Safety Climate and the Impact of the COVID-19 Pandemic: An Investigation on Safety Perceptions among Farmers in Italy
Abstract
:1. Introduction
2. Research Background and Motivations
2.1. OHS in Agriculture
2.2. Safety Measures to Prevent COVID-19 in Agriculture
- Use of specific personal protective equipment (PPE), such as respiratory protection masks and disposable gloves;
- Distancing, reduction of the number of workers allowed to stay at the workplace simultaneously, definition of specific routes to avoid workers’ gathering, working shifts;
- Disinfection and cleaning procedures for workers, work equipment, workplaces;
- Worker screening, such as temperature checking, COVID-19 test campaigns, etc.;
- Specific information and training of workers.
2.3. Research Issues
3. Research Approach
3.1. The NOSACQ-50 Questionnaire
- Dim1—Management safety priority, commitment, and competence: 9 items to assess how workers perceive safety management;
- Dim2—Management safety empowerment: 7 items to assess how workers perceive management empowerment;
- Dim3—Management safety justice: 6 items to assess workers’ perceptions of accident management;
- Dim4—Workers’ safety commitment: 6 items to estimate the perception of workers’ commitment to safety;
- Dim5—Workers’ safety priority and risk non-acceptance: 7 items to evaluate risk-taking attitudes and safety prioritization in working tasks;
- Dim6—Safety communication, learning, and trust in coworkers’ safety competence: 8 items to assess the perception of the exchange of safety knowledge and experiences among workers;
- Dim7—Trust in the efficacy of safety systems: 7 items to evaluate how workers perceive the benefits due to safety planning, training, monitoring, etc.
3.2. The COVID-19 Questionnaire
- C1.
- The management provides adequate information on the OHS risks related to COVID-19.
- C2.
- OHS procedures for preventing COVID-19 have been modified adequately.
- C3.
- The use of safety devices and Personal Protective Equipment (PPE) is adequate.
- C4.
- Work procedures (i.e., those related to daily activities) have substantially changed due to the COVID-19 outbreak.
3.3. Survey Features
4. Results
4.1. The NOSACQ-50 Output
4.2. The COVID-19 Questionnaire
- C1.
- The management provides adequate information on the OHS risks related to COVID-19.
- C2.
- OHS procedures for preventing COVID-19 have been modified adequately.
- C3.
- The use of safety devices and Personal Protective Equipment (PPE) is adequate.
- C4.
- Work procedures (i.e., those related to daily activities) have changed due to the COVID-19 outbreak substantially.
5. Discussion of Results
5.1. Implications of the Study
5.2. Limitations
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
- Nicola, M.; Alsafi, Z.; Sohrabi, C.; Kerwan, A.; Al-Jabir, A.; Iosifidis, C.; Agha, M.; Agha, R. The socio-economic implications of the coronavirus pandemic (COVID-19): A review. Int. J. Surg. 2020, 78, 185–193. [Google Scholar] [CrossRef] [PubMed]
- Pulighe, G.; Lupia, F. Food first: COVID-19 outbreak and cities lockdown a booster for a wider vision on urban agriculture. Sustainability 2020, 12, 5012. [Google Scholar] [CrossRef]
- Devereux, S.; Béné, C.; Hoddinott, J. Conceptualising COVID-19′s impacts on household. Food Secur. 2020, 12, 769–772. [Google Scholar] [CrossRef] [PubMed]
- Worldometer. COVID-19 Coronavirus Pandemic. Available online: https://www.worldometers.info/coronavirus/ (accessed on 31 March 2021).
- Prati, G.; Mancini, A.D. The psychological impact of COVID-19 pandemic lockdowns: A review and meta-analysis of longitudinal studies and natural experiments. Psychol. Med. 2021, 51, 201–211. [Google Scholar] [CrossRef] [PubMed]
- Li, H.Y.; Cao, H.; Leung, D.Y.P.; Mak, Y.W. The Psychological Impacts of a COVID-19 Outbreak on College Students in China: A Longitudinal Study. Int. J. Environ. Res. Public Health 2020, 17, 3933. [Google Scholar] [CrossRef] [PubMed]
- The Nordic Council of Ministers. Safety Climate Questionnaire—NOSACQ-50. Available online: https://nfa.dk/da/Vaerktoejer/Sporgeskemaer/Safety-Climate-Questionnaire-NOSACQ50/ (accessed on 19 January 2021).
- Fargnoli, M.; Lombardi, M. NOSACQ-50 for Safety Climate Assessment in Agricultural Activities: A Case Study in Central Italy. Int. J. Environ. Res. Public Health 2020, 17, 9177. [Google Scholar] [CrossRef] [PubMed]
- Marin, L.S.; Lipscomb, H.; Cifuentes, M.; Punnett, L. Perceptions of safety climate across construction personnel: Associations with injury rates. Saf. Sci. 2019, 118, 487–496. [Google Scholar] [CrossRef]
- Marín, L.S.; Lipscomb, H.; Cifuentes, M.; Punnett, L. Associations between safety climate and safety management practices in the construction industry. Am. J. Ind. Med. 2017, 60, 557–568. [Google Scholar] [CrossRef] [PubMed]
- Pinzke, S.; Svennefelt, C.A.; Lundqvist, P. Occupational injuries in Swedish agriculture–development and Preventive actions. J. Agric. Saf. Health 2018, 24, 193–211. [Google Scholar] [CrossRef]
- Randall, J.R.; Pennetta De Oliveira, L.; Belton, K.; Voaklander, D. Agriculture-related Injuries: Discussion in Canadian Media. J. Agromed. 2020, 25, 312–318. [Google Scholar] [CrossRef] [PubMed]
- Mishra, D.; Satapathy, S. A framework designed for macro-ergonomical analysis of Indian farmers: Assessment and analysis of occupational injuries of agricultural farmers of South Odisha in India. In Advanced Macroergonomics and Sociotechnical Approaches for Optimal Organizational Performance; Realyvásquez, A., Maldonado-Macías, A.A., Arredondo, K.C., Eds.; IGI Global: Hershey, PA, USA; pp. 162–183. [CrossRef] [Green Version]
- Fargnoli, M.; Vita, L.; Gattamelata, D.; Laurendi, V.; Tronci, M. A reverse engineering approach to enhance machinery design for safety. In DS 70, Proceedings of the DESIGN 2012, the 12th International Design Conference, Dubrovnik, Croatia, 21–24 May 2012; Marjanovic, D., Storga, M., Pavkovic, N., Bojcetic, N., Eds.; International Design Conference: Dubrovnik, Croatia, 2012; pp. 627–636. ISBN 978-953-7738-17-4. [Google Scholar]
- Micheletti Cremasco, M.; Caffaro, F.; Giustetto, A.; Vigoroso, L.; Paletto, G.; Cavallo, E. Tractor rollover protection: Is the incorrect use of foldable rollover protective structures due to human or to technical issues? Hum. Factors 2020, 62, 64–76. [Google Scholar] [CrossRef] [PubMed]
- Taattola, K.; Rautiainen, R.H.; Karttunen, J.P.; Suutarinen, J.; Viluksela, M.K.; Louhelainen, K.; Mäittälä, J. Risk factors for occupational injuries among full-time farmers in Finland. J. Agric. Saf. Health 2012, 18, 83–93. [Google Scholar] [CrossRef] [PubMed]
- Fargnoli, M.; Lombardi, M.; Haber, N.; Puri, D. The Impact of Human Error in the Use of Agricultural Tractors: A Case Study Research in Vineyard Cultivation in Italy. Agriculture 2018, 8, 82. [Google Scholar] [CrossRef] [Green Version]
- Kogler, R.; Quendler, E.; Boxberger, J. Occupational accidents with agricultural machinery in Austria. J. Agromed. 2016, 21, 61–70. [Google Scholar] [CrossRef] [PubMed]
- Caffaro, F.; Lundqvist, P.; Micheletti Cremasco, M.; Pinzke, S.; Cavallo, E. Machinery-related perceived risks and safety attitudes in senior Swedish farmers. J. Agromed. 2018, 23, 78–91. [Google Scholar] [CrossRef] [PubMed]
- Olowogbon, T.S.; Babatunde, R.O.; Asiedu, E.; Yoder, A.M. Agrochemical Health Risks Exposure and Its Determinants: Empirical Evidence among Cassava Farmers in Nigeria. J. Agromed. 2020, 199–210. [Google Scholar] [CrossRef] [PubMed]
- Italian National Institute of Statistics (ISTAT). Survey on the Labour Market in Italy. Available online: https://www.istat.it/en/archive/labour+market (accessed on 25 January 2021).
