2,589 research outputs found

    Improving Community Advisory Board Engagement In Precision Medicine Research To Reduce Health Disparities

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    Community Advisory Boards (CABs) are used in efforts to reduce health disparities; however, there is little documentation in the literature regarding their use in precision medicine research. In this case study, an academic-CAB partnership developed a questionnaire and patient educational materials for two precision smoking cessation interventions that involved use of genetic information. The community-engaged research (CEnR) literature provided a framework for enhancing benefits to CAB members involved in developing research documents for use with a low-income, ethnically diverse population of smokers. The academic partners integrated three CEnR strategies: 1) in-meeting statements acknowledging their desire to learn from community partners, 2) in-meeting written feedback to and from community partners, and 3) a survey to obtain CAB member feedback post-meetings. Strategies 1 and 2 yielded modifications to pertinent study materials, as well as suggestions for improving meeting operations that were then adopted, as appropriate, by the academic partners. The survey indicated that CAB members valued the meeting procedure changes which appeared to have contributed to improvements in attendance and satisfaction with the meetings. Further operationalization of relevant partnership constructs and development of tools for measuring these aspects of community-academic partnerships is warranted to support community engagement in precision medicine research studies

    Recruiting Women to a Mobile Health Smoking Cessation Trial: Low- and No-Cost Strategies

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    Background: Successful recruitment of participants to mobile health (mHealth) studies presents unique challenges over in-person studies. It is important to identify recruitment strategies that maximize the limited recruitment resources available to researchers. Objective: The objective of this study was to describe a case study of a unique recruitment process used in a recent mHealth software app designed to increase smoking cessation among weight-concerned women smokers. The See Me Smoke-Free app was deployed to the Google Play Store (Alphabet, Inc., Google, LLC), where potential participants could download the app and enroll in the study. Users were invited in-app to participate in the study, with no in-person contact. The recruitment activities relied primarily on earned (free) and social media. Methods: To determine the relationship between recruitment activities and participant enrollment, the researchers explored trends in earned and social media activity in relation to app installations, examined social media messaging in relation to reach or impressions, and described app users’ self-reported referral source. The researchers collected and descriptively analyzed data regarding recruitment activities, social media audience, and app use during the 18-week recruitment period (March 30, 2015-July 31, 2015). Data were collected and aggregated from internal staff activity tracking documents and from Web-based data analytics software such as SumAll, Facebook Insights (Facebook, Inc.), and Google Analytics (Alphabet, Inc., Google, LLC). Results: Media coverage was documented across 75 publications and radio or television broadcasts, 35 of which were local, 39 national, and 1 international. The research team made 30 Facebook posts and 49 tweets, yielding 1821 reaches and 6336 impressions, respectively. From March 30, 2015 to July 31, 2015, 289 unique users downloaded the app, and 151 participants enrolled in the study. Conclusions: Research identifying effective online recruitment methods for mHealth studies remains minimal, and findings are inconsistent. We demonstrated how earned media can be leveraged to recruit women to an mHealth smoking cessation trial at low cost. Using earned media and leveraging social media allowed us to enroll 3 times the number of participants that we anticipated enrolling. The cost of earned media resides in the staff time required to manage it, particularly the regular interaction with social media. We recommend communication and cooperation with university public affairs and social media offices, as well as affiliate programs in journalism and communications, so that earned media can be used as a recruitment strategy for mHealth behavior change interventions. However, press releases are not always picked up by the media and should not be considered as a stand-alone method of recruitment. Careful consideration of an intervention’s broad appeal and how that translates into potential media interest is needed when including earned media as part of a comprehensive recruitment plan for mHealth research

    “Keep Calm, it's just Vapour”: A Mixed Methods Investigation of Online E-Cigarette Discourse and User Perspectives in Western Australia

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    The aim of this research was to understand how electronic cigarettes (e-cigarettes) are promoted, accessed, and used within a tightly regulated environment, by exploring the Australian online e-cigarette discourse, and the perspectives of e-cigarette users residing within the Greater Capital City Statistical Area of Perth, Western Australia. To achieve this aim three substudies were undertaken: a) scoping review, b) Twitter inquiry and c) qualitative inquiry

