Development and Pilot Testing of Text Messages to Help Reduce Sugar-Sweetened Beverage Intake Among Rural Caregivers and Adolescents: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: A high consumption of sugar-sweetened beverages (SSBs) poses significant health concerns, particularly for rural adults and adolescents. A manner in which the health of both caregivers and adolescents can be improved is by developing innovative strategies that target caregivers as the agents of change. Sending text messages through mobile phones has been cited as an effective way to improve behavioral outcomes, although little research has been conducted in rural areas, particularly focusing on SSB intake. OBJECTIVE: By targeting rural caregivers, this 2-phase study aimed to (1) understand caregivers' perceptions and language preferences for SSB-related text messages to inform and refine message development and delivery and (2) evaluate the acceptability of text messages for SSB intake behavior change and examine short-term effects on SSB intake behavior. METHODS: A convergent mixed methods design was used to systematically develop and pilot-test text messages with caregivers in Southwest Virginia. In phase 1, 5 focus groups that included a card-sorting activity were conducted to explore advantages/disadvantages, language preferences (ie, tone of voice, audience, and phrase preferences), and perceived use of text messages. In phase 2, caregivers participated in a 5-week text message pilot trial that included weekly educational and personalized strategy messages and SSB intake assessments at baseline and follow-up. Before the focus groups and after completing the pilot trial, caregivers also completed a pre-post survey that assessed SSB intake, SSB home availability, and caregivers' SSB-related practices. Caregivers also completed individual follow-up telephone interviews following the pilot trial. RESULTS: In phase 1, caregivers (N=33) reported that text messages were convenient, accessible, and easy to read. In addition, they preferred messages with empathetic and authoritative tones that provided useful strategies and stayed away from using absolute words (eg, always and never). In the phase 2 pilot trial (N=30), 87% of caregivers completed baseline and 77% completed follow-up assessment, suggesting a high utilization rate. Other ways in which caregivers reported benefiting from the text messages included sharing messages with family members and friends (80%), making mental notes (57%), and looking back at messages as reminders (50%). Caregivers reported significant improvements in home environment, parenting practices, and rulemaking around SSB (P=.003, P=.02, and P=.04, respectively). In addition, the frequency of SSB intake among caregivers and adolescents significantly decreased (P=.003 and P=.005, respectively). CONCLUSIONS: Spending time in the formative phases of text message development helped understand the unique perspectives and language preferences of the target population. Furthermore, delivering an intervention through text messages has the potential to improve caregiver behaviors and reduce SSB intake among rural caregivers and adolescents. Findings from this study were used to develop a larger bank of text messages, which would be used in a future study, testing the effectiveness of a text message intervention targeting SSB intake-related caregiver behaviors.
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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 | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".