Leveraging Digital Technologies for Management of Peripartum Depression to Mitigate Health Disparities

Author: Alexandra Zingg, MPH, MS (2023)

Primary advisor: Sahiti Myneni, PhD

Committee members: Amy Franklin, PhD; Angela Ross, DNP, MPH, PMP, PHCNS-BC

PhD thesis, The University of Texas School of Biomedical Informatics at Houston.

ABSTRACT

Health disparities are adverse, preventable differences in health outcomes that affect disadvantaged populations. Examples of health disparities can be seen in the condition of peripartum depression (PPD), a mood disorder affecting approximately 10-15% of peripartum women. For example, Hispanic and African-American women are less likely to start or continue PPD treatment. Digital health technologies have emerged as practical solutions for PPD care and self-management. However, existing digital solutions lack an incorporation of behavior theory and distinctive information needs based on women’s personal, social, and clinical profiles. Bridging this gap, I adapt Digilego, an integrative digital health development framework consisting of: a) mixed-methods user needs analysis, (b) behavior and health literacy theory mapping, and (c) content and feature engineering specifications for future programmatic development, to address health disparities. This enhanced framework is then used to design and develop a digital platform (MomMind) for PPD prevention among women in their peripartum period. This platform contains a digital journal, social forum, a library repository of PPD patient education materials, and a repository of PPD self-monitoring surveys. In line with the existing Digilego digital health framework, throughout my iterative process of design and development, I gather design insights from my target population (n=19) and their health providers (n=9) using qualitative research methods (e.g., interviews) and secondary analysis of peer interactions in two PPD online forums (n=55,301 posts from 9,364 users spanning years 2008-2022). These multimodal needs gathering efforts allowed me to a) compile women’s information and technology needs, and b) utilize them as a guide for MomMind intervention development and evaluation. One key MomMind strength is its grounding in theory-driven behavior change techniques (e.g., shaping knowledge) and patient engagement features (e.g., electronic questionnaires) as facilitated by Digilego. Also, I extend Digilego by incorporating literacy domains (e.g., health literacy) and cognitive processes (e.g., understanding) from the eHealth literacy framework into my content engineering approach. After an in-house usability assessment, I conducted a pilot acceptability evaluation of MomMind using cross-sectional acceptability surveys and PPD health literacy surveys administered pre-and-post use of MomMind. Interviews were also conducted to assess participant’s personal opinions and feedback. The study sample included n=30 peripartum women, of whom 16 (53.3%) were Hispanic and 17 (56.7%) were in low-income ranges. A total of 29/30 (96.6%) participants approved of MomMind, 28/30 (93.3%) deemed it a good fit, and 29/30 (96.67%) deemed it easy to use. Participants showed statistically significant improvement (p<=0.05) in their ability to recognize PPD symptoms, knowledge of how to seek information related to PPD, and knowledge and beliefs about self-care activities. Core interview themes included application’s ease of use and benefits of communicating with peers and providers about PPD. Results reveal that the enhanced Digilego framework infused with health literacy models can enable development of digital health platforms widely acceptable to my target population. This work integrates siloed theories from multiple disciplines into a single approach towards addressing health disparities, and delivered a new digital health intervention for disease management among a disadvantaged population.