    Internet All Nation Breath of life (I-ANBL) a Tribal College Student Engaged Development of an Internet-based Smoking Cessation Intervention

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    Background: Compared to non-Hispanic white college students, American Indian (AI) tribal college students have the highest smoking prevalence in the U.S. (~34%). Culturally-tailored smoking cessation programs have proven to be successful in reducing smoking rates but may require new methods to reach college students. Currently, there is little documentation on the development and success of Internet-based smoking interventions for AI tribal college students. Objectives: To develop an Internet-based smoking cessation program (Internet-All Nations Breath of Life or I-ANBL) with tribal college students. Methods: We conducted six focus groups (n=41) at a tribal college. Focus groups included tribal college students who smoked and groups were stratified by sex. Transcripts were analyzed using insider and outsider perspectives. After analysis, an Internet-based smoking cessation program was developed, based on insight gained. Results: Numerous suggestions for creating the program were offered. There was consensus on the need for a variety of visuals including cultural images, videos, and interactive content. The students also suggested the integration of familiar platforms such as FacebookTM. Conclusion: When culturally tailoring a web-based smoking cessation program for tribal college students, it is important to incorporate cultural aspects and recognize gender differences. One important aspect is to recognize that for many AI, tobacco is a sacred plant and images of tobacco should be respectful. Now that this intervention has been developed, next we will test it for efficacy in a randomized controlled trial. Keywords: American Indians, tribal college, tobacco, program development, smoking cessation, community-based participatory researc

    Does addition of craving management tools in a stop smoking app improve quit rates among adult smokers? Results from BupaQuit pragmatic pilot randomised controlled trial

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    Introduction: Delivery of craving management tools (CMTs) via smartphone applications (apps) may improve smoking cessation rates, but research on such programmes remains limited, especially in real-world settings. This study evaluated the effectiveness of adding CMTs in a cessation app (BupaQuit). / Methods: The study was a two-arm pragmatic pilot parallel randomised controlled trial, comparing a fully-automated BupaQuit app with CMT with a control app version without CMT. A total of 425 adult UK-based daily smokers were enrolled through open online recruitment (February 2015-March 2016), with no researcher involvement, and individually randomised within the app to the intervention (n=208) or control (n=217). The primary outcome was self-reported 14-day continuous abstinence assessed at 4-week follow-up. Secondary outcomes included 6-month point-prevalence and sustained abstinence, and app usage. The primary outcome was assessed with Fisher’s exact test using intent to treat with those lost to follow-up counted as smoking. Participants were not reimbursed. / Results: Re-contact rates were 50.4% at 4 weeks and 40.2% at 6 months. There was no significant difference between intervention and control arms on the primary outcome (13.5% vs 15.7%; p=0.58;RR=0.86, 95% Confidence Interval (CI)=0.54-1.36) or secondary cessation outcomes (6-month point prevalence: 14.4% vs. 17.1%, p=0.51;RR=0.85, 95%CI=0.54-1.32; 6-month sustained: 11.1% vs 13.4%, p=0.55,RR=0.83,95%CI=0.50-1.38). Bayes factors supported the null hypothesis (B[0, 0,1.0986]=.20). Usage was similar across the conditions (mean/median logins: 9.6/4 vs. 10.5/5; time spent: 401.8/202s vs. 325.8/209s). / Conclusions: The addition of craving management tools did not affect cessation, and the limited engagement with the app may have contributed to this

    “You Come Back to the Same Ole Shit:” A Qualitative Study of Smoking Cessation Barriers among Women Living with HIV: Implications for Intervention Development

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    Although tobacco use among women living with HIV (WLWH) is decreasing, the prevalence is more than double that of women in the general population and remains an important health behavior to target among WLWH. Few smoking cessation interventions specifically focus on the unique social and medical needs of women living with HIV (WLWH). Thus, the investigative team engaged WLWH (N=18) in qualitative focus groups to: 1) understand barriers and facilitators to smoking cessation; and 2) inform intervention structure and content priorities. Participants identified salient reasons for smoking and barriers to smoking cessation, which included coping mechanisms for life stressors, HIV-related stress, HIV-related stigma, and social isolation. Further, WLWH highlighted the importance of long-term smoking cessation support, peer support, mental health content, religion/spirituality, and targeted risk messaging in smoking cessation intervention development. Study findings provide concrete, operational strategies for future use in a theory-based smoking cessation intervention, and underscore the importance of formative research to inform smoking cessation interventions for WLWH

