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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.065 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".