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A Randomized Feasibility Trial of a New Lifestyle Referral Assessment Versus Usual Assessment in an Acute Cardiology Setting

Hill, Kate PhD; Walwyn, Rebecca PhD; Camidge, Diana MSc; Murray, Jenni PhD; Meads, David MSc; Reynolds, Greg FRCP; Farrin, Amanda MSc; House, Allan DM

The Journal of Cardiovascular Nursing: November/December 2016 - Volume 31 - Issue 6 - p 507–516
doi: 10.1097/JCN.0000000000000294
ARTICLES: Prevention

Background: A healthy diet, taking exercise, and not smoking or consuming alcohol in excess are important to reduce the risk of cardiovascular disease either alone or in combination with statin medication. Health education, including providing information to patients on healthy living and guidance on how to achieve it, is a key nursing function.

Objectives: This study aims first to assess the feasibility of conducting a full-scale trial of lifestyle referral assessment as shown by recruitment rate, data collection, and follow-up and second to assess proof of concept and explore possible mechanisms of change.

Methods: This was a single-center, randomized, 2-arm, parallel-group, unblinded feasibility trial conducted in an acute teaching hospital trust. Participants were followed up at 3 and 6 months after randomization.

Results: Eight hundred eighty-seven patients were screened for eligibility, of whom 132 (15%) were randomized into the trial. Of the patients allocated to the individualized assessment, 27% accepted referral or self-referred by 3 months in comparison to 5% allocated to the usual assessment.

Conclusions: We demonstrated that a full-scale trial is feasible and that an individualized approach increased the number of patients accepting referral to a formal program and initiating lifestyle change. However, we should consider the aim of the assessment and ways in which the process of change can be optimized in order to produce long-term benefit for patients.

Trial registration: current controlled trials ISRCTN41781196.

Kate Hill, PhD Senior Research Fellow, Leeds Institute of Health Sciences, University of Leeds, United Kingdom.

Rebecca Walwyn, PhD Principal Statistician, Clinical Trials Research Unit, University of Leeds, United Kingdom.

Diana Camidge, MSc Research Officer, Leeds Institute of Health Sciences, University of Leeds, United Kingdom.

Jenni Murray, PhD Senior Research Fellow, Leeds Institute of Health Sciences, University of Leeds, United Kingdom.

David Meads, MSc Associate Professor, Leeds Institute of Health Sciences, University of Leeds, United Kingdom.

Greg Reynolds, FRCP Consultant Cardiologist, Leeds Teaching Hospitals Trust, Leeds, United Kingdom.

Amanda Farrin, MSc Chair, Clinical Trials Research Unit, University of Leeds, United Kingdom.

Allan House, DM Professor of Liaison Psychiatry, Leeds Institute of Health Sciences, University of Leeds, United Kingdom.

The CLAHRC LYB vascular theme collaborators: Prof Bob Lewin, Prof Simon Gilbody, and Prof Ian Watt at the University of York and Dr Lucy Jackson at NHS Leeds, and the CLAHRC Improve project team. Data collection was assisted by Sian Davies, a student at Leeds University Medical School, during a summer research placement.

This work was supported by a National Institute for Health Research (NIHR) grant (reference KRD/012/001/006).

This article presents independent research by the NIHR Collaboration for Leadership in Applied Health Research and Care for Leeds, York, and Bradford (CLAHRC LYB), a pilot that ended in 2013. Further details about the new NIHR CLAHRC Yorkshire and Humber can be found at The views and opinions expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health.

The authors have disclosed that they have no significant relationship with, or financial interest in, any commercial companies pertaining to this article.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (

Correspondence Kate Hill, PhD, Academic Unit of Psychiatry Behavioural Sciences Leeds Institute of Health Sciences, University of Leeds, Charles Thackrah Bldg, 101 Clarendon Rd, Leeds, United Kingdom LS2 9LJ (

The global burden of cardiovascular disease (CVD) and its risk factors are well documented. Some risk factors for CVD cannot be modified, but some can be controlled by medication or modified by lifestyle change.1,2 Health education, including providing information to patients on healthy living and guidance on how to achieve it, is a key nursing function.

