Mobile Phone Text Messaging for Tobacco Risk Communication Among Young Adult Community College Students: Protocol and Baseline Overview for a Randomized Controlled Trial
Bibliographic record
Abstract
Background: Community-college students are at high risk for tobacco use. Because the use of mobile phone text messaging is nearly ubiquitous today, short message service (SMS) may be an effective strategy for tobacco risk communication in this population. Little is known, however, concerning the message structure significantly influencing perceived tobacco risk. Objective: We aim to outline the rationale and design of Project Debunk, a randomized trial comparing the effects of different SMS text message structures. Methods: We conducted a 6-month randomized trial comparing 8 arms, based on the combination of the 3 message structures delivered to young adults in a 2×2×2 study design: framing (gain-framed or loss-framed), depth (simple or complex), and appeal (emotional or rational). Participants were invited to participate from 3 community colleges in Houston from September 2016 to July 2017. Participants were randomized to 1 arm and received text messages in 2 separate campaigns. Each campaign consisted of 2 text messages per day for 30 days. Perceived tobacco risk was assessed at baseline, 2 months after the first campaign, and 2 months after the second campaign. We assessed the perceived risk of using conventional products (eg, combustible cigarettes) and new and emerging products (eg, electronic cigarettes). The validity of message structures was assessed weekly for each campaign. A 1-week follow-up assessment was also conducted to understand immediate reactions from participants. Results: We completed data collection for the baseline survey on a rolling basis during this time and assessed the validity of the message structure after 1 week of SMS text messages. For the entire sample (N=636), the average age was 20.92 years (SD 2.52), about two-thirds were male (430/636, 67.6%), and most were black or African American (259/636, 40.7%) or white (236/636, 37.1%). After 1 week of receiving text messages, the following was noted: (a) loss-framed messages were more likely to be perceived as presenting a loss than gain-framed messages (F7,522=13.13, P<.001), (b) complex messages were perceived to be more complex than simple messages (F7,520=2.04, P=.05), and (c) emotional messages were perceived to be more emotionally involving than rational messages (F7,520=6.46, P<.001). Conclusions: This study confirms that the recruitment, randomization, and message composition have been successfully implemented. Further analyses will identify specific types of messages that are more effective than others in increasing the perceived risk of tobacco use. If our results suggest that any of the 8 specific message structures are more effective for helping young adults understand tobacco risk, this would provide evidence to include such messages as part of a larger technology-based campaign such as mobile phone apps, entertainment-based campaigns, and social media. Trial Registration: ClinicalTrials.gov NCT03457480; https://clinicaltrials.gov/ct2/show/NCT03457480 (Archived by WebCite at http://www.webcitation.org/6ykd4IIap) Registered Report Identifier: RR1-10.2196/10977
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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 | 0.036 | 0.032 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.076 | 0.011 |
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".