Please submit your resume and a brief cover letter outlining your interest and relevant experience.

Training Provided

No prior experience with content analysis or qualitative coding is required. The selected student will be trained on the study's content analysis and qualitative coding methods, including codebook development, applying codes in qualitative analysis software, and intercoder reliability procedures. Applicants do not need to know these methods in advance, a willingness to learn and apply structured procedures carefully is what matters.

We are seeking a motivated nurse-midwifery or DNP student to serve as a Graduate Research Assistant on a mixed-methods content analysis study examining how self-managed and medication abortion is discussed, represented, and experienced on TikTok. Following the 2022 Dobbs decision, growing numbers of people turn to social media to fill informational and emotional gaps left by the formal healthcare system, yet TikTok remains largely unexamined in the research literature. This study analyzes approximately 300 TikTok videos to identify prevalent themes, misinformation and disinformation, and unmet patient needs, and to translate those findings into evidence-based talking points that improve clinician communication. The position centers on qualitative coding: the assistant will help build and apply coding frameworks to the video corpus. This role is ideal for a student who wants to pair clinical training in midwifery with rigorous qualitative research experience at the intersection of reproductive health, digital communication, and equity.

Hours:  10-20 hours per week, flexible around clinical and academic schedule

Term:  July 2026 - June 2027 (renewable based on funding and performance)

Location: Hybrid primarily work-from-home, with occasional in-person meetings in the Ann Arbor area

• Watch and systematically code a corpus of approximately 300 English-language TikTok videos addressing medication and self-managed abortion.
• Assist in developing, refining, and documenting the codebook, including both inductive (emergent) and deductive (theory-driven) codes for themes, misinformation, and disinformation.
• Apply qualitative codes using analysis software documenting coding decisions and emerging themes.
• Participate in intercoder reliability testing, reconcile coding discrepancies with the research team, and help calculate and report agreement metrics.
• Distinguish unintentional misinformation from deliberate disinformation, and flag scientifically unsupported claims (e.g., unverified herbal alternatives or unsafe practices).
• Organize and manage the video corpus and associated metadata (engagement metrics, posting dates, creator data) in accordance with the study's data governance plan.
• Help contextualize coded narratives using engagement metrics such as views, likes, comments, and shares.
• Synthesize coded data into themes, summaries, and analytic matrices, and contribute to drafting clinical talking points and manuscript sections.
• Conduct supporting literature reviews on reproductive health communication, social media, and qualitative methodology.
• Maintain accurate records and ensure compliance with IRB guidance, TikTok research data use policies, and confidentiality and data-handling protocols (including encrypted University of Michigan Box storage and the 30-day refresh/deletion protocol).
• Participate in regular research team meetings, coding sessions, and analytic discussions.

This position is intended for nurse-midwifery / DNP students. No prior research-coding experience is required; the items below are the baseline an applicant must meet to be considered.

• Current enrollment at a University of Michigan campus (Ann Arbor, Dearborn, or Flint) in an accredited nurse-midwifery or DNP program (or a closely related graduate nursing/midwifery track).
• A foundational understanding of reproductive healthcare and women's health, consistent with nurse-midwifery training.
• Demonstrated interest in reproductive rights, reproductive justice, or maternal and reproductive health.
• Strong reading and listening comprehension and the ability to closely and consistently interpret video and textual content.
• Strong written and verbal communication skills.
• Excellent organization, attention to detail, and consistency in following systematic procedures.
• Ability to work independently, meet deadlines, and collaborate effectively as part of a team.
• Commitment to research integrity, confidentiality, and ethical conduct.

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks.  Background checks are performed in compliance with the Fair Credit Reporting Act.

The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.