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Introduction Smoking during pregnancy is harmful to unborn babies, infants and women. Nicotine replacement therapy (NRT) is offered as the usual stop-smoking support in the UK. However, this is often used in insufficient doses, intermittently or for too short a time to be effective. This randomised controlled trial (RCT) explores whether a bespoke intervention, delivered in pregnancy, improves adherence to NRT and is effective and cost-effective for promoting smoking cessation.Methods and analysis A two-arm parallel-group RCT was conducted for pregnant women aged ≥16 years and who smoke ≥1 daily cigarette (pre-pregnancy smoked ≥5) and who agree to use NRT in an attempt to quit. Recruitment is from antenatal care settings and via social media adverts. Participants are randomised using blocked randomisation with varying block sizes, stratified by gestational age (

Background During a quit attempt, cues from a smoker’s environment are a major cause of brief smoking lapses, which increase the risk of relapse. Quit Sense is a theory-guided Just-In-Time Adaptive Intervention smartphone app, providing smokers with the means to learn about their environmental smoking cues and provides ‘in the moment’ support to help them manage these during a quit attempt. Objective To undertake a feasibility randomised controlled trial to estimate key parameters to inform a definitive randomised controlled trial of Quit Sense. Design A parallel, two-arm randomised controlled trial with a qualitative process evaluation and a ‘Study Within A Trial’ evaluating incentives on attrition. The research team were blind to allocation except for the study statistician, database developers and lead researcher. Participants were not blind to allocation. Setting Online with recruitment, enrolment, randomisation and data collection (excluding manual telephone follow-up) automated through the study website. Participants Smokers (323 screened, 297 eligible, 209 enrolled) recruited via online adverts on Google search, Facebook and Instagram. Interventions Participants were allocated to ‘usual care’ arm (n = 105; text message referral to the National Health Service SmokeFree website) or ‘usual care’ plus Quit Sense (n = 104), via a text message invitation to install the Quit Sense app. Main outcome measures Follow-up at 6 weeks and 6 months post enrolment was undertaken by automated text messages with an online questionnaire link and, for non-responders, by telephone. Definitive trial progression criteria were met if a priori thresholds were included in or lower than the 95% confidence interval of the estimate. Measures included health economic and outcome data completion rates (progression criterion #1 threshold: ≥ 70%), including biochemical validation rates (progression criterion #2 threshold: ≥ 70%), recruitment costs, app installation (progression criterion #3 threshold: ≥ 70%) and engagement rates (progression criterion #4 threshold: ≥ 60%), biochemically verified 6-month abstinence and hypothesised mechanisms of action and participant views of the app (qualitative). Results Self-reported smoking outcome completion rates were 77% (95% confidence interval 71% to 82%) and health economic data (resource use and quality of life) 70% (95% CI 64% to 77%) at 6 months. Return rate of viable saliva samples for abstinence verification was 39% (95% CI 24% to 54%). The per-participant recruitment cost was £19.20, which included advert (£5.82) and running costs (£13.38). In the Quit Sense arm, 75% (95% CI 67% to 83%; 78/104) installed the app and, of these, 100% set a quit date within the app and 51% engaged with it for more than 1 week. The rate of 6-month biochemically verified sustained abstinence, which we anticipated would be used as a primary outcome in a future study, was 11.5% (12/104) in the Quit Sense arm and 2.9% (3/105) in the usual care arm (estimated effect size: adjusted odds ratio = 4.57, 95% CIs 1.23 to 16.94). There was no evidence of between-arm differences in hypothesised mechanisms of action. Three out of four progression criteria were met. The Study Within A Trial analysis found a £20 versus £10 incentive did not significantly increase follow-up rates though reduced the need for manual follow-up and increased response speed. The process evaluation identified several potential pathways to abstinence for Quit Sense, factors which led to disengagement with the app, and app improvement suggestions. Limitations Biochemical validation rates were lower than anticipated and imbalanced between arms. COVID-19-related restrictions likely limited opportunities for Quit Sense to provide location tailored support. Conclusions The trial design and procedures demonstrated feasibility and evidence was generated supporting the efficacy potential of Quit Sense. Future work Progression to a definitive trial is warranted providing improved biochemical validation rates. Trial registration This trial is registered as ISRCTN12326962. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: 17/92/31) and is published in full in Public Health Research; Vol. 12, No. 4. See the NIHR Funding and Awards website for further award information. Plain language summary Smokers often fail to quit because of urges to smoke triggered by their surroundings (e.g. being around smokers). We developed a smartphone app (‘Quit Sense’) which learns about an individual’s surroundings and locations where they smoke. During a quit attempt, Quit Sense uses in-built sensors to identify when smokers are in those locations and sends ‘in the moment’ advice to help prevent them from smoking. We ran a feasibility study to help plan for a future large study to see if Quit Sense helps smokers to quit. This feasibility study was designed to tell us how many participants complete study measures; recruitment costs; how many participants install and use Quit Sense; and estimate whether Quit Sense may help smokers to stop and how it might do this. We recruited 209 smokers using online adverts on Google search, Facebook and Instagram, costing £19 per participant. Participants then had an equal chance of receiving a web link to the National Health Service SmokeFree website (‘usual care group’) or receive that same web link plus a link to the Quit Sense app (‘Quit Sense group’). Three-quarters of the Quit Sense group installed the app on their phone and half of these used the app for more than 1 week. We followed up 77% of participants at 6 months to collect study data, though only 39% of quitters returned a saliva sample for abstinence verification. At 6 months, more people in the Quit Sense group had stopped smoking (12%) than the usual care group (3%). It was not clear how the app helped smokers to quit based on study measures, though interviews found that the process of training the app helped people quit through learning about what triggered their smoking behaviour. The findings support undertaking a large study to tell us whether Quit Sense really does help smokers to quit. Scientific summary Background Three million UK smokers attempt to stop smoking each year, but over 80% relapse. A lapse (any smoking) early on in a quit attempt is strongly associated with subsequent relapse back to smoking. Approximately half of all lapses are due to environmental smoking cues which can elicit cravings to smoke, such as the presence of cigarettes or being in a location which a smoker associates with smoking. Few interventions are effective at targeting cue-induced cravings. Smokers are more likely to prevent lapses if they better understand their smoking cues and use lapse prevention strategies, such as controlled deep breathing or avoiding other smokers, to combat these. This would likely help them avoid or cope with cue-induced cravings, but smokers typically lack skills in applying these effectively. If smokers trying to quit used effective lapse prevention strategies, this would very likely increase their chances of success. With patient and public involvement, we developed, refined and piloted a theory-guided Just-In-Time Adaptive Intervention smartphone app called Quit Sense that provides support to help smokers manage environmental cues to smoke as they arise. Pilot studies have shown that Quit Sense can provide ‘in the moment’ support to smokers, including lapse prevention strategies, and that users will engage with the app and find it acceptable. As Quit Sense is such a novel intervention, before a ‘definitive’ randomised controlled trial (RCT) can be conducted to test effectiveness, it is important to first undertake a RCT to establish whether such a study might be feasible. Objectives The main objective was to conduct a feasibility RCT of Quit Sense to inform a definitive effectiveness trial, by estimating: completion rates for the anticipated primary outcome for a full trial (6-month self-reported abstinence with biochemical validation, based on the Russell standard); usual care arm cessation rate; cost of recruitment using online advertising; rates of app installation, use and acceptability; completion of smoking cessation-related resource use and quality-of-life data; intervention effect on anticipated primary outcome; intervention effect on hypothesised mechanisms of action of app at 6 weeks post enrolment; participant views of the app, as part of a qualitative process evaluation. Design A parallel, two-arm RCT with an embedded qualitative interview process evaluation was undertaken. The evaluation included a preliminary cost-effectiveness analysis and a nested randomised study [Study Within A Trial (SWAT)] assessing the effects of different financial incentives on 6-month follow-up rates. Setting The study setting was online and trial procedures were primarily automated. Participants Participants were recruited via online adverts on Google search, Facebook and Instagram, screened for eligibility on the study website and enrolled if they were regular smokers, aged 16 years and above, were willing to make a quit attempt and owned an Android smartphone. Interventions After completing the baseline questionnaire participants were then randomly allocated to a ‘usual care’ arm (text message referral to NHS SmokeFree website) or a ‘usual care’ plus Quit Sense arm, via a text message invitation to install the Quit Sense app. The Quit Sense app required users to set a quit date and then, leading up to their quit date, alongside other support features, invited them to report their smoking in real time and indicate the presence of key environmental smoking cues using a smoking behaviour logging tool. Once their quit date arrived, the app used location sensing and what it had learnt about the individual’s smoking behaviour to tailor the timing and content of support messages when they spent time in self-identified high-risk locations. The support and advice aimed to help smokers learn about their smoking behaviour, prepare for their quit attempt and promoted the use of effective lapse prevention strategies during their quit attempt. Main outcomes measures All participants were contacted at 6-week and 6-month follow-up. This was done initially by text message with an embedded link to the follow-up questionnaires or, if no response, manually by telephone. As part of a SWAT, participants underwent secondary randomisation to receive either a £10 or £20 incentive for completion of the 6-month questionnaire. Four progression criteria and corresponding thresholds for seeking to undertake a definitive trial were set a priori. Criteria were met if each threshold was included in or lower than the 95% confidence interval (CI) of the estimate. Trial measures included health economic and outcome data completion rates (progression criterion #1 threshold: ≥ 70%), including biochemical validation rates (progression criterion #2 threshold: ≥ 70%), recruitment costs, app installation (progression criterion #3 threshold: ≥ 70%) and engagement rates (progression criterion #4 threshold: ≥ 60%), the app’s effect on biochemically verified abstinence at 6 months (anticipated primary outcome of definitive trial) and hypothesised mechanisms of action. The qualitative process evaluation sought to identify participants’ views of the trial and the Quit Sense app. The protocol and statistical and health economics analysis plan were pre-specified and published (open access). Results Of the people screened (N = 323), 299 (93%) were eligible and 209 (65% of screened) were consented and randomised either to the usual care arm (n = 105) or to the Quit Sense arm (n = 104). Completion of self-reported smoking questions was 71% (149/209; 95% CI 65% to 77%) and 77% (160/209; 95% CI 71% to 82%) at 6 weeks and 6 months, respectively, and at 6 months 70% provided both cessation support resource use data and EuroQol-5 Dimensions five level (EQ-5D-5L) data. Among those self-reporting abstinence at 6 months follow-up, 39% (95% CI 24% to 54%) returned a viable sample for biochemical verification, although return rates were higher in the Quit Sense than the usual care arm (52% vs. 19%). Online recruitment was completed successfully within the planned 6-week period, split into two campaigns, with a per-participant cost of £19.20, split into advert (£5.82) and running costs (£13.38). In the Quit Sense arm, 75% (95% CI 67% to 83%) of participants installed the app and, of these, 100% set a quit date within the app and 51% (95% CI 39% to 63%) engaged with it for more than 1 week. At final follow-up, the rate of 6-month biochemically verified sustained abstinence, which we anticipated would be used as a primary outcome in a future study, was 11.5% (12/104) in the Quit Sense arm and 2.9% (3/105) in the usual care arm (estimated effect size: adjusted odds ratio = 4.57, 95% CI 1.23 to 16.94). Similar effects were observed for biochemically verified secondary abstinence outcomes at 6-month follow-up and sensitivity analyses. Effect sizes were smaller and non-significant for self-report only abstinence and there was no evidence of a between-arm difference in abstinence at 6-week follow-up. Participants in the Quit Sense arm had higher rates of lapse avoidance in the first 2 weeks of their quit attempt or post enrolment compared to usual care though this was not statistically significant (29.6% vs. 19.2%; p = 0.14). There was no evidence of between-arm differences in hypothesised mechanisms of action of the app, including the mean frequency of lapse prevention strategy use [mean difference (MD) −0.07; p = 0.46], smoking cessation self-efficacy (MD 0.18; p = 0.39), strength (p = 0.23) and frequency (p = 0.83) of urges to smoke or the Wisconsin Inventory of Smoking Dependence Motives subscales of automaticity (p = 0.51) and associative processes (p = 0.58). The qualitative process evaluation identified several potential pathways to abstinence among Quit Sense arm participants. Interviewed participants reported finding the insights gained from engaging with the smoking behaviour learning tool before their quit attempt started particularly valuable. They reported that this reinforced their commitment to quit, helped them better understand the drivers of their smoking behaviour and challenged the need for them to smoke. Some also reported finding regular and location-specific support messages encouraging and motivational and that this reinforced the goal of quitting and made them feel equipped when they spent time in locations that they used to smoke in. Participants highlighted several factors which led to disengagement with the app, including relapse, no longer feeling they needed support, not finding the app met their needs and technical issues. Participants also provided suggestions for app improvement relating to logging smoking, adding gamification elements and improved support triggering. Interviewed participants from both arms highlighted how COVID-19 measures had affected their smoking behaviour and restricted the time they spent outside of their home, which would have had implications for location-based cessation support. In terms of the main cost-drivers, e-cigarettes/vaporisers and nicotine replacement therapy accounted for more than 70% of the total non-intervention costs. The total intervention cost (recruitment advertising and maintaining the Quit Sense app) was estimated to be £28.51 per participant. In both groups, the mean EQ-5D-5L score at both 6-week and 6-month follow-up was lower than that at baseline. A preliminary cost-effectiveness analysis using EQ-5D-5L score as the outcome estimated that the intervention was both more costly and less effective, compared to standard care, though there was no significant difference in cost or effect between the two groups. The SWAT analysis indicated that increasing the incentive for completing follow-up from £10 to £20 did not increase response rates at 6 months (74% vs. 79%; p = 0.36) but did reduce the proportion of participants requiring manual follow-up (62% vs. 46%; p = 0.018) and the median response time to responding (15 days vs. 7 days; p = 0.016). Conclusions The Quit Sense RCT design and procedures demonstrated feasibility and generated preliminary efficacy evidence of the app on abstinence at 6-month follow-up, although how the app may achieve this is not clear. Three out of the four pre-specified feasibility progression criteria for moving to a definitive trial – completion rate of self-reported abstinence at final follow-up and the rate of Quit Sense installation and engagement – were met. The return of saliva samples among quitters was lower than anticipated, though this can likely be increased in a future trial through increased incentivisation and enhanced procedures. Progression to a definitive trial is warranted. Trial registration This trial is registered as ISRCTN12326962. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: 17/92/31) and is published in full in Public Health Research; Vol. 12, No. 4. See the NIHR Funding and Awards website for further award information.

