Factors influencing the willingness to adopt telerehabilitation among rehabilitation professionals in Austria and Germany: a survey comparing data before and during COVID-19

Abstract Purpose To investigate determinants of willingness to adopt telerehabilitation, willingness of technology use, core affect regarding using telerehabilitation, and digital competencies in rehabilitation professionals in Austria and Germany before and during the COVID-19 pandemic. Materials and methods A cross-sectional paper-based and online survey was conducted before and during COVID-19, respectively, with three cohorts of rehabilitation professionals. Outcomes were the willingness to adopt telerehabilitation evaluated using the extended Unified Theory of Acceptance and Use of Technology; willingness of technology use using the short scale for assessing the willingness of technology use; digital competencies and core affect using the Digital Competence Framework and semantic differential, respectively. Multivariate ordinal regression analysis was performed to determine predictors. Results Included were 603 rehabilitation professionals. Analysis revealed differences between Austria and Germany and before and during the pandemic for most outcomes. German residency, the pandemic, and a higher educational level were most important predictors of higher willingness to adopt telerehabilitation, willingness of technology use, digital competencies, and positive core affect. Conclusions The pandemic increased most aspects of willingness to adopt telerehabilitation, willingness of technology use, digital competencies, and positive core affect. Results confirm that rehabilitation professionals with higher degrees are more prone to adopt innovations in healthcare.Registration: German Clinical Trials Register (DRKS00021464) IMPLICATIONS FOR REHABILITATION The willingness to adopt telerehabilitation is associated with external factors increasing the need for alternative rehabilitation delivery, such as COVID-19, and with financial facilitators, such as reimbursement. As the willingness to adopt telerehabilitation is higher among speech and language therapists and dietitians, efforts are necessary to enhance its use in physiotherapists and occupational therapists. As a higher willingness to adopt telerehabilitation was observed in younger rehabilitation professionals and those with higher education, increasing the importance of telerehabilitation in education curricula and further knowledge transfer into practice for those already working in the field seems necessary.


Introduction
Rehabilitation is an increasingly important healthcare service due to an aging global population and a rising prevalence of noncommunicable diseases [1].According to a systematic analysis for the Global Burden of Disease Study 2019 [2], at least every third person worldwide requires rehabilitation at some stage of their disease or injury.However, at present, the need for rehabilitation greatly exceeds its availability [1].There are many possible reasons which may limit patients' access to rehabilitation services, such as large geographical distances, inadequate technical resources, economic reasons, and time constraints which are mostly related to a shortage of rehabilitation professionals [3].
Technological solutions may help address this limited access to rehabilitation services.Based on rapid technological advances overall, novel technological solutions have been adopted aiming at providing rehabilitation services outside the clinical environment, i.e., telerehabilitation.Telerehabilitation is characterized by "the use of information and communication technologies to provide rehabilitation services to people remotely in their homes or other environments" [4, abstract].Owing to the identified advantages of telerehabilitation, including cost-savings, increased access to resources, and improvement in the quality of healthcare services, its effectiveness has been investigated extensively.A recent rapid review has analyzed the results of 53 systematic reviews conducted in different populations, including those with cardiorespiratory, musculoskeletal, and neurological disorders, and reported that telerehabilitation is as effective as traditional in-person rehabilitation or better than no rehabilitation [5].However, systematic reviews on the effectiveness of telerehabilitation in people with neurological disorders [6] and chronic obstructive pulmonary disease [7] have concluded that there is a lack of evidence with respect to high-quality randomised controlled trials and on determining relevant telerehabilitation features such as feedback, monitoring and decision-making.
Although telerehabilitation has been used for more than two decades, its acceptance has been reported as being relatively low among rehabilitation professionals and patients due to reasons such as complicated equipment setup, internet connection failure, and a limited range of feasible exercises [8].Except for technical barriers, a mixed-method systematic review has identified barriers to staff acceptance of telerehabilitation including a negative impact on the staff-patient relationship and staff autonomy or credibility, and low patient outcome expectations.This study further revealed facilitators to staff acceptance comprising collaboration between medical professionals within newly established multidisciplinary teams, flexible working practices, and patient risk and safety assessment [9].In-depth qualitative work has proposed strategies for increasing allied health and nursing professionals' acceptance of telerehabilitation and its sustainability, such as legitimation associated with telerehabilitation safety, effectiveness and normality, and relationship building between providers [10].Moreover, the unprecedented coronavirus pandemic (COVID-19) has boosted the popularity of telerehabilitation, given its potential as a promising alternative approach to traditional in-person clinical rehabilitation, which had been affected due to COVID-19 restrictions [11].Although telerehabilitation could be viewed as a temporary solution during the COVID-19 pandemic, its well-documented benefits will likely facilitate its continued use thereafter.
Users of telerehabilitation are the patients, their caregivers, and rehabilitation professionals [3].There is a necessity to identify the factors influencing users' acceptance of telerehabilitation since their perspectives may determine their intention to adopt telerehabilitation [3,12].Previous studies have mainly focused on the patients' perspectives and satisfaction with telerehabilitation [3], although the attitudes of rehabilitation professionals toward telerehabilitation directly impact on its actual use [12].Further research is needed, therefore, to determine the factors influencing the acceptance of telerehabilitation and technology in rehabilitation experts to inform both rehabilitation practice and research.A recent study by Rettinger et al. [13] has investigated Austrian physiotherapists' (PT), occupational and speech-language therapists' (OT, SLT) attitudes towards and perceived barriers to telerehabilitation during and before the COVID-19 lockdown using retrospective ratings.The authors found relatively high levels of telerehabilitation appreciation which improved during COVID-19, despite therapists' request for stable reimbursement policies and secure software solutions [13].Although retrospective survey questions have frequently been employed in COVID-19 studies, research has shown their limitations e.g., large variations in measurement error due to subjectivity and question complexity [14].Studies including participants' ratings of the current situation may hence yield more accurate results.
The primary aim of the present study was, therefore, to investigate the factors influencing the willingness to adopt telerehabilitation in rehabilitation professionals, and differences between Austria and Germany.Secondary aims were to explore the factors associated with positive core affect with respect to using telerehabilitation, and willingness of technology use and digital competencies.Due to the COVID-19 pandemic breakout during the initial study period, we expanded our study aims and included a comparison between the pre and during COVID-19 breakout cohorts.

