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Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study
5 references·16 citing·53 second hop
Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study (2018)Predicting Mood Disturbance Severity with…Estimating the true global burden of mental illness (2016)Estimating the true global bu…Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study (2015)Mobile Phone Sensor Correlate…Seeing Everyone Else's Highlight Reels: How Facebook Usage is Linked to Depressive Symptoms (2014)Seeing Everyone Else's Highli…Ecological Momentary Assessment (2007)Ecological Momentary Assessme…A RATING SCALE FOR DEPRESSION (1960)A RATING SCALE FOR DEPRESSIONEthical Dimensions of Digital Phenotyping Within the Context of Mental Healthcare (2024)Ethical Dimensions of Digital…Differential temporal utility of passively sensed smartphone features for depression and anxiety symptom prediction: a longitudinal cohort study (2024)Differential temporal utility…Digital tools for the assessment of pharmacological treatment for depressive disorder: State of the art (2022)Digital tools for the assessm…Digital phenotyping in psychiatry: A scoping review (2022)Digital phenotyping in psychi…AWARE-Light: a smartphone tool for experience sampling and digital phenotyping (2022)AWARE-Light: a smartphone too…The relationship between text message sentiment and self-reported depression (2021)The relationship between text…Reproducible Analysis Pipeline for Data Streams: Open-Source Software to Process Data Collected With Mobile Devices (2021)Reproducible Analysis Pipelin…Addressing anhedonia to increase depression treatment engagement (2021)Addressing anhedonia to incre…The crossroads of digital phenotyping (2020)The crossroads of digital phe…Passive Sensing of Prediction of Moment-To-Moment Depressed Mood among Undergraduates with Clinical Levels of Depression Sample Using Smartphones (2020)Passive Sensing of Prediction…Effects of mood and aging on keystroke dynamics metadata and their diurnal patterns in a large open-science sample: A BiAffect iOS study (2020)Effects of mood and aging on …Distant mood monitoring for depressive and bipolar disorders: a systematic review (2020)Distant mood monitoring for d…Touchscreen typing pattern analysis for remote detection of the depressive tendency (2019)Touchscreen typing pattern an…Smartphone-Based Tracking of Sleep in Depression, Anxiety, and Psychotic Disorders (2019)Smartphone-Based Tracking of …Integrating digital phenotyping in clinical characterization of individuals with mood disorders (2019)Integrating digital phenotypi…Detecting relapse in youth with psychotic disorders utilizing patient-generated and patient-contributed digital data from Facebook (2019)Detecting relapse in youth wi…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)Availability: A heuristic for judging frequency and probability (1973)Relation of implicit theories to the construction of personal histories. (1989)Daily Well-Being: The Role of Autonomy, Competence, and Relatedness (2000)Integrating Person‐Centered and Variable‐Centered Analyses: Growth Mixture Modeling With Latent Trajectory Classes (2000)Twelve‐month and lifetime prevalence and lifetime morbid risk of anxiety and mood disorders in the United States (2012)Subjective wellbeing, health, and ageing (2014)A Theory of Social Comparison Processes (1954)Understanding Media: The Extensions of Man (1964)The CES-D Scale (1977)Problematic social media use and depressive symptoms among U.S. young adults: A nationally-representative study (2017)Social Network Sites and Well-Being: The Role of Social Connection (2017)Time Spent on Social Network Sites and Psychological Well-Being: A Meta-Analysis (2017)Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010 (2012)Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010 (2013)Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013 (2015)The burden of mental disorders across the states of India: the Global Burden of Disease Study 1990–2017 (2019)The Lancet Psychiatry Commission: a blueprint for protecting physical health in people with mental illness (2019)Handbook of Religion and Health (2023)The Role of Actigraphy in the Study of Sleep and Circadian Rhythms (2003)Adolescents’ Electronic Media Use at Night, Sleep Disturbance, and Depressive Symptoms in the Smartphone Age (2014)Sleep and mental disorders: A meta-analysis of polysomnographic research. (2016)Towards clinically actionable digital phenotyping targets in schizophrenia (2020)Detecting Mental Health Behaviors Using Mobile Interactions: Exploratory Study Focusing on Binge Eating (2022)Diagnosis of Depressive Disorder Model on Facial Expression Based on Fast R-CNN (2022)Diagnostic and Statistical Manual of Mental Disorders (2008)Diagnostic and Statistical Manual of Mental Disorders (2013)Variability in phase and amplitude of diurnal rhythms is related to variation of mood in bipolar and borderline personality disorder (2018)A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors (2020)Balancing Ethics and Opportunities: The Role of AI in Psychotherapy and Counselling (2025)The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods (2009)Research Domain Criteria (RDoC): Toward a New Classification Framework for Research on Mental Disorders (2010)Diagnostic and Statistical Manual of Mental Disorders (2013)Anomaly detection to predict relapse risk in schizophrenia (2021)Machine learning for passive mental health symptom prediction: Generalization across different longitudinal mobile sensing studies (2022)The promise of a model-based psychiatry: building computational models of mental ill health (2022)Validation and Utility of a Self-report Version of PRIME-MD The PHQ Primary Care Study (1999)The PHQ-8 as a measure of current depression in the general population (2008)A model of healthy aging based on smartphone interactions reveals advanced behavioral age in neurological disease (2022)Evaluating the Acceptability and Feasibility of Collecting Passive Smartphone Data to Estimate Psychological Functioning in U.S. Service Members and Veterans: A Pilot Study (2024)Depression Anxiety Stress Scales (1995)Psychometric properties of the Depression Anxiety Stress Scales (DASS) in clinical samples (1997)Loneliness as a specific risk factor for depressive symptoms: Cross-sectional and longitudinal analyses. (2006)Personalized machine learning of depressed mood using wearables (2021)The dynamics, processes, mechanisms, and functioning of personality: An overview of the field (2021)Implementing precision methods in personalizing psychological therapies: Barriers and possible ways forward (2023)Development and validation of a geriatric depression screening scale: A preliminary report (1982)The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research (1989)
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References

