Attributes and Generic Competencies Required of Doctors In 21st Century Health-Care Systems: A Participatory Concept Mapping Study


 Background: Health professionals’ education should ensure graduates are equipped for practice in modern health-care systems. One hundred years after the Flexner Report on medical education, transformation in health-care systems has warranted reflection on priorities for medical education. Practicing effectively in modern health-care systems requires contemporary attributes and competencies, complimenting core clinical competencies. These need to be made overt and opportunities to develop and practice them provided. This study explicates these attributes and generic competencies using Group Concept Mapping methodology, with the aim of informing curriculum development in pre-vocational medical education.Methods: Group Concept Mapping consists of four phases: 1) Idea generation, review and synthesis; 2) Sorting and rating 3) Analysis of data using quantitative and qualitative techniques to produce a visual concept map; and 4) Confirmation and interpretation of results using logic model transformation. Multiple stakeholders contributed to the development of the conceptual model, including junior doctors who rated competencies according to importance to their practice and preparedness at graduation.Results: Sixty-seven participants from stakeholder groups generated 338 responses to the prompt: ‘An attribute or non-clinical competency required of doctors for effective practice in modern health-care systems is...’ These responses were synthesised into 60 statements which were sorted by participants into groupings according to similarity. Multi-dimensional scaling and hierarchical cluster analysis led to a conceptual map of seven clusters representing: Value-led professionalism; Attributes for self-awareness and reflective practice; Cognitive capability; Active engagement; Communication to build and manage relationships; Patient-centredness and advocacy; and Systems awareness, thinking and contribution. Logic model transformation identified three overarching meta-competencies: Leadership and systems thinking; Learning and cognitive processes; and Interpersonal capability. Ratings indicated that junior doctors believe system-related competencies are less important than other competencies, and they feel less prepared to carry them out. Conclusion: Group Concept Mapping was used to conceptualise the attributes and generic competencies required for effective practice modern health-care systems. The operationalization of the model through logic model transformation further identifies the links between attributes, their application through competency, and the outputs that they lead to. Rating of items can identify priorities for ensuring a medical education which addresses contemporary health-care needs.

Report prompted re ection on current medical education. On one hand Flexner has been lauded for the enormous contribution in bringing medical education into the 20th Century progressive education movement [2], and on the other hand, arguments are made that the Flexner Report led to an individualistic, expert-centric culture which may now work against the collaboration needed in modern health-care [3]. The debate has led to discussion and speculation about what is required of medical education to produce doctors equipped to practice effectively over the next century [4,5,6,7,8,9].
Health and health-care have undergone an extraordinary transformation in the past 100 years in ways that Flexner could never have anticipated. Burgeoning knowledge and evidence-base about medical conditions and their management, coupled with a dramatic increase in preventable, non-communicable chronic illness and multi-morbidity, changes in community expectations of health-care, and increasing ethical and professional challenges have created a circumstance whereby the contemporary requirements of doctors continues to be re-evaluated [9].
It is now recognised that young doctors must have capabilities beyond core clinical knowledge and skills and medical education must embrace cultural change to address 21st century health-care needs, including generic capabilities such as working in collaborative teams, transformational leadership, innovation and improvement, and stewardship of funding [3]. In 2010 the global independent Commission on the Education of Health Professionals for the 21st century noted that "Health professionals have made huge contributions to health and socioeconomic development over the past century, but we cannot carry out 21st century health reforms with outdated or inadequate competencies" [9, p. 1954].
While medical education prepares doctors with the knowledge, skills and attitudes to deliver high quality direct care to patients, the attributes and competencies required for newly trained doctors to understand or meet the requirements of delivery of care within a complex system are less explicit [10]. Required competencies for pre-vocational medical education are implicit in statements from regulatory bodies (for example: [11,12]), and outlined more explicitly in frameworks that largely are driven by post-graduate education bodies (for example: [13,14,15,16,17,18]). However, the attributes that are required of doctors to achieve competencies are more obscure and guidance about how to achieve them in medical education is less clear. Enabling their development requires making these competencies overt and guiding the provision of learning opportunities [19,20,21]. These transformations necessitate re ection on the pedagogical strategies required to produce doctors for future health-care systems [22,23,24].
We aim to contribute to the re-shaping of medical education to suit the needs of current and future healthcare systems, by further conceptualising and making explicit competencies which are required for doctors in 21st century health-care systems, with a speci c focus on the attributes and competencies which are required to complement fundamental clinical knowledge and skills and enable effective doctoring. Terminologies used to represent these attributes and competencies are varied, including 'soft-skills,' [25] 'non-technical skills' [26], 'non-academic attributes' [27], 'non-cognitive attributes' [28], 'generic skills' [29] and 'personal attributes' [30]. Collectively they can be considered as the scaffolding which enables doctors to work effectively within modern health-care systems to optimise the delivery of health-care.
They are referred to here as attributes and generic competencies, where generic competencies are those which are not speci cally clinical, albeit often carried out in a clinical setting.
We used participatory Group Concept-Mapping [31] to conceptualise the attributes and generic competencies required for effective practice in modern health-care systems. Logic model transformation and ratings of importance to practice and preparedness, sought from junior doctors, further develop the conceptualisation in the context of medical education.

