Abstract
Background
Menopause-related symptoms are common but undertreated. Digital tools that support symptom assessment and patient education may improve engagement.
Objective
To assess whether a previsit digital menopause symptom assessment and education tool increased treatment initiation and patient engagement compared to an educational pamphlet.
Design
Women aged 45–55 years with upcoming primary care appointments were invited to participate. Those with a total Menopause Rating Scale (MRS) score ≥5 indicating bothersome menopause symptoms were included. Participants were randomized to a digital menopause symptom assessment tool or a digital educational pamphlet and completed a post-visit survey (NCT06919887).
Participants
Of the 14,726 women invited to participate between May 12, 2025, and December 5, 2025, there were 653 (4.4%) enrolled that met eligibility criteria.
Interventions
Randomized to an mHealth app called emmii or a standard digital menopause educational pamphlet.
Main measures
Menopause treatment initiation within 30 days of the clinical visit was assessed by electronic health data. Baseline and post-visit surveys were collected assessing patient experience, engagement, and perceived usefulness. Rates of menopause hormone therapy (HT) prescribing were compared with a reference population of nonparticipants aged 45–55 who had a primary care appointment at Mayo Clinic during the same period and received no study education materials.
Key results
Of 653 participants enrolled and randomized, 383 completed both the baseline and post-surveys (171 intervention and 212 control). HT initiation among study participants was significantly higher than in the reference population of women (9.3% vs. 4.4%, p < 0.001). There was no difference in HT initiation between the intervention (9.1%) and control groups (9.6%) (p = 0.83). Initiation rates were 3.8% and 4.5%, respectively (p = 0.64) for nonhormone therapies.
Conclusions
Among women with bothersome menopause symptoms, those who underwent previsit symptom screening and received educational materials had higher rates of HT initiation than women who did not participate in the study. These findings suggest that structured menopause education may improve recognition and management of menopause symptoms in routine clinical practice.
Keywords: digital tool, education, health application, menopause, menopause education
Introduction
Menopause is diagnosed retrospectively after 12 consecutive months of amenorrhea (1). During perimenopause and menopause, approximately 50%–75% of women experience vasomotor symptoms, 45%–68% experience psychological symptoms, and more than 50% develop genitourinary symptoms (2, 3). Menopause hormone therapy (HT) is the first-line treatment for bothersome vasomotor and genitourinary symptoms in symptomatic women without contraindications at and around the time of menopause. HT may also alleviate menopause-related sleep and psychological symptoms (2, 3). For women with contraindications to HT or a personal preference not to use it, multiple effective nonhormonal treatments and lifestyle interventions exist (4).
Barriers to menopause treatment exist in clinical settings. Women may hesitate to report menopause symptoms due to prior negative experiences, discomfort discussing menopause, or due to the belief that primary care is not the appropriate setting to address such concerns (5, 6). Furthermore, clinicians often lack the training, confidence, or time to routinely screen for and manage menopause-related symptoms (7, 8). Identifying solutions to these barriers could help to address treatment gaps, including with emerging technologies such as mobile health (mHealth) apps.
With the widespread use of smartphones, mHealth apps have emerged as useful tools for health care management (9). These apps offer a range of functions, from educational resources and symptom tracking to medical record access and therapeutic guidance, with an estimated one app for every medical condition (10, 11). Research suggests that menstrual health and cognitive behavioral therapy apps can enhance physical and psychological well-being (12, 13). A small, but growing, number of mHealth apps focus specifically on menopause, addressing patient education, symptom tracking, and therapeutic guidance (11). A longitudinal study of 1,900 women using the “Health & Her” app found that those who engaged more frequently with the app's features such as symptom tracking, period logging, and using in-app activities experienced significantly greater reductions in menopause symptoms over a 2-month period (14). Women randomized to use Caria, an mHealth app for menopause with an artificial intelligence chatbot-assisted symptom assessment and a 6-week self-guided program with daily cognitive behavioral therapy, mindfulness-based exercises, physical activity video sessions, and community-based peer support had significantly reduced distress related to hot flashes compared to controls with no difference in the frequency of hot flashes (15). The app did not directly facilitate engagement with clinicians or support shared decision-making about medication management.
