Content area
Aim/objective
To investigate the underlying constructs of the 29 digital adaptability competencies to identify the phenomenon's key or conceptual properties.
BackgroundA shift towards a strong and increasing presence of eHealth in future practice requires the competencies of nurses and midwives. This ability to adapt to technological evolutions is called digital adaptability. A set of 29 items representing the competencies of digital adaptability for nurses and midwives provides the first comprehensive description of this relatively new concept.
DesignCross-sectional survey with a total sample size of 557 Flemish midwives and nurses.
MethodsInternal consistency and construct validity were established using Cronbach's alpha, exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA).
ResultsEFA revealed two factors: 'me and the digital world' (17 items) and 'me, the digital world, and my patient' (12 items). CFA tested the model and showed a good model-fit. Strong internal consistency was observed.
ConclusionsTwo factors were identified. The first, ‘me & the digital world,’ is task-oriented and focuses on nurses/midwives’ personal use of technology. The second, ‘me, the digital world, and my patient,’ is patient-centered and focuses on nurses' and midwives’ use of technology while interacting with their patients during care provision.
Electronic healthcare services, also known as eHealth, is defined as the use of information and communication technologies (ICT) in health and healthcare ( WHO, 2016). eHealth is dynamic and rapidly evolving in current healthcare services ( Aluoch, 2016). The use of technology in healthcare is not new. Before the COVID-19 pandemic, the care delivered through eHealth was estimated to grow at an annual rate of 16.8 %. However, during the pandemic, it increased to 80 % ( Rutledge et al., 2021). While the development and deployment of eHealth have continued at a rapid pace, healthcare professionals are expected to keep up and adapt to this digital evolution ( Honey and Wright, 2018). A study, using structuration theory and intuitive logics scenario planning methods, showed a shift towards a strong and increasing presence of eHealth in future midwifery practice ( Bleijenbergh et al., 2022). The extensive eHealth development provides new contexts for care, with both opportunities and new challenges ( Ali et al., 2022). Technological innovations are an opportunity to address the challenges of modern health (i.e. an ageing population and the high prevalence of chronic diseases), but only if accompanied by a behavioral transformation and the engagement of healthcare professionals ( Barchielli et al., 2021; Puckett, 2020; van der Zijpp et al., 2018).
Nurses and midwives represent a large group of healthcare professionals and are regarded as important actors in the successful implementation of eHealth. Essentially, their work has a practical hands-on focus in direct contact with patients, instead of a digital one ( Honey and Wright, 2018; Ten Hoeve et al., 2017). The digital health transformation has created demands for nurses and midwives to acquire additional skills and competencies. This enables them to engage in eHealth safely and effectively and assist patients in adapting to digital health ( Ali et al., 2022). Moreover, professionals would benefit from a learning process on how to use and organize eHealth within healthcare – adapting to digital health. A digital adaptable healthcare professional is flexible between (in)direct patient care and the (simultaneous) use of technology and will consult eHealth as a resource to answer problems and provide care via eHealth, to support or improve care ( Bleijenbergh et al., 2023; Puckett, 2020).
Training nurses and midwives on how to be more digitally adaptable might encourage them to engage in eHealth ( Risling, 2017; van Houwelingen et al., 2016). To educate these professionals, it is important to critically assess the competencies required to be a digital adaptable healthcare professional ( Ahonen et al., 2016; Sharma and Clarke, 2014). A modified three-round e-Delphi study on digital adaptability used expert consensus to identify the necessary competencies to be(come) a digital adaptable healthcare professional, resulting in a set of items representing the competencies of digital adaptability for nurses and midwives. This set contains 29 practice-oriented items providing the first comprehensive description of the relatively new competencies of digital adaptability ( Bleijenbergh et al., 2023).
The Belgian eHealth Monitor and the USA National League for Nursing issued a call for further action in preparing (student) healthcare professionals for a technological healthcare future ( Bleijenbergh et al., 2023; Risling, 2017; Verhellen et al., 2020). These 29 items are therefore an informative series of skills and other abilities essential to be(come) a digital adaptable healthcare professional. Examining the conceptual structure of digital adaptability makes explicit what properties are relevant, as these form the foundational cognitive operationalization in practice and the education of future nurses and midwives. This study therefore aimed to investigate the underlying constructs between the 29 practice-orientated items of the competencies of digital adaptability.
