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Menstruation is a physical symptom that occurs in women of reproductive age and can bring pain or cramps during the menstrual period (hereafter dysmenorrhea) and premenstrual syndrome (PMS), which includes symptoms experienced before the menstrual period. Menstruation significantly impacts women's daily lives when their academic and social activities are most active [-], with 85.4% experiencing dysmenorrhea, and 38.4% reporting reduced activity due to menstrual pain [].
Period tracker apps (PTA), introduced in 2013, offer a new way to manage menstrual cycles, helping over 50 million women globally to track their menstrual cycles, mood changes, and symptoms []. PTA users may better understand these patterns, control their moods, and improve their general well-being with the help of PTA.
The main purpose of PTA is to provide information on the number of days left until the next cycle and ovulation. Most apps provide additional features such as cycle-related mood changes, pain and sleep pattern records, and statistical information about average cycles []. These apps provide valuable data on cycle patterns, which can help women manage their menstruation more effectively. In the United Kingdom, 38% of women use PTAs mainly for cycle monitoring (72%), pregnancy planning (34%), and obtaining information on infertility treatment (12%) [].
While PTAs are not specifically designed to treat PMS or dysmenorrhea, studies suggest that they may help alleviate these symptoms []. Studies have been focused on the experience of using PTAs or PTA data to understand the experience and app use [,,], feasibility of apps [-], effectiveness of period prediction [], and evaluate the apps from various aspects, such as the information and functions they provide [-]. In addition, the association between dysmenorrhea and PMS compared the characteristics of PTA users and nonusers was conducted [,].
While numerous studies have focused on PTAs, there remains a significant gap in understanding how these apps are integrated into women's daily lives and how user characteristics influence app usage.
This study aims to explore the relationship between menstruation-related experiences and PTA use among millennials and generation Z (gen Z), who are adept with smartphones and digital devices. This study proposes future implications for the development of women's health mobile apps by providing basic research data on menstrual experiences and management in millennial and gen Z women. The research addresses the following research questions: (1) What is the menstrual cycle management and app usage status of millennials and gen Z? (2) Which social factors and menstrual-related experiences affect PTA use in millennials and gen Z? (3) Which social factors and menstrual-related experiences influence their cycle management level in millennials and gen Z? (4) What are the motivators and barriers to using PTAs in millennials and gen Z?
A mixed methods approach was used in this study. A quantitative survey was first conducted, and qualitative research data were collected through interviews with some of the survey respondents. This explanatory sequential design has the advantage of detailing the quantitative results using a qualitative method [,]. The detailed research design is shown in . It includes a first phase to collect and analyze quantitative data, a connecting procedure between the first and second phases, and a second phase to collect and analyze qualitative data. Quantitative and qualitative data were linked using panel codes. The study design was planned by referring to the mixed methods research guideline published by the National Institutes of Health [].
Figure 1. Study design. Ethical ConsiderationsThe study protocol was reviewed and approved by the institutional review board of Severance Hospital (4-2023-0097). This approval ensures that the study complies with ethical standards and regulations for research involving human subjects.
Participants responded to the survey only after reading the study's purpose and agreement details provided through the mobile app. Given the nature of the survey, which involved minimal risk and was conducted via a mobile application, the requirement for written consent was waived by the institutional review board. The comprehensive survey information sheet for participants is presented in Table S1 in .
To protect the privacy and confidentiality of participants, all collected data were anonymized. Identifiable information was not collected, ensuring that individual responses could not be traced back to any participant. Data were securely stored and only accessible to the research team. Additionally, any published results do not include information that could potentially identify participants.
Survey participants received 500 credits, equivalent to 500 Korean won, as compensation for their participation. Additionally, participants in the focus group interviews (FGIs) received 60,000 credits, equivalent to 60,000 Korean won. These incentives were provided to recognize the time and effort contributed by the participants while ensuring transparency and fairness in the compensation process.
ParticipantsThe target population of this study was women aged 20-39 years. Participants were recruited from “Open survey” (Ovey), which is a platform that can provide surveys and pay compensation and has 830,000 voluntarily registered panels. Among those who met the criteria, participants were randomly recruited through an app push, and only those who read and agreed with the explanation participated in the survey. The target number of participants was 700, including 350 females aged 20-29 years and 350 females aged 30-39 years, respectively. We defined gen Z as those aged ≤27 years and millennials as those aged 28-39 years at the time of response.
SurveyThe survey was conducted on the web in March 2023, using the Ovey application. The web-based survey comprised 29 multiple choices, Likert, open-ended questions. Questions were related to respondents’ menstrual experience, menstrual cycle management behavior, usage of PTAs, and thoughts about PTAs. Depending on the preceding response, the number of questions to be answered could change; the participants responded to 15-26 questions.
The questions in the survey were developed based on previous research and the specific objectives of this study. We conducted pilot testing with a sample of 20 women. Based on the feedback and comments received during the pilot test, we revised the questionnaire to improve clarity and construction. On average, it took participants approximately 5 minutes to complete the questionnaire. We designed the survey to be concise to minimize the burden on respondents while still collecting essential information. The reporting of the survey was guided by the CHERRIES (Checklist for Reporting Results of Internet E-Surveys; Table S2 in ).