Introduction There is a lack of evidence that the benefits of screening for atrial fibrillation (AF) outweigh the harms. Following the completion of the Screening for Atrial Fibrillation with ECG to Reduce stroke (SAFER) pilot trial, the aim of the main SAFER trial is to establish whether population screening for AF reduces incidence of stroke risk.Methods and analysis Approximately 82 000 people aged 70 years and over and not on oral anticoagulation are being recruited from general practices in England. Patients on the palliative care register or residents in a nursing home are excluded. Eligible people are identified using electronic patient records from general practices and sent an invitation and consent form to participate by post. Consenting participants are randomised at a ratio of 2:1 (control:intervention) with clustering by household. Those randomised to the intervention arm are sent an information leaflet inviting them to participate in screening, which involves use of a handheld single-lead ECG four times a day for 3 weeks. ECG traces identified by an algorithm as possible AF are reviewed by cardiologists. Participants with AF are seen by a general practitioner for consideration of anticoagulation. The primary outcome is stroke. Major secondary outcomes are: death, major bleeding and cardiovascular events. Follow-up will be via electronic health records for an average of 4 years. The primary analysis will be by intention-to-treat using time-to-event modelling. Results from this trial will be combined with follow-up data from the cluster-randomised pilot trial by fixed-effects meta-analysis.Ethics and dissemination The London—Central National Health Service Research Ethics Committee (19/LO/1597) provided ethical approval. Dissemination will include public-friendly summaries, reports and engagement with the UK National Screening Committee.Trial registration number ISRCTN72104369.

Introduction Physical activity (PA) is protective against type 2 diabetes (T2D). However, data on pragmatic long-term interventions to reduce the risk of developing T2D via increased PA are lacking. This study investigated the cost-effectiveness of a pragmatic PA intervention in a multiethnic population at high risk of T2D.Materials and methods We adapted the School for Public Health Research diabetes prevention model, using the PROPELS trial data and analyses of the NAVIGATOR trial. Lifetime costs, lifetime quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) were calculated for each intervention (Walking Away (WA) and Walking Away Plus (WA+)) versus usual care and compared with National Institute for Health and Care Excellence’s willingness-to-pay of £20 000–£30 000 per QALY gained. We conducted scenario analyses on the outcomes of the PROPELS trial data and a threshold analysis to determine the change in step count that would be needed for the interventions to be cost-effective.Results Estimated lifetime costs for usual care, WA, and WA+ were £22 598, £23 018, and £22 945, respectively. Estimated QALYs were 9.323, 9.312, and 9.330, respectively. WA+ was estimated to be more effective and cheaper than WA. WA+ had an ICER of £49 273 per QALY gained versus usual care. In none of our scenario analyses did either WA or WA+ have an ICER below £20 000 per QALY gained. Our threshold analysis suggested that a PA intervention costing the same as WA+ would have an ICER below £20 000/QALY if it were to achieve an increase in step count of 500 steps per day which was 100% maintained at 4 years.Conclusions We found that neither WA nor WA+ was cost-effective at a limit of £20 000 per QALY gained. Our threshold analysis showed that interventions to increase step count can be cost-effective at this limit if they achieve greater long-term maintenance of effect.Trial Registration number ISRCTN registration: ISRCTN83465245: The PRomotion Of Physical activity through structuredEducation with differing Levels of ongoing Support for those with pre-diabetes (PROPELS)https://doi.org/10.1186/ISRCTN83465245.

