Factors Associated with AI Use in a Norwegian Sample.

Sebastian Oltedal Thorp, Lars M Rimol, Martine Klock Fleten, Simen Kristoffer Berg Hoel

Abstract read

In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Sebastian Oltedal ThorpDepartment of Psychology, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway.

Lars M RimolDepartment of Psychology, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway.

Martine Klock FletenDepartment of Psychology, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway.ORCID 0009-0005-9530-1870

Simen Kristoffer Berg HoelDepartment of Psychology, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway.ORCID 0009-0002-0877-5698

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examined factors associated with self-reported workplace artificial intelligence (AI) use in a Norwegian employee sample (N = 196). Hierarchical logistic regression tested whether education, job sector, gender, age, leadership role, strengths-based leadership (SBL), perceived work training, and work engagement were associated with AI use. Higher education, employment in knowledge-intensive sectors, male gender, and higher perceived SBL were associated with greater odds of reporting AI use, whereas age, leadership role, general work training, and work engagement were not. The study's contribution is exploratory: it suggests that organizational context, and particularly perceived SBL, may add explanatory value beyond demographic and sectoral differences in a Norwegian setting. Because the study relies on a cross-sectional convenience sample, a binary self-report measure of AI use, and models affected by sparse cells, the findings should be interpreted as tentative associations rather than causal evidence about AI adoption.

Indexed as

AI useartificial intelligenceeducationgenderlogistic regressionNorwaystrengths-based leadershipworkplace

Identifiers

PMID42073900

DOI10.3390/bs16040537

PMCPMC13114194

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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.