COVID-19 Fear, Health Behaviors, and Subjective Health Status of Call Center Workers
Abstract
:1. Introduction
2. Methods
2.1. Study Design and Participants
2.2. Data Collection
2.3. Measurements
2.3.1. COVID-19 Fear
2.3.2. Health Behaviors
2.3.3. Time Pressure at Work
2.3.4. Subjective Health Status
2.4. Data Analysis
2.5. Ethical Considerations
3. Results
3.1. Demographic Characteristics of Participants
3.2. Health Behavior and Subjective Health Status According to the COVID-19 Era
3.3. Health Behavior and Subjective Health Status, According to Fear of COVID-19
3.4. Factors for Health Behavior and Subjective Health Status
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Barriga Medina, H.R.; Campoverde Aguirre, R.; Coello-Montecel, D.; Ochoa Pacheco, P.; Paredes-Aguirre, M.I. The influence of work–family conflict on burnout during the COVID-19 Pandemic: The effect of teleworking overload. Int. J. Environ. Res. Public Health 2021, 18, 10302. [Google Scholar] [CrossRef]
- Pera, A. Cognitive, behavioral, and emotional disorders in populations affected by the COVID-19 outbreak. Front. Psychol. 2020, 11, 2263. [Google Scholar] [CrossRef] [PubMed]
- Lovreglio, P.; Leso, V.; Riccardi, E.; Stufano, A.; Pacella, D.; Cagnazzo, F.; Luigia Ercolano, M.; Iavicoli, I. Coronavirus disease (COVID-19) pandemic: The psychological well-being in a cohort of workers of a multinational company. Saf. Health Work 2021, 13, 66–72. [Google Scholar] [CrossRef] [PubMed]
- Lo Coco, G.; Gentile, A.; Bosnar, K.; Milovanović, I.; Bianco, A.; Drid, P.; Pišot, S. A cross-country examination on the fear of COVID-19 and the sense of loneliness during the first wave of COVID-19 outbreak. Int. J. Environ Res. Public Health 2021, 18, 2586. [Google Scholar] [CrossRef] [PubMed]
- Wang, C.; Pan, R.; Wan, X.; Tan, Y.; Xu, L.; Ho, C.S.; Ho, R.C. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int. J. Environ. Res. Public Health 2020, 17, 1729. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lee, J.; Kim, M. Estimation of the number of working population at high-risk of COVID-19 infection in Korea. Epidemiol. Health 2020, 42, e2020051. [Google Scholar] [CrossRef]
- Cho, S.S.; Kim, H.; Lee, J.; Lim, S.; Jeong, W.C. Combined exposure of emotional labor and job insecurity on depressive symptoms among female call-center workers: A cross-sectional study. Medicine (Baltimore) 2019, 98, e14894. [Google Scholar] [CrossRef]
- Cori, L.; Curzio, O.; Adorni, F.; Prinelli, F.; Noale, M.; Trevisan, C.; Fortunato, L.; Giacomelli, A.; Bianchi, F. Fear of COVID-19 for individuals and family members: Indications from the national cross-sectional study of the epicovid19 web-based survey. Int. J. Environ. Res. Public Health 2021, 18, 3248. [Google Scholar] [CrossRef]
- Serpas, D.G.; Ignacio, D.A. COVID-19 fear mediates the relationship between perceived risk and preventive behaviors: The moderating role of perceived effectiveness. Psychol. Health 2021, 1–14. [Google Scholar] [CrossRef]
- Kaya, S.; Uzdil, Z.; Cakiroğlu, F.P. Evaluation of the effects of fear and anxiety on nutrition during the COVID-19 pandemic in turkey. Public Health Nutr. 2021, 24, 282–289. [Google Scholar] [CrossRef]
- Flanagan, E.W.; Beyl, R.A.; Fearnbach, S.N.; Altazan, A.D.; Martin, C.K.; Redman, L.M. The impact of COVID-19 stay-at-home orders on health behaviors in adults. Obesity 2021, 29, 438–445. [Google Scholar] [CrossRef] [PubMed]
- Santiago, A.M.; Bil, C.J.B.A.; Curam, R.; Torrero, K.A.; Tus, J. Call center agents’ job burnout and its’ influence on their job satisfaction during the COVID-19 pandemic in the philippines. Int. J. Adv. Res. Innov. Ideas Educ. 2021, 7, 2651–2664. [Google Scholar]
- Aazami, S.; Shamsuddin, K.; Akmal, S. Examining behavioural coping strategies as mediators between work-family conflict and psychological distress. Sci. World J. 2015, 2015, 343075. [Google Scholar] [CrossRef] [Green Version]
- Ahorsu, D.K.; Lin, C.-Y.; Imani, V.; Saffari, M.; Griffiths, M.D.; Pakpour, A.H. The fear of COVID-19 scale: Development and initial validation. Int. J. Ment. Health Addict. 2022, 20, 1537–1545. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Abd-Ellatif, E.E.; Anwar, M.M.; AlJifri, A.A.; El Dalatony, M.M. Fear of COVID-19 and its impact on job satisfaction and turnover intention among egyptian physicians. Saf. Health Work 2021, 12, 490–495. [Google Scholar] [CrossRef] [PubMed]
- Korea Centers for Disease Control and Prevention. High-Risk Alcohol DRINKING. Available online: https://health.kdca.go.kr/healthinfo/biz/pblcVis/details.do?ctgrSn=47 (accessed on 11 January 2022).
