Pilot Study of the Use of Personal Carbon Monoxide Monitoring to Achieve Radical Smoking Reduction

Implementation of a smoking cessation intervention for people with severe mental illness in ambulatory mental healthcare (KISMET): A process evaluation

BACKGROUND

Recently, a cluster-randomised controlled trial was conducted within Dutch ambulatory mental healthcare to assess the effectiveness of a one-year smoking cessation intervention consisting of group sessions, peer support and pharmacological treatment (KISMET). This article presents its process evaluation, exploring the perceptions of patients and mental healthcare professionals (MHPs) regarding the implementation of KISMET.

METHODS

We conducted a mixed methods study, including 26 semi-structured interviews (10 MHPs and 16 patients) following the RE-AIM framework. Qualitative data was thematically analysed with MAXQDA software. We collected additional data on inclusion, drop-out and assessed treatment adherence during on-site observations.

RESULTS

Recruitment and subsequent retention of patients in the RCT was found to be challenging (58% drop-out at one-year follow-up). MHPs suggested more motivational enhancement techniques to aid recruitment and reduce study attrition. The intervention components were generally assessed positively. Patients experienced the group and peer support sessions as supportive and beneficial. Inconsistent group attendance was demotivating and disrupted implementation. Pharmacological treatment was found to be helpful, although MHPs mentioned the treating psychiatrist or clinical nurse specialist need to facilitate better to ensure medication supply. The handbook offered MHPs excellent guidance and significantly contributed to treatment fidelity. Surprisingly, the carbon monoxide monitoring (originally included in the study protocol for research purposes) was appraised as a motivational tool. Finally, shortage of staff, limited collaboration and high turnover were barriers for the delivery of the intervention. Implementation heavily depends on the quality of the collaboration between MHPs and patients, as well as the infrastructure created by the organisation.

CONCLUSION

This study demonstrates the benefits, unique demands and challenges of a smoking cessation intervention for people with SMI. Results could guide and improve the implementation of smoking cessation interventions in mental healthcare settings. Fostering a culture of connectivity through team development, along with the provision of supportive and communicative supervision is critical for the effective recruitment and retention in smoking cessation studies in psychiatric care.

Lottery incentives for smoking cessation at the workplace: design and protocol of the smoke-free lottery - a cluster randomized trial

BACKGROUND

Smoking is the leading behavioral risk factor for the loss of healthy life years. Many smokers want to quit, but have trouble doing so. Financial incentives in workplace settings have shown promising results in supporting smokers and their design influences their impact. Lotteries that leverage behavioral economic insights might improve the effectiveness of workplace cessation support.

METHODS AND DESIGN

We examine in a cluster randomized trial if a workplace cessation group training paired with lottery deadlines will increase continuous abstinence rates over and above the cessation training alone. Organizations are randomized to either the control arm or lottery arm. The lotteries capitalize regret aversion by always informing winners at the deadline, but withholding prizes if they smoked. In the lottery-arm, winners are drawn out of all participants within a training group, regardless of their smoking status. In weeks 1-13 there are weekly lotteries. Winners are informed about their prize (€50), but can only claim it if they did not smoke that week, validated biochemically. After 26 weeks, there is a long-term lottery where the winners are informed about their prize (vacation voucher worth €400), but can only claim it if they were abstinent between weeks 13 and 26. The primary outcome is continuous abstinence 52 weeks after the quit date.

DISCUSSION

There is a quest for incentives to support smoking cessation that are considered fair, affordable and effective across different socioeconomic groups. Previous use of behavioral economics in the design of lotteries have shown promising results in changing health behavior. This cluster randomized trial aims to demonstrate if these lotteries are also effective for supporting smoking cessation. Therefore the study design and protocol are described in detail in this paper. Findings might contribute to the application and development of effective cessation support at the workplace.

TRIAL REGISTRATION

Netherlands Trial Register Identifier: NL8463 . Date of registration: 17-03-2020.

Outcomes of a Comprehensive Mobile Smoking Cessation Program With Nicotine Replacement Therapy in Adult Smokers: Pilot Randomized Controlled Trial

BACKGROUND

Cigarette smoking remains the leading cause of preventable illness and death, underscoring ongoing need for evidence-based solutions. Pivot, a US Clinical Practice Guideline-based mobile smoking cessation program, comprises a personal carbon monoxide breath sensor; a smartphone app; in-app, text-based human-provided coaching; nicotine replacement therapy; and a moderated web-based community. Promising Pivot cohort studies have established the foundation for comparative assessment.

OBJECTIVE

This study aimed to compare engagement, retention, attitudes toward quitting smoking, smoking behavior, and participant feedback between Pivot and QuitGuide, a US Clinical Practice Guideline-based smoking cessation smartphone app from the National Cancer Institute.