- INAIL (Italian Workers’ Compensation Authority). Database on Occupational Accidents. Available online: https://www.inail.it/cs/internet/attivita/dati-e-statistiche/banca--dati-statistica.html (accessed on 25 January 2021).
- Fargnoli, M.; Lombardi, M.; Haber, N. A fuzzy-QFD approach for the enhancement of work equipment safety: A case study in the agriculture sector. Int. J. Reliab. Saf. 2018, 12, 306–326. [Google Scholar] [CrossRef]
- Zambon, I.; Cecchini, M.; Egidi, G.; Saporito, M.G.; Colantoni, A. Revolution 4.0: Industry vs. Agriculture in a Future Development for SMEs. Processes 2019, 7, 36. [Google Scholar] [CrossRef] [Green Version]
- Colantoni, A.; Monarca, D.; Laurendi, V.; Villarini, M.; Gambella, F.; Cecchini, M. Smart Machines, Remote Sensing, Precision Farming, Processes, Mechatronic, Materials and Policies for Safety and Health Aspects. Agriculture 2018, 8, 47. [Google Scholar] [CrossRef] [Green Version]
- Fargnoli, M.; Lombardi, M.; Puri, D.; Casorri, L.; Masciarelli, E.; Mandić-Rajčević, S.; Colosio, C. The Safe Use of Pesticides: A Risk Assessment Procedure for the Enhancement of Occupational Health and Safety (OHS) Management. Int. J. Environ. Res. Public Health 2019, 16, 310. [Google Scholar] [CrossRef] [Green Version]
- Yoder, A.M.; Sorensen, J.A.; Foster, F.; Myers, M.; Murphy, D.; Cook, G.; May, J.; Jenkins, P. Selecting Target Populations for ROPS Retrofit Programs in Pennsylvania and Vermont. J. Agric. Saf. Health 2013, 19, 175–190. [Google Scholar] [CrossRef] [PubMed]
- Rajmohan, K.S.; Chandrasekaran, R.; Varjani, S. A Review on occurrence of pesticides in environment and current technologies for their remediation and management. Indian J. Microbiol. 2020, 60, 125–138. [Google Scholar] [CrossRef]
- Svennefelt, C.A.; Hunter, E.; Lundqvis, P. Evaluating the Swedish approach to motivating improved work safety conditions on farms: Insights from fear appeals and the extended parallel processing model. J. Agromed. 2018, 4, 355–373. [Google Scholar] [CrossRef]
- Wilmsen, C.; Castro, A.B.D.; Bush, D.; Harrington, M.J. System failure: Work organization and injury outcomes among Latino forest workers. J. Agromed. 2019, 24, 186–196. [Google Scholar] [CrossRef] [PubMed]
- Fugas, C.S.; Silva, S.A.; Meliá, J.L. Another look at safety climate and safety behavior: Deepening the cognitive and social mediator mechanisms. Accid. Anal. Prev. 2012, 45, 468–477. [Google Scholar] [CrossRef] [PubMed]
- Irwin, A.; Poots, J. Investigation of UK farmer go/no-go decisions in response to tractor-based risk scenarios. J. Agromed. 2018, 23, 154–165. [Google Scholar] [CrossRef] [PubMed]
- Fargnoli, M.; Lombardi, M. Safety Vision of Agricultural Tractors: An Engineering Perspective Based on Recent Studies (2009–2019). Safety 2020, 6, 1. [Google Scholar] [CrossRef] [Green Version]
- Caffaro, F.; Roccato, M.; Micheletti Cremasco, M.; Cavallo, E. Falls from Agricultural Machinery: Risk Factors Related to Work Experience, Worked Hours, and Operators’ Behavior. Hum. Factors 2018, 60, 20–30. [Google Scholar] [CrossRef] [PubMed]
- Ruiz-Frutos, C.; Ortega-Moreno, M.; Allande-Cussó, R.; Dominguez-Salas, S.; Dias, A.; Gomez-Salgado, J. Health-related factors of psychological distress during the COVID-19 pandemic among non-health workers in Spain. Saf. Sci. 2021, 133, 104996. [Google Scholar] [CrossRef] [PubMed]
