Smoking, nicotine and pregnancy 2 (SNAP2) trial: protocol for a randomised controlled trial of an intervention to improve adherence to nicotine replacement therapy during pregnancy.

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 (<14 or ≥14 weeks) to receive: (1) usual care (UC) for stop smoking support or (2) UC plus an intervention to increase adherence to NRT, called 'Baby, Me and NRT' (BMN), comprising adherence counselling, automated tailored text messages, a leaflet and website. The primary outcome is biochemically validated smoking abstinence at or around childbirth, measured from 36 weeks gestation. Secondary outcomes include NRT adherence, other smoking measures and birth outcomes. Questionnaires collect follow-up data augmented by medical record information. We anticipate quit rates of 10% and 16% in the control and intervention groups, respectively (risk ratio=1.6). By recruiting 1320 participants, the trial should have 90% power (alpha=5%) to detect this intervention effect. An economic analysis will use the Economics of Smoking in Pregnancy model to determine cost-effectiveness. ETHICS AND DISSEMINATION: Ethics approval was granted by Bloomsbury National Health Service's Research Ethics Committee (21/LO/0123). Written informed consent will be obtained from all participants. Findings will be disseminated to the public, funders, relevant practice/policy representatives, researchers and participants. TRIAL REGISTRATION NUMBER: ISRCTN16830506. PROTOCOL VERSION: 5.0, 10 Oct 2023.

Randomised controlled trial of population screening for atrial fibrillation in people aged 70 years and over to reduce stroke: protocol for the SAFER trial.

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.

A smoking cessation smartphone app that delivers real-time 'context aware' behavioural support: the Quit Sense feasibility RCT.

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.

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.

An Automated, Online Feasibility Randomized Controlled Trial of a Just-In-Time Adaptive Intervention for Smoking Cessation (Quit Sense).

INTRODUCTION: Learned smoking cues from a smoker's environment are a major cause of lapse and relapse. Quit Sense, a theory-guided Just-In-Time Adaptive Intervention smartphone app, aims to help smokers learn about their situational smoking cues and provide in-the-moment support to help manage these when quitting. METHODS: A two-arm feasibility randomized controlled trial (N = 209) to estimate parameters to inform a definitive evaluation. Smoker's willing to make a quit attempt were recruited using online paid-for adverts and randomized to "usual care" (text message referral to NHS SmokeFree website) or "usual care" plus a text message invitation to install Quit Sense. Procedures, excluding manual follow-up for nonresponders, were automated. Follow-up at 6 weeks and 6 months included feasibility, intervention engagement, smoking-related, and economic outcomes. Abstinence was verified using cotinine assessment from posted saliva samples. RESULTS: Self-reported smoking outcome completion rates at 6 months were 77% (95% CI 71%, 82%), viable saliva sample return rate was 39% (95% CI 24%, 54%), and health economic data 70% (95% CI 64%, 77%). Among Quit Sense participants, 75% (95% CI 67%, 83%) installed the app and set a quit date and, of those, 51% engaged for more than one week. The 6-month biochemically verified sustained abstinence rate (anticipated primary outcome for definitive trial), was 11.5% (12/104) among Quit Sense participants and 2.9% (3/105) for usual care (adjusted odds ratio = 4.57, 95% CIs 1.23, 16.94). No evidence of between-group differences in hypothesized mechanisms of action was found. CONCLUSIONS: Evaluation feasibility was demonstrated alongside evidence supporting the effectiveness potential of Quit Sense. IMPLICATIONS: Running a primarily automated trial to initially evaluate Quit Sense was feasible, resulting in modest recruitment costs and researcher time, and high trial engagement. When invited, as part of trial participation, to install a smoking cessation app, most participants are likely to do so, and, for those using Quit Sense, an estimated one-half will engage with it for more than 1 week. Evidence that Quit Sense may increase verified abstinence at 6-month follow-up, relative to usual care, was generated, although low saliva return rates to verify smoking status contributed to considerable imprecision in the effect size estimate.

A systematic review and meta-analysis of studies of reactivity to digital in-the-moment measurement of health behaviour.

