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Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality

Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality

Suicidal individuals endorsed significantly less belongingness (one-tailed independent sample t (133) = -5.84, p<.001; Cohen’s d=-1.52, 95% CI [-2.05, -0.97]), and significantly higher burdensomeness (t (133) = -8.41, p<.001; d=-2.18, 95% CI [-2.75, -

Scott R. Braithwaite, Christophe Giraud-Carrier, Josh West, Michael D. Barnes, Carl Lee Hanson

JMIR Ment Health 2016;3(2):e21


There's an App for That: Content Analysis of Paid Health and Fitness Apps

There's an App for That: Content Analysis of Paid Health and Fitness Apps

Calorie Track (factor-enabling); D. i Weight Track (factor-enabling); E. Diabetes Plus (factor-reinforcing); F. ithlete (factor-reinforcing).

Joshua H. West, P. Cougar Hall, Carl L. Hanson, Michael D. Barnes, Christophe Giraud-Carrier, James Barrett

J Med Internet Res 2012;14(3):e72


Investigating Nutrition-Related Complications and Quality of Life in Patients With Gastroenteropancreatic Neuroendocrine Tumors: Protocol for a Mixed-Methods Prospective Study

Investigating Nutrition-Related Complications and Quality of Life in Patients With Gastroenteropancreatic Neuroendocrine Tumors: Protocol for a Mixed-Methods Prospective Study

Scores from the HADS are divided into 2 subscales: depression (HADS-D) and anxiety (HADS-A), which are calculated by summation, with increasing scores indicating an increasing burden of depression and anxiety [29].

Erin Laing, Nicole Kiss, Michael Michael, Karla Gough, Meinir Krishnasamy

JMIR Res Protoc 2018;7(12):e11228