Evidence map›Paper›PMID 41060458›Full record

ReviewEuropean archives of psychiatry and clinical neuroscience2026

Anthropomorphic technology in everyday life: focus on chatbots and impacts on mental health.

Scott Monteith, Tasha Glenn, John R Geddes, Peter C Whybrow, Eric Achtyes, Michael Bauer

Abstract readReview
In one paragraph

Review in European archives of psychiatry and clinical neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Evaluation of large language model chatbot responses to psychotic prompts.medRxiv : the preprint server for health sciences · 2025
    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

6 authors.

Scott MonteithMichigan State University College of Human Medicine, Traverse City Campus, 1400 Medical Campus Drive, Traverse City, MI, 49684, USA. monteit2@msu.edu.ORCID http://orcid.org/0000-0002-9289-4544
Tasha GlennChronoRecord Association, Fullerton, CA, USA.
John R GeddesDepartment of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK.
Peter C WhybrowDepartment of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles (UCLA), Los Angeles, CA, USA.
Eric AchtyesDepartment of Psychiatry, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, USA.
Michael BauerDepartment of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus Medical Faculty, Technische Universität Dresden, Dresden, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chatbots are widely used by business in everyday life to interact with consumers in e-commerce, social networking, education, and government settings. Anthropomorphism is a fundamental aspect of chatbot design and implementation, and increases the interaction of chatbots with humans. As part of the recent expansion of artificial intelligence (AI) technologies, chatbots incorporated AI to engage more personally with consumers. The anthropomorphic characteristics of chatbots, including both visual appearance and language, influence the interaction of chatbots with humans in diverse ways that may have both positive and negative consequences. The purpose of this review is to increase physician awareness of the use of chatbots which use AI to enhance anthropomorphism. Consumers routinely anthropomorphize products including chatbots. Physicians need to be aware of the wide-ranging and routine use of chatbots, and the importance of anthropomorphism in chatbot design and implementation. Physicians also need to recognize potential negative consequences of anthropomorphism of chatbots on mental health.

Indexed as

Artificial IntelligenceMental HealthHumansAnthropomorphismArtificial intelligenceChatbotsMental health

Identifiers

PMID41060458
PMCPMC12904903

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.