Literature DB >> 28304259

An Extended Expectation-Confirmation Model for Mobile Nursing Information System Continuance.

Pi-Jung Hsieh1, Hui-Min Lai, Chen-Chung Ma, Judith W Alexander, Memg-Yi Lin.   

Abstract

Nursing is critical in health care systems and comprises the planning, execution, and documentation of nursing care. To better manage health care information during patient care, the use of a mobile nursing information system (MNIS) provides more time to care for inpatients by reducing time-consuming and redundant paperwork. The purpose of this study was to extend the expectation-confirmation model and explore the roles of nursing professional competency (skill in use), habit (customary use), satisfaction (with use), and frequency of prior use in the context of MNIS continuance usage. We randomly chose 3 hospitals from among 14 hospitals in Taiwan that had indicated they used an MNIS. We conducted a field survey of nurses who had experience using the MNIS. We used a valid sample of 90 nurses to test the research model, using structural equation modeling with the partial least squares method. The results show that habit and frequency of prior use had a significant impact on MNIS continuance usage. Satisfaction and frequency of prior use had a significant impact on habit. Nurses' professional competence is crucial to perceived usefulness and, thus, is relevant in the context of MNIS continuance usage. When habit weakens over time, the continuance intention predicts continuance usage. This study showed that the extended expectation-confirmation model effectively predicts nurses' MNIS continuance usage and provides implications. Academics and practitioners should understand how nurses' habits form and how they affect continued MNIS use. Understanding the antecedents of habits can help nursing managers identify and manipulate habit formation.

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Year:  2016        PMID: 28304259     DOI: 10.1891/1541-6577.30.4.282

Source DB:  PubMed          Journal:  Res Theory Nurs Pract        ISSN: 1541-6577            Impact factor:   0.688


  2 in total

1.  Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model.

Authors:  Huixian Zha; Kouying Liu; Ting Tang; Yue-Heng Yin; Bei Dou; Ling Jiang; Hongyun Yan; Xingyue Tian; Rong Wang; Weiping Xie
Journal:  BMC Med Inform Decis Mak       Date:  2022-08-19       Impact factor: 3.298

Review 2.  Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis.

Authors:  Tong Wang; Wei Wang; Jun Liang; Mingfu Nuo; Qinglian Wen; Wei Wei; Hongbin Han; Jianbo Lei
Journal:  NPJ Digit Med       Date:  2022-09-15
  2 in total

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