To make a difference to health, lifestyle change has to be not only initiated but also maintained. Psychological theories such as the transtheoretical model3 and the theory of planned behavior4 attempt to explain the process of change but assume a degree of persistence. In reality, people tend to dip in and out of lifestyle change, dieting or increasing physical activity, for example, in preparation for a summer holiday or special event. Interventions based on theoretical models of this type need to take this into account when implemented in real-life contexts.5

Many studies measure outcome by uptake of lifestyle change programs, but there is a difference between taking up a lifestyle change program and the initiation of actual change. In previous work, we reviewed the evidence to identify the main influences on lifestyle change and identified 5 key factors that affect uptake and continued participation in lifestyle change programs: (i) beliefs about the need to change; (ii) knowledge about lifestyles; (iii) support from family and friends; (iv) emotional state, and (v) problems with finance and travel.6

Following the Marmot Review,7 the UK Department of Health introduced a raft of initiatives to improve health and well-being including “Every Contact Counts,”8 which encourages nurses and other public-facing staff to engage patients conversationally about lifestyle and give brief advice about health and lifestyle choices. However, coverage both in terms of the staff who engage patients in this way and the topics they address is patchy. We hypothesize that acceptance of referral and uptake of lifestyle change will have a better chance of success if a systematic approach is adopted to produce an individualized plan for change. We therefore developed a lifestyle referral assessment based on the factors that emerged from our synthesis of the evidence,9 which aims to elicit individual difficulties in order to produce a tailored plan for lifestyle change. Our approach is compatible with the recommendations of the most recent National Institute for Health and Care Excellence guidelines for lifestyle change.10

In this study, we test the feasibility of conducting a full-scale trial of lifestyle assessment and referral by comparing our new individually tailored assessment with local usual practice. We explore acceptance of referral to a lifestyle management program, either self-directed change or a formal, routinely available program, and its effect on lifestyle change in patients with modifiable risk factors for CVD admitted to acute cardiology services with a suspected cardiac event.

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Study Design

The Healthy Hospital Trial is a single-center, randomized controlled, 2-arm, parallel-group, unblinded feasibility trial that was conducted on 2 cardiology wards at the Leeds Teaching Hospitals Trust. Its primary aim was to explore the feasibility of individualized lifestyle referral assessment, estimate the rate of recruitment, and explore the feasibility of collecting the data and follow-up of participants to inform the sample size of a definitive trial. A secondary aim was to test the concept that an individually tailored assessment improves uptake of lifestyle change compared with usual assessment. The trial protocol has been published elsewhere.11

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We aimed to recruit people at risk of heart disease who would not usually be referred to a cardiac rehabilitation program. Eligibility criteria for the study were broad:

  1. patients admitted to hospital with a suspected diagnosis of acute coronary event, myocardial infarction, or symptoms of a cardiac nature;
  2. male or female aged between 40 and 74 years (within the NHS Health Check age range) at the time of screening for recruitment; and
  3. willing and able to give written informed consent.

We excluded patients currently receiving specialist treatment with a primary focus on alcohol, smoking, diet, or exercise; those with no modifiable risk factors for vascular events; those of no-fixed abode or mainly resident abroad or currently serving a sentence in prison or with outstanding legal issues likely to lead to imprisonment (ie, not available for follow-up); or those who were unable to take part in either intervention using spoken English or unable to self-complete the English-language outcome measure instruments.

The flow of patients through the trial and exclusion categories are shown in the CONSORT diagram (Figure). Demographic details of the participants are given in Table 1.



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The new individualized assessment was an add-on to the local usual assessment used by the cardiac rehabilitation nurses. The usual assessment was delivered in both arms of the trial (see Documents, Supplemental Digital Content 1,, and Supplemental Digital Content 2, Both the new and usual assessments are simple checklists that include an option for referral to lifestyle change services. The new assessment differs by incorporating a discussion of barriers and facilitators based on the key factors influencing lifestyle change.9 It includes an option for self-directed change with support to set goals. For the purpose of the trial, both new and usual assessments were delivered by 1 researcher.