  • 1960A RATING SCALE FOR DEPRESSION32,812 cited
  • 2007Ecological Momentary Assessment6,416 cited
  • 2016Estimating the true global burden of mental illness2,491 cited
  • 2015Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study781 cited
  • 2014Seeing Everyone Else's Highlight Reels: How Facebook Usage is Linked to Depressive Symptoms534 cited

Cited by

  • 2020Passive Sensing of Prediction of Moment-To-Moment Depressed Mood among Undergraduates with Clinical Levels of Depression Sample Using Smartphones139 cited
  • 2019Detecting relapse in youth with psychotic disorders utilizing patient-generated and patient-contributed digital data from Facebook109 cited
  • 2019Touchscreen typing pattern analysis for remote detection of the depressive tendency102 cited
  • 2019Smartphone-Based Tracking of Sleep in Depression, Anxiety, and Psychotic Disorders90 cited
  • 2020Effects of mood and aging on keystroke dynamics metadata and their diurnal patterns in a large open-science sample: A BiAffect iOS study77 cited
  • 2019Integrating digital phenotyping in clinical characterization of individuals with mood disorders66 cited
  • 2021The relationship between text message sentiment and self-reported depression65 cited
  • 2021Reproducible Analysis Pipeline for Data Streams: Open-Source Software to Process Data Collected With Mobile Devices

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53 cited
  • 2024Differential temporal utility of passively sensed smartphone features for depression and anxiety symptom prediction: a longitudinal cohort study46 cited
  • 2021Addressing anhedonia to increase depression treatment engagement45 cited
  • 2022Digital tools for the assessment of pharmacological treatment for depressive disorder: State of the art39 cited
  • 2022AWARE-Light: a smartphone tool for experience sampling and digital phenotyping38 cited
  • 2020The crossroads of digital phenotyping37 cited
  • 2020Distant mood monitoring for depressive and bipolar disorders: a systematic review28 cited
  • 2022Digital phenotyping in psychiatry: A scoping review26 cited
  • 2024Ethical Dimensions of Digital Phenotyping Within the Context of Mental Healthcare22 cited