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RESEARCH ARTICLE
Markers of achievement for assessing and
monitoring gender equity in a UK National
Institute for Health Research Biomedical
Research Centre: A two-factor model
Lorna R. HendersonID
1,2‡
*, Syed Ghulam Sarwar ShahID
1,2‡
, Pavel V. Ovseiko
2
,
Rinita DamID
2
, Alastair M. Buchan
2
, Helen McShaneID
1,3
, Vasiliki Kiparoglou
1,4
1National Institute for Health Research Oxford Biomedical Research Centre, John Radcliffe Hospital,
Oxford, United Kingdom, 2Radcliffe Department of Medicine, University of Oxford, Oxford, Oxford, United
Kingdom, 3Nuffield Department of Medicine, University of Oxford, Oxford, Oxford, United Kingdom,
4Nuffield Department of Primary Health Care Sciences University of Oxford, Oxford, United Kingdom
‡ These authors are joint senior authors on this work.
*Lorna.henderson@ouh.nhs.uk
Abstract
Background
The underrepresentation of women in academic medicine at senior level and in leadership
positions is well documented. Biomedical Research Centres (BRC), partnerships between
leading National Health Service (NHS) organisations and universities, conduct world class
translational research funded by the National Institute for Health Research (NIHR) in the
UK. Since 2011 BRCs are required to demonstrate significant progress in gender equity
(GE) to be eligible to apply for funding. However, the evidence base for monitoring GE spe-
cifically in BRC settings is underdeveloped. This is the first survey tool designed to rank and
identify new GE markers specific to the NIHR BRCs.
Methods
An online survey distributed to senior leadership, clinical and non-clinical researchers, train-
ees, administrative and other professionals affiliated to the NIHR Oxford BRC (N = 683).
Participants ranked 13 markers of GE on a five point Likert scale by importance. Data were
summarised using frequencies and descriptive statistics. Interrelationships between mark-
ers and underlying latent dimensions (factors) were determined by exploratory and confir-
matory factor analyses.
Results
The response rate was 36% (243 respondents). Respondents were more frequently female
(55%, n = 133), aged 41–50 years (33%, n = 81), investigators (33%, n = 81) affiliated to the
BRC for 2–7 years (39.5%, n = 96). Overall participants ranked ‘BRC senior leadership
roles’ and ‘organisational policies on gender equity’, to be the most important markers of
GE. 58% (n = 141) and 57% (n = 139) respectively. Female participants ranked
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OPEN ACCESS
Citation: Henderson LR, Shah SGS, Ovseiko PV,
Dam R, Buchan AM, McShane H, et al. (2020)
Markers of achievement for assessing and
monitoring gender equity in a UK National Institute
for Health Research Biomedical Research Centre: A
two-factor model. PLoS ONE 15(10): e0239589.
https://doi.org/10.1371/journal.pone.0239589
Editor: Frantisek Sudzina, Aalborg University,
DENMARK
Received: February 3, 2020
Accepted: September 9, 2020
Published: October 14, 2020
Copyright: ©2020 Henderson et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the manuscript and its Supporting
Information files.
Funding: PVO, RD, AMB were funded by the
European Union’s Horizon 2020 research and
innovation programme award STARBIOS2 under
grant agreement No. 709517. https://starbios2.eu/
LRH, SGSS, VK, HMcS were funded by the NIHR
Oxford Biomedical Research Centre. https://
oxfordbrc.nihr.ac.uk/ The views expressed are
‘organisational policies’ (64.7%, n = 86/133) and ‘recruitment and retention’ (60.9%, n = 81/
133) most highly, whereas male participants ranked ‘leadership development’ (52.1%, n =
50/96) and ‘BRC senior leadership roles’ (50%, n = 48/96) as most important. Factor analy-
ses identified two distinct latent dimensions: “organisational markers” and “individual mark-
ers” of GE in BRCs.
Conclusions
A two-factor model of markers of achievement for GE with “organisational” and “individual”
dimensions was identified. Implementation and sustainability of gender equity requires com-
mitment at senior leadership and organisational policy level.
Introduction
Underutilisation of female talent and potential in academic medicine, particularly at senior
levels and leadership roles, as well as the health workforce more broadly is well documented
[1–4]. This has been referred to as a “leaky talent pipeline” [5].
In 2011 the challenge to address gender equity (GE) in medical schools was linked directly
to BRCs in England. The UK Department of Health’s Chief Medical Officer announced that
(NIHR) would not shortlist any National Health Service (NHS) / University partnership for
NIHR BRC designation and funding: “where the academic partner (generally the Medical
School/Faculty of Medicine) has not achieved at least a Silver Award of the Athena SWAN
Charter for Women in Science” [6].
Athena SWAN charter
The Athena SWAN charter advances women’s careers in Universities in terms of represen-
tation, progression of students into academia, journey through career milestones and
working environment [7]. Universities may be awarded Bronze, Silver or Gold Athena
SWAN award, based on their action plans, achievements and impact in advancing gender
equity [7]. Athena SWAN awards are useful markers of GE achievement in Universities but
not specifically designed for translational research organisations (TROs) such as NIHR
BRCs, partnerships between UK’s leading NHS organisations and universities [8]. Further-
more, recent GE research has focussed on Universities [9–13]. There is therefore a gap in
GE research and practice in the context of NIHR BRCs [14]. This study aims to address gap
by identifying new markers of achievement for assessing and monitoring GE in NIHR
BRCs.
