Addressing Pregnant Women's First Trimester Worries and Information Needs With mHealth Solutions

Exploring the Anxieties and Health Information Needs of Women in the First Trimester to Inform mHealth Solutions for Antenatal Care

The first 12 weeks of pregnancy, known as the first trimester, can be one of the most worrying times for women. (Where this lay summary refers to women, it should be taken to include people who do not identify as women but who have the capacity to become pregnant). Many experience nausea, bleeding, or anxiety about whether the pregnancy is progressing normally. Despite this, most women do not see a midwife or doctor until around 10 weeks into the pregnancy. This leaves a gap where they may have important questions but little professional support. As a result, many turn to mobile phone applications or the internet to find answers - but the quality of information online is mixed, and it can be confusing or even unsafe.

This research aims to understand what support women really need in early pregnancy, what concerns they have, and whether a mobile health application (mHealth app) could help fill this gap in current pregnancy care in a safe and personalised way. The study will also ask healthcare professionals and digital health experts what such an application should include, and how it can be made accessible, and easy to understand for all women - including those with different levels of health knowledge and digital skills.

To carry out the research, we will use a combination of online surveys and interviews. Women who are currently pregnant or have had a baby in the last two years will be invited to take part, along with healthcare professionals such as midwives and doctors, and experts in digital health. The survey will ask about their experiences in early pregnancy, how they have used digital tools or apps, and whether they felt their questions were answered before their first NHS appointment. The interview stage will allow participants to talk in more depth about what support they wanted and what would have helped them most. All participants will receive information about support services because we realise that discussing unmet information needs or worries in early pregnancy may be upsetting for some women.

The views collected will inform the design of a new mobile application to support women during early pregnancy. The application will use artificial intelligence (AI) to personalise information based on each woman's needs and background, and to explain things clearly and simply. The content and design of the application will be reviewed by doctors and digital health specialists to make sure it is safe, accurate, and easy to use.

Public and patient involvement is central to this project. A diverse group of women and representatives from grassroots organisations will be invited to shape the questions we ask, review the design of the application, and help us make it inclusive for people from different backgrounds.

This research will help us create a practical, trustworthy, and inclusive tool to support women during one of the most vulnerable times in pregnancy when women don't usually see a doctor. If successful, it could be used widely across the NHS to help reduce anxiety, improve understanding, and ensure women get the right support earlier in their pregnancy with the long-term aim of improving outcomes for women, babies, and families across the UK.

Study Overview

• Status: Not yet recruiting
• Conditions: Anxiety; Health Knowledge, Attitudes, Practice; Antenatal Care; Mobile Application; Patient Education as Topic; mHealth Application; Worries; Pregnancy Trimester, First

• Study Type: Observational
• Enrollment (Estimated): 1450

Contacts and Locations

• Study Contact: Name: Stephanie Gorgievska, MBBS BSc MRCOG; Phone Number: 00442037334385; Email: sgorgievska@bournemouth.ac.uk

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

The study will draw participants from three cohorts, all based in the United Kingdom:

First-Trimester Women:

Pregnant women or those who have given birth within the past two years, who present for care at one of two single-centre sites-The Lister Hospital (London) and Chelsea and Westminster Hospital NHS Foundation Trust-either following IVF confirmation, during pregnancy scans, routine antenatal visits, or via posters/leaflets in these clinics. The secure online Qualtrics survey will be advertised using social-media campaigns and partnerships with national pregnancy support charities and organisations.

Healthcare Professionals:

Will be recruited via email invitations sent through professional organisations' distribution lists

Digital-Health Experts:

Will be recruited through academic networks, industry contacts and professional organisations' distribution lists.

Description

Pregnant women

Inclusion criteria

• To ensure that participants have the first trimester of pregnancy fresh in their minds the sample will include women that are currently pregnant or have had a child within the last 2 years
• Living in the UK
• Over the age of 18
• Able to give informed consent Exclusion criteria
• Evidence of/diagnosis of cognitive impairment

Healthcare professionals

Inclusion criteria

- Belonging to one of the following professional groups i.e. healthcare professionals involved in the care of pregnant women

• Doctor in obstetrics and gynaecology
• Midwives
• Nurses (within the field of obstetrics and gynaecology),
• Sonographers that scan pregnant women
• General practitioners
• Psychologists (that work with pregnant women)
• Physiotherapists (that work with pregnant women)
• Living in the UK
• Over the age of 18
• Able to give informed consent Exclusion criteria
• Evidence of/diagnosis of cognitive impairment

Digital Health Experts

Inclusion criteria

• Professionals with at least 3 year's experience in digital health, health informatics or mobile health application development
• Based in the United Kingdom Exclusion criteria
• Evidence of/diagnosis of cognitive impairment

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort
Pregnant women; Currently pregnant women, women who have had a child or have been pregnant in the last 2 years
Healthcare Professionals; Healthcare Professionals involved in the care of pregnant women
Digital Health Experts; Professionals with a least 3 years experience in digital health, health informatics or mobile health application development

