Use of mobile technology to identify behavioral mechanisms linked to mental health outcomes in Kenya: protocol for development and validation of a predictive model

Authors

Willie Njoroge, Aga Khan UniversityFollow
Rachel Maina, Aga Khan UniversityFollow
Frank Elena, University of Michigan, USA
Lukoye Atwoli, Aga Khan UniversityFollow
Anthony Ngugi, Aga Khan UniversityFollow
Srijan Sen, Aga Khan University
Stephen Wong, Aga Khan UniversityFollow
Linda Khakali, Aga Khan UniversityFollow
Andrew Aballa, Aga Khan UniversityFollow
James Orwa, Aga Khan UniversityFollow
Moses Nyongesa, Aga Khan UniversityFollow
Jasmit Shah, Aga Khan UniversityFollow
Amina Abubakar, Aga Khan UniversityFollow
Zul Merali, Aga Khan UniversityFollow

Document Type

Article

Department

Internal Medicine (East Africa); Population Health (East Africa); Institute for Human Development; Brain and Mind Institute

Abstract

Objective:This study proposes to identify and validate weighted sensor stream signatures that predict near-term risk of a major depressive episode and future mood among healthcare workers in Kenya.

Approach: The study will deploy a mobile application (app) platform and use novel data science analytic approaches (Artificial Intelligence and Machine Learning) to identifying predictors of mental health disorders among 500 randomly sampled healthcare workers from five healthcare facilities in Nairobi, Kenya.

Expectation: This study will lay the basis for creating agile and scalable systems for rapid diagnostics that could inform precise interventions for mitigating depression and ensure a healthy, resilient healthcare workforce to develop sustainable economic growth in Kenya, East Africa, and ultimately neighboring countries in sub-Saharan Africa. This protocol paper provides an opportunity to share the planned study implementation methods and approaches.

Conclusion: A mobile technology platform that is scalable and can be used to understand and improve mental health outcomes is of critical importance.

Publication (Name of Journal)

BMC Research Notes

DOI

https://doi.org/10.1186/s13104-023-06498-6

Recommended Citation

Njoroge, W., Maina, R., Elena, F., Atwoli, L., Ngugi, A., Sen, S., Wong, S., Khakali, L., Aballa, A., Orwa, J., Nyongesa, M., Shah, J., Abubakar, A., Merali, Z. (2024). Use of mobile technology to identify behavioral mechanisms linked to mental health outcomes in Kenya: protocol for development and validation of a predictive model. BMC Research Notes, 16(226), 1-9.
Available at: https://ecommons.aku.edu/bmi/408

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.