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This study attempts to understand the factors that influence clinician resistance to the implementation of health information technology in a mandatory setting. A survey study was conducted with 202 clinicians regarding their perceptions of the implementation of electronic medication management systems (eMMS) in an Australian hospital. The data was collected during the initial roll-out of eMMS for model validation and quantitative analysis. The overall results indicated that performance expectancy, switching costs, and facilitating conditions are direct predictors of clinician resistance, whereas effort expectancy and social influence showed indirect effects on clinician resistance through performance expectancy or switching costs. The study is among the first study that investigates passive clinician resistance to the implementation of health information technology in a health organisation. This study also focused on opposition behaviour among under-examined degrees of resistance. This study provides some insights to the hospital management on how to mitigate clinician resistance in the implementation of health information technology. Other types of clinician resistance, such as postponement and rejection, are not examined in this study. Future research on postponement behaviour and rejection behaviour is needed to have a more comprehensive view of clinician resistance. [ABSTRACT FROM AUTHOR]

Despite the innovation of technology products providing much convenience to our daily lives, many people still have a reserved attitude toward these innovated products. The study investigates factors that affect people’s technology acceptance behavior toward smart phones. Both the enabling factors and inhibiting factors are taken into research within a two-year study framework. Two sets of questionnaires were provided respectively: One with 377 valid questionnaires that was returned in the first year, and another with 379 valid questionnaires was received back in the second year. The data were analyzed through factor analysis and structural equation modeling (SEM). The experimental result among users’ enabling factors, the presence advantage, self-efficacy and ease of use, and perceptions of external control of when using smart devices shows a positive influence on the attitudes of smart devices users. In user-inhibiting factors, anxiety and perceived need inertia reduce the user’s desire in using a smart device. [ABSTRACT FROM AUTHOR]

Recent technological trends such as the health cloud provide a strong infrastructure and offer a true enabler for healthcare services on the Internet. Despite its great potential, gaps exist in our understanding of how users evaluate change related to the health cloud and how they decide to resist it. According to dual factor perspectives, this study develops an integrated model to explain patients’ intention to use health cloud services and their intention to resist it. A field survey was conducted in Taiwan to collect data from patients and a structural equation model was used to examine the data. The results show that patient resistance to use the health cloud is caused by suck costs, inertia, perceived value, transition costs, and uncertainty. Performance expectancy, effort expectancy, social influence, and facilitating conditions are shown to have positive and direct effects on patients’ intention to use the health cloud. The results also indicate that the relationship between the patients’ intention to use the health cloud and their resistance to using it had a significant negative effect. Our study illustrates the importance of incorporating user resistance in technology acceptance studies in general and health technology usage studies in particular. [ABSTRACT FROM AUTHOR]

Purpose -- This paper aims to expose the behaviours through which modern professional people commonly obstruct information system (IS) implementations in their workplace. Users often resist IS implementations, and it has been established that this can cause an implementation to fail. As the initial analysis of an on-going research project, this paper does not yet seek to present IS resistance as a good or a bad thing, it simply identifies and codifies forms of IS resistance. Design/methodology/approach -- Inductive interviews with IS implementers threw light on 29 resisted projects across 21 organisations. Interviewees were introduced to established theories of attitude change from social and cognitive psychology then asked to reflect on their experiences of IS implementations using these theories as a lens. Findings -- Although it is not claimed that all approaches by which users obstruct IS implementations are identified here, we believe that those most commonly deployed have been uncovered. It is also revealed that such behaviours result from negative user attitudes and that their impact can be significant They can emotionally or psychologically affect system champions and can often cause implementation projects to fail Research limitations/implications -- Our method was based on an epistemic assumption that significant understanding is found in the experience and knowledge (tacit and explicit) of IS implementation experts. The paper's contents are drawn from reflections on a combined 302 years of experience using attitude change psychology as a lens. Using this method, a range of obstructive behaviours was identified. Although it is claimed that the obstructive behaviours most commonly deployed have been unveiled, it is not probable that this list is comprehensive and could be appended to using alternative approaches. Practical implications -- This paper has significant implications for stakeholders in IS implementations. It enables project risks originating from users to be better identified, and it highlights the critical role that negative user attitudes can play in an implementation. Social implications -- This paper considers a common area of conflict in professional organisations, modelling its nature and effect. It also encourages system champions to consider user attitude cultivation as a critical part of any implementation project. Originality/value -- The contribution of this research is twofold. In the arena of user resistance, it is the first to focus on how implementations are resisted and is accordingly the first to identify and taxonomise forms of IS resistance. A contribution is also made to an ongoing literature conversation on the role of attitude in technology acceptance. This paper is the first to focus, not on user attitudes but on how negative attitudes are manifest in behaviour. [ABSTRACT FROM AUTHOR]

Background: Sensor-based technologies offer numerous benefits in hospital environments as they can be used (1) to improve efficiency defined processes and (2) to monitor their conduction in order to prevent errors. However, the impact of these technologies on the stakeholders involved such as professional ward nurses is largely unexplored. The early assessment of technology acceptance and user resistance is crucial to anticipate potential conflicts and to improve future implementation success. Objectives: To understand the attitudes and intentions of usage of professional ward nurses toward sensor-based medication systems based on an adjusted extended technology acceptance model (TAM2) in a pre-implementation stage. Design: A scenario-based research design was used in a nation-wide empirical study. Settings: Nurses of Australian associations/unions evaluated a scenario of a sensor-based medication support system. Participants: A randomly selected sample of 579 professional ward nurses participated in this study. Methods: Data were collected using an online questionnaire and explored using hierarchical regression analysis. Results: The majority of nurses intend to use the system but 25% - not voluntarily. 8% reject the system entirely. In assessing the nurses' perceived usefulness, image, demonstrability, qualitative and quantitative overload as well as personal innovativeness were found to have a significant impact. Qualitative and quantitative overload also have a significant negative effect on personal innovativeness. Regarding the nurses' usage intention, we identified a significant negative influence of subjective norm, moderated by experience and a positive effect of perceived usefulness on intention to use the system. Image, qualitative and quantitative overload as well as personal innovativeness are significantly influenced by age. Conclusions: Our findings support a successful implementation of medication support systems in hospitals by stating acceptance drivers and barriers. Nurses' adoption is promoted once a high degree of perceived usefulness is achieved by result demonstrability, a positive image of the technology and a high degree of personal innovativeness. Image and innovativeness are moderated by age, showing that an increase in age leads to an increase in user resistance toward the perceived usefulness of the envisioned medication support systems. Future studies should investigate these barriers in further stages of implementation to extend understanding of sensor-based medication system acceptance. [ABSTRACT FROM AUTHOR]

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