Overview for developing Delphi-based interdisciplinary consensus statements on imaging: pros and cons
Tobias Johannes Dietrich
Radiology and Nuclear Medicine, Kantonsspital St. GallenSt. Gallen, Switzerland
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, Vasco V. Mascarenhas
- Musculoskeletal Imaging Unit, Imaging Center, Radiology Department, Hospital da Luz, Grupo Luz SaúdeLisbon, Portugal
- Advanced Imaging Research Consortium, AIRCLisbon, Portugal
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, Luis Cerezal
Radiology Department, Diagnóstico Médico CantabriaSantander, Spain
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, P. Diana Afonso
- Musculoskeletal Imaging Unit, Imaging Center, Radiology Department, Hospital da Luz, Grupo Luz SaúdeLisbon, Portugal
- Musculoskeletal Imaging Unit, Imaging Center, Radiology, Hospital Particular da Madeira, HPA, FunchalMadeira, Portugal
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oraz Iwona Sudoł-Szopińska
Department of Radiology, National Institute of Geriatrics, Rheumatology and RehabilitationWarsaw, Poland
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08 lis 2024
O artykule
Kategoria artykułu: Review paper
Data publikacji: 08 lis 2024
Zakres stron: 1 - 6
Otrzymano: 01 lut 2024
Przyjęty: 02 mar 2024
DOI: https://doi.org/10.15557/jou.2024.0015
Słowa kluczowe
© 2024 Tobias Johannes Dietrich et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Fig. 1.
Fundamentals of the Delphi Methodology: pros and cons
| Fundamentals of the Delphi Methodology | |
|---|---|
| Pros | Cons |
| Systematic and structured approach to consolidate, assess, and summarize limited scientific evidence, enabling a majority of experts to converge toward consensus | If experts lack sufficient experience, then the generated knowledge may be unreliable |
| Balanced work between panelists – all panelists involved at various stages | If engagement of panelists is poor, then the quality of delivered statements may not be optimal |
| Anonymity among participants to prevent any single individual or group applying too much influence over others | Bias may occur on the final consensus statements and discussion due to leaders who have access to all anonymized data |
| Iterative rounds: Statements are presented repeatedly, allowing controlled feedback | If literature research has not been well-conducted and bibliography is incomplete and outdated, then the consensus statements may not be up-to date |
| Informed decision-making: After each round, participants gain insight into the collective panel’s previous responses | If leaders are not objective, then bias to the consensus statements may occur |
| Providing both individual and collective feedback between the rounds | |
| Statistical group responses and a structured interaction inherent in the Delphi methodology | |
| Potential to reconsider and adjust individual positions in subsequent rounds |
If experts are from a similar background, then the newly generated knowledge may not be generally applicable |
| The higher the threshold for consensus, the more refined the questions must be in subsequent Delphi rounds to yield acceptance by the majority of panelists | The higher the threshold for consensus, the higher the challenge to yield consensus statements |
| Determination of the maximum number of Delphi process rounds before the first round to yield a high motivation of the panelists for their tasks | Unnecessarily prolonged process of reaching consensus if the number of Delphi rounds is not initially determined – time discipline |
| Inclusion of panelists from diverse countries ensures that consensus statements are rooted in a wide range of expert opinions, enhancing their potential generalizability across various health systems | Panelists consisting of subspecialized imaging specialists with academic backgrounds from a small number of countries poses a risk of bias against the viewpoints of non-academic imaging specialists practicing in other regions worldwide |