METHODS

In this remote pilot randomized controlled trial, cigarette smokers in the United States were recruited on the web and randomized to Pivot or QuitGuide. Participants were offered 12 weeks of free nicotine replacement therapy. Data were self-reported via weekly web-based questionnaires for 12 weeks and at 26 weeks. Outcomes included engagement and retention, attitudes toward quitting smoking, smoking behavior, and participant feedback. The primary outcome was self-reported app openings at 12 weeks. Cessation outcomes included self-reported 7- and 30-day point prevalence abstinence (PPA), abstinence from all tobacco products, and continuous abstinence at 12 and 26 weeks. PPA and continuous abstinence were biovalidated via breath carbon monoxide samples.

RESULTS

Participants comprised 188 smokers (94 Pivot and 94 QuitGuide): mean age 46.4 (SD 9.2) years, 104 (55.3%) women, 128 (68.1%) White individuals, and mean cigarettes per day 17.6 (SD 9.0). Engagement via mean "total app openings through 12 weeks" (primary outcome) was Pivot, 157.9 (SD 210.6) versus QuitGuide, 86.5 (SD 66.3; P<.001). Self-reported 7-day PPA at 12 and 26 weeks was Pivot, 35% (33/94) versus QuitGuide, 28% (26/94; intention to treat [ITT]: P=.28) and Pivot, 36% (34/94) versus QuitGuide, 27% (25/94; ITT: P=.12), respectively. Self-reported 30-day PPA at 12 and 26 weeks was Pivot, 29% (27/94) versus QuitGuide, 22% (21/94; ITT: P=.32) and Pivot, 32% (30/94) versus QuitGuide, 22% (21/94; ITT: P=.12), respectively. The biovalidated abstinence rate at 12 weeks was Pivot, 29% (27/94) versus QuitGuide, 13% (12/94; ITT: P=.008). Biovalidated continuous abstinence at 26 weeks was Pivot, 21% (20/94) versus QuitGuide, 10% (9/94; ITT: P=.03). Participant feedback, including ease of setup, impact on smoking, and likelihood of program recommendation were favorable for Pivot.

CONCLUSIONS

In this randomized controlled trial comparing the app-based smoking cessation programs Pivot and QuitGuide, Pivot participants had higher engagement and biovalidated cessation rates and more favorable user feedback at 12 and 26 weeks. These findings support Pivot as an effective, durable mobile smoking cessation program.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04955639; https://clinicaltrials.gov/ct2/show/NCT04955639.

An innovation involving self-surveillance and serious gaming to increase smoking quit rate: Protocol for a pilot randomized controlled trial

Smoking is a health hazard. Current smoking cessation measures such as behavioral change counselling by trained professionals, nicotine replacement therapy and medications have limited success. Smoking intensity is assessed using a portable device to measure the smokers’ exhaled breath carbon monoxide (eCO) level. A systematic review suggests the potential of serious gaming to increase smoking quit rate. However, the related studies were unable to explain and determine the effect gamification on smoking cessation.

A handy personalized eCO measurement device linked to a smart-phone applications (app) has been developed (integrated STEADES-2 system). This novel system incorporates app-based video and print learning resources, authentication function and gamification using the eCO data as game element. Trained multidisciplinary healthcare professionals access the STEADES-2 data to monitor smoking status and support smokers via asynchronous virtual coaching. The pilot randomized controlled trial will enroll 20 smokers to use the STEADES-2 system (intervention group) and another 20 to the existing smoking cessation programme (control group) in primary care. The primary feasibility outcomes will include the recruitment response rate, the smokers’ usability of the STEADES-2 system, their self eCO monitoring, frequencies of participation in the serious games and interactions with their virtual coaches. Their smoking literacy, utility and experience of the STEADES-2 system are other outcomes. Smokers in both groups will be compared on their cigarette abstinence as secondary outcome based on eCO levels and urine cotinine test (primary outcomes after 12 weeks).

The results will be disseminated via conferences and publications.

Durability of Abstinence After Completing a Comprehensive Digital Smoking Cessation Program Incorporating a Mobile App, Breath Sensor, and Coaching: Cohort Study

BACKGROUND

Despite decreasing prevalence over the last several decades, cigarette smoking remains the leading cause of preventable death and disease, underscoring the need for innovative, effective solutions. Pivot is a novel, inclusive smoking cessation program designed for smokers along the entire spectrum of readiness to quit. Pivot leverages proven methods and technological advancements, including a personal portable breath carbon monoxide sensor, smartphone app, and in-app text-based coaching. We previously reported outcomes from the end of active Pivot program participation in 319 adult smokers. Herein, we report longer-term follow up in this cohort.

