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Exploration of Women's Experiences and Technology Usage Before, During, and After Pregnancy in Singapore

Exploration of Women's Experiences and Technology Usage Before, During, and After Pregnancy in Singapore

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05099900
Enrollment
60
Registered
2021-10-29
Start date
2021-11-08
Completion date
2022-11-08
Last updated
2021-11-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Pregnancy Related

Keywords

User experience, Technology usage, Qualitative study, Digital health, Obesity, Gestational Weight, Gestational Diabetes Mellitus

Brief summary

This study seek to understand the motivations and contextual influences that can induce and sustain behaviour change to inform future interventions for women before, during and after pregnancy, through a qualitative interview-based assessment of 60 participants. As digital health intervention in pregnant women has been shown to be cost-effective and scalable, the current study also aims to understand women's usage of technology throughout the process of trying to conceive, being pregnant and being a new mother within the local Singapore context.

Detailed description

Maternal overweight and obesity is a growing public health concern in Singapore. A recent Singaporean prospective cohort study examined 724 pregnant women and reported that 26.2% of the women had a total gestational weight gain (GWG) which exceed the Institute of Medicine's (IOM) 2009 guidelines. When examined based on body mass index (BMI), overweight and obese women had significantly increased risk of gaining gestational weight above IOM recommendations, compared to normal weight women. Higher GWG have previously been linked to adverse maternal and infant outcomes including higher rates of gestational diabetes mellitus (GDM) and primary caesarean delivery, large for age (LGA) infant, macrosomia and increased risk of childhood overweight/obesity. Given the impact of maternal GWG on pregnancy and infant outcomes, there is a need for a targeted behavioural intervention. As effective health behaviour change requires early initiation and maintenance of change, women before, during and after pregnancy should be targeted. Furthermore, high pre-pregnancy BMI have been shown to be linked with increased risk of GDM and type 2 diabetes post-delivery, and higher infant birthweight, child obesity and atypical child neurodevelopment. Accordingly, this highlights the need for early behavioural intervention beginning with women trying to get pregnant. Current studies have focused predominantly on individual factors contributing to maternal obesity in relation to infant outcomes, both immediately postpartum and prospectively into early childhood. Based on Bronfenbrenner's ecological model, key contextual factors involving the micro-, meso-, exo-, macro- and chronosystem are important factors contributing to the efficacy of digital means on health behavioural change among pregnant women. From this theoretical orientation, understanding individual factors involving motivation and contextual influences is central to facilitating health behaviour change. Specifically, elucidating the proximal (e.g. peers, family) and distal factors (e.g. community, health services) embedded within specific cultural contexts ensure sustainability of behaviour change among pregnant women. As Singapore is a culturally diverse society, there is a need to understand the impact of cultural factors on maternal behaviours and decision making. Accordingly, the current study will consist of a qualitative assessment of 60 participants who will undergo semi-structured interviews with the aim to understand motivations and contextual influences that induce and sustain behaviour change, so as to inform future interventions for women before, during and after pregnancy. As digital health intervention in pregnant women has been shown to be cost-effective and scalable, the current study also aims to understand women's usage of technology throughout the process of trying to conceive, being pregnant and being a new mother within the local Singapore context.

Interventions

None listed

Sponsors

National University of Singapore
Lead SponsorOTHER

Study design

Observational model
OTHER
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
FEMALE
Age
21 Years to 45 Years
Healthy volunteers
Yes

Inclusion criteria

* English fluency; * Aged 21 years and above; * Actively trying to conceive (pre-pregnancy) or currently in first to third trimester of pregnancy (during pregnancy) or have a child aged 0-2 years (post-pregnancy).

Exclusion criteria

* Evidence/diagnosis of cognitive impairment (e.g. history of dementia, intellectual disability, traumatic brain injury); * Current diagnosis of psychiatric disorder (e.g. severe anxiety, depression, schizophrenia); * Significant hearing impairment; * Inability to complete the study at the judgement of the clinician investigators; * Women requiring or who had any form of assisted conception.

Design outcomes

Primary

MeasureTime frameDescription
Experiences and technology usage among women1 yearWe will conduct semi-structured interviews with women who are either trying to conceive, pregnant or have a child aged 0 to 2 years. The interviews seek to find out about the participants' pregnancy/maternal-related experiences including the challenges faced, lifestyle changes made, support systems and experience with the health system. Participants will also be asked about their previous and current experiences with technology usage, such as the type of technology used and the purposes of technology usage. Additionally, there will also be two questionnaires, conducted pre- and post-interview, on the participants' demographics and their opinions on technical aspects of digital platforms.

Countries

Singapore

Contacts

Primary ContactXavier Tadeo, PhD
lsixtc@nus.edu.sg+65 66017766
Backup ContactYoong Hun Ong, MSc
yoong@nus.edu.sg+65 66017766

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 5, 2026