Mobile Health Technology in Prenatal Care: Understanding OBGYN Providers’ Beliefs About Using Technology to Manage Gestational Weight Gain

Erica L. Rauff, Danielle Symons Downs

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


High gestational weight gain (GWG) is linked to adverse maternal/infant outcomes. Scant research has examined OB/GYN providers’ (1) beliefs and barriers to using mobile health (mHealth) technology and (2) their perceptions of patient beliefs/barriers for using mHealth technology for managing GWG. Semi-structured interviews and focus groups with OB/GYN providers (N = 25) were conducted in person and via telephone. Principles of thematic analysis were used to content analyze the interviews; sample size was determined via data saturation. Most providers did not use technology when providing prenatal care (94%), recommended public websites for patients to obtain health information (72%), and reported a smartphone/tablet as the ideal tool for clinical care (83%). Providers also believed mHealth tools would be beneficial for high risk patients (e.g., overweight/obese; 67%). For the use of mHealth tools in clinical care, the most salient provider barriers were lack of time (78%), costs (61%), facility/technology issues (56%), and lack of provider willingness to adapt to change (44%). The most important provider-perceived patient barriers were access (72%) and lack of interest (67%). These findings suggest some OB/GYN providers may be open to using mHealth technology in prenatal clinics to help their patients manage GWG if the technology is time efficient, and both providers and patients can overcome barriers. The success of incorporating mHealth technology for diet/exercise counseling in prenatal clinics will lie in making it time efficient and interesting for the patient. Novel strategies to overcome provider and patient barriers are essential.

Original languageEnglish (US)
Pages (from-to)17-24
Number of pages8
JournalJournal of Technology in Behavioral Science
Issue number1
StatePublished - Mar 15 2019

All Science Journal Classification (ASJC) codes

  • Health(social science)
  • Applied Psychology
  • Human-Computer Interaction
  • Computer Science Applications

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