Skip to main content
Download PDF

Poor personal protective equipment practices were associated with heat-related symptoms among Asian healthcare workers: a large-scale multi-national questionnaire survey

BMC Nursing volume 23, Article number: 145 (2024) Cite this article

Abstract

Background

It is pertinent to understand the perceptions of healthcare workers (HCWs) with their associated personal protective equipment (PPE) usage and heat strain symptoms experienced to effectively combat the negative effects of heat stress during treatment and care activities.

Methods

We evaluated the associated heat stress perceived by HCWs across Asia and validated a questionnaire on perceptions of heat stress, associated PPE usage, and heat strain symptoms experienced. The questionnaire was administered to 3,082 HCWs in six Asian regions. Factor analyses, including Cronbach’s alpha, assessed the questionnaire’s validity and reliability. Structural equation modelling analysed the effects of knowledge, attitudes and practices, and heat strain symptoms.

Results

The questionnaire was found to be reliable in assessing HCWs’ knowledge, and attitudes and practices towards heat stress and PPE usage (both Cronbach’s alpha = 0.9), but not heat strain symptoms (Cronbach’s alpha = 0.6). Despite knowledge of heat stress, HCWs had negative attitudes and practices regarding PPE usage (β1 = 0.6, p < 0.001). Knowledge (path coefficient = 0.2, p < 0.001), and negative attitudes and practices (path coefficient = 0.2, p < 0.001) of HCWs towards heat stress and PPE usage adversely affected symptoms experienced.

Conclusions

The questionnaire was not reliable in assessing symptoms. HCWs should, nevertheless, still self-assess their symptoms for early detection of heat strain. To effectively attenuate heat strain, understanding HCWs’ attitudes and practices towards PPE usage should guide policymakers in implementing targeted heat management strategies.

Peer Review reports

Background

From January 2020 to May 2023, the world was plagued by the coronavirus disease 2019 (COVID-19) pandemic. Since then, over 268 million cases have been recorded across the Western Pacific and Southeast Asia, with the number of deaths exceeding 1.2 million [1]. Despite wide availability of vaccinations, infections continued to rise due to the emergence of new variants and outbreak clusters. To combat the pandemic, a resilient healthcare system was necessary.

Dealing with infection control and heat stress exposure simultaneously was a new challenge for healthcare workers (HCWs) [2]. HCWs worked longer hours and more shifts due to high patient count and manpower shortages [3, 4]. Additionally, HCWs were required to wear personal protective equipment (PPE) when treating patients to reduce risk of viral transmission. PPE usage prevents heat dissipation via evaporative cooling and heat exchange with the environment, which can increase heat strain [5,6,7]. Compounded by rising global temperatures due to climate change [8], the heat stress experienced by HCWs is worsened by environmental stressors when working in warm outdoor conditions [9, 10]. Beyond their workplace, increasing temperatures can also affect HCWs, such as during night sleep, by further exposing them to dehydrating conditions [4]. With the known negative effects of prolonged heat stress exposure on HCWs’ health and well-being, and also knock-on effects on the patients under their dedicated care [3, 7], it is imperative to understand and alleviate the heat stress experienced by HCWs.

Understanding HCWs’ perceptions of heat stress, associated PPE usage, and heat strain symptoms experienced is an important step in developing targeted management strategies. Surveys have been used to understand the knowledge, and attitudes and practices of HCWs who wear PPE during the pandemic [3, 4]. However, the overall validity of such self-administered questionnaires remains unknown. It is important for questionnaires to be validated so their results can be appropriately interpreted [11]. This may be achieved using factor analysis, which studies the relationships between constructs within the questionnaire items to determine how close responses on different constructs relate to one another [11]. Exploratory factor analysis identifies questionnaire items from the same construct, and removes those that do not belong [11]. Subsequently, confirmatory factor analysis specifies the relationship among the confirmed constructs and questionnaire items [11, 12]. Through this approach, policymakers will be able to develop more effective solutions which target the root cause of the perceived heat stress by HCWs when working in PPE.

We aimed (i) to evaluate the heat stress perceived by HCWs engaged in different activities across Asia and (ii) to use factor analysis to validate a previously administered questionnaire on their perceptions of heat stress, associated PPE usage, and heat strain symptoms experienced [3].

Methods

A questionnaire survey was carried out in six Southeast and South Asian countries and regions, namely India, Indonesia, Singapore, Taiwan, Thailand, and Vietnam, from May 2020 to July 2022. HCWs were invited to participate anonymously in the questionnaire either physically, or via an online platform in regions with larger land area and less-accessible hospitals where physical questionnaires may not be feasible. This study received ethical approval from the Research Ethics Committee of National Taiwan University (Taiwan; 202106HM031), Sri Ramachandra Institution of Higher Education and Research (India; IEC-NI/17/APR/59/54), National Healthcare Group Domain Specific Review Board (Singapore; 2020/00590), Siriraj Institutional Review Board (Thailand; Si277/2020), Vietnam Military Medical University Ethics Committee for Biomedical Research (Vietnam; 4812/QD-HVQY), Medical and Health Research Ethics Committee (Indonesia; KE/FK/0302/EC/2021) and Universitas Indonesia (Indonesia; KET-566/UN2.F1/ETIK/PPM.00.02/2021). All methods were performed in accordance with the relevant guidelines and regulations. The respondents provided informed consent before commencing the questionnaire. For physical questionnaires, written consent was obtained. For online questionnaires, consent was obtained electronically before participants could fill the questionnaire. To avoid duplicates, participants were asked to fill the questionnaire only once. An English version of the questionnaire is presented as Supplementary File 1.

Questionnaire

The questionnaire was initially developed by the authors in a previously published study to assess HCWs’ perceptions of heat stress, associated PPE usage, and heat strain symptoms experienced when performing treatment and care activities [3]. The first part of the questionnaire gathered information about respondents’ demographic data, PPE usage, and heat exposure during the pandemic. The second part used a 5-point Likert scale (1 being “Strongly disagree” and 5 being “Strongly agree”) to investigate both HCWs’ knowledge about the effects of heat stress, and attitudes and practices towards PPE usage. The third part of the questionnaire examined heat strain symptoms experienced by HCWs while working in PPE.

Content validity

Content validity was performed to assess the comprehensiveness of the items for measuring the constructs. Occupational and environmental medicine physicians and experts from epidemiology and statistics, environmental health, occupational health, and physiology were involved in this process. Ambiguous questions were rephrased for clarity. Local experts translated the English items into local languages while preserving their original meaning, fluency, and appropriateness.

Construct validity

Construct validity for knowledge of heat stress, attitudes and practices regarding heat stress and PPE usage, and heat strain symptoms experienced was tested using exploratory factor analysis. Prior to factor extraction, Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Bartlett’s Test of Sphericity were performed to assess the suitability of the data for factor analysis. Subsequently, factor extraction was performed using principal component analysis and varimax rotation. Factors with eigenvalues > 1 were extracted. Construct reliability was measured using Cronbach’s alpha. A Cronbach’s alpha ≥ 0.7 was considered to represent good internal consistency [13].

Confirmatory factor analysis was then conducted to verify the factorial structure of HCWs’ knowledge of heat stress, attitudes and practices regarding heat stress and PPE usage, and heat strain symptoms experienced. Analyses were performed using all items with factor loading > 0.5 [12]. The models’ goodness-of-fit was assessed using the following statistics: (i) Comparative Fit Index > 0.9, (ii) Goodness-of-Fit Index > 0.9, and (iii) Root-Mean-Square Error of Approximation < 0.08 [14].

Convergent validity

Convergent validity was assessed by the average variance extracted, and the composite reliability of the questionnaire was calculated. Convergent validity was accepted if the average variance extracted > 0.5 and composite reliability > 0.7 [12, 15].

Statistical analysis

Statistical analysis was performed using SPSS Statistics 18 (IBM Corp., Armonk City, NY, USA) to assess the construct validity and reliability. The “lavaan” package of R software was used for structural equation modelling [16], the “semTools” to calculate the average variance extracted value [17], and the “semPlot” package for drawing path diagram [18]. Continuous variables were expressed in mean ± standard deviation (SD) while categorical variables were expressed in percentages (%). A p-value less than 0.05 was considered to be statistically significant.

Results

Respondents’ demographic data and work conditions

The questionnaire was completed by 3,082 HCWs from six Southeast and South Asian countries and regions. Table 1 shows the breakdown of respondents’ demographic data, work conditions and PPE usage based on country or region. There were 2161 respondents from Taiwan, 110 from India, 407 from Indonesia, 55 from Singapore, 142 from Thailand, and 207 from Vietnam. The mean respondent age was 35.7 ± 10.3 years. 83.5% of the respondents were female. There were 339 medical doctors (11.0%), 2,630 nurses (85.3%), 16 technicians (0.5%), 22 sanitary workers (0.7%), and the remaining 75 workers held other roles (e.g., laboratory staff, radiologists) not previously mentioned (2.4%). Among respondents, 628 (20.4%) mainly worked in non-air-conditioned areas, and 215 respondents (7.0%) worked outdoors. There were 978 respondents (31.7%) that reported not having access to a dedicated rest area.