Self-report measures of health behaviour have several limitations including measurement reactivity, i.e., changes in people's behaviour, cognitions or emotions due to taking part in research. This systematic review investigates whether digital in-the-moment measures induce reactivity to a similar extent and why it occurs. Four databases were searched in December 2020. All observational or experimental studies investigating reactivity to digital in-the-moment measurement of a range of health behaviours were included if they were published in English in 2008 or later. Of the 11,723 records initially screened, 30 publications reporting on 31 studies were included in the qualitative synthesis/ 7 studies in the quantitative synthesis. Eighty-one percent of studies focused on reactivity to the measurement of physical activity indicators; small but meaningful pooled effects were found (Cohen's ds: 0.27-0.30). Only a small number of studies included other behaviours, yielding mixed results. Digital in-the-moment measurement of behaviour thus may be as prone to reactivity as self-reports in questionnaires. Measurement reactivity may be amplified by (1) ease of changing the behaviour (2) awareness of being measured and social desirability, and (3) resolving discrepancies between actual and desired behaviour through self-regulation.

Effectiveness of offering tailored text message, self-help smoking cessation support to pregnant women who want information on stopping smoking: MiQuit3 randomised controlled trial and meta-analysis.

AIMS: To test the efficacy of 'MiQuit', a tailored, self-help, text message stop smoking programme for pregnancy, as an adjunct to usual care (UC) for smoking cessation in pregnancy. DESIGN: Multicentre, open, two-arm, parallel-group, superiority randomised controlled trial (RCT) and a trial sequential analysis (TSA) meta-analysis combining trial findings with two previous ones. SETTING: Twenty-four English hospital antenatal clinics. PARTICIPANTS: A total of 1002 pregnant women who were ≥16 years old, were ≤25 weeks gestation and smoked ≥1 daily cigarette and accepted information on cessation with no requirement to set quit dates. INTERVENTIONS: UC or UC plus 'MiQuit': 12 weeks of tailored, smoking cessation text messages focussed on inducing and aiding cessation. MEASUREMENTS: Primary outcome: biochemically validated cessation between 4 weeks after randomisation and late pregnancy. SECONDARY OUTCOMES: shorter and non-validated abstinence periods, pregnancy outcomes and incremental cost-effectiveness ratios. FINDINGS: RCT: cessation was 5.19% (26/501) and 4.59% (23/501) in MiQuit and UC groups (adjusted odds ratio [adj OR] for quitting with MiQuit versus UC, 95% CI = 1.15 [0.65-2.04]); other abstinence findings were similar, with higher point estimates. Primary outcome ascertainment was 61.7% (309) and 67.3% (337) in MiQuit and UC groups with 71.1% (54/76) and 69.5% (41/59) abstinence validation rates, respectively. Pregnancy outcomes were similar and the incremental cost per quality-adjusted life year was -£1118 (95% CI = -£4806-£1911). More MiQuit group women reported making at least one quit attempt (adj OR [95% CI]) for making an attempt, 1.50 (1.07-2.09). TSA meta-analysis: this found no significant difference in prolonged abstinence between MiQuit and UC (pooled OR = 1.49, adjusted 95% CI = 0.62-3.60). CONCLUSIONS: Irrespective of whether they want to try quitting, when offered a tailored, self-help, text message stop smoking programme for pregnancy (MiQuit) as an adjunct to usual care, pregnant women are not more likely to stop smoking until childbirth but they report more attempts at stopping smoking.

The effect of nicotine dependence and withdrawal symptoms on use of nicotine replacement therapy: Secondary analysis of a randomized controlled trial in primary care.

