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FuY, etal. BMJ Open 2022;12:e058951. doi:10.1136/bmjopen-2021-058951
Open access
Tailoring lipid management interventions
to reduce inequalities in cardiovascular
disease risk management in primary care
for deprived communities in Northern
England: a mixed- methods intervention
development protocol
Yu Fu ,1,2 Eugene YH Tang,1 Sarah Sowden ,1 Julia L Newton,1,3
Paula Whitty2,4
To cite: FuY, TangEYH,
SowdenS, etal. Tailoring lipid
management interventions
to reduce inequalities in
cardiovascular disease
risk management in
primary care for deprived
communities in Northern
England: a mixed- methods
intervention development
protocol. BMJ Open
2022;12:e058951. doi:10.1136/
bmjopen-2021-058951
►Prepublication history and
additional supplemental material
for this paper are available
online. To view these les,
please visit the journal online
(http://dx.doi.org/10.1136/
bmjopen-2021-058951).
Received 03 November 2021
Accepted 13 June 2022
For numbered afliations see
end of article.
Correspondence to
Dr Yu Fu;
yu. fu@ newcastle. ac. uk
Protocol
© Author(s) (or their
employer(s)) 2022. Re- use
permitted under CC BY.
Published by BMJ.
ABSTRACT
Introduction Hyperlipidaemia contributes a signicant
proportion of modiable cardiovascular disease (CVD)
risk, which is a condition that disproportionally affects
disadvantaged socioeconomic communities, with death
rates in the most deprived areas being four times higher
than those in the least deprived. With the national CVD
Prevention programme being delivered to minimise
risk factors, no evidence is available on what has been
implemented in primary care for deprived populations.
This study describes the protocol for the development of a
tailored intervention aiming to optimise lipid management
in primary care settings to help reduce inequalities in CVD
risks and improve outcomes in deprived communities.
Methods and analysis A mixed- methods approach will
be employed consisting of four work packages: (1) rapid
review and logic model; (2) assessment and comparison
of CVD risk management for deprived with non- deprived
populations in Northern England to England overall; (3)
interviews with health professionals; and (4) intervention
development. A systematic search and narrative synthesis
will be undertaken to identify evidence- based interventions
and targeted outcomes in deprived areas. General
practice- level data will be assessed to establish the
prole of lipid management, compared with the regional
and national levels. Health professionals involved in the
organisation and delivery of routine lipid management to
deprived populations will be interviewed to understand the
implementation and delivery of current lipid management
and associated challenges. The prototype intervention
will be informed by the evidence generated from
workpackages 1–3, which will be reviewed and assessed
using the nominal group technique to reach consensus.
Training and skills development materials will also be
developed as needed.
Ethics and dissemination Ethics approval has been
obtained from the Faculty of Medical Sciences Research
Ethics Committee at Newcastle University, UK. Findings
will be disseminated to the participating sites, participants,
commissioners, and in peer- reviewed journals and
academic conferences.
INTRODUCTION
Hyperlipidaemia contributes a significant
proportion of modifiable cardiovascular
disease (CVD) risk, which is the leading cause
of mortality and morbidity in England and
Europe,1 2 accounting for a third of deaths
in the UK. Hyperlipidaemia, a high level of
cholesterol or triglycerides in the blood, can
be inherited, is often found in people who
are overweight, have alcohol abuse or have an
unhealthy diet.3 Elevated levels of blood lipids
represent a major risk factor for the develop-
ment of coronary heart disease and other cere-
brovascular diseases including stroke, transient
ischaemic attack (TIA) and peripheral arterial
disease. People with a history of these events
are also at increased risk of experiencing subse-
quent CVDs. Management of CVDs also places
a significant economic burden on the National
Health Service (NHS), with an estimated cost
of £7.4 billion per annum.4
STRENGTHS AND LIMITATIONS OF THIS STUDY
⇒This study will develop a tailored lipid management
intervention for deprived populations to help reduce
health inequalities, using multiple methods.
⇒Multiple data sources will be used to assess and
compare cardiovascular disease risk management
for deprived with non- deprived populations in
Northern England to England overall.
⇒Primary care staff needs and challenges in deliver-
ing current lipid management and resources related
to implementation will be identied.
⇒Some limitations to the study design include exclu-
sion of non- English studies, publication bias, quali-
ty of data and selection bias in the rapid evidence
review.
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Both national and international guidelines recommend
the use of statins in people at risk of CVD.1 5 Their use
aims to reduce the synthesis of cholesterol, but evidence
suggests that there is an underuse of lipid- lowering drugs
among eligible patients.6 7 CVD is also a condition that
is strongly associated with health inequalities and dispro-
portionally affects disadvantaged socioeconomic commu-
nities. People in disadvantaged socioeconomic groups
experience a higher prevalence of CVD events but poorer
outcomes and premature mortality, leading to the fact
that people in the most deprived areas in England are
four times more likely to die prematurely than those in
the least deprived.8 In addition, those living in socioeco-
nomically disadvantaged neighbourhoods are found to
have poor engagement with preventive health services,
even though they are likely to benefit from screening
and early treatment.9 This may lead to an exacerbation
of existing health inequalities. The National Institute
for Health and Care Excellence (NICE) guidance has
recognised socioeconomic status as an additional factor
that contributes to CVD risk. The NHS Long Term Plan10
has also identified CVD as a clinical priority and stressed
the wider impact on health inequalities, highlighting
that heart disease- related mortality is the single largest
contributor to the life expectancy gap between the most
and least deprived. However, it failed to establish how
health inequalities could be approached or addressed
within local systems.
The North East of England is consistently ranked as
having the highest poverty levels and the lowest health
outcomes in England.11 Scotland has established a
programme to support general practices caring for the
most deprived communities (the ‘Deep End’ project)12
and, in early 2020, local General practitioners (GPs),
Public Health leaders and academics collaborated to form
a Deep End Steering Group for the North East and North
Cumbria (NENC). Funding was then granted from the
North East and North Cumbria Integrated Care System
(NENC ICS) Prevention strand to establish and codesign
a Deep End network for the region. The Deep End NENC
network consists of 35 practices; practices identified as
Deep End are those that fall into the 10% most deprived
practice populations in England. These practices have
between 95.7% and 57.7% of registered patients living in
the most deprived 15% of indices of multiple deprivation
data zones. Due to the high rates of long- term conditions,
unhealthy diets and physical inactivity, together with
other competing priorities,13 people in areas of depri-
vation are likely to face greater challenges in managing
CVDs. Ongoing effects from the pandemic are exacer-
bating these challenges and include difficulties attending
review appointments in person, digital poverty impeding
remote review, low levels of health literacy resulting in
misunderstandings about the need to continue long-
term treatments, and closure of other support services,14
potentially widening health inequalities.
The NHS has set up the national CVD Prevention
programme15 which aims to develop targeted interven-
tions to minimise risk factors by maximising diagnosis
and treatment, accompanied by the GP contract to
commission a new national CVD prevention audit for
primary care.16 However, no evidence is available on what
and how the intervention has been implemented and for
what health outcomes for deprived populations. There
is therefore an urgent need to seek a theoretical under-
pinning to tailor the national programme in this context,
which could support the CVD element of the NHS post-
COVID- 19 recovery plan with the region.
This study will examine the literature and practice-
level data and undertake engagement with staff who
provide primary care for deprived populations to define
the components and mechanisms through which lipid
management can be optimised to meet the identified
needs. The study aims to (1) synthesise the evidence on
interventions for deprived populations with CVDs or those
with high risks and understand the outcomes associated
with these interventions, (2) assess CVD risk management
for deprived populations in the NENC in comparison
with non- deprived populations in Northern England and
with England overall in order to identify clinical gaps and
needs, (3) investigate the implementation and delivery of
current interventions for patients with CVDs and those
with high risks, and (4) tailor and optimise the national
prevention programme to suit the context and needs of
deprived communities.
METHODS AND ANALYSIS
Study design
A mixed- methods approach will be employed to inform
the development of the intervention comprising a rapid
review, a population- based observational study and quali-
tative interviews. Four work packages (WPs) are proposed
(figure 1).
A project advisory group consisting of 6–8 members will
be established to involve key opinion leaders across core
fields, who will advise at each project stage, review inter-
vention components for the consensus process and help
disseminate the study outputs. Members will recruit from
the Deep End network, ICS Prevention Board, Academic
Health Science Network (AHSN) NENC lipid steering
group, regional professional leads for lipid management,
public members and academics with methodology exper-
tise. This group will meet quarterly with the research
team to oversee the execution of the study and provide
advice and assistance.
