Professional Identity Formation,Professionalism,Leadership and Resilience (PILLAR) in Medical Students: Methodology and Early Results

Abstract

Objectives

The fundamental role of medical education is the transformation of students to doctors, through a process of education and professional identity formation (PIF), which can be informed by several educational, behavioural and emotional factors. PIF has been deemed to be of equal importance to the acquisition of clinical knowledge and skills and includes constructs such as professionalism, leadership and resilience. We aimed to assess professional identity formation, professionalism, leadership and resilience (PILLAR) in the junior years of medical school in the 2020/2021 academic year and illustrate the potential role of quantitative assessment to demonstrate progression in these areas. In this research, we provide the methods and baseline results for the PILLAR study.

Methods

We implemented a compulsory assessment in pre-clinical years of graduate entry and direct entry medicine at the Royal College of Surgeons in Ireland University of Medicine and Health Sciences, Dublin, Ireland. Validated scales were used to assess students’ PILLAR. Descriptive and univariable statistical techniques were used to compare student scores between respective years.

Results

A total of 1311 students (92% response rate) provided their consent for research. For the psychometric scales, there were no evident trends among the years on these assessment measures. Results indicated significant differences in all measures, however, these did not correspond to ascending years of seniority.

Conclusion

The PILLAR methodology provides important information on the challenges of quantitatively assessing medical students in the four key areas of PIF, professionalism, leadership, and resilience. Our cross-sectional results point to cohort effects, without the expected progression per year in the cross-sectional data, or suggest that the chosen quantitative measures may be problematic for these constructs in pre-clinical students. Therefore, while we believe that PILLAR has potential as a progress test for these constructs, this will only truly be elucidated by repeated measures of each cohort over time.

Keywords

medical education research PIF professionalism leadership resilience progress testing

Introduction

The fundamental role of medical education is the transformation of students to doctors, through a process of education and professional identity formation (PIF). The paradigm of PIF is complex, multi-factorial and closely linked to societal expectations, and both personal and social identity.¹ It has been described as a core component of post-Flexnerian medical education^2,3 and can be significantly impacted by university programmes.^4,5 Professional identity may be defined as ‘A representation of self, achieved in stages over time during which the characteristics, values, and norms of the medical profession are internalized, resulting in an individual thinking, acting, and feeling like a physician’.³ In order to support the development of a professional identity in medical education, a cognitive base should be included as an educational objective in the formal curriculum and students should be engaged in the development of their own identities.^6,7 Specifically, experiences during clinical education have been identified as key contributors to the student's development of their professional identity.^8–10

The theoretical framework that underpins PIF recognizes the importance of facilitating student engagement with communities of practice, emphasizing the social nature of learning.¹¹ This framework proposes that learning is a social activity which takes place in communities that are heavily influenced by history and culture,^12,13 and that full participation requires the achievement of community-determined standards of competence within the chosen domain (practice of medicine).¹⁴ If PIF is to be a significant educational objective, robust assessment or indicators of its achievement should be established.⁷ Historically, the summative assessment of professional behaviours has been used as a surrogate for PIF,⁷ supplemented by formative methods in which learners are asked to chart their own progress over time. However, there is a dearth of literature relating to quantitative assessment of PIF, with the majority of research into professional identity conducted using qualitative methods.^5,8 Medical schools need further information on the assessment of PIF and its subcomponents so that students are appropriately supported to develop their professional identity. Therefore, while qualitative research has provided researchers with a critical understanding of professional identity in undergraduate students, and educational research tells us that learning is not only cognitive and behavioural, but also emotional, social, affective and socio-cultural,^15,16 quantitative methods would provide additional statistical evidence to further support qualitative research findings and assist with educational design and decision-making.

