Clinical trial NCT05369806: Leveraging Interactive Text Messaging to Monitor and Support Maternal Health in Kenya
Official title: Leveraging Interactive Text Messaging to Monitor and Support Maternal Health in Kenya
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Neonatal Death
Perinatal Death
Depression
Keywords: Kenya
SMS
Natural Language Processing
NLP
mHealth
Lead sponsor: University of Washington
Sponsor class: OTHER
Collaborators: name: National Institute of Mental Health (NIMH)
First posted: 2022-05-11
Enrollment: 80
Sex: FEMALE
Minimum age (years): 14
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: All participants are enrolled into the MWACh SMS system
Primary purpose: HEALTH_SERVICES_RESEARCH

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.

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

Primary outcomes:
measure: Acceptability
timeFrame: Enrollment through 4 weeks postpartum
measure: Nurse Response Time
timeFrame: Enrollment through 4 weeks postpartum
Secondary outcomes:
Other outcomes:
Locations:
city: Ahero
country: Kenya
facility: Ahero Sub-District Hospital
state: Kisumu
city: Kisumu
country: Kenya
facility: Kisumu County Hospital
Study officials:
affiliation: University of Washington
name: Keshet Ronen, PhD
role: PRINCIPAL_INVESTIGATOR
References: