JOURNAL ARTICLE
Smoking cessation in pregnancy: exploring service users' lived experiences.
Published In: British Journal of Midwifery, 2025, v. 33, n. 7. P. 382 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Allison, Seamus; Akbar, M Bilal; Allison, Claire; Padley, Karla 3 of 3
Abstract
Background/Aims: Sherwood Forest Hospitals NHS Foundation Trust established a specialist tobacco dependency team to run an in-house opt-out smoking cessation service supported by an incentive scheme. This study's aim was to understand service-users' perceptions of engaging with the team during the intervention. Methods: Semi-structured interviews were conducted with a convenience sample of 13 pregnant people who had achieved a smoke-free birth following attendance at the service. The data were analysed inductively through thematic analysis. Results: The participants reported strong emotional responses to the team. Non-judgemental support helped reduce barriers, minimise stigma and enhance their ability to achieve a smoke-free birth. Concern for the baby's health was a key motivation to quit smoking. Conclusions: This study reports rich insights into service-users' lived experiences of smoking cessation while pregnant. Such insights are useful for service design, clinician training and the design of smoking-cessation messages. Implications for practice: Using a non-judgemental behaviour change approach will reduce barriers of perceived shame and stigma to increase engagement with tobacco dependence treatment services. Healthcare professionals should not assume that people are fully aware of the dangers of tobacco use. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:British Journal of Midwifery. 2025/07, Vol. 33, Issue 7, p382
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2025
- ISSN:0969-4900
- DOI:10.12968/bjom.2024.0115
- Accession Number:186250892
- Copyright Statement:Copyright of British Journal of Midwifery is the property of Mark Allen Holdings Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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