From day one, science has been at the heart of what we do at Unmind. Our goal is to improve the mental health of people across the world, and without scientific rigour, that simply wouldn’t be possible. This series will walk you through how we approach the research that gives our platform its evidence base.
Part one sets the scene for digital mental health research. After outlining our research mission, we’ll take a deeper dive into efficacy research, looking at what efficacy actually means, and why it should be a crucial factor when evaluating your digital mental health intervention.
Why is research important for digital mental health tools?
Digital mental health is a rapidly expanding field. One recent study reported the availability of over 1000 apps covering a range of mental health and wellbeing topics, from stress and anxiety to low mood and sleep. Digital tools are desirable for many reasons, not least because they’re easy to use and widely accessible. But it’s important that we can trust that these apps are actually able to manage our mental health. Because here’s the problem: only 2% of health apps are supported by original research1. In other words, most aren’t backed by scientific evidence.
How we approach research at Unmind
As a dedicated psychology team within Unmind, we make sure our platform is backed by high-quality scientific evidence. Our research mission has four pillars:
1. Generate robust empirical evidence on the power of the Unmind platform to maintain, improve, and promote positive mental health and workplace outcomes.
This means conducting studies that evaluate the impact of our platform, and following research best practices while doing so.
2. Help evolve our product to be the most effective and engaging on the market
The findings from our studies can also help us continually improve our platform, for example by elucidating how and why specific platform features are effective.
3. Position Unmind at the forefront of mental health research
We aspire to be thought leaders in the field of digital mental health. By also committing to research that advances our wider scientific understanding of mental health, we are using the data and methods available to us for the greater good.
4. Our methods and findings are transparent and widely accessible
We commit to our methodologies in advance of a study and aim to publish all our research, communicating clearly to a wide audience, including clients, Unmind users, and academics.
Our research roadmap outlines the various studies we’re currently conducting and planning, with each aligned with our research mission. The second part in this series will talk more about our roadmap and take you on a journey through some of our specific research plans. But two key areas we’re focusing on here are:
Evaluating the impact of the content on our platform (Series and Tools) on mental health and wellbeing and workplace outcomes.
Index validation studies
Evaluating the robustness of our mental wellbeing measurement tool.
So, what actually is ‘efficacy research’ and why is it important?
You may have come across the term efficacy before, and perhaps wondered what it actually means. How does it differ from ‘effectiveness’? Are they just the same thing?
An important part of digital mental health research involves investigating whether an intervention has the ability to produce a desired outcome (for example, reducing symptoms of low mood, or promoting better sleep).
Efficacy research is a crucial first step to this evaluation process, in which researchers have much control over the study’s circumstances, such as who takes part in the study, or what the research participants are instructed to do. This means that if a desired outcome is achieved, it can be attributed to the intervention.
Effectiveness research, on the other hand, may be carried out at a later stage, to further explore the impact of the intervention and how people interact with it in real-world, less controlled settings.
How is efficacy research carried out at Unmind?
We approach each of our efficacy studies using the ‘gold-standard’ design for efficacy research – a Randomised Controlled Trial (RCT).
This means we recruit participants for efficacy research externally: people who have never used Unmind before, and participate voluntarily.
Randomised: Participants are randomly allocated to different groups. This will include one or more intervention groups, and a control group. The randomisation process should ensure a roughly even distribution of various characteristics (such as age, gender and ethnicity) across all study groups, to help reduce bias.
Controlled: A group of participants (the ‘control group’) do not use the intervention, and act as a comparison.
Over a set intervention period, participants in the intervention groups interact with the component of the platform that we’re testing (e.g. a specific Series or collection of Tools), while the control group doesn’t have access to the platform. All participants complete a selection of questionnaires to measure specific aspects of their mental health and wellbeing, both before and after the intervention period. By comparing the groups who engaged with the Unmind content to those who didn’t access the platform, we can see the true effect of Unmind.
RCTs provide the highest quality of evidence for a single intervention-based study. The rigorous and systematic process involved in a RCT mean they're designed to be unbiased and exhibit less risk of systematic errors than other designs, and that they produce valid and reliable findings. The approach makes sure we generate robust empirical evidence about the impact of our platform, in line with the first pillar of our research mission.
Given that only 2% of health apps are supported by original research1, we know we’re in a position to add real value to the existing evidence base through our efficacy research.
Once we’ve established the efficacy of our platform, we plan to conduct effectiveness research in the future. This will tell us the impact of Unmind in real-world conditions.
So that’s our research mission and an introduction to efficacy research. Part two will delve into our research roadmap, and show you what we’ve got planned for the year ahead.
This blog post references:
1Lau, N., O'Daffer, A., Colt, S., Yi-Frazier, J. P., Palermo, T. M., McCauley, E., & Rosenberg, A. R. (2020). Android and iPhone Mobile Apps for Psychosocial Wellness and Stress Management: Systematic Search in App Stores and Literature Review. JMIR Mhealth Uhealth, 8(5), e17798. doi:10.2196/17798
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