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Author

Alison O'Mara-Eves

Other affiliations: University College London
Bio: Alison O'Mara-Eves is an academic researcher from Institute of Education. The author has contributed to research in topics: Systematic review & Psychological intervention. The author has an hindex of 18, co-authored 45 publications receiving 2312 citations. Previous affiliations of Alison O'Mara-Eves include University College London.

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Journal ArticleDOI
TL;DR: It was unclear whether interventions prevented smoking relapse among women who had stopped smoking spontaneously in early pregnancy, but high-quality evidence suggests incentive-based interventions are effective when compared with an alternative (non-contingent incentive) intervention.
Abstract: BACKGROUND: Tobacco smoking in pregnancy remains one of the few preventable factors associated with complications in pregnancy, stillbirth, low birthweight and preterm birth and has serious long-term implications for women and babies. Smoking in pregnancy is decreasing in high-income countries, but is strongly associated with poverty and increasing in low- to middle-income countries. OBJECTIVES: To assess the effects of smoking cessation interventions during pregnancy on smoking behaviour and perinatal health outcomes. SEARCH METHODS: In this fifth update, we searched the Cochrane Pregnancy and Childbirth Group's Trials Register (1 March 2013), checked reference lists of retrieved studies and contacted trial authors to locate additional unpublished data. SELECTION CRITERIA: Randomised controlled trials, cluster-randomised trials, randomised cross-over trials, and quasi-randomised controlled trials (with allocation by maternal birth date or hospital record number) of psychosocial smoking cessation interventions during pregnancy. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed trials for inclusion and trial quality, and extracted data. Direct comparisons were conducted in RevMan, and subgroup analyses and sensitivity analysis were conducted in SPSS. MAIN RESULTS: Eighty-six trials were included in this updated review, with 77 trials (involving over 29,000 women) providing data on smoking abstinence in late pregnancy.In separate comparisons, counselling interventions demonstrated a significant effect compared with usual care (27 studies; average risk ratio (RR) 1.44, 95% confidence interval (CI) 1.19 to 1.75), and a borderline effect compared with less intensive interventions (16 studies; average RR 1.35, 95% CI 1.00 to 1.82). However, a significant effect was only seen in subsets where counselling was provided in conjunction with other strategies. It was unclear whether any type of counselling strategy is more effective than others (one study; RR 1.15, 95% CI 0.86 to 1.53). In studies comparing counselling and usual care (the largest comparison), it was unclear whether interventions prevented smoking relapse among women who had stopped smoking spontaneously in early pregnancy (eight studies; average RR 1.06, 95% CI 0.93 to 1.21). However, a clear effect was seen in smoking abstinence at zero to five months postpartum (10 studies; average RR 1.76, 95% CI 1.05 to 2.95), a borderline effect at six to 11 months (six studies; average RR 1.33, 95% CI 1.00 to 1.77), and a significant effect at 12 to 17 months (two studies, average RR 2.20, 95% CI 1.23 to 3.96), but not in the longer term. In other comparisons, the effect was not significantly different from the null effect for most secondary outcomes, but sample sizes were small.Incentive-based interventions had the largest effect size compared with a less intensive intervention (one study; RR 3.64, 95% CI 1.84 to 7.23) and an alternative intervention (one study; RR 4.05, 95% CI 1.48 to 11.11).Feedback interventions demonstrated a significant effect only when compared with usual care and provided in conjunction with other strategies, such as counselling (two studies; average RR 4.39, 95% CI 1.89 to 10.21), but the effect was unclear when compared with a less intensive intervention (two studies; average RR 1.19, 95% CI 0.45 to 3.12).The effect of health education was unclear when compared with usual care (three studies; average RR 1.51, 95% CI 0.64 to 3.59) or less intensive interventions (two studies; average RR 1.50, 95% CI 0.97 to 2.31).Social support interventions appeared effective when provided by peers (five studies; average RR 1.49, 95% CI 1.01 to 2.19), but the effect was unclear in a single trial of support provided by partners.The effects were mixed where the smoking interventions were provided as part of broader interventions to improve maternal health, rather than targeted smoking cessation interventions.Subgroup analyses on primary outcome for all studies showed the intensity of interventions and comparisons has increased over time, with higher intensity interventions more likely to have higher intensity comparisons. While there was no significant difference, trials where the comparison group received usual care had the largest pooled effect size (37 studies; average RR 1.34, 95% CI 1.25 to 1.44), with lower effect sizes when the comparison group received less intensive interventions (30 studies; average RR 1.20, 95% CI 1.08 to 1.31), or alternative interventions (two studies; average RR 1.26, 95% CI 0.98 to 1.53). More recent studies included in this update had a lower effect size (20 studies; average RR 1.26, 95% CI 1.00 to 1.59), I(2)= 3%, compared to those in the previous version of the review (50 studies; average RR 1.50, 95% CI 1.30 to 1.73). There were similar effect sizes in trials with biochemically validated smoking abstinence (49 studies; average RR 1.43, 95% CI 1.22 to 1.67) and those with self-reported abstinence (20 studies; average RR 1.48, 95% CI 1.17 to 1.87). There was no significant difference between trials implemented by researchers (efficacy studies), and those implemented by routine pregnancy staff (effectiveness studies), however the effect was unclear in three dissemination trials of counselling interventions where the focus on the intervention was at an organisational level (average RR 0.96, 95% CI 0.37 to 2.50). The pooled effects were similar in interventions provided for women with predominantly low socio-economic status (44 studies; average RR 1.41, 95% CI 1.19 to 1.66), compared to other women (26 studies; average RR 1.47, 95% CI 1.21 to 1.79); though the effect was unclear in interventions among women from ethnic minority groups (five studies; average RR 1.08, 95% CI 0.83 to 1.40) and aboriginal women (two studies; average RR 0.40, 95% CI 0.06 to 2.67). Importantly, pooled results demonstrated that women who received psychosocial interventions had an 18% reduction in preterm births (14 studies; average RR 0.82, 95% CI 0.70 to 0.96), and infants born with low birthweight (14 studies; average RR 0.82, 95% CI 0.71 to 0.94). There did not appear to be any adverse effects from the psychosocial interventions, and three studies measured an improvement in women's psychological wellbeing. AUTHORS' CONCLUSIONS: Psychosocial interventions to support women to stop smoking in pregnancy can increase the proportion of women who stop smoking in late pregnancy, and reduce low birthweight and preterm births.

