Next Article in Journal
Evaluation Metrics for Generative Models: An Empirical Study
Previous Article in Journal
A Cognitive Load Theory (CLT) Analysis of Machine Learning Explainability, Transparency, Interpretability, and Shared Interpretability
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Learning Experiences and Didactic Needs of German Healthcare Professions: A Focus Group Study for the Design of Personalized Interprofessional Further Education in Dementia Healthcare

1
School of Didactics and Educational Research in Health Care, Witten/Herdecke University, Alfred-Herrhausen-Straße 50, 58455 Witten, Germany
2
School of Nursing Science, Witten/Herdecke University, Alfred-Herrhausen-Straße 50, 58455 Witten, Germany
*
Authors to whom correspondence should be addressed.
Mach. Learn. Knowl. Extr. 2024, 6(3), 1510-1530; https://doi.org/10.3390/make6030072
Submission received: 19 April 2024 / Revised: 24 June 2024 / Accepted: 24 June 2024 / Published: 3 July 2024
(This article belongs to the Topic Artificial Intelligence for Education)

Abstract

:
Considering the multifaceted nature of neurodegenerative diseases like dementia and the necessity for interprofessional knowledge, this research extends its scope to encompass professionals with diverse levels of training and experience in dementia care. A need analysis for the project “My INdividual Digital EDucation.RUHR” (MINDED.RUHR) is conducted to develop an automatized recommender system for individual learning content using AI. In this sub-study, the aim was to reveal didactic specialties, knowledge gaps, and structural challenges of further education in dementia care of different health professions and to derive learning preference personae. Eight focus group interviews among nine health professions and up to six participants (N = 34) each took place to survey distinct didactic experiences and learning needs. The results reflect various learning preferences, with a propensity to multimedia, practical, and interactive tasks. Health professions are used to digital education but show aversions against synchronous e-learning formats. The derived learning preference personae constitute profound blueprints for a user-centered digital education design process, aiming to establish personalized and representative further education in dementia care applicable to various individual preferences and structural workplace challenges of healthcare professions.

1. Introduction

The field of healthcare can be challenging in terms of maintaining personal and structural resources and managing stressful working conditions [1,2,3]. The demanding nature of healthcare professions’ daily workload, characterized by the need for constant vigilance, critical thinking, managing high caseloads, and prioritizing tasks, as well as the emotional toll of patient care, challenges individuals in the high-pressure work environment of healthcare settings [4]. In addition to difficulties in daily work situations, changes in demography and increases in disease prevalence require health professionals to adapt continuously to provide high-quality care [5,6].
Neurodegenerative diseases like dementia are multifactorial illnesses requiring specialized knowledge and treatments. The rising prevalence of diseases like dementia in recent decades, due to increasing life expectancy and decreasing mortality, complicates this need [7]. As dementia is an irreversible neurocognitive syndrome, patients can only be supported in maintaining their existing functionality and must be cared for according to the symptoms of the disease. To provide extensive and high-quality care for people with dementia while managing rising prevalence rates, it is crucial to have precise knowledge about the diverse symptoms and forms of dementia to offer suitable nursing, therapeutic, or psychosocial treatment options [6,7]. It is known that professional experiences and knowledge are prognostic factors of the quality of a professional’s treatment [8]. Facing demographic changes and various needs of people with dementia, it is essential for health professionals to continuously inform themselves about such diseases [9,10].
On the one hand, research has shown the importance of knowledge to manage uncertainty and change processes, which are major work stressors not only in critical but also in daily healthcare situations [3,11,12]. On the other hand, health professionals report problems of information overload and difficulties in orienting themselves regarding the changing needs of patients in complex working environments [13]. Digital learning environments might help address these challenges in healthcare by preventing issues with filtering relevant information, structuring and clarifying contexts of meaning for complex diseases, and embedding the constant learning requirements into the everyday work life of health professionals [14].
The implementation of digital education is a flexible solution that is already widely applied in education for healthcare professions [6,15]. Providing digital education can help save time, budget, and room capacities for both educational facilities and learners [6,16]. It can further facilitate the process of self-regulated learning, helping the learner implement their own learning structures [17,18]. However, the positive effects of digital learning may be diminished when a learning program does not match the learner’s preferences, learning difficulty, or interests, forcing them to adapt to unfamiliar learning structures. This misalignment may prevent the learner from reaching flow conditions, where the learning process is perceived as optimal in terms of the challenge and the learner’s ability [19]. Furthermore, generic material could negatively influence the learner’s perceived locus of control, sense of value of the material, and self-esteem [20]. Consequently, the learner (here: health professional) may become demotivated, reject the learning material, or complete learning tasks only to meet given requirements [19,20]. Learning environments should, therefore, fit the learner’s habits to reduce complexity in learning processes, keep learners motivated, and assist in transferring learning content to actual working situations, making it accessible and applicable in daily work with patients and clients [21]. For specific personnel like rural and remote working health professionals, it may be necessary to have flexible access possibilities to ensure ongoing dementia learning [22].
In conclusion, for multifactorial and transdisciplinary treated diseases like dementia, there should be learning solutions flexible in reception date, location, and complexity of the content, which can depict the multi-layered behaviors, communication needs, and special personality features of persons with dementia to the extent required by both the learner and the patient [23,24]. Hence, composing a learner-centered program for long-term education may be a first step to ensure the continued implementation of high-quality dementia care.
To establish this learning solution, a shift from process-focused learning to competency-based learning, altering the focus to the learner rather than the teacher, may support the learner in their individual process [13]. It is shown that learners are likely to be intrinsically motivated by learning programs that fit their needs, whereas generic learning tools may provoke reactance in learning behavior [7,25]. Consequently, learning success itself might depend on a personalized presentation of learning material [13]. To promote self-determined learning and support the users’ motivation to actively engage with new learning content, the learning system should analyze learning preferences first and then recommend suitable learning content based on the users’ habits and previous knowledge [26]. Recommender systems, a form of AI, can support the self-regulation learning process in this way [27,28]. As eliciting valuable information can be challenging, recommender systems help users choose information based on personal needs and previous information given. However, designing recommender systems presents the cold-start problem, which occurs when initial data sets lack sufficient data points for the system to adapt to individual needs and preferences [26,27].
One solution to this cold-start problem is the collaborative filtering method, which recommends items to users preferred by similar users [26]. Among healthcare professionals, these similar users may be distinguished by shared learning experiences, professional affiliations, qualifications, and experiences [6]. Physicians tend to learn while working and focus on practical experience [28,29], nurses prefer communication with colleagues over auditory material, and nursing and medicine students prefer multimodal and overall digital education [30]. Hence, clustering these various and shared preferences to create comparable learning personae appears useful. Personae are models of distinct real users of a program, reflecting the behaviors and motivations of this type of user regarding one topic [31]. They can be seen as hypothetical users, constructed with personal attributes and goals to provide insight into the user’s needs. Instead of gathering quantitative data about each user with potentially high economic costs, persona modeling can efficiently create behavioral archetypes of real users to depict their interaction with a program or topic [32,33,34]. Personae are commonly built using participatory approaches to gather a variety of individual characteristics for one type of (here:) healthcare professional. Participatory approaches are methods for gathering vivid information about the personal characteristics of targeted users [35]. By sharing experiences and needs, possible future needs and uses of an intervention may be imagined to ensure a tailored and effective program in terms of behavior-adapted design [36,37]. Another advantage is the improved inclusivity of a program and the empowerment of learners as co-engineers, benefiting from first-hand practical knowledge and further reinforcing self-regulated learning processes [37,38]. In this study, participatory approaches are used to improve the congruence between the learning perceptions and needs of health professionals and theoretical insights of the interdisciplinary research team (here: as engineers) by establishing a collaborative design process of the learning material [38].
The aim of this study is to gain knowledge about learning preferences to construct didactic personae, including distinct didactic requirements of various German healthcare professions. As dementia is a multifactorial disease needing multidisciplinary treatment perspectives, it is useful to include various groups of professionals with different levels of training and experience in dementia care to analyze and provide fitting dementia learning options for the expected heterogeneous learning needs of healthcare professionals [13]. The results of this qualitative study are used for an interdisciplinary project that aims to develop, implement, and evaluate an adaptive digital learning platform for healthcare professionals and other personnel in dementia care. The MINDED.RUHR project is a ministry-supported project funded by the Federal Ministry of Education and Research (BMBF) and supported by the Federal Institute for Vocational Training (BIBB). The present study is embedded in the subproject MR_UWH “Development and preparation of individual learning content using the example of challenging behavior of people living with dementia”.
This results in the following research questions for the current study: What are the learning habits of health professionals regarding ideal learning structures, challenges, and transfers to the workplace? How do various health professions differ in their learning habits and needs?