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Levels of Self-Reported Anxiety in the First Trimester (Quantitative Survey Data)	Measured using a single-item 5-point Likert scale (1 = not anxious at all, 5 = extremely anxious). Outcomes will be reported as the proportion of participants selecting each response category (1 through 5).	Day 1
Themes of Anxiety During the First Trimester (Qualitative Survey Data)	Free-text responses in the survey describing anxieties/worries will be coded and analysed thematically using NVivo. Outcomes will be reported as a list of key themes.	Day 1
Themes of Anxiety During the First Trimester (Interview Data)	Semi-structured interview transcripts will be thematically analysed in NVivo to identify common sources of anxiety in the first trimester. Outcome reported as major and minor themes.	Day 1
Information Needs During the First Trimester (Survey responses)	Measured by 8 multiple-choice and Likert-scale survey items assessing participants' perceived gaps in information during the first trimester, preferred information sources, and level of trust in sources they currently use. Outcomes will be reported as the proportion of participants selecting each response option, with summary statistics for each category.	Day 1
Information Needs During the First Trimester (Interview Data)	Interview responses regarding informational gaps will be analysed thematically using NVivo. Outcomes reported as a list of core unmet information needs.	Day 1

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
mHealth Applications Perspectives and Feature Preferences from a Healthcare Professional Perspective (Qualitative survey data)	Survey responses from healthcare professionals will include Likert-scale and multiple-choice items on the use and perceived value of mobile health tools in early pregnancy. Likert items use a 5-point scale (1 = strongly disagree, 5 = strongly agree). Outcomes will be reported as the proportion of participants selecting each response option, and the mean and standard deviation for each Likert item	Day 1
mHealth Application Content Preferences and Perceived Gaps from a Healthcare Professional perspective (Quantitative Survey Data)	Survey responses from healthcare professionals will include open-ended questions regarding ideal application content for the first trimester of pregnancy and perceived gaps in current digital health resources. Free-text responses will be thematically analysed.	Day 1
Key Themes from Healthcare Professionals on Design, Implementation, and AI Use in Pregnancy mHealth Tools (Interview Data)	Semi-structured interviews with healthcare professionals will explore three domains: 1) desired features and functions of a first trimester pregnancy app, 2) perceived clinical, ethical, technical, and organisational barriers and facilitators to its implementation, and 3) attitudes toward the integration of artificial intelligence (AI) into digital health tools for early pregnancy support. Interview transcripts will be analysed thematically using NVivo.	Day 1
mHealth Applications Perspectives and Feature Preferences from a Digital Health Expert Perspective (Quantitative survey data)	Survey responses from digital health experts will include Likert-scale and multiple-choice items on the design, usage, and perceived utility of digital tools in pregnancy. Likert items will use a 5-point scale (1 = strongly disagree, 5 = strongly agree).Outcomes will be reported as the proportion of participants selecting each response option and mean and standard deviation for each Likert item.	Day 1
Feature Preferences and Content Gaps in current mHealth tools from a Digital Health expert perspective (Qualititative survey data)	Survey responses from digital health experts will include open-ended questions about ideal features, perceived gaps in current tools, and suggestions for app content. Free-text responses will be thematically using NVivo. Outcomes will be reported as a list of key themes.	Day 1
Key Themes from Digital Health Experts on App Design, Implementation, and AI Use in Pregnancy mHealth Applications (Interview Data)	Semi-structured interviews with digital health experts will explore three key areas: 1) desired design and content features for a first trimester pregnancy app, 2) perceived logistical, technical, or policy-related barriers and facilitators to implementation, and 3) attitudes toward the integration of artificial intelligence (AI) in digital pregnancy tools. Interview transcripts will be thematically analysed using NVivo. Outcomes will be reported as a list of key themes	Day 1

Collaborators and Investigators

• Sponsor: Bournemouth University
• Collaborators: Chelsea and Westminster NHS Foundation Trust; Kendall Healthcare Group, Ltd.

Study record dates

Study Major Dates

• Study Start (Estimated): September 1, 2025
• Primary Completion (Estimated): March 1, 2026
• Study Completion (Estimated): October 1, 2027

Study Registration Dates

• First Submitted: July 17, 2025
• First Submitted That Met QC Criteria: August 6, 2025
• First Posted (Actual): August 11, 2025

Study Record Updates

• Last Update Posted (Actual): August 14, 2025
• Last Update Submitted That Met QC Criteria: August 11, 2025
• Last Verified: July 1, 2025

More Information

Terms related to this study

• Keywords: Health Literacy; Observational Study; Digital Health; Interview; Surveys and Questionnaires; Pregnant People; User Centered Design
• Additional Relevant MeSH Terms: Mental Disorders; Anxiety Disorders
• Other Study ID Numbers: 14945

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No