Evidence map›Paper›PMID 35503248›Full record

ArticleJMIR human factors2022

Determinants of Laypersons' Trust in Medical Decision Aids: Randomized Controlled Trial.

Marvin Kopka, Malte L Schmieding, Tobias Rieger, Eileen Roesler, Felix Balzer, Markus A Feufel

Open access · goldAbstract read
In one paragraph

Article in JMIR human factors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
8.5field-weighted citation impact, top 2% of its field
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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Marvin Kopka *Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0003-3848-1471
Malte L Schmieding *Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0002-5844-7791
Tobias RiegerWork, Engineering and Organizational Psychology, Department of Psychology and Ergonomics (IPA), Technische Universität Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0002-5097-6613
Eileen RoeslerWork, Engineering and Organizational Psychology, Department of Psychology and Ergonomics (IPA), Technische Universität Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0002-7243-4882
Felix Balzer *Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0003-1575-2056
Markus A Feufel *Division of Ergonomics, Department of Psychology and Ergonomics (IPA), Technische Universität Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0003-0563-8831
Humboldt-Universität zu Berlin · DETechnische Universität Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSymptom checker apps are patient-facing decision support systems aimed at providing advice to laypersons on whether, where, and how to seek health care (disposition advice). Such advice can improve laypersons' self-assessment and ultimately improve medical outcomes. Past research has mainly focused on the accuracy of symptom checker apps' suggestions. To support decision-making, such apps need to provide not only accurate but also trustworthy advice. To date, only few studies have addressed the question of the extent to which laypersons trust symptom checker app advice or the factors that moderate their trust. Studies on general decision support systems have shown that framing automated systems (anthropomorphic or emphasizing expertise), for example, by using icons symbolizing artificial intelligence (AI), affects users' trust.

objectiveThis study aims to identify the factors influencing laypersons' trust in the advice provided by symptom checker apps. Primarily, we investigated whether designs using anthropomorphic framing or framing the app as an AI increases users' trust compared with no such framing.

methodsThrough a web-based survey, we recruited 494 US residents with no professional medical training. The participants had to first appraise the urgency of a fictitious patient description (case vignette). Subsequently, a decision aid (mock symptom checker app) provided disposition advice contradicting the participants' appraisal, and they had to subsequently reappraise the vignette. Participants were randomized into 3 groups: 2 experimental groups using visual framing (anthropomorphic, 160/494, 32.4%, vs AI, 161/494, 32.6%) and a neutral group without such framing (173/494, 35%).

resultsMost participants (384/494, 77.7%) followed the decision aid's advice, regardless of its urgency level. Neither anthropomorphic framing (odds ratio 1.120, 95% CI 0.664-1.897) nor framing as AI (odds ratio 0.942, 95% CI 0.565-1.570) increased behavioral or subjective trust (P=.99) compared with the no-frame condition. Even participants who were extremely certain in their own decisions (ie, 100% certain) commonly changed it in favor of the symptom checker's advice (19/34, 56%). Propensity to trust and eHealth literacy were associated with increased subjective trust in the symptom checker (propensity to trust b=0.25; eHealth literacy b=0.2), whereas sociodemographic variables showed no such link with either subjective or behavioral trust.

conclusionsContrary to our expectation, neither the anthropomorphic framing nor the emphasis on AI increased trust in symptom checker advice compared with that of a neutral control condition. However, independent of the interface, most participants trusted the mock app's advice, even when they were very certain of their own assessment. Thus, the question arises as to whether laypersons use such symptom checkers as substitutes rather than as aids in their own decision-making. With trust in symptom checkers already high at baseline, the benefit of symptom checkers depends on interface designs that enable users to adequately calibrate their trust levels during usage.

trial registrationDeutsches Register Klinischer Studien DRKS00028561; https://tinyurl.com/rv4utcfb (retrospectively registered).

Indexed as

anthropomorphismartificial intelligenceconsumer healthdisposition advicehuman-computer interactioninformation technologyITmobile phonepatient-centered caresymptom checkersurgency assessment

Identifiers

PMID35503248
PMCPMC9115664
OpenAlexW4225396572

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.