Published on in Vol 8, No 11 (2019): November

Preprints (earlier versions) of this paper are available at, first published .
Social Media Intervention to Promote Smoking Treatment Utilization and Cessation Among Alaska Native People Who Smoke: Protocol for the Connecting Alaska Native People to Quit Smoking (CAN Quit) Pilot Study

Social Media Intervention to Promote Smoking Treatment Utilization and Cessation Among Alaska Native People Who Smoke: Protocol for the Connecting Alaska Native People to Quit Smoking (CAN Quit) Pilot Study

Social Media Intervention to Promote Smoking Treatment Utilization and Cessation Among Alaska Native People Who Smoke: Protocol for the Connecting Alaska Native People to Quit Smoking (CAN Quit) Pilot Study


1Department of Psychiatry and Psychology and Behavioral Health Research Program, Mayo Clinic, Rochester, MN, United States

2Clinical and Research Services, Division of Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, United States

3Stanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, CA, United States

4Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United States

5School of Public Health, University of Michigan, Ann Arbor, MI, United States

Corresponding Author:

Pamela S Sinicrope, DrPH

Department of Psychiatry and Psychology and Behavioral Health Research Program

Mayo Clinic

200 1st St SW

Rochester, MN, 55905

United States

Phone: 1 507 266 1238


Background: Despite the high prevalence of tobacco use among Alaska Native (AN) people, tobacco cessation interventions developed specifically for this group are lacking. Social media hold promise as a scalable intervention strategy to promote smoking treatment utilization and cessation, given the barriers to treatment delivery (ie, geographic remoteness, limited funding, climate, and travel costs) in the state of Alaska (AK). Building on a longstanding tobacco control research partnership with the AK Tribal Health System, in this study, we are developing and pilot-testing a culturally relevant, Facebook (FB)-delivered intervention that incorporates a digital storytelling approach adapted from the effective Centers for Disease Control Tips from Former Smokers campaign.

Objective: This study aims to promote evidence-based smoking treatment (eg, state quitline and Tribal cessation programs) uptake and cessation among AN people.

Methods: This study fulfills the objectives for stage 1 of the National Institute on Drug Abuse behavioral integrative treatment development program. In stage 1a, we will use a mixed method approach to develop the FB intervention. Cultural variance and surface/deep structure frameworks will address the influence of culture in designing health messages. These developmental activities will include qualitative and quantitative assessments, followed by beta testing of proposed intervention content. In stage 1b, we will conduct a randomized pilot trial enrolling 60 AN adults who smoke. We will evaluate the feasibility, uptake, consumer response, and potential efficacy of the FB intervention compared with a control condition (quitline/treatment referral only). Primary outcome measures include feasibility and biochemically verified smoking abstinence at 1-, 3-, and 6-month follow-ups. Secondary outcomes will include self-reported smoking cessation treatment utilization and abstinence from tobacco/nicotine products. We will also explore interdependence (relationship orientation and collaborative efforts in lifestyle change) as a culturally relevant mediator of intervention efficacy.

Results: The study enrolled 40 participants for phase 1, with data saturation being achieved at 30 AN people who smoke and 10 stakeholders. For phase 2, we enrolled 40 participants. Qualitative assessment of proposed intervention content was completed with 30 AN smokers and 10 stakeholders. We are currently analyzing data from the quantitative assessment with 40 participants in preparation for the beta testing, followed by the randomized pilot trial.

Conclusions: The project is innovative for its use of social media communication tools that are culturally relevant in a behavioral intervention designed to reach AN people statewide to promote smoking treatment utilization and cessation. The study will further advance tobacco cessation research in an underserved disparity group. If the pilot intervention is successful, we will have a blueprint to conduct a large randomized controlled efficacy trial. Our approach could be considered for other remote AN communities to enhance the reach of evidence-based tobacco cessation treatments.

International Registered Report Identifier (IRRID): DERR1-10.2196/15155

JMIR Res Protoc 2019;8(11):e15155



Background and Significance

Cigarette smoking, the most preventable cause of morbidity, mortality, and excess health cost in the United States, accounts for 480,000 premature deaths yearly [1]. At 22%, American Indian (AI)/Alaska Native (AN) persons have the highest US smoking prevalence; and within this group, AN residents of Alaska (AK) have a prevalence of smoking more than double that of Alaskan whites (42% vs 17%) [2]. Accordingly, AN people who smoke experience more tobacco-related diseases and mortality compared with non-Native people living in AK or US whites [3-6]. A national public health objective is to reduce tobacco-caused health disparities [7,8]. The state of AK developed its own health improvement plan, Healthy Alaskans 2020, that identifies priority health indicators. Decreasing smoking prevalence among AN adults to 17% is one of the priorities [9]. We will address both objectives by developing effective strategies to decrease tobacco use within AN communities across the state of AK and among AN people as a whole. With approximately 20% of the state’s population self-identifying as AN race [10], substantial reductions in tobacco use will greatly contribute to reducing statewide tobacco use rates.

Quitlines have proven efficacy [11] but remain underutilized by AN people [12,13]. In addition, only 4% to 7% of unaided quit attempts are successful among AN smokers compared with 10% among non-Native smokers. Evidence-based counseling and medication treatments could boost quit rates to as high as 30% to 40% [14,15]. Therefore, a need exists to increase utilization of available, low/no cost, and evidence-based smoking cessation resources such as AK’s Tobacco Quitline or Tribal tobacco cessation resources.

The Alaska Native Tribal Health Consortium (ANTHC), a consortium of regional Tribal health leaders, represents diverse AN people in AK. ANTHC co-owns and comanages the Alaska Native Medical Center (ANMC) in Anchorage. ANMC provides specialty care to AN people statewide, serving as the AK Tribal Health System’s only tertiary care facility. ANTHC’s Community Health Services Tobacco Prevention and Control Program provides tobacco cessation counseling and nicotine replacement therapy (NRT) to inpatients at ANMC. Upon discharge, patients are referred to cessation services at their regional Tribal health organization, which vary widely, or to AK’s Tobacco Quitline. AK’s Tobacco Quitline, operated by the state, is available to all Alaskans but provides free NRT for only 1 month. Given these barriers, the ANTHC Tobacco Prevention and Control Program appealed to ANTHC’s Clinical and Research Services to explore ways to expand capacity for support of AN Tribal members’ cessation efforts statewide.

Although our study with AN pregnant women and youth demonstrated that face-to-face interventions had limited reach and efficacy [16,17], Web-based social networks, such as Facebook (FB), are potentially powerful tools for reaching, engaging, and connecting AN people who smoke in cessation efforts [18] because of their large reach, relatively low cost, and potential for greater adoption and sustainability. The following section reviews the literature on the topic of social media use for health promotion with ANs and, generally, in the area of tobacco cessation. Utilization of the internet to access health information and social media use have increased among AN people, even in remote regions. In a representative survey of 340 households in rural southwest AK (73% AN adults), 87% had at least 1 cell phone, 60% had a smartphone, and 81% used FB, Twitter, or other social media sites [19,20]. A survey of 362 AN females from a rural census area reported that 80% used internet, 78% had smartphones, and 90% used FB [21]. Although the potential of social media to enhance smoking cessation is understudied, it remains a priority research area [18,22,23], with some trials using social media platforms for smoking cessation reporting effectiveness [24-27].