InterviewsAmong the participants who responded to the survey, those who were available for FGIs were recruited. A total of 8 people were interviewed by selecting 4 from PTA users and 4 from nonusers. In May 2023, FGIs were conducted twice on the web, and each interview lasted approximately 60 minutes. The first and second interviews were conducted among 4 app users and 4 nonusers, respectively. FGIs were recorded on Zoom and transcribed automatically using Clova Note from Naver. The questionnaire for the FGI can be found in Table S3 in of the FGI guide. The reporting of the focus groups was guided by the COREQ (consolidated criteria for reporting qualitative research; Table S4 in )
Data AnalysesData analysis was performed in 3 parts. First, we gathered data from app users’ information. Second, a survey was conducted to determine women’s menstrual experiences, app use, and tracking practices. Cycle management level is an indicator used to represent the degree to which women manage their menstrual cycles, and it is divided into 6 levels. Level 0=No record; 1=Record sometimes; 2=Record regularly; 3=Record and predict next cycle; 4=Record, predict, and reference plans; and 5=Record, predict, and change plans. Logistic regression and a generalized linear model (with log link and gamma distribution) were used to analyze the survey data. Logistic regression was used to determine the association between user characteristics and app usage, and gamma regression was used to identify factors influencing cycle management level. We examined collinearity of variables and the results of the collinearity test indicated that the VIF values for all variables were confirmed to be 2.7 or below. Third, the FGI results of the verbalized transcripts were coded, and the transcriptions were analyzed using inductive thematic analysis. Two authors independently coded each record after reviewing the encoded transcripts, implying a significant user perspective. The team then repeatedly incorporated and altered the codes to create a set of themes. Finally, the themes were identified and described using illustrative participant comments. The collected data were quantitatively analyzed using STATA (version 17.0; StataCorp), and qualitative data were analyzed using NVivo software (version 14; QSR International).
A total of 700 responses were collected, and 8 responses which gave inconsistent answers were excluded from the screening process. presents the demographics of the survey respondents. Most of these individuals were at the university level (n=450, 73.9%) in education, were employed (n=403, 58.2%), and were unmarried (n=475, 68.6%). Millennials made up 64% (n=443) of the total respondents, with the majority aged 30-34 years (n=190, 42.9%).
Table 1. Demographics of the total 692 survey respondents.CharacteristicsOverallGeneration ZMillennialsTotal, n (%)692 (100.0)249 (36.0)443 (64.0)Age in years, mean (95% CI)29.9 (29.6-30.3)24.3 (24.1-24.6)33.1 (32.8-33.4)Age groups (years), n (%)aNot applicable.
bEducation level includes both students and graduates.
Menstruation Experience and Cycle ManagementThe results of the survey on menstrual experiences and behaviors are presented in . Approximately half of the millennial and gen Z individuals reported a menarche age between 12 and 13 years. The most frequently reported average period length was 27-29 days (n=257, 36.9%), followed by 30-32 days (n=160, 23%), and 505 out of 692 (75.3%) had regular or relatively regular menstrual cycles. The proportion of those who reported irregular cycles (including relatively irregular cycles) was higher among gen Z than individuals than among millennials. A total of 68 respondents reported having severe PMS, and half of the respondents indicated that they experience strong or severe PMS. Regarding dysmenorrhea, more than half of both millennial and gen Z individuals experienced severe or strong period cramps. Regarding gynecologist visits over the past 3 years, excluding visits during pregnancy or childbirth, 445 (63.8%) respondents had never visited the clinic. Participants’ regularity in recording their period duration and date was evaluated by the period cycle management level. In total, 614 (88.7%) respondents routinely recorded their menstrual cycles. A total of 431 (62.3%) respondents reported using PTAs to record and track their menstrual cycles, with no significant difference between millennials and gen Z in PTA use.
Table 2. Survey participants menstrual experience and behavior.CategoryOverallGeneration ZMillennialsTotal, n (%)692 (100)249 (100)443 (100)Menarche, n (%)aPMS: premenstrual syndrome.
bOBGY: obstetrics and gynecology.
cNumber of visits to obstetricians and gynecologists related to menstruation, such as menstrual irregularities. Visits owing to pregnancy or childbirth were excluded.
dPTA: Period tracker apps.
Factors Affecting PTA UsePTA user and nonuser characteristics are shown in . Chi-square analysis was used to analyze the differences between the 2 groups according to several predictors. App users and nonusers showed statistically significant differences in marital status (P=.006), with unmarried individuals being more likely to use PTA. Childbirth experience significantly impacts PTA app usage (P<.001), with those who have not experienced childbirth being more likely to use the app. Logistic regression was used to determine factors that affect PTA use; marriage, childbirth experience, number of PMS symptoms, and number of dysmenorrhea symptoms were found to be statistically significant (). As an important social factor, childbirth experience was found to affect PTA use. In women with childbirth experience, the likelihood of using a PTA decreased by 52.5% compared to women without childbirth experience. To estimate the levels of PMS and dysmenorrhea, we used 3 indicators: perceived severity, effect on daily life, and number of symptoms. Among these indicators, only the number of dysmenorrhea symptoms showed statistical significance. A higher number of dysmenorrhea symptoms is significantly associated with increased PTA usage (P=.04). Each additional symptom increases the likelihood of using PTA by approximately 13.6%. The number of dysmenorrhea symptoms and cycle management level were positively associated with app use. Individuals with higher cycle management levels are significantly more likely to use PTA (P<.001). They are more than twice as likely to use PTA compared to those with lower cycle management levels.
