44-46 - Why healthcare still hasn’t cracked Gen Z

Through no fault of its own, the NHS isn’t prepared for the rapid change to how young patients deal with information and education in 2021. As one-size-fits-all models fail to cope with the most diverse generation ever, the world of healthcare is a long way off cracking how to communicate with Gen Z adolescents.

Misunderstandings about Gen Z’s age means many mistakenly reduce them to ‘the youth’ – yet the oldest are entering the workforce, whilst the youngest are barely twelve years old. And whilst doctors and healthcare providers understand that children and adults are different, many are not equipped with the right tools to speak to the people in between: adolescents.

From all-purpose content, to sweeping generalisations, there’s a race going on to tackle the issues associated with communicating with this disparate and complex audience. Moreover, in healthcare, existing processes simply aren’t designed for them. Most systems are based on cost-benefit analysis. As with content, providers are striving to apply a standardised approach to as many people as possible, which does not – and cannot – translate to Gen Z.

Fortunately, there are actions that health systems and providers alike can take right now. It starts with learning about the unique challenges of young people today, and designing new models and processes that truly have them and their needs in mind.

This also means acknowledging that Gen Z are, by far, the most generationally unique group ever – from ethnicity to neurodiversity and behaviours. This is often attributed to their ‘digital native’ status. They were the first to grow up online and are literate in the self-reflective languages of social media.

But this sophisticated, diverse and open-minded cohort has also been shaped by constant societal upheaval, punctured with concerns about the economy, schooling, the prospect of a work culture that requires being constantly ‘on’. No wonder, then, that they engage with people, channels and content differently from those before them. So how can we, as healthcare professionals and services, communicate with them the way that we need to? It’s not by taking information designed for adults and repurposing it. It’s not by talking down to them as if they’re still children. It’s by understanding the deeper emotional and personal side to communication.

Here we’ll consider how.

The healthcare industry has fallen in love with the concept of building apps to serve its digital audience.

Apps are seen as an efficient fix to many logical challenges, from online appointment bookings, to medicine adherence, food diaries and reminders. UI and UX have thus become core design priorities – but this often leads to building complex (and expensive) platforms, crammed with features and capabilities that a patient will soon get bored using. In fact, research shows that most adolescents only use an app for two-to-three hours before they move onto something else unless there’s something sticky to incentivise them.

Look carefully at how Gen Z engages with the world digitally, and you will see a different model emerging.

Gen Z consumes the world through a stream of short-form content in 20-30 second bites. Whether it’s TikTok, Discord, Instagram, WhatsApp or Snapchat – any longer than 30 seconds and you have probably lost their attention. These established content streams have a simple UI that allows the users to scroll until something gets their attention. Crucially, these apps aren’t filled with features, buttons and dropdowns – instead they are relevant, evolving, contextual and highly engaging.

Gen Z’s trusted sources of information have also changed significantly over the last decade. Content creators, influencers and digital social communities have become the new role models. Within a healthcare context, there is the ability for anybody with a chronic condition to tell their own story online, and be heard by millions like them around the world in real time. This shifting engagement opportunity is colossal, but is one that many in healthcare have yet to grasp.

In addition to the significant shift in modes of engagement, enormous changes take place along the journey from an adolescent to a young adult.

Adults have learned behaviours, consistent habits, similarities that transfer regardless of age. But many of these behaviors form and become established as an adolescent. The importance of this life-phase cannot be more significant: it is when you construct your ‘emotional blueprint’, accompanying you for the rest of your life.

With this in mind, applying standard healthcare operating and engagement models to this group lacks the appropriate flexibility. It simply doesn’t work. So whilst there are well-established health engagement models for adults and models for children (Adult and Paediatric care), there’s a chasm for those in the transition phase – yet we don’t prepare adolescents for what adult healthcare will be like. This is what needs to change.

Take a fifteen-year-old in the UK, who is living with T1 diabetes under the careful management of the NHS. Since their diagnosis they will have received paediatric care. They will have visited hospital wards designed for children: rainbows on the walls, lego sets in the waiting rooms. Human understanding and connection makes this challenging time more bearable.

And then they become an ‘adult’ – they turn 16 or 17, and suddenly this individual will be invited to an NHS adult diabetes clinic. Transitioning from a child to an adult patient in the space of two clinic visits, with maybe a final goodbye from their Paediatric team – if they are lucky – they are unprepared for what comes next.

Their first visit to their adult diabetologist will be a very different experience from the one they experienced in paediatric care. If they didn’t understand the life risks of being a T1 diabetic before, then they certainly will now.

It’s more than a possibility that their first adult clinic experience could be sitting in a waiting room next to a patient with their leg recently amputated, or a patient who has significant visual impairment, about to go blind. The trauma of this transition causes many adolescents to drop out of the health system completely, ultimately leading them to disengage with their treatment.

Digital technology can help bridge the chasm by better preparing adolescents for the transition, providing simple and contextual digital content in a language they empathise with and trust, via the channels that they already use.

Most people (outside of solely healthcare) assume that tech –specifically artificial intelligence – poses the solution. Unfortunately, this is too simplistic.
The challenge with AI is that it relies on being fed data, and sharing some interpretation of that back with the user. It’s strictly transactional, neglecting the personalised aspects of delivery that this demographic sorely needs.

So how do we incorporate relevance, empathy and emotion, using some of the newer engagement models we talked about earlier, into real life AI Health projects?
An example of this is LovedBy’s ongoing work with Dexcom. Dexcom is a wearable Blood Glucose Device manufacturer headquartered in the US, and a leading tech player in T1 and T2 Diabetes.

It manufactures and distributes advanced wearable technology, real-time data and AI, which manifests as a small patch that sits on the patient’s arm or waist. This clever patch connects to a mobile device, enabling a constant stream of graphs that show real-time blood sugar data.

It’s a fantastic piece of technology – but only when the patient is able to understand the data enough to make improvements to their management programme.
More often than not, it requires time with the patient’s diabetologist who translates the data for the patient. It’s the clinician’s responsibility to present options and advice to the patient in a meaningful way, based on the data.

And that’s the problem with rich AI data, such as that produced by Dexcom. You need an expert to make the translation.

We do this by using video content of real people with relatable lived experience. A simple dynamic translation ensures that the data is presented in a way that is easily digestible, understandable and in small 30-second snippets. It’s all about creating context.

About developing human AI. About bringing balance to machine learning by bringing in the emotional, empathic aspect that’s so pivotal to making data insights personal and meaningful and trusted.

Get your target audience involved with identifying the problem and designing the solution. Co-design with them, create products they love and are emotionally attached to.
Ensure you add real-life stories on top of your data to make it resonate. The data is important, but they need to see someone going through what they are to get the message to stick.
Keep content short and to the point. Provide quick facts in an engaging way, and then signpost viewers to additional content if required.
Utilise the digital channels Gen Z already use. By proactively engaging with them in their own spaces (TikTok, Instagram, Snapchat) it’ll feel much more personable.
It’s not all about celebrity endorsement. Trust is massive in healthcare, and many medtech companies attempt to use celebrities to onboard kids. However, Gen Z increasingly shun traditional endorsements, and instead seek out people like them with digital communities to put their faith into.

We’ve made great strides in understanding Gen Z in recent years – however, we still have a long way to go. With breakthrough funding and collaboration, we can harness new models for really positive health outcomes. 