MDM Policy and Practice最新文献

{"title":"Primary Care Provider Preferences Regarding Artificial Intelligence in Point-of-Care Cancer Screening.","authors":"Vinayak S Ahluwalia, Marilyn M Schapira, Gary E Weissman, Ravi B Parikh","doi":"10.1177/23814683251329007","DOIUrl":"10.1177/23814683251329007","url":null,"abstract":"<p><p><b>Background.</b> It is unclear how to optimize the user interface and user experience of cancer screening artificial intelligence (AI) tools for clinical decision-making in primary care. <b>Methods.</b> We developed an electronic survey for US primary care clinicians to assess 1) general attitudes toward AI in cancer screening and 2) preferences for various aspects of AI model deployment in the context of colorectal, breast, and lung cancer screening. We descriptively analyzed the responses. <b>Results.</b> Ninety-nine surveys met criteria for analysis out of 733 potential respondents (response rate 14%). Ninety (>90%) somewhat or strongly agreed that their medical education did not provide adequate AI training. A plurality (52%, 39%, and 37% for colon, breast, and lung cancers, respectively) preferred that AI tools recommend the interval to the next screening as compared with the 5-y probability of future cancer diagnosis, a binary recommendation of \"screen now,\" or identification of suspicious imaging findings. In terms of workflow, respondents preferred generating a flag in the electronic health record to communicate an AI prediction versus an interactive smartphone application or the delegation of findings to another healthcare professional. No majority preference emerged for an explainability method for breast cancer screening. <b>Limitations.</b> The sample was primarily obtained from a single health care system in the Northeast. <b>Conclusions.</b> Providers indicated that AI models can be most helpful in cancer screening by providing prescriptive outputs, such as recommended intervals until next screening, and by integrating with the electronic health record. <b>Implications.</b> A preliminary framework for AI model development in cancer screening may help ensure effective integration into clinical workflow. These findings can better inform how healthcare systems govern and receive reimbursement for services that use AI.</p><p><strong>Highlights: </strong>Clinicians do not feel their undergraduate or graduate medical education has properly prepared them to engage with AI in patient care.We provide a preliminary framework for deploying AI models in primary care-based cancer screening.This framework may have implications for health system governance and provider reimbursement in the age of AI.</p>","PeriodicalId":36567,"journal":{"name":"MDM Policy and Practice","volume":"10 1","pages":"23814683251329007"},"PeriodicalIF":1.9,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970086/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143796260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Cost-Effectiveness of Tenofovir Alafenamide for Chronic Hepatitis B Virus in Taiwan.","authors":"Elise Chia-Hui Tan, Alon Yehoshua, Sushanth Jeyakumar, Pongo Peng, Amy Lin, Nathaniel J Smith, Nandita Kachru","doi":"10.1177/23814683251328659","DOIUrl":"10.1177/23814683251328659","url":null,"abstract":"<p><p><b>Background.</b> Chronic hepatitis B (CHB) is a lifelong disease requiring long-term or indefinite therapy, resulting in substantial economic burden. Thus, careful consideration must be used in the selection of therapies. <b>Aim.</b> This analysis assessed the cost-effectiveness of tenofovir alafenamide (TAF) compared with tenofovir disoproxil fumarate (TDF) and entecavir (ETV) from the perspective of the Taiwan National Health Insurance Administration Healthcare payer for the management of CHB over a lifetime horizon. <b>Methods.</b> An individual patient simulation model assessed the impact of treatment on CHB infection for liver- and safety-related outcomes. Patients could achieve spontaneous or treatment-induced responses, experience a reactivation of the disease, develop long-term liver complications, or experience treatment-related renal or bone complications. Patient population profiles were based on clinical trial and real-world data. Data on clinical parameters (safety, mortality, resistance risk, and flare), health utilities, and costs were sourced from the published literature. <b>Results.</b> TAF was associated with fewer liver disease events and fewer cases of bone and renal complications per 100 person-years. TAF also had higher eAg and sAg seroconversion compared with TDF and ETV. As compared with both treatments, TAF was both more effective and more costly, resulting in incremental cost-effectiveness ratios of USD 3,348 and USD 3,940 per quality-adjusted life-year gained versus TDF and ETV, respectively. <b>Conclusion.</b> TAF leads to better health outcomes at acceptable incremental costs compared with the most commonly used therapies in the management of CHB, thus making it a cost-effective option for the treatment of CHB in Taiwan.</p><p><strong>Highlights: </strong>The cost-effectiveness of tenofovir alafenamide (TAF) versus tenofovir disoproxil fumarate (TDF) and entecavir (ETV) was assessed in patients with chronic hepatitis B in Taiwan.TAF was associated with fewer liver disease events, fewer cases of bone and renal complications, and higher eAG and sAG seroconversion compared with TDF and ETV; TAF was found to be cost-effective compared with both treatments.</p>","PeriodicalId":36567,"journal":{"name":"MDM Policy and Practice","volume":"10 1","pages":"23814683251328659"},"PeriodicalIF":1.9,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954167/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143754706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging the Gap: A Mixed-Methods Study on Factors Influencing Breast Cancer Clinicians' Decisions to Use Clinical Prediction Models.","authors":"Mary Ann E Binuya, Sabine C Linn, Annelies H Boekhout, Marjanka K Schmidt, Ellen G Engelhardt","doi":"10.1177/23814683251328377","DOIUrl":"10.1177/23814683251328377","url":null,"abstract":"&lt;p&gt;&lt;p&gt;&lt;b&gt;Background.&lt;/b&gt; Clinical prediction models provide tailored risk estimates that can help guide decisions in breast cancer care. Despite their potential, few models are widely used in clinical practice. We aimed to identify the factors influencing breast cancer clinicians' decisions to adopt prediction models and assess their relative importance. &lt;b&gt;Methods.&lt;/b&gt; We conducted a mixed-methods study, beginning with semi-structured interviews, followed by a nationwide online survey. Thematic analysis was used to qualitatively summarize the interviews and identify key factors. For the survey, we used descriptive analysis to characterize the sample and Mann-Whitney &lt;i&gt;U&lt;/i&gt; and Kruskal-Wallis tests to explore differences in score (0 = &lt;i&gt;not important&lt;/i&gt; to 10 = &lt;i&gt;very important&lt;/i&gt;) distributions. &lt;b&gt;Results.&lt;/b&gt; Interviews (&lt;i&gt;N&lt;/i&gt; = 16) identified eight key factors influencing model use. Practical/methodological factors included accessibility, cost, understandability, &lt;i&gt;objective&lt;/i&gt; accuracy, actionability, and clinical relevance. Perceptual factors included acceptability, &lt;i&gt;subjective&lt;/i&gt; accuracy, and risk communication. In the survey (&lt;i&gt;N&lt;/i&gt; = 146; 137 model users), clinicians ranked online accessibility (median score = 9 [interquartile range = 8-10]) as most important. Cost was also highly rated, with preferences for freely available models (9 [8-10]) and those with reimbursable tests (8 [8-10]). Formal regulatory approval (7 [5-8]) and direct integration with electronic health records (6 [3-8]) were considered less critical. Subgroup analysis revealed differences in score distributions; for example, clinicians from general hospitals prioritized inclusion of new biomarkers more than those in academic settings. &lt;b&gt;Conclusions.&lt;/b&gt; Breast cancer clinicians' decisions to initiate use of prediction models are influenced by practical and perceptual factors, extending beyond technical metrics such as discrimination and calibration. Addressing these factors more holistically through collaborative efforts between model developers, clinicians, and communication and implementation experts, for instance, by developing clinician-friendly online tools that prioritize usability and local adaptability, could increase model uptake.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Highlights: &lt;/strong&gt;Accessibility, cost, and practical considerations, such as ease of use and clinical utility, were prioritized slightly more than technical validation metrics, such as discrimination and calibration, when deciding to start using a clinical prediction model.Most breast cancer clinicians valued models with clear inputs (e.g., variable definitions, cutoffs) and outputs; few were interested in the exact model specifications.Perceptual or subjective factors, including perceived accuracy and peer acceptability, also influenced model adoption but were secondary to practical considerations.Sociodemographic variables, such as clinical specialization and hospital setting, influenced the importa","PeriodicalId":36567,"journal":{"name":"MDM Policy and Practice","volume":"10 1","pages":"23814683251328377"},"PeriodicalIF":1.