Understanding nursing graduates' intention to work with older adults: An exploratory structural framework

Gerontogeriatric competencies are considered essential for preparing nurses to meet the complex care needs of ageing populations. However, the intention to work with older adults remains comparatively low among nursing professionals, particularly among newly graduated registered nurses (NGRNs).

This study explored the structural relationships between nursing education, gerontogeriatric competencies, ageism, and the intention to work with older adults.

A nationwide cross-sectional study was conducted.

This nationwide cross-sectional study was conducted in Portugal and included NGRNs who had completed their undergraduate nursing degree in the 2021-2022 academic year. The final sample comprised 242 NGRNs from public and private nursing education institutions.

An exploratory structural equation modelling approach was used to examine potential relationships among five latent constructs: Nursing Education (NEDU), Gerontogeriatric Competencies (GGC), Hostile Ageism (AAS_HA), Benevolent Ageism (AAS_BA), and Intention to Work with Older Adults (INT_OA). Model estimation followed an iterative refinement process.

Model estimation encountered convergence difficulties, and the full structural framework could not be fully identified. Consequently, global model fit indices could not be obtained, and the results should be interpreted as exploratory structural associations. Among the estimated paths, a statistically significant association was identified between nursing education and gerontogeriatric competencies (b = 0.437, 95% CI [0.31, 0.57], p < 0.0001), while no statistically significant structural associations were observed between competencies or ageism to the intention to work with older adults.

Nursing education was positively associated with perceived gerontogeriatric competence; however, the intention to work with older adults appears to be shaped by more complex and potentially contextual factors. These findings highlight the need for theoretical refinement and further research using alternative modelling strategies and larger samples.