Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
698 participants
OBSERVATIONAL
2021-06-09
2022-05-23
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Menstrual patterns
Regular menstrual cycles and irregular menstrual cycles; irregular menstrual cycles are defined as having variation in menstrual cycles of greater than 2 days and less than 2 months
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Can communicate in written and spoken English
* Own functioning iPhone iOS 14 or later, with access to reliable data plan and Wifi
* Access to reliable Wifi in the bedroom
* Willingness to participate in remote visits and follow study procedures for the duration of the study, including use of Apple Watch and a wrist-work hardware prototype
* Able to read and understand the written consent form
* Reside in the US for the duration of the study
14 Years
FEMALE
No
Sponsors
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Exponent
UNKNOWN
Apple Inc.
INDUSTRY
Responsible Party
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Principal Investigators
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Bo Qing, PhD
Role: PRINCIPAL_INVESTIGATOR
Exponent
Locations
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Exponent
Phoenix, Arizona, United States
Countries
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References
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Wang Y, Park J, Zhang CY, Jukic AMZ, Baird DD, Coull BA, Hauser R, Mahalingaiah S, Zhang S, Curry CL. Performance of algorithms using wrist temperature for retrospective ovulation day estimate and next menses start day prediction: a prospective cohort study. Hum Reprod. 2025 Mar 1;40(3):469-478. doi: 10.1093/humrep/deaf005.
Other Identifiers
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Pro00054031
Identifier Type: -
Identifier Source: org_study_id
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