2 Methods2.1 Design
A survey among a sample of Flemish (Dutch speaking part of Belgium) nurses and midwives was conducted.
2.1.1 Set of itemsThe set of the 29 practice-oriented items, originating from an earlier modified e-Delphi study ( Bleijenbergh et al., 2023), was distributed to midwives and nurses. The 29 items representing actual performance of digital adaptability were measured by requesting subjects to consider ‘I do this’, with ratings on a five-point scale: ‘Never’ (0), ‘Rarely’ (1), ‘Occasionally’ (2), ‘Frequently’ (3) to ‘Always’ (4).
2.1.2 Participants and samplingMidwives and nurses in primary-, secondary- and tertiary healthcare settings in Belgium were considered eligible and were recruited using convenience sampling. Participants had to be proficient in the Dutch language. To inform nurses and midwives about the study, the researchers' network was used to contact 59 primary care practices, midwifery practices, hospitals, nursing and midwifery organizations/associations and residential care centers about the study by e-mail and via an online poster (including the link to the study). In addition, the announcement of the study and the invitation to participate were distributed via social media platforms such as Facebook© and Instagram©, to allow snowballing. The questionnaire was widely distributed to minimize sampling bias. Data was collected from February 2021 to June 2022, using the LimeSurvey© online survey tool.
The sample size was calculated using the subject-to-variable ratio of a minimum 10:1 ( Arrindell, J., 1985; Field, 2013). The calculation showed a sample of a minimum of 290 participants (10 ×29 items) was needed, to allow meaningful statistical inferences.
2.1.3 AnalysisNo missing data techniques were used. Normality of the distribution was checked using the Shapiro-Wilk test. Internal consistency was calculated using Cronbach's alpha (α). An α≥ 0.70 was considered acceptable ( Field, 2013). Construct validity was calculated with Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) ( Swisher et al., 2004). The sample size was tested with the Kaiser-Meyer-Olkin (KMO) and Barlett's test of sphericity. A KMO of ≥ 0.80 and a Barlett's test with p < 0.05 were considered acceptable ( Field, 2013). EFA was performed using Principal Axis Factoring (PAF) with a Varimax rotation ( Smyth and Johnson, s.d.). Factor extraction was performed based on the Scree plot and Eigenvalues ( Field, 2013). The factor loading of each item had to be at least 0.40 ( Costello and Osborne, 2005; Field, 2013). CFA was conducted to determine the goodness-of-fit ( Köberich and Farin, 2015). The model-of-fit was determined based on the Chi-square ( X 2), Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), Tucker-Lewis Index (TLI) and the Standardized Root Mean Squared Residual (SRMSR). We regarded CMIN/df 3–5, GFI > 0.90, CFI > 0.90, TLI > 0.90, SRMR < 0.08 and RMSEA < 0.08 as a good fit. Modification Indices (MI) have optimized the goodness-of-fit. If the MI was > 20.00, covariances were applied ( van Geel and Verboon, 2015). Statistical Package for the Social Sciences (SPSS)© version 27.0 and Analysis of Moment Structures (AMOS)© version 26.0. were used to analyze the data.
2.1.4 EthicsThe study was approved by the Ethical Advisory Committee on Social and Human Sciences of the University of Antwerp on September 28, 2020 (SHW_20_74). The questionnaire included a privacy note explaining confidentiality, anonymity, and data handling. Participation was voluntary, and informed consent was obtained via box ticking before the questionnaire could be completed.
3 Results3.1 Participants
The total sample included 557 Flemish midwives and nurses. Most of the participants identified as female, worked as a nurse in secondary care and had a bachelor’s degree. Details of the sample are presented in Table 1.
3.2 Construct validity3.2.1 Exploratory factor analysis
PAF showed a KMO of 0.96 and Bartlett’s test was statistically significant (p < 0.001). PAF and Varimax rotation showed three factors with an Eigenvalue of ≥ 1.00, with a total cumulative explanatory variance of 60.71 %. The Eigenvalues are presented in a Scree plot (see Fig. 1). Three factors showed an eigenvalue ≥ 1.00. The inflection point of the curve was observed at factor 3, showing a two-dimensional factor predominating the factor loadings. Table 2 shows the factor load for each item for the two factors “me & the digital world” and “me, the digital world & my patient”. After extraction, a two-factor model was obtained which explained 58.03 % of the total variance.
