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A levels and intelligence as predictors of medical careers in UK doctors: 20 year prospective study.

ABSTRACT: To assess whether A level grades (achievement) and intelligence (ability) predict doctors' careers.Prospective cohort study with follow up after 20 years by postal questionnaire.A UK medical school in London.511 doctors who had entered Westminster Medical School as clinical students between 1975 and 1982 were followed up in January 2002.Time taken to reach different career grades in hospital or general practice, postgraduate qualifications obtained (membership/fellowships, diplomas, higher academic degrees), number of research publications, and measures of stress and burnout related to A level grades and intelligence (result of AH5 intelligence test) at entry to clinical school. General health questionnaire, Maslach burnout inventory, and questionnaire on satisfaction with career at follow up.47 (9%) doctors were no longer on the Medical Register. They had lower A level grades than those who were still on the register (P < 0.001). A levels also predicted performance in undergraduate training, performance in postregistration house officer posts, and time to achieve membership qualifications (Cox regression, P < 0.001; b=0.376, SE=0.098, exp(b)=1.457). Intelligence did not independently predict dropping off the register, career outcome, or other measures. A levels did not predict diploma or higher academic qualifications, research publications, or stress or burnout. Diplomas, higher academic degrees, and research publications did, however, significantly correlate with personality measures.Results of achievement tests, in this case A level grades, which are particularly used for selection of students in the United Kingdom, have long term predictive validity for undergraduate and postgraduate careers. In contrast, a test of ability or aptitude (AH5) was of little predictive validity for subsequent medical careers.

SUBMITTER: McManus IC

PROVIDER: S-EPMC165701 | biostudies-literature | 2003 Jul

REPOSITORIES: biostudies-literature

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A levels and intelligence as predictors of medical careers in UK doctors: 20 year prospective study.

McManus I C IC Smithers Eleni E Partridge Philippa P Keeling A A Fleming Peter R PR

BMJ (Clinical research ed.) 20030701 7407

<h4>Objective</h4>To assess whether A level grades (achievement) and intelligence (ability) predict doctors' careers.<h4>Design</h4>Prospective cohort study with follow up after 20 years by postal questionnaire.<h4>Setting</h4>A UK medical school in London.<h4>Participants</h4>511 doctors who had entered Westminster Medical School as clinical students between 1975 and 1982 were followed up in January 2002.<h4>Main outcome measures</h4>Time taken to reach different career grades in hospital or ge ...[more]

PMID: 12869457

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Project description:BackgroundThe medical specialities chosen by doctors for their careers play an important part in the workforce planning of health-care services. However, there is little theoretical understanding of how different medical specialities are perceived or how choices are made, despite there being much work in general on this topic in occupational psychology, which is influenced by Holland's RIASEC (Realistic-Investigative-Artistic-Social-Enterprising-Conventional) typology of careers, and Gottfredson's model of circumscription and compromise. In this study, we use three large-scale cohorts of medical students to produce maps of medical careers.MethodsInformation on between 24 and 28 specialities was collected in three UK cohorts of medical students (1981, 1986 and 1991 entry), in applicants (1981 and 1986 cohorts, N = 1135 and 2032) or entrants (1991 cohort, N = 2973) and in final-year students (N = 330, 376, and 1437). Mapping used Individual Differences Scaling (INDSCAL) on sub-groups broken down by age and sex. The method was validated in a population sample using a full range of careers, and demonstrating that the RIASEC structure could be extracted.ResultsMedical specialities in each cohort, at application and in the final-year, were well represented by a two-dimensional space. The representations showed a close similarity to Holland's RIASEC typology, with the main orthogonal dimensions appearing similar to Prediger's derived orthogonal dimensions of 'Things-People' and 'Data-Ideas'.ConclusionsThere are close parallels between Holland's general typology of careers, and the structure we have found in medical careers. Medical specialities typical of Holland's six RIASEC categories are Surgery (Realistic), Hospital Medicine (Investigative), Psychiatry (Artistic), Public Health (Social), Administrative Medicine (Enterprising), and Laboratory Medicine (Conventional). The homology between medical careers and RIASEC may mean that the map can be used as the basis for understanding career choice, and for providing career counselling.

