Sociodemographic and Psychological Variables and Concerns Related to COVID-19 Vaccination among Polish Citizens
Abstract
:1. Introduction
1.1. The COVID-19 Pandemic and the Ways to Overcome It
1.2. COVID-19 Vaccination in POLAND
1.3. Factors Important for the Acceptance/Rejection of the Idea of Vaccination against COVID-19
1.3.1. The Role of the Demographic Variables for the Acceptance/Rejection of the Idea of Vaccination against COVID-19
1.3.2. The Role of the Cognitive Variables (Beliefs) for the Acceptance/Rejection of the Idea of Vaccination against COVID-19
1.3.3. The Role of the Emotional Variables (Fears and Concerns) for the Acceptance/Rejection of the Idea of Vaccination against COVID-19
1.4. The Aim of the Study
2. Materials and Methods
2.1. Participants
2.2. Measures
2.2.1. Sociodemographic Variables
2.2.2. Mood
2.2.3. Emotions
2.2.4. Satisfaction with Life
2.2.5. Optimism
2.2.6. Coping with Stress
2.3. Design and Procedure
2.4. Data Analysis
3. Results
4. Discussion
5. Conclusions
6. Research Limitations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Coronavirus Statistics. Available online: www.statvirus.pl (accessed on 22 July 2022).
- Kaur, S.P.; Gupta, V. COVID-19 Vaccine: A comprehensive status report. Virus Res. 2020, 288, 198114. [Google Scholar] [CrossRef] [PubMed]
- Lurie, N.; Saville, M.; Hatchett, R.; Halton, J. Developing Covid-19 Vaccines at Pandemic Speed. N. Engl. J. Med. 2020, 382, 1969–1973. [Google Scholar] [CrossRef] [PubMed]
- Mancilla-Galindo, J.; García-Méndez, J.Ó.; Márquez-Sánchez, J.; Reyes-Casarrubias, R.E.; Aguirre-Aguilar, E.; Rocha-González, H.I.; Kammar-García, A. All-cause mortality among patients treated with repurposed antivirals and antibiotics for COVID-19 in Mexico City: A real-world observational study. EXCLI J. 2021, 20, 199–222. [Google Scholar] [CrossRef]
- Kumar, R.; Rathi, H.; Haq, A.; Wimalawansa, S.J.; Sharma, A. Putative roles of vitamin D in modulating immune response and immunopathology associated with COVID-19. Virus Res. 2021, 292, 198235. [Google Scholar] [CrossRef] [PubMed]
- Orish, V.N.; Boakye-Yiadom, E.; Ansah, E.K.; Alhassan, R.K.; Duedu, K.; Awuku, Y.A.; Owusu-Agyei, S.; Gyapong, J.O. Is malaria immunity a possible protection against severe symptoms and outcomes of COVID-19? Ghana Med. J. 2021, 55 (Suppl. 2), 56–63. [Google Scholar] [CrossRef] [PubMed]
- Alzoughool, F.; Alanagreh, L. Coronavirus drugs: Using plasma from recovered patients as a treatment for COVID-19. Int. J. Risk Saf. Med. 2021, 31, 47–51. [Google Scholar] [CrossRef] [Green Version]
- EMA. Recommends First COVID-19 Vaccine for Authorisation in the EU. Available online: https://www.ema.europa.eu/en/news/ema-recommends-first-covid-19-vaccine-authorisation-eu (accessed on 28 April 2022).
- EMA. Recommends COVID-19 Vaccine AstraZeneca for Authorisation in the EU. Available online: https://www.ema.europa.eu/en/news/ema-recommends-covid-19-vaccine-astrazeneca-authorisation-eu (accessed on 28 April 2022).
- EMA. Recommends COVID-19 Vaccine Moderna for Authorisation in the EU. Available online: https://www.ema.europa.eