Evidence map›Paper›PMID 39638287›Full record

ArticleEpidemiology and health2024

A decision tree model for traffic accident prediction among food delivery riders in Thailand.

Muslimah Molo, Suttida Changsan, Lila Madares, Ruchirada Changkwanyeun, Supang Wattanasoei, Supa Vittaporn, Patcharin Khamnuan, Surangrat Pongpan, Kasama Pooseesod, Sayambhu Saita

Abstract read
In one paragraph

Article in Epidemiology and health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

10 authors.

Muslimah MoloFaculty of Public Health, Thammasat University, Lampang, Thailand.
Suttida ChangsanFaculty of Public Health, Thammasat University, Lampang, Thailand.
Lila MadaresFaculty of Public Health, Thammasat University, Lampang, Thailand.
Ruchirada ChangkwanyeunFaculty of Public Health, Thammasat University, Lampang, Thailand.
Supang WattanasoeiFaculty of Public Health, Thammasat University, Lampang, Thailand.
Supa VittapornFaculty of Public Health, Thammasat University, Lampang, Thailand.
Patcharin KhamnuanFaculty of Public Health, Thammasat University, Lampang, Thailand.
Surangrat PongpanFaculty of Public Health, Thammasat University, Lampang, Thailand.
Kasama PooseesodFaculty of Public Health, Thammasat University, Lampang, Thailand.
Sayambhu SaitaFaculty of Public Health, Thammasat University, Lampang, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesFood delivery riders (FDRs) play a crucial role in the food delivery industry but face considerable challenges, including a rising number of traffic accidents. This study aimed to examine the incidence of traffic accidents and develop a decision tree model to predict the likelihood of traffic accidents among FDRs.

methodsA cross-sectional study was conducted with 257 FDRs in Chiang Mai and Lampang Province, Thailand. Participants were interviewed using questionnaires and provided self-reports of accidents over the previous 6 months. Univariable logistic regression was used to identify factors influencing traffic accidents. Subsequently, a decision tree model was developed to predict traffic accidents using a training and validation dataset split in a 70:30 ratio.

resultsThe results indicated that 45.1% of FDRs had been involved in a traffic accident. The decision tree model identified several significant predictors of traffic accidents, including delivering food in the rain, job stress, fatigue, inadequate sleep, and the use of a modified motorcycle, achieving a prediction accuracy of 66.5%.

conclusionsBased on this model, we recommend several measures to minimize accidents among FDRs: ensuring adequate sleep, implementing work-rest schedules to mitigate fatigue, managing job-related stress effectively, inspecting motorcycle conditions before use, and exercising increased caution when delivering food during rainy conditions.

Indexed as

Accidents, TrafficDecision TreesAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedMotorcyclesRisk FactorsThailandYoung AdultDecision tree modelFood delivery ridersMitigationPredictionTraffic accidents

Identifiers

PMID39638287
PMCPMC11840416

What OpenQuestion holds

Textmetadata
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.