Professionalism, emotional resilience, and leadership are key elements in forming a personal and professional identity.^1,17 In addition to supporting the development of a professional identity, teaching professionalism is considered a key aspect of medical education.^18,19 Notably, unprofessional behaviours can now warrant dismissal from medical school.²⁰ The need to strengthen the assessment of professionalism has been highlighted, and that method of assessment should match the definable elements of professionalism²¹ in terms of its individual, interpersonal and societal dimensions, resulting in a need to consider multidimensional assessment.²² Along with the characteristics of professionalism, future doctors will need to have leadership capability in order to influence and manage change on the front line of healthcare.²³ Concerningly, reports suggest a lack of leadership training at the undergraduate level.²⁴ For medical schools that incorporate leadership development programmes, the majority evaluate their learning through self-assessment or self-report measures.^25,26 To our knowledge, leadership has not yet been assessed as a core component of PIF, or its potential contribution to PIF identified.

Learning the key skills of emotional resilience is also core to the development of PIF. Resilience is defined as the process and outcome of successfully adapting to difficult or challenging life experiences, especially through mental, emotional, and behavioural flexibility and adjustment to external and internal demands.²⁷ Medical school is challenging and educators have recognised that the stress of medical school can be significant, including impact from academic pressures, educational debt, personal life events, gender identity, learning environment, and exposure to human suffering.^28–30 We have previously published a study, using this study's methodology, which demonstrated a high incidence of depression, anxiety, burnout, and comorbidity in medical students.³¹ There is an increasing recognition of the importance of self-awareness and self-care for the health and well-being of healthcare professionals,³² brought into sharper focus by the COVID-19 pandemic.³³ It has been suggested that robust professional identity development could also prove protective against medical burnout³⁴ by making physicians more resilient. However, an assessment of resilience in medical students and the potential correlation with PIF has yet to be determined.

Aim

The study aimed to develop a method for the assessment of the PIF, professionalism, leadership and resilience (PILLAR) – the PILLAR assessment. We aim to report this method and explore differences among years on the outline constructs.

Our main objectives were to descriptively examine PILLAR across a cohort of medical students. Our second objective was to examine if there was a relationship between these measures and the year of medical training of the students. Ethical approval was sought and obtained from the Royal College of Surgeons in Ireland (RCSI) Research Ethics Committee prior to conducting the study (REC202005016).

Methods

All methods were carried out in accordance with relevant guidelines and methodology approved by the RCSI Research Ethics Committee. The methods are reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist for reporting results of cross-sectional observational studies (Appendix A).³⁵

Design

The study was a baseline cross-sectional assessment of the entire cohort of medical students in the RCSI University of Medicine and Health Sciences, Dublin, using established quantitative measures. At the RCSI, there is a five-year direct entry medicine (DEM) programme, along with a four-year graduate entry medicine (GEM) programme. DEM and GEM classes combine for the final two senior years. Furthermore, there is a foundation year (FY) programme completed by a proportion of students (approximately 50%) prior to commencing the DEM programme. Due to the involvement of a large cohort of students (entire years), it was decided that an online assessment would be the optimal method for data collection.

We did not receive any funding for this study so we were limited in the scales available to us. We conducted a comprehensive literature search to identify suitable scales. An expert panel composed of educationalists, psychologists and clinicians agreed by consensus on the most appropriate scale for each of the four constructs within PILLAR, based on the appropriateness of content, psychometric validity, appropriate population focus, reliability and free accessibility (Appendix B). The length of each measure was also a key concern to be mindful and respectful of students’ time, especially to facilitate future longitudinal study, and to ensure satisfactory completion rates. A 76-item questionnaire (Appendix C) was compiled, combining four validated scales along with a selection of demographic questions.

Following the completion of a pilot study (n = 9 participants), where it was identified that no major changes to the format were required, the PILLAR study assessment was embedded within modules in each pre-clinical year as a core element of the professionalism curriculum. While completion of PILLAR was compulsory, students gave voluntary, fully informed consent (or not) for their data to be used for research purposes, as per previous research.^36,37 Students were reassured that their decision to consent to their data being used for research would have no impact on assessment grades and faculty would not be aware of students who did or did not consent to their data being used in this research. The assessment responses were anonymised. Akin to progress testing, we incorporated a student feedback loop providing students with their individual responses to each question along with general feedback on the results (class averages).

Data collection

PILLAR was administered by the RCSI Quality Enhancement Office (QEO), which acted as the study's independent data controller, using online survey software. PILLAR was pseudonymised in order to assign respective credits to students for completion. On receipt of responses, the QEO fully anonymised the results so that any identifiable data had been erased prior to the transfer of data to the study research team.