2. Materials and Methods

Ethical approval was obtained from the ethics committee of Witten Herdecke University, Germany (210/2021).
To identify the learning requirements of health professionals regarding dementia care and implement the first step of the framework for the design and evaluation of digital health interventions (DEDHI), focus group interviews were conducted. This method was used to initiate the participative design process by gathering didactic information about general learning associations, learning habits, maintaining learning motivation, handling frustrations while learning, and challenges of transferring knowledge into the daily work life of health professionals. Other methodological advantages included emerging group identification processes, which can help clarify the perspective of the group compared to individual survey methods [39,40]. This was conducted to initiate a participative design process so that the opinions and values of the target group could be expressed [41].
In addition, existing knowledge about dementia care and previous experiences were gathered from a care science perspective. The participants of the study were health professionals with different levels of care work experience and thematic knowledge of dementia and related care implications to guarantee an extensive overview of the learning target group [6]. Nursing care students, experienced professionals in stationary and outpatient services, and stationary working nursing professionals of different experience levels, as well as physicians, represented the participants in the focus groups. Additionally, relevant health professionals with more infrequent but intense points of contact with people with dementia were integrated. These were represented by physiotherapists, patient-serving personnel, and facility managers in this study.
To ensure the structure of the focus group interviews, a semi-structured interview guide was implemented. Beforehand, the guide was tested for understandability and usability in pilot interviews by students of care science and human medicine at Witten/Herdecke University (UW/H). This took place both digitally and in person to ensure the fit of the structured focus group interviews, even for facilities with contact precautions due to COVID-19. However, it was planned and preferred to hold the interviews on-site at the care institutions. The semistructured interview was chosen to guarantee openly expressed viewpoints of the participants as opposed to a questionnaire or fully structured interview [42]. It contained six didactic main questions regarding previous learning habits in the workplace, ideal conceptions of learning material, information about personal learning flow moments, and previous work situations with learning transfer possibilities. The didactic part of the interview was closed with a question to identify previous points of discontinuation while learning and challenges while trying to transfer knowledge to daily work situations. In addition, thematic questions were included regarding the specific problems and transfer possibilities of dementia care knowledge. The main questions were accompanied by sub-questions to ensure specified answers and to guide the participants to their previous learning experiences and reactions. Furthermore, structural directions and time units for each question were defined to keep the focus group interview fluent.
The recruitment process took place within two German care institutions of the consortium: an elderly care institution and a hospital. One interview was held for each group of professionals, resulting in eight focus group interviews. After receiving instructions about the target group and information regarding the planned interviews, the care institutions recruited the participants for the focus groups and scheduled the interviews. The interviewers included a business psychologist and researcher of didactics, JN, and a researcher of nursing science, MM, from UW/H to present the didactic and thematic specialties of the interview, which were defined as interdependent. Additionally, this was decided to ensure an economical data collection process during a global pandemic and with respect to possible cancellations. The interviews were further recorded with a tape recorder and transcribed afterward by an external agency in accordance with data protection guidelines. The thematic analysis of the data was implemented using the Mayring method [43]. The didactic part of the emerged data was coded by the project worker and interviewer JN and the project manager JE within a coding circle. Subsequently, the gathered didactic and thematic themes were integrated into archetypical learner personae to reflect the vivid information of learning preferences and experiences of the health personnel and to demonstrate possible types of learners (here: users) to the technical consortium partners. The coding of the interviews was used to check which statements were made, how often, and what characterizes the group in comparison to others. The most important statements were those that were related to the activities relevant to the persona and described the work situation and environment well. The socio-demographic data were averaged from the data of the interviewees and compared with the average values of people from the occupational groups in Germany. Additionally, instruction manuals based on didactic preferences and experiences were given to the technical consortium partners to initiate the generation process of the learning nuggets. The category system in the coding procedure was deduced from the described main research questions and was further extended with categories inductively. Furthermore, this system was reviewed by JN and MM and enlarged in an iterative process.

