mHealth Intervention to Reduce Maternal Postnatal Depression and Promote Family Health
NCT ID: NCT05275413
Last Updated: 2022-08-22
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
1578 participants
INTERVENTIONAL
2022-06-16
2023-12-31
Brief Summary
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Detailed Description
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Specifically, the family-based mHealth intervention consists of a smartphone app with different versions designed for expectant mothers, fathers, and grandparents. The smartphone app will provide a user-friendly platform for users to receive psychoeducation materials related to pregnancy (e.g. antenatal care, postnatal care, and infant care) and an interactive forum for all users to ask questions related to pregnancy and family communication, which will be answered by health and social care professionals. To enhance family's engagement, we will also include other functions in the app to encourage communications among family members and enhance family cohesion. These functions include a platform for family members to send texts and share photos, and a shared schedule with alerts for dates related to pregnancy (e.g. appointments for antenatal check-ups and expected delivery date).
Using a randomized controlled design, the proposed study will evaluate the effectiveness of the family-based mHealth intervention in reducing maternal postnatal depression and promoting health in expectant mothers and their family members (expectant fathers and grandparents). The study will recruit 1,578 expectant mothers and their family members at the antenatal clinics at two selected public hospitals in Hong Kong. The participants will be randomized into three groups (i) family-based mHealth intervention; (ii) mother-only mHealth intervention; and (iii) health information control. Participants will be asked to complete a survey with question items related to their physical and mental health, perceived social support and family cohesion, at recruitment and four weeks after childbirth.
It is hypothesized that the family-based mHealth intervention is more effective in reducing symptoms of postnatal depression, promoting health of expectant mothers and their family members, and promoting family cohesion than the mother-only mHealth intervention and the control.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
SUPPORTIVE_CARE
SINGLE
Study Groups
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family-based mHealth intervention
The expectant mothers and their family members (fathers and grandparents) in this group will receive health education and support and family support via a smartphone app.
family-based mHealth Intervention
The intervention consists of three versions: mother, father, and grandparent. The app consists of health information about pregnancy, postnatal care, and infant care in the form of brief texts and short videos. Each versions have their unique features, such as a platform to ask questions in mother version, a quiz game to promote fathers' knowledge related to father's involvement, educational materials tailored for grandparents. An obstetrician and a social worker will respond to the questions. Details please refer to the proposal.
mother-only mHealth intervention
The expectant mothers in this group will receive health education and support via a smartphone app.
mother-only mHealth Intervention
The expectant mothers in this group will receive information about pregnancy, postnatal care, and infant care in the form of brief texts and short videos via a smartphone app. The expectant mothers will also have access to a platform in the smartphone app to ask questions about their pregnancy. An obstetrician will respond to the questions.
Health education
The expectant mothers in the control group will receive health education via a smartphone app.
Health education
The expectant mothers in the control group will receive information about pregnancy, postnatal care, and infant care in the form of brief texts and short videos via a smartphone app.
Interventions
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family-based mHealth Intervention
The intervention consists of three versions: mother, father, and grandparent. The app consists of health information about pregnancy, postnatal care, and infant care in the form of brief texts and short videos. Each versions have their unique features, such as a platform to ask questions in mother version, a quiz game to promote fathers' knowledge related to father's involvement, educational materials tailored for grandparents. An obstetrician and a social worker will respond to the questions. Details please refer to the proposal.
mother-only mHealth Intervention
The expectant mothers in this group will receive information about pregnancy, postnatal care, and infant care in the form of brief texts and short videos via a smartphone app. The expectant mothers will also have access to a platform in the smartphone app to ask questions about their pregnancy. An obstetrician will respond to the questions.
Health education
The expectant mothers in the control group will receive information about pregnancy, postnatal care, and infant care in the form of brief texts and short videos via a smartphone app.
Eligibility Criteria
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Inclusion Criteria
2. Possession of a smartphone and a personal email address for receiving and sending information relevant to the study.
3. Willing to accept the study arrangements.
Exclusion Criteria
2. Expectant mothers whose EPDS score is equal to or high than the cut-off score of 10.
3. Not willing or not able to provide informed consent.
ALL
Yes
Sponsors
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Kwong Wah Hospital
OTHER
The University of Hong Kong
OTHER
University of Glasgow
OTHER
Tsan Yuk Hospital, Hong Kong
UNKNOWN
The Hong Kong Polytechnic University
OTHER
Responsible Party
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Dr Camilla Lo
Assistant Professor
Locations
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Kwong Wah Hospital
Hong Kong, , Hong Kong
Tsan Yuk Hospital
Hong Kong, , Hong Kong
Countries
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Central Contacts
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Facility Contacts
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Wing Cheong Leung
Role: primary
Ka Wang Cheung
Role: primary
Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Other Identifiers
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KC/KE-20-0119/ER-2
Identifier Type: -
Identifier Source: org_study_id
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