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11948560/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143732081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Screening Mammography for Young Women in Israel: Between Guidelines and Common Practice.","authors":"Neta Essar Schvartz, Michal Rotem-Green, Dikla Kruger, Anat Gaver, Inbar Safra, Danielle Mira Harari, Nadav Niego, Mordechai Alperin","doi":"10.1177/23814683251317524","DOIUrl":"10.1177/23814683251317524","url":null,"abstract":"<p><p><b>Background.</b> Breast cancer screening via mammography for women younger than 50 y sparks controversy due to balancing benefits and risks. In Israel, specific criteria govern early screening initiation, yet global studies reveal low adherence to guidelines for this demographic. <b>Objectives.</b> This study aims to report on young women's referrals for screening mammography in Israel, assess adherence to guidelines, and identify factors influencing guideline adherence. <b>Design, Setting, and Participants.</b> A cross-sectional study analyzed referral letters for screening mammography issued to women aged 18 to 49 y from March 2019 to February 2020 in 2 districts of Israel's largest health care provider. Exclusions included women with a history of breast cancer or BRCA mutations. Of 9,960 letters, 1,287 were randomly selected for adherence assessment, with 13% of nonadherent cases further reviewed. <b>Main Outcomes and Measures.</b> Primary outcomes included categorizing referrals as adherent or nonadherent to guidelines. Additional measures explored correlations between adherence and patient characteristics (e.g., age, comorbidities) and the referring physician's specialty. <b>Results.</b> A total of 999 referral letters were included in the statistical analysis. Referrals spanned all ages but skewed toward women older than 40 y. Of the referrals, 45% (452) came from general surgeons and 32% (327) from family physicians. Twenty-four percent (303) of referrals were blank, and 1% (4) involved risk-benefit discussions. In total, 109 (10.9%) of the referrals strictly adhered to guidelines; under a lenient approach, 30.6% (307) adhered. General surgeons adhered more frequently than gynecologists did (32.8% [109] v. 14.9% [11], <i>P</i> = 0.014). <b>Conclusions and Relevance.</b> Despite official guidelines, many physicians in Israel did not follow recommendations for breast cancer screening in women younger than 50 y, highlighting a gap between evidence-based medicine and clinical practice.</p><p><strong>Highlights: </strong><b>Question</b> Are screening mammography referrals, given to women younger than 50 y of age, adherent to current guidelines? <b>Findings</b> In this cross-sectional study of a randomly selected sample of 1,287 referral letters, given to women aged 18 to 50 y, only 10.9% were adherent with the guidelines when examined with a strict approach and 30.6% with a forgiving approach. Adherence significantly correlated with the field of the referring physician. <b>Meaning</b> Despite known risks of screening mammography, women younger than 50 y are commonly referred to such screening in a deviation from current guidelines.</p>","PeriodicalId":36567,"journal":{"name":"MDM Policy and Practice","volume":"10 1","pages":"23814683251317524"},"PeriodicalIF":1.9,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905013/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143625964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Difference Tasks Are Affected by Probability Format, Part 1: A Making Numbers Meaningful Systematic Review.","authors":"Natalie C Benda, Brian J Zikmund-Fisher, Mohit M Sharma, Stephen B Johnson, Michelle Demetres, Diana Delgado, Jessica S Ancker","doi":"10.1177/23814683241294077","DOIUrl":"10.1177/23814683241294077","url":null,"abstract":"<p><p><b>Background.</b> To develop guidance on the effect of data presentation format on communication of health probabilities, the Making Numbers Meaningful project undertook a systematic review. <b>Purpose.</b> This article, one in a series, covers evidence about \"difference tasks,\" in which a reader examines a stimulus to evaluate differences between probabilities, such as the effect of a risk factor or therapy on the chance of a disease. This article covers the effect of format on 4 outcomes: 1) identifying a probability difference (identification) or recalling it (recall), 2) identifying the largest or smallest of a set of probability differences (contrast outcome), 3) placing a probability difference into a category such as \"elevated\" or \"below average\" (categorization outcome), and 4) performing computations (computation outcome). <b>Data Sources.