Current, future and potential use of mobile and wearable technologies and social media data in the ABCD study to increase understanding of contributors to child health

[1]  L. Hilton.  The ethics of social media , 2017 .

[2]  D. Spruijt-Metz,et al.  Compliance With Mobile Ecological Momentary Assessment Protocols in Children and Adolescents: A Systematic Review and Meta-Analysis , 2017, Journal of medical Internet research.

[3]  Skyler Place,et al.  Behavioral Indicators on a Mobile Sensing Platform Predict Clinically Validated Psychiatric Symptoms of Mood and Anxiety Disorders , 2017, Journal of medical Internet research.

[4]  S. Lee.  Studying “Friends”: The Ethics of Using Social Media as Research Platforms , 2017, The American journal of bioethics : AJOB.

[5]  S. Matthews,et al.  The Long Arm of Poverty: Extended and Relational Geographies of Child Victimization and Neighborhood Violence Exposures , 2017, Justice quarterly : JQ.

[6]  Heleen Riper,et al.  The Pace of Technologic Change: Implications for Digital Health Behavior Intervention Research. , 2016, American journal of preventive medicine.

[7]  Michael R. Kramer,et al.  Confidentiality considerations for use of social-spatial data on the social determinants of health: Sexual and reproductive health case study. , 2016, Social science & medicine.

[8]  J. Etter,et al.  Ecological Momentary Assessment and Smartphone Application Intervention in Adolescents with Substance Use and Comorbid Severe Psychiatric Disorders: Study Protocol , 2016, Front. Psychiatry.

[9]  V. K. Thomas,et al.  Longitudinal effects of prenatal exposure to air pollutants on self-regulatory capacities and social competence. , 2016, Journal of child psychology and psychiatry, and allied disciplines.

[10]  N. Petry,et al.  A Randomized Trial of Adjunct mHealth Abstinence Reinforcement With Transdermal Nicotine and Counseling for Smoking Cessation , 2016, Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco.

[11]  Ruoling Chen,et al.  Exposure to air pollution and cognitive functioning across the life course--A systematic literature review. , 2016, Environmental research.

[12]  Job G. Godino,et al.  Measures of sleep and cardiac functioning during sleep using a multi-sensory commercially-available wristband in adolescents , 2016, Physiology & Behavior.

[13]  Rebecca M. C. Spencer,et al.  Reliability of Sleep Measures from Four Personal Health Monitoring Devices Compared to Research-Based Actigraphy and Polysomnography , 2016, Sensors.

[14]  Carolien Beckx,et al.  Dynamic assessment of exposure to air pollution using mobile phone data , 2016, International Journal of Health Geographics.

[15]  Piotr Jankowski,et al.  Privacy and spatial pattern preservation in masked GPS trajectory data , 2016, Int. J. Geogr. Inf. Sci..

[16]  Scout Calvert,et al.  Opportunities and challenges in the use of personal health data for health research , 2016, J. Am. Medical Informatics Assoc..

[17]  Shalini Prasad,et al.  A wearable biochemical sensor for monitoring alcohol consumption lifestyle through Ethyl glucuronide (EtG) detection in human sweat , 2016, Scientific Reports.

[18]  Margot J Davey,et al.  Comparison of Commercial Wrist-Based and Smartphone Accelerometers, Actigraphy, and PSG in a Clinical Cohort of Children and Adolescents. , 2016, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.

[19]  Hua Fang,et al.  iMStrong: Deployment of a Biosensor System to Detect Cocaine Use , 2015, Journal of Medical Systems.

[20]  Kwong-Sak Leung,et al.  A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems , 2015, Sensors.

[21]  Emre Ertin,et al.  puffMarker: a multi-sensor approach for pinpointing the timing of first lapse in smoking cessation , 2015, UbiComp.

[22]  Ian M Colrain,et al.  Validation of Sleep-Tracking Technology Compared with Polysomnography in Adolescents. , 2015, Sleep.

