Exploration of Women's Experiences and Technology Usage Before, During, and After Pregnancy in Singapore
1 other identifier
observational
60
1 country
2
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P25-P50 for all trials
Started Nov 2021
Shorter than P25 for all trials
2 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
September 15, 2021
CompletedFirst Posted
Study publicly available on registry
October 29, 2021
CompletedStudy Start
First participant enrolled
November 8, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
May 8, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
November 8, 2022
CompletedNovember 10, 2021
November 1, 2021
6 months
September 15, 2021
November 8, 2021
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Experiences and technology usage among women
We 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.
1 year
Study Arms (3)
Pre-pregnancy
During pregnancy
Post-pregnancy
Eligibility Criteria
Women who are 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).
You may qualify if:
- 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).
You may not qualify if:
- 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.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (2)
The N.1 Institute for Health (N.1), NUS, Singapore
Singapore, 117456, Singapore
National University Hospital
Singapore, 119074, Singapore
Related Publications (16)
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.
PMID: 22548595BACKGROUNDFrederick 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.
PMID: 17713848BACKGROUNDGoldstein 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.
PMID: 28586887BACKGROUNDHe 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.
PMID: 31409285BACKGROUNDHeslehurst 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.
PMID: 31185012BACKGROUNDHung 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.
PMID: 27590385BACKGROUNDInternational 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.
PMID: 28724518BACKGROUNDGaillard 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.
PMID: 27855382BACKGROUNDLindlof TR, Taylor BC. Sensemaking: Qualitative data analysis and interpretation. Qualitative communication research methods. 2011;3(1):241-81.
BACKGROUNDRedman 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.
PMID: 28903892BACKGROUNDSanchez 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.
PMID: 29164765BACKGROUNDSingapore Department of Statistics. (2010). Census of Population 2010. Retrieved from: http:// www.singstat.gov.sg/publications/publications-and-papers/population/census10_admin
BACKGROUNDTorloni 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.
PMID: 19055539BACKGROUNDVoerman 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.
PMID: 30742624BACKGROUNDWang 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.
PMID: 31452666BACKGROUNDNg 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.
PMID: 39352732DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Dean Ho, Prof
National University of Singapore
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- OTHER
- Time Perspective
- CROSS SECTIONAL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor
Study Record Dates
First Submitted
September 15, 2021
First Posted
October 29, 2021
Study Start
November 8, 2021
Primary Completion
May 8, 2022
Study Completion
November 8, 2022
Last Updated
November 10, 2021
Record last verified: 2021-11
Data Sharing
- IPD Sharing
- Will not share