Abstract
Accessibility of evidence-based behavioral health interventions is one of the main challenges in health care and effective treatment approaches are not always available for patients that would benefit from them. Digitization has dramatically changed the health care landscape. Although mHealth has shown promise in addressing issues of accessibility and reach, there is vast room for improvements. The integration of technical innovations and theory driven development is a key concern. Digital solutions developed by industry alone often lack a clear theoretical framework and the solutions are not properly evaluated to meet the standards of scientifically proven efficacy. On the other hand, mHealth interventions developed in academia may be theory driven but lack user friendliness and are commonly technically outdated by the time they are implemented in regular care, if they ever are. In an ongoing project aimed at scientific innovation, the mHealth Agile Development and Evaluation Lifecycle was used to combine strengths from both industry and academia in the development of ACTsmart – a smartphone-based Acceptance and Commitment Therapy treatment for adult chronic pain patients. The present study describes the early development of ACTsmart, in the process of moving the product from alpha testing to a clinical trial ready solution.
Highlights
For many health conditions, such as chronic pain, access to evidence-based behavioral health interventions is limited due to geographical and financial reasons
Most digital health interventions developed within industry lack theory-based strategies known to drive behavior change,[2,3,4] evidence-based content,[5,6,7,8] and systematic efficacy-testing.[9]
The lengthy process of efficacy testing prevents rapid dissemination, and novel digital interventions developed within academia are at risk of being technically outdated when implemented in routine health care
Summary
For many health conditions, such as chronic pain, access to evidence-based behavioral health interventions is limited due to geographical and financial reasons. Most digital health interventions developed within industry lack theory-based strategies known to drive behavior change,[2,3,4] evidence-based content,[5,6,7,8] and systematic efficacy-testing.[9] In contrast, interventions developed within academia are usually derived from behavioral theory and evaluated scientifically.[10] methods such as randomized controlled trials are time-consuming and costly, which implies that the academic approach is less flexible than commercial mHealth development processes that utilize repeated rapid cycles of fine-tuning based on user feedback.[11] The lengthy process of efficacy testing prevents rapid dissemination, and novel digital interventions developed within academia are at risk of being technically outdated when implemented in routine health care. Poor retention rates are common in digital solutions[12] and negatively influence effect sizes.[13]
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