Methods
Study aims and objectives
The aims of this study are two fold: firstly, to inform women’s advancement in translational
research settings through the development of markers of achievement for assessing and moni-
toring gender equity. Secondly, to test and develop a survey tool which captures the major
dimensions of gender equity in the NIHR BRC to inform future planning and monitoring of
GE in a Biomedical research setting [14].
We adopt the UNESCO definition of gender equity: “fairness of treatment for women and
men, according to their respective needs. This may include equal treatment or treatment that
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those of the author(s) and not necessarily those of
the funders i.e. EU, NHS, the NIHR or the
Department of Health. The funders had no role in
study design, analysis and interpretation of this
study.
Competing interests: HMcS is Director of the
NIHR Oxford Biomedical Research Centre, VK is
Chief Operating Officer of the NIHR Oxford
Biomedical Research Centre, LRH is Clinical
Research Manager, SGSS is Senior Research
Fellow. AMB was the founding Director of the NIHR
Oxford BRC. This does not alter our adherence to
PLOS ONE policies on sharing data and materials.
is different but which is considered equivalent in terms of rights, benefits, obligations and
opportunities” [15].
Study setting
The NIHR is the UK’s largest funder of health and care research [16]. There are currently 20
BRCs: collaborations between universities and NHS organisations bringing together academ-
ics and clinicians to translate scientific breakthroughs into new treatments, diagnostics and
medical technologies [17]. The study was conducted at the NIHR Oxford BRC—a collabora-
tion between the Oxford University Hospitals NHS Foundation Trust and the University of
Oxford. It is based at the Oxford University Hospitals—one of the largest UK acute teaching
hospitals with an International reputation for services and research [18]. It is run in partner-
ship with the University of Oxford which is consistently ranked as the world’s best institution
for medical teaching and research [19].
The NIHR Oxford BRC was established in 2007 with competitive funding from NIHR of
£57 million over 5 years, £96 million in 2012 to recognise its outstanding contribution to
research and £113.6 million in 2016 making it one of the largest BRCs in the UK [18]. This
funding supports NHS clinicians and world leading academics to conduct translational
research. The BRC is divided into twenty research themes (e.g. Genomics, Cardiovascular,
Diabetes, etc.) and four clusters (Precision Medicine, Technology and Big Data, Immunity and
Infection and Chronic Diseases) [18].
Study population
In contrast to existing studies focussing on GE in Universities, our study population is inten-
tionally broader including both university and NHS employees.
Study population (N = 683) including all researchers and affiliates were invited to partici-
pate. The participants were categorised as Investigators: researchers leading and undertaking
research, associates supporting research led by others (i.e. facilitators and administrative staff),
and academic trainees (trainees/PhD students). In addition, patient and public involvement
representatives, industry managers and leaders (including senior executive and non-executive
committees) funded / supported the NIHR Oxford BRC (herewith referred to as BRC affiliates)
were invited to participate. Names and contact details of all affiliates were extracted from the
BRC’s internal databases. To ensure accuracy, all BRC theme managers were also contacted
and asked to provide up to date email addresses of affiliates within their respective themes. List
of participants invited to survey included 311 male names (45.5%) and 372 female names
(54.5%). There were 341 (49.9%) investigators ((e.g. PI (Principal Investigators) / co-PI / CI
(co-investigators)), 210 (30.7%) research associates (e.g. researchers and research fellows), 25
(3.7%) trainees/PhD students, 79 (11.6%) administrative / technical and other professional
staff, and 28 (4.1%) other professionals associated with the BRC.
Development of the questionnaire
Participants were asked to rank the importance of 13 markers of achievement of GE in BRCs
on a five point Likert scale: Very important” (score 5), “Important” (score 4), “Neutral” (score
3), “Not important” (score 2) and “Not at all important” (score 1). Potential markers were
identified from the literature reported in the study protocol [14]. We then checked the face
validity of the identified potential markers.
Participants’ were asked to provide demographic characteristics i.e. age, gender; current
role in the NIHR Oxford BRC and how long they had been affiliated to the BRC. Taking into
account the diverse identities of women and men and based on the University of Oxford staff
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survey categories we did not use a binary sex indicator for gender but added “self describe”
and “not report” following guidance from the University of Oxford’s equality and diversity
team.
Piloting of the questionnaire
The questionnaire was piloted in face-to-face interviews with potential participants (n = 10) to
ensure it was easily understood and met the purpose of what it was intended to measure. It
was also tested via email to a small sample (n = 16) from the population of interest to assess
readability and clarity of the items and appropriateness of participants interpretations. Follow-
ing piloting, a few minor changes were made in wording and formatting prior to the main sur-
vey study (S1 Appendix).
Administration of survey
The survey was conducted from May to July 2019. The NIHR Oxford BRC’s Chief Operating
Officer sent an email via SurveyMonkey1with a web link to the anonymous online survey to
all survey participants (N = 683) informing them about the survey. The clinical research man-
ager of the NIHR Oxford BRC also sent an email to BRC theme liaisons (theme managers) to
inform their theme members, i.e. theme leaders, researchers and supporting BRC affiliates
about the survey. Up to 3 automated email reminders over the 6 weeks were sent via Survey-
Monkey1to participants who had not completed or partially completed the survey.
Data analysis
Online data from SurveyMonkey1was downloaded in SPSS and Microsoft Excel spreadsheet
formats. Frequencies of participants’ demographic characteristics and descriptive statistics of
scores of the importance of 13 markers of GE in BRCs were analysed. The Mann-Whitney U
test was used to determine statistical differences in ranking the importance of GE markers by
participants’ gender (only male and female categories). The Kruskall-Wallis H test with Bon-
ferroni corrections was applied to evaluate differences in ranking markers by participants’ age
(3 categories: 18–40 years, 41–50 year, and 51 and more years), BRC role (3 categories: Investi-
gators, research associates, and admin/tech/prof. staff) and duration of affiliation to the BRC
(3 categories: up to 2 years, 3–7 years, and more than 7 years). For statistical significance, a p-
value <0.05 was applied.
