Who may see my cycle? Consent-first sharing in menstrual and reproductive health tracking: a survey of young adults in Nepal

1. Introduction

A period-tracking app that lets a user share her cycle with someone else is, in practice, a consent system. It decides what the other person can see, from when, for how long, and what they learn when access ends. Most of the menstrual-tracking literature in human-computer interaction (HCI) treats tracking as a personal practice, and most privacy work treats it as a relationship between the user and a company. Sharing with a partner, a mother or a sister sits between those two framings, and it has received less attention.

The question matters more in some places than in others. In Nepal, menstruation is still widely associated with impurity, and many women and girls are restricted from worship, cooking, touching others or sleeping at home during their period (Amatya et al., 2018; Mukherjee et al., 2020; Thapa & Aro, 2021). Phones in South Asian households are also often shared with or checked by family members (Ahmed et al., 2017; Sambasivan et al., 2018). Under those conditions, the visibility of menstrual data inside the household is a design problem in its own right, not only a question of what a server stores.

This paper reports a survey run in April–May 2025 for Myra, a student women's-health venture in Nepal that I founded with three co-founders. Myra proposed a "Companion Mode" through which a partner or family member could follow a woman's cycle. Before building anything, the team asked young women whether they would want this, and asked young men what they would want to receive. The venture has since paused, and no app was released. The survey is the only primary dataset the project produced, and I report it here as a compact, descriptive study with its limits stated.

I address three research questions:

• RQ1 (tracking practices). How do young women in this sample track their cycle, and what do they track?
• RQ2 (perceived impact and stigma). How do respondents describe the physical, emotional and social impact of menstruation, including restriction at home?
• RQ3 (companion sharing). Would women let a partner or family member follow their cycle, and on what conditions? What would the men who might receive that information want from it?

The contribution is modest: a two-sided, descriptive account from an under-studied setting, and a set of design implications for what I call consent-first sharing. Section 2 places the study in prior work. Section 3 describes the instrument, the sample and the analysis. Section 4 reports results by research question, and Section 5 discusses design implications and what changed in Myra's design. Section 6 sets out the threats to validity, which are substantial.

A note on voice: "we" refers to the Myra team, which wrote and fielded the questionnaire; "I" refers to the analysis and this write-up, which are my own.

2. Related work

2.1 Menstrual tracking in HCI

Epstein et al. (2017) combined 2,000 app reviews, a survey of 687 people and follow-up interviews to examine why and how women track their cycles. They found varied reasons, including remembering and predicting a period and informing conversations with healthcare providers; that tracking methods ranged from apps to simply remembering; that apps fail when predictions are inaccurate; and that existing apps generally ignore life stages such as young adulthood, pregnancy and menopause. Fox and Epstein (2020) showed how menstrual apps are inscribed with particular visions of menstruation, assuming for instance that users are heterosexual women with a "normal" cycle who track to gauge fertility. Pichon et al. (2022) compared the literature on menstruators' identities and needs with how menstrual-tracking apps describe themselves, found narrow characterisations and design for limited needs, and argued for treating an irregular cycle as the norm. Feminist HCI work on intimate health, such as Labella (Almeida et al., 2016), has explored designs that support intimate bodily self-knowledge in the face of taboo.

This study draws on these accounts in two ways. Its tracking items ask not only whether people track but what they track, so that the gap between recorded data and experienced symptoms can be described. And it treats partners and relatives as stakeholders whose wants can be asked about directly.

2.2 Femtech and the privacy of menstrual data

A second body of work concerns what happens to menstrual data once it is collected. Shipp and Blasco (2020) analysed the privacy policies and behaviour of 30 Android menstrual apps and found that reproductive data was, in most cases, not covered by the privacy policies at all. Mehrnezhad and Almeida (2021) evaluated the privacy notices and tracking practices of 30 fertility apps and showed that intimate data is collected and shared beyond users' knowledge or consent. Gross et al. (2021) analysed the ethics of monetising menstruation-app data, and Kressbach (2021) placed menstrual tracking within a wider big-data economy.