Despite their potential benefits, most available menopause mHealth apps do not explicitly support shared decision-making or used evidence-based tools to address women's individual needs. Key gaps in menopause mHealth apps include menopause knowledge deficits, lack of guidance on treatment options, limited shared decision-making support, and challenges in symptom self-management. A 2019 systematic review of 22 mHealth menopause apps found that only 27.3% of the apps involved medical professionals in their development, and only 22.7% used evidence-based information, raising concerns about the quality and reliability of these tools (11). As a result, many women remain underinformed about available therapies or uncertain about how to engage with clinicians regarding their menopause symptoms and treatment preferences.
To address these gaps, the Mayo Clinic Center for Women's Health, in collaboration with a digital health company, BettrHealth, codeveloped a patient-centered mHealth app called emmii for menopause symptom identification and management. The app was designed to provide evidence-based menopause education, individualized symptom assessment, treatment guidance, and a printable discussion guide to facilitate shared decision-making in the primary care setting. This study evaluated whether the app increased new HT initiation in a clinical setting compared with a standard menopause educational pamphlet.
Methods
Design and participants
This study was a randomized controlled trial evaluating the emmii app vs. an educational pamphlet in women aged 45–55 years of age with a primary care appointment within three weeks of enrollment at any of the following Mayo Clinic locations (Arizona, Florida, Minnesota, or Wisconsin), between May 12, 2025 and December 5, 2025 (NCT06919887). Participants that met this inclusion criteria were identified through the electronic health record (EHR) and sent a link via email inviting them to complete the Menopause Rating Scale (MRS) and the informed consent form. Women who had a total MRS score of ≥5, indicating bothersome menopause symptoms, were randomized to either the intervention group or the control group. Participants were randomly assigned to one of two groups in a 1:1 allocation using a computer-generated random number generator. The intervention group received access to the emmii app, and the control group digitally received a standard menopause educational pamphlet. The materials were provided to participants before their primary care visits. After the visit, participants were asked to complete a post-visit survey about their experiences. The pamphlet included educational content on perimenopause and menopause symptoms, hormone and nonhormone treatment options, and lifestyle strategies based on clinical guidelines. Although it offered similar content to the app, it did not include emmii's interactive or personalized features (Supplementary Appendix 1). Patients who were unable to provide consent or were unwilling to engage with the app were excluded from the study. Participants provided informed consent prior to taking part in the study which was approved by the Mayo Clinic Institutional Review Board (IRB ID# 24-013662) (Supplementary Appendix 2).
Post-visit survey
A post-visit survey was distributed 1–3 weeks after the participant's primary care visit to assess their use of the app or pamphlet. The post-visit survey included quantitative questions with 65 discrete questions for those who received the app and 54 discrete questions for those who received the pamphlet. The additional questions for those who received the app were related to satisfaction with the app. Participants rated how important common menopause-related symptoms, on a scale from 1 (not at all important) to 5 (extremely important), are to their current healthcare needs. In addition, the survey assessed whether menopause symptoms were discussed during the clinic visit, their priorities for menopause-related health care, their perceived access to menopause care, and preferences for receiving information on menopause symptoms and treatment options. Women received up to 3 reminder messages and had up to 3 weeks after their appointments to complete the survey.
Clinical outcomes were assessed based on the use of HT at baseline and 30 days following the primary care visit. HT initiation was defined as a new estrogen prescription order within 30 days after the appointment date and with a 1-year washout period with no qualifying estrogen orders. The current definition includes both systemic and vaginal estrogen formulations.
To assess the effect of menopause education more broadly, rates of HT prescribing were compared between the combined study population (intervention and control groups) and a reference population comprising women aged 45–55 who had a primary care appointment at Mayo Clinic during the same study period but did not participate in this study nor receive menopause education materials (16).