- Centers for Disease Control and Prevention. Physical Activity. Available online: https://www.cdc.gov/physicalactivity/basics/adults/index.htm (accessed on 11 January 2022).
- Pereira, D.; Semmer, N.K.; Elfering, A. Illegitimate tasks and sleep quality: An ambulatory study. Stress Health 2014, 30, 209–221. [Google Scholar] [CrossRef] [Green Version]
- Labrague, L.J.; de Los Santos, J.A.A. Fear of COVID-19, psychological distress, work satisfaction and turnover intention among frontline nurses. J. Nurs. Manag. 2021, 29, 395–403. [Google Scholar] [CrossRef]
- Kosendiak, A.; Król, M.; Ściskalska, M.; Kepinska, M. The changes in stress coping, alcohol use, cigarette smoking and physical activity during COVID-19 related lockdown in medical students in poland. Int. J. Environ. Res. Public Health 2021, 19, 302. [Google Scholar] [CrossRef]
- Johnson, B.T.; Scott-Sheldon, L.A.; Carey, M.P. Meta-synthesis of health behavior change meta-analyses. Am. J. Public Health 2010, 100, 2193–2198. [Google Scholar] [CrossRef]
- Weerakoon, S.M.; Jetelina, K.K.; Knell, G. Longer time spent at home during COVID-19 pandemic is associated with binge drinking among us adults. Am. J. Drug Alcohol Abuse 2021, 47, 98–106. [Google Scholar] [CrossRef]
- Folkman, S.; Lazarus, R.S. An analysis of coping in a middle-aged community sample. J. Health Soc.Behav. 1980, 21, 219–239. [Google Scholar] [CrossRef]
- Bianchi, D.; Baiocco, R.; Pompili, S.; Lonigro, A.; Di Norcia, A.; Cannoni, E.; Longobardi, E.; Zammuto, M.; Di Tata, D.; Laghi, F. Binge eating and binge drinking in emerging adults during COVID-19 lockdown in italy: An examination of protective and risk factors. Emerg. Adulthood 2021, 10, 291–303. [Google Scholar] [CrossRef]
- Partinen, M. Sleep research in 2020: COVID-19-related sleep disorders. Lancet Neurol. 2021, 20, 15–17. [Google Scholar] [CrossRef]
- Masoumi, M.; Shokraee, K.; Mohammadi, S.; Moradi, S.; Bagherzade, M.; Balasi, J.; Smiley, A. Sleep duration as the main indicator of self-rated wellness and health among healthcare workers involved in the COVID-19 pandemic. Int. J. Environ. Res. Public Health 2021, 19, 136. [Google Scholar] [CrossRef] [PubMed]
- Brandl, C.; Zimmermann, M.E.; Günther, F.; Dietl, A.; Küchenhoff, H.; Loss, J.; Stark, K.J.; Heid, I.M. Changes in healthcare seeking and lifestyle in old aged individuals during COVID-19 lockdown in germany: The population-based augur study. BMC Geriatr. 2022, 22, 34. [Google Scholar] [CrossRef] [PubMed]
- Salway, R.; Su, T.T.; Ismail, R.; Glynis Armstrong, M.E.; Foster, C.; Johnson, L. The impact of COVID-19 movement restrictions on physical activity in a low-income semi-rural population in malaysia: A longitudinal study. J. Glob. Health 2021, 11, 05029. [Google Scholar] [CrossRef] [PubMed]
- Nagata, J.M.; Cortez, C.A.; Dooley, E.E.; Iyer, P.; Ganson, K.T.; Pettee Gabriel, K. Moderate-to-vigorous intensity physical activity among adolescents in the USA during the COVID-19 pandemic. Prev. Med. Rep. 2022, 25, 101685. [Google Scholar] [CrossRef] [PubMed]
