Tracking Depression Symptoms With a Health Chatbot

Overview

The goal of this research is to bridge a significant "effectiveness" gap in the treatment of depression. The investigators have developed a chatbot which will assist in performing measurement-based care (MBC) via Facebook Messenger. Participants will be randomized to either Usual Care or Usual Care with additional Chatbot Care.

The goal of this research is to bridge a significant "effectiveness" gap in the treatment of depression. The investigators will be looking specifically at depressed women soon after they give birth, otherwise known as known as perinatal depression. Measurement-based care (MBC) which involves the use of quantitative assessments for depression screening, diagnosis, and symptom monitoring is recognized as one of the keys to depression management. MBC can be difficult to implement within the clinical setting due to the administrative overhead and close follow-up required. It is reasonable to hypothesize that low rates of MBC adoption are responsible for low rates of adequate depression care. The investigators have developed an automated conversational agent or "chatbot" (CB) for delivering MBC via Facebook Messenger. The investigators hypothesize that the use of CB-MBC, which combines a conversational interface with state-of-the-art quantitative assessments, will improve depression symptom severity for patients with perinatal depression. If successful, this project will provide primary care physicians with a new and inexpensive method for delivering better and safer care to their patients with depression. This study works to determine the impact of the chatbot in improving depression outcomes for patients under treatment for perinatal depression.

Conditions

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Eligibility

Locations (2)

Outcomes