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A mixed methods UTAUT2-based approach to assess mobile health adoption

机译：基于utaut2的混合方法评估移动健康采用的方法

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Drawing on UTAUT2, this study examines the number of causal recipes that foster mHealth adoption, using a mixed approach combining Partial Least Squares (PLS-SEM) and fuzzy-set qualitative comparative analysis. Two general research propositions are assessed using data collected through a survey administered to 120 mHealth users. The findings point that PLS-SEM and fsQCA are complementary analytical approaches providing comparable results. PLS-SEM indicates that performance expectancy, hedonic motivation, and habit have the ability to predict mHealth adoption, while fsQCA reveals six configurations including the factors identified by PLS-SEM. The findings suggest that several conditions that were not significant in PLS-SEM are in fact sufficient conditions when combined with other conditions. For practitioners concerned with fostering mHealth adoption, the findings stress the importance of adopting an integrated approach centered on performance expectancy, facilitating conditions, and habit, targeting well-educated young women. The existence of multiple solutions also points to the presence of equifinality.
机译：绘图在utaut2上，本研究审查了使用混合方法组合局部最小二乘（PLS-SEM）和模糊定性比较分析的混合方法来培养MHECHEATION的因果关系的数量。使用通过管理到120 MEHEALTE用户的调查收集的数据进行评估两次一般研究命题。 PLS-SEM和FSQCA是提供可比结果的互补分析方法的调查结果。 PLS-SEM表明性能期望，蜂鸟动机和习惯具有预测MHECHEATION的能力，而FSQCA揭示了六种配置，包括PLS-SEM所识别的因素。研究结果表明，在PLS-SEM中没有显着的若干条件实际上与其他条件相结合的条件。对于涉及培养MHECHEATION的从业者，调查结果强调采用综合方法，以绩效预期，促进条件和习惯为目标，旨在受过良好受过良好的年轻女性。多种解决方案的存在也指向平等性的存在。

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