The top 3 behaviour change techniques used by personalised nutrition innovators
Over the last decade, personalised nutrition has enjoyed an explosion of success. As a result, traditional dietetics and health practitioner communities have fully accepted that personalised approaches to diagnosing, managing and prescribing solutions for primary health and nutrition-related issues must (and can only be) implemented on an entirely bespoke basis.
At its core, personalised nutrition is not only an effective bio-hack, but it also facilitates the necessary changes to our underlying behaviours, where our health and lifestyles are concerned.
The use and impact of behaviour change techniques (34 in total) in clinical practice are well researched: Some key papers in the field, include Chen et al 2015 and Ferrara et al 2019 and Briggs et al who conducted thorough assessments of popular nutrition apps. Overall, there is ample opportunity for a hybrid approach that blends digital with human interaction for enhanced benefit and health outcomes.
Fast-forward to 2021, we’ve entered an exciting era where personalised nutrition, technology and startup culture have crossed paths. These forces have conspired to create numerous exciting businesses and apps which not only further the philosophy of personalised nutrition, but also employ BCTs (behaviour change techniques) to drive real, meaningful and sustainable behavioural change in the lives of their users.
At Qina, we believe that behaviour change takes time, and requires effort and motivation on the side of the consumer. We believe that the right BCTs should be employed for the individual based on their preferences, personality and even social determinants of health.
In terms of BCTs, at Qina we have been tracking personalised nutrition solutions in terms of how many and which BCT’s are incorporated in the industry.
From our Qina database, we’ve identified the top 3 BCTs incorporated in PN (personalised nutrition) solutions. They are:
- Action planning
An action plan allows a consumer to break up the process of achieving a goal (ie. losing 15 kgs or switching to a plant-based diet) into smaller, detailed steps. Various studies have given credit to this BCT as a simple yet effective behaviour change driver, highlighting intentionality and self-monitoring to achieve specific goals.
- Diet tracking
Thanks to the ever-improving user experience within apps and mobile technologies, regular self-tracking of one’s nutritional intake has never been easier (or more accurate). Whether it be keeping image-based food diaries or logging daily meals in an app, allowing users to track and assess their own progress towards their goal in real-time has proven to be an enormously powerful behaviour change tool. It has also given rise to a trove of data, enabling an entire secondary market of highly personalised products, services and upsells to converge on consumers on their journey of change.
Creating an informed, discerning consumer is an essential element when influencing positive behaviour change towards a specific goal. Education comes in various forms (ie. self-research, courses, professional consultation, academic studies, surveys, other online content) but it would appear that, in order to drive effective behaviour change, the most successful apps and businesses make use of education over a sustained period, rather than only once or intermittently.
Below is a visual representation of the split between these three BCTs used in personalised nutrition currently:
Here are three examples of companies who incorporate all 3 BCTs:
Boldly disrupting the at-home self-testing space, Bisu offers personalised nutrition services and coaching through its app. Making use of DIY urine tests linked to a proprietary app, Bisu offers fast, accurate results on a wide range of dietary assessments. This allows them to tailor nutrition advice on everything from eating plans and recommended supplements to managing chronic conditions.
Headquartered in Amsterdam, Clear provides real-time blood and glucose level readouts thanks to its self-applied sensor. Using this data, users benefit from personalised eating and dietary plans and advice, paid for on a simple monthly membership subscription. Clear is an excellent example of the hybrid approach we are observing in the PN industry, where technology, expert advice and active user participation (influenced by BCTs) converge.
Supporting consumers afflicted with IBS and IBD, Cara Care’s app allows users to track their food intake over time. In return, a bespoke eating plan is provided that minds each user’s digestive system-related illness or symptoms. In addition, the app’s outstanding design, intuitive user experience and additional resources (such as one-on-one dietitian chat and access to exercises and quizzes), makes Cara Care’s offering a compelling case for driving real behaviour change.
What does this mean for future innovations and research?
- Certain BCT (such as incentives) are still largely underused in PN solutions
- More research is needed on the best combinations of BCTs for different individuals to influence behaviour change
- Whilst the number of PN solutions which have incorporated coaching has increased following COVID, it is still not the most used. This represents an opportunity for growth
- Web 3.0 will enable consumers greater control over their personal data. In the future, AI/ML can help to identify patterns in individual behaviour, which can be used to personalise diet and lifestyle recommendations to the individual
At Qina, we believe that there is plenty of scope for improvement to develop solutions that will drive behaviour change and that consumers can trust. Our experts in nutrition and behaviour change can provide insights and support into the best way to engage and entertain your customers towards their health goals.
Get in touch!
Mariette Abrahams CEO & Founder of Qina
- Ferrara G, Kim J, Lin S, Hua J, Seto E. A Focused Review of Smartphone Diet-Tracking Apps: Usability, Functionality, Coherence With Behavior Change Theory, and Comparative Validity of Nutrient Intake and Energy Estimates. JMIR Mhealth Uhealth. 2019;7(5):e9232. Published 2019 May 17. doi:10.2196/mhealth.9232
- Chen J, Cade JE, Allman-Farinelli M. The Most Popular Smartphone Apps for Weight Loss: A Quality Assessment. JMIR Mhealth Uhealth. 2015 Dec 16;3(4):e104. doi: 10.2196/mhealth.4334. PMID: 26678569; PMCID: PMC4704947.
- Telema Briggs, Virginia Quick, William K. Hallman.Feature Availability Comparison in Free and Paid Versions of Popular Smartphone Weight Management Applications. Journal of Nutrition Education and Behavior, Volume 53, Issue 9, 2021,Pages 732-741,ISSN 1499-4046, https://doi.org/10.1016/j.jneb.2021.05.010.