In advance of the administration of PILLAR and invitations to participate being sent to students, the study investigators gave brief presentations to each year introducing the assessment. At those class times, the QEO sent out an automated, personalised email to every eligible student with an individualised link to complete the assessment as part of the assigned module, followed by two weekly reminders. The individualised link took participants to an online participant information leaflet and consent form where they consented or declined that their information may be used for the purposes of research.

Sample

During September 2020 and February 2021, all students in FY (pre-medicine), years 1–3 of undergraduate DEM, and years 1 and 2 of GEM completed the assessment and were invited to participate in this study (n = 1427).

Measures

Measures incorporated in the assessment included a measure of each of the core PILLAR constructs of PIF, professionalism, resilience, and leadership, as follows:

Professional identity formation (PIF)

PIF was assessed using a 9-item questionnaire with nine themes, which included common domains of professional activity for healthcare professionals.³⁸ The themes were teamwork, communication, patient or client assessment, cultural awareness, ethical awareness, using patient or client records, dealing with emergencies, reflective practice and teaching. Participants were asked to indicate on a scale of 0 (indicating a first-day student doctor) to 6 (indicating a newly qualified doctor) how they would feel at present undertaking a list of nine activities, with each activity reflecting one of the nine themes. A higher mean score reflected a higher professional self-identity score.

Through feedback from our pilot study, it was decided to include one further item relating to PIF: ‘I feel like a member of the medical profession’ to which participants were given five response options from strongly disagree to strongly agree, with lower scores indicating lower levels of PIF.

Professionalism

The scale for professionalism examined both student perceptions of and participation in unprofessional behaviours.³⁹ Participants were asked to consider 25 statements and then answer if they had observed the behaviour, participated in the behaviour and stated whether they felt the behaviour was professional or not. For each behaviour, listed, descriptive statistics were used to describe student observation of, participation in, and perception of the behaviour as unprofessional.

Leadership

We used the medical leadership competency framework (MLCF), which outlines the competencies expected of practising clinicians.²³ The MLCF has been demonstrated to aid curriculum design, highlight individual strengths and development areas through self-assessment, and assist with personal development planning and career progression.²³ Participants were asked to self-assess in two areas only – demonstrating personal qualities and working with others, totalling 15 items. We assigned a scoring system to identify the average for each domain where a lot of the time = 2, some of the time = 1 and very little/none of the time = 0, with higher total scores indicating higher levels of leadership.

Resilience and Well-Being

Two measures were chosen to investigate resilience and well-being – the brief resilience scale (BRS) and the EPOCH Measure of Adolescent Well-Being.^40,41 The BRS was chosen to measure resilience because it is a short, validated measure that is simple and widely used.^42,43 Participants are asked to self-assess on a 5-point Likert scale of agreeableness against six specific statements describing their typical response in relation to bouncing back or recovering from stress, with higher scores indicating greater resilience.⁴⁰ EPOCH measures five positive psychological characteristics that together support higher levels of well-being: engagement, perseverance, optimism, connectedness, and happiness. This measure is composed of 20 items, with item responses rated on a 5-point scale ranging from 1 for ‘never’ to 5 for ‘always’. Scores are calculated for each domain as the average of the four items.⁴¹

Statistical Analysis

Stata v.16 was used for cleaning and statistical analyses.⁴⁴ Descriptive statistics were used to profile the demographic characteristics of participants. Means and standard deviations (SDs) were calculated for continuous variables and total scale scores. Linear regression analysis was carried out to explore potential differences across years.

Results

A total of 1427 students were invited to complete the PILLAR assessment, with n = 1331 (93%) students responding and n = 1311 (92%) consenting to their data being used for research. If a measure was missing >60% of the data, the results from that participants’ measure were not included in the analysis. Sample descriptive statistics are presented in Table 1. The mean age was 22 ± 3.0 years with just over half of the participants being female. In terms of country of origin, the majority of students were from four individual regions/countries, the Middle East (29%), North America (21.3%), Ireland (16.5%) and Malaysia (11.5%), reflecting the diversity of our student population.

