Norah L Crossnohere, Rosa Negash, Manny Schwimmer, Christiane Voisin, John F P Bridges, Daniel E Jonas
{"title":"Values Clarification Methods in Decision Support Tools for Lung Cancer Screening: A Systematic Review and Content Analysis.","authors":"Norah L Crossnohere, Rosa Negash, Manny Schwimmer, Christiane Voisin, John F P Bridges, Daniel E Jonas","doi":"10.1177/0272989X251355906","DOIUrl":null,"url":null,"abstract":"<p><p>BackgroundValues clarification methods may be particularly appropriate for decision support in lung cancer screening (LCS), for which patients must consider a complex tradeoff of benefits and harms. Values clarification methods that are explicit and use theory-based methods may best support decision making.PurposeTo characterize values clarification methods in decision support tools for LCS and explore associations with behavioral and decisional outcomes.Data SourcesPubMed, Cochrane Library, CINAHL, APA PsycINFO, and Embase, supplemented with gray literature and hand searches.Study SelectionStudies evaluating patient-facing LCS decision support tools.Data ExtractionWe extracted information on study characteristics and the decision support tools evaluated in each study, including method of values clarification (explicit, implicit, or none). Study quality was evaluated using an adapted version of the SUNDAE Checklist.Data SynthesisWe identified 48 studies (10,233 participants) evaluating 32 unique decision support tools for LCS. More than 80% of tools included values clarification methods, split between explicit (<i>n</i> = 13) and implicit (<i>n</i> = 13) methods. Only 1 explicit values clarification used a theory-based method. Meta-analysis of randomized controlled trials indicated that using a decision support tool doubled the odds of receiving LCS (pooled odds ratio 1.98, 95% confidence interval 1.21-3.25, 9 studies), a pattern driven by increased uptake of screening following use of tools with explicit or no values clarification. Studies lacking values clarification were of lower quality than those with explicit or implicit methods (<i>P</i> = 0.04).LimitationsAlmost no tools applied theory-based methods for explicit values clarification, limiting conclusions about their impact.ConclusionsLCS decision support tools routinely incorporate values clarification methods and appear to enhance screening uptake. However, theory-based values clarification methods, which may further improve decision support quality, remain underutilized.HighlightsValues clarification is a core aspect of shared decision making. It may be especially valuable for decision making regarding lung cancer screening (LCS), as patients must weigh a complex balance of benefits and harms.This systematic review identified 48 studies assessing 32 unique decision support tools for LCS. More than 80% of these tools incorporated values clarification methods, with an equal distribution of explicit and implicit methods.Among the subset of studies using a randomized controlled trial, the use of a decision support tool doubled the odds of an individual undergoing LCS.Decision support tools designed to support shared decision making in LCS commonly incorporate values clarification methods. However, they infrequently use theory-based methods, which are increasingly thought to provide high-quality decision support.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"811-825"},"PeriodicalIF":3.1000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Decision Making","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/0272989X251355906","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/17 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
BackgroundValues clarification methods may be particularly appropriate for decision support in lung cancer screening (LCS), for which patients must consider a complex tradeoff of benefits and harms. Values clarification methods that are explicit and use theory-based methods may best support decision making.PurposeTo characterize values clarification methods in decision support tools for LCS and explore associations with behavioral and decisional outcomes.Data SourcesPubMed, Cochrane Library, CINAHL, APA PsycINFO, and Embase, supplemented with gray literature and hand searches.Study SelectionStudies evaluating patient-facing LCS decision support tools.Data ExtractionWe extracted information on study characteristics and the decision support tools evaluated in each study, including method of values clarification (explicit, implicit, or none). Study quality was evaluated using an adapted version of the SUNDAE Checklist.Data SynthesisWe identified 48 studies (10,233 participants) evaluating 32 unique decision support tools for LCS. More than 80% of tools included values clarification methods, split between explicit (n = 13) and implicit (n = 13) methods. Only 1 explicit values clarification used a theory-based method. Meta-analysis of randomized controlled trials indicated that using a decision support tool doubled the odds of receiving LCS (pooled odds ratio 1.98, 95% confidence interval 1.21-3.25, 9 studies), a pattern driven by increased uptake of screening following use of tools with explicit or no values clarification. Studies lacking values clarification were of lower quality than those with explicit or implicit methods (P = 0.04).LimitationsAlmost no tools applied theory-based methods for explicit values clarification, limiting conclusions about their impact.ConclusionsLCS decision support tools routinely incorporate values clarification methods and appear to enhance screening uptake. However, theory-based values clarification methods, which may further improve decision support quality, remain underutilized.HighlightsValues clarification is a core aspect of shared decision making. It may be especially valuable for decision making regarding lung cancer screening (LCS), as patients must weigh a complex balance of benefits and harms.This systematic review identified 48 studies assessing 32 unique decision support tools for LCS. More than 80% of these tools incorporated values clarification methods, with an equal distribution of explicit and implicit methods.Among the subset of studies using a randomized controlled trial, the use of a decision support tool doubled the odds of an individual undergoing LCS.Decision support tools designed to support shared decision making in LCS commonly incorporate values clarification methods. However, they infrequently use theory-based methods, which are increasingly thought to provide high-quality decision support.
期刊介绍:
Medical Decision Making offers rigorous and systematic approaches to decision making that are designed to improve the health and clinical care of individuals and to assist with health care policy development. Using the fundamentals of decision analysis and theory, economic evaluation, and evidence based quality assessment, Medical Decision Making presents both theoretical and practical statistical and modeling techniques and methods from a variety of disciplines.