Design and participants
This study was a cross-sectional survey conducted at three time points in rehabilitation experts, i.e., PTs, OTs, SLTs, dietitians, and undergraduate students in their final year, in the respective subject areas.Phase 1 was carried out in Austria from 7 January 2020 to 20 February 2020, i.e., before the outbreak of the COVID-19 pandemic.Phases 2 and 3 were performed in Austria from 2 June 2020 to 28 October 2020 and in Germany from 1 October 2020-31 March 2021, i.e., during the pandemic (Figure 1).The Checklist for Reporting Results of Internet E-Surveys (CHERRIES) [15] was used to guide this research.
Using convenience and snowball sampling, rehabilitation experts (PTs, OTs, SLTs, dietitians, late-stage students) of any gender, working in Austria or Germany, aged 20-65 years, with overall proficiency in German, were included in this survey.The sample size of this study was based on sample sizes from relevant other studies and systematic reviews [16][17][18].Therapists were contacted through their institutions via mail, email, and social media, as well as email newsletters from professional organizations, where contact was established via telephone and permission obtained after submitting written project information (supplementary material 1).They were informed about the study's purpose, aims, procedures, research team, and data protection before responding to questions.Paper-based (Phase 1) or online (Phases 2 and 3) questionnaires were completed after therapists' consent to participate.Several reminders were sent out to ensure a match of the target population and sampling frame.
The survey was conducted according to ethical standards and the European Union General Data Protection Regulation (DSGVO 20216/679), the Austrian (DSG 2019) and German (BDSG 2017) Data Protection Laws and the principles stated in the Declaration of Helsinki (2013).No names, dates of birth, telephone numbers, workplace or private addresses were collected in the paper-based and online surveys.Respondents of the online survey could leave their email address if they wished to be informed about the survey results, which was stored separately from the survey data and not used in any other way.The data collection surveying German therapists was part of a Bachelor thesis of one of the co-authors ("X").The present study protocol was exempt from review by the ethics committee of the Medical University of Innsbruck, Austria, nor does the joint ethics committee of Heidelberg University of Education and SRH University Heidelberg currently review research protocols that are part of Bachelor or Master theses.The study was registered prospectively with the German Clinical Trials Register ("X").

