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Patterning in Patient Referral to and Uptake of a National Exercise Referral Scheme (NERS) in Wales From 2008 to 2017: A Data Linkage Study


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Exercise referral schemes have shown small but positive impacts in randomized controlled trials (RCTs). Less is known about the long-term reach of scaled up schemes following a RCT. A RCT of the National Exercise Referral Scheme (NERS) in Wales was completed in 2010, and the scheme scaled up across Wales. In this study, using a retrospective data linkage design, anonymized NERS data were linked to routine health records for referrals between 2008 and 2017. Rates of referral and uptake were modelled across years and a multilevel logistic regression model examined predictors of uptake. In total, 83,598 patients have been referred to the scheme and 67.31% of eligible patients took up NERS. Older adults and referrals for a musculoskeletal or level four condition were more likely to take up NERS. Males, mental health referrals, non-GP referrals and those in the most deprived groupings were less likely to take up NERS. Trends revealed an overall decrease over time in referrals and uptake rates among the most deprived grouping relative to those in the least deprived group. Findings indicate a widening of inequality in referral and uptake following positive RCT findings, both in terms of patient socioeconomic status and referrals for mental health.
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Int. J. Environ. Res. Public Health 2020, 17, 3942; doi:10.3390/ijerph17113942
Patterning in Patient Referral to and Uptake of a
National Exercise Referral Scheme (NERS) in Wales
From 2008 to 2017: A Data Linkage Study
Kelly Morgan
*, Muhammad Rahman
and Graham Moore
Centre for Development, Evaluation, Complexity and Implementation in Public Health Improvement
(DECIPHer), School of Social Sciences, Cardiff University, 1-3 Museum Place, Cardiff CF10 3BD, UK;
Swansea University Medical School, Swansea University, Swansea SA2 8PP, UK;
* Correspondence:; Tel.: +44-(0)-2920-870296
Received: 15 May 2020; Accepted: 30 May 2020; Published: 2 June 2020
Abstract: Exercise referral schemes have shown small but positive impacts in randomized
controlled trials (RCTs). Less is known about the long-term reach of scaled up schemes following a
RCT. A RCT of the National Exercise Referral Scheme (NERS) in Wales was completed in 2010, and
the scheme scaled up across Wales. In this study, using a retrospective data linkage design,
anonymized NERS data were linked to routine health records for referrals between 2008 and 2017.
Rates of referral and uptake were modelled across years and a multilevel logistic regression model
examined predictors of uptake. In total, 83,598 patients have been referred to the scheme and 67.31%
of eligible patients took up NERS. Older adults and referrals for a musculoskeletal or level four
condition were more likely to take up NERS. Males, mental health referrals, non-GP referrals and
those in the most deprived groupings were less likely to take up NERS. Trends revealed an overall
decrease over time in referrals and uptake rates among the most deprived grouping relative to those
in the least deprived group. Findings indicate a widening of inequality in referral and uptake
following positive RCT findings, both in terms of patient socioeconomic status and referrals for
mental health.
Keywords: physical activity; public health; intervention; exercise referral; primary care
1. Introduction
Globally it is estimated that 1.4 billion adults are insufficiently active, with one in four exercising
for less than 30 min five times a week [1]. Such levels of inactivity date back to the 1990s [2] and today
women and adults from high income countries are shown to be among the least active [1]. Inactivity
has been shown to increase the risk of developing diabetes, certain cancer types and heart disease,
and it is currently the fourth leading risk factor for mortality [3]. As such, increasing physical activity
at the population level, and amongst at-risk populations, is a global public health priority [4].
A wide range of universal approaches have been employed to increase physical activity levels,
both at the individual and population level. One such approach originating in the early 1990s and
continuing to increase in popularity is the use of an Exercise Referral Scheme (ERS) [5,6]. Essentially,
an ERS involves the referral of individuals deemed to be insufficiently inactive from a health
practitioner to a structured exercise programme which is led by a third party.
The number of existing ERS is thought to be in excess of 600 schemes in the UK. However,
evidence concerning their effectiveness remains mixed [7]. A recent review [8] including six
Randomised Controlled Trials (RCTs) noted positive impacts among patients referred for
cardiovascular or mental health reasons, yet a lack of evidence for musculoskeletal referrals. Weak
Int. J. Environ. Res. Public Health 2020, 17, 3942 2 of 16
evidence was found for ERS less than 12-weeks in duration and scheme uptake and adherence were
highlighted as inherent determinants of ERS success. Despite the basis of sound theory and well-
designed studies, evidence-based interventions are not being adopted widely or implemented with
sufficient quality and fidelity [9,10]. As such, it is recognised that RCTs are only the beginning of a
process which may lead to better public health outcomes [11]; ultimately an intervention, in this case
an ERS, needs to be adopted, implemented and sustained in order to have the greatest impact.
The number of individuals who are referred to any one scheme remains unknown, with studies
typically reporting on those patients who take up a scheme only. Understanding the volume of
patients referred to an ERS and, more so, the characteristics of those referred is essential in order to
begin to interpret the generalisability of findings to the wider population. These data would also
provide an insight into the accessibility or ERS, ascertaining whether schemes are being delivered
equitably as stipulated in the National Quality Assurance Framework for Exercise Referral [12]. Some
have highlighted the potential for ERS to have an inequitable impact [13,14], with resources being
allocated and misspent on individuals who are ’worried well’, that is individuals who would have
taken up exercise anyway. Furthermore, concerns surrounding the ability of leisure sectors to attract
and retain individuals who are most likely to benefit from an active lifestyle have also been raised
After a patient is referred to an ERS, the patient may or may not then take up the scheme. Scheme
uptake has commonly been defined as a patient attending an initial consultation; however, this
definition is variable and at times lacking throughout the existing literature. Historically, patient
uptake rates have been reported at around 65% [15–17], with individual study reports ranging
between 35% [18] to 85% [19] and higher rates apparent among RCTs, suggesting participants in RCTs
may exhibit higher scheme engagement than the population as a whole where an intervention is
delivered outside of a RCT context. In cases where participants in RCTs are not reflective of the
intended wider population, for example, with higher motivation levels or younger ages, the external
validity of a RCT to the wider population is threatened [20] and as such the effectiveness of an
intervention within the real-setting remains unknown. A review of reviews [21] recently noted that
no progress has been made in increasing the number of participants starting ERS over the years since
the emergence of ERS. As Glasgow et al. argue [22], for an intervention to achieve population health
benefits it needs to be both efficacious for those who participate and to achieve wide reach through
its target population, as well as being widely adopted, implemented and maintained by the systems
in which it is intended to be delivered. Moving forward, there is a need for thoughtful approaches to
clinical evidence generation, supplementing RCT evidence with data generated from observational
studies for a greater understanding of what happens beyond a trial or study setting. Understanding
factors associated with patient uptake can help inform decision making processes of scheme referrers
and deliverers to help optimise uptake rates across patient sub-groups. Review findings suggest that
women [17,23] and older aged adults [23] are more likely to uptake ERS yet some individual studies
have found no patterning by patient gender [24,25] or age [26,27]. Evidence surrounding uptake rates
and patient socioeconomic status is currently deemed insufficient to determine any conclusion [21].
One review suggests reason for referral as a predictor of scheme uptake [23], with those referred for
a specific medical condition more likely to uptake, while other reviews report less clear findings [21].
A recent qualitative study [28] offers some insight into factors which influence uptake decisions,
highlighting factors across the intrapersonal (past physical activity experience, motivation,
competing demands), interpersonal (support and scheme understanding) and organisational
(promotion, communication and cost) levels of the socioecological model. As portrayed above, the
current evidence base appears somewhat conflicting, which is a likely reflection of the adoption of
different uptake definitions and, even more so, the notable divergence in ERSs both within and across
countries [29]. Furthermore, to our knowledge, no study to date has reported detailed characteristics
of participants who are referred but later fail to take up an ERS.