3.2.2 Confirmatory factor analysisCFA was computed to test the model ( Swisher et al., 2004). As part of CFA, factor loadings were assessed for each item, no items were removed due to low factor loadings (<0.05). The model-fit measures were used to assess the model’s overall goodness of fit (CMIN/df, GFI, CFI, TLI, SRMR and RMSEA) and all values were within their respective common acceptance level ( van Geel and Verboon, 2015), as shown in Table 3. The two-factor model (“me, digital world” – “me, digital world & my patient”) yielded a good fit and is shown in Fig. 2.
3.3 Internal consistencyThe internal consistency was α= 0.964 and for the two factors: “me & the digital world” α= 0.959 and “me, the digital world & my patient” α= 0.926 ( Table 4).
4 DiscussionThis study aimed to investigate the underlying key constructs of 29 practice-oriented items, which are the foundation of the competencies of digital adaptability as identified by Bleijenbergh et al. (2023). This study is among the first to provide a detailed description of the competencies required of a digitally adaptable healthcare professional to engage with the healthcare of the future. The abstract concept of digital adaptability is given greater shape in this study, which is unique in shedding light on the profile of the nurse and midwife of the future.
Our results showed that digital adaptability consists of two major factors: “Me & the digital world” and “Me, the digital world & my patient”, with a strong internal consistency and a good model-of-fit. Both exploratory and confirmatory factor analysis were used to validate the constructs. The specific indices of CFA indicate a strong model fit, reinforcing the robustness of the findings. The strong internal consistency and the rigorous statistical methods ensure the reliability and validity of the findings. Our study results echo the findings of the development of DigiHealthCom, a questionnaire to measure the dimensions of digital health competence among various healthcare professionals, also showing a two-dimensional construct of a more functional and a more human-centered dimension in digital healthcare ( Jarva et al., 2023). Peiró and Martínez-Tur (2022) also recognize a two-dimensional structure of digital adaptability: digital competences and non-digital competences, including relational competencies. Both studies argue that digital and non-digital skills need to co-exist as they do not exist in separate vacuums ( Jarva et al., 2023; Peiró and Martínez-Tur, 2022). Our study shows to connect digital proficiency with the non-digital human-centered dimension through digital adaptability – being flexible between (in)direct patient care and the (simultaneous) use of technology ( Bleijenbergh et al., 2023), digital adaptability being an added competence of the healthcare professional using digital healthcare providing synergy between digital and non-digital competences.
Factor one, “Me & the digital world”, consists of 17 items of the competencies of digital adaptability. These items are organizational and task oriented. It also includes items about intrapersonal use of eHealth and basic computer competencies. Barakat et al. (2013) identified that without basic computer skills, healthcare professionals are likely to continue to rely on the traditional mechanisms of observation and monitoring, abstaining from being or becoming digital adaptable. Computer competencies thus being a basic requirement for digital adaptability. Although the lack of digital proficiency is still being regarded as a barrier to digital healthcare ( Ferreira et al., 2025), the literature shows that overall healthcare professionals have above basic digital skills, specifically younger care professionals who engaged with digital tools during their studies or who graduated after the introduction of eHealth. This suggests that the factor “Me & the digital world” will become more self-evident as future healthcare professionals will be digital competent, contributing to sustaining digital adaptability ( Jarva et al., 2024). The ability of healthcare professionals to use technology ensures that patients receive patient-centered care when technology solutions are used in the delivery of care. ( Konttila et al., 2019). The factor, “Me & the digital world” is intrapersonal and focuses on the nurses/midwives’ own use of technology, coping with and managing eHealth. Factor one, “Me & the digital world”, does not refer to communicating or interacting with patients via eHealth. These dimensions of digital adaptability, known as patient-centric digital communication and digital solutions, have been studied by Jarva et al. (2023). The constant use of technology may act as a barrier between the nurses or midwives and their patients ( Ali et al., 2022).