App development and beta testing
The emmii app was codeveloped through a collaboration between the Mayo Clinic Center for Women's Health and BettrHealth, a digital health company, to offer comprehensive menopause education, evidence-based treatment options, and a personalized discussion guide for patients. The app then underwent beta testing where a convenience sample of 24 women aged 40 years and older were recruited by email to test the app for usability (16).
Statistical analysis
Descriptive statistics were calculated for both clinical outcomes and survey responses, including frequencies and percentages for categorical variables, and means and standard deviations (SD) for continuous variables. Chi-square (χ2) tests of independence were used to assess associations between categorical variables. Independent sample t-tests were conducted to compare group differences on continuous variables.
For ranking variables, response distributions were summarized as categorical frequencies and percentages. Mann–Whitney U tests were then conducted to compare rankings between two independent groups, given the ordinal nature of the data. Results are reported with the corresponding p-values. Comparisons for specific symptoms were considered exploratory, and p-values were not adjusted for multiple comparisons. Accordingly, findings from these analyses should be interpreted cautiously. The statistical analysis was conducted and verified independently of BettrHealth. For all analyses, a significance threshold of p < 0.05 was applied. All the analyses were conducted using SAS 9.04.
Results
A total of 14,726 eligible participants who were established primary care patients at any Mayo Clinic site were identified and invited to participate. Of those, 653 (4.4%) agreed to participate, met the criteria of MRS score ≥5, and were included in the study. Both the pre-visit and post-visit surveys were completed by 383 participants who were then included in the analytic sample: 171 in the intervention group and 212 in the control group (Figure 1). The reference sample consisted of 14,032 women aged 45–55 years old who had a primary care appointment during the study period.
Figure 1.
Study recruitment and participation data.
Demographics
Mean age was 50.0 ± 3.31 years in the intervention group and 49.9 ± 3.07 years in the control group. The mean BMI was 29.4 ± 7.02 kg/m2 and 30.5 ± 8.43 kg/m2, respectively. The majority of participants in both groups identified as White (94.1% intervention group and 92.5% control group) and were not Hispanic or Latino (96.5% vs. 94.8%). Educational attainment was similarly distributed, with approximately 70% of participants in each group holding a bachelor's degree or higher (70.8% intervention, 69.7% control). Most participants carried commercial insurance (94.2% intervention, 91.0% control) (Table 1). Total MRS scores did not differ between groups (intervention: 18.0 ± 6.86; control: 17.0 ± 6.59), indicating that symptom severity was comparable.
Table 1.
Baseline demographics survey.
| Variable | Intervention (N = 171) | Control (N = 212) | Total (N = 383) |
|---|---|---|---|
| Age | |||
| Mean (SD) | 50.0 (3.31) | 49.9 (3.07) | 49.9 (3.18) |
| Median | 50.0 | 50.0 | 50.0 |
| Range | 45.0, 55.0 | 45.0, 55.0 | 45.0, 55.0 |
| BMI (kg/m2) | |||
