Evidence map›Paper›PMID 37251278›Full record

ArticleInternational journal of social robotics2023

Ethics 4.0: Ethical Dilemmas in Healthcare Mediated by Social Robots.

Antonio Soares, Nuno Piçarra, Jean-Christophe Giger, Raquel Oliveira, Patrícia Arriaga

Abstract read
In one paragraph

Article in International journal of social robotics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

5 authors.

Antonio SoaresISCTE-Instituto Universitário de Lisboa, CIS-IUL, Lisboa, Portugal.ORCID 0000-0001-7519-4370
Nuno PiçarraISCTE-Instituto Universitário de Lisboa, CIS-IUL, Lisboa, Portugal.ORCID 0000-0001-9832-5724
Jean-Christophe GigerPsychology Research Centre (CIP), University of Algarve, Faro, Portugal.ORCID 0000-0002-4184-1741
Raquel OliveiraISCTE-Instituto Universitário de Lisboa, CIS-IUL, Lisboa, Portugal.ORCID 0000-0002-3542-2065
Patrícia ArriagaISCTE-Instituto Universitário de Lisboa, CIS-IUL, Lisboa, Portugal.ORCID 0000-0001-5766-0489

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examined people's moral judgments and trait perception toward a healthcare agent's response to a patient who refuses to take medication. A sample of 524 participants was randomly assigned to one of eight vignettes in which the type of healthcare agent (human vs. robot), the use of a health message framing (emphasizing health-losses for not taking vs. health-gains in taking the medication), and the ethical decision (respect the autonomy vs. beneficence/nonmaleficence) were manipulated to investigate their effects on moral judgments (acceptance and responsibility) and traits perception (warmth, competence, trustworthiness). The results indicated that moral acceptance was higher when the agents respected the patient's autonomy than when the agents prioritized beneficence/nonmaleficence. Moral responsibility and perceived warmth were higher for the human agent than for the robot, and the agent who respected the patient's autonomy was perceived as warmer, but less competent and trustworthy than the agent who decided for the patient's beneficence/nonmaleficence. Agents who prioritized beneficence/nonmaleficence and framed the health gains were also perceived as more trustworthy. Our findings contribute to the understanding of moral judgments in the healthcare domain mediated by both healthcare humans and artificial agents.

Indexed as

CompetenceHealth framingMoral judgmentsNursing robotsTrustworthinessWarmth

Identifiers

PMID37251278
PMCPMC9989998

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.