An intervention with both a website and an FB group evaluated quasi-experimentally among 238 young adult smokers resulted in greater self-reported 7- and 30-day smoking abstinence rates and quit attempts, compared with an unmatched comparison group of quitline users at a 3-month follow-up [24]. Participants interacted significantly more with FB than the website; of FB users, 56% were men and 44% were women, with women more actively posting and engaging than men. An analysis of sex differences in communication styles revealed that women emphasized support and connecting, whereas men expressed strong assertions about quitting smoking [25].

Another study evaluated a 100-day Twitter intervention [26]. Among 160 smokers aged 18 to 59 years, Tweet2Quit doubled the rate of self-reported sustained abstinence at 2 months post quit date compared with a control condition ( cessation website referral plus nicotine patches), 40% versus 20%. Sex, but not age, was related to treatment outcome, with women less likely to quit smoking than men in both study conditions.

An uncontrolled FB study for young adult smokers tested whether monetary incentives enhanced FB intervention engagement [27]. FB engagement was high, did not differ by incentive, and self-reported smoking abstinence at 6 months was 18%. Another observational study evaluated social media to support smoking cessation efforts among participants enrolled in a state-run cessation program in Saudi Arabia. Investigators found that WhatsApp- and Twitter-based social media support groups were more likely to report a decrease in smoking frequency compared with those not using social media [27].

A total of 3 other feasibility studies examined FB use among smokers. Haines-Saah et al [28] found more postings to the Picture Me Smokefree FB page among women than men (ie, 189 total photos posted among women, mean 9.5, vs 94 posted by men, mean 4.2). Content analysis revealed that postings were of similar quality for both sexes; sharing of photos and captions about experiences with tobacco use and struggles with quitting in the context of family life and relationships were the main themes. Evaluation of the FB page [29] found that increased frequency of moderator postings to facilitate dialogue and provide support engaged existing and new users, resulting in a marked increase in user postings and reach. Finally, an FB intervention using health communication messaging and supportive moderator postings was associated with a decrease in cigarettes smoked per day from baseline to 2-week follow-up; increased engagement was associated with greater smoking reduction [30].


To overcome barriers of geography, climate, and scalability, we proposed to create and pilot-test a culturally salient social media (ie, FB) intervention to promote evidence-based smoking treatment utilization and cessation for AN people that will eventually be maintained by ANTHC’s Tobacco Prevention and Control Program. The project builds on ANTHC and Mayo Clinic’s longstanding tobacco control research partnership with the AN community and is informed by our understanding of cultural factors that can both impede (eg, stress and adverse childhood experiences) and encourage (eg, close family ties and community values) cessation in this population. The goal of this formative study is to develop an FB intervention that will be a hidden and closed FB group. The goal of the randomized pilot trial is to obtain effect size estimates to adequately power a larger scale efficacy trial. For this phase of the research, the main outcome measures will be intervention feasibility (treatment acceptability and program satisfaction) and verified smoking abstinence. Secondary outcome measures will be self-reported other tobacco abstinence, smoking treatment utilization, and interdependence as a culturally relevant mediator of intervention effectiveness. Additional feasibility measures such as social media engagement, usability, and satisfaction will also be addressed.

The goal of the pilot trial is to obtain effect size estimates to adequately power a larger scale stage 2 efficacy trial.

Theoretical Framework

We used cultural variance and surface/deep structure frameworks [31,32] to address the influence of culture in designing health messages. Cultural variance framework considers AN cultural influences on health behaviors, including beliefs and norms (ie, communication styles and social acceptance of tobacco use), values (eg, interdependence), and AN knowledge systems/ways of knowing [33-38]. Surface and deep structure inform content and format of messages. Surface structure matches materials/messages to observable social and behavioral characteristics (eg, AN people, music, and clothing), and deep structure incorporates cultural beliefs and values. Surface structure generally enhances receptivity, comprehension, and acceptance of messages, whereas deep structure conveys salience. We will also use a planning framework based on the National Cancer Institute [39] and Centers for Disease Control (CDC) [40] recommendations for developing social media and other digital health communication tools, addressing key components of message construction [41,42] that are also consistent with stage 1 of the 3-stage model of behavioral therapies development [43] that includes intervention development, refinement, modification/adaptation, and pilot testing. In summary, we will conduct the research in 4 phases. In phase 1, we will use qualitative in-depth interviews and then in phase 2, quantitative methods to develop/refine message concepts. Next, in phase 3, we will develop and beta-test the intervention prototype; and finally, in phase 4, we will conduct a randomized pilot trial of the intervention (Figure 1).

Figure 1. Overview of process to develop CAN Quit Facebook intervention. AN: Alaska Native; RCT: randomized controlled trial. CAN Quit: Connecting Alaska Native people to quit smoking (CAN Quit).
View this figure

Intervention Content

Content for our FB intervention is culturally relevant, adapting the storytelling approach used in both the ANTHC digital stories about smoking cessation from AN people and the CDC Tips mass media campaign [44]. On the basis of factual health communication messaging, Tips features graphic, emotional, true stories from former smokers to increase awareness of smoking harms and encourage quitting. It includes the call to use free, evidence-based statewide quitline numbers and smoking cessation website resources ( The campaign increased quitline utilization and quit attempts on a population level [44,45].

Tips stories promote salience and reduce tendency for smokers to discount adverse health outcomes as uncommon because stories feature real people [46]. Numerous studies, including a previous study by our team [33], suggest that storytelling is congruent with AN culture (strong oral storytelling tradition) [47-49], making the Tips format ideal for social media content development. Digital storytelling and other narrative forms of communication (eg, photonovela and photovoice) have emerged as important tools for health behavior change [50-52]. The communication forms reinforce traditional knowledge systems and cross-generational learning and build social connections [36,38]. Also relevant to the Tips campaign is the study conducted by our team indicating that AN adults preferred graphic, factual messages on tobacco use harms compared with other appeals, although this research was limited to interventions communicating risks during pregnancy [53,54].

The intervention will comprise an FB group moderated by a facilitator. To address potential concerns about FB privacy [55], we will utilize a closed and hidden FB group and a group policy/guideline that emphasizes confidentiality of all content. A hidden group is defined as invitation only, with the group and content not visible to anyone on FB except participants. Thus, anyone searching on FB would not find the group nor be able to request to join. Also, group membership or postings through news feeds will not be visible on the participants’ personal FB page.

We chose to use a moderated group based on research indicating that moderators play a critical role in directing and tailoring content to the group and enhancing overall social media engagement [25,56]. Also, the frequency of moderator FB postings is associated with increased participant engagement [29].


This study was reviewed and approved by the Institutional Review Boards for the AK area and Mayo Clinic. Tribal approval for the study was received from ANTHC. Our study fulfills objectives for stage 1 of the National Institute on Drug Abuse (NIDA) behavioral integrative treatment development program, where the intervention is developed in stage 1a and then evaluated for feasibility in 1b (Figure 1) [43].

Participants and Recruitment

For all study phases, we will recruit AN men and women who smoke, statewide, using targeted and paid FB ads (ie, digital targeting) based on the following: (1) aged >19 years, (2) self-reported AN race/ethnicity, and (3) keywords related to tobacco use. FB ads are a successful method of recruiting for research studies, especially among hard-to-reach populations [57,58]. We developed ads that include an image and short text consistent with FB’s advertising guidelines. We will partner with organizations that have a large FB following, such as the Alaska Federation of Natives, along with community-specific FB pages to advertise the study. We will also advertise in Tribal newsletters, newspapers, and websites and hand out flyers.

