviews have investigated the relationship between empathy and burnout. However, these are now out of date, did not capture the effect of the pandemic, did not include healthcare professionals other than doctors and nurses or medical students, did not assess the impact of differences in profession and did not pool the data, which made estimating the strength of the association unclear. We therefore aim to address these shortcomings in an up-to-date, rigorous, systematic review and meta-analysis.

Findings will be reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines and flowchart.

We will search American Psychological Association (APA) PsycINFO, APA PsycArticles, Cumulative Index to Nursing and Allied Health Literature (CINAHL), The Cochrane Library, PubMed and Scopus. We will also search ResearchSquare and Social Science Research Network (SSRN) for preprints; ProQuest Dissertations and Theses and Electronic Theses Online Service for relevant theses. Forward and backward citation searches will identify additional studies. Two independent reviewers will screen titles, abstracts and full texts and extract data. Two independent reviewers will assess risk of bias using Risk of Bias 2 (RoB 2) for randomised controlled trials, Risk of Bias in Non-randomised Studies of Interventions (ROBINS-I) for non-randomised interventional studies and Risk of Bias in Non-randomised Studies of Exposures (ROBINS-E) for observational studies.

For all included studies, we will summarise the study characteristics, including number of participants; health profession, specialty and career stage; country and gender. If data are suitable, we will pool results and conduct subgroup analyses (including by health profession, career stage and clinical specialty). We will also explore the relationships between subscales of empathy and burnout. We will use metaregression to explore the impact of theoretically derived factors (such as study design and profession) on the strength of the association. Sensitivity analyses will assess the impact of low-quality research. In our discussion, we will summarise results, the limitations and provide a general interpretation of the results and implications.

Ethical approval is not required for this review, as primary data will not be collected. The review will be disseminated through peer-reviewed publication and presentation at conferences.

CRD420251075618.