All participants were given basic lifestyle advice and contact details for a locally provided, online healthy living program (Leeds Let’s Change),12 which is based on advice and support provided by the national “Change for Life” program developed by the UK Department of Health.13 Requests for referrals from participants in the control arm were passed to ward staff for action.

The level of support provided in the intervention arm was more individualized. The researcher talked to the patients about their lifestyle to identify what was important to them and what they wanted to change. Patients were encouraged to identify their personal priorities, for example, whether to focus on 1 specific lifestyle factor or tackle 2 or more things together. Methods to effect change were discussed, and an approach chosen based on individual needs and preferences; for example, those choosing self-led change were encouraged to identify personal goals and use an individualized record card; those opting for a formal program were assisted to access the Leeds Let’s Change Web site using a laptop computer and helped to identify a suitable, local program. Referrals were made without delay, or information was provided to permit self-enrollment after discharge.

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Data Collection

Participants were assessed for eligibility in hospital and provided with written information. After consent was obtained, baseline assessment of lifestyle and randomization was carried out on the ward before discharge. We used simple randomization with no stratification, details of which are reported elsewhere.11 Participants were followed up 3 and 6 months after randomization to determine self-reported changes in lifestyle. We defined uptake as acceptance of referral to a formal program or an expression of willingness to undertake a self-led program of change, scored as binary (yes/no), and initiation of change as participation in a formal program or a self-directed program that was intended to result in change either in diet, physical activity, smoking, or alcohol consumption at any time (binary). Within initiation, we identified 3 categories of change to represent the maximum achieved change in any 1 of the participant’s nominated lifestyle factors: (a) no change, (b) lifestyle change in progress, and (c) maintenance of lifestyle change (sustained change that persisted over 10 weeks) (ordinal). In our published protocol, we had proposed 4 categories of change, but we found it difficult to distinguish between “persisted” and “maintained” in the qualitative follow-up interviews; hence, we combined persistence and maintenance of change in 1 category.

Validated questionnaires were administered at baseline and follow-up points. Social satisfaction was measured using the Social Satisfaction Questionnaire (SSQ), an 8-item scale scored 0 to 3, where a higher score indicates less satisfaction with the respondent’s social situation.14 Subjective well-being and psychological status were measured using the Clinical Outcomes in Routine Evaluation (10-item version: CORE-10) scored 0 to 4, with higher scores indicating more severe psychological distress.15 Health-related quality of life was assessed using the European Quality of Life–5 Dimensions (EQ-5D), a generic measure of health status where health is characterized on 5 dimensions (mobility, self-care, ability to undertake usual activities, pain, anxiety, or depression), and a visual analog scale.16 We collected data on psychosocial elements because our review of the evidence showed that factors such as beliefs, family support, finances, and transport affected uptake and participation in lifestyle change. We thus considered these factors relevant to an individualized referral assessment and tested our assumptions as part of the proof-of-concept study.

Follow-up was conducted by interview over the telephone and only occasionally in patients’ homes or at the research office. We assessed self-reported participation in lifestyle change interventions using the outcome in which most change had been identified for the component domains (ie, alcohol, smoking, dieting, and physical activity). As part of usual care, participants in both arms could opt for a lifestyle referral at any time. In these cases, trial participants were reminded about the Leeds Let’s Change Web site and advised to contact their general practitioner or practice nurse for further advice.

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Data Analysis

Feasibility of recruitment, data collection, the intervention, and follow-up were assessed qualitatively, supported by descriptive statistics summarized primarily in a CONSORT diagram. Proof-of-concept analyses were conducted once at the end of the trial on an intention-to-treat basis. We used SAS software and focused on confidence interval (CI) estimation, in accordance with a prespecified statistical analysis plan. Missing data were assumed to be missing completely at random, with only complete cases used in the analyses. Adjusted and unadjusted odds ratios, with 95% CIs, were calculated for each component of successful uptake of lifestyle advice using exact logistic regression for binary outcomes and proportional odds ordinal logistic regression for ordinal ones. Participation was further summarized by primary lifestyle factor. Drawing on these analyses, it would be feasible to proceed to a large-scale evaluation, modifying the protocol, based on acceptable (i) recruitment rates, (ii) retention rates, (iii) levels of missing data, (iv) a representative sample, (v) effective trial and treatment procedures, and (vi) proof of concept.