Ascertaining ways in which scheme uptake can be maximised has been identified as a key
challenge for future research [8]. To address this challenge, there is a need to improve our
understanding of the characteristics of referred patients in addition to the factors which predict
Int. J. Environ. Res. Public Health 2020, 17, 3942 3 of 16
patient uptake. Such information is vital in order to inform the current use of ERSs across the world
and to help address the levels of physical inactivity. One avenue is to utilise existing data
infrastructures and capitalise on patient data which is routinely collected by an ERS, a
recommendation within the 2014 National Institute for Health and Care Excellence (NICE) guidelines
[29]. To date, only one database has been cited in the UK which contains longitudinal ERS data on
approximately 24,000 individuals across 19 schemes [30]. Given the fragmented ERS system across
the UK, however, this database reflects the sporadic nature of local schemes and as such the
heterogeneity in scheme design skews early findings.
In Wales, UK, the National Exercise Referral Scheme (NERS) offers a unique opportunity to
harness readily available patient-level data to facilitate evaluative methods and inform evidence-
based policymaking. NERS is a standardised, evidence-based ERS which continues to be delivered
across all regions of Wales following positive findings from a RCT conducted from 2007–2010 [19].
Since its inception in 2007, the scheme has continued to collate data at the local level, gathering data
on each patient referred to the scheme. Specifically, data are collated from the point of scheme referral
through to a 12-month post-scheme follow-up. Given the growing international infrastructure
dedicated to facilitating data linkage [31] and the high level of granularity in data collected by NERS
over the years, this dataset has the potential to considerably influence policy and enhance our
understanding of patient journeys across an ERS, and to understand what happens with regards to
scheme participation once an intervention moves beyond the confines of a RCT and into every day
practice. Importantly, in the trial of NERS, improved outcomes were observed only among patients
who engaged fully with the intervention, with uptake and completion of the scheme offering useful
though imprecise proxies for effectiveness. If scheme engagement has increased since the trial, this
perhaps provides some indirect evidence that its population level impacts are likely greater than
suggested by the RCT. Conversely, if engagement has declined in routine practice, effectiveness is
also under threat.
The present study will utilise the National Exercise Referral scheme (NERS) as a case study for
addressing the above needs. Specifically, for all patients referred to NERS via a generic pathway, this
study aims to perform record linkage between NERS data and routine health records, model rates of
patient referral between 2008 and 2017 and understand factors associated with scheme uptake.
2. Materials and Methods
2.1. Setting and Participants
The NERS intervention is delivered by all of the 22 local authorities in Wales, in a variety of
settings including council owned leisure centers and private gyms. For referral, patients must be aged
16 years or above, be sedentary (not moderately active for 3 times per week/deconditioned through
age or inactivity), and have at least one of the following: raised blood pressure over 140/90, Body
Mass Index (BMI) over 28, cholesterol over 5.0, controlled diabetes or impaired glucose intolerance,
family history of heart disease or diabetes, at risk of osteoporosis or musculoskeletal pain, mild
arthritis or poor mobility, mild-moderate COPD (Chronic obstructive pulmonary disease), mild
anxiety or depression, multiple sclerosis. All patients referred via the generic pathway to the NERS
intervention between 13 February 2008 to 31 December 2017 were eligible to be included in this study.
2.2. NERS Intervention
The NERS intervention has been described previously in detail [19]. Briefly, the scheme involves
the referral of a patient to an exercise professional and a subsequent 16-week programme of
subsidized, supervised group-based activity. Patients are predominantly referred via a General
Practitioner (GP) or physiotherapist. During the programme there is an initial consultation and a
follow-up contact at 4-weeks, 16-weeks and at 12-months, with all data recorded on a national
database by each local area. Following completion of the programme, patients are signposted to
alternative physical opportunities (i.e. ‘exit routes’), which typically remain within the leisure setting.
Int. J. Environ. Res. Public Health 2020, 17, 3942 4 of 16
2.3. Study Data
For each patient referred to NERS, data are routinely collected and recorded within the NERS
national database, provided by scheme referrers and scheme deliverers. Data held within the NERS
National database have been anonymised and deposited into the Secure Anonymous Information
Linkage (SAIL) databank [31], a well-established health-informatics which houses a wide array of
health and non-health datasets. The anonymization process uses a split-file approach whereby the
demographic data and clinical data for each patient are separated by the data provider and sent to a
third party provider. The third party assigns a unique linkage field (ALF) to each patient which
allows the split files to be recombined while removing any identifiable data during the process [32].
For the purpose of the current study and wider research project, the NERS national database
was linked to the following datasets: Welsh Demographic Service (WDS), Primary Care Dataset
(GPD), Patient Episode Database Wales (PEDW), Outpatient dataset (OPD), and the Annual District
Death Extract (ADDE). That is, for each patient within the NERS national database, scheme data were
linked to the clinical records within each of the aforementioned datasets. Before analyses, the linked
database was checked for consistency and errors. Data relating specifically to the current study are
outlined as follows.
Patient age (scheme referral date minus date of birth) and gender (Male/Female/Unknown) were
extracted from the GPD. For each patient, a deprivation score was assigned at the Lower Super
Output Area (LSOA) using the 2014 Welsh Index of Multiple Deprivation (WIMD) [33]. WIMD 2014
comprises eight domains of social deprivation whereby each LSOA is ranked by an overall score and
categorised into quintiles. Quintile 1 represents the 20% most deprived LSOAs and quintile 5 the 20%
least deprived LSOAs. Further detail on the domains and score calculations is available elsewhere
Patient referral date, the occupation of the referring health professional and the reason for
patient referral were provided by the NERS national database. Referring health professionals (23
categories) were recoded as General Practitioner (GP; including practice nurse referrals),
physiotherapist or other. Reasons for referral (121 codes) were recoded as Coronary Heart Disease
(CHD) only, mental health only, CHD and mental health, musculoskeletal, and level four conditions.
Level four conditions signify patients deemed to be at ‘higher risk’ and who need to undertake
tailored exercise sessions as part of their rehabilitation following an NHS (National Health Service)
intervention or to manage a chronic condition and use physical activity as a means of secondary
Each local authority was categorised according to their involvement in the earlier RCT as trial
(1) or non-trial (0) area. An aggregated deprivation score was assigned to each local authority, based
on the percentage of LSOAs within each local authority which are ranked in the most deprived 50%
of LSOAs in Wales [33].
Within the present study, a referral indicated an action by a referring health professional while
uptake was defined as a patient attending a first consultation. Reasons for not taking up the scheme
were recorded within the NERS database (193 codes) which were recoded into 10 sub-categories:
intrinsic factors, scheme specifics, health-related, unknown, other commitments, exercising
elsewhere, work-related, transferred area/GP, bereavement, and accessibility.
2.4. Statistical Analysis
All quantitative statistical analyses were conducted in Stata v.16StataCorp. 2019. College
Station, TX: StataCorp LLC). Descriptive analyses were performed to describe participant
characteristics (i.e. age, gender and socioeconomic status) across the whole sample and each uptake
group. Rates of referral and scheme uptake were modelled over time, with accompanying confidence
intervals to reveal any increase or decrease in rates across years. To assess whether patient
socioeconomic levels have changed over time, interaction effects were examined between the year of
referral and LSOA quintile.
As data were hierarchical in nature and individuals nested within local authorities, a multilevel
modelling approach was adopted. Specifically, a multi-level mixed-effects logistic regression model
Int. J. Environ. Res. Public Health 2020, 17, 3942 5 of 16
was used to examine predictors of scheme uptake, comparing characteristics of patients who took up
the scheme (uptake) to those who did not (non-uptake). Individual-level predictors included age,
gender, socioeconomic status, referral reason, referring professional and year of referral. Area-level
predictors included trial area (yes or no) and area deprivation. ‘Uptake’ was set as the reference
category and odds ratios (ORs) were reported alongside 95% confidence intervals (95%CI) and
accompanying p values. Differences were considered statistically significant if the p value was <0.05.
2.5. Ethics
Ethical approval for this study was obtained from Cardiff University’s School of Social Sciences
Research Ethics committee (SREC/2163). This study was approved by the Health Information
Research Unit’s independent Information Governance Review Panel (project 0670).
3. Results
3.1. Data Linkage
The provision of identifiable data enabled 93.58% (n = 168,977) of patient records to be
successfully anonymised. Of these, 78.61% (n = 141,955) were deterministically linked. For 8668
records (containing 2 duplicate records) within the NERS database, data linkage was not possible.