| Mean (SD) | 29.4 (7.02) | 30.5 (8.43) | 30.0 (7.84) |
| Median | 27.4 | 28.6 | 27.9 |
| Range | 17.4, 51.5 | 17.7, 70.2 | 17.4, 70.2 |
| Ethnicity, n (%) | |||
| Hispanic or Latino | 3 (1.8%) | 7 (3.3%) | 10 (2.6%) |
| Not Hispanic or Latino | 165 (96.5%) | 201 (94.8%) | 366 (95.6%) |
| Unknown | 3 (1.8%) | 4 (1.9%) | 7 (1.8%) |
| Race, n (%) | |||
| American Indian or Alaska Native | 0 (0.0%) | 4 (1.9%) | 4 (1.0%) |
| Black or African American | 5 (2.9%) | 6 (2.8%) | 11 (2.9%) |
| East Asian | 1 (0.6%) | 0 (0.0%) | 1 (0.3%) |
| South Asian | 0 (0.0%) | 3 (1.4%) | 3 (0.8%) |
| Southeast Asian | 1 (0.6%) | 3 (1.4%) | 4 (1.0%) |
| White | 160 (94.1%) | 196 (92.5%) | 356 (93.2%) |
| Other | 3 (1.8%) | 0 (0.0%) | 3 (0.8%) |
| Missing | 1 | 0 | 1 |
| Education, n (%) | |||
| High school degree or equivalent (e.g., GED) | 8 (4.7%) | 7 (3.3%) | 15 (3.9%) |
| Some college, no degree | 21 (12.3%) | 25 (11.8%) | 46 (12.0%) |
| Associate degree | 21 (12.3%) | 32 (15.2%) | 53 (13.9%) |
| Bachelor degree | 62 (36.3%) | 70 (33.2%) | 132 (34.6%) |
| Graduate degree (e.g., MA, MD, PhD) | 59 (34.5%) | 77 (36.5%) | 136 (35.6%) |
| Missing | 0 | 1 | 1 |
| Income, n (%) | |||
| Less than $20,000 | 3 (1.8%) | 9 (4.2%) | 12 (3.1%) |
| $20,000 to $34,999 | 4 (2.3%) | 2 (0.9%) | 6 (1.6%) |
| $35,000 to $49,999 | 3 (1.8%) | 11 (5.2%) | 14 (3.7%) |
| $50,000 to $74,999 | 17 (9.9%) | 9 (4.2%) | 26 (6.8%) |
| $75,000 to $99,999 | 22 (12.9%) | 23 (10.8%) | 45 (11.7%) |
| $100,000 to $149,999 | 43 (25.1%) | 55 (25.9%) | 98 (25.6%) |
| Over $150,000 | 67 (39.2%) | 87 (41.0%) | 154 (40.2%) |
| Prefer not to answer | 12 (7.0%) | 16 (7.5%) | 28 (7.3%) |
| Residence state, n (%) | |||
| AZ | 29 (17.0%) | 37 (17.5%) | 66 (17.2%) |
| FL | 34 (19.9%) | 30 (14.2%) | 64 (16.7%) |
| MN | 78 (45.6%) | 97 (45.8%) | 175 (45.7%) |
| Other | 3 (1.8%) | 9 (4.2%) | 12 (3.1%) |
| WI | 27 (15.8%) | 39 (18.4%) | 66 (17.2%) |
| Insurance, n (%) | |||
| Commercial | 161 (94.2%) | 193 (91.0%) | 354 (92.4%) |
| Medicaid | 6 (3.5%) | 11 (5.2%) | 17 (4.4%) |
| Medicare | 2 (1.2%) | 5 (2.4%) | 7 (1.8%) |
| Other | 2 (1.2%) | 3 (1.4%) | 5 (1.3%) |
| MRS score | |||
| Mean (SD) | 18.0 (6.86) | 17.0 (6.59) | 17.4 (6.72) |
| Median | 17.0 | 17.0 | 17.0 |
| Range | 5.0, 37.0 | 5.0, 35.0 | 5.0, 37.0 |
The survey analyses below only included patients who completed both baseline and post-surveys (N = 383).
Hormonal therapy initiation
The rate of new HT initiation within 30 days after the appointment was higher in the study population than in the general population [61/653 (9.34%) vs. 623/14,032 (4.44%); absolute difference, 4.90 percentage points; 95% CI: 2.64–7.16; p < 0.001]. Prior HT use in the year preceding the appointment was higher in the study population than in the general population [187/653 (28.64%) vs. 2,440/14,032 (17.39%); absolute difference, 11.25 percentage points; 95% CI: 7.73–14.77; p < 0.001]. Within the randomized study population, there was no evidence of a difference in new HT initiation within 30 days between the intervention group [29/319 (9.09%)] and the control group [32/334 (9.58%); absolute difference, −0.49 percentage points; 95% CI: −4.95 to 3.97; p = 0.83]. Among these participants, baseline MRS total scores were similar between those who initiated HT and those who did not (18.8 ± 7.0 vs. 17.9 ± 6.8), respectively; data not shown.
