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Physicians' resistance toward healthcare information technology: A theoretical model and empirical test
Abstract and Figures
The article presents a theoretical model of physician resistance of healthcare information technology (HIT) usage by integrating the technology acceptance and resistance to change literatures with the use of a dual-factor model of technology usage. The author mentions that the theoretical model presented in the study elaborates the interdependent and asymmetric effects of inhibiting usage perceptions on HIT usage intentions relative to enabling perceptions. He explains that the model is supported using a field survey of a computerized physician order entry system among 129 practicing physicians. He explains that the importance of incorporating user resistance in technology usage is illustrated throughout the study.
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... In contrast to acceptance, which represents factual behavior, resistance can be understood as a cognitive force that precludes such behavior (Bhattacherjee & Hikmet, 2007;Kim, & Kankanhalli, 2009;Lewin, 1947). The present research focuses on active resistance, "an attitudinal outcome that follows an unfavorable evaluation of a new product" (Talke & Heidenreich, 2014, p. 898). ...
... Most studies from the IS field examining resistance have focused on organizational contexts where resistance may emerge in response to the mandatory introduction of organizational technologies (e.g., Bhattacherjee & Hikmet, 2007;Lapointe, & Rivard, 2005;Markus, 1983). The present work diverges from prior research by examining resistance as a response to emerging technologies in the consumer domain, where individuals freely exercise agency over their adoption decisions. ...
... Past studies on technology resistance have focused on artifacts such as apps (Prakash & Dash, 2022), mobile wallets (Leong et al., 2020), healthcare information technology (Bhattacherjee & Hikmet, 2007;Lapointe & Rivard, 2005), human resources information systems (Laumer et al., 2016), and online teaching platforms (Craig et al., 2019). These studies show that technology resistance is highly context-and technology-dependent. ...
Smart home assistants (SHAs) have gained a foothold in many households. Although SHAs have many beneficial capabilities, they also have characteristics that are colloquially described as creepy-a fact that may deter potential users from adopting and utilizing them. Previous research has examined SHAs neither from the perspective of resistance nor the perspective of creepiness. The present research addresses this gap and adopts a multi-method research design with four sequential studies. Study 1 serves as a pre-study and provides initial exploratory insights into the concept of creepiness in the context of SHAs. Study 2 focuses on developing a measurement instrument to assess perceived creepiness. Study 3 uses an online experiment to test the nomological validity of the construct of creepiness in a larger conceptual model. Study 4 further elucidates the underlying behavioral dynamics using focus group analysis. The findings contribute to the literature on the dark side of smart technology by analyzing the triggers and mechanisms underlying perceived creepiness as a novel inhibitor to SHAs. In addition, this study provides actionable design recommendations that allow practitioners to mitigate end users' potential perceptions of creepiness associated with SHAs and similar smart technologies.
... H5: There is a positive relationship between innovativeness and consumers' intentions Resistance to Change (RTC): For this study, resistance to change refers to consumers' reluctance to change how they receive parcels, from home delivery to parcel locker delivery. Past research indicates that user resistance may influence their decision whether or not to use technology, such as their willingness to adopt electronic health records (EHR) , healthcare information systems (Bhattacherjee & Hikmet, 2007), and mobile health systems (Hoque & Sorwar, 2017). However, a last-mile delivery study has not investigated the study on resistance to change. ...
... Previous studies determined all the measurement items for each construct. The measurement items for performance expectancy and effort expectancy were adapted from Zhou et al. (2020), social influence and facilitating conditions (Zhou et al., 2020;Venkatesh et al., 2012), resistance to change from Bhattacherjee and Hikmet (2007), and behaviour intention from Venkatesh et al. (2012). This study was carried out using structural equation modeling (SEM), and the research model was created using SmartPLS 4. The outer and inner models of path models were constructed using partial least squares (PLS), which are two sets of linear equations. ...
... We refer to an IS system's compatibility with physicians' work practices and processes, which is a key factor in telemedicine acceptance [50][51][52]. Since medical treatment involves various tests and information, and medical diagnosis and healthcare provision mistakes should be avoided, the compatibility of different systems has a key role [50]. ...