These concerns are not hypothetical. In 2021 the United States Federal Trade Commission finalised an order against Flo Health, the maker of one of the most widely used period apps, over allegations that it had shared users' health data with marketing and analytics firms despite promising privacy (Federal Trade Commission, 2021). After the 2022 United States Supreme Court decision that ended the federal constitutional right to abortion, Mozilla's review of 25 period and pregnancy apps and wearables gave 18 of them a privacy warning label (Mozilla Foundation, 2022). Malki et al. (2024) studied 20 popular female mHealth apps in that post-Roe setting and reported, among other problems, flawed consent and data-deletion mechanisms. Nepal's legal context differs, but the same apps are used there: in this survey, more than half of app users named Flo.

2.3 Sharing intimate and health data with others

Contextual integrity holds that privacy concerns appropriate flows of information, judged against the norms of a context, rather than secrecy alone (Nissenbaum, 2004). That framing suits companion sharing: the same information (she may need rest this week) can be appropriate to share with a sister and not with an in-law, and appropriate this month but not the next.

Work on family informatics shows that health monitoring is often a collaborative household practice (Pina et al., 2017). Research on intimate relationships shows, at the same time, that sharing features can be turned into monitoring. Levy and Schneier (2020) describe "intimate threats" within families, romantic partnerships, friendships and caregiving relationships: the people closest to us know the answers to our secret questions, have access to our devices and can exercise coercive power over us. Freed et al. (2018) document how abusive partners exploit ordinary technologies and features. Any design that lets one person see another's cycle has to be judged against these risks, not only against its benefits.

Flo introduced a partner feature in October 2023: the user shares a code, the connected partner sees cycle phase and general information but not every logged detail, and "stop sharing" immediately revokes access (Flo Health, 2023). I came across it only after the survey, during a later review of competing apps. I mention it because the design reasoning in Section 5 reaches a similar shape from different evidence.

2.4 Menstrual health and health technology in South Asia and Nepal

In Nepal, chhaupadi, the practice of isolating menstruating women and girls, has been studied mostly in the far west, where adolescent girls have described exile from the home and its effects on their lives (Amatya et al., 2018). Restrictions are not confined to rural districts. In a survey of 1,342 adolescent girls and women in three urban districts of the Kathmandu valley, Mukherjee et al. (2020) found that 83.1% did not pray during menstruation and that mothers commonly encouraged a range of restrictions. Thapa and Aro (2021) argue that the taboo is held in place at several levels at once and needs multilevel interventions.

HCI research in neighbouring India has studied menstrual health education as a sensitive, stigmatised topic. Tuli et al. (2018) studied Menstrupedia, a website and comic for menstrual health education, through a feminist HCI lens. Tuli et al. (2019) examined the perspectives of young adults, parents, teachers, social workers and health professionals, and found a disconnect between parents' and teachers' expectations about who should introduce the topic. Kumar and Anderson (2015) studied rural Indian women's mobile phone practices around a maternal-health initiative and showed that, within strict social conventions and patriarchal norms, women exercised agency and mobilised help within their communities. Sambasivan et al. (2018) found that women in India, Pakistan and Bangladesh use "performative" practices, such as app locks, deleting content and avoiding technology, to keep some privacy on phones that others borrow and monitor; Ahmed et al. (2017) report related challenges with shared phone use in Bangladesh.

I found little published HCI work on menstrual-tracking apps or companion sharing in Nepal specifically. This study does not fill that gap, but it offers a small, descriptive starting point from a young, urban, connected sample.

3. Method

3.1 Instrument

The Myra team wrote the questionnaire and fielded it as an online Tally form. The draft has six sections: demographics; tracking habits and cycle impact; cultural context and emotional well-being; Companion Mode and support; health, medical and premium features; and final thoughts with an early-access opt-in. Question types were single choice, multiple choice ("select all that apply"), 0–5 rating scales, one full ranking of five features, and open text.

The live form differed from the draft in four ways that matter for interpretation:

1. Gender branching. A gender question routed respondents into a women's branch (tracking, cycle impact, culture and Companion Mode) or a men's branch (eleven questions about following someone's cycle). The one non-binary respondent answered the women's branch.
2. Price. The draft's fixed price tiers were replaced by an open question asking what monthly amount, in Nepali rupees (NPR), the respondent would pay "considering similar pricing in other apps and that basic features stay free".
3. Untitled fields. Two fields in the men's branch had no title on the form: a 0–5 scale and a multiple-choice list of things the respondent might want to receive. I report the list as published and do not interpret the scale.
4. A late device question. A question about phone platform was answered by only 21 people and is not used.

