Using machine learning to extract information and predict outcomes from reports of randomised trials of smoking cessation interventions in the Human Behaviour-Change Project.

Background: Using reports of randomised trials of smoking cessation interventions as a test case, this study aimed to develop and evaluate machine learning (ML) algorithms for extracting information from study reports and predicting outcomes as part of the Human Behaviour-Change Project. It is the first of two linked papers, with the second paper reporting on further development of a prediction system.

Methods: Researchers manually annotated 70 items of information ('entities') in 512 reports of randomised trials of smoking cessation interventions covering intervention content and delivery, population, setting, outcome and study methodology using the Behaviour Change Intervention Ontology.

Using systems perspectives in evidence synthesis: A methodological mapping review.

Reviewing complex interventions is challenging because they include many elements that can interact dynamically in a nonlinear manner. A systems perspective offers a way of thinking to help understand complex issues, but its application in evidence synthesis is not established. The aim of this project was to understand how and why systems perspectives have been applied in evidence synthesis.

Are medical procedures that induce coughing or involve respiratory suctioning associated with increased generation of aerosols and risk of SARS-CoV-2 infection? A rapid systematic review.

Background: The risk of transmission of SARS-CoV-2 from aerosols generated by medical procedures is a cause for concern.

Aim: To evaluate the evidence for aerosol production and transmission of respiratory infection associated with procedures that involve airway suctioning or induce coughing/sneezing.

Methods: The review was informed by PRISMA guidelines.

School closure in response to epidemic outbreaks: Systems-based logic model of downstream impacts.

School closures have been a recommended non-pharmaceutical intervention in pandemic response owing to the potential to reduce transmission of infection between children, school staff and those that they contact. However, given the many roles that schools play in society, closure for any extended period is likely to have additional impacts. Literature reviews of research exploring school closure to date have focused upon epidemiological effects; there is an unmet need for research that considers the multiplicity of potential impacts of school closures.

The Human Behaviour-Change Project: An artificial intelligence system to answer questions about changing behaviour.

Changing behaviour is necessary to address many of the threats facing human populations.  However, identifying behaviour change interventions likely to be effective in particular contexts as a basis for improving them presents a major challenge. The Human Behaviour-Change Project harnesses the power of artificial intelligence and behavioural science to organise global evidence about behaviour change to predict outcomes in common and unknown behaviour change scenarios.

Handsearching had best recall but poor efficiency when exporting to a bibliographic tool: case study.

Objectives: The objective of this study was to compare the effectiveness and efficiency of methods used to identify and export conference abstracts into a bibliographic management tool.

Study Design And Setting: This is a case study. The effectiveness and efficiency of methods to identify and export conference abstracts presented at the American Society of Hematology (ASH) conference 2016-2018 for a systematic review were evaluated.

The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews.

The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process.

Just how plain are plain tobacco packs: re-analysis of a systematic review using multilevel meta-analysis suggests lessons about the comparative benefits of synthesis methods.

Background: Comparisons between narrative synthesis and meta-analysis as synthesis methods in systematic reviews are uncommon within the same systematic review. We re-analysed a systematic review on the effects of plain packaging of tobacco on attractiveness. We sought to compare different synthesis approaches within the same systematic review and shed light on the comparative benefits of each approach.

How can additional secondary data analysis of observational data enhance the generalisability of meta-analytic evidence for local public health decision making?

This paper critically explores how survey and routinely collected data could aid in assessing the generalisability of public health evidence. We propose developing approaches that could be employed in understanding the relevance of public health evidence, and investigate ways of producing meta-analytic estimates tailored to reflect local circumstances, based on analyses of secondary data. Currently, public health decision makers face challenges in interpreting global review evidence to assess its meaning in local contexts.

Narratives of community engagement: a systematic review-derived conceptual framework for public health interventions.

Background: Government policy increasingly supports engaging communities to promote health. It is critical to consider whether such strategies are effective, for whom, and under what circumstances. However, 'community engagement' is defined in diverse ways and employed for different reasons.

The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation.

Background: Behaviour change is key to addressing both the challenges facing human health and wellbeing and to promoting the uptake of research findings in health policy and practice. We need to make better use of the vast amount of accumulating evidence from behaviour change intervention (BCI) evaluations and promote the uptake of that evidence into a wide range of contexts. The scale and complexity of the task of synthesising and interpreting this evidence, and increasing evidence timeliness and accessibility, will require increased computer support.

Text mining for search term development in systematic reviewing: A discussion of some methods and challenges.