Overview
Group Concept Mapping (GCM) provides a structured approach for consensus building, using quantitative and qualitative methods, allowing for the integration of input from multiple sources into a visual representation of a conceptual framework, and is described in detail by Kane and Trochim [31]. GCM leads to a visual representation of composite thinking of participants and stakeholder groups with the ability to engage in and represent complexity. An online platform supports the collection, management and analysis of data [32]. Stakeholders are engaged to generate ideas, sort the ideas into groups, and rate ideas according to value. The statistical techniques of multi-dimensional scaling and hierarchical cluster analysis aggregate data to reveal patterns through visualisation, allowing for interpretation to support further utility of the model. GCM is a structured applied social research methodology, to connect theory to observation and research to practice, has been widely used in the health-care sector for policy and planning for health services [33,34,35,36,37] and increasingly in the medical education sector to understand educational processes and outcomes [38,39,40].
The GCM process consisted of four key phases: 1) Idea generation, review and synthesis [31]; 2) Sorting and rating facilitated by the online platform [32]; 3) Analysis of data using quantitative and qualitative techniques to produce a visual concept map; 4) Con rmation and further interpretation of results using logic model transformation [41]. This study was approved by the Human Research Ethics Committee of Tasmania (reference number H0015769).

Participants
Participants were identi ed using a purposive sampling strategy which aimed to ensure representation from the following stakeholder groups: patients and carers, clinicians from a variety of disciplines, healthcare managers, educators and professional association representatives. Potential participants were invited to participate in one or more stages of the project. Junior doctors were recruited for the rating component. Approaches were made both directly by researchers, and through third parties who distributed the invitation via email. This study was conducted between October 2017 and October 2019 with participants across ve of eight Australian states and territories.

Generating ideas
Participants were invited via email to contribute responses using an online platform [32]. They were asked to complete the focus statement "An attribute or non-clinical competency required of doctors for effective practice in modern health-care systems is . . . " as many times as they liked. Participants were provided with the following de nitions: Attribute: A quality or feature regarded as a characteristic or inherent part of someone or something and does not depend on acquired knowledge; and Non-Clinical Competency: Transferable, generic professional skills which are not rooted in the medical profession. They may be carried out in a clinical or non-clinical environment by health-care workers but are not uniquely clinical in nature (e.g. communication related skills).
Statements were iteratively reviewed, re ned and synthesised with duplicates and irrelevant ideas removed, and similar ideas combined. Guidelines for this review process included determining whether statements needed to be split into more than one idea, elimination of repeated ideas, elimination of statements which were not relevant to the focus statements (e.g. health-care speci c clinical skills), and clari cation of content if required to ensure ideas were concise and understandable [31]. We determined data saturation through iterative synthesis and comparison of ideas as they were generated onto the online platform. Once we were satis ed that the point of saturation had been reached a research advisory group convened for the project which composed of ve clinicians from the disciplines of nursing, medicine and psychology, and one consumer, reviewed the statement list and provided feedback with regards to relevance of the statements to the research, clarity of statements, and completeness of the statement list to con rm saturation. A nal set of statements detailing attributes and non-clinical competencies was generated.