3. Results

The focus group study took place mainly in the first quarter of 2022, with a total of eight interviews involving two to six participants and two interviewers each. Specifically, four interviews took place at a hospital in Essen, Germany, and four interviews proceeded at an elderly care institution in Oberhausen, Germany. These facilities were chosen due to their role as partners in the MINDED.RUHR consortium. The interviews were conducted from November 2021 to August 2022. The first focus group took place with six participants among nursing students of the hospital: four female and two male participants with an age span from 22 to 32 years, each with two years of professional practice experience. Four participants constituted the second focus group among nurses of the nursing home. Among these, there were three female and one male nurse with a mean of 11 years of practice experience and ages ranging from 31 to 46 years. At this institution, one focus group interview was held among three housekeeper staff members, as well as two other groups consisting of three physiotherapists and three home care nurses. The former group was all female participants with a mean of eight years of practice experience and ages ranging from 32 to 58 years. There were two male and one female physiotherapists as participants with an average practice experience of five years, varying in age from 27 to 32 years. The home care nurses were 31 to 55 years old and had a mean of 15 years of practice experience, with two female and one male participants. In February 2022, another three focus group interviews were held with the contribution of five stationary nurses, four patient service professionals, and two physicians, respectively. Four female and one male nurse with an average of 19 years of practice experience and an age span from 24 to 56 years contributed. The patient service professionals varied in age from 23 to 62 years, had an average practice experience of four years, and included four female and one male participants. Two 32-year-old male physicians with four years of practice experience participated as well. The interviews varied in length from 39 min up to 86 min. A descriptive questionnaire given to the professionals afterward demonstrated the variance of the respondents in overall age (18 to 61 years), gender, professional qualification, employment status, form of employment, current profession, as well as experience in professional practice. The corresponding table can be viewed in the attached Table A1 Appendix A.
To analyze the qualitative data, a Mayring coding procedure was initiated [43]. To prepare the analysis process, an initial code system was prepared, based on the semistructured interview guide. This code system consisted of 8 main categories as well as 12 subcategories. The main categories were descriptions of learning experiences, with subcategories in positive and negative experiences as well as learning associations. Reports of previous participation in seminars were accompanied by the subcodes online and attendance meetings to characterize common learning environments. The category requests according to learning were accompanied by the subcodes Video, contact persons, exchange with others, text, audio, documents for reference, and revisions. The main category information procurement, description of learning flow as well as the cancellation of learning situations were fixed further to understand critical motivational learning situations. The category of implementation of new knowledge was accompanied by the description of obstacles in this process. Lastly, general conditions of learning were set as a main category for the interview analysis process. In the main category, previous learning experiences should be described by the participants. A total of 108 nominations were made by the participants to do so. The results reflected 30 positive nominations of learning, though predominantly negative experiences (63). The character of these negative experiences reflected, for example, individual motivational issues and lacking time to learn in the demanding working field. Fifteen learning associations, reflecting how learning in general is individually valuated for the profession, were described as well. An example positive statement of learning and motivation is:
“We had a topic called epigenetics (). And I found that super exciting at the time and got two A4 sheets of paper from school and read them very quickly. Then I also read a lot of other things on the internet because I found it so exciting. () I think that was the first time I really realized: Wow, somehow () knowledge is unlimited, and you can learn so much and I found that really fascinating”
(B_7, l.35).
Reports of previous participation in seminars reflects concrete learning experiences of online and presence seminars with 48 nominations. In total, 27 of these nominations reflect that the majority of the professions are used to the presence of seminar experiences, whereas three mentions could be linked to online seminar experiences. The subcategory blended learning was added post hoc to summarize mixed learning experiences, mostly due to COVID-19 presence restrictions. The category requests include 154 statements that specify concrete methodological wishes and improvements for given seminars. Previously expected wishes are reflected in the subcodes Video (10 nominations), contact persons (1), exchange with others (7), text (7), audio (10), documents for reference (11), and revisions (4); 14 subcodes were added in the analysis phase. Examples of these added subcodes were wishes for practical exercises (18 nominations), a practical topic in the focus of the seminar (17), a lively design of learning material (14) as well as interactive tasks (10). The participants also mentioned wishes according to the learning platform (7) and reservations about the synchronous online learning format (11). One example quote reflects the reservation as follows:
“() If you have a lecture and you log in, you can still switch off your screen, you can also mute yourself, you can also mute the other side [laughing] () I think you’re more distracted there. Overall, you’re more distracted at home than when you’re taking part in a course”
(A_1, l.39).
To gather data of the general information procurement in the daily lives of the professions, 94 statements of obtaining information for problem solving in the working life were summarized. Statements were allocated to the attendance of training courses (5 nominations), case discussions (8), analogue research (6), digital research (28), and asking colleagues (45). The predominantly mentioned collegial consultation for information procurement is exemplarily reflected as follows:
“Yes, the nice thing about it is that no one is left to their own devices, but that it’s done in a collective. In that way it’s always fun and it’s also solution-oriented. ”
(A_1, l.75).
The category implementation of new knowledge contains 70 statements that describe how participants further process new knowledge in their work life. Within nine subcategories such as the exchange with colleagues (19 nominations), lack of time (8), finding allies (4), the usability of knowledge (4) and motivation (4), this implementation was characterized. Conflict with colleagues was often mentioned as a barrier of transferring knowledge to work life (25 nominations). An example statement regarding the conflict with colleagues is
“() You feel really pushed into the typical role of the trainee and you also try to deal openly with the fact that everyone has been trained at a different level of knowledge and that something new is always being added, but if there is no openness at all () then it is not possible to work in a team to ensure that you always work based on latest scientific research or, yes, keep up with the state-of-the-art in nursing science”.
(B_1, l.47).
The category of general conditions of learning reflects common learning environments in the working life of health professions and was subsumed in five quotes. These were further divided into the subcategories (needed) quietness (3 nominations) and time pressure (2). One sample quote regarding conditions of learning in work life is
“() and also that it takes a lot more time when you change something, for example. Or simply because you can’t do it quite as quickly because you must be more focused”.
(B_3, l.70).
None of the statements thematized the expected character of learning flow or the point of cancellation of learning situations. The categories concerning the daily work life and description of preferred learning methods were added post hoc and subsume 59 and 108 nominations. To show the variability in learning methods, 12 subcategories were formed. Learning by doing (12 nominations), summaries (19), reading (16), practical visualization (10), and textualization of learning material (8) represent the most mentioned learning methods preferred by the health professions. An overview of the subsumed categories can be reviewed in Table 1.
As a qualitative clustering method, the identified learning preferences and needs of the focus group interviews were summarized in eight personae of different health professions, illustrating the variety of individual learning experiences and didactic requirements of learners for a possible design process. Each persona reflects an exemplary type of learner in the field of healthcare, representing the usual framework of learning, learning media, didactic specialties, as well as personal information regarding age, gender, and practical experience.
The first persona reflects a 36-year-old nurse at a hospital named Anna H., with 10 years of practical experience, who is used to learning remotely in predetermined time slots and states previous negative learning experiences. Preferred learning media are audio, reference material, speaking with experts, and collaborative tasks. Anna has didactic specialties in a preferred exchange with colleagues as well as reservations about digital education programs. Furthermore, interdisciplinarity regarding health education is challenging for Anna.
Another persona is a 25-year-old nursing trainee named Sarah R. with one year of practical experience. She is used to learning continuously and remotely and has negative previous learning experiences as well. Her preferred learning materials are interactive tasks with practice examples, images and videos, reference material and summaries, and further collaborative tasks. Didactic specialties for Sarah focus on the exchange with colleagues, desired reviews of learning outcomes, and the appreciation of these outcomes. Interdisciplinarity is a desired specialty for this persona as well.
Yvonne S., a 42-year-old patient service health professional with four years in practice, tends to learn remotely in a short and efficient way and further has previous negative learning experiences. She likes to learn by doing practical tasks and practice-oriented topics. Regarding didactic specialties, exchange with colleagues has a high priority for her too. Learning is a desired way to solve problems, and practical and professionally relevant content is important as well as interdisciplinarity.
Pierre G. is a 31-year-old physician with four years of practical experience who prefers to learn during working times. He learns continuously and reports negative previous working experiences. Clear images and videos, flashcards, reference material and summaries, as well as references to medical guidelines, are preferred materials. Existing digital learning experience and interdisciplinarity as a challenge can be noted as didactic specialties.
Another persona is 29-year-old physiotherapist André P. with seven years in practice, who prefers to learn remotely, continuously, and in weekend seminars and reports previous negative experiences. Preferred learning materials are texts, practice examples, reference material and summaries, as well as questions for reflection. As didactic specialties, existing digital learning experiences, a priority for the exchange with colleagues, as well as desired interdisciplinarity, are noted.
Sandra N., a 37-year-old nurse in a nursing home, is another persona with extended practical experience (15 years), who tends to learn remotely. She prefers short and efficient learning sessions and reports neutral learning experiences. The learning process is preferably supported by practical and collaborative tasks and operation guidelines. Sandra reports practical, professionally relevant, and realistic content as a didactic specialty. She also desires learning to be a matter of problem solving and implementing interdisciplinarity.
Another persona is Mara B., a 56-year-old nurse with 25 years of practical experience in a mobile nursing service. She learns remotely, in short bursts, and efficiently and reports positive previous learning experiences. The learning process is optimally presented when it is by practical tasks, images, and videos, as well as instructions to copy. Specialties are the priority of the exchange with colleagues, a realistic and practical relevance, as well as the mobile availability of learning content.
The last persona is Heike S., a 51-year-old facility manager in a nursing home with eight years in practice. She also tends to learn remotely, in short bursts, and efficiently and reports both positive and negative learning experiences. She likes interactive tasks, images, and videos, as well as instructions to copy as learning material. For didactic specialties, there are reservations about digital educational programs and a preference for realistic, practical, and professional relevance of learning content. Thematic specialties according to the collaborative work with care sciences as well as quotes from the focus group interviews supplement each persona report as well (see Appendix B: Didactic personae).