- Tomczyk, S.; Rahn, M.; Schmidt, S. Social Distancing and Stigma: Association between Compliance with Behavioral Recommendations, Risk Perception, and Stigmatizing Attitudes during the COVID-19 Outbreak. Front. Psychol. 2020, 11. [Google Scholar] [CrossRef] [PubMed]
- Cirrincione, L.; Plescia, F.; Ledda, C.; Rapisarda, V.; Martorana, D.; Moldovan, R.E.; Theodoridou, K.; Cannizzaro, E. COVID-19 Pandemic: Prevention and Protection Measures to Be Adopted at the Workplace. Sustainability 2020, 12, 3603. [Google Scholar] [CrossRef]
- Italian Ministry of Health. Safety Measures to Mitigate Covid-19 Outbreak. Available online: http://www.salute.gov.it/portale/nuovocoronavirus/dettaglioContenutiNuovoCoronavirus.jsp?lingua=italiano&id=5383&area=nuovoCoronavirus&menu=vuoto (accessed on 25 January 2021). (In Italian)
- Trentino Agricoltura. Covid-19 Safety Measures in Agriculture. Available online: http://www.trentinoagricoltura.it/Trentino-Agricoltura/COVID-19-Disposizioni-ed-informazioni-utili/Protocolli-di-salute-e-sicurezza-sul-lavoro-in-agricoltura-e-lavori-forestali-e-altri-settori-di-interesse (accessed on 25 January 2021). (In Italian).
- Kim, S.; Kim, P.B.; Lee, G. Predicting hospitality employees’ safety performance behaviours in the COVID-19 pandemic. Int. J. Hosp. Manag. 2021, 93, 102797. [Google Scholar] [CrossRef]
- Xie, K.; Liang, B.; Dulebenets, M.A.; Mei, Y. The Impact of Risk Perception on Social Distancing during the COVID-19 Pandemic in China. Int. J. Environ. Res. Public Health 2020, 17, 6256. [Google Scholar] [CrossRef] [PubMed]
- Flocks, J. The potential impact of COVID-19 on H-2A agricultural workers. J. Agromed. 2020, 367–369. [Google Scholar] [CrossRef] [PubMed]
- Butu, A.; Brumă, I.S.; Tanasă, L.; Rodino, S.; Dinu Vasiliu, C.; Doboș, S.; Butu, M. The Impact of COVID-19 Crisis upon the Consumer Buying Behavior of Fresh Vegetables Directly from Local Producers. Case Study: The Quarantined Area of Suceava County, Romania. Int. J. Environ. Res. Public Health 2020, 17, 5485. [Google Scholar] [CrossRef] [PubMed]
- Sharma, R.; Shishodia, A.; Kamble, S.; Gunasekaran, A.; Belhadi, A. Agriculture supply chain risks and COVID-19: Mitigation strategies and implications for the practitioners. Int. J. Logist. Res. Appl. 2020, 1–27. [Google Scholar] [CrossRef]
- Bochtis, D.; Benos, L.; Lampridi, M.; Marinoudi, V.; Pearson, S.; Sørensen, C.G. Agricultural Workforce Crisis in Light of the COVID-19 Pandemic. Sustainability 2020, 12, 8212. [Google Scholar] [CrossRef]
- Riden, H.E.; Schilli, K.; Pinkerton, K.E. Rapid Response to COVID-19 in Agriculture: A Model for Future Crises. J. Agromed. 2020, 392–395. [Google Scholar] [CrossRef] [PubMed]
- Kines, P.; Lappalainen, J.; Mikkelsen, K.L.; Olsen, E.; Pousette, A.; Tharaldsen, J.; Tómasson, K.; Törner, M. Nordic Safety Climate Questionnaire (NOSACQ-50): A new tool for diagnosing occupational safety climate. Int. J. Ind. Ergon. 2011, 41, 634–646. [Google Scholar] [CrossRef]
- Kines, P.; Lappalainen, J.; Mikkelsen, K.L.; Olsen, E.; Pousette, A.; Tharaldsen, J.; Tómasson, K.M.T. The Nordic Safety Climate Questionnaire (NOSACQ-50). Available online: http://www.arbejdsmiljoforskning.dk/da/publikationer/spoergeskemaer/nosacq-50 (accessed on 16 January 2021).
