Publications
Search
1.
Barrett, Trevor J.; Sobhani, Mona; Fox, Glenn R.; Files, Benjamin; Patitsas, Nicholas; Duhaime, Josiah; Ebert, Rebecca; Faulk, Rob; Saxon, Leslie
Diverse predictors of early attrition in an elite Marine training school Journal Article
In: Military Psychology, vol. 34, no. 4, pp. 388–397, 2022, ISSN: 0899-5605, 1532-7876.
@article{barrett_diverse_2022,
title = {Diverse predictors of early attrition in an elite Marine training school},
author = {Trevor J. Barrett and Mona Sobhani and Glenn R. Fox and Benjamin Files and Nicholas Patitsas and Josiah Duhaime and Rebecca Ebert and Rob Faulk and Leslie Saxon},
url = {https://www.tandfonline.com/doi/full/10.1080/08995605.2021.1993721},
doi = {10.1080/08995605.2021.1993721},
issn = {0899-5605, 1532-7876},
year = {2022},
date = {2022-07-01},
urldate = {2022-09-27},
journal = {Military Psychology},
volume = {34},
number = {4},
pages = {388--397},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2.
Cleland, John G. F.; Bristow, Michael R.; Freemantle, Nicholas; Olshansky, Brian; Gras, Daniel; Saxon, Leslie; Tavazzi, Luigi; Boehmer, John; Ghio, Stefano; Feldman, Arthur M.; Daubert, Jean‐Claude; Mets, David
In: European J of Heart Fail, vol. 24, no. 6, pp. 1080–1090, 2022, ISSN: 1388-9842, 1879-0844.
@article{cleland_effect_2022,
title = {The effect of cardiac resynchronization without a defibrillator on morbidity and mortality: an individual patient data meta‐analysis of companion and care-hf},
author = {John G. F. Cleland and Michael R. Bristow and Nicholas Freemantle and Brian Olshansky and Daniel Gras and Leslie Saxon and Luigi Tavazzi and John Boehmer and Stefano Ghio and Arthur M. Feldman and Jean‐Claude Daubert and David Mets},
url = {https://onlinelibrary.wiley.com/doi/10.1002/ejhf.2524},
doi = {10.1002/ejhf.2524},
issn = {1388-9842, 1879-0844},
year = {2022},
date = {2022-06-01},
urldate = {2022-09-27},
journal = {European J of Heart Fail},
volume = {24},
number = {6},
pages = {1080--1090},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
3.
We've Entered a New Era of Streaming Health Care. Now What? Journal Article
In: IEEE Spectrum, 2021.
@article{noauthor_weve_2021,
title = {We've Entered a New Era of Streaming Health Care. Now What?},
url = {https://spectrum.ieee.org/digital-health},
year = {2021},
date = {2021-11-01},
urldate = {2022-09-29},
journal = {IEEE Spectrum},
abstract = {COVID-19 forced the transition to digital medicine, but there's much still to do.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
COVID-19 forced the transition to digital medicine, but there's much still to do.
4.
Ghasem, Wesley; Valenzuela, Joshua; Saxon, Leslie A.
Player Tracking Technology and Data for Injury Prevention in the National Football League Journal Article
In: Curr Sports Med Rep, vol. 20, no. 9, pp. 436–439, 2021, ISSN: 1537-8918.
@article{ghasem_player_2021,
title = {Player Tracking Technology and Data for Injury Prevention in the National Football League},
author = {Wesley Ghasem and Joshua Valenzuela and Leslie A. Saxon},
url = {https://journals.lww.com/10.1249/JSR.0000000000000873},
doi = {10.1249/JSR.0000000000000873},
issn = {1537-8918},
year = {2021},
date = {2021-09-01},
urldate = {2022-09-28},
journal = {Curr Sports Med Rep},
volume = {20},
number = {9},
pages = {436--439},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
5.
Saxon, Leslie; DiPaula, Brooks; Fox, Glenn R; Ebert, Rebecca; Duhaime, Josiah; Nocera, Luciano; Tran, Luan; Sobhani, Mona
Continuous Measurement of Reconnaissance Marines in Training With Custom Smartphone App and Watch: Observational Cohort Study Journal Article
In: JMIR mHealth and uHealth, vol. 8, no. 6, pp. e14116, 2020, ISSN: 2291-5222.