Measures
Participants completed a 15-min paper-based survey in Phase 1 and an online SurveyMonkey survey (San Mateo, California, USA) in Phases 2 and 3.The paper survey was distributed via mail, email, and social media after contacting rehabilitation departments of hospitals and rehabilitation centers, and rehabilitation outpatient clinics by email or telephone.SurveyMonkey enables generating an online link for participants and data extraction using Excel files.Survey functionality and ease of use were pretested and optimized three times.Personal (age, gender) and professional demographic data (profession, professional experience and setting, highest degree, present undergraduate or postgraduate studies) were collected.The willingness to adopt telerehabilitation and willingness of technology use were assessed in this study because the acceptability of a novel technology and technological readiness facilitate the adoption of a new technology or service [19,20].The primary outcome was the willingness to adopt telerehabilitation, defined according to an established theoretical model explaining individuals' acceptance of technology and including predictors of the behavioral intention to use a technology [21].
As the most suitable model, the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) [21] was chosen for this study.The valid and reliable German version [22] of a questionnaire applying the UTAUT2 was adapted to the field of telerehabilitation because it had originally investigated the acceptance and use of the mobile application Pokémon Go. "Playing Pokémon go" was replaced by "using telerehabilitation."The 25-item UTAUT2 questionnaire comprises seven key constructs (dimensions) that influence the willingness to adopt telerehabilitation: habit, performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and behavioral intention [22,23].All items are measured with a 7-point Likert scale, ranging from "strongly disagree" to "strongly agree," with no total score being calculated and higher scores reflecting greater willingness to adopt telerehabilitation [22].
Secondary outcomes were the willingness of technology use, core affect with respect to using telerehabilitation, and digital competencies.The willingness of technology use was assessed using the validated German-language short scale for assessing the willingness of technology use (Kurzskala zur Erfassung von Technikbereitschaft, TB) [24].Facets of the 12-item short scale are technology acceptance, technology competence confidence, and technology control confidence, all of which consists of 4 items and are measured using a 5-point Likert scale ranging from "strongly disagree" to "strongly agree."Higher scores indicate greater willingness of technology use.A total score is estimated from facet scores.
Core effect with respect to using telerehabilitation was measured because it is known that emotional responses affect the technology adoption in healthcare delivery [25].Core affect with respect to using telerehabilitation was measured using the validated and widely used Semantic Differential (SD) that includes a series of bipolar, 7-step scales defined by verbal opposites (negative -positive, unpleasant -pleasant, boring -exciting, pleasureless -enjoyable, uninteresting -interesting, and unfamiliar -familiar) [26,27].For scoring an SD scale, responses are coded from −3 to +3, with higher numbers reflecting more positive responses.
Digital competencies were assessed as digital literacy likely enhances the adoption of telerehabilitation [28].Digital competencies were evaluated using the Digital Competence Framework (DigComp) developed by the European Commission [29] and using specific guidelines on its use [30].Digital competence has been defined as a so-called transversal key competence, which facilitates the development of other key competencies such as technical capabilities and learning to learn [31].Dimension 1 of the DigComp includes the competence areas of information processing, communication, content creation, safety, and problem-solving Dimension 2 comprises the different competencies associated with each competence area, such as browsing, searching and filtering information; sharing information and content; programming; protecting devices; and solving technical problems [31].The EUROPASS curriculum vitae (CV) includes a 5-competencies self-assessment tool that is based on the DigComp (https:// europass.cedefop.europa.eu/editors/en/cv/compose)and has been developed by Cedefop (the European Centre for the Development of Vocational Training).For each one of the five DigComp areas, a series of statements and descriptors of digital competence are provided, representing three user profiles ("basic," "independent" and "proficient" user), which are rated on a 6-point Likert scale (1 = "strongly disagree" to 6 = "strongly agree") [32].Higher scores signify lower digital competencies.For survey details, see supplementary material 2.