Table 1 Demographic information, work conditions, and use of personal protective equipment (PPE) among healthcare workers respondents
Full size table

Use of personal protective equipment

Gloves were the most commonly used PPE (90.3%), followed by surgical masks (85.5%), gowns (85.1%), N95 or equivalent (73.5%), face shields (63.2%), and goggles (61.8%). The mean number of days in a week that respondents worked in PPE was 4.0 ± 2.2 days, and the mean number of hours that PPE was worn for each shift was 6.2 ± 3.3 h. 23.7% of respondents did not remove PPE during breaks.

Knowledge about the effects of heat stress

Figure 1 shows the responses of the knowledge section of the questionnaire. For all items, more than 50% of the responses were “Agree” and “Strongly Agree”.

Fig. 1
figure 1

Healthcare workers’ responses to items on the knowledge about the effects of heat stress

Full size image

Attitudes and practices regarding PPE usage

Figure 2 shows the responses of the attitudes and practices towards PPE usage section of the questionnaire. The responses “Agree” and “Strongly Agree” made up more than 50% of all responses for all items except for the statement “Drinking ice slurry will improve my heat tolerance” which majority responded “Neutral”.

Fig. 2
figure 2

Healthcare workers’ responses to items on the attitudes and pratices regarding PPE usage

Full size image

Heat strain symptoms

HCWs reported heat strain symptoms, including headache (28.2%), dizziness (37.2%), thirst (61.7%), vomiting (4.0%), excessive sweating (59.6%), breathing difficulty (31.8%), dehydration (21.1%), exhaustion (16.0%), and wanting to go to a more comfortable area (51.3%). Days spent wearing PPE per week correlated with the number of heat strain symptoms (r = 0.17, p < 0.001).

Construct validity

Table 2 shows the results of exploratory factor analysis for knowledge (nine items) and attitudes and practices (seven items). The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.9, and the significant Bartlett’s value (p < 0.001) suggested that the data was suitable for factor analysis.

Table 2 Principal component analysis for the constructs knowledge, attitudes and practices, and heat strain symptoms, and their individual items
Full size table

Reliability of questionnaire

Reliability analysis indicated Cronbach’s alpha of 0.9 for all items, 0.9 for knowledge, 0.9 for attitudes and practices, and 0.6 for heat strain symptoms, respectively (Table 2), which represents good internal consistency within the constructs of knowledge, and attitudes and practices, and poor internal consistency within the construct of heat strain symptoms.

Convergent validity

Table 3 shows the convergent validity and composite reliability of the domains. Two of the three constructs were valid and reliable for measuring knowledge, and attitudes and practices towards PPE usage and heat stress.

Table 3 Item factor loading within each construct and the convergent validity and composite reliability of constructs
Full size table

The structural model between the variables of knowledge, attitudes and practices, and heat strain symptoms is shown in Fig. 3; Table 3. The Comparative Fit Index was 0.8, Goodness-of-Fit Index was 0.8, and Root-Mean-Square Error of Approximation was 0.1, suggesting an acceptable model fit. There was a significant relationship between knowledge, and attitudes and practices (β1 = 0.6, p < 0.001) (Fig. 3). The magnitude and direction of the model suggested that knowledge (path coefficient = 0.2, p < 0.001), and attitudes and practices (path coefficient = 0.2, p < 0.001) directly affected heat strain symptoms (Fig. 3). “I avoid taking breaks to conserve PPE (a6)”, “I avoid taking breaks to maintain infection control (a7)” and “I avoid drinking and/or eating to avoid going to the toilet (a8)” were the most crucial factor contributing to heat strain symptoms (Table 2). Main findings are summarised in Fig. 4.

Fig. 3
figure 3

Confirmatory factor analysis of the knowledge, attitudes and practices, and heat strain symptoms model. Large circles represent latent variables and rectangles represent observed variables. Single arrows represent a uni-directional effect from one variable to another, while dual-head arrows represent factor covariances. Standardised path coefficients are indicated by the numbers above the arrows and represent the correlation or strength of the relationship between factors. Small circles represent variance in each observed variable that cannot be accounted for by the model, such as biological variability and measurement error. K: knowledge; AP: attitudes and practices; S: heat strain symptoms; hdc: headache; dzz: dizziness; thr: thirst; swt: excessive sweating; dys: breathing difficulty; dhy: dehydration; exh: exhaustion