Thereafter, data on participants’ scores of the importance of 13 markers of GE in BRCs
were analysed using exploratory and confirmatory factor analyses for identifying underlying
latent factors / constructs, as described below.
Exploratory factor analysis. We determined interrelationships between markers and
underlying latent dimensions (factors) by exploratory factor analysis (EFA) [20]. EFA was run
to extract the latent factors (dimensions) covered in the measured 13 markers of GE. For the
EFA, we used Principal Component Analysis (PCA) as a factor-extraction method, the Vari-
max with Kaiser Normalization as a rotation method and the Kaiser’s Eigen values >1
(EVG1) criterion and breaks in the scree plot for determining the number of latent factors
[21]. We applied minimum communalities 0.50, with no cross loadings 0.45 on more than
one latent factor [21] and the minimum acceptable factor loading as 0.50 on only one factor
[20]. Our sample size was 243 and the participant-to-variable ratio was 18:1, which was higher
than the minimum acceptable participant-to-variable ratio of 10:1 [20].
Confirmatory factor analysis. Subsequent to the EFA, we ran the confirmatory factor
analysis (CFA) [22]. The internal consistency of latent dimensions identified in the EFA was
checked by running scale reliabilities using the Cronbach’s alpha coefficient [23]. The
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measurement model identified in CFA was checked for convergent and discriminant validity
by calculating the Average Variance Extracted (AVE) as suggested [20,24].
Participants’ ratings of GE markers were positively skewed, which was reduced by log transfor-
mation prior to running EFA and CFA [22]. All statistical analyses were undertaken using IBM
SPSS Statistics for Windows, version 25.0 (IBM Corp INC: Armonk, NY) except the CFA for
which we used the IBM SPSS AMOS for windows, version 26.0 (IBM Corp INC: Armonk, NY).
Ethics
The study was reviewed by Oxford University Medical Sciences Inter-divisional Research Eth-
ics Committee and University of Oxford Clinical Trials and Research Governance office who
determined that the study was exempt from full ethical review. The information sheet provided
on the first page of the online survey informed participants that their participation in the sur-
vey was voluntary and they could withdraw at any time. They were also informed that their
data and responses provided in the survey would be held securely, confidential, processed and
reported anonymously and in aggregated format. Participants were informed that ‘if you do
not wish to complete the survey, please click on ‘No, I do not consent’ and then the survey will
be aborted’. Consequently, only those participants who gave their online informed consent by
clicking the option ‘Yes, I consent’ were able to complete the survey via SurveyMonkey1.
Results
Response rate
The survey was completed by 277 out of 683 participants invited. 34 responses were ineligible
for inclusion as they provided partial or missing data; hence, were removed from the sample
and data analysis. One participant did not consent and opted out of the survey. Therefore, the
final sample comprised 243 respondents and the effective response rate was 36%.
Demographic characteristics of participants
The majority of respondents were female (55%, n = 133), aged 41–50 years (33.3%, n = 81),
investigators e.g. principal, co and chief investigators (33.3%, n = 81) affiliated with the BRC
for 2–7 years (39.5%, n = 96) (Table 1).
Ranking of markers of achievement for gender equity
Table 2 presents participants’ rankings of the importance of 13 markers of GE. The top two
markers with the highest overall mean rankings were BRC senior leadership roles
(mean = 4.43, standard deviation (SD) = 0.80) and organisational policies on gender equity
(mean = 4.40, SD = 0.85).
When participants scores were combined, the majority (58%, n = 141) scored BRC senior
leadership roles as a very important marker of GE. Organisational policies on GE ranked as
the second highest very important marker by 57.2% (n = 139) of participants (Fig 1). Collabo-
ration with industry and Intellectual property emerged as the last and second last very impor-
tant markers of GE in BRCs 35.4% (n = 86) and 35.8% (n = 87) respectively (Fig 1).
The Mann-Whitney U test results showed that statistically significant differences in the
mean rankings by gender i.e. male and female participants for eight markers. These were BRC
senior leadership roles (U = 5492 p = 0.040), BRC staff category (U = 5471, p = 0.040), recruit-
ment and retention, (U = 5211, p = 0.008), BRC funding (U = 5335, p = 0.023), external grant
funding, (U = 5444, p = 0.042), collaboration with industry (U = 5434, p = 0.041), organisa-
tional policies on gender equity (U = 5462, p 0.034), and organisational targets (U = 5375,
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p = 0.026 (Table 2). Overall, a higher proportion of female participants ranked all 13 markers
of GE as the most important marker compared to male participants (Fig 2).
We created a priority ranking order from 1 to 13 of all markers of GE ((highest (Rank 1)
lowest (Rank 13)) based on the percentage of participants ranking each marker as very impor-
tant (Table 3).
Differences in ranking by gender
Men ranked “leadership development” (53.7%) and “BRC senior leadership roles”, (52.4%) as
the most important markers of GE(53.7% and 52.4% respectively). Conversely, women ranked
“organisational policies on gender equity” (66.3%) and “recruitment and retention” (65.4%)
(66.3% and 65.4% respectively) (Table 3).