Figure 1 Study design and related WPs. WPs, work
packages.
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Patient and public involvement
Patients’ experiences are central to the research question
and outcomes, although the focus of this project is on
clinicians’ experiences. The Deep End Steering group,
consisting of local GPs, representatives from the North
East Commissioning Support Unit (NECS), Newcastle
University Medical School, Health Education England
North East and the Postgraduate School of Primary Care,
Directors of Public Health, NHS England, the Northern
Cancer Alliance and local voluntary, community and
social enterprise organisations, was consulted in order
to shape the research focus and question, methods of
data collection and dissemination. While the focus of the
research is initially on clinicians’ experience, the devel-
opment of a patient and public involvement strategy was
recognised in the consultation as an urgent requirement,
and this is currently being developed. The results of this
study will be widely shared via the Public Involvement
and Community Engagement network for the National
Institute for Health Research (NIHR) Applied Research
Collaboration NENC.
WP1: rapid review and logic model (months 1–3)
WP 1 will be a rapid review and synthesis of current
evidence, aiming to identify evidence- based interventions
for lipid management in deprived areas and targeted
outcomes. The review will be conducted following
Cochrane guidance on rapid reviews.17 A logic model will
be developed, informed by existing literature to describe
how lipid management works in theory to benefit services
and patients.
Type of studies
Empirical studies (ie, original data collection) describing
the setting, problem addressed, resource requirements,
aim, intervention components, provider, method of
delivery and objective and subjective outcomes will be
included if conducted in an Organisation for Economic
Co- operation and Development (OECD) country18 (to
ensure a degree of commonality in health system and
socioeconomic and demographic context), published in
peer- reviewed scientific journals, within the last 10 years
(to mirror the NHS long- term plan) and in the English
language.
Type of participants
Studies that focus on people with disadvantaged socioeco-
nomic status (education, income, occupation, social class,
deprivation, poverty or an area- based proxy for depriva-
tion derived from place of residence) will be included.
Adults with CVD including angina, previous myocardial
infarction, revascularisation, stroke or TIA or symptom-
atic peripheral arterial disease, and those who do not have
established CVD but are identified as having a high risk
of developing CVDs1 considering age, ethnicity, socioeco-
nomic status, body mass index, history of taking antihyper-
tensive or lipid modification therapy, Cardiovascular Risk
Score (QRISK) ≥10%, diabetes, nephropathy, familial
hypercholesterolaemia or other inherited disorder of
lipid metabolism, and other underlying medical condi-
tions or treatment including people treated for HIV, with
serious mental health problems, taking medicines that
can cause dyslipidaemia or with autoimmune disorders.
Type of interventions
Multifaceted interventions delivered to deprived popula-
tions that aim to optimise care by maximising diagnosis
and/or treatment to minimise individual risk factors will
be considered.
Type of outcome measures
Studies with individual, area- based or both types of
measures of socioeconomic deprivation will be included.
This may be measured according to several characteris-
tics including income, employment, education, disability,
crime, housing and services and living environment
deprivation. Because there is no universal recommen-
dation for core outcome sets in studies on CVD preven-
tion,19–21 studies will be eligible for inclusion regardless
of outcomes measured or reported for health outcomes,
this may include vascular- related outcomes, cognitive and
functional outcomes, lifestyle, medical risk factors, cardi-
oprotective medications and patient- reported outcome
measures. Any measures of professionals’, patients’ and/
or families’ knowledge, attitudes or satisfaction will also
be included.
Study identication
Cochrane CENTRAL, MEDLINE, PsycInfo, CINAHL will
be searched for eligible studies. Detailed search strategies
will be developed for each database. A preliminary search
strategy developed for MEDLINE is designed by YF and
validated by an information specialist (online supple-
mental material 1). This search strategy was piloted in
MEDLINE on 16 October 2021.
Study selection
Identified citations will be exported to Endnote X922 for
deduplication and screening. A random selection (10%)
of study titles and abstracts will be screened independently
by another researcher. Full text will be retrieved where
citations appeared to meet the eligibility criteria or where
a decision to exclude will not be made on the information
provided. Any discrepancies will be resolved by discussion
with a third researcher.
