Engaging the Whole Family to Support Expectant Mothers: A Family-based mHealth Intervention to Reduce Maternal Postnatal Depression and Promote Family Health
Phase: NA
Conditions: Postnatal Depression, Quality of Life, Family Relations
Sponsor: The Hong Kong Polytechnic University

 
 
 
 
Unique Protocol ID: KC/KE-20-0119/ER-2 
 
Title: 
Engaging the whole family to support expectant mothers: A family-based mHealth intervention to 
reduce maternal postnatal depression and promote family health 
Dr. Camilla Kin Ming LO 
 Assistant Professor,  
Department of Applied Social Sciences,  
The Hong Kong Polytechnic University 
 
Document date:  
March 02, 2022 
 

 
 
 2 
 
 
Research Proposal 
 
PI:  
Dr. Camilla Kin Ming LO 
 Assistant Professor, Department of Applied Social Sciences, The Hong Kong 
Polytechnic University 
 
(a)  Title:   
 
Engaging the whole family to support expectant mothers: A family-based mHealth 
intervention to reduce maternal postnatal depression and promote family health      
 
      
(b)  Justification for conducting the project: 
 
 
(i)  
Health Needs of Expectant Mothers 
 
Globally, about 10% of pregnant women and 13% of postpartum women 
experience a mental disorder, primarily depression.1 Findings from meta-analyses 
show that 11% of pregnant women in Asia have experienced pregnancy 
depression,2 and 26% have shown symptoms of postnatal depression (PND).3 In 
Hong Kong, a cohort study conducted by our research team revealed a 26% rate of 
pregnancy depression and a 9% rate of PND.4  
 
In response to the issue, the Hong Kong government and the Hospital 
Authority (HA) have been making an effort to promote maternal and infant health, 
for example, through providing antenatal classes and health advice for pregnant 
women. Although empirical evidence has proven the effectiveness of face-to-face 
education and advising services for expectant mothers and fathers,5 the availability 
of such support is often limited and is insufficient to benefit all parents who need 
it.6 Our team found that 39% of first-time mothers were unable to join face-to-face 
antenatal classes in Hong Kong due to the limited seats available.7 Clearly, there 
is a need for more effective measures that could deliver support to a wider 
population of expectant mothers. 

 
 
 3 
 
Another challenge in pregnancy support in Hong Kong is the failure to 
engage family members in providing support for expectant mothers. In some 
previous studies, our team highlighted the importance of involving fathers in 
pregnancy and childcare to promote family health,4,8 while other researchers have 
suggested the potential benefits of grandparental support and care in reducing 
maternal PND.9 Unfortunately, there has been a lack of empirically supported 
programmes to engage family members in supporting pregnant women in Hong 
Kong, indicating a need for development and implementation of a family-based 
approach in providing pregnancy support in the community. 
 
 
 
 
(ii) 
Existing Strategies and Work Done by the Research Team to Address Health 
Needs 
 
 
To address the limitations of traditional face-to-face services, mobile health 
(mHealth) technologies have been widely employed in healthcare services in 
recent years.10 mHealth is defined as the use of mobile technologies for medical 
and public health practices.11 Some major strengths of mHealth over traditional 
approaches include the accessibility to service without time and location 
constraints, the opportunity for instant interaction with professionals and peers, 
and the relatively low running costs.10,12 A meta-analysis conducted by the research 
team revealed moderate to large effect sizes of pregnancy related mHealth apps in 
promoting maternal physical health (d = 0.72), mental health (d = 0.84), and 
improving knowledge about pregnancy (d = 0.80).12 
 
In Hong Kong, there have been similar attempts to adopt mHealth 
technologies in pregnancy care. In 2015, a telephone-based cognitive behavioural 
therapy for PND was demonstrated to be effective in reducing PND when 
compared to standard care.13 In 2017, the HA developed a smartphone app called 
“HApi Journey” to provide support for expectant mothers. In 2019, the research 
team developed and evaluated an mHealth intervention for expectant mothers 

 
 