- Voon, H.; Ariff, T.M. Factors influencing safety behaviour among primary school teachers in Kuala Nerus, Malaysia. Int. J. Recent Technol. Eng. 2019, 8, 345–351. [Google Scholar] [CrossRef]
- Lagerstrom, E.; Magzamen, S.; Kines, P.; Brazile, W.; Rosecrance, J. Determinants of Safety Climate in the Professional Logging Industry. Safety 2019, 5, 35. [Google Scholar] [CrossRef] [Green Version]
- Sukapto, P.; Octavia, J.R.; Pundarikasutra, P.A.D.; Ariningsh, P.K.; Susanto, S. Improving occupational health and safety and in the home-based footwear industry through im-plementation of ILO-PATRIS, NOSACQ-50 and participatory ergonomics: A case study. Int. J. Technol. 2019, 10, 908–917. [Google Scholar] [CrossRef] [Green Version]
- Kwon, Y.T.; Son, S.; Kim, S.; Ha, S.G.; Son, K. Worker safety perception analysis of South Korean construction sites. Int. J. Occup. Saf. Ergon. 2019, 488–496. [Google Scholar] [CrossRef] [PubMed]
- Sukapto, P.; Djojosoebroto, H.; Bonita; Susanto, S.; Ariningsih, P.K. A new approach to the assessment of the safety environment and performance in the footwear industry. Int. J. Simul. Sys. Sci. Technol. 2018, 19, 14.1–14.7. [Google Scholar] [CrossRef]
- Nadhim, E.; Hon, C.; Xia, B.; Stewart, I.; Fang, D. Investigating the Relationships between Safety Climate and Safety Performance Indicators in Retrofitting Works. Constr. Econ. Build. 2018, 18, 110–129. [Google Scholar] [CrossRef] [Green Version]
- Arifin, K.; Abudin, R.; Razman, M.R.; Ismail, Z.S. Safety of climate levels related to the safety management on empowerment dimension aspects. Information 2017, 20, 4921–4926. [Google Scholar]
- Yousefi, Y.; Jahangiri, M.; Choobineh, A.; Tabatabaei, H.; Keshavarzi, S.; Shams, A.; Mohammadi, Y. Validity assessment of the Persian version of the Nordic Safety Climate Questionnaire (NOSACQ-50): A case study in a steel company. Saf. Health Work 2016, 7, 326–330. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sutalaksana, I.Z.; Anatasia, M. Linking safety climate perception to types of behavior. Work 2016, 55, 231–239. [Google Scholar] [CrossRef] [PubMed]
- Lipscomb, H.J.; Schoenfisch, A.L.; Cameron, W. Non-reporting of work injuries and aspects of jobsite safety climate and behavioral-based safety elements among carpenters in Washington state. Am. J. Ind. Med. 2015, 58, 411–421. [Google Scholar] [CrossRef] [PubMed]
- Guldenmund, F.; Cleal, B.; Mearns, K. An exploratory study of migrant workers and safety in three European countries. Saf. Sci. 2013, 52, 92–99. [Google Scholar] [CrossRef]
- Bergh, M.; Shahriari, M.; Kines, P. Occupational safety climate and shift work. Chem. Eng. Trans. 2013, 31, 403–408. [Google Scholar] [CrossRef]
- Gao, R.; Chan, A.; Utama, W.; Zahoor, H. Multilevel Safety Climate and Safety Performance in the Construction Industry: Development and Validation of a Top-Down Mechanism. Int. J. Environ. Res. Public Health 2016, 13, 1100. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zahoor, H.; Chan, A.; Utama, W.; Gao, R.; Zafar, I. Modeling the Relationship between Safety Climate and Safety Performance in a Developing Construction Industry: A Cross-Cultural Validation Study. Int. J. Environ. Res. Public Health 2017, 14, 351. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mazzetti, G.; Valente, E.; Guglielmi, D.; Vignoli, M. Safety Doesn’t Happen by Accident: A Longitudinal Investigation on the Antecedents of Safety Behavior. Int. J. Environ. Res. Public Health 2020, 17, 4332. [Google Scholar] [CrossRef] [PubMed]