Sorting of statements
Participants were invited to sort the statements into groups in a way that made sense to them [31, p.72], and provide a relevant name for each group. This activity occurred online using the Concept Systems Global Max tm platform [32]. We set a minimum target of 30 sorters with representation from all stakeholder groups, which is in line with the recommended number (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) to provide reliable results while acknowledging that larger number of sorters yields higher inter-rater reliability estimates [42].

Data analysis for cluster map
A cluster map was built and labels determined using the online Concept Systems Global Max analysis program [31,32] which integrates qualitative and quantitative methods [43,44], in addition to a qualitative sense-making process.
A similarity matrix was created to identify how often statements were sorted together. Through the process of multidimensional scaling [45], this similarity matrix was then used to create a two-dimensional 'point map' of each statement to visually represent the sorting data, with statements sorted together more often placed closer on the map. A stress value statistic was generated as an indicator of how well the point map represented raw sorting data [42].
Hierarchical agglomerative cluster analysis using Ward's algorithm [46] was used to group statements into clusters. A bridging value was identi ed for each statement, indicating whether it was anchoringsorted primarily with others close by, or bridging -sorted with others across a larger area of the map. The option of imposing a lter on the analysis which would require statements to be sorted together more than one time was explored but did not signi cantly change the outcome and therefore was not utilised.
Determining the number of clusters relied on qualitative review by researchers [44] using interpretive analysis [47]. Statements in each cluster were examined from maps with ve through to 15 clusters, and using expertise in medical education and clinical medicine, the optimal cluster solution was determined [42]. This process was undertaken by one author (KO) and reviewed and con rmed by other authors and the research advisory group. Examination of statements was then made to determine whether there were any statements placed on a cluster boundary which were deemed to better t in an adjacent cluster and if so the boundary was changed.
Cluster labels were determined using three sources of information: GCM software provides list of 10 best t labels provided by participants [48]; the statement bridging values provided information about which statements are the most central to the cluster; and researchers read and synthesised their understanding of the statements in each cluster.
One author (KO) proposed cluster names, the other authors and research advisory group reviewed the decision and made alternative suggestions until agreement was reached. All participants in the GCM process were provided with a provisional set of results and invited to make comment over a 2-week period. A further seven clinicians were interviewed and their feedback on the relevance and utility of the model sought (not reported here). Feedback was considered by the research team for incorporation into the models.
Data analysis for logic model Subsequently we developed a logic model as a tool to further operationalise the data incorporating inputs, processes and activities, and outputs [49,50]. Impacts and outcomes are not incorporated in the model as they were not included as part of the initial concept mapping process, rather the logic model focuses on strategies [50]. Each statement was examined to determine whether it related to input, process or activity, or output elements. Statements which incorporated more than one of these categories were split into individual elements and re-worded to ensure that they were understandable. Each element was then grouped according to thematic similarity, starting with elements within the same cluster but incorporating those from other clusters if appropriate. Groupings were then examined for causal linkages between inputs, processes and activities, and outputs, including feedback loops. This process was performed by one author (KO) and the logic model reviewed by all other authors and the research advisory committee to provide input and ultimately con rm the model.

Ratings
Junior doctors were invited to rate each of the statements generated in the above process using Likert scales according to the following two prompts: 1. Relatively how important is this attribute or competency to your role as a doctor? (1=Relatively less important to 5=Relatively more important) 2. How well prepared were you when you graduated? (1=not prepared; 2=somewhat prepared; 3=reasonably prepared; 4=well prepared; 5=very well prepared) Data were entered directly onto a web-based platform. Ratings for each statement were averaged, to provide indicative representation of the relative importance and preparedness as reported by respondents for each statement. The nature of the scale and signi cantly skewed data warrants caution in further analyses, however these averages were used to produce visual tools to enable a 'birds-eye' view of the data. Importance and Preparedness ratings were graphed against each other for all data and for each cluster to produce 'go-zones'. Go-zones also allow for the identi cation of statements into one of four quadrants using the average of all statements to determine the distinction between high and low ( Figure  1).

Figure 1. Go-zone template
Averages were calculated for illustrative purposes for each cluster and clusters ranked according to leastmost important, and least-most prepared. A visual 'pattern match' was produced which demonstrates for each cluster, relative importance and preparedness, allowing the easy identi cation of clusters which are perceived as more or less important, and how this relates to perception of preparedness.

Participants
There were 67 participants, 43 (62.7%) female, from across the stakeholder groups contributing to brainstorming (51) and to structuring the statements through sorting (37), they nominated up to two roles in health-care (  The Concept Map Participants contributed 338 ideas which were iteratively reviewed and synthesised into statements, while at the same time evidence of saturation was sought. A detailed representation of this process is provided (Online Appendix, Item 1). The nal statement list consisted of 60 attributes and generic competencies.
Sorting data from 36 participants were analysed and statements located in a two-dimensional point map with a stress value of 0.259, which indicates a good t between the raw sorting data and the twodimensional con guration [42]. Participant and working group review of the concept model led to minor changes in wording. Interviews were conducted to elaborate on its relevance and utility however are beyond the scope of this report.
Hierarchical cluster analysis and interpretive analysis led to a seven-cluster concept map of attributes and generic competencies of required of doctors for practice in modern health-care systems (Fig. 2). Yellow dots in Fig. 2 represent each statement and their number. Close examination of the statements within each cluster led to four statements being moved from one cluster to an adjacent cluster (Online Appendix, Item 2). A summary of the construct of each cluster is provided (Table 2), however the full list is fundamental to the interpretation and meaning of the overarching map (Online Appendix, Item 3).

Value-led professionalism
Cluster 1 is underpinned by a professional commitment and work ethic, integrity, empathy, initiative and willingness to make time when needed. Elements relate to effective role-modelling and leadership; and conduct in a manner that is consistent with community expectations. Cluster 2. Attributes for self-awareness and re ective practice Cluster 2 is underpinned by curiosity, self-awareness, insight, resilience and perseverance. The ability to re ect and learn from failures, an awareness of limitations, and ensuring own well-being are also highlighted.

Cluster 3. Cognitive capability
Cluster 3 is underpinned by attributes which lead to cognitive ability, including exibility, analytical capacity, creativeness and innovation, situational awareness, resourcefulness and self-directed learning. Highlighted is the ability for decisive action, clarity of thought processes, and ability to manage uncertainty and ambiguity.

Cluster 4. Active engagement
Cluster 4 relates to a set of attributes and skills which promote full engagement between doctors and those who they work with -patients and colleagues. It includes the embracing of cultural diversity, responsiveness to the communication needs of patients, engaging in narrative, and ensuring seamless transfer of care through the health system. Highlighted are skills in negotiation and con ict resolution, effective interpersonal dynamics and working relationships, trust, and ability to manage differing agendas.
Cluster 6. Patientcentredness and advocacy Cluster 6 is underpinned by an approach to care which recognises the context in which patients exist, the importance of their priorities for care, and a willingness to advocate and prioritise activities for the bene t of patients. It is exempli ed by an agile and pragmatic approach to the delivery of individualised care, ability to assist patients to navigate the health-care system, maintaining respectful relationships, and a commitment to the notion of co-creation of health Cluster 7. Systems awareness, thinking and contribution Cluster 7 is underpinned by an awareness and understanding of systems and the organisational aspects of health-care, an understanding of the doctor's role within the system and the local community, leading collaborative care, commitment to the team, and courage to advocate for systemic change.

Logic Model
The 60 statements represented in the concept map were transformed into 51 input elements, 37 process/activity elements, and 35 output elements. This organisation of the data distinguished between attributes (input elements) and competencies (processes and activities), with the interaction of these leading to desirable outputs. Connections between elements were identi ed, including feedback loops, to produce a logic model. Through this process it emerged that there were three overarching domains or meta-competencies to the conceptual model, with signi cant interaction between the items from each cluster within the domains. These were: 1. Leadership and systems thinking: Incorporating Cluster 1: Value led professionalism and leadership, and Cluster 7: Systems awareness, thinking and contribution 2. Learning and cognitive processes: Incorporating Cluster 2: Attributes for self-awareness and re ective practice, and Cluster 3. Cognitive capability. 3. Interpersonal capability: Incorporating Cluster 4: Active engagement Cluster 5: Communication to build and manage relationships, and Cluster 6: Patient-centredness and advocacy.
Three logic models, one for each domain, were identi ed, with numbering indicating the cluster and statement number (e.g. 7-22 comes from cluster 7, statement 22). The models demonstrate the integration of clusters into domains or meta-competencies, with statements which spanned across domains are highlighted in italics. The model for Leadership and systems thinking is shown (Fig. 3), the other two are available in the Online Appendix (Item 4).

Go-zones For Individual Statements
All but one go-zones had positive correlations of between 0.45 and 0.77, indicating that items that respondents felt were more important, they were generally more prepared for (Online Appendix, Item 6). Cluster 2 however, showed a negative correlation between responses for Importance and Preparedness (Fig. 6), with one notable statement (43. A skill set that ensures own well being and an appropriate worklife balance) which rated highly for importance but lowly for preparedness. This is one of seven statements which rated above the overall average for importance and below the average for preaparedness (Table 3).