Full size image
Fig. 4
figure 4

Summary of main findings from questionnaire administered to 3,082 healthcare workers

Full size image

Discussion

This study aimed to (i) to evaluate the heat stress perceived by HCWs engaged in different activities across Asia and (ii) to use factor analysis to validate a previously administered questionnaire on their perceptions of heat stress, associated PPE usage, and heat strain symptoms experienced. The authors found that HCWs displayed knowledge on the effects of heat stress, negative attitudes and practices regarding PPE usage, and experienced heat strain symptoms. From factor analysis, the questionnaire adequately and appropriately covered the constructs of knowledge, attitudes and practices, but not heat strain symptoms. There is also an association between knowledge of heat stress, and negative attitudes and practices towards PPE usage. Heat stress knowledge and negative attitudes towards PPE usage negatively affected the symptoms experienced by HCWs.

Based on the questionnaire results, HCWs displayed knowledge on the effects of heat stress. More than 72% of HCWs were aware that heat stress has potential negative physical, psychological, and emotional impacts. More than 65% of HCWs were also aware that heat stress can affect their work productivity, judgement, and commitment. Having knowledge on the effects of heat stress was also observed in other studies involving HCWs during the COVID-19 pandemic [3, 4, 19]. This should be expected of most HCWs involved in the questionnaire given that they are medical professionals. However, HCWs displayed negative attitudes and practices regarding PPE usage. More than half of HCWs responded that PPE usage caused discomfort and prevented sweat evaporation, and that they avoided taking breaks to conserve PPE and maintain infection control, and avoided drinking and/or eating to avoid going to the toilet. These negative attitudes and practices were also observed in other qualitative studies conducted during the pandemic [4, 20,21,22]. Poor attitudes and practices regarding PPE usage can increase HCWs’ heat stress exposure, especially when faced with a greater workload duringthe pandemic. This is exacerbated by rising global temperatures, especially if workers work outdoors, or do not have access to air-conditioning. From our study, more than three-quarters of HCWs in India and Vietnam were working in areas without air-conditioning. Taken together, the combination of increasing global temperatures and workload can increase the heat stress exposure faced by HCWs working in PPE, which can worsen their health and well-being during treatment and care activities.

The questionnaire was confirmed using factor analysis to be valid and reliable in measuring HCWs’ knowledge, attitudes and practices towards heat stress and PPE usage. Good internal consistency was observed within these two constructs. Good composite reliability and average variance extracted represented that the questionnaire had sufficient psychometric properties in the areas of knowledge, and attitudes and practices. This was not shown when the questionnaire was administered to HCWs in Singapore and India [3]. However, the questionnaire might not be reliable in assessing heat strain symptoms experienced by the HCWs. A possible reason is that symptoms were self-reported. As some respondents are not medical professionals, self-reported symptoms from these respondents might be inaccurate. Respondents might have also associated the symptoms experienced with other sources such as increased cardiovascular strain, and therefore under-reported heat strain symptoms experienced [3]. Additionally, the dichotomous nature of the items on heat strain symptoms might have caused underestimation of Cronbach’s alpha [23]. The self-reported and dichotomous nature of heat strain symptoms items can explain the low reliability of the questionnaire in assessing heat strain symptoms. Nonetheless, it is important to assess heat strain symptoms experienced by HCWs as early detection of heat strain can prevent the onset of serious heat illnesses. HCWs should be educated on the various heat strain symptoms, and encouraged to take rest or seek medical advice upon experiencing any of the symptoms when working in PPE. Using factor analysis to validate the current questionnaire allowed us to understand the interactions between knowledge, attitudes and practices, and symptoms in relation to heat stress and PPE usage, which could aid the development of better diagnostic tools and more specific heat management strategies.

Using factor analysis, an association was found between HCWs’ knowledge on heat stress and negative attitudes and practices regarding PPE usage. While HCWs have shown knowledge on heat stress [3], their negative attitudes and practices can be due to circumstances at work such as PPE shortages and long working hours during the pandemic [24]. In our study, almost one in four HCWs reported not removing PPE during breaks. Negative practices such as not taking breaks to conserve PPE or to maintain infection control, and not drinking and/or eating to avoid going to the toilet were most associated with heat strain symptoms. Adopting such negative practices can put HCWs at higher risk of heat illnesses. During a pilot study involving HCWs wearing PPE in a high-level isolation unit during a 4 h shift, half the participants had body core temperatures exceeding 38.5°C [25]. In particular, HCWs who avoid drinking and/or eating to avoid going to the toilet are at risk of dehydration and heat-induced kidney diseases [26]. Therefore, while HCWs understood the effects of heat stress, their negative practices towards PPE usage, along with poor attitudes displayed towards PPE usage, exposed them to occupational heat stress and could lead to negative health impacts.

