Is ‘technology before the end-user’ the new ‘cart before the horse’? When digital delivery is only part of the solution : JBI Evidence Implementation

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Is ‘technology before the end-user’ the new ‘cart before the horse’? When digital delivery is only part of the solution

Wilkinson, Shelley A. BSc(Hons)(Psyc), GradDipNut & Diet, PhD1; Willcox, Jane C. BSc, GradDipDietetics, BFood & NutrSci(Hons), MMark1,2,3

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doi: 10.1097/XEB.0000000000000346
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’What is your intervention?’

’It is an app.’

‘That is your delivery mechanism. What is your intervention or behaviour target?’

’It is an app!!!’

(Conversation with a health researcher colleague, 2022)

The advent of digital ‘solutions’ to help people improve their health have been vaunted since the 1990s when we, as health professionals, were told that websites would make our jobs redundant. Fortunately for our careers, this did not come to pass, but it demonstrated that we cannot change people's complex health behaviours simply through digitally delivered words, videos or pictures. Fast forward to the 2020s and an exciting array of technologies offer potential for us to reach people beyond traditional healthcare models to encourage positive health behaviours or optimize health system function.1 On the contrary, some health promoters, program designers and health consumers may make an implicit assumption that the technology itself is the intervention rather than the delivery mechanism. Too often, the focus of research is then on the digital delivery modality driving the intervention, often neglecting the complex nature of the behaviour change on which it should be designed to focus.2

Many of us are familiar with the foundation of implementation science for health service improvement requiring assessment of influencing factors and design of interventions needing to be systematic and theory-driven.3 This approach is the antithesis to adopting a practice or procedure seen to be effective in another setting or site or doing it because it ‘feels right’ or you ‘think it will work’. Guiding this methodology are the four steps outlined by French et al.4 The first step is to systematically investigate who needs to do what differently? This process allows you to determine current practice through identifying what needs to change, who is involved, and which interests are relevant. The second step is to use a theoretical framework to identify barriers and enablers, then to identify and apply evidence-based interventions to overcome barriers and enhance enablers. The final step is to measure and understand the change you have planned. This approach aligns with design thinking for the development of digital interventions.

Person-centred design processes, such as design thinking,5 are viewed as critical for the development of effective and innovative health-related systems or interventions, particularly those digitally delivered.6 The steps include empathizing with end user; defining the user needs and behaviours to be targeted; ideating around the behaviours to be targeted by challenging assumptions and creating ideas; prototyping scaled-down versions of potential solutions or products; and testing to derive an understanding of the product and its users. These steps may not be linear and may occur in parallel in a circular fashion.

Consistent with theories, models and frameworks from implementation science,7 health promotion, innovation, social marketing and digital program development, person-centred design reframes the problem in human-centric ways identified. By understanding the person and behavioural context, it allows potential solutions to be mapped to the target behaviours and determinants (barriers and enablers), underpinned by behavioural theoretical frameworks (e.g.4,8–10). These steps are crucial to then anchor the discrete functionality of the digital technology to achieve the objectives and fit with the end user culture and context.11 This step is sometimes eliminated by digital health interventions, missing the opportunity to understand where interventions may best utilize technology, or other delivery mechanisms, directly related to the behaviour on which it should be targeted.

Understanding digital technology as a delivery mechanism with unique opportunities to facilitate access, decisions, cognition and motivation is critical in optimizing interventions.1 Also critical is developing the intervention content to align with the behaviour change and digital functionality being delivered. In digital-led interventions, the content or messaging may sometimes be neglected. Beethoven's Ninth Symphony played on a record player is the same piece of music on a streaming service (apologies to all musicologists; for illustrative purposes only) but the streaming service offers the listener convenient engagement across time and place, access to other music, sharing opportunities with friends, ability to custom engagement, no need for physical storage and syncing music across devices. When recommending the music to a friend, to whom we think it will appeal, we recommend the Symphony via the streaming and not the streaming service alone. Interventions developers write the music, as well as tailor the delivery for the platform, and not solely focus on the platform alone. If the music engages the end user, it can be enhanced and adapted for different platforms as the technology delivery evolves. In doing so though we must evolve from a traditional healthcare paradigm where the technology directly replaces a printed resource, such as using an information-only website or ‘app’ with text taken directly from a pamphlet. Content development and health or service messaging requires content development tailored for the digital platform as well as the targeted behaviour.

Partnering with the end users, or those that receive benefit, is also critical in the evolution of this process. Failing to collaborate and codesign with end users and being slow to innovate technology reduces the opportunity to create collective agency and unite people in system thinking committed to improvement. In one example, the hacking of insulin pumps and continuous blood glucose monitors by people in the type 1 diabetes community, who develop and share open-source code, in response to the lack of personalization and slow technological innovation.12 Collaborating with those that receive benefit could evolve the technological intervention to be of higher value, more likely to meet their needs or ‘what matters to them’ and provide safe access for evidence-based care to the wider population. Further, working with end users to capture data about their targeted behaviours and determinants and how they interact with technology, provides opportunities to identify segments or phenotypes within a population with specific patterns of behaviours.13 This will enable developers to personalize and tailor interventions to maximize effectiveness rather than develop for a broad cross-section of the population.

The COVID-19 pandemic has enforced digital healthcare delivery with rapid increase in digitally mediated consultations and rapid evolution of technology in healthcare. This has provided previously inaccessible opportunities for healthcare organizations and the community.14 There is still much to be learned about marrying behaviour theory, implementation science and digital models as well as access, equity and the digital divide plus the time and financial opportunities or costs to organizations, clinicians and communities. Rather than just adopting a digital practice or procedure seen to be effective in another setting or site (also known as the ‘When you have a hammer, everything looks like a nail’ approach) it is crucial for implementation practitioners that user-centred evidence-based interventions aided by technology are constructed rather than leading with the technology and crafting an intervention to suit. We need to scaffold digitally mediated interventions so that we do not go the way of those 1990s start-up tech companies who failed to deliver, lacking an understanding of behaviour theory and business models.


Conflicts of interest

The authors report there are no conflicts of interest.


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A video commentary on implementation project titled: How do health professionals prioritise clinical areas for implementation of evidence into practice? The commentary is provided by Andrea Rochon RN, MNSc, Research Assistant, Queen's University, Ontario, Canada