Heterogeneity in Preferences for Primary Care Consultations: Results from a Discrete Choice Experiment
Bibliographic record
Abstract
Purpose: The increasing importance of flexibility in the general practitioner (GP) -patient consultation approach in primary care requires healthcare managers and physicians to find a balance among all the potentially important characteristics of consultation. This study used a discrete choice experiment (DCE) to assess patients’ preferences for different attributes of GP consultation and how the rate at which they traded between different attributes is affected by socio-demographic characteristics and past experiences with primary care services . Methods: A survey was conducted to a sample of 6970 residents in Tuscany region, Italy. Besides socio-demographic characteristics the survey collected information about participants’ past experience with GP consultation in the last 12 months. Moreover, participants were asked to select their preferred option in a series of pairwise choices, defined by the following attributes: level of involvement in decision making, amount of information received from the GP and waiting time for the visit. Results: Results revealed that receiving information from the GP was more important than being involved in the decisions and that, approximately, a complete involvement had the same importance as a partial involvement. Participants' past experience with GP’s consultation appeared to have the greatest influence on the involvement level. The amount of information required by the respondents was also influenced by a complex interplay of personal and contextual factors. Conclusions: This large-scale study extends the body of literature on DCE applications for different GP consultation approaches, providing new information about the influence that patients’ socio-demographic characteristics and past experiences could have on consultation preferences.
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How this classification was reachedexpand
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 | 0.002 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".