- Sadeghi, L.; Dantan, J.Y.; Siadat, A.; Marsot, J. Design for human safety in manufacturing systems: Applications of design theories, methodologies, tools and techniques. J. Eng. Des. 2016, 27, 844–877. [Google Scholar] [CrossRef] [Green Version]
- Tavakol, M.; Dennick, R. Making sense of Cronbach’s alpha. Int. J. Med. Educ. 2011, 2, 53. [Google Scholar] [CrossRef] [PubMed]
- Pearson, K. Note on regression and inheritance in the case of two parents. Proc. R. Soc. Lond. 1895, 58, 240–242. [Google Scholar]
- Gyekye, S. A. Workers’ perceptions of workplace safety: An African perspective. Int. J. Occup. Saf. Ergon. 2006, 12, 31–42. [Google Scholar] [CrossRef] [PubMed]
- Sorensen, J.A.; Tinc, P.J.; Weil, R.; Droullard, D. Symbolic interactionism: A framework for understanding risk-taking behaviors in farm communities. J. Agromed. 2017, 22, 26–35. [Google Scholar] [CrossRef] [PubMed]
- Caffaro, F.; Micheletti Cremasco, M.; Roccato, M.; Cavallo, E. It does not occur by chance: A mediation model of the influence of workers’ characteristics, work environment factors, and near misses on agricultural machinery-related accidents. Int. J. Occup. Environ. Health 2017, 23, 52–59. [Google Scholar] [CrossRef] [PubMed]
- Damalas, C.A.; Koutroubas, S.D.; Abdollahzadeh, G. Drivers of Personal Safety in Agriculture: A Case Study with Pesticide Operators. Agriculture 2019, 9, 34. [Google Scholar] [CrossRef] [Green Version]
- Marin, L.S.; Cifuentes, M.; Roelofs, C. Results of a community-based survey of construction safety climate for Hispanic workers. Int. J. Occup. Environ. 2015, 21, 223–231. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fargnoli, M.; Lombardi, M.; Haber, N.; Guadagno, F. Hazard Function Deployment: A QFD based tool for the assessment of working tasks—A practical study in the construction industry. Int. J. Occup. Saf. Ergon. 2020, 26, 348–369. [Google Scholar] [CrossRef] [PubMed]
- Mosly, I.; Makki, A.A. Safety Climate Perceptions in the Construction Industry of Saudi Arabia: The Current Situation. Int. J. Environ. Res. Public Health 2020, 17, 6717. [Google Scholar] [CrossRef] [PubMed]
- Gittleman, J.L.; Gardner, P.C.; Haile, E.; Sampson, J.M.; Cigularov, K.P.; Ermann, E.D.; Stafford, P.; Chen, P.Y. Case study citycenter and cosmopolitan construction projects, las vegas, nevada: Lessons learned from the use of multiple sources and mixed methods in a safety needs assessment. J. Saf. Res. 2010, 41, 263–281. [Google Scholar] [CrossRef] [PubMed]
- Prussia, G.E.; Brown, K.A.; Willis, P. Mental models of safety: Do managers and employees see eye to eye? J. Saf. Res. 2003, 34, 143–156. [Google Scholar] [CrossRef]
- Seddighi, H.; Dollard, M.F.; Salmani, I. Psychosocial Safety Climate of Employees during COVID-19 in Iran: A Policy Analysis. Disaster Med. Pub. Health Prep. 2020, 1–19. [Google Scholar] [CrossRef] [PubMed]
- Lestari, F.; Sunindijo, R.Y.; Loosemore, M.; Kusminanti, Y.; Widanarko, B. A Safety Climate Framework for Improving Health and Safety in the Indonesian Construction Industry. Int. J. Environ. Res. Public Health 2020, 17, 7462. [Google Scholar] [CrossRef]