OBJECTIVE

The aim of this study was to assess and report participant outcomes 3 months after completion of Pivot, including smoking behavior, quit rates, continuous abstinence rates and durability, and predictors of abstinence.

METHODS

This prospective remote cohort study included US-based cigarette smokers aged 18 to 65 years who smoked ≥5 cigarettes per day (CPD). Three months after completion of active participation in Pivot, final follow-up data were collected via an online questionnaire. Outcomes included smoking behavior (CPD and quit attempts), self-reported quit rates (7- and 30-day point prevalence abstinence [PPA]), and continuous abstinence rates (proportion who achieved uninterrupted abstinence) and duration. Exploratory regression analyses were performed to identify baseline characteristics associated with achievement of 7-day PPA, 30-day PPA, and continuous abstinence.

RESULTS

A total of 319 participants completed onboarding (intention-to-treat [ITT]); 288/319 participants (90.3%) completed follow up (completers) at a mean of 7.2 (SD 1.2) months after onboarding. At final follow up, CPD were reduced by 52.6% (SE 2.1; P<.001) among all 319 participants, and most completers (152/288, 52.8%) reduced their CPD by at least 50%. Overall, most completers (232/288, 80.6%) made at least one quit attempt. Quit rates increased after the end of Pivot; using ITT analyses, 35.4% (113/319) achieved 7-day PPA and 31.3% (100/319) achieved 30-day PPA at final follow up compared with 32.0% (102/319) and 27.6% (88/319), respectively, at the end of the Pivot program. Continuous abstinence was achieved in about a quarter of those who onboarded (76/319, 23.8%) and in most who reported 30-day PPA at the end of Pivot (76/88, 86.4%), with a mean abstinence duration of 5.8 (SD 0.6) months. In exploratory regression analyses, lower baseline CPD, more positive baseline attitudes reflecting higher self-efficacy (higher confidence to quit and lower perceived difficulty of quitting), and higher education were associated with achieving abstinence.

CONCLUSIONS

This study provides the first longer-term outcomes of the Pivot smoking cessation program. At final follow up, quit rates increased and continuous abstinence was favorable; the majority who achieved abstinence at the end of Pivot sustained abstinence throughout follow up. Decreases in CPD persisted and most participants made a quit attempt. Overall, final follow-up outcomes were stable or improved when compared to previous outcomes from the end of the program. These findings validate earlier results, and suggest that Pivot is an effective and durable solution for smoking cessation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03295643; https://clinicaltrials.gov/ct2/show/NCT03295643.

Assessment of a Personal Interactive Carbon Monoxide Breath Sensor in People Who Smoke Cigarettes: Single-Arm Cohort Study

Background

Tobacco use is the leading cause of preventable morbidity and mortality. Existing evidence-based treatments are underutilized and have seen little recent innovation. The success of personal biofeedback interventions in other disease states portends a similar opportunity in smoking cessation. The Pivot Breath Sensor is a personal interactive FDA-cleared (over-the-counter) device that measures carbon monoxide (CO) in exhaled breath, enabling users to link their smoking behavior and CO values, and track their progress in reducing or quitting smoking.

Objective

The objective of this study is to assess the Pivot Breath Sensor in people who smoke cigarettes, evaluating changes in attitudes toward quitting smoking, changes in smoking behavior, and use experience.

Methods

US adults (18-80 years of age, ≥10 cigarettes per day [CPD]) were recruited online for this remote 12-week study. Participants completed a screening call, informed consent, and baseline questionnaire, and then were mailed their sensor. Participants were asked to submit 4 or more breath samples per day and complete questionnaires at 1-4, 8, and 12 weeks. Outcomes included attitudes toward quitting smoking (Stage of Change, success to quit, and perceived difficulty of quitting), smoking behavior (quit attempts, CPD reduction, and 7-, 30-day point prevalence abstinence [PPA]), and use experience (impact and learning).

Results

Participants comprised 234 smokers, mean age 39.9 (SD 11.3) years, 52.6% (123/234) female, mean CPD 20.3 (SD 8.0). The 4- and 12-week questionnaires were completed by 92.3% (216/234) and 91.9% (215/234) of participants, respectively. Concerning attitude outcomes, at baseline, 15.4% (36/234) were seriously thinking of quitting in the next 30 days, increasing to 38.9% (84/216) at 4 weeks and 47.9% (103/215) at 12 weeks (both P<.001). At 12 weeks, motivation to quit was increased in 39.1% (84/215), unchanged in 54.9% (118/215), and decreased in 6.0% (13/215; P<.001). Additional attitudes toward quitting improved from baseline to 12 weeks: success to quit 3.3 versus 5.0 (P<.001) and difficulty of quitting 2.8 versus 4.3 (P<.001). Regarding smoking behavior, at 4 weeks, 28.2% (66/234) had made 1 or more quit attempts (≥1 day of abstinence), increasing to 48.3% (113/234) at 12 weeks. At 4 weeks, 23.1% (54/234) had reduced CPD by 50% or more, increasing to 38.5% (90/234) at 12 weeks. At 12 weeks, CPD decreased by 41.1% from baseline (P<.001), and 7- and 30-day PPA were 12.0% (28/234) and 6.0% (14/234), respectively. Concerning use experience, 75.3% (171/227) reported the sensor increased their motivation to quit. More than 90% (>196/214) indicated the sensor taught them about their CO levels and smoking behavior, and 73.1% (166/227) reported that seeing their CO values made them want to quit smoking.

