Selection for medical education: a review of the literature
Prepared for the Access to Medicine Project at King’s College London
Dylan Wiliam, Monica Millar & Hannah Bartholomew
King’s College London, February 2004
Background
Access to health care in the United Kingdom is not equitable, partly because some areas
(especially inner cities) have high concentrations of disadvantaged and vulnerable people, and
partly because the health services find some of the barriers to best practice difficult to overcome.
Some vulnerable groups are difficult to reach and differences in language, sex, class, ethnicity
and culture between patients and their doctors have been shown to affect the doctor-patient
relationship and can thus have important adverse clinical consequences (Flores, 2000). Thus
widening access to the medical profession to make it representative of the population it serves
can contribute in the long term towards the provision of more culturally competent health
services. There is, for example, evidence that medical students from more socio-economically
deprived backgrounds are more likely to work in socio-economically disadvantaged areas
(Magnus & Mick, 2000).
The Council of Heads of Medical schools (CHMS) has committed to a statement of principles,
which includes the following;
The purpose of a medical education is to graduate individuals well-fitted to meet the present
and future needs of society for medical care [...] The social, cultural and ethnic backgrounds
of medical graduates should reflect broadly the diversity of those they are called upon to
serve (Council of Heads of Medical Schools, 1998).
The Government’s emphasis on widening participation in higher education (Higher Education
Funding Council for England, 1998; Higher Education Funding Council for England, 1999;
Woodrow, 1998) increased the pressure on all universities to examine their admissions
procedures, and amendments to the Race Relations Act now make this a legal requirement. With
6000 extra medical school places opening between 2002 and 2005, selection procedures for
medical education will be under particularly intense examination (Crail, 1999).
This report is based on a study undertaken in the Department of Education and Professional
Studies in the School of Social Science and Public Policy at King’s College, University of London
(KCL). The aim of the study was to explore methods of selecting and supporting students
following medical school programmes in the industrialised world, in order to support the work
of the Access to Medicine programme at King’s College London, and other initiatives designed to
increase participation in medical education by those who are currently under-represented.
Method of review
In order to ensure that the review was as wide-ranging as possible, we did not limit our search of
the literature related to medical education by date or country. Due to time constraints, only
sources that were available in English were reviewed, and in a few cases, the review was limited
by the availability of copies of the journals or books in the UK. We began by compiling a list of
journals publishing articles identified as important to this review, and began a manual search
through these, identifying relevant articles. We also searched online databases, including ‘Web of
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Science’, MEDLINE and ERIC for all years that were available. The most productive search was
generated by requiring the key words for the citations to contain one of the key words ‘selection’,
‘admissions’ or ‘recruitment ‘ and either ‘medical students’ or ‘medical education’. The results
were scanned for relevance to our theme of undergraduate medical student selection and the
nature of the research evidence contained (in this context, it is worth noting that many of the
articles on medical student selection are discussions or commentaries rather than original
empirical research). We also obtained copies of the prospectus material of all UK medical schools
(as of November 2001) and collected relevant materials from their web-sites, including details of
admission criteria, admissions process, published student support services and widening
participation initiatives.
By following up references in research reports and key review articles, and reviewing all articles
citing original papers, and reviewing papers which cited these, we identified a total of 871
references which are included in the EndNote™ library that accompanies this report. As the
references were read, a system of key-words was built up, and entered into the keyword field of
the database. A final list of the 159 keywords used in the database is included as an appendix to
this report.
In order to keep an overview of the field, given the proliferation of key words, we also developed
a series of key themes running through the resources we had identified as relevant to the study.
The final list of the key themes is:
Choice of Higher Education by different groups in the UK
Identity
Intellectual and moral development
Interviews
Learning and teaching medicine (undergraduate and professional education)
Medical school attrition/persistence/stress
Mentoring and counselling medical students
Personality
Personal statements
Race and higher education in the UK
Recruitment and retention programs in medical schools
Selective admissions
Selection criteria and admissions testing
Study habits, styles and strategies
Widening participation in Higher Education
However, despite the large number of references generated, and despite the time that has been
spent in collating this report, we are aware that this is, at best, a work in progress. We hope that
others will find the bibliographic database that accompanies this report a useful resource, and
that they will add, both to the database and to this report.
Existing methods of selection for medical education
For most of the last century, admission to medical education in developed and developing
countries has been based on measures of cognitive ability and academic achievement. Such
measures have repeatedly been shown to be some of the most significant predictors of
performance in medical school (Campos-Outcalt et al, 1994; Gottheil & Miller Michael, 1957;
Gough, 1967; Gough & Hall, 1975; Rolfe et al, 1995; Swanson & Mitchell, 1989; Walton, 1987;
McManus, 198; Mitchell et al, 1994, Vancouver et al, 1990) and of later clinical competence
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(Tamblyn et al, 1998). Less obviously, these predictions have been found to hold across cultural
groups (Lynch & Woode, 1990; Sedlacek & Prieto, 1990; Vancouver et al, 1990).
At most medical schools in the UK, details from the official application form (submitted through
the Universities and Colleges Admissions Service, or UCAS), including a personal statement and
the reference written by the school, together with other demographic information, are used in the
first stage of the selection process. Applicants who clear this initial screening process are
interviewed in order to provide information about motivation, awareness of ethical issues related
to medicine, and personality.