BackgroundInsufficient physical activity is a public health concern. New technologies may improve physical activity levels and enable the identification of its predictors with high accuracy. The Precious smartphone app was developed to investigate the effect of specific modular intervention elements on physical activity and examine theory-based predictors within individuals. ObjectiveThis study pilot-tested a fully automated factorial N-of-1 randomized controlled trial (RCT) with the Precious app and examined whether digitalized motivational interviewing (dMI) and heart rate variability–based biofeedback features increased objectively recorded steps. The secondary aim was to assess whether daily self-efficacy and motivation predicted within-person variability in daily steps. MethodsIn total, 15 adults recruited from newspaper advertisements participated in a 40-day factorial N-of-1 RCT. They installed 2 study apps on their phones: one to receive intervention elements and one to collect ecological momentary assessment (EMA) data on self-efficacy, motivation, perceived barriers, pain, and illness. Steps were tracked using Xiaomi Mi Band activity bracelets. The factorial design included seven 2-day biofeedback interventions with a Firstbeat Bodyguard 2 (Firstbeat Technologies Ltd) heart rate variability sensor, seven 2-day dMI interventions, a wash-out day after each intervention, and 11 control days. EMA questions were sent twice per day. The effects of self-efficacy, motivation, and the interventions on subsequent steps were analyzed using within-person dynamic regression models and aggregated data using longitudinal multilevel modeling (level 1: daily observations; level 2: participants). The analyses were adjusted for covariates (ie, within- and between-person perceived barriers, pain or illness, time trends, and recurring events). ResultsAll participants completed the study, and adherence to activity bracelets and EMA measurements was high. The implementation of the factorial design was successful, with the dMI features used, on average, 5.1 (SD 1.0) times of the 7 available interventions. Biofeedback interventions were used, on average, 5.7 (SD 1.4) times out of 7, although 3 participants used this feature a day later than suggested and 1 did not use it at all. Neither within- nor between-person analyses revealed significant intervention effects on step counts. Self-efficacy predicted steps in 27% (4/15) of the participants. Motivation predicted steps in 20% (3/15) of the participants. Aggregated data showed significant group-level effects of day-level self-efficacy (B=0.462; P

Introduction Atrial fibrillation (AF) is a common arrhythmia associated with 30% of strokes, as well as other cardiovascular disease, dementia and death. AF meets many criteria for screening, but there is limited evidence that AF screening reduces stroke. Consequently, no countries recommend national screening programmes for AF. The Screening for Atrial Fibrillation with ECG to Reduce stroke (SAFER) trial aims to determine whether screening for AF is effective at reducing risk of stroke. The aim of the pilot study is to assess feasibility of the main trial and inform implementation of screening and trial procedures.Methods and analysis SAFER is planned to be a pragmatic randomised controlled trial (RCT) of over 100 000 participants aged 70 years and over, not on long-term anticoagulation therapy at baseline, with an average follow-up of 5 years. Participants are asked to record four traces every day for 3 weeks on a hand-held single-lead ECG device. Cardiologists remotely confirm episodes of AF identified by the device algorithm, and general practitioners follow-up with anticoagulation as appropriate. The pilot study is a cluster RCT in 36 UK general practices, randomised 2:1 control to intervention, recruiting approximately 12 600 participants. Pilot study outcomes include AF detection rate, anticoagulation uptake and other parameters to incorporate into sample size calculations for the main trial. Questionnaires sent to a sample of participants will assess impact of screening on psychological health. Process evaluation and qualitative studies will underpin implementation of screening during the main trial. An economic evaluation using the pilot data will confirm whether it is plausible that screening might be cost-effective.Ethics and dissemination The London—Central Research Ethics Committee (19/LO/1597) and Confidentiality Advisory Group (19/CAG/0226) provided ethical approval. Dissemination will be via publications, patient-friendly summaries, reports and engagement with the UK National Screening Committee.Trial registration number ISRCTN72104369.

Abstract Background Physical activity is associated with a reduced risk of type 2 diabetes and cardiovascular disease but limited evidence exists for the sustained promotion of increased physical activity within diabetes prevention trials. The aim of the study was to investigate the long-term effectiveness of the Walking Away programme, an established group-based behavioural physical activity intervention with pedometer use, when delivered alone or with a supporting mHealth intervention. Methods Those at risk of diabetes (nondiabetic hyperglycaemia) were recruited from primary care, 2013–2015, and randomised to (1) Control (information leaflet); (2) Walking Away (WA), a structured group education session followed by annual group-based support; or (3) Walking Away Plus (WAP), comprising WA annual group-based support and an mHealth intervention delivering tailored text messages supported by telephone calls. Follow-up was conducted at 12 and 48 months. The primary outcome was accelerometer measured ambulatory activity (steps/day). Change in primary outcome was analysed using analysis of covariance with adjustment for baseline, randomisation and stratification variables. Results One thousand three hundred sixty-six individuals were randomised (median age = 61 years, ambulatory activity = 6638 steps/day, women = 49%, ethnic minorities = 28%). Accelerometer data were available for 1017 (74%) individuals at 12 months and 993 (73%) at 48 months. At 12 months, WAP increased their ambulatory activity by 547 (97.5% CI 211, 882) steps/day compared to control and were 1.61 (97.5% CI 1.05, 2.45) times more likely to achieve 150 min/week of moderate-to-vigorous physical activity. Differences were not maintained at 48 months. WA was no different to control at 12 or 48 months. Secondary anthropometric and health outcomes were largely unaltered in both intervention groups apart from small reductions in body weight in WA (~ 1 kg) at 12- and 48-month follow-up. Conclusions Combining a pragmatic group-based intervention with text messaging and telephone support resulted in modest changes to physical activity at 12 months, but changes were not maintained at 48 months. Trial registration ISRCTN 83465245 (registered on 14 June 2012).

Abstract The PAM intervention is a behavioural intervention to support adherence to anti-hypertensive medications and therefore to lower blood pressure. This feasibility trial recruited 101 nonadherent patients (54% male, mean age 65.8 years) with hypertension and high blood pressure from nine general practices in the UK. The trial had 15.5% uptake and 7.9% attrition rate. Patients were randomly allocated to two groups: the intervention group (n = 61) received the PAM intervention as an adjunct to usual care; the control group (n = 40) received usual care only. At 3 months, biochemically validated medication adherence was improved by 20% (95% CI 3–36%) in the intervention than control, and systolic blood pressure was reduced by 9.16 mmHg (95% CI 5.69–12.64) in intervention than control. Improvements in medication adherence and reductions in blood pressure suggested potential intervention effectiveness. For a subsample of patients, improvements in medication adherence and reductions in full lipid profile (cholesterol 1.39 mmol/mol 95% CI 0.64–1.40) and in glycated haemoglobin (3.08 mmol/mol, 95% CI 0.42–5.73) favoured the intervention. A larger trial will obtain rigorous evidence about the potential clinical effectiveness and cost-effectiveness of the intervention. Trial registration Trial date of first registration 28/01/2019. ISRCTN74504989. https://doi.org/10.1186/ISRCTN74504989 .

Abstract Background Approximately 40% of cancers could be prevented if people lived healthier lifestyles. We have developed a theory-based brief intervention to share personalised cancer risk information and promote behaviour change within primary care. This study aimed to assess the feasibility and acceptability of incorporating this intervention into primary care consultations. Method Patients eligible for an NHS Health Check or annual chronic disease review at five general practices were invited to participate in a non-randomised pilot study. In addition to the NHS Health Check or chronic disease review, those receiving the intervention were provided with their estimated risk of developing the most common preventable cancers alongside tailored behaviour change advice. Patients completed online questionnaires at baseline, immediately post-consultation and at 3-month follow-up. Consultations were audio/video recorded. Patients (n = 12) and healthcare professionals (HCPs) (n = 7) participated in post-intervention qualitative interviews that were analysed using thematic analysis. Results 62 patients took part. Thirty-four attended for an NHS Health Check plus the intervention; 7 for a standard NHS Health Check; 16 for a chronic disease review plus the intervention; and 5 for a standard chronic disease review. The mean time for delivery of the intervention was 9.6 min (SD 3) within NHS Health Checks and 9 min (SD 4) within chronic disease reviews. Fidelity of delivery of the intervention was high. Data from the questionnaires demonstrates potential improvements in health-related behaviours following the intervention. Patients receiving the intervention found the cancer risk information and lifestyle advice understandable, useful and motivating. HCPs felt that the intervention fitted well within NHS Health Checks and facilitated conversations around behaviour change. Integrating the intervention within chronic disease reviews was more challenging. Conclusions Incorporating a risk-based intervention to promote behaviour change for cancer prevention into primary care consultations is feasible and acceptable to both patients and HCPs. A randomised trial is now needed to assess the effect on health behaviours. When designing that trial, and other prevention activities within primary care, it is necessary to consider challenges around patient recruitment, the HCP contact time needed for delivery of interventions, and how best to integrate discussions about disease risk within routine care.