4. Discussion

The eight participative focus group interviews contribute to a detailed understanding of the previous learning experiences, preferences, as well as difficulties in the reception and implementation of further education in German healthcare everyday work. These distinctive features of learning behavior among health professions in comparison to the didactic literature are further examined to develop an understanding of various healthcare learner features as a foundation for needs-based learning material and suggestions for the structural promotion of efficient learning experiences in healthcare further education.
Regarding previous learning experiences, the negative connotation of learning among this sample of health professions is noticeable (60 mentions). Negative associations concern the time intensity besides a challenging work life, redundancies in further education material, unstructured further education material, non-practical or non-activating education formats, stress due to masses of learning content, as well as overload regarding prioritization for competence validation. However, for an enjoyable, successful, and sustainable learning experience, a positive attitude towards learning objects or learning in general may be crucial, suggesting a general need to support learning motivation and the restructuring of further education among health professions not only in Germany [44,45]. On the other hand, a positive attitude towards learning is reflected in 30 mentions among health professions. The character of these learning attitudes, reflecting personal enrichment and flow through new knowledge, cooperation with colleagues, practical or otherwise exciting topics, as well as the successful application of knowledge for medical routines, may be hints for enhancing the intrinsic learning motivation of health professions as a key quality to promote self-regulated learning and continued autonomous further education [6,15,19,20].
Concerning previous seminar and further education experiences, it is prominent that the interviewed health professions report few experiences with blended learning formats (5 mentions) or e-learning formats (3 mentions) in comparison to presence formats (27 mentions). More than a few participants even report reservations about the online format (11 mentions), addressing problems like concentration issues in longer digital seminars, insufficient memory performance due to situationally remote content, lacking commitment due to reduced social control, and possible interfering disturbances in the environment of the e-learner. This attitude and lack of remote learning experience might impede efficient further education and knowledge implementation in light of rising challenges for healthcare professions, e.g., information overload in clinical environments, lack of interprofessional exchange, and time and personnel resource scarcity [6,46]. Synchronous or asynchronous digital education formats do have advantages to address these challenges, making further education more accessible, flexible, and time and cost-efficient in healthcare [6]. The general procurement of information, on the contrary, is preferably digital (28 mentions) in comparison to analogue procurement of information (6 mentions). This is comparable to the learning experiences from other healthcare professions that have already been examined in other studies [47,48]. However, the variety of digital education format possibilities and experiences show that the digital format content surveyed in this study may have to be further differentiated for general statements about digital format motivation issues in further research. Participants mainly referred to the format of synchronous social formats, e.g., ZOOM sessions, where they find it difficult to concentrate over a longer time period due to distractions. These referred digital classroom sessions might have disadvantages, e.g., in distractibility and difficulties to cultivate social interactivity [49]. However, research shows that asynchronous formats can be even more effective than face-to-face formats, and it could be the case that the reservations of the health professions might differ for this asynchronous kind of e-learning planned for the MINDED.Ruhr Project [50]. Further evaluation could focus on the acceptance of different digital formats and how to foster motivation and concentration over longer time periods, if necessary. Furthermore, it seems reasonable to integrate the preferred quality of asking colleagues for information procurement (45 mentions) into the learning material to meet the learning preferences of healthcare professions, to amplify identification and the actual continued usage of the learning material, as well as to facilitate the shift from analogue learning habits to digital ones for all types of health professions [17,51,52].
Another prominent specialty shown by the focus interviews in this study is the quantity of requests regarding the design, structuring, and didactical features of the learning nuggets (154 mentions). It can be demonstrated that the target group of health professions does have a lively interest in the co-design of their learning process, indicating the acceptability of a participative procedure of further education development. This may constitute a good foundation for self-directed learning among health professions in general and an acceptability and usability of digital education material developed for these professions, supported by constructivist learning theories [15,53]. Among the requests, a variety of preferred multimedia learning objects are evident, regarding the transparent structure of a learning platform (7 mentions), practical tasks to internalize medical processes and empathize with residents and patients, as well as interactive tasks (14 mentions; 10 mentions). Moreover, requests of documents (11 mentions) for reference, audio formats (10 mentions), and learning performance checks (4 mentions) are mentioned. These various didactic needs may reflect the initial suggestion of a need for individualized learning recommendations to keep health professions motivated with demand-oriented, multimedia learning material in their self-directed learning experience [7,21,25]. Within the domain “information procurement”, it is noteworthy among health professions participating that this process is preferably digital. Health professions do inform themselves regarding uncertain workflows or situations via clinical websites or other evidence-based digital tools and therefore in an efficient way (28 mentions) [13,54,55]. This appears beneficial concerning the immediacy of this way of information procurement and possible rapid problem solving in the situation due to access to updated, evidence-based knowledge [6]. However, most of the participants report asking colleagues to procure new information in and around daily work situations (45 mentions). This has been presented as valuable for both the health profession itself and patients’ care, not only in terms of content-specific knowledge. In fact, improved overall teamwork skills, a patient-centered focus, specific communication skills, as well as shared global values are examined along with the exchange with colleagues in healthcare, especially among interprofessional ones [56]. Conveying the social aspect of information procurement when designing learning material might, therefore, additionally support individual competencies of health professions beneficial for patient care quality [57].
Although this appears beneficial due to the reciprocal social support and exchange of experiences, possible interpersonal conflicts might cause a gap between the procurement and the actual implementation of gathered health-related knowledge in the daily work lives of health professions participating (25 mentions). Regarding the knowledge implementation, more than a few participants report experiencing conflicts with colleagues when trying to implement new workflows or suggest updated health-related information after attending seminars or after the acquisition of new evidence-based knowledge (25 mentions). This is mainly reported due to hierarchical structures and prior work experience, established working standards, breaching of which is refused, or individual accustomed working preferences, which may be hard to address for optimization. In other health-related studies and institutions, these conflicts are reported as linked to updated knowledge, hierarchical structures, a challenging work environment, and personal experiences of personnel [58,59]. The nature of this conflictual process is examined in fundamental learning and organizational–psychological theories as well, referring to the importance of the co-creation of cultural knowledge in health organizations [6,53]. Cognitivist knowledge theories try to represent and model processes into schematic solutions, trying to represent generic information structures and workflows based on information processing and logical reasoning [53,60]. Constructivist theories refer to a non-universal understanding of knowledge, which is individually or systemically built and influenced by the experiences, the values, and the current perception of the persons perceiving it. The information then is “true” when it is confirmed through its applicability and functionality. In this context, constructivists refer to explicit (or factual) and tacit knowledge; the latter requires practice and is rather acted out than actively held conscious [53,61]. Transferring explicit knowledge into actable, tacit knowledge, e.g., workflows, requires time and cognitive capability resources, which are utilized to capacity in health-related working fields [62]. It can be challenging for healthcare professions to integrate derived knowledge from seminars, etc., into the established cumulated organizational experiences and relations, organizational time or personal resources, history of the resident or patient, as well as prior interpersonal collaboration experiences [6,53,63]. This may explain the conflicts or non-compliance of colleagues reported by the surveyed professions, referring to mentions of time famine (8 mentions) and a limited applicability (4 mentions) of knowledge given the circumstances in the institution. Reported strategies to cope with these barriers are finding allies to implement new knowledge (4 mentions) as well as the open-minded exchange with colleagues (13 mentions). Within constructivist learning theories, this collaborative exchange has been described in terms of constructing a new, common knowledge culture, fusing existing values, prior experiences to cultivate process-enriching knowledge, and reflection structures [53,64]. However, an overall negative assessment of knowledge implementation is prominent among the surveyed health professions (41 mentions), putting the practical use of individual learning for some of these health professions for their working life and patients in doubt. Structural support needs, e.g., by the care or clinical institution or legislators in medical and care training for the implementation of new knowledge and optimizing workflows, are revealed to facilitate interprofessional and overall collaboration among health colleagues as well as the cultivation of a common ground of updated knowledge and problem solving within a hierarchical and resource-consuming working field [53,63,65].
Speaking of institutional circumstances of learning, it is shown that requested, but not existing peace and quiet, as well as time pressure at the workplace, are mentioned, demonstrating a possible non-optimal learning environment for at least a few health professions participating. Non-optimal further education conditions are reported by healthcare workers in other samples as well [62,65,66]. An optimal health workplace could provide marked out times and places for learning and individual process reflection, activating workspace leaders with challenging questions as well as the empowerment of personnel in terms of collaboration and participation within working structures [65,67,68]. Besides these structural improvements, implications for the design of learning material result in short learning units, a decentralized presentation, and guided, structured learning material to guarantee the fit of the learning formats in challenging daily work routines [6]. Various needs of mostly practice-oriented formats (12 subcategories) are evident in this study, indicating a necessity for a needs-sensitive learning platform to include the variety of format requests in an economical way. Mostly, it is recommended to develop practical tasks and storytelling (19 mentions) as well as summarizing formats (22 mentions) to meet these needs [67].
There might be limitations to the procedure in this study that might restrict the results and their scientific applicability. Although the focus group method is a widely established method in health-related research and can stimulate described common knowledge in constructivist matter, it might be possible that participants influence each other’s opinion or are influenced by the guidance of the moderator themselves [39,68,69]. Group dynamics like relational experiences, invisible social hierarchies, or a minority position in an opinion may hereinafter impede sharing the genuine contribution to the group due to social desirability matters. The moderator can bias the natural dynamic of the group and lead the discussion explicitly or implicitly in a desired direction [38,69]. By adhering to the semistructured interview guide, this previously known risk appears minimized. The following used persona method is a widely used standard method to communicate needs in user-centered design. However, personae cannot be verified or falsified, indicating a limited validity [70]. The importance of certain personae for a sample cannot be weighted and it cannot be illustrated if there are users “between” the personae, indicating a possible greater variability than among given archetypal types. The dimensionality of a persona is another weakness, indicating a lower probability of this actual user type among all possible users with rising features describing it and required multivariate correlations to assess the accuracy of these various features, which are not made due to a large statistical outlay. In practical matters, there are limitations linked to the interpreter’s associations of the personae, possibly biased by personal experience and context, and resulting in a subjective conclusion [70].
However, the planned construction of a variety-sensitive recommender system based on stepwise integrated user interaction data might help users build learning paths according to their individual preferences and learning experiences and therefore provide additional customization and variability to the underlying archetypical personae characteristics in the further course of the project.