445 citations

Journal ArticleDOI
TL;DR: Using text mining to prioritise the order in which items are screened should be considered safe and ready for use in ‘live’ reviews, and the use of text mining as a ‘second screener’ may also be used cautiously.
Abstract: The large and growing number of published studies, and their increasing rate of publication, makes the task of identifying relevant studies in an unbiased way for inclusion in systematic reviews both complex and time consuming. Text mining has been offered as a potential solution: through automating some of the screening process, reviewer time can be saved. The evidence base around the use of text mining for screening has not yet been pulled together systematically; this systematic review fills that research gap. Focusing mainly on non-technical issues, the review aims to increase awareness of the potential of these technologies and promote further collaborative research between the computer science and systematic review communities. Five research questions led our review: what is the state of the evidence base; how has workload reduction been evaluated; what are the purposes of semi-automation and how effective are they; how have key contextual problems of applying text mining to the systematic review field been addressed; and what challenges to implementation have emerged? We answered these questions using standard systematic review methods: systematic and exhaustive searching, quality-assured data extraction and a narrative synthesis to synthesise findings. The evidence base is active and diverse; there is almost no replication between studies or collaboration between research teams and, whilst it is difficult to establish any overall conclusions about best approaches, it is clear that efficiencies and reductions in workload are potentially achievable. On the whole, most suggested that a saving in workload of between 30% and 70% might be possible, though sometimes the saving in workload is accompanied by the loss of 5% of relevant studies (i.e. a 95% recall). Using text mining to prioritise the order in which items are screened should be considered safe and ready for use in ‘live’ reviews. The use of text mining as a ‘second screener’ may also be used cautiously. The use of text mining to eliminate studies automatically should be considered promising, but not yet fully proven. In highly technical/clinical areas, it may be used with a high degree of confidence; but more developmental and evaluative work is needed in other disciplines.

