ReviewThe patient2025
Developing Tools for the Efficient Design of Health Preference Studies: Taxonomy of Attributes and Prototype of an Attribute Library.
Review in The patient, 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.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Preference information describes the relative desirability or acceptability of specified alternatives that differ across health states, interventions, or services. Studies that generate preference information are being designed to support patient-centered decision making across all stages of the medical product lifecycle, as well as in healthcare more generally. Ensuring high-quality preference research with the potential for impact requires transparent and thoughtful study design, a core aspect of which often includes the development of attributes. Good practices for attribute development in preference studies have started to emerge and demonstrate that developing attributes requires substantial time and effort. Resources to more easily and systematically identify potentially relevant attributes may support the accessibility, interoperability, and reusability of attributes, in turn improving the efficiency of preference study design and comparability of findings across studies. In this paper, we first describe the need for and potential benefit of tools that promote the purposeful re-use of attributes for preference studies. We next present a taxonomy for categorizing and describing attributes that could be applied to facilitate their identification. Finally, we apply this taxonomy to a prototype "attribute library," developed as a part of a Medical Device Innovation Consortium work group, to demonstrate the potential value of these resources to support the preference research community.
Indexed as
Identifiers
40610706What 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.