5. Conclusions

The DEDHI-Framework, as well as health-related, participative design studies, have already initiated the applicability of the needs analysis within focus group interviews as well as the persona method to represent user- and learning particularities and to design digital education material [49,71,72,73,74]. It can be illustrated that healthcare professions of the surveyed institutions clustered within eight qualitative personae reflect various levels of experiences over different age spans. Learning preferences shift from working remotely to learning at work, different learning materials, and continuity of learning. Similarities among health professions can be noted in preferred multimedia material, practical topics, and desired interdisciplinarity among different kinds of health professions. Interprofessional and collegial exchange is the main source for applicable information, and reservations against synchronous digital education formats are visible. The demonstrated needs for user-centered and decentralized learning are reflected in other samples of health institutions and health professions as well [59,65]. A representativity of the presented user data and an added value to the understanding of learning needs of health professions in German healthcare institutions is therefore given. Showed by the negative learning experiences of the professions and identified structural barriers in working life, it is further suggested that individual further education in healthcare needs to be supported, preferably by colleagues, instructors, and on the organizational level. Barriers of transferring new knowledge need to be identified to cultivate a positive explicit and tacit learning environment, in which all interprofessional elements of a health institution can provide optimal healthcare work collaboratively and up to the latest state of science [6,65]. In this study, the closeness to application is given by the participating consortia partners B and GH so that a room is provided for questioning existing further education structures. For implementation of this findings, the resulting archetypical personae and gathered learning experiences form the basis for the development of prototypical learning units for the subproject of the MINDED-Ruhr consortia project MR_UWH “Development and preparation of individual learning content using the example of challenging behavior of people living with dementia”, ensuring a user-centered design of specific learning units as well as adaptive learning paths supported by AI for the facilitation of individual further education in German healthcare.

Author Contributions

All authors contributed to the manuscript, and reviewed and approved the final version of the paper. All have agreed both to be personally accountable for their own contributions, and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated and resolved, and the resolution documented in the literature. The contributions are specified as follows: conceptualization, J.N. and M.M.; methodology, J.N. and M.M.; validation, M.S., J.N. and M.M.; formal analysis, J.N., J.E., M.M. and M.S.; investigation, J.N. and M.M.; resources, J.N.; writing—original draft preparation, M.S. and J.N.; writing—review and editing, M.S., J.N. and M.M.; visualization, M.S. and J.N.; supervision, J.E. and M.H.; project administration, J.E. and M.H.; funding acquisition, J.E. and M.H. All authors have read and agreed to the published version of the manuscript.

Funding

This study is financially funded by the Federal Ministry of Education and Research (BMBF) and supported by the Federal Institute for Vocational Training (BIBB), grant number 21INVI0301.

Institutional Review Board Statement

Ethical approval to conduct the study was sought and granted by the Ethics Committee of UW/H (Nr. 210/2021). Written informed consent to participate and be audio-recorded was obtained from all participants. Data management and storage will be subject to the European General Data Protection Regulation [43]. Participants are assured that their personal data, data supplied in questionnaires, and audio recordings will remain anonymous during analysis and reporting. The participants are asked to respect the confidentiality of their observations about colleagues’ participation in the focus group interviews.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The materials described in this paper pertain to the focus group interview report only, and there are no raw data reported. The data sets have been collected and analyzed and can be made available from the corresponding authors on reasonable request.

Acknowledgments

We would like to mention all consortia partners: MedEcon.RUHR (consortium leadership), DATATREE AG, Fraunhofer Institut für Software und Systemtechnik (ISST), TUTOOLIO GmbH, and Duisburg-Essen University. A special thanks goes to the consortial participants of this study including Alfried Krupp Krankenhaus (B) as well as Gute Hoffnung.

Conflicts of Interest

The authors declare that they have no competing interests.

Appendix A. (SM1)

The following table represents the participant demographic data of the surveyed health professions.
Table A1. Demographic data of the participants of 8 focus groups.
Table A1. Demographic data of the participants of 8 focus groups.
GroupTotal (n)
Age
18–246
25–3414
35–443
45–543
55–647
Gender
female24
male10
diverse-
Professional qualification
University degree8
Professional—operational degree11
Professional—educational degree9
No degree5
Other degree1
Employment status
In training9
Employed25
Self-employed-
Civil servant-
Other-
Form of employment
Full-time22
Part-time10
Mini job2
Parental leave or other leave of absence-
Current profession
Physician2
Student physician assistant2
Physiotherapist3
Nurse11
Nursing assistant1
Patient-serving personnel2
Additional caregiver3
Facility manager3
In training7
Experience in professional practice (by years)
1–418
5–1011
11–15-
16–201
20+4
Total (N)34

Appendix B. (SM2)

The following figures display the didactic personae, derived from the needs and preferences of the surveyed health professions.
Figure A1. Persona 1—Anna H.
Figure A1. Persona 1—Anna H.
Make 06 00072 g0a1
Figure A2. Persona 2—Sarah R.
Figure A2. Persona 2—Sarah R.
Make 06 00072 g0a2
Figure A3. Persona 3—Yvonne S.
Figure A3. Persona 3—Yvonne S.
Make 06 00072 g0a3
Figure A4. Persona 4—Pierre G.
Figure A4. Persona 4—Pierre G.
Make 06 00072 g0a4
Figure A5. Persona 5—André P.
Figure A5. Persona 5—André P.
Make 06 00072 g0a5
Figure A6. Persona 6—Sandra N.
Figure A6. Persona 6—Sandra N.
Make 06 00072 g0a6
Figure A7. Persona 7—Mara B.
Figure A7. Persona 7—Mara B.
Make 06 00072 g0a7
Figure A8. Persona 8—Heike S.
Figure A8. Persona 8—Heike S.
Make 06 00072 g0a8

