Published on 20.07.16 in Vol 4, No 3 (2016): Jul-Sept
Works citing "Psychologist in a Pocket: Lexicon Development and Content Validation of a Mobile-Based App for Depression Screening"
According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.5284):
(note that this is only a small subset of citations)
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Trotzek M, Koitka S, Friedrich CM. Utilizing Neural Networks and Linguistic Metadata for Early Detection of Depression Indications in Text Sequences. IEEE Transactions on Knowledge and Data Engineering 2020;32(3):588
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Rawlins F, Sumpter C, Sutphin D, Garner HR. Quantifying medical student clinical experiences via an ICD Code Logging App. International Journal of Medical Informatics 2018;111:51
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Losada DE, Gamallo P. Evaluating and improving lexical resources for detecting signs of depression in text. Language Resources and Evaluation 2020;54(1):1
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Guohou S, Lina Z, Dongsong Z. What reveals about depression level? The role of multimodal features at the level of interview questions. Information & Management 2020;57(7):103349
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Ramos RM, Cheng PGF, Jonas SM. 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
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Ghosh CC, McVicar D, Davidson G, Shannon C. Measuring diagnostic heterogeneity using text-mining of the lived experiences of patients. BMC Psychiatry 2021;21(1)
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Patoz M, Hidalgo-Mazzei D, Blanc O, Verdolini N, Pacchiarotti I, Murru A, Zukerwar L, Vieta E, Llorca P, Samalin L. Patient and physician perspectives of a smartphone application for depression: a qualitative study. BMC Psychiatry 2021;21(1)
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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)
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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
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Willis M, Jozkowski KN, Bridges AJ, Davis RE, Veilleux JC. Developing Valid and Feasible Measures of Sexual Consent for Experience Sampling Methodology. The Journal of Sex Research 2021;58(8):996
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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
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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)
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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
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Koops S, Brederoo SG, de Boer JN, Nadema FG, Voppel AE, Sommer IE. Speech as a Biomarker for Depression. CNS & Neurological Disorders - Drug Targets 2023;22(2):152
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Zhao L, Chen J, Lan L, Deng N, Liao Y, Yue L, Chen I, Wen SW, Xie R. Effectiveness of Telehealth Interventions for Women With Postpartum Depression: Systematic Review and Meta-analysis. JMIR mHealth and uHealth 2021;9(10):e32544
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Milton A, Pera MS. Into the Unknown: Exploration of Search Engines’ Responses to Users with Depression and Anxiety. ACM Transactions on the Web 2023;17(4):1
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According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.5284):
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McDaniel M, Anwar M. Smart Health. 2017. Chapter 12:123
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Farruque N, Zaiane O, Goebel R. Machine Learning and Knowledge Discovery in Databases. 2020. Chapter 22:359
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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. 2023. Chapter 27:381
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