A Digital Therapeutic Intervention Delivering Biofeedback for Panic Attacks (PanicMechanic): Feasibility and Usability Study (Preprint)

Abstract

UNSTRUCTURED Panic attacks are an impairing mental health problem that affects more than 11% of adults every year. Panic attacks are episodic, and it is difficult to predict when or where they may occur, thus they are challenging to study and treat. To this end, we present PanicMechanic, a novel mobile health (mHealth) application that captures heartrate-based data and delivers biofeedback during panic attacks. We leverage this tool to capture profiles of real-world panic attacks in a largest sample to date and present results from a pilot study to assess the feasibility and usefulness of PanicMechanic as a panic attack intervention. Results demonstrate that heart rate fluctuates by about 15 beats per minute during a panic attack and takes about 30 seconds to return to baseline from peak, cycling 4 to 5 times during each attack and that anxiety ratings consistently decrease throughout the attack. Thoughts about health were the most common trigger during the observed panic attacks, and potential lifestyle contributors include slightly worse stress, sleep, and eating habits, slightly less exercise, and slightly less drug/alcohol consumption than typical. The pilot study revealed that PanicMechanic is largely feasible to use, but would be made more so with simple modifications to the app and particularly the integration of consumer wearables. Similarly, participants found PanicMechanic useful, with 94% indicating that they would recommend PanicMechanic to a friend. These results point toward the need for future development and a controlled trial to establish effectiveness of this digital therapeutic for preventing panic attacks.

The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health

“…In the past decade, we have seen a rise in validated mobile applications and platforms that aim to increase awareness, monitoring, and intervention of mental illness (e.g., PanicMechanic [51], [52], LAMP [25], FOCUS [53]). There is an increase in commercial and research platforms that incorporate aspects of the digital phenotyping lifecycle (i.e., study protocol portal, data collection tool, mechanism for storing and accessing data, data analysis tools), but very few feature all of the necessary components and data to replicate and validate findings [15].…”