Conclusions

Use of the Pivot Breath Sensor resulted in a significant increase in motivation to quit, a reduction in CPD, and favorable quit attempt rates. These outcomes confer increased likelihood of quitting smoking. Accordingly, the results support a role for biofeedback via personal CO breath sampling in smoking cessation.

Trial Registration

ClinicalTrials.gov NCT04133064; https://clinicaltrials.gov/ct2/show/NCT04133064

COach2Quit: A Pilot Randomized Controlled Trial of a Personal Carbon Monoxide Monitor for Smoking Cessation

INTRODUCTION

Mobile phone-based messaging support and biomarker feedback independently show evidence of increasing an individual's likelihood of quitting smoking. However, the combination of these two strategies to facilitate smoking cessation has not been adequately explored.

METHODS

We conducted a randomized controlled trial in Baltimore, Maryland, to assess the efficacy of COach2Quit, a smartphone application that provides exhaled carbon monoxide readings with message support. The primary outcome was self-reported and biochemically verified smoking cessation at 30-day follow-up. Secondary outcomes were reduction in smoking, motivation to quit, and engagement and satisfaction with COach2Quit. An intention-to-treat analysis was conducted.

RESULTS

Adult smokers were randomized 1:1 to receive brief advice and COach2Quit (intervention, n = 50) or brief advice only (control, n = 52). Thirteen participants were lost to follow-up. At 30-day follow-up, one participant in each arm quit smoking. Median change in carbon monoxide levels (in parts per million (ppm)) (intervention: -3.0 [interquartile range (IQR) -12.0, 2.0]; control: -2.5 [IQR -9.0, 2.0]) and median change in number of cigarettes smoked per day (intervention: -5.5 [IQR -14.0, -1.0]; control: -6.0 [IQR -10.0, -2.0]) was similar between study arms. There was no significant difference in mean percent change in the Reasons for Quitting scale score (intervention: 6.3 [95% confidence interval = -2.2% to 14.8%]; control: -3.6 [95% confidence interval = -9.2% to 2.1%]). A majority (n = 32, 91%) of participants liked having COach2Quit to help them quit smoking.

CONCLUSIONS

There were no significant differences in smoking cessation, smoking reduction, and motivation to quit between study arms. However, high satisfaction with the COach2Quit application indicates its feasibility and acceptability as a smoking cessation tool.

IMPLICATIONS

Smoking is the leading preventable cause of morbidity and mortality in the United States. Although counseling and pharmacotherapy are efficacious for smoking cessation, they are not easily accessible or desirable to all smokers, highlighting the need for identifying other interventions. There is evidence for the efficacy of mobile phone-based messaging support for smoking cessation. However, there is limited research on the efficacy of biomarker feedback, much less interventions that combine these two approaches. This research contributes to filling this gap and identifying novel interventions to facilitate smoking cessation.

Novel Application of Exhaled Carbon Monoxide Monitors: Smoking Cessation in Orthopaedic Trauma Patients

OBJECTIVES

To determine whether an in-office exhaled carbon monoxide (CO) monitor can increase interest in smoking cessation among the orthopaedic trauma population.

DESIGN

Prospective.

SETTING

Level I trauma center.

PATIENTS

One hundred twenty-four orthopaedic trauma patients.

INTERVENTION

In-office measurement of exhaled CO.

MAIN OUTCOME MEASURES

Stage of change, Likert scale score on willingness to quit today, patient's request for referral to a quitline, and increase in readiness to quit.

RESULTS

The use of an exhaled CO monitor increased willingness to quit in 71% of participants still smoking and increased willingness to quit on average by 0.8 points on a 10-point Likert scale (P < 0.001). Fifteen percent of patients modified their stage of change toward quitting. Forty percent of patients after exhaled CO monitor requested referral to a quitline, compared with 4% presurvey (P < 0.001). Anecdotally, most participants were very interested in the monitoring device and its reading, expressing concern with the result. The value of exhaled CO was not associated with any measured outcomes.