References

  1. Junne, F.; Michaelis, M.; Rothermund, E.; Stuber, F.; Gündel, H.; Zipfel, S.; Rieger, M.A. The Role of Work-Related Factors in the Development of Psychological Distress and Associated Mental Disorders: Differential Views of Human Resource Managers, Occupational Physicians, Primary Care Physicians, and Psychotherapists in Germany. Int. J. Environ. Res. Public Health 2018, 15, 559. [Google Scholar] [CrossRef] [PubMed]
  2. Mendes, A. Establishing the boundaries between work and home. J. Kidney Care 2018, 3, 262–263. [Google Scholar] [CrossRef]
  3. Radeva, S. Challenges before the management of human resources in the health organization. EurasianUnionScientists 2020, 1, 54–57. [Google Scholar] [CrossRef]
  4. Moss, M.; Good, V.S.; Gozal, D.; Kleinpell, R.; Sessler, C.N. A Critical Care Societies Collaborative Statement: Burnout Syndrome in Critical Care Health-care Professionals. A Call for Action. Am. J. Respir. Crit. Care Med. 2016, 194, 106–113. [Google Scholar] [CrossRef] [PubMed]
  5. Pantel, J. Differentialdiagnose und Pathophysiologie der Demenz. In Demenz—Prävention und Therapie. Ein Handbuch der Komplementärmedizinischen und Nichtmedikamentösen Verfahren; Walach, H., Loef, M., Eds.; KVC Verlag: Essen, Germany, 2019; pp. 9–32. [Google Scholar]
  6. Ruggeri, K.; Farrington, C.; Brayne, C. A Global Model for Effective Use and Evaluation of e-Learning in Health. Telemed. J. E-Health 2013, 19, 312–321. [Google Scholar] [CrossRef] [PubMed]
  7. Thyrian, J.R.; Boekholt, M.; Hoffmann, W.; Leiz, M.; Monsees, J.; Schmachtenberg, T.; Schumacher-Schönert, F.; Stentzel, U. Die Prävalenz an Demenz erkrankter Menschen in Deutschland–eine bundesweite Analyse auf Kreisebene. Nervenarzt 2020, 91, 1058–1061. [Google Scholar] [CrossRef]
  8. Holmboe, E.S.; Lipner, R.S.; Greiner, A.C. Assessing Quality of Care. JAMA 2008, 299, 338. [Google Scholar] [CrossRef] [PubMed]
  9. Okun, S.; Goodwin, K. Building a Learning Health Community: By the People, for the People. Learn. Health Syst. 2017, 1, e10028. [Google Scholar] [CrossRef]
  10. Rodriguez, F.S.; Jackson, J.; Ware, C.; Churchyard, R.; Hanseeuw, B.; International Interdisciplinary Young Investigators Alzheimer’s & Dementia. Interdisciplinary and Transdisciplinary Perspectives: On the Road to a Holistic Approach to Dementia Prevention and Care. J. Alzheimer’s Dis. Rep. 2020, 4, 39–48. [Google Scholar] [CrossRef]
  11. Frenkel, M.O.; Pollak, K.M.; Schilling, O.; Voigt, L.; Fritzsching, B.; Wrzus, C.; Egger-Lampl, S.; Merle, U.; Weigand, M.A.; Mohr, S. Stressors Faced by Healthcare Professionals and Coping Strategies During the Early Stage of the COVID-19 Pandemic in Germany. PLoS ONE 2022, 17, e0261502. [Google Scholar] [CrossRef]
  12. Sensky, T. The Unconscious at Work: Individual and Organizational Stress in the Human Services. BMJ 1995, 310, 608–609. [Google Scholar] [CrossRef]
  13. Klass, D. Will E-Learning Improve Clinical Judgement? BMJ 2004, 328, 1147–1148. [Google Scholar] [CrossRef] [PubMed]
  14. Klerings, I.; Weinhandl, A.S.; Thaler, K.J. Information Overload in Healthcare: Too Much of a Good Thing? Z. Evid. Fortbild. Qual. Gesundhwes. 2015, 109, 285–290. [Google Scholar] [CrossRef]
  15. Piotrkowicz, A.; Dimitrova, V.; Hallam, J.; Price, R. Towards Personalisation for Learner Motivation in Healthcare: A study on using learner characteristics to personalise nudges in an e-Learning context. In Proceedings of the UMAP’20 Adjunct, Genoa, Italy, 14–17 July 2020; Association for Computing Machinery: New York, NY, USA, 2020. [Google Scholar]
  16. Akyuz, S.; Yavuz, F. Digital Learning in EFL Classrooms. Procedia Soc. Behav. Sci. 2015, 197, 766–769. [Google Scholar] [CrossRef]
  17. O’Shea, E. Self-directed learning in nurse education: A review of the literature. J. Adv. Nurs. 2003, 43, 62–70. [Google Scholar] [CrossRef]
  18. Kim, M.H. Web-based E-Learning System Supporting an Effective Self-Directed Learning Environment. J. Korea Contents Assoc. 2011, 11, 524–535. [Google Scholar] [CrossRef]
  19. Challco, G.C.; Andrade, F.R.H.; Borges, S.S.; Bittencourt, I.I.; Isotani, S. Toward a Unified Modeling of Learner’s Growth Process and Flow Theory. Educ. Technol. Soc. 2016, 19, 215–227. [Google Scholar]
  20. Littlejohn, A. The Tip of the Iceberg. RELC J. 2008, 39, 214–225. [Google Scholar] [CrossRef]
  21. Gooding, H.C.; Mann, K.; Armstrong, E. Twelve Tips for Applying the Science of Learning to Health Professions Education. Med. Technol. 2017, 39, 26–31. [Google Scholar] [CrossRef]
  22. Kosteniuk, J.G.; Morgan, D.G.; O’Connell, M.E.; Kirk, A.; Crossley, M.; Teare, G.T.; Stewart, N.J.; Bello-Haas, V.D.; McBain, L.; Mou, H.; et al. Simultaneous Temporal Trends in Dementia Incidence and Prevalence, 2005–2013: A Population-Based Retrospective Cohort Study in Saskatchewan, Canada. Int. Psychogeriatr. 2016, 28, 1643–1658. [Google Scholar] [CrossRef] [PubMed]
  23. Malek, M.; Nitsche, J.; Dinand, C.; Ehlers, J.; Lissek, V.; Böhm, P.; Derksen, E.-M.; Halek, M. Interprofessional Needs Analysis and User-Centred Prototype Evaluation as a Foundation for Building Individualized Digital Education in Dementia Healthcare Supported by Artificial Intelligence: A Study Protocol. Healthcare 2023, 11, 1508. [Google Scholar] [CrossRef] [PubMed]
  24. Scerbe, A.; O’Connell, M.E.; Astell, A.; Morgan, D.; Kosteniuk, J.; DesRoches, A. Digital Tools for Delivery of Dementia Education for Healthcare Providers: A Systematic Review. Educ. Gerontol. 2019, 45, 681–699. [Google Scholar] [CrossRef]
  25. Alamri, H.; Lowell, V.L.; Watson, W.R.; Watson, S.L. Using Personalized Learning as an Instructional Approach to Motivate Learners in Online Higher Education: Learner Self-Determination and Intrinsic Motivation. J. Res. Technol. Educ. 2020, 52, 322–352. [Google Scholar] [CrossRef]
  26. Joy, J.; Renumol, V.G. An Ontology-Based Hybrid E-Learning Content Recommender System for Alleviating the Cold-Start Problem. Educ. Inf. Technol. 2021, 26, 4993–5022. [Google Scholar]
  27. Benhamdi, S.; Babouri, A.; Chiky, R. Personalized Recommender System for e-Learning Environment. Educ. Inf. Technol. 2016, 22, 1455–1477. [Google Scholar] [CrossRef]
  28. Hoffman, K.G.; Donaldson, J.F. Contextual Tensions of the Clinical Environment and Their Influence on Teaching and Learning. Med. Educ. 2004, 38, 448–454. [Google Scholar] [CrossRef] [PubMed]
  29. Van De Wiel, M.W.J.; Van Den Bossche, P.; Janßen, S.; Jossberger, H. Exploring Deliberate Practice in Medicine: How Do Physicians Learn in the Workplace? Adv. Health Sci. Educ. 2010, 16, 81–95. [Google Scholar] [CrossRef] [PubMed]
  30. Tsiakas, K.; Barakova, E.; Khan, J.V.; Markopoulos, P. BrainHood: Towards an Explainable Recommendation System for Self-Regulated Cognitive Training in Children. In Proceedings of the 13th Pervasive Technologies Related to Assistive Environments Conference (PETRA’20), Corfu, Greece, 30 June–3 July 2020; ACM: New York, NY, USA, 2020. [Google Scholar]
  31. Cooper, A. About Face 3: The Essentials of Interaction Design; John Wiley & Sons Inc.: Hoboken, NJ, USA, 2007. [Google Scholar]
  32. Showalter, J.W.; Showalter, G.L. From Form to Function and Appeal: Increasing Workplace Adoption of AI Through a Functional Framework and Persona-Based Approach. J. AI Robot. Workplace Autom. 2021, 1, 142–156. [Google Scholar]
  33. Casiddu, N.; Burlando, F.; Nevoso, I.; Porfirione, C.; Vacanti, A. Beyond personas. Machine Learning to personalise the project. Agathón Int. J. Archit. Art Des. 2022, 12, 226–233. [Google Scholar]
  34. Holzinger, A.; Kargl, M.; Kipperer, B.; Regitnig, P.; Plass, M.; Muller, H. Personas for Artificial Intelligence (AI) an Open Source Toolbox. IEEE Access 2022, 10, 23732–23747. [Google Scholar]
  35. Gonzales, S.; O’Keefe, L.; Gutzman, K.; Viger, G.; Wescott, A.B.; Farrow, B.; Heath, A.P.; Kim, M.C.; Taylor, D.; Champieux, R.; et al. Personas for the Translational Workforce. J. Clin. Transl. Sci. 2020, 4, 286–293. [Google Scholar] [CrossRef] [PubMed]
  36. Björgvinsson, E.; Ehn, P.; Hillgren, P.A. Design Things and Design Thinking: Contemporary Participatory. Design Issues 2012, 28, 101–116. [Google Scholar] [CrossRef]