Table 3. PTAa users and nonuser’s characteristics.PredictorNonuserApp userP valuebTotal, n (%)261 (37.7)431 (62.3)—cSocial factoraPTA: Period tracking app.
bDerived from Chi-square test.
cNot applicable.
dEducation level includes both students and graduates.
Table 4. Results of statistical analyses using logistic regression to determine likelihood of period tracking app (PTA) usage.VariablesCrude ORaP valuea95% CIaAdjusted ORbP valueb95% CIbSocial FactoraCrude odds ratio value from univariate model.
bMultivariate model. Adjusted odds ratio using the following predictors: age, marriage, menarche age, area group, visit obstetrics and gynecology in 3 years and occupation.
cNot applicable.
dPMS: premenstrual syndrome.
Factors Affecting Cycle Management LevelTwo models were used to analyze the factors affecting cycle management level (). As shown in , cycle management level was categorized into 6 levels, from “no record” (level 0) to “record, predict cycle, and change plan” (level 5). A larger value indicates a more active attitude in cycle management level. Model 1 was established to investigate social factors such as childbirth experience and education level, while Model 2 was established to investigate menstrual experience. Childbirth experience was negatively associated with cycle management level. In women with childbirth experience, the odds of having a certain cycle management level decreased by approximately 9.8%. Different education levels were compared with the baseline data (high school level). College-level and University-level education were associated with increased odds of having a certain cycle management level, with odds ratios of 1.119 and 1.122, respectively. However, graduate school level did not show a significant effect on cycle management level.
Table 5. Results of statistical analyses using logistic regression to determine likelihood of period tracking app (PTA) usage.VariablesCrude ORa95% CIaP valueaAdjusted ORb95% CIbP valuebModel 1 social factoraCrude odds ratio value from univariate model.
bMultivariate model. Adjusted odds ratio using the following predictors: age, marriage, menarche age, area group, visit obstetrics and gynecology in 3 years and occupation.
cNot applicable.
dPMS: premenstrual syndrome.
Among the menstrual experience variables, period irregularity and number of dysmenorrhea symptoms had statistically significant effects on the cycle management level (with 95% confidence). When period irregularity increased by one level, the odds of reaching a certain cycle management level decreased by approximately 0.929. In contrast, the number of dysmenorrhea symptoms and cycle management levels were positively associated with an odds ratio of 1.024. (Ordinal logistic regression results are shown in Table S5 in ).
Results of the FGIsFGIs were conducted among eight participants and their responses were recorded and coded. The profiles of interview participants can be found in Table S6 in . The participants’ comments and opinions revealed four major themes and fourteen subthemes as follows: (I) menstruation management: (1) self-calendar, (2) pain management, and (3) app use; (II) barriers to following the cycle management: (4) period irregularity, and (5) childbirth and care; (III) motivators to use apps: (6) dysmenorrhea, (7) pregnancy plan, (8) reminders, (9) reference to doctor meeting, (10) set/adjust schedule (11) self-health check; (IV) barriers to continued use of PTAs: (12) lack of app literacy, (13) lack of app accuracy, and (14) time and update issue ().
Table 6. Results of focus group interviews in thematic analysis.ThemeQuoteMenstruation managementSelf-calendar“I don\'t record it separately since it\'s a normal cycle, but sometimes it\'s difficult when I go out without sanitary pads. I sometimes note it in my Naver calendar.” [NU2, Unmarried]In total, 431 participants used PTAs as a tool to record their menstrual cycle. More than two-thirds (n=290, 67.3%) of the PTA users have been app users for more than 3 years, and 116 (26.9%) participants have been app users for more than 7 years. The most frequently used application was the Pink diary, which is an official PTA accredited by the Korean Association of Obstetricians and Gynecologists, and 103 (23.9%) respondents were using this app []. In addition, a few respondents (n=65, 15%) reported using a period tracker function embedded in their mobile phone health applications, such as Apple Health and Samsung Health (Table S7 in ).
shows the reasons for using PTAs. Most of the app users (n=368, 85%) used the app to predict their next cycle. More than half of the app users used a PTA to keep record (n=235, 54.5%) and to set or adjust their schedule (n=234, 54.3%). The most frequently used feature of PTAs was cycle prediction; 348 (80%) app users used cycle prediction features in their app and period records, while more than half of the respondents used the next period alarm and fertile window prediction features.
Figure 2. Reasons for using period tracker apps (A) and frequently used features in period tracker apps (B). OBGY: obstetrics and gynecology. We asked about the accuracy of the cycle prediction and the utility level of the app; 199 (46.2%) app users replied that their app predicted the next cycle with a 2-day error range
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