Differences in ranking by role
Ranking also differed by participants’ seniority. Investigators ranked “Leadership develop-
ment” to be the most important (65.7%), associates ranked “recruitment and retention”
(68.9%) whereas less senior staff ranked “organisational policies on gender equity” for 53.8%
as most important (53.8%) (Table 3). The Kruskal-Wallis H test with Bonferroni corrections
Table 1. Socio-demographic characteristics of survey respondents.
Socio-demographic characteristics Frequency Percentage
Gender
Female 133 54.7
Male 96 39.5
Prefer to self describe 3 1.2
Prefer not to say 10 4.1
Missing data 1 0.4
Age (years)
18–30 21 8.6
31–40 60 27.4
41–50 81 33.3
51–60 52 21.4
61+ 17 7.0
Prefer not to say 11 4.5
Missing data 1 0.4
Affiliate category / Role in the BRC
Investigators (e.g. PI/co-PI/CI) 81 33.3
Research Associates (e.g. Researchers and research fellows) 67 27.6
Admin/technical/Professional/Support Associates 59 24.3
Trainees/PhD students 3 1.2
Other 21 8.6
Prefer not to say 9 3.7
Missing data 3 1.2
Duration of affiliation with the BRC
Up to 2 years 86 35.4
3-7years 96 39.5
More than 7 years 52 21.4
Prefer not to say 6 2.5
Missing data 3 1.2
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showed that the mean scores of ranking the importance of the markers by the role in the BRC
(3 categories: Investigators, research associates, and admin/tech/prof. staff) were statistically
significantly different for six markers: BRC senior leadership roles (χ
2
(2) = 8.89, p = .012),
BRC staff category (χ
2
(2) = 14.39, p = .001), recruitment and retention (χ
2
(2) = 13.25, p =
.001), BRC funding (χ
2
(2) = 11.46, p = .003), external grant funding (χ
2
(2) = 12.12, p = .002),
and publications (χ
2
(2) = 10.59, p = .005) (Table 3).
Differences in ranking by duration of affiliation to BRC
Participants affiliated to the BRC for over seven years ranked “BRC senior leadership roles” as
most important marker (67.6%) in contrast those affiliated for up to 2 years or 3–7 years ranked
“organisational policies on gender equity” most highly (57.9% and 60.3% respectively) (Table 3).
Differences in ranking by age
“Leadership development” was the top most important marker of GE for participants aged 40
years and older whereas the under 40 group ranked notably lower (rank 6). “Organisational
Table 2. Participants rankingof markers of achievement of gender equity in biomedical research centres (N = 243).
Descriptive statistics (rating by all participants) Differences in rating by gender
a
—Male and
Female participants only
Mean Standard
Deviation
Median Mode Percentiles Gender Mann-
Whitney U
Z
score
P Value
(2-tailed)
Markers of achievement of gender equity 25 50 75 Male Female
1. BRC senior leadership roles: e.g. Director, Steering
Committee Member, Theme leader & Co-lead.
4.43 0.8 5 5 4 5 5 4.35 4.53 5492 -2.055 0.04
2. Leadership development: e.g. Gender-sensitive
leadership programmes, succession plans.
4.34 0.91 5 5 4 5 5 4.39 4.40 6128 -0.582 0.561
3. BRC staff category: e.g. Principal Investigator,
Researchers, Trainees and Admin & Support staff.
4.33 0.87 5 5 4 5 5 4.26 4.46 5471 -2.053 0.04
4. Recruitment & retention: e.g. Number of Staff recruited
and promoted.
4.34 0.86 5 5 4 5 5 4.24 4.50 5211 -2.651 0.008
5. BRC funding: e.g. Distribution by Theme, Gender and
Role.
4.13 0.96 4 5 4 4 5 4.03 4.28 5335 -2.278 0.023
6. External grant funding: e.g. Total amount, Role on the
grant, Number of grants and Success rate.
4.09 0.94 4 5 4 4 5 4.01 4.24 5444 -2.032 0.042
7. Esteem indicators: e.g. NIHR Senior Investigators,
Funding panel membership, Invited plenary speakers,
Fellowships of learned societies, Honours and Awards.
4.25 0.91 4 5 4 4 5 4.20 4.38 5522 -1.912 0.056
8. Publications: e.g. Authorship (First / Corresponding /
Senior author) and Type of Publication (Journal articles
and Conference papers).
4.09 0.97 4 5 4 4 5 4.02 4.21 5483 -1.955 0.051
9. Intellectual property: e.g. Number of Patents, Licenses
and Spinouts.
3.9 1.06 4 5 3 4 5 3.80 4.05 5505.5 -1.867 0.062
10. Collaboration with industry: e.g. Board membership,
Joint grants and Advisory roles (non-executive
directorships).
3.99 1 4 4 3 4 5 3.91 4.13 5434 -2.045 0.041
11. Patient and public involvement: e.g. Representative
Number of Men and Women Speakers and Participants.
4.19 0.9 4 5 4 4 5 4.14 4.31 5536 -1.856 0.063
12. Organisational policies on gender equity: e.g. Personal
Development Training, Mentoring, Sponsorship and
Career Development.
4.4 0.85 5 5 4 5 5 4.35 4.49 5462 -2.115 0.034
13. Organisational Targets: e.g. Creating BRC targets for
Gender Equity.
4.21 0.98 4 5 4 4 5 4.14 4.36 5375 -2.23 0.026
Scores: 1 = Not important at all, 2 = Not important, 3 = Neutral, 4 = Important, 5 = Very Important. a. Grouping Variable: Gender—male and female only.