@article{saxon_continuous_2020,
title = {Continuous Measurement of Reconnaissance Marines in Training With Custom Smartphone App and Watch: Observational Cohort Study},
author = {Leslie Saxon and Brooks DiPaula and Glenn R Fox and Rebecca Ebert and Josiah Duhaime and Luciano Nocera and Luan Tran and Mona Sobhani},
url = {https://mhealth.jmir.org/2020/6/e14116},
doi = {10.2196/14116},
issn = {2291-5222},
year = {2020},
date = {2020-06-01},
journal = {JMIR mHealth and uHealth},
volume = {8},
number = {6},
pages = {e14116},
abstract = {Background: Specialized training for elite US military units is associated with high attrition due to intense psychological and physical demands. The need to graduate more service members without degrading performance standards necessitates the identification of factors to predict success or failure in targeted training interventions. Objective: The aim of this study was to continuously quantify the mental and physical status of trainees of an elite military unit to identify novel predictors of success in training. Methods: A total of 3 consecutive classes of a specialized training course were provided with an Apple iPhone, Watch, and specially designed mobile app. Baseline personality assessments and continuous daily measures of mental status, physical pain, heart rate, activity, sleep, hydration, and nutrition were collected from the app and Watch data. Results: A total of 115 trainees enrolled and completed the study (100% male; age: mean 22 years, SD 4 years) and 64 (55.7%) successfully graduated. Most training withdrawals (27/115, 23.5%) occurred by day 7 (mean 5.5 days, SD 3.4 days; range 1-22 days). Extraversion, positive affect personality traits, and daily psychological profiles were associated with course completion; key psychological factors could predict withdrawals 1-2 days in advance (P=.009). Conclusions: Gathering accurate and continuous mental and physical status data during elite military training is possible with early predictors of withdrawal providing an opportunity for intervention.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background: Specialized training for elite US military units is associated with high attrition due to intense psychological and physical demands. The need to graduate more service members without degrading performance standards necessitates the identification of factors to predict success or failure in targeted training interventions. Objective: The aim of this study was to continuously quantify the mental and physical status of trainees of an elite military unit to identify novel predictors of success in training. Methods: A total of 3 consecutive classes of a specialized training course were provided with an Apple iPhone, Watch, and specially designed mobile app. Baseline personality assessments and continuous daily measures of mental status, physical pain, heart rate, activity, sleep, hydration, and nutrition were collected from the app and Watch data. Results: A total of 115 trainees enrolled and completed the study (100% male; age: mean 22 years, SD 4 years) and 64 (55.7%) successfully graduated. Most training withdrawals (27/115, 23.5%) occurred by day 7 (mean 5.5 days, SD 3.4 days; range 1-22 days). Extraversion, positive affect personality traits, and daily psychological profiles were associated with course completion; key psychological factors could predict withdrawals 1-2 days in advance (P=.009). Conclusions: Gathering accurate and continuous mental and physical status data during elite military training is possible with early predictors of withdrawal providing an opportunity for intervention.
Filter
2022
Barrett, Trevor J.; Sobhani, Mona; Fox, Glenn R.; Files, Benjamin; Patitsas, Nicholas; Duhaime, Josiah; Ebert, Rebecca; Faulk, Rob; Saxon, Leslie
Diverse predictors of early attrition in an elite Marine training school Journal Article
In: Military Psychology, vol. 34, no. 4, pp. 388–397, 2022, ISSN: 0899-5605, 1532-7876.
Links | BibTeX | Tags: CBC, DTIC
@article{barrett_diverse_2022,
title = {Diverse predictors of early attrition in an elite Marine training school},
author = {Trevor J. Barrett and Mona Sobhani and Glenn R. Fox and Benjamin Files and Nicholas Patitsas and Josiah Duhaime and Rebecca Ebert and Rob Faulk and Leslie Saxon},
url = {https://www.tandfonline.com/doi/full/10.1080/08995605.2021.1993721},
doi = {10.1080/08995605.2021.1993721},
issn = {0899-5605, 1532-7876},
year = {2022},
date = {2022-07-01},
urldate = {2022-09-27},
journal = {Military Psychology},
volume = {34},
number = {4},
pages = {388--397},
keywords = {CBC, DTIC},
pubstate = {published},
tppubtype = {article}
}
Cleland, John G. F.; Bristow, Michael R.; Freemantle, Nicholas; Olshansky, Brian; Gras, Daniel; Saxon, Leslie; Tavazzi, Luigi; Boehmer, John; Ghio, Stefano; Feldman, Arthur M.; Daubert, Jean‐Claude; Mets, David
In: European J of Heart Fail, vol. 24, no. 6, pp. 1080–1090, 2022, ISSN: 1388-9842, 1879-0844.
@article{cleland_effect_2022,
title = {The effect of cardiac resynchronization without a defibrillator on morbidity and mortality: an individual patient data meta‐analysis of companion and care-hf},
author = {John G. F. Cleland and Michael R. Bristow and Nicholas Freemantle and Brian Olshansky and Daniel Gras and Leslie Saxon and Luigi Tavazzi and John Boehmer and Stefano Ghio and Arthur M. Feldman and Jean‐Claude Daubert and David Mets},
url = {https://onlinelibrary.wiley.com/doi/10.1002/ejhf.2524},
doi = {10.1002/ejhf.2524},
issn = {1388-9842, 1879-0844},
year = {2022},
date = {2022-06-01},
urldate = {2022-09-27},
journal = {European J of Heart Fail},
volume = {24},
number = {6},
pages = {1080--1090},
keywords = {CBC},
pubstate = {published},
tppubtype = {article}
}
2021
We've Entered a New Era of Streaming Health Care. Now What? Journal Article
In: IEEE Spectrum, 2021.