After the removal of duplicate patient linkages, 143,170 patients remained. Next, duplicate records
within the NERS national database (N = 19) and patients who had been referred on more than one
occasion (N = 9849) were discounted, creating a final dataset of 83,598 patients. Figure 1 provides an
overview of the process in creating a linked dataset, whereby the final dataset does not contain any
duplicate patients.
Figure 1. Overview of data linkage process.
Int. J. Environ. Res. Public Health 2020, 17, 3942 6 of 16
3.2. Scheme Referral
Since 2007, a total of 83,598 patients with linked data have been referred to NERS via the generic
pathway on one occasion. Patients were aged between 9 and 99 years (mean 53, SD 16.6) and
predominantly women (61.6%). The age profile of women (52.33 years, SD 16.53, range 9–99 years)
and men (55.54 years, SD 16.65, range 12–97 years) was comparable. Table 1 shows the proportion of
referrals across deprivation quintiles and that the most common reason for referral was
musculoskeletal related (50.4%) and most common referrer a GP (57.8%). Similar proportions were
noted among NERS referrals where data linkage was not possible (67.24% GP referrals and 43.23%
musculoskeletal related referrals; Supplementary Table S1).
Table 1. Characteristics of all National Exercise Referral Scheme (NERS) referrals between 2008 and
2017 *.
Sex 83,487
Age (years)
LSOA quintile
5 (Least deprived)
1 (Most deprived)
Reason for referral
CHD only
Mental health only
Level 4
CHD and mental health
Referrer type
* does not include patients with repeat referrals.
Figure 2 displays overall referral rates across each year and presents patients referred as a
percentage of the overall inactive population in Wales (based on waves of the National Survey for
Wales [34]). The graph displays referrals between 2011 and 2017 only as preceding data did not
provide a true picture of the total referrals. In total 3.3% of the population have been referred to NERS
since 2011. As shown, the percentage of referred patients gradually increased with a peak during
2013 before decreasing to a steady plateau between 2014 to 2017. Figure 3 provides a breakdown of
referrals over the years according to socioeconomic grouping. Trends reveal an overall decrease in
referrals of patients from the most deprived grouping alongside an increase in referrals of those in
the least deprived group. Following the divergence in referral rates between these two groups over
time, comparable rates are shown in 2017.
Int. J. Environ. Res. Public Health 2020, 17, 3942 7 of 16
Figure 2. Generic pathway referrals shown as a percentage of the total inactive population in Wales
(N = 83,598 patients).
Figure 3. Generic pathway referrals according to socioeconomic groups between 2011 and 2017 (5 =
lowest deprivation, 1 = highest deprivation) (N = 76,628 patients).
3.3. Scheme Uptake
Patients on a waiting list (7487), under age 16 years (n = 48) or classified as an inappropriate
referral (n = 593) were removed from analyses. The sample comprised a total of 75,470 patients, of
which 61.65% were women and 60.44% were aged 59 years or younger (range 16–99 years). As shown
in Table 2, patient deprivation scores indicate that 40.70% of the population were in the top two
deprived quintiles. Over half of patients (57.96%) had been referred by a GP, with musculoskeletal
referrals recorded as the most common referral reason (50.53%). Mental health related referrals
accounted for approximately one fifth of all patients (20.72%).
2011 2012 2013 2014 2015 2016 2017
% of population referred
% of referrals % of inactive (33%)
2011 2012 2013 2014 2015 2016 2017
% of patients
5 4 3 2 1
Int. J. Environ. Res. Public Health 2020, 17, 3942 8 of 16
Table 2. Characteristics of patients according to scheme uptake (N = 75,470).
Did Not Take Up
28,873 38.26 19,229 (66.60) 9644 (33.40)
31,524 (67.75)
15,003 (32.25)
47 (67.14)
23 (32.86)
Age (years)
12,959 (56.06)
10,158 (43.94)
15,028 (66.81)
7466 (33.19)
22,813 (76.40)
7046 (23.60)
LSOA quintile
5 (Least deprived)
9129 (72.42)
3476 (27.58)
13,721 19.79 9594 (69.92) 4127 (30.08)
10,165 (68.79)
4611 (31.21)
9503 (65.21)
5070 (34.79)
1 (Most deprived)
8300 (60.85)
5341 (39.15)
Reason for referral
CHD only
10,699 (67.72)
5101 (32.28)
Mental health only
4677 (54.36)
3926 (45.64)
26,301 (68.99)
11,820 (31.01)
Level 4
5370 (77.95)
1519 (22.05)
CHD and mental health
3730 (61.87)
2299 (38.13)
Referrer type
29,449 (67.32)
14,293 (32.68)
16,170 (68.42)
7463 (31.58)
5181 (64.00)
2914 (36.00)
Year of referral ^
2171 (80.32)
532 (19.68)
7975 (67.50)
3839 (32.50)
10,438 (63.58)
5979 (36.42)
8086 (65.68)
4225 (34.32)
7349 (67.36)
3561 (32.64)
7206 (68.15)
3367 (31.85)
7122 (69.51)
3124 (30.49)
Trial area
29,486 (68.90)
13,310 (31.10)
21,314 (65.23)
11,360 (34.77)
^ Years 2008–2010 statistical disclosure with numbers reflecting magnitude.
In total, 50,800 (67.31%) patients took up the scheme with rates across each year displayed in
Figure 4A. As shown, rates of uptake were highest in 2010 (above 80%) and declining thereafter to
2013 (63.58%). A slight increase in rates is shown between 2013 and 2017 (69.51%). Figure 4B shows
uptakes rates according to a patient’s deprivation quintile. For patients within the least deprived
group (quintile 5), uptake rates have steadily increased since 2010. For those among the most
deprived groups (quintiles 1 and 2), a continual decrease in uptake rates was found since 2009, and
in 2017 the lowest uptake was among those in the most deprived quintile.
Int. J. Environ. Res. Public Health 2020, 17, 3942 9 of 16
Figure 4. (A) Percentage of generic pathway patients taking up NERS across 2009 to 2017 (95%CI) (N
= 75,470 patients). (B) Percentage of generic pathway patients up taking NERS across 2009 to 2017
according to deprivation quintile (5 = least deprivation, 1 = most deprived) (N = 69,316 patients).
Reasons for not taking up the scheme were unknown for the majority of patients (83.51%) while
health-related (3.84%), other commitments (3.32%) and exercising elsewhere (3.36%) were the next
commonly recorded reasons.
3.4. Predictors of Scheme Uptake
Results from multilevel logistic regression analyses (Table 3) revealed that patients taking up
the scheme were more likely to be older (aged 45–59: OR 1.50: 95%CI:1.44–1.56; aged 60 plus: OR 2.37:
95%CI:2.27–2.47) or referred for a musculoskeletal (OR 1.15: 95%CI:1.09–1.20) or level four condition
(OR 1.90: 95%CI:1.76–2.05) in comparison to patients not taking up the scheme. Contrastingly,
2009 2010 2011 2012 2013 2014 2015 2016 2017
% of patients
Upper CI % Lower CI
2009 2010 2011 2012 2013 2014 2015 2016 2017
5 4 3 2 1
Int. J. Environ. Res. Public Health 2020, 17, 3942 10 of 16
patients who were male (OR 0.90: 95%CI:0.87–0.94), referred for mental health only (OR 0.79:
95%CI:0.74–0.84) or referred by a physiotherapist (OR 0.88: 95%CI:0.85–0.92) or a professional outside
of a GP surgery (OR 0.84: 95%CI:0.80–0.89) were found to be less likely to take up the scheme. No
area level variables were found to be associated with patient scheme uptake. As shown, a downward
linear trend was observed between deprivation quintile and uptake, with patients less likely to
uptake the scheme as the deprivation level increased.
Table 3. Multilevel logistic regression outputs of correlates to scheme uptake (N = 69,291).
Characteristic OR p
95% Confidence Interval
Gender (Female)
Age (16–44 years)
Deprivation quintile (5-least deprived)
1 (most deprived)
Reason for referral (CHD only)
Mental health only
Level 4
CHD and mental health
Referrer (GP)
Referral year (2017)
2009 3.15 0.006 1.39 7.14
Trial area (Yes)
Area deprivation
ICC—constant only
ICC—level 1 variables
ICC—level 1 & 2 variables
Bold values signify significant findings p < 0.05.