Data extraction
Data will be extracted on author’s first name, publication
date, location (country in which the study was under-
taken), study design, sample size, intervention details,
control/comparison groups (if any), outcome measures
and results, using a data extraction sheet that will be piloted
on two retrieved study reports. Accuracy and consistency
will be monitored through random double extraction of
10% included studies by an independent researcher. Any
discrepancies will be resolved by discussion with a third
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researcher. Where a study appears to have multiple cita-
tions, original authors will be contacted for clarification.
All information from multiple citations will be used if no
replies received.
Quality assessment
Quality appraisal of included studies will be performed
using standardised tools adapted for purpose. Appro-
priate Critical Appraisal Skills Programme tool will be used
according to the study design, a random sample (10%)
will be independently assessed by another researcher. Any
discrepancies will be resolved by discussion with a third
researcher.
Data synthesis
A narrative synthesis will be undertaken following Popay
et al’s23 approach to conducting synthesis systemati-
cally and transparently. It will focus on the intervention
components, effects of the interventions and mecha-
nisms leading to the outcomes. Studies, interventions
and outcomes will be examined and grouped according
to the aim and components of the interventions. The
variation on different characteristics of health systems
will be taken into account when interpreting the inter-
vention across OECD countries. A logic model will be
produced to present context, intervention components
and outcomes. Possible unintended adverse outcomes
will also be provided.
WP2: assessment and comparison of CVD risk management
for deprived with non-deprived populations to England overall
(months 2–4)
WP2 will be a population- based observational study
comparing retrospective data from practices in deprived
communities in the NENC, practices in regional non-
deprived communities and national practice- level data
obtained from publicly accessible datasets and anony-
mised data requested from the NECS that securely house
primary and secondary care datasets.
Data sources
The primary data source for this study will be the GP
Practice Profiles24 via Fingertips, a publicly accessible web
tool containing national general practice profiles gener-
ated for all Quality and Outcomes Framework (QOF)25
2019/2020 with a list size of at least 750 patients. Avail-
able practice- level data include local demography, QOF
domains and patient satisfaction. Other data sources used
include the QOF, OpenPerscribing26 and data requested
from the NECS via Secondary Uses Services (SUS)27 data
(table 1).
Table 1 Data sources and variables
Data source Description Level of data available Variables and variable description
GP Practice
Proles
Date reported by GPs to the
NHS that refers to all patients
in a practice
►Individual practice ►Practice size
►Mean practice age
►Deprivation score
►Age groups
►Percentage of patients positive experiences as
‘good’
►Percentage of practice access rated by patients
as ‘good’
►Percentage with a long- term condition
►Education status
►Working status
►Life expectancy by sex
QOF An indication of the overall
achievement of a practice
through a points system,
concerning clinical, public
health, public health—
additional services, and
quality improvement. It also
has cardiovascular group
data.
►Individual practice ►QOF score
►Total on the AF register, prevalence
►Total on the CVD- primary prevention (CVD- PP)
register, prevalence
►Total on the CHD register, prevalence
►Total on the HF register, prevalence
►Total on the LVSD register, prevalence
►Total on the HYP register, prevalence
►Total on the PAD register, prevalence
►Total on the STIA register, prevalence
Open Prescribing Imports national prescribing
data published by NHS
Business Services Authority
►Individual practice
►CCG level
►Total statin
►Total low and medium intensity statin
AF, atrial brillation; CCG, Clinical commissioning group; CHD, coronary heart disease; CVD, cardiovascular disease; HF, heart failure; HYP,
hypertension; LVSD, left ventricular systolic dysfunction; NHS, National Health Service; PAD, peripheral arterial disease; QOF, Quality and
Outcomes Framework; STIA, stroke and transient ischaemic attack.
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Study population
The study population are patients aged 16 and above
who have registered with the 34 Deep End practices in
the NENC and have been diagnosed with any form of
CVDs recorded on the QOF from 2019 to 2020. The study
comparators are the patients registered in non- Deep
End practices in the region and all registered patients
in England where data are available. Data are aggre-
gated to the GP practice level in which variables will be
summarised if they are at the patient level.
Data analysis
Descriptive analysis will be used to provide a quick and
low cost approach to assess CVD risk management and
give descriptive statistics or investigate relationships
between factors. GP practice code will be used to link data
across all datasets. Due to the nature of the aggregated
data available from the public sources used (Fingertips24
and QOF), it will be not possible to control any of the
comparisons for age, gender, deprivation or ethnicity.
