Neonatal DeathAI-NEONCT05369806
Leveraging Interactive Text Messaging to Monitor and Support Maternal Health in Kenya
A study testing Interactive two-way SMS dialogue in people with Neonatal Death and Perinatal Death, run by University of Washington at 2 sites in Kenya.
Trial 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. Read more about this study
- Who is it for?
- Ages 14 years and older, women onlyHealthy volunteers can take part
- Conditions the study is for
- Neonatal Death, Perinatal Death, Depression
- What is being tested?
- Interactive two-way SMS dialogue
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 80 participants
- Where
- 2 sitesKenya
- Study dates
- 4 May 2022to 31 Oct 2022
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 14 years and older
- Women only
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- 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
Who cannot join
- Currently enrolled in another research study
Trial locations and contacts
2 sites in 1 country.
Kenya2 sites
Ahero Sub-District Hospital
Ahero, Kisumu County
Kisumu County Hospital
Kisumu
About this study
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.
Read the 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
- Being tested
- Interactive two-way SMS dialogue
- Keywords
- Kenya, SMS, Natural Language Processing, NLP, mHealth
- Medical subject headings
- Perinatal Death, Depression
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Interactive two-way SMS dialogueBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| Interactive two-way SMS dialogue | Experimental | 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. Receives: Behavioral: Interactive two-way SMS dialogue |
What is being measured
The primary outcome is the main question the study is designed to answer.
Acceptability
AIM (Acceptability of Intervention Measure) score (Weiner et al instrument. Score range 1-5; higher score indicates higher acceptability)
Measured: Enrollment through 4 weeks postpartum
Nurse Response Time
Minutes from urgent participant message to nurse response
Measured: Enrollment through 4 weeks postpartum
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 May 2022
- Study start4 May 2022
- Primary completion31 Oct 2022
- Study completion31 Oct 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Other trials for Neonatal DeathStudies of the same condition, open and under way.
- More trials run by University of WashingtonThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- All participants are enrolled into the MWACh SMS system
- Masking
- None (open label)
- Enrolment
- 80 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Washington
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute of Mental Health (NIMH)
- Responsible party
- Principal investigator, Keshet Ronen, University of Washington
- Investigators
- Keshet Ronen, PhD, Principal investigator, University of Washington
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05369806
- Sponsor's protocol ID
- STUDY00014447
- Other IDs
- K18MH122978
- Acronym
- AI-NEO
- Status last verified
- Dec 2023
- First submitted
- 11 Apr 2022
- Last updated
- 29 Dec 2023
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Data from AI-NEO will be available at end of the project by contacting the study team at the University of Washington (keshet@uw.edu).
Study at a glance
From the registry record, last updated by the sponsor on 29 Dec 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Leveraging Interactive Text Messaging to Monitor and Support Maternal Health in Kenya
- ClinicalTrials.gov ID
- NCT05369806
- Acronym / sponsor ID
- AI-NEO / STUDY00014447
- Conditions
- Neonatal Death, Perinatal Death, Depression
- Keywords
- Kenya, SMS, Natural Language Processing, NLP, mHealth
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 80 participants (actual)
- Lead sponsor
- University of WashingtonUniversity, hospital or other
- Collaborators
- National Institute of Mental Health (NIMH)
- Study start
- 4 May 2022 (actual)
- Primary completion
- 31 Oct 2022 (actual)
- Study completion
- 31 Oct 2022 (actual)
- First posted
- 11 May 2022 (actual)
- Results
- Posted 29 Dec 2023
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Health services research
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- All participants are enrolled into the MWACh SMS system
| Arm | Type | Receives |
|---|---|---|
| Interactive two-way SMS dialogue | Experimental | Behavioral: Interactive two-way SMS dialogueParticipants 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. |
Who may qualify
- Ages
- 14 years and older
- Sex
- Female only
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (6 listed)
- Pregnant
- ≥28 weeks gestation
- Daily access to a mobile phone (own or shared) on the Safaricom network
- Willing to receive SMS
- Age ≥14 years
Key exclusion criteria (1 listed)
- Currently enrolled in another research study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Interactive two-way SMS dialogueThis 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. | Behavioural | Interactive two-way SMS dialogue |
Primary outcome
Acceptability
Time frame: Enrollment through 4 weeks postpartum
AIM (Acceptability of Intervention Measure) score (Weiner et al instrument. Score range 1-5; higher score indicates higher acceptability)
Nurse Response Time
Time frame: Enrollment through 4 weeks postpartum
Minutes from urgent participant message to nurse response
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Dec 2023.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Individual participant dataSharing planned: Yes. Data from AI-NEO will be available at end of the project by contacting the study team at the University of Washington (keshet@uw.edu).
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Keshet Ronen, PhD principal investigator
University of Washington
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Interactive two-way SMS dialogue in people with Neonatal Death and Perinatal Death, run by University of Washington at 2 sites in Kenya.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 29 Dec 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Kenya. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 29 Dec 2023). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Acceptability (time frame: Enrollment through 4 weeks postpartum). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 29 Dec 2023.