Table 1.

Participant demographics.

Demographics	Foundation year	DEM year 1	DEM year 2	DEM year 3	GEM 1	GEM 2	Overall
Consented responses/recipients	158/182	362/388	329/353	293/ 327	81/87	88 /90	1311/1427
Response rate	87%	93%	93%	89%	93%	98%	92%
Age (years)
Mean (SD)	19 (±1.7)	21 (±2.9)	22 (±2.8)	22 (±2.5)	24 (±2.1)	26 (+3.4)	22 (±3.0)
Gender
Male	n = 78 (44%)	n = 156 (44%)	n = 133 (40%)	n = 116 (40%)	n = 39 (48%)	n = 34 (38%)	n = 556 (43%)
Female	n = 71 (46%)	n = 199 (55%)	n = 191 (58%)	n = 166 (58%)	n = 42 (52%)	n = 52 (59%)	n = 721 (56%)
Non-binary/prefer to self-describe/prefer not to say	n = 5 (4%)	n = 4 (1%)	n = 5 (2%)	n = 5 (2%)	–	n = 3 (3%)	n = 21 (1%)
Nationality/region of origin
Ireland	n = 5 (3%)	n = 49 (13%)	n = 46 (14%)	n = 48 (17%)	n = 28 (35%)	n = 20(23%)	n = 230 (16.5%)
North America	n = 30 (20%)	n = 38 (11%)	n = 53 (16%)	n = 51 (18%)	n = 41 (51%)	n = 52 (58%)	n = 297 (21.3%)
Malaysia	n = 2 (1%)	n = 53 (15%)	n = 65 (20%)	n = 39 (14%)	n = 1 (1%)	n = 0	n = 162 (11.5%)
Middle East	n = 92 (60%)	n = 128 (36%)	n = 84 (25%)	n = 91 (31%)	n = 1 (1%)	n = 2 (2%)	n = 411 (29.4%)
Other	n = 24 (16%)	n = 90 (25%)	n = 81 (25%)	n = 58 (20%)	n = 10 (12%)	n = 15 (17%)	n = 297 (21.3%)
Total	n = 158	n = 362	n = 329	n = 293	n = 81	n = 88	n = 1311

Abbreviations: DEM, direct entry medicine; GEM, graduate entry medicine; SD, standard deviation.

Table 2 provides means and SDs of each scale by year of medical training. Table 3 provides the results of the regression analysis by year of intake, using FY as the comparator group. In comparison to FY, GEM1, GEM2 and DEM year 1 had significantly higher resilience scores, but this pattern was not seen for DEM year 2 or DEM year 3. GEM2, DEM year 2, and DEM year 3 had significantly lower engagement scores, with year 2 and year 3 also having significantly lower perseverance and optimism scores than FY. Only GEM1 had higher connectedness scores, while only year 1 had higher happiness scores. In terms of leadership (working with others), there were no significant differences from FY, except that year 3 had lower scores. GEM1 and GEM2 had higher leadership (personal qualities) scores, but there were no differences among DEM years compared to FY. The PIF results indicated that GEM1 were less likely to report feeling like a member of the medical profession than FY. They were also less likely to rate themselves as feeling like a qualified doctor than FY, whereas GEM2 and Year 3 scored higher than FY on this scale. Overall, there was no clear consistent evidence of increasing or decreasing scores by cohort.

Table 2.

Means and standard deviations for each variable of interest when stratified by year of assessment.

