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AI tapped to alleviate postpartum depression in developing regions

The researchers’ long-term goal is to expand access to treatment services to people in emerging markets who currently cannot receive care from mental health professionals because of cost and human resource constraints.

Jeff Rowe | May 02, 2019 02:24 pm

As AI spreads across the healthcare sector, researchers are increasingly exploring the myriad ways in which it can be put to use alleviating longstanding shortages in care services.

For example, a team of researchers in Kenya has begun looking into whether live and automated text messaging augmented by AI can help treat or ward off postpartum depression for women in that country, and they recently published their research protocol online in the Journal of Medical Internet Research.

In the background description of their project, the team points out that depression during pregnancy and in the postpartum period has been associated with a number of poor outcomes for women and their children, and this situation is particularly acute in countries like Kenya, which, they point out, has “only 180 psychiatric nurses outside of the capital city, a ratio of 1 provider per 200,000 people.”

Indeed, they point out, “although effective interventions exist for common mental disorders that occur during pregnancy and the postpartum period, most cases in low- and middle-income countries go untreated because of a lack of trained professionals.”

The pilot study focuses on adapting the World Health Organization’s “Thinking Healthy” program, which guides mental healthcare for perinatal depression.  Specifically, they say, “the idea is to make it possible for anyone with a basic phone to receive high-quality, evidence-based psychological support anytime, anywhere. We will do this in the context of perinatal depression by adapting Thinking Healthy to an existing artificial intelligence (AI) system for automated psychological support called Tess (which we have named Zuri in Kenya). This idea is innovative because it introduces an entirely new delivery channel that has the potential for a step change in expanding access to care, while also potentially augmenting and strengthening existing task-sharing models.”

The team adapted the content of the intervention last year after testing it with 10 women at a private maternity hospital. These users offered feedback, and the researchers incorporated their input to fine-tune the innovation.

Recruitment for the Kenya phase of their project began in January, with the results expected toward the end of this year.

The researchers acknowledge as a limitation their reliance on women who live in and around cities, as much of the Kenyan population lives in rural or remote areas.

“The results of this study may not generalize to the broader population of Kenyan women, but that is not an objective of this phase of work,” they write. “Our primary objective is to gather preliminary data to know how to build and test a more robust service. We are working toward a larger study with a more diverse population.”