Alison Calear is an Associate Professor at the Centre for Mental Health Research, The Australian National University in Canberra, Australia. She currently holds a National Health and Medical Research Council (NHMRC) Career Development Fellowship. Her research interests include youth mental health, e-health and the prevention and early intervention of anxiety, depression and suicide. Phil Batterham is an Associate Professor and Deputy Head of the Centre for Mental Health Research, The Australian National University in Canberra, Australia. He currently holds a Career Development Fellowship from the National Health and Medical Research Council (NHMRC). His research interests include developing and implementing online programs to prevent mental disorders, developing tailored screening measures for mental disorders, reducing suicide risk, and challenging the stigma of mental illness.

Digital health interventions include internet-based programs and mobile apps that aim to improve or manage health. There is a plethora of digital health interventions available – searching an app store for health apps results in an overwhelming variety of options. So how do you determine which programs are most likely to be effective for you? We propose 3 pillars of guidance: scientific evidence, expert clinical guidance, and user experience.

Scientific Evidence

The most reliable indication that a digital health intervention is likely to be broadly effective is that a randomized controlled trial with a positive outcome has been conducted and published in a peer-reviewed academic journal. A randomized controlled trial is a type of evaluation where participants are randomly allocated to receive the treatment of interest (a digital health intervention) or to a control condition, allowing the effects of the intervention to be rigorously assessed.

However, rigorously evaluated digital health interventions are scarce, and there are important limitations to the results obtained from controlled clinical trials, such as their validity in real world settings. Some established online programs may have had many trials demonstrating their effectiveness. However, there are other challenges in evaluating the evidence for existing programs. As technology changes and interfaces are updated, we cannot be certain that a program that was effective ten years ago would be equally effective today.

Digital technology evolves at a rapid pace, while research is a slow process, often taking many years to establish that an intervention provides effective treatment. Interventions that seek to prevent the onset of a new disease or disorder can take even longer to evaluate. Furthermore, the resources required to conduct a rigorous evaluation of a digital health intervention can be immense. It is becoming increasingly difficult for researchers to obtain funding to evaluate a new intervention, unless they can demonstrate that it delivers a novel solution, surpassing what is offered by existing interventions. Developers may have little incentive to conduct a rigorous trial, except to pass regulatory barriers.

Scientific evidence has further limitations in guiding users. It is difficult to identify which interventions are suitable for a specific individual, as few interventions are tailored or have been tested across a wide variety of subgroups. In addition, effectiveness is not the only metric of interest when choosing a digital health intervention. Interventions that are effective may not appeal to everyone, resulting in poor engagement. Engagement might be better captured in our proposed pillar of user experience.

Expert Clinical Guidance

Expert clinical judgement as to whether a digital health intervention contains and is consistent with evidence-based strategies is another way to assess whether it is likely to be helpful. The minimum standard for digital health interventions should be demonstration that the content is unlikely to be harmful. Expert clinical guidance is one approach to identifying interventions that meet minimum standards of evidence-based content. Clinicians can provide expert ratings as to whether a digital intervention conforms with treatment approaches that have been shown to be effective previously. Interventions are more likely to be effective if they incorporate content with an evidence base, and exclude content that has no basis in evidence. Nevertheless, an intervention that conforms with clinical treatment guidelines may not always be engaging or appropriate for its audience. Consequently, expert clinical guidance is not the only solution in identifying appropriate digital interventions.

User Experience

Users should play a central role in the development, optimization and evaluation of digital health interventions. Involving people with a lived experience of the health problem of interest is crucial for developing an engaging intervention that will be used by the community and for determining what the outcomes of the intervention should be. User satisfaction and engagement with an intervention can be a useful guide to other users.

Nevertheless, there are potential dangers in relying solely on user ratings when choosing a digital intervention. Just because an app is colorful, engaging and fun doesn’t mean that it will be effective in reducing symptoms of ill health. Reviews of available mental health apps have found that a large proportion of apps contain information or strategies that may be counterproductive and therefore potentially unsafe.

Better Standards and Responsible Use

For the research and development community, there is a need to confront the challenges of the free market of digital health interventions. Supporting the development of digital health standards, calling for more rigorous research to be conducted, accumulating expert clinical guidance, and building on the experience of individuals who have used existing interventions are important pillars in providing better guidance for those seeking health support through technology.

So what are the solutions for users and clinicians who seek to identify appropriate digital health interventions? Sites like PsyberGuide and Beacon provide a summary of the evidence for existing interventions. The most effective interventions are likely to be those with existing scientific evidence, although the absence of evidence doesn’t necessarily mean that an intervention is not going to be helpful. Considering the three pillars of scientific evidence, clinical judgement and user experience may provide a comprehensive picture of the advantages and disadvantages of specific digital interventions.

Given the challenges in rigorously evaluating digital interventions, it is worth noting that such interventions might be better thought of as a component of support representing a mixture of modalities. For the individual experiencing a mental or physical health problem, engaging with multiple solutions may be worthwhile. This combination of solutions may include engaging in face-to-face treatment from a health professional, trying an evidence-based digital therapy intervention, or trying a supportive digital intervention that complements therapy, such as a symptom monitoring app.

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