4. Discussion
This study has performed the most comprehensive assessment yet of referrals to and uptake of
an ERS. In doing so, this is the first study to create an electronic cohort of ERS patients, whereby
routinely collected ERS data have been linked to routine healthcare records. As such, data are now
available for wider research in an anonymized format and patients referred to NERS can be both
retrospectively and prospectively followed up within the SAIL databank.
Between 2008 and 2017, over 83,500 patients have been referred to NERS via the generic referral
pathway and since linked to routine data. Not taking into account those with existing comorbidities,
this suggests that approximately 3.3% of the ‘at risk’ inactive population [34] have been referred over
the 10-year period. Over this time, we observed a peak in referrals during 2013 which would reflect
Int. J. Environ. Res. Public Health 2020, 17, 3942 11 of 16
a time point at which NERS fully operated in all 22 local authorities in Wales. Thereafter, we found a
decline in referrals followed by a plateau in numbers in recent years. One possible explanation for
this observation relates to the expansion of NERS since the earlier RCT. Given the evidence-base for
generic referrals [19] and increasing demand from wider healthcare professionals, trial areas began
to increase the number of referral pathways available, with up to 13 currently running in some areas.
As such, the expansion of alternate referral pathways, alongside no increase in funding or capacity
for delivery, is a likely explanation for a drop in the number of generic referrals.
Of those referred to NERS, over two thirds of patients have taken up the scheme, which is
somewhat significantly lower than the earlier RCT [19] (at 85%) yet it is reflective of other ERS uptake
rates [15–17]. This finding enhances our understanding of what happens beyond a trial, denoting ERS
uptake rates in the real-world setting. This perhaps indicates that no matter how pragmatic, RCTs
represent a particular context in which to implement an intervention, which may not be wholly
reflective of real world practice, and hence there is a need for careful monitoring in real world practice
beyond a RCT [35]. Effects of NERS for those patients who took it up might have been similar to those
observed in the trial but declines in uptake perhaps indicate that average effects per referred patient
are likely to have slightly reduced.
In contrast to our observed pattern of referral rates, uptakes rate showed a decline from 2010 to
2013, but a plateauing or marginal steady increase since. The initial spike of uptake rates in 2011 could
reflect uptake among a group of highly motivated individuals following the immediate period after
the RCT. Earlier interviews indicated that some GPs were hesitant to refer patients until
randomisation was removed [36], while the scheme was likely eagerly awaited in areas joining after
the trial, leading to high initial demand. While reviewing reviews, Shore et al., [21] recently noted
that no progress has been made in increasing the number of participants starting a scheme over the
years. As ours is the first study to model national trends within the same ERS, the stable rate of uptake
over the past five years is somewhat encouraging, portraying the continued demand ten years on
from scheme inception. Similar to other studies, we noted that older adults [23] and women [17,23]
were more likely to take up the scheme, while patients referred via a physiotherapist or alternate
health professional were found to be less likely to take up the scheme compared to GP referrals. Given
the important role that health professionals play in facilitating change in physical activity [37], the
latter finding provides insight into the varying roles and influences referrers may have. Previous
studies have shown significant individual inter-clinician variability on how physical activity is
prescribed among patient groups [38], while Yarborough and colleagues noted key clinician traits for
helping patients with mental illnesses initiate and maintain lifestyle changes [39]. Findings may also
reflect patient characteristics, with those from highly-educated or highly-motivated groups seeking
a referral via a GP [40]. Wider literature has indicated that the type of referring professional may be
important for patient adherence to ERS [41].
Several studies [42–44], including the earlier RCT [19], have shown the positive impacts of ERS
for individuals suffering from anxiety and depression, with improved mental health outcomes post-
scheme completion. Moreover, above and beyond the ERS literature, exercise is recommended as an
evidence-based treatment for depression, the first and only mental health disorder whereby exercise
is recommended in clinical guidelines [45]. In the present study, however, we found that patients
referred for a mental health reason were substantially less likely to take up the scheme compared to
those with a CHD referral. This finding reflects earlier reports from two other UK-based studies
[40,46]. With one in six individuals suffering from a mental health disorder [47] and approximately
two-thirds of individuals with a known mental illness not seeking help from a health professional
[48], major depressive disorder is predicted to become the leading cause of disability in the world by
2030 [49]. Of all referrals to NERS, approximately 11% were dedicated to mental health and of these,
just over half of patients took up the scheme, representing a large decline in uptake among this group
compared to levels observed in the trial period. It is therefore important for future work to
understand the reasons underpinning the observed findings and, more so, vital to identify potential
facilitators to improve referral rates and uptake among this sub-group.
Int. J. Environ. Res. Public Health 2020, 17, 3942 12 of 16
Historically, an objective of local ERSs has been to improve health inequalities [40]. Findings of
the present study showed that patients are being referred across the full spectrum of socioeconomic
circumstances, a finding which is consistent with the earlier RCT. As most chronic conditions and
physical activity levels are patterned by socioeconomic status [50], the need for ERS will be greater
among those in deprived groups compared to more affluent peers. That said, we noted a clear
downward trend for the referral of patients in the most deprived groupings over time, coupled with
a marked pattern of disparity in uptake rates, with patients in the most deprived groups least likely
to take up the scheme. Of note, the rapid decline in uptake rates among the most deprived groups
coincides with a change to the scheme pricing. In 2011, following the RCT, the scheme saw an increase
in cost from £1.00 to £1.50 per session. Thereafter, between 2013 and 2014 local authorities were
informed that scheme prices could be determined locally before once again becoming standardized
across all areas at £2 per session in 2014. Trends observed over the years are indicative of a growing
inequality—as uptake rates of the most affluent groups are continuing to increase, uptake rates of the
most deprived groups are continuing to decrease. Our observations are supportive of the inverse care
law, whereby patients considered most likely in need of health care are the least likely to receive the
care [51]. While the trial reported no difference in effects by socioeconomic status, these data suggest
that in the period following the trial, it is likely that the intervention has become increasingly
inequality generating. Implicating factors could involve the length of waiting lists in areas and also
factors at the referral level. Drawing comparisons between health services within deprived and
affluent communities, studies have noted shorter GP appointment times [52] and fewer GP staff in
deprived areas [53]. Only one other study has reported on scheme uptake according to patient
deprivation status. Harrison et al., [24] found that patients who were more deprived and suffered
from a respiratory diagnosis were more likely to take up ERS compared to more affluent patients
with the same diagnoses. Further research is needed to understand the reasons underpinning the
observed patterning of referrals and uptake so that NERS can ensure that future services are
continued to be equitably available and accessible.
The totality of evidence presented in the current study can be used as a guide for both scheme
referrers and deliverers in identifying the best referral approaches across patient sub-groups. It could
be argued that different approaches need to be adopted according to patient characteristics and
current referral methods and follow-on processes need to be reviewed. A key strength of this study
is the population approach, involving over 85,000 patients and data spanning a ten-year period. This
is also the first study to examine an ERS following a RCT and national scale-up, therefore findings
are reflective of an established scheme. Our measures of socioeconomic status incorporated both
individual- and area-level data, reducing the likelihood of encountering the problem of ecological
fallacy [54]. That said, our study lacks data on patient ethnicity, levels of physical activity and cases
where patients have requested a referral (i.e. ‘self-referral’). Such information would have provided
a greater insight into sub-groups and our observed trends. While we noted that 3.3% of patients
reported alternate exercise as a reason for not taking up the scheme, poor data capture prevents us
from analyzing this data further. In addition, the coding criteria used by health professionals to define
a referral health condition limits the ability to study differing degrees of health conditions (for
example, whether mild anxiety and/or depression).
As Wales is faced with the largest aging population of all UK nations [55] and levels of inactivity
persist, research into NERS continues to be as important as ever. The projected rise in the number of
over 70s in the coming years [56] is likely to place considerable pressure on the scheme and wider
public services. Future research will continue to follow each patient along the NERS journey, to
examine rates of scheme completion and patient drop-out, along with associated characteristics.
Analyses are currently underway to uncover any longer-term impacts of the scheme on patient health
outcomes and qualitative work is set to provide invaluable insight into the current findings.
