| Literature DB >> 29843689 |
Alexander J Martin1, Benjamin J Beska1, Greta Wood1, Nicola Wyatt1, Anthony Codd2, Gillian Vance2, Bryan Burford3.
Abstract
BACKGROUND: Under-representation of some socio-economic groups in medicine is rooted in under-representation of those groups in applications to medical school. This study aimed to explore what may deter school-age children from applying to study medicine.Entities:
Keywords: Medical careers; Medical school admissions; Selection; Widening access; Widening participation
Mesh:
Year: 2018 PMID: 29843689 PMCID: PMC5975409 DOI: 10.1186/s12909-018-1221-3
Source DB: PubMed Journal: BMC Med Educ ISSN: 1472-6920 Impact factor: 2.463
Mapped Session 2 prompts
| Prompt | Category based upon |
|---|---|
| I don’t know enough the application process | Application process |
| It’s competitive: I don’t want to waste a UCAS choice | Application process |
| I don’t know how to get work experience | Application process |
| I think there are problems in the NHS and the future is uncertain | Careers |
| I might find the course too difficult | Course content |
| I don’t know enough about the course: I may change my mind | Course content |
| I don’t know how I will pay for the course | Finance |
| I may not fit in | Social |
Numbers of participants and those meeting Widening Participation criteria at each Year 12 session
| Number attending MaD day | Number taking part in research (%) a | Frequency (and % of session sample) of each of five Widening Participation criteria among respondents | n with Widening Participation > 1 (% of sample) | |||||
|---|---|---|---|---|---|---|---|---|
| Postcode | School | Free School Meals | Care | Parents | ||||
| Session 1 | 44 | 36 (82%) | 25 (69%) | 17 (47%) | 10 (28%) | 1 (3%) | 26 (72%) | 28 (77%) |
| Session 2 | 60 | 46 (77%) | 29 (63%) | 7 (15%) | 4 (9%) | 0 | 23 (50%) | 24 (52%) |
| Session 3 | 60 | 40 (67%) | 15 (38%) | 7 (18%) | 3 (8%) | 0 | 19 (48%) | 4 (10%) |
| Total | 164 | 122 (74%) | 69 (57%) | 31 (25%) | 17 (14%) | 1 (1%) | 68 (56%) | 56 (46%) |
a Including participants who did not provide details to link to Widening Participation indices (Session 1 = 3 students, Session 2 = 6 students)
High priority deterrents identified in Year 12 Session 1
| Deterrent (number of groups ranking deterrent in top five) | Category of deterrent |
|---|---|
| I don’t think I’ll get in (4) | Anticipation of application process |
| I might not get the grades (4) | Anticipation of application process |
| I think there are problems in the NHS (3) | Political context |
| Medical students are from a different background to me and I won’t fit in (3) | Social background |
| Having to do the UKCAT (2) | Anticipation of application process |
| Studying medicine is expensive (2) | Financial cost |
| Five years is a long course (1) | Concerns about course |
| Having to have an interview to get in (1) | Anticipation of application process |
| I don’t know if I could be a doctor (1) | Social background |
| I don’t know how I will pay for the course (1) | Financial cost |
| I may not like the subject (1) | Concerns about course |
| I might find the course difficult (1) | Concerns about course |
| My family don’t know how to support me in applying (1) | Social background |
| My school don’t have anyone who can give me advice about applying (1) | Social background |
| Negative stories about doctors or medicine in the news (1) | Political context |
| I don’t know how to get work experience (1) | Anticipation of application process |
The number in brackets indicates the number of groups (out of 4) that ranked the deterrent as among their ‘top five’, meaning that those at the top indicate more consensus
Frequency of correct identification of medical and non-medical occupations
| Medical occupations | Session 2 | Session 3 | Non-medical occupations | Session 2 | Session 3 |
|---|---|---|---|---|---|
| General practitioner | 8 (100%) | 8 (100%) | Dentist | 5 (62%) | 4 (50%) |
| Paediatrician | 8 (100%) | 8 (100%) | Pharmacist | 5 (62%) | 3 (38%) |
| Radiologist | 8 (100%) | 8 (100%) | Optician | 4 (50%) | 3 (38%) |
| Anaesthetist | 7 (88%) | 8 (100%) | Psychologist | 4 (50%) | 5 (62%) |
| Cardiologist | 7 (88%) | 7 (88%) | Midwife | 3 (38%) | 2 (25%) |
| Psychiatrist | 7 (88%) | 6 (75%) | Chiropractor | 2 (25%) | 4 (50%) |
| Surgeon | 7 (88%) | 8 (100%) | Paramedic | 2 (25%) | 2 (25%) |
| Forensic pathologist | 2 (25%) | 2 (25%) | Physiotherapist | 2 (25%) | 3 (38%) |