The stated minimum criteria for admission to medical schools in the UK rose in the 1970s
(McManus, 1982) but have remained steady in recent years. Different medical schools in the UK
have always differed in their admissions (GMC, 1977), but a typical University (Nottingham, for
example) will require Chemistry (as required by the GMC), one other science subject and any
other mainstream academic subject at A-level. All UK medical schools now require a minimum of
ABB at A-level or its equivalent (and typically AAB outside London, although Sheffield is
pioneering a selective admissions process including lower academic achievement criteria for
some of its medical students; see Angel & Johnson, 2000). However, due to the intense
competition for places, in practice most students entering medical school obtain three grade As at
A-level, and since 25% of students taking A-levels get a grade A, many medical schools also take
GCSE grades into account. Students with three As at A-level may thus be ‘let down’ by less than
perfect GCSE results.
Students who do reach the threshold of three grade As at A-level are typically invited for
interview at the medical school. Concerns about the cost, the reliability and the validity of
interviews had led some institutions to abandon selection interviews in the 1970s, although
concerns about drop-out rates resulted in their re-introduction during the 1990s (Crail, 1999) and
almost all applicants to medical school are now interviewed.
Critiques of traditional selection methods
The reliance on achievement and ability (often grouped together as ‘cognitive’ factors in the
literature) in selecting for medical education has recently come under attack for a variety of
reasons, all of which can be regarded as aspects of validity.
While some authors, such as David Powis, have argued forcefully for selection on the basis that
factors other than academic achievement and cognitive ability (Powis et al, 1992), others regard
the attempt to select on individual characteristics as futile (McManus, 1997; Ryten, 1988).
Certainly the existing research basis is at best equivocal (Tutton, 1996; Morris, 1999) and it is clear
that much more work is needed to determine what factors are associated with success in medical
education, and subsequent medical practice.
The use of an invalid tool as a selection instrument is worse than using no tool at all, for an invalid tool
will, by definition, unbalance the cohort of entrants in some dimension. This will affect the nature of
the student body and, ultimately the graduate body, possibly to its detriment. It will also affect research
into the efficacy of the selection process, since the tool will have eliminated candidates with (or
without) certain qualities. Indeed, there may be other desirable qualities associated with those that are
the overt goal of the tool, which will also be eliminated without ever being identified. (Powis, 1994 pp.
453).
The first source of concern is that the correlation of cognitive factors with success in medical
education and subsequent practice in medical education is low (although, because of the large
numbers involved statistically significant). Typical values for correlations of scores such as A3
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level with final performance in medical education are in the range 0.3 to 0.5 (McManus et al,
2003). Even taking the most optimistic value, this indicates that at most 25% of the variance in
students’ final scores in medical education is attributable to their achievement and ability on
entry. Put another way, given two applicants for a single place at medical school, with no other
information, one has a 50% chance of selecting the ‘best’ applicant (in the sense of the one who
will go on to get the best results at medical school). By taking the one with the better A-level
performance, we improve our chances of getting the better student to 65%. This is a significant
improvement, but it is not a large improvement.
Correlations with subsequent performance in post are even lower. A recent synthesis of the
available research evidence suggests that the correlation of A-levels and job performance is as
low as 0.25, suggesting that only 6% of the variability in job performance is attributable to
academic achievement on entering medical education (Ferguson et al, 2002). Now of course, these
findings do not mean that prior achievement is unimportant. One of the reasons these
correlations are so low is the restriction of the range of applicants—we are selecting from a very
narrow stratum of the general population—but nevertheless, these findings indicate the limits of
cognitive and academic predictors of success.
The second reason for concern with over-reliance on A-level grades is that they are ‘impure’
measures, in that they measure some things that are related to the individual such as ability and
perseverance, but others that are not, such as quality of teaching. Many talented students in state
schools, sixth-form and further education (FE) colleges do not gain the A-level grades necessary
to be considered for medical education because their schools do not have teachers with
experience of teaching at this level, or sufficient resources for students to gain the highest grades
at A-level. Furthermore, the presence of high-attaining students in a school is known to increase
the achievement of other students in the school, so that students in schools and colleges where
there are few high-attaining students are at a disadvantage (Bursten, 1992; Sammons, 1999; Smith
& Naylor, 1999). Another complexity relevant to medical education is that students from
minority ethnic communities are more likely to choose A-level combinations that effectively
preclude undergraduate admission to medical school (Coffield, 1999; Coffield & Vignoles, 1997;
Rasekoala, 1997a; Rasekoala, 1997b; National Committee of Inquiry into Higher Education, 1997).
For example, African-Caribbean students are more likely to study arts and humanities
programmes and are under-represented in science, engineering and technology programmes and
some professional programmes. Moreover, the narrowing down of options begins well before
students choose their A-levels. One study (Mason, 2000) found that choices of options
supposedly made by 14-year-old students and their parents “were typically structured by staff
assessments of ability (not all of them based on formal testing), motivation, and behaviour. They
had the effect of determining at what level students would be entered for 16+ public
examinations and in what subjects.”