Abstract Aims and objectives This paper describes a pilot non-randomised controlled study of a highly tailored 56-day text messaging and smartphone app prototype intervention to increase adherence to anti-hypertensive medication in primary care. The aim of this study was to evaluate the acceptability of the intervention and obtain patients’ views about the intervention content, the delivery mode, and the mechanisms by which the intervention supported medication adherence. Methods Patients diagnosed with hypertension were invited and recruited to the study via general practice text messages and attended a face to face meeting with a member of the researcher team. Participants were asked to test the text messaging intervention for 28 consecutive days and switch to the smartphone app for 28 more days. Participants completed baseline and follow-up questionnaires and took part in semi-structured telephone interviews. Digital log files captured patients’ engagement with the intervention. Participant transcripts were analysed using thematic analysis. Descriptive statistics were used to summarise data from questionnaires and log files. A mixed methods analysis generated data to respond to the research questions. Results Seventy-nine patients expressed interest to participate in this study, of whom 23 (64% male, 82% above 60 years old) were registered to take part. With one drop-out, 22 participants tested the text messaging delivery mode (with 20 being interviewed) and four of them (17%) switched to the app (with 3 being interviewed). All participants engaged and interacted with the text messages and app notifications, and all participants found the intervention content and delivery mode acceptable. They also self-reported that the interactive elements of the intervention motivated them to take their medications as prescribed. Conclusion This study provides evidence that the digital intervention is acceptable by hypertensive patients recruited in primary care. Future research could usefully investigate its feasibility and effectiveness using rigorous research methods. Trial registration ISRCTN12805654

Objectives To explore patients’ and healthcare practitioners’ (HCPs) views about non-adherence to hypertension medication and potential content of a combined very brief face-to-face discussion (VBI) and digital intervention (DI).Methods A qualitative study (N=31): interviews with patients with hypertension (n=6) and HCPs (n=11) and four focus groups with patients with hypertension (n=14). Participants were recruited through general practices in Eastern England and London. Topic guides explored reasons for medication non-adherence and attitudes towards a potential intervention to support adherence. Stimuli to facilitate discussion included example SMS messages and smartphone app features, including mobile sensing. Analysis was informed methodologically by the constant comparative approach and theoretically by perceptions and practicalities approach.Results Participants’ overarching explanations for non-adherence were non-intentional (forgetting) and intentional (concerns about side effects, reluctance to medicate). These underpinned their views on intervention components: messages that targeted forgetting medication or obtaining prescriptions were considered more useful than messages providing information on consequences of non-adherence. Tailoring the DI to the individuals’ needs, regarding timing and number of messages, was considered important for user engagement. Patients wanted control over the DI and information about data use associated with any location sensing. While the DI was considered limited in its potential to address intentional non-adherence, HCPs saw the potential for a VBI in addressing this gap, if conducted in a non-judgemental manner. Incorporating a VBI into routine primary care was considered feasible, provided it complemented existing GP practice software and HCPs received sufficient training.Conclusions A combined VBI-DI can potentially address intentional and non-intentional reasons for non-adherence to hypertension medication. For optimal engagement, recommendations from this work include a VBI conducted in a non-judgmental manner and focusing on non-intentional factors, followed by a DI that is easy-to-use, highly tailored and with provision of data privacy details about any sensing technology used.

Background: Medication adherence can prevent health risks, but many patients do not adhere to their prescribed treatment. Our recent trial found that a digital intervention was effective at improving medication adherence in non-adherent patients with Hypertension or Type 2 Diabetes; but we do not know how it brought about behavioural changes. This research is a post-trial process evaluation of the mechanism by which the intervention achieved its intended effects.Methods: A mixed methods design with quantitative and qualitative evidence synthesis was employed. Data was generated by two studies. Study 1 used questionnaires to measure the underlying mechanisms of and the medication adherence behaviour, and digital logfiles to objectively capture intervention effects on the process of behaviour change. Multilevel regression analysis on 57 complete intervention group cases tested the effects of the intervention at modifying the mechanism of behaviour change and in turn at improving medication adherence. Study 2 used in depth interviews with a subsample of 20 intervention patients, and eight practise nurses. Thematic analysis provided evidence about the overarching intervention functions and recommendations to improve intervention reach and impact in primary care.Results: Study 1 found that intervention effectiveness was significantly associated with positive changes in the underlying mechanisms of behaviour change (R2 = 0.26, SE = 0.98, P = 0.00); and this effect was heightened twofold when the tailored intervention content and reporting on medication taking (R2 = 0.59, SE = 0.74, P = 0.00) was interested into the regression model. Study 2 suggested that the intervention supported motivation and ability to adherence, although clinically meaningful effects would require very brief medication adherence risk appraisal and signposting to ongoing digitally delivered behavioural support during clinical consultations.Conclusion: This post trial process evaluation used objective methods to capture the intervention effect on the mechanisms of behaviour change to explain intervention effectiveness, and subjective accounts to explore the circumstances under which these effects were achieved. The results of this process evaluation will inform a large scale randomised controlled trial in primary care.

Background: Type 2 diabetes is a leading cause of mortality globally and accounts for significant health resource expenditure. Increased physical activity can reduce the risk of diabetes. However, the longer-term clinical effectiveness and cost-effectiveness of physical activity interventions in those at high risk of type 2 diabetes is unknown. Objectives: To investigate whether or not Walking Away from Diabetes (Walking Away) – a low-resource, 3-hour group-based behavioural intervention designed to promote physical activity through pedometer use in those with prediabetes – leads to sustained increases in physical activity when delivered with and without an integrated mobile health intervention compared with control. Design: Three-arm, parallel-group, pragmatic, superiority randomised controlled trial with follow-up conducted at 12 and 48 months. Setting: Primary care and the community. Participants: Adults whose primary care record included a prediabetic blood glucose measurement recorded within the past 5 years [HbA1c ≥ 42 mmol/mol (6.0%),

Background: Measurement can affect the people being measured; for example, asking people to complete a questionnaire can result in changes in behaviour (the ‘question–behaviour effect’). The usual methods of conduct and analysis of randomised controlled trials implicitly assume that the taking of measurements has no effect on research participants. Changes in measured behaviour and other outcomes due to measurement reactivity may therefore introduce bias in otherwise well-conducted randomised controlled trials, yielding incorrect estimates of intervention effects, including underestimates. Objectives: The main objectives were (1) to promote awareness of how and where taking measurements can lead to bias and (2) to provide recommendations on how best to avoid or minimise bias due to measurement reactivity in randomised controlled trials of interventions to improve health. Methods: We conducted (1) a series of systematic and rapid reviews, (2) a Delphi study and (3) an expert workshop. A protocol paper was published [Miles LM, Elbourne D, Farmer A, Gulliford M, Locock L, McCambridge J, et al. Bias due to MEasurement Reactions In Trials to improve health (MERIT): protocol for research to develop MRC guidance. Trials 2018;19:653]. An updated systematic review examined whether or not measuring participants had an effect on participants’ health-related behaviours relative to no-measurement controls. Three new rapid systematic reviews were conducted to identify (1) existing guidance on measurement reactivity, (2) existing systematic reviews of studies that have quantified the effects of measurement on outcomes relating to behaviour and affective outcomes and (3) experimental studies that have investigated the effects of exposure to objective measurements of behaviour on health-related behaviour. The views of 40 experts defined the scope of the recommendations in two waves of data collection during the Delphi procedure. A workshop aimed to produce a set of recommendations that were formed in discussion in groups. Results: Systematic reviews – we identified a total of 43 studies that compared interview or questionnaire measurement with no measurement and these had an overall small effect (standardised mean difference 0.06, 95% confidence interval 0.02 to 0.09; n = 104,096, I2 = 54%). The three rapid systematic reviews identified no existing guidance on measurement reactivity, but we did identify five systematic reviews that quantified the effects of measurement on outcomes (all focused on the question–behaviour effect, with all standardised mean differences in the range of 0.09—0.28) and 16 studies that examined reactive effects of objective measurement of behaviour, with most evidence of reactivity of small effect and short duration. Delphi procedure – substantial agreement was reached on the scope of the present recommendations. Workshop – 14 recommendations and three main aims were produced. The aims were to identify whether or not bias is likely to be a problem for a trial, to decide whether or not to collect further quantitative or qualitative data to inform decisions about if bias is likely to be a problem, and to identify how to design trials to minimise the likelihood of this bias. Limitation: The main limitation was the shortage of high-quality evidence regarding the extent of measurement reactivity, with some notable exceptions, and the circumstances that are likely to bring it about. Conclusion: We hope that these recommendations will be used to develop new trials that are less likely to be at risk of bias. Future work: The greatest need is to increase the number of high-quality primary studies regarding the extent of measurement reactivity. Study registration: The first systematic review in this study is registered as PROSPERO CRD42018102511. Funding: Funded by the Medical Research Council UK and the National Institute for Health Research as part of the Medical Research Council–National Institute for Health Research Methodology Research Programme.

