Investigating the effects of augmented reality-based interventions on pediatric patient outcomes in the clinical setting: A systematic review

Abstract

Background and aim: Augmented reality (AR)-based interventions are increasingly being used in pediatric healthcare settings as non-pharmacological tools to reduce distress and improve patient outcomes. This review aimed to synthesize current evidence on the effectiveness, feasibility, and usability of AR interventions in improving physical, emotional, and psychological outcomes among pediatric patients. Methods: A comprehensive literature search was conducted across six databases-PubMed, Cochrane Library, MEDLINE, Scopus, Web of Science, and CINAHL-for studies published up to December 12, 2024. Eligible studies included those evaluating AR-based interventions with outcomes related to physical, emotional, or psychological health. Two reviewers independently conducted data extraction and assessed methodological quality using the Joanna Briggs Institute critical appraisal tools. The review followed the PRISMA 2020 guidelines and was registered in PROSPERO (ID: CRD42025638915). Results: The review included 14 studies involving 1057 children across diverse clinical settings such as surgery, oncology, dentistry, rehabilitation, and anesthesia induction. AR interventions were associated with reduced procedural pain and anxiety, improved cooperation and emotional comfort, increased knowledge acquisition, and enhanced satisfaction with care. Conclusion: AR-based interventions show significant promise in improving pediatric patient experiences and outcomes across a variety of healthcare domains. However, current evidence is limited by small sample sizes, methodological variability, and short-term evaluations. Implication to practice: AR-based interventions can enhance pediatric care by reducing pain and anxiety, improving cooperation, and increasing patient satisfaction. Their integration into clinical routines may support more positive healthcare experiences for children. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.