Evidence map›Paper›PMID 42584822›Full record

ReviewJournal of prevention (2022)2026

Intervention Models and Behaviour Change Techniques to Reduce the Risk of Alcohol Exposed Pregnancies: A Systematic Review of Interventions for Non-pregnant Women.

Oluwakemi Akagwu, Rohan Shah, Charis Chi Yun Ng, Jo Armes, Lesley Smith, Afrodita Marcu, Anand Ahankari

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of prevention (2022), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Oluwakemi AkagwuSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, England. o.akagwu@surrey.ac.uk.ORCID http://orcid.org/0009-0001-2796-6046
Rohan ShahHarvard T.H. Chan School of Public Health - India Research Centre, Mumbai, India.
Charis Chi Yun NgSchool of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, England.
Jo ArmesSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, England.
Lesley SmithDepartment of Nursing and Midwifery, Faculty of Health Sciences, University of Hull, Hull, England.
Afrodita MarcuSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, England.
Anand AhankariSchool of Nursing and Public Health, Faculty of Health, Psychology and Social Care, Manchester Metropolitan University, Manchester, England. A.Ahankari@mmu.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Trials of behavioural interventions aimed at preventing an Alcohol-Exposed Pregnancy (AEP) before conception report variable effectiveness. Understanding which intervention components, such as Behaviour Change Techniques (BCTs), are effective is essential when adapting for real-world implementation. This review describes the intervention models, the BCTs utilised, and the BCT combinations in effective interventions. An earlier systematic review of studies published from 1970 to 2018 was updated using the same search strategy to identify additional articles published subsequently. Searches were conducted on CINAHL, PsycINFO, Embase and PubMed to identify studies published between 2019 and 2025. Eligible study designs were randomised controlled trials (RCTs), non-randomised comparative studies, cohort studies and before-and-after studies. Studies were included if they were in English, included non-pregnant women of reproductive age or their social networks and aimed to prevent AEP. Outcomes reviewed were measures of knowledge of guidelines and attitudes towards alcohol consumption in pregnancy or when planning a pregnancy, changes in alcohol consumption and changes in behaviours to prevent unplanned pregnancies, such as effective contraception use at every sexual encounter that could lead to pregnancy. Narrative synthesis was used to describe intervention models and annotate BCTs guided by the BCT Ontology (BCTO) and alcohol-specific taxonomy. Risk of bias was assessed using the ROB 2 tool and the Modified Downs and Black Checklist. Twenty-five studies, comprising 18 studies from the previous systematic review and seven published between 2019 and 2025, were identified with 6,020 participants. Three intervention models were identified: (i) alcohol-only educational, (ii) alcohol-only screening and brief interventions (SBIs), and (iii) dual-focused (alcohol and contraception) interventions. Models included single- and multiple-session interventions, which were delivered face-to-face, remotely or digitally. Fifty-one BCTs were coded across all studies. Within the alcohol-only SBIs and dual-focused (alcohol and contraception) models, multi-session interventions generally demonstrated greater effects in intervention groups than controls and utilised more BCTs from the goal-directed and monitoring BCTO groups compared to single-session interventions. These findings deepen our understanding of why some interventions are more effective than others and suggest that tailored interactions with certain goal-directed and monitoring BCTs may enhance their effectiveness. Future research can explore greater incorporation of BCT combinations from these groups into single-session interventions and pathways to identify women who need more intense interventions for referral or support.

Indexed as

Alcohol exposed pregnanciesBehaviour change techniquesFoetal alcohol spectrum disorder (FASD)Harm reductionPreconceptionPrevention

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.