Data analysis
SPSS software, release 27.0 (IBM Corporation, Armonk, NY, USA) and GraphPad Prism 9, San Diego, California, were used for all statistical analyses.Statistical significance was defined as a two-tailed p-value <0.05.Descriptive statistics were used to summarize demographic variables.Continuous data were checked for normal distribution using the Shapiro-Wilk Test, Q-Q plots, and histograms.Frequencies (percentages) were presented for counted and nominal variables and the mean (standard deviation) or median (minimum-maximum) for continuous variables as appropriate.Groups were compared using the Kruskal-Wallis or Chi-Square test, with p-values corrected for multiple comparisons.
In the next step, regression analyses were performed to determine predictors of higher willingness to adopt telerehabilitation, core affect with respect to using telerehabilitation, willingness of technology use and digital competencies.Since the data did not meet the assumptions of a linear regression model, categorical and continuous data values were grouped according to their size using tertiles (0th-33rd, 34th-66th, 67th-100th).Multivariate ordinal logistic regression was then employed to determine which factors accounted for the willingness to adopt telerehabilitation, willingness of technology use, core affect, and digital competencies.Dependent variables comprised 7 UTAUT2 domains, 6 SD bipolar pairs, 3 facets and the total score of TB and 5 DigComp competencies.Predictors (i.e., independent variables) included the timepoint of the survey (before, during the COVID-19 pandemic), country in which the data were collected (Austria, Germany), age (20-30 years, 31-45 years, 46-65 years), gender (female, male, diverse), profession (PT, OT, SLT, dietitian, undergraduate students in final year or currently enrolled in another Bachelor program), professional setting (employed, self-employed or both, teaching and research, mixed employment including clinical work, teaching and research, undergraduate students in final year), highest degree (studying, diploma, Bachelor degree, Master degree or doctorate) and therapists currently enrolled in a Master program (no, yes).Odd's ratios (OR) with 95% confidence intervals (CI) were used to compare the odds of an event, i.e., the probability that the event occurs (e.g., high acceptance of telerehabilitation) divided by the probability that the event does not occur [33].Reference variables were predetermined (OR = 1) as a comparator for calculating the OR using two reference variables with respect to the COVID-19 pandemic and the most representative groups (e.g., measurement timepoint before or during COVID-19; PTs; Bachelor degree; 20-30 years of age; females; employed therapists).Given that p < 0.05, for instance, when OR = 2, the odds of success (high willingness to adopt telerehabilitation) in one group were twice the odds of success in another group [33].Furthermore, Spearman's rank correlations were performed to explore associations between the primary and secondary outcomes.

Results
A total of 603 participants (53.5% of the being PTs) were included in the survey; thereof 334 (55.4%) worked in Austria and 269 (44.6%) in Germany (Table 1).A participation rate of 90.01%(consented therapists divided by third-page completers) and a  completion rate of 88.6% (consented therapists divided by total survey completers) were observed.Overall, 80.6% of the participants were female, and the median age was 33.0 (20.0-65.0)years and similar in both countries.Correspondingly, respondents reported a median professional experience of 8 (0-41) years.Seventy (11.6%) participants indicated currently being enrolled in a Master program, as compared to 107 (16.7%) undergraduate students in the final year or currently being enrolled in another Bachelor program, while 90 (14.9%) reported undergoing undergraduate studies in the final year as their main professional setting.When asked for their highest degree, only 3 participants reported a doctorate, which is why the degrees of doctorate and Master were merged (Table 1).Therapists' responses showed that a majority (40.1%) were working as employed therapists.
Primary and secondary outcomes according to country and the COVID-19 pandemic are presented in Table 2. Significant   differences across groups were observed for all outcomes except UTAUT2 habit, hedonic motivation, and behavioral intention.Test assumptions and overall goodness of fit for multivariate ordinal regression models were met.Regression analysis results showed significant differences between Austria and Germany and before and after the COVID-19 outbreak for most of the outcomes.German residency, the COVID-19 pandemic, a higher education level, and mixed employment settings were the most relevant predictors of a higher willingness to adopt telerehabilitation, of a higher positive core affect with respect to using telerehabilitation, higher willingness of technology use and digital competencies (Figure 2).Further positive predictors were a younger age, male gender, postgraduate or undergraduate studies, and a profession of SLT or dietetics (for details, see Figure 2).Details are described in supplementary material 3, and results on the statistically significant predictors including ORs (95% CI) are illustrated in Supplementary figures 1-4.Spearman's rank correlational analyses across all measurement timepoints showed moderate to strong positive associations between UTAUT2, SD and the TD technology acceptance subscale, and no or weak positive or negative correlations with DigComp and the remaining TB scales.TB and DigComp presented with low to moderate associations (Figure 3).

