350 research outputs found
Risk of cardiovascular serious adverse events associated with varenicline use for tobacco cessation: systematic review and meta-analysis
Objective To examine the risk of treatment emergent, cardiovascular serious adverse events associated with varenicline use for tobacco cessation
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The Use of Web-Based Support Groups Versus Usual Quit-Smoking Care for Men and Women Aged 21-59 Years: Protocol for a Randomized Controlled Trial (Preprint)
BACKGROUND
Existing smoking cessation treatments are challenged by low engagement and high relapse rates, suggesting the need for more innovative, accessible, and interactive treatment strategies. Twitter is a Web-based platform that allows people to communicate with each other throughout the day using their phone.
OBJECTIVE
This study aims to leverage the social media platform of Twitter for fostering peer-to-peer support to decrease relapse with quitting smoking. Furthermore, the study will compare the effects of coed versus women-only groups on women’s success with quitting smoking.
METHODS
The study design is a Web-based, three-arm randomized controlled trial with two treatment arms (a coed or women-only Twitter support group) and a control arm. Participants are recruited online and are randomized to one of the conditions. All participants will receive 8 weeks of combination nicotine replacement therapy (patches plus their choice of gum or lozenges), serial emails with links to Smokefree.gov quit guides, and instructions to record their quit date online (and to quit smoking on that date) on a date falling within a week of initiation of the study. Participants randomized to a treatment arm are placed in a fully automated Twitter support group (coed or women-only), paired with a buddy (matched on age, gender, location, and education), and encouraged to communicate with the group and buddy via daily tweeted discussion topics and daily automated feedback texts (a positive tweet if they tweet and an encouraging tweet if they miss tweeting). Recruited online from across the continental United States, the sample consists of 215 male and 745 female current cigarette smokers wanting to quit, aged between 21 and 59 years. Self-assessed follow-up surveys are completed online at 1, 3, and 6 months after the date they selected to quit smoking, with salivary cotinine validation at 3 and 6 months. The primary outcome is sustained biochemically confirmed abstinence at the 6-month follow-up.
RESULTS
From November 2016 to September 2018, 960 participants in 36 groups were recruited for the randomized controlled trial, in addition to 20 participants in an initial pilot group. Data analysis will commence soon for the randomized controlled trial based on data from 896 of the 960 participants (93.3%), with 56 participants lost to follow-up and 8 dropouts.
CONCLUSIONS
This study combines the mobile platform of Twitter with a support group for quitting smoking. Findings will inform the efficacy of virtual peer-to-peer support groups for quitting smoking and potentially elucidate gender differences in quit rates found in prior research.
CLINICALTRIAL
ClinicalTrials.gov NCT02823028; https://clinicaltrials.gov/ct2/show/NCT0282302
Methods of quantifying change in multiple risk factor interventions
Objective: Risky behaviors such as smoking, alcohol abuse, physical inactivity, and poor diet are detrimental to health, costly, and often co-occur. Greater efforts are being targeted at changing multiple risk behaviors to more comprehensively address the health needs of individuals and populations. With increased interest in multiple risk factor interventions, the field will need ways to conceptualize the issue of overall behavior change. Method: Analyzing data from over 8000 participants in four multibehavioral interventions, we present five different methods for quantifying and reporting changes in multiple risk behaviors.
Results: The methods are: (a) the traditional approach of reporting changes in individual risk behaviors; (b) creating a combined statistical index of overall behavior change, standardizing scores across behaviors on different metrics; (c) using a behavioral index; (d) calculating an overall impact factor; and (e) using overarching outcome measures such as quality of life, related biometrics, or cost outcomes. We discuss the methods\u27 interpretations, strengths, and limitations.
Conclusion: Given the lack of consensus in the field on how to examine change in multiple risk behaviors, we recommend researchers employ and compare multiple methods in their publications. A dialogue is needed to work toward developing a consensus for optimal ways of conceptualizing and reporting changes in multibehavioral interventions
Medical Students’ Use of the Stages of Change Model in Tobacco Cessation Counseling
BACKGROUND: Many medical schools have incorporated the Stages of Change Model into their curricula with specific application to tobacco cessation. OBJECTIVE: This study examined the extent to which medical students were prepared to provide stage-based interventions to treat nicotine dependence. DESIGN: Using a quasi-experimental design, medical students’ counseling interactions were evaluated with a standardized patient portraying a smoker in either the precontemplation or preparation stage of change. PARTICIPANTS: Participants were 147 third-year medical students at the University of California, San Francisco. MEASUREMENTS: Checklists completed by standardized patients evaluated students’ clinical performance. Surveys administered before and after the encounters assessed students’ knowledge, attitudes, confidence and previous experience with treating smoking. RESULTS: Most students asked about tobacco use (89%), advised patients of the health benefits of quitting (74%), and assessed the patient’s readiness to quit (76%). The students were more likely to prescribe medications and offer referrals to patients in the preparation than in the precontemplation stage of change (P < 0.001); however, many students had difficulty identifying patients ready to quit, and few encouraged patients to set a quit date or arranged follow-up to assess progress. Students’ tobacco-related knowledge, but not their attitudes, confidence, or previous experience predicted their clinical performance. CONCLUSIONS: The findings indicated evidence of students tailoring their counseling strategies to the patients’ stage of change; however, they still could do more to assist their patients in quitting. Additional training and integration of cessation counseling into clinical rotations are needed
The benefits and challenges of multiple health behavior change in research and in practice
Objective: The major chronic diseases are caused by multiple risks, yet the science of multiple health behavior change (MHBC) is at an early stage, and factors that facilitate or impede scientists\u27 involvement in MHBC research are unknown. Benefits and challenges of MHBC interventions were investigated to strengthen researchers\u27 commitment and prepare them for challenges.
