Leveraging Interactive Text Messaging to Monitor and Support Maternal Health in Kenya

NCT ID: NCT05369806

Last Updated: 2023-12-29

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 80 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-05-04
• Study Completion Date: 2022-10-31

Brief Summary

Mobile health (mHealth) interventions such as interactive short message service (SMS) text messaging with healthcare workers (HCWs) have been proposed as efficient, accessible additions to traditional health care in resource-limited settings. Realizing the full public health potential of mHealth for maternal health requires use of new technological tools that dynamically adapt to user needs. This study will test use of a natural language processing computer algorithm on incoming SMS messages with pregnant people and new mothers in Kenya to see if it can help to identify urgent messages.

Detailed Description

Despite recent achievements in reducing child mortality, neonatal deaths remain high, accounting for 46% of all deaths in children under 5 worldwide. Addressing the high neonatal mortality demands efforts focused on getting proven interventions to at-risk neonates and their families. mHealth interventions have the potential to improve neonatal care and healthcare seeking by caregivers. Impact of such interventions will be maximized by ensuring healthcare workers accurately triage messages from caregivers and respond appropriately and quickly to messages that indicate an urgent medical question. This study adds to current knowledge by testing a novel natural language processing (NLP) tool to detect urgent messages. To the investigators' knowledge, such a tool has not been developed and empirically tested in a "real-world" implementation. Moreover, NLP tools to date have mostly been developed for high-resource languages; the investigators are not aware of any tools developed for detecting urgency in Swahili and Luo languages.

This study's overarching hypothesis is that development of an adaptive variant of the Mobile WACh SMS platform that automatically detects and prioritizes urgent messages will be feasible and acceptable to nurses and end-users, and will reduce the time from message receipt to HCW response.

Broad Objectives The study's overarching aim is to implement an NLP model into the Mobile WACh SMS platform and test its acceptability and impact on HCW response time.

Aim: Pilot the adapted Mobile WACh system (AI-NEO) and evaluate its acceptability and effect on nurse response time.

Eighty pregnant women will be enrolled to receive the AI-NEO SMS intervention. Women will be enrolled at >=28 weeks gestation and will receive automated SMS regarding neonatal health from enrollment until 6 weeks postpartum, and will have the ability to interactively message with study nurses. Participant messages will be automatically categorized by urgency. Intervention acceptability and recommended improvements will be evaluated among clients and nurses using quantitative and qualitative data collection at study exit (quantitative questionnaires with all client participants and qualitative interviews with 4 nurses). Nurse response time to urgent and non-urgent participant messages will be compared in the AI-NEO pilot vs. the ongoing Mobile WACh NEO trial, in which a non-adapted Mobile WACh system is used.

Conditions

Neonatal Death; Perinatal Death; Depression

Keywords

Kenya; SMS; Natural Language Processing; NLP; mHealth

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: HEALTH_SERVICES_RESEARCH
• Blinding Strategy: NONE

Study Groups

Interactive two-way SMS dialogue

Participants will receive automated SMS messages with prompts to reply. They will have the ability to both respond to and initiate SMS dialogue. Trained Study Nurses will monitor and respond to participant messages. The NLP model will be applied to messages and will highlight those determined to be urgent.

Group Type: EXPERIMENTAL

Interactive two-way SMS dialogue

Intervention Type: BEHAVIORAL

This study uses Mobile WACh, a human-computer hybrid system that enables two-way SMS communication and patient tracking, to provide consistent support to women and their infants during the peripartum period and 6 weeks into the baby's life. Women will receive automated SMS messages targeting the appropriate peripartum period and will have the capability to respond and spontaneously message a nurse based at the clinic. During pregnancy, automated SMS will be delivered weekly. Two weeks prior to the participant's estimated due date (EDD), daily messaging will begin, and will continue for two weeks after delivery is ascertained. Thereafter, SMS will be delivered every other day. Women who experience pregnancy or infant loss will be enrolled into an infant loss track. The NLP model will be applied to incoming participant messages. Those flagged as urgent by the model will be flagged within the SMS system, allowing study nurses to triage and appropriately respond to those messages.

Interventions

Interactive two-way SMS dialogue

This study uses Mobile WACh, a human-computer hybrid system that enables two-way SMS communication and patient tracking, to provide consistent support to women and their infants during the peripartum period and 6 weeks into the baby's life. Women will receive automated SMS messages targeting the appropriate peripartum period and will have the capability to respond and spontaneously message a nurse based at the clinic. During pregnancy, automated SMS will be delivered weekly. Two weeks prior to the participant's estimated due date (EDD), daily messaging will begin, and will continue for two weeks after delivery is ascertained. Thereafter, SMS will be delivered every other day. Women who experience pregnancy or infant loss will be enrolled into an infant loss track. The NLP model will be applied to incoming participant messages. Those flagged as urgent by the model will be flagged within the SMS system, allowing study nurses to triage and appropriately respond to those messages.

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

• Pregnant
• ≥28 weeks gestation
• Daily access to a mobile phone (own or shared) on the Safaricom network
• Willing to receive SMS
• Age ≥14 years
• Able to read and respond to text messages in English, Kiswahili or Luo, or have someone in the household who can help

Exclusion Criteria

• Currently enrolled in another research study

• Minimum Eligible Age: 14 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: Yes

Sponsors

National Institute of Mental Health (NIMH)

NIH

Sponsor Role: collaborator

University of Washington

OTHER

Sponsor Role: lead

Responsible Party

Keshet Ronen

Acting Assistant Professor, School of Public Health: Global Health

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Keshet Ronen, PhD

Role: PRINCIPAL_INVESTIGATOR

University of Washington

Locations

Ahero Sub-District Hospital

Ahero, Kisumu County, Kenya

Kisumu County Hospital

Kisumu, , Kenya

Countries

Kenya

Provided Documents

Document Type: Study Protocol

View Document

Document Type: Informed Consent Form

View Document

Other Identifiers

K18MH122978

Identifier Type: NIH

Identifier Source: secondary_id

View Link

STUDY00014447

Identifier Type: -

Identifier Source: org_study_id