INTRODUCTION: Nicotine replacement therapy (NRT) is effective for smoking cessation, but the optimal method of using NRT to maximize benefit is unclear. We examined whether nicotine dependence was associated with consumption of NRT, whether this was mediated by withdrawal symptoms, and the impact of these factors on cessation, in a population advised to use as much NRT as needed. METHODS: Secondary analysis of data from an open label, parallel group randomized controlled trial. Participants (n = 539) attended a smoking cessation clinic in primary care and remained engaged with treatment for at least one week following a quit attempt. Baseline dependence was measured by the Fagerström Test for Cigarette Dependence (FTCD), with tobacco exposure assessed via an exhaled carbon monoxide test. At one week after quit day, mean daily consumption of NRT was measured for all participants; withdrawal (Mood and Physical Symptoms Scale (MPSS)) was also assessed in the subsample who reported being completely abstinent to that point (n = 279). Abstinence was biochemically assessed at four weeks for all participants as the principal smoking cessation outcome. RESULTS: Each point higher on the FTCD was associated with 0.83 mg/day more NRT consumption, controlling for tobacco exposure. This relationship was diminished when withdrawal was controlled for, and withdrawal was associated with NRT consumption, with each point higher on the MPSS associated with a 0.12 mg/day increase. Increased consumption of NRT directly predicted subsequent smoking cessation. CONCLUSIONS: Higher dependence appears to lead to greater withdrawal, which appears to drive greater use of NRT. This effect may partly offset lower abstinence rates in people with higher dependence. Advice to use sufficient NRT to suppress withdrawal may increase abstinence rates.

Does self-monitoring diet and physical activity behaviors using digital technology support adults with obesity or overweight to lose weight? A systematic literature review with meta-analysis.

Establish whether digital self-monitoring of diet and physical activity is effective at supporting weight loss, increasing physical activity and improving eating behavior in adults with obesity or overweight, and determine the intervention components that might explain variations in its effectiveness. A systematic search of MEDLINE, Embase, PsycINFO, Web of Science, Scopus, Cinahl, and CENTRAL identified 4068 studies, of which 12 randomized controlled trials were eligible and included in the review. A random-effect meta-analysis evaluated intervention effectiveness and subgroup analyses tested for effective intervention content. Twelve studies were included in the review and meta-analysis. Digital self-monitoring of both diet and physical activity had a statistically significant effect at supporting weight loss (mean difference [MD] = -2.87 [95% CI -3.78, -1.96], P < 0.001, I2  = 69%), improving moderate physical activity (standardized mean difference [SMD] = 0.44 [95% CI 0.26, 0.62], P < 0.001, I2  = 0%), and reducing calorie intake (MD = -181.71 [95% CI -304.72, -58.70], P < 0.01, I2  = 0%). Tailored interventions were significantly more effective than nontailored interventions (x2 = 12.92, P < 0.001). Digital self-monitoring of physical activity and diet is an effective intervention to support weight loss in adults with obesity or overweight. This effect is significantly associated with tailored advice. Future studies should use rigorous designs to explore intervention effectiveness to support weight loss as an adjunct to weight management services.

Randomised controlled trial of a just-in-time adaptive intervention (JITAI) smoking cessation smartphone app: the Quit Sense feasibility trial protocol.

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 (<16 vs ≥16 cigarettes/day) and socioeconomic status (low vs high). Recruitment, enrolment, baseline data collection, allocation and intervention delivery will be automated through the study website. Outcomes will be collected at 6 weeks and 6 months follow-up via the study website or telephone, and during app usage. The study aims to recruit 200 smokers to estimate key feasibility outcomes, the preliminary impact of Quit Sense and potential cost-effectiveness, in addition to gaining insights on user views of the app through qualitative interviews. ETHICS AND DISSEMINATION: Ethics approval has been granted by the Wales NHS Research Ethics Committee 7 (19/WA/0361). The findings will be disseminated to the public, the funders, relevant practice and policy representatives and other researchers. TRIAL REGISTRATION NUMBER: ISRCTN12326962.

Incorporating a brief intervention for personalised cancer risk assessment to promote behaviour change into primary care: a multi-methods pilot study.

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.

A general method for elicitation, imputation, and sensitivity analysis for incomplete repeated binary data.

