Emerging Technologies and Employability in People with Visual Disabilities in a City in Northern Peru: A Model Based on Psychometric Network Analysis
Emerging technologies are reshaping labor market dynamics and redefining the competencies required for employability. However, their benefits remain unevenly distributed, particularly among socially vulnerable populations such as people with visual impairments. This study examined the relationship b...
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| Autores principales: | , , , , , |
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| Formato: | Artículo |
| Lenguaje: | inglés |
| Publicado: |
2026
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| Acceso en línea: | Enlace permanente (DOI o Handle) Ver en el sistema de origen |
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| Sumario: | Emerging technologies are reshaping labor market dynamics and redefining the competencies required for employability. However, their benefits remain unevenly distributed, particularly among socially vulnerable populations such as people with visual impairments. This study examined the relationship between emerging technologies and employability among individuals with visual disabilities in a city in northern Peru, within the broader framework of inclusive development and equal opportunity. A quantitative, non-experimental, cross-sectional design was employed with a sample of 132 participants. Data were collected through a Likert-type questionnaire measuring indicators associated with emerging technologies and employability. To capture the structural interdependencies between both domains, the study used psychometric network analysis based on ordinal correlations and EBICglasso estimation. The resulting network comprised 17 nodes and 89 edges, with a predominance of cross-domain associations between technology and employability indicators. The nodes with the strongest expected influence were EM5, TE7, and TE9, suggesting that these indicators occupied relatively central positions within the estimated exploratory network. Taken together, the results suggest preliminary associations between employability-related indicators and technology-related indicators, particularly those linked to technological access, skills development, autonomy, and innovation. Given the exploratory nature of the instrument, the cross-sectional design, and the sample size, these findings should be interpreted as preliminary. In this context, psychometric network analysis is best understood as a complementary exploratory approach that helps identify conditional associations between indicators, while further psychometric confirmation of the instrument remains necessary. |
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