5. Conclusions
The creation of an e-cohort allows us to maximize opportunities to conduct longitudinal research
and uncover any longer-term effects of participation in NERS. That said, our findings raise questions
Int. J. Environ. Res. Public Health 2020, 17, 3942 13 of 16
about the equity of NERS with diverging trends among referrals and uptake rates of socioeconomic
groups. Having uncovered different patterns of uptake according to patient sub-groups, findings can
be used by scheme referrers and deliverers to inform future processes.
Supplementary Materials: The following are available online at, Table
S1: Records of NERS referrals with no data linkage (N = 8666).
Author Contributions: Conceptualization, K.M.; methodology, K.M and G.M.; software, M.R.; formal analysis,
K.M.; data curation, K.M and M.R.; writing—original draft preparation, K.M.; writing—review and editing, K.M
and G.M.; funding acquisition, K.M. All authors have read and agreed to the published version of the
Funding: This work was funded by a Health and Care Research Wales Health Fellowship Award [grant number
HF-16-1164 to K.M.]. The Centre for Development, Evaluation, Complexity and Implementation in Public Health
Improvement (DECIPHer) is funded by Welsh Government through Health and Care Research Wales. This work
was supported also by the Public Health Division, Welsh Government with the support of The Centre for the
Development and Evaluation of Complex Interventions for Public Health Improvement (DECIPHer), a UKCRC
Public Health Research Centre of Excellence. Joint funding [grant number MR/KO232331/1] from the British
Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the
Welsh Government, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is
gratefully acknowledged.
Acknowledgments: The authors would like to thank the National Exercise Referral Scheme (NERS) delivery
team for their support during this study and Welsh Local Government Association for their assistance with data
curation. We would also like to thank Dan Thayer and Daniel Mallory for their assistance with acquiring WIMD
data. We are thankful for the invaluable input and guidance from our Public Involvement Community, Karen
Shepherd and Alan Meudell.
Conflicts of Interest: G.M. was part of the team who undertook the earlier RCT of the National Exercise Referral
Scheme in Wales. Other authors declare no conflict of interest. The funders had no role in the design of the study;
in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish
the results.
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... Low vision rehabilitation officers were also included as it is expected that people with visual impairment are contacted by vision rehabilitation services within two days of being certified as sight impaired or severely sight impaired, thus all people with significant include PA advice and support [28]. Participants were also asked if they would follow advice from a GP to examine if people would be more willing to follow PA advice from a GP than eyecare or sight loss service professionals, as previous studies have suggested people may be less willing to follow PA advice from professionals other than a GP [29]. ...
... Four adjusted logistic regression models were used to examine the association between age (continuous variable), gender, level of education, level of sight loss, PA levels, presence of [29,31]. In this study, level of education was used as a proxy measure of socioeconomic status. ...
... Of the participants who reported a history of depression or anxiety, 66.6% (n=30/45) reported that they would Our study also found that most people would increase their PA based on advice from more than one of the following: GPs, optometrists or ophthalmologist and low vision rehabilitation officers. A study which examined the uptake of exercise schemes among the general population in Wales reported that uptake is lower among people referred to the scheme by physiotherapists or 'other' health professionals, compared to when the referral was made by a GP [29]. However, to our knowledge, no studies have explored the effectiveness of referrals from eyecare or sight loss services to PA interventions. ...
Purpose (1) To identify if adults with uncorrectable sight loss would increase their physical activity (PA) following advice from general healthcare, eyecare or sight loss service professionals. (2) To identify what resources could be provided alongside advice from a professional to facilitate PA. Materials and methods Survey data from 100 UK adults with uncorrectable sight loss were analysed. Adjusted logistic regression models were used to examine the association between participant characteristics, and the likelihood that participants would increase PA if advised to by different professionals. Results Most of our sample would increase their PA if advised to by a general practitioner (GP) (n = 78), ophthalmologist or optometrist (n = 70) or a low vision rehabilitation officer (n = 75). Thirty-one participants would increase their PA if advised to by a dispensing optician. Participants with a history of anxiety and depression were less likely to report they would increase their PA based on advice from a GP (p = 0.002). Sight loss specific and community-based PA groups, exercise specialist support, a sighted guide, and a travel plan, were considered by most participants to be useful facilitators of PA. Conclusion The results suggest eyecare and sight loss service professionals could facilitate increases in PA among adults with sight loss.
... A further 1360 were excluded following screening of titles and abstracts (Fig. 1). After full-text screening of 52 articles, 9 manuscripts [27][28][29][30][31][32][33][34][35] were included in this review (Additional file 3). ...
... Characteristics of the nine included [27][28][29][30][31][32][33][34][35] studies are shown in Table 2. Data from Murphy et al. [30] and Moore et al. [31] originated from the same trial but since they presented different outcome measures, they are referred to as separate studies. The most common study type was a retrospective analysis of ERS data [27,28,[33][34][35]; or an RCT [29][30][31][32]. ...
... Characteristics of the nine included [27][28][29][30][31][32][33][34][35] studies are shown in Table 2. Data from Murphy et al. [30] and Moore et al. [31] originated from the same trial but since they presented different outcome measures, they are referred to as separate studies. The most common study type was a retrospective analysis of ERS data [27,28,[33][34][35]; or an RCT [29][30][31][32]. Studies targeted patients treated for mental ill health [29,32] or mental ill health and other chronic health conditions [27,28,30,31,35]. ...
Full-text available
Background: Exercise is a recognised element of health-care management of mental-health conditions. In primary health care, it has been delivered through exercise referral schemes (ERS). The National Institute for Health and Care Excellence has highlighted uncertainty regarding the effectiveness of ERS in improving exercise participation and health outcomes among those referred for mental-health reasons. This review aims, therefore, to evaluate ERSs for individuals who are referred specifically for mental-health reasons. Methods: Studies were reviewed that assessed the effectiveness of ERSs in improving initiation of and/or adherence to exercise and/or their effectiveness in improving long-term participation in exercise and health outcomes among primary care patients who had been referred to the scheme for mental-health reasons. The data were extracted and their quality assessed. Data were analysed through a narrative synthesis approach. Results: Nine studies met the eligibility criteria. Three assessed clinical effectiveness of the schemes, eight assessed ERS uptake and/or adherence to the exercise schedule, and two assessed the impact of the ERSs on long-term exercise levels. In one study, it was found that ERSs that were based in leisure centres significantly improved long-term symptoms in those who had been referred due to their mental ill health (P<0.05). ERSs that involved face-to-face consultations and telephone calls had the highest rates of mean uptake (91.5%) and adherence (71.7%), but a difference was observed between uptake/adherence in trials (86.8%/55.3%) and in routine practice (57.9%/37.2%). ERSs that included face-to-face consultations and telephone calls increased the amount of long-term physical activity that was undertaken by people who had been referred for mental-health reasons (P=0.003). Conclusions: Uptake and effectiveness of ERSs for mental health conditions was related to programme content and setting with more effective programmes providing both face-to-face and telephone consultations. Good uptake of yoga among those referred for mental health reasons suggests that mindful exercise options should be investigated further. Existing ERSs could be improved through application of individual tailoring and the provision of more face-to-face consultations, and social support. Further research is required to identify the types of ERSs that are most clinically effective for those with mental ill health.
... In Wales, UK, a national ERS continues to be delivered across all local authorities (LAs), following positive impacts found in an earlier randomized controlled trial (RCT) [8]. More than ten years later, this evidence-based ERS, formally known as NERS (National Exercise Referral Scheme), has received over 80,000 referrals [12]. NERS comprises a supervised 16-week exercise programme for patients over aged 16 years who have, or are at risk of developing, a chronic disease. ...
... Our recent findings found a widening of inequality in patient referral and uptake of NERS since the earlier RCT [12]. Over a ten-year period, we observed a downward trend for the referral of patients in the most deprived groupings, coupled with a marked pattern of disparity in uptake rates. ...
... Setting NERS is delivered across all 22 LAs in Wales and has received a total of 83,598 generic pathway patient referrals between 2007 and 2017 [12]. In order to attend the programme, a patient requires a referral from a health professional to a community-based facility within their LA whereby they undertake an initial scheme consultation. ...