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Table 3. Priority ranking order of markers of gender equity by participants’ gender, role in the BRC, duration of affiliation with the BRC and age.
Very important scores only
Gender Role in the BRC Duration of affiliation to the BRC Age group
Male Female Investigators Research
associates
Admin/Tech/
Prof. Staff
Up to 2 years 3–7 years >7 years 18–30years 30–40 years 41–50 years 51–60years 60+ years
Markers of gender equity Rank % Rank % Rank % Rank % Rank % Rank % Rank % Rank % Rank % Rank % Rank % Rank % Rank %
1. Leadership development 1 53.7 5 60.6 1 65.7 6 59 4 44.2 4 53.9 3 57.5 2 64.9 6 43.8 6 60.8 1 50.8 1 62.5 1 78.6
2. BRC senior leadership roles 2 52.4 3 64.4 2 64.3 2 65.6 3 44.2 2 56.6 2 57.5 1 67.6 2 56.3 3 64.7 2 49.2 2 62.5 2 78.6
3. BRC Staff category 3 47.6 4 61.5 3 60 3 65.6 7 38.5 5 53.9 4 54.8 4 59.5 7 43.8 4 62.7 4 46.2 4 57.5 3 78.6
4. Recruitment and retention 5 45.1 2 65.4 4 58.6 1 68.9 5 40.4 3 56.6 5 53.4 5 59.5 4 50 1 72.5 5 43.1 5 57.5 5 64.3
5. BRC funding 8 36.6 8 53.8 5 52.9 8 50.8 9 30.8 6 53.9 8 46.6 10 51.4 12 37.5 8 51 8 40 8 52.5 11 50
6. Esteem indicators 6 42.7 7 57.7 6 52.9 5 60.7 8 34.6 9 44.7 6 52.1 3 62.2 3 56.3 7 58.8 7 40 9 50 4 71.4
7. Organisational policies on gender equity 4 47.6 1 66.3 7 52.9 4 65.6 1 53.8 1 57.9 1 60.3 6 54.1 1 75 2 64.7 3 47.7 3 60 6 57.1
8. Organisational Targets 7 40.2 6 58.7 8 47.1 7 57.4 2 46.2 8 48.7 7 50.7 7 54.1 8 43.8 5 62.7 6 40 7 52.5 8 57.1
9. External grant funding 10 32.9 10 49 9 45.7 11 47.5 11 28.8 7 53.9 9 45.2 8 54.1 9 43.8 10 41.2 9 35.4 10 50 12 50
10. Publications 11 32.9 11 45.2 10 42.9 9 50.8 13 23.1 11 31.6 11 41.1 9 54.1 10 43.8 11 37.3 10 35.4 11 45 13 50
11. Patient and public involvement 9 35.4 9 51.9 11 41.4 10 50.8 6 40.4 10 43.4 10 42.5 11 51.4 11 43.8 9 49 11 30.8 6 57.5 7 57.1
12. Intellectual property 12 30.5 13 41.3 12 38.6 12 44.3 12 25 13 27.6 12 39.7 13 48.6 13 37.5 12 33.3 12 30.8 13 42.5 10 57.1
13. Collaboration with industry 13 29.3 12 42.3 13 35.7 13 41 10 30.8 12 27.6 13 38.4 12 51.4 5 50 13 29.4 13 29.2 12 45 9 57.1
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policies on gender equity” were the most important marker for a notably high number of
younger participants (75% aged 18–30 years), similarly “recruitment and retention” for 72.5%
of participants the 30–40 years career group whereas the >40 career group ranked it notably
lower (rank 5) (Table 3).
However, Kruskal-Wallis H tests with Bonferroni corrections showed that there were no
statistically significant differences in the mean rankings of all markers between different age
categories (3 categories: 18–40 years, 41–50 year, and 51 and more years) or duration of affilia-
tion to the BRC (3 categories: up to 2 years, 3–7 years, and more than 7 years).
Exploratory factor analysis
Results of the first EFA model that included all 13 measured markers revealed a two factor
solution but the rotated component matrix showed that marker No. 5 (i.e., BRC funding) had
very high cross loadings i.e., 0.53 on factor 1 and 0.68 on factor 2. We removed this marker
Fig 1. Importance of markers of gender equity in BRCs by all respondents.
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and re-ran the EFA model with 12 markers, which again resulted in a 2 latent factor solution
but again the rotated component matrix revealed that measured marker No. 7 (i.e., esteem
indicators) had very high cross loadings i.e., 0.50 and 0.67 on factor 1 and factor 2 respectively.
Consequently, we removed marker No. 7 and re-ran the EFA, which again resulted in a 2 latent
factor solution with the rotated component matrix showing marker No. 11 (i.e., patient and
public involvement) with higher cross loadings i.e., 0.61 on factor 1 and 0.45 on factor 2.
Subsequently, we removed marker No. 11 from the EFA and re-ran the model, which
showed no marker having cross loading 0.45 on more than one factor “Table 4”. We selected
this model as a final EFA model with the Kaiser-Meyer-Olkin (KMO) Measure of Sampling
Adequacy = 0.884 and statistically significant Bartlett’s Test of Sphericity (χ
2
= 1553.69,
p<0.0001), which confirmed the suitability of the data for running the EFA model. Table 4
presents the statistics about the extracted communalities, total variance explained and Rotated
Factor Matrix. Based on the content of loaded measured items on latent factor 1 and factor 2,
we identified these markers as the organisational and individual markers respectively
(Table 4).
Fig 2. Markers of gender equity marked as very important by gender.