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Ethical Approval

All patients gave written informed consent, and the study was approved by the committee of the National Research Ethics Service for Yorkshire and the Humber (Leeds East) on March 12, 2012 (reference 12/YH/0086).

Trial registration: current controlled trials ISRCTN41781196.

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Feasibility Outcomes

In total, 887 patients (male/female: 53%/47%) were screened for eligibility over the 4-month recruitment period, and 132 (15%) were randomized at a rate of approximately 33 per month. Participants in the 2 arms of the trial were similar in terms of age, gender, ethnicity, and other baseline characteristics (Table 1).

We asked participants about their preferred method of follow-up. Post and phone were preferred at baseline and at 3 months. Home visits were preferred by 21% of respondents, but resources did not permit this option to be offered routinely. Of those who responded at 3 months, roughly 60% responded to the initial attempt to follow-up, 25% to the second attempt, and 15% to further attempts. At 6 months, roughly 40% responded to the initial attempt, 35% to the second attempt, and 25% to further attempts. Increased researcher input was needed to achieve the response rates at 6 months.

Active withdrawal of consent to follow-up was minimal (4%), and only 2 deaths occurred during the trial; the 2 major factors causing loss to follow-up were (a) nonreturn of postal questionnaires and (b) being unable to contact participants by telephone. At 3 months, loss to follow-up was 15% in those allocated to the new assessment and 12% in those allocated to the usual assessment. At 6 months, this was 17% and 18%, respectively. Questionnaires were missing in 38% of those allocated to the new assessment and 39% of those allocated to usual assessment at 3 months, and 23% and 24%, respectively, at 6 months. Questionnaire data were improved at 6 months by the introduction of telephone data collection.

Missing item data for CORE-10, SSQ, and EQ-5D were minimal. We explored the predictors of missing questionnaire data at 3 and 6 months as part of the feasibility analysis. We found some indication that treatment arm, gender, ethnicity, education, employment, living circumstances, and having a hobby all predicted missing outcomes at 3 months. Those with missing 3-month outcomes also had higher baseline CORE-10 scores. Nonwhite British men and participants living alone, less educated, and not employed were less likely to have missing data. Treatment arm and gender were not predictive of missing outcome data at 6 months. Those with missing 6-month outcomes were more likely to smoke, drink, diet, and exercise at baseline. They also had higher CORE-10 and SSQ scores at baseline and lower quality of life as measured by the EQ-5D thermometer.

All 132 patients (15%) (male/female: 61%:39%; mean age, 59 [SD, 15] years) randomized received the usual assessment, and 62 of 66 patients in the intervention arm received the individualized assessment as intended. In 1 case, this was due to a misunderstood allocation; the reasons why the remaining 3 did not receive the new assessment are unknown.

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Proof-of-Concept Analysis

Tables 2 and 3 show the descriptive and inferential statistics relating to the proof of concept. Of the patients in the individualized assessment arm, 27% accepted referral or self-referred by 3 months in comparison to 5% of those allocated to the usual assessment. By 6 months, percentages were similar (23% and 4%, respectively), suggesting a favorable effect on uptake for the intervention that was maintained over time in our sample (because simple randomization was used, the unadjusted odds ratio is primary, at 6.52 [95% CI, 1.66–37.82] at 3 months and 7.20 [95% CI, 1.48–69.84] at 6 months). Confidence intervals are wide, reflecting the preliminary nature of these findings.



Rates of initiation of lifestyle change also favored the individualized assessment arm but less clearly. At 3 months, 75% of the individualized assessment arm and 68% of the usual assessment arm had initiated changes in their lifestyle (unadjusted odds ratio, 1.38 [95% CI, 0.55–3.52]). At 6 months, the percentages were 85% and 75%, suggesting increased initiation of change over time in both arms, with the gap widening slightly (unadjusted odds ratio, 1.86 [95% CI, 0.64–5.77]).