It is therefore hardly surprising that the intake of medical schools around the country is rarely
representative of local populations (Bedi & Gilthorpe, 2000a; 2000b). It is also worth noting here
that while there are systematic differences between ethnic groups, the variation within each
group is far greater, and social class and sex are stronger determinants of academic success than
ethnicity (Gillborn & Gipps, 1996; Rasekoala, 1997a; 1997b; Sammons, 1995; Demack et al, 2000),
although the effects of these characteristics are difficult to disentangle (Ball et al, 2001; Demack et
al, 2000; Gillborn & Mirza, 2000; Tomlinson, 1987).
The third reason for concern is that effective clinical competence requires much more than just
good knowledge. To be effective, doctors need good interpersonal skills, and thus it seems that
aspects of personality such as interests, values, motivation, interpersonal skills and concern with
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other people’s problems need also to be taken into account. As the eighth recommendation of the
World Federation for Medical Education made in 1994 states:
Medical schools should design admission criteria that address both academic and non-intellectual
characteristics, such as social commitment and minority status. Attitudinal assessment techniques
should be studied in every medical school for validity in identifying the necessary non-cognitive
qualities in would be applicants.
The same report, however, also required that, “The principles of selection should be clear,
equitable and valid” which is much more difficult to establish with non-cognitive factors than
with (say) A-level results. Carl Whitehouse reviewed recent research on selection (Whitehouse,
1997) and concluded, as did the BMA in its discussion paper (Board of Medical Education, 1998),
that current medical school selection procedures are often arbitrary. In particular, it has been
suggested that admissions process used by medical schools in the UK are biased against students
from minority ethnic communities (McManus, 1998a; 1998b), although this has been contested by
others (see, for example, Bland, 1999). Part of the problem is that current methods seek to select
from within the current applicant pool (i.e. selection) rather than seeking to diversify that pool (i.e.
recruitment). If the students who choose to apply to medical school are not representative of the
population as a whole, then it is very difficult to ‘re-balance’ the sample through selection
methods. As Powis (1994) noted “It is self selection out that is of value, not attempts to select in.”
A fourth difficulty with interpreting the research on predictors of success in medical education is
that almost all studies examine the progress of students in the existing systems of medical
education. These systems have been designed to cater for students who are successful at school,
and who arrive at university with more or less well-developed study skills. That students
without this amount of preparation do less well tells us only about the existing systems of
medical education, not what might be possible with different forms of medical education.
Measures of personality in selection for medical education
The most common recommendations for enhancing recruitment to medical education include the
selection of students on the basis of non-cognitive factors such as beliefs, attitudes and other
aspects related to personality.
Traditionally personality, understood either as ‘the structures, dynamics, and processes inside a
person that explain why he or she behaves in a particular way (Mount & Barrick, 1995), or as the
functional equivalent of a person’s ‘reputation’, has been seen as a variable with low validity for
predicting job performance. The last decade has seen the emergence of an increasingly influential
framework for structuring and understanding personality traits. Earlier work on the use of
personality measures for selection treated personality as a stable trait, if not innate (or even
inherited) then at least fixed relatively early in life. Early factor analytic studies such as those by
Eysenck identified as many as 16 different traits, but subsequent factor analyses of self- and peerreport measures of personality traits have consistently found convergent evidence for the
presence of five broad factors (O'Hehir, 1998; Wiggins, 1996), although the exact form and
definition of these factors differs between authors. There is considerable evidence that the ‘Five
Factor’ model is broadly congruent with the personality models of Cattell, Comrey and Eysenck
(Noller et al, 1987), Murray (Deary & Mathews, 1993) and Wiggins (McCrae & Costa, 1989b).
The Five Factor Model (FFM) is a descriptive taxonomy that provides surface characteristics of
recurrent behavioural patterns that are readily observed. Most taxonomic systems of cognitive
and non-cognitive attributes are hierarchical: clustering similar behaviours into narrow traits,
then clustering these into higher order traits, and eventually into a limited number of
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dimensional types. It is widely agreed that the first factor in the five-factor model of personality
is Eysenck’s Extraversion (E), and individuals who score highly on this factor are active,
assertive, energetic, enthusiastic, outgoing and talkative. There is also widespread agreement
about the second factor, Neuroticism (N), with high-scoring individuals being anxious, selfpitying, tense, touchy, unstable and worrying. The third factor is generally interpreted as
Agreeableness (A) focusing on whether individuals are appreciative, forgiving, generous, kind,
sympathetic and trusting. The fourth factor is most frequently called Conscientiousness (C), for
which the associated traits are efficiency, being well-organised, planful, reliable, responsible and
thorough. The fifth factor is the most difficult to identify. It has been interpreted as Intellect or
Intellectance but is most commonly known as Openness to Experience (O) accounting for the
extent to which individuals are artistic, curious, imaginative, insightful and original.
The utility of the five-factor model (FFM) for personnel selection is still a matter of great debate.
There are difficulties in the use of the FFM because authors vary in their interpretation of factors
(Newman, 1996). McCrae and John argue that the ‘Five Factor model is comprehensive and is
applicable across observers and cultures (McCrae & John, 1992), but it is unlikely to be the
definitive integrative model of personality, because the science of personality traits is young and
continues to evolve.