... We refer to an IS system's compatibility with physicians' work practices and processes, which is a key factor in telemedicine acceptance [50][51][52]. Since medical treatment involves various tests and information, and medical diagnosis and healthcare provision mistakes should be avoided, the compatibility of different systems has a key role [50]. If telemedical online consultations are not perceived to be compatible with existing work practices and processes, they may not be perceived as easy to use and may therefore not be accepted by physicians. ...
As healthcare demands exceed outpatient physicians’ capacities, telemedicine holds far-reaching potential for both physicians and patients. It is crucial to holistically analyze physicians’ acceptance of telemedical applications, such as online consultations. This study seeks to identify supporting and constraining factors that influence outpatient physicians’ acceptance of telemedicine.
We develop a model based on the unified theory of acceptance and use of technology (UTAUT). To empirically examine our research model, we conducted a survey among German physicians (n = 127) in 2018–2019. We used the partial least squares (PLS) modeling approach to test our model, including a mediation analysis.
The results indicate that performance expectancy (β = .397, P < .001), effort expectancy (β = .134, P = .03), and social influence (β = .337, P < .001) strongly impact the intention to conduct online consultations and explain 55% of its variance. Structural conditions regarding data security comprise a key antecedent, associating with performance expectancy (β = .193, P < .001) and effort expectancy (β = .295, P < .001). Regarding potential barriers to usage intentions, we find that IT anxiety predicts performance (β = –.342, P < .001) and effort expectancy (β = –.364, P < .001), while performance expectancy fully mediates (βdirect = .022, P = .71; βindirect = -.138, P < .001) the direct relationship between IT anxiety and the intention to use telemedical applications.
This research provides explanations for physicians’ behavioral intention to use online consultations, underlining UTAUT’s applicability in healthcare contexts. To boost acceptance, social influences, such as personal connections and networking are vital, as colleagues can serve as multipliers to reach convergence on online consultations among peers. To overcome physicians’ IT anxiety, training, demonstrations, knowledge sharing, and management incentives are recommended. Furthermore, regulations and standards to build trust in the compliance of online consultations with data protection guidelines need reinforcement from policymakers and hospital management alike.
... RTC is a concept that refers to the challenge of breaking one's habit or the mental tension that occurs as one is confronted with change (Guo et al., 2013). As a result, RTC is positioned among the major barriers human values that only have a negative influence upon the acceptance of a certain technology-when it comes to technological adoption (Cenfetelli, 2004), a group of elements that has gotten little attention in the academic (Bhattacherjee & Hikmet, 2007). Individual issues are frequently disregarded in organizational transformation studies, which have mostly focused on organizational difficulties. ...
Psychological capital (PsyCap) has been found as a substantial contributor to a range of desirable organizational outcomes. Emotional intelligence (EI) and PsyCap have both been shown to be effective in overcoming resistance to change (RTC). In an ever-changing field such as the banking sector, one of the biggest problems with managing change is that employees may resist it when they have to adapt to the change. The data for the study was gathered via the use of a questionnaire that was sent online to 253 private bank employees. After the validating factor analysis with the help of SPSS AMOS 26 program, the structural equation model was drawn and the relationships between the variables were evaluated. This research examines the influence of EI and PsyCap on employee RTC. The findings show that EI has a positive impact on PsyCap and a negative impact on RTC. PsyCap has a negative impact on RTC. PsyCap mediated the impact of EI on RTC.
... Ultimately, technology reactance can significantly impact the success of ehealth solutions. By understanding the potential for technology reactance and taking appropriate steps to address it, developers and promoters can help ensure that their intended audiences adopt and utilize their e-health solutions [2,15]. ...
... Here, previous studies have identified the "perceived usefulness" and "perceived ease-of-use" to be particularly important for the acceptance or declination of innovations [26,27] as part of the frequently used extended Technology Acceptance Model (TAM2) [28][29][30]. Additionally, the physician's willingness to change his/her workflow and the future compatibility of the CDSS to daily work practice were included in the questionnaire [26,28,31]. Response formats included the Likert scale (five-point: 1: does not apply at all; 2: does rather not apply; 3: partly applies; 4: largely applies; 5: fully applies; or 1: unimportant -5: very important, respectively) or multiple choice with preselected options for closed questions. ...
