Published on in Vol 24, No 10 (2022): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38963, first published .
Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis

Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis

Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis

Journals

  1. Rahmillah F, Tariq A, King M, Oviedo-Trespalacios O. Evaluating the Effectiveness of Apps Designed to Reduce Mobile Phone Use and Prevent Maladaptive Mobile Phone Use: Multimethod Study. Journal of Medical Internet Research 2023;25:e42541 View
  2. Gao W, Hu Y, Ji J, Liu X. Relationship between depression, smartphone addiction, and sleep among Chinese engineering students during the COVID-19 pandemic. World Journal of Psychiatry 2023;13(6):361 View
  3. Muehlensiepen F, Petit P, Knitza J, Welcker M, Vuillerme N. Prediction of the acceptance of telemedicine among rheumatic patients: a machine learning-powered secondary analysis of German survey data. Rheumatology International 2024;44(3):523 View
  4. Ben Brahim F, Courtois R, Vera Cruz G, Khazaal Y. Predictors of compulsive cyberporn use: A machine learning analysis. Addictive Behaviors Reports 2024;19:100542 View
  5. Nagata J, Paul A, Yen F, Smith-Russack Z, Shao I, Al-shoaibi A, Ganson K, Testa A, Kiss O, He J, Baker F. Associations between media parenting practices and early adolescent screen use. Pediatric Research 2024 View

Books/Policy Documents

  1. Graziani P, Romo L. Soigner les Addictions par les TCC. View