Digital Technology for Building Capacity of Nonspecialist Health Workers for Task Sharing and Scaling Up Mental Health Care Globally

Digital Technology for Building Capacity of Nonspecialist Health Workers for Task Sharing and Scaling Up Mental Health Care Globally
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DOI:
10.1097/hrp.0000000000000217
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发表时间:
2019-05-01
影响因子:
3.8
通讯作者:
Patel, Vikram
Patel, Vikram
中科院分区:
医学3区
文献类型:
--
作者:
Naslund, John A.;Shidhaye, Rahul;Patel, Vikram

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Workforce shortages pose major obstacles to delivering adequate mental health care and scaling up services to address the global treatment gap. Mounting evidence demonstrates the clinical effectiveness of having nonspecialist health workers, such as community health workers, lay health workers, midwives, or nurses, deliver brief psychosocial treatments for common mental disorders in primary care settings. With rapidly increasing access to, and use of, digital technology worldwide, new opportunities are available to leverage these emerging digital technologies to support nonspecialist health workers and increase mental health workforce capacity. This Perspectives article considers the potential that digital technology holds for supporting nonspecialist health workers in delivering evidence-based mental health care. Specifically, from our search of the academic literature, we identified seven promising examples from primary care settings in different low- and middle-income countries (India, Pakistan, Zimbabwe, Peru, China, and Nigeria) where digital platforms are being used to support delivery of mental health care from a variety of nonspecialist providers by offering training, providing digital tools for diagnosis, guiding treatment, facilitating supervision, and integrating services. We summarize these examples and discuss future opportunities to use digital technology for supporting the development of a trained, effective, and sustainable mental health workforce. We also consider the potential to leverage these technologies for integrating mental health care into existing health systems in low-resource settings.