430 citations

Journal ArticleDOI
TL;DR: A multimethod systematic review builds on the evidence that underpins the current UK guidance on community engagement to identify theoretical models underpinning community engagement and to explore mechanisms and contexts through which communities are engaged to identify community engagement approaches that are effective in reducing health inequalities.
Abstract: Background: Community engagement has been advanced as a promising way of improving health and reducing health inequalities; however, the approach is not yet supported by a strong evidence base. Objectives: To undertake a multimethod systematic review which builds on the evidence that underpins the current UK guidance on community engagement; to identify theoretical models underpinning community engagement; to explore mechanisms and contexts through which communities are engaged; to identify community engagement approaches that are effective in reducing health inequalities, under what circumstances and for whom; and to determine the processes and costs associated with their implementation. Data sources: Databases including the Cochrane Database of Systematic Reviews (CDSR), The Campbell Library, the Database of Abstracts of Reviews of Effects (DARE), the Health Technology Assessment (HTA) database, the NHS Economic Evaluation Database (NHS EED) and EPPI-Centre’s Trials Register of Promoting Health Interventions (TRoPHI) and Database of Promoting Health Effectiveness Reviews (DoPHER) were searched from 1990 to August 2011 for systematic reviews and primary studies. Trials evaluating community engagement interventions reporting health outcomes were included. Review methods: Study eligibility criteria: published after 1990; outcome, economic, or process evaluation; intervention relevant to community engagement; written in English; measured and reported health or community outcomes, or presents cost, resource, or implementation data characterises study populations or reports differential impacts in terms of social determinants of health; conducted in an Organisation for Economic Co-operation and Development (OECD) country. Study appraisal: risk of bias for outcome evaluations; assessment of validity and relevance for process evaluations; comparison against an economic evaluation checklist for economic evaluations. Synthesis methods: four synthesis approaches were adopted for the different evidence types: theoretical, quantitative, process, and economic evidence. Results: The theoretical synthesis identified key models of community engagement that are underpinned by different theories of changes. Results from 131 studies included in a meta-analysis indicate that there is solid evidence that community engagement interventions have a positive impact on health behaviours, health consequences, self-efficacy and perceived social support outcomes, across various conditions There is insufficient evidence – particularly for long-term outcomes and indirect beneficiaries – to determine whether one particular model of community engagement is likely to be more effective than any other. There are also insufficient data to test the effects on health inequalities, although there is some evidence to suggest that interventions that improve social inequalities (as measured by social support) also improve health behaviours. There is weak evidence from the effectiveness and process evaluations that certain implementation factors may affect intervention success. From the economic analysis, there is weak but inconsistent evidence that community engagement interventions are cost-effective. By combining findings across the syntheses, we produced a new conceptual framework. Limitations: Differences in the populations, intervention approaches and health outcomes made it difficult to pinpoint specific strategies for intervention effectiveness. The syntheses of process and economic evidence were limited by the small (generally not rigorous) evidence base. Conclusions: Community engagement interventions are effective across a wide range of contexts and using a variety of mechanisms. Public health initiatives should incorporate community engagement into intervention design. Evaluations should place greater emphasis on long-term outcomes, outcomes for indirect beneficiaries, process evaluation, and reporting costs and resources data. The theories of change identified and the newly developed conceptual framework are useful tools for researchers and practitioners. We identified trends in the evidence that could provide useful directions for future intervention design and evaluation.