Eligibility criteria for participation are as follows: (1) AN person (male or female); (2) aged >19 years; (3) smoked at least 1 cigarette per day over the past 7-day period; (4) person with cigarettes as main tobacco product used; (5) considering or willing to make a quit attempt; (6) has access to broadband (high speed) internet on a mobile phone, at home, work, or other location; (7) has an FB account or willing to set one up before study enrollment; and (8) has not been enrolled in a program or using pharmacotherapy to stop smoking over the last 3 months. Participants will participate in the study only once, not in multiple phases (Table 1).

Table 1. Participant eligibility and rationale for both the formative study and pilot trial.
Study inclusion criteriaRationale
ANa person (based on self-reported race/ethnicity) and resides in AKbStudy targets a population with the highest prevalence of tobacco use in the United States. We chose to conduct this initial study in AK to reduce sample and intervention design heterogeneity. Across the nation, there is immense cultural and geographic variability among ANs, for example, urban versus reservation dwelling and ceremonial versus nonceremonial tobacco use. ANs do not commonly use tobacco for ceremonial purposes. Also, AK has the highest percentage of AN residents versus all other states (19% vs 2%) [59,60]. If effective, the intervention could be adapted for and disseminated to AN adults nationwide.
Aged ≥19 yearsLegal smoking age in AK is 19 years. Different social media venues and content may be warranted to address developmental issues among those <18 years. A Twitter-based intervention for adult smokers aged 20 to 59 years found that age was not related to engagement or cessation [61]; thus, we chose not to restrict the upper age limit.
Both men and women will be includedThere are no preliminary data to indicate that sex-specific interventions are warranted at this stage of the research. We will explore sex differences on feasibility and efficacy as a research question.
Smoked at least 1 cigarette per day over the past 7-day periodThis allows for participation of AN smokers who report fewer cigarettes per day and are considered light smokers but have cotinine concentrations equivalent to heavy white smokers, indicating differences in nicotine metabolism [15,62].
If other tobacco products are used, cigarettes are the main tobacco product usedCigarette smoking in combination with other tobacco product use is highly prevalent in some AK rural regions [2]; thus, results are more generalizable if other tobacco use is allowed.
Considering or willing to make a quit attemptIntervention promotes treatment utilization and quitting. We will explore readiness to quit as a potential moderator of FB engagement and efficacy.
Has access to broadband (high-speed) internet on mobile phone, at home, work, or other locationFB can be accessed on a variety of technology devices, such as computers, iPads, and mobile phones. Broadband internet access is needed to access social media and upload and download videos and other links.
Has an existing FB account or willing to set up an account before study enrollmentThere is already good adoption of FB in rural regions of AK. Including participants familiar with regular social media interaction enhances participation, whereas nonusers or those unfamiliar with FB are less likely to engage in the intervention [61,63]. To provide study access to a broader group, we will offer a Web- or paper-based tutorial for those without an FB account.
For past 3 months, not enrolled in a program or using pharmacotherapy to stop smokingStudy promotes treatment uptake, utilization, and quitting.

aAN: Alaska Native.

bAK: Alaska.

Enrollment will occur online and by phone. All advertisements will contain the study toll-free phone number, email address, and a website link to Qualtrics, where interested participants can verify eligibility and enroll. Individuals emailing or calling will receive a brief description of the study and a link to the study website. The website will contain a short description of the study and eligibility criteria. Participants will receive a US $25 Visa gift card as appreciation for their participation for each assessment they complete.


For all phases, we will ask the same sociodemographic and tobacco use questions: sex, age, Tribal affiliation, cultural identity (eg, language and traditionalism) [34], region of residence, marital status, education, employment, and current frequency of use of FB and other social media platforms. Tobacco use measures will include cigarettes per day, readiness to quit (Contemplation Ladder) [64], use of other tobacco and nicotine products, time to first cigarette after waking (<30 min vs >30 min) [65-67].


Sample characteristics will be summarized using descriptive statistics including means, percentages, and frequencies. Further analyses are described later by phase.

Quality Assurance

For all phases, we use the same coordination and communication procedures successfully utilized in our previous study that include regular study team meetings held via teleconference and a systematic plan for following up with participants to ensure as high a follow-up rate as possible is achieved with regard to key outcomes. First, to track follow-up (number and type) and reasons for attrition, the study coordinator keeps a database of all contacted and consented participants. Generally, subjects are contacted up to about 3 times (with actual contact) before being considered lost to follow-up. This same process is followed for mailed saliva collection kits that include a self-addressed, stamped return envelope with every mailing. For survey data, missing data will be minimized through Web-based assessments using Qualtrics. An email link will be sent automatically by the Mayo Clinic Survey Research Center to complete the assessment. If a participant does not complete Web-based assessments, he/she will be contacted through email or by phone by the project coordinator and prompted to complete the assessment. The baseline and follow-up surveys will be done on the Web or by phone, or the survey will be mailed with a postage-paid return envelope depending on participant preference. These surveys will take about 15 to 30 min each to complete. Participants will be mailed a US $25 Visa gift card as remuneration for completing each assessment, including returned saliva cotinine kits (Mayo Clinic Laboratories).

Stage 1a, Phases 1 to 3

We evaluated existing content using a mixed method approach, beginning with qualitative work to refine intervention content and a quantitative survey to evaluate the perceived effectiveness (PE) of selected content (phases 1-2). Once content was evaluated both qualitatively and quantitatively, a content library and moderator guide were developed, group moderators were trained, and the FB group prototype was developed. The complete FB group is now being beta-tested for final refinement (phase 3) using quantitative measures.

Stage 1a, Phase 1

We used a stratified purposeful sample [68] of AN adults who smoke with divisions based on audience segment (sex; age group 19-29, 30-49, and ≥50 years; and region—urban and rural). Krueger [69] recommends conducting at least 10 to 15 interviews per major subset before reaching data saturation, whereby no new information is being learned [69]. We estimate about 50 interviews, 40 with AN smokers (20 men, 20 women; 20 urban, 20 rural; 12-13 within each age group) and 10 with stakeholders (eg, AK’s Tobacco Quitline coaches and Tribal cessation program counselors) before reaching data saturation. An interview and moderator guide were developed to qualitatively assess potential intervention content. All participants being interviewed received a US $25 gift card for remuneration.

Moderator Guide and Training

In all, 2 ANTHC research associates conducted interviews. They are experienced in phone interviewing and completed Tobacco Treatment Specialist training and training on qualitative research methods.


Recordings were transcribed and content analysis [70] was performed using QSR NVivo software [71] to generate response themes. Codes and categories were developed based on moderator guide topics and themes emerging from the data. A total of 2 study team members coded responses for each topic area. During this open-coding process, themes were extracted for analysis when there was code endorsement or elaboration by several interviews. In addition to open coding, planned comparisons within and across sex, age, and region strata were conducted and connections were made between identified categories. Coding discrepancies were resolved through discussion with a third study team member until consensus was reached.

Stage 1a, Phase 2

From qualitative results, the research team selected 6 test concepts: 4 videos and 2 image/text moderator postings representing different types of appeals and message sources to evaluate for PE [72] via a quantitative Web-based survey.