Full-text available
Background Over ten years on from a randomised controlled trial and subsequent national roll-out, the National Exercise Referral Scheme (NERS) continues to be routinely delivered in primary care across Wales, UK. Few studies have revisited effective interventions years into their delivery in routine practice to understand how implementation, and perceived effects, have been maintained over time. This study explores perceptions and experiences of referral to NERS among referrers, scheme deliverers and patients. Methods Individual, semi-structured interviews were conducted with 50 stakeholders: scheme referrers (n = 9); scheme deliverers (n = 22); and referred patients (n = 19). Convenience sampling techniques were used to recruit scheme referrers and purposive sampling to recruit scheme deliverers and patients. Thematic analysis was employed. Results Analyses resulted in five key themes; referrer characteristics, geographical disparities in referral and scheme access, reinforcements for awareness of the scheme, patient characteristics and processes and context underpinning a referral. Overall there was a high concordance of views between all three stakeholder groups and barriers and facilitators were found to be entwined within and across themes. Referral barriers persisting since the earlier trial included a lack of consultation time and a lack of referral feedback. Newly identified barriers included a lack of scheme awareness and a referral system perceived to be time intensive and disjointed. Key referral facilitators included patient self-referrals, a growing scheme reputation and promotional activities of scheme deliverers. Conclusions Findings provide evidence that could inform the further development of NERS and wider exercise referral schemes to ensure the referral process is timely, efficient and equitable.
... A systematic review showed that average uptake to ERS ranged from 66 to 81%, and average adherence rates (attending ≥ 75% of sessions) ranged from 43% in randomised trials to 49% in observational studies [5]. In a recent retrospective data linkage study of over 83,000 referred patients, 67% had actually attended the ERS [6]. Various determinants have been linked to patient uptake and adherence including gender, age, clinical condition, and socio-economic status [5,6]. ...
... In a recent retrospective data linkage study of over 83,000 referred patients, 67% had actually attended the ERS [6]. Various determinants have been linked to patient uptake and adherence including gender, age, clinical condition, and socio-economic status [5,6]. A systematic review of 33 qualitative studies found that inconvenient timing, cost, and location of sessions were key participant reported barriers to engagement in gym-based ERS schemes. ...
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Background: The e-coachER trial aimed to determine whether adding web-based behavioural support to exercise referral schemes (ERS) increased long-term device-measured physical activity (PA) for patients with chronic conditions, compared to ERS alone, within a randomised controlled trial. This study explores the mechanisms of action of the e-coachER intervention using measures of the behaviour change processes integral to the intervention's logic model. Methods: Four hundred fifty adults with obesity, diabetes, hypertension, osteoarthritis or history of depression referred to an ERS were recruited in Plymouth, Birmingham and Glasgow. The e-coachER intervention comprising 7-Steps to Health was aligned with Self-Determination Theory and mapped against evidence-based behaviour change techniques (BCTs). Participants completed questionnaires at 0, 4, and 12 months to assess PA and self-reported offline engagement with core BCTs in day-to-day life (including action planning and self-monitoring) and beliefs relating to PA (including perceived importance, confidence, competence, autonomy and support). We compared groups at 4 and 12 months, controlling for baseline measures and other covariates. Mediation analysis using the product of coefficients method was used to determine if changes in process variables mediated intervention effects on moderate to vigorous physical activity (MVPA) recorded by accelerometer and self-report at 4- and 12-months. Results: The internal reliability (Cronbach's alpha) for all multi-item scales was > 0.77. At 4-months, those randomised to e-coachER reported higher levels of PA beliefs relating to importance (1.01, 95% confidence interval (CI): 0.42 to 1.61, p = 0.001), confidence (1.28, 95% CI: 0.57 to 1.98, p < 0.001), competence (1.61, 95% CI: .68 to 2.54, p = 0.001), availability of support (0.77, 95% CI: 0.07 to 1.48, p = 0.031), use of action planning (1.54, 95% CI: 0.23 to 2.85, p = 0.021) and use of self-monitoring (0.76, 95% CI: 0.19 to 1.32, p = 0.009) compared to ERS alone. There were no intervention effects on autonomous beliefs or perceived frequency of support, compared to ERS alone. At the 12-month follow-up, participants belief in the importance of PA was the only process measure to remain significantly higher in the e-coachER group when compared to ERS alone (0.75, 95% CI: 0.05 to 1.45). Intervention effects on perceived importance (2.52, 95% CI: 0.45 to 5.39), action planning (1.56, 95% CI: 0.10 to 3.54) and self-monitoring (1.92, 95% CI: 0.21 to 4.33) at 4-months significantly mediated change in accelerometer measured MVPA at 12-months (recorded in ≥ 10-min bouts). Conclusions: e-coachER led to some short-term changes in most process outcomes. Some of these processes also appeared to mediate e-coachER effects on changes in accelerometer measured MVPA. Further work should be carried out to understand how best to design and implement theoretically underpinned web-based physical activity promotion interventions within ERS. Trial registration: ISRCTN, ISRCTN15644451 . Registered 12 February 2015.
... The investigators only knew the number of patients who accepted taking part in the program. Knowing the volume of patients referred to a HEPA program and, moreover, the characteristics of those referred are critical to begin to interpret the generalizability of the findings to the broader population [76]. ...
Introduction: Depression is a challenge for public health policies, as it is the number one leading cause of disability in the world. In order to combat and prevent it, different social and health interventions are being developed to promote health through physical activity. Objective: Analyze and describe the user profile of the patients with depression from the Exercise Looks After You program, which is a physical activity program that works on improving public health and has an essential role preventing chronic diseases and improving the quality of life of the elderly in Extremadura. Design: Cross-sectional study. Participants: total sample of 1972 users (96.4% women, 3.6% men), of whom 724 (94.6% women, 5.4% men) suffer from depression. Results: It was observed that the dominant user profile of the patients with depression within the program is female, 71 years old, physically active, overweight, married, with low educational level, non-smoker, no alcohol consumption and below average physical fitness and health-related quality of life, which translates into a high incidence of primary care, nursing and prescription visits. Conclusions: This study presents the user profile of depressive versus non-depressive participants of the Exercise Looks After You physical activity program. This data could be meaningful in order to improve and optimize public health programs and resources.
... ERS participants undertake programmes of supervised, safe, appropriate, prescribed exercises, where they may benefit physiologically and psychologically from increasing their level of PA [2]. However, the evidence base for ERS has been questioned, notably the inconsistent and weak evidence base and assessment [4,5], limited increase in PA levels [6,7], wellbeing, quality of life or health outcomes [7,8] and inequalities [9]. ...
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Exercise referral schemes are designed to support people with non-communicable diseases to increase their levels of exercise to improve health. However, uptake and attendance are low. This exploratory qualitative study aims to understand uptake and attendance from the perspectives of exercise referral instructors using semi-structured interviews. Six exercise referral instructors from one exercise referral scheme across four exercise referral sites were interviewed. Four themes emerged: (i) the role that instructors perceive they have and approaches instructors take to motivate participants to take-up, attend exercise referral and adhere to their exercise prescription; (ii) instructors’ use of different techniques, which could help elicit behaviour change; (iii) instructors’ perceptions of participants’ views of exercise referral schemes; and (iv) barriers towards providing an exercise referral scheme. Exercise referral instructors play an important, multifaceted role in the uptake, attendance and adherence to exercise referral. On-going education and peer support for instructors may be useful. Instructors’ perspectives help us to further understand how health and leisure services can design successful exercise referral schemes.
... For example, within the National Exercise Referral Scheme in Wales, routine data analysed 10 years after completion of a randomised trial indicated increased socioeconomic patterning over time in terms of engagement with the programme. 57 If interventions have been implemented elsewhere, adaptation teams could consider whether harmonisation of monitoring systems is appropriate to enable comparisons across different contexts. As context changes over time, the process of making responsive adaptations will continue after interventions are taken to scale. ...
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Implementing interventions with a previous evidence base in new contexts might be more efficient than developing new interventions for each context. Although some interventions transfer well, effectiveness and implementation often depend on the context. Achieving a good fit between intervention and context then requires careful and systematic adaptation. This paper presents new evidence and consensus informed guidance for adapting and transferring interventions to new contexts.
... Indeed, the use of health databases has been argued to have a considerable impact upon promotion of scientific endeavour [10]. Excellent work regarding the large Welsh National Exercise Referral Scheme has been conducted linking with routine health records and reported in this special issue [11]. However, an open resource such as this for ERS across the UK with a focus on outcome data has yet to be produced. ...