The scale labels for "Rate how openly periods are discussed in your family or community" were not preserved in the export. The draft describes the scale as running between "very open" and "very hidden" without saying which end is 5. I infer from the data that 5 means "very open" (Section 4.3) and flag this as an assumption.

3.2 Recruitment and fielding

The survey was fielded in April–May 2025; the exact open and close dates were not preserved with the anonymised export. Recruitment was by convenience, through the team's own channels: messages to friends and colleagues, email, Instagram, LinkedIn and student organisations. There were no quotas, no screening beyond the gender branch and no incentive.

Respondents could optionally say how they found the survey. Of the 80 who did, 27 (33.8%) named a friend or colleague, 14 (17.5%) named a member of the team, 13 (16.2%) said email, 6 (7.5%) Instagram, 1 (1.2%) Instagram and email, 6 (7.5%) LinkedIn, 6 (7.5%) other social or online channels and 3 (3.8%) a student organisation or competition; 4 (5.0%) gave answers that did not describe a channel. These categories are my own grouping of free text.

3.3 Consent and ethics

According to the team's questionnaire draft, the form opened with a short statement explaining that the team was building a health app for Nepali women, that responses were anonymous, and that they would be used to help shape the product. Submitting the form was the only indication of agreement. There was no separate consent item, no information about withdrawal or data retention, and no contact for questions outside the team. The study was not reviewed by an institutional review board or ethics committee. I return to this in Section 6.

Before this analysis, contact details given for the early-access list were removed from the export. Only aggregates are reported here, and no free-text answer is quoted.

3.4 Data preparation

The export has 171 rows. In one row the answers had shifted by a column relative to their headers, which pushed its gender answer into the wrong field. I realigned it by moving each answer back under its header, which places it in the women's branch; this is the same correction made in the earlier analysis for the Myra case study. One pair of rows is identical in every answered field. It may be a double submission, but that cannot be confirmed, so both rows are kept. The pair falls in the men's branch, and removing one would change no men's-branch percentage by more than 1.5 percentage points. After realignment the women's branch has 106 respondents (105 women and one non-binary respondent) and the men's branch 65.

Free-text answers to the price question were coded to a number by a single coder after the study, for this write-up. A range was coded at its midpoint ("300–500" as 400), and "up to" or "under" an amount as that amount; unsure or conditional answers were coded as unsure. Open answers to "What is one thing that is currently missing from existing period tracking methods or apps?" were grouped into themes by that single coder, with no second rater and no codebook prepared in advance.

3.5 Analysis

The analysis is descriptive. For each question I report the number who answered (n), and counts and percentages of those who answered. For 0–5 scales I report the mean and the share rating 4 or 5. For the feature ranking I report counts at each rank and the mean rank. Multiple-choice percentages do not sum to 100.

I report two crosstabs: comfort with Companion Mode against the option "I prefer to manage it alone", because it bears directly on RQ3; and restriction against the openness scale, which also serves as a check on the inferred scale direction. For these I ran two exploratory tests: a two-sided Fisher's exact test on a 2 × 2 table, and a two-sided Mann–Whitney U test with the rank-biserial correlation as effect size. Neither test was specified before data collection. With two tests, a Bonferroni-adjusted threshold would be 0.025. Given the sampling, I treat both as descriptions of patterns within this sample, not as estimates for any population. For the same reason I give 95% Wilson intervals only for the main sharing items, as a rough indication of precision under assumptions that this sample does not meet.

The analysis was done in Python with the standard library and SciPy.

4. Results

4.1 Sample

	Women's branch (n = 106)	Men's branch (n = 65)	All (n = 171)
Under 18	3 (2.8%)	1 (1.5%)	4 (2.3%)
18–24	94 (88.7%)	55 (84.6%)	149 (87.1%)
25–34	9 (8.5%)	9 (13.8%)	18 (10.5%)
Over 34	0	0	0
Prefers English	61 (57.5%)	34 (52.3%)	95 (55.6%)
Prefers both	40 (37.7%)	30 (46.2%)	70 (40.9%)
Prefers Nepali	5 (4.7%)	1 (1.5%)	6 (3.5%)

Table 1. Age and preferred language, by branch.

The sample is young and comfortable in English. No respondent was over 34, and only six preferred Nepali alone. Every result below describes this sample.

