Examining Willingness-to-Pay and Zero Valuations for a Health Improvement with Logistic Regression
Bibliographic Data
| ID | 13775504 |
|---|---|
| Authors | Afentoula Mavrodi (0000-0002-8415-2196, University of Macedonia, Thessaloniki, Greece, corresponding author), Stavros Chatzopoulos (0000-0001-9488-1811, Aristotle University of Thessaloniki), Stavros A Chatzopoulos (Aristotle University of Thessaloniki, Thessaloniki, Greece), Vassilis Aletras (0000-0002-3367-7777, University of Macedonia), Vassilis H Aletras (University of Macedonia, Thessaloniki, Greece) |
| Year | 2021 |
| Volume | 58 |
| Pages | 469580211028102-469580211028102 |
| Publication date | 2021-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | INQUIRY The Journal of Health Care Organization Provision and Financing (JOURNAL) |
| Journal identifiers | ISSN: 0046-9580 • E-ISSN: 1945-7243 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/00469580211028102 |
| PMID | 34271848 |
| OpenAlex | W3178331971 |
| Language | EN |
| Citations received | 3 |
| References cited | 40 |
Study aim was to elicit the Greek general population's willingness-to-pay (WTP) for a health improvement (recovery to perfect health), examine attitudinal differences between willing- and unwilling-to-pay individuals regarding healthcare services provision, and investigate -using a logistic regression model-demographic/socioeconomic factors impact on their intention to pay for a health improvement. A research tool was developed to conduct a cross-sectional stated-preference telephone-based survey (January-February 2019) and a representative sample (n = 1342) of the Greek general population was queried. The computer-assisted telephone-interview (CATI) method was used to ensure random sampling. WTP was elicited using the iterative bidding technique. Participants' attitudes toward healthcare services provision were assessed through pre-defined statements. Test-retest reliability of these statements was assessed using intraclass correlation coefficients (ICC). Logistic regression was employed to identify sociodemographic factors' effect on WTP intention. Differences among individuals' attitudes were assessed using the chi-square test. All analyses were conducted using the IBM SPSS Software v.25.0. Analysis showed acceptable reliability for WTP estimates (ICC = .67) and good reliability for healthcare services assessment statements (ICC = .83-.94). Mean WTP was estimated at €439.8. Respondents with higher educational level and higher household income were more likely to be willing to pay for a health improvement. On the contrary, older participants were less likely to be willing to pay. Most participants who considered public healthcare services to be of high quality were unwilling to pay. Logistic regression analysis led to the development of an effective predictive model regarding factors affecting individuals' WTP intention for a health improvement. Further classification of unwilling-to-pay individuals into protest responders and "true" zero valuators showed that protest responders are unlikely to be representative of the population. Hence, study results can be used for debiasing WTP responses, leading to a more accurate use of WTP estimates by policy makers, exploiting WTP values in medical interventions cost-benefit analysis within reimbursement decisions framework
Actuarial science · Bidding · Business · Economics · Environmental health · Health care · Intraclass correlation · Logistic regression · Population · Psychometrics · Test (biology · Willingness to pay · Clinical Psychology · Economic and Environmental Valuation · Health Systems, Economic Evaluations, Quality of Life · Marketing · Medicine · Patient Satisfaction in Healthcare · Psychology
Economic Valuation with Stated Preference Techniques
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Effects of the economic crisis on health and healthcare in Greece in the literature from 2009 to 2013
Consumer willingness to invest money and time for benefits of lifestyle behaviour change
Willingness to Pay per Quality-Adjusted Life Year
Contingent Valuation
| Unique citing works | 3 |
|---|---|
| Citations per year | 1 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |