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Managing diversity

Managing challenges for learners

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The general practice workforce in Australia is now quite diverse, with more women in the profession, more overseas-trained doctors and doctors from different cultures. This may impact on the general practice’s learning environment and requires a flexible and adaptive approach to teaching.

Gender issues

Over half the medical students and a third of the GPs in Australia are now female. This change has happened quite rapidly and some workplaces are struggling with the changes this may bring.

General practices, like all workplaces must now be mindful of their workers’ needs relating to caring for children, pregnancy and parental leave, provision for breastfeeding mothers et cetera.

One of the difficulties for learners, particularly women who are still often the primary carers, is that they may be separated from families and children because of the distant location of their training term from their homes. This can create additional stress and may require negotiation around work schedules.

Recognising the different cultural issues relating to gender is important for patient care, but may also be important for learners and their supervisors. For example, some male learners may be reluctant to see a woman, particularly about any gynaecological problems.

Understanding and being respectful of broader gender issues, particularly those relating to the LGBTIQ community, is also an emerging component of general practice. Recognising and respecting the needs of patients, GP supervisors and learners is important.

Cultural issues

Being aware of cultural issues is important in any workplace in the Australian multicultural society. In general practice this applies to patients, practice staff and learners.

Training in multicultural health and refugee health in patient care is provided as part of formal curricula. However, it also needs to be recognised that cultural issues are not just important in the patient–doctor interaction but also in the student–teacher interactions in a teaching practice.

Some of the common issues to consider in cross-cultural exchanges between learners and supervisors are:

1. Communication

   Communication norms vary from culture to culture. One of the common areas of communication difficulty in ML teaching practices is the differing expectation of registrars about giving feedback on their performance. Some may take any constructive negative feedback very personally and not use it as a learning opportunity. Supervisors may need to be flexible and responsive to the learners in how they frame any feedback.

2. Team building

   The role and status of a doctor in a team varies from culture to culture and even from the general practice to the hospital sector. Some registrars may expect hierarchical team structures and deference in a general practice staff team and have difficulty relating to administrative staff.

3. Time

   Time is often viewed differently by different cultures. In some cases, work deadlines may not be considered as important as family obligations, which will take precedence. This can create misunderstandings between supervisors and learners.

4. Calendar events

   Different cultures celebrate different calendar events. Respecting the needs of learners to participate in and attend such events is important.

Aboriginal and Torres Strait Islander health

Aboriginal and Torres Strait Islander health training is a core component of the curricula of both Colleges and in Australian medical schools. Many learners, particularly overseas-trained doctors will have had limited experience with Aboriginal or Torres Strait Islander people, either as patients or as colleagues.

Setting up appropriate learning opportunities in practice is important; particularly ensuring the learner is culturally safe.

International medical graduates (IMGs)

A significant number of doctors training as GP registrars in Australia are IMGs. In addition, there are IMGs working under other work programs requiring supervision in some ML training practices.

Studies have revealed several issues that may arise for international medical graduates in their training:

1. Change in status

   Many IMGs have been trained and worked in other specialties in their countries of origin and have often held very senior roles. Returning to student or registrar positions is often difficult.

2. English proficiency

   High English proficiency is now part of the requirement for IMGs entering training; however, some difficulties may still be encountered, particularly with the Australian vernacular.

3. Communication skills with patients

   Communication norms vary in cultures. In some, the doctor is expected to tell patients what to do and not engage in a two-way dialogue. Learning new forms of communication with patients can be quite challenging for some IMGs. Learning to interact with a broad range of people effectively is a challenge for any learner in general practice, even more so for the IMG.

4. Expectations of teaching and learning

   Teaching methods and expectations vary from culture to culture. Some registrars will be more used to lecture-style, didactic forms of teaching and not be used to one-on-one case discussions with individual feedback on performance.

Learners can have difficulties in general practice for a variety of reasons and in the ML learning environment this can present challenges for the learning community. Early identification of specific learning issues for individuals is crucial and it is important that this is done in a safe environment, ideally a private conversation between supervisor and learner. With a range of leaners at different stages, it can also be challenging to identify the specific learning issues for different stages of training and expectations for that stage of training. In an ML learning environment, learners will likely compare themselves to each other and this can create confusion as to expected level of competence for each stage. For example, a third-year medical student may compare themselves to a registrar and feel inadequate in knowledge and skills when they are actually at an expected level of competence. Below is a case study which gives an example of how to manage different level learners so there is a focus on their competence and their needs as opposed to their gaps.

Supervisors need to be skilled and able to provide one-on-one attention to learners separately and to provide feedback specifically to a learner in difficulty. Often there is not a global problem but a specific area that learning and teaching needs to focus on. This identification and development of a learning plan is best done by an experienced supervisor, but other members of the team can be involved in addressing the learning plan. In an ideal learning environment, 360-degree feedback would be part of an assessment, either formally or informally. It is also a risk that in an ML learning environment a quiet, poorly performing student or junior doctor can fall under the radar if they are not assessed and monitored through other feedback activities such as individual observation of consultations or audits.

Possible signs that an individual learner is struggling.

• Avoiding teaching sessions.

• Not being willing to ask questions or contribute within an ML teaching session.

• “Not asking for help.” A learner who never asks a supervisor for help with a patient or what to do in a specific situation is very unusual and is always a red flag for potential issues.

• A junior learner who only asks near-peers for help, but never their allocated supervisor.

• Patient complaints—reception staff may hear complaints from patients at the front desk as they leave slightly disgruntled. This is very important in the context of parallel consulting.

• Poor note keeping.

• Running late all the time.

• Not following up with patients or learning tasks set by the supervisor.

• Poor interaction with staff, both medical and administrative.

• Emotional overreactions to situations or staff.

• Highly defensive attitude to feedback.

• Highly critical of others in the treating team.

An approach to identifying the learner in difficulty is to consider what the specific issue for the learner is and how to manage this individually and within an ML learning environment. This applies at all stages of training.

The learner with difficulty

In this scenario the learner has poor medical knowledge or skills and may or may not be aware of their knowledge gaps and limitations. Often the problem is not with knowledge as such, but with clinical reasoning and application of knowledge in the real-world context of patient care. This will obviously depend on the stage of the learner. Medical students, for example, are of concern if they have huge gaps in basic science knowledge but would be expected to be in the early stages of applying clinical reasoning to patient care and it is likely that their management skills are minimal. However, by a senior registrar level it would be expected that the registrar is fairly competent in clinical reasoning, has high level communication skills and is able to come up with a relevant management plan.

An ML tutorial as described in the case study can actually help these struggling learners by modelling and normalising gaps in knowledge and clinical reasoning. For example, if a registrar has poor clinical reasoning skills then a tutorial with medical students that explores the diagnosis and differential diagnoses will be helpful but non-threatening as it is targeted to the student.

The learner in difficulty

Consider whether the learner has difficulties outside the practice setting which impact on their performance? Are there personal issues at home, medical issues such as anxiety, depression or a physical health issue? Are there family problems or financial issues that are impacting? Many students will have part-time jobs they need to get to after-hours so as to support themselves. Students and junior doctors with young children may need to get to child care to pick up their children. Students and registrars are often doing hours of private study after-hours to prepare for exams while trying to balance this with family demands. All these issues may impact on the learner being able to attend ML tutorials and learning opportunities.

Maximising efficiency of learning is probably crucial for the learner in difficulty. Allowing a student to leave earlier rather than forcing them to stay for a whole session is likely to enhance learning rather than diminish it. Multi-level tutorials are rarely useful at the end of the day when people are tired and need to get home to meet personal and family needs. Focusing learning towards exam preparation and assessment will be helpful when specific exams are coming up for either students or registrars.

The difficult learner

The learner with intrapersonal or professional problems can be very challenging to an ML learning environment in which teamwork and communication are essential. The difficult learner can have issues with working in teams, communicating with other staff, taking responsibility, boundary setting and often even attendance. Some of them are just chaotic and poorly organised, with no insight into how this impacts patient care and learning. Sometimes their interpersonal skills can impact on others in the learning community through harsh criticism, negativity, bullying and even harassment. They can affect the tone and atmosphere of a practice if they are unhappy with rostering, supervision, scope of work and workload. If the issues are not addressed early these learners can have a huge effect on the learning experience for all, particularly medical students, as they infect the learning culture with their negativity. It is important to remember that some of these learners will come across as looking very arrogant and confident but underneath they are feeling anxious, overwhelmed and under siege. With these learners it is important that their designated supervisor meets with them individually to debrief and unpack what is going on for them and address early expectations about respect, teamwork and communication within the ML learning team. Learners who have just come out of the hierarchical hospital environment can take some time to adapt to a more egalitarian way of relating in the general practice environment.

However, it can be beneficial to use the ML learning tutorial to cover topics such as professionalism and team communication as a way to diffuse the conversation between the supervisor and the ‘difficult learner’ and thereby normalise and set expectations for all members of the team. If well facilitated, an ML discussion can allow students and doctors to express their vulnerabilities and gain support from each other. An example is normalising that it is okay not to always have an answer. If senior GPs discuss how they struggle with uncertainty and are comfortable with looking things up when they need to they model learning as a lifelong skill. Students and registrars realise it is okay to not know so long as you then go and find the answer.

The learner who doesn’t contribute to tutorials — Organise a roster ahead of time so their tasks are clearly set for specific dates and contributions are shared equally between all participants. During group learning formalise people’s contribution so that everyone has a chance to contribute. For example, go around in a circle and give everyone a chance to express their opinion or say what they think.

The learner who needs to be the expert all the time — Engage them in bringing complex cases for discussion where there is no answer. Invite them to ask questions rather than give answers in tutorials. Engage the group in questions about best practice and how that relates to this patient. Students have often been taught ideal, evidence-based medicine but are yet to understand evidence-based practice that involves the patient’s desires or decisions.

The learner who is chaotic or disorganised — This person may need clear guidelines or a timetable for certain duties that are not being carried out. For example, the supervisor may say: “You will be expected to present a case in two weeks. Let’s discuss in one week what case you might choose.” Learning plans and breaking tasks or goals into small chunks may assist these learners.

The enthusiastic learner who wants to contribute all the time — These learners are often engaging and make positive contributions, but if they dominate then they can stifle other people’s learning. It can be helpful to give them a job as scribe on a whiteboard or looking up evidence. If they are registrars, engage them in developing teaching skills and improving their feedback and listening skills. Discussion about teamwork can also help these learners gain insight.

Finally, if a specific learner continues to have difficulty or be challenging then it is very important to get help. Most universities and training organisations will have a nominated person to talk to about your learner and the issues you have. Make sure you contact them early on and get support and help with the issues. In medical training there has been a long history of ‘difficult’ students or trainees being identified right at the end of a placement and then moved on without a chance for remediation or behavioural change. Supervisors just tried to avoid them and the issue and, in the process, have let the learner down. If we care about patients, then we need to care about the difficult learner so as to help them practise high-quality care in the future.

Not all GPs in a practice want to teach or be a supervisor. Many GPs have never had training in supervision or teaching. It comes easily to some and not to others. However, for an ML learning practice, it is crucial that there is a team of at least two supervisors to support and help each other, otherwise it is likely to lead to early burn-out. Supporting new supervisors is very important. Start out by engaging them in some of the teaching activities or parallel consulting. Then give them responsibility for supervision and oversight of one of the learners in the practice. For many supervisors, starting with supervision of medical students is easier than registrars because there is more control over knowing what the student is doing and less potential for error in patient care because of the very close supervision. Most students are in the practice for a much more limited time than a registrar placement. When recruiting new doctors to an ML learning practice it is important to be up-front about the expectations of GP staff about contributions to teaching.

Evaluating your effectiveness as a supervisor is important but can be challenging when you have such a close relationship with the learners. Other factors such as pay, assessment and working conditions will all affect your relationship with registrars. It is important to get feedback about your teaching and learning environment in an anonymous way, if possible, so the learners can be honest and open. This can often be provided through university and training organisation feedback processes, but it doesn’t always address what a supervisor is keen to know. Rather than a survey, an exit discussion with your practice manager may be a way of gaining feedback. Learners can have high expectations of what they will achieve, so it is important to recognise your limitations as a supervisor and acknowledge that you can’t do everything for everyone. Your practice itself may have limitations in terms of patient characteristics, style of practice and senior role models.

Pilotto LS, Duncan GF & Anderson Wurf J. Issues for clinicians training international medical graduates: a systematic review. Med J Aust 2007; 187(4):225–228.

This article gives a good summary of the issues the supervisors may face in teaching IMGs in their practices.

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