Project description:ObjectivesTo evaluate surgical experience among current doctors appointed into ophthalmology training posts since the introduction of the Modernising Medical Careers programme. Additionally, to identify regional variations in surgical experience and training programme delivery.DesignA cross-sectional survey.SettingThe UK's four largest deaneries (Schools of Ophthalmology).ParticipantsTrainee ophthalmologists, all having completed three or more years of training, who were appointed to the new ophthalmic specialty training programme.Primary and secondary outcome measuresThe mean annual surgical rate for each deanery in phacoemulsification cataract extractions and experience in other common elective and emergency surgical operations. Second, to calculate the mean timetabled clinical activity.ResultsThe responses of 40 doctors were analysed, with a response rate of 83%. Overall, the phacoemulsification rate was 73.52±29.24 operations/year. This was significantly higher in the South Thames Deanery (99.69±26.16, p=0.0005) and significantly lower in the North Western Deanery (48.08±19.72, p=0.0008). The annual mean complex cataract rate was 5.21±4.38. Only 40% were confident in dealing with the most common complication of cataract surgery (vitreous loss). The mean trabeculectomy (surgery for glaucoma) rate was 0.47±1.16 and for squint surgery it was 3.54±2.82 operations/year. Regarding the common ocular trauma surgery, 42.5% had not sutured a corneal laceration and 60% a globe rupture. 50% thought the training programme would adequately prepare them surgically. The timetabled clinical activity was highest in the South Thames Deanery (48.17 h/week) and lowest in the North Western Deanery (40.82 h/week) due to variations in the European Working Time Directive implementation and on-call commitments.ConclusionsSignificant regional variations in surgical training experience exist between UK deaneries, particularly with respect to cataract surgery, and they appear to be correlated to timetabled activity. Experience and confidence levels in managing complex cataract surgery and complications were low and experience with previously commonly performed elective and emergency operations was minimal. Although doctors from all the regions surveyed were very likely to achieve the minimum cataract extractions required for specialist training completion, we have identified shortcomings of the current training programme that need attention.

Project description:ObjectiveTo understand the association between medical negligence claims and doctors' sex, age, specialty, working hours, work location, personality, social supports, family circumstances, self-rated health, self-rated life satisfaction and presence of recent injury or illness.Design and settingProspective cohort study of Australian doctors.Participants12 134 doctors who completed the Medicine in Australia: Balancing Employment and Life survey between 2013 and 2019.Primary outcome measureDoctors named as a defendant in a medical negligence claim in the preceding 12 months.Results649 (5.35%) doctors reported being named in a medical negligence claim during the study period. In addition to previously identified demographic factors (sex, age and specialty), we identified the following vocational and psychosocial risk factors for claims: working full time (OR=1.48, 95% CI 1.13 to 1.94) or overtime hours (OR 1.70, 95% CI 1.29 to 2.23), working in a regional centre (OR 1.69, 95% CI 1.37 to 2.08), increasing job demands (OR 1.16, 95% CI 1.04 to 1.30), low self-rated life satisfaction (OR 1.43, 95% CI 1.08 to 1.91) and recent serious personal injury or illness (OR 1.40, 95% CI 1.13 to 1.72). Having an agreeable personality was mildly protective (OR 0.91, 95% CI 0.83 to 1.00). When stratified according to sex, we found that working in a regional area, low self-rated life satisfaction and not achieving work-life balance predicted medical negligence claims in male, but not female, doctors. However, working more than part-time hours and having a recent personal injury or illness predicted medical negligence claims in female, but not male, doctors. Increasing age predicted claims more strongly in male doctors. Personality type predicted claims in both male and female doctors.ConclusionsModifiable risk factors contribute to an increased risk of medical negligence claims among doctors in Australia. Creating more supportive work environments and targeting interventions that improve doctors' health and well-being could reduce the risk of medical negligence claims and contribute to improved patient safety.

Project description:BackgroundSimilar to understanding how blood pressure is measured by a sphygmomanometer, physicians will soon have to understand how an artificial intelligence-based application has come to the conclusion that a patient has hypertension, diabetes, or cancer. Although there are an increasing number of use cases where artificial intelligence is or can be applied to improve medical outcomes, the extent to which medical doctors and students are ready to work and leverage this paradigm is unclear.ObjectiveThis research aims to capture medical students' and doctors' level of familiarity toward artificial intelligence in medicine as well as their challenges, barriers, and potential risks linked to the democratization of this new paradigm.MethodsA web-based questionnaire comprising five dimensions-demographics, concepts and definitions, training and education, implementation, and risks-was systematically designed from a literature search. It was completed by 207 participants in total, of which 105 (50.7%) medical doctors and 102 (49.3%) medical students trained in all continents, with most of them in Europe, the Middle East, Asia, and North America.ResultsThe results revealed no significant difference in the familiarity of artificial intelligence between medical doctors and students (P=.91), except that medical students perceived artificial intelligence in medicine to lead to higher risks for patients and the field of medicine in general (P<.001). We also identified a rather low level of familiarity with artificial intelligence (medical students=2.11/5; medical doctors=2.06/5) as well as a low attendance to education or training. Only 2.9% (3/105) of medical doctors attended a course on artificial intelligence within the previous year, compared with 9.8% (10/102) of medical students. The complexity of the field of medicine was considered one of the biggest challenges (medical doctors=3.5/5; medical students=3.8/5), whereas the reduction of physicians' skills was the most important risk (medical doctors=3.3; medical students=3.6; P=.03).ConclusionsThe question is not whether artificial intelligence will be used in medicine, but when it will become a standard practice for optimizing health care. The low level of familiarity with artificial intelligence identified in this study calls for the implementation of specific education and training in medical schools and hospitals to ensure that medical professionals can leverage this new paradigm and improve health outcomes.

Dataset Information

A levels and intelligence as predictors of medical careers in UK doctors: 20 year prospective study.

Publications

A levels and intelligence as predictors of medical careers in UK doctors: 20 year prospective study.

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