 4 
using a randomized controlled trial (RCT).7 The intervention was designed to 
deliver psycho-education on antenatal care, postnatal care, and infant care. The 
study revealed positive benefits of the mHealth intervention (a smartphone app) 
for expectant mothers in reducing maternal PND at four weeks postpartum.7 
 
 
 
 
(iii) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Scientific Evidence Supporting the Strategies to Address the Needs Proposed 
in This Project      
 
 
The success of the mHealth intervention for expectant mothers has warranted 
the development of other mHealth interventions to engage more family members 
to support expectant mothers. In this project, we propose to develop a mHealth 
intervention that engages not only expectant mothers but also expectant fathers and 
grandparents in supporting pregnancy and infant care. 
 
The literature shows that involving fathers in different stages of pregnancy 
and childbirth may have positive impacts on promoting family health and 
improving marital relationships.14 In a local study, an intervention programme 
called Positive Fathering was successfully in improving physical health, mental 
health, and marital relationship of expectant fathers.15 These positive outcomes in 
fathers may have potential benefits to expectant mothers, which may in turn, 
improving overall family health. 
 
Engaging and educating expectant grandparents is equally essential to 
enhance pregnancy support, especially in Hong Kong households.16 In Hong Kong, 
approximately 30% of grandparents were living with young children more than 
five days a week, and more than 25% were responsible for providing primary 
childcare during the daytime.17 Grandparental involvement in pregnancy and 
childcare has been demonstrated to improve family health and reduce PND by 
increasing the levels of perceived social support among mothers,8 and promoting 
a healthy and non-violent family environment.18 

 
 
 5 
 
Possible mechanisms underlying the positive impacts of father and 
grandparent involvement may include increased social support, improved 
knowledge on pregnancy, and enhanced family communication and relationships. 
In a study on social capital during pregnancy, it was shown that close family was 
one of the most important sources of social capital that significantly influences 
maternal health other than medical professionals.19 As the immediate environment 
that expectant mothers primarily inhabit, the family could provide valuable 
psychosocial resources through strong family cohesion.19 
 
In the proposed study, we aim to develop and test a new mHealth 
intervention by including a smartphone app with different versions specifically 
designed for expectant mother, father, and grandparents who are part of the same 
household. To our best knowledge, there has been no empirically evaluated family-
based mHealth intervention for pregnancy support.  
 
 
(c)  Aim and Objectives: 
 
Aim 
 
To develop a cultural-specific, family-based mHealth intervention to reduce PND 
and promote health among expectant mothers in Hong Kong by engaging all family 
members, including expectant fathers and grandparents, in giving support. Additionally, 
the family-based mHealth intervention aims to promote health of expectant fathers and 
grandparents, as well as cohesion of families. In alignment with World Health 
Organization’s definition of health as a state of physical, mental, and social well-being20, 
in this study we assess participants’ health in multiple dimensions, including symptoms 
of depression, anxiety, and stress, health-related quality of life, and social support. 
Objectives 
(i) 
To develop a family-based mHealth intervention to engage family members in supporting 
expectant mothers during pregnancy; 

 
 
 6 
(ii) 
To evaluate the effectiveness of the family-based mHealth intervention in reducing PND 
and promoting health (symptoms of depression, anxiety, and stress, health-related quality 
of life, and social support) among expectant mothers; and 
(iii) 
To evaluate the effectiveness of the family-based mHealth intervention in promoting the 
health (symptoms of anxiety and stress, and health-related quality of life) of the expectant 
fathers and grandparents and promoting family cohesion. 
Hypotheses 
(i) 
The family-based mHealth intervention is more effective in reducing PND and promoting 
health among expectant mothers than the previously developed mHealth intervention for 
expectant mothers (mother-only mHealth intervention) and the control; and 
(ii) 
The family-based mHealth intervention is more effective in improving promoting health of 
the expectant fathers and grandparents and promoting family cohesion than the mother-
only mHealth intervention and the control. 
 
