Evidence map›Paper›PMID 42459764›Full record

ArticleFrontiers in artificial intelligence2026

Typology of civil engineers' mental model about artificial intelligence.

Ardalan Feili, Masih Rajabi Shabankareh, Sima Alipour, Shahrzad Entezaralmahdi, Shahryar Sorooshian

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2026. 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
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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

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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

5 authors.

Ardalan FeiliDepartment of Management, Apadana Higher Education Institute, Shiraz, Iran.
Masih Rajabi ShabankarehDepartment of Civil Engineering, Apadana Higher Education Institute, Shiraz, Iran.
Sima AlipourDepartment of Management, Apadana Higher Education Institute, Shiraz, Iran.
Shahrzad EntezaralmahdiDepartment of Civil Engineering, University of Texas at Arlington, Arlington, TX, United States.
Shahryar SorooshianDepartment of Business Administration, University of Gothenburg, Gothenburg, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aims to identify, classify, and typologize the mental models of civil engineers, the diversity of their perspectives, and their intellectual structures regarding the integration of artificial intelligence in the industry. Method: The philosophical framework of this research is based on an interpretive-positivist paradigm (Q method) and its application. The 11 participants were selected from individuals with sufficient knowledge, expertise, and experience related to the research topic, and who could provide the necessary information to achieve the study's objectives. The purpose of this sampling is to classify them and identify common mental patterns within a small and targeted group, rather than to generalize the findings to a larger population. Findings: The results indicate that civil engineers' mental models regarding the applications of artificial intelligence are divided into three categories: hopeful-concerned, black-box thinkers, and results-oriented. Conclusion: Analyzing the distinct thought patterns among civil engineers reveals significant heterogeneity in the acceptance of AI, highlighting the need for fundamental changes in communication strategies. The study shows that to facilitate use, key information must be delivered through tailored content. For example, for the black-box group, content should emphasize algorithmic transparency and how models work. For the hopeful-concerned group, content should reduce ethical and employment-related concerns. Meanwhile, for the results-oriented group, content should highlight economic returns and proven successes. Ultimately, this approach is essential for effective and successful integration of AI into the infrastructure industry.

Indexed as

artificial intelligencebehaviorcivil engineersmental modelsQ methodology

Identifiers

PMID42459764
PMCPMC13368919

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.