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.

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.

Cost-effectiveness analysis of two interventions to promote physical activity in a multiethnic population at high risk of diabetes: an economic evaluation of the 48-month PROPELS randomized controlled trial.

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.

Biofeedback and Digitalized Motivational Interviewing to Increase Daily Physical Activity: Series of Factorial N-of-1 Randomized Controlled Trials Piloting the Precious App.

BACKGROUND: Insufficient 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. OBJECTIVE: This 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. METHODS: In 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). RESULTS: All 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<.001), motivation (B=0.390; P<.001), and pain or illness (B=-1524; P<.001) on daily steps. CONCLUSIONS: The automated factorial N-of-1 trial with the Precious app was mostly feasible and acceptable, especially the automated delivery of the dMI components, whereas self-conducted biofeedback measurements were more difficult to time correctly. The findings suggest that changes in self-efficacy and motivation may have same-day effects on physical activity, but the effects vary across individuals. This study provides recommendations based on the lessons learned on the implementation of factorial N-of-1 RCTs.

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.

Evaluating the Effectiveness of Remote Behavioral Interventions Facilitated by Health Care Providers at Improving Medication Adherence in Cardiometabolic Conditions: A Systematic Review and Meta-Analysis.

BACKGROUND: Although cardiometabolic conditions account for over 32% of all global deaths, nearly half of the patients with cardiometabolic conditions do not take medication as prescribed. Remote behavioral interventions have been shown to potentially improve adherence in these patients and further support cost effective clinical practice. PURPOSE: To evaluate the effectiveness of remote behavioral interventions at improving treatment adherence and to explore behavioral intervention components associated with it. METHODS: We searched MEDLINE, EMBASE, PsycINFO, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Web of Science in April 2021. Random-effects meta-analyses were utilized. RESULTS: In total, 40 studies, including 24,672 participants, were included. The overall quality of evidence, assessed using the RoB2 tool, was low. The intervention had a small (odds ratios [OR] = 1.70, 95% CI: 1.47, 1.96, N = 4823 p < .001) to moderate effect (SMD = 0.57, 95% CI: 0.38, 0.76, N = 20,271, p < .001) on the dichotomous and continuous outcomes, respectively. Systolic blood pressure (SBP) was reduced by 3.71 mmHg (95% CI: 3.99, 3.43, N = 6,527, p < .001) and participants receiving the intervention were twice more likely to achieve blood pressure (BP) control (OR = 2.14, 95% CI: 1.61, 2.84, N = 1,172, p < .001). Generally, HBA1c decreased by 0.25% (95% CI: 0.33, 0.17, N = 6,734, p < .001), whereas low-density lipoprotein (LDL)-cholesterol dropped by 6.82 mg/dL (95% CI: 8.33, 5.30, N = 4,550, p < .001) in favor of the intervention. There was a trend suggesting a potential positive effects on reducing visits to emergency department (OR=0.76, 95% CI: 0.57, 1.01, N = 4,182) and mortality rates (OR=0.78, 95% CI: 0.42, 1.42, N = 1,971), and no risk for hospital readmission (OR=1.00, 95% CI: 0.83, 1.20, N = 5,402), favoring the intervention. CONCLUSIONS: Despite low quality of evidence, remote consultations are effective at improving medication adherence and clinical indicators, and potentially cost-effective solution for health care services.

A Systematic Review and Meta-analysis of Face-to-face Medication Adherence Interventions for Patients with Long Term Health Conditions.

BACKGROUND: Although previous reviews demonstrated effectiveness related to medication adherence interventions, they incorporated various digital platforms and other multiple delivery modes, which makes difficult to distinguish what aspects of the interventions led to effectiveness. PURPOSE: This review aimed to (i) estimate the efficacy of face-to-face medication adherence interventions on adherence outcomes, in adults with Long Term Health Conditions (LTHCs) and (ii) identify the Behaviour Change Techniques (BCTs) used in the interventions and examine their potential impact on efficacy. METHODS: Cochrane Controlled Register of Trials, Embase, MEDLINE (Ovid), PsycINFO, Web of Science, PubMed, and Scopus databases were searched. Randomized controlled trials were included if they described an intervention to improve medication adherence, delivered via face-to-face only, and included patients with LTHCs. Studies were excluded if they used additional delivery modes, involved family members or used a group format. In addition, use of BCTs was coded. RESULTS: 20 studies were included (n = 3667). Statistically significant pooled effects were found favoring the intervention than control, for the following MEMS (electronic monitoring) measures: percentage of prescribed doses taken on time over a period of 3 weeks to 2 months (MD 9.34, 95% CI 4.36-14.33, p = .0002; I2 =0%); percentage of prescribed doses taken for a period of 1 week to 2 months (MD 5.63, 95% CI 1.62-9.64, p = .006; I2 = 51%) and for 1 month (OR = 2.51, 95% CI 1.37-4.57, p = .003; I2 = 0%); percentage of days correct doses taken for 1 month to 14 weeks (MD 6.59, 95% CI 0.74-13.15, p = .03; I2 = 68%). Studies using the Morisky scale showed a significant between group difference for 1-3 months (MD 0.86, 95% CI 0.59-1.13, p < .00001; I2 = 0%). Overall, more BCTs were identified in intervention conditions than in comparison conditions (22 vs. 10). The impact of BCTs on intervention effectiveness could not be established as the analyses were underpowered. CONCLUSIONS: Face-to-face interventions increased adherence to medication among adult patients with LTHCs. Although we were able to identify BCTs among interventions, data were insufficient to determine the impact of particular BCTs on intervention effectiveness.

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.

Patient and practitioner views on a combined face-to-face and digital intervention to support medication adherence in hypertension: a qualitative study within primary care.

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.

Will 'the feeling of abandonment' remain? Persisting impacts of the COVID-19 pandemic on rheumatology patients and clinicians.

OBJECTIVE: To better understand rheumatology patient and clinician pandemic-related experiences, medical relationships and behaviours in order to help identify the persisting impacts of the COVID-19 pandemic and inform efforts to ameliorate the negative impacts and build upon the positive ones. METHODS: Rheumatology patients and clinicians completed surveys (patients n = 1543, clinicians n = 111) and interviews (patients n = 41, clinicians n = 32) between April 2021 and August 2021. A cohort (n = 139) of systemic autoimmune rheumatic disease patients was also followed up from March 2020 to April 2021. Analyses used sequential mixed methods. Pre-specified outcome measures included the Warwick-Edinburgh Mental wellbeing score (WEMWBS), satisfaction with care and healthcare behaviours. RESULTS: We identified multiple ongoing pandemic-induced/increased barriers to receiving care. The percentage of patients agreeing they were medically supported reduced from 74.4% pre-pandemic to 39.7% during-pandemic. Ratings for medical support, medical security and trust were significantly (P <0.001) positively correlated with patient WEMWBS and healthcare behaviours, and decreased during the pandemic. Healthcare-seeking was reduced, potentially long-term, including from patients feeling 'abandoned' by clinicians, and a 'burden' from government messaging to protect the NHS. Blame and distrust were frequent, particularly between primary and secondary care, and towards the UK government, who <10% of clinicians felt had supported clinicians during the pandemic. Clinicians' efforts were reported to be impeded by inefficient administration systems and chronic understaffing, suggestive of the pandemic having exposed and exacerbated existing healthcare system weaknesses. CONCLUSION: Without concerted action-such as rebuilding trust, improved administrative systems and more support for clinicians-barriers to care and negative impacts of the pandemic on trust, medical relationships, medical security and patient help-seeking may persist in the longer term. TRIAL REGISTRATION: This study is part of a pre-registered longitudinal multi-stage trial, the LISTEN study (ISRCTN-14966097), with later COVID-related additions registered in March 2021, including a pre-registered statistical analysis plan.

Telemedicine in rheumatology: a mixed methods study exploring acceptability, preferences and experiences among patients and clinicians.

