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Monintoring Student Depression by Mobile Devices with Autoencoder Networks
8 references·0 citing·42 second hopsampled
Monintoring Student Depression by Mobile Devices with Autoencoder Networks (2023)Monintoring Student Depression by Mobile …The Mental Health Effects of Student Activism: Persisting Despite Psychological Costs (2021)The Mental Health Effects of …Using Autoencoders to Automatically Extract Mobility Features for Predicting Depressive States (2018)Using Autoencoders to Automat…The accuracy of passive phone sensors in predicting daily mood (2018)The accuracy of passive phone…Measurement-based Care in Psychiatry-Past, Present, and Future. (2018)Measurement-based Care in Psy…Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review (2018)Correlations Between Objectiv…StudentLife (2014)StudentLifeDimensionality of somatic complaints: Factor structure and psychometric properties of the Self-Rating Anxiety Scale (2005)Dimensionality of somatic com…The PHQ-9 (2001)The PHQ-9A Rationale and Test for the Number of Factors in Factor Analysis (1965)The CES-D Scale (1977)An inventory for measuring clinical anxiety: Psychometric properties. (1988)A randomized controlled trial of the effects of brief mindfulness meditation on anxiety symptoms and systolic blood pressure in Chinese nursing students (2012)Effects of Sleep Quality on the Association between Problematic Mobile Phone Use and Mental Health Symptoms in Chinese College Students (2017)Anxiety in Older Adolescents at the Time of COVID-19 (2020)An Inventory for Measuring Depression (1961)A New Depression Scale Designed to be Sensitive to Change (1979)The Structured Clinical Interview for DSM-III-R (SCID) (1992)The PHQ-9: A New Depression Diagnostic and Severity Measure (2002)The Patient Health Questionnaire-2 (2003)A Brief Measure for Assessing Generalized Anxiety Disorder (2006)A Global Measure of Perceived Stress (1983)Development and validation of brief measures of positive and negative affect: The PANAS scales. (1988)Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study (2015)Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning (2017)Mental Health and Behavior of College Students During the Early Phases of the COVID-19 Pandemic: Longitudinal Smartphone and Ecological Momentary Assessment Study (2020)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Using Digital Phenotyping to Accurately Detect Depression Severity (2019)Evaluating depression with multimodal wristband-type wearable device: screening and assessing patient severity utilizing machine-learning (2020)Predicting Depressive Symptom Severity Through Individuals’ Nearby Bluetooth Device Count Data Collected by Mobile Phones: Preliminary Longitudinal Study (2021)The Epidemiology of Major Depressive Disorder (2003)Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010 (2013)Testing the Efficacy of a Multicomponent, Self-Guided, Smartphone-Based Meditation App: Three-Armed Randomized Controlled Trial (2020)Evaluation of Changes in Depression, Anxiety, and Social Anxiety Using Smartphone Sensor Features: Longitudinal Cohort Study (2021)The PHQ-8 as a measure of current depression in the general population (2008)The Patient Health Questionnaire Somatic, Anxiety, and Depressive Symptom Scales: a systematic review (2010)Extraction and Interpretation of Deep Autoencoder-based Temporal Features from Wearables for Forecasting Personalized Mood, Health, and Stress (2020)Detecting Depression and Predicting its Onset Using Longitudinal Symptoms Captured by Passive Sensing (2021)Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach (2021)A RATING SCALE FOR DEPRESSION (1960)The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10 (1998)Evidence Base for Measurement-Based Care in Child and Adolescent Psychiatry (2020)Implementing Measurement-Based Care for Depression: Practical Solutions for Psychiatrists and Primary Care Physicians (2021)TARGET JNL: Neuropsychiatric Disease and Treatment Clinically Significant Changes in the 17- and 6-Item Hamilton Rating Scales for Depression: A STAR*D Report (2021)Small wins: Redefining the scale of social problems. (1984)The new life stage of emerging adulthood at ages 18–29 years: implications for mental health (2014)Applications of Social Research Methods to Questions in Information and Library Science (2016)Critical Reflection and Cognitive Empowerment among Youth Involved in Community Organizing (2021)Civic Engagement to Empower Young People to Impact Health and Well-Being (2023)The Effect of Civic Engagement on Different Dimensions of Well-Being in Youth: A Scoping Review (2024)
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References

  • 2001The PHQ-944,795 cited
  • 2014StudentLife1,117 cited
  • 2018Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review194 cited
  • 2005Dimensionality of somatic complaints: Factor structure and psychometric properties of the Self-Rating Anxiety Scale191 cited
  • 2018Measurement-based Care in Psychiatry-Past, Present, and Future.121 cited
  • 2018The accuracy of passive phone sensors in predicting daily mood119 cited
  • 2021The Mental Health Effects of Student Activism: Persisting Despite Psychological Costs87 cited
  • 2018Using Autoencoders to Automatically Extract Mobility Features for Predicting Depressive States54 cited

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