Descriptive statistics, using means, SD and range, will be
used to compare the practice profile of the 34 Deep End
practices with non- Deep End in the region and England
average level. The prevalence of risk factors and statin
prescribing will be analysed with an appropriate statistical
test (ie, two- sample t- test, single sample t- test and paired
t- test), which will yield p values that indicate the statistical
significance of any differences between Deep End, non-
Deep End and England level. A paired t- test will be used
to understand whether there was a difference in outcomes
before and at the time of the COVID- 19 pandemic. CIs
for differences in means, medians or percentages will be
calculated. All significance tests will be performed at the
5% level. Stata V.16 will be used to facilitate data analysis.
WP3: interviews with health professionals (months 3–8)
WP3 will be qualitative interviews with staff involved in
the organisation and delivery of routine lipid manage-
ment in practices that are part of the Deep End Network.
The aim of the interviews will be to understand the imple-
mentation and delivery of current lipid management and
identify their needs and challenges.
Participants and recruitment
All health professionals involved in the management of
CVDs in the practice are eligible to take part including
GPs, pharmacists, assistant practitioners, practice nurses
and social prescribers.
Study recruitment will be supported by the Deep End
practice Network, who will send an email containing brief
study information to healthcare professionals working in
participating practices. Health professionals can express
their interests by responding to the email straight to the
research team. A reminder will be sent to those who have
not responded in 2 weeks. Maximum variation sampling
will be used to ensure a broad representation of health
professionals on dimensions including job titles/roles,
grade, specialty, length of working and demographics.
Reasons given by practices for declining to participate will
be recorded to inform feasibility assessment to further
studies.
Data collection
With participants' informed written consent, semistruc-
tured interviews will be conducted via telephone or online
(ie, Zoom or MS Teams) for up to 60 mins. A topic guide
was drafted to address the research questions and piloted
with two primary care health professionals to ensure
the questions prepared are relevant for the context
and acceptable. Questions considered important but
not originally included were also sought from the pilot
interviews, and the topic guide was amended accordingly
(online supplemental material 2). As interviews continue,
the topic guide will also allow a deeper exploration of
emerging themes and participants’ feedback, while main-
taining a consistent core of questions. Data collection will
end when data saturation is reached indicating no new
information is discovered.
Data analysis
Interviews will be digitally recorded (with consent),
transcribed and data managed using NVivo V.12, a
qualitative software programme to assist with the
organisation and coding of data. Data will be analysed
using Framework Analysis, which provides a system-
atic approach to sifting, charting and sorting material
using the key themes and issues. Initial line- by- line
coding will be undertaken. The connections and rela-
tionships of these codes will be explored, contrib-
uting to the development of themes. An analytical
framework will have been developed as the coding
process progresses and themes emerge. Codes and
themes from each transcript will be compared and
integrated using the constant comparison process,
enabling continuous updates on the interview topic
guide and the thorough interpretation of the study
data. To ensure trustworthiness and rigour of the
analysis, the coding framework will be developed and
assured by double coding of a random sample of tran-
scripts (10%) as a validity check and exploring alter-
native interpretations of the data.
WP4: intervention development (months 7–9)
WP4 will develop the prototype of the intervention in
collaboration with the Academic Health Science Network
NENC which delivers the CVD Prevention programme,
part of which includes a national programme mandated
by NHS England and NHS Improvement.
Guided by the Medical Research Council Framework
for developing and evaluating complex interventions,28
the development of intervention will be informed by inte-
grating the outcomes of the literature evidence, current
CVD management profile and stakeholder engagement
undertaken in WPs1–3, in an iterative and progressive
approach. The national programme and its key compo-
nents will be examined against the gaps, needs and
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challenges identified to consider the wider context. The
prototype intervention will be designed taking account of
health professionals’ existing commitments in these prac-
tices and challenging working environments. Training
and skills development materials for health professionals
will also be developed to facilitate them in delivering the
tailored intervention. The logic model produced in WP1
will be refined to map key intervention processes and
outcomes.
Design
The prototype intervention will be reviewed and assessed
by the project advisory group, guided by a nominal group
technique, a consensus method that allows for the gener-
ation of views and thoughts from group participants while
maintaining anonymity throughout.29
Data collection
The group will be provided with details of the interven-
tions and refined logic model, to seek further comments
and explore if the intervention is feasible, acceptable and
implementable in the context. The APEASE criteria30
will be used to determine the acceptability, practicability,
effectiveness, affordability, side effects and equity aspects
of the intervention. The nominal group technique will
involve two main sections:
1. The group will be asked to provide their comments on
the intervention, training materials and logic model.