  37. Luck, R. Participatory Design in Architectural Practice: Changing Practices in Future Making in Uncertain Times. Des. Stud. 2018, 59, 139–157. [Google Scholar] [CrossRef]
  38. Könings, K.D.; Seidel, T.; Van Merriënboer, J.J. Participatory design of learning environments: Integrating perspectives of students, teachers, and designers. Instr. Sci. 2014, 42, 1–9. [Google Scholar] [CrossRef]
  39. Kitzinger, J. Qualitative Research: Introducing Focus Groups. BMJ 1995, 311, 299. [Google Scholar] [CrossRef] [PubMed]
  40. Tausch, A.; Menold, N. Methodological Aspects of Focus Groups in Health Research. Global Qual. Nurs. Res. 2016, 3, 233339361663046. [Google Scholar] [CrossRef]
  41. Birchall, M.A.; Lee, L.; Richardson, A. Focus Groups. Eur. J. Surg. Oncol. 1999, 25, 556–557. [Google Scholar] [CrossRef]
  42. Al Balushi, K. The Use of Online Semi-Structured Interviews in Interpretive Research. Int. J. Sci. Res. (IJSR) 2018, 7, 2319–7064. [Google Scholar]
  43. Mayring, P. Qualitative Inhaltsanalyse; UVK Univ.-Verl. Konstanz: Konstanz, Germany, 1994; Volume 14. [Google Scholar]
  44. Kettanurak, V.; Ramamurthy, K.; Haseman, W. User Attitude as a Mediator of Learning Performance Improvement in an Interactive Multimedia Environment: An Empirical Investigation of the Degree of Interactivity and Learning Styles. Int. J. Hum. Comput. Stud. 2001, 54, 541–583. [Google Scholar] [CrossRef]
  45. Lefkowitz, R.F. Enhancement of Achievement and Attitudes Toward Learning of Allied Health Students Presented with Traditional Versus Learning-Style Instruction on Medical/Legal Issues of Healthcare. Perspect. Health Inf. Manag. 2006, 3, 1. [Google Scholar]
  46. Frenk, J.; Chen, L.; Bhutta, Z.; Cohen, J.; Crisp, N.; Evans, T.; Fineberg, H.; Garcia, P.; Ke, Y.; Kelley, P.; et al. Health Professionals for a New Century: Transforming Education to Strengthen Health Systems in an Interdependent World. Lancet 2010, 376, 1923–1958. [Google Scholar] [CrossRef] [PubMed]
  47. Back, D.A.; Behringer, F.; Haberstroh, N.; Ehlers, J.P.; Sostmann, K.; Peters, H. Learning Management System and e-learning tools: An experience of medical students’ usage and expectations. Int. J. Med. Educ. 2016, 7, 267–273. [Google Scholar] [CrossRef]
  48. Curran, V.; Fleet, L. A Review of Evaluation Outcomes of Web-Based Continuing Medical Education. Med. Educ. 2005, 39, 561–567. [Google Scholar] [CrossRef] [PubMed]
  49. Lam, P.; Tong, A. Digital Devices in Classroom–Hesitations of Teachers-to-Be. Electron. J. -Learn. 2012, 10, 387–395. [Google Scholar]
  50. Neuhauser, C. Learning Style and Effectiveness of Online and Face-to-Face Instruction. Am. J. Distance Educ. 2002, 16, 99–113. [Google Scholar] [CrossRef]
  51. Mertens, F.; De Groot, E.; Meijer, L.; Wens, J.; Cherry, M.G.; Deveugele, M.; Damoiseaux, R.; Stes, A.; Pype, P. Workplace Learning Through Collaboration in Primary Healthcare: A BEME Realist Review of What Works, for Whom and in What Circumstances: BEME Guide No. 46. Med. Technol. 2017, 40, 117–134. [Google Scholar] [CrossRef]
  52. Srinivasan, D. Medical Students’ Perceptions and an Anatomy Teacher’s Personal Experience Using an E-Learning Platform for Tutorials During the COVID-19 Crisis. Anat. Sci. Educ. 2020, 13, 318–319. [Google Scholar] [CrossRef]
  53. Stefanelli, M. Knowledge and Process Management in Health Care Organizations. Methods Inf. Med. 2004, 43, 525–535. [Google Scholar] [CrossRef]
  54. Soong, A.; Car, L. Digital Education for Guidelines Adoption and Adherence: Preliminary Findings from a Systematic Review. BMJ Evid.-Based Med. 2018, 23, A16–A17. [Google Scholar]
  55. Pontefract, S.; Wilson, K. Using electronic patient records: Defining learning outcomes for undergraduate education. BMC Med. Educ. 2019, 19, 30. [Google Scholar] [CrossRef]
  56. Bell, S.K.; Langer, T.; Luff, D.; Rider, E.A.; Brandano, J.; Meyer, E.C. Interprofessional Learning to Improve Communication in Challenging Healthcare Conversations: What Clinicians Learn From Each Other. J. Contin. Educ. Health Prof. 2019, 39, 201–209. [Google Scholar] [CrossRef] [PubMed]
  57. Chopra, V.; Flanders, S.A.; O’Malley, M.; Malani, A.N.; Prescott, H.C. Sixty-Day Outcomes Among Patients Hospitalized with COVID-19. Ann. Intern. Med. 2021, 174, 576–578. [Google Scholar] [CrossRef] [PubMed]
  58. Hanson, S.; MacLeod, M.; Schiller, C. ’It’s Complicated’: Staff Nurse Perceptions of Their Influence on Nursing Students’ Learning. Nurse Educ. Today 2018, 63, 76–80. [Google Scholar] [CrossRef]
  59. Turner, M.; Payne, S.; Froggatt, K. All Tooled Up: An Evaluation of End-of-Life Care Tools in Care Homes in North Lancashire. End Life Care 2009, 3, 73. [Google Scholar]
  60. Block, B.N. The Computer Model of Mind. Osherson,, D.H., Smith, S.E., Eds.; In Thinking: An Invitation to Cognitive Science; MIT Press: Cambridge, MA, USA, 1990. [Google Scholar]
  61. Varela, F.; Thompson, J.E.; Rosch, E. The Embodied Mind; MIT Press: Cambridge, MA, USA, 1992. [Google Scholar]
  62. Attenborough, J.; Abbott, S.; Brook, J.; Knight, R. Everywhere and nowhere: Work-based learning in healthcare education. Nurse Educ. Pract. 2019, 36, 132–138. [Google Scholar] [CrossRef]
  63. McDermott, R. Why Information Technology Inspired, but Cannot Deliver Knowledge Management. Calif. Manag. Rev. 1999, 41, 103–117. [Google Scholar] [CrossRef]
  64. Nonaka, I.; Takeuchi, H. The Knowledge-Creating Company; Oxford University Press: New York, NY, USA, 1995. [Google Scholar]
  65. Frankel, A. Nurses’ Learning Styles: Promoting Better Integration of Theory into Practice. Nurs. Times 2009, 105, 24–27. [Google Scholar] [PubMed]
  66. Barton, A. Improving Environments for Learning: Implications for Nursing Faculty. J. Nurs. Educ. 2018, 57, 515–516. [Google Scholar] [CrossRef]
  67. Ahmed, H.M.S. Hybrid E-Learning Acceptance Model: Learner Perceptions. Decis. Sci. J. Innov. Educ. 2010, 8, 313–346. [Google Scholar] [CrossRef]
  68. Parker, A.; Tritter, J. Focus Group Method and Methodology: Current Practice and Recent Debate. Int. J. Res. Method Educ. 2006, 29, 23–37. [Google Scholar] [CrossRef]
  69. Wong, L.P. Focus Group Discussion: A Tool for Health and Medical Research. Singap. Med. J. 2008, 49, 256–260. [Google Scholar]
  70. Chapman, C.; Milham, R.P. The Personas’ New Clothes: Methodological and Practical Arguments Against a Popular Method. Proc. Hum. Factors Ergon. Soc. Annu. Meet. 2006, 50, 634–636. [Google Scholar] [CrossRef]
  71. Kowatsch, T.; Otto, L.; Harperink, S.; Cotti, A.; Schlieter, H. A Design and Evaluation Framework for Digital Health Interventions. IT 2019, 61, 253–263. [Google Scholar] [CrossRef]
  72. Ling, L.; Xiao, J. Persona Profiling: A Multi-dimensional Model to Study Learner Subgroups in Massive Open Online Courses. Educ. Inf. Technol. 2022, 27, 5521–5549. [Google Scholar]
  73. Schäfer, K.; Rasche, P.; Bröhl, C.; Theis, S.; Barton, L.; Brandl, C.; Wille, M.; Nitsch, V.; Mertens, A. Survey-based personas for a target-group-specific consideration of elderly end users of information and communication systems in the German health-care sector. Int. J. Med. Inform. 2019, 132, 103924. [Google Scholar] [CrossRef] [PubMed]
  74. Yström, A.; Peterson, L.; Von Sydow, B.; Malmqvist, J. Using Personas to Guide Education Needs Analysis and Program Design. In Proceedings of the 6th International CDIO Conference, École Polytechnique, Montreal, QC, Canada, 15–18 June 2010. [Google Scholar]
Table 1. Categories and subcategories of the focus group interviews.
Table 1. Categories and subcategories of the focus group interviews.
CategoriesMentionsAnchor Quotes
Learning experiences108“Learning by doing and looking at colleagues, how do they do it?” (A_1, l.60)
Learning associations15
Negative63“I never enjoyed learning (laughing). So, for me it was more the utility of learning () but having fun? Never!” (B_7, l. 37)
Positive30“We had a topic called epigenetics (). And I found that super exciting at the time and got two A4 sheets of paper from school and read them very quickly. Then I also read a lot of other things on the internet because I found it so exciting. () I think that was the first time I really realised: Wow, somehow () knowledge is unlimited, and you can learn so much and I found that really fascinating” (B_7, l.35)
