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Period tracker applications: What menstrual cycle information are they giving women?

BACKGROUND: Period tracking applications (apps) allow women to track their menstrual cycles and receive a prediction for their period dates. The majority of apps also provide predictions of ovulation day and the fertile window. Research indicates apps are basing predictions on assuming women undergo...

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Autores principales: Worsfold, Lauren, Marriott, Lorrae, Johnson, Sarah, Harper, Joyce C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504278/
https://www.ncbi.nlm.nih.gov/pubmed/34629005
http://dx.doi.org/10.1177/17455065211049905
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author Worsfold, Lauren
Marriott, Lorrae
Johnson, Sarah
Harper, Joyce C
author_facet Worsfold, Lauren
Marriott, Lorrae
Johnson, Sarah
Harper, Joyce C
author_sort Worsfold, Lauren
collection PubMed
description BACKGROUND: Period tracking applications (apps) allow women to track their menstrual cycles and receive a prediction for their period dates. The majority of apps also provide predictions of ovulation day and the fertile window. Research indicates apps are basing predictions on assuming women undergo a textbook 28-day cycle with ovulation occurring on day 14 and a fertile window between days 10 and 16. OBJECTIVE: To determine how the information period tracker apps give women on their period dates, ovulation day and fertile window compares to expected results from big data. METHODS: Five women’s profiles for 6 menstrual cycles were created and entered into 10 apps. Cycle length and ovulation day for the sixth cycle were Woman 1—Constant 28 day cycle length, ovulation day 16; Woman 2—Average 23 day cycle length, ovulation day 13; Woman 3—Average 28 day cycle length, ovulation day 17; Woman 4—Average 33 day cycle length, ovulation day 20; and Woman 5—Irregular, average 31 day cycle length, ovulation day 14. RESULTS: The 10 period tracker apps examined gave conflicting information on period dates, ovulation day and the fertile window. For cycle length, the apps all predicted woman 1’s cycles correctly but for women 2–5, the apps predicted 0 to 8 days shorter or longer than expected. For day of ovulation, for women 1–4, of the 36 predictions, 3 (8%) were exactly correct, 9 predicted 1 day too early (25%) and 67% of predictions were 2–9 days early. For woman 5, most of the apps predicted a later day of ovulation. CONCLUSION: Period tracker apps should ensure they only give women accurate information, especially for the day of ovulation and the fertile window which can only be predicted if using a marker of ovulation, such as basal body temperature, ovulation sticks or cervical mucus.
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spelling pubmed-85042782021-10-12 Period tracker applications: What menstrual cycle information are they giving women? Worsfold, Lauren Marriott, Lorrae Johnson, Sarah Harper, Joyce C Womens Health (Lond) Original Research Article BACKGROUND: Period tracking applications (apps) allow women to track their menstrual cycles and receive a prediction for their period dates. The majority of apps also provide predictions of ovulation day and the fertile window. Research indicates apps are basing predictions on assuming women undergo a textbook 28-day cycle with ovulation occurring on day 14 and a fertile window between days 10 and 16. OBJECTIVE: To determine how the information period tracker apps give women on their period dates, ovulation day and fertile window compares to expected results from big data. METHODS: Five women’s profiles for 6 menstrual cycles were created and entered into 10 apps. Cycle length and ovulation day for the sixth cycle were Woman 1—Constant 28 day cycle length, ovulation day 16; Woman 2—Average 23 day cycle length, ovulation day 13; Woman 3—Average 28 day cycle length, ovulation day 17; Woman 4—Average 33 day cycle length, ovulation day 20; and Woman 5—Irregular, average 31 day cycle length, ovulation day 14. RESULTS: The 10 period tracker apps examined gave conflicting information on period dates, ovulation day and the fertile window. For cycle length, the apps all predicted woman 1’s cycles correctly but for women 2–5, the apps predicted 0 to 8 days shorter or longer than expected. For day of ovulation, for women 1–4, of the 36 predictions, 3 (8%) were exactly correct, 9 predicted 1 day too early (25%) and 67% of predictions were 2–9 days early. For woman 5, most of the apps predicted a later day of ovulation. CONCLUSION: Period tracker apps should ensure they only give women accurate information, especially for the day of ovulation and the fertile window which can only be predicted if using a marker of ovulation, such as basal body temperature, ovulation sticks or cervical mucus. SAGE Publications 2021-10-09 /pmc/articles/PMC8504278/ /pubmed/34629005 http://dx.doi.org/10.1177/17455065211049905 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research Article
Worsfold, Lauren
Marriott, Lorrae
Johnson, Sarah
Harper, Joyce C
Period tracker applications: What menstrual cycle information are they giving women?
title Period tracker applications: What menstrual cycle information are they giving women?
title_full Period tracker applications: What menstrual cycle information are they giving women?
title_fullStr Period tracker applications: What menstrual cycle information are they giving women?
title_full_unstemmed Period tracker applications: What menstrual cycle information are they giving women?
title_short Period tracker applications: What menstrual cycle information are they giving women?
title_sort period tracker applications: what menstrual cycle information are they giving women?
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504278/
https://www.ncbi.nlm.nih.gov/pubmed/34629005
http://dx.doi.org/10.1177/17455065211049905
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