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Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study
TLDR
The detection of daily-life behavioral markers using mobile phone global positioning systems and usage sensors and their use in identifying depressive symptom severity suggest that phone sensors offer numerous clinical opportunities, including continuous monitoring of at-risk populations with little patient burden and interventions that can provide just-in-time outreach.
The Behavioral Intervention Technology Model: An Integrated Conceptual and Technological Framework for eHealth and mHealth Interventions
TLDR
The BIT model provides a step towards formalizing the translation of developer aims into intervention components, larger treatments, and methods of delivery in a manner that supports research and communication between investigators on how to design, develop, and deploy BITs.
Pursuit of pleasure, engagement, and meaning: Relationships to subjective and objective measures of well-being
Pleasure, engagement, and meaning are all unique predictors of individuals’ well-being. We explored the relationship between the pursuit of each of these pathways and well-being. Participants (N =
IntelliCare: An Eclectic, Skills-Based App Suite for the Treatment of Depression and Anxiety
TLDR
This study supports the IntelliCare framework of providing a suite of skills-focused apps that can be used frequently and briefly to reduce symptoms of depression and anxiety.
The relationship between mobile phone location sensor data and depressive symptom severity
TLDR
The finding that GPS features predict depressive symptom severity up to 10 weeks prior to assessment suggests that GPS Features may have the potential as early warning signals of depression.
Preferences for positive psychology exercises
Positive psychologists have developed a variety of techniques to increase well-being. This study explored whether preferences for some interventions are linked to preferences for other interventions.
Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning.
TLDR
A layered, hierarchical model for translating raw sensor data into markers of behaviors and states related to mental health is provided, focused principally on smartphones, but also including studies of wearables, social media, and computers.
Efficacy of a Web-Based, Crowdsourced Peer-To-Peer Cognitive Reappraisal Platform for Depression: Randomized Controlled Trial
TLDR
Panoply engaged its users and was especially helpful for depressed individuals and for those who might ordinarily underutilize reappraisal techniques.
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