- Shirali, G.A.; Shekari, M.; Angali, K.A. Quantitative assessment of resilience safety culture using principal components analysis and numerical taxonomy: A case study in a petrochemical plant. J. Loss Prev. Process Ind. 2016, 40, 277–284. [Google Scholar] [CrossRef]
- Wu, X.; Li, Y.; Yao, Y.; Luo, X.; He, X.; Yin, W. Development of Construction Workers Job Stress Scale to Study and the Relationship between Job Stress and Safety Behavior: An Empirical Study in Beijing. Int. J. Environ. Res. Public Health 2018, 15, 2409. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chen, W.; Lu, C.; Liu, S.; Wang, M. Measuring the perception of safety among Taiwan construction managers. J. Civ. Eng. Manag. 2013, 19, 37–48. [Google Scholar] [CrossRef] [Green Version]
- Yin, R.K. Qualitative Research from Start to Finish; The Guilford Press: New York, NY, USA, 2011. [Google Scholar]
Score (s) | Level | Meaning |
---|---|---|
s > 3.30 | good | maintain and continue the development of the safety climate dimension |
3.00 < s < 3.30 | fairly good | the safety climate dimension requires a certain improvement |
2.70 < s < 2.99 | fairly low | the safety climate dimension requires an improvement |
s < 2.70 | low | the safety climate dimension requires a considerable improvement |
Authors | Year | Investigation Sector/Industry |
---|---|---|
Fargnoli and Lombardi [8] | 2020 | Agriculture |
Marín, L.S. et al. [9] | 2019 | Construction |
Voon and Ariff [49] | 2019 | Teachers |
Lagerstrom et a. [50] | 2019 | Logging |
Sukapto et al. [51] | 2019 | Footwear |
Kwon et al. [52] | 2019 | Construction |
Sukapto et al. [53] | 2018 | Footwear |
Nadhim et al. [54] | 2018 | Construction |
Arifin et al. [55] | 2017 | Public sector (office workers) |
Yousefi et al. [56] | 2016 | Iron and steel |
Sutalaksana et al. [57] | 2016 | Chemical, Mining, Oil, Gas |
Lipscomb et al. [58] | 2015 | Construction |
Guldenmund et al. [59] | 2013 | Construction, Industry, Agriculture |
Bergh et al. [60] | 2013 | Chemical |
Kines et al. [47] | 2011 | Construction, Food industry |
Score (s) | Level | Meaning |
---|---|---|
s > 3.30 | good | High impact of the COVID-19 measure |
3.00 < s < 3.30 | fairly good | Moderate impact of the COVID-19 measure |
2.70 < s < 2.99 | fairly low | Little impact of the COVID-19 measure |
s < 2.70 | low | Scarce impact of the COVID-19 measure |
Title 1 | Title 2 | Title 3 |
---|---|---|
Age | Mean | 42.9 years |
Max | 67 years | |
Min | 25 years | |
Gender | Male | 57 (71.2%) |
Female | 23 (28.7%) | |
Position | Manager | 26 (32.5%) |
Worker | 54 (67.5%) |
Dimensions | Meaning | Total | Managers | Workers |
---|---|---|---|---|
Dim1 | Management safety priority, commitment, and competence | 3.16 | 3.51 | 2.99 |
Dim2 | Management safety empowerment | 3.04 | 3.40 | 2.88 |
Dim3 | Management safety justice | 3.11 | 3.38 | 2.98 |
Dim4 | Workers’ safety commitment | 3.10 | 3.17 | 3.06 |
Dim5 | Workers’ safety priority and risk non-acceptance | 2.80 | 3.00 | 2.70 |
Dim6 | Safety communication, learning, and trust in co-workers safety competence | 3.01 | 2.98 | 3.03 |
Dim7 | Trust in the efficacy of safety systems | 3.09 | 3.38 | 2.95 |
Cronbach’s Alpha | Test reliability α > 0.70 | 0.82 | 0.83 | 0.71 |
Total | Managers | Workers | ||||
---|---|---|---|---|---|---|
Value | % | Value | % | Value | % | |