From the structural model, the knowledge, and attitudes and practices displayed by HCWs on heat stress and its associated PPE usage negatively affected the symptoms experienced. Symptoms of thirst, excessive sweating, and dizziness were most experienced. These symptoms were also reported in other surveys administered to HCWs during the pandemic [4, 19, 27,28,29,30]. Similarly, the current study found that the number of heat strain symptoms increased with the number of days spent wearing PPE per week. Despite the inaccuracy of self-reported symptoms, it is essential for HCWs to acknowledge heat strain symptoms they experience. Compounded by the increasing COVID-19 cases requiring hospital care, HCWs who continue working despite thermal discomfort can negatively affect patients under their care due to poor decision-making. Therefore, targeted heat management strategies must be implemented to alleviate these heat strain symptoms.

In the various countries and regions where the questionnaire was administered, there were different safety regulations in place [3, 31, 32]. Based on questionnaire responses, some of the known adverse effects of PPE usage were already well understood by HCWs. However, the use of factor analysis revealed that knowledge on heat stress was not necessarily translated into actions due to the negative attitudes that HCWs displayed towards PPE. This suggests that employers should ascertain the underlying reasons behind HCWs’ negative attitudes and practices regarding PPE usage in order to enforce targeted heat management strategies.

Possible strategies to combat heat stress among HCWs that employers can consider include the provision of sufficient PPE, cool drinking water, and dedicated rest areas for donning and doffing PPE. To mitigate against dehydration and increased body core temperature due to occupational heat exposure [7, 33], cold water dispensers should be easily accessible to HCWs. In Singapore, pre-shift ingestion of ice slurry or cold water was suggested [3, 34], though this might depend on the context of application. Employers should also consider conducting training for donning and doffing of PPE, and managing HCWs’ expectations regarding PPE discomfort [35], which may improve attitudes and practices regarding PPE usage. With global temperatures expected to rise further, implementation of targeted management strategies, and availability of adequate resources, are necessary during a pandemic to protect healthcare workers from heat exposure due to PPE usage and their added workload. Ensuring the health and well-being of HCWs can facilitate a better healthcare system for patient care, especially in the face of global warming and in the event of future pandemics.

Limitations

The authors would like to acknowledge some limitations in this study. Firstly, there might be non-response bias as the survey was conducted voluntarily. Secondly, self-reported data was collected in this study, which relied on the respondents’ memory and could be subjected to social desirability bias, resulting in HCWs over-reporting good practices despite not actually adhering to them. Thirdly, the symptoms HCWs experienced might not have been fully understood due to the low reliability in the symptoms construct. This might have resulted in under-reporting or over-reporting of heat stress symptoms experienced. Future research should aim to develop a better assessment tool for understanding such symptoms.

Conclusion

In summary, self-reported symptoms might not be as accurate as diagnostic assessments, However, HCWs should still self-assess their symptoms for early management of heat stress. Despite knowledge on heat stress, it was suggested that negative attitudes and practices regarding PPE usage contributed to the heat strain symptoms HCWs experienced. Further empirical research is still warranted to ascertain any causative effects. To further improve the understanding of PPE usage and its associated heat stress, healthcare institutions should continue to educate HCWs on occupational heat stress. Additionally, understanding that HCWs’ negative attitudes and practices can lead to occupational heat stress exposure is essential when implementating targeted health management policies and to ensure adequate resources are available for HCWs to manage heat stress. This uncovers an important lesson learnt during the current pandemic, which is relevant and applicable for future emergencies. Further research should aim to investigate the main issues in each country or region in order for more targeted solutions to be implemented to ensure that HCWs caring for patients are also being cared for.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

COVID-19:

Coronavirus disease 2019

HCW:

Healthcare worker

PPE:

Personal protective equipment

References

  1. World Health Organisation. WHO Coronavirus (COVID-19) Dashboard 2023. https://covid19.who.int/. Accessed 3 November 2023.

  2. Bose-O’Reilly S, Daanen H, Deering K, Gerrett N, Huynen M, Lee J, et al. COVID-19 and heat waves: new challenges for healthcare systems. Environ Res. 2021;198:111153.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Lee J, Venugopal V, Latha PK, Alhadad SB, Leow CHW, Goh NY, et al. Heat stress and thermal perception amongst Healthcare Workers during the COVID-19 pandemic in India and Singapore. Int J Environ Res Public Health. 2020;17:21.