CONCLUSIONS

The use of an exhaled CO monitor increased willingness to quit smoking in 71% of patients, but the effect size was relatively small (0.8 points on a 10-point Likert scale). However, use of the CO monitor resulted in a large increase (40% vs. 4%) in referral to the national Quitline. Use of the Quitline typically increases the chance of smoking cessation by 10 times the baseline rate, suggesting that this finding might be clinically important.

LEVEL OF EVIDENCE

Therapeutic Level II. See Instructions for Authors for a complete description of levels of evidence.

Technology-based contingency management and e-cigarettes during the initial weeks of a smoking quit attempt

Contingency management (CM) interventions are among the most effective behavioral interventions for smoking. This study assessed the effects of CM and electronic cigarettes (ECs) on smoking reductions and abstinence for durations of 30-36 days. Twelve participants were exposed to Baseline, EC alone, and EC + CM conditions. An internet-based platform was used to monitor smoking via breath carbon monoxide (CO) and deliver CM for smoking abstinence (CO ≤4 ppm). A Bluetooth-enabled EC monitored daily EC puffs. Abstinence rates were equivalent between EC (34.4%) and EC + CM (30.4%) conditions. Both conditions promoted smoking reductions. We observed an inverse correlation between smoking and EC puffs (r = -.62, p < .05). Results suggest the use of electronic cigarettes can promote smoking reductions and abstinence, and CM did not improve these outcomes. Larger magnitude consequences or tailoring EC characteristics (e.g., flavor) may have improved outcomes. Technology-based methods to collect intensive, longitudinal measures of smoking and electronic cigarette use may be useful to characterize their environmental determinants.

Lessons learned from unsuccessful use of personal carbon monoxide monitors to remotely assess abstinence in a pragmatic trial of a smartphone stop smoking app - A secondary analysis

INTRODUCTION

Verifying abstinence remotely in trials of digital cessation interventions remains a major challenge. This study reports on using personal carbon monoxide (CO) monitors to assess abstinence in a pragmatic trial of a standalone cessation app involving automated recruitment with no researcher contact.

METHODS

The study involved secondary data analysis of remote CO testing in a randomized trial (ISRCTN10548241) comparing two versions of a cessation app (BupaQuit). Trial participants were adult UK-based smokers interested in quitting, who were recruited online (02/2015-03/2016). Participants were followed-up through the app, email or phone at 4 weeks. Fifty-nine participants reporting not smoking were posted a personal CO monitor with instructions, and emailed two reminders. The monitors required installing software on a Windows PC. Participants were not reimbursed but retained the device. We recorded the proportion of CO tests returned, test results, self-reported ease of use, correct use, acceptability, and reasons for missing results.

RESULTS

Fifteen (25.4%) CO results were returned, of which 86.6% were <10 ppm and 53.3% were <5 ppm, indicating abstinence (corresponding to 20.9% and 12.9% of all trial participants self-reporting abstinence, respectively). These 15 participants found the test easy, acceptable and believed they conducted it correctly. Eight (18.2%) of the missing results were accounted for, including no access to a Windows PC, barriers to receiving packages, and unwillingness to share results.

CONCLUSION

Remote validation using personal CO monitors may not yet be feasible in pragmatic studies of cessation apps in which participants are recruited with no reimbursement or direct contact with researchers.

Exploring mental health professionals' practice in relation to smoke-free policy within a mental health trust: a qualitative study using the COM-B model of behaviour

BACKGROUND

Smoking has played a significant role in the historical culture of mental healthcare settings. Mental health professionals (MHPs) often hold dismissive attitudes regarding the importance of smoking cessation in the context of mental healthcare. In 2007, English mental health inpatient buildings were required by law to become smoke-free, and healthcare trusts have more recently begun to implement comprehensive policies (i.e. smoke-free grounds and buildings) and staff training in response to national guidance. It is therefore important to explore MHPs practice around smoking, smoking cessation, and smoke-free policy adherence. This study aimed to explore these issues by using the COM-B (capability, opportunity, motivation, behaviour) model to systematically identify barriers to, and facilitators for, MHPs addressing smoking with their patients.

METHODS

Five focus groups with a total of 36 MHPs were conducted between March and August 2017. MHPs were recruited from one of the largest mental health trusts in Europe. Discussions were guided by a semi-structured guide. Responses were audio recorded, transcribed and coded using thematic analysis and the COM-B framework.

RESULTS

Addressing smoking with patients was undermined by MHPs' 1) psychological capability to recall training content, misunderstand the potential benefits of addressing patient smoking and harm reduction approaches; 2) physical opportunity in terms of time constraints, and easy accessibility of tobacco in the community; 3) social opportunity in terms of increased cultural value of tobacco following inpatient smoke-free policy implementation, and lack of support from colleagues to enforce the smoke-free policy; 4) automatic motivation, including intrinsic biases regarding patients abilities and motivations to quit, and 5) reflective motivation, including perceived job role and decision making processes related to addressing behaviours deemed more important than smoking. The main facilitating factors identified were MHPs' having opportunity in the form of patients asking directly for support, and MHPs having access to resources such as stop smoking services and spirometers.