      
(d)  Project Plan: 
 
 
(i) 
Target Group  
 
 
1,578 families with expectant mothers will be recruited in Kwong Wah 
Hospital (KWH) and Tsan Yuk Hospital (TYH), two public hospitals that are 
managed by the Hospital Authority in Hong Kong, on a 1:1 basis. 
 
Sample size calculation 
 
Assuming a Cohen’s d effect size of 0.20, an effective sample of 1,182 would be 
required to achieve 80% statistical power in detecting the effect in pairwise comparison. 
Assuming a retention rate of 75% for the current sample, a total of 1,578 families will be 
recruited. 
 
 
 
 
(ii) 
Implementation Plan 
 
This project will involve development, implementation and evaluation of the 
family-based 
mHealth 
intervention. 
Details 
of 
the 
development 
and 
implementation of the intervention are elaborated below, and the evaluation of the 
intervention is detailed in Section (v). 

 
 
 7 
Development of family-based mHealth intervention 
Mother-only mHealth intervention (previously developed by the research team) 
 
The mother-only mHealth intervention contains all psycho-educational 
materials from routine education practice promoting healthy pregnancy, guides for 
antenatal care, postnatal care, and infant care that are available at the hospital.7 
Most of the information is re-organised into small topics to increase readability 
and accessibility and is presented in the form of short videos, illustrations, and 
brief messages. There is also a platform for users to ask questions, and our affiliate 
member, who is an obstetrician, will answer these questions. Answers will be 
provided via private messages in the App, or by publicly posted on the FAQ section 
of the app at users’ choice after removing personal identifiable information. In the 
FAQ section of the app, there will be a message reminding participants that the 
purpose of the FAQ is for them to ask questions on pregnancy care that do not 
require professional’s immediate attention or care. For emergency medical issues, 
they are advised to seek medical treatment from their doctors or go to the Accident 
and Emergency Department at hospitals. Also, there will be information about 
social services and 24-hour hotlines. 
 
Family-based mHealth intervention (to be developed in this project) 
 
We will develop a new smartphone app on the basis of the previous mother-
only mHealth intervention. There will be three versions of the app to meet different 
needs of family members:  
 
 
The mother version will contain all psycho-educational materials in the 
mother-only mHealth intervention app.  
 
 
The father version will include all materials of the mother version and 
additional information tailored for fathers. Psychoeducational materials on family 

 
 
 8 
communication, father’s involvement in pregnancy and child care are delivered in 
a format of a quiz game.  
 
 
The grandparent version will include all materials of the mother version and 
additional information on physical and mental health, and family communication 
tailored for grandparents to enhance their health awareness. Specifically, the 
information includes educating grandparents to identify sources of stress and the 
effect of stress on their well-being and interpersonal relationship, introducing ways 
to reduce stress, including eight videos demonstrating the Eight Section Qigong 
exercises (one video for each Section) and a series of yoga exercises suitable for 
older adults. Regarding family communication, there will be materials to enhance 
grandparents’ awareness of their own intergenerational communication pattern and 
competence in effective communication with family members. All of the materials 
were previously developed by the research team and successfully delivered to local 
grandparents. 
 
 
Similar to the mother-only mHealth intervention, users of all versions will 
be granted access to a platform to raise questions related to pregnancy care, which 
will be answered by our affiliate member who is an obstetrician. In addition to 
questions related to pregnancy care, users of the family-based mHealth 
intervention can ask questions related to family communication, which will be 
answered by a social worker. Answers will be provided via private messages in the 
app, or publicly posted on the FAQ section of the app, at users’ discretion, after 
removing personal identifiable information.  
 
 
Additionally, the app will utilize the family approach of intervention and 
incorporate several new functions to enhance family cohesion. There will be a 
platform for members within the same family to send and share texts and photos 

 
 
 9 
using the app. Besides, the app will provide a shared calendar for users to set 
reminders for all family members on important dates related to pregnancy and 
other family activities. The messages and photos shared via the app will not be 
used for data analysis. All messages will be deleted upon completion of the study. 
 