    CAS  Google Scholar 

  4. Messeri A, Bonafede M, Pietrafesa E, Pinto I, de’Donato F, Crisci A, et al. A web survey to evaluate the thermal stress associated with personal protective equipment among healthcare workers during the COVID-19 pandemic in Italy. Int J Env Res Pub He. 2021;18(8):3861.

    Article  CAS  Google Scholar 

  5. Foster J, Hodder SG, Goodwin J, Havenith G. Occupational heat stress and practical cooling solutions for healthcare and industry workers during the COVID-19 pandemic. Ann Work Expos Heal. 2020;64(9):915–22.

    Article  Google Scholar 

  6. Potter AW, Gonzalez JA, Xu X. Ebola response: modeling the risk of heat stress from personal protective clothing. PLoS ONE. 2015;10(11):e0143461.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Chaudhari N, Strutton P, Wickham A, McGregor A, Mullington C. Heat stress associated with aerosol PPE and its impact. Occup Med. 2022.

  8. Watts N, Amann M, Arnell N, Ayeb-Karlsson S, Beagley J, Belesova K, et al. The 2020 report of the Lancet countdown on health and climate change: responding to converging crises. The Lancet. 2021;397(10269):129–70.

    Article  Google Scholar 

  9. Daanen H, Bose-O’Reilly S, Brearley M, Flouris DA, Gerrett NM, Huynen M, et al. COVID-19 and thermoregulation-related problems: practical recommendations. Temp (Austin). 2020;8(1):1–11.

    Google Scholar 

  10. Sungbun S, Naknoi S, Somboon P, Thosingha O. Impact of the COVID-19 pandemic crisis on turnover intention among nurses in emergency departments in Thailand: a cross sectional study. BMC Nurs. 2023;22(1):337.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Knekta E, Runyon C, Eddy S. One size doesn’t fit all: using factor analysis to gather validity evidence when using surveys in your research. CBE—Life Sci Educ. 2019;18(1):rm1.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Arifin WN, Yusoff MSB. Confirmatory factor analysis of the Universiti Sains Malaysia Emotional Quotient Inventory among medical students in Malaysia. Sage Open 2016;6(2).

  13. Taber KS. The use of Cronbach’s alpha when developing and reporting research instruments in science education. Res Sci Educ. 2018;48(6):1273–96.

    Article  Google Scholar 

  14. Hooper D, Coughlan J, Mullen MR. Structural equation modelling: guidelines for determining model fit. Electron J Bus Res Methods. 2008;6(1):53–60.

    Google Scholar 

  15. Toth-Kiraly I, Bothe B, Rigo A, Orosz G. An illustration of the exploratory structural equation modeling (ESEM) framework on the passion scale. Front Psychol. 2017;8:1968.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Oberski D. lavaan.survey: an R Package for Complex Survey Analysis of Structural equation models. J Stat Softw. 2014;57(1):1–27.

    Article  Google Scholar 

  17. Svetina D, Rutkowski L, Rutkowski D. Multiple-group invariance with categorical outcomes using updated guidelines: an illustration using Mplus and the lavaan/semTools packages. Struct Equation Modeling-a Multidisciplinary J. 2020;27(1):111–30.

    Article  Google Scholar 

  18. Epskamp S, semPlot. Unified visualizations of structural equation models. Struct Equation Modeling-a Multidisciplinary J. 2015;22(3):474–83.

    Article  MathSciNet  Google Scholar 

  19. Davey SL, Lee BJ, Robbins T, Randeva H, Thake CD. Heat stress and PPE during COVID-19: impact on healthcare workers’ performance, safety and well-being in NHS settings. J Hosp Infect. 2021;108:185–8.

    Article  CAS  PubMed  Google Scholar 

  20. Chen F, Zang Y, Liu Y, Wang X, Lin X. Dispatched nurses’ experience of wearing full gear personal protective equipment to care for COVID-19 patients in China—A descriptive qualitative study. J Clin Nurs. 2021;30(13–14):2001–14.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Hoernke K, Djellouli N, Andrews L, Lewis-Jackson S, Manby L, Martin S, et al. Frontline healthcare workers’ experiences with personal protective equipment during the COVID-19 pandemic in the UK: a rapid qualitative appraisal. Bmj Open. 2021;11(1):e046199.

    Article  PubMed  Google Scholar 

  22. Konwar G, Kakati S, Sarma N. Experiences of nursing professionals involved in the care of COVID-19 patients: a qualitative study. Linguistics and Culture Review. 2022;6:49–58.

