Behavioural Design thinking for nutrition, food and health brands - why and how to start

Behaviour change is the conscious process of making decisions and acting on these. Whilst still considered a relatively new and niche area, behaviour change is a scientific discipline which has gathered steam over the last decade owing to growing evidence on the importance of understanding individual behaviours that can be explained by behavioural theories in order to target or integrated interventions that can impact health.

The goal of this post is to synthesize the current research on behaviour change, and the role this important scientific discipline has become in ensuring the actionability and effectiveness of Personalized nutrition solutions.

Furthermore, the goal is to provide an actionable framework for executives in R & D, Digital transformation and marketing in F & B, Ingredients, Nutrition and Health technology who are looking to develop consumer-focused solutions using a design thinking approach.

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Relevance of behaviour change in health

It has been established that our behaviour contributes over 45% towards our health (WHO, 2009). That is more than genetics which contributes only around 20% (DHHS). This means that chronic illnesses such as Diabetes and Obesity are largely a result of our behaviours and mostly preventable. Most of the work that leverages behavioural science has been in the public health domain. These have focused on smoking cessation, improving public health, increasing physical activity and healthy pregnancies (Michie et al 2011). As technology has advanced, and consumer perception towards health has shifted towards prevention, so have public health initiatives, incentives and campaigns to nudge individuals towards adopting healthier habits. Understanding how individuals make decisions and how to support these decisions with relevant products and solutions is therefore key in shifting healthcare from reactive to proactive.

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Behaviour change in Digital health

Rapid advances in science, technology, computing power and an increased focus on precision medicine have led to the growing area of digital health. The goal and promise of digital health is to:

·??????? Increase access to information and care

·??????? Lower cost of health care

·??????? Increase self-management

·??????? Provide 24/7 support

·??????? Leverage new technology to provide personalized care

Examples include Artificial intelligent chatbots that can triage call to emergency rooms; blood pressure monitors that can measure blood pressure using a chest band and sending data to the general practitioner, digital therapeutics that can be prescribed by a Dr without the need for medication for specific conditions such as migraines or Irritable Bowel Syndrome.

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The effectiveness of digital tools on Nutrition and behavioural outcomes

The nutrition and wellness industry have not been left behind in the technological era. In fact, a recent survey found that there are around 400K nutrition and health apps combined in Apple and Google play stores. Digital Nutrition solutions can range from wellbeing such as tracking food intake, all the way to medical nutrition such as those supporting the management of Diabetes. Behaviour change is inextricably linked to nutrition as previous research has demonstrated the impact that individual behaviours and psychology can determine outcomes of interventions.

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Weight loss

For example, individuals who use digital tools such as a food diary lost significantly more weight (Patel et al., 2021), however the use of apps for weight loss in the long term is less effective (Chew et al ., 2022).

Similar findings were reported by another group who concluded that apps-based mobile interventions have a positive impact on the management of chronic diseases especially weight loss (El Khoury et al 2019)

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Eating & physical activity

In an opinion paper published by European nutrition experts, concluded that depressive symptoms, emotional distress, fatigue and anxiety affect nutritional and behavioural outcomes such as eating and physical activity (Kohlenberg- Muller et al ., 2019).

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Diabetes management

In another service review study conducted by Diabetes and weight management platform Oviva, researchers found no difference in the weight loss achieved and acceptability of the service between face-to-face vs digital support (Huntriss et al., 2021) which indicates that digital offers a convenient and equally effective alternative to in-person care.?

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Body Mass Index (BMI) & Fruit & vegetable intake

Based on a recent systematic review and meta-analysis of 41 studies by Villinger et al 2019, researchers found beneficial effects of app-based mobile interventions on health-related outcomes such as BMI (Body mass index and blood pressure), clinical parameters (such as blood lipids) as well as a significant effect on fruit & vegetable intake. Whilst the effect sizes of the app-based mobile interventions were generally small (0.21 - 0.3), this points to the potential of integrating app-based mobile interventions as part of the nutrition care process.

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Food as medicine

To date, most clinical effectiveness has been demonstrated in the Food as medicine approach, where individuals living with chronic conditions? having received specific interventions to modify their behaviour. (Doyle et al., 2024)

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Why does it matter? - The potential of leverage behavioural science to improve existing or develop new solution for brands.

The reality is that while global smartphone penetration is high, the adoption of nutrition apps with the goal of improving health remains low at around 7 – 10% (Statista).? Furthermore, for those who have adopted apps to self-monitor or improve their health, adherence is generally poor.

Behavioural science gets to the crux of why and how individuals make decisions or behave in a certain way. It is important for brands to understand the triggers, motivations and desires of why they are looking for a particular solution and the context in which those specific choices are being made as outlined above. Understanding the end-user at a deeper level can drive the development or incorporation of specific features that result in the desired behaviour and health outcomes.

For example, recent studies have found that ambivalence towards personalized nutrition can lead to a reduced uptake of the service, meaning that if consumers are not clear that an investment would lead to definite value or benefit, they are unlikely to demonstrate interest (Reinders et al 2020). In another study, researchers found that contextual factors influenced impact of personalised nutrition advice (Bouwman et al., 2022) whilst other researchers found that psychological characteristics determined their preference for the frequency and intensity of receiving personalised advice (Dijksterhuis et al., 2021).

A recent systematic review demonstrated that barriers to and facilitators to using nutrition apps can be grouped into 4 main reasons.

·??????? The Individual – such as lack of motivation or capability

·??????? The Technology – eg incomplete food databases privacy concerns or poor

UX/UI

·??????? The intended outcomes – such as goals, behaviour and emotional outcomes

·??????? The social environment – such as social support and recommendations

Solutions that therefore best match an individual's preferences, (health) goals, expectations and capabilities can lead to higher satisfaction; higher engagement and better adherence to the advice provided. This will undoubtedly lead to higher revenue and better data generation, as well as a bigger social impact.

Yet, despite the potential of incorporating behavioural science into digital solutions, many companies do not know how to get started, or do not have access to domain experts to execute. This results in behaviour change being integrated as an afterthought rather than a core focus during ideation. Including behavioural assessment grounded in theory at the start, can lead to increased adherence and improved eating behaviour. This gap in design and delivery can be addressed by adopting Behavioural design thinking principles.

This is an excerpt from our recent Qina Executive Data Brief.

To read the full Executive Data Brief on Behavioral Design Thinking to find out:

·??????? Which of the behavioural theories are most used

·??????? Which behaviour change techniques are most often used in Personalized

nutrition solutions in the market

·??????? How Digital features are connected to Behaviour change effectiveness

·??????? How you can use Behavioural Design thinking to create the next generation of AI solutions

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