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In 2014, The National Institute for Health and Care Excellence (NICE) called for the development of a system to collate local data on exercise referral schemes (ERS). This database would be used to facilitate continued evaluation of ERS. The use of health databases can spur scientific investigation and the generation of evidence regarding healthcare practice. NICE’s recommendation has not yet been met by public health bodies. Through collaboration between ukactive, ReferAll, a specialist in software solutions for exercise referral, and the National Centre for Sport and Exercise Medicine, which has its research hub at the Advanced Wellbeing Research Centre, in Sheffield, data has been collated from multiple UK-based ERS to generate one of the largest databases of its kind. This database moves the research community towards meeting NICEs recommendation. This paper describes the formation and open sharing of The National ReferAll Database, data-cleaning processes, and its structure, including outcome measures. Collating data from 123 ERSs on 39,283 individuals, a database has been created containing both scheme and referral level characteristics in addition to outcome measures over time. The National ReferAll Database is openly available for researchers to interrogate. The National ReferAll Database represents a potentially valuable resource for the wider research community, as well as policy makers and practitioners in this area, which will facilitate a better understanding of ERS and other physical-activity-related social prescribing pathways to help inform public health policy and practice.
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This commentary highlights the challenges of clinical trials, especially as related to trials on exercise for older adults with advanced cancer, and comments on the study by Mikkelsen et al.
Despite widespread use, community-based physical activity prescription is controversial. Data limitations have resulted in a lack of clarity about what works, under what circumstances, and for whom, reflected in conservative policy recommendations. In this commentary we challenge a predominantly negative discourse, using contemporary research to highlight promising findings and “lessons learnt” for design, delivery, and evaluation. In doing so, we argue for the importance of a more nuanced approach to future commissioning and evaluation. Novelty: Amalgamating learning from multiple research teams to create recommendations for advancing physical activity prescription.
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Background: Randomized controlled trials (RCTs) are regarded as the most internally valid means of estimating the effectiveness of complex public health interventions, but the recruitment of participants can be difficult. The aim of this study was to explore factors that may have affected the recruitment of employees with musculoskeletal disorders (MSDs) to a multicenter worksite health promotion program from the perspective of recruiting case managers. Methods: Factors in recruitment to the RCT were explored using three focus group discussions with case managers. Data were processed using MAXQDA and analyzed with a combination of content and sequence analysis. Results: Findings showed that randomization is a major challenge for recruitment. Case managers adapted their communication with, and approaches to possible participants because of the randomization design and employed coping strategies to compensate for allocation into the control arm of the study. Perceptions of the superiority of the intervention group over the control group, perceptions of the (mis)match of participants to one of the groups, as well as the understanding of the necessity of randomization for effectiveness evaluations, further affected recruitment. Perceived expectations of possible participants and their (emotional) reactions to the randomization allocation also complicated recruitment. Conclusion: We were able to gain insight into the challenges of randomization for the recruitment of participants to a multicenter RCT. This study assisted the development of strategies to overcome barriers in the ongoing implementation process of the trial (i.e., the adaption of best practice information sheets and newsletters). There remains a need to develop effective interventions to help those recruiting to trials.
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Background The Secure Anonymised Information Linkage (SAIL) Databank is a national data safe haven of de‑identified datasets principally about the population of Wales, made available in anonymised form to researchers across the world. It was established to enable the vast arrays of data collected about individuals in the course of health and other public service delivery to be made available to answer important questions that could not otherwise be addressed without prohibitive effort. The SAIL Databank is the bedrock of other funded centres relying on the data for research. Approach SAIL is a data repository surrounded by a suite of physical, technical and procedural control measures embodying a proportionate privacy-by-design governance model, informed by public engagement, to safeguard the data and facilitate data utility. SAIL operates on the UK Secure Research Platform (SeRP), which is a customisable technology and analysis platform. Researchers access anonymised data via this secure research environment, from which results can be released following scrutiny for disclosure risk. SAIL data are being used in multiple research areas to evaluate the impact of health and social exposures and policy interventions. Discussion Lessons learned and their applications include: managing evolving legislative and regulatory requirements; employing multiple, tiered security mechanisms; working hard to increase analytical capacity efficiency; and developing a multi-faceted programme of public engagement. Further work includes: incorporating new data types; enabling alternative means of data access; and developing further efficiencies across our operations. Conclusion SAIL represents an ongoing programme of work to develop and maintain an extensive, whole population data resource for research. Its privacy-by-design model and UK SeRP technology have received international acclaim, and we continually endeavour to demonstrate trustworthiness to support data provider assurance and public acceptability in data use. We strive for further improvement and continue a mutual learning process with our contemporaries in this rapidly developing field.
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Objectives To examine if exercise referral schemes (ERSs) are associated with meaningful changes in health and well-being in a large cohort of individuals throughout England, Scotland, and Wales from the National Referral Database. Methods Data were obtained from 23 731 participants from 13 different ERSs lasting 6 weeks to 3 months. Changes from pre- to post-ERS in health and well-being outcomes were examined including body mass index (BMI), blood pressure (systolic (SBP) and diastolic (DBP)), resting heart rate (RHR), short Warwick Edinburgh Mental Wellbeing Scale (SWEMWBS), WHO Well-Being Index (WHO-5), Exercise Related Quality of Life scale (ERQoL), and Exercise Self-Efficacy Scale (ESES). Two-stage individual patient data meta-analysis was used to generate effect estimates. Results Estimates (95% CIs) revealed statistically significant changes occurred compared with point nulls for BMI (−0.55 kg.m ² (−0.69 to −0.41)), SBP (−2.95 mmHg (−3.97 to −1.92)), SWEMWBS (2.99 pts (1.61 to 4.36)), WHO-5 (8.78 pts (6.84 to 10.63)), ERQoL (15.26 pts (4.71 to 25.82)), and ESES (2.58 pts (1.76 to 3.40)), but not RHR (0.22 fc (−1.57 to 1.12)) or DBP (−0.93 mmHg (−1.51 to −0.35)). However, comparisons of estimates (95% CIs) against null intervals suggested the majority of outcomes may not improve meaningfully. Conclusions We considered whether meaningful health and well-being changes occur in people who are undergoing ERSs. These results demonstrate that, although many health and well-being outcomes improved, the changes did not achieve meaningful levels. This suggests the need to consider the implementation of ERSs more critically to discern how to maximise their effectiveness.
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Objective The aim of this article is to describe this systematic and phased process in developing the evidence-based ‘Exercise and Depression Toolkit’ for health care providers working with adults with depression. Methods The Appraisal of Guidelines, Research and Evaluation (AGREE) II tool was consulted throughout the developmental phased process, and used to guide toolkit content and dissemination strategies. The four phases included a review of relevant literature, formative interviews, an expert panel meeting, and finally toolkit development. A Theoretical Domains Framework (TDF) analysis was also used to determine behaviour change techniques (BCT) to be included in the toolkit. Various stakeholders were involved throughout the process including health care providers, adults who have lived experience with depression, researchers, and exercise professionals who have experience working with adults with depression. Results Recommendations from the consultation process included that the toolkit be ‘depression tailored’ including specific barriers that adults with depression face to engaging in physical activity (PA) and strategies they can use. The toolkit should promote collaboration and a person-centered approach. Different parts of the toolkit should be created for the intended audience of health care providers and adults with depression. BCTs were included to target the ‘Emotion’ and ‘Social Influences’ domains of the TDF. Conclusions These recommendations have resulted in the development of the ‘Exercise and Depression Toolkit’. This toolkit is a resource for health care providers, adults with depression, and exercise professionals to help exercise become an accessible treatment option for the many Canadians living with depression.
