This paper is in the following e-collection/theme issue:

Mobile Health in Psychiatry (438) Mobile Health (mhealth) (2982) mHealth in a Clinical Setting (624) Depression and Mood Disorders; Suicide Prevention (1392)

Published on in Vol 4, No 3 (2016): Jul-Sept

Psychologist in a Pocket: Lexicon Development and Content Validation of a Mobile-Based App for Depression Screening

Psychologist in a Pocket: Lexicon Development and Content Validation of a Mobile-Based App for Depression Screening

Psychologist in a Pocket: Lexicon Development and Content Validation of a Mobile-Based App for Depression Screening

Authors of this article:

Paula Glenda Ferrer Cheng1, 2 Author Orcid Image ;   Roann Munoz Ramos3 Author Orcid Image ;   Jó Ágila Bitsch4 Author Orcid Image ;   Stephan Michael Jonas3 Author Orcid Image ;   Tim Ix4 Author Orcid Image ;   Portia Lynn Quetulio See5 Author Orcid Image ;   Klaus Wehrle4 Author Orcid Image
Article Authors Cited by (22) Tweetations (24) Metrics

Journals

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  5. Ramos R, Cheng P, Jonas S. Validation of an mHealth App for Depression Screening and Monitoring (Psychologist in a Pocket): Correlational Study and Concurrence Analysis. JMIR mHealth and uHealth 2019;7(9):e12051 View
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  8. Patoz M, Hidalgo-Mazzei D, Pereira B, Blanc O, de Chazeron I, Murru A, Verdolini N, Pacchiarotti I, Vieta E, Llorca P, Samalin L. Patients’ adherence to smartphone apps in the management of bipolar disorder: a systematic review. International Journal of Bipolar Disorders 2021;9(1) View
  9. Liu P, Zhao Y, Fan H, Wu Y, Liu L, Zhang J, Li D, Tan Y, Wang Z, Tan S. Behavioral and electrophysiological analyses of self-referential neural processing in major depressive disorder. Asian Journal of Psychiatry 2023;79:103401 View
  10. Willis M, Jozkowski K, Bridges A, Davis R, Veilleux J. Developing Valid and Feasible Measures of Sexual Consent for Experience Sampling Methodology. The Journal of Sex Research 2021;58(8):996 View
  11. Bao W, Wang Y, Fu X, Yue C, Luo J. Is the Negative Bias in Self-appraisal of Late-adolescents with Mild Depression Derived from their Mother?. Current Psychology 2023;42(17):14962 View
  12. Cha J, Kim S, Park E. A lexicon-based approach to examine depression detection in social media: the case of Twitter and university community. Humanities and Social Sciences Communications 2022;9(1) View
  13. Fernández-Gutiérrez M, Bas-Sarmiento P, Jesús Marín-Paz A, Castro-Yuste C, Sánchez-Sánchez E, Hernández-Encuentra E, Jesus Vinolo-Gil M, Carmona-Barrientos I, Poza-Méndez M. Self-management in heart failure using mHealth: A content validation. International Journal of Medical Informatics 2023;171:104986 View
  14. Koops S, Brederoo S, de Boer J, Nadema F, Voppel A, Sommer I. Speech as a Biomarker for Depression. CNS & Neurological Disorders - Drug Targets 2023;22(2):152 View
  15. Zhao L, Chen J, Lan L, Deng N, Liao Y, Yue L, Chen I, Wen S, Xie R. Effectiveness of Telehealth Interventions for Women With Postpartum Depression: Systematic Review and Meta-analysis. JMIR mHealth and uHealth 2021;9(10):e32544 View
  16. Milton A, Pera M. Into the Unknown: Exploration of Search Engines’ Responses to Users with Depression and Anxiety. ACM Transactions on the Web 2023;17(4):1 View
  17. Zhang D, Zhou L, Tao J, Zhu T, Gao G. KETCH: A Knowledge-Enhanced Transformer-Based Approach to Suicidal Ideation Detection from Social Media Content. Information Systems Research 2024 View
  18. Janssen Daalen J, van den Bergh R, Prins E, Moghadam M, van den Heuvel R, Veen J, Mathur S, Meijerink H, Mirelman A, Darweesh S, Evers L, Bloem B. Digital biomarkers for non-motor symptoms in Parkinson’s disease: the state of the art. npj Digital Medicine 2024;7(1) View

Books/Policy Documents

  1. McDaniel M, Anwar M. Smart Health. View
  2. Farruque N, Zaiane O, Goebel R. Machine Learning and Knowledge Discovery in Databases. View
  3. Lee Y, Pham V, Zhang J, Chung T. Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. View