[23]  L. Blaisdell,et al.  Social Media Use in Research: Engaging Communities in Cohort Studies to Support Recruitment and Retention , 2015, JMIR research protocols.

[24]  David P. Semanek,et al.  Effects of prenatal exposure to air pollutants (polycyclic aromatic hydrocarbons) on the development of brain white matter, cognition, and behavior in later childhood. , 2015, JAMA psychiatry.

[25]  G. Pratt,et al.  Traffic, Air Pollution, Minority and Socio-Economic Status: Addressing Inequities in Exposure and Risk , 2015, International journal of environmental research and public health.

[26]  Jesse Dallery,et al.  A randomized controlled trial of smartphone-based mindfulness training for smoking cessation: a study protocol , 2015, BMC Psychiatry.

[27]  Andrew T. Campbell,et al.  Next-generation psychiatric assessment: Using smartphone sensors to monitor behavior and mental health. , 2015, Psychiatric rehabilitation journal.

[28]  B. Sivertsen,et al.  Sleep and use of alcohol and drug in adolescence. A large population-based study of Norwegian adolescents aged 16 to 19 years. , 2015, Drug and alcohol dependence.

[29]  Y. Kaminer,et al.  Adolescent Initiation of Cannabis Use and Early-Onset Psychosis , 2015, Substance abuse.

[30]  J. Schwartz,et al.  Abstract MP11: Fitbit: An Accurate and Reliable Device for Wireless Physical Activity Tracking , 2015 .

[31]  Mar Viana,et al.  Association between Traffic-Related Air Pollution in Schools and Cognitive Development in Primary School Children: A Prospective Cohort Study , 2015, PLoS medicine.

[32]  Jing Zhang,et al.  Text Messaging Interventions for Adolescent and Young Adult Substance Use: a Meta-Analysis , 2015, Prevention Science.

[33]  F. Perera,et al.  Early-Life Exposure to Polycyclic Aromatic Hydrocarbons and ADHD Behavior Problems , 2014, PloS one.

[34]  Rosalind W. Picard,et al.  Real-Time Mobile Detection of Drug Use with Wearable Biosensors: A Pilot Study , 2014, Journal of Medical Toxicology.

[35]  Kathleen Baldwin,et al.  The Impact of Health Education Transmitted Via Social Media or Text Messaging on Adolescent and Young Adult Risky Sexual Behavior: A Systematic Review of the Literature , 2014, Sexually transmitted diseases.

[36]  Tara M Cousineau,et al.  Text Messaging Intervention for Teens and Young Adults With Diabetes , 2014, Journal of diabetes science and technology.

[37]  P. Best,et al.  Online communication, social media and adolescent wellbeing: A systematic narrative review , 2014 .

[38]  J. Bruce German,et al.  A Feasibility Study of Wearable Activity Monitors for Pre-Adolescent School-Age Children , 2014, Preventing chronic disease.

[39]  B. Brunekreef,et al.  Determinants of the Spatial Distributions of Elemental Carbon and Particulate Matter in Eight Southern Californian Communities. , 2014, Atmospheric environment.

[40]  L. Clark,et al.  The Use of Cell Phone Support for Non-adherent HIV-Infected Youth and Young Adults: An Initial Randomized and Controlled Intervention Trial , 2014, AIDS and Behavior.

[41]  Scott Fruin,et al.  Spatial Variation in Particulate Matter Components over a Large Urban Area. , 2014, Atmospheric environment.

[42]  Lei Zhang,et al.  Teenagers and Texting: Use of a Youth Ecological Momentary Assessment System in Trajectory Health Research With Latina Adolescents , 2014, JMIR mHealth and uHealth.

[43]  Hai-Ying Liu,et al.  Mobile phone tracking: in support of modelling traffic-related air pollution contribution to individual exposure and its implications for public health impact assessment , 2013, Environmental Health.

[44]  Megan A. Moreno,et al.  Ethics of Social Media Research: Common Concerns and Practical Considerations , 2013, Cyberpsychology Behav. Soc. Netw..

