JMIR Publications

ABSTRACT

Background:

People with Premenstrual Dysphoric Disorder (PMDD) experience a range of symptoms that increase and decline as a result of the natural hormonal fluctuations of the menstrual cycle. For the diagnosis of PMDD, symptoms severity needs to be recorded daily for at least two symptomatic cycles. In recent years, the rise in interest in Femtech (tools and technology developed to address women’s health issues) has resulted in a large quantity of ‘Period-tracking apps’ being developed and downloaded. However, there is not currently a menstrual and mood tracking app that has the full capabilities to accurately capture the symptoms of PMDD to aid with diagnosis.

Objective:

Our aim was to collect feedback and insights from potential users (i.e., people with lived experience of PMDD/severe PMS) to inform the development of a prototype app that could support prospective mood monitoring of PMDD symptoms for research, and to support diagnosis.

Methods:

We conducted two user-centered design studies. Study 1 consisted of 4 interviews with individual participants who had taken part in our previous web-based mood tracking study for PMDD. During the interviews participants were encouraged to identify the strengths and weaknesses of the existing web-based mood tracking system. Study 2 consisted of 2 workshops with a total of 8 participants, in which participants were asked to discuss the needs and desirable features they would like in a PMDD-specific tracking app. Interviews and workshops were recorded and the transcripts were analyzed inductively following a thematic approach.

Results:

Four themes were identified from the interviews and workshops with potential users: 1) Ease of use as key consideration for users with PMDD; 2) Avoiding a reductionist approach for a broad range of symptoms; 3) Recognizing the importance of correct language; and 4) Integrating features for the users’ benefits. These suggestions align with the current understanding of the implications of PMDD symptoms on daily activities, and with findings from previous research on encouraging long-term engagement with apps.

Conclusions:

To meet the needs of potential users with PMDD or suspected PMDD, there needs to be a special consideration to how their symptoms impact the way they might interact with the app. In order for users to want to interact with the app daily, particularly during the days where they may not have symptoms to track, the app needs to be simple yet engaging. Additionally, if the app provides insights and feedback that can benefit the well-being of the users, it’s suggested that this could ensure prolonged use.