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Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning

Annual review of clinical psychology, 2017-05, Vol.13, p.23

2017

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Supportive accountability: a model for providing human support to enhance adherence to eHealth interventions

Journal of medical Internet research, 2011-03, Vol.13 (1), p.e30-e30

2011

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Self-guided psychological treatment for depressive symptoms: a meta-analysis

PloS one, 2011-06, Vol.6 (6), p.e21274-e21274

2011

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Standards for randomized controlled trials of efficacy of psychological treatments

World psychiatry, 2024-06, Vol.23 (2), p.286-287

Mohr, David C.

2024

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A Solution-Focused Research Approach to Achieve an Implementable Revolution in Digital Mental Health

JAMA psychiatry (Chicago, Ill.), 2018-02, Vol.75 (2), p.113

2018

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A randomized controlled trial evaluating a manualized TeleCoaching protocol for improving adherence to a web-based intervention for the treatment of depression

PloS one, 2013-08, Vol.8 (8), p.e70086-e70086

2013

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Machine learning for passive mental health symptom prediction: Generalization across different longitudinal mobile sensing studies

PloS one, 2022-04, Vol.17 (4), p.e0266516-e0266516

2022

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Behavioral Intervention Technologies: Evidence review and recommendations for future research in mental health

General hospital psychiatry, 2013-07, Vol.35 (4), p.332-338

2013

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Three Problems With Current Digital Mental Health Research . . . and Three Things We Can Do About Them

Psychiatric services (Washington, D.C.), 2017-05, Vol.68 (5), p.427-429

2017

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Integrating Human Support Into Behavioral Intervention Technologies: The Efficiency Model of Support

Clinical psychology (New York, N.Y.), 2017-03, Vol.24 (1), p.27-45

2017

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The behavioral intervention technology model: an integrated conceptual and technological framework for eHealth and mHealth interventions

Journal of medical Internet research, 2014-06, Vol.16 (6), p.e146-e146

2014

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Ecological momentary interventions for depression and anxiety

Depression and anxiety, 2017-06, Vol.34 (6), p.540-545

2017

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Feasibility, Acceptability, and Preliminary Efficacy of a Smartphone Intervention for Schizophrenia

Schizophrenia bulletin, 2014-11, Vol.40 (6), p.1244-1253

2014

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Accelerating Digital Mental Health Research From Early Design and Creation to Successful Implementation and Sustainment

Journal of medical Internet research, 2017-05, Vol.19 (5), p.e153

2017

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Experimental Therapeutics for Digital Mental Health

JAMA psychiatry (Chicago, Ill.), 2019-12, Vol.76 (12), p.1223

2019

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Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study

Journal of medical Internet research, 2015-07, Vol.17 (7), p.e175-e175

2015

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The need to approximate the use-case in clinical machine learning

Gigascience, 2017-05, Vol.6 (5), p.1-9

2017

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Relationship Between Sleep Quality and Mood: Ecological Momentary Assessment Study

JMIR mental health, 2019-03, Vol.6 (3), p.e12613

2019

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The Pace of Technologic Change: Implications for Digital Health Behavior Intervention Research

American journal of preventive medicine, 2016-11, Vol.51 (5), p.816-824

2016

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The relationship between mobile phone location sensor data and depressive symptom severity

PeerJ (San Francisco, CA), 2016-09, Vol.4, p.e2537-e2537, Article e2537

2016

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Major depressive disorder

Nature reviews. Disease primers, 2016-09, Vol.2 (1), p.16065, Article 16065

2016

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Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data

Frontiers in psychiatry, 2021-01, Vol.12, p.625247-625247

2021

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Coached Mobile App Platform for the Treatment of Depression and Anxiety Among Primary Care Patients: A Randomized Clinical Trial

JAMA psychiatry (Chicago, Ill.), 2020-09, Vol.77 (9), p.906

2020

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Diagnostic utility of telomere length testing in a hospital-based setting

Proceedings of the National Academy of Sciences - PNAS, 2018-03, Vol.115 (10), p.E2358-E2365

2018

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Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning

Supportive accountability: a model for providing human support to enhance adherence to eHealth interventions

Self-guided psychological treatment for depressive symptoms: a meta-analysis

Standards for randomized controlled trials of efficacy of psychological treatments

A Solution-Focused Research Approach to Achieve an Implementable Revolution in Digital Mental Health

A randomized controlled trial evaluating a manualized TeleCoaching protocol for improving adherence to a web-based intervention for the treatment of depression

Machine learning for passive mental health symptom prediction: Generalization across different longitudinal mobile sensing studies

Behavioral Intervention Technologies: Evidence review and recommendations for future research in mental health

Three Problems With Current Digital Mental Health Research . . . and Three Things We Can Do About Them

Integrating Human Support Into Behavioral Intervention Technologies: The Efficiency Model of Support

The behavioral intervention technology model: an integrated conceptual and technological framework for eHealth and mHealth interventions

The symptom‐specific efficacy of antidepressant medication vs. cognitive behavioral therapy in the treatment of depression: results from an individual patient data meta‐analysis

Ecological momentary interventions for depression and anxiety

Feasibility, Acceptability, and Preliminary Efficacy of a Smartphone Intervention for Schizophrenia

Accelerating Digital Mental Health Research From Early Design and Creation to Successful Implementation and Sustainment

Experimental Therapeutics for Digital Mental Health

Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study

The need to approximate the use-case in clinical machine learning

Relationship Between Sleep Quality and Mood: Ecological Momentary Assessment Study

The Pace of Technologic Change: Implications for Digital Health Behavior Intervention Research

The relationship between mobile phone location sensor data and depressive symptom severity

Major depressive disorder

Predicting Symptoms of Depression and Anxiety Using Smartphone and Wearable Data

Coached Mobile App Platform for the Treatment of Depression and Anxiety Among Primary Care Patients: A Randomized Clinical Trial

Diagnostic utility of telomere length testing in a hospital-based setting

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