We develop and demonstrate methods to perform sensitivity analyses to assess sensitivity to plausible departures from missing at random in incomplete repeated binary outcome data. We use multiple imputation in the not at random fully conditional specification framework, which includes one or more sensitivity parameters (SPs) for each incomplete variable. The use of an online elicitation questionnaire is demonstrated to obtain expert opinion on the SPs, and highest prior density regions are used alongside opinion pooling methods to display credible regions for SPs. We demonstrate that substantive conclusions can be far more sensitive to departures from the missing at random assumption (MAR) when control and intervention nonresponders depart from MAR differently, and show that the correlation of arm specific SPs in expert opinion is particularly important. We illustrate these methods on the iQuit in Practice smoking cessation trial, which compared the impact of a tailored text messaging system versus standard care on smoking cessation. We show that conclusions about the effect of intervention on smoking cessation outcomes at 8 week and 6 months are broadly insensitive to departures from MAR, with conclusions significantly affected only when the differences in behavior between the nonresponders in the two trial arms is larger than expert opinion judges to be realistic.

Assessment of the Effectiveness and Cost-Effectiveness of Tailored Web- and Text-Based Smoking Cessation Support in Primary Care (iQuit in Practice II): Protocol for a Randomized Controlled Trial.

BACKGROUND: The prevalence of smoking is declining; however, it continues to be a major public health burden. In England, primary care is the health setting that provides smoking cessation support to most smokers. However, this setting has one of the lowest success rates. The iQuit in practice intervention (iQuit) is a tailored web-based and text message intervention developed for use in primary care consultations as an adjunct to routine smoking cessation support with the aim of increasing success rates. iQuit has demonstrated feasibility, acceptability, and potential effectiveness. OBJECTIVE: This definitive trial aims to determine the effectiveness and cost-effectiveness of iQuit when used as an adjunct to the usual support provided to patients who wish to quit smoking, compared with usual care alone. METHODS: The iQuit in Practice II trial is a two-arm, parallel-group, randomized controlled trial (RCT) with a 1:1 individual allocation comparing usual care (ie, pharmacotherapy combined with multisession behavioral support)-the control-with usual care plus iQuit-the intervention. Participants were recruited through primary care clinics and talked to a smoking cessation advisor. Participants were randomized during the initial consultation, and those allocated to the intervention group received a tailored advice report and 90 days of text messaging in addition to the standard support provided to all patients. RESULTS: The primary outcome is self-reported prolonged abstinence biochemically verified using saliva cotinine at 6 months after the quit date. A sample size of 1700 participants, with 850 per arm, would yield 90% power to detect a 4.3% difference in validated quit rates between the groups at the two-sided 5% level of significance. The Cambridge East Research Ethics Committee approved the study in February 2016, and funding for the study was granted from May 2016. In total, 1671 participants were recruited between August 2016 and July 2019. Follow-up for all participants was completed in January 2020. Data analysis will begin in the summer of 2020. CONCLUSIONS: iQuit in Practice II is a definitive, pragmatic RCT assessing whether a digital intervention can augment the impact of routine smoking cessation support in primary care. Previous research has found good acceptability and feasibility for delivering iQuit among smoking cessation advisors working in primary care. If demonstrated to be cost-effective, iQuit could be delivered across primary care and other settings, such as community pharmacies. The potential benefit would likely be highest where less behavioral support is delivered. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN): 44559004; http://www.isrctn.com /ISRCTN44559004. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17160.

A randomised controlled trial of the effect of providing online risk information and lifestyle advice for the most common preventable cancers.

Few trial data are available concerning the impact of personalised cancer risk information on behaviour. This study assessed the short-term effects of providing personalised cancer risk information on cancer risk beliefs and self-reported behaviour. We randomised 1018 participants, recruited through the online platform Prolific, to either a control group receiving cancer-specific lifestyle advice or one of three intervention groups receiving their computed 10-year risk of developing one of the five most common preventable cancers either as a bar chart, a pictograph or a qualitative scale alongside the same lifestyle advice. The primary outcome was change from baseline in computed risk relative to an individual with a recommended lifestyle (RRI)1 at three months. Secondary outcomes included: health-related behaviours, risk perception, anxiety, worry, intention to change behaviour, and a newly defined concept, risk conviction. After three months there were no between-group differences in change in RRI (p = 0.71). At immediate follow-up, accuracy of absolute risk perception (p < 0.001), absolute and comparative risk conviction (p < 0.001) and intention to increase fruit and vegetables (p = 0.026) and decrease processed meat (p = 0.033) were higher in all intervention groups relative to the control group. The increases in accuracy and conviction were only seen in individuals with high numeracy and low baseline conviction, respectively. These findings suggest that personalised cancer risk information alongside lifestyle advice can increase short-term risk accuracy and conviction without increasing worry or anxiety but has little impact on health-related behaviour. Trial registration: ISRCTN17450583. Registered 30 January 2018.