Post-appointment survey
In the follow-up survey, among the 383 patients who completed the survey, conditions rated as important (score of 4 or 5) by more than half of participants included weight gain and diet (70.0%), cognitive changes such as memory problems and difficulty concentrating (69.2%), sleep disturbances (62.4%), mood swings and emotional changes (60.6%), hot flashes and night sweats (55.6%), and joint pain and stiffness (54.6%) (Figure 2).
Figure 2.
Percentage of respondents rating specific symptoms or conditions as important (4 or 5) in their healthcare needs within the next year.
Across all symptoms surveyed, satisfaction with current healthcare offerings was consistently lower than participants' corresponding importance ratings (Figure 3). For example, while 70.0% of participants rated weight gain and diet as an important healthcare need, only 35.2% were satisfied with the care they currently receive for this condition. In exploratory analyses on specific symptoms, sleep disturbances were the only symptom for which importance ratings differed between the intervention and control groups at the nominal significance threshold (unadjusted p = 0.04). Given that the symptom-specific analyses were not adjusted for multiple comparisons, this finding should be interpreted as exploratory. No statistically significant differences in satisfaction ratings were observed between the intervention and control groups for any symptom surveyed.
Figure 3.
Percentage of respondents rating satisfied (4 or 5) with current healthcare offering for the specific symptom or condition.
After the intervention, 75% of users reported improved understanding of menopause symptoms, 68% reported that completing the digital tool before their appointment was useful, and more than half reported increased confidence in asking questions about and discussing symptoms related to menopause with their clinicians after using emmii. The control group was not asked these additional questions in the post-visit survey.
Discussion
In this pilot study, receiving menopause education through either the emmii app or an educational pamphlet was associated with a higher rate of HT initiation compared with women in the reference population. This finding suggests that access to menopause education, regardless of delivery format, may meaningfully increase HT usage rates. However, as the study population was self-selected, restricted to women with MRS ≥5, and had a higher prevalence of prior HT use than the reference population, the observed difference in HT initiation may reflect differences in baseline characteristics or selection bias rather than an effect of menopause education.
Our findings are consistent with prior literature that examined the relationship between menopause education and HT initiation. A cross-sectional study identifying factors that influenced women's decisions to seek HT found that physician counseling, patient knowledge about HT, and employment status were significant predictors of treatment initiation (17). Similarly, a study examining nurse-assisted telephone counseling found that patient knowledge about menopause symptoms and treatment options increased significantly (p = 0.007) and treatment decisional conflict decreased significantly (p < 0.001) when comparing the baseline and endpoint survey data, with nurse-assisted counseling occurring between the two surveys. This further supports the premise that informed patients are more likely to engage with treatment decisions (18). These results highlight the importance of patient education and its role in menopause management, findings that are consistent with the current study which demonstrated that menopause education, regardless of format, was associated with higher HT initiation than observed in the reference population.
The absence of a significant difference between the emmii app and the educational pamphlet is also consistent with prior work comparing multiple education modalities. One study randomized women across three educational interventions with equivalent content: a brochure, a traditional lecture-discussion format, and an interactive format involving individualized risk assessment and values clarification (19). All three modalities were deemed to effectively communicate the risks and benefits of HT with no significant differences between groups. Notably, that study was limited to women with higher levels of education, which may have attenuated any differential effect between the individual modalities (19). Taken together, the literature suggests that the content and availability of menopause education is more consequential than its format.
A central gap in existing literature is the absence of a standardized, evidence-based framework for menopause education. While prior studies have consistently demonstrated that no single modality outperforms another, the field has not yet identified the optimal content of menopause education, independent of its delivery format (20). Future research might investigate differences in educational content, such as whether instruction focused specifically on symptom recognition vs. treatment options produces differential effects on patient knowledge and treatment uptake. Identifying the most effective content and framing for menopause education would be a meaningful step toward developing standardized educational resources that ensure all women have access to accurate, consistent menopause information and available treatment options.