Implementation of intervention 
 
The interventions will be implemented at antenatal clinics at KWH and 
TYH. The interventions will be provided to participants free-of-charge. Families 
with expectant mothers attending the two clinics will be recruited. For the purpose 
of intervention evaluation, participants in the intervention groups will receive the 
intervention. As the interventions will be delivered via smartphone apps, research 
staff will be stationed at the clinics to assist participants in downloading and 
installing the apps.  
 
 
 
 
(iii
) 
Contingency/Alternative Plan if any Problems are Encountered During 
Implementation 
 
 
A potential challenge may come from the non-100% penetration rate of 
smartphone usage, particularly among older adults. According to the census 
statistics in Hong Kong, the penetration rate was about 95% in general and 58%-
70% among elderly people over 60 years of age.21 We will encourage the use of 
smartphones among eligible participants; however, if participants refuse, they will 
be excluded from our study, before randomisation is performed. 
 
 
Possible cross-contamination between groups may also be a challenge in this 
project. To ensure that only participants in the intervention groups can get access 
to the app, we will provide unique login credentials for each of them. We will also 

 
 
 10 
ask all participants to report their use of the family-based app or other similar 
parenting apps during the study period. 
 
 
 
 
 
 
 
(iv) Indicators and Targets 
Corresponding to Objective (i) 
 
The coverage and usage of the app among expectant mothers, expectant 
fathers and grandparents, as well as their feedback on the app will be used as 
preliminary indicators of the success of the smartphone intervention. We expect 
high coverage and high usage, and positive user feedback. 
 
Corresponding to Objective (ii) 
 
Findings of the RCT will provide empirical evidence for the effectiveness of 
the family-based mHealth intervention in reducing maternal PND and promoting 
health among mothers. We expect to see a greater effect of the new family-based 
mHealth intervention in reducing maternal PND and promoting health among 
mothers than in the mother-only mHealth intervention and the control group. 
 
Corresponding to Objective (iii) 
 
Findings of the RCT will also provide empirical evidence for the 
effectiveness of the family-based mHealth intervention in promoting health among 
fathers and grandparents and promoting family cohesion. We expect to see a 
greater effect of the family-based mHealth intervention in promoting health and 
cohesion of the family than in the mother-only mHealth intervention app and the 
control group. 
 
 
 
 
(v) 
Evaluation Plan 
Corresponding to Objective (i) 

 
 
 11 
 
The coverage and usage of the family-based mHealth intervention will be 
recorded automatically within the app, while feedback will be elicited from all 
users during the follow-up survey. 
 
Corresponding to Objectives (ii) and (iii) 
Study design 
 
We will conduct a three-arm RCT to evaluate the effectiveness of the family-
based mHealth intervention, and the three arms include two intervention groups: 
(i) the mother-only mHealth intervention, and (ii) the new family-based mHealth 
intervention, and (iii) the control group: basic health information. A three-arm 
RCT in this project allows evaluation of additional benefits of the family-based 
mHealth intervention over the mother-only intervention and of the control group.  
 
Subject recruitment 
 
The subject recruitment and baseline survey will be conducted when eligible 
expectant mothers show up for their first visit to the antenatal clinics of TYH and 
KWH. Given that there are approximately 231 births per month at each hospital 
and a response rate of 82.2% achieved in the previous study,7 a 5-month 
recruitment period will achieve the required sample size.  
 
Inclusion criteria:  
 
Eligible families are those with an expectant mother who is 18 years old or 
above and is attending the antenatal clinics at the two selected public hospitals, 
Kwong Wah Hospital and Tsan Yuk Hospital in Hong Kong. Other inclusion 
criteria will be the possession of a smartphone and a personal email address for 
receiving and sending information relevant to the study of each of the participating 
family members, and the willingness to accept our study arrangements. Whether 
or not the family members co-reside with the mother is not an eligibility criteria. 
 
Exclusion criteria: 

 
 
 12 
 
Families will be excluded if the expectant mother scores 10 or higher on the 
EPDS. Participants will be excluded if the expectant mothers, fathers, or 
grandparents are not able to understand written or spoken Chinese or are unable/not 
willing to give informed consent.  
 