- Yong, M.; Nasterlack, M.; Pluto, R.P.; Lang, S.; Oberlinner, C. Occupational stress perception and its potential impact on work ability. Work 2013, 46, 347–354. [Google Scholar] [CrossRef]
- Bakker, A.; Demerouti, E.; Schaufeli, W. Dual processes at work in a call centre: An application of the job demands–Resources model. Eur. J. Work Organ. Psychol. 2003, 12, 393–417. [Google Scholar] [CrossRef]
Variables | N (%) or Mean ± SD | Range |
---|---|---|
Age (year) | 43.9 ± 7.53 | 22.0–60.0 |
Gender | ||
Female | 306 (90.3) | |
Male | 33 (9.7) | |
Education (≥College) | 184 (54.3) | |
Marital status | ||
Married | 185 (54.6) | |
Unmarried/separated/divorced | 154 (45.4) | |
Number of children | 1.0 ± 0.96 | 0.0–3.0 |
Monthly household income (≥4 million KRW) | 163 (48.1) | |
Perceived socioeconomic level (1–5) | 2.6 ± 0.61 | 1.0–4.0 |
Years of current work experience | 5.9 ± 3.45 | 2.0–34.0 |
Type of employment | ||
Full-time worker | 323 (95.3) | |
Part-time worker | 16 (4.7) | |
Occupational category | ||
Counselor | 275 (81.1) | |
Team or center leader | 51 (15.1) | |
Support staff | 13 (3.8) | |
Counseling service characteristics | ||
Inbound | 192 (56.6) | |
Outbound | 99 (29.2) | |
Call blending | 7 (2.1) | |
Business support | 41 (12.1) | |
Home-based working | 120 (35.4) | |
Office-based working | 219 (64.6) | |
Working hours per week | 33.6 ± 14.48 | 4.0–70.0 |
Working hours per week (>40 h) | 88 (26.0) | |
Time-pressure at work | 3.1 ± 0.80 | 1.0–5.0 |
Degree of fear of COVID-19 (total score) | 19.8 ± 5.43 | 7.0–35.0 |
Normal | 87 (25.7) | |
Moderate | 215 (63.4) | |
Severe | 37 (10.9) |
Variables | N (%) or Mean ± SD | t/χ2 | p | |
---|---|---|---|---|
Pre-COVID 19 | Present | |||
Current smoking (yes) | 77 (22.7) | 77 (22.7) | 339.00 | 1.000 |
High-risk alcohol drinking | 79 (23.3) | 79 (23.3) | 282.17 | 1.000 |
Moderate PA (≥5 days/week) | 22 (6.5) | 17 (5.0) | 169.74 | 0.227 |
Stress management (1–5 scores) | 2.9 ± 0.99 | 2.7 ± 0.98 | 4.43 | <0.001 |
Binge eating (0–7 scores) | 1.2 ± 1.21 | 1.4 ± 1.50 | −4.54 | <0.001 |
Sedentary behavior hours/day | 8.6 ± 5.31 | 9.0 ± 5.35 | −5.40 | <0.001 |
Sleep hours/day | 6.3 ± 1.36 | 6.1 ± 1.34 | 3.16 | 0.002 |
Subjective health status (0–100 scores) | 70.6 ± 15.87 | 65.9 ± 15.79 | 5.68 | <0.001 |
Variables | Normal a (n = 87) | Moderate b (n = 215) | Severe c (n = 37) | F/χ2 | p | Scheffe’s Test |
---|---|---|---|---|---|---|
N (%) or Mean ± SD | ||||||
Current smoking (yes) | 27 (31.0) | 41 (19.1) | 9 (24.3) | 5.112 | 0.078 | |
High-risk alcohol drinking | 22 (25.3) | 43 (20.0) | 14 (37.8) | 5.877 | 0.054 | |
Moderate PA (≥5 days/week) | 5 (5.7) | 12 (5.6) | 0 (0.0) | 2.196 | 0.333 | |
Stress management (1–5 scores) | 2.8 ± 1.02 | 2.8 ± 0.95 | 2.3 ± 0.97 | 4.394 | 0.013 | c < a = b |
Binge eating (0–7 scores) | 1.3 ± 1.44 | 1.3 ± 1.39 | 2.5 ± 1.82 | 11.776 | <0.001 | a = b < c |
