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      Does Talking on a Cell Phone, With a Passenger, or Dialing Affect Driving Performance? An Updated Systematic Review and Meta-Analysis of Experimental Studies

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          Abstract

          Objective An up-to-date meta-analysis of experimental research on talking and driving is needed to provide a comprehensive, empirical, and credible basis for policy, legislation, countermeasures, and future research. Background The effects of cell, mobile, and smart phone use on driving safety continues to be a contentious societal issue. Method All available studies that measured the effects of cell phone use on driving were identified through a variety of search methods and databases. A total of 93 studies containing 106 experiments met the inclusion criteria. Coded independent variables included conversation target (handheld, hands-free, and passenger), setting (laboratory, simulation, or on road), and conversation type (natural, cognitive task, and dialing). Coded dependent variables included reaction time, stimulus detection, lane positioning, speed, headway, eye movements, and collisions. Results The overall sample had 4,382 participants, with driver ages ranging from 14 to 84 years ( M = 25.5, SD = 5.2). Conversation on a handheld or hands-free phone resulted in performance costs when compared with baseline driving for reaction time, stimulus detection, and collisions. Passenger conversation had a similar pattern of effect sizes. Dialing while driving had large performance costs for many variables. Conclusion This meta-analysis found that cell phone and passenger conversation produced moderate performance costs. Drivers minimally compensated while conversing on a cell phone by increasing headway or reducing speed. A number of additional meta-analytic questions are discussed. Application The results can be used to guide legislation, policy, countermeasures, and future research.

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          Meta-analysis: recent developments in quantitative methods for literature reviews.

          We describe the history and current status of the meta-analytic enterprise. The advantages and historical criticisms of meta-analysis are described, as are the basic steps in a meta-analysis and the role of effect sizes as chief coins of the meta-analytic realm. Advantages of the meta-analytic procedures include seeing the "landscape" of a research domain, keeping statistical significance in perspective, minimizing wasted data, becoming intimate with the data summarized, asking focused research questions, and finding moderator variables. Much of the criticism of meta-analysis has been based on simple misunderstanding of how meta-analyses are actually carried out. Criticisms of meta-analysis that are applicable are equally applicable to traditional, nonquantitative, narrative reviews of the literature. Much of the remainder of the chapter deals with the processes of effect size estimation, the understanding of the heterogeneity of the obtained effect sizes, and the practical and scientific importance of the effect sizes obtained.
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            How quickly do systematic reviews go out of date? A survival analysis.

            Systematic reviews are often advocated as the best source of evidence to guide clinical decisions and health care policy, yet we know little about the extent to which they require updating. To estimate the average time to changes in evidence that are sufficiently important to warrant updating systematic reviews. Survival analysis of 100 quantitative systematic reviews. Systematic reviews published from 1995 to 2005 and indexed in ACP Journal Club. Eligible reviews evaluated a specific drug or class of drug, device, or procedure and included only randomized or quasi-randomized, controlled trials. Quantitative signals for updating were changes in statistical significance or relative changes in effect magnitude of at least 50% involving 1 of the primary outcomes of the original systematic review or any mortality outcome. Qualitative signals included substantial differences in characterizations of effectiveness, new information about harm, and caveats about the previously reported findings that would affect clinical decision making. The cohort of 100 systematic reviews included a median of 13 studies and 2663 participants per review. A qualitative or quantitative signal for updating occurred for 57% of reviews (95% CI, 47% to 67%). Median duration of survival free of a signal for updating was 5.5 years (CI, 4.6 to 7.6 years). However, a signal occurred within 2 years for 23% of reviews and within 1 year for 15%. In 7%, a signal had already occurred at the time of publication. Only 4% of reviews had a signal within 1 year of the end of the reported search period; 11% had a signal within 2 years of the search. Shorter survival was associated with cardiovascular topics (hazard ratio, 2.70 [CI, 1.36 to 5.34]) and heterogeneity in the original review (hazard ratio, 2.15 [CI, 1.12 to 4.11]). Judgments of the need for updating were made without involving content experts. In a cohort of high-quality systematic reviews directly relevant to clinical practice, signals for updating occurred frequently and within a relatively short time.
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              Methods of Meta-Analysis: Correcting Error and Bias in Research Findings

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                Author and article information

                Journal
                Human Factors: The Journal of the Human Factors and Ergonomics Society
                Hum Factors
                SAGE Publications
                0018-7208
                1547-8181
                October 05 2017
                January 19 2018
                : 60
                : 1
                : 101-133
                Article
                10.1177/0018720817748145
                29351023
                343989dd-58d0-4062-a03e-12193a44fe79
                © 2018

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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