A mixed-method approach to assess users' intention to use mobile health (mHealth) using PLS-SEM and fsQCA

Purpose Despite the enormous potential of mobile health (mHealth), identifying the asymmetric relationship among the predictors towards intention to use (ITU) of mHealth tends to remain unresolved. This study aims to investigate the predictors and their asymmetric effects on ITU of mHealth through patients and healthcare professionals. Design/methodology/approach An integrated information systems (IS) model with four additional constructs has been developed to analyze symmetric and asymmetric effects on ITU of mHealth. An exploratory survey on 452 mHealth users with prior experience was conducted to evaluate the model using a mixed-method approach including partial least squares-based structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) technique. Findings The findings show that facilitating conditions, personal awareness building, perceived enjoyment, effort expectancy and perceived usefulness have predictive power for ITU of mHealth. In contrast, fsQCA reveals four more alternative solutions, including the main drivers explored by PLS-SEM. The results indicate that various conditions that were not crucial in PLS-SEM analysis are shown to be sufficient conditions in fsQCA. Research limitations/implications This study contributes to theory by integrating self-actualization factors (i.e. personal awareness building, patients as decision support unit) into the IS model. And practically, this study makes an essential contribution to users' ITU of mHealth, enabling relevant stakeholders to build strategies to implement mHealth successfully. Originality/value While mHealth has revolutionized healthcare and the prior literature only showed linear relationships, this empirical study revealed asymmetrical relationships among the determinants of ITU of mHealth. Thus, this study extends to the growing body of literature on the use of mHealth technology in the least developing nation.

Automated summary

This study investigates the predictors and their asymmetric effects on the intention to use (ITU) of mobile health (mHealth) among patients and healthcare professionals. The results show that various factors have predictive power for ITU of mHealth, and there are asymmetrical relationships among these determinants. The study contributes to theory by integrating self-actualization factors into the information systems model, and it has practical implications for stakeholders to build successful mHealth strategies.