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Every picture tells a story: Content analysis of medical school website and prospectus images in the United Kingdom Cover

Every picture tells a story: Content analysis of medical school website and prospectus images in the United Kingdom

Open Access
|Jul 2019

Figures & Tables

Table 1

Data on assumed roles and image information

Data group

Image

People

Student

Teacher

Doctor

Patient

Nurse

Other

Entire dataset (%)

650 (100)

1817 (100)

1423 (78)

100 (6)

108 (6)

70 (4)

37 (2)

79 (4)

Research intensive (%)

384 (59)

1083 (60)

 879 (81)

 60 (6)

 57 (5)

35 (3)

18 (2)

34 (3)

Non-research intensive (%)

266 (41)

 734 (40)

 544 (74)

 40 (5)

 51 (7)

35 (5)

19 (3)

45 (6)

England (%)

511 (79)

1421 (78)

1110 (78)

 74 (5)

 90 (6)

52 (4)

30 (2)

65 (5)

Other UK countries (%)

139 (21)

 396 (22)

 313 (76)

 26 (8)

 18 (5)

18 (5)

 7 (2)

14 (4)

Table 2

Data on overall theme of the image and the assumed specialty group of the portrayed doctors

Data Group

Academic

Community

Hospital

Other

Community-based doctor

Hospital-based doctor

Entire dataset (%)

223 (34)

14 (2)

154 (24)

259 (40)

10 (9)

98 (91)

Research intensive (%)

142 (37)

 6 (2)

 81 (21)

155 (40)

 6 (11)

51 (89)

Non-research intensive (%)

 81 (30)

 8 (3)

 73 (27)

104 (39)

 4 (8)

47 (92)

England (%)

179 (35)

13 (3)

117 (23)

202 (40)

 9 (10)

81 (90)

Other UK countries (%)

 44 (31)

 1 (0)

 37 (26)

 57 (43)

 1 (6)

17 (94)

Table 3

Data for assumed gender and assumed ethnicity

Data group

Female

Male

Asian

Black

White

Other

Entire dataset (%)

1025 (56)

792 (44)

401 (22)

88 (5)

1328 (73)

0 (0)

Student (%)

 823 (58)

600 (42)

364 (26)

74 (5)

 985 (69)

0 (0)

Teacher (%)

  36 (36)

 64 (64)

 13 (13)

 2 (2)

  85 (85)

0 (0)

Doctor (%)

  41 (38)

 67 (62)

 15 (14)

 4 (4)

  89 (82)

0

Patient (%)

  34 (49)

 36 (51)

  2 (3)

 1 (1)

  67 (96)

0 (0)

Nurse (%)

  36 (97)

  1 (3)

  2 (5)

 5 (14)

  30 (81)

0 (0)

Table 4

Results for chi squared goodness of fit

Data for

Observed Frequency

Expected frequency

Chi squared

Degree of freedom

P value

Sex

Entire dataset

Census

 1.045

1

 0.307

Research intensive

Census

 1.276

1

 0.259

Non-research intensive

Census

 0.676

1

 0.411

England

Census

 1.000

1

 0.317

Other UK countries

Census

 2.632

1

 0.105

Doctor

NHS

 2.151

1

 0.143

Other roles

Census

14.612

1

<0.001

Patient

Census

 0.143

1

 0.705

Nurse

NHS

 6.839

1

 0.009

Teacher

HESA

 3.792

1

 0.052

Student

GMC

 0.514

1

 0.473

Student—research intensive

GMC

 0.842

1

 0.359

Student—non-research intensive

GMC

 0.099

1

 0.753

Student—England

GMC

 0.362

1

 0.547

Student—other UK countries

GMC

 1.251

1

 0.263

Ethnicity

Entire dataset

Census

37.343

3

<0.001

Research intensive

Census

36.052

3

<0.001

Non-research intensive

Census

39.314

3

<0.001

England

Census

24.676

3

<0.001

Other UK countries

Census

51.949

3

<0.001

Doctor

NHS

35.646

3

<0.001

Other roles

Census

 1.510

3

 0.680

Patient

Census

 5.636

3

 0.131

Nurse

NHS

14.031

3

 0.003

Teacher

HESA

12.910

3

 0.005

Student

GMC

12.378

3

 0.006

Student—research intensive

GMC

12.364

3

 0.006

Student—non-research intensive

GMC

14.921

3

 0.002

Student—England

GMC

13.161

3

 0.004

Student—other UK countries

GMC

11.886

3

 0.008

Theme

Entire dataset

Equal

33.440

3

<0.001

Research intensive

Equal

36.560

3

<0.001

Non-research intensive

Equal

28.636

3

<0.001

England

Equal

32.188

3

<0.001

Other UK countries

Equal

37.099

3

<0.001

Speciality

Entire dataset

Equal

67.240

1

<0.001

Research intensive

Equal

70.560

1

<0.001

Non-research intensive

Equal

60.840

1

<0.001

England

Equal

64.000

1

Other UK countries

Equal

72.516

1

<0.001

NHS National Health Service Digital, HESA Higher Education Statistics Agency, GMC General Medical Council

Language: English
Published on: Jul 25, 2019
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2019 Jack Macarthur, Mike Eaton, Karen Mattick, published by Bohn Stafleu van Loghum
This work is licensed under the Creative Commons Attribution 4.0 License.