Participation in seminars48
Blended learning5“(…) At the beginning of last year, I completed my further training as a care supervisor. (…) Yes, it was just mixed. A lot online due to COVID. And then there were PowerPoint presentations that were simply played back to us and maybe a few sentences were said” (A_4, l.22).
Presence seminar27“On the one hand, to see how it is implemented in practice and to really talk to the colleagues locally who presented it afterwards, they also did PowerPoint presentations () but to really experience how it is lived in everyday life, I think that was the biggest learning effect” (B_2, l.24)
Online seminar3“It’s a lot of stuff that’s discussed at the beginning, where you actually have to sit and listen for hours on end and() often the training courses don’t take place just around the corner, you have to travel a long way to get there. () It would be super cool to really take the time from home to go through everything in detail ()” (A_3, l.16).
Requests154
Practical exercises18“I think that’s actually the best kind of training or lecture, when it’s very practice-oriented and you don’t just sit there and get told something, but rather () are accompanied in such cases and are really shown: Hey, this is how you have to do it” (A_3, l.26).
Practical topic17“And if they [teachers] () tell us stories about the patient () and an example, then I can listen especially well, then there’s a real suspense” (B_2, l.31).
Lively learning material14“But it also must be interesting, if someone just reads out something (), then I don’t listen at all, then I switch off very quickly, but if two people talk with interest () and also give examples from practice () then a lot remains in my head” (B_2, l.27).
Documents for reference11“[would use a learning portal] to look at it again later. So, I think I would use that as a learning method” (B_1, l.26)
Reservations against online format11“() If you have a lecture and you log in, you can still switch off your screen, you can also mute yourself, you can also mute the other side [laughing] () I think you’re more distracted there. Overall, you’re more distracted at home than when you’re taking part in a course” (A_1, l.39).
Interactive tasks10“() actively think for yourself and perhaps also find examples from everyday practice” (B_2, l.32).
Audio10“I also like to listen to podcasts from time to time, so I can take something away with me” (A_4, l.28).
Video10“With examples from life, I also enjoy a short film (..) as it’s more likely to stick than someone standing there telling you something or reading something ()” (A_2, l.45).
Information procurement94
Asking colleagues45“Yes, the nice thing about it is that no one is left to their own devices, but that it’s done in a collective. In that way it’s always fun and it’s also solution-oriented” (A_1, l.75).
Digital research28“Yes, we have (digital) biographies. And if we want to have specific things - we’re working to digitize the other generations as well. And you can look up a lot of things on computers. If you don’t know what someone likes to eat () we have these biographies (..) Or you can also read up on whether someone has behavioural problems or not, i.e., if you can’t find anyone at all because the nursing staff are under stress or the attendance staff or the social services. Anyone can go in there, everyone has their own code, and you can read a lot of things there” (A_2, l.75).
Case discussion8“That’s always really good because lots of people then have lots of information and we usually come up with a solution” (A_1, l.71).
Analogue research6“What make sense is to browse through the script again when you know: Okay, you somehow had a technique for that, you just have to repeat it again” (A_3, l.42).
Attendance of training course5“What I needed () were the training courses that take place here regularly, such as basic live support or first aid” (B_3, l.8).
Implementation of new knowledge70
Conflict with colleagues25“() You feel really pushed into the typical role of the trainee and you also try to deal openly with the fact that everyone has been trained at a different level of knowledge and that something new is always being added, but if there is no openness at all () then it is not possible to work in a team to ensure that you always work based on latest scientific research or, yes, keep up with the state-of-the-art in nursing science” (B_1, l.47).
Exchange with colleagues13“Then you can talk about it: One person does it like this, the other like that, everyone has their preferences () you can try it with the other technique that the other person has used” (A_3, l.38).
Lack of time (for implementation)8“And also that it takes a lot more time when you change something, for example. Or simply because you can’t do it quite as quickly because you have to be more focused” (B_3, l.70).
Finding allies (for implementation)4“If you are on the ward and () want to present something new then it is very good that the ward manager supports you, that you are offered a setting where you can incorporate new knowledge into the team, that you say at the team meeting, for example, hey, can I have another five minutes and bring in a few more points from my further training XY, that is definitely good” (B_2, l.89).
Motivation4“When you come back from a good training course, I () always have the feeling that I have to go straight into the company and try everything out straight away” (A_2, l.111).
General conditions of learning5
Quietness3“[learning happens] when I have a lot of peace and quiet, preferably at home” (A_1, l.16).
Time pressure2“So, time is a factor for me. If I have to study because I have an exam or whatever coming up, I do it at the very last minute when I really have to” (A_1, l.38).
Learning methods108
Learning by doing22“But there is no magic formula. For me, a magic formula simply means listening, looking, and trying things out. I can just try things out for myself” (A_2, l.220).
Summaries19„And I usually proceed by reading everything, crossing out the most important parts and signing them with a highlighter. In the final phase, I always write index cards to summarize everything” (A_4, l.14).
Reading16“And then, just read it out loud again and again, that’s my strategy, that’s what sticks with me the most” (A_4, l.14).
Practical visualisation13“When I read something () I can’t internalise it, I immediately forget it again. When I’m shown it, I can somehow remember it better” (A_1, l.41).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Stelter, M.; Malek, M.; Halek, M.; Ehlers, J.; Nitsche, J. Learning Experiences and Didactic Needs of German Healthcare Professions: A Focus Group Study for the Design of Personalized Interprofessional Further Education in Dementia Healthcare. Mach. Learn. Knowl. Extr. 2024, 6, 1510-1530. https://doi.org/10.3390/make6030072

AMA Style

Stelter M, Malek M, Halek M, Ehlers J, Nitsche J. Learning Experiences and Didactic Needs of German Healthcare Professions: A Focus Group Study for the Design of Personalized Interprofessional Further Education in Dementia Healthcare. Machine Learning and Knowledge Extraction. 2024; 6(3):1510-1530. https://doi.org/10.3390/make6030072

Chicago/Turabian Style

Stelter, Marie, Manuela Malek, Margareta Halek, Jan Ehlers, and Julia Nitsche. 2024. "Learning Experiences and Didactic Needs of German Healthcare Professions: A Focus Group Study for the Design of Personalized Interprofessional Further Education in Dementia Healthcare" Machine Learning and Knowledge Extraction 6, no. 3: 1510-1530. https://doi.org/10.3390/make6030072

APA Style

Stelter, M., Malek, M., Halek, M., Ehlers, J., & Nitsche, J. (2024). Learning Experiences and Didactic Needs of German Healthcare Professions: A Focus Group Study for the Design of Personalized Interprofessional Further Education in Dementia Healthcare. Machine Learning and Knowledge Extraction, 6(3), 1510-1530. https://doi.org/10.3390/make6030072

Article Metrics

Back to TopTop