We tested these concepts using a Web-based survey with a new sample of 40 AN adults who smoke (eligibility criteria Table 1) via a stratified purposeful sample [68], with divisions based on audience segment (eg, sex, age group, and urban/rural region) [69].


Respondents viewed test concepts (eg, video, pictures, and text) embedded in a Web-based survey via Qualtrics survey software, or by phone if preferred, with the option to be mailed or emailed the concepts for review in advance of the survey.


Measures included a validated measure of PE to pretest each concept. PE is useful for assessing the likelihood of success of potential messages when large-scale efficacy pretesting for behavioral impact is impractical [72]. We used a 6-item validated measure of PE used to evaluate Tips stories [72], similar to PE measures used in other research [73]. After viewing each concept, respondents rated their level of agreement on a scale from 1 (strongly disagree) to 5 (strongly agree) with the following statements: (1) this was worth remembering; (2) this grabbed my attention; (3) this was powerful; (4) this was informative; (5) this was meaningful; and (6) this was convincing. Participants also rated each concept for this fits with my culture.


PE items were summarized using descriptive statistics including means, percentages, and frequencies. The Chi-square goodness of fit test was used to summarize concepts most and least preferred by the participants. The associations of participant sex, age, and region with message concept preferences were examined using linear regression. Following the analysis of PE data, the research team reviewed and synthesized results from the previous phases to develop the prototype intervention for beta testing. Postings that were consistent with the content had high scores for PE, and those that qualitatively generated a positive reaction as being culturally salient and emotional and included images specific to AN culture as expressed by the interview participants were included.

Stage 1a, Phase 3

The Mayo Clinic Social Media Department created the FB group page, and members of the research team developed the content library of moderator postings and set up the software to capture participant use data. Existing Tips and ANTHC digital stories deemed culturally acceptable in the formative phases were utilized for moderator postings. Additional content was added from an ANTHC photo library based on participant feedback and the expertise on AN culture provided by our ANTHC partners [47-49]. We created a content library of 66 postings that included 8 videos and 58 image/text postings. For each piece of content, a sample of accompanying text is provided for moderators to use, as well as a probe for generating further discussion or ways to respond to users’ questions. All sample text ends in a question to spark discussion among group members. All content includes the phone number of the AK state Quitline as well as a study-specific link that connects participants to the Quitline and AN Tribal cessation resources. Although the content library is crucial for generating discussion among participants, a central aspect of the intervention is the way that the moderators interact with group members. Therefore, in addition to rigorously refining our content, we also engaged our moderators in a structured training process where they were taught principles of group moderation, best practices for moderating and engaging participants, how to promote appropriate conversations and redirect engagement, and how to respond to difficult situations that often arise in a Web-based group among other topics. Moderators also participated in didactic training to learn about basic communication principles consistent with active listening and motivational interviewing. Finally, moderators were given the opportunity to practice their moderating skills with a social media expert/consultant using a role-playing format. This reinforced the content of the structured training and developed the moderators’ skills in writing posts to promote engagement, promoting participation and support of group members, and pulling in and welcoming new members. Moderators were encouraged to help generate daily participation in the FB group until group members became the main drivers of communication, but not to post new content daily, to avoid the risk of participants simply reading content rather than engaging with it.

The FB group is currently being beta-tested over a 30-day period. Results will be used to evaluate our processes and make any final refinements to our content (Figure 1).

Beta Test

We will beta-test the FB group with 10 AN adult smokers (Table 1) via a stratified purposeful sample [68], with divisions based on audience segment (eg, sex, age group, and urban/rural region) [69]. An FB group size of 10 was the minimum number for optimal engagement in previous studies [74,75]. The purpose of this phase will be to expose participants to the 30 days of moderator postings and obtain feedback to ensure that the system works as intended, note any technical issues that need to be remedied, and facilitate any refinements of the program.


We will utilize a Web-based survey that includes the 3-item Social Media Usability Measure: perceived ease of use, usefulness, and satisfaction rated on 5-point scales (1-strongly disagree and 5-strongly agree) [76] as well as open-ended questions. Refinements will be made based on user feedback.


Sample characteristics, Social Media Usability measures, and concepts most and least preferred will be summarized using descriptive statistics including means, percentages, and frequencies. Open-ended questions will be summarized, and themes will be generated using content analysis [70]. Results from this phase are for beta testing purposes, only for purposes of refining the content for the pilot randomized trial.

Stage 1b, Phase 4

We will use rigorous design and methodology to evaluate the FB intervention’s feasibility and potential efficacy via a pilot randomized controlled trial.


Although not able to detect statistically significant study group differences on smoking abstinence, the study can obtain estimates of the intervention effect toward planning a definitive stage 2 efficacy trial. For the dichotomous variable of point prevalence abstinence, 30 subjects per condition should provide relatively stable group proportions for effect size estimates. Effect size estimates will include odds ratios for smoking abstinence. In addition to demonstrating feasibility, a doubling of the abstinence rate for the intervention versus control condition at 6 months will be considered to be of clinical significance and warrant proceeding to an efficacy trial [77]. This approach is consistent with recommendations for stage 1 study in behavioral addictions treatment development [43] and conducting small-scale trials to advance electronic health interventions [65]. Given the small sample size, proposed mediational analyses are exploratory.

Both recruitment and eligibility will be similar to the previous 3 phases of the research, whereby flyers and targeted FB ads of AN people who smoke will be used (Table 1).


We will utilize a 2-arm, parallel-group, randomized controlled design with 60 participants randomized with 1:1 allocation to the intervention or control condition. Participants will be randomized within stratified blocks based on sex (ie, male or female), age group (eg, 19-29, 30-49, and ≥50 years), and region (ie, urban or rural)—potential variables related to outcomes [78,79]. Assessments will be conducted for both study groups at baseline and at 1-, 3-, and 6-month follow-ups. The primary outcomes are feasibility indicators and the 7-day biochemically confirmed smoking abstinence rate at the 6-month follow-up. Secondary end points are self-reported engagement in smoking cessation treatment and quit attempts (Figure 1).

Study Conditions

All participants will receive evidence-based [14] tobacco treatment referral information by postal mail (printed materials) and/or email, including information on their regional Tribal tobacco treatment program, state quitline and information on access to NRT, and quit smoking resources. The control condition will receive no additional intervention provided by research staff. The intervention condition will, additionally, receive the FB intervention developed in stage 1a.

The FB intervention, comprising 30 days of prewritten and evaluated postings, will be moderated daily by an ANTHC tobacco research counselor. When participants enter the study, they will be informed about the policies for posting content and that any inappropriate postings will be removed. As engagement may be optimal in the first 4 weeks, we will have 30 days of moderator postings available. However, we opted to have the FB group active for 3 months because participants might continue to engage in the intervention for continued social support; thus, the 30 postings will be repeated for each month the group is active. We will, therefore, measure engagement over time to empirically inform decisions about treatment duration in future trials. Accordingly, our assessments are timed to capture smoking behavior changes within the first 30 days (ie, 1 month), at the end of treatment (3 months), and at 6-month follow-up (Figure 2).

