Article type
Year
Abstract
Background: The explosion of new information technologies and the global growth in the academic sector present challenges to systematic reviewers that have grown in parallel to the burgeoning of electronic databases. Reviewers are increasingly at risk of either being overwhelmed by unmanageable search results, or missing evidence. The challenges are greatest for reviews of 'broad' social determinants of health and interventions, particularly when they include phrases such as 'health information'. New information technologies/methods also provide potential solutions.
Objectives: Our scoping review aimed to describe the extent and nature of evidence on patients’ responses to different forms of information on their health status/risk of disease, with the objectives of mapping key concepts, sources and types of evidence, commonalities, themes and gaps in the research.
Methods: To strike the balance between sensitivity (finding all articles in an area) and specificity (finding only relevant articles), the review used standard systematic review approaches to develop search strategies in conjunction with text mining approaches utilising Automatic Term Recognition (ATR) software. Sample papers were identified in initial searches and screened for inclusion. ATR software identified search terms/phrases within the sample papers, producing 107 precise phrases (as opposed to Boolean searches of words, e.g. 'health NEAR/3 information') after manual selection by reviewers. Phrases were combined with simple operators and run across nine databases.
Results: The searches identified 6662 unique articles, compared to standard approaches which identified 100,000+ articles. Title and abstract screening identified 358 papers for full text screening - high numbers here being a measure of the sensitivity of the search of this broad area. Twenty-six articles were included in the review.
Conclusions: Our systematic approach combining traditional search term development methods and new text mining methods produced results that were sensitive, specific and, of growing importance to the increasingly overwhelmed community of reviewers, manageable.
Objectives: Our scoping review aimed to describe the extent and nature of evidence on patients’ responses to different forms of information on their health status/risk of disease, with the objectives of mapping key concepts, sources and types of evidence, commonalities, themes and gaps in the research.
Methods: To strike the balance between sensitivity (finding all articles in an area) and specificity (finding only relevant articles), the review used standard systematic review approaches to develop search strategies in conjunction with text mining approaches utilising Automatic Term Recognition (ATR) software. Sample papers were identified in initial searches and screened for inclusion. ATR software identified search terms/phrases within the sample papers, producing 107 precise phrases (as opposed to Boolean searches of words, e.g. 'health NEAR/3 information') after manual selection by reviewers. Phrases were combined with simple operators and run across nine databases.
Results: The searches identified 6662 unique articles, compared to standard approaches which identified 100,000+ articles. Title and abstract screening identified 358 papers for full text screening - high numbers here being a measure of the sensitivity of the search of this broad area. Twenty-six articles were included in the review.
Conclusions: Our systematic approach combining traditional search term development methods and new text mining methods produced results that were sensitive, specific and, of growing importance to the increasingly overwhelmed community of reviewers, manageable.