JMIR Research Protocols (Apr 2014)

Preventing Postpartum Smoking Relapse Among Inner City Women: Development of a Theory-Based and Evidence-Guided Text Messaging Intervention

  • Wen, Kuang-Yi,
  • Miller, Suzanne M,
  • Kilby, Linda,
  • Fleisher, Linda,
  • Belton, Tanisha D,
  • Roy, Gem,
  • Hernandez, Enrique

DOI
https://doi.org/10.2196/resprot.3059
Journal volume & issue
Vol. 3, no. 2
p. e20

Abstract

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BackgroundUnderserved women are at high risk for smoking relapse after childbirth due to their unique socioeconomic and postpartum stressors and barriers. Mobile text messaging technology allows delivery of relapse prevention programs targeted to their personal needs over time. ObjectiveTo describe the development of a social-cognitive theory-based and evidence-guided text messaging intervention for preventing postpartum smoking relapse among inner city women. MethodsGuided by the cognitive-social health information processing framework, user-centered design, and health communication best practices, the intervention was developed through a systematic process that included needs assessment, followed by an iterative cycling through message drafting, health literacy evaluation and rewriting, review by target community members and a scientific advisory panel, and message revision, concluding with usability testing. ResultsAll message content was theory-grounded, derived by needs assessment analysis and evidence-based materials, reviewed and revised by the target population, health literacy experts, and scientific advisors. The final program, “Txt2Commit,” was developed as a fully automated system, designed to deliver 3 proactive messages per day for a 1-month postpartum smoking relapse intervention, with crave and lapse user-initiated message functions available when needed. ConclusionsThe developmental process suggests that the application of theory and best practices in the design of text messaging smoking cessation interventions is not only feasible but necessary for ensuring that the interventions are evidence based and user-centered.