The second factor “Me, the digital world & my patient” consists of 12 items of the competencies of digital adaptability, being more patient-centered and refer to the skill to simultaneously interact with technology and patients. This factor focuses on nurses and midwives’ use of technology while interacting with their patients during care performance, including ethical-related items. This factor is recognized as a form of human-centered care and self-reports of healthcare professionals show this competence to be low and should be enhanced in education ( Jarva et al., 2024). A healthcare professional needs to act professionally with respect for the patient when using eHealth and must also reflect on the norms and values that are compromised when technology is deployed ( Daes et al., 2020). Although human interaction cannot be replaced by eHealth, and it is important to maintain the ability to provide humanistic and caring practices, studies have shown that being digitally adaptable has great benefits for both healthcare professionals and their patients. If nurses and midwives remain engaged and connected with their patients, using eHealth and understand that eHealth tools are there to support rather than hinder the care they provide, the use of technology can help strengthen relationships and communication between patients and nurses or midwives, empower the patient's sense of wellbeing, and support health professionals and patients to make better decisions. This can have a significant impact on how the patient experiences the potential benefits of the digital solution. ( Ali et al., 2022; Bleijenbergh et al., 2023; ElKefi and Asan, 2021; Mikkonen et al., 2023).
4.1 LimitationsWe used convenience sampling via social media. While this approach allowed us to reach a large number of participants efficiently, it may have introduced selection bias. Individuals who engage with social media more frequently are potentially more digitally adaptable ( Bethlehem, 2010). Another limitation of this study is the reliance on self-reported data. While self-report measures are a common and practical method for data collection, they are subject to biases such as social desirability bias and recall bias. Participants may overestimate or underestimate certain behaviors or attitudes, which could affect the accuracy of our findings ( Kalimeri et al., 2020).
All items had a factor load above 0.40, except for the item “I have the skills to communicate via eHealth with persons seeking care”, which has a factor load of 0.354. We assigned this item to factor two, as it fits better with “me, the digital world & my patient”. Had we assigned the item to factor one, we would have had a higher factor load, presumably a higher explanatory total variance of the model and a better model-of-fit. The questionnaire was distributed among midwives and nurses in primary-, secondary- and tertiary healthcare settings in Belgium and via social media platforms, using convenience sampling which may have introduced sampling bias, as respondents with outspoken ideas regarding eHealth may have been more inclined to participate. The characteristics of the sample do not fully correspond to the Belgian population of nurses and midwives. The sample included a greater proportion of nurses than midwives, which may limit the generalizability of the findings to midwifery. However, in percentage terms, the sample included a greater proportion of midwives than the ratio in the field. We also included a different male-to-female ratio than in the actual population of nurses (15 % male vs. 85 % female) and midwives (1 % male vs. 99 % female) ( Belgium, 2022a, b).
Because the data was collected from a sample of Flemish nurses and midwives, which may limit the generalizability of the findings to other countries or settings. However, studies from other countries have identified similar challenges regarding the utilization of eHealth by healthcare professionals ( Barchielli et al., 2021; Puckett, 2020; van der Zijpp et al., 2018). Therefore, it can be assumed that the two factors identified in our study are transferable to healthcare contexts outside of Flanders.
We are aware of the rapid evolution of technology in healthcare, which may affect the relevance of the identified constructs over time. We suggest that ongoing research is needed to update and refine the concept of digital adaptability as new technologies emerge.
