Factors associated with preventive behaviors for COVID-19 infection among healthcare workers by a health behavior model
Tropical Medicine and Health volume 50, Article number: 65 (2022)
Coronavirus disease 2019 (COVID-19) is a pandemic disease. There are limited data on predictors of good preventive behaviors among healthcare workers. This study aimed to evaluate if any factors were predictors of good preventive behaviors in healthcare workers under the theory of health behavior model.
This was a cross-sectional study in healthcare workers who were willing to participate in the study. Participants were requested to fill out a self-administered questionnaire that comprised health behavior model and preventive behaviors from COVID-19 infection. Factors associated with preventive behavior, an outcome, were analyzed by multivariate linear regression analysis.
There were 273 healthcare workers who participated in this study. The average (SD) age and working duration of participants was 38.9 (12.1) and 11.4 (9.8) years. The preventive behavior category had an average score of 87.6% (70.3/80). After adjusted, knowledge and perception of personal preventability were independently associated with preventive behaviors. The adjusted coefficients of both factors were—0.911 (p 0.009) and 0.477 (p < 0.001).
Specific knowledge and perception of personal ability questions were associated with preventive behaviors for COVID-19 infection. To improve personal preventive behaviors in healthcare workers, these factors should be emphasized.
Coronavirus disease 2019 (COVID-19) is a pandemic disease with mortality rate of 45% if invasive mechanical ventilator is required . One risk factor of COVID-19 infection is occupation . Healthcare workers (HCWs) are one occupation recognized as high-risk group for COVID-19 infection . The database study found that health care practitioners had the highest case count at 1,208 cases followed by transportation and material moving at 1096 cases, healthcare support at 989 cases, and production at 964 cases . There were 114,529 HCWs in the US infected with COVID-19 resulting in 574 deaths . Additionally, HCWs may experience psychiatric conditions. A study from Ecuador found that HCWs reported depression in 27.3% and anxiety in 39.2% during the COVID-19 pandemic . Even though COVID-19 vaccination is important, preventive behaviors remain necessary.
Knowledge, attitude, and practice are key factors for COVID-19 prevention. A study from China and United Arab Emirates found that college students and HCWs had knowledge of COVID-19 infection of 73.81% and 61% [5, 6]. A study on general population found that women and other factors such as perceived benefits were associated with preventive behaviors . Health belief model (HBM) by Rosenstock et al. is a widely accepted and popular theoretical guideline for health behaviors in public health research. It contains the perception of susceptibility, severity, benefits, barriers, health behaviors and cues to action [8, 9]. We used this model for construct our questions in the survey to explore reasons why HCWs have COVID-19 infection prevention behaviors. There are limited data on predictors of good preventive behaviors in healthcare workers. This study aimed to evaluate if any factors were predictors of good preventive behaviors among HCWs.
This was a cross-sectional study conducted at Panyananthaphikkhu Chonprathan Medical Center, Nonthaburi, an affiliated Hospital to Srinakharinwirot University, Thailand. The inclusion criteria were HCWs who were willing to participate in the study. The HCWs included nurses, nurse assistants, medical service staff, medical technologists, dentists, dentist assistants, pharmacists, pharmacist assistants, physical/occupational therapists, radiological technologist, medical scientists, public health staff, patient assistants, and office staffs. The study period was between September and October 2020.
Participants were randomly selected from the hospital personnel list and requested to fill out a self-administered questionnaire. The questionnaire comprised nine sections: baseline characteristics, knowledge (10 items), perception towards risky possibility of COVID-19 infection (10 items), perception of COVID-19 severity (10 items), benefits of abiding by medical advice on COVID-19 preventive measures (12 items), barriers of prevention strategies of COVID-19 infection (12 items), factors leading to COVID-19 preventive behaviors (12 items), perception of personal preventability (12 items), and preventive behaviors from COVID-19 infection (16 items). The knowledge part was a yes/no question, while the preventive behaviors had five responses as always, often, sometimes, rarely, and never. The other categories had five Likert rating scales: strongly agree, partially agree, neutral, partially disagree, and strongly disagree. The knowledge part had a total score of 10, while the other part had scores according to the scale from 1 to 5. The questionnaire was checked for content validity and reliability. An item-objective congruence and the Cronbach’s alpha reliability coefficient of the questionnaire were 0.86 and 0.88, respectively.