</b> MEDLINE, Embase, CINAHL, the Cochrane Library, PsycINFO, ERIC, ACM Digital Library; hand search of 4 journals. <b>Finding Selection.</b> Pairwise screening to identify experimental/quasi-experimental research comparing 2 or more formats for quantitative health information. This article reports on 53 findings derived from 35 unique studies reported in 32 papers. <b>Data Extraction.</b> Pairwise extraction of information on stimulus (data in a data presentation format), cognitive task, and perceptual, affective, cognitive, or behavioral outcomes. <b>Data Synthesis.</b> Most evidence involving outcomes of difference-level cognitive tasks was weak or insufficient. Evidence was strong that 1) computations involving differences are easier with rates per 10ⁿ than with percentages or 1 in X rates and 2) adding graphics to numbers makes it easier to perform difference-level computations. <b>Limitations.</b> A granular level of evidence syntheses leads to narrow guidance rather than broad statements. <b>Conclusions.</b> Although many studies examined differences between probabilities, few were comparable enough to generate strong evidence.</p><p><strong>Highlights: </strong>Most evidence about the effect of format on ability to evaluate differences in probabilities was weak or insufficient because of too few comparable studies.Strong evidence showed that computations relevant to differences in probabilities are easier with rates per 10ⁿ than with 1 in X rates.Adding graphics to probabilities helps readers compute differences between probabilities.</p>","PeriodicalId":36567,"journal":{"name":"MDM Policy and Practice","volume":"10 1","pages":"23814683241294077"},"PeriodicalIF":1.9,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11848882/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scope, Methods, and Overview Findings for the Making Numbers Meaningful Evidence Review of Communicating Probabilities in Health: A Systematic Review.","authors":"Jessica S Ancker, Natalie C Benda, Mohit M Sharma, Stephen B Johnson, Michelle Demetres, Diana Delgado, Brian J Zikmund-Fisher","doi":"10.1177/23814683241255334","DOIUrl":"10.1177/23814683241255334","url":null,"abstract":"&lt;p&gt;&lt;p&gt;&lt;b&gt;Background.&lt;/b&gt; The format in which probabilities are presented influences comprehension and interpretation. &lt;b&gt;Purpose.&lt;/b&gt; To develop comprehensive evidence-based guidance about how to communicate probabilities in health and to identify strengths and weaknesses in the literature. This article presents methods for the review of &lt;i&gt;probability communication&lt;/i&gt; and is accompanied by several results articles. &lt;b&gt;Data Sources.&lt;/b&gt; MEDLINE, Embase, CINAHL, the Cochrane Library, PsycINFO, ERIC, ACM Digital Library; hand search of 4 journals. &lt;b&gt;Study Selection.&lt;/b&gt; Two reviewers conducted screening to identify experimental and quasi-experimental research that compared 2 or more formats for presenting quantitative health information to patients or lay audiences. &lt;b&gt;Data Extraction.&lt;/b&gt; In our conceptual framework, people make sense of a stimulus (data in a data presentation format) by performing cognitive tasks, resulting in perceptual, affective, cognitive, or behavioral responses measured as 1 of 14 distinct outcomes. The study team developed custom instruments to extract concepts, conduct risk-of-bias evaluation, and evaluate individual findings for credibility. &lt;b&gt;Data Synthesis.&lt;/b&gt; Findings were grouped into tables by task and outcome for evidence synthesis. &lt;b&gt;Limitations.&lt;/b&gt; Reviewer error could have led to missing relevant studies despite having 2 independent reviewers screening each article. The granular data extraction and syntheses slowed the work and may have made it less replicable. Credibility was evaluated by only 2 experts. &lt;b&gt;Conclusions.&lt;/b&gt; After reviewing 26,793 titles and abstracts, we identified 316 articles about probability communication. Data extraction produced 1,119 individual findings, which were grouped into 37 evidence tables, each containing evidence on up to 10 data presentation format comparisons. The Making Numbers Meaningful project required novel methods for classifying and synthesizing research, which reveal patterns of strength and weakness in the probability communication literature.