Trial reportScientific reports2023
Discounting money and health effects from communicable and noncommunicable diseases in Thailand.
Trial report in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.
- Whether temporal discounting is domain-specific between health outcomes and money: a systematic review and meta-analysis.International journal of clinical pharmacy · 2025Pooled it
- Domain-specific discounting of health and money: implications for health technology assessment.The European journal of health economics : HEPAC : health economics in prevention and care · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this study was to determine the discount rates for money and health outcomes in the Thai context, including the discount rates for communicable and non-communicable diseases. Moreover, this study aimed to explore the socio-demographic characteristics that influence discounting. The computer-based experimental design was used to obtain time preferences for money and health in a total of 1202 Chiang Mai province population, aged 25-50, individually interviewed by trained interviewers. Money-related questions were carried out in all subjects. For health-related questions, all subjects were randomly assigned in a 1:1 ratio for response to questions about Coronavirus Disease 2019 (COVID-19) (N = 602) and air pollution (N = 600). A choice-based elicitation procedure was performed in the experiment to obtain the indifference values from subjects' time preferences. The cumulative weighting functions were generated using the indifference values to indicate the degree of discounting. The discount factors were computed from the cumulative weighting functions. The discount rates were estimated using a continuous approximation based on the relationship between the discount factors and the parameters governing the discounting model. The Tobit model was applied to investigate the relationships between discounting and socio-demographic characteristics. Discounting for money was greater than discounting for health. Money and health had annual discount rates of 6.2% and 1.3%, respectively. Furthermore, in the COVID -19 situation, the annual discount rate for health was higher than that in the air pollution situation (2.4% vs. 0.7%). Generation X subjects (aged 42 years and above), children under the age of 15 in the household, and underlying diseases were positively related to discounting, while household income was negatively related to discounting. Health should be discounted at a lower rate than money. Moreover, different discount rates should be considered for different types of diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.