Mean (SD)	BRS	EPOCH engagement	EPOCH perseverance	EPOCH optimism	EPOCH connectedness	EPOCH happiness	Leadership working with others	Leadership personal qualities	PIF 1 member of medical profession	PIF 2 first-day student Dr – qualified Dr
FY	3.16 (± 0.68)	3.00 (±0.77)	3.57 (±0.88)	3.48 (±0.95)	4.04 (±0.88)	3.31 (±0.97)	1.63 (±0.30)	1.48 (±0.28)	3.44 (±1.03)	1.64 (±1.55)
DEM year 1	3.36 (± 0.80)	2.89 (±0.77)	3.63 (±0.77)	3.51 (±0.85)	4.14 (±0.85)	3.50 (±0.85)	1.60 (±0.33)	1.50 (±0.33)	3.66 (±0.99)	1.61 (±1.38)
DEM year 2	3.23 (± 0.75)	2.81 (±0.88)	3.29 (±0.88)	3.19 (±0.95)	3.92 (±0.93)	3.18 (±0.97)	1.60 (±0.33)	1.46 (±0.32)	3.53 (±0.93)	1.90 (±1.31)
DEM year 3	3.10 (±0.8)	2.79 (±0.88)	3.38 (±0.89)	3.22 (±0.95)	3.92 (±0.97)	3.18 (±0.96)	1.53 (±0.36)	1.45 (±0.33)	3.49 (±1.01)	1.81 (±1.31)
GEM 1	3.57 (±0.68)	2.98 (±0.74)	3.71 (±0.76)	3.43 (±0.80)	4.41 (±0.66)	3.47 (±0.85)	1.60 (±0.29)	1.57 (±0.56)	3.01 (±0.98)	0.91 (±0.80)
GEM 2	3.51 (±0.72)	2.64 (±0.78)	3.40 (±0.83)	3.39 (±0.87)	4.16 (±0.85)	3.30 (±0.90)	1.61 (±0.34)	1.55 (±0.27)	3.46 (±0.84)	2.11 (±0.88)
Combined total	3.27 (±0.75)	2.84 (±0.83)	3.47 (±0.85)	3.34 (±0.92)	4.06 (±0.90)	3.30 (±0.94)	1.60 (±0.33)	1.49 (±0.31)	3.51 (±0.98)	1.81 (±1.36)

Abbreviations: BRS, brief resilience scale; PIF, professional identity formation; FY, foundation year; DEM, direct entry medicine; GEM, graduate entry medicine.

Table 3.

Beta coefficients and 95% confidence intervals for the relationship between the year of assessment and each variable of interest.

	BRS	EPOCH engagement	EPOCH perseverance	EPOCH optimism	EPOCH connectedness	EPOCH happiness	Leadership working with others	Leadership personal qualities	PIF member of medical profession	PIF first-day student Dr – qualified Dr
FY	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref	Ref
DEM year 1	0.206* (.066, .345) 0.004	−0.105 (−.260, .0503) 0.185	0.058 (−.104, .217) 0.488	0.038 (−.135, .211) 0.666	0.137 (−.0324, .306) 0.113	0.184† (.009, .359) 0.040	−0.028 (−.092, .035) 0.380	0.0256 (−.033, .085) 0.394	0.218† (.032, .405) 0.022	−0.024 (−.290, .243) 0.862
DEM year 2	0.0694 (−.072, .211) 0.337	−0.180† (−.338, −.023) 0.025	−0.282* (−.444, −.119) 0.001	−0.284* (−.459, −.109) 0.001	−0.114 (−.286, .057) 0.191	−0.135 (−.313, .043) 0.136	−0.030 (−.094, .035) 0.368	−0.021 (−.080, .039) 0.493	0.092 (−.097, .280) 0.342	0.263‡ (−.006, .533) 0.056
DEM year 3	−0.0592 (−.204, .086) 0.423	−0.197† (−.358, −.037) 0.016	−0.185† (−.351,−.019) 0.029	−0.259* (−.439, −.080) 0.005	−0.0932 (−.268, .082) 0.296	−0.129 (−.310, .053) 0.165	−0.097† (−.170, −.031) 0.004	−0.025 (−.086, .036) 0.414	0.049 (−.144, .242) 0.620	0.175 (−.099, .448) 0.210
GEM 1	0.417* (.219, .615) <0.001	−0.0198 (−.241, .201) 0.860	0.132 (−.097, .362) 0.259	−0.045 (−.290, .200) 0.718	0.380* (.138, .621) 0.002	0.153 (−.097, .402) 0.230	−0.035 (−.126, .056) 0.450	0.090* (.007, .174) 0.007	−0.428* (−.693, −.164) 0.002	−.730* (−1.104, −.356) 0.000
GEM 2	0.352* (.159, .545) 0.000	−0.346† (−.561, −.132) 0.002	−0.175 (−.396, .046) 0.121	−0.087 (−.325, .151) 0.473	0.129 (−.105, .363) 0.280	−0.0183 (−.261, .224) 0.883	−0.0190 (−.107, .069) 0.673	0.0758‡ (−.005, .156) 0.065	0.020 (−.237, .276) 0.879	0.476† (.102, .850) 0.013

Abbreviations: BRS, brief resilience scale; PIF, professional identity formation; FY, foundation year; DEM, direct entry medicine; GEM, graduate entry medicine.