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Background: Exercise referral schemes (ERS) are prescribed programs to tackle physical inactivity and associated noncommunicable disease. Inconsistencies in reporting, recording, and delivering ERS make it challenging to identify what works, why, and for whom. Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analyses guided this narrative review of reviews. Electronic databases were searched for systematic reviews of ERS. Inclusion criteria and quality assessed through A Measurement Tool to Assess Systematic Reviews (AMSTAR). Data on uptake, attendance, and adherence were extracted. Results: Eleven reviews met inclusion criteria. AMSTAR quality was medium. Uptake ranged between 35% and 81%. Groups more likely to take up ERS included (1) females and (2) older adults. Attendance ranged from 12% to 49%. Men were more likely to attend ERS. Effect of medical diagnosis upon uptake and attendance was inconsistent. Exercises prescribed were unreported; therefore, adherence to exercise prescriptions was unreported. The influence of theoretically informed approaches on uptake, attendance, and adherence was generally lacking; however, self-determination, peer support, and supervision were reported as influencing attendance. Conclusions: There was insufficient reporting across studies about uptake, attendance, and adherence. Complex interventions such as ERS require consistent definitions, recording, and reporting of these key facets, but this is not evident from the existing literature.
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Background: In 2014 The National Institute for Health and Care Excellence (NICE) called for development of a system to collate local data on exercise referral schemes (ERS) to inform future practice. This database would be used to facilitate continued evaluation of ERS. ‘Big data’ analytics is a current trend in healthcare with the potential to influence decision making. Indeed, the use of health databases can spur scientific investigation and generation of evidence regarding healthcare practice. NICEs recommendation has not yet been met by public health bodies. However, through collaboration between ukactive, ReferAll, a specialist in software solutions for exercise referral, and the National Centre for Sport and Exercise Medicine, data has been collated from multiple UK based ERS to generate one of the largest databases of its kind and move towards meeting NICEs recommendation. Method: This paper describes the formation of The National Referral Database, its structure including outcome measures, data cleaning processes, and in two accompanying manuscripts the first initial observational insights are presented from analysis of this data. Results: Collating data from 19 ERSs on 24,086 individuals, a database has been created containing pre and post referral data for metrics including; physical activity, blood pressure, BMI, resting heart rate, SWEMWBS scores, ESES scores, WHO5 scores and ERQoL scores. After data cleaning processes there were 14 ERSs remaining covering 23,782 participants with an average age of 51±15 years and 68% of whom were female. Further, the database contains demographic information, reason for referral, medical conditions, and information on the referrer. Conclusion: This database has now been created and the initial data is available for researchers to interrogate. The National Referral Database represents a potentially valuable resource for the wider research community, as well as policy makers and practitioners in this area, which will facilitate a better understanding of ERS and other physical activity related social prescribing pathways to help inform public health policy and practice. Longer term plans include establishment of the database as an open resource, continually updated with additional data and version controls, for researchers to access for further research and policy makers and practitioners to use to inform their policies/practices.
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Exercise referral schemes aim to increase physical activity amongst inactive individuals with or at risk of long-term health conditions. Yet many patients referred to these schemes (by health professionals) fail to take up the exercise opportunities on offer. Understanding factors influencing uptake to exercise referral schemes may help improve future attendance. Using the Socio-Ecological Model as a framework, this qualitative study aimed to explore factors influencing uptake to an exercise referral scheme based in the North West of England. Semi-structured interviews were conducted with referred patients (n = 38) about their reasons for referral, interactions with referring health professionals, events following referral and ideas to improve future uptake. Data were analysed thematically and mapped onto the constructs of the Socio-Ecological Model. Factors reported to influence uptake included intrapersonal (past PA experiences, motivation, competing priorities), interpersonal (scheme explanations, support) and organizational influences (scheme promotion, communication between service, cost). Whilst several intrapersonal-level factors influenced patient decisions to uptake the exercise referral scheme, modifiable interpersonal and organizational factors were identified as potential targets for intervention. Recommendations are made for improving awareness of exercise referral schemes and for enhancing communication between referring practitioners, patients and referral scheme staff.
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Background: Insufficient physical activity is a leading risk factor for non-communicable diseases, and has a negative effect on mental health and quality of life. We describe levels of insufficient physical activity across countries, and estimate global and regional trends. Methods: We pooled data from population-based surveys reporting the prevalence of insufficient physical activity, which included physical activity at work, at home, for transport, and during leisure time (ie, not doing at least 150 min of moderate-intensity, or 75 min of vigorous-intensity physical activity per week, or any equivalent combination of the two). We used regression models to adjust survey data to a standard definition and age groups. We estimated time trends using multilevel mixed-effects modelling. Findings: We included data from 358 surveys across 168 countries, including 1·9 million participants. Global age-standardised prevalence of insufficient physical activity was 27·5% (95% uncertainty interval 25·0-32·2) in 2016, with a difference between sexes of more than 8 percentage points (23·4%, 21·1-30·7, in men vs 31·7%, 28·6-39·0, in women). Between 2001, and 2016, levels of insufficient activity were stable (28·5%, 23·9-33·9, in 2001; change not significant). The highest levels in 2016, were in women in Latin America and the Caribbean (43·7%, 42·9-46·5), south Asia (43·0%, 29·6-74·9), and high-income Western countries (42·3%, 39·1-45·4), whereas the lowest levels were in men from Oceania (12·3%, 11·2-17·7), east and southeast Asia (17·6%, 15·7-23·9), and sub-Saharan Africa (17·9%, 15·1-20·5). Prevalence in 2016 was more than twice as high in high-income countries (36·8%, 35·0-38·0) as in low-income countries (16·2%, 14·2-17·9), and insufficient activity has increased in high-income countries over time (31·6%, 27·1-37·2, in 2001). Interpretation: If current trends continue, the 2025 global physical activity target (a 10% relative reduction in insufficient physical activity) will not be met. Policies to increase population levels of physical activity need to be prioritised and scaled up urgently. Funding: None.
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Background Exercise referral schemes within clinical populations may offer benefits for inactive and sedentary individuals, and improve and aid treatment of specific health disorders. This systematic review aims to provide an overview, and examine the impact, of exercise referral schemes in patients with cardiovascular, mental health, and musculoskeletal disorders. This review focuses on populations within the United Kingdom (UK) only, with an aim to inform national exercise referral policies and guidelines. Method Data was collected from specific sources using validated methodology through PRISMA. Systematic searches were performed using Locate, PubMed, Scopus and Pro Quest: Public Health databases. Thirteen studies met inclusion criteria set for each sub group. This included that all studies aimed to prevent, observe, or decrease ill-health relating to the disorder, participants over the age of sixteen, and health disorders and outcomes were reviewed. All studies were conducted in the UK only. Results In the 13 articles, a variety of modes and types of exercise were utilised. One-to-one supervised exercise sessions based in a gym environment were most frequently employed. Results showed that longer length schemes (20+ weeks) produced better health outcomes, and had higher adherence to physical activity prescribed, than those of shorter length (8–12 weeks). In patients referred with cardiovascular disorders, cardiovascular-related measures showed significant decreases including blood pressure. Schemes increased physical activity levels over the length of scheme for all disorders. Conclusion Longer length schemes (20+ weeks) improved adherence to physical activity prescribed over the course of the scheme, and could support longer term exercise adherence upon completion, however additional research on larger samples should examine this further. An implication is that schemes currently recommended in guidelines do not tailor programmes to support long term adherence to exercise, which must be addressed. There is currently a lack of research examining programmes tailored to suit the individual’s health conditions thus further research might allow providers to tailor delivery and build upon policy recommendations in the UK.
Objective: To understand the ways that mental health symptoms interfere with achieving health goals. Methods: Individuals with mental illness diagnoses and varying levels of preventive service use were recruited from federally qualified health centers and an integrated health care delivery system and interviewed. Thematic analysis was used to characterize descriptions of how mental illness experiences influenced lifestyle change efforts. Results: Three themes described patients' (n = 163) perspectives on barriers to making healthy lifestyle changes: 1) Thinking about making lifestyle changes is overwhelming for individuals already managing the burdens of mental illnesses; 2) Depression makes it difficult to care about a healthy future; and 3) When mental illness symptoms are not adequately treated unhealthy behaviors that provide relief are unlikely to be discontinued. Participants also made suggestions for improving health care delivery to facilitate positive behavior change. Conclusion: Patients with mental illnesses need their clinicians to be empathic, help them envision a healthier future, address unmet mental health needs, and provide resources. Practice implications: Primary care clinicians should encourage their patients with mental illnesses to make healthy lifestyle changes within the context of a supportive relationship. Lifestyle change can be overwhelming; clinicians should acknowledge progress and provide ongoing tangible support.