Evidence map›Paper›PMID 35329238›Full record

ReviewInternational journal of environmental research and public health2022

A Comprehensive Review on the Behaviour of Motorcyclists: Motivations, Issues, Challenges, Substantial Analysis and Recommendations.

Sarah Najm Abdulwahid, Moamin A Mahmoud, Bilal Bahaa Zaidan, Abdullah Hussein Alamoodi, Salem Garfan, Mohammed Talal, Aws Alaa Zaidan

Open access · goldAbstract readReview
In one paragraph

Review in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.8field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 2 countries.

Sarah Najm AbdulwahidCollege of Graduate Studies, Universiti Tenaga Nasional, Kajang 43000, Malaysia.
Moamin A MahmoudInstitute of Informatics and Computing in Energy, Universiti Tenaga Nasional, Kajang 43000, Malaysia.ORCID 0000-0001-8333-5575
Bilal Bahaa ZaidanFuture Technology Research Center, National Yunlin University of Science and Technology, Douliu 64002, Taiwan.
Abdullah Hussein AlamoodiDepartment of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim 35900, Malaysia.ORCID 0000-0003-4393-5570
Salem GarfanDepartment of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim 35900, Malaysia.ORCID 0000-0003-1310-6931
Mohammed TalalDepartment of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), Batu Pahat 86400, Malaysia.
Aws Alaa ZaidanDepartment of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim 35900, Malaysia.
Sultan Idris Education University · MYUniversiti Tenaga Nasional · MYNational Yunlin University of Science and Technology · TWTun Hussein Onn University of Malaysia · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the continuous emergence of new technologies and the adaptation of smart systems in transportation, motorcyclist driving behaviour plays an important role in the transition towards intelligent transportation systems (ITS). Studying motorcyclist driving behaviour requires accurate models with accurate and complete datasets for better road safety and traffic management. As accuracy is needed in modelling, motorcyclist driving behaviour analyses can be performed using sensors that collect driving behaviour characteristics during real-time experiments. This review article systematically investigates the literature on motorcyclist driving behaviour to present many findings related to the issues, problems, challenges, and research gaps that have existed over the last 10 years (2011-2021). A number of digital databases (i.e., IEEE Xplore

Indexed as

Automobile DrivingMotivationdriver behaviourintelligent transportation systemmotorcycliststraffic violation

Identifiers

PMID35329238
PMCPMC8950571
OpenAlexW4220999749

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.