Figure 2. Study design. AK: Alaska; AN: Alaska Native.
View this figure

We will collect data on the number of potential participants screened, number eligible based on the inclusion/exclusion criteria, number of eligible participants enrolled, and reasons for exclusion or nonparticipation. The proportion of 60 participants completing the 6-month follow-up assessment (ie, retention) and the proportion providing a saliva cotinine specimen at each assessment will also be summarized. Treatment acceptability will be assessed with brief intervention satisfaction rating scales [16].

For each week of the study, we will extract for each intervention participant the following engagement metrics: number of logins; number of digital story downloads; number of user-generated posts, comments, questions, and responses to the moderator or other users; number of likes, shares, and reactions; and time and date of each. In addition, a transcript of all participant postings will be generated for content analysis.


Assessments will be completed at baseline and 1-, 3-, and 6-month follow-ups. With the exception of obtaining a saliva specimen from all participants for cotinine analysis, all measures will be administered on the Web using Qualtrics (Table 2).

Table 2. Pilot trial measures.
MeasuresBaseline1, 3, and 6 months
Sociodemographics and tobacco useXa
Feasibility measures (eg, retention, Facebook use, and engagement)X
Self-reported smoking abstinenceX
Self-reported tobacco/nicotine product useXX
Saliva cotinine to verify smoking abstinenceX
Self-reported smoking treatment utilizationX
Communal Orientation Scale (mediator)XX

aNot applicable.

Smoking Abstinence

At each follow-up, we will obtain self-reported cigarette use in the past 7 and 30 days, number of cigarettes smoked per day, and quit attempts. We will also assess current use of smokeless tobacco/iqmik, electronic cigarettes, and other tobacco/nicotine products. All participants will be mailed a saliva kit with a collection tube and postage-paid return envelope. Participants returning a saliva specimen will receive an additional US $25 Visa gift card. The specimen will be shipped to and assayed by Mayo Clinic laboratories, a standard approach for randomized trials, especially those with sample sizes <500 [30,79].

Smoking Treatment Utilization

As a secondary aim, we will document the self-reported use of any evidence-based cessation aid during the 6-month study period. For this pilot study, it is not practical to objectively verify self-reported treatment use given heterogeneity of potential services/medications used.

Communal Orientation Scale

The 14-item validated Communal Orientation Scale (COS) [80,81] will be administered at baseline and follow-up to examine interdependence as a culturally relevant mediator of intervention efficacy. In the intervention condition, we will also explore association of COS baseline scores with the degree of FB engagement, whereby a higher COS score would most likely be associated with a higher degree of engagement. This measure assesses the extent to which individuals are relationship- versus self-oriented.


Recruitment data will be summarized, including the number of potential participants screened, number excluded for each inclusion/exclusion criteria, and number of eligible individuals agreeing to participate. To assess program reach, we will calculate proportion of subjects enrolled to total eligible subjects and compare enrollment rates by region (rural or urban) using the Chi-square test. Baseline demographics will be summarized and compared between study groups using the Chi-square test for categorical variables and the 2-sample t test/rank sum test for continuous variables. Percentage of enrolled participants completing each follow-up assessment (ie, study retention) and ratings of treatment acceptability will be compared between study groups using the Chi-square test (Fisher exact test). FB use and engagement will be summarized using descriptive statistics and time effects over the 3-month treatment period and assessed via mixed effects models as appropriate to explore sex, age group, and region effects, respectively. The association of COS baseline scores and FB engagement will be evaluated using linear regression. Qualitative (content) analysis [70] will be utilized to generate themes in FB postings and comments.

Biochemically confirmed 7-day point prevalence tobacco use rate at 1-, 3-, and 6-month follow-ups will be compared between conditions using logistic regression (with odds ratio and 95% confidence interval estimates). Using an intent-to-treat approach, we will classify participants eligible but lost to follow-up or not providing biochemical verification of smoking abstinence as smoking. We will also explore multiple imputation methods [82-84] to classify lost to follow-up as cigarette smokers or nonsmokers and conduct sensitivity analyses as appropriate. For these analyses, we will adjust for stratification factors (eg, sex, age group, and urban/rural region) and any baseline differences observed between treatment conditions if data allow (ie, adequate numbers of subjects verified as abstinent). Secondary analyses using logistic regression will explore intervention effects on self-reported abstinence from all tobacco/nicotine products, quit attempts, and self-reported tobacco treatment utilization. We will follow procedures suggested by MacKinnon [85,86] to assess mediation, fitting logistic/linear regression models to the data.

The study enrolled 40 participants for phase 1, with data saturation being achieved at 30 AN people who smoke and 10 stakeholders. For phase 2, we enrolled 40 participants. Qualitative assessment of proposed intervention content was completed with 30 AN smokers and 10 stakeholders. We are currently analyzing data from the quantitative assessment with 40 participants in preparation for the beta testing, followed by the randomized pilot trial.

Principal Findings

This multistage pilot project will develop a social media intervention to promote smoking cessation among AN people through utilization of existing evidence-based approaches, such as AK’s Tobacco Quitline.

The proposed study, focusing on AN smokers, advances the methods of published social media intervention studies through the use of biochemical verification of smoking abstinence and extended duration of follow-up. Previously, most studies have targeted only young adults, whereas we plan to include a wide age range. We will also explore potential sex, age, and regional (urban/rural) effects on FB engagement and quitting, as there is limited research exploring these variables within the context of social media platforms for smoking cessation [24,26]. Within smoking cessation intervention efficacy and effectiveness trials generally, a recent literature review on sex/gender differences found that of 126 tests conducted, only 2 observed that women were significantly more likely to quit smoking than men, compared with 59 that found women were significantly less likely to quit smoking than men; the remaining 65 studies reported no difference by gender [87].


This pilot project is innovative for using social media communication tools that are culturally relevant and have already been adopted and that create statewide intervention access, thus promoting a scalable and sustainable approach that is tailored to the culture of AN people. The study is significant because it will advance research on population-specific treatments for ANs, an underserved, tobacco-use disparity group. If the pilot intervention is successful, we will have a blueprint to conduct a large randomized controlled efficacy trial.


Despite our strong mixed method experimental design, there are some limitations to our approach. First of all, although FB adoption is high among AN people overall, those not using social media will not be reached by this intervention. It is possible that some age groups will be more represented in this study than others because of possible gender-based differences in FB use and engagement. Finally, from the study design, we will not be able to assess the relative contribution of each component to intervention efficacy. Furthermore, FB utilizes certain algorithms to notify their users about topics that may be of interest to them based on their usage. However, as this is a hidden and closed group, none of the page posts will be added to a user’s news feed. Despite this, it is possible that exposure to Quitline-related ads or posts may be increased among those who participate in the group—an aspect to an FB intervention that the authors will have no control over. To explore these possible exposures, we will query intervention participants at the close of the FB group, a question about the perceptions about whether or not they received more than normal notifications, posts, or ads related to smoking, smoking cessation, or quitlines.


The described intervention has potential for promoting engagement with evidence-based smoking cessation treatment including AK’s Tobacco Quitline and Tribal cessation programs statewide and holds promise for AN people because it is scalable and sustainable. It utilizes a popular channel of communication and an existing, evidence-based treatment that could be considered for other remote AN communities to enhance the reach of evidence-based tobacco cessation treatments.


This study was supported by the NIDA, grant number R34 DA046008 (CAP). The funding source had no role in the design and conduct of this study or the drafting of this paper (CAP, PI; KRK, PI).