4.2 RQ1: Tracking practices

Of the 105 women's-branch respondents who answered the tracking question, 64 (61.0%) tracked with an app, 11 (10.5%) in a notebook or calendar and 6 (5.7%) with mental notes; 17 (16.2%) tried to remember and 7 (6.7%) had never tracked. Among the 64 app users, 34 (53.1%) named Flo and 10 (15.6%) Period Calendar; the rest named a phone's built-in health or calendar app, Clue or MeetYou.

What do you track? (multiple choice, n = 106)	n	%
Dates	93	87.7
Cramps or pain	33	31.1
Flow intensity	32	30.2
Mood	31	29.2
Skin or hair changes	8	7.5
Nothing at all	6	5.7

Table 2. Items tracked.

Tracking centred on the date: 51 respondents (48.1%) tracked dates and nothing else. Self-rated understanding of one's own cycle was moderate (n = 106; mean 3.35 on the 0–5 scale; 54, or 50.9%, at 4–5).

The gap between what was tracked and what was experienced is clearest for mood. Of the 69 women who rated mood swings at 4–5 in frequency, 26 tracked mood. Of the 53 who rated cramps at 4–5, 22 tracked cramps or pain.

4.3 RQ2: Perceived impact and stigma

Symptom (0–5, n = 106)	Mean	Rated 4–5
Mood swings	3.66	69 (65.1%)
Cramps	3.28	53 (50.0%)
Bloating	3.02	46 (43.4%)
Fatigue	2.77	43 (40.6%)
Anxiety or stress	3.02	42 (39.6%)
Headaches	1.41	12 (11.3%)

Table 3. Symptom frequency.

Mood swings were the most frequently reported symptom. The cycle's impact on daily life had a mean of 3.07 (n = 106), with 41 (38.7%) at 4–5. Asked which emotions they associated with their cycle (choose two or three; n = 106), 78 (73.6%) chose irritation and 48 (45.3%) sadness, against 9 (8.5%) relief and 3 (2.8%) empowerment. Asked whether mental health affects their period (n = 106), 37 (34.9%) said "yes, deeply" and 36 (34.0%) "sometimes". Interest in mood and mental well-being features was high: mean 4.00 (n = 106), with 74 (69.8%) at 4–5.

Restriction was common. Of 106 respondents, 79 (74.5%) said they had been restricted from doing something because of their period, 23 (21.7%) said no and 2 (1.9%) preferred not to say. Two more did not tick an option but described a restriction around worship (puja) in their own words.

Openness of discussion at home or in the community had a mean of 3.45 (n = 106). Respondents who had been restricted rated it lower (n = 79; mean 3.30, median 3) than those who had not (n = 23; mean 4.13, median 5). Within this sample the difference is unlikely to be due to chance alone (Mann–Whitney U = 554, p = .003; rank-biserial correlation 0.39). This is the pattern one would expect if 5 means "very open", and it is the basis for my inferred scale direction. Read the other way round, restricted respondents would be describing their families as more open, which is less plausible. The inference remains an assumption.

4.4 RQ3: Willingness and conditions for companion sharing

Women's branch

Women were asked: "Would you feel comfortable if your partner/family member could follow your cycle respectfully through 'Companion Mode'?"

Response (n = 106)	n	%	95% Wilson interval
Yes, definitely	52	49.1	39.7–58.4
Maybe, if I could control what they see	34	32.1	24.0–41.5
No, not comfortable	11	10.4	5.9–17.6
Not sure	9	8.5	4.5–15.4

Table 4. Comfort with a companion following one's cycle.

Taken together, 86 of 106 (81.1%) were open to some form of sharing, but for a large minority that openness was explicitly conditional on control. The question named the feature and called it "respectful", which may have raised acceptance (Section 6).

Asked whom they would trust as a companion (multiple choice, n = 106), 62 (58.5%) chose a romantic partner, 26 (24.5%) their mother, 25 (23.6%) a close friend and 24 (22.6%) a sister. Thirty-nine (36.8%) ticked "I prefer to manage it alone"; of those 39, 24 ticked no one else and 15 also ticked at least one person.

Comfort response	n	Also ticked "manage it alone"	%
Yes, definitely	52	10	19.2
Maybe, if I could control what they see	34	16	47.1
No, not comfortable	11	9	81.8
Not sure	9	4	44.4
All	106	39	36.8

Table 5. Comfort with Companion Mode against the wish to manage alone.

