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Digital phenotyping in psychiatry: A scoping review
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Digital phenotyping in psychiatry: A scoping review (2022)Digital phenotyping in psychiatry: A scop…The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021)The PRISMA 2020 statement: an…Digital Biomarkers of Social Anxiety Severity: Digital Phenotyping Using Passive Smartphone Sensors (2020)Digital Biomarkers of Social …Global Burden of Disease and the Impact of Mental and Addictive Disorders (2019)Global Burden of Disease and …Smartphones, Sensors, and Machine Learning to Advance Real-Time Prediction and Interventions for Suicide Prevention: a Review of Current Progress and Next Steps (2018)Smartphones, Sensors, and Mac…Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study (2018)Predicting Mood Disturbance S…Digital biomarkers of cognitive function (2018)Digital biomarkers of cogniti…Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students (2017)Using Mobile Sensing to Test …The new field of ‘precision psychiatry’ (2017)The new field of ‘precision p…Digital Phenotyping (2017)Digital PhenotypingThe relationship between mobile phone location sensor data and depressive symptom severity (2016)The relationship between mobi…Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild (2016)Mobile Sensing and Support fo…Detecting Bipolar Depression From Geographic Location Data (2016)Detecting Bipolar Depression …Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study (2015)Mobile Phone Sensor Correlate…Smartphone Ownership and Interest in Mobile Applications to Monitor Symptoms of Mental Health Conditions (2014)Smartphone Ownership and Inte…Patient Smartphone Ownership and Interest in Mobile Apps to Monitor Symptoms of Mental Health Conditions: A Survey in Four Geographically Distinct Psychiatric Clinics (2014)Patient Smartphone Ownership …Community Attitudes to the Appropriation of Mobile Phones for Monitoring and Managing Depression, Anxiety, and Stress (2010)Community Attitudes to the Ap…Lifetime and 12-Month Prevalence of DSM-III-R Psychiatric Disorders in the United States (1994)The PHQ-9 (2001)Lifetime Prevalence and Age-of-Onset Distributions of DSM-IV Disorders in the National Comorbidity Survey Replication (2005)The WPA- Lancet Psychiatry Commission on the Future of Psychiatry (2017)Facebook language predicts depression in medical records (2018)Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study (2018)Handbook of Qualitative Research (1994)The SAGE handbook of qualitative research (2005)Using thematic analysis in psychology (2006)Theme Issue on E-Mental Health: A Growing Field in Internet Research (2010)Mobile mental health: Review of the emerging field and proof of concept study (2011)Implementation strategies for digital mental health interventions in health care settings. 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References

  • 2021The PRISMA 2020 statement: an updated guideline for reporting systematic reviews107,380 cited
  • 2019Global Burden of Disease and the Impact of Mental and Addictive Disorders1,382 cited
  • 2017Digital Phenotyping832 cited
  • 2015Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study781 cited
  • 2017The new field of ‘precision psychiatry’552 cited
  • 2016Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild333 cited
  • 2016The relationship between mobile phone location sensor data and depressive symptom severity314 cited
  • 2014Smartphone Ownership and Interest in Mobile Applications to Monitor Symptoms of Mental Health Conditions287 cited
  • 2010Community Attitudes to the Appropriation of Mobile Phones for Monitoring and Managing Depression, Anxiety, and Stress274 cited
  • 2018Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study233 cited
  • 2014Patient Smartphone Ownership and Interest in Mobile Apps to Monitor Symptoms of Mental Health Conditions: A Survey in Four Geographically Distinct Psychiatric Clinics228 cited
  • 2018Smartphones, Sensors, and Machine Learning to Advance Real-Time Prediction and Interventions for Suicide Prevention: a Review of Current Progress and Next Steps207 cited
  • 2018Digital biomarkers of cognitive function188 cited

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  • 2016Detecting Bipolar Depression From Geographic Location Data180 cited
  • 2017Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students172 cited
  • 2020Digital Biomarkers of Social Anxiety Severity: Digital Phenotyping Using Passive Smartphone Sensors162 cited
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