    Article  Google Scholar 

  23. Sun W, Chou C-P, Stacy AW, Ma H, Unger J, Gallaher P. SAS and SPSS macros to calculate standardized Cronbach’s alpha using the upper bound of the phi coefficient for dichotomous items. Behav Res Methods. 2007;39(1):71–81.

    Article  PubMed  Google Scholar 

  24. Mhango M, Dzobo M, Chitungo I, Dzinamarira T. COVID-19 risk factors among health workers: a rapid review. Saf Health work. 2020;11(3):262–5.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Herstein JJ, Abdoulaye AA, Jelden KC, Le AB, Beam EL, Gibbs SG, et al. A pilot study of core body temperatures in healthcare workers wearing personal protective equipment in a high-level isolation unit. J Occup Environ Hyg. 2021;18(9):430–5.

    Article  PubMed  Google Scholar 

  26. Chang JC, Yang HY. Epidemiology of chronic kidney disease of undetermined aetiology in Taiwanese farmers: a cross-sectional study from Changhua Community-based Integrated Screening programme. Occup Environ Med. 2021;78(12):849–58.

    Article  PubMed  Google Scholar 

  27. Bongers CC, de Korte JQ, Zwartkruis M, Levels K, Kingma BR, Eijsvogels TM. Heat strain and use of Heat Mitigation Strategies among COVID-19 Healthcare workers wearing personal Protective Equipment—A Retrospective Study. Int J Env Res Pub He. 2022;19(3):1905.

    Article  CAS  Google Scholar 

  28. Tabah A, Ramanan M, Laupland KB, Buetti N, Cortegiani A, Mellinghoff J, et al. Personal protective equipment and intensive care unit healthcare worker safety in the COVID-19 era (PPE-SAFE): an international survey. J Crit Care. 2020;59:70–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Ahmadidarrehsima S, Salari N, Dastyar N, Rafati F. Exploring the experiences of nurses caring for patients with COVID-19: a qualitative study in Iran. BMC Nurs. 2022;21(1):1–7.

    Article  Google Scholar 

  30. Irandoost SF, Yoosefi Lebni J, Safari H, Khorami F, Ahmadi S, Soofizad G, et al. Explaining the challenges and adaptation strategies of nurses in caring for patients with COVID-19: a qualitative study in Iran. BMC Nurs. 2022;21(1):1–16.

    Article  Google Scholar 

  31. Setiawan HW, Pratiwi IN, Nimah L, Pawanis Z, Bakhtiar A, Fauziningtyas R, et al. Challenges for healthcare workers caring for COVID-19 patients in Indonesia: a qualitative study. INQUIRY: The Journal of Health Care Organization Provision and Financing. 2021;58:00469580211060291.

    Google Scholar 

  32. Natural Resources Defense Council International: India. Expanding Heat Resilience Across India: Heat Action Plan Highlights NRDC International: India, May 2020. https://www.nrdc.org/sites/default/files/india-heat-resilient-cities-ib.pdf. Accessed 7 December 2022.

  33. Chapman CL, Hess HW, Lucas RAI, Glaser J, Saran R, Bragg-Gresham J, et al. Occupational heat exposure and the risk of chronic kidney disease of nontraditional origin in the United States. Am J Physiol Regul Integr Comp Physiol. 2021;321(2):R141–R51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Daanen H, Bose-O’Reilly S, Brearley M, Flouris DA, Gerrett NM, Huynen M, et al. COVID-19 and thermoregulation-related problems: practical recommendations. Temperature. 2021;8(1):1–11.

    Article  Google Scholar 

  35. Ruskin KJ, Ruskin AC, Musselman BT, Harvey JR, Nesthus TE, O’Connor M. COVID-19, personal protective equipment, and human performance. Anesthesiology. 2021;134(4):518–25.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study was supported by the Ministry of Science and Technology in Taiwan (grant number MOST 109-2314-B-002-166-MY3), the Population Health Research Center from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan (grant number NTU-112L9004), the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme, and the Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada. The funding bodies played no role in the design or execution of these studies beyond financial support.

