Supporting Personalized prEgnancy Care wIth Artificial inteLligence (SPECIAL): An Acceptability Study of a Personalized Educational Platform.

Journal: Studies in health technology and informatics
Published Date:

Abstract

Postpartum depression (PPD) affects approximately 20% of pregnant individuals, yet half of these cases remain under-treated despite the availability of educational interventions. To address this gap, the Supporting Personalized prEgnancy Care wIth Artificial inteLligence (SPECIAL) project leverages Artificial Intelligence (AI) to deliver personalized health education materials for PPD prevention and management. This study evaluated the acceptability of a web-based prototype in SPECIAL, developed with patient input, using the Unified Theory of Acceptance of Use of Technology (UTAUT) framework. Survey data from 41 participants indicated high acceptance of this tool. Regression analysis showed that Social Influence (SI) is positively associated with the Behavioral Intention (BI) to use SPECIAL. Patient feedbacks informed further personalization of this prototype, and enhancement of peer-to-peer support features in patient-centered design process.

Authors

  • Ziwen Zhang
    Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
  • Haijing Hao
    Department of Computer Information Systems, Bentley University, Waltham, MA, USA.
  • Xiaotong Zhu
    College of Environmental Science and Engineering/Sino-Canada Joint R&D Centre for Water and Environmental Safety, Nankai University, Tianjin, 300457, China.
  • Rochelle Joly
    Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY 10065, United States.
  • Yifan Zhang
    Department of Food Science and Nutrition, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang University, Hangzhou, Zhejiang 310058, China.
  • Yiye Zhang
    Department of Healthcare Policy and Research, Weill Cornell Medical College/New York Presbyterian, NY, USA.