Dim1 | 0.24 | 5.92 | 0.36 | 8.96 | 0.19 | 4.75 |
Dim2 | 0.05 | 1.37 | 0.11 | 2.64 | −0.05 | −1.25 |
Dim3 | 0.05 | 1.21 | 0.15 | 3.87 | 0.00 | 0.00 |
Dim4 | 0.26 | 6.40 | 0.26 | 6.58 | 0.27 | 6.75 |
Dim5 | 0.13 | 3.16 | 0.24 | 6.00 | 0.08 | 2.00 |
Dim6 | −0.01 | −0.23 | −0.09 | −2.35 | 0.04 | 1.00 |
Dim7 | 0.14 | 3.48 | 0.21 | 5.23 | 0.10 | 2.50 |
C1 | C2 | C3 | C4 | Ctot | Cronbach’s Alpha | |
---|---|---|---|---|---|---|
Total | 3.61 | 2.90 | 3.31 | 2.45 | 3.07 | 0.73 |
Managers | 3.54 | 3.04 | 3.38 | 2.62 | 3.14 | 0.70 |
Workers | 3.65 | 2.83 | 3.28 | 2.37 | 3.03 | 0.76 |
Dim1 | Dim2 | Dim3 | Dim4 | Dim5 | Dim6 | Dim7 | |
---|---|---|---|---|---|---|---|
Ctot | 0.27 | 0.10 | 0.01 | −0.05 | −0.07 | 0.04 | 0.18 |
Cman | 0.03 | −0.07 | −0.38 | −0.32 | −0.31 | −0.08 | −0.16 |
Cwork | 0.39 | 0.14 | 0.18 | 0.11 | 0.01 | 0.17 | 0.30 |
Dim1 | Dim2 | Dim3 | Dim4 | Dim5 | Dim6 | Dim7 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
t | p | t | p | t | p | t | p | t | p | t | p | t | p | |
Ctot | 1.177 | 0.241 | 0.322 | 0.748 | 0.532 | 0.596 | 0.334 | 0.739 | 3.386 | 0.001 * | 0.870 | 0.386 | 0.264 | 0.792 |
Cman | 2.907 | 0.005 * | 1.843 | 0.071 | 1.779 | 0.081 | 0.179 | 0.859 | 0.982 | 0.331 | 1.333 | 0.189 | 1.788 | 0.080 |
Cwork | 0.531 | 0.596 | 1.953 | 0.053 | 0.683 | 0.496 | 0.285 | 0.776 | 3.571 | 0.001 * | 0.060 | 0.953 | 0.912 | 0.364 |
Workers (Dataset 1)—Managers (Dataset 2) | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Dim1 | Dim2 | Dim3 | Dim4 | Dim5 | Dim6 | Dim7 | ||||||||
Dataset | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 |
Sample size | 54 | 26 | 54 | 26 | 54 | 26 | 54 | 26 | 54 | 26 | 54 | 26 | 54 | 26 |
Average value | 2.99 | 3.51 | 2.88 | 3.40 | 2.98 | 3.38 | 3.06 | 3.17 | 2.70 | 3.00 | 3.03 | 2.98 | 2.95 | 3.38 |
Standard Deviation | 0.32 | 0.37 | 0.26 | 0.46 | 0.31 | 0.45 | 0.42 | 0.64 | 0.44 | 0.54 | 0.21 | 0.38 | 0.40 | 0.42 |
t | 6.475 | 6.459 | 4.734 | 0.959 | 2.674 | 0.781 | 4.395 | |||||||
p | 7.73 × 10−9 * | 8.27 × 10−9 * | 0.00001 * | 0.3403 | 0.00913 * | 0.43701 | 0.00003 * |
Workers (Dataset 1)—Managers (Dataset 2) | |||||
---|---|---|---|---|---|
C1 | C2 | C3 | C4 | Ctot | |
Dataset | 1 | 2 | 1 | 2 | 1 |
Sample size | 54 | 26 | 54 | 26 | 54 |
Average value | 3.65 | 3.54 | 2.83 | 3.04 | 3.28 |
Standard Deviation | 0.48 | 0.58 | 0.72 | 0.72 | 0.66 |
t | 0.89 | 1.193 | 0.668 | 1.182 | 0.889 |
p | 0.376 | 0.236 | 0.505 | 0.2405 | 0.37667 |
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Fargnoli, M.; Lombardi, M. Safety Climate and the Impact of the COVID-19 Pandemic: An Investigation on Safety Perceptions among Farmers in Italy. Safety 2021, 7, 52. https://doi.org/10.3390/safety7030052
Fargnoli M, Lombardi M. Safety Climate and the Impact of the COVID-19 Pandemic: An Investigation on Safety Perceptions among Farmers in Italy. Safety. 2021; 7(3):52. https://doi.org/10.3390/safety7030052
Chicago/Turabian StyleFargnoli, Mario, and Mara Lombardi. 2021. "Safety Climate and the Impact of the COVID-19 Pandemic: An Investigation on Safety Perceptions among Farmers in Italy" Safety 7, no. 3: 52. https://doi.org/10.3390/safety7030052
APA StyleFargnoli, M., & Lombardi, M. (2021). Safety Climate and the Impact of the COVID-19 Pandemic: An Investigation on Safety Perceptions among Farmers in Italy. Safety, 7(3), 52. https://doi.org/10.3390/safety7030052