[45]  Stephen A Matthews,et al.  Spatial Polygamy and Contextual Exposures (SPACEs) , 2013, The American behavioral scientist.

[46]  R. Roberts,et al.  Depression and insomnia among adolescents: a prospective perspective. , 2013, Journal of affective disorders.

[47]  Rosalind J Wright,et al.  Associations between Traffic-Related Black Carbon Exposure and Attention in a Prospective Birth Cohort of Urban Children , 2013, Environmental health perspectives.

[48]  N. Petry,et al.  A randomized study of cellphone technology to reinforce alcohol abstinence in the natural environment. , 2013, Addiction.

[49]  James H Fowler,et al.  Parental influence on substance use in adolescent social networks. , 2012, Archives of pediatrics & adolescent medicine.

[50]  William G. Griswold,et al.  CitiSense: improving geospatial environmental assessment of air quality using a wireless personal exposure monitoring system , 2012, Wireless Health.

[51]  Wanmin Wu,et al.  Classification Accuracies of Physical Activities Using Smartphone Motion Sensors , 2012, Journal of medical Internet research.

[52]  S. Blair,et al.  Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy , 2012, BDJ.

[53]  G. Harold,et al.  Girls’ Tobacco and Alcohol Use During Early Adolescence: Prediction From Trajectories of Depressive Symptoms Across Two Studies , 2012, Journal of child & adolescent substance abuse.

[54]  F. Perera,et al.  Prenatal Polycyclic Aromatic Hydrocarbon (PAH) Exposure and Child Behavior at Age 6–7 Years , 2012, Environmental health perspectives.

[55]  Alex Pentland,et al.  Modeling Dynamical Influence in Human Interaction: Using data to make better inferences about influence within social systems , 2012, IEEE Signal Processing Magazine.

[56]  Brigitte Walther,et al.  Comparison of Electronic Data Capture (EDC) with the Standard Data Capture Method for Clinical Trial Data , 2011, PloS one.

[57]  N. Fakier,et al.  Associations among sleep problems, learning difficulties and substance use in adolescence. , 2011, Journal of adolescence.

[58]  Elizabeth D. Cox,et al.  Feeling bad on Facebook: depression disclosures by college students on a social networking site , 2011, Depression and anxiety.

[59]  David W. S. Wong,et al.  Measuring segregation: an activity space approach , 2011, J. Geogr. Syst..

[60]  G. S. O'Keeffe,et al.  The Impact of Social Media on Children, Adolescents, and Families , 2011, Pediatrics.

[61]  Douglas J Wiebe,et al.  Neighborhoods, daily activities, and measuring health risks experienced in urban environments. , 2010, Social science & medicine.

[62]  Leslie A Lytle,et al.  Adolescent sleep, risk behaviors, and depressive symptoms: are they linked? , 2010, American journal of health behavior.

[63]  Emiliano Miluzzo,et al.  A survey of mobile phone sensing , 2010, IEEE Communications Magazine.

[64]  William B Allshouse,et al.  Geomasking sensitive health data and privacy protection: an evaluation using an E911 database , 2010, Geocarto international.

[65]  F. Perera,et al.  Prenatal Exposure to Airborne Polycyclic Aromatic Hydrocarbons and Children’s Intelligence at 5 Years of Age in a Prospective Cohort Study in Poland , 2010, Environmental health perspectives.

[66]  Cameron Marlow,et al.  Social network activity and social well-being , 2010, CHI.

[67]  Ulf Ekelund,et al.  Assessment of physical activity – a review of methodologies with reference to epidemiological research: a report of the exercise physiology section of the European Association of Cardiovascular Prevention and Rehabilitation , 2010, European journal of cardiovascular prevention and rehabilitation : official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology.

[68]  Jukka-Pekka Onnela,et al.  Community Structure in Time-Dependent, Multiscale, and Multiplex Networks , 2009, Science.

