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

RCTs - Protocols/Proposals (eHealth) (538) Chatbots and Conversational Agents (531) mHealth for Wellness, Behavior Change and Prevention (2871) Text-messaging (SMS, WeChat etc)-Based Interventions (650) Depression and Mood Disorders; Suicide Prevention (1363) Perinatal Depression; Postpartum Depression; PPD (94) Perinatal Education for Parents (219)

Published on in Vol 8, No 4 (2019): April

Expanding Access to Depression Treatment in Kenya Through Automated Psychological Support: Protocol for a Single-Case Experimental Design Pilot Study

Expanding Access to Depression Treatment in Kenya Through Automated Psychological Support: Protocol for a Single-Case Experimental Design Pilot Study

Expanding Access to Depression Treatment in Kenya Through Automated Psychological Support: Protocol for a Single-Case Experimental Design Pilot Study

Authors of this article:

Eric P Green1 Author Orcid Image ;   Nicholas Pearson1, 2 Author Orcid Image ;   Sathyanath Rajasekharan3 Author Orcid Image ;   Michiel Rauws4 Author Orcid Image ;   Angela Joerin4 Author Orcid Image ;   Edith Kwobah5 Author Orcid Image ;   Christine Musyimi6 Author Orcid Image ;   Chaya Bhat1 Author Orcid Image ;   Rachel M Jones3 Author Orcid Image ;   Yihuan Lai1 Author Orcid Image
Article Authors Cited by (14) Tweetations (11) Metrics

Journals

  1. Hussain-Shamsy N, Shah A, Vigod S, Zaheer J, Seto E. Mobile Health for Perinatal Depression and Anxiety: Scoping Review. Journal of Medical Internet Research 2020;22(4):e17011 View
  2. Kohrt B, Ottman K, Panter-Brick C, Konner M, Patel V. Why we heal: The evolution of psychological healing and implications for global mental health. Clinical Psychology Review 2020;82:101920 View
  3. Rahman A, Waqas A, Nisar A, Nazir H, Sikander S, Atif N. Improving access to psychosocial interventions for perinatal depression in low- and middle-income countries: lessons from the field. International Review of Psychiatry 2021;33(1-2):198 View
  4. Davidson L, Boland M. Towards deep phenotyping pregnancy: a systematic review on artificial intelligence and machine learning methods to improve pregnancy outcomes. Briefings in Bioinformatics 2021;22(5) View
  5. Dosani A, Arora H, Mazmudar S. mHealth and Perinatal Depression in Low-and Middle-Income Countries: A Scoping Review of the Literature. International Journal of Environmental Research and Public Health 2020;17(20):7679 View
  6. Green E, Lai Y, Pearson N, Rajasekharan S, Rauws M, Joerin A, Kwobah E, Musyimi C, Jones R, Bhat C, Mulinge A, Puffer E. Expanding Access to Perinatal Depression Treatment in Kenya Through Automated Psychological Support: Development and Usability Study. JMIR Formative Research 2020;4(10):e17895 View
  7. Oprescu A, Miro-Amarante G, Garcia-Diaz L, Beltran L, Rey V, Romero-Ternero M. Artificial Intelligence in Pregnancy: A Scoping Review. IEEE Access 2020;8:181450 View
  8. Jellinek M, Bergmann P, Holcomb J, Riobueno-Naylor A, Dutta A, Haile H, Sturner R, Howard B, Murphy J. Recognizing Adolescent Depression with Parent- and Youth-Report Screens in Pediatric Primary Care. The Journal of Pediatrics 2021;233:220 View
  9. Kharb S, Joshi A. Multi-omics and machine learning for the prevention and management of female reproductive health. Frontiers in Endocrinology 2023;14 View
  10. Carvalho L, Teixeira J, Unger R, Motti V, Lovisi G, Grincenkov F. Technologies Applied to the Mental Health Care of Pregnant Women: A Systematic Literature Review. Revista Brasileira de Ginecologia e Obstetrícia / RBGO Gynecology and Obstetrics 2023;45(03):149 View
  11. Rakers M, van de Vijver S, Bossio P, Moens N, Rauws M, Orera M, Shen H, Hallensleben C, Brakema E, Guldemond N, Chavannes N, Villalobos-Quesada M. SERIES: eHealth in primary care. Part 6: Global perspectives: Learning from eHealth for low-resource primary care settings and across high-, middle- and low-income countries. European Journal of General Practice 2023;29(1) View
  12. Inkster B, Kadaba M, Subramanian V. Understanding the impact of an AI-enabled conversational agent mobile app on users’ mental health and wellbeing with a self-reported maternal event: a mixed method real-world data mHealth study. Frontiers in Global Women's Health 2023;4 View

Books/Policy Documents

  1. Mattioli M. Governing Privacy in Knowledge Commons. View
  2. Waqas A, Rahman A. Shaping the Future of Child and Adolescent Mental Health. View