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

NCT ID: NCT05099900

Last Updated: 2021-11-10

Study Results

Results pending

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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Recruitment Status

UNKNOWN

Total Enrollment

60 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-11-08

Study Completion Date

2022-11-08

Brief Summary

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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

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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.

Conditions

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Pregnancy Related

Keywords

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

Study Design

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Observational Model Type

OTHER

Study Time Perspective

CROSS_SECTIONAL

Study Groups

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Pre-pregnancy

No interventions assigned to this group

During pregnancy

No interventions assigned to this group

Post-pregnancy

No interventions assigned to this group

Eligibility Criteria

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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.
Minimum Eligible Age

21 Years

Maximum Eligible Age

45 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

Yes

Sponsors

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National University of Singapore

OTHER

Sponsor Role lead

Responsible Party

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Prof. Dean Ho

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Dean Ho, Prof

Role: PRINCIPAL_INVESTIGATOR

National University of Singapore

Locations

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The N.1 Institute for Health (N.1), NUS, Singapore

Singapore, , Singapore

Site Status RECRUITING

National University Hospital

Singapore, , Singapore

Site Status NOT_YET_RECRUITING

Countries

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Singapore

Central Contacts

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Xavier Tadeo, PhD

Role: CONTACT

Phone: +65 66017766

Email: [email protected]

Yoong Hun Ong, MSc

Role: CONTACT

Phone: +65 66017766

Email: [email protected]

Facility Contacts

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Xavier Tadeo, PhD

Role: primary

Yoong Hun Ong, MSc

Role: backup

Delicia Shu Qin Ooi, PhD

Role: primary

Maria Catherine Dado Celes

Role: backup

References

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Evans WD, Abroms LC, Poropatich R, Nielsen PE, Wallace JL. Mobile health evaluation methods: the Text4baby case study. J Health Commun. 2012;17 Suppl 1:22-9. doi: 10.1080/10810730.2011.649157.

Reference Type BACKGROUND
PMID: 22548595 (View on PubMed)

Frederick IO, Williams MA, Sales AE, Martin DP, Killien M. Pre-pregnancy body mass index, gestational weight gain, and other maternal characteristics in relation to infant birth weight. Matern Child Health J. 2008 Sep;12(5):557-67. doi: 10.1007/s10995-007-0276-2. Epub 2007 Aug 23.

Reference Type BACKGROUND
PMID: 17713848 (View on PubMed)

Goldstein RF, Abell SK, Ranasinha S, Misso M, Boyle JA, Black MH, Li N, Hu G, Corrado F, Rode L, Kim YJ, Haugen M, Song WO, Kim MH, Bogaerts A, Devlieger R, Chung JH, Teede HJ. Association of Gestational Weight Gain With Maternal and Infant Outcomes: A Systematic Review and Meta-analysis. JAMA. 2017 Jun 6;317(21):2207-2225. doi: 10.1001/jama.2017.3635.

Reference Type BACKGROUND
PMID: 28586887 (View on PubMed)

He S, Allen JC, Razali NS, Win NM, Zhang JJ, Ng MJ, Yeo GSH, Chern BSM, Tan KH. Are women in Singapore gaining weight appropriately during pregnancy: a prospective cohort study. BMC Pregnancy Childbirth. 2019 Aug 13;19(1):290. doi: 10.1186/s12884-019-2443-z.

Reference Type BACKGROUND
PMID: 31409285 (View on PubMed)

Heslehurst N, Vieira R, Akhter Z, Bailey H, Slack E, Ngongalah L, Pemu A, Rankin J. The association between maternal body mass index and child obesity: A systematic review and meta-analysis. PLoS Med. 2019 Jun 11;16(6):e1002817. doi: 10.1371/journal.pmed.1002817. eCollection 2019 Jun.

Reference Type BACKGROUND
PMID: 31185012 (View on PubMed)

Hung TH, Hsieh TT. Pregestational body mass index, gestational weight gain, and risks for adverse pregnancy outcomes among Taiwanese women: A retrospective cohort study. Taiwan J Obstet Gynecol. 2016 Aug;55(4):575-81. doi: 10.1016/j.tjog.2016.06.016.

Reference Type BACKGROUND
PMID: 27590385 (View on PubMed)

International Weight Management in Pregnancy (i-WIP) Collaborative Group. Effect of diet and physical activity based interventions in pregnancy on gestational weight gain and pregnancy outcomes: meta-analysis of individual participant data from randomised trials. BMJ. 2017 Jul 19;358:j3119. doi: 10.1136/bmj.j3119.

Reference Type BACKGROUND
PMID: 28724518 (View on PubMed)

Gaillard R, Santos S, Duijts L, Felix JF. Childhood Health Consequences of Maternal Obesity during Pregnancy: A Narrative Review. Ann Nutr Metab. 2016;69(3-4):171-180. doi: 10.1159/000453077. Epub 2016 Nov 18.