The authors wish to thank the ANTHC Research Consultation Committee for providing feedback on the development of this study and Selma Oskolkoff-Simon, Program Administrator for ANTHC Marketing and Communication, who provided them with pictures for the flyers.

Conflicts of Interest

JJP has consulted to technology and pharmaceutical companies focused on smoking cessation and served as an expert in litigation against the tobacco companies. All other authors have no conflicts of interest to disclose.

Multimedia Appendix 1

Peer-review reports.

PDF File (Adobe PDF File), 170 KB

  1. Jamal A, King BA, Neff LJ, Whitmill J, Babb SD, Graffunder CM. Current cigarette smoking among adults - United States, 2005-2015. MMWR Morb Mortal Wkly Rep 2016 Nov 11;65(44):1205-1211 [FREE Full text] [CrossRef] [Medline]
  2. Alaska DOHS(. Alaska Tobacco Facts. 2016. 2016.   URL: [accessed 2017-04-30]
  3. Espey DK, Jim MA, Cobb N, Bartholomew M, Becker T, Haverkamp D, et al. Leading causes of death and all-cause mortality in American Indians and Alaska Natives. Am J Public Health 2014 Jun;104(Suppl 3):S303-S311. [CrossRef] [Medline]
  4. Heron M. Deaths: leading causes for 2016. Natl Vital Stat Rep 2018 Jul;67(6):1-77 [FREE Full text] [Medline]
  5. Galloway JM. Cardiovascular health among American Indians and Alaska Natives: successes, challenges, and potentials. Am J Prev Med 2005 Dec;29(5):11-17. [CrossRef] [Medline]
  6. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. Tobacco use among US racial/ethnic minority groups--African Americans, American Indians and Alaska natives, Asian Americans and Pacific islanders, Hispanics. A report of the surgeon general. Executive summary. MMWR Recomm Rep 1998 Oct 9;47(RR-18):v-xv, 1 [FREE Full text] [Medline]
  7. Passey M, Bonevski B. The importance of tobacco research focusing on marginalized groups. Addiction 2014 Jul;109(7):1049-1051. [CrossRef] [Medline]
  8. Healthy People.   URL: [accessed 2017-03-01]
  9. Healthy Alaskans 2020. 2016.   URL: [accessed 2019-10-09]
  10. Alaska DOL. Alaska's native population. Alaska Economic Trends 2013 Apr;33(4):1-19.
  11. Lichtenstein E, Zhu S, Tedeschi GJ. Smoking cessation quitlines: an underrecognized intervention success story. Am Psychol 2010;65(4):252-261 [FREE Full text] [CrossRef] [Medline]
  12. Kaufman A, Augustson E, Davis K, Finney Rutten LJ. Awareness and use of tobacco quitlines: evidence from the Health Information National Trends Survey. J Health Commun 2010;15(Suppl 3):264-278 [FREE Full text] [CrossRef] [Medline]
  13. Ossip-Klein DJ, McIntosh S. Quitlines in North America: evidence base and applications. Am J Med Sci 2003 Oct;326(4):201-205. [CrossRef] [Medline]
  14. Fiore M, Jaen C, Baker T, Human Services, US Department of Health, Public Health Service. Treating Tobacco Use and Dependence - Quick Reference Guide for Clinicians: 2008 Update. Rockville, MD: U.S. Department of Health and Human Services. Public Health Service; 2008.
  15. Zhu AZX, Binnington MJ, Renner CC, Lanier AP, Hatsukami DK, Stepanov I, et al. Alaska Native smokers and smokeless tobacco users with slower CYP2A6 activity have lower tobacco consumption, lower tobacco-specific nitrosamine exposure and lower tobacco-specific nitrosamine bioactivation. Carcinogenesis 2013 Jan;34(1):93-101 [FREE Full text] [CrossRef] [Medline]
  16. Patten CA, Windsor RA, Renner CC, Enoch C, Hochreiter A, Nevak C, et al. Feasibility of a tobacco cessation intervention for pregnant Alaska Native women. Nicotine Tob Res 2010 Feb;12(2):79-87 [FREE Full text] [CrossRef] [Medline]
  17. Patten CA, Fadahunsi O, Hanza MM, Smith CA, Decker PA, Boyer R, et al. Tobacco cessation treatment for Alaska native adolescents: group randomized pilot trial. Nicotine Tob Res 2014 Jun;16(6):836-845 [FREE Full text] [CrossRef] [Medline]
  18. Cobb NK, Graham AL, Byron MJ, Niaura RS, Abrams DB, Workshop Participants. Online social networks and smoking cessation: a scientific research agenda. J Med Internet Res 2011 Dec 19;13(4):e119 [FREE Full text] [CrossRef] [Medline]
  19. Hudson HE. Digital diversity: broadband and indigenous populations in Alaska. J Inf Policy 2011;1:378-393. [CrossRef]
  20. Hudson HE. Institute of Social and Economic Research. 2012. Toward Universal Broadband in Rural Alaska - Part 1: An Analysis of Internet Use in Southwest Alaska Part 2: Literature Review.   URL: [accessed 2017-05-08]
  21. Power JM, Bersamin A. The FASEB Journal. 2016. Exploring the potential for technology-based nutrition education for Alaska Native WIC recipients in rural southwest Alaska.   URL: [accessed 2019-10-09]
  22. Papale G, Caponnetto P. Social media: potential tool for smoking cessation. In: Palosa R, Caponnetto P, editors. Advances in smoking cessation. London, UK: Future Medicine Ltd; 2013:152-163.
  23. Division of Cancer Control and Population Sciences. 2016. Tobacco Control Research Priorities for the Next Decade: Working Group Recommendations for 2016 - 2025.   URL: [accessed 2017-06-10]
  24. Baskerville NB, Struik LL, Hammond D, Guindon GE, Norman CD, Whittaker R, et al. Effect of a mobile phone intervention on quitting smoking in a young adult population of smokers: randomized controlled trial study protocol. JMIR Res Protoc 2015 Jan 19;4(1):e10 [FREE Full text] [CrossRef] [Medline]
  25. Struik LL, Baskerville NB. The role of Facebook in Crush the Crave, a mobile- and social media-based smoking cessation intervention: qualitative framework analysis of posts. J Med Internet Res 2014 Jul 11;16(7):e170 [FREE Full text] [CrossRef] [Medline]
  26. Pechmann C, Pan L, Delucchi K, Lakon CM, Prochaska JJ. Development of a Twitter-based intervention for smoking cessation that encourages high-quality social media interactions via automessages. J Med Internet Res 2015 Feb 23;17(2):e50 [FREE Full text] [CrossRef] [Medline]
  27. Onezi HA, Khalifa M, El-Metwally A, Househ M. The impact of social media-based support groups on smoking relapse prevention in Saudi Arabia. Comput Methods Programs Biomed 2018 Jun;159:135-143. [CrossRef] [Medline]
  28. Haines-Saah RJ, Kelly MT, Oliffe JL, Bottorff JL. Picture Me Smokefree: a qualitative study using social media and digital photography to engage young adults in tobacco reduction and cessation. J Med Internet Res 2015 Jan 26;17(1):e27 [FREE Full text] [CrossRef] [Medline]
