Evidence map›Paper›PMID 40435517›Full record

ArticleJMIR human factors2025

Framing the Human-Centered Artificial Intelligence Concepts and Methods: Scoping Review.

Roberta Bevilacqua, Tania Bailoni, Elvira Maranesi, Giulio Amabili, Federico Barbarossa, Marta Ponzano, Michele Virgolesi, Teresa Rea, Maddalena Illario, Enrico Maria Piras and 3 more

Abstract readScoping Review
In one paragraph

Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

13 authors.

Roberta BevilacquaScientific Direction, IRCCS INRCA, Via Santa Margherita 5, Ancona, Italy, 39 0718004767.ORCID 0000-0002-3851-3552
Tania BailoniIntelligent Digital Agents (IDA) Research Group, Fondazione Bruno Kessler (FBK), Trento, Italy.ORCID 0000-0003-4360-566X
Elvira MaranesiScientific Direction, IRCCS INRCA, Via Santa Margherita 5, Ancona, Italy, 39 0718004767.ORCID 0000-0002-2414-3773
Giulio AmabiliScientific Direction, IRCCS INRCA, Via Santa Margherita 5, Ancona, Italy, 39 0718004767.ORCID 0000-0002-2005-4319
Federico BarbarossaScientific Direction, IRCCS INRCA, Via Santa Margherita 5, Ancona, Italy, 39 0718004767.ORCID 0000-0001-8701-9879
Marta PonzanoDepartment of Health Sciences, Section of Biostatistics, University of Genoa, Genoa, Italy.ORCID 0000-0003-4091-4686
Michele VirgolesiDepartment of Public Health, University of Naples "Federico II", Naples, Italy.ORCID 0000-0003-4619-0711
Teresa ReaDepartment of Public Health, University of Naples "Federico II", Naples, Italy.ORCID 0000-0001-6444-0951
Maddalena IllarioDepartment of Public Health, University of Naples "Federico II", Naples, Italy.ORCID 0000-0001-9834-6517
Enrico Maria PirasDigital Health & Wellbeing, Fondazione Bruno Kessler, Trento, Italy.ORCID 0000-0002-6115-0577
Matteo LengeNeuroscience and Human Genetics Department, Meyer Children's Hospital IRCCS, Florence, Italy.ORCID 0000-0003-2848-621X
Elisa BarbiNeuroscience and Human Genetics Department, Meyer Children's Hospital IRCCS, Florence, Italy.ORCID 0009-0001-9350-7614
Garifallia SakellariouDepartment of Internal Medicine and Therapeutics, University of Pavia, Pavia, Italy.ORCID 0000-0002-1849-5123

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the rapid expansion of artificial intelligence (AI) applications, researchers have begun focusing on the concept of human-centered artificial intelligence (HCAI). This field is dedicated to designing AI systems that augment and improve human abilities, rather than substituting them. Objective: The objective of the paper was to review the information on design principles, techniques, applications, methods, and outcomes adopted in the field of HCAI, in order to provide some insights on the discipline, in relation with the broader concepts of human-centered and user-centered design. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist guidelines, we conducted a scoping review in PubMed, ScienceDirect, and IEEE Xplore, including all study types, excluding narrative reviews and editorials. Results: Out of the 1035 studies retrieved, 14 studies conducted between 2018 and 2023 met the inclusion criteria. The main fields of application were the health sector and AI applications. Human-centered design methodologies were adopted in 3 studies, personas in 2 studies, while the remaining methodologies were adopted in individual studies. Conclusions: HCAI emphasizes designing AI systems that prioritize human needs, satisfaction, and trustworthiness, but current principles and guidelines are often vague and difficult to implement. The review highlights the importance of involving users early in the development process to enhance trust, especially in fields like health care, but notes that there is a lack of standardized HCAI methodologies and limited practical applications adhering to these principles.

Indexed as

Artificial IntelligenceHumansacceptabilityAI applicationsAI principlesalgorithmanalyticsdeep learningdesign principlesearly detectionearly warningethicsHCAIhuman-centered artificial intelligencehuman-centered designmachine learningMLpredictive analyticspredictive modelreviewUCDusabilityuser-centered design

Identifiers

PMID40435517
PMCPMC12136509

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.