Discussion
The primary purpose of this study was to understand factors influencing the willingness to adopt telerehabilitation in rehabilitation professionals, and the differences between Austria and Germany.Secondary aims were to explore the factors associated with positive core affect with respect to using telerehabilitation, willingness of technology use and digital competencies.Further study aims included a comparison between the pre and during COVID-19 breakout cohorts.Results showed positive associations between a higher education level, being a student, and a greater willingness to adopt telerehabilitation.A mixed employment setting including clinical work, teaching and research was identified as a significant predictor of higher willingness to adopt telerehabilitation, core affect with respect to using telerehabilitation and digital competencies.These findings could be explained by close links between healthcare education and healthcare innovation, and evidence showing that health professionals with higher degrees implement innovations more comprehensibly than those with lower degrees [34].However, this group represented only a small portion (8%) of our sample.Lower levels willingness to adopt telerehabilitation among clinically working therapists could have been related to a lack of specific training, previously highlighted as a prerequisite for a strong telehealth adoption [35].
Results further demonstrated significant effects of country and COVID-19 for a majority of the outcomes, with German residency and the COVID-19 pandemic being the most relevant predictors of a higher willingness to adopt telerehabilitation.Due to a missing reimbursement model for telerehabilitation at that time in Austria, therapists likely were resistant to its adoption, confirming results from a systematic review, that has identified a lack of reimbursement as one of the main barriers to adopting telemedicine worldwide [36].Although telehealth has been used increasingly within the last decades, the public health emergency resulting from COVID-19 multiplied its demand worldwide and led to a rapid expansion of this model of care [37,38].In our study, demographic variables such as the profession of SLT or dietician and younger age were found to significantly enhance the willingness to adopt telerehabilitation and positive core effect.Our results agree with those from a comparable Finnish study showing a significantly higher OR in SLTs whereas OTs did not differ from PTs [39].
We had anticipated that the willingness of technology use and digital competencies would be closely related to the willingness to adopt telerehabilitation, but we found only weak or no significant correlations between these variables.Professional practices and personal interaction could be contributing factors.Moreover, participants' affective reactions towards telerehabilitation were highly correlated with the willingness to its adoption and therefore, emotions are suggested to have influenced the results.Research has demonstrated an interaction between affect and anxiety and their moderating role on technology acceptance [40].
Being German, highly educated, male, young, a PT or final year undergraduate student were positive predictors of higher digital competencies.Similarly, German residency and a higher education predicted a higher willingness of technology use.Since students are mostly younger compared to their graduated colleagues and younger populations are typically inclined toward new technologies, this seems a plausible result.Probably due to a lack of knowledge of and experience in telerehabilitation, higher technology control confidence was associated with Austrian residence and the pre-COVID-19 period.Men reported a greater willingness of technology use and higher digital competencies, but not a greater willingness to adopt telerehabilitation.Noteworthy, Rettinger et al. [13] have reported higher technical affinity in women when compared to men.The literature had attributed gender a significant role in explaining the technology acceptance behavior of humans, yet the results were similarly mixed [41,42].In the context of information technology usage on which telerehabilitation is mainly based, gender was demonstrated to affect the adoption and use of technology, and men were described as more technologically adept than women [41,42].
Our results showed that younger age was a positive factor contributing to higher willingness to adopt telerehabilitation and positiveness with respect to using telerehabilitation.Contrastingly, another Austrian study on attitudes towards teletherapy during the COVID-19 pandemic has found a significantly higher technological affinity in older therapists [13].However, results cannot be compared directly due to the different methodologies used.A large Finnish study has shown the lowest use of telerehabilitation among therapists with over 30 years of work experience, implying higher age, compared to those with fewer experience [39].A Croatian study did not find any difference between different age groups [43]; so, the inconsistency in results calls for further large, high-quality studies.
There are some implications of the present study's results for practice, research, and policy.The COVID-19 pandemic had a major impact on rehabilitation practice and research, with face-toface interventions not being possible due to lockdowns and other safety measures.This situation facilitated the development and utilization of telerehabilitation and research on this topic.Over the next years, telerehabilitation is expected to develop further in parallel with the developments in technologies such as biosensors, smartphones, and smart homes.In fact, although the current technological advances are quite sufficient for telerehabilitation applications, a change in the perspectives of rehabilitation professionals and patients seems warranted, albeit challenging.Increasing the importance of telerehabilitation in education curricula may be beneficial in changing the perspectives of current and future rehabilitation professionals, as our study revealed that a high level of education and being a student are important predictors.These findings emphasize the relevance of education and training, including further knowledge transfer into practice for those already working in the field.Proper telerehabilitation education and training modules should be implemented into all curriculum frameworks, and they can be provided as postgraduate courses to rehabilitation professionals.In addition, although we did not directly investigate the financial facilitators, such as reimbursement in Germany, we believe that a positive policy towards reimbursement might facilitate the willingness to adopt telerehabilitation among rehabilitation professionals.Future studies should consider how best to implement these recommendations and examine the implications of such changes.A cost-effectiveness analysis of telerehabilitation may be needed to further evaluate the relationship between health insurance reimbursement and therapist willingness to adopt telerehabilitation.

