Explanipedia

Building virtual patients for training mental health professionals Open

Patrick Staples, P. R. R. Clarke, Carly Leininger, C. Principato, Meysam Shafiei , et al. · 2025

We present a framework for developing “virtual patients” to augment training for Mental Health Professionals (MHPs) with a process that is more scalable and systematic than current practice which relies on human role-play for the training …

Building virtual patients for training mental health professionals Open

Patrick Staples, Patrick Clarke, Carly Leininger, C. Principato, Meysam Shafiei , et al. · 2025

We present a framework for developing “virtual patients” to augment training for Mental Health Professionals (MHPs) with a process that is more scalable and systematic than current practice which relies on human role-play for the training …

From a Large Language Model to Three-Dimensional Sentiment Open

Patrick Clarke, Carly Leininger, C. Principato, Patrick Staples, Guy M. Goodwin , et al. · 2023

We present an automated model of sentiment which assigns to any arbitrary text three values: valence, arousal, and confidence (VAC) and is based on the three-dimensional framework of emotion introduced by Mehrabian and Russell [1]. While s…

Leveraging Contact Network Information in Clustered Randomized Studies of Contagion Processes Open

Maxwell H Wang, Patrick Staples, Mélanie Prague, RK Goyal, Victor DeGruttola , et al. · 2023

In a randomized study, leveraging covariates related to the outcome (e.g. disease status) may produce less variable estimates of the effect of exposure. For contagion processes operating on a contact network, transmission can only occur th…

Estimating longitudinal depressive symptoms from smartphone data in a transdiagnostic cohort Open

Amelia M. Pellegrini, Emily J. Huang, Patrick Staples, Kamber L. Hart, Jeanette Lorme , et al. · 2022

Background Passive measures collected using smartphones have been suggested to represent efficient proxies for depression severity, but the performance of such measures across diagnoses has not been studied. Methods We enrolled a cohort of…

Author response for "Estimating Longitudinal Depressive Symptoms from Smartphone Data in a Transdiagnostic Cohort" Open

Amelia M. Pellegrini, Emily J. Huang, Patrick Staples, Kamber L. Hart, Jeanette Lorme , et al. · 2021

Author response for "Estimating Longitudinal Depressive Symptoms from Smartphone Data in a Transdiagnostic Cohort" Open

Amelia M. Pellegrini, Emily J. Huang, Patrick Staples, Kamber L. Hart, Jeanette Lorme , et al. · 2020

An Online Calculator for the Prediction of Survival in Glioblastoma Patients Using Classical Statistics and Machine Learning Open

Joeky T. Senders, Patrick Staples, Alireza Mehrtash, David J. Coté, Martin Taphoorn , et al. · 2019

BACKGROUND Although survival statistics in patients with glioblastoma multiforme (GBM) are well-defined at the group level, predicting individual patient survival remains challenging because of significant variation within strata. OBJECTIV…

Design and results of a smartphone‐based digital phenotyping study to quantify ALS progression Open

James D. Berry, Sabrina Paganoni, Kenzie W. Carlson, Katherine M. Burke, Harli Weber , et al. · 2019

Objective The amyotrophic lateral sclerosis (ALS) trial outcome measures are clinic based. Active and passive smartphone data can provide important longitudinal information about ALS progression outside the clinic. Methods We used Beiwe, a…

HOUT-20. AN ONLINE CALCULATOR FOR THE PREDICTION OF SURVIVAL AND ADJUVANT TREATMENT BENEFIT IN GLIOBLASTOMA PATIENTS Open

Joeky T. Senders, Patrick Staples, William B. Gormley, Timothy R. Smith, Marike L. D. Broekman , et al. · 2018

BACKGROUND: Although survival statistics for glioblastoma patients are well-defined on population-scale, individualizing survival prognostication remains challenging. Furthermore, treatment efficacy proven on group-level does not directly …

Beyond smartphones and sensors: choosing appropriate statistical methods for the analysis of longitudinal data Open

Ian Barnett, John Torous, Patrick Staples, Matcheri S. Keshavan, Jukka‐Pekka Onnela · 2018

Objectives As smartphones and sensors become more prominently used in mobile health, the methods used to analyze the resulting data must also be carefully considered. The advantages of smartphone-based studies, including large quantities o…

Supervised Kernel PCA For Longitudinal Data Open

Patrick Staples, Min Ouyang, Robert F. Dougherty, Gregory Ryslik, Paul Dagum · 2018

In statistical learning, high covariate dimensionality poses challenges for robust prediction and inference. To address this challenge, supervised dimension reduction is often performed, where dependence on the outcome is maximized for a s…

The HOPE Pilot Study: Harnessing Patient-Reported Outcomes and Biometric Data to Enhance Cancer Care Open

Alexi A. Wright, Nikita Raman, Patrick Staples, Stephanie M. Schonholz, Angel M. Cronin , et al. · 2018

Purpose Integrating patient-reported outcomes (PROs) into clinical practice is an increasingly promising strategy for improving patients’ symptoms, communication, and clinical outcomes. The objective of the current study was to assess the …

Information-Based Medicine in Glioma Patients: A Clinical Perspective Open

Joeky T. Senders, Maya Harary, Brittany M. Stopa, Patrick Staples, Marike L. D. Broekman , et al. · 2018

Glioma constitutes the most common type of primary brain tumor with a dismal survival, often measured in terms of months or years. The thin line between treatment effectiveness and patient harm underpins the importance of tailoring clinica…

