Evidence map›Paper›PMID 38628537›Full record

ArticleSurgical neurology international2024

Assessing the impact of mixed reality-assisted informed consent: A study protocol.

Gianluca Scalia, Stefano Maria Priola, Sruthi Ranganathan, Tejas Venkataram, Valeria Orestano, Salvatore Marrone, Bipin Chaurasia, Rosario Maugeri, Domenico Gerardo Iacopino, Lidia Strigari and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Surgical neurology international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.2field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 8 institutions in 4 countries.

Gianluca ScaliaNeurosurgery Unit, Department of Head and Neck Sugery, Garibaldi Hospital, Catania, Italy.
Stefano Maria PriolaDepartment of Neurosurgery, Health Sciences North, Northern Ontario School of Medicine, Sudbury, Ontario, Canada.
Sruthi RanganathanDepartment of Medicine, University of Cambridge, Cambridge CB2 OQQ, United Kingdom.
Tejas VenkataramDepartment of Neurosurgery, Trauma Center, Gamma Knife Center, Cannizzaro Hospital, Catania, Italy.
Valeria OrestanoPsychology Center Orestano-Pittera, "l'Intreccio" Association, San Giovanni la Punta (CT), Italy.
Salvatore MarroneNeurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in Neurologic Surgery, Department of Biomedicine Neurosciences and Advanced Diagnostics, School of Medicine, University of Palermo, Palermo, Italy.
Bipin ChaurasiaDepartment of Neurosurgery, Neurosurgery Clinic, Birgunj, Nepal.
Rosario MaugeriNeurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in Neurologic Surgery, Department of Biomedicine Neurosciences and Advanced Diagnostics, School of Medicine, University of Palermo, Palermo, Italy.
Domenico Gerardo IacopinoNeurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in Neurologic Surgery, Department of Biomedicine Neurosciences and Advanced Diagnostics, School of Medicine, University of Palermo, Palermo, Italy.
Lidia StrigariDepartment of Medical Physics, University Hospital of Bologna, Bologna, Italy.
Maurizio SalvatiDepartment of Neurosurgery, Policlinico "Tor Vergata", University of Rome "Tor Vergata", Rome, Italy.
Giuseppe Emmanuele UmanaDepartment of Neurosurgery, Trauma Center, Gamma Knife Center, Cannizzaro Hospital, Catania, Italy.
University of Palermo · ITOspedale Cannizzaro · ITBir Hospital · NPHealth Sciences North · CAOspedale Garibaldi · ITUniversity of Bologna · ITUniversity of Cambridge · GBUniversity of Rome Tor Vergata · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Informed consent is a crucial aspect of modern medicine, but it can be challenging due to the complexity of the information involved. Mixed reality (MR) has emerged as a promising technology to improve communication. However, there is a lack of comprehensive research on the impact of MR on medical informed consent. The proposed research protocol provides a solid foundation for conducting future investigations and developing MR-based protocols that can enhance patients' understanding and engagement in the decision-making process. Methods: This study will employ a randomized controlled trial design. Two arms will be defined: MR-assisted informed consent (MRaIC) as the experimental arm and conventional informed consent (CIC) as the control arm consent, with 52 patients in each group. The protocol includes the use of questionnaires to analyze the anxiety levels and the awareness of the procedure that the patient is going to perform to study the impact of MRaIC versus CIC before medical procedures. Results: The study will evaluate the impact of MR on patients' information comprehension, engagement during the process of obtaining informed consent, emotional reactions, and consent decisions. Ethical concerns will be addressed. Conclusion: This study protocol provides a comprehensive approach to investigate the impact of MR on medical informed consent. The findings may contribute to a better understanding of the effects of MR on information comprehension, engagement during the process of obtaining informed consent, psychological experience, consent decisions, and ethical considerations. The integration of MR technology has the potential to enhance surgical communication practices and improve the informed consent process.

Indexed as

Informed consentMixed realityPatient engagementSurgical interventionsSurgical outcomes

Identifiers

PMID38628537
PMCPMC11021117
OpenAlexW4392863189

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.