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Highlights: &lt;/strong&gt;The Making Numbers Meaningful project conducted a comprehensive systematic review of experimental and quasi-experimental research that compared 2 or more formats for presenting quantitative health information to patients or other lay audiences. The current article focuses on probability information.Based on a conceptual taxonomy, we reviewed studies based on the cognitive tasks required of participants, assessing 14 distinct possible outcomes.Our review identified 316 articles involving probability communications that generated 1,119 distinct research findings, each of which was reviewed by multiple experts for credibility.The overall pattern of findings highlights which probability communication questions have been well researched and which have not. For example, there has been far more research on communicating single probabilities than on communicating more complex information such as ","PeriodicalId":36567,"journal":{"name":"MDM Policy and Practice","volume":"10 1","pages":"23814683241255334"},"PeriodicalIF":1.9,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11848889/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Synthesis Tasks Are Affected by Probability Format: A Making Numbers Meaningful Systematic Review.","authors":"Natalie C Benda, Mohit M Sharma, Jessica S Ancker, Michelle Demetres, Diana Delgado, Stephen B Johnson, Brian J Zikmund-Fisher","doi":"10.1177/23814683241293796","DOIUrl":"10.1177/23814683241293796","url":null,"abstract":"<p><p><b>Background.</b> To develop guidance on the effect of data presentation format on communication of health probabilities, the Making Numbers Meaningful project undertook a systematic review. <b>Purpose.</b> This article, one in a series, covers evidence about a \"synthesis task,\" in which readers examine stimuli to synthesize information about multiple features of health options, such as chances of both harm and benefit for a treatment. This article presents evidence of the effect of format on perceptual, cognitive, affective, and behavioral outcomes. <b>Data Sources.</b> MEDLINE, Embase, CINAHL, the Cochrane Library, PsycINFO, ERIC, ACM Digital Library; hand search of 4 journals. <b>Finding Selection.</b> Manual pairwise screening to identify experimental and quasi-experimental research comparing 2 or more formats for presenting quantitative health information to lay audiences. This article reports on 91 findings derived from 45 unique studies reported in 42 articles. <b>Data Extraction.</b> Pairwise extraction of information on stimulus (data in a data presentation format), cognitive task, and perceptual, affective, cognitive, or behavioral outcomes. <b>Data Synthesis.</b> Evidence was found about 6 outcomes: identification/recall, contrast, effectiveness perceptions/feelings, behavioral intentions/behavior, trust, and preference. No strong evidence was found. Moderate evidence suggests that for synthesis tasks, behavioral intention is not affected by whether the risk and benefit probabilities are in text or in tables, that people prefer tables to text for presenting this information, and that effectiveness feelings are not affected by whether or not numbers are supplemented by narratives. <b>Limitations.</b> Granular data extraction and evidence syntheses lead to narrow evidence statements. <b>Conclusions.</b> Current evidence on synthesis tasks is moderate strength at best. Future studies should enrich the evidence on how to present information needed to synthesize multiple features of health options, given the importance of this task.</p><p><strong>Highlights: </strong>This study found a moderate number of studies assessing strategies for evaluating sets of probabilities conveying information such as risks and benefits.Evidence is moderate that although presenting sets of probabilities in table versus sentences may not affect behavioral intentions, people may prefer tables.Contrary to previous studies about probability feelings, moderate evidence suggested that narratives may not affect effectiveness feelings.Evidence was insufficient to draw conclusions regarding contrast, identification, and trust outcomes, and no studies assessed recall, categorization, computation, or discrimination outcomes.</p>","PeriodicalId":36567,"journal":{"name":"MDM Policy and Practice","volume":"10 1","pages":"23814683241293796"},"PeriodicalIF":1.9,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11848887/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Point (Single-Probability) Tasks Are Affected by Probability Format, Part 1: A Making Numbers Meaningful Systematic Review.","authors":"Jessica S Ancker, Natalie C Benda, Mohit M Sharma, Stephen B Johnson, Michelle Demetres, Diana Delgado, Brian J Zikmund-Fisher","doi":"10.1177/23814683241255333","DOIUrl":"10.1177/23814683241255333","url":null,"abstract":"<p><p><b>Background.