*p < .01. †p < .05. ‡p < .1.

Appendix D shows the results of the professionalism scale and indicates in each year what percentage of students perceive the respective statements as unprofessional behaviour. This table also includes the percentages of students who have (A) observed and or (B) participated in the behaviour statements. Overall, ≥75% of the entire cohort deemed that 19 out of the 25 behaviours were unprofessional. Precisely, 90% of FY students responded being intoxicated at school events as being unprofessional in comparison with 73% of DEM year 3 students. There was a similar difference between DEM year 1 and year 3, with 90% DEM 1% and 75% of DEM year 3 participants identifying Using workrooms for nonclinical activities as being unprofessional behaviour; 52% of DEM year 3 students reported being absent from mandatory lectures as unprofessional in contrast with 24% of DEM year 1 students.

Discussion

This study presents the development of a method for the quantitative assessment of PILLAR in a large group of medical students. Precisely, 1311 (92%) eligible participants consented to their data being used for research. Results indicate that student engagement, connectedness, and happiness may decrease as students progress through medical school. In addition, results suggest that students’ opinion of their leadership skills decreases in relation to ascending year of seniority. Regression analysis demonstrated significance among years on certain variables, however, there was no clear consistent evidence of increasing or decreasing scores by cohort.

Strengths and Limitations

To our knowledge, this is the first time PILLAR has been assessed in combination across a large cohort (n = 1427) of medical students and thus a range of perspectives attained. A strength of our cohort was that it included a wide range of nationalities (n = 52). Through our methodology, we ensured an excellent response rate (93%), reducing the study's non-response bias and strengthening the results. A further strength of this study is that most other research in this area is purely qualitative⁵ and the proposed methodology herein provides an important supplement to further the existing understanding of professional identity provided by previous qualitative findings.⁸ This study establishes PILLAR as a method to quantitatively assess the four areas of interest and has demonstrated the feasibility of administering a combination of validated scales. Future work will examine PILLAR's potential to test the effectiveness of curricular interventions in these areas as part of formative feedback and summative assessment. We also intend to explore the relationship between PIF, gender, and region of origin along with other findings in future research.

A limitation of this research is that a cross-sectional study of this kind can only imply association, not causation. However, future work will demonstrate the longitudinal progress of students in these areas. Another limitation is that a power calculation was not completed for our study as we assessed the entire student classes per year, however, the large sample size provides sufficient power to detect moderate effects, and power will increase over time as repeated measures are used. It is important to note that the assessment was not carried out at the same time or place for all participants, which may have affected the results. A further limitation is that the other elements of PIF, such as empathy, advocacy, and reflection, were not assessed in our study. However, empathy and advocacy are introduced to the students in year 1 and they submit reflective assignments at intervals throughout their medical training. Our focus was on professionalism, leadership, and resilience as they are important components in our new curriculum and may potentially benefit from continuous assessment. We have identified that the validated scales do not seem to discriminate consistently over the years. It is unclear as to why this is but it could be attributed to cohort effects, changing curriculum or a lack of formalised curricular input on each of these concepts. Future iterations of PILLAR, with longitudinal data for each student, will shed light on these issues.

In the years 2020 and 2021, when this research was carried out, the fundamental principles of professionalism, leadership, and resilience have all been tested as never before. The emergence of COVID-19 has had an impact on global health and society that is unprecedented in modern times. In addition, it has significantly disrupted medical education and demanded rapid attention from medical educators.^45,46 Furthermore, the ‘hidden’ medical learning environment has changed with the learning opportunities from interactions with faculty, peers, patients, and university staff being modified or limited. PILLAR was conducted in this context, so it may have influenced the results. We are very cognizant of the potential impact of clinical rotations on students’ PIF, professionalism and resilience.^10,30,47 PILLAR has been designed as a longitudinal study and we plan to continue administering PILLAR in subsequent years – with clinical years also being included. We intend on accruing data from the pre- and post-clinical rotation time points and analysing the potential impact of commencing clinical rotations on students' PIF.

