An App for What Ails You – How Do You Know They Work?

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More Phones than Humans on Planet Earth

We reached a milestone in 2014: the number of phones on the planet surpassed the number of people for the first time – 7.22 billion phones to 7.2 billion people, a staggering statistic, and global business models based on phones only continue to grow. In an earlier blog post, I referenced the fact that there are over 50,000 health-related apps available to download; if you wanted to know what apps could help you stay healthy or manage illness, how would you begin to evaluate them? Would the slick marketing often employed to sell a product entice you? What’s important to you in your decision-making process? The evidence base on this topic has been growing at a rapid pace, so let’s review what we know so far.

Scaling Digital Therapeutics – is it feasible?

Professor Mark Tomlinson and colleagues from Sellenbosch University in South Africa looked at the evidence for mobile-phone-related health delivery, or mHealth, and reported their findings in PLOS Medicine. They point out that while enthusiasm is high, evidence of effectiveness and efficacy lags behind. The authors propose a multi-step framework to close the enthusiasm-evidence gap: they recommend using the Society of Prevention Research’s Standards Model as a framework for mHealth interventions, which introduces some foundational elements that should inform implementation at scale. The model proposes interventions should include at least two high-quality efficacy trials (does the intervention work in ideal circumstances) as well as at least two high-quality effectiveness trials (does the intervention work in real-world settings). Additionally, dissemination research that demonstrates the intervention can be reliably delivered at scale, and lastly, articulation of costs of the intervention to inform spread and scale should also be included. Since this article came out, many new studies have emerged that show the mHealth space is moving toward greater rigor, but the gap is still vast.

Dr. Oyungerel Byambasuren and colleagues from Bond University in Australia reported on their systematic review in this month’s Nature Digital Medicine that the overall field of mHealth apps still shows a weak evidence base for evidence of effectiveness. They examined six systematic reviews that included 23 randomized control trials – the gold standard for study design. Most of the apps they looked at investigated approaches to obesity, diabetes and mental health. They reported that most of the trials were brief and had small sample sizes, and they cautioned against wide prescribing of apps unless they have been studied and have demonstrated benefit.

The exciting aspect of leveraging phones to support health and wellness is the fact that most people have a phone – many interventions can be and are delivered via phone today. However, in many respects, this nascent field is still like the Wild West. Consumers, employers, healthcare companies and government agencies are starting to hold these solutions to a higher standard, which will be necessary to evolve the mHealth field to meet the criteria outlined above. What is clear is that companies which leverage the evidence-base, translate what works into a superior user experience, and demonstrate superior outcomes cost-effectively, will have an opportunity to grow their market-share as they implement at scale.

As a consumer, don’t just accept the marketing for any app; look for the science they base their product on: have they engaged scientists in their development? What outcomes are they reporting? If you don’t see any of this clearly on their website, it may not be a good investment of your time or your money.

Thanks for reading- Trina
(Opinions are my own)

References

Boren, ZD- Active mobile phones outnumber humans for the first time. International Business Times.
https://www.ibtimes.co.uk/there-are-more-gadgets-there-are-people-world-1468947

Scaling up MHealth-Where is the Evidence?
http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001382

Society for Prevention Standards Model
https://link.springer.com/article/10.1007/s11121-005-5553-y

Prescribable mHealth apps identified from an overview of systematic reviews
https://www.nature.com/articles/s41746-018-0021-9

 

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