Background
Chronic kidney disease (CKD), a major public health problem with differing disease etiologies, leads to complications, comorbidities, polypharmacy, and mortality. Monitoring disease progression and personalized treatment efforts are crucial for long-term patient outcomes. Physicians need to integrate different data levels, e.g., clinical parameters, biomarkers, and drug information, with medical knowledge. Clinical decision support systems (CDSS) can tackle these issues and improve patient management. Knowledge about the awareness and implementation of CDSS in Germany within the field of nephrology is scarce.
Purpose
Nephrologists’ attitude towards any CDSS and potential CDSS features of interest, like adverse event prediction algorithms, is important for a successful implementation. This survey investigates nephrologists’ experiences with and expectations towards a useful CDSS for daily medical routine in the outpatient setting.
Methods
The 38-item questionnaire survey was conducted either by telephone or as a do-it-yourself online interview amongst nephrologists across all of Germany. Answers were collected and analysed using the Electronic Data Capture System REDCap, as well as Stata SE 15.1, and Excel. The survey consisted of four modules: experiences with CDSS (M1), expectations towards a helpful CDSS (M2), evaluation of adverse event prediction algorithms (M3), and ethical aspects of CDSS (M4). Descriptive statistical analyses of all questions were conducted.
Results
The study population comprised 54 physicians, with a response rate of about 80–100% per question. Most participants were aged between 51–60 years (45.1%), 64% were male, and most participants had been working in nephrology out-patient clinics for a median of 10.5 years. Overall, CDSS use was poor (81.2%), often due to lack of knowledge about existing CDSS. Most participants (79%) believed CDSS to be helpful in the management of CKD patients with a high willingness to try out a CDSS. Of all adverse event prediction algorithms, prediction of CKD progression (97.8%) and in-silico simulations of disease progression when changing, e. g., lifestyle or medication (97.7%) were rated most important. The spectrum of answers on ethical aspects of CDSS was diverse.
Conclusion
This survey provides insights into experience with and expectations of out-patient nephrologists on CDSS. Despite the current lack of knowledge on CDSS, the willingness to integrate CDSS into daily patient care, and the need for adverse event prediction algorithms was high.
... Veri gizliliğinin yönetimi veya internet yoluyla uygun hasta iletişimini geliştirmek için dijital yeterlilikler, dokümantasyona harcanan zamanın artması, elektronik sağlık kayıtlarını doldurma zorlukları ve meslektaşlar arasında teknik destek gibi pek çok uygulama, daha önce sağlık profesyonellerinin çalışma kapsamı dışında olan uygulamalardan bazılarıdır (4)(5)(6)(7)(8)(9) . Sağlık teknolojileri (ST) ile ilgili umut vaat eden pek çok şey olsa da bununla ilişkili olarak yüksek düzeyde stres yaşadıklarını bildiren bakım sağlayıcılar üzerinde teknolojik bir yük oluşturabilir (10) . Yapılan araştırmalar, ST'nin kullanımının sağlık hizmetlerinde çalışan kişilerin %73'e kadarında strese neden olabileceğini ve %40'a kadarının orta ile yüksek düzeyde stres yaşadığını göstermiştir (11) . ...
... Berente et al. (2019) suggest that understanding the interplay of multiple logics and stakeholders is crucial for managing user resistance in complex IT projects. Ferneley and Sobreperez (2006), as well as Bhattacherjee and Hikmet (2007) both demonstrate the role of social influence and users' professional context in shaping resistance and non-use. Finally, Kim and Kankanhalli (2009) suggest that users may resist new IT due to a desire to maintain their current situation or "the status quo", whilst Lee and Joshi (2017) elaborate further so as to include cognitive biases. ...