| Microbiologist | 2 (25%) | 2 (25%) | Podiatrist | 1 (12%) | 1 (12%) |
Frequency indicates the number of 8 groups to correctly identify each response
Frequency of correct identification of activities and number of indications of interest
| No. groups correctly identifying activity a | Expressions of interest b | |||||
|---|---|---|---|---|---|---|
| Activity | Session 2 | Session 3 | Total | Session 2 | Session 3 | Total |
| Examining dead bodies from a crime scene | 8 (100%) | 7 (88%) | 15 (94%) | 30 (14.9%) | 24 (12%) | 54 (13.5%) |
| Examining dead bodies to work out the cause of death | 7 (88%) | 7 (88%) | 14 (88%) | 15 (7.5%) | 16 (8%) | 31 (7.7%) |
| Working with sports teams and athletes | 1 (12%) | 1 (12%) | 2 (13%) | 13 (6.5%) | 17 (8.5%) | 30 (7.5%) |
| Looking after children and young people when they are in hospital | 6 (75%) | 7 (88%) | 13 (81%) | 8 (4%) | 21 (10.5%) | 29 (7.2%) |
| Working in the Army/RAF/Navy | 5 (62%) | 7 (88%) | 12 (75%) | 12 (6%) | 17 (8.5%) | 29 (7.2%) |
| Talking to people with mental health problems | 5 (62%) | 2 (25%) | 7 (44%) | 11 (5.5%) | 16 (8%) | 27 (6.7%) |
| Helping people with cancer | 8 (100%) | 8 (100%) | 16 (100%) | 10 (5%) | 16 (8%) | 26 (6.5%) |
| Performing operations | 8 (100%) | 8 (100%) | 16 (100%) | 18 (9%) | 7 (3.5%) | 25 (6.2%) |
| Developing new treatments or drugs | 5 (62%) | 6 (75%) | 11 (69%) | 12 (6%) | 13 (6.5%) | 25 (6.2%) |
| Looking after babies when they are born prematurely | 4 (50%) | 5 (62%) | 9 (56%) | 12 (6%) | 7 (3.5%) | 19 (4.7%) |
| Researching new ways to try and cure diseases | 5 (62%) | 4 (50%) | 9 (56%) | 8 (4%) | 7 (3.5%) | 15 (3.7%) |
| Diagnosing illness from X-rays and scans | 8 (100%) | 7 (88%) | 15 (94%) | 8 (4%) | 2 (1%) | 10 (2.5%) |
| Talking to people about their everyday problems | 1 (12%) | 4 (50%) | 5 (31%) | 4 (2%) | 6 (3%) | 10 (2.5%) |
| Putting people to sleep before an operation | 8 (100%) | 8 (100%) | 16 (100%) | 9 (4.5%) | 0 | 9 (2.2%) |
| Tracking the spread of diseases and trying to prevent spreading | 7 (88%) | 7 (88%) | 14 (88%) | 2 (1%) | 6 (3%) | 8 (2%) |
| Teaching students | 2 (25%) | 5 (62%) | 7 (44%) | 2 (1%) | 5 (2.5%) | 7 (1.7%) |
| Helping people overcome disability | 2 (25%) | 4 (50%) | 6 (38%) | 5 (2.5%) | 2 (1%) | 7 (1.7%) |
| Caring for people at the end of their life | 2 (25%) | 2 (25%) | 4 (25%) | 5 (2.5%) | 2 (1%) | 7 (1.7%) |
| Looking through a microscope to diagnose diseases | 8 (100%) | 8 (100%) | 16 (100%) | 6 (3%) | 0 | 6 (1.5%) |
| Finding out what people are allergic to | 8 (100%) | 7 (88%) | 15 (94%) | 2 (1%) | 3 (1.5%) | 5 (1.2%) |
| Helping elderly people | 1 (12%) | 5 (62%) | 6 (38%) | 4 (2%) | 1 (0.5%) | 5 (1.2%) |
| Delivering babies by performing an operation (C-section) | 7 (88%) | 8 (100%) | 15 (94%) | 1 (0.5%) | 3 (1.5%) | 4 (1%) |
| Giving injections | 7 (88%) | 8 (100%) | 15 (94%) | 1 (0.5%) | 3 (1.5%) | 4 (1%) |
| Performing CPR (resuscitation) to try and save someone’s life | 7 (88%) | 7 (88%) | 14 (88%) | 1 (0.5%) | 2 (1%) | 3 (0.7%) |
| Helping pregnant women if they develop problems | 2 (25%) | 8 (100%) | 10 (63%) | 1 (0.5%) | 2 (1%) | 3 (0.7%) |
| Prescribing medicines to people | 5 (62%) | 6 (75%) | 11 (69%) | 1 (0.5%) | 1 (0.5%) | 2 (0.5%) |
| Sending people home from hospital | 5 (62%) | 5 (62%) | 10 (63%) | 0 | 1 (0.5%) | 1 (0.2%) |
| Organising the delivery of healthcare in a region | 3 (38%) | 1 (12%) | 4 (25%) | 0 | 0 | 0 |
| Developing campaigns to improve the health of everyone - stopping smoking, sexual health | 0 | 0 | 0 | 0 | 0 | 0 |
| Working for a company to make sure people’s workplaces are safe | 0 | 0 | 0 | 0 | 0 | 0 |
| Total | 201 | 200 | 401 | |||
aThe number of 8 groups per session, 16 in total, to correctly identify each response as part of doctors’ work
bEach participant was given two adhesive dots to allocate to the available activities to indicate which attracted them most. They could give two to the same activity, one each to separate activities, or allocate one or neither. The total is the sum of those allocated, which may be less than the number distributed to participants
Combined frequencies of interest in medicine pre- and post-intervention for Session 2 and 3
| Definitely not | Probably not | Maybe | Definitely | |
|---|---|---|---|---|
| Pre-intervention | 15 (7%) | 47 (23%) | 103 (51%) | 36 (18%) |
| Post-intervention | 8 (4%) | 25 (12%) | 113 (56%) | 55 (27%) |
Includes data from both Session 2 (n = 101) and Session 3 (n = 100)