Why mixed methods matter in bleeding disorders research

From clinical trials to observational studies, people with bleeding disorders are often included in research. There’s no denying that this is a good thing. As well as being essential in developing new and better therapies, involving patients in research can help clarify expectations, preferences and needs.

But the way we approach the inclusion of patients in research matters.

Good on paper

If you live with a bleeding disorder, your involvement in research will almost inevitably involve filling in forms to complete quality of life (QoL) assessment tools. Using these tools in research means we can compare different groups of people with the same condition, access to treatment, all kinds of things. In that sense, they’re incredibly useful.

However, it’s possible to tick boxes and obtain a good QoL score – and so appear to be living well – when, in fact, the reality feels rather different. In other words, while your QoL might look good on paper, form-filling hasn’t told the whole story.

So, how can we – or how should we – research the more elusive but innately human aspects of living with a bleeding disorder?

Our mixed approach

From its earliest days, Haemnet has pioneered a mixed methods approach to research in the bleeding disorders community. We think of it as our ‘360 Methodology’ because it provides an all-round, comprehensive view on the research questions we want to answer.

We use validated research tools, but we also make sure our surveys are tailored to the particular condition, or aspect of a condition, that we want to learn more about. We then go a step further, undertaking in-depth interviews to find out about the day-to-day realities of living with a bleeding disorder. And when we do this, we often look beyond the affected individual and consider the impact of bleeding disorders on partners, parents and siblings too.

Speaking with people and hearing about their experiences gives more substance to what we discover in our study surveys. In this way, mixing the methods we use for our research helps build up a bigger picture – which means we’re able to understand much more.

P is for people

All of the surveys we undertake generate statistical data that provide a p-value (or level of significance) for our study results. This is important because it helps establish the strength of the relationship between different elements of the research data we collect. In other words, it tells us whether or not a particular finding is an important trend to be aware of in a particular disorder or group of people.

However, the interviews we do alongside surveys provide us with another ‘p’. They tell us about the individual People behind the p-values. They tell us how happy those people are and what, if any, difficulties they face on a daily basis. It’s here that we discover unmet need that might not be identified in a survey – and understanding unmet need is crucial to improving health-related outcomes.

About the author

Kate Khair is Director of Research at Haemnet. Email: research@haemnet.com

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