Sample size calculation. A previous study found that 98% of participants had preventive behavior, while we expected that 95% of participants had preventive behavior . For a single study group with an alpha error of 5% and power of 80%, the required sample size was 233 participants. The questionnaire was distributed randomly to approximately 30% of total HCWs of 1060 persons.
Statistical analyses. Descriptive statistics were used to calculate mean (SD) and number (percentage) of variables in the questionnaire. Scores of knowledge (10 points), perception of risk factors of COVID-19 infection (50 points), perception of severity of COVID-19 infection (50 points), benefits of following medical advices of COVID-19 infection (60 points), barriers of prevention strategies of COVID-19 infection (60 points), factors associated with preventive behaviors of COVID-19 infection (60 points), perception of personal ability to prevent COVID-19 infection (60 points), and preventive behaviors (80 points) were calculated for each participant. Factors associated with preventive behavior, an outcome, were executed by multivariate linear regression analysis. Questions in the significant parts were also executed for prediction of preventive behavior score by linear regression analysis. The analyses were performed by STATA software, version 10.1 (College Station, Texas, USA).
There were 273 HCWs that participated in this study. An average (SD) age and working duration of participants was 38.9 (12.1) and 11.4 (9.8) years. Most participants were female (88.8%), holding bachelor degree (58.6%), and had job title as nurse (36.6%) as shown in Table 1. Additional file 1, comprising seven tables, shows details of responses to seven categories of the questionnaire. The outcome, preventive behaviors in healthcare workers, is shown in Table 2. The participants had average knowledge score (SD) of 7.0 (1.3)/10, while the perception of personal preventability category had the highest average score (SD) of 49.2 (6.2)/60 (Table 3). The preventive behavior category had an average score of 87.6% (70.3/80), as shown in Table 3.
Among studied variables, there were five factors significantly associated with preventive behaviors by univariate linear regression analysis including perception towards risky possibility of COVID-19 infection (coefficient 0.335; p < 0.001), barriers of prevention strategies (coefficient 0.343; p < 0.001), benefits of abiding by medical advice on COVID-19 preventive measures (coefficient 0. 279; p < 0.001), factors leading to COVID-19 preventive behaviors (coefficient 0.287; p < 0.001), and perception of personal preventability (coefficient 0.481; p < 0.001), as shown in Table 4. After adjusted, knowledge and perception of personal preventability were independently associated with preventive behaviors. The adjusted coefficients of both factors were − 0.911 (p 0.009) and 0.477 (p < 0.001), as shown in Table 4. One question in the knowledge part was negatively associated with preventive behavior score (coefficient of − 1.978; p 0.012), as shown in Table 5, while four questions in the perception of personal ability to prevent COVID-19 infection were positively associated with preventive behavior score (Table 6).
Specific knowledge question and perception of personal preventability were found to be predictors of good preventive behaviors for COVID-19 infection among HCWs in this study.
A study from Bangladesh conducted in the general population found that higher knowledge scores were positively associated with higher preventive behaviors for COVID-19 (beta 0.053; p < 0.001) as well as in HCWs [7, 11,12,13]. Despite the average knowledge score and preventive behavior were not different from general population (70.00% vs 71.82%) and (87.88% vs 84.75%), respectively, we found the opposite results (Table 4) . Our study showed that non-medical doctor (MD) HCWs with good knowledge score had lower preventive behavior score (beta 0.911; p 0.009). These findings may explain from difficulty of our questions. From our analysis, those with high preventive behavior had low score on question no. 4 in the questionnaire with a coefficient of − 1.978 (p 0.012). Since COVID-19 infection is an emerging disease, we have gap of knowledge among infected children at that period of time. Also, there were few cases of COVID-19-infected children reported in Thailand during the study period, Subsequently, the low score on the question about children resulting in negative association with the preventive behavior. Other possible explanations are the shortage of personal protective equipments at that period of time for whole country and finally HCWs may feel difficult to change their habits as previously reported .