Randomization 
 
The RCT will require recruitment of three groups, on a 1:1:1 basis, for 
comparison: (i) mother-only mHealth intervention; (ii) family-based mHealth 
intervention; and (iii) health information control. A computerized blocked 
randomisation programme will be used to generate a series of random numbers to 
determine the group to which the family is assigned.  
 
Baseline survey 
 
Participants will be briefed by a trained research assistant about the purpose 
and the details of the study, and will be asked to provide written consent. Blocked 
randomisation will be performed using a centralised online website upon 
participation. Depending on their group assignment, expectant mothers will be 
asked to download the respective smartphone app, log in to the app with a unique 
username and password that they will be assigned. The expectant mothers will also 
be asked to complete the baseline survey via online, which will take about 15-20 
minutes to complete. After that, the participants will be asked about their expected 
delivery date, and their preferred contact method for the follow-up survey. 
 
 
Eligible expectant fathers and grandparents who are not present at the clinics 
will be contacted by the research assistant using the contact methods given by the 
participating mothers, study details will be explained to them, and they will be 
asked to provide informed consent. They will be instructed to complete a structured 
questionnaire, which will take about 15 minutes. Fathers and grandparents who are 

 
 
 13 
allocated to the family-based intervention group will then be provided with a link 
to download the father or grandparent version of the app, and a unique login 
information.  
 
Intervention arms 
 
Participants in the two intervention groups (family-based mHealth 
intervention and mother-only mHealth intervention) will be granted free and 
unlimited access to the respective smartphone app from the time of recruitment up 
to four weeks after childbirth. Their usage of the app will be recorded in terms of 
the time spent on the app (in minutes). For ethical reasons, the participants in the 
intervention groups will not be deprived from usual face-to-face antenatal classes 
at the hospitals; instead, they will be provided something more than they can obtain 
in existing service. 
 
Control arm 
 
The control group will receive routine services provided by KWH and TYH, 
i.e., they will be provided with information and videos about all the essential 
information for expectant parents via a smartphone app. They can be enrolled to 
nurse-led face-to-face antenatal classes, although 39% of first-time mothers 
previously reported that they were unable to join the face-to-face antenatal classes 
due to the limited seats available.7 For those who are not offered a place for the 
antenatal classes, they will not have the opportunity to ask questions about their 
pregnancy until their antenatal visits.  
 
Follow up survey 
 
Participants will be contacted for the follow-up survey around four weeks 
after childbirth via their preferred contact method indicated in the baseline survey.  
 

 
 
 14 
Measurements 
Specific outcome indicators and the target respondents are listed both in Table 2 
and as follows: 
 
Primary outcome:  
 
Symptoms of Maternal Pregnancy depression and PND at four weeks 
postpartum will be assessed with the validated Chinese version of the 10-item 
Edinburgh Postnatal Depression Scale (EPDS).22 
 
Secondary outcomes:  
 
Perceived social support levels of expectant mothers will be assessed with 
the Chinese version of the 12-item Multidimensional Scale of Perceived Social 
Support (MSPSS). 23 
 
Anxiety and stress levels of all participants (including the expectant mother, 
father, and grandparents) will be assessed with the Anxiety and Stress subscales of 
the Chinese version of the Depression Anxiety Stress Scale (DASS21). 24 
 
Health-related quality of life (QoL) of all participants will be measured with 
the validated Chinese version of the Short-form-12 Health survey (SF-12 v2),25 
which consists of 12 items to be computed as two composite scores: physical 
component score and mental component score. 
 
Perceived family cohesion levels of all participants will be assessed using 
the nine-item Family Cohesion subscale of the Chinese version of the Family 
Environment Scale.26 Sample questions include: “Family members really help and 
support one another”, “We put a lot of energy into what we do at home”, and “We 
often seem to be killing time at home”. Each item is rated on a 6-point scale, 
ranging from 1 = strongly agree to 6 =strongly disagree. The scale showed 
adequate reliability and validity in a previous study in a Chinese sample.27 
 
Covariates 

 
 
 15 
 
Demographic information including age, education level, marital status, 
family monthly income adjusted for household size, number of children, and 
family living arrangement will be collected. 
Service utilisation: App users’ feedback and engagement data will be 
obtained via: 1) participants’ self-reported usage of the app and 2) the app itself 
which will capture users’ usage of the app, in terms of frequencies and duration of 
access. For all participants, information about their utilisation of services, such as 
participation in face-to-face antenatal classes, usage of other similar app and 
resources on pregnancy care, etc. will be collected via the self-report 
questionnaire.  
 