Despite the limitations outlined above PILLAR can offer important insights. Evidence from other research indicates that attitudes to professionalism can worsen over medical school training and some of our results are supportive of this.^19,48 Therefore, while there is extensive literature on the teaching and assessment of PIF, there is a significant need to explore its quantitative assessment and its subcomponents, over time. This process of assessing students repeatedly and combining their results on these assessments referred to as ‘progress testing’, has been demonstrated to be a valuable way of making predictions about future competence and/or performance.⁴⁹ Progress testing has been demonstrated to be of value by undergraduate medical students and deemed to be a useful assessment to support their learning needs, allowing students to focus on learning and understanding ideas instead of rote learning facts.^50–52 Furthermore, it has been communicated that it produces a reduction in assessment-associated stress.⁵³ Incorporating PILLAR at regular intervals would allow evaluation and tracking of PIF at individual and cohort levels, as well as monitor the impact of focused curricular changes. The next iteration of this study plans to explore whether the principles of progress testing can also be applied to quantitative PIF assessment. This research has been published as a pre-print.⁵⁴

Conclusions

The PILLAR methodology provides important information on the challenges of quantitatively assessing medical students in the four key areas of PIF, professionalism, leadership, and resilience. Our cross-sectional results point to cohort effects, without the expected progression per year in the cross-sectional data, or could suggest that the chosen quantitative measures may be problematic for these constructs in pre-clinical students. Therefore, while we believe that PILLAR has potential as a progress test for these constructs, this will only truly be elucidated by repeated measures of each cohort over time.

In medical education, we have an obligation to ensure that the next generation of clinicians have the resilience, leadership skills, and professional behaviours to deliver/ provide safe and high-quality healthcare. In addition to this, there is a curriculum need to identify a method to quantitatively assess these key areas. PILLAR presents one potential mechanism to assess these areas in a quantitative manner.

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Footnotes

Acknowledgements

We acknowledge our pilot participants who provided very valuable feedback on the data collection materials. We are very grateful to all our student participants in the study along with the RSCI Quality Enhancement Office who acted as independent data controllers. We would also like to acknowledge the advice from Dr Colm Healy (RCSI) and Dr Catherine Nora Moran (RCSI) on the development of this paper.

Ethics approval and consent to participate

Ethical approval was sought and obtained from the Research Ethics Committee of the RCSI prior to conducting the study (REC202005016). Fully informed consent was obtained from all subjects.

Consent for publication

Consent was received from all participants for the publication of results from this research.

Availability data materials

The data that support the findings of this study are available from the corresponding author but restrictions apply to the availability of these data, which were used with permission for the current study, and so are not publicly available. Data is, however, available from the authors upon reasonable request and with permission of the RCSI Research Ethics Committee.

Authors’ contributions

AR, FD, and AH conceived the idea and study design. AR completed the acquisition and cleaning of the data, conducted analysis, interpreted the data, and drafted and revised the manuscript. AR, FD, AH, FB, MEC, and DWH advised on the interpretation of the data along with contributing to drafting and revising the manuscript. FB gave specific advice on Stata and statistical analysis along with contributing to drafting and reviewing the manuscript. MEC gave specific advice on Leadership along with reviewing the manuscript. FD oversaw all aspects of the study and specifically advised on study design, analysis and write-up. All authors were involved in writing and approving the final manuscript.

FUNDING

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Dr Ryan's and Professor Harkin's roles are supported by the RCSI and the Bons Secours Health System. The Bons Secours Health System had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

DECLARATION OF CONFLICTING INTERESTS

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

ORCID iD

Aine Ryan

Supplementary materials

Supplementary materials are provided and are tagged in the metadata. Please reflect standard text for Supplementary materials section.

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Supplementary Material

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