CONCLUSION

Multiple barriers were identified across all key domains of the COM-B framework that undermine MHPs' practice regarding smoking cessation. Few facilitators were identified which may have implications for future smoke-free policy and clinical practice.

Initial Assessment of a Comprehensive Digital Smoking Cessation Program That Incorporates a Mobile App, Breath Sensor, and Coaching: Cohort Study

BACKGROUND

Cigarette smoking is the leading cause of preventable morbidity and mortality, excess health care expenditure, and lost work productivity. Otherwise effective evidence-based treatments have had limited success owing to challenges with access, engagement, and scale. Pivot is a comprehensive digital smoking cessation program that incorporates a Food and Drug Administration-cleared carbon monoxide breath sensor, smartphone app, and text-based human coaching.

OBJECTIVE

This initial evaluation of Pivot aimed to assess participant engagement, changes in attitudes toward quitting, and changes in smoking behavior.

METHODS

US cigarette smokers aged 18 to 65 years who smoked ≥5 cigarettes per day (CPD) were recruited online. Participants completed a screening call, electronic informed consent, registration, and onboarding before beginning Pivot. Pivot includes 5 sequential stages (Explore, Build, Mobilize, Quit, and Secure), taking 14.5 to 18.5 weeks to complete. Data were collected via app and online questionnaires. Outcomes included engagement and retention (ie, weeks of active engagement and Pivot stage progression); attitudes toward quitting (ie, quit readiness, quit confidence, and expected difficulty maintaining quit); and smoking behavior (ie, quit attempts, cigarette reduction, and abstinence (7- and 30-day point prevalence abstinence [PPA]).

RESULTS

A total of 319 participants completed onboarding (intention-to-treat [ITT] sample); 272/319 participants (85.3%) completed the end-of-Pivot questionnaire (study completer sample). Most (212/319, 66.5%) were not ready to quit in the next 30 days at baseline. On average, participants actively engaged in the program for a mean 12.4 (SD 7.1) weeks. Pivot stage completion rates were Explore: 88.7% (283/319), Build: 57.4% (183/319), Mobilize: 43.6% (139/319), Quit: 41.1% (131/319), and Secure: 39.5% (126/319). Repeated measures linear mixed model analyses demonstrated positive changes in attitudes from baseline to Mobilize (pre-Quit): increased confidence to quit (4.2 to 7.4, P<.001) and decreased expected difficulty maintaining quit (3.1 to 6.8, P<.001). The quit attempt rate (ie, those making ≥1 quit attempt lasting ≥1 day) was 79.4% (216/272, completer). At the end of Pivot, 7-day PPA rates were 32.0% (102/319, ITT) and 37.5% (102/272, completer); 30-day PPA rates were 27.6% (88/319, ITT) and 32.4% (88/272, completer). Moreover, 30-day PPA rates were comparable among those ready and not ready to quit in the next 30 days at baseline. Of those not achieving abstinence, 25.9% (44/170, completer) achieved ≥50% reduction in CPD by study end.

CONCLUSIONS

This study evaluated Pivot's initial performance with comparable quit rates among those ready and not ready to quit in the next 30 days at entry. The present data, considered with the program's accessibility, innovation, evidence-based foundation, and design for all smokers, suggest Pivot has the potential to address limitations of reach and scale and thereby advance smoking cessation efforts.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03295643; https://clinicaltrials.gov/ct2/show/NCT03295643 (Archived by WebCite at http://www.webcitation.org/75TiNe6BE).

A Comprehensive Digital Program for Smoking Cessation: Assessing Feasibility in a Single-Group Cohort Study

Background

Cigarette smoking remains the leading cause of preventable death and disease worldwide. Evidence-based approaches are available, but few people access them. Although digital solutions offer great promise for population reach, few multicomponent programs exist. Pivot is a comprehensive digital solution combining a Food and Drug Administration–cleared carbon monoxide (CO) breath sensor; cigarette logging; a 6-phase, app-delivered smoking cessation program based on the US Clinical Practice Guidelines; and dedicated human coaching via text-based chat.

Objective

The purpose of this study was to assess program engagement, changes in attitudes toward smoking, self-reported changes in smoking behavior, and program acceptability for the initial phase of Pivot: Explore.

Methods

A total of 48 participants enrolled, and 41 completed the study. About half the participants (54%, 22/41) were men, and the mean age was 43 years. Most (85%, 35/41) were daily smokers and smoked an average of 12 cigarettes per day. Explore includes CO breath sensing, logging cigarettes in-app, learning via in-app activities, and dedicated human coaching through a text messaging interface. Participants completed surveys at baseline and exit assessing attitudes toward quitting including readiness, perceived difficulty, and confidence in quit success. At exit, participants also completed a survey of changes in smoking behavior and ratings of program acceptability.