For self-reported participation in lifestyle change, 73% of the individualized assessment arm had only initiated and 2% initiated and maintained change at 3 months compared with 65% and 2% of those allocated to the usual assessment (unadjusted odds ratio, 0.68 [95% CI, 0.30–1.53]). At 6 months, these percentages were 36% and 53% for the individualized assessment arm and 21% and 56% in the usual assessment arm (unadjusted odds ratio, 0.46 [95% CI, 0.22–0.98]). As such, more patients had initiated change in the individualized assessment arm at 6 months, but no more had maintained this change. Wide CIs again point to the degree of uncertainty around this conclusion.

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No association was found between quality of life (EQ-5D), psychological status (CORE-10), or social satisfaction at baseline and 3 months and uptake of referral at 3 months.

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Lifestyle plays a role in reducing the risk of CVD, but changes in diet, increasing exercise, quitting smoking or drinking less alcohol can be difficult to achieve, even in response to a major health event.17 The challenge of encouraging patients to follow recommendations for lifestyle change is usually tackled by nurses in primary or secondary care either with routine advice or by referral to a specific intervention. The evidence for the effectiveness of multiple risk factor interventions for primary prevention is not conclusive: randomized trials have shown some reduction in risk factors,18,19 but a Cochrane systematic review, updated in 2011, concluded they had no impact on mortality.20 This lack of consensus is not surprising, given that lifestyle interventions are complex, and their components vary, patients are heterogeneous, and achieving meaningful change across multiple factors is inherently difficult.

The first step on the path to lifestyle change is the uptake of advice or referral to an appropriate intervention. Checklists are useful instruments for the coordination of this process, and over the last few years, many versions of lifestyle assessment instruments and checklists have been developed. A Google search using the search term “lifestyle referral assessment checklist” yields more than 12 million results. Notwithstanding the proliferation of assessment instruments, there is little evidence underpinning their format or assessing their effectiveness. This is an important gap to close because referral rates reported in studies of routine practice are low.21 If simple and effective methods of initiating referrals can be developed, prevention of vascular events might be improved.

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The Feasibility Study

Our trial was designed to assess the feasibility of a full-scale trial of lifestyle referrals. Recruitment targets and a retention rate of 75% at 6 months were met, and recruitment targets could easily have been increased if research resources had permitted more people to be approached before they were discharged. The missing data target of less than 25% at 6 months was also met, and contrary to usual research experience, we found nonwhite British men and participants living alone, less educated, and not employed were less likely to have missing data. However, in common with many research studies, minority ethnic representation was low in our sample, and fewer participants were randomized from more socially deprived areas.22 We improved our follow-up rates at 6 months by introducing telephone interviews to collect questionnaire data if postal attempts failed. A dual approach to the collection of follow-up data would therefore be recommended in a full-scale trial.

We originally conceived the trial to test an intervention that could be relevant to both primary and secondary care settings and therefore opted to match the NHS Health Checks age range in our hospital sample. However, the participants’ profile and high number of exclusions based on age argue against an upper age limit in secondary care.

We reviewed the trial procedures and, subject to the issues identified in recruitment and the collection of follow-up data, found them suitable for delivering the intervention and conducting assessments. In our study, the intervention was delivered by a researcher; rollout to a full-scale trial would require a further assessment of the acceptability to ward staff of using the new, individualized assessment on a routine basis.

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Proof of Concept

The feasibility trial produced some interesting but preliminary findings in the proof-of-concept analysis. Most patients admitted to hospital with a diagnosed cardiac event are referred to cardiac rehabilitation programs, but the participants in this study were not because they had no confirmed cardiac diagnosis. All participants had at least 1 risk factor for CVD, and many expressed concerns about their weight. Introduction of an individualized lifestyle assessment with a built-in referral mechanism could be a useful intervention in this group of patients, many of whom are likely to benefit from lifestyle change but are not eligible for mainstream rehabilitation. EXERT (Exercise Evaluation Randomised Trial), for example, found that referral for tailored advice, supported by written materials, including details of locally available facilities, supplemented by detailed assessments was effective in increasing physical activity.23

When we compared the individualized assessment with the usual assessment, we found that referrals to lifestyle change programs or a self-managed program of change and the initiation of change appear to be increased by our individualized approach. However, we found no association between the measures of mood and uptake of referral and lifestyle change, although there was some indication that participants were more likely to accept referral and attempt lifestyle change if they scored higher for mood symptoms on CORE-10. This is an interesting observation because the evidence from our review identified mood disturbance as a barrier to lifestyle change, not a facilitator.9 This dissonance may arise from small sample size or the trial intervention. Participants may have been unsettled by their hospital event and were therefore more likely to try and address the factors that contributed to their admission.

