Evidence map›Paper›PMID 40764336›Full record

ArticleScientific reports2025

The practical impact of indoor temperature on the productivity of prefabricated construction workers using electroencephalogram data.

Hao Bai, Yian Lu, Xinying Cao, Shulong Zhuo

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Hao BaiCollege of Information Engineering, Hainan Vocational University of Science and Technology, Haikou, 571126, China.
Yian LuSchool of Civil Engineering and Architecture, Hainan University, Haikou, 570228, China.
Xinying CaoSchool of Civil Engineering and Architecture, Hainan University, Haikou, 570228, China. 992987@hainanu.edu.cn.
Shulong ZhuoCollege of Information Engineering, Hainan Vocational University of Science and Technology, Haikou, 571126, China.

Funding

Education Department of Hainan Province Hnky2025ZD-17Haikou Municipal Key Science and Technology Project 2024-044Hainan Provincial Natural Science Foundation of China 625RC794National Natural Science Foundation of China 72161007Research Project of Hainan Vocational University of Science and Technology HKKY2024-TD-09Technology Research and Development Topic PT-2022-08
6 · The paper itself

Abstract

Comprehending the optimal indoor temperature to augment the productivity and cognitive well-being of prefabricated construction workers (PCWs) is essential for enhancing efficiency and safety in construction. Twenty-four workers participated in experiments conducted at indoor temperatures of 24℃, 27℃, 30℃, and 33℃. During the experiments, workers underwent neurobehavioral tests at different indoor temperatures, and thermal sensation and comfort questionnaires were administered post-test to evaluate thermal comfort. Productivity was measured by the accuracy and reaction time in the neurobehavioral tests. Electroencephalogram (EEG) recordings during the tests provided data on attention, mental workload, vigilance, and mental fatigue. The results demonstrate that indoor temperature directly affects workers' productivity and indirectly impacts it through cognitive states and thermal comfort. Analyzing correlations of cognitive state indicators and their changes over time, 27℃ and 30℃ are more conducive to enhancing PCWs' productivity. Furthermore, it was observed that workers' productivity is higher in longer tasks at the same indoor temperature compared to shorter tasks. These results offer practical guidelines for optimizing indoor temperature to better PCWs' working conditions. By identifying productivity-enhancing temperature ranges, the study provides actionable insights to boost worker efficiency, reduce cognitive strain, and sustain performance.

Indexed as

Construction IndustryEfficiencyElectroencephalographyTemperatureAdultAttentionCognitionFemaleHumansMaleReaction TimeSurveys and QuestionnairesYoung AdultCognitive stateElectroencephalogramIndoor temperaturePrefabricated construction workersProductivity

Identifiers

PMID40764336
PMCPMC12325621

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.