Results

More than 80% of participants (34-39 of 41) took ≥1 CO breath sample each day, and more than 55% (23-27 of 41) took ≥5 samples each day. More than 65% of participants (27-34 of 41) logged ≥1 cigarette using the in-app logging feature each day. All 9 in-app activities had completion rates ≥80% (33-40 of 41). Response to coach-initiated outreach was also high, with all contacts receiving ≥73% (30-39 of 41) response. In matched pair analyses, significant positive changes in mean attitudes toward quitting (scale 1-10) were evident from baseline (T1) to study exit (T2), including increased readiness to quit (T1 mean=6.1, T2 mean=7.4, P=.005), lower perceived difficulty (T1 mean=3.7, T2 mean=5.6, P=.001), and greater expectations of success (T1 mean=4.5, T2 mean=6.5, P<.001). At exit, 78% (32/41) of participants reported decreasing the number of cigarettes smoked per day during the study. Participants rated program quality and satisfaction very high (mean ≥8 for all items).

Conclusions

These results support the feasibility and acceptability of the initial 9-day phase of Pivot: Explore. Participants had high levels of engagement with sensing, logging, learning, and coaching. Attitudes toward quitting improved significantly, and the majority of users indicated decreasing smoking behavior. Explore was designed to raise smoker awareness and motivation. Additional research is underway to assess how users progress through the full Pivot smoking cessation program and determine the program’s effectiveness for achieving sustained cessation.

Estimation of the limit of detection in semiconductor gas sensors through linearized calibration models

The limit of detection (LOD) is a key figure of merit in chemical sensing. However, the estimation of this figure of merit is hindered by the non-linear calibration curve characteristic of semiconductor gas sensor technologies such as, metal oxide (MOX), gasFETs or thermoelectric sensors. Additionally, chemical sensors suffer from cross-sensitivities and temporal stability problems. The application of the International Union of Pure and Applied Chemistry (IUPAC) recommendations for univariate LOD estimation in non-linear semiconductor gas sensors is not straightforward due to the strong statistical requirements of the IUPAC methodology (linearity, homoscedasticity, normality). Here, we propose a methodological approach to LOD estimation through linearized calibration models. As an example, the methodology is applied to the detection of low concentrations of carbon monoxide using MOX gas sensors in a scenario where the main source of error is the presence of uncontrolled levels of humidity.

Smokers' Views on Personal Carbon Monoxide Monitors, Associated Apps, and Their Use: An Interview and Think-Aloud Study

Smartphone-based personal carbon monoxide (CO) monitors and associated apps, or "CO Smartphone Systems" (CSSs) for short, could enable smokers to independently monitor their smoking and quitting. This study explored views and preferences regarding CSSs and their use among 16 adult, UK-based smokers. First, semi-structured interviews explored participants' expectations of CSSs. Secondly, a think-aloud study identified participants' reactions to a personal CO monitor and to existing or prototype apps. Framework Analysis identified five themes: (1) General views, needs, and motivation to use CSSs; (2) Views on the personal CO monitor; (3) Practicalities of CSS use; (4) Desired features in associated apps; and (5) Factors affecting preferences for CSSs and their use. Participants had high expectations of CSSs and their potential to increase motivation. Priority app features included: easy CO testing journeys, relevant and motivating feedback, and recording of contextual data. Appearance and usability of the personal CO monitor, and accuracy and relevance of CO testing were considered important for engagement. Participants differed in their motivation to use and preferences for CSSs features and use, which might have non-trivial impact on evaluation efforts. Personal CO monitors and associated apps may be attractive tools for smokers, but making CSSs easy to use and evaluating these among different groups of smokers may be challenging.

Low Power Operation of Temperature-Modulated Metal Oxide Semiconductor Gas Sensors

