Evidence map›Paper›PMID 41756604›Full record

ArticleDigital health

Perceived credibility and social competence of chatbots in mental health apps and the influence of algorithm literacy.

Maria F Grub, Teresa K Naab

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Maria F GrubInstitute for Media and Communication Studies, University of Mannheim, Mannheim, Germany.ORCID https://orcid.org/0009-0004-3676-1984
Teresa K NaabInstitute for Media and Communication Studies, University of Mannheim, Mannheim, Germany.ORCID https://orcid.org/0000-0001-7345-2559

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To examine user perceptions of human advisors versus chatbots in mental health apps and assess the impact of algorithm literacy interventions. Methods: In an online experiment, participants engaged in simulated chats about digital stress. A within-subjects condition compared effects of human advisors and chatbots on perceived likeability, credibility, and social competence. A between-subjects condition tested information interventions (positive vs. negative vs. no evaluation of algorithms) aimed at increasing algorithm literacy. Results: Participants rated human advisors more favorably than chatbots on all measured dimensions ( Conclusion: Users consistently preferred human advisors over chatbots for mental health advice. Brief algorithm literacy interventions had no significant effect on these preferences. This suggests that simply increasing users' understanding of chatbots is insufficient to enhance their acceptance in mental health settings, underscoring the need for more effective approaches to improve their adoption.

Indexed as

algorithm literacyartificial intelligenceChatbotsmental healthperceived credibilitysocial competence

Identifiers

PMID41756604
PMCPMC12932880

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.