Patients' preferred and perceived level of involvement in decision making for cancer treatment: A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Patient involvement in decision making is conditional for personalised treatment decisions. We aim to provide an up-to-date overview of patients' preferred and perceived level of involvement in decision making for cancer treatment. METHODS: A systematic search was performed in PubMed, EMBASE, PsycINFO and CINAHL for articles published between January 2009 and January 2020. Search terms were 'decision making', 'patient participation', 'oncology', 'perception' and 'treatment'. Inclusion criteria were: written in English, peer-reviewed, reporting patients' preferred and perceived level of involvement, including adult cancer patients and concerning decision making for cancer treatment. The percentages of patients preferring and perceiving an active, shared or passive decision role and the (dis)concordance are presented. Quality assessment was performed with a modified version of the New-Castle Ottawa Scale. RESULTS: 31 studies were included. The median percentage of patients preferring an active, shared or passive role in decision making was respectively 25%, 46%, and 27%. The median percentage of patients perceiving an active, shared or passive role was respectively 27%, 39%, and 34%. The median concordance in preferred and perceived role of all studies was 70%. Disconcordance was highest for a shared role; 42%. CONCLUSIONS: Patients' preferences for involvement in cancer treatment decision vary widely. A significant number of patients perceived a decisional role other than preferred. Improvements in patient involvement have been observed in the last decade. However, there is still room for improvement and physicians should explore patients' preferences for involvement in decision making in order to truly deliver personalised cancer care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it