Development and usability testing of a very brief intervention for personalised cancer risk assessment to promote behaviour change in primary care using normalisation process theory.

BACKGROUND: Cancer is the second leading cause of death worldwide. Lifestyle choices play an important role in the aetiology of cancer with up to 4 in 10 cases potentially preventable. Interventions delivered by healthcare professionals (HCPs) that incorporate risk information have the potential to promote behaviour change. Our aim was to develop a very brief intervention incorporating cancer risk, which could be implemented within primary care. METHODS: Guided by normalisation process theory (NPT), we developed a prototype intervention using literature reviews, consultation with patient and public representatives and pilot work with patients and HCPs. We conducted focus groups and interviews with 65 HCPs involved in delivering prevention activities. Findings were used to refine the intervention before 22 HCPs completed an online usability test and provided further feedback via a questionnaire incorporating a modified version of the NoMAD checklist. RESULTS: The intervention included a website where individuals could provide information on lifestyle risk factors view their estimated 10-year risk of developing one or more of the five most common preventable cancers and access lifestyle advice incorporating behaviour change techniques. Changes incorporated from feedback from the focus groups and interviews included signposting to local services and websites, simplified wording and labelling of risk information. In the usability testing, all participants felt it would be easy to collect the risk information. Ninety-one percent felt the intervention would enable discussion about cancer risk and believed it had potential to be easily integrated into National Health Service (NHS) Health Checks. However, only 36% agreed it could be delivered within 5 min. CONCLUSIONS: With the use of NPT, we developed a very brief intervention that is acceptable to HCPs in primary care and could be potentially integrated into NHS Health Checks. However, further work is needed to assess its feasibility and potential effectiveness.

Effect of interventions including provision of personalised cancer risk information on accuracy of risk perception and psychological responses: A systematic review and meta-analysis.

OBJECTIVE: To synthesize the literature on the effect of provision of personalised cancer risk information to individuals at population level risk on accuracy of risk perception and psychological responses. METHODS: A systematic review and random effects meta-analysis of articles published from 01/01/2000 to 01/07/2017. RESULTS: We included 23 studies. Immediately after provision of risk information 87% of individuals were able to recall the absolute risk estimate. Less than half believed that to be their risk, with up to 71% believing their risk to be higher than the estimate. Provision of risk information increased accuracy of perceived absolute risk immediately after risk information compared with no information (pooled RR 4.16 (95%CI 1.28-13.49), 3 studies). There was no significant effect on comparative risk accuracy (pooled RR 1.39 (0.72-2.69), 2 studies) and either no change or a reduction in cancer worry, anxiety and fear. CONCLUSION: These findings highlight the complex cognitive processes involved in the conceptualisation of risk. PRACTICE IMPLICATIONS: Individuals who appear to understand and are able to recall risk information most likely do not believe it reflects their own risk.

Interest in and Use of Smoking Cessation Support Across Pregnancy and Postpartum.