The use of any factor, cognitive or non-cognitive, as a criterion of admission to a programme of
professional education requires these factors to have a logical association with end-product
professional performance and that the factor should demonstrate relative stability within
individuals in the time interval separating application and professional practice. The FFM is a
version of trait theory and a fundamental tenet of psychological trait theory is that there is
relatively little likelihood of radically altering a personality structure of (medical) students during
their training (Rothman et al, 1973).
From the FFM perspective, O’Hehir (1998) concludes that the cumulative evidence indicates that
conscientiousness and neuroticism are valid predictors for all occupational groups and all job related criteria studied. High scores on E are associated with success where interpersonal skills
are required. Therefore, conscientious, emotionally stable, and extraverted individuals should
perform better in the working environment. There is consistent evidence that individuals who are
open to experience and, to a lesser extent, agreeable, may be people who are most likely to benefit
from training programmes.
Recent analyses of correlations of the FFM, obtained from child, adolescent, and adult samples,
suggest the presence of two higher-order factors. These constructs furnish the links between a
theoretical FFM and various theoretical systems of traditional and contemporary personology
(O'Hehir, 1998), ‘which, under a variety of interpretations, have dealt with one or the other – or
both – of these high-level factors’ (Digman, 1997). The first factor involves the common aspects of
Agreeableness (vs. Hostility), Conscientiousness (vs. Heedlessness), and Emotional Stability (vs.
Neuroticism). The second factor contains Extraversion and Intellect. The factors are termed Factor
Alpha and Factor Beta respectively. Digman (Digman, 1997) suggests that Factor Alpha may
represent socialisation and Factor Beta may represent personal growth (versus personal constriction).
A recent study of the predictive validity of personal statements and the role of the five factor
model (FFM) of personality in relation to the first year of medical training, proved negative
(Ferguson, 2002), except for conscientiousness which was positively related to success in the first
year. Previous academic performance was the only other predictor of success in the first year, but
conscientiousness demonstrated incremental validity over previous academic performance.
Previous academic performance has generally been found to be a more or less valid predictor of
pre-clinical performance but the predictive validity of pre-medical grades has been shown to
decrease during the period of clinical training. During this latter period of clinical training other
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factors such as personality and motivation become increasingly important. Whilst the FFM
domains A and C and Factor Alpha (A, C and N) were the predominant associates of pre-clinical
training success (above and beyond pre-medical grades) there was a notable lack of association
between the predictors and the criterion of clinical training success in O’Hehir’s study of the FFM
and the Alpha and Beta Personality Models in Medical selection and training at Nottingham
(O'Hehir, 1998). In other words, taking into account personality provided no improvement in
prediction over the use of previous academic performance. This is consistent with the findings of
McManus and Richards, who analysed a sample of approximately 12.5% of all the applicants to
British medical schools in October 1981 (McManus & Richards, 1984). They found that there were
few differences in personality, career preference or attitudes between those accepted and those
rejected—the only major difference was in performance at A-level.
While the relationship between personality and clinical performance is weak, changes in
personality variables have been claimed using different assessment instruments during medical
education. Parlow and Rothman (Parlow & Rothman, 1974) compared medical students with
those in other disciplines. They found that they scored higher on ‘Nurturance’ than the other
students and this discrepancy increased over the course of their education. However they scored
lower than the other non-medical students on measures of flexibility and their ability to tolerate
uncertainty.
The most widely-used personality inventory is the Myers-Briggs Type Inventory (MBTI), which
is used globally in counselling, education, personnel, management and business, largely because
it is so widely available, and can be self-scored (Kendall, 1998). It was originally based on Jung’s
theory that individuals differ in the way they prefer to use their minds, but its application has
been developed, validating and refining questions extensively across groups so that in practice it
may no longer reflect wholly the theory on which it was originally based.
Correlations have been found between Extroversion (E) and a preference on the Myers-Briggs
Type Inventory (MBTI) for Extraversion (obviously, perhaps) and Intuition. Similarly, those
scoring high on Openness (O) in the FFM with the MBTI Sensing/Intuition have been found. An
inverse relationship has been found between the MBTI Thinking/Feeling scale and
Agreeableness (A). Conscientiousness (C) has been shown to correspond with the
Judging/Perceiving orientation in the MBTI (McCrae & Costa, 1989a; Newman, 1996)
Gill Clack administered the MBTI questionnaire to 351 students entering Years 1, 2, and 3 of the
medical course at King’s at the start of the 1996/97 academic year (Clack & Head, 1997). Slightly
over half the students expressed a preference for ‘extraversion’ over ‘introversion’’; they were
almost equally divided between the two perceiving preferences of ‘sensing’ and ‘intuition’ and
nearly two-thirds preferred ‘thinking/deciding’ to ‘feeling/deciding’ and to lead their lives in a
structured, planned and organised way. A majority of female students preferred ‘extraversion’
compared to the majority of males preference for ‘introversion’ (the difference was significant:
p<0.01). More males preferred the ‘intuitive’ mode of perceiving whereas the females reported a
slight preference toward ‘sensing’; the majority of both males and females preferred the
‘thinking’ mode of decision making, and here the female medical students were opposite to the
general population in which two-thirds of females prefer the ‘feeling deciding’ decision mode.