4.2 Practical implicationsThe enhancement of sustainability in healthcare systems and the cultivation of digital competencies are poised to elevate the standards of practice among nurses. This, in turn, is expected to engender an improvement in the quality of health services, thereby aligning with the Sustainable Development Goals (SDGs) ( Rosa et al., 2019). The digital health transformation created demands for nurses and midwives to acquire new skills and competencies enabling the safe use of eHealth and assisting patients in adapting to digital health ( Ali et al., 2022). Evidence showed that healthcare professionals lack digital adaptability competencies to motivate and advise patients through eHealth ( Kujala et al., 2018), to communicate through patient portals ( Laukka et al., 2020) or to express, and preserve compassion for patients when they use digital health technologies ( Ali et al., 2022). Therefore, systematic and individually designed education seems required ( Nazeha et al., 2020). Digital proficiency and digital healthcare skills should not only be included in undergraduate programs but should also be part of continuous professional development to empower healthcare professionals ( Ferreira et al., 2025). Our findings enhance the importance of educating and professional development of the current and next generation of nurses and midwives about digital adaptability competencies early in their nursing programs is critically important so that they are adequately prepared when they join the workforce ( Ali et al., 2022). The two factors can serve as conceptual elements of digital adaptability to shape the education of (student) healthcare professionals as the Belgian eHealth Monitor and the USA National League for Nursing issued a call for further action in preparing (student) healthcare professionals for a technological healthcare future ( Risling, 2017; Verhellen et al., 2020). Nursing and midwifery education has always required competencies essential to supporting sound technology-based practice such as clinical knowledge and skills, interprofessional communication, critical thinking, and problem-solving abilities ( Bleijenbergh et al., 2023; Risling, 2017), aligning with our two-factor model. Moreover, the use of computers and smart devices (phones or tablets), electronic communication and software to create and share professional documents are likely to be familiar to future healthcare professionals, as the majority are part of Generation Z and have grown up using technology. Therefore, a technology-infused healthcare future may not require a complete transformation of healthcare education. Whether the focus in education and professional development needs to be on ‘Me, the digital world & my patient’, on ‘Me & the digital world’ or both factors need to be explored in further research. The items of the two factors can serve to inform the content or parameters of the undergraduate education program or workforce development programs ( Brunner et al., 2018).
5 ConclusionAfter investigating the underlying constructs between 29 practice-orientated items of the competencies of digital adaptability, two major factors: ‘Me & the digital world’ and ‘Me, the digital world & my patient’ were identified with a strong internal consistency and a good model-of-fit. The factors are distinct as the first factor focuses on the nurses/midwives’ personal use of technology, while the second factor has a patient-centered focus on nurses and midwives’ use of technology while interacting with their patient and during care performance. The abstract concept of digital adaptability is given greater shape in this study, which is unique in shedding light on the profile of the nurse and midwife of the future. Because the current and the new generation of nurses and midwives are very likely to be familiar with technology, it is possible that education needs to focus more on the patient-centered factor, but this needs to be explored in further research.
CRediT authorship contribution statementRoxanne Bleijenbergh: Conceptualization, Formal analysis, Methodology, Writing – original draft. Eveline Mestdagh: Conceptualization, Writing – review & editing. Bart Van Rompaey: Conceptualization, Writing – review & editing. Olaf Timmermans: Conceptualization, Writing – review & editing. Yvonne J. Kuipers: Conceptualization, Methodology, Writing – review & editing, Supervision.
Declaration of Competing InterestNone
AcknowledgmentsNo acknowledgments are stated.
Ethical approvalThe study was approved by the Ethical Advisory Committee on Social and Human Sciences of the University of Antwerp (SHW_20_74, 9/28/2020).
