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      The Drives for Driving Simulation: A Scientometric Analysis and a Selective Review of Reviews on Simulated Driving Research

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          Abstract

          Driving behaviors and fitness to drive have been assessed over time using different tools: standardized neuropsychological, on-road and driving simulation testing. Nowadays, the great variability of topics related to driving simulation has elicited a high number of reviews. The present work aims to perform a scientometric analysis on driving simulation reviews and to propose a selective review of reviews focusing on relevant aspects related to validity and fidelity. A scientometric analysis of driving simulation reviews published from 1988 to 2019 was conducted. Bibliographic data from 298 reviews were extracted from Scopus and WoS. Performance analysis was conducted to investigate most prolific Countries, Journals, Institutes and Authors. A cluster analysis on authors’ keywords was performed to identify relevant associations between different research topics. Based on the reviews extracted from cluster analysis, a selective review of reviews was conducted to answer questions regarding validity, fidelity and critical issues. United States and Germany are the first two Countries for number of driving simulation reviews. United States is the leading Country with 5 Institutes in the top-ten. Top Authors wrote from 3 to 7 reviews each and belong to Institutes located in North America and Europe. Cluster analysis identified three clusters and eight keywords. The selective review of reviews showed a substantial agreement for supporting validity of driving simulation with respect to neuropsychological and on-road testing, while for fidelity with respect to real-world driving experience a blurred representation emerged. The most relevant critical issues were the a) lack of a common set of standards, b) phenomenon of simulation sickness, c) need for psychometric properties, lack of studies investigating d) predictive validity with respect to collision rates and e) ecological validity. Driving simulation represents a cross-cutting topic in scientific literature on driving, and there are several evidences for considering it as a valid alternative to neuropsychological and on-road testing. Further research efforts could be aimed at establishing a consensus statement for protocols assessing fitness to drive, in order to (a) use standardized systems, (b) compare systematically driving simulators with regard to their validity and fidelity, and (c) employ shared criteria for conducting studies in a given sub-topic.

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          bibliometrix : An R-tool for comprehensive science mapping analysis

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            Cognitive, sensory and physical factors enabling driving safety in older adults.

            We reviewed literature on cognitive, sensory, motor and physical factors associated with safe driving and crash risk in older adults with the goal of developing a model of factors enabling safe driving behaviour. Thirteen empirical studies reporting associations between cognitive, sensory, motor and physical factors and either self-reported crashes, state crash records or on-road driving measures were identified. Measures of attention, reaction time, memory, executive function, mental status, visual function, and physical function variables were associated with driving outcome measures. Self-monitoring was also identified as a factor that may moderate observed effects by influencing driving behavior. We propose that three enabling factors (cognition, sensory function and physical function/medical conditions) predict driving ability, but that accurate self-monitoring of these enabling factors is required for safe driving behaviour.
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              Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature

              Systematic reviews of scientific literature are important for mapping the existing state of research and highlighting further growth channels in a field of study, but systematic reviews are inherently tedious, time consuming, and manual in nature. In recent years, keyword co-occurrence networks (KCNs) are exploited for knowledge mapping. In a KCN, each keyword is represented as a node and each co-occurrence of a pair of words is represented as a link. The number of times that a pair of words co-occurs in multiple articles constitutes the weight of the link connecting the pair. The network constructed in this manner represents cumulative knowledge of a domain and helps to uncover meaningful knowledge components and insights based on the patterns and strength of links between keywords that appear in the literature. In this work, we propose a KCN-based approach that can be implemented prior to undertaking a systematic review to guide and accelerate the review process. The novelty of this method lies in the new metrics used for statistical analysis of a KCN that differ from those typically used for KCN analysis. The approach is demonstrated through its application to nano-related Environmental, Health, and Safety (EHS) risk literature. The KCN approach identified the knowledge components, knowledge structure, and research trends that match with those discovered through a traditional systematic review of the nanoEHS field. Because KCN-based analyses can be conducted more quickly to explore a vast amount of literature, this method can provide a knowledge map and insights prior to undertaking a rigorous traditional systematic review. This two-step approach can significantly reduce the effort and time required for a traditional systematic literature review. The proposed KCN-based pre-systematic review method is universal. It can be applied to any scientific field of study to prepare a knowledge map.
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                Author and article information

                Contributors
                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                27 May 2020
                2020
                : 11
                : 917
                Affiliations
                [1] 1Dipartimento di Scienze della Formazione, Psicologia, Comunicazione, Università degli Studi di Bari Aldo Moro , Bari, Italy
                [2] 2Department of Agricultural and Environmental Science, Faculty of Agricultural Science, University of Bari Aldo Moro , Bari, Italy
                [3] 3Giustino Fortunato University , Benevento, Italy
                [4] 4Department of Interdisciplinary Medicine, School of Medicine, University of Bari Aldo Moro , Bari, Italy
                [5] 5Commissione Medica Locale Patenti Speciali, Azienda Sanitaria Locale , Bari, Italy
                Author notes

                Edited by: Pietro Cipresso, Italian Auxological Institute (IRCCS), Italy

                Reviewed by: Leonardo Carlucci, Università degli Studi “G. d’Annunzio” Chieti – Pescara, Italy; Zaida Chinchilla-Rodríguez, Consejo Superior de Investigaciones Científicas (CSIC), Spain

                *Correspondence: Alessandro Oronzo Caffò, alessandro.caffo@ 123456uniba.it

                This article was submitted to Quantitative Psychology and Measurement, a section of the journal Frontiers in Psychology

                Article
                10.3389/fpsyg.2020.00917
                7266970
                32528360
                866680cc-0f31-49d5-b84d-aa72b1518f6a
                Copyright © 2020 Caffò, Tinella, Lopez, Spano, Massaro, Lisi, Stasolla, Catanesi, Nardulli, Grattagliano and Bosco.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 30 November 2019
                : 14 April 2020
                Page count
                Figures: 2, Tables: 6, Equations: 0, References: 113, Pages: 19, Words: 0
                Funding
                Funded by: Regione Puglia 10.13039/501100009886
                Categories
                Psychology
                Review

                Clinical Psychology & Psychiatry
                driving simulation,driving simulator,fitness to drive,scientometric analysis,review

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