    Does addition of craving management tools in a stop smoking app improve quit rates among adult smokers? Results from BupaQuit pragmatic pilot randomised controlled trial

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    Objectives: Delivery of craving management tools via smartphone applications (apps) may improve smoking cessation rates, but research on such programmes remains limited, especially in real-world settings. This study evaluated the effectiveness of adding craving management tools in a cessation app (BupaQuit). Methods: The study was a two-arm pragmatic pilot parallel randomised controlled trial, comparing a fully-automated BupaQuit app with craving management tool with a control app version without craving management tool. A total of 425 adult UK-based daily smokers were enrolled through open online recruitment (February 2015–March 2016), with no researcher involvement, and individually randomised within the app to the intervention (n = 208) or control (n = 217). The primary outcome was self-reported 14-day continuous abstinence assessed at 4-week follow-up. Secondary outcomes included 6-month point-prevalence and sustained abstinence, and app usage. The primary outcome was assessed with Fisher's exact test using intent to treat with those lost to follow-up counted as smoking. Participants were not reimbursed. Results: Re-contact rates were 50.4% at 4 weeks and 40.2% at 6 months. There was no significant difference between intervention and control arms on the primary outcome (13.5% vs 15.7%; p = 0.58; relative risk = 0.86, 95% confidence interval = 0.54–1.36) or secondary cessation outcomes (6-month point prevalence: 14.4% vs 17.1%, p = 0.51; relative risk = 0.85, 95% confidence interval = 0.54–1.32; 6-month sustained: 11.1% vs 13.4%, p = 0.55; relative risk = 0.83, 95% confidence interval = 0.50–1.38). Bayes factors supported the null hypothesis (B[0, 0, 1.0986] = 0.20). Usage was similar across the conditions (mean/median logins: 9.6/4 vs 10.5/5; time spent: 401.8/202 s vs 325.8/209 s). Conclusions: The addition of craving management tools did not affect cessation, and the limited engagement with the app may have contributed to this

    Why do smokers try to quit without medication or counselling? A qualitative study with ex-smokers.

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    Objective When tobacco smokers quit, between half and two-thirds quit unassisted: that is, they do not consult their general practitioner (GP), use pharmacotherapy (nicotine-replacement therapy, bupropion or varenicline), or phone a quitline. We sought to understand why smokers quit unassisted. Design Qualitative grounded theory study (in-depth interviews, theoretical sampling, concurrent data collection and data analysis). Participants 21 Australian adult ex-smokers (aged 28–68 years; 9 males and 12 females) who quit unassisted within the past 6 months to 2 years. 12 participants had previous experience of using assistance to quit; 9 had never previously used assistance. Setting Community, Australia. Results Along with previously identified barriers to use of cessation assistance (cost, access, lack of awareness or knowledge of assistance, including misperceptions about effectiveness or safety), our study produced new explanations of why smokers quit unassisted: (1) they prioritise lay knowledge gained directly from personal experiences and indirectly from others over professional or theoretical knowledge; (2) their evaluation of the costs and benefits of quitting unassisted versus those of using assistance favours quitting unassisted; (3) they believe quitting is their personal responsibility; and (4) they perceive quitting unassisted to be the ‘right’ or ‘better’ choice in terms of how this relates to their own self-identity or self-image. Deep-rooted personal and societal values such as independence, strength, autonomy and self-control appear to be influencing smokers’ beliefs and decisions about quitting. Conclusions The reasons for smokers’ rejection of the conventional medical model for smoking cessation are complex and go beyond modifiable or correctable problems relating to misperceptions or treatment barriers. These findings suggest that GPs could recognise and respect smokers’ reasons for rejecting assistance, validate and approve their choices, and modify brief interventions to support their preference for quitting unassisted, where preferred. Further research and translation may assist in developing such strategies for use in practice.NHMR
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