How do you know what a good app is? Great strides have been made in guiding consumers, employers, and health systems in making better decisions when choosing digital mental health tools.
A new paper by Sarah Lagan and colleagues from Beth Israel Deaconess at Harvard share the updated framework for app evaluation for the American Psychiatric Association (APA). The article appears in Nature Digital Medicine. This model has been evolving over the past few years and concentrates on critical dimensions like accessibility, security, privacy, interoperability, and the application of evidence-based principles.
The figure below shows all the dimensions in detail, which can guide the app review. To date, there has not been a searchable database of tools that include these criteria, but the paper contains an early version of a database to make the process practical.
Source: https://doi.org/10.1038/s41746-020-00312-4
The authors translated the evaluation model’s dimensions into 105 questions, answerable in a binary or numeric fashion, then converted into a database format. While still in its nascency, new data suggests the database criteria show excellent inter-rater reliability and certainly advances our decision-making capabilities as the app market expands.
This database is a welcome addition in making the decisions about apps easier and the process more navigable. It will also have the added impact for app companies to know the criteria that matter to health systems going forward to build these functions into their development roadmap. Another database launched in collaboration with the Northeast Business Group on Health and Psyberguide serves as a support for employer groups to determine useful mental health apps for their employees. These evaluation tools provide tremendous value in narrowing down a crowded field.
Thanks for reading – Trina
(Opinions are my own)
References
Lagan, S., Aquino, P., Emerson, M.R. et al. Actionable health app evaluation: translating expert frameworks into objective metrics. npj Digit. Med. 3, 100 (2020). https://doi.org/10.1038/s41746-020-00312-4
Psyberguide