OBJECTIVES: The Covid-19 pandemic necessitated a rapid global transition towards telemedicine; yet much remains unknown about telemedicine's acceptability and safety in rheumatology. To help address this gap and inform practice, this study investigated rheumatology patient and clinician experiences and views of telemedicine. METHODS: Sequential mixed methodology combined analysis of surveys and in-depth interviews. Between and within-group differences in views of telemedicine were examined for patients and clinicians using t-tests. RESULTS: Surveys (patients n = 1340, clinicians n = 111) and interviews (patients n = 31, clinicians n = 29) were completed between April 2021 and July 2021. The majority of patients were from the UK (96%) and had inflammatory arthritis (32%) or lupus (32%). Patients and clinicians rated telemedicine as worse than face-to-face consultations in almost all categories, although >60% found it more convenient. Building trusting medical relationships and assessment accuracy were great concerns (93% of clinicians and 86% of patients rated telemedicine as worse than face-to-face for assessment accuracy). Telemedicine was perceived to have increased misdiagnoses, inequalities and barriers to accessing care. Participants reported highly disparate telemedicine delivery and responsiveness from primary and secondary care. Although rheumatology clinicians highlighted the importance of a quick response to flaring patients, only 55% of patients were confident that their rheumatology department would respond within 48 hours. CONCLUSION: Findings indicate a preference for face-to-face consultations. Some negative experiences may be due to the pandemic rather than telemedicine specifically, although the risk of greater diagnostic inaccuracies using telemedicine is unlikely to be fully resolved. Training, choice, careful patient selection, and further consultation with clinicians and patients is required to increase telemedicine's acceptability and safety. TRIAL REGISTRATION: This telemedicine study is part of a pre-registered longitudinal multi-stage trial, the LISTEN study (ISRCTN-14966097), with later Covid-related additions registered in March 2021, including a pre-registered statistical analysis plan.

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.

Medication decision-making and adherence in lupus: patient-physician discordance and the impact of previous 'adverse medical experiences'.

OBJECTIVES: Medication adherence is critical in the successful management of lupus. There is very limited existing literature on reasons why non-adherence is not reported. This study explores the impact of current and previous medical experiences on patient satisfaction, adherence and reporting of non-adherence. METHODS: Mixed methodology involved thematic analysis of in-depth interviews (n = 23) to further explore the statistically analysed quantitative survey findings (n = 186). RESULTS: This study identified five themes: (i) physician-patient discordance and a 'hierarchy of evidence' in medication decisions; (ii) the association of adherence with satisfaction with care; (iii) the persisting impact of past adverse medical experiences (AMEs); (iv) the dynamic balance of patient-physician control; and (v) holistic care, beyond a purely medication-based focus. Improving quality of life (43% of participants) and a supportive medical relationship (24%) were the main reasons for adherence. Patient-priorities and self-reported symptoms were perceived as less important to physicians than organ-protection and blood results. Non-reporters of non-adherence, non-adherers and those with past AMEs (e.g. psychosomatic misdiagnoses) had statistically significant lower satisfaction with care. The importance of listening to patients was a key component of every theme, and associated with patient satisfaction and adherence. The mean rating for rheumatologist's listening skills was 2.88 for non-adherers compared with 3.53 for other participants (mean difference 0.65, P = 0.003). CONCLUSION: Patients would like more weight and discussion given to self-reported symptoms and quality of life in medication decisions. Greater understanding and interventions are required to alleviate the persisting impact of past AMEs on some patients' wellbeing, behaviour and current medical relationships.

Characteristics of smartphone-based dietary assessment tools: a systematic review.

Smartphones have become popular in assessing eating behaviour in real-life and real-time. This systematic review provides a comprehensive overview of smartphone-based dietary assessment tools, focusing on how dietary data is assessed and its completeness ensured. Seven databases from behavioural, social and computer science were searched in March 2020. All observational, experimental or intervention studies and study protocols using a smartphone-based assessment tool for dietary intake were included if they reported data collected by adults and were published in English. Out of 21,722 records initially screened, 117 publications using 129 tools were included. Five core assessment features were identified: photo-based assessment (48.8% of tools), assessed serving/ portion sizes (48.8%), free-text descriptions of food intake (42.6%), food databases (30.2%), and classification systems (27.9%). On average, a tool used two features. The majority of studies did not implement any features to improve completeness of the records. This review provides a comprehensive overview and framework of smartphone-based dietary assessment tools to help researchers identify suitable assessment tools for their studies. Future research needs to address the potential impact of specific dietary assessment methods on data quality and participants' willingness to record their behaviour to ultimately improve the quality of smartphone-based dietary assessment for health research.