This paper problematizes the literature on the non-use of algorithmic decision-making systems (ADMS), commonly examined as algorithm aversion. Whilst prior literature attributes algorithm aversion primarily to human bias and irrationality, assuming utility-based evaluations, we argue that it may also stem from values-based evaluations of technology, which are overlooked. Through an integrated ethical analysis, drawing upon the "big three" ethical theories of consequentialism, deontology, and virtue ethics, we examine implicit normative judgments within the algorithm aversion literature. Consequently, we positively reframe algorithm aversion as a potentially principled resistance to ADMS, expanding prior views of the phenomenon. We argue that such resistance may be constructive and lead to a better alignment of ADMS with societal needs and values. Thus, we call on IS scholars to explore this phenomenon as an ethical and sociotechnical issue, rather than as a costly problem to be mitigated, as prior literature might suggest.
Cross-sectional studies of attitude-behavior relationships are vulnerable to the inflation of correlations by common method variance (CMV). Here, a model is presented that allows partial correlation analysis to adjust the observed correlations for CMV contamination and determine if conclusions about the statistical and practical significance of a predictor have been influenced by the presence of CMV. This method also suggests procedures for designing questionnaires to increase the precision of this adjustment.
Provides a nontechnical introduction to the partial least squares (PLS) approach. As a logical base for comparison, the PLS approach for structural path estimation is contrasted to the covariance-based approach. In so doing, a set of considerations are then provided with the goal of helping the reader understand the conditions under which it might be reasonable or even more appropriate to employ this technique. This chapter builds up from various simple 2 latent variable models to a more complex one. The formal PLS model is provided along with a discussion of the properties of its estimates. An empirical example is provided as a basis for highlighting the various analytic considerations when using PLS and the set of tests that one can employ is assessing the validity of a PLS-based model. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
In this article I review studies of resistance to change and advocate new research based on a reconceptualization of individual responses to change as multidimensional attitudes. A challenging question for research and practice arises: How can we balance the organizational need to foster ambivalent attitudes toward change and the individual need to minimize the potentially debilitating effects of ambivalence? I conclude by highlighting the importance of examining the evolution of employee responses to change over time and the need to understand responses to change proposals that emerge from bottom-up, egalitarian change processes.
Presents a theory of norms and normality and applies the theory to phenomena of emotional responses, social judgment, and conversations about causes. Norms are assumed to be constructed ad hoc by recruiting specific representations. Category norms are derived by recruiting exemplars. Specific objects or events generate their own norms by retrieval of similar experiences stored in memory or by construction of counterfactual alternatives. The normality of a stimulus is evaluated by comparing it with the norms that it evokes after the fact, rather than to precomputed expectations. Norm theory is applied in analyses of the enhanced emotional response to events that have abnormal causes, of the generation of predictions and inferences from observations of behavior, and of the role of norms in causal questions and answers. (3 p ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
: In 1988 the University of Virginia Medical Center began implementation of a medical information system based on mandatory physician order entry. The implementation process was much more difficult than expected. The program experienced considerable delays, and cost much more than was originally estimated. Although there were some legitimate questions concerning the user-friendliness of the new technology, these were less significant than the cultural and behavioral problems encountered. The new system challenged basic institutional assumptions; it disturbed traditional patterns of conduct and forced people to modify established practice routines. Real progress toward the integration of the system into the center's operational culture occurred only after a senior management team representing important sectors of the hospital staff and administration began meeting regularly to address the institution-wide issues that had been raised. The author describes the problems that occurred and the organizational behaviors on which they were based, analyzes the lessons learned, documents the progress that has been achieved, and outlines the challenges that remain. The center's experience provides insight into the issue of technology-driven organizational transformation in academic medical centers. Recommendations for successful introduction of similar agents of institutional change are presented. Academic Medicine 68(1993):20-25.
This article proposes an attributional explanation for individual resistance (or acceptance of) information technology. The focus of the article is on the dynamic process of how individuals make attributions for failed as well as successful experiences with information technology and how this process influences individual resistance of new or changing information technologies. Procedures for decreasing individual resistance to (and, hence, increasing acceptance and use of) information technologies are suggested.
This article proposes an attributional explanation for individual resistance or acceptance of information technology. The focus of the article is on the dynamic process of how individuals make attributions for failed as well as successful experiences with information technology and how this process influences individual resistance of new or changing information technologies. Procedures for decreasing individual resistance to and, hence, increasing acceptance and use of information technologies are suggested.