Abstract Background Acoustic telemetry is increasingly being used as a tool to measure survival, migration timing and behaviour of fish. Tagged fish may fall prey to other animals with the tag continuing to be detected whilst it remains in the gastrointestinal tract of the predator. Failure to identify post-predation detections introduces “predation bias” into the data. We employed a new predator tag technology in the first known field trial to understand the extent these tags could reduce predation bias in Atlantic salmon (Salmo salar L.) smolt migration through a 65-km zone beginning in freshwater and extending through an estuary. These tags signal predation by detecting a pH change in the predators’ gut during digestion of a tagged prey. We quantified survival and timing bias by comparing measurements from non- and post-predated detections of tagged individuals’ to only those detections where predation was not signalled. Results Of the 50 fish tagged, 41 were detected with 24 of these signalling as predated. Predation bias was greatest in the upper estuary and decreased towards the bay. Survival bias peaked at 11.6% at river km 54. Minimum and maximum migration time were both biased long and were 16% and 4% greater than bias corrected timing at river km 66 and 54, respectively. After correcting for bias, the apparent survival from release through freshwater and estuary was 19% and minimum and maximum migration timing was 6.6 and 7.0 days, respectively. Conclusions Using this tag, we identified a high proportion of predation events that may have otherwise gone unnoticed using conventional acoustic tags. Estimated survival presented the greatest predation bias in the upper estuary which gradually declined to nearly no apparent bias in the lower estuary as predated tags failed through time to be detected. This is most likely due to tag expulsion from the predator between or upstream of receiver arrays. Whilst we have demonstrated that predation can bias telemetry results, it appears to be rather short-lived given the apparent retention times of these tags within the predators introducing the bias.

Abstract Background Novel diagnostic triage and testing strategies to support early detection of cancer could improve clinical outcomes. Most apparently promising diagnostic tests ultimately fail because of inadequate performance in real-world, low prevalence populations such as primary care or general community populations. They should therefore be systematically evaluated before implementation to determine whether they lead to earlier detection, are cost-effective, and improve patient safety and quality of care, while minimising over-investigation and over-diagnosis. Methods We performed a systematic scoping review of frameworks for the evaluation of tests and diagnostic approaches. Results We identified 16 frameworks: none addressed the entire continuum from test development to impact on diagnosis and patient outcomes in the intended population, nor the way in which tests may be used for triage purposes as part of a wider diagnostic strategy. Informed by these findings, we developed a new framework, the ‘CanTest Framework’, which proposes five iterative research phases forming a clear translational pathway from new test development to health system implementation and evaluation. Conclusion This framework is suitable for testing in low prevalence populations, where tests are often applied for triage testing and incorporated into a wider diagnostic strategy. It has relevance for a wide range of stakeholders including patients, policymakers, purchasers, healthcare providers and industry.

Abstract Background Smoking in pregnancy is a major international public health problem. Self-help support (SHS) increases the likelihood of women stopping smoking in pregnancy and delivering this kind of support by text message could be a cost-effective way to deliver SHS to pregnant women who smoke. SHS delivered by text message helps non-pregnant smokers to stop but the currently available message programmes are not appropriate for use in pregnancy. A randomised controlled trial (RCT) has demonstrated the feasibility and acceptability of using a programme called ‘MiQuit’ to text SHS support to pregnant women who smoke. Another pilot RCT has shown that it would be feasible to run a larger, multi-centre trial within the UK National Health Service (NHS). The aim of this third RCT is to complete MiQuit’s evaluation, demonstrating whether or not this is efficacious for smoking cessation in pregnancy. Methods/design This is a multi-centre, parallel-group RCT. Pregnant women aged over 16 years, of less than 25 weeks’ gestation who smoke one or more daily cigarettes but smoked at least five daily cigarettes before pregnancy and who understand written English and are being identified in 24 English antenatal care hospitals. Participants are randomised to control or intervention groups in a 1:1 ratio stratified by gestation (

Abstract Background Self-reported data have consistently shown South Asians (SAs) to be less physically active than White Europeans (WEs) in developed countries, however objective data is lacking. Differences in sedentary time have not been elucidated in this population. This study aimed to quantify differences in objectively measured physical activity and sedentary behaviour between WEs and SAs recruited from primary care and to investigate differences in demographic and lifestyle correlates of these behaviours. Methodology Baseline data were utilised from a randomised control trial recruiting individuals identified at high risk of type 2 diabetes from primary care. Light intensity physical activity, moderate-to-vigorous intensity physical activity (MVPA) and steps were measured using the Actigraph GT3X+, while sitting, standing and stepping time were measured using the activPAL3™. Devices were worn concurrently for seven days. Demographic (employment, sex, age, education, postcode) and behavioural (fruit and vegetable consumption, alcohol consumption, smoking status) characteristics were measured via self and interview administered questionnaires. Results A total of 963 WE (age = 62 ± 8, female 51%) and 289 SA (age = 55 ± 11, female 43%) were included. Compared to WEs, SAs did less MVPA (24 vs 33 min/day, p = 0.001) and fewer steps (6404 vs 7405 per day, p ≤ 0.001), but sat less (516 vs 552 min/day, p ≤ 0.001) and stood more (328 vs 283 min/day, p ≤ 0.001). Ethnicity also modified the extent to which demographic and behavioural factors act as correlates of physical activity and sedentary behaviour. Differences between sex in levels of MVPA and sitting time were greater in SAs compared to WEs, with SA women undertaking the least amount of MVPA (19 min/day), the least sitting time (475 min/day) and most standing time (377 min/day) than any other group. Smoking and alcohol status also acted as stronger correlates of sitting time in SAs compared to WEs. In contrast, education level acted as a stronger correlate of physical activity in WEs compared to SAs. Conclusion SAs were less active yet less sedentary than WEs, which demonstrates the need to tailor the behavioural targets of interventions in multi-ethnic communities. Common correlates of physical activity and sedentary behaviour also differed between ethnicities. Trial registration ISRCTN83465245 Trial registration date: 14/06/2012.

Introduction A lapse (any smoking) early in a smoking cessation attempt is strongly associated with reduced success. A substantial proportion of lapses are due to urges to smoke triggered by situational cues. Currently, no available interventions proactively respond to such cues in real time. Quit Sense is a theory-guided just-in-time adaptive intervention smartphone app that uses a learning tool and smartphone sensing to provide in-the-moment tailored support to help smokers manage cue-induced urges to smoke. The primary aim of this randomised controlled trial (RCT) is to assess the feasibility of delivering a definitive online efficacy trial of Quit Sense.Methods and analyses A two-arm parallel-group RCT allocating smokers willing to make a quit attempt, recruited via online adverts, to usual care (referral to the NHS SmokeFree website) or usual care plus Quit Sense. Randomisation will be stratified by smoking rate (

