About this trial
The overall objective of this pilot study is to assess the feasibility of a RCT comparing Lōvu-augmented with usual prenatal care at UU. This would be a critical next step toward the long-term goal to identify technology-based interventions to improve maternal mental health in the Intermountain West. The investigator's central hypothesis is that Lōvu will be both feasible and have high patient and clinician satisfaction, and that Lōvu-generated data will be a promising substrate for AI-based mental health risk stratification.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Pregnant people receiving care at University of Utah Clinics
Less than 14 weeks gestation at enrollment
Disqualifiers
Patients enrolled in other studies utilizing remote monitoring
Trial design
Parallel
Treatments tested in this trial
Lōvu platform
BehavioralStandard prenatal care + Lōvu platform. Participant receives a Bluetooth-enabled scale, BP cuff, and handheld fetal Doppler. Orientation to Lōvu app and device use. Lōvu-generated data (e.g., weight, BP, HR) will be visible to the Lovu team and sent to the UU clinical team weekly Participant-reported outcomes (satisfaction, usability) collected via System Usability Scale (SUS)
Standard Care Arm
BehavioralStandard prenatal care per UU clinical protocols Mental health screening via PHQ-9, GAD-7, EPDS, and NIDA Quick Screen at standard intervals (these are all validated surveys) Data collected from EHR.
Treatment groups
Trial outcomes
Primary outcomes
Feasibility Outcomes
Recruitment rate and retention rate at 12 months
Secondary outcomes
Mental Health Screening Completion & Clinical Care Metrics
Proportion of participants completing PHQ-9, GAD-7, NIDA. Time to referral and first mental health visit analyzed using non-parametric t-test such as Mann Whitney U. All surveys have their own scales however investigators are only assessing the proportion of participants who complete them, not the scores themself.
Care Utilization
Counts of e-messages and phone calls compared between arms using non-parametric t-test such as Mann Whitney U.
Satisfaction & Usability
Continuous scale scores compared using t-tests or non-parametric equivalents if distributions are non-normal
AI Preparation
Data integration and variable harmonization will be evaluated descriptively. No AI model training will occur during the pilot, but variables will be characterized by frequency, completeness, and time series properties to inform future modeling.
Sponsors and contacts
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