Evidence map›Paper›PMID 38370149›Full record

ArticleMDM policy & practice

What Affects Perceived Trustworthiness of Online Medical Information and Subsequent Treatment Decision Making? Randomized Trials on the Role of Uncertainty and Institutional Cues.

Gabriel Recchia, Karin S Moser, Alexandra L J Freeman

Abstract read
In one paragraph

Article in MDM policy & practice. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Gabriel RecchiaWinton Centre for Risk & Evidence Communication, Department of Pure Maths and Mathematical Statistics, University of Cambridge, Cambridge, UK.
Karin S MoserUniDistance Suisse, Faculty of Psychology, Brig, Switzerland.ORCID https://orcid.org/0000-0003-0120-9327
Alexandra L J FreemanWinton Centre for Risk & Evidence Communication, Department of Pure Maths and Mathematical Statistics, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0002-4115-161X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Highlights: In a world where information for medical decision making is increasingly going to be provided through digital, online tools, institutions providing such tools need guidance on how best to communicate about their trustworthiness and precision.We find that people are fairly insensitive to cues designed to communicate uncertainty around the outputs of such tools. Even putting "ATTENTION" in bold font or explicitly pointing out the weaknesses in the data did not appear to affect people's decision making using the tool's outputs. Institutions should take note, and further work is required to determine how best to communicate uncertainty in a way that elicits appropriate caution in lay users.People were much more sensitive to institutional logos associated with the outputs. Generalized institutional trust (rather than trust in the specific institution whose logo was shown) was associated with how trustworthy, accurate, and reliable the tool, its algorithm, and the numbers it produced were perceived to be. This underscores the role of societal trust in institutions at large.Finally, as a note to researchers, we found a significant effect of how hypothetical or believable participants felt the experimental scenario was. This is a variable that seems rarely controlled for in studies and yet played as much of a role as some of our variables of interest, so we suggest that it is measured in future experiments.

Indexed as

algorithmsinstitutional cuesmedical decision makingpsychological distancetrustuncertainty

Identifiers

PMID38370149
PMCPMC10870812

What OpenQuestion holds

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Registered trials

None linked

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.