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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Dataset for: Substituting confidence for competence in health literacy: A review of studies, citations, and trial registrations

Authors: Jagemann, Inga; Thiele, Christian; Ruth, von Brachel; Hirschfeld, Gerrit;

Dataset for: Substituting confidence for competence in health literacy: A review of studies, citations, and trial registrations

Abstract

Patient health literacy is crucial for effective patient–physician communication, and interventions targeting health literacy can use measures based on either actual performance (competence) or self-ratings (confidence). This paper analyzed the development of these measures through three studies. Study 1 reviewed articles describing the development of novel measures; Study 2 examined the citations of these studies, and Study 3 evaluated data from clinical trials registries. The literature search was conducted from April 14–27, 2023. PubMed was used as the main database in which studies on health literacy measures were searched for the systematic review (Study 1). We then used Google Scholar and the OpenCitations database to describe citation patterns of the included health literacy measures (Study 2). Finally, we evaluated confidence- or competence-based health literacy measures by extracting and analyzing trial data from ClinicalTrials.gov (Study 3). Our review included 55 health literacy measures, among which 23 (42%) were competence-based, 28 (51%) confidence-based, and 4 (7%) assessed both. Recent trends show a shift toward developing more confidence-based measures and a decline in creating new competence-based measures. Confidence-based measures were increasingly cited, whereas citations for competence-based measures have plateaued. Lastly, our findings showed a steady increase in the use of confidence-based measures in recent clinical trials and a decrease in the use of competence-based measures when controlling for sample size. This shift may be detrimental to public health given our limited knowledge about patients’ ability to meet demands of shared decision-making, especially regarding new technologies like artificial intelligence in healthcare.

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  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average