Cluster randomised controlled trial of screening for atrial fibrillation in people aged 70 years and over to reduce stroke: protocol for the pilot study for the SAFER trial.

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.

Reducing bias in trials from reactions to measurement: the MERIT study including developmental work and expert workshop.

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.

When people are asked to complete measures such as questionnaires in research studies this can produce changes in the behaviour or emotions of those people. For example, people who are asked to complete questionnaires about drinking alcohol have been found to drink slightly less, on average, than people who are not asked to complete questionnaires. Current established methods of research usually ignore these reactions to measurement. The present research aimed to produce recommendations for how best to deal with reactions to measurement. The scope of these recommendations was limited to 'trials' used to test whether or not a treatment improves health. To do this, we identified relevant research studies that have investigated various different aspects of whether or not measurement affects the people being measured. We then consulted 40 experts about what the current recommendations should consider and what was not within the scope of the current recommendations. We then gathered 23 experts together for 2 days to produce a set of recommendations. We found 43 research studies that have looked at whether or not being asked to complete questionnaires or being interviewed affects the behaviour of those people invited. In general, there were some effects of completing questionnaires, but the effects were not very consistent across research studies. There were few studies that have looked at the effects of using measures of behaviour other than questionnaires (e.g. blood pressure cuffs). We could find no existing recommendations for how best to deal with reactions to measurement in research studies that examine whether or not treatments improve health. We have produced 14 recommendations for researchers to better take account of the issue of measuring affecting the people being measured. We hope that this will help future research produce more accurate answers. We also identified that there is a need for more studies of the effects of measures other than questionnaires.

Reducing bias in trials due to reactions to measurement: experts produced recommendations informed by evidence.

OBJECTIVE: This study (MEasurement Reactions In Trials) aimed to produce recommendations on how best to minimize bias from measurement reactivity (MR) in randomized controlled trials of interventions to improve health. STUDY DESIGN AND SETTING: The MERIT study consisted of: (1) an updated systematic review that examined whether measuring participants had effects on participants' health-related behaviors, relative to no-measurement controls, and three rapid reviews to identify: (i) existing guidance on MR; (ii) existing systematic reviews of studies that have quantified the effects of measurement on behavioral or affective outcomes; and (iii) studies that have investigated the effects of objective measurements of behavior on health-related behavior; (2) a Delphi study to identify the scope of the recommendations; and (3) an expert workshop in October 2018 to discuss potential recommendations in groups. RESULTS: Fourteen recommendations were produced by the expert group to: (1) identify whether bias is likely to be a problem for a trial; (2) decide whether to collect data about whether bias is likely to be a problem; (3) design trials to minimize the likelihood of this bias. CONCLUSION: These recommendations raise awareness of how and where taking measurements can produce bias in trials, and are thus helpful for trial design.

Modelling the Reallocation of Time Spent Sitting into Physical Activity: Isotemporal Substitution vs. Compositional Isotemporal Substitution.

Isotemporal substitution modelling (ISM) and compositional isotemporal modelling (CISM) are statistical approaches used in epidemiology to model the associations of replacing time in one physical behaviour with time in another. This study's aim was to use both ISM and CISM to examine and compare associations of reallocating 60 min of sitting into standing or stepping with markers of cardiometabolic health. Cross-sectional data collected during three randomised control trials (RCTs) were utilised. All participants (n = 1554) were identified as being at high risk of developing type 2 diabetes. Reallocating 60 min from sitting to standing and to stepping was associated with a lower BMI, waist circumference, and triglycerides and higher high-density lipoprotein cholesterol using both ISM and CISM (p < 0.05). The direction and magnitude of significant associations were consistent across methods. No associations were observed for hemoglobin A1c, total cholesterol, or low-density lipoprotein cholesterol for either method. Results of both ISM and CISM were broadly similar, allowing for the interpretation of previous research, and should enable future research in order to make informed methodological, data-driven decisions.

Promoting physical activity in a multi-ethnic population at high risk of diabetes: the 48-month PROPELS randomised controlled trial.

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).