</b> To create guidance on the effect of data presentation format on communication of health numbers, the Making Numbers Meaningful project undertook a systematic review. <b>Purpose.</b> This article (one of a series) covers research studying so-called \"point tasks,\" in which a reader examines stimuli to obtain information about single probabilities. The current article presents the evidence on the effects of data presentation format on multiple outcomes: identification and recall, contrast, categorization, and computation. <b>Data Sources.</b> MEDLINE, Embase, CINAHL, the Cochrane Library, PsycINFO, ERIC, ACM Digital Library; hand search of 4 journals. <b>Finding Selection.</b> Manual pairwise screening to identify experimental and quasi-experimental research comparing 2 or more formats for quantitative health information for patients or other lay audiences. This article reports on 218 findings from 99 articles on single probability communication. <b>Data Extraction.</b> Pairwise extraction of data on stimulus (data in a data presentation format), task, and perceptual/affective/cognitive/behavioral outcomes. <b>Data Synthesis.</b> Most evidence on these outcomes was weak or insufficient. There was moderate to strong evidence that 1) recall was better with icon arrays with human figures than icon arrays with blocks, 2) survival curves make it easier to identify points of highest survival than mortality curves (contrast outcome), 3) adding an average population probability to a message about an individual probability may not affect recall, 4) computation performance is better with bar charts combined with data labels than with either numbers or graphics alone, 5) computation performance with rates is better when denominators match, and 6) framing strongly affects risky choices (contrast). <b>Limitations.</b> Heterogeneous study designs reduced the ability to develop strong evidence. <b>Conclusions.</b> Few findings assessing identification or recall, contrast, categorization, or computation outcomes for point tasks were comparable enough to each other to generate strong evidence.</p><p><strong>Highlights: </strong>Many researchers have studied the effects of data presentation formats of single probabilities on different outcomes.However, few findings are comparable enough to allow for strong evidence-based conclusions about the impact on identification, recall, contrast, categorization, and computation outcomes.</p>","PeriodicalId":36567,"journal":{"name":"MDM Policy and Practice","volume":"10 1","pages":"23814683241255333"},"PeriodicalIF":1.9,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11848880/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Point (Single-Probability) Tasks Are Affected by Probability Format, Part 2: A Making Numbers Meaningful Systematic Review.","authors":"Jessica S Ancker, Natalie C Benda, Mohit M Sharma, Stephen B Johnson, Michelle Demetres, Diana Delgado, Brian J Zikmund-Fisher","doi":"10.1177/23814683241255337","DOIUrl":"10.1177/23814683241255337","url":null,"abstract":"<p><p><b>Background.</b> The Making Numbers Meaningful review is intended to create guidance on the effect of data presentation format on comprehension of numbers in health. <b>Purpose.</b> This article (one of a series) covers research studying so-called \"point tasks,\" in which a reader examines materials to obtain information about single probabilities. The current article presents evidence on the effects of data presentation format on probability perceptions and feelings, health behaviors and behavioral intentions, trust, preference, and discrimination outcomes. <b>Data Sources.</b> MEDLINE, Embase, CINAHL, the Cochrane Library, PsycINFO, ERIC, ACM Digital Library; hand search of 4 journals. <b>Study Selection.</b> Manual pairwise screening to identify experimental and quasi-experimental research that compared 2 or more formats for presenting quantitative health information to patients or other lay audiences. This article reports 466 findings of probability communication from 161 articles. <b>Data Extraction.</b> Pairwise extraction of information on stimulus (data in a data presentation format), task, and outcomes. <b>Data Synthesis.</b> Moderate to strong evidence is available on the effects of several format interventions to influence probability perceptions and feelings, including the 1-in-X number format, foreground-only (numerator-only) icon arrays, bar charts, anecdotes, framing, and verbal probabilities. However, only 3 (the 1-in-X effect, anecdotes, and framing) had moderate to strong evidence of influencing health behaviors and behavioral intentions. Research on patient preferences for numerical, graphical, and verbal formats yielded only weak evidence. <b>Conclusions.