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

Non-Randomized Studies (funded, eHealth) (105) Ecological Momentary Assessment (EMA) (309) mHealth for Data Collection and Research (954) Participatory Research Protocols and Proposals (138) Depression and Mood Disorders; Suicide Prevention (1360) Systemic Racism and Racial Bias in Health Care and Society (85) Anxiety and Stress Disorders (1049)

Published on in Vol 10, No 10 (2021): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31241, first published .
Assessing the Real-time Influence of Racism-Related Stress and Suicidality Among Black Men: Protocol for an Ecological Momentary Assessment Study

Assessing the Real-time Influence of Racism-Related Stress and Suicidality Among Black Men: Protocol for an Ecological Momentary Assessment Study

Assessing the Real-time Influence of Racism-Related Stress and Suicidality Among Black Men: Protocol for an Ecological Momentary Assessment Study

Authors of this article:

Leslie Adams1 Author Orcid Image ;   Godwin Igbinedion1 Author Orcid Image ;   Aubrey DeVinney1 Author Orcid Image ;   Enoch Azasu2 Author Orcid Image ;   Paul Nestadt1 Author Orcid Image ;   Johannes Thrul1, 3, 4 Author Orcid Image ;   Sean Joe2 Author Orcid Image
Article Authors Cited by (6) Tweetations (4) Metrics

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  1. Kim H, Park S, Kim Y, Kwon S, Kim H. Ecological momentary assessment of mental health in adults at suicide risk: An observational study protocol. Journal of Advanced Nursing 2022;78(3):883 View
  2. Liu Y, Kang K, Doe M. HADD: High-Accuracy Detection of Depressed Mood. Technologies 2022;10(6):123 View
  3. Dauber S, Beacham A, Hammond C, West A, Thrul J. Adaptive Text Messaging for Postpartum Risky Drinking: Conceptual Model and Protocol for an Ecological Momentary Assessment Study. JMIR Research Protocols 2022;11(4):e36849 View
  4. Adams L, Thorpe R. Achieving mental health equity in Black male suicide prevention. Frontiers in Public Health 2023;11 View
  5. Sun Y, Kargarandehkordi A, Slade C, Jaiswal A, Busch G, Guerrero A, Phillips K, Washington P. Personalized Deep Learning for Substance Use in Hawaii: Protocol for a Passive Sensing and Ecological Momentary Assessment Study. JMIR Research Protocols 2024;13:e46493 View
  6. Wang S, Van Genugten R, Yacoby Y, Pan W, Bentley K, Bird S, Buonopane R, Christie A, Daniel M, DeMarco D, Haim A, Follet L, Fortgang R, Kelly-Brunyak F, Kleiman E, Millner A, Obi-Obasi O, Onnela J, Ramlal N, Ricard J, Smoller J, Tambedou T, Zuromski K, Nock M. Building personalized machine learning models using real-time monitoring data to predict idiographic suicidal thoughts. Nature Mental Health 2024;2(11):1382 View