Abstract | Links | BibTeX | Tags: CBC
@article{noauthor_weve_2021,
title = {We've Entered a New Era of Streaming Health Care. Now What?},
url = {https://spectrum.ieee.org/digital-health},
year = {2021},
date = {2021-11-01},
urldate = {2022-09-29},
journal = {IEEE Spectrum},
abstract = {COVID-19 forced the transition to digital medicine, but there's much still to do.},
keywords = {CBC},
pubstate = {published},
tppubtype = {article}
}
COVID-19 forced the transition to digital medicine, but there's much still to do.
Ghasem, Wesley; Valenzuela, Joshua; Saxon, Leslie A.
Player Tracking Technology and Data for Injury Prevention in the National Football League Journal Article
In: Curr Sports Med Rep, vol. 20, no. 9, pp. 436–439, 2021, ISSN: 1537-8918.
@article{ghasem_player_2021,
title = {Player Tracking Technology and Data for Injury Prevention in the National Football League},
author = {Wesley Ghasem and Joshua Valenzuela and Leslie A. Saxon},
url = {https://journals.lww.com/10.1249/JSR.0000000000000873},
doi = {10.1249/JSR.0000000000000873},
issn = {1537-8918},
year = {2021},
date = {2021-09-01},
urldate = {2022-09-28},
journal = {Curr Sports Med Rep},
volume = {20},
number = {9},
pages = {436--439},
keywords = {CBC},
pubstate = {published},
tppubtype = {article}
}
2020
Saxon, Leslie; DiPaula, Brooks; Fox, Glenn R; Ebert, Rebecca; Duhaime, Josiah; Nocera, Luciano; Tran, Luan; Sobhani, Mona
Continuous Measurement of Reconnaissance Marines in Training With Custom Smartphone App and Watch: Observational Cohort Study Journal Article
In: JMIR mHealth and uHealth, vol. 8, no. 6, pp. e14116, 2020, ISSN: 2291-5222.
Abstract | Links | BibTeX | Tags: CBC
@article{saxon_continuous_2020,
title = {Continuous Measurement of Reconnaissance Marines in Training With Custom Smartphone App and Watch: Observational Cohort Study},
author = {Leslie Saxon and Brooks DiPaula and Glenn R Fox and Rebecca Ebert and Josiah Duhaime and Luciano Nocera and Luan Tran and Mona Sobhani},
url = {https://mhealth.jmir.org/2020/6/e14116},
doi = {10.2196/14116},
issn = {2291-5222},
year = {2020},
date = {2020-06-01},
journal = {JMIR mHealth and uHealth},
volume = {8},
number = {6},
pages = {e14116},
abstract = {Background: Specialized training for elite US military units is associated with high attrition due to intense psychological and physical demands. The need to graduate more service members without degrading performance standards necessitates the identification of factors to predict success or failure in targeted training interventions. Objective: The aim of this study was to continuously quantify the mental and physical status of trainees of an elite military unit to identify novel predictors of success in training. Methods: A total of 3 consecutive classes of a specialized training course were provided with an Apple iPhone, Watch, and specially designed mobile app. Baseline personality assessments and continuous daily measures of mental status, physical pain, heart rate, activity, sleep, hydration, and nutrition were collected from the app and Watch data. Results: A total of 115 trainees enrolled and completed the study (100% male; age: mean 22 years, SD 4 years) and 64 (55.7%) successfully graduated. Most training withdrawals (27/115, 23.5%) occurred by day 7 (mean 5.5 days, SD 3.4 days; range 1-22 days). Extraversion, positive affect personality traits, and daily psychological profiles were associated with course completion; key psychological factors could predict withdrawals 1-2 days in advance (P=.009). Conclusions: Gathering accurate and continuous mental and physical status data during elite military training is possible with early predictors of withdrawal providing an opportunity for intervention.},
keywords = {CBC},
pubstate = {published},
tppubtype = {article}
}
Background: Specialized training for elite US military units is associated with high attrition due to intense psychological and physical demands. The need to graduate more service members without degrading performance standards necessitates the identification of factors to predict success or failure in targeted training interventions. Objective: The aim of this study was to continuously quantify the mental and physical status of trainees of an elite military unit to identify novel predictors of success in training. Methods: A total of 3 consecutive classes of a specialized training course were provided with an Apple iPhone, Watch, and specially designed mobile app. Baseline personality assessments and continuous daily measures of mental status, physical pain, heart rate, activity, sleep, hydration, and nutrition were collected from the app and Watch data. Results: A total of 115 trainees enrolled and completed the study (100% male; age: mean 22 years, SD 4 years) and 64 (55.7%) successfully graduated. Most training withdrawals (27/115, 23.5%) occurred by day 7 (mean 5.5 days, SD 3.4 days; range 1-22 days). Extraversion, positive affect personality traits, and daily psychological profiles were associated with course completion; key psychological factors could predict withdrawals 1-2 days in advance (P=.009). Conclusions: Gathering accurate and continuous mental and physical status data during elite military training is possible with early predictors of withdrawal providing an opportunity for intervention.