Web-Based Public Ratings of General Practitioners in Norway: Validation Study
Bibliographic record
Abstract
BACKGROUND: Understanding the complex relationships among multiple strategies for gathering users' perspectives in the evaluation of the performance of services is crucial for the interpretation of user-reported measures. OBJECTIVE: The main objectives were to (1) evaluate the psychometric performance of an 11-item web-based questionnaire of ratings of general practitioners (GPs) currently used in Norway (Legelisten.no) and (2) assess the association between web-based and survey-based patient experience indicators. METHODS: We included all published ratings on GPs and practices on Legelisten.no in the period of May 5, 2012, to December 15, 2021 (N=76,521). The questionnaire consists of 1 mandatory item and 10 voluntary items with 5 response categories (1 to 5 stars), alongside an open-ended review question and background variables. Questionnaire dimensionality and internal consistency were assessed with Cronbach α, exploratory factor, and item response theory analyses, and a priori hypotheses were developed for assessing construct validity (chi-square analysis). We calculated Spearman correlations between web-based ratings and reference patient experience indicators based on survey data using the patient experiences with the GP questionnaire (n=5623 respondents for a random sample of 50 GPs). RESULTS: Web-based raters were predominantly women (n=32,074, 64.0%), in the age range of 20-50 years (n=35,113, 74.6%), and reporting 5 or fewer consultations with the GP each year (n=28,798, 64.5%). Ratings were missing for 18.9% (n=14,500) to 27.4% (n=20,960) of nonmandatory items. A total of 4 of 11 rating items showed a U-shaped distribution, with >60% reporting 5 stars. Factor analysis and internal consistency testing identified 2 rating scales: "GP" (5 items; α=.98) and "practice" (6 items; α=.85). Some associations were not consistent with a priori hypotheses and allowed only partial confirmation of the construct validity of ratings. Item response theory analysis results were adequate for the "practice" scale but not for the "GP" scale, with items with inflated discrimination (>5) distributed over a narrow interval of the scale. The correlations between the web-based ratings GP scale and GP reference indicators ranged from 0.34 (P=.021) to 0.44 (P=.002), while the correlation between the web-based ratings practice scale and reference indicators ranged from 0.17 (not significant) to 0.49 (P<.001). The strongest correlations between web-based and survey scores were found for items measuring practice-related experiences: phone availability (ρ=0.51), waiting time in the office (ρ=0.62), other staff (ρ=0.54-0.58; P<.001). CONCLUSIONS: The practice scale of the web-based ratings has adequate psychometric performance, while the GP suffers from important limitations. The associations with survey-based patient experience indicators were accordingly mostly weak to modest. Our study underlines the importance of interpreting web-based ratings with caution and the need to further develop rating sites.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".