BackgroundThe majority of people do not achieve recommended levels of physical activity. There is a need for effective, scalable interventions to promote activity. Self-monitoring by pedometer is a potentially suitable strategy. We assessed the effectiveness and cost-effectiveness of a very brief (5-minute) pedometer-based intervention ('Step It Up') delivered as part of National Health Service (NHS) Health Checks in primary care.Methods and findingsThe Very Brief Intervention (VBI) Trial was a two parallel-group, randomised controlled trial (RCT) with 3-month follow-up, conducted in 23 primary care practices in the East of England. Participants were 1,007 healthy adults aged 40 to 74 years eligible for an NHS Health Check. They were randomly allocated (1:1) using a web-based tool between October 1, 2014, and December 31, 2015, to either intervention (505) or control group (502), stratified by primary care practice. Participants were aware of study group allocation. Control participants received the NHS Health Check only. Intervention participants additionally received Step It Up: a 5-minute face-to-face discussion, written materials, pedometer, and step chart. The primary outcome was accelerometer-based physical activity volume at 3-month follow-up adjusted for sex, 5-year age group, and general practice. Secondary outcomes included time spent in different intensities of physical activity, self-reported physical activity, and economic measures. We conducted an in-depth fidelity assessment on a subsample of Health Check consultations. Participants' mean age was 56 years, two-thirds were female, they were predominantly white, and two-thirds were in paid employment. The primary outcome was available in 859 (85.3%) participants. There was no significant between-group difference in activity volume at 3 months (adjusted intervention effect 8.8 counts per minute [cpm]; 95% CI -18.7 to 36.3; p = 0.53). We found no significant between-group differences in the secondary outcomes of step counts per day, time spent in moderate or vigorous activity, time spent in vigorous activity, and time spent in moderate-intensity activity (accelerometer-derived variables); as well as in total physical activity, home-based activity, work-based activity, leisure-based activity, commuting physical activity, and screen or TV time (self-reported physical activity variables). Of the 505 intervention participants, 491 (97%) received the Step it Up intervention. Analysis of 37 intervention consultations showed that 60% of Step it Up components were delivered faithfully. The intervention cost £18.04 per participant. Incremental cost to the NHS per 1,000-step increase per day was £96 and to society was £239. Adverse events were reported by 5 intervention participants (of which 2 were serious) and 5 control participants (of which 2 were serious). The study's limitations include a participation rate of 16% and low return of audiotapes by practices for fidelity assessment.ConclusionsIn this large well-conducted trial, we found no evidence of effect of a plausible very brief pedometer intervention embedded in NHS Health Checks on objectively measured activity at 3-month follow-up.Trial registrationCurrent Controlled Trials (ISRCTN72691150).

Abstract Background There is now clear systematic review evidence that measurement can affect the people being measured; much of this evidence focusses on how asking people to complete a questionnaire can result in changes in behaviour. Changes in measured behaviour and other outcomes due to this reactivity may introduce bias in otherwise well-conducted randomised controlled trials (RCTs), yielding incorrect estimates of intervention effects. Despite this, measurement reactivity is not currently adequately considered in risk of bias frameworks. The present research aims to produce a set of guidance statements on how best to avoid or minimise bias due to measurement reactivity in studies of interventions to improve health, with a particular focus on bias in RCTs. Methods The MERIT study consists of a series of systematic and rapid reviews, a Delphi study and an expert workshop to develop guidance on how to minimise bias in trials due to measurement reactivity. An existing systematic review on question-behaviour effects on health-related behaviours will be updated and three new rapid reviews will be conducted to identify (1) existing guidance on measurement reactivity; (2) systematic reviews of studies that have quantified the effects of measurement on outcomes relating to behaviour and affective outcomes in health and non-health contexts and (3) trials that have investigated the effects of objective measurements of behaviour on concurrent or subsequent behaviour itself. A Delphi procedure will be used to combine the views of experts with a view to reaching agreement on the scope of the guidance statements. Finally, a workshop will be held in autumn 2018, with the aim of producing a set of guidance statements that will form the central part of new MRC guidance on how best to avoid bias due to measurement reactivity in studies of interventions to improve health. Discussion Our ambition is to produce MRC guidance on measurement reactions in trials which will be used by future trial researchers, leading to the development of trials that are less likely to be at risk of bias.

Abstract Background Cancer is a leading cause of mortality and morbidity worldwide. Prevention is recognised by many, including the World Health Organization, to offer the most cost-effective long-term strategy for the control of cancer. One approach that focuses on individuals is the provision of personalised risk information. However, whether such information motivates behaviour change and whether the effect is different with varying formats of risk presentation is unclear. We aim to assess the short-term effect of providing information about personalised risk of cancer in three different formats alongside lifestyle advice on health-related behaviours, risk perception and risk conviction. Methods In a parallel group, randomised controlled trial 1000 participants will be recruited through the online platform Prolific. Participants will be allocated to either a control group receiving cancer-specific lifestyle advice alone or one of three intervention groups receiving the same lifestyle advice alongside their estimated 10-year risk of developing one of the five most common preventable cancers, calculated from self-reported modifiable behavioural risk factors, in one of three different formats (bar chart, pictograph or qualitative scale). The primary outcome is change from baseline in computed risk relative to an individual with a recommended lifestyle at three months. Secondary outcomes include: perceived risk of cancer; anxiety; cancer-related worry; intention to change behaviour; and awareness of cancer risk factors. Discussion This study will provide evidence on the short-term effect of providing online information about personalised risk of cancer alongside lifestyle advice on risk perception and health-related behaviours and inform the development of interventions. Trial registration ISRCTN17450583. Registered 30 January 2018.

Abstract Background Mobile applications (apps) have been heralded as transformative tools to deliver behavioral health interventions at scale, but few have been tested in rigorous randomized controlled trials. We tested the effect of a mobile app to increase vegetable consumption among overweight adults attempting weight loss maintenance. Methods Overweight adults (n=135) aged 18–50 years with BMI=28–40 kg/m2 near Stanford, CA were recruited from an ongoing 12-month weight loss trial (parent trial) and randomly assigned to either the stand-alone, theory-based Vegethon mobile app (enabling goal setting, self-monitoring, and feedback and using “process motivators” including fun, surprise, choice, control, social comparison, and competition) or a wait-listed control condition. The primary outcome was daily vegetables servings, measured by an adapted Harvard food frequency questionnaire (FFQ) 8 weeks post-randomization. Daily vegetable servings from 24-hour dietary recalls, administered by trained, certified, and blinded interviewers 5 weeks post-randomization, was included as a secondary outcome. All analyses were conducted according to principles of intention-to-treat. Results Daily vegetable consumption was significantly greater in the intervention versus control condition for both measures (adjusted mean difference: 2.0 servings; 95% CI: 0.1, 3.8, p=0.04 for FFQ; and 1.0 servings; 95% CI: 0.2, 1.9; p=0.02 for 24-hour recalls). Baseline vegetable consumption was a significant moderator of intervention effects (p=0.002) in which effects increased as baseline consumption increased. Conclusions These results demonstrate the efficacy of a mobile app to increase vegetable consumption among overweight adults. Theory-based mobile interventions may present a low-cost, scalable, and effective approach to improving dietary behaviors and preventing associated chronic diseases. Trial registration ClinicalTrials.gov NCT01826591. Registered 27 March 2013.

Introduction Survival after stroke is improving, leading to increased demand on primary care and community services to meet the long-term care needs of people living with stroke. No formal primary care-based holistic model of care with clinical trial evidence exists to support stroke survivors living in the community, and stroke survivors report that many of their needs are not being met. We have developed a multifactorial primary care model to address these longer term needs. We aim to evaluate the clinical and cost-effectiveness of this new model of primary care for stroke survivors compared with standard care.Methods and analysis Improving Primary Care After Stroke (IPCAS) is a two-arm cluster-randomised controlled trial with general practice as the unit of randomisation. People on the stroke registers of general practices will be invited to participate. One arm will receive the IPCAS model of care including a structured review using a checklist; a self-management programme; enhanced communication pathways between primary care and specialist services; and direct point of contact for patients. The other arm will receive usual care. We aim to recruit 920 people with stroke registered with 46 general practices. The primary endpoint is two subscales (emotion and handicap) of the Stroke Impact Scale (SIS) as coprimary outcomes at 12 months (adjusted for baseline). Secondary outcomes include: SIS Short Form, EuroQol EQ-5D-5L, ICEpop CAPability measure for Adults, Southampton Stroke Self-management Questionnaire, Health Literacy Questionnaire and medication use. Cost-effectiveness of the new model will be determined in a within-trial economic evaluation.Ethics and dissemination Favourable ethical opinion was gained from Yorkshire and the Humber-Bradford Leeds NHS Research Ethics Committee. Approval to start was given by the Health Research Authority prior to recruitment of participants at any NHS site. Data will be presented at national and international conferences and published in peer-reviewed journals. Patient and public involvement helped develop the dissemination plan.Trial registration number NCT03353519

Objective Develop a behavioural analysis of factors influencing postnatal physical activity (PA) according to the ‘capability, opportunity, motivation and behaviour’ (COM-B) model of behaviour to inform intervention development using the Behaviour Change Wheel (BCW).Design Cross-sectional, multi-method study using semi-structured interviews and a quantitative questionnaire.Setting Children’s centres and mother and baby groups in Hertfordshire and Cambridgeshire, UK.Participants Convenience samples of postnatal women were interviewed (n=16) and completed the questionnaire (n=158).Methods Semi-structured interviews followed a preprepared topic guide exploring the COM-B model components and analysed using framework analysis. The questionnaire, based on the self-evaluation of behaviour questionnaire, was adapted using patient and public involvement and findings from the interviews. Questionnaire participants rated their agreement with 22 predefined statements related to COM-B model components. Mean, SD and 95% CI were calculated and each item categorised according to importance. Demographic data were collected.Results The questionnaire identified that new mothers would be more active if they had more time, felt less tired, had accessible childcare, were part of a group, advised by a healthcare professional, able to develop a habit and had more motivation. Additional themes emerging from qualitative data were engaging in PA groups with other new mothers, limited physical stamina following complicated births, social interaction, enjoyment and parental beliefs as motivation, provision of child-friendly PA facilities and environments and babies’ unpredictable routines.Conclusion The behavioural analysis presented in this paper identifies and adds detail on the range of factors influencing the target behaviour. Some are unique to the target population, requiring targeted interventions for postnatal women, whereas some are individualised, suggesting the need for individually tailored interventions. We will use the behavioural analysis presented to design an intervention using the subsequent steps in the BCW.