Relatedly, participants in this cohort identified weight gain and diet, for example, as among the most prominent menopause-related healthcare needs. However, weight gain is not currently represented in the MRS. This discrepancy underscores the need for instruments that incorporate a metabolic domain, as currently widely used, validated instruments may not capture the full spectrum of symptoms women prioritize, potentially limiting the acknowledgment and recognition of these concerns in both clinical encounters and research. In this context, the consistently lower satisfaction ratings compared with participants' ratings of the importance of these healthcare needs suggest a potential gap between the concerns women prioritize and the care currently available to address them.
These findings have several implications for clinical practice. Women who received any structured menopause education initiated HT at significantly higher rates than those who received none, suggesting that access to accurate education at the point of care may matter more than its delivery format. Clinicians and healthcare systems may benefit from prioritizing the integration of menopause education into routine clinical care encounters, irrespective of format.
Strengths and limitations
This study has several notable strengths. The randomized controlled design minimizes the risk of selection bias and strengthens causal inference regarding the effect of education modality on menopause treatment initiation. Menopause symptom severity, as measured by the MRS, did not differ significantly between groups, allowing any observed differences in outcomes to be attributed to the mode of education rather than to differences in symptom burden at enrollment.
There are limitations to this study that merit discussion. The study population was recruited exclusively from Mayo Clinic, which may limit the generalizability of findings to broader clinical settings. The sample was also limited in both racial and ethnic diversity, and educational diversity, which constrains the degree to which results can be extrapolated to more heterogeneous populations. Menopause status was not directly assessed, and eligibility was based on age and MRS score, which limits our ability to analyze outcomes across different stages of the menopause transition. While this study invited participation by several methods including email, patient portal message, or phone call, it is possible that these methods are not equally perceived among eligible participants of various backgrounds (21). Additionally, all participants in the study were insured, which may further limit applicability to women without consistent access to healthcare. Expanding approaches to obtain input from more heterogeneous populations will be valuable to better understand the menopause experiences in primary care for all women.
Participation bias must be considered as a possibility, potentially with women who elected to participate in this study being more symptomatic or having a heightened interest in the topic. In addition, unlike the study population, which was restricted to women with an MRS score ≥5, the reference population was identified based on age alone and MRS scores were not available. Therefore, it is possible that the lower HT prescribing rates in this group could be, at least in part, due to lower symptom burden or other differences in baseline characteristics. Survey completion also differed between groups, with a lower completion rate in the app group than in the control group. The longer survey administered to participants in the app group, which included additional questions about app satisfaction, may have contributed to this difference in completion rates and introduces the possibility of response bias in the survey findings. Lastly, the 30-day follow-up period may have been too short to capture treatment decisions that can take longer to develop.
Conclusions
This study found that structured menopause education, regardless of delivery format, was associated with significantly higher rates of HT initiation compared to women who did not receive educational materials. Potential residual confounding, stemming in part from limited information about the menopause symptoms and educational needs of women in the reference population, limits causal interpretation. However, these findings highlight a potential opportunity to improve menopause education at the point of care, encompassing both patient-facing resources and clinician training to support informed, evidence-based conversations about treatment options. Future research should prioritize identifying the optimal content of menopause education as well as conducting larger studies in more diverse populations. Addressing these gaps will be essential to ensuring that all women have equitable access to the information they need to make informed decisions about their menopause care.
Acknowledgments
This research was made possible in part by the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery.
Funding Statement
The author(s) declared that financial support was not received for this work and/or its publication.
