An overview of the methodological aspects and policy implications of willingness-to-pay studies in oral health: a scoping review of existing literature
Bibliographic record
Abstract
BACKGROUND: Demands for dental services seem to be beyond the capacities of most healthcare systems these days. Patient preferences have been increasingly emphasized to be considered in the joint decision-making process. Willingness-to-pay (WTP) is a recommended method for measuring the utility of health services; increasingly being used in recent decades. Taking these points into consideration, this article aims to provide an overview of the methodological aspects and policy implications of WTP studies in the field of oral health. METHODS: The research was conducted in ISPOR, PubMed and Google Scholar databases. In addition, reference lists of included articles were checked to identify the relevant studies. All studies published were included that were in the English language and reported using WTP for oral health-related goods and services. A data-charting form was developed by a focus group discussion panel of seven experts to derive the main methodological aspects of WTP. Also, Core policy suggestions were categorized through thematic content analysis of the included papers. RESULTS: The search strategy yielded 389 studies of which 52 were included. WTP studies in oral health show an increasing trend in global publications. The UK and Canada have a greater share in published material than in any other country. The dominant field of these researches is in restorative and prosthetic dentistry, and a wide range of different methodological aspects was documented. Policy suggestions were categorized in three main themes: (A) setting new tariffs or subsidizing the item, (B) provision of the item due to population preferences, and (C) improving literacy regarding the item. CONCLUSIONS: An urgent need for a common framework regarding the design of WTP studies in dentistry seems paramount. Some policy suggestions seem not to be applicable, perhaps due to insufficient familiarity of the researchers with the complexities of the public policymaking process.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".