The majority of both males and females preferred a judging orientation. The results of this study
were similar to other personality explorations among groups of medical students. There was a
wide range of preferences, predicting a diversity of preferred learning styles. However, given the
lack of evidence about the extent to which the MBTI is well-founded theoretically, or even stable
from one testing occasion to another, the likelihood that it has any utility in medical selection (or
indeed in any other area of personnel selection) remains doubtful (Pittenger, 1993).
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Learning styles, strategies and skills
Closely related to the research on personality, and sometimes overlapping with it significantly, is
a body of research on preferences for particular ways of learning. Although there is no agreed
definition of the distinction between learning styles, strategies and skills, the following usages,
taken from Adey, Fairbrother and Wiliam (Adey et al, 1999), appear to be the most common:
A Learning Style is a deep-rooted preference an individual has for a particular type of learning.
One can think of this as being similar to the way one folds ones arms. Each person has a
preferred way to do it even though they are quite capable of folding their arms the other way.
However, in order to fold one’s arms ‘the wrong way’ one has to think much harder about what
one is doing, and it never feels quite as ‘natural’. In the same way some people are imagers (they
prefer to learn from pictures and diagrams), whilst others are verbalisers (they prefer to learn from
words) although imagers can learn from words and verbalisers can learn from images.
At the other extreme, Learning Skills are almost like ‘tricks’ which are specific, designed to do
one job and can be taught. One example of a learning skill is a mnemonic to help remember a
series of facts, such as “Richard of York Gave Battle in Vain” in order to help remember the seven
colours of the rainbow are red, orange, yellow, green, blue, indigo and violet. Other examples of
learning skills are continuous repetition to remember text and high lighting or underlining
important pieces of text.
Somewhere in between these two extremes, the term Learning Strategy is used for groups of
skills, which a learner uses together for a particular purpose. Examples include setting objectives,
selecting and formulating questions, and comparing characteristics.
There is no sharp dividing line between learning styles, strategies and skills. They form a
continuum from the generally deeply embedded (and possibly innate) styles at one end to the
teachable subject-specific skills at the other.
Over the last fifty or so years, a large number of typologies and taxonomies of learning styles
have been produced (see Adey et al for a review), but some of the distinctions are only weakly
grounded in empirical data. In focusing on psychological principles, Riding and Rayner (1998)
concluded that robust evidence supports only two distinctions. The first is that between a wholist
style, descriptive of learners who prefer to get an idea of the ‘big picture’ before engaging in the
details and an analytic style, where learners prefer to start work with details. The second
important distinction is between verbalisers, who like to think in terms of words, and imagers,
who prefer to think in diagrams and pictures.
Kolb’s Learning Styles Inventory (LSI) also classifies individuals along two dimensions. The first
is concerned with whether an individual is more comfortable with concrete or abstract ideas
(Feeling-Thinking). The second dimension relates to the extent to which an individual would
rather think and reflect on something or get involved (Watching-Doing). Since these two
continua are independent of each other, this gives rise to a four-fold classification of learning
styles:
watching + feeling
watching + thinking
doing + feeling
doing + thinking
‘divergers’
‘assimilators’
‘accomodators’
‘convergers’
Davies, Rutledge and Davies (1997) administered Kolb’s LSI to 200 students entering Eastern
Virginia Medical School in 1991 and 1992. They found that 21% were divergers, 33% were
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assimilators, 22% were accomodators and 24% were convergers. Accomodators performed better
in interviews, but worst in physiology examinations, whilst convergers were best in physiology,
and worst at interviews.
Hofboll et al, (1982) explored the relationship between interview performance and personality (as
measured by the Californian Psychological Inventory) and subsequent clinical and academic
performance. They found positive associations between ratings of interview performance and the
CPI categories ‘Dominance’, ‘Self-acceptance’, ‘Well-being’, ‘Tolerance’, ‘Responsibility’ and
‘Achievement via conformance’. Academic and teaching staff ratings were positively associated
with ‘Achievement by independence’, Achievement by conformance’, ‘Self-acceptance’ and
‘Dominance’. However there were no significant correlations between the CPI variables and
clinical performance.
Therefore, whilst there is strong evidence that these learning styles are relatively stable, it is by no
means clear that these findings have any implications for education in general, and for selection
in medical education in particular. First, the associations with outcomes are so weak that the
issue of learning style may not be worth bothering with. Second, even if they are significant,
individualising learning to take into account the preferred learning style of each student in a
cohort of medical undergraduates is unlikely to be practicable, and may not even be advisable—
Perry (1968) found that sometimes the discomfort of struggling with learning attuned to a style
different from one’s preference enhanced learning. The only clear message from the literature on
learning styles is that it is advisable for teachers to ensure that they vary the presentation of work
to take into account the range of learning styles that may exist in the class.
Racism in medicine and medical education
In attempting to make the medical profession more representative of the population it serves, it is
necessary to expand both the ethnic and the socio-economic diversity of the population of
medical students, and these two aspects interact in complex ways. For example, applications
from blacks, Indians and whites come disproportionately from the higher socio-economic groups,
but are distributed evenly across the socio-economic range from students from Bangladeshi,
Chinese or Pakistani communities (Bedi & Gilthorpe, 2000). Students from black communities
had a similar social class profile to white students, whilst more students from professional than
intermediate backgrounds were observed for the Indian and Bangladeshi communities (a 95%
odds ratio extends from 1.32 to 1.80, with a mean at 1.54). As well as these differences between
groups, it is also necessary to be aware that the differences within these groups is usually at least
as great:
The dilemma which lies in the study of inequalities and differences of treatment among Britain's
minority ethnic groups is that such measurements, by definition, use some set categories in terms of
which data can be collected. However sensitively we seek to be toward people's self-definitions, any
category system runs the risk of failing to capture the richness and complexity of people’s identity
choices. There is then a danger that we may reproduce the very divisions we seek to problematize.