Introduction: Despite the availability of effective stop smoking assistance, most smokers do not utilise formal cessation programmes such as the English Stop Smoking Services (SSS). We modified the Treatment Barriers Questionnaire (TBQ), developed in the USA, and distributed it to a sample of English smokers to explore the most important barriers to the use of the SSS. Methods: Participants of Start2quit, a randomised controlled trial aiming to increase attendance at the SSS using tailored risk information and ‘taster’ sessions, who reported at follow-up that they had not attended the SSS, were asked to complete the TBQ; 672 (76.9% response rate) were retained for analysis. Principal Component Analysis (PCA) was conducted to examine the structure of the data. Multiple linear regressions were used to determine whether any participant characteristics were associated with particular barriers. Results: The most commonly endorsed items related to a lack of information on and a lack of confidence in the efficacy of the SSS. PCA yielded seven factors: Work and time constraints (Factor1); Smokers should quit on their own (Factor2); Nothing can help in quitting smoking(Factor3); Disinterest in quitting (Factor4); Lack of social support to attend (Factor5); Lack of privacy at programmes (Factor6); Lack of information and perceived availability (Factor7). Age was associated with Factors 1, 3 and 4, motivation to quit with Factors 2 and 4, and confidence in quitting with Factors 1, 2, and 3. Conclusions: The findings suggest that many barriers exist, and they vary according to smoker demographics and characteristics, pointing to the need for tailored recruitment strategies. Trial registration: ISRCTN76561916. Keywords: Smoking cessation, Stop smoking service, Treatment access

Abstract Background Very brief interventions (VBIs) for physical activity are promising, but there is uncertainty about their potential effectiveness and cost. We assessed potential efficacy, feasibility, acceptability, and cost of three VBIs in primary care, in order to select the most promising intervention for evaluation in a subsequent large-scale RCT. Methods Three hundred and ninety four adults aged 40–74 years were randomised to a Motivational (n = 83), Pedometer (n = 74), or Combined (n = 80) intervention, delivered immediately after a preventative health check in primary care, or control (Health Check only; n = 157). Potential efficacy was measured as the probability of a positive difference between an intervention arm and the control arm in mean physical activity, measured by accelerometry at 4 weeks. Results For the primary outcome the estimated effect sizes (95 % CI) relative to the Control arm for the Motivational, Pedometer and Combined arms were respectively: +20.3 (−45.0, +85.7), +23.5 (−51.3, +98.3), and −3.1 (−69.3, +63.1) counts per minute. There was a73% probability of a positive effect on physical activity for each of the Motivational and Pedometer VBIs relative to control, but only 46 % for the Combined VBI. Only the Pedometer VBI was deliverable within 5 min. All VBIs were acceptable and low cost. Conclusions Based on the four criteria, the Pedometer VBI was selected for evaluation in a large-scale trial. Trial registration Current Controlled Trials ISRCTN02863077 . Retrospectively registered 05/10/2012.

An amendment to this paper has been published and can be accessed via the original article.

Objective This study was performed to evaluate the perceptions of the use of technology to improve cardiovascular medicine taking among patients aged >65 years. Methods This qualitative study used focus groups with people aged >65 years taking cardiovascular medications from two East London community centres. Thematic analysis was informed by the Perceptions and Practicalities Approach framework. Results Participants welcomed technologies they considered familiar, accessible, and easy to use. They valued the opportunity to receive alerts to help with forgetting and monitoring their treatment. More advanced technologies such as ingestible sensor systems were considered helpful for elderly people with significant cognitive impairments still living in the community because of improved monitoring by caregivers and clinicians and prolonging independence. Although generally adapting to the increase in technology in everyday life, participants raised a number of concerns that included potential reduction in face-to-face communication, data security, becoming dependent on technology, and worrying about the consequences of technological failure. Conclusions Participants raised a number of concerns and practical barriers that would need to be addressed for technologies to be accepted and adopted in this patient group.

BackgroundPrevious studies have shown that smoking and smoking cessation may be associated with health-related quality of life (HRQoL). In this study, we compared changes in HRQoL in people who maintained abstinence with people who had relapsed to smoking.MethodsThis was a secondary analysis of data from a trial of a relapse prevention intervention in 1,407 short-term quitters. The European Quality of Life -5 Dimensions (EQ-5D) measured HRQoL at baseline, 3 and 12 months. Smoking outcome was continuous abstinence from 2 to 12 months, and 7-day smoking at 3 and 12 months. We used nonparametric test for differences in EQ-5D utility scores, and chi-square test for dichotomised response to each of the five EQ-5D dimensions. Multivariable regression analyses were conducted to evaluate associations between smoking relapse and HRQoL or anxiety/depression problems.ResultsThe mean EQ-5D tariff score was 0.8252 at baseline. People who maintained abstinence experienced a statistically non-significant increase in the EQ-5D score (mean change 0.0015, P = 0.88), while returning to smoking was associated with a statistically significant decrease in the EQ-5D score (mean change -0.0270, P = 0.004). After adjusting for multiple baseline characteristics, the utility change during baseline and 12 months was statistically significantly associated with continuous abstinence, with a difference of 0.0288 (95% CI: 0.0006 to 0.0571, P = 0.045) between relapsers and continuous quitters. The only difference in quality of life dimensions between those who relapsed and those who maintained abstinence was in the proportion of participants with anxiety/depression problems at 12 months (30% vs. 22%, P = 0.001). Smoking relapse was associated with a simultaneous increase in anxiety/depression problems.ConclusionsPeople who achieve short-term smoking abstinence but subsequently relapse to smoking have a reduced quality of life, which appears mostly due to worsening of symptoms of anxiety and depression. Further research is required to more fully understand the relationship between smoking and health-related quality of life, and to develop cessation interventions by taking into account the impact of anxiety or depression on smoking.

Background: The NHS Stop Smoking Services (SSSs) offer help to smokers who want to quit. However, the proportion of smokers attending the SSSs is low and current figures show a continuing downward trend. This research addressed the problem of how to motivate more smokers to accept help to quit. Objectives: To assess the relative effectiveness, and cost-effectiveness, of an intervention consisting of proactive recruitment by a brief computer-tailored personal risk letter and an invitation to a ‘Come and Try it’ taster session to provide information about the SSSs, compared with a standard generic letter advertising the service, in terms of attendance at the SSSs of at least one session and validated 7-day point prevalent abstinence at the 6-month follow-up. Design: Randomised controlled trial of a complex intervention with follow-up 6 months after the date of randomisation. Setting: SSSs and general practices in England. Participants: All smokers aged ≥ 16 years identified from medical records in participating practices who were motivated to quit and who had not attended the SSS in the previous 12 months. Participants were randomised in the ratio 3 : 2 (intervention to control) by a computer program. Interventions: Intervention – brief personalised and tailored letter sent from the general practitioner using information obtained from the screening questionnaire and from medical records, and an invitation to attend a taster session, run by the local SSS. Control – standard generic letter from the general practice advertising the local SSS and the therapies available, and asking the smoker to contact the service to make an appointment. Main outcome measures: (1) Proportion of people attending the first session of a 6-week course over a period of 6 months from the receipt of the invitation letter, measured by records of attendance at the SSSs; (2) 7-day point prevalent abstinence at the 6-month follow-up, validated by salivary cotinine analysis; and (3) cost-effectiveness of the intervention. Results: Eighteen SSSs and 99 practices within the SSS areas participated; 4384 participants were randomised to the intervention (n = 2636) or control (n = 1748). One participant withdrew and 4383 were analysed. The proportion of people attending the first session of a SSS course was significantly higher in the intervention group than in the control group [17.4% vs. 9.0%; unadjusted odds ratio (OR) 2.12, 95% confidence interval (CI) 1.75 to 2.57; p 86% over a lifetime horizon. Limitations: Participating SSSs may not be representative of all SSSs in England. Recruitment was low, at 4%. Conclusions: The Start2quit trial added to evidence that a proactive approach with an intensive intervention to deliver personalised risk information and offer a no-commitment introductory session can be successful in reaching more smokers and increasing the uptake of the SSS and quit rates. The intervention appears less likely to be cost-effective in the short term, but is highly likely to be cost-effective over a lifetime horizon. Future work: Further research could assess the separate effects of these components. Trial registration: Current Controlled Trials ISRCTN76561916. Funding details: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 21, No. 3. See the NIHR Journals Library website for further project information.