Footnotes
Edited by: Xiaohui Sem, Women in Global Health Singapore, Singapore
Reviewed by: Meeta Meeta, Tanvir Hospital, Centre for Women and Child Health, India
Doğukan Kurç, Istanbul Medipol University Faculty of Health Sciences, Türkiye
Abbreviations MRS, menopause rating scale; HT, hormone therapy; SD, standard deviation; mHealth, mobile health; EHR, electronic health record; BMI, body mass index; RCT, randomized controlled trial.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving humans were approved by Mayo Clinic Institutional Review Board (IRB ID# 24-013662). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
JK: Writing – review & editing, Writing – original draft, Conceptualization, Supervision. CAF: Writing – review & editing, Writing – original draft. EK: Writing – review & editing, Supervision, Writing – original draft, Resources, Conceptualization, Project administration, Methodology. MH: Writing – original draft, Supervision, Writing – review & editing, Conceptualization. MP: Validation, Writing – review & editing, Project administration, Data curation, Methodology, Writing – original draft, Conceptualization, Resources. YD: Formal analysis, Writing – review & editing, Validation, Data curation, Writing – original draft. RCh: Writing – review & editing, Conceptualization, Writing – original draft. JS: Project administration, Writing – review & editing, Methodology, Formal analysis, Writing – original draft. RCa: Writing – review & editing, Writing – original draft. KC: Writing – review & editing, Data curation, Formal analysis, Writing – original draft. CS: Writing – review & editing, Writing – original draft. AK: Writing – original draft, Writing – review & editing. SF: Conceptualization, Resources, Writing – review & editing, Project administration, Supervision, Writing – original draft, Methodology.
Conflict of interest
JK has advised for Bayer Pharmaceutics, Y Story and Naviday, as well as delivered CME lectures for AiCME, Decera, Vindico and EPG Health. EK has received research support from Estetra SRL, consulting fees from Astellas Pharma, Novo Nordisk, Estetra SRL, Fresenius Kabi, Exeltis Inc., Dexcom, Bayer, and WellFound Inc. CS is an advisor for Bayer Pharmaceutics. SSF is a consultant for Era Women's Health Platform, delivers CME lectures for PriMed, AiCME, MedAll, and Medscape, and serves on the scientific advisory board for Weight Watchers. AK is founder and CEO of Bettr Health, the company that codeveloped the emmii application used in this study in collaboration with the Mayo Clinic Center for Women's Health.
The remaining author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frph.2026.1952673/full#supplementary-material
References
- 1.Harlow SD, Gass M, Hall JE, Lobo R, Maki P, Rebar RW, et al. Executive summary of the stages of reproductive aging workshop + 10: addressing the unfinished agenda of staging reproductive aging. J Clin Endocrinol Metab. (2012) 97(4):1159–68. (eng). 10.1210/jc.2011-3362 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Crandall CJ, Mehta JM, Manson JE. Management of menopausal symptoms: a review. JAMA. (2023) 329(5):405–20. 10.1001/jama.2022.24140 [DOI] [PubMed] [Google Scholar]
- 3.Faubion SS, Crandall CJ, Davis L, El Khoudary SR, Hodis HN, Lobo RA, et al. The 2022 hormone therapy position statement of the north American menopause society. Menopause. (2022) 29(7):767–94. (eng). 10.1097/gme.0000000000002028 [DOI] [PubMed] [Google Scholar]
- 4.Shufelt CL, Brown V, Carpenter JS, Chism LA, Faubion SS, Joffe H, et al. The 2023 nonhormone therapy position statement of the north American menopause society. Menopause. (2023) 30(6):573–90. (eng). 10.1097/gme.0000000000002200 [DOI] [PubMed] [Google Scholar]
- 5.Utian WH, Maamari R. Attitudes and approaches to vaginal atrophy in postmenopausal women: a focus group qualitative study. Climacteric. (2014) 17(1):29–36. 10.3109/13697137.2013.850480 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Dominus S. Women have been misled about menopause. New York Times Magazine (2023). Available online at: https://www.nytimes.com/2023/02/01/magazine/menopause-hot-flashes-hormone-therapy.html (Accessed August 21, 2026)