321 citations

Journal ArticleDOI
TL;DR: There is solid evidence that community engagement interventions have a positive impact on a range of health outcomes across various conditions.
Abstract: Inequalities in health are acknowledged in many developed countries, whereby disadvantaged groups systematically suffer from worse health outcomes such as lower life expectancy than non-disadvantaged groups. Engaging members of disadvantaged communities in public health initiatives has been suggested as a way to reduce health inequities. This systematic review was conducted to evaluate the effectiveness of public health interventions that engage the community on a range of health outcomes across diverse health issues. We searched the following sources for systematic reviews of public health interventions: Cochrane CDSR and CENTRAL, Campbell Library, DARE, NIHR HTA programme website, HTA database, and DoPHER. Through the identified reviews, we collated a database of primary studies that appeared to be relevant, and screened the full-text documents of those primary studies against our inclusion criteria. In parallel, we searched the NHS EED and TRoPHI databases for additional primary studies. For the purposes of these analyses, study design was limited to randomised and non-randomised controlled trials. Only interventions conducted in OECD countries and published since 1990 were included. We conducted a random effects meta-analysis of health behaviour, health consequences, self-efficacy, and social support outcomes, and a narrative summary of community outcomes. We tested a range of moderator variables, with a particular emphasis on the model of community engagement used as a potential moderator of intervention effectiveness. Of the 9,467 primary studies scanned, we identified 131 for inclusion in the meta-analysis. The overall effect size for health behaviour outcomes is d = .33 (95% CI .26, .40). The interventions were also effective in increasing health consequences (d = .16, 95% CI .06, .27); health behaviour self-efficacy (d = .41, 95% CI .16, .65) and perceived social support (d = .41, 95% CI .23, .65). Although the type of community engagement was not a significant moderator of effect, we identified some trends across studies. There is solid evidence that community engagement interventions have a positive impact on a range of health outcomes across various conditions. There is insufficient evidence to determine whether one particular model of community engagement is more effective than any other.

281 citations

Journal ArticleDOI
TL;DR: The Human Behaviour-Change Project will use Artificial Intelligence and Machine Learning to develop and evaluate a ‘Knowledge System’ that automatically extracts, synthesises and interprets findings from BCI evaluation reports to generate new insights about behaviour change and improve prediction of intervention effectiveness.
Abstract: The project is funded by a Wellcome Trust collaborative award [The Human Behaviour-Change Project: Building the science of behaviour change for complex intervention development’, 201,524/Z/16/Z]. During the preparation of the manuscript RW’s salary was funded by Cancer Research UK.

203 citations


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Journal ArticleDOI
29 Mar 2021-BMJ
TL;DR: The preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement as discussed by the authors was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found.
Abstract: The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.

16,613 citations

Journal ArticleDOI
TL;DR: The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users.
Abstract: Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan ( http://rayyan.qcri.org ), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.

7,527 citations

Journal ArticleDOI
TL;DR: Trends in mean BMI have recently flattened in northwestern Europe and the high-income English-speaking and Asia-Pacific regions for both sexes, southwestern Europe for boys, and central and Andean Latin America for girls, and by contrast, the rise in BMI has accelerated in east and south Asia forboth sexes, and southeast Asia for boys.

4,317 citations

Journal Article

4,293 citations

Journal ArticleDOI
29 Mar 2021-BMJ
TL;DR: The preferred reporting items for systematic reviews and meta-analyses (PRISMA 2020) as mentioned in this paper was developed to facilitate transparent and complete reporting of systematic reviews, and has been updated to reflect recent advances in systematic review methodology and terminology.
Abstract: The methods and results of systematic reviews should be reported in sufficient detail to allow users to assess the trustworthiness and applicability of the review findings. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement was developed to facilitate transparent and complete reporting of systematic reviews and has been updated (to PRISMA 2020) to reflect recent advances in systematic review methodology and terminology. Here, we present the explanation and elaboration paper for PRISMA 2020, where we explain why reporting of each item is recommended, present bullet points that detail the reporting recommendations, and present examples from published reviews. We hope that changes to the content and structure of PRISMA 2020 will facilitate uptake of the guideline and lead to more transparent, complete, and accurate reporting of systematic reviews.

2,217 citations