Ethical consideration 
 
Approval for the ethics of this study has been obtained from the institutional 
review boards of the respective institutions. Participation in the study will be 
completely voluntary. Participants will be reminded that they have the right to 
terminate their participation at any time during the study, and this will not affect 
the standard of care they receive at the hospital. All personally identifiable 
information will be removed before data analysis.  In this study, we will obtain 
information about participants’ symptoms of pregnancy depression and PND via 
the self-reported EPDS at baseline and follow-up. For mothers whose EPDS score 
is equal to or higher than the cut-off score of 10, we will encourage them to seek 
help from health and social services. All mothers will receive regular health 
services and treatments in the hospital as usual. The only difference between the 
intervention groups and the others will be the use of the mother-only mHealth 
intervention app or the family-based mHealth intervention app. We will remind 
mothers that there are relevant services (e.g., the Comprehensive Child 
Development Service) in the routine hospital care that they can approach when in 
need. 

 
 
 16 
 
 
 
 
(vi) Results analysis       
 
 
With regards to Objective (i), we will conduct descriptive analyses to obtain 
the usage and the coverage of the intervention.  
 
 
To fulfil Objectives (ii) and (iii), we will conduct general linear model 
(GLM) to analyse the data. In each GLM, we will use one outcome indicator 
measured in the follow-up survey as the dependent variable, the corresponding 
outcome indicator in the baseline survey as the covariate, and the group (family-
based mHealth intervention, mother-only mHealth intervention, control [referent 
group]) as independent variable. We will also conduct sub-group analyses to 
explore whether the effectiveness of the family-based intervention is affected by 
various demographic or family factors. 
 
 
All statistical analyses will be conducted with the intention-to-treat principle. 
All missing data will be treated with multiple imputation method or full 
information maximum likelihood depending on the analysis model. Nonetheless, 
analysis will be performed to compare any baseline differences between dropouts 
and retained participants. The baseline difference will also be examined by 
descriptive statistics. SPSS 20.0 will be used, and two-tailed p-values < .05 will be 
regarded as statistical significance. 
 
 
 
 
 
      
 
Impact and Sustainability: 
 
 
 
This proposed project entails the development and evaluation of a family-based 
mHealth intervention programme for families with pregnant women to promote 
family health. The evaluated intervention will be the first attempt to provide 
pregnancy support to expectant mothers using a family approach, by engaging and 

 
 
 17 
educating expectant mothers, fathers, and grandparents, with a low-cost, user-
friendly smartphone app. Importantly, the app comes in three versions that involve 
a continuously accessible, constraint-free platform for different family members to 
receive all the essential information about how to better support expectant mothers 
during and after pregnancy, and for members to build strong family cohesion. 
 
Compared with traditional pregnancy support services, our new family-
based mHealth intervention programme is believed to be a more effective way to 
reach out to a larger population and engage family members to provide proper 
pregnancy support to expectant women and to maintain a good relationship among 
family members. With less manpower required for the smartphone app than 
traditional face-to-face training, the former could provide longer-term support at 
lower costs. The non-face-to-face basis of the app may also encourage those 
parents and grandparents who are too shy to ask questions to discuss their issues 
with health professionals via the platform provided by the app. 
 
Our mHealth intervention requires minimal manpower: a few IT staff for app 
maintenance and a few medical or health professionals to occasionally answer 
questions. Due to its low running cost, it has the potential to be promoted as a 
routine practice for every family with an expectant mother. We believe that the 
mHealth intervention will shed light favouring the reform of pregnancy support 
services. 
 
 
 
 
 
 
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