Using text mining to aid the development of database search strings for topics described by diverse terminology has potential benefits for systematic reviews; however, methods and tools for accomplishing this are poorly covered in the research methods literature. We briefly review the literature on applications of text mining for search term development for systematic reviewing. We found that the tools can be used in 5 overarching ways: improving the precision of searches; identifying search terms to improve search sensitivity; aiding the translation of search strategies across databases; searching and screening within an integrated system; and developing objectively derived search strategies.

Using the realist perspective to link theory from qualitative evidence synthesis to quantitative studies: Broadening the matrix approach.

Background: This study describes an approach for the use of a specific type of qualitative evidence synthesis in the matrix approach, a mixed studies reviewing method. The matrix approach compares quantitative and qualitative data on the review level by juxtaposing concrete recommendations from the qualitative evidence synthesis against interventions in primary quantitative studies. However, types of qualitative evidence syntheses that are associated with theory building generate theoretical models instead of recommendations.

Psychosocial interventions for supporting women to stop smoking in pregnancy.

Background: Tobacco smoking remains one of the few preventable factors associated with complications in pregnancy, 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 is 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.

Interpretive analysis of 85 systematic reviews suggests that narrative syntheses and meta-analyses are incommensurate in argumentation.

Using Toulmin's argumentation theory, we analysed the texts of systematic reviews in the area of workplace health promotion to explore differences in the modes of reasoning embedded in reports of narrative synthesis as compared with reports of meta-analysis. We used framework synthesis, grounded theory and cross-case analysis methods to analyse 85 systematic reviews addressing intervention effectiveness in workplace health promotion. Two core categories, or 'modes of reasoning', emerged to frame the contrast between narrative synthesis and meta-analysis: practical-configurational reasoning in narrative synthesis ('what is going on here? What picture emerges?') and inferential-predictive reasoning in meta-analysis ('does it work, and how well? Will it work again?').

Meta-analysis, complexity, and heterogeneity: a qualitative interview study of researchers' methodological values and practices.

Background: Complex or heterogeneous data pose challenges for systematic review and meta-analysis. In recent years, a number of new methods have been developed to meet these challenges. This qualitative interview study aimed to understand researchers' understanding of complexity and heterogeneity and the factors which may influence the choices researchers make in synthesising complex data.

Alcohol advertising and public health: systems perspectives versus narrow perspectives.

Background: Alcohol consumption is influenced by a complex causal system of interconnected psychological, behavioural, social, economic, legal and environmental factors. These factors are shaped by governments (eg, licensing laws and taxation), by consumers (eg, patterns of alcohol consumption drive demand) and by alcohol industry practices, such as advertising. The marketing and advertising of alcoholic products contributes to an 'alcogenic environment' and is a modifiable influence on alcohol consumption and harm.

The effectiveness of community engagement in public health interventions for disadvantaged groups: a meta-analysis.

Background: 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.

Using text mining for study identification in systematic reviews: a systematic review of current approaches.

Background: 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.

Reducing systematic review workload through certainty-based screening.

In systematic reviews, the growing number of published studies imposes a significant screening workload on reviewers. Active learning is a promising approach to reduce the workload by automating some of the screening decisions, but it has been evaluated for a limited number of disciplines. The suitability of applying active learning to complex topics in disciplines such as social science has not been studied, and the selection of useful criteria and enhancements to address the data imbalance problem in systematic reviews remains an open problem.

Using qualitative comparative analysis (QCA) in systematic reviews of complex interventions: a worked example.

Background: Systematic reviews that address policy and practice questions in relation to complex interventions frequently need not only to assess the efficacy of a given intervention but to identify which intervention - and which intervention components - might be most effective in particular situations. Here, intervention replication is rare, and commonly used synthesis methods are less useful when the focus of analysis is the identification of those components of an intervention that are critical to its success.

Methods: Having identified initial theories of change in a previous analysis, we explore the potential of qualitative comparative analysis (QCA) to assist with complex syntheses through a worked example.

The 'active ingredients' for successful community engagement with disadvantaged expectant and new mothers: a qualitative comparative analysis.

Aims: To explore which conditions of community engagement are implicated in effective interventions targeting disadvantaged pregnant women and new mothers.

Background: Adaptive experiences during pregnancy and the early years are key to reducing health inequalities in women and children worldwide. Public health nurses, health visitors and community midwives are well placed to address such disadvantage, often using community engagement strategies.

Techniques for identifying cross-disciplinary and 'hard-to-detect' evidence for systematic review.

Driven by necessity in our own complex review, we developed alternative systematic ways of identifying relevant evidence where the key concepts are generally not focal to the primary studies' aims and are found across multiple disciplines-that is, hard-to-detect evidence. Specifically, we sought to identify evidence on community engagement in public health interventions that aim to reduce health inequalities. Our initial search strategy used text mining to identify synonyms for the concept 'community engagement'.