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Mobile technology for remotely sensing key health indicators about patients receiving long-term or outpatient care continues to become more affordable and more easily embedded, but there remain certain patient variables, especially mental health and adaptive functioning characteristics, that are difficult to automatically detect or problematic to self-report. To address this problem, we are working on technology that integrates input from caregivers (as well as patients) with enhanced context reporting. We describe how leveraging both methods in an application designed for use by PTSD/mTBI patients and their caregivers can potentially lead to more informed clinical care teams, better family engagement of the care process, and potentially better treatment outcomes.

Most state-of-the-art treatments for mental health disorders such as post-traumatic stress (PTSD) rely substantially on in-person interactions between therapist and patient. Whereas traditional treatments can suffer high rates of attrition, the integration of mobile technology potentially enhances patient engagement. Furthermore, such technology can include others that care about the patient, to provide more regular and deeper insights for clinicians into the needs and status of those being treated. In this paper, we discuss our experiences building Connectd for PTSD and anger, a mobile app for use by both patients and a designated family member or friend, and deploying it within the context of an evidence-based CBT treatment. Built upon a flexible mobile health platform, we discuss how we built the app to adaptively target a specific population, included "supporters" that ranged in relationship to the patient, complemented a manualized treatment with heterogeneous online resources, and leveraged artificial intelligence techniques to further personalize the experience. We also discuss general app usage statistics and, via a sample dyad, demonstrate the value that continuous data collection can yield.

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