Possible Benefits of Smart Application Technology Among BSN Students for Asthma Care: A Validation Study Using Confirmatory Factor Analysis and Structural Equation Modeling

Malachi Brannon, Treshawna Cook, Jennifer Diggs, Danielle Zilpa Juray, Chanho Kwak, Sunita Paltoo, Jose Robert, Tashanah Vallon

Abstract


This study aims to evaluate the psychometric properties of the 17-item “Smart Applications for Asthma Care: Nursing Students’ Insights Survey,” which includes subscales such as “Being Mindful of the Client’s Breathing,” “Caring abilities of the student nurse,” and “Integrating smart application technology into client care.” The questionnaire measures the effectiveness of smart app technology in asthma patient care among nursing students. While the questionnaire demonstrates reliability through composite reliability, only the subscale “Integrating smart application technology into client care” exhibits convergent validity as confirmed by the confirmatory factor analysis (CFA). The results of the structural equation modeling (SEM) indicate a significant relationship between caring abilities and asthma knowledge, as evidenced by a strong positive path coefficient (β = 0.916, p = .006), suggesting that nursing students with higher levels of caring abilities tend to possess greater knowledge about asthma. However, no significant relationships arise between smart app use and either caring abilities (β = 0.007, p = 1.00) or asthma knowledge (β = 0.231, p = .227). Similarly, mindful breathing did not show a significant relationship with either caring abilities (β = 0.006, p = .999) or asthma knowledge. The results suggest that while caring abilities are positively associated with asthma knowledge, the use of smart apps and mindful breathing may not directly impact either caring abilities or asthma knowledge among nursing students in this study. Moreover, the relationship between smart app use and mindful breathing is not statistically significant. Pretest Q3 (0.83571), Posttest Q3 (0.86561), and Posttest Average (0.85415) have high R² values, indicating their significant predictive power in the performance of nursing students in this study. Further research is warranted to address these results, given the significant differences between the user and baseline structural models, and to optimize the integration of smart app technologies.

Keywords: structural equation modeling, confirmatory factor analysis, smart app, smart application, healthcare technology, nursing education, nursing students, asthma management

DOI: 10.7176/JHMN/116-03

Publication date: May 30th 2024


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