Data Driven Support for Substance Addiction Recovery Communities

This project aims to assist those suffering from substance addiction so that they might better understand their mental health. I propose a user level in-app relapse report classifier that has an overall accuracy of 0.882 in a dataset where 18% of users report a substance relapse. Interactions between engagement and views of inspirational messages of the day are complex, yet significant. Predictive analytics inspire design implications for sociotechnical systems, which aim to facilitate the addiction recovery process.

[1]  Ben Shneiderman,et al.  Temporal Event Sequence Simplification , 2013, IEEE Transactions on Visualization and Computer Graphics.

[2]  Joel J. P. C. Rodrigues,et al.  Analysis of mobile health applications for a broad spectrum of consumers: A user experience approach , 2014, Health Informatics J..

[3]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[4]  Wei-Yin Loh,et al.  Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..

[5]  Svetlana Yarosh,et al.  Shifting dynamics or breaking sacred traditions?: the role of technology in twelve-step fellowships , 2013, CHI.

[6]  S. Lemon,et al.  Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression , 2003, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[7]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[8]  Trevor Hastie,et al.  An Introduction to Statistical Learning , 2013, Springer Texts in Statistics.

[9]  Hao-Chuan Wang,et al.  KeDiary: Using Mobile Phones to Assist Patients in Recovering from Drug Addiction , 2016, CHI.

[10]  Jodi Forlizzi,et al.  A stage-based model of personal informatics systems , 2010, CHI.

[11]  Dana L. Wolff-Hughes,et al.  Characterizing user engagement with health app data: a data mining approach , 2017, Translational behavioral medicine.

[12]  Jeffrey Heer,et al.  Forum77: An Analysis of an Online Health Forum Dedicated to Addiction Recovery , 2015, CSCW.

[13]  K. Weinfurt,et al.  An Evaluation of Mobile Health Application Tools , 2014, JMIR mHealth and uHealth.