Reference Type BACKGROUND
PMID: 27855382 (View on PubMed)

Lindlof TR, Taylor BC. Sensemaking: Qualitative data analysis and interpretation. Qualitative communication research methods. 2011;3(1):241-81.

Reference Type BACKGROUND

Redman LM, Gilmore LA, Breaux J, Thomas DM, Elkind-Hirsch K, Stewart T, Hsia DS, Burton J, Apolzan JW, Cain LE, Altazan AD, Ragusa S, Brady H, Davis A, Tilford JM, Sutton EF, Martin CK. Effectiveness of SmartMoms, a Novel eHealth Intervention for Management of Gestational Weight Gain: Randomized Controlled Pilot Trial. JMIR Mhealth Uhealth. 2017 Sep 13;5(9):e133. doi: 10.2196/mhealth.8228.

Reference Type BACKGROUND
PMID: 28903892 (View on PubMed)

Sanchez CE, Barry C, Sabhlok A, Russell K, Majors A, Kollins SH, Fuemmeler BF. Maternal pre-pregnancy obesity and child neurodevelopmental outcomes: a meta-analysis. Obes Rev. 2018 Apr;19(4):464-484. doi: 10.1111/obr.12643. Epub 2017 Nov 22.

Reference Type BACKGROUND
PMID: 29164765 (View on PubMed)

Singapore Department of Statistics. (2010). Census of Population 2010. Retrieved from: http:// www.singstat.gov.sg/publications/publications-and-papers/population/census10_admin

Reference Type BACKGROUND

Torloni MR, Betran AP, Horta BL, Nakamura MU, Atallah AN, Moron AF, Valente O. Prepregnancy BMI and the risk of gestational diabetes: a systematic review of the literature with meta-analysis. Obes Rev. 2009 Mar;10(2):194-203. doi: 10.1111/j.1467-789X.2008.00541.x. Epub 2008 Nov 24.

Reference Type BACKGROUND
PMID: 19055539 (View on PubMed)

Voerman E, Santos S, Patro Golab B, Amiano P, Ballester F, Barros H, Bergstrom A, Charles MA, Chatzi L, Chevrier C, Chrousos GP, Corpeleijn E, Costet N, Crozier S, Devereux G, Eggesbo M, Ekstrom S, Fantini MP, Farchi S, Forastiere F, Georgiu V, Godfrey KM, Gori D, Grote V, Hanke W, Hertz-Picciotto I, Heude B, Hryhorczuk D, Huang RC, Inskip H, Iszatt N, Karvonen AM, Kenny LC, Koletzko B, Kupers LK, Lagstrom H, Lehmann I, Magnus P, Majewska R, Makela J, Manios Y, McAuliffe FM, McDonald SW, Mehegan J, Mommers M, Morgen CS, Mori TA, Moschonis G, Murray D, Chaoimh CN, Nohr EA, Nybo Andersen AM, Oken E, Oostvogels AJJM, Pac A, Papadopoulou E, Pekkanen J, Pizzi C, Polanska K, Porta D, Richiardi L, Rifas-Shiman SL, Ronfani L, Santos AC, Standl M, Stoltenberg C, Thiering E, Thijs C, Torrent M, Tough SC, Trnovec T, Turner S, van Rossem L, von Berg A, Vrijheid M, Vrijkotte TGM, West J, Wijga A, Wright J, Zvinchuk O, Sorensen TIA, Lawlor DA, Gaillard R, Jaddoe VWV. Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood: An individual participant data meta-analysis. PLoS Med. 2019 Feb 11;16(2):e1002744. doi: 10.1371/journal.pmed.1002744. eCollection 2019 Feb.

Reference Type BACKGROUND
PMID: 30742624 (View on PubMed)

Wang X, Zhang X, Zhou M, Juan J, Wang X. Association of prepregnancy body mass index, rate of gestational weight gain with pregnancy outcomes in Chinese urban women. Nutr Metab (Lond). 2019 Aug 19;16:54. doi: 10.1186/s12986-019-0386-z. eCollection 2019.

Reference Type BACKGROUND
PMID: 31452666 (View on PubMed)

Ng WY, Lau NY, Lee VV, Vijayakumar S, Leong QY, Ooi SQD, Su LL, Lee YS, Chan SY, Blasiak A, Ho D. Shaping Adoption and Sustained Use Across the Maternal Journey: Qualitative Study on Perceived Usability and Credibility in Digital Health Tools. JMIR Hum Factors. 2024 Oct 1;11:e59269. doi: 10.2196/59269.

Reference Type DERIVED
PMID: 39352732 (View on PubMed)

Other Identifiers

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2021/00034

Identifier Type: -

Identifier Source: org_study_id