All comments will be collated and grouped into main
themes for each member to rate their top 10 priorities
of the comments. Group ratings will be summated, and
the group’s collective top 10 priorities will be present-
ed to the group and discussed.
2. Each will rerate the group’s top 10 priorities and pro-
vide a weighting for their top 10 comments in the scale
ranging from 1=least important to 100=most import-
ant. These weightings will be summated after the meet-
ing, which will be used to refine the intervention and
the logic model. The refined version will be sent out
to each member for further comments. It is expected
that this process will be repeated twice until a census
is reached.
Data analysis
The initial listing of comments, clarification and
discussion of comments in section 1 of the nominal
group technique (listed above) will be analysed
thematically, with further discussion with the research
team. The scale data generated in section 2 of the
nominal group technique will be averaged so that the
comments can be reordered according to weighted
ranked priority. The individual/group rankings
produced in sections 1 and 2 will be compared to esti-
mate the level of agreement between the sections and
to observe the process of reaching consensus. First,
these comparisons will be made by calculating the
percentage agreement between the sections, in terms
of the comments that appear in the top 10 priorities
each time. Second, the movement in ranking between
sections 1 and 2 will be estimated using Cohen’s kappa
statistic of chance- corrected agreement.31 A kappa
value of >0.40 is considered to represent a moderate
level of agreement.32
ETHICS AND DISSEMINATION
Ethics approval has been sought from the Faculty
of Medical Sciences Research Ethics Committee at
Newcastle University (reference no.: 2209/14251) UK, a
letter of support has also been issued by the NENC Deep
End Network.
Dissemination will be led by the research team and
supported by the project advisory group. Reports will
be produced and shared with the NENC ICS Prevention
Board, Inequalities Board, Deep End network, National
Institute for Health Research (NIHR) Applied Research
Collaboration (ARC) NENC and AHSN NENC. The find-
ings will be disseminated to the participating sites, partic-
ipants, commissioners and in peer- reviewed journals and
academic conferences.
Author afliations
1Faculty of Medical Sciences, Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, UK
2NIHR Applied Research Collaborative North East and North Cumbria, Cumbria,
Northumberland and Tyne and Wear NHS Foundation Trust, Newcastle upto Tyne, UK
3Academic Health Science Network for the North East and North Cumbria,
Newcastle upon Tyne, UK
4North East Quality Observatory Service, Cumbria Northumberland Tyne and Wear
NHS Foundation Trust, Newcastle upon Tyne, UK
Twitter Sarah Sowden @SarahLSowden
Acknowledgements We thank NENC Deep End Steering Group and NECSU for
their support in this study.
Contributors YF, JLN and PW conceived the study design. YF drafted and revised
the manuscript and obtained ethics approval. EYHT, SS, JLN and PW independently
reviewed and contributed to revising and approving the nal version.
Funding This project is supported by the National Institute of Health Research
(NIHR) [Applied Research Collaboration North East and North Cumbria
(NIHR200173)]. The views expressed are those of the author(s) and not necessarily
those of the NIHR or the Department of Health and Social Care. EYHT (National
Institute for Health Research (NIHR) Clinical Lecturer) is funded by the NIHR. The
views expressed in this publication are those of the author(s) and not necessarily
those of the NIHR, NHS or the UK Department of Health and Social Care.
Competing interests None declared.
Patient and public involvement Patients and/or the public were involved in the
design, or conduct, or reporting or dissemination plans of this research. Refer to the
Methods section for further details.
Patient consent for publication Not applicable.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has
not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been
peer- reviewed. Any opinions or recommendations discussed are solely those
of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and
responsibility arising from any reliance placed on the content. Where the content
includes any translated material, BMJ does not warrant the accuracy and reliability
of the translations (including but not limited to local regulations, clinical guidelines,
terminology, drug names and drug dosages), and is not responsible for any error
and/or omissions arising from translation and adaptation or otherwise.
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ORCID iDs
YuFu http://orcid.org/0000-0003-4972-0626
SarahSowden http://orcid.org/0000-0001-9359-3463
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