Artificial intelligence (AI) has the potential to revolutionise healthcare delivery, particularly in the domain of emergency medicine. With the rise of telemedicine and virtual care, AI-powered tools could assist in triage, diagnosis and treatment recommendations for patients seeking emergency care remotely. This systematic review aims to synthesise the current state of research on AI applications in virtual emergency care, identify key challenges and opportunities and provide recommendations for future research and implementation.

We will conduct a comprehensive search of multiple electronic databases (PubMed, Web of Science, Embase, CINAHL, MEDLINE, The Cochrane Library, Scopus) from each database’s inception to March 2025. The search will include terms related to AI, machine learning, deep learning, virtual care, telemedicine and emergency medicine. We will include original research articles, conference proceedings and preprints that describe the development, validation or implementation of AI models for virtual emergency care. Two reviewers will independently screen titles and abstracts, review full texts, extract data and assess risk of bias using the PROBAST (Prediction model Risk Of Bias ASsessment Tool) tool for prediction model studies, Cochrane Risk-of-Bias tool for randomised trials for randomised trials and Risk Of Bias In Non-randomised Studies of Interventions for non-randomised studies. Data synthesis will involve a narrative review of included studies, summarising key findings, methodological approaches and implications for practice and research. The results will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

No ethical approval is required for this systematic review as it will use only published data. The findings will be disseminated through publication in a peer-reviewed journal, presentations at relevant conferences and engagement with clinicians, health system leaders, policymakers and researchers. This review will provide a timely and comprehensive overview of the applications of AI in virtual emergency care to inform evidence-based guidelines, policies and practices for leveraging these technologies to enhance access, quality and efficiency of emergency care delivery.

CRD42025648202.

The efficacy and safety of SMS text message-delivered interventions for providing pain self-management education and improving clinical pain outcomes have been demonstrated in several randomised controlled trials. However, little is known about the feasibility and effectiveness of these interventions within Australian hospital settings. The current protocol describes a trial designed to evaluate the effectiveness and implementation of an SMS text message-delivered intervention designed to support patients’ engagement with pain self-management strategies and improve clinical pain outcomes after total knee replacement surgery.

A hybrid, type 1 effectiveness-implementation trial will be conducted at a private hospital in Australia. Participants (n=130) will be randomised to either the intervention group (receiving a pain self-management educational video prior to surgery, plus daily SMS text message reminders for 3 weeks after surgery) or an active control group (receiving the pre-surgery video alone, without text message reminders) in addition to usual care. Effectiveness outcomes will be pain intensity (primary), opioid dose, knee function and pain-related distress and will be recorded at baseline, 3 days, 3 weeks, 6 weeks, 3 months and 6 months after surgery using self-reported surveys. Pain self-efficacy and health-related quality of life will be measured at 6 weeks, 3 months and 6 months post-surgery. Implementation outcomes (Reach, Experience, Adoption, Implementation, Maintenance) will be evaluated using mixed (qualitative and quantitative) methods. This trial represents a first step towards the translation of digitally delivered postoperative support for engaging with pain self-management in the Australian healthcare system.

The study protocol was reviewed and approved by the Austin Health Human Ethics Research Committee (Australia, HREC/110142/Austin-2024). Study results will be published in a peer-reviewed journal and presented at scientific and professional meetings.

ACTRN12624001060538

Clinicians and patients have been found to attribute musculoskeletal (MSK) pain to normal age-related changes seen on imaging, which can negatively impact patient outcomes and increase healthcare costs. While some studies have tested interventions to improve how MSK imaging findings are communicated, their impact has been limited. Applying a behavioural science framework has the potential to identify the rationale and target of these interventions to inform future intervention design—an analysis that has not yet been conducted. This study aims to identify the Behaviour Change Techniques (BCTs), the behavioural targets and the theoretical basis of interventions seeking to affect the communication of MSK imaging.

Scoping review using the Capability, Opportunity, Motivation - Behaviour (COM-B) model.

Searches of MEDLINE, EMBASE, CINAHL, AMED and PsycINFO from inception to 9 February 2024.

We included studies that have developed or evaluated interventions which target the communication of MSK imaging findings. Interventions targeting both patients and clinicians were included. Experimental and quasi-experimental study designs were included, and studies that focused on serious or specific known causes of MSK pain were excluded.

Two independent authors extracted study participant data and intervention details. A theory of behaviour called the COM-B model was used to map the BCTs and behavioural components targeted by studies.

We identified 11 studies from 2486 studies in our electronic search. 11 different BCTs were identified across 11 studies. The most common techniques were framing/reframing (nine studies), adding objects to the environment (eight studies), incompatible beliefs (seven studies) and avoidance/reducing exposure to cues for the behaviour (four studies). Only two studies (feasibility studies) used behavioural theory to guide their intervention design. While one study showed a large effect, most interventions had little to no impact on pain, disability, or fear over time.

This review highlighted a lack of studies targeting clinician knowledge and the provision of high-quality patient resources about the nature of MSK pain, even though the broader literature identifies both as enablers of effective health communication. Additionally, the absence of a theory-informed design likely resulted in attempts to reassure patients about normal age-related imaging findings without providing an alternate, more coherent explanation for symptoms. Future interventions should focus on enhancing clinician psychological capability (knowledge) as well as clinician and patient reflective motivation (beliefs) to enable more helpful explanations of MSK symptoms. The key challenge for future interventions will be achieving these aims in a way that is effective, consistent and practical.

Open Science Framework (https://doi.org/10.17605/OSF.IO/ECYS8).