Evidence map›Paper›PMID 42741368›Full record

ArticleFrontiers in medicine2026

Distinct perception profiles of gig economy employment among nursing students in Saudi Arabia: a latent profile analysis.

Alya Alghamdi, Bandar S Alharbi, Majed M Aljabri

Abstract read
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Article in Frontiers in medicine, 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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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Alya AlghamdiDepartment of Community and Psychiatric Mental Health Nursing, College of Nursing, King Saud University, Riyadh, Saudi Arabia.
Bandar S AlharbiDepartment of Community and Psychiatric Mental Health Nursing, College of Nursing, King Saud University, Riyadh, Saudi Arabia.
Majed M AljabriDepartment of Community and Psychiatric Mental Health Nursing, College of Nursing, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The gig economy has become an innovative employment model with the potential to enhance workforce flexibility and support healthcare delivery. However, concerns regarding employment security, professional regulation, and continuity of care remain. Understanding how future nurses perceive this evolving employment model is important because these perceptions may influence future career decisions and the adoption of flexible workforce strategies. This study aimed to identify distinct latent profiles of nursing students based on their perceptions of gig economy employment and to examine factors associated with profile membership. Methods: We performed a cross-sectional survey among undergraduate nursing students in four public universities in Riyadh, Saudi Arabia. All eligible undergraduate nursing students who registered during the study period were invited to participate. Data were collected using a structured self-administered questionnaire. The questionnaire assessed nursing challenges, gig economy characteristics, gig economy perceptions, perceived benefits, and perceived impact. Model selection was based on information criteria, entropy, the bootstrap likelihood ratio test (BLRT), profile size, and interpretability. Multinomial logistic regression was performed to identify factors associated with latent profile membership. Results: A total of 291 nursing students were included in the analysis. Although the four-profile solution showed slightly better information criteria and higher entropy, these improvements were modest and were accompanied by increased model complexity. Considering the overall balance between statistical fit, profile size, parsimony, and substantive interpretability, the three-profile solution was selected for subsequent analyses, comprising Gig Economy Enthusiasts (39.2%), Pragmatic Evaluators (37.8%), and Personal Impact-Oriented Supporters (23.0%). Compared to Gig Economy Enthusiasts, higher perceived nursing challenges were significantly associated with increased odds of belonging to the Pragmatic Evaluators profile (OR = 2.12, 95% CI: 1.23 to 3.67). Nationality, age, and sex were not significantly associated with membership in this profile. Similarly, higher nursing challenge scores were independently associated with membership in the Personal Impact-Oriented Supporters profile (OR = 2.48, 95% CI: 1.31 to 4.69). Conclusion: Nursing students showed heterogeneous perceptions of gig economy employment, with three distinct attitudinal profiles identified. The findings highlight the importance of incorporating flexible employment concepts into nursing education and workforce planning while addressing concerns related to nursing practice.

Indexed as

employment modelsgig economylatent profile analysismultinomial logistic regressionnursing studentsnursing workforceSaudi Arabiaworkforce flexibility

Identifiers

PMID42741368
PMCPMC13572654

What Socratic holds

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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 Socratic graph.