Pregnancy RelatedNCT05099900
Exploration of Women's Experiences and Technology Usage Before, During, and After Pregnancy in Singapore
An observational study of Pregnancy Related, run by National University of Singapore at 2 sites in Singapore.
Trial 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. Read more about this study
- Who is it for?
- Ages 21 to 45 years, women onlyHealthy volunteers can take part
- Conditions the study is for
- Pregnancy Related
- How many people
- 60 participants
- Where
- 2 sitesSingapore
- Study dates
- 8 Nov 2021to 8 Nov 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 21 to 45 years
- Women only
- Healthy volunteers accepted
- Adult
Study population: 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).
Who may be able to join
- 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).
Who cannot join
- 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.
Trial locations and contacts
2 sites in 1 country.
Singapore2 sites, 2 recruiting
- Recruiting
The N.1 Institute for Health (N.1), NUS, Singapore
Singapore, 117456
Xavier Tadeo, PhD, lsixtc@nus.edu.sg
Yoong Hun Ong, MSc, yoong@nus.edu.sg
- Not yet recruiting
National University Hospital
Singapore, 119074
Delicia Shu Qin Ooi, PhD, paeosqd@nus.edu.sg
Maria Catherine Dado Celes, obgcmcd@nus.edu.sg
About this study
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.
Read the 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.
- Conditions
- Pregnancy Related
- Keywords
- User experience, Technology usage, Qualitative study, Digital health, Obesity, Gestational Weight, Gestational Diabetes Mellitus
- Medical subject headings
- Obesity, Diabetes, Gestational
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Pre-pregnancy | Not described | |
| During pregnancy | Not described | |
| Post-pregnancy | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Oct 2021
- Study start8 Nov 2021
- Primary completion8 May 2022 (estimated)
- Study completion8 Nov 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (16)Papers the sponsor has linked to this study.
- Other trials for Pregnancy RelatedStudies of the same condition, open and under way.
- More trials run by National University of SingaporeThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Cross-sectional
- Enrolment
- 60 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National University of Singapore
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Prof. Dean Ho, National University of Singapore
- Investigators
- Dean Ho, Prof, Principal investigator, National University of Singapore
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05099900
- Sponsor's protocol ID
- 2021/00034
- Status last verified
- Nov 2021
- First submitted
- 15 Sep 2021
- Last updated
- 10 Nov 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
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.
PubMed 22548595Frederick 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.
PubMed 17713848Goldstein 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.
PubMed 28586887He 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.
PubMed 31409285Heslehurst 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.
PubMed 31185012Hung 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.
PubMed 27590385International 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.
PubMed 28724518Gaillard 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.
PubMed 27855382Lindlof TR, Taylor BC. Sensemaking: Qualitative data analysis and interpretation. Qualitative communication research methods. 2011;3(1):241-81.
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.
PubMed 28903892Sanchez 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.
PubMed 29164765Singapore Department of Statistics. (2010). Census of Population 2010. Retrieved from: http:// www.singstat.gov.sg/publications/publications-and-papers/population/census10_admin
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.
PubMed 19055539Voerman 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.
PubMed 30742624Wang 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.
PubMed 31452666
Study at a glance
From the registry record, last updated by the sponsor on 10 Nov 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Exploration of Women's Experiences and Technology Usage Before, During, and After Pregnancy in Singapore
- ClinicalTrials.gov ID
- NCT05099900
- Acronym / sponsor ID
- 2021/00034
- Conditions
- Pregnancy Related
- Keywords
- User experience, Technology usage, Qualitative study, Digital health, Obesity, Gestational Weight, Gestational Diabetes Mellitus
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 60 participants (estimated)
- Lead sponsor
- National University of SingaporeUniversity, hospital or other
- Study start
- 8 Nov 2021 (actual)
- Primary completion
- 8 May 2022 (estimated)
- Study completion
- 8 Nov 2022 (estimated)
- First posted
- 29 Oct 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Other
- Time perspective
- Cross-sectional
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Pre-pregnancy | – | – |
| During pregnancy | – | – |
| Post-pregnancy | – | – |
Who may qualify
- Ages
- 21 to 45 years
- Sex
- Female only
- Healthy volunteers
- Accepted
- Age groups
- Adult
- Study population
- 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).
Key inclusion criteria (3 listed)
- 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).
Key exclusion criteria (5 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Experiences and technology usage among women
Time frame: 1 year
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.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Nov 2021.
- Background: PubMed 22548595Evans 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.
- Background: PubMed 17713848Frederick 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.
- Background: PubMed 28586887Goldstein 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.
- Background: PubMed 31409285He 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.
- Background: PubMed 31185012Heslehurst 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.
- Background: PubMed 27590385Hung 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.
- Background: PubMed 28724518International 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.
- Background: PubMed 27855382Gaillard 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.
- BackgroundLindlof TR, Taylor BC. Sensemaking: Qualitative data analysis and interpretation. Qualitative communication research methods. 2011;3(1):241-81.
- Background: PubMed 28903892Redman 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.
- Background: PubMed 29164765Sanchez 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.
- BackgroundSingapore Department of Statistics. (2010). Census of Population 2010. Retrieved from: http:// www.singstat.gov.sg/publications/publications-and-papers/population/census10_admin
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Dean Ho, Prof principal investigator
National University of Singapore
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pregnancy Related, run by National University of Singapore at 2 sites in Singapore.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 10 Nov 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Singapore. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Xavier Tadeo, PhD (+65 66017766, lsixtc@nus.edu.sg), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Experiences and technology usage among women (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05099900, which also lists 16 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 Nov 2021.