(Mason, 2000)
The debate about racial discrimination in medical school admission in the UK is difficult to
understand without an appreciation of the history of ethnic minority applicants to medicine.
Ethnic minorities have always been over-represented in medicine when compared to the
proportion in the general population (Modood & Acland, 1998). However the racial mix of the
applicants to medical schools is almost exclusively made up of applicants who classify
themselves as Indians. Applicants who classify themselves as Bangladeshi, Pakistani and AfroCaribbean are under-represented when compared to the proportion in the general population
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(Esmail et al, 1995). Esmail also showed that whilst there was no discrimination between groups
for candidates with the highest academic achievement, there appeared to be a selection bias in
favour of white candidates among applicants with lower A-level scores (for applicants to medical
school in the UK in 1990).
In the past, a typical response has been to ‘blame the victim’ (or at least their parents), with
underachievement being regarded as a function of family and community integration, even
though there was clear evidence of structural factors producing disadvantage (Tomlinson, 2000).
For example, in the 1980s, the ILEA was unable to provide sufficient school places for children in
Tower Hamlets and 95% of the resulting ‘out of school children’ were of Bangladeshi origin
(Tomlinson, 1992).
Manifestations of racism in the field of medicine in the NHS, the medical profession and other
areas of the UK health system have recently been described in a King’s Fund publication Racism
in medicine: an agenda for change (Coker, 2001). The authors claim the impossibility of the NHS
meeting its core values and ambitions, if it does not eradicate racism. Racism, the report suggests
may be manifested in beliefs, and in behaviours including hostility, passive neglect, exclusion,
isolation, injustice, harassment or violent attacks.
This seems close to the definition of ‘institutional racism’ proposed by Macpherson (1999) in the
report of the inquiry into the murder of Stephen Lawrence as “the collective failure of an
organisation to provide an appropriate and professional service to people because of their colour,
culture or ethnic origin. It can be seen or detected in processes, attitudes or behaviour which
amount to discrimination, through unwitting prejudice, ignorance, thoughtlessness and racist
stereotyping, which disadvantage minority ethnic people” (Jones, 1999).
Diversification of the medical student body, in terms of cultural background, age and class, may
in itself strengthen the profession’s ability to respond to change but the very strong culture and
traditions of medicine itself, and the social structure of medical schools (Bloom, 1989; Towle,
1998) are likely to make change difficult and slow.
Under-represented minorities and medical education
From the foregoing discussion, it is clear that selecting students for medical education is fraught
with difficulties, and that there is no clear way forward even if all we want to do is to improve
selection from amongst those who are already well-represented in medical education. It is hardly
surprising therefore, that the existing research base offers even fewer clear suggestions about
how to diversify the population of students attending medical schools, and qualifying as doctors.
In the United States in the 1970s, many medical students explored the use of affirmative action
programmes—typically admitting students from under-represented minorities with lower scores
than white students would need. As might be expected, the outcomes in medical education have
been mixed (Cohen, 1997; Petersdorf, 1992; Petersdorf et al, 1990), but much has been learned
about enrolling black students in the competitive environment of selective colleges (Bowen &
Bok, 1998). In particular, it is clear that findings related to segregated systems (as existed for
many years in the United States) do not generalise in any simple way to de-segregated systems.
Despite much evidence that African-American students are increasingly developing their
academic competitiveness for medical school application, and that the MCAT is predictive for
both blacks and whites of success in medical school (Mitchell et al, 1994; Mitchell, 1990), it
appears that traditional predictors are not so robust for minority students (Sedlacek & Prieto,
1990). As well as the necessary academic ability, students from underrepresented minorities need
an ability to deal with racism (which in turn presupposes that an individual has a strong sense of
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his racial identity), and also need to know the ‘rules of the game’. “Handling racism seems
related to contextual intelligence, and this type of ability seems even less likely than experiential
intelligence, to be reflected in standardised tests” (Sedlacek & Prieto, 1990).
Cariaga-Lo et al. studied the cognitive and non-cognitive effects of academic difficulty and
attrition in a medical school in North Carolina (Cariaga-Lo et al, 1997). They modelled the
probability of failure at any time point during the four years of medical school and found that the
risk of failure was significantly greater for non-white students and for non norm-favouring /selfrealised students. In general terms, risk of failure was higher for women at this medical school.
As might be expected, the risk of failure was inversely proportional to the student’s score on the
Medical College Admissions Test (MCAT) and science GPA. However, when demographic and
psychological variables (the California Psychological Inventory or CPI) were taken into account,
the risk of failure narrowed between the high and the low scoring students. This suggests that
academic achievement is only part of the issue, and that personal characteristics play a strong
part in determining success and failure in medical students, especially those from underrepresented minorities.