BackgroundInformation about genetic and phenotypic risk of type 2 diabetes is now widely available and is being incorporated into disease prevention programs. Whether such information motivates behavior change or has adverse effects is uncertain. We examined the effect of communicating an estimate of genetic or phenotypic risk of type 2 diabetes in a parallel group, open, randomized controlled trial.Methods and findingsWe recruited 569 healthy middle-aged adults from the Fenland Study, an ongoing population-based, observational study in the east of England (Cambridgeshire, UK). We used a computer-generated random list to assign participants in blocks of six to receive either standard lifestyle advice alone (control group, n = 190) or in combination with a genetic (n = 189) or a phenotypic (n = 190) risk estimate for type 2 diabetes (intervention groups). After 8 wk, we measured the primary outcome, objectively measured physical activity (kJ/kg/day), and also measured several secondary outcomes (including self-reported diet, self-reported weight, worry, anxiety, and perceived risk). The study was powered to detect a between-group difference of 4.1 kJ/kg/d at follow-up. 557 (98%) participants completed the trial. There were no significant intervention effects on physical activity (difference in adjusted mean change from baseline: genetic risk group versus control group 0.85 kJ/kg/d (95% CI -2.07 to 3.77, p = 0.57); phenotypic risk group versus control group 1.32 (95% CI -1.61 to 4.25, p = 0.38); and genetic risk group versus phenotypic risk group -0.47 (95% CI -3.40 to 2.46, p = 0.75). No significant differences in self-reported diet, self-reported weight, worry, and anxiety were observed between trial groups. Estimates of perceived risk were significantly more accurate among those who received risk information than among those who did not. Key limitations include the recruitment of a sample that may not be representative of the UK population, use of self-reported secondary outcome measures, and a short follow-up period.ConclusionsIn this study, we did not observe short-term changes in behavior associated with the communication of an estimate of genetic or phenotypic risk of type 2 diabetes. We also did not observe changes in worry or anxiety in the study population. Additional research is needed to investigate the conditions under which risk information might enhance preventive strategies. (Current Controlled Trials ISRCTN09650496; Date applied: April 4, 2011; Date assigned: June 10, 2011).Trial registrationThe trial is registered with Current Controlled Trials, ISRCTN09650496.

Background: Most people who quit smoking successfully for a short period will return to smoking again in 12 months. A previous exploratory meta-analysis indicated that self-help booklets may be effective for smoking relapse prevention in unaided quitters. Objectives: This study aimed to evaluate the effectiveness of a set of self-help educational booklets to prevent smoking relapse in people who had stopped smoking with the aid of behavioural support. Design: This is an open, randomised controlled trial and qualitative process evaluation. Trial participants were randomly allocated to one of two groups, using a simple randomisation process without attempts to stratify by participant characteristics. The participant allocation was ‘concealed’ because the recruitment of quitters occurred before the random allocation. Setting: Short-term quitters were recruited from NHS Stop Smoking Clinics, and self-help educational materials were posted to study participants at home. Participants: A total of 1407 carbon monoxide (CO)-validated quitters at 4 weeks after quit date in NHS Stop Smoking Clinics. The trial excluded pregnant women and quitters who were not able to read the educational materials in English. Interventions: Participants in the experimental group (n = 703) received a set of eight revised Forever Free booklets, and participants in the control group (n = 704) received a single leaflet that is currently given to NHS patients. Main outcome measures: Follow-up telephone interviews were conducted 3 and 12 months after quit date. The primary outcome was prolonged, CO-verified abstinence from months 4 to 12 during which time no more than five cigarettes were smoked. The secondary outcomes included self-reported abstinence during the previous 7 days at 3 and 12 months, CO-verified abstinence at 12 months, costs (NHS and NHS and participant medication costs perspectives) and quality-adjusted life-years. Logistic regression analyses were conducted to investigate effect-modifying variables. A simultaneous qualitative process evaluation was conducted to help interpret the trial results. Results: Data from 1404 participants were used for the final analysis, after excluding three participants who died before the 12-month follow-up. The proportion with prolonged abstinence from months 4 to 12 after quit date was 36.9% in the intervention group and 38.6% in the control group. There was no statistically significant difference between the groups (odds ratio 0.93, 95% confidence interval 0.75 to 1.15; p = 0.509). There were no statistically significant differences between the groups in secondary smoking outcomes. People who reported knowing risky situations for relapse and using strategies to handle urges to smoke were less likely to relapse. However, there were no differences between the groups in the proportion of participants who reported that they knew any more about coping skills, and no differences in reported use of strategies to cope with urges to smoke between the trial groups. The qualitative study found that some quitters considered self-help booklets unhelpful for smoking relapse prevention, although positive feedback by participants was common. Conclusions: Among quitters who had stopped smoking with the aid of intensive behavioural support, there was no significant difference in the likelihood of smoking relapse between those who subsequently received a set of eight revised Forever Free booklets and those who received a single leaflet. Although many people had suboptimal strategies to prevent relapse and most relapsed, the Forever Free booklets proved an ineffective medium for teaching them the skills to prevent relapse. Further research should focus on interventions that may increase the use of coping skills when required. Trial registration: Current Controlled Trials ISRCTN36980856. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 19, No. 59. See the NIHR Journals Library website for further project information.

Low levels of physical activity are a major public health concern, and interventions to promote physical activity have had limited success. Whether or not personalised feedback about physical activity following objective measurement motivates behaviour change has yet to be rigorously examined.And Findings: In a parallel group, open randomised controlled trial, 466 healthy adults aged 32 to 54 years were recruited from the ongoing population-based Fenland Study (Cambridgeshire, UK). Participants were randomised to receive either no feedback until the end of the trial (control group, n=120) or one of three different types of feedback: simple, visual, or contextualised (intervention groups, n=346). The primary outcome was physical activity (physical activity energy expenditure (PAEE) in kJ/kg/day and average body acceleration (ACC) in m/s(2)) measured objectively using a combined heart rate monitor and accelerometer (Actiheart(®)). The main secondary outcomes included self-reported physical activity, intention to increase physical activity, and awareness of physical activity (the agreement between self-rated and objectively measured physical activity). At 8 weeks, 391 (83.9%) participants had complete physical activity data. The intervention had no effect on objectively measured physical activity (PAEE: β=-0.92, 95% CI=-3.50 to 1.66, p=0.48 and ACC: β=0.01, 95% CI=-0.00 to 0.02, p=0.21), self-reported physical activity (β=-0.39, 95% CI=-1.59 to 0.81), or intention to increase physical activity (β=-0.05, 95% CI=-0.22 to 0.11). However, it was associated with an increase in awareness of physical activity (OR=1.74, 95% CI=1.05 to 2.89). Results did not differ according to the type of feedback.Personalised feedback about physical activity following objective measurement increased awareness but did not result in changes in physical activity in the short term. Measurement and feedback may have a role in promoting behaviour change but are ineffective on their own.Current Controlled Trials ISRCTN92551397 http://www.controlled-trials.com/ISRCTN92551397.

The behavioural impact of pharmacogenomics is untested. We tested two hypotheses concerning the behavioural impact of informing smokers their oral dose of NRT is tailored to analysis of DNA.We conducted an RCT with smokers in smoking cessation clinics (N = 633). In combination with NRT patch, participants were informed that their doses of oral NRT were based either on their mu-opioid receptor (OPRM1) genotype, or their nicotine dependence questionnaire score (phenotype). The proportion of prescribed NRT consumed in the first 28 days following quitting was not significantly different between groups: (68.5% of prescribed NRT consumed in genotype vs 63.6%, phenotype group, difference = 5.0%, 95% CI -0.9,10.8, p = 0.098). Motivation to make another quit attempt among those (n = 331) not abstinent at six months was not significantly different between groups (p = 0.23). Abstinence at 28 days was not different between groups (p = 0.67); at six months was greater in genotype than phenotype group (13.7% vs 7.9%, difference = 5.8%, 95% CI 1.0,10.7, p = 0.018).Informing smokers their oral dose of NRT was tailored to genotype not phenotype had a small, statistically non-significant effect on 28-day adherence to NRT. Among those still smoking at six months, there was no evidence that saying NRT was tailored to genotype adversely affected motivation to make another quit attempt. Higher abstinence rate at six months in the genotype arm requires investigation.Controlled-Trials.com ISRCTN14352545.