BACKGROUND: Limited research exists on interest in and use of smoking cessation support in pregnancy and postpartum. METHODS: A longitudinal cohort of pregnant smokers and recent ex-smokers were recruited in Nottinghamshire, United Kingdom (N = 850). Data were collected at 8-26 weeks gestation, 34-36 weeks gestation, and 3 months postpartum and used as three cross-sectional surveys. Interest and use of cessation support and belief and behavior measures were collected at all waves. Key data were adjusted for nonresponse and analyzed descriptively, and multiple regression was used to identify associations. RESULTS: In early and late pregnancy, 44% (95% CI 40% to 48%) and 43% (95% CI 37% to 49%) of smokers, respectively, were interested in cessation support with 33% (95% CI 27% to 39%) interested postpartum. In early pregnancy, 43% of smokers reported discussing cessation with a midwife and, in late pregnancy, 27% did so. Over one-third (38%) did not report discussing quitting with a health professional during pregnancy. Twenty-seven percent of smokers reported using any National Health Service (NHS) cessation support and 12% accessed NHS Stop Smoking Services during pregnancy. Lower quitting confidence (self-efficacy), higher confidence in stopping with support, higher quitting motivation, and higher age were associated with higher interest in support (ps ≤ .001). A recent quit attempt and greater interest in support was associated with speaking to a health professional about quitting and use of NHS cessation support (ps ≤ .001). CONCLUSIONS: When asked in early or late pregnancy, about half of pregnant smokers were interested in cessation support, though most did not engage. Cessation support should be offered throughout pregnancy and after delivery. IMPLICATIONS: There is relatively high interest in cessation support in early and late pregnancy and postpartum among smokers; however, a much smaller proportion of pregnant or postpartum women access any cessation support, highlighting a gap between interest and engagement. Reflecting women's interest, offers of cessation support should be provided throughout pregnancy and after delivery. Increasing motivation to quit and confidence in quitting with assistance may enhance interest in support, and promoting the discussion of stopping smoking between women and health practitioners may contribute to higher support engagement rates.

Evaluating diagnostic strategies for early detection of cancer: the CanTest framework.

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.

An exploration of the barriers to attendance at the English Stop Smoking Services.

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.

Effectiveness and cost-effectiveness of a tailored text-message programme (MiQuit) for smoking cessation in pregnancy: study protocol for a randomised controlled trial (RCT) and meta-analysis.

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 (< 16 weeks versus ≥ 16 weeks). All participants receive a leaflet on stopping smoking during pregnancy; they are also able to access standard NHS smoking cessation support. Intervention group women also receive the 12-week MiQuit programme of tailored, interactive text message, and self-help cessation support. Women are followed up by telephone at 4 weeks after randomisation and 36 weeks' gestation. The RCT will recruit 692 women (346 per group), enabling a 95% confidence interval for the difference in quit rates to be estimated within ± 3%. To determine whether or not MiQuit helps pregnant smokers to stop, intervention group quit rates from this trial will be combined with those from the two earlier trials in a Trial Sequential Analysis (TSA) meta-analysis to derive a pooled efficacy estimate. DISCUSSION: If effective, MiQuit will be a cheap, cost-effective method to help pregnant women to stop smoking. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT03231553 . Registered on 20 July 2017.

Do cognitive heuristics underpin symptom appraisal for symptoms of cancer?: A secondary qualitative analysis across seven cancers.

OBJECTIVES: To explore the evidence for cognitive heuristics or "rules of thumb" used within patients' reports of symptom appraisal and decisions to seek help for symptoms of cancer. METHODS: A secondary analysis of interviews from existing studies that explored symptom appraisal in patients who had sought help for potential symptoms of cancer. Transcripts from n = 50 in-depth interviews with patients referred with symptoms suspicious of cancer (pancreas, colorectal, oral, lung, melanoma, breast, and prostate) were re-analysed using a deductive thematic approach underpinned by the heuristics outlined in the Common Sense Model of Illness Self-regulation as set within the Model of Pathways to Treatment. RESULTS: The most dominant heuristic in patient reports was the Rate of change rule (ie, symptoms that are worsening, increasing, or have a sudden onset [rather than improving, stable or decreasing in number] are more likely to indicate illness). There was also support for the Duration rule, Pattern rule, Chronology rule, Severity (of interference) rule, Age-illness rule, Novelty rule, Similarity rule, Location rule, and Optimistic bias rule. There was a lack of evidence for the Prevalence and Stress-illness rules. CONCLUSIONS: People do appear to use heuristics to guide their appraisal of symptoms and their perceived need for healthcare. Heuristics may be an important aspect underlying symptom misinterpretation, thus making them key targets for interventions. For instance, campaigns could tackle cognitive biases rather than focusing on specific symptom awareness. Myth-busting messages could highlight that intermittent, mild symptoms, and symptoms that are not worsening can be signs of a serious health problem.