Evidence mapPaperPMID 40499161Full record

ArticleJMIR cancer2025

Examining How Technology Supports Shared Decision-Making in Oncology Consultations: Qualitative Thematic Analysis.

Alan Yung, Tim Shaw, Judy Kay, Anna Janssen

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In one paragraph

Article in JMIR cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Alan Yung *Research in Implementation Science and eHealth Group, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-1608-1680
Tim Shaw *Research in Implementation Science and eHealth Group, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0003-0783-1918
Judy Kay *Human Centred Technology Research Cluster, School of Computer Science, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0001-6728-2768
Anna Janssen *Research in Implementation Science and eHealth Group, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0001-6611-9651

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCommonly used digital health technologies, such as electronic health record systems and patient portals as well as custom-built digital decision aids, have the potential to enhance person-centered shared decision-making (SDM) in cancer care. SDM is a 2-way exchange of information between at least a clinician and the patient and a shared commitment to make informed decisions. However, there is little evidence in the literature on how technologies are used for SDM or how best they can be designed and integrated into workflows and practice. This may be due to the nature of SDM, which is fundamentally human interactions and conversations that produce desired human outcomes. Therefore, technology must be nonintrusive while supporting the human decision-making process.

objectiveThis study examined how digital technologies can help cancer care professionals improve SDM in oncology consultations.

methodsHealth care professionals who treat patients with cancer were invited to participate in online co-design focus group meetings. During these sessions, they shared their experiences using digital technologies for SDM and provided suggestions to improve their use of digital technologies. The session recordings were transcribed and then analyzed using qualitative thematic analysis. The 3-talk SDM model, which consists of 3 steps-team talk, option talk, and decision talk-was used as the guiding framework. This approach was chosen because the 3-talk SDM model has been adopted in Australia. The researchers walked the participants through the SDM model and discussed their routine clinical workflows.

resultsIn total, 9 health care professionals with experience treating patients with cancer and using technologies participated in the study. Two focus groups and 2 interviews were conducted in 2024. Three themes and 7 subthemes were generated from the thematic analysis. The findings indicated that various digital technologies, such as electronic health record systems, mobile devices, and patient portals, are used by cancer care professionals to help improve patients' understanding of their disease and available care options. Digital technologies can both improve and undermine SDM. Current systems are generally not designed to support SDM. Key issues such as data integration and interoperability between systems negatively impact the ability of digital technologies to support SDM. Emerging technologies such as generative artificial intelligence were discussed as potential facilitators of SDM by automating information gathering and sharing with patients and between health professionals.

conclusionsThis research indicates that digital technologies have the potential to impact SDM in oncology consultations. However, this potential has not yet been fully realized, and significant modifications are required to optimize their usefulness in person-centered SDM. Although technology can facilitate information sharing and improve the efficiency of consultation workflows, it is only part of a complex human communication process that needs support from multiple sources, including the broader multidisciplinary cancer team.

Indexed as

Decision Making, SharedDigital TechnologyMedical OncologyNeoplasmsReferral and ConsultationElectronic Health RecordsFemaleFocus GroupsHumansMalePatient ParticipationQualitative ResearchAIartificial intelligencecancer caredigital healthoncologypatient-centered careperson-centered careshared decision-making

Identifiers

PMID40499161
PMCPMC12198703

What Socratic holds

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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 Socratic graph.