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Confirmatory factor analysis
To check the two latent factor solution observed in the EFA (Table 4), we ran CFA (henceforth
mentioned as the initial CFA model) as shown in Fig 3A.
A model summary of the goodness of fit (GoF) indices for the initial CFA model is pre-
sented in (Table 5). The GOF indices suggested that the initial CFA model did not fit with the
data. Consequently we created post-hoc modifications by correlating error estimates of some
parameters (measured items) as suggested in the Modification indices in the initial AMOS
model (Fig 3A). This helped in improving the model fit to given data in the final model (Fig
3B), henceforth mentioned as the post-hoc CFA model.
The GOF indices of the post-hoc model (Table 5) showed a good fit of the post-hoc model
with the data. We therefore accepted the post-hoc CFA model as the final CFA model.
The estimates of standardized regression weights (β) of measured items on to the latent fac-
tors along with their significance level (p) observed in both the initial and the post-hoc CFA
models (Table 6), demonstrate that all measured markers had statistically significant higher
loadings on organisational makers factor (β0.68, p<0.001) and individual markers factor (β
0.85, p<0.001) (Table 6,Fig 3A and 3B).
We checked the internal consistency and convergence of both latent factors by the compos-
ite reliability and average variance extracted (AVE) respectively. Six measured items (markers)
that loaded on to the organisational markers factor explained 64 AVE and 63 AVE in the initial
and the post-hoc CFA models respectively whereas four items that loaded on to the individual
markers factor explained 76 AVE and 78 AVE in the initial and post-hoc CFA models
Table 4. Exploratory factor analysis: Measured markers of gender equity, latent factors with loadings, communal-
ities, Eigen values, KMO Measure of Sampling Adequacy, Bartlett’s Test of Sphericity, total variance explained
and scale reliabilities.
Rotated Component Matrix
a
Measured items/ Markers of gender
equity
Component loadings Communalities
Factor 1 (Organisational
markers)
Factor 2 (Individual
markers)
h
2
BRC senior leadership roles .84 .30 .80
Leadership development .81 .29 .74
BRC staff category .78 .39 .76
Recruitment & retention .77 .28 .67
External grant funding .42 .79 .79
Publications .34 .83 .80
Intellectual property .34 .87 .87
Collaboration with industry .30 .85 .81
Organisational policies on gender equity .68 .33 .58
Organisational Targets .72 .35 .64
Eigenvalues 6.40 1.06
Kaiser-Meyer-Olkin (KMO) Measure of
Sampling Adequacy
.884
Bartlett's Test of Sphericity χ2 = 1553.69
Significance (P) <0.0001
of total variance explained 63.98 10.65
Cronbach’s αreliability (Standardised) .912 .925
a
Extraction Method: Principal Component Analysis; Rotation Method: Varimax with Kaiser Normalization; Rotation
converged in 3 iterations.
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Fig 3. A Initial CFA-model. Notes: Rectangles represent measured items (endogenous variables); circles represent latent (unmeasured/exogenous) variables. Marker 1
(BRC senior leadership roles), Marker 2 (Leadership development), Marker 3 (BRC staff category), Marker 4 (Recruitment and retention), Marker 6 (External grant
funding), Marker 8 (Publications e.g. authorship), Marker 9 (Intellectual property), Marker 10 (Collaboration with industry), Marker 12 (Organisational policies on
gender equity) and Marker 13 (Organisational Targets for gender equity). B Post-hoc CFA model. Notes: Rectangles represent measured items (endogenous variables);
circles represent latent (unmeasured/exogenous) variables. Marker 1 (BRC senior leadership roles), Marker 2 (Leadership development), Marker 3 (BRC staff category),
Marker 4 (Recruitment and retention), Marker 6 (External grant funding), Marker 8 (Publications e.g. authorship), Marker 9 (Intellectual property), Marker 10
(Collaboration with industry), Marker 12 (Organisational policies on gender equity) and Marker 13 (Organisational Targets for gender equity).
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respectively. The observed AVE for both factors was higher than the minimum 0.5 that is sug-
gested for adequate convergence [17,18].
We calculated the composite reliability for the organisational markers factor as 0.91 for
both the initial and the post-hoc CFA models and the composite reliability for the personal
markers factor as 0.93 and 0.94 in the initial and post-hoc CFA models respectively. The com-
posite reliabilities for both latent factors were higher than the minimum required composite
reliability of 0.7, which indicated that both latent factors have a high internal consistency sug-
gesting that the loaded measured markers (items) consistently represented the respective iden-
tified latent factor [17,18]. The CFA models showed that both latent factors i.e., the
organisational markers and the individual markers have a strong correlation i.e., 0.76 and 0.75
in the initial and post-hoc CFA models respectively. The EFA and CFA results identified and
confirmed two significant dimensions i.e., organisational and individual markers of GE in
BRCs.
Table 5. Summary of goodness of fit indices observed in the initial and post-hoc CFA models.
Values χ
2
Df Sig (p)χ
2
/df IFI NFI CFI RMSEA
Recommended >0.05 3.00 0.9 0.9 0.9 0.08 (p>0.05)
Observed in initial CFA
model
239.95 43 <0.0001 5.58 0.88 0.86 0.88 0.16‡
Observed in Post-hoc CFA
model
48.81 26 0.004 1.88 0.98 0.97 0.99 .07‡(Low 90.038, High 90.098), p
Close 0.141
χ
2
, Chi-square; Df, degrees of freedom; Sig, significance level (p),CFI, comparative fit index; IFI, Incremental fit
index; NFI, normed fit index; RMSEA, root mean square error of approximation
‡90 confidence interval for RMSEA.
