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.

Effects of an Increased Financial Incentive on Follow-up in an Online, Automated Smoking Cessation Trial: A randomized Controlled Study Within a Trial.

INTRODUCTION: Poor retention in clinical trials can impact on statistical power, reliability, validity, and generalizability of findings and is a particular challenge in smoking cessation studies. In online trials with automated follow-up mechanisms, poor response also increases the resource need for manual follow-up. This study compared two financial incentives on response rates at 6 months follow up, in an online, automated smoking cessation feasibility trial of a cessation smartphone app (Quit Sense). AIMS AND METHODS: A study within a trial (SWAT), embedded within a host randomized controlled trial. Host trial participants were randomized 1:1 to receive either a £10 or £20 voucher incentive, for completing the 6-month questionnaire. Stratification for randomization to the SWAT was by minimization to ensure an even split of host trial arm participants and by 6-week response rate. Outcome measures were: Questionnaire completion rate, time to completion, number of completers requiring manual follow-up, and completeness of responses. RESULTS: Two hundred and four participants were randomized to the SWAT. The £20 and £10 incentives did not differ in completion rate at 6 months (79% vs. 74%; p = .362) but did reduce the proportion of participants requiring manual follow-up (46% vs. 62%; p = .018) and the median completion time (7 days vs. 15 days; p = .008). Measure response completeness rates were higher among £20 incentive participants, though differences were small for the host trial's primary smoking outcome. CONCLUSIONS: Benefits to using relatively modest increases in incentive for online smoking cessation trials include more rapid completion of follow-up questionnaires and reduced manual follow-up. IMPLICATIONS: A modest increase in incentive (from £10 to £20) to promote the completion of follow-up questionnaires in online smoking cessation trials may not increase overall response rates but could lead to more rapid data collection, a reduced need for manual follow-up and reduced missing data among those who initiate completing a questionnaire. Such an improvement may help to reduce bias, increase validity and generalizability, and improve statistical power in smoking cessation trials. TRIAL REGISTRATION: Host trial ISRCTN12326962, SWAT repository store ID 164.

CompreHensive geriAtRician-led MEdication Review (CHARMER): protocol for a feasibility study of a hospital deprescribing behaviour change intervention.

INTRODUCTION: Over 50% of older adults are prescribed a medicine where the risk of harm outweighs the chances of benefit. During a hospital admission, older adults and carers expect medicines to be reviewed for appropriateness and any inappropriate medicines proactively deprescribed. While the principle of proactive deprescribing is an expectation of good prescribing practice, it is yet to become routine. The CompreHensive geriAtRician-led MEdication Review (CHARMER) study aims to develop and test a five-component behaviour change intervention to equip geriatricians and pharmacists to proactively deprescribe inappropriate medicines with older adults in hospital. This study aims to test the feasibility and acceptability of study processes and CHARMER implementation. METHODS AND ANALYSIS: A two-arm purposive allocation feasibility study is being undertaken at four acute hospitals in England, UK (three intervention and one control). The target sample is 400 patients across all hospitals. Primary outcome measures are: (1) participant recruitment rate and (2) participant attrition rate. Secondary outcome measures are: (1) hospital readmission rate; (2) mortality rate and (3) quality of life. Quantitative data will be checked for completeness and quality, and practitioner and patient demographics descriptively analysed. We will undertake a rapid qualitative analysis on observations, interviews and study meeting minutes data. A subsequent thematic analysis will be undertaken with codes mapped to the Theoretical Domains Framework and Normalisation Process Theory. Triangulation of qualitative and quantitative data will be undertaken. ETHICS AND DISSEMINATION: Ethics approval was obtained from Wales Research Ethics Committee 1 (IRAS ID 312494) and study approval from the Health Research Authority (22/WA/0087). Informed consent will be sought from all hospital staff involved in data collection activities and for patients involved in enhanced data collection activities. The findings of this study will be disseminated in peer-reviewed journals and conference presentations. TRIAL REGISTRATION: ISRCTN11899506.

Multicentre evaluation of two multiplex PCR platforms for the rapid microbiological investigation of nosocomial pneumonia in UK ICUs: the INHALE WP1 study.

BACKGROUND: Culture-based microbiological investigation of hospital-acquired or ventilator-associated pneumonia (HAP or VAP) is insensitive, with aetiological agents often unidentified. This can lead to excess antimicrobial treatment of patients with susceptible pathogens, while those with resistant bacteria are treated inadequately for prolonged periods. Using PCR to seek pathogens and their resistance genes directly from clinical samples may improve therapy and stewardship. METHODS: Surplus routine lower respiratory tract samples were collected from intensive care unit patients about to receive new or changed antibiotics for hospital-onset lower respiratory tract infections at 15 UK hospitals. Testing was performed using the BioFire FilmArray Pneumonia Panel (bioMérieux) and Unyvero Pneumonia Panel (Curetis). Concordance analysis compared machine and routine microbiology results, while Bayesian latent class (BLC) analysis estimated the sensitivity and specificity of each test, incorporating information from both PCR panels and routine microbiology. FINDINGS: In 652 eligible samples; PCR identified pathogens in considerably more samples compared with routine microbiology: 60.4% and 74.2% for Unyvero and FilmArray respectively vs 44.2% by routine microbiology. PCR tests also detected more pathogens per sample than routine microbiology. For common HAP/VAP pathogens, FilmArray had sensitivity of 91.7%-100.0% and specificity of 87.5%-99.5%; Unyvero had sensitivity of 50.0%-100.0%%, and specificity of 89.4%-99.0%. BLC analysis indicated that, compared with PCR, routine microbiology had low sensitivity, ranging from 27.0% to 69.4%. INTERPRETATION: Conventional and BLC analysis demonstrated that both platforms performed similarly and were considerably more sensitive than routine microbiology, detecting potential pathogens in patient samples reported as culture negative. The increased sensitivity of detection realised by PCR offers potential for improved antimicrobial prescribing.