The wish to manage alone rose as comfort fell, as one would expect. Two features of the table are more informative. One in five women who said "yes, definitely" also said they would prefer to manage alone, so wanting support and wanting privacy were not opposites. And nearly half of the conditional group ticked "manage it alone". Comparing only the "yes" and conditional groups, the difference is unlikely to be due to chance alone within this sample (Fisher's exact test, two-sided, p = .008; odds ratio 0.27). I did not run a chi-squared test on the full 4 × 2 table because three cells have expected counts below five.

Restriction did not obviously change willingness. Among the 79 restricted respondents, 36 (45.6%) said "yes, definitely" and 27 (34.2%) gave the conditional answer; among the 23 who had not been restricted, the figures were 15 (65.2%) and 5 (21.7%). These subgroups are small, and I did not test the difference.

Asked what support from a companion would help most (multiple choice, n = 106), 78 (73.6%) chose emotional support and understanding, 76 (71.7%) understanding when they might be experiencing discomfort or mood changes, 63 (59.4%) reminders for self-care such as rest and hydration, and 51 (48.1%) practical help with tasks.

Men's branch

Of the 65 men, 16 (24.6%) had ever used a period-tracking app for someone else. Asked whom they would use Companion Mode for (multiple choice, n = 65), 43 (66.2%) chose a girlfriend, 38 (58.5%) their mother, 35 (53.8%) a sister, 29 (44.6%) a friend and 17 (26.2%) a wife. The low share for "wife" fits the age profile.

How important is it to know… (0–5, n = 65)	Mean	Rated 4–5
Her physical symptoms (e.g., cramps, fatigue)	4.42	56 (86.2%)
When she might need rest or comfort	4.42	56 (86.2%)
The start and end of her period	4.12	51 (78.5%)
Her mood changes	3.95	45 (69.2%)
Her ovulation or fertility phase	3.88	44 (67.7%)

Table 6. What men rated as important to know.

What would you want to receive? (multiple choice, untitled field, n = 65)	n	%
Daily mood or health summary	41	63.1
Notifications about expected period days	35	53.8
Tips for emotional support	33	50.8
Meal or exercise suggestions	27	41.5
Educational resources	15	23.1
Gift or care-package reminders	10	15.4
Symptom updates	7	10.8
Chat prompts or check-in ideas	2	3.1

Table 7. What men would want to receive.

The contrast between Tables 6 and 7 is the clearest two-sided finding. Men rated knowing her symptoms as very important, but few chose symptom updates as something to receive; they chose summaries and guidance instead. Asked whether the app should suggest supportive actions, such as sending a kind message or giving space, 44 (67.7%) said yes, 18 (27.7%) maybe and 3 (4.6%) no. Asked whether they would want reminders or tips about being emotionally available during her period, 34 (52.3%; 95% Wilson interval 40.4–64.0) chose "only if she chooses to share that info", 29 (44.6%) yes and 2 (3.1%) no. The conditional answer was offered by the form rather than volunteered, but a majority chose it over an unconditional yes.

4.5 Help channels, feature priorities and price

These items were not part of the research questions, but they give context for the design discussion.

If their cycle pattern changed suddenly (multiple choice, n = 105), 61 (58.1%) would want to talk to a doctor in the app, 29 (27.6%) would want automated suggestions, 20 (19.0%) would answer quick surveys, and 25 (23.8%) chose none of these.

Feature (n = 106; 1 = most important)	Mean rank	Ranked first	Ranked last
Nutrition and fitness plans for periods	2.25	36	4
Doctor consultation via app	2.85	20	12
Pregnancy tracking and reminders	3.04	26	28
Reminders for period-product refills	3.19	20	28
Community support space for women	3.68	4	34

Table 8. Ranking of five features.

Pregnancy tracking was polarised: 26 respondents ranked it first and 28 last. Asked which premium features they would pay for (multiple choice, n = 106), 71 (67.0%) ticked "I would prefer a completely free app", and 55 (51.9%) ticked only that option; 29 (27.4%) would pay for telehealth consultations. In the open price question (n = 106), 70 respondents named a positive monthly amount, 20 gave zero, 14 were unsure and 2 preferred to pay per consultation. Among the 70, the median was NPR 225 and the mean NPR 388, pulled up by four answers of NPR 2,000. These figures depend on my coding of free text.