What the research from the United States does show clearly is that one of the most important
predictors of persistence in medical education is the degree to which students become integrated
into the institutions at which they study, and not surprisingly, this becomes more important the
longer the programme and the more residential it is (Tinto, 1998). What is less obvious is that the
there are two aspects of integration, which interact in complex ways. Social integration refers to
the extent to which students feel they ‘belong’ to the institution, and there is little doubt that
student persistence is greater at institutions that make students feel they are treated as valued
members of the institution (Cabrera et al, 1999), although many students who experience a low
sense of belonging, do not drop out and it may be that proximal affiliations (a sense of belonging
to small social networks) is more important in student persistence (Hurtado & Carter 1997).
Cabrera et al. acknowledge that differences in academic preparedness and patterns of financing
minority students, along with changes in high school completion rates and expectation, have
contributed to increased enrolment and persistence for minority students. Yet, exposure to
prejudice and discrimination in the classroom and on campus, has gained attention as the main
factor accounting for differences in withdrawal behaviour between minorities and nonminorities:
Racism and discrimination are unique psychological and socio-cultural stressors, which heighten the
feeling of not belonging at an institution with spill-over effect on a students academic performance”
(Cabrera et al, 1999).
In their study of 1,454 students (1,139 whites, 315 African Americans) in 1992, Cabrera et al. found
that minorities and non-minorities adjust to college in a similar manner, but exposure to campus
climate of prejudice and intolerance lessens commitment to the institution, for both blacks and
whites. Along with all researchers in the field of attrition from college, Cabrera concludes that
adjustment to college represents a complex process that links student motivations, attitudes, and
abilities with institutional features. He believes that encouragement and support from significant
others, can negate the deleterious effects of perceived prejudice and discrimination.
Support from the institution can also mitigate some of the deleterious effects of perceived
prejudice and discrimination. However, by itself, social integration is not enough. It is also
important for students to be academically integrated into their studies, for example by discussing
programme content with other students outside scheduled tuition periods. While disentangling
the effects of social and academic integration is difficult it does appear as if academic integration
is at least as important as, if not more important than, social integration, although it is important
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to note that some studies have found that the relationship between academic and social
integration is different for students from different ethnic groups, and for males and females
(Allen, 1992; Cabrera et al, 1999; Hurtado & Carter, 1997; Stage, 1989).
Allen found that academic achievement was highest, in African-American college students in
students with: high educational aspirations, who were certain that their college choice was
correct, and who reported positive relationships with faculty (Allen, 1992). Black students on
predominantly white campuses did not fare as well as white students in persistence rates,
academic achievement, postgraduate study, or overall psychological adjustment. This author
believes his results do not show phenomena shrouded in mystery. He remarks, they are “.... the
result of the same historical, political, economic and psychological patterns that have perpetuated
Black subjugation and oppression since Blacks arrived (on these shores) in 1619”.
For example, a study by Strayhorn and Frierson (1989) looked at the 640 students enrolling at the
University of North Carolina medical school and found that black students experienced
considerable stress from their minority status and racial concerns that were obviously not issues
for white students. As Cabrera et al. (1999) note, “Racism and discrimination are unique
psychological and socio-cultural stressors, which heighten the feeling of not belonging at an
institution with spill-over effect on a student’s academic performance”.
It is also important to note that some of these differences cannot be attributed to pre-existing
differences in the students themselves. A study at the University of Chicago medical school in the
1980s compared 184 medical students from different racial backgrounds in terms of psychosocial
assets and mental health during the first year of the programme (Pyskoty et al, 1990). At the
beginning of the programme black and Hispanic students reported greater social support and
more advantageous mental health than white students which they attributed to pre-entrance
programs and more supportive ethnic cultural backgrounds. Even though minority students
incurred greater debts than white students, they did not report greater stress, although over the
course of the programme, white students reduced the extent to which they attributed their
academic outcomes to external factors, while this increased for minority students. In other words,
the process of medical education itself made minority students feel less in control of their success,
while white students felt more so. It is also important to note that programmes to support social
integration are time consuming for students—there is a real issue of equity if minority students
have to attend extra classes or sessions in order to ‘level the playing field’ taking up time that
could be used for study or leisure.
Other stress factors, however, appear to impact equally on black and white students when
differences in science knowledge and other predictors of success are controlled. Although there
have been a large number of studies of stress in medical education, based in the main on
questionnaires (see, for example, Firth-Cozens, 1989; Firth-Cozens, 2001; Gaensbauer & Mizner,
1980; Guthrie et al, 1995; Mitchell et al, 1983; Post et al, 1995; Wolf, 1989; Wolf & Kissling, 1984;
Wolf et al, 1998; Wolf et al, 1991; Pyskoty et al, 1990; Richman & Flaherty, 1985; Richman &
Flaherty, 1990) the result of these studies are inconsistent, suggesting that the issues are still
relatively under-theorised.
Few studies have explored differences amongst medical students from different ethnic or socioeconomic backgrounds in the UK, in terms of student progress. McManus presented an analysis
of retrospective data for two cohorts of London medical students entering medical school in 1981
and 1985 (McManus et al, 1996). He showed differences between white and non-white students,
but he did not take into account social class or socio-economic status. An investigation at
Manchester University medical school (Dillner, 1995) found that there were systematic
differences in progress between white and non-white students which, though small, may well
have accounted for the fact that all ten students who failed the final exam were Asian. This raises
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important questions about the possibility of racial bias, the conduct of the clinical examinations
and the future monitoring and performance of students (Esmail & Dewart, 1998).
