Design Engineering
Showcase 2020

It goes without saying that raising a child is a rewarding experience; but the drastic lifestyle changes that come with welcoming a new-born, alongside social and financial pressures, can result in mental health issues for parents. The complicated social stigma and lack of awareness surrounding mental health issues mean that nearly half of all perinatal mental health problems are unidentified by healthcare professionals (NCT, 2017). Not to mention the specific dangers of neglecting paternal mental health, as men are less likely to ask for help (Russell, 2017). With the high prevalence of general mental health problems, increasing demands on parents, and oversubscription of the NHS, it is vital that parents are provided with appropriate perinatal mental health and wellbeing support.

There are over 10,000 apps available on the market related to mental health and psychiatry (Torous, 2018), few of which have been properly tested and none of which are strictly regulated by governing bodies (NIMH, 2019). This recent boom in online health and wellbeing services, has rightly led to increased scrutiny from the healthcare industry to ensure mental health platforms are safe for use. As such, new product development demands the use of evidence-based design and as we are working with vulnerable people, it is important to use robust research and design methods in developing product features.

To better understand the experiences of new parents, a questionnaire was developed with three goals in mind:

1. Plot the perinatal care pathway and identify the gaps in support services so KamiCoach can complement the NHS to serve parents better.

2. Develop a clear understanding of the challenges parents face so we can design a support service that helps parents when they need it most.

3. Investigate the predictors of postpartum mental health issues to help inform data collection for KamiCoach’s machine learning algorithm.

Results from the survey were divided into two categories: those with categorical responses and those with descriptive responses. Categorical responses were analysed by systematically grouping data and using significance tests to compare the prevalence of mental health issues. The most significant predictors for postpartum mental health were experiencing complications during birth and the transition of care. Those who experienced no complications during birth and a smooth transition of care were less likely to develop postpartum mental health issues.

Long text-based answers were analysed through two methods: tagging and affinity diagramming. To begin with, responses were manually tagged to pinpoint recurring themes. This showed that the biggest challenges faced by parents in the first six weeks were breastfeeding, postpartum recovery, and sleep deprivation. After the first six weeks and into the first year, additional children, adjustment, and work-life balance, became more prevalent obstacles. When asked how they handled these challenges most parents mention something along the lines of “persevering” or “getting on with it”. The next most common coping mechanisms were relying on partners and family. After identifying the most common challenges, all unique observations were compiled into an affinity diagram to help brainstorm features for the support platform which would cover all bases.

After the the preliminary data analysis customer journey mapping and benchmarking exercises were carried out to help consolidate insights from research. These exercises helped brainstorm over 50 possible features to develop however to make product development manageable and meet delivery deadlines, these features had to be prioritised; this was done using a Kano Analysis.

Finally the comprehensive research which preceded designing the features developed were outlined using the Elito Method (Hanington & Martin, 2012). This not only helped consolidate the arguments behind the design of individual features, but also made it easier to spot gaps in logic.

This project and previous research has shown that mental health issues can develop through a complex combination of causes. This inevitably makes perinatal mental illness difficult to diagnose and treat but Kami is working towards a future where all parents can receive the reliable, personalised care they need.

With an eye on the horizon, feature validation and testing methods outline to guide the next steps in product development. In line with previous work, these methods were based on validated protocols, such as the APA mental health app evaluation framework, to increase KamiCoach’s legitimacy in the highly regulated healthcare industry. This project lays the foundation for Kami to produce a robust MVP for its user base and train their proprietary machine learning algorithm. They can then redirect their efforts to start developing secondary features which were ideated but not prioritised for the scope of this project.

The process for designing and testing KamiCoach which was created as part of this project was used in a successful application for an Innovate UK Grant. This served as an excellent validating step for the work done to date and the awarded funding has launched KamiCoach from the starting blocks.