Limitations
This study has some limitations.First and foremost, the study design was cross-sectional which did not allow to analyze behavior over a defined period of time or determine cause and effect.Other studies were large retrospective, observational [11] or qualitative [44,45] in nature.A majority of recent studies on the perceived usefulness [46], benefits, challenges [47,48] and determinants of telerehabilitation [49][50][51] were cross-sectional studies, however.Second, the survey was conducted at different times in each country because the COVID-19 outbreak led to discontinuation of the data collection in Austria, and the continuation of the survey in an adapted format (i.e., online) required reorganization and time.Furthermore, before the COVID-19 outbreak, a paper-based survey was used, which was then switched to an online survey.Third, the COVID-19 pandemic occurred unexpectedly.Therefore, this variable was introduced after the start of the study, as it seemed significant to the authors.This could have influenced the results; however, similar sampling strategies and reminders were used for reasons of consistency.
Biases could have been a possible limitation of this study.The concept of bias in relation to the sampling strategy and in relationship with the nature of the outcomes collected was addressed using different strategies.The survey goals and outcomes, sampling frame, and target population were clearly described.Selection bias was mitigated by choosing wide inclusion criteria allowing physio-, occupational and speech and language therapists, dietitians and final-year students of any gender, age, working in any setting and professional field etc. to participate in the survey.Using advertising strategies of the surveys, by contacting all available professional organizations and as many therapists as possible and sending several reminders, it was strived to achieve a sample that is representative to the target population.The survey could easily be accessed using an online link and completed in around 15 min, which seems sufficiently short.Observer bias was mitigated using standardized questionnaires, with analyses of results carried out by a researcher who was not involved in the advertising and data collection processes.For the analysis, all groups of gender, age, degree, etc. were used in the regression model.With respect to the outcomes, positive and negative responses were achieved indicating that there was no issue of self-selection bias.Results showed that therapists participated in the study who accepted or did not accept or appreciate the use of telerehabilitation and technology.Although our numbers are similar to those reported by another Austrian survey [13] and the Austrian register of health professions, we recognize, however, that more therapists with higher degrees may participate in surveys.

Conclusion
The willingness to adopt telerehabilitation was associated with external factors increasing the need for alternative rehabilitation delivery, such as COVID-19.The willingness to adopt telerehabilitation was greater in German health-care professionals and highest in SLTs and dietitians, in younger and higher educated experts working in mixed professional settings.

Figure 1 .
Figure 1.Participant flow chart using a three-stage sampling technique.the outbreak of the CoViD-19 pandemic is highlighted in red.

Table 2 .
Primary and secondary outcomes according to country and CoViD-19 pandemic.

Figure 2 .
Figure2.summary of significant predictors contributing to a higher willingness to adopt telerehabilitation.Main predictors are highlighted by boxes with thick borders whereas all other predictors are illustrated using boxes with thin borders.Common predictors are highlighted in the same color, with discrepancies indicated by slightly diverging color: for example, before the CoViD-19 pandemic, higher technology competence and willingness of using technology were more likely than after the CoViD-19 outbreak (bright red) whereas the opposite was the case for all other dependent variables (dark red).

Figure 3 .
Figure 3. Relationship between independent variables analyzed by spearman's rank correlations.spearman's rank correlation coefficients (ρ) between all independent variables are visualized by a heat map, with the strength of the association from −1 to +1 being shown at the right side.DigComp: Digital Competence Framework (competence areas 1-5 and total digital competencies); sD: semantic Differential (bipolar pairs 1-6); tb: short scale for assessing the willingness of technology use (German, "technikbereitschaft"; subscales 1-3 and total scale); UtaUt2: extended Unified theory of acceptance and Use of technology (dimensions 1-7).
Data are presented as medians with 25th-75th percentiles.a Groups were statistically compared using the Kruskal-Wallis test.b p-Values were adjusted for multiple (23) comparisons using bonferroni's correction for multiple comparisons.c Groups were statistically compared using multivariate ordinal logistic regression, with age, gender, profession, professional setting, highest degree, and present postgraduate studies included as predictors in the model.asterisks mark the statistically