Author information

Author notes

  1. Hsiao-Yu Yang and Clarence Hong Wei Leow contributed equally to this work and should be considered co-first authors.

Authors and Affiliations

  1. Institute of Environmental and Occupational Health Sciences, National Taiwan University College of Public Health, 10055, Taipei, Taiwan

    Hsiao-Yu Yang

  2. Department of Public Health, National Taiwan University College of Public Health, 10055, Taipei, Taiwan

    Hsiao-Yu Yang

  3. Department of Environmental and Occupational Medicine, National Taiwan University Hospital, 100225, Taipei, Taiwan

    Hsiao-Yu Yang

  4. Population Health Research Center, National Taiwan University, 10617, Taipei City, Taiwan

    Hsiao-Yu Yang

  5. Department of Nursing, Asia Eastern University of Science and Technology, 220303, New Taipei City, Taiwan

    Hsiu-Ling Chou

  6. Department of Nursing, Far Eastern Memorial Hospital, 220216, New Taipei City, Taiwan

    Hsiu-Ling Chou

  7. Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, 117593, Singapore, Singapore

    Clarence Hong Wei Leow & Jason Kai Wei Lee

  8. Campus for Research Excellence and Technological Enterprise (CREATE), National University of Singapore, 138602, Singapore, Singapore

    Clarence Hong Wei Leow & Jason Kai Wei Lee

  9. Department of Nursing, Wan Fang Hospital, Taipei Medical University, 116079, Taipei, Taiwan

    Ching-Chiu Kao

  10. School of Nursing, College of Nursing, Taipei Medical University, 110301, Taipei, Taiwan

    Ching-Chiu Kao

  11. Department of Health Behaviour, Environment and Social Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, 55281, Yogyakarta, Indonesia

    D. Daniel & Vena Jaladara

  12. Department of Community Medicine, Faculty of Medicine, Universitas Indonesia, 10430, Jakarta, Indonesia

    Levina Chandra Khoe & Dewi Sumaryani Soemarko

  13. Sri Ramachandra Institute of Higher Education & Research, 600116, Chennai, Tamil Nadu, India

    P K Latha & Vidhya Venugopal

  14. Center for Tropical Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, 55281, Yogyakarta, Indonesia

    Yodi Mahendradhata

  15. Department of Health Policy and Management, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, 55281, Yogyakarta, Indonesia

    Yodi Mahendradhata

  16. Department of Military Occupational Medicine, Vietnam Military Medical University, Hanoi, Vietnam

    Phuong Minh Nguyen

  17. Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, 10700, Bangkok, Thailand

    Rujipas Sirijatuphat

  18. Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, 12144, Rensselaer, NY, USA

    Kai Zhang

  19. Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, 117593, Singapore, Singapore

    Jason Kai Wei Lee

  20. Heat Resilience and Performance Centre, Yong Loo Lin School of Medicine, National University of Singapore, Block MD9, 2 Medical Drive Level 4, 117593, Singapore, Singapore

    Jason Kai Wei Lee

Authors
  1. Hsiao-Yu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hsiu-Ling Chou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Clarence Hong Wei Leow
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ching-Chiu Kao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. D. Daniel
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Vena Jaladara
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Levina Chandra Khoe
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. P K Latha
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yodi Mahendradhata
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Phuong Minh Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Rujipas Sirijatuphat
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Dewi Sumaryani Soemarko
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Vidhya Venugopal
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Kai Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Jason Kai Wei Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

HYY, HLC and JKWL conceptualized and designed the study. HYY, HLC, CHWL, CCK, DD, VJ, LCK, PKL, YM, PMN, RS, DSS, VV and JKWL contributed to the data collection. HYY and HWCL analysed and interpreted the data. HYY prepared the original draft and HYY, CHWL, DD, VJ, LCK, PKL, YM, PMN, RS, DSS, VV, KZ and JKWL reviewed and edited the draft. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Jason Kai Wei Lee.

Ethics declarations

Ethical approval and consent to participate

This study received ethical approval from the Research Ethics Committee of National Taiwan University (Taiwan; 202106HM031), Sri Ramachandra Institution of Higher Education and Research (India; IEC-NI/17/APR/59/54), National Healthcare Group Domain Specific Review Board (Singapore; 2020/00590), Siriraj Institutional Review Board (Thailand; Si277/2020), Vietnam Military Medical University Ethics Committee for Biomedical Research (Vietnam; 4812/QD-HVQY), Medical and Health Research Ethics Committee (Indonesia; KE/FK/0302/EC/2021) and Universitas Indonesia (Indonesia; KET-566/UN2.F1/ETIK/PPM.00.02/2021). All methods were performed in accordance with the relevant guidelines and regulations. All participants provided informed consent before commencing the questionnaire.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, HY., Chou, HL., Leow, C.H.W. et al. Poor personal protective equipment practices were associated with heat-related symptoms among Asian healthcare workers: a large-scale multi-national questionnaire survey. BMC Nurs 23, 145 (2024). https://doi.org/10.1186/s12912-024-01770-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12912-024-01770-x

Keywords

BMC Nursing

ISSN: 1472-6955

Contact us