</b> The link between probability perceptions/feelings and health behaviors is not strongly reflected in the evidence about communicating numbers because many communication-focused studies measure short-term response rather than longer-term behaviors. Also, research into patient preferences for numerical, graphical, and verbal formats has not yielded strong evidence suggesting stable and predictable preferences.</p><p><strong>Highlights: </strong>Formatting a probability as 1 in X, using a foreground-only icon array, adding anecdotes to numbers, and gain-loss framing all affect probability perceptions and feelings.The evidence on communicating numbers to influence perceptions is far stronger than the evidence on using it to change health behavior or behavioral intention.Only weak evidence is available on patient preferences for verbal, graphical, and numerical probability formats.</p>","PeriodicalId":36567,"journal":{"name":"MDM Policy and Practice","volume":"10 1","pages":"23814683241255337"},"PeriodicalIF":1.9,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11848894/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Time-Trend Tasks Are Affected by Probability Format: A Making Numbers Meaningful Systematic Review.","authors":"Mohit M Sharma, Jessica S Ancker, Natalie C Benda, Stephen B Johnson, Michelle Demetres, Diana Delgado, Brian J Zikmund-Fisher","doi":"10.1177/23814683241301702","DOIUrl":"10.1177/23814683241301702","url":null,"abstract":"<p><p><b>Background.</b> To develop guidance on the effects of format on communication of health probabilities, the Making Numbers Meaningful team conducted a systematic review. <b>Purpose.</b> This article (one of a series) covers research on time-trend tasks, in which participants evaluate stimuli for information about probability trends, such as changing chances of cancer recurrence over time. <b>Data Sources.</b> MEDLINE, Embase, CINAHL, the Cochrane Library, PsycINFO, ERIC, ACM Digital Library; hand search of 4 journals. <b>Study Selection.</b> We conducted independent dual screening to identify experimental or quasi-experimental research comparing 2 or more formats for presenting quantitative health information to lay audiences. This article reports on 11 findings from 6 unique studies. <b>Data Extraction.</b> Independent dual extraction of information on stimulus (data in a data presentation format), task, and perceptual, affective, cognitive, and behavioral outcomes. <b>Data Synthesis.</b> We identified research on the impact of format on the following outcomes: contrast, computation, effectiveness perceptions, health behaviors and behavioral intentions, discrimination, and preference. Strong evidence suggests that graphing probability curves over longer (rather than shorter) time periods increases perceived differences between curves (effectiveness perception outcome). Weak evidence suggested 1) survival versus mortality curves do not affect perceived differences between curves or ability to perform computations, 2) survival curves may help people identify the option with the highest survival, and 3) graphing probabilities over longer time periods may not affect the ability to identify the highest survival. <b>Limitations.</b> Granular data extraction and evidence syntheses lead to narrow conclusions rather than broader statements. <b>Conclusions.</b> The very limited evidence available about probability time-trend tasks is primarily about the effects of framing (survival v. mortality curves) and the effects of using shorter versus longer time periods.</p><p><strong>Highlights: </strong>This systematic review found that few studies of probability trend data compared similar formats or used comparable outcome measures.The only strong piece of evidence was that graphing probabilities over longer time periods such that the distance between curves widens will tend to increase the perceived difference between the curves.Weak evidence suggests that survival curves (versus mortality curves) may make it easier to identify the option with the highest overall survival.Weak evidence suggests that graphing probabilities over longer (rather than shorter) time periods may increase the ability to distinguish between small survival differences.Evidence was insufficient to determine whether any format influenced behaviors or behavioral intentions.</p>","PeriodicalId":36567,"journal":{"name":"MDM Policy and Practice","volume":"10 1","pages":"23814683241301702"},"PeriodicalIF":1.9,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11848886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}