- 7.Lea CM, Stogdill ER, Mara KC, Bevry ML, Lovaas AM, Chaudhry R, et al. Addressing menopause symptoms in the primary care setting: opportunity to bridge care delivery gaps. Menopause. (2024) 31(12):1044–8. 10.1097/GME.0000000000002439 [DOI] [PubMed] [Google Scholar]
- 8.Kling JM, MacLaughlin KL, Schnatz PF, Crandall CJ, Skinner LJ, Stuenkel CA, et al. Menopause management knowledge in postgraduate family medicine, internal medicine, and obstetrics and gynecology residents: a cross-sectional survey. Mayo Clin Proc. (2019) 94(2):242–53. 10.1016/j.mayocp.2018.08.033 [DOI] [PubMed] [Google Scholar]
- 9.Lin J, Bates SM, Allen LN, Wright M, Mao L, Kidd M. Integrating Mobile health app data into electronic medical or health record systems and its impact on health care delivery and patient health outcomes: scoping review. JMIR Mhealth Uhealth. (2025) 13:e66650. 10.2196/66650 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Slomian J, Reginster J-Y, Ethgen O, Appelboom G, Bruyère O. Opportunity and challenges of eHealth and mHealth for patients and caregivers. Austin J Public Health Epidemiol. (2014) 1(2):3. (English). [Google Scholar]
- 11.Gkrozou F, Tsonis O, Godden M, Siafaka V, Paschopoulos M. Mobile health (mHealth) apps focused on menopause: are they any good? Post Reprod Health. (2019) 25(4):191–8. (eng). 10.1177/2053369119878978 [DOI] [PubMed] [Google Scholar]
- 12.McCloud T, Jones R, Lewis G, Bell V, Tsakanikos E. Effectiveness of a mobile app intervention for anxiety and depression symptoms in university students: randomized controlled trial. JMIR Mhealth Uhealth. (2020) 8(7):e15418. 10.2196/15418 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Zhaunova L, Bamford R, Radovic T, Wickham A, Peven K, Croft J, et al. Characterization of self-reported improvements in knowledge and health among users of flo period tracking app: cross-sectional survey. JMIR Mhealth Uhealth. (2023) 11:e40427. 10.2196/40427 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Andrews R, Lancastle D, Bache K, Lacey AS. Does health & her app use improve menopausal symptoms? A longitudinal cohort study. BMJ Open. (2023) 13(12):e077185. 10.1136/bmjopen-2023-077185 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Duffecy J, Rehman A, Gorman S, Huang YL, Klumpp H. Evaluating a mobile digital therapeutic for vasomotor and behavioral health symptoms among women in midlife: randomized controlled trial. JMIR Mhealth Uhealth. (2025) 13:e58204. 10.2196/58204 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Karam J, Paul MM, Shufelt C, Ravikumar P, Fratianni AM, Oloyede S, et al. Evaluating the efficacy of a mobile phone app in enhancing menopause knowledge and shared decision-making: protocol for a randomized controlled trial. JMIR Res Protoc. (2025) 14(1):e76536. 10.2196/76536 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Çilgin H. Predictors of initiating hormone replacement therapy in postmenopausal women: a cross-sectional study. Sci World J. (2019) 2019:1814804. (eng). 10.1155/2019/1814804 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Myers R, Quinn A, Lambert E, Petrich A, Hegarty SE, DiCarlo M, et al. Preparing women experiencing symptoms of menopause for shared decision making about treatment. Menopause. (2021) 28(9):1060–6. 10.1097/GME.0000000000001807 [DOI] [PubMed] [Google Scholar]
- 19.Rothert ML, Holmes-Rovner M, Rovner D, Kroll J, Breer L, Talarczyk G, et al. An educational intervention as decision support for menopausal women. Res Nurs Health. (1997) 20(5):377–87. 10.1002/(SICI)1098-240X(199710)20:5<377::AID-NUR2>3.0.CO;2-L [DOI] [PubMed] [Google Scholar]
- 20.Keye C, Murphy M, Saab MM, O'Driscoll M. Mapping menopause education for healthcare professionals: a scoping review. Climacteric. (2026):1–9. (eng). 10.1080/13697137.2026.2676683 [DOI] [PubMed] [Google Scholar]
- 21.Navar AM, Esselink K, Lingvay I, Varghese M, Li H, Brunson FA, et al. Response to electronic health record patient portal–based clinical study invitations. JAMA Netw Open. (2025) 8(9):e2531624. 10.1001/jamanetworkopen.2025.31624 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.