Shared decision-making experienced by Canadians facing health care decisions: a Web-based survey
Bibliographic record
Abstract
BACKGROUND: Despite health policy that promotes shared decision-making, it is not yet the norm in clinical practice. We aimed to assess how much shared decision-making Canadians experienced in health-related decisions in 2017. METHODS: We conducted a cross-sectional online survey in January 2018 with a Web-based panel of Canadians representing all 10 provinces. We assessed their involvement in health-related decisions made with a health care professional over the previous year by asking about 1) discussion of choice of treatment or care plan, 2) presentation of advantages and disadvantages, 3) exploration of ideas and preferences, 4) discussion of preferred option and 5) match between preferred and actual level of participation. We computed an average shared decision-making score (range 1 [never] to 5 [always]). We presented characteristics of participants and responses using descriptive statistics and explored variations across sociodemographic factors, jurisdictions, geographical areas and care settings (home care or not) using multivariate weighted regressions. RESULTS: Of the 1591 participants surveyed, 1010 (63.5%) reported receiving health care in the previous 12 months. The mean of the average shared decision-making score was 2.25/5 (standard deviation [SD] 1.16). After weighting, 42.8% of respondents reported that their health care professional often or always mentioned that they had a choice of treatment or care plan, 45.4% reported that advantages and disadvantages were often or always presented, 38.8% reported that they were often or always asked for their ideas or preferences, 40.2% reported that they were often or always asked about their preferred option, and 54.1% stated that their level of participation in decision-making often or always matched their preferred level of participation. Increasing age, rural setting, living in the province of Quebec and not being white significantly decreased the level of shared decision-making experienced. Older respondents (age ≥ 65 yr) receiving home care reported the least shared decision-making (mean score 1.7 [SD 0.5]). INTERPRETATION: Canadians in all 10 provinces experienced a low degree of shared decision-making in 2017, with variations across sociodemographic factors, jurisdictions, care settings and geographical areas. Further efforts to foster implementation of shared decision-making are needed and should take these variations into account.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".