ArticleFrontiers in public health2020
A "Third Wheel" Effect in Health Decision Making Involving Artificial Entities: A Psychological Perspective.
Article in Frontiers in public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
37 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Physicians' required competencies in AI-assisted clinical settings: a systematic review.British medical bulletin · 2025Pooled it
- Precision cancer medicine and the doctor-patient relationship: a systematic review and narrative synthesis.BMC medical informatics and decision making · 2023Pooled it
- Trial
- Generative Artificial Intelligence (AI)-Assisted Self-Diagnosis and the Patient-Physician Relationship: Mixed Methods Study of Calibration, Participation, and Trust.Journal of medical Internet research · 2026Article
- Can health technologies be "care optimizers"? A normative evaluation of digital health technologies in light of postphenomenological reflections.Medicine, health care, and philosophy · 2026Article
- Viewpoint on the Consequences and Mitigation of Cognitive Bias in the Radiological Interpretation of Breast Cancer Imaging Using Artificial Intelligence.JMIR medical informatics · 2026Review
- Patient Perceptions of Artificial Intelligence in Diabetes Self-Management: Cross-Sectional Survey Study.JMIR formative research · 2026Article
- "The science of teaching": Understanding anatomy demonstrators' pedagogical content knowledge.Anatomical sciences education · 2026Article
- Development of the perceived AI-physician consistency and trust scale for cardiology: a Delphi-based study.Frontiers in digital health · 2026Article
- "First, Trust Needs to Develop": Hematologists' Perspectives on Factors Influencing Black Persons' Participation in Clinical Trials.Journal of racial and ethnic health disparities · 2025Article
- Exploring doctors' perspectives on precision medicine and AI in colorectal cancer: opportunities and challenges for the doctor-patient relationship.BMC medical informatics and decision making · 2025Article
- The Use of AI in Mental Health Services to Support Decision-Making: Scoping Review.Journal of medical Internet research · 2025Article
- Attitudes toward the use of ChatGPT to seek oncological information: a qualitative study.Frontiers in psychology · 2025Article
- Evaluation of Health Science Students' Knowledge, Attitudes, and Practices Toward Artificial Intelligence in Northern Saudi Arabia: Implications for Curriculum Refinement and Healthcare Delivery.Journal of multidisciplinary healthcare · 2025Article
- Factors influencing the acceptance of medical AI chat assistants among healthcare professionals and patients: a survey-based study in China.Frontiers in public health · 2025Article
- Prospects and challenges of deep learning in gynecologic malignancies.Frontiers in oncology · 2025Review
- Healthcare Professionals' perspectives on AI-driven decision support in young adult mental health: an analysis through the lens of a shared decision-making framework.Frontiers in digital health · 2025Article
- AI in Radiology: Navigating Medical Responsibility.Diagnostics (Basel, Switzerland) · 2024Review
- Scoping Review Shows the Dynamics and Complexities Inherent to the Notion of "Responsibility" in Artificial Intelligence within the Healthcare Context.Asian bioethics review · 2024Article
- Radiologic Technology Students' Perceptions on Adoption of Artificial Intelligence Technology in Radiology.International journal of general medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the near future, Artificial Intelligence (AI) is expected to participate more and more in decision making processes, in contexts ranging from healthcare to politics. For example, in the healthcare context, doctors will increasingly use AI and machine learning devices to improve precision in diagnosis and to identify therapy regimens. One hot topic regards the necessity for health professionals to adapt shared decision making with patients to include the contribution of AI into clinical practice, such as acting as mediators between the patient with his or her healthcare needs and the recommendations coming from artificial entities. In this scenario, a "third wheel" effect may intervene, potentially affecting the effectiveness of shared decision making in three different ways: first, clinical decisions could be delayed or paralyzed when AI recommendations are difficult to understand or to explain to patients; second, patients' symptomatology and medical diagnosis could be misinterpreted when adapting them to AI classifications; third, there may be confusion about the roles and responsibilities of the protagonists in the healthcare process (e.g., Who
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.