[69]  R. Roberts,et al.  Sleepless in adolescence: prospective data on sleep deprivation, health and functioning. , 2009, Journal of adolescence.

[70]  Kalevi Korpela,et al.  Activity spaces and urban adolescent substance use and emotional health. , 2009, Journal of adolescence.

[71]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[72]  E. Basch,et al.  Electronic patient-reported outcomes for collecting sensitive information from patients. , 2009, The journal of supportive oncology.

[73]  Shannon C. Wieland,et al.  Revealing the spatial distribution of a disease while preserving privacy , 2008, Proceedings of the National Academy of Sciences.

[74]  Brandy M. Roane,et al.  Adolescent insomnia as a risk factor for early adult depression and substance abuse. , 2008, Sleep.

[75]  S. Fortunato,et al.  Statistical physics of social dynamics , 2007, 0710.3256.

[76]  K. Westerterp,et al.  Physical Activity Assessment With Accelerometers: An Evaluation Against Doubly Labeled Water , 2007, Obesity.

[77]  E A Leicht,et al.  Community structure in directed networks. , 2007, Physical review letters.

[78]  Søren Brage,et al.  Accelerometers and pedometers: methodology and clinical application , 2007, Current opinion in clinical nutrition and metabolic care.

[79]  James H. Fowler,et al.  Turnout in a Small World , 2007 .

[80]  A. Ritter,et al.  A review of the efficacy and effectiveness of harm reduction strategies for alcohol, tobacco and illicit drugs. , 2006, Drug and alcohol review.

[81]  T. Glass,et al.  Behavioral science at the crossroads in public health: extending horizons, envisioning the future. , 2006, Social science & medicine.

[82]  Jodi A. Mindell,et al.  Sleep and Risk-Taking Behavior in Adolescents , 2005, Behavioral sleep medicine.

[83]  C. Wild.  Complementing the Genome with an “Exposome”: The Outstanding Challenge of Environmental Exposure Measurement in Molecular Epidemiology , 2005, Cancer Epidemiology Biomarkers & Prevention.

[84]  Ling Bao,et al.  Activity Recognition from User-Annotated Acceleration Data , 2004, Pervasive.

[85]  L. Berkman,et al.  Neighborhoods and health , 2003 .

[86]  M. Lagory,et al.  Unhealthy Places: The Ecology of Risk in the Urban Landscape , 2000 .

[87]  G. Rushton,et al.  Geographically masking health data to preserve confidentiality. , 1999, Statistics in medicine.

[88]  Richard Rothenberg,et al.  Choosing a centrality measure: Epidemiologic correlates in the Colorado Springs study of social networks☆ , 1995 .

[89]  L. Freeman,et al.  Centrality in valued graphs: A measure of betweenness based on network flow , 1991 .

[90]  L. Friberg.  Air Pollution , 1984, Svenska lakartidningen.

[91]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[92]  Gert Sabidussi,et al.  The centrality index of a graph , 1966 .

[93]  B. Fitzgerald.  Guidance Regarding Methods for De-identification of Protected Health Information in Accordance with the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule , 2015 .

[94]  Jianghong Liu,et al.  Environmental toxicity and poor cognitive outcomes in children and adults. , 2014, Journal of environmental health.

[95]  Christopher R. Browning,et al.  Moving Beyond Neighborhood: Activity Spaces and Ecological Networks As Contexts for Youth Development. , 2014, Cityscape.

[96]  Lena Sanci,et al.  Investigating the utility of mobile phones for collecting data about adolescent alcohol use and related mood, stress and coping behaviours: lessons and recommendations. , 2009, Drug and alcohol review.

[97]  J. Stockman.  The Spread of Obesity in a Large Social Network over 32 Years , 2009 .

[98]  D. Morawetz.  Depression and insomnia. , 2000, Australian family physician.

[99]  Molly K Fitch,et al.  American Journal of Epidemiology Practice of Epidemiology Mapping Health Data: Improved Privacy Protection with Donut Method Geomasking , 2022 .