TAM and UTAUT in healthcare
The TAM has attracted a lot of empirical and theoretical attention over the years of its existence but despite being the popular model for ICT adoption and use, it is still not seen as a healthcare specific model. Some have further argued that if used in its generic form, it may fail to capture or even contradict some unique contextual features of computerised healthcare, that is, indicating a significant gap in knowledge.14,17,41 Many studies have attempted to utilise the TAM in explaining or predicting ICT adoption in healthcare by applying it to specific healthcare applications20,22,26,42 or modifying the model to test new variables or hypotheses.6,18,20,43
Aggelidis and Chatzoglou42 used a modified TAM to examine health information systems (HIS) among HIS users by testing 23 hypotheses within the model using structural equation modelling (SEM) as seen in Table 1. They reported that the relationships between the initial TAM constructs hold and are significant. However, despite using a quantitative approach, the researchers identified among the limitations that a small and disproportionate sample was used, and that also emphasis was more on the information system (rather than the views of the users). Also, Gagnon et al.20 used a modified TAM to examine factors that influence the decision of HCPs’ use of an e-health resource. They identified a response rate of 39.7% and using logistic regression analysis, they reported that the TAM is a good model for predicting HCPs’ intention to use an e-health resource. Also, the researchers acknowledged that they adopted a questionnaire that has already been used in another TAM study and has not undergone test–retest reliability as consistent with quantitative studies. Emphasis within the study was also on the e-health resource and not the views of the users within the health sector. This study was similar to the study by Chismar and Wiley-Patton17 which also used a regression analysis to examine physicians’ acceptance of technology using the TAM modified by Venkatesh and Davis30 and adopting the questionnaire associated with the model. They have also identified as a limitation to their study, a small sample was used. Despite the stated limitation, they have identified that the relationship between the constructs within the TAM they used holds except for PEOU and subjective norm. In similar TAM related research, Bennani and Oumlil9 explored factors that influence IT acceptance by nurses. They modified the initial TAM model by adding two new constructs: trust and image. They tested 11 hypotheses using quantitative testing like those identified previously and used SEM. They also reported that the relationships within the constructs for TAM hold except for PEOU and the ‘trust’ construct they added.
Like studies involving the TAM, UTAUT research in healthcare mainly used quantitative approaches. Most researchers21,39,44 tested the empirical strengths of the model in their studies.
Kijsanayotin et al.39 employed a modified UTAUT to explore factors influencing health IT (HIT) adoption in community health centres in Thailand. They employed quantitative methods using SEM like in previously mentioned TAM studies, and their emphasis was on the HIT and model rather than the views of the participants on the factors influencing their adoption of HIT. Similarly, Sharifian et al.44 also used the UTAUT to identify factors influencing nurses’ acceptance of e-health resources in Iran again using a quantitative approach to identify the factors which influence e-health resource acceptance by testing the strength of the relationship within the model. The personal views of the participants regarding the e-health acceptance were not explored. Venkatesh et al.21 also utilised the UTAUT to explore an e-health resource adoption and use among physicians. SEM was used to predict the strength of the relationship within the model and although they established a relationship with the constructs with an explained variance of 44% this compared to 76% which was established when using the model in a previous study outside healthcare. However, they justified that the UTAUT should be integrated with other theories to enrich it when adopting it to the healthcare context.
Therefore, TAM and UTAUT have been the most consistently used models in exploring ICT within healthcare due to their reliable and validated robustness in technology adoption/acceptance and use literature. Despite this, however, more emphasis has been on establishing the relationships within the constructs of both models rather than the subjective views of the users’ interaction with the e-health resources. Some researchers11,45,46 suggested a move from the traditional quantitative methodology use in technology acceptance and use to a mixed approach. They argued that by using mixed methods in such studies, an understanding of the context will develop through the opinions of people who use such e-health resources. Others such as Venkatesh et al.21 have suggested using more than one model to explore factors that influence technology acceptance and use among HCPs. One such approach is Q-methodology which forms the basis of this paper. The paper aims to use both TAM and UTAUT to develop a comprehensive set of statements that reflect the views of HCPs on adoption and use technologies in clinical practice in SSA.
Q-methodology
Ami-Narh and Williams11 used a mixed method approach called Q-methodology48–50 to understand participants’ perspectives on e-health. This methodology has been described as the scientific study of subjectivity.51–53 It was developed by William Stephenson to explore individuals’ perception relating to an issue of discourse.54,55 This methodology allows participants to interpret items relating to an issue based on their own practice.51,55–57 It combines both qualitative and quantitative techniques. Each participant completes a sorting exercise where he/she will rank order a set of items in the form of statements drawn from the discourse (what is known about the topic) according to how they perceive it influences their practice. Q-methodology is less prevalent in the technology literature, where survey studies are frequently used.10,58,59
Q-methodology places emphasis on understanding the viewpoints of participants by focusing on their subjective standpoint on issues affecting them and how this standpoint is shared with other participants within the same study environment. Barker55 identified that the traditional methods of studying subjectivities such as focus group discussions and interviews or quantitative surveys pose difficulties in data reduction to a meaningful account. She also argued that using surveys presents the viewpoints of the participants into a homogenous whole rather than shared or individual perspectives.
Thus, the strength of Q-methodology lies in its approach to the study of subjectivity and its limitation is evident in its non-generalisable findings. However, Thomas and Baas60 suggested that the concept generated from a Q-study could be used beyond the population of study.
This will be the first time Q-methodology has been employed in conjunction with the models of technology acceptance to explore HCPs’ adoption and use of e-health within clinical practice.