Patients and healthcare professionals’ perspectives on the implementation of shared decision making in multiple myeloma: a multinational qualitative study
Bibliographic record
Abstract
BACKGROUND: Shared decision making (SDM) is highly relevant in oncology and cancer care, yet its application within multiple myeloma (MM) remains underexplored. This study aims to (1) investigate SDM implementation in MM clinical practice, (2) assess the role of various stakeholders next to haematologists in the SDM process, and (3) identify barriers and potential solutions to SDM implementation in MM care. METHODS: This qualitative study consisted of semi-structured interviews with patients (n = 39), haematologists (n = 15), and haematology nurses (n = 5) from nine countries in Europe and Israel. Interviews were analysed thematically. RESULTS: MM patients expressed diverse preferences for involvement in treatment decisions, emphasising the importance of receiving information, engaging in discussions, and having their opinions considered. However, participants reported varied experiences regarding the application of SDM. While most haematologists believed SDM was consistently attempted, patients frequently indicated that their preferences, concerns, and desired level of involvement were not explicitly solicited. Discussions about the option of no treatment were notably under-discussed, as observed by patients and acknowledged by haematologists. Patients uniformly reported that the assessment of their preferred information-seeking approach was consistently overlooked, a critical step in SDM. Haematology nurses, the multidisciplinary team, family members, and patient organisations were found to play an invaluable role in the SDM process, each having their own complementary role alongside haematologists. Barriers to SDM implementation included haematologists' reluctance to inform or involve patients, patients' emotional status, lack of reliable patient-focused information, absence of haematology nurses, and time constraints. Patient decision aids (PtDAs) were perceived as tools to facilitate SDM, with a majority of participants expressing positive attitudes towards them, recognising their value in specific contexts. CONCLUSION: While SDM is partially applied in MM care, there remains room for improvement. This can be done by amplifying the role of haematology nurses and other multidisciplinary team members in the SDM process. Additionally, efforts should focus on increasing the role of patient organisations in raising awareness about SDM and empowering patients to actively participate in SDM. The recommendations derived from this study along with the insights for PtDA development can serve as an initial stride towards increasing SDM implementation in MM care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".