Mobile applications based on gas sensing present new opportunities for low-cost air quality monitoring, safety, and healthcare. Metal oxide semiconductor (MOX) gas sensors represent the most prominent technology for integration into portable devices, such as smartphones and wearables. Traditionally, MOX sensors have been continuously powered to increase the stability of the sensing layer. However, continuous power is not feasible in many battery-operated applications due to power consumption limitations or the intended intermittent device operation. This work benchmarks two low-power, duty-cycling, and on-demand modes against the continuous power one. The duty-cycling mode periodically turns the sensors on and off and represents a trade-off between power consumption and stability. On-demand operation achieves the lowest power consumption by powering the sensors only while taking a measurement. Twelve thermally modulated SB-500-12 (FIS Inc. Jacksonville, FL, USA) sensors were exposed to low concentrations of carbon monoxide (0-9 ppm) with environmental conditions, such as ambient humidity (15-75% relative humidity) and temperature (21-27 °C), varying within the indicated ranges. Partial Least Squares (PLS) models were built using calibration data, and the prediction error in external validation samples was evaluated during the two weeks following calibration. We found that on-demand operation produced a deformation of the sensor conductance patterns, which led to an increase in the prediction error by almost a factor of 5 as compared to continuous operation (2.2 versus 0.45 ppm). Applying a 10% duty-cycling operation of 10-min periods reduced this prediction error to a factor of 2 (0.9 versus 0.45 ppm). The proposed duty-cycling powering scheme saved up to 90% energy as compared to the continuous operating mode. This low-power mode may be advantageous for applications that do not require continuous and periodic measurements, and which can tolerate slightly higher prediction errors.

Use of Expired Air Carbon Monoxide Testing in Clinical Tobacco Treatment Settings

Carbon monoxide (CO) testing is considered an easy, noninvasive, and objective contribution to the assessment of smoking behavior, as CO is rapidly absorbed into the bloodstream when lit cigarettes or cigars are inhaled. CO testing is a medically important billable outpatient service that can contribute to sustainability of face to face tobacco use treatment services by clinicians. This article reviews research on the clinical use of CO testing to provide biomedical feedback in assessing smoking behavior, educating smokers on tobacco health effects, assisting with treatment planning, and as a motivational tool to encourage people to become tobacco free. Further research can focus on how to best incorporate CO testing into clinical practice, including more research on outcomes and methods to ensure that insurers reimburse for testing and improved ways to use CO testing to initiate attempts to quit tobacco use, to maintain cessation, and to prevent relapse.

A mobile-phone-based breath carbon monoxide meter to detect cigarette smoking

INTRODUCTION

Mobile phones hold considerable promise for delivering evidence-based smoking cessation interventions that require frequent and objective assessment of smoking status via breath carbon monoxide (Breath CO) measurement. However, there are currently no commercially available mobile-phone-based Breath CO meters. We developed a mobile-phone-based Breath CO meter prototype that attaches to and communicates with a smartphone through an audio port. We then evaluated the reliability and the validity of Breath CO measures collected with the mobile meter prototype and assessed the usability and acceptability of the meter.

METHODS

Participants included 20 regular smokers (≥10 cigarettes/day), 20 light smokers (<10 cigarettes/day), and 20 nonsmokers. Expired air samples were collected 4 times from each participant: twice with the mobile meter and twice with a commercially available Breath CO meter.

RESULTS

Measures calculated by the mobile meter correlated strongly with measures calculated by the commercial meter (r = .96, p < .001). Additionally, the mobile meter accurately distinguished between smokers and nonsmokers. The area under the receiver-operating characteristic curve for the mobile meter was 94.7%, and the meter had a combined sensitivity and specificity of 1.86 at an abstinence threshold of ≤6 ppm. Responses on an acceptability survey indicated that smokers liked the meter and would be interested in using it during a quit attempt.

CONCLUSIONS

The results of our study suggest that a mobile-phone-based Breath CO meter is a reliable, valid, and acceptable device for distinguishing between smokers and nonsmokers.

Negative affect and smoking motives sequentially mediate the effect of panic attacks on tobacco-relevant processes

INTRODUCTION

Empirical work has documented a robust and consistent relation between panic attacks and smoking behavior. Theoretical models posit smokers with panic attacks may rely on smoking to help them manage chronically elevated negative affect due to uncomfortable bodily states, which may explain higher levels of nicotine dependence and quit problems.

METHODS

The current study examined the effects of panic attack history on nicotine dependence, perceived barriers for quitting, smoking inflexibility when emotionally distressed, and expired carbon monoxide among 461 treatment-seeking smokers. A multiple mediator path model was evaluated to examine the indirect effects of negative affect and negative affect reduction motives as mediators of the panic attack-smoking relations.

RESULTS

Panic attack history was indirectly related to greater levels of nicotine dependence (b = 0.039, CI95% = 0.008, 0.097), perceived barriers to smoking cessation (b = 0.195, CI95% = 0.043, 0.479), smoking inflexibility/avoidance when emotionally distressed (b = 0.188, CI95% = 0.041, 0.445), and higher levels of expired carbon monoxide (b = 0.071, CI95% = 0.010, 0.230) through the sequential effects of negative affect and negative affect smoking motives.

CONCLUSIONS

The present results provide empirical support for the sequential mediating role of negative affect and smoking motives for negative affect reduction in the relation between panic attacks and a variety of smoking variables in treatment-seeking smokers. These mediating variables are likely important processes to address in smoking cessation treatment, especially in panic-vulnerable smokers.