DOI: 10.6078/d1g42r
title: Indoor temperature - office work performance database

description: The objective of developing this database was to summarise all relevant
 published studies that have linked the thermal environment to office work
 performance within the most representative temperature range for office
 buildings (20 °C to 30 °C). We conducted a comprehensive literature review
 and collected the relevant published data into our database. A variety of
 combinations of keywords including temperature, thermal sensation, work,
 cognitive, and task performance, and office and commercial buildings, were
 used. In total, we found thirty-five studies, in 29 peer-reviewed journal
 publications and 571 measures of performance, met our inclusion criteria.
 We normalised these measures using a method originally proposed by
 Seppänen et al. (2006; 2006). This method uses the change in work
 performance per 1 °C increment in temperature (λ%), which is measured in
 percentage per degree Celsius (%/°C). Our database comprised a total of
 358 data points for λ%. Furthermore, we developed a web-based interactive
 tool with an easy-to-use interface to visualize the relationship
 between temperature and office work performance. This tool can
 automatically calculate the model’s equation and accuracy metrics via
 different data subsets and regression models.
description: Our literature search strategies and data collection criteria are
 specified below: We searched electronic
 databases of scientific publications from September 2019- March
 2020, including Google Scholar, Web of Science, Elsevier,
 PubMed, and ProQuest.       A variety of
 combinations of keywords were used. We
 looked only for peer-reviewed journal articles that reported both thermal
 environment measurement data and the subject’s performance of office work.
 Diverse measures were considered to describe office work performance
 including diagnostic tests, simulated office work tasks, and existing
 outcome metrics. We used air temperature as a proxy
 of the thermal environment in our research scope because it was
 extensively measured in most of the studies. We did
 not include the following conditions in our database: 
 Physiological measurements providing information on cognitive
 load EEG, ECG, heart rate variability, and pupillary responses;
 Studies that reporting only self-estimated
 performance; Proxies for reduced performance, such as
 the prevalence and intensity of acute health symptoms, especially for
 fatigue, difficulty in concentrating, sleepiness, or headaches;
 Data from factory workers, university students, or
 primary/secondary school children; Any experimental
 conditions that have a low-temperature condition
 (<i>T<sub>L</sub></i>) below 17 °C or the
 high-temperature condition (<i>T<sub>H</sub></i>)
 above 36 °C; Studies where thermal stress was induced
 by any means other than the indoor thermal conditions (e.g., exercise
 or water immersion). 
 From each study, we retrieved the year of publication, journal,
 and information regarding the study location, whether the study was or was
 not performed in a controlled environment, the sample size, age group,
 occupation of the participants, clothing, and physical activity level. We
 also collected the tasks or tests used to measure performance, the
 performance metrics and outcomes, and the temperature conditions to which
 the participants were exposed. We normalised the
 performance data obtained from the studies using the method proposed by
 Seppänen et al.(2006). This approach assumes that performance changes
 linearly within the high temperature (TH) and low temperature (TL) range
 examined in each study regardless of the performance measure used and the
 temperature range. We calculated the change in work performance in % per 1
 °C increment in temperature (λ%), whereby positive λ% indicates an
 increase in performance with increasing temperature; while negative λ%
 indicates a decrease in performance with increasing temperature. The
 detailed normalisation process can be seen in Porras-Salazar et al.
 (2021).
 <strong>References:</strong>
 Seppänen, O., & Fisk, W. J. (2006). Some quantitative
 relations between indoor environmental quality and work performance or
 health. <i>HVAC and R Research</i>, <i>12</i>(4),
 957–973. https://doi.org/10.1080/10789669.2006.10391446
 Seppänen, O., Fisk, W. J., & Lei, Q. H. (2006). Effect of
 Temperature on Task Performance in Office Environment.
 <i>Proceedings of 5th International Conference on Cold
 ClimateHeating, Ventilating and Air Conditioning</i>. Moscow,
 Russia. Porras-Salazar, J.A.; Schiavon, S.; Wargocki,
 P.; Cheung, T. & Tham, K.W. (2021) Meta-Analysis of 35 Studies
 Examining the Effect of Indoor Temperature on Office Work Performance.
 <em>Building and Environment,
 203</em>. https://doi.org/10.1016/j.buildenv.2021.108037
description: <b>Parameter
 Description</b> <b>Name of
 column</b> <b>Description</b> Study Study code Authors Authors of the study Source Journal where the study was published City_Region City or region where the study was conducted Climate Climate classification according to the city or region where the study was conducted. We used the main climate groups (A: Tropical, B: Dry, C: Temperate, and D: Continental) of the Köppen-Geiger climate categorisation. Number_Participants The number of people who participated in the study Male The number of males who participated in the study Female The number of females who participated in the study Age Mean age of the people who participated in the study Occupation Main occupation of the people who participated in the study Anthropometric_Data Tells if anthropometric data of the participants were reported in the study (Yes/No). Anthropometric data refers to height, weight or body mass index (BMI) Health_Status Tells if the health status of the participants was reported in the study (Yes/No) Clothing_Insulation Shows information about the clothing insulation as was reported in the studies Clothing_Insulation2 Shows the clothing insulation in Clo units. For those studies where only the participants’ attire was reported, we estimated the corresponding insulation in Clo units using the CBE Thermal Comfort Tool. https://comfort.cbe.berkeley.edu/ Exposure_Time Duration of exposure per temperature condition. Time in minutes Measure Name given in the study to the measure of performance. E.g., Serial digit learning, Text typing, Talk time, etc. Measure_Type We classified the measures of performance into 23 different types Metric Metrics used in the studies to measure the participants’ individual performance. FP: False positives, RMSE: Root Mean Square Error, SC: Scores, NOL: Number of lags, RE: Percentage of correct, MI: Missed, NOC: Number of correct, NER: Number of errors, REER: Percentage of errors, SP: Span, NOE: Number of exercises, RT: Reaction time, T: Time. SA We classified the metrics into Accuracy or Speed based on the information provided in the publications TSLow Mean thermal sensation of the study’s participants under the low thermal condition TSHigh Mean thermal sensation of the study’s participants under the high thermal condition TLow_C Mean temperature at the low thermal condition in degree Celsius (°C) THigh_C Mean temperature at the high thermal condition in degree Celsius (°C) TLow_F Mean temperature at the low thermal condition in degree Fahrenheit (°F) THigh_F Mean temperature at the high thermal condition in degree Fahrenheit (°F) PLow Mean performance of the study’s participants under the low thermal condition PHigh Mean performance of the study’s participants under the high thermal condition