By 6 months, there was no difference between participants in the arms in terms of sustained lifestyle change.

Current theory does not deal adequately with the complexities of maintaining change so interventions based on them may not be successful.5 We need to design interventions that work in the context of peoples’ lives and that overcome the barriers to the maintenance of change in the longer term. For example, instigating organizational change to raise the issue of lifestyle change with patients in noncontingent appointments and offer advice is 1 approach, but advice alone is not enough. A recent randomized trial showed that enduring lifestyle change was unlikely after a single routine consultation even with a clinician trained in lifestyle counseling without additional intervention.24 A full-scale trial should consider the collection and analysis of longitudinal data from the lifestyle-change programs that are accessed to track newly referred patients prospectively through the lifestyle change process. An evaluation of the effectiveness of interventions would provide further evidence to inform future approaches.

Advice and interventions also need to be backed up by sustained programs of support, but this is clearly difficult to achieve in healthcare systems where resources are limited and the evidence for effective methods to maintain lifestyle change is lacking. Our synthesis of qualitative evidence showed that maintenance of change is, by and large, affected by the same factors that influence uptake and participation in lifestyle change programs.25 If these factors are addressed at an early stage and patients referred to appropriate lifestyle change interventions, there may be a better chance of change being maintained in the longer term. This hypothesis was not supported by the findings of this feasibility study and would need to be tested in a full-scale trial.

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Limitations of the Study

The original study design proposed that a researcher would recruit and randomize patients and collect data, whereas lifestyle assessment and referrals would be conducted by ward staff. This proved difficult to implement, and in the final study protocol (as approved by the ethics committee), all assessments were to be conducted by a researcher. Consequently, we were unable to evaluate the feasibility of introducing the new assessment as part of routine practice in the event of a full-scale trial.

In practice, the group of patients for which this study was designed often has very short stays in hospital, and some are discharged before they receive any advice about lifestyle. It was a condition of ethical approval that patients in the usual assessment arm should be given a Leeds Let’s Change contact card to ensure they were not disadvantaged by participating in the study. We therefore defined usual assessment as brief lifestyle advice plus the contact card. This is a limitation of the study, but its effect would be to reduce the difference between the assessments; nevertheless, the proof-of-concept study showed that the new assessment improved uptake of referrals or lifestyle advice compared with the standardized usual assessment.

There was some loss to follow-up at 3 months using postal questionnaire data collection. This was addressed at the 6-month follow-up point by using the telephone interview to complete the questionnaires with patients if they were willing to do so. It proved to be a more reliable method, reducing not only loss to follow-up but also missing data compared with the questionnaires returned by post. We would therefore recommend that either telephone follow-up or face-to-face interviews should be included in the design of a full-scale trial.

Finally, we acknowledge that self-reported outcomes are prone to bias and inaccuracy, but this study was designed to allow participants to choose the method of lifestyle change they preferred including self-managed lifestyle change. In practice, therefore, outcomes would be difficult to monitor, and the resources required to track uptake and attendance at a wide range of lifestyle interventions would be prohibitive.

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This feasibility trial shows that before embarking on a full-scale trial we need to consider 2 things: first, the implications of an assessment instrument and its aims and acceptability in routine practice, and second, how the process of change can be optimized in order to produce long-term benefit for patients. The public health benefits of success are obvious, but we need to ensure that health policy and the systems that support its delivery work closely together to find methods that will have a positive impact on our health system.26

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What’s New and Important?

  • A lifestyle referral assessment that identifies individual barriers in order to produce a tailored plan for lifestyle change.
  • Referrals to lifestyle change programs or a self-managed program of change and the initiation of change are improved using an individualized approach.
  • Advice needs to be backed up by sustained programs of support to maintain lifestyle change.
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cardiovascular risk factors; lifestyle and behavior change; randomized controlled trial

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