  29. Post SD, Taylor SC, Sanders AE, Goldfarb JM, Hunt YM, Augustson EM. If you build (and moderate) it, they will come: the Smokefree Women Facebook page. J Natl Cancer Inst Monogr 2013 Dec;2013(47):206-208 [FREE Full text] [CrossRef] [Medline]
  30. Kim SJ, Marsch LA, Brunette MF, Dallery J. Harnessing Facebook for smoking reduction and cessation interventions: Facebook user engagement and social support predict smoking reduction. J Med Internet Res 2017 May 23;19(5):e168 [FREE Full text] [CrossRef] [Medline]
  31. Davis RE, Resnicow K. The cultural variance framework for tailoring health messages. In: Cho H, editor. Health Communication Message Design: Theory and Practice. Thousand Oaks, CA: Sage Publications Inc; 2012:115-136.
  32. Resnicow K, Braithwaite RL. Cultural sensitivity in public health. In: Braithwaite RL, Taylor SE, editors. Health Issues in the Black Community. Second Edition. San Francisco, CA: Jossey-Bass; 2001:516-542.
  33. Renner CC, Patten CA, Enoch C, Petraitis J, Offord KP, Angstman S, et al. Focus groups of Y-K Delta Alaska Natives: attitudes toward tobacco use and tobacco dependence interventions. Prev Med 2004 Apr;38(4):421-431. [CrossRef] [Medline]
  34. Mohatt G, McDiarmid G, Montoya V. Societies, families, and change: the Alaskan example. In: Manson SM, Dinges NG, editors. Behavioral Health Issues Among American Indians and Alaska Natives: Explorations on the Frontiers of the Biobehavioral Sciences. American Indian and Alaska Native Mental Health Research, Monograph no. 1. CA: University of Colorado Health Sciences Center; 1988:325-365.
  35. Wolsko C, Lardon C, Hopkins S, Ruppert E. Conceptions of wellness among the Yup'ik of the Yukon-Kuskokwim Delta: the vitality of social and natural connection. Ethn Health 2006 Nov;11(4):345-363. [CrossRef] [Medline]
  36. Barnhardt R, Oscar Kawagley A. Indigenous knowledge systems and Alaska native ways of knowing. Anthropol Edu Quart 2005;36(1):8-23 [FREE Full text] [CrossRef]
  37. Carmack E, Macdonald R. Water and ice-related phenomena in the Coastal Region of the Beaufort Sea: some parallels between Native experience and western science. Arctic 2008;61(3):265-280 [FREE Full text] [CrossRef]
  38. Cochran PA, Marshall CA, Garcia-Downing C, Kendall E, Cook D, McCubbin L, et al. Indigenous ways of knowing: implications for participatory research and community. Am J Public Health 2008 Jan;98(1):22-27. [CrossRef] [Medline]
  39. National Cancer Institute. 2004. Making Health Communication Programs Work.   URL: [accessed 2017-06-01]
  40. Centers for Disease Control and Prevention. 2016. CDC’s Guide to Writing for Social Media.   URL: [accessed 2017-05-08]
  41. Mummah SA, Robinson TN, King AC, Gardner CD, Sutton S. IDEAS (Integrate, Design, Assess, and Share): a framework and toolkit of strategies for the development of more effective digital interventions to change health behavior. J Med Internet Res 2016 Dec 16;18(12):e317 [FREE Full text] [CrossRef] [Medline]
  42. Pagoto S, Bennett GG. How behavioral science can advance digital health. Transl Behav Med 2013 Sep;3(3):271-276 [FREE Full text] [CrossRef] [Medline]
  43. Rounsaville BJ, Carroll KM, Onken LS. A stage model of behavioral therapies research: getting started and moving on from stage I. Clin Psychol-Sci and Pr 2001;8(2):133-142 [FREE Full text] [CrossRef]
  44. McAfee T, Davis KC, Alexander RL, Pechacek TF, Bunnell R. Effect of the first federally funded US antismoking national media campaign. Lancet 2013 Dec 14;382(9909):2003-2011. [CrossRef] [Medline]
  45. Centers for Disease Control and Prevention (CDC). Impact of a national tobacco education campaign on weekly numbers of quitline calls and website visitors--United States, March 4-June 23, 2013. MMWR Morb Mortal Wkly Rep 2013 Sep 20;62(37):763-767 [FREE Full text] [Medline]
  46. Rigotti NA, Wakefield M. Real people, real stories: a new mass media campaign that could help smokers quit. Ann Intern Med 2012 Dec 18;157(12):907-909. [CrossRef] [Medline]
  47. Cueva M, Kuhnley R, Revels L, Schoenberg NE, Dignan M. Digital storytelling: a tool for health promotion and cancer awareness in rural Alaskan communities. Int J Circumpolar Health 2015;74:28781 [FREE Full text] [CrossRef] [Medline]
  48. Cueva M, Kuhnley R, Revels L, Schoenberg NE, Lanier A, Dignan M. Engaging elements of cancer-related digital stories in Alaska. J Cancer Educ 2016 Sep;31(3):500-505 [FREE Full text] [CrossRef] [Medline]
  49. Cueva M, Kuhnley R, Revels LJ, Cueva K, Dignan M, Lanier AP. Bridging storytelling traditions with digital technology. Int J Circumpolar Health 2013;72 [FREE Full text] [CrossRef] [Medline]
  50. Gubrium A. Digital storytelling: an emergent method for health promotion research and practice. Health Promot Pract 2009 Apr;10(2):186-191. [CrossRef] [Medline]
  51. Kreuter MW, Green MC, Cappella JN, Slater MD, Wise ME, Storey D, et al. Narrative communication in cancer prevention and control: a framework to guide research and application. Ann Behav Med 2007 Jun;33(3):221-235. [CrossRef] [Medline]
  52. Dohan D, Garrett SB, Rendle KA, Halley M, Abramson C. The importance of integrating narrative into health care decision making. Health Aff (Millwood) 2016 Apr;35(4):720-725. [CrossRef] [Medline]
  53. Koller KR, Flanagan CA, Day GE, Thomas TK, Smith CA, Wolfe AW, et al. Developing a biomarker feedback intervention to motivate smoking cessation during pregnancy: phase II MAW study. Nicotine Tob Res 2017 Aug 1;19(8):930-936 [FREE Full text] [CrossRef] [Medline]
  54. Patten C, Lando H, Resnicow K, Decker P, Smith C, Hanza M, et al. Developing health communication messaging for a social marketing campaign to reduce tobacco use in pregnancy among Alaska Native women. J Commun Healthc 2018;11(4):252-262 [FREE Full text] [CrossRef] [Medline]
  55. Ramo DE, Liu H, Prochaska JJ. A mixed-methods study of young adults' receptivity to using Facebook for smoking cessation: if you build it, will they come? Am J Health Promot 2015;29(4):e126-e135 [FREE Full text] [CrossRef] [Medline]
  56. Ploderer B, Smith W, Howard S, Pearce J, Borland R. Patterns of Support in an Online Community for Smoking Cessation. In: Proceedings of the 6th International Conference on Communities and Technologies. 2013 Presented at: C&T'13; June 29-July 2, 2013; Munich, Germany p. 26-35. [CrossRef]