There were four questions regarding perception of personal ability to prevent COVID-19 infection, including seeking medical attention, crowded places, surveillance test after exposure, and disposal of protective equipment (Table 6; Additional file 1). These perceptions have been reported to be associated with preventive behaviors for COVID-19 infection in HCWs [15, 16]. From our analysis, factors on perception are more important than knowledge on practice of prevention. In other words, personal attitude may be crucial for prevention practice in COVID-19 infection. These findings may be different from a study from Vietnam which reported that knowledge was a significant factor associated with practice level (p 0.00) but not barriers of practice (p 0.056) . It might be due to differences on questions in the questionnaire. Further studies are required to conclude this issue.
Four questions about perception of personal ability to prevent COVID-19 infection which significantly associated with preventive behaviors should be concerned (Table 6). Our suggestions were HCWs should encourage persons at risk of COVID-19 to seek medical attention. The hospital should sufficiently provide surveillance test opportunities after exposure with persons at risk as well as endow with safe management system for infectious waste disposal. Finally, HCWs essentially use personal protective personal protective equipments (PPEs) in public area. This may contribute to improving good practices and preventive behavior among HCWs in particular. However, even with PPEs, some HCWs may still be at risk for COVID-19 infection such as dentists or nurses. These two occupations had prevalence ratio of 2.62 and 2.61 with 95% confidence interval of 1.23–4.02 and 1.16–4.14, respectively .
Our study had some limitations. First, the study population was HCWs in affiliated hospital of medical school, who are non-MD staffs. The findings of this study may not be generalizable for all HCWs in other hospital levels. However, this questionnaire was already validated. Second, the data were collected after the third wave of epidemic period in Thailand. Consequently, the results may vary with the stage of COVID-19 outbreak and the method of data collection is based only on the responses to the developed questionnaire which cannot verify the truth of the answer. Note that no specific clinical risk factors are evaluated such as obstructive sleep apnea [17,18,19,20,21,22]. Finally, there might be might be cultural differences or norm with other population such as general population [11, 13].
In conclusion, one knowledge question and four questions related to the perception of personal ability were significantly associated with preventive behaviors for COVID-19 infection. To improve personal preventive behaviors in healthcare workers, these factors should be emphasized.
Availability of data and materials
The data relating to this manuscript are available upon request.
Lim ZJ, Subramaniam A, Ponnapa RM, Blecher G, Kadam U, Afroz A, et al. Case fatality rates for patients with COVID-19 requiring invasive mechanical ventilation a meta-analysis. Am J Respir Crit Care Med. 2021;203(1):54–66.
Zhang M. Estimation of differential occupational risk of COVID-19 by comparing risk factors with case data by occupational group. Am J Ind Med. 2021;64(1):39–47.
Erdem H, Lucey DR. Healthcare worker infections and deaths due to COVID-19: A survey from 37 nations and a call for WHO to post national data on their website. Int J Infect Dis IJID Off Publ Int Soc Infect Dis. 2021;102:239–41.
Pazmiño Erazo EE, Alvear Velásquez MJ, Saltos Chávez IG, Pazmiño Pullas DE. Factors associated with psychiatric adverse effects in healthcare personnel during the COVID-19 pandemic in Ecuador. Rev Colomb Psiquiatr Engl Ed. 2021;S2530–3120(21):00068.
Peng Y, Pei C, Zheng Y, Wang J, Zhang K, Zheng Z, et al. A cross-sectional survey of knowledge, attitude and practice associated with COVID-19 among undergraduate students in China. BMC Public Health. 2020;20(1):1292.
Bhagavathula AS, Aldhaleei WA, Rahmani J, Mahabadi MA, Bandari DK. Knowledge and Perceptions of COVID-19 Among Health Care Workers: Cross-Sectional Study. JMIR Public Health Surveill. 2020;6(2): e19160.
Shahnazi H, Ahmadi-Livani M, Pahlavanzadeh B, Rajabi A, Hamrah MS, Charkazi A. Assessing preventive health behaviors from COVID-19: a cross sectional study with health belief model in Golestan Province, Northern of Iran. Infect Dis Poverty. 2020;9(1):157.
Rosenstock IM, Strecher VJ, Becker MH. Social learning theory and the Health Belief Model. Health Educ Q. 1988;15(2):175–83.