4.6 Open answers

Ninety-five respondents answered the open question about what is missing from current tools (62 in the women's branch, 33 in the men's). Many answers were non-substantive ("don't know", "never used one"). Among the rest, the most frequent themes in my single-coder grouping were access to a doctor, nutrition and diet, local context (such as Nepali calendar dates and festivals), the companion feature itself, and emotional well-being. Three answers raised consent or anonymity directly, including a request that both people agree to what is shared. Two described notifications from an existing app that felt embarrassing or alarming, such as a "late" warning after a single day. These counts are small and soft, and I use them only to illustrate the closed-question results.

5. Discussion

5.1 Summary

For RQ1, tracking in this sample was common but shallow: most women recorded dates, and few recorded the mood and pain they reported experiencing often. For RQ2, menstruation was described in emotional terms, mostly irritation and sadness; three in four women had experienced restriction, which went with lower ratings of openness at home. For RQ3, about half the women would let a companion follow their cycle without conditions and a third only with control over what is seen, while a third would rather manage alone, including some who also said yes. The men wanted to understand and help, but asked for interpretations and suggestions rather than a feed, and half made emotional prompts conditional on her choice.

5.2 Sharing is conditional, not binary

The most important result for design is that willingness and the wish for privacy co-existed. A single "share with partner" switch would treat the 52 women who said yes and the 34 who said yes-with-control as one group, and would offer nothing to the 10 who said yes and also preferred to manage alone. In contextual-integrity terms (Nissenbaum, 2004), these respondents were not refusing a flow of information; they were asking to set its norms. A companion feature should let them do that item by item and person by person.

The finding about relationships points the same way. Women most often named a romantic partner, but men would follow a mother or sister almost as often as a girlfriend. A sharing model built for one romantic partner fits neither side's answers. In a joint-family household, different relatives would plausibly warrant different grants.

5.3 Receivers want interpretation

The men's answers suggest that the useful unit of sharing is an interpretation, not a record. "She may need more rest this week", with one suggested action, matches what they asked for (a summary and tips) and avoids what women were wary of (someone else reading their logs). It also reduces what can be misused. Research on intimate relationships shows how ordinary sharing features become tools for monitoring and control (Freed et al., 2018; Levy & Schneier, 2020). An interpretation layer does not remove that risk, but it limits the detail available to a controlling partner, and it is compatible with stopping silently.

5.4 Household visibility is part of privacy

Most femtech privacy research concerns flows to companies, advertisers and, since 2022, law enforcement (Shipp & Blasco, 2020; Mozilla Foundation, 2022; Malki et al., 2024). In this sample, three quarters of women had been restricted at home, and prior work in the region shows that phones are borrowed and checked by family members (Ahmed et al., 2017; Sambasivan et al., 2018). For these users, a lock-screen notification that says "your period is due" can be a disclosure to a parent. Privacy design for this context has to consider who might see the phone, not only who receives the data.

5.5 Design implications: consent-first sharing

I summarise the implications as five properties of consent-first sharing. They are design hypotheses drawn from survey answers, not tested results.

1. Off by default. Nothing is shared until she chooses an item. Inviting a companion shares nothing by itself.
2. Scoped. Grants are per item (for example, a derived rest signal, period dates, a weekly mood summary) and per person. More sensitive items, such as raw symptoms or the fertility window, need an extra confirmation. Private notes cannot be shared.
3. Interpreted. The companion sees derived signals and suggested actions, never her logs.
4. Revocable without notice. She can remove one item or stop sharing entirely at any time. Anything that reduces access is silent: the companion sees less, or "sharing paused", without being told what was removed or why.
5. Discreet. Notification text is generic by default, and an anonymous or private mode blocks sharing rather than running alongside it.

5.6 What changed in Myra

The survey changed Myra's design in specific ways. Before it, Companion Mode was one of five broad pillars in the pitch, described loosely as letting partners and family follow a cycle. Afterwards it became the centre of the concept, specified as the interpretation layer above, with per-person grants that start off, a silent stop, and a rule that anonymous mode and sharing cannot run together. Mood moved into the same quick log as flow and pain. Notification copy became discreet by default. Language became an explicit choice at the start of onboarding, because the sample did not support a Nepali-only default but also could not speak for Nepali-only users. Clinician access was framed as a service around a free core, because many respondents wanted a doctor but few would pay a subscription.