  57. Ramo DE, Rodriguez TM, Chavez K, Sommer MJ, Prochaska JJ. Facebook recruitment of young adult smokers for a cessation trial: methods, metrics, and lessons learned. Internet Interv 2014 Apr;1(2):58-64 [FREE Full text] [CrossRef] [Medline]
  58. Topolovec-Vranic J, Natarajan K. The use of social media in recruitment for medical research studies: a scoping review. J Med Internet Res 2016 Nov 7;18(11):e286 [FREE Full text] [CrossRef] [Medline]
  59. Fortuine R. Historical notes on the introduction of tobacco into Alaska. Alaska Med 1996;38(1):3-7. [Medline]
  60. United States Census Bureau. 2015. American Community Survey.   URL: [accessed 2017-03-31]
  61. Pechmann C, Delucchi K, Lakon CM, Prochaska JJ. Randomised controlled trial evaluation of Tweet2Quit: a social network quit-smoking intervention. Tob Control 2017 Mar;26(2):188-194 [FREE Full text] [CrossRef] [Medline]
  62. Benowitz NL, Renner CC, Lanier AP, Tyndale RF, Hatsukami DK, Lindgren B, et al. Exposure to nicotine and carcinogens among Southwestern Alaskan Native cigarette smokers and smokeless tobacco users. Cancer Epidemiol Biomarkers Prev 2012 Jun;21(6):934-942 [FREE Full text] [CrossRef] [Medline]
  63. Pagoto S, Waring ME, May CN, Ding EY, Kunz WH, Hayes R, et al. Adapting behavioral interventions for social media delivery. J Med Internet Res 2016 Jan 29;18(1):e24 [FREE Full text] [CrossRef] [Medline]
  64. Biener L, Abrams DB. The Contemplation Ladder: validation of a measure of readiness to consider smoking cessation. Health Psychol 1991;10(5):360-365. [CrossRef] [Medline]
  65. Baker TB, Gustafson DH, Shah D. How can research keep up with eHealth? Ten strategies for increasing the timeliness and usefulness of eHealth research. J Med Internet Res 2014 Feb 19;16(2):e36 [FREE Full text] [CrossRef] [Medline]
  66. Fagerström K. Determinants of tobacco use and renaming the FTND to the Fagerstrom Test for Cigarette Dependence. Nicotine Tob Res 2012 Jan;14(1):75-78. [CrossRef] [Medline]
  67. Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO. The Fagerström Test for Nicotine Dependence: a revision of the Fagerström Tolerance Questionnaire. Br J Addict 1991 Sep;86(9):1119-1127. [CrossRef] [Medline]
  68. Patton MQ. Qualitative Research & Evaluation Methods: Integrating Theory And Practice. Fourth Edition. Thousand Oaks, CA: Sage Publications Inc; 2015.
  69. Krueger RA, Casey MA. Focus Groups: A Practical Guide for Applied Research. Fifth Edition. Thousand Oaks, CA: Sage Publications Inc; 2014.
  70. Krippendorff K. Content Analysis: An Introduction To Its Methodology. Third Edition. Thousand Oaks, CA: Sage Publications Inc; 2013.
  71. QSR International. 2015. NVivo Qualitative Data Analysis Software Version 10.   URL: [accessed 2019-10-09]
  72. Davis KC, Duke J, Shafer P, Patel D, Rodes R, Beistle D. Perceived effectiveness of antismoking ads and association with quit attempts among smokers: evidence from the tips from former smokers campaign. Health Commun 2017 Aug;32(8):931-938. [CrossRef] [Medline]
  73. Biener L. Adult and youth response to the Massachusetts anti-tobacco television campaign. J Public Health Manag Pract 2000 May;6(3):40-44. [CrossRef] [Medline]
  74. Ramo DE, Thrul J, Delucchi KL, Ling PM, Hall SM, Prochaska JJ. The Tobacco Status Project (TSP): Study protocol for a randomized controlled trial of a Facebook smoking cessation intervention for young adults. BMC Public Health 2015 Sep 15;15:897 [FREE Full text] [CrossRef] [Medline]
  75. Ramo DE, Thrul J, Chavez K, Delucchi KL, Prochaska JJ. Feasibility and quit rates of the tobacco status project: a Facebook smoking cessation intervention for young adults. J Med Internet Res 2015 Dec 31;17(12):e291 [FREE Full text] [CrossRef] [Medline]
  76. Lund AM. Measuring usability with the USE questionnaire. Usability Interface 2001;8(2):3-6 [FREE Full text]
  77. Kraemer HC, Kupfer DJ. Size of treatment effects and their importance to clinical research and practice. Biol Psychiatry 2006 Jun 1;59(11):990-996. [CrossRef] [Medline]
  78. Redwood D, Lanier AP, Renner C, Smith J, Tom-Orme L, Slattery ML. Differences in cigarette and smokeless tobacco use among American Indian and Alaska Native people living in Alaska and the Southwest United States. Nicotine Tob Res 2010 Jul;12(7):791-796 [FREE Full text] [CrossRef] [Medline]
  79. Smith JJ, Ferucci ED, Dillard DA, Lanier AP. Tobacco use among Alaska Native people in the EARTH study. Nicotine Tob Res 2010 Aug;12(8):839-844 [FREE Full text] [CrossRef] [Medline]
  80. Clark MS, Ouellette R, Powell MC, Milberg S. Recipient's mood, relationship type, and helping. J Pers Soc Psychol 1987 Jul;53(1):94-103. [CrossRef] [Medline]
  81. Cohen S, Lemay EP. Why would social networks be linked to affect and health practices? Health Psychol 2007 Jul;26(4):410-417. [CrossRef] [Medline]
  82. Rubin DB. Multiple Imputation for Nonresponse in Surveys. Hoboken, NJ: John Wiley & Sons; 2004.
  83. Schafer J. Analysis of Incomplete Multivariate Data. Boca Raton, FL: CRC Press; 1997.
  84. Schafer JL. Multiple imputation: a primer. Stat Methods Med Res 1999 Mar;8(1):3-15. [CrossRef] [Medline]
  85. MacKinnon DP. Introduction to Statistical Mediation Analysis. First Edition. New York, NY: Routledge: Taylor & Francis Group; 2008.
  86. MacKinnon DP, Fairchild AJ, Fritz MS. Mediation analysis. Annu Rev Psychol 2007;58:593-614 [FREE Full text] [CrossRef] [Medline]
  87. Smith PH, Bessette AJ, Weinberger AH, Sheffer CE, McKee SA. Sex/gender differences in smoking cessation: A review. Prev Med 2016 Nov;92:135-140 [FREE Full text] [CrossRef] [Medline]

AI: American Indian
AK: Alaska
AN: Alaska Native
ANMC: Alaska Native Medical Center
ANTHC: The Alaska Native Tribal Health Consortium
CDC: Centers for Disease Control
COS: Communal Orientation Scale
FB: Facebook
NIDA: National Institute on Drug Abuse
NRT: nicotine replacement therapy
PE: perceived effectiveness

Edited by G Eysenbach; submitted 02.07.19; peer-reviewed by N Baskerville, L Akers; comments to author 28.08.19; accepted 05.09.19; published 22.11.19


©Pamela S Sinicrope Sinicrope, Kathryn R Koller, Judith J Prochaska, Christine A Hughes, Martha J Bock, Paul A Decker, Christie A Flanagan, Zoe T Merritt, Crystal D Meade, Abbie L Willetto, Ken Resnicow, Timothy K Thomas, Christi A Patten. Originally published in JMIR Research Protocols (, 22.11.2019.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on, as well as this copyright and license information must be included.