Dataset Information

Effectiveness of Digital Interventions for Preventing Alcohol Consumption in Pregnancy: Systematic Review and Meta-analysis.

ABSTRACT:

Background

Alcohol consumption in pregnancy has been associated with serious fetal health risks and maternal complications. While previous systematic reviews of digital interventions during pregnancy have targeted smoking cessation and flu vaccine uptake, few studies have sought to evaluate their effectiveness in preventing alcohol consumption during pregnancy.

Objective

This systematic review aims to assess (1) whether digital interventions are effective in preventing alcohol consumption during the pregnancy/pregnancy-planning period, and (2) the differential effectiveness of alternative digital intervention platforms (ie, computers, mobiles, and text messaging services).

Methods

PubMed, Embase, CINAHL, and Web of Science were searched for studies with digital interventions aiming to prevent alcohol consumption among pregnant women or women planning to become pregnant. A random effects primary meta-analysis was conducted to estimate the combined effect size and extent to which different digital platforms were successful in preventing alcohol consumption in pregnancy.

Results

Six studies were identified and included in the final review. The primary meta-analysis produced a sample-weighted odds ratio (OR) of 0.62 (95% CI 0.42-0.91; P=.02) in favor of digital interventions decreasing the risk of alcohol consumption during pregnancy when compared to controls. Computer/internet-based interventions (OR 0.59, 95% CI 0.38-0.93) were an effective platform for preventing alcohol consumption. Too few studies of text messaging (OR 0.29, 95% CI 0.29-2.52) were available to draw a conclusion.

Conclusions

Overall, our review highlights the potential for digital interventions to prevent alcohol consumption among pregnant women and women planning to become pregnant. Considering the advantages of digital interventions in promoting healthy behavioral changes, future research is necessary to understand how certain platforms may increase user engagement and intervention effectiveness to prevent women from consuming alcohol during their pregnancies.

SUBMITTER: Oh SS

PROVIDER: S-EPMC9039809 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Publications

Effectiveness of Digital Interventions for Preventing Alcohol Consumption in Pregnancy: Systematic Review and Meta-analysis.

Oh Sarah Soyeon SS Moon Jong Youn JY Chon Doukyoung D Mita Carol C Lawrence Jourdyn A JA Park Eun-Cheol EC Kawachi Ichiro I

Journal of medical Internet research 20220411 4

<h4>Background</h4>Alcohol consumption in pregnancy has been associated with serious fetal health risks and maternal complications. While previous systematic reviews of digital interventions during pregnancy have targeted smoking cessation and flu vaccine uptake, few studies have sought to evaluate their effectiveness in preventing alcohol consumption during pregnancy.<h4>Objective</h4>This systematic review aims to assess (1) whether digital interventions are effective in preventing alcohol con ...[more]

PMID: 35404257

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Project description:BackgroundYoga is a popular mind-body medicine frequently recommended to pregnant women. Gaps remain in our understanding of the core components of effective pregnancy yoga programmes. This systematic review and meta-analysis examined the characteristics and effectiveness of pregnancy yoga interventions, incorporating the FITT (frequency, intensity, time/duration and type) principle of exercise prescription.MethodsNine electronic databases were searched: MEDLINE, PsycINFO, EMBASE, CINAHL, WHOLiS, AMED, ScieLo, ASSIA and Web of Science. Randomised control trials and quasi-experimental studies examining pregnancy yoga interventions were eligible. Covidence was used to screen titles, abstracts, and full-text articles. Outcomes of interest were stress, anxiety, depression, quality of life, labour duration, pain management in labour and mode of birth. The Cochrane Collaboration's Risk of Bias Assessment tool was used to assess methodological quality of studies and GRADE criteria (GRADEpro) evaluated quality of the evidence. Meta-analysis was performed using RevMan 5.3.ResultsOf 862 citations retrieved, 31 studies met inclusion criteria. Twenty-nine studies with 2217 pregnant women were included for meta-analysis. Pregnancy yoga interventions reduced anxiety (SMD: -0.91; 95% CI: - 1.49 to - 0.33; p = 0.002), depression (SMD: -0.47; 95% CI: - 0.9 to - 0.04, P = 0.03) and perceived stress (SMD: -1.03; 95% CI: - 1.55 to - 0.52; p < 0.001). Yoga interventions also reduced duration of labour (MD = - 117.75; 95% CI - 153.80 to - 81.71, p < 0.001) and, increased odds of normal vaginal birth (OR 2.58; 95% CI 1.46-4.56, p < 0.001) and tolerance for pain. The quality of evidence (GRADE criteria) was low to very low for all outcomes. Twelve or more yoga sessions delivered weekly/bi-weekly had a statistically significant impact on mode of birth, while 12 or more yoga sessions of long duration (> 60 min) had a statistically significant impact on perceived stress.ConclusionThe evidence highlights positive effects of pregnancy yoga on anxiety, depression, perceived stress, mode of birth and duration of labour.Systematic review registrationPROSPERO, CRD42019119916. Registered on 11th January 2019.

Project description:BackgroundPrenatal alcohol exposure (PAE) can result in a range of adverse neonatal outcomes, including Fetal Alcohol Spectrum Disorder (FASD). This systematic review and meta-analysis sought to investigate the effectiveness of brief interventions (BIs) in eliminating or reducing 1) alcohol consumption during pregnancy; and 2) PAE-related adverse neonatal outcomes; and 3) cost-effectiveness of BIs.MethodWe conducted a systematic literature search for original controlled studies (randomized control trials (RCTs); quasi-experimental) in any setting, published from 1987 to 2021. The comparison group was no/minimal intervention, where a measure of alcohol consumption was reported. Studies were critically appraised using the Centre for Evidence-based Medicine Oxford critical appraisal tool for RCTs (1). The certainty in the evidence for each outcome was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) (2). Meta-analysis of continuous and binary estimates of effect-size for similar outcome measures for BIs versus control groups were pooled and reported as mean difference (MD) Hedges' g and odds ratios (ORs), respectively.ResultsIn total, 26 studies, all from high income countries, met inclusion criteria. Alcohol abstinence outcome available in 12 studies (n = 2620) found modest effects in favor of BIs conditions by increasing the odds of abstinence by 56% (OR = 1.56, 95% confidence interval (CI) = 1.15-2.13, I2 = 46.75%; p = 0.04). BIs effects for reduction in mean drinks/week (Cohen's d = - 0.21, 95%CI = - 0.78 to 0.36; p = 0.08) and AUDIT scores (g = 0.10, 95%CI = - 0.06 to 0.26; p = 0.17) were not statistically significant. Among seven studies (n = 740) reporting neonatal outcomes, BI receipt was associated with a modest and significant reduction in preterm birth (OR = 0.67, 95% CI = 0.46-0.98, I2 = 0.00%; p = 0.58). No statistically significant differences were observed for mean birthweight or lower likelihood of low birth weight (LBW). Certainty in the evidence was rated as 'low'. No eligible studies were found on cost-effectiveness of BIs.ConclusionBIs are moderately effective in increasing abstinence during pregnancy and preventing preterm birth. More studies on the effectiveness of BIs are needed from low- and middle-income countries, as well as with younger mothers and with a broader range of ethnic groups.

Dataset Information

Effectiveness of Digital Interventions for Preventing Alcohol Consumption in Pregnancy: Systematic Review and Meta-analysis.

Background

Objective

Methods

Results

Conclusions

Publications

Effectiveness of Digital Interventions for Preventing Alcohol Consumption in Pregnancy: Systematic Review and Meta-analysis.

Similar Datasets

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