A crossroad for validating digital tools in schizophrenia and mental health Open

John Torous, Patrick Staples, Ian Barnett, Jukka‐Pekka Onnela, Matcheri S. Keshavan · 2018

Characterizing the clinical relevance of digital phenotyping data quality with applications to a cohort with schizophrenia Open

John Torous, Patrick Staples, Ian Barnett, Luis Sandoval, Matcheri S. Keshavan , et al. · 2018

Digital phenotyping, or the moment-by-moment quantification of the individual-level human phenotype in situ using data from personal digital devices and smartphones, in particular, holds great potential for behavioral monitoring of patient…

Relapse prediction in schizophrenia through digital phenotyping: a pilot study Open

Ian Barnett, John Torous, Patrick Staples, Luis Sandoval, Matcheri S. Keshavan , et al. · 2018

Among individuals diagnosed, hospitalized, and treated for schizophrenia, up to 40% of those discharged may relapse within 1 year even with appropriate treatment. Passively collected smartphone behavioral data present a scalable and at pre…

QLIF-18. DIGITAL PHENOTYPING: A NOVEL METHOD FOR QUALITY OF LIFE ASSESSMENT IN PATIENTS WITH BRAIN TUMORS Open

David J. Coté, Ian Barnett, Joeky T. Senders, Hassan Y. Dawood, Patrick Staples , et al. · 2017

INTRODUCTION: Digital phenotyping (DP) is a novel approach for moment-by-moment quantification of the individual-level human social and behavioral phenotype in-situ using data from personal digital devices. Here, we report the first applic…

A comparison of passive and active estimates of sleep in a cohort with schizophrenia Open

Patrick Staples, John Torous, Ian Barnett, Kenzie W. Carlson, Luis Sandoval , et al. · 2017

OS05.3 Digital Phenotyping: A Novel Method for Quality of Life Assessment in Patients with Brain Tumors Open

David J. Coté, Ian Barnett, Joeky T. Senders, Hassan Y. Dawood, Patrick Staples , et al. · 2017

\nIntroduction: Digital phenotyping (DP) is a novel approach for moment-by-moment quantification of the individual-level human social and behavioral phenotype in-situ using sensor data from personal digital devices. Here, we report the fir…

M48. Digital Phenotyping in Schizophrenia Using Smartphones Open

John Torous, Matcheri S. Keshavan, Jukka‐Pekka Onnela, Patrick Staples, Ian Barnett · 2017

Background: The purpose of our study is to determine if self-reported symptom surveys and passive data (GPS, accelerometer, voice samples, call logs, text logs, and phone use data) collected from patients with schizophrenia in real time on…

Using a network-based approach and targeted maximum likelihood estimation to evaluate the effect of adding pre-exposure prophylaxis to an ongoing test-and-treat trial Open

Laura B. Balzer, Patrick Staples, Jukka‐Pekka Onnela, Victor DeGruttola · 2017

Background: Several cluster-randomized trials are underway to investigate the implementation and effectiveness of a universal test-and-treat strategy on the HIV epidemic in sub-Saharan Africa. We consider nesting studies of pre-exposure pr…

Leveraging Contact Network Information in Clustered Randomized Trials of Infectious Processes Open

Patrick Staples, Mélanie Prague, De Gruttola Victor, Jukka‐Pekka Onnela · 2016

In some infectious processes, transmission occurs between specific ties between individuals, which ties constitute a contact network. To estimate the effect of an exposure on infectious outcomes within a collection of contact networks, the…

Leveraging Contact Network Information in Clustered Observational Studies of Contagion Processes Open

Patrick Staples, Mélanie Prague, Victor De Gruttola, Jukka‐Pekka Onnela · 2016

In an observational study, obtaining unbiased estimates of an exposure effect requires adjusting for all potential confounders. When this condition is met, leveraging additional covariates related to the outcome may produce less variable e…

Leveraging Contact Network Information in Clustered Randomized Studies of Contagion Processes Open

Maxwell H Wang, Patrick Staples, Mélanie Prague, Victor De Gruttola, Jukka‐Pekka Onnela · 2016

In a randomized study, leveraging covariates related to the outcome (e.g. disease status) may produce less variable estimates of the effect of exposure. For contagion processes operating on a contact network, transmission can only occur th…

Corrigendum: Barriers, Benefits, and Beliefs of Brain Training Smartphone Apps: An Internet Survey of Younger US Consumers Open

John Torous, Patrick Staples, Elizabeth Fenstermacher, Jason Dean, Matcheri S. Keshavan · 2016

[This corrects the article on p. 180 in vol. 10, PMID: 27148026.].

On the Statistical Properties of Epidemics on Networks Open

Patrick Staples · 2016

One major aim of statistics is to systematically study outcomes of interest in a population by observing the properties of a sample of that population. Some outcomes, such as the total number of people infected in an epidemic, can depend o…

Barriers, Benefits, and Beliefs of Brain Training Smartphone Apps: An Internet Survey of Younger US Consumers Open

John Torous, Patrick Staples, Elizabeth Fenstermacher, Jason Dean, Matcheri S. Keshavan · 2016

RESULTS suggest a high level of interest in brain training apps among the US public, especially those in younger demographics. The stability of positive perception of these apps among app-naïve and app-exposed participants suggests an impo…

Incorporating Contact Network Structure in Cluster Randomized Trials Open

Patrick Staples, Elizabeth L. Ogburn, Jukka‐Pekka Onnela · 2015

Realizing the Potential of Mobile Mental Health: New Methods for New Data in Psychiatry Open

John Torous, Patrick Staples, Jukka‐Pekka Onnela · 2015

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