Funding sourcesThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
| | ||
| | | 88.50 (493)
11.00 (61) 0.50 (3) |
| | | 40.04 (12.41) |
| | | 14.75 (12.66) |
| | ||
| | | 32.30 (180)
67.70 (277) |
| | ||
| | | 42.90 (239)
46.10 (257) 11.00 (61) |
| | ||
| | | 13.50 (75)
69.70 (388) 16.00 (89) 0.90 (5) |
| | ||
| Me & the digital world | Me, the digital world & my patient | |
| | | |
| I show interest in eHealth. | | 0.308 |
| I conduct myself in a professional manner in the use of eHealth. | | 0.281 |
| I critically evaluate the reliability of data collected with eHealth. | | 0.405 |
| I communicate in a professional manner with other healthcare providers via eHealth. | | 0.434 |
| I use eHealth for storing information. | | 0.264 |
| I use eHealth in my professional routine. | | 0.257 |
| I use eHealth as a tool to support healthcare. | | 0.282 |
| I use eHealth as a tool to improve healthcare. | | 0.314 |
| I am able to use the software/programmes to access patient information. | | 0.178 |
| I am competent in clinical reasoning using eHealth. | | 0.310 |
| I feel confident in using eHealth to make healthcare related decisions. | | 0.349 |
| I feel that using eHealth in most situations improves the quality of life of the person seeking care. | | 0.325 |
| I have the skills to communicate via eHealth with healthcare providers. | | 0.354 |
| I have the basic skills for using technology, such as a computer or a smartphone. | | 0.117 |
| I am aware of the benefits of eHealth. | | 0.332 |
| I know where to gather reliable information obtained with eHealth. | | 0.347 |
| I understand the impact of eHealth on improving the quality of healthcare. | | 0.362 |
| I discuss the advantages and disadvantages of eHealth with the person seeking care. | 0.184 | |
| I support the person seeking care in the use of eHealth. | 0.292 | |
| I encourage the person seeking care to use eHealth. | 0.243 | |
| I provide health advice using technological evidence-based healthcare tools. | 0.273 | |
| I communicate in a professional way with persons seeking care through eHealth. | 0.550 | |
| I present the information obtained via eHealth in an understandable way to the person seeking care. | 0.386 | |
| I adapt eHealth to the needs of the person seeking care. | 0.376 | |
| I actively and regularly ask for the consent of persons seeking care about access to personal data. | 0.172 | |
| I recognize ethical dilemmas that exist between upholding ethical principles and integrating technology into healthcare. | 0.280 | |
| I discuss ethical dilemmas that exist between upholding ethical principles and integrating technology into healthcare with the person seeking care. | 0.178 | |
| I am kept up with developments in healthcare technology through learning. | 0.365 | |
| I have the skills to communicate via eHealth with persons seeking care. | 0.693 | |
| | | |
| | Insignificant | < 0.001 |
| CMIN/df | < 5 | 3.088 |
| GFI | > 0.90 | 0.876 |
| CFI | > 0.90 | 0.944 |
| TLI | > 0.90 | 0.936 |
| SRMR | < 0.08 | 0.0478 |
| RMSEA | < 0.08 | 0.061 |
| | |||
| | | | |
| I show interest in eHealth. | 0.625 | I discuss the advantages and disadvantages of eHealth with the person seeking care. | 0.745 |
| I conduct myself in a professional manner in the use of eHealth. | 0.699 | I support the person seeking care in the use of eHealth. | 0.741 |
| I critically evaluate the reliability of data collected with eHealth. | 0.578 | I encourage the person seeking care to use eHealth. | 0.763 |
| I communicate in a professional manner with other healthcare providers via eHealth. | 0.550 | I provide health advice using technological evidence-based healthcare tools. | 0.693 |
| I use eHealth for storing information. | 0.746 | I communicate in a professional way with persons seeking care through eHealth. | 0.434 |
| I use eHealth in my professional routine. | 0.761 | I present the information obtained via eHealth in an understandable way to the person seeking care. | 0.660 |
| I use eHealth as a tool to support healthcare. | 0.773 | I adapt eHealth to the needs of the person seeking care. | 0.684 |
| I use eHealth as a tool to improve healthcare. | 0.765 | I actively and regularly ask for the consent of persons seeking care about access to personal data. | 0.567 |
| I am able to use the software/programs to access patient information. | 0.770 | I recognize ethical dilemmas that exist between upholding ethical principles and integrating technology into healthcare. | 0.659 |
| I am competent in clinical reasoning using eHealth. | 0.773 | I discuss ethical dilemmas that exist between upholding ethical principles and integrating technology into healthcare with the person seeking care. | 0.748 |
| I feel confident in using eHealth to make healthcare related decisions. | 0.774 | I am kept up with developments in healthcare technology through learning. | 0.550 |
| I feel that using eHealth in most situations improves the quality of life of the person seeking care. | 0.705 | I have the skills to communicate via eHealth with persons seeking care. | 0.354 |
| I have the skills to communicate via eHealth with healthcare providers. | 0.693 | ||
| I have the basic skills for using technology, such as a computer or a smartphone. | 0.691 | ||
| I am aware of the benefits of eHealth. | 0.728 | ||
| I know where to gather reliable information obtained with eHealth. | 0.726 | ||
| I understand the impact of eHealth on improving the quality of healthcare. | 0.722 | ||
©2025. Elsevier Ltd