Will an App Fill the Gap? Innovative Technology to Provide Point-of-Care Information

Quality of Smartphone Apps Related to Alcohol Use Disorder

BACKGROUND

Apps for smartphones are opening an important range of opportunities for improving the care of people with alcohol use disorders (AUDs).

AIMS

This study aimed to evaluate the quality of English language apps for AUDs and to compare paid and free apps. The keywords 'alcohol', 'alcohol addiction', 'alcohol help' and 'stop drinking' were entered into the iTunes Store search engine. Apps were evaluated using a standardized assessment designed to rate the quality of apps in terms of accountability, interactivity, self-help score and evidence-based content. The Brief DISCERN score and the criteria of the 'Health on the Net' label were also used as content quality indicators.

RESULTS AND CONCLUSIONS

Of the 137 unique apps identified, 52 met the inclusion criteria. Overall, the content quality and self-help scores of these AUD apps were poor. The main quality indicators were not linked to payment status. Multiple linear regressions showed that the Brief DISCERN score significantly predicted content quality. Poor content quality and self-help scores of AUD smartphone apps underline the gap between their potential promises and the overall quality of available products in stores. The quality indicators used in the present study may be used for further app developments.

Quality of Smartphone Apps Related to Panic Disorder

Quality of smartphone apps related to panic: smartphone apps have a growing role in health care. This study assessed the quality of English-language apps for panic disorder (PD) and compared paid and free apps. Keywords related to PD were entered into the Google Play Store search engine. Apps were assessed using the following quality indicators: accountability, interactivity, self-help score (the potential of smartphone apps to help users in daily life), and evidence-based content quality. The Brief DISCERN score and the criteria of the "Health on the Net" label were also used as content quality indicators as well as the number of downloads. Of 247 apps identified, 52 met all inclusion criteria. The content quality and self-help scores of these PD apps were poor. None of the assessed indicators were associated with payment status or number of downloads. Multiple linear regressions showed that the Brief DISCERN score significantly predicted the content quality and self-help scores. Poor content quality and self-help scores of PD smartphone apps highlight the gap between their technological potential and the overall quality of available products.