Method: An online anonymous survey was e-mailed to listservs of the Society of Behavioral Medicine between May 2006 and 2007. Respondents (N = 69) were 83% female; 94% held a doctoral degree; 64% were psychologists, 24% were in public health; and 83% targeted MHBC in their work.
Results: A sample majority rated 23 of the 24 benefits, but only 1 of 31 challenge items, as very to extremely important. Those engaged in MHBC rated the total benefits significantly higher than respondents focused on single behaviors, F(1,69) = 4.21, p \u3c .05, and rated the benefits significantly higher than the challenges: paired t(57) = 7.50, p \u3c .001. The two groups did not differ in ratings of challenges.
Conclusion: It appears that individuals focused solely on single behaviors do not fully appreciate the benefits that impress MHBC researchers; it is not that substantial barriers are holding them back. Benefits of MHBC interventions need emphasizing more broadly to advance this research area
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Facebook Recruitment Using Zip Codes to Improve Diversity in Health Research: Longitudinal Observational Study (Preprint)
BACKGROUND
Facebook’s advertising platform reaches most US households and has been used for health-related research recruitment. The platform allows for advertising segmentation by age, gender, and location; however, it does not explicitly allow for targeting by race or ethnicity to facilitate a diverse participant pool.
OBJECTIVE
This study looked at the efficacy of zip code targeting in Facebook advertising to reach blacks/African Americans and Hispanics/Latinos who smoke daily for a quit-smoking web-based social media study.
METHODS
We ran a general market campaign for 61 weeks using all continental US zip codes as a baseline. Concurrently, we ran 2 campaigns to reach black/African American and Hispanic-/Latino-identified adults, targeting zip codes ranked first by the percentage of households of the racial or ethnic group of interest and then by cigarette expenditure per household. We also ran a Spanish language campaign for 13 weeks, targeting all continental US zip codes but utilizing Facebook’s Spanish language targeting. The advertising images and language were common across campaigns. Costs were compared for advertisement clicks, queries, applications, and participants, and yields were compared for the final three outcomes. We examined outcomes before and after the Cambridge Analytica scandal that broke in March 2018. Finally, we examined 2 promoted Facebook features: lookalike audiences and audience network placement.
RESULTS
Zip code targeting campaigns were effective for yielding the racial or ethnic groups of interest. The black-/African American–focused versus general market campaign increased black/African American weekly queries (mean 9.48, SD 5.69 vs general market mean 2.83, SD 2.05; P<.001) and applicants (mean 1.11, SD 1.21 vs general market mean 0.54, SD 0.58; P<.001). The Hispanic-/Latino-focused versus general market campaign increased Hispanic/Latino weekly queries (mean 3.10, SD 2.16 vs general market mean 0.71, SD 0.48; P<.001) and applicants (mean 0.36, SD 0.55 vs general market mean 0.10, SD 0.14; P=.001). Cost metrics did not differ between campaigns at generating participants (overall P=.54). Costs increased post- versus prescandal for the black-/African American–focused campaign for queries (mean US 5.87, SD 1.89; P=.001) and applicants (mean US 38.96, SD 28.31; P=.004) and for the Hispanic-/Latino-focused campaign for queries (mean US 7.04, SD 3.39; P=.005) and applicants (mean US 38.19, SD 21.20; P=.001).
CONCLUSIONS
Zip code targeting in Facebook advertising is an effective way to recruit diverse populations for health-based interventions. Audience network placement should be avoided. The Facebook lookalike audience may not be necessary for recruitment, with drawbacks including an unknown algorithm and unclear use of Facebook user data, and so public concerns around data privacy should be considered.
CLINICALTRIAL
ClinicalTrial.gov NCT02823028; https://clinicaltrials.gov/ct2/show/NCT0282302
Integration of Tobacco Treatment Services into Cancer Care at Stanford.
As part of a National Cancer Institute Moonshot P30 Supplement, the Stanford Cancer Center piloted and integrated tobacco treatment into cancer care. This quality improvement (QI) project reports on the process from initial pilot to adoption within 14 clinics. The Head and Neck Oncology Clinic was engaged first in January 2019 as a pilot site given staff receptivity, elevated smoking prevalence, and a high tobacco screening rate (95%) yet low levels of tobacco cessation treatment referrals (<10%) and patient engagement (<1% of smokers treated). To improve referrals and engagement, system changes included an automated "opt-out" referral process and provision of tobacco cessation treatment as a covered benefit with flexible delivery options that included phone and telemedicine. Screening rates increased to 99%, referrals to 100%, 74% of patients were reached by counselors, and 33% of those reached engaged in treatment. Patient-reported abstinence from all tobacco products at 6-month follow-up is 20%. In July 2019, two additional oncology clinics were added. In December 2019, less than one year from initiating the QI pilot, with demonstrated feasibility, acceptability, and efficacy, the tobacco treatment services were integrated into 14 clinics at Stanford Cancer Center
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