Discussion
Through participatory concept mapping, we have developed a conceptual model of attributes and generic competencies that are required for doctors to contribute effectively in modern health-care systems.
Harnessing the views and experience of multiple stakeholder groups, all of whom have regular contact with health-care systems, enabled a shared representation of these requirements into a seven-cluster concept map, represented in 60 statements of attribute and generic competency. Seven key areas were identi ed: Value-led leadership and professionalism; Attributes for self-awareness and re ective practice; Cognitive capability; Active engagement; Communication to build and manage relationships; Patientcentredness and advocacy; and Systems awareness, thinking and contribution. On examination, the statements could be transformed into a logic model of inputs (pre-requisite attributes), processes and activities (applied competencies), and outputs that can contribute to an optimal health-care. This empirically derived model represents the integrated views of a range of stakeholders. Unique to this model is the identi cation of links between these elements, through transformation into a logic model.
The explicit demonstration of how attributes and competencies are incorporated into practice through inputs, processes and activities, leading to desirable outputs provides educators with a translational blueprint upon which to map activities and ensure curricula opportunities to develop and demonstrate relevant behaviours. The logic model transformation highlights a clear distinction between attributes, identi ed as inputs in the logic models, and behaviours, identi ed as processes and activities.
As highlighted in the introduction, frameworks to guide medical education exist and provide comprehensive appraisal of both clinical and generic requirements. The post-graduate colleges are particularly advanced in framework development. CanMEDS [51] is one of the most cited frameworks and the attributes and generic competencies identi ed in this research are visible throughout CanMEDS.
However, our deliberate strategy to make explicit what is often tacit, by challenging our participants to focus attention solely on attributes and generic competencies, enabled us to detail a rich behavioural conceptualization of these aspects of doctoring. Mapping of the outcomes from this study to the CanMEDS framework showed that the vast majority of competencies in CanMEDS can be identi ed in the Concept Map, and vice versa, however highlighted that the items in the Concept Map are more behaviourally anchored and attributional, that is, they describe how the competencies in CanMEDS can be achieved through desirable attributes and their application in practice (Online Appendix 2).
Emphasised in this research are behaviors that have been identi ed by stakeholders who work in or engage with health-care systems, collectively in multiple ways, bringing a practicality to the outcomes of the research. A former president of the Royal Australasian College of Surgeons (Personal communication, J Batten, August 2020) noted on review of the model that "The professional colleges are looking for candidates who are trustworthy, diligent, an ethical team player who has leadership qualities and will model ideal behaviour for younger trainees and staff...someone they would be proud and pleased to work alongside. This model encapsulates and highlights these qualities and it is crucial that [pre-registration] medical education is able to deliver." Identifying candidates with the desired attributes provides a challenge for specialty program selection, with academic parameters heavily weighted and theoretical and conceptual frameworks for holistic and equitable selection lacking [52].
On examination, it is apparent that the attributes and competencies identi ed are transferable professional skills, required across a range of professional contexts. For example, the pre-requisite attributes (inputs) and activities (processes) which lead to trust, making a difference and contributing to community, ensuring quality, and advocating for change (all outcomes), are desirable attributes across many professions. Achieving rapport, possessing excellent communication skills, and achieving respectful relationships with patients/clients are relevant across the professional landscape, as do the cognitive skills of learning, decisive action, re ection and managing uncertainty. This a rms that we have achieved our objective of highlighting attributes and skills which are not speci c to the clinical setting, despite being important in the clinical setting. The notion of generic skills in education is not new [53], however differentiating generic skills from disciplinary knowledge can be challenging, and nding a way for different disciplines to interpret the skills in their context remains important [54]. In medical education, students need to be provided with opportunities to develop and practice generic skills [29], and explicating them can aid this process.
Fraser and Greenhalgh urge that we move beyond educating for competency, to educating for capability -"the ability to adapt to change, generate new knowledge, and continuously improve performance" [55, p. 799]. The product of this research highlights requirements of doctors that will lead to capability; medical educationalists are entrusted to provide opportunities for students to acquire, practice and master. Understanding these enables mapping of curricula and development of innovative pedagogies and opportunities required for capability and to transform the medical workforce to meet current and future health-care needs [55,56], moving beyond a reductionist approach [57]. The design of educational programs must adapt to ensure that future doctors are equipped for the challenges of modern healthcare, exempli ed by lens of complexity science on health-care systems [58,59,60].
Further work in identifying how to develop and teach these attributes and competencies is needed, however it is apparent that a wide range of opportunities will be required. The need to place greater weight on non-clinical competencies in medical education has been identi ed [61] as has a need for incorporation of systems sciences [62,63]. A small sample of newly graduated doctors rated each of the 63 attributes and competencies according to their perceived importance and their preparedness to perform in the way described on graduation. This group identi ed the cluster of statements relating to 'systems awareness, thinking and contribution' as relatively less important, and for which they were less prepared, compared with all other clusters. The nding is consistent with experiences in two medical schools in the US [64] where systematic introduction of a health-systems curriculum has been challenging on several fronts, one of the most notable challenges being mixed receptivity of students. The authors identi ed tensions in students' perception of their professional roles, not seeing systems reform as something which is important for them or feeling powerless to contribute [64]. Further, there are seven important items which were rated highly for importance, and lowly for preparedness. Although a small sample, this illustrates how the conceptual model can be used to inform medical education.
We acknowledge that there are limitations to this study. It is relatively small, undertaken in a limited geographic region and its external validity has not been demonstrated. However, mapping of the constructs and domains to existing competency frameworks provides some validation of the content of the model broadly, with this study a distinctive extension of existing frameworks due to the participatory concept mapping methodology it uses, the focus on a limited set of attributes and competencies, and the attitudinal and behavioural constructs that are identi ed. Ratings were completed by one distinct population with a limited sample, however they demonstrate how this methodology can be used locally to identify priorities in local areas, with the potential to survey other populations. Further work is required to determine how doctors acquire the attributes and competencies, and how they are enacted in clinical practice to lead to positive outcomes for patients and for the health-care systems. This can then inform the necessary educational opportunities that will lead to their acquisition.

Conclusion
Participatory concept mapping has proven useful to detail the attributes and non-clinical competencies required for effective practice in complex adaptive health-care systems. This can contribute to informing the education of students to operate effectively within modern health-care systems and be prepared for post-graduate training. They model has been operationalised through a logic model transformation and rating of items in the concept map. This allows the links between attributes, their functional application through competency, and the outputs that they lead to, for both patient care and health-care systems to be made clear, and priorities identi ed. There are three datasets generated from the study. The similarity matrix (representative of sorting data) and rating data are available as appendices. Data representing statements generated from brainstorming was iteratively edited and is di cult to represent simply. The authors are willing to provide this upon request, given a detailed explanation of the process undertaken is required to make sense of the spreadsheets on which they are stored.

Abbreviations
Competing interests