Sedentary behavior hours/day | 9.4 ± 5.53 | 9.0 ± 5.39 | 8.3 ± 4.71 | 0.522 | 0.594 | |
Sleep hours/day | 6.5 ± 1.92 | 6.1 ± 1.03 | 5.7 ± 1.10 | 4.773 | 0.009 | b = c < a |
Subjective health status (0–100 scores) | 67.9 ± 17.74 | 66.5 ± 15.09 | 57.8 ± 17.82 | 5.861 | 0.003 | c < a = b |
Variables | Stress Management (1–5 Scores) | Binge Eating (0–7 Scores) | Sedentary Behavior Hour/Day | Sleep Hours/Day | Subjective Health Status (0–100 Scores) |
---|---|---|---|---|---|
β (SE) | |||||
Age | 0.054 (0.009) | −0.289 (0.012) ** | −0.049 (0.048) | −0.020 (0.012) | 0.209 (0.438) ** |
Gender (men) | −0.039 (0.187) | −0.142 (0.266) ** | 0.068 (1.026) | 0.089 (0.252) | 0.031 (2.955) |
Education (≥College) | 0.089 (0.109) | 0.027 (0.156) | 0.085 (0.601) | 0.029 (0.147) | 0.043 (1.730) |
Marital status (married) | 0.139 (0.154) | 0.119 (0.219) | −0.129 (0.844) | −0.141 (0.207) | −0.031 (2.429) |
Number of children | −0.240 (0.086) ** | −0.098 (0.113) | −0.018 (0.474) | 0.117 (0.116) | −0.009 (1.365) |
Years of current work experience | 0.018 (0.016) | 0.004 (0.023) | −0.022 (0.090) | 0.169 (0.022) ** | −0.055 (0.260) |
Type of employment (regular) | −0.027 (0.253) | 0.029 (0.360) | 0.010 (1.389) | −0.070 (0.341) | 0.022 (3.998) |
Occupational Category (counselor) | 0.039 (0.147) | 0.017 (0.210) | −0.032 (0.810) | 0.053 (0.199) | −0.100 (2.332) |
Counseling service (inbound) | −0.089 (0.121) | 0.094 (0.172) | −0.001 (0.664) | −0.017 (0.163) | −0.094 (1.911) |
Home-based working | −0.020 (0.118) | −0.002 (0.168) | −0.030 (0.650) | 0.128 (0.159) * | 0.060 (1.871) |
Working hours per week (>40 h) | 0.025 (0.129) | 0.008 (0.183) | 0.083 (0.707) | 0.026 (0.174) | 0.002 (2.037) |
Time-pressure at work | −0.072 (0.068) | 0.053 (0.096) | 0.089 (0.371) | 0.003 (0.091) | −0.107 (1.069) * |
Fear of COVID-19 | −0.151 (0.010) ** | 0.227 (0.014) ** | −0.038 (0.055) | −0.116 (0.014) * | −0.151 (0.159) ** |
R-square | 0.07 | 0.20 | 0.06 | 0.10 | 0.11 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Kim, H.-R.; Yang, H.-M. COVID-19 Fear, Health Behaviors, and Subjective Health Status of Call Center Workers. Int. J. Environ. Res. Public Health 2022, 19, 9005. https://doi.org/10.3390/ijerph19159005
Kim H-R, Yang H-M. COVID-19 Fear, Health Behaviors, and Subjective Health Status of Call Center Workers. International Journal of Environmental Research and Public Health. 2022; 19(15):9005. https://doi.org/10.3390/ijerph19159005
Chicago/Turabian StyleKim, Hye-Ryoung, and Hwa-Mi Yang. 2022. "COVID-19 Fear, Health Behaviors, and Subjective Health Status of Call Center Workers" International Journal of Environmental Research and Public Health 19, no. 15: 9005. https://doi.org/10.3390/ijerph19159005
APA StyleKim, H. -R., & Yang, H. -M. (2022). COVID-19 Fear, Health Behaviors, and Subjective Health Status of Call Center Workers. International Journal of Environmental Research and Public Health, 19(15), 9005. https://doi.org/10.3390/ijerph19159005