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May 31, 20260 citationsOpen Access

Improving Contraceptive Counseling for College-Aged People with Uteruses: Implementing an Artificial Intelligence-Based Contraceptive Decision Aid at a University Health Clinic

SEStephanie Edwards-Latchu

Key Points

  • The project aims to enhance contraceptive counseling for college-aged individuals with uteruses using an AI-based decision aid.
  • Implemented SARHAchat™ over four iterative cycles at a university health clinic.
  • Evaluated patient and provider satisfaction using various tools: PCCC Measure and SURE tool for patients, Likert-scale for providers.
  • Collected data from eligible patients with a 27.5% survey completion rate.
  • High contraception initiation rate of 92% among participants.
  • Patient satisfaction was 68% and provider satisfaction was 69%, below the 80% benchmark.
  • SARHAchat™ users rated their providers lower than non-users (33% vs. 79%), with p=0.07.

Abstract

Unintended pregnancy disproportionately affects college-aged people with a uterus, with rates of 76% among those aged 18-19 and 56% among those aged 20–24. Contributing barriers include digital misinformation, limited appointment time, and inconsistent provider training in contraceptive counseling. This quality improvement project evaluated the impact of an AI-based contraceptive decision aid (SARHAchat™) on patient and provider satisfaction with contraceptive counseling at a university health clinic. SARHAchat™ was implemented across four iterative, two-week Plan-Do-Study-Act cycles (September–November 2025) in the Gynecology department at UNC Campus Health. A pre-appointment link was distributed to patients for voluntary completion. Patient satisfaction and decisional conflict were assessed using the Person-Centered Contraceptive Counseling (PCCC) Measure and SURE tool. Provider satisfaction was evaluated via a Likert-scale survey. Of 91 eligible patients, 27.5% completed surveys and 19.8% of provider-reported encounters involved SARHAchat™ use. Decisional conflict was low (96% reported none), and contraception initiation was high (92%), though neither patient nor provider satisfaction met the 80% benchmark (68% and 69%, respectively). SARHAchat™ users were less likely to rate their provider as "Excellent" than non-users (33% vs. 79%), a clinically meaningful though statistically non-significant difference (p = 0.07), likely reflecting the small user sample. Low SARHAchat™ uptake (19.8%) limited the ability to draw conclusions, though high decisional clarity and contraception initiation suggest promise. Satisfaction benchmarks were not met, and lower provider ratings among SARHAchat™ users warrant further investigation. Future efforts should focus on improving pre-appointment engagement to enable more definitive evaluation of the tool's effectiveness.

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Stephanie Edwards-Latchu (2026) studied this question.

synapsesocial.com/papers/6a1bd0525783ba022b6fc2dchttps://doi.org/10.17615/sf90-h093
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