Rosenstock IM. Historical Origins of the Health Belief Model. Health Educ Monogr. 1974;2(4):328–35.
Zhong BL, Luo W, Li HM, Zhang QQ, Liu XG, Li WT, et al. Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: a quick online cross-sectional survey. Int J Biol Sci. 2020;16(10):1745–52.
Ejeh FE, Saidu AS, Owoicho S, Maurice NA, Jauro S, Madukaji L, et al. Knowledge, attitude, and practice among healthcare workers towards COVID-19 outbreak in Nigeria. Heliyon. 2020;6(11): e05557.
Tien TQ, Tuyet-Hanh TT, Linh TNQ, Hai Phuc H, Van Nhu H. Knowledge, Attitudes, and Practices Regarding COVID-19 prevention among Vietnamese Healthcare Workers in 2020. Health Serv Insights. 2021;14:11786329211019224.
Zhang M, Zhou M, Tang F, Wang Y, Nie H, Zhang L, et al. Knowledge, attitude, and practice regarding COVID-19 among healthcare workers in Henan. China J Hosp Infect. 2020;105(2):183–7.
Hosen I, Pakpour AH, Sakib N, Hussain N, Al Mamun F, Mamun MA. Knowledge and preventive behaviors regarding COVID-19 in Bangladesh: A nationwide distribution. PLoS ONE. 2021;16(5): e0251151.
Firouzbakht M, Omidvar S, Firouzbakht S, Asadi-Amoli A. COVID-19 preventive behaviors and influencing factors in the Iranian population; a web-based survey. BMC Public Health. 2021;21(1):143.
Kanu S, James PB, Bah AJ, Kabba JA, Kamara MS, Williams CEE, et al. Healthcare Workers’ Knowledge, Attitude, Practice and Perceived Health Facility Preparedness Regarding COVID-19 in Sierra Leone. J Multidiscip Healthc. 2021;14:67–80.
Khamsai S, Chootrakool A, Limpawattana P, Chindaprasirt J, Sukeepaisarnjaroen W, Chotmongkol V, et al. Hypertensive crisis in patients with obstructive sleep apnea-induced hypertension. BMC Cardiovasc Disord. 2021;21(1):310.
Sawunyavisuth B, Ngamjarus C, Sawanyawisuth K. A meta-analysis to identify factors associated with CPAP machine purchasing in patients with obstructive sleep apnea. Biomed Rep. 2022;16(6):45.
Soontornrungsun B, Khamsai S, Sawunyavisuth B, Limpawattana P, Chindaprasirt J, Senthong V, et al. Obstructive sleep apnea in patients with diabetes less than 40 years of age. Diabetes Metab Syndr. 2020;14(6):1859–63.
Sanlung T, Sawanyawisuth K, Silaruks S, Chattakul P, Limpawattana P, Chindaprasirt J, et al. Clinical characteristics and complications of obstructive sleep apnea in Srinagarind hospital. J Med Assoc Thai. 2020;103(1):36–9.
Cunha TCA, Rossi R, Marson LCG, Guimaraes TM, Machado MAC, Meira-E-Cruz M, et al. COVID-19 and dental sleep medicine: risks, precautions and patient guidance. Sleep Sci Sao Paulo Braz. 2020;13(3):195–8.
Kaewkes C, Sawanyawisuth K, Sawunyavisuth B. Are symptoms of obstructive sleep apnoea related to good continuous positive airway pressure compliance? ERJ Open Res. 2020;6(3):00169–2019.
The authors would like to thank the participants of this study.
This study was supported by a grant from Panyananthaphikkhu Chonprathan Medical Center, Srinakharinwirot University, Nonthaburi, Thailand.
Ethics approval and consent to participate
The study protocol was approved by the institutional review board of Panyananthaphikkhu Chonprathan Medical Center, Srinakharinwirot University, Nonthaburi, Thailand (010/63).
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Limkunakul, C., Phuthomdee, S., Srinithiwat, P. et al. Factors associated with preventive behaviors for COVID-19 infection among healthcare workers by a health behavior model. Trop Med Health 50, 65 (2022). https://doi.org/10.1186/s41182-022-00454-z