The survey also argued against a later direction. In 2026 the team explored a pregnancy-first product. This sample, almost entirely aged 18–24 and split on pregnancy tracking, cannot support that direction, and the lack of a sample of pregnant and postpartum women is part of why it stalled. Myra is now paused. None of the design above was built or tested with users, and there is no measured outcome.

6. Limitations and threats to validity

Convenience sample. Respondents were recruited through the team's own networks, and half of those who said how they found the survey named a friend, colleague or team member. Selection probably favours people who are comfortable discussing menstruation, open to new apps and well disposed towards the team. The results describe people like the team's contacts, not women or men in Nepal.

Age and language skew. Of 171 respondents, 149 (87.1%) were 18–24 and none was over 34; only six preferred Nepali alone. The sample says nothing about older women, married women in joint families, rural women or people who do not read English, who are exactly the groups for whom household visibility may matter most.

Self-report and stated intention. A survey measures what people say. Answering "maybe, if I could control what they see" is not the same as linking a sister's phone, and stated willingness to pay is a weak guide to paying. Social desirability may have raised men's ratings of how much they want to understand.

Framing and instrument. The team that wanted to build Companion Mode wrote the questions. The comfort item named the feature and called it "respectful", which may have raised acceptance. The men's branch offered a consent-conditional option, so the 52.3% who chose it chose from a list rather than volunteering the condition. Two men's fields were untitled; the openness scale had no exported labels, so its direction is inferred; one option on the mental-health item appears in the export as "Not rarely", where the draft has "Not really" (5 respondents); and the device question was added late. As far as I have a record, the form was not piloted. Fielding dates and the exact live wording of the introduction were not kept with the export.

Analysis after the fact. The analysis was done after the study, for this write-up, by a single analyst. Free-text price amounts and open answers were coded by one coder, with no second rater and no prior codebook, so those numbers are soft. The two statistical tests were exploratory, and with a non-probability sample their p-values describe patterns within these data, not population effects.

Interviews. The team also held informal interviews and conversations alongside the survey. No notes were kept, so nothing in this paper relies on them.

No ethics review. The study was not reviewed by an ethics board. Consent was implied by submitting a form that described its purpose and promised anonymity; there was no explicit consent item and no information about withdrawal or retention. The form also offered an early-access list, which sits uneasily beside the promise of anonymity. The topic is sensitive, and four respondents reported being under 18. A future study should obtain ethics approval, use an information sheet and an explicit consent step, handle minors appropriately and separate contact details from responses at the point of collection.

Researcher position. I was the founder analysing demand for my own product. I have tried to counter that by reporting the counts that cut against the venture (a third of women would rather manage alone; 28 women ranked pregnancy tracking last; most would not pay) beside the ones that supported it.

7. Conclusion

In a young, network-recruited sample in Nepal, most women who answered tracked only the date, although mood swings and cramps were common, and three in four had been restricted because of their period. Most were open to a partner or relative following their cycle, but a third of all women only on the condition of control, and a third would rather manage alone. The men who might receive that information wanted interpretations and suggestions rather than symptom feeds, and half wanted emotional prompts only if she chose to share.

These are descriptive findings from a convenience sample, collected without ethics review, and they cannot be generalised. They do point in a consistent direction for design: sharing in menstrual and reproductive health tools should be consent-first, meaning off by default, scoped by item and person, interpreted rather than raw, revocable without notice, and discreet on a phone that others may see. Testing that direction properly would need an ethics-reviewed interview study with a wider range of women, including Nepali-only speakers and women outside Kathmandu, and a usability study of the consent flow in which the main measure is whether a participant can say correctly what a companion will see.

Acknowledgements

I thank my Myra co-founders, all students at the time: the co-founder responsible for healthcare strategy and marketing (and later research synthesis), the technical lead, and the co-founder responsible for data and analytics. The team wrote and distributed the questionnaire together. I also thank everyone who answered it and the friends who passed it on. The analysis, interpretation and any errors here are mine.

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@techreport{saakha2026consent,
  author      = {Saakha, Bibhushan},
  title       = {Who may see my cycle? Consent-first sharing in menstrual and reproductive health tracking: a survey of young adults in Nepal},
  institution = {Independent researcher},
  type        = {Working paper},
  address     = {Kathmandu, Nepal},
  year        = {2026},
  month       = oct,
  url = {https://www.bibhushansaakha.com.np/research/consent-first-sharing-survey}
}