ArticleHealth science reports2025
Measuring Experienced Utility in the Context of Health Economic Evaluation: A Narrative Overview.
Article in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Deploying projected utility to predict health behaviour in health economics: a quantitative study.Scientific reports · 2025Article
- Personalising Supportive Healthcare for Immune-Mediated Inflammatory Disorders: A Qualitative Exploration of Patient Needs and Behaviours Based on the Subjective Health Experience Model.International journal of integrated careArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: Expected utility is deeply ingrained in the field of health economic evaluation, but critics highlight its theoretical flaws, including assumptions of complete information, bounded rationality, and stable preferences. They propose incorporating experienced utility for greater accuracy and suggest certain measurement methods. However, the applicability of these measurement methods in health economic evaluation remains uncertain. Therefore, this article examines the advantages, disadvantages and potential use of these measurement methods in the context of health economic evaluation. Methods: The measurement methods suggested in the literature include assessing physiological indicators, peak-end perceptions, approach-avoidance tendencies, and retrospective impact. The advantages, disadvantages, and potential use of these measurement methods in the context of health economic evaluation are analyzed using the discourse dialectic method. Results: Evaluation of physiological indicators is minimally intrusive and relatively objective, but it relies on laboratory data collection, limits comparability across scales, and emphasizes direct experiences. Assessment of peak-end perceptions enhances memory accuracy, yet elicits exaggerated recollections, neglects experience duration, promotes faded peak or overvalued end experiences, and disregards experiences without end. Measurement of approach-avoidance tendencies detects implicit experiences but similarly depends on laboratory conditions, fixates on immediate automatic emotional associations, overlooks unavoidable events or states, and remains indifferent to approach-avoidance conflicts. Evaluation of retrospective impact fosters holistic reflection and highlights temporally extended experiences, yet it fails to account for external information contamination, disregards individual rationalization processes, and overlooks constraints on reflective capabilities. Conclusion: Each proposed measurement method had drawbacks affecting its suitability for health economic evaluation. However, retrospective impact assessment emerged as the most promising one, although further scholarly inquiry is warranted to examine the theoretical and practical complexities of this approach within health economic evaluation.
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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.