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Using Passive Smartphone Sensing for Improved Risk Stratification of Patients With Depression and Diabetes: Cross-Sectional Observational Study

16 references·12 citing·51 second hopsampled

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References

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2016Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild333 cited
2016

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

314 cited

2007Cost-effectiveness of Systematic Depression Treatment Among People With Diabetes Mellitus312 cited

2014Smartphone Ownership and Interest in Mobile Applications to Monitor Symptoms of Mental Health Conditions287 cited

Cited by

2021Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review100 cited
2022Machine learning for passive mental health symptom prediction: Generalization across different longitudinal mobile sensing studies75 cited
2022Technology and Mental Health: State of the Art for Assessment and Treatment45 cited
2022Digital Health Interventions for Depression and Anxiety Among People With Chronic Conditions: Scoping Review38 cited
2022A Machine Learning Approach for Detecting Digital Behavioral Patterns of Depression Using Nonintrusive Smartphone Data (Complementary Path to Patient Health Questionnaire-9 Assessment): Prospective Observational Study30 cited
2024Digital biomarkers in depression: A systematic review and call for standardization and harmonization of feature engineering29 cited
2022Digital phenotyping in psychiatry: A scoping review26 cited
2025Smartphone digital phenotyping in mental health disorders: A review of raw sensors utilized, machine learning processing pipelines, and derived behavioral features26 cited
2022Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review19 cited
2022The comfort of adolescent patients and their parents with mobile sensing and digital phenotyping13 cited
2026Smartphone-Based Digital Phenotyping Across Health Conditions: Scoping Review6 cited
2025Links between self-monitoring data collected through smartphones and smartwatches and the individual disease trajectories of adult patients with depressive disorders: Study protocol of a one-year observational trial4 cited