Conclusion
As noted above, few firm conclusions can be drawn from the existing research evidence. There is
simply insufficient good evidence to provide clear guidance about what kinds of measures are
likely to be the most effective in diversifying the pool of applicants to medical education, and
eventually the medical profession. In short, the research doesn’t tell us what to do. However, the
research does indicate more and less fruitful directions, and to the extent that the research says
anything, it suggests that the Access to Medicine programme at King’s has got it just about right.
First, as is acknowledged in the Access to Medicine programme, diversifying the medical
profession cannot be achieved simply by changing selection into medical education. Many
suitable applicants never even think of medicine as a realistic possibility, or make decisions in
their choices of options at 14 that make entry to a medical degree much more difficult. The first
stage must therefore be not selection, but recruitment—changing the pool of well-qualified
students applying to medical education in the first place.
Second, selection methods need to strike a fine balance between requiring the skills and aptitudes
needed to complete medical education on the one hand, and yet also try to make selection as
independent as possible of the quality of teaching applicants have received. As the research on
affirmative action in the United States shows, aptitude is not enough if programmes assume a
particular level of knowledge, experience or maturity. But it is also important to bear in mind that
in the US medical education is undertaken at graduate level. Selecting 18-year-olds for medicine
is a much more difficult task than selecting 21-year-olds.
Third, selection methods have to be designed in tandem with the programmes they are to be used
with. For example, because we want our doctors to have strong ethical values, some people have
argued that ethical considerations should be part of our selection criteria, but this follows only if
ethical values cannot be changed during medical education. Even if it were shown that ethical
values do not change during the course of medical education, this would not warrant the
inclusion of ethical criteria for selection unless it could also be shown that even with revised
curricula, and more attention given, ethical values could not be changed. In short, selection
criteria should be based only on those attributes that are impossible, impracticable, or too timeconsuming to change. As one professional basketball coach said when he was asked about what
he looked for in drafting professional players, “You can’t teach height”.
Fourth, and most importantly, ways have to be found to minimise the extra burdens on students
from under-represented minorities. These students will often, through no fault of their own, be
less well-prepared for undergraduate study, and will, because of the racism they will encounter,
have to work harder and display higher levels of maturity than their white peers. In responding
to this, it is important to see the whole project of diversifying the medical profession not as one of
‘being nice to disadvantaged students’ but as one of seeing students from under-represented
minorities as key resources that can help us improve the cultural competence of the medical
profession. In the short term, Access to Medicine must change the programme offered to all
undergraduate students. In the longer term, Access to Medicine must become at least invisible,
and ideally unnecessary—not a ‘special route’ into the profession for students who somehow
need special help to get in, but rather a way of looking at the whole of medical education.
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Appendix
The keywords used in the keywords field in the EndNote™ library that accompanies this report
are as follows:
academic criteria for selection
academic performance
academic support
admissions process
adolescence
affirmative action
approaches to study
assessment
assessment professional
assessment psychological
athleticism
attitudes
attrition
clinical academics
clinical competence
clinical governance
cognitive conflict
cognitive flexibility
communication skills
counseling service
curriculum
decision making
development intellectual
development moral
development personal
development professional
disadvantage cultural
disadvantage educational
disadvantage socioeconomic
discrimination
diversification of medical
students
doctor patient relationship
education policy
emotional intelligence
empathy
employment after higher
education
employment financial
rewards
ethical behaviour
ethics formal teaching of
ethnicity
ethnography
family support
financial support
formative assessment
professional
funding policy
general practice
graduate entry
20
health inequalities
health service
higher education
higher education choices
higher education transition to
house job allocation
humanism
identity
information technology and
evidence based learning
institution student
commitment to
institutional policy
interview
job satisfaction
leadership
learning environment
learning strategies
learning style
licensing examinations
locus of control
marginalisation
medical care
medical careers
medical education
medical educators
medical school
medical students
medical workforce
memory
mental health
mentoring
metacognition
metalearning
motivation
multicultural awareness
overseas students
parental education
parental income
patient centredness
person institution
compatibility
personal interests
personal relationships
personal statement
personal support institutional
personal tutor
personality
portfolio assessment
positive action
post modernism
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powerlessness
pre entry programme
preclinical medicine
premed research experience
privilege
problem based learning
problem solving
profession
profession medical
professional responsibility
psychological adjustment
qualitative research
racism
recruitment and outreach
remediation
remediation preselection
retention
review process of
role models
school grades
school mix
school reference
science education
science education curriculum
selection
selection monitoring
self assessment
self efficacy
self esteem
self knowledge
sex
sexual orientation
social awareness
social capital
social class
social contract
socialisation
sociology of education
sociology of illness
status of physics
stereotyping
stress
students perceptions
supported self study
teaching
test bias
test of knowledge
test of moral reasoning
test of performance
test of understanding
test of verbal reasoning
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test preparation
test reliability
test validity
tiredness
training posts
underserved communities
values
widening participation
work experience
writing skills
written assessment
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