Using the Technology Acceptance Model to Develop StartSmart: mHealth for Screening, Brief Intervention, and Referral for Risk and Protective Factors in Pregnancy

J Midwifery Womens Health. 2019 Sep;64(5):630-640. doi: 10.1111/jmwh.13009. Epub 2019 Jul 26.

Abstract

Introduction: Technology decision support with tailored patient education has the potential to improve maternal and child health outcomes. The purpose of this study was to develop StartSmart, a mobile health (mHealth) intervention to support evidence-based prenatal screening, brief intervention, and referral to treatment for risk and protective factors in pregnancy.

Methods: StartSmart was developed using Davis' Technology Acceptance Model with end users engaged in the technology development from initial concept to clinical testing. The prototype was developed based upon the current guidelines, focus group findings, and consultation with patient and provider experts. The prototype was then alpha tested by clinicians and patients. Clinicians were asked to give feedback on the screening questions, treatment, brief motivational interviewing, referral algorithms, and the individualized education materials. Clinicians were asked about the feasibility of using the materials to provide brief intervention or referral to treatment. Patients were interviewed using the think aloud technique, a cognitive engineering method used to inform the design of mHealth interventions. Interview questions were guided by the Screening, Brief Intervention, Referral to Treatment theory and attention to usefulness and usability.

Results: Expert clinicians provided guidance on the screening instruments, resources, and practice guidelines. Clinicians suggested identifying specific prenatal visits for the screening (first prenatal visit, 28-week visit, and 36-week visit). Patients reported that the tablet-based screening was useful to promote adherence to guidelines and provided suggestions for improvement including more information on the diabetic diet and more resources for diabetes. During alpha testing, participants commented on navigability and usability. Patients reported favorable responses about question wording and ease of use.

Discussion: Clinicians reported the use of mHealth to screen and counsel pregnant patients on risk and protective factors facilitated their ability to provide comprehensive care.

Keywords: antepartum care; health informatics; intimate partner violence; mental health disorders; obesity; preventive health care; screening and diagnostic tests; substance use disorder.

MeSH terms

  • Decision Support Systems, Clinical*
  • Female
  • Guideline Adherence
  • Humans
  • Mass Screening
  • Motivational Interviewing
  • Patient Education as Topic
  • Practice Guidelines as Topic
  • Pregnancy
  • Prenatal Care*
  • Referral and Consultation
  • Telemedicine*