Factors Influencing Patients’ Contract Choice With General Practitioners in Shanghai
Bibliographic record
Abstract
The general practitioner (GP) system has been widely applied around the world and experimented with in Shanghai, China. To analyze some of the influencing factors on patient-GP contracts, we developed a questionnaire and conducted site investigations in 2011 and 2012 to 1200 patients by random sampling from 6 pilot community health service (CHS) centers in Pudong, Shanghai. The t test, χ(2) test, factor analysis, and logistic regression analysis were used to analyze the data. The factors influencing patients' contract behavior were age (OR = 1.03; 95%CI = 1.02-1.04), education level (OR = 0.83; 95% CI = 0.75-0.93), social interaction of social capital (OR = 1.34; 95% CI = 1.15-1.56), acceptance of first contact in community (OR = 3.25; 95% CI = 2.07-5.12), the year of investigation (OR = 2.58; 95% CI = 1.92-3.47), and the exposure to publicity (OR = 1.60; 95% CI = 1.39-1.85). Elderly patients formed a focus group to sign contracts with GPs. To increase trust in GPs by patients, it is recommended to improve the level of CHSs, strengthen publicity, and cultivate social capital among patients.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".