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Table 6. Latent factors, measured markers and standardised estimates observed in initial and post-hoc CFA
models.
Initial CFA Model Post-hoc CFA Model
Latent factors Measured markers Estimate† (β) C.R. P Estimate† (β) C.R. P
Organisational Markers !Marker 1 0.88 ‡ ‡ 0.85 ‡ ‡
!Marker 2 0.83 15 0.78 15.9
!Marker 3 0.87 16.4 0.92 16.1
!Marker 4 0.78 13.3 0.79 13.2
!Marker 12 0.68 10.7 0.65 9.34
!Marker 13 0.73 12.1 0.74 10.3
Individual Markers !Marker 10 0.85 ‡ ‡ 0.85 ‡ ‡
!Marker 9 0.92 16.7 0.94 16.1
!Marker 8 0.86 15.1 0.86 14.1
!Marker 6 0.85 14.7 0.89 14.5
Marker 1 (BRC senior leadership roles), Marker 2 (Leadership development), Marker 3 (BRC staff category), Marker
4 (Recruitment and retention), Marker 6 (External grant funding), Marker 8 (Publications e.g. authorship), Marker 9
(Intellectual property), Marker 10 (Collaboration with industry), Marker 12 (Organisational policies on gender
equity) and Marker 13 (Organisational Targets for gender equity)
†Estimates of standardized regression weights
‡Not estimated because of loading set to fixed value i.e., 1.0
Significance value (p): <.001.
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Discussion
The survey identified a new statistically significant model of GE markers with two distinct
dimensions of GE markers (1) organisational markers and (2) individual markers (Fig 4). The
present study is the first, to our knowledge, that has developed such a model attuned to the
context of NIHR BRCs. Firstly, we discuss the findings in relation to the findings and implica-
tions regarding organisational markers, secondly, individual markers.
Findings and implications regarding organisational markers of gender
equity
The dimension of organisational markers of GE identified in our study comprised six markers
of GE (Tables 4and 6,Fig 4). The scrutiny of the wording and content of these six markers by
authors showed these six markers could be sub-divided into three sub-dimensions; leadership
markers, BRC staff markers and organisational policies and targets markers (Fig 4).
Leadership markers. The leadership sub-dimension comprised two markers i.e., leader-
ship development and senior leadership roles. The BRC staff sub-dimension included two
markers, i.e. staff category and staff recruitment and retention. While the third sub-dimension
Fig 4. Organisational and individual markers of gender equity in BRCs.
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of organisational policies and targets encompassed two markers: organisational policies on
gender equity and organisational targets (Fig 4).
The high ranking of leadership for GE in this study suggests further local organisational
policies may be appropriate. As highlighted elsewhere, local drivers are important to support
existing GE initiatives. For example a recent evaluation of Athena SWAN did not indicate a
statistical relationship between the Charter and increase in the proportion of female staff over
time [10].
Organisational policies and targets. Our study provides new potential GE markers
within the specific setting of NIHR BRCs. The population is intentionally broader than previ-
ous GE research which has predominantly focussed on clinical academic settings [3,25–31] or
Athena SWAN research project populations which focus on university and academic staff [10,
11]. In contrast, this study population includes both NHS staff and clinical and non-clinical
university staff at all levels.
Leadership roles
When scores for all participants were combined, BRC senior leadership roles ranked as the
most important marker of GE followed by organisational policies on gender equity (Fig 4)
This may reflect findings from a recent evaluation of the Athena SWAN programme which
highlighted significant challenges remain in addressing gender balance in the most senior
positions in higher education (e.g. professorial, senior management) [9]. It also supports the
finding that leadership is a key driver for sustainable organisational change in terms of GE
[31].
Organisational policies on gender equity
Our results suggest that organisational policies on GE are an important measure required.
This is typically facilitated at an organisational level by Athena SWAN, but the results suggest
more BRC focussed targets may be beneficial at a local level. Linking the direct impact of the
introduction of Athena SWAN to the acceleration of GE in an institution is challenging due to
the complexity of issues [12].
Findings and implications for Individual markers of gender equity
The second dimension, i.e. individual markers of gender equity identified included four mark-
ers of GE (Tables 4and 6,Fig 4). The review of the wording and content of these four markers
by authors suggested these four markers could be sub-divided into four sub-dimensions,
which include research funding, publications, intellectual property and industry collaboration
and each of these sub-dimensions included only one GE marker, i.e. marker 6, 8, 9 and 10
respectively (Tables 4and 6). These findings concur with a recent analysis of lessons learned
from the Athena SWAN demonstrates the importance of baseline data for the purposes of
benchmarking, and importance of leadership to enable systemic change [12]. At the NIHR
Oxford BRC, benchmarking of gender and BRC publications and staff is in place. However,
TRO funders may consider encouraging gender benchmarking or making it mandatory. For
example, currently the only mandatory request for gender data within BRCs is NIHR academy
members (PhD students etc.).
Markers of achievement in industry and gender equity
Interestingly, collaboration with industry and the Intellectual property emerged as the last and
second last very important markers of GE in BRCs reported by 35.4 (n = 86) and 35.8 (n = 87)
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of participants respectively (Table 2). This may reflect relatively low participation of women in
industry [28,29]. However it is an important area to address given that collaboration with
industry is an important metric in BRCs to report to their funder the NIHR.
Analysis of ranking by gender of participants
Men ranked “leadership development” and “BRC senior leadership roles”, to be most impor-
tant. Conversely women ranked “organisational policies on gender equity” and “recruitment
and retention” to be most important (Table 3). This may reflect women’s perceptions that
organisational policies are important drivers of GE and further work is required to support
leadership development.
The response rate (36%) in our study is consistent with online questionnaire survey
response rates which are typically lower than mail based questionnaires [32] and when partici-
pants include clinical professionals [33]. Our results show that the majority of respondents
were female suggesting that women were slightly more likely to respond. Research has shown
that the relevance of the study topic may impact response rates and so this may have been a
factor too [34]. The results also show that women and men rank the importance of the markers
of GE differently and a greater proportion of women ranked all markers as the most important
compared to the proportion of male participants. However a relatively high proportion of
respondents were male (40%) this is key as research has indicated men’s support and perspec-
tive is also an important driver of GE in institutions [35].
In regards to the representativeness of the findings in relations to participants who were
invited and those who responded, there were no statistically significant differences by partici-
pants’ gender and their role in the BRC when Bonferroni corrections were applied.
Strengths and limitations
To our knowledge, this is the first study to explore views on new markers of achievement for
women in academic science specifically in an NIHR BRC setting. Previous research in this
field has focussed predominantly on clinical academic settings and Athena SWAN evaluations
in Universities [11,12,27]. Our study proposes a two-factor model of GE markers in a NIHR
BRC setting (Fig 4) based on the conceptual framework derived from the existing literature
[14] and views of BRC affiliates across different genders, staff categories, and levels of seniority.
Our study compliments the existing literature on gender equity in universities by contributing
a context-specific perspective on NIHR BRCs—partnerships between universities and NHS
organisations. In doing so, our study contributes to the growing body of literature recognising
the complexity of factors producing gender inequality and the importance of context-specific
interventions for different categories of staff [36–40] Under the complexity approach, address-
ing gender inequality requires multiple areas of intervention with a focus on the local context
and dynamics [40–42]. Therefore, context-specific GE markers can help to identify areas for
improvement, plan interventions, and monitor progress against the goals and strategic objec-
tives for different categories of staff.
Given the significant investment in NIHR BRCs and direct link of demonstrable progress
in GE equity, the proposed two-factor model of GE markers is of particular practical relevance
to the NIHR Oxford BRC, other NIHR BRCs and policy makers in the UK, and possibly simi-
lar translational research organisations in other settings [6]. As a result of this study, the NIHR
Oxford BRC has committed to set annual objectives concerning gender equality and monitor
progress based on the proposed GE markers in addition to the ongoing support and participa-
tion by university department in the Athena SWAN Charter. Moreover, the NIHR Oxford
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BRC has committed to support new research initiatives on equality, diversity and inclusion
[43].
Notwithstanding its strengths, the current study has limitations, which could be usefully
addressed in future research. One limitation is that our study is a single-centre study. Given
that all 20 NIHR BRCs are structurally similar, future research could establish collaborations
across NIHR BRCs to generate large data sets to monitor progress to gender equality on the
national level. Gender has been defined as social and cultural constructs associated with being
female or male [44]. Due to the relative low numbers we removed the category “self-identify”
from the final analysis. Furthermore, we did not collect demographic information to explore
intersectional connections between gender, race/ethnicity, and other minority identities.
Future research should explicitly take diverse gender identities and intersectional connections
with minority identities into account.
Finally, whilst this study did not examine research culture specifically, the importance of
the culture of academic medicine for women’s leadership and advancement has been acknowl-
edged in previous research [27,45]. Future studies should explore cultural issues more in-
depth through qualitative research.
Conclusions
The study has highlighted GE in the workforce is an important indicator for internationally
competitive organisations. The findings suggest a two-factor model of markers of achievement
for GE with “organisational” and “individual” dimensions. Implementation and sustainability
of gender equity requires commitment at senior leadership and organisational policy level.
The findings have important implications to inform prospective planning and monitoring
within the field of organisational policies and leadership policies to accelerate women’s
advancement and leadership within the NIHR Oxford BRC, other NIHR BRCs in the UK, and
possibly similar translational research organisations in other settings. Enhanced collaborations
across NIHR BRCs are suggested to generate large data sets to monitor progress to gender
equality at the national level.
Supporting information
S1 Appendix. Survey questionnaire.
(DOCX)
S2 Appendix.
(DOCX)
Acknowledgments
The authors wish to thank the participants for taking part in this study and completing the
survey.
Author Contributions
Conceptualization: Lorna R. Henderson, Syed Ghulam Sarwar Shah, Pavel V. Ovseiko, Vasi-
liki Kiparoglou.
Data curation: Lorna R. Henderson.
Formal analysis: Lorna R. Henderson, Syed Ghulam Sarwar Shah, Rinita Dam.
Funding acquisition: Pavel V. Ovseiko, Alastair M. Buchan, Vasiliki Kiparoglou.
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Methodology: Lorna R. Henderson, Syed Ghulam Sarwar Shah, Vasiliki Kiparoglou.
Project administration: Lorna R. Henderson, Syed Ghulam Sarwar Shah.
Software: Lorna R. Henderson, Syed Ghulam Sarwar Shah.
Supervision: Vasiliki Kiparoglou.
Validation: Lorna R. Henderson, Syed Ghulam Sarwar Shah.
Visualization: Syed Ghulam Sarwar Shah.
Writing – original draft: Lorna R. Henderson.
Writing – review & editing: Lorna R. Henderson, Syed Ghulam Sarwar Shah, Pavel V.
Ovseiko, Rinita Dam, Alastair M. Buchan, Helen McShane, Vasiliki Kiparoglou.
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