Towards understanding healthcare professionals’ adoption and use of technologies in clinical practice: using Q-methodology and models of technology acceptance

Ladan, Muhammad Awwal; Wharrad, Heather; Windle, Richard

doi:10.14236/jhi.v25i1.965

Cited by 19 publications

(24 citation statements)

References 52 publications

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“…Some of the previous studies utilising the Q method related to health systems software platforms focused on e health (Banna et al, 2010), health professional adaption and use of technologies in clinical practice (Ladan et al, 2018) and the definition and utility of clinical health research (Kim & Bates, 2011). The present study contributes to the available literature through the evaluation of stakeholders (technical development teams, end users) perspectives at critical time points during the MIDAS project.…”

Section: Resultsmentioning

confidence: 93%

Q-Method Evaluation of a European Health Data Analytic End User Framework

et al. 2019

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. AbstractMIDAS (Meaningful Integration of Data Analytics and Services) project is developing a big data platform to facilitate the utilisation of a wide range of health and social care data to support better policy making. Our aim is to explore the use of Qmethodology as part of the evaluation of the implementation of the MIDAS project. Q-methodology is used to identify perspectives and viewpoints on a particular topic. In our case, we defined a concourse of statements relevant to project implementation and goals, by working from a logic model previously developed for the evaluation, and structured interviews with project participants. A 36-item concourse was delivered to participants, using the HTMLQ system. Analysis was done in the qmethod package. Participants had a range of professional backgrounds, and a range of roles in the project, including developers, end-users, policy staff, and health professionals. The qsort is carried out at 14 months into the project, a few months before the intended first release of the software being developed. Sixteen people took part, 6 developers, 5 managers, 2 health professionals and 3 others. Three factors (distinct perspectives) were identified in the data. These were tentatively labelled 'Technical optimism', 'Enduser focus' and 'End-user optimism'. These loaded well onto individuals, and there were few consensus statements. Analysis of these factors loaded well onto individuals with a significant number of consensus statements identified.

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Section: Resultsmentioning

confidence: 93%

Q-Method Evaluation of a European Health Data Analytic End User Framework

et al. 2019

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“…Social influence represents the degree to which a user experiences social pressures to use technology. Facilitating conditions are the extent of a user's perceptions regarding whether the organization facilitates circumstances to use technology [23,26]. The variables performance expectancy and effort expectancy of the UTAUT are equal to the variables perceived usefulness and perceived ease of use of the TAM [27,28].…”

Section: Acceptance Theories and Modelsmentioning

confidence: 99%

“…Objective user data might lead to insights into both use and the relationship between affective and behavioral responses [10,22]. Besides, most studies on technology acceptance focus on a quantitative design [23], and in order to get a better understanding of actual and employees' opinions of technology use, this study also uses semi-structured interviews. This study is relevant practically, since findings are translatable into applications that improve technology use.…”

Section: Introductionmentioning

confidence: 99%

Advanced Technology Use by Care Professionals

Brandsma

Stoffers

Schrijver

2020

IJERPH

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Advanced technology is a primary solution for the shortage of care professionals and increasing demand for care, and thus acceptance of such technology is paramount. This study investigates factors that increase use of advanced technology during elderly care, focusing on current use of advanced technology, factors that influence its use, and care professionals’ experiences with the use. This study uses a mixed-method design. Logfiles were used (longitudinal design) to determine current use of advanced technology, questionnaires assessed which factors increase such use, and in-depth interviews were administered to retrieve care professionals’ experiences. Findings suggest that 73% of care professionals use advanced technology, such as camera monitoring, and consult clients’ records electronically. Six of nine hypotheses tested in this study were supported, with correlations strongest between performance expectancy and attitudes toward use, attitudes toward use and satisfaction, and effort expectancy and performance expectancy. Suggested improvements for advanced technology include expanding client information, adding report functionality, solving log-in problems, and increasing speed. Moreover, the quickest way to increase acceptance is by improving performance expectancy. Care professionals scored performance expectancy of advanced technology lowest, though it had the strongest effect on attitudes toward the technology.

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“…Don’t let mention of Q-methodologies, technology acceptance model (TAM) or unified theory of acceptance and use of technology (UTAUT) put you off an excellent article by Ladan et al 9. To start with let me give each of the above a brief explanation:

Q-methodology (also called Q-sort) is the systematic study of participant viewpoints.

…”

Section: A Good Theoretical Basis Will Strengthen Our Discipline!mentioning

confidence: 99%

“…Jump to Figures 1 and 2 in the paper by Ladan et al 9 to see how TAM and UTAUT are set out diagrammatically; then Figure 4, where they draw things together. As informatics develops as a discipline, we need to strengthen our theoretical underpinnings and define our core theory.…”

Section: A Good Theoretical Basis Will Strengthen Our Discipline!mentioning

confidence: 99%

In this issue – patient risks are ignored at organisation level

Lusignan

2018

BMJ Health Care Inform

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Towards understanding healthcare professionals’ adoption and use of technologies in clinical practice: using Q-methodology and models of technology acceptance

Cited by 19 publications

References 52 publications

Q-Method Evaluation of a European Health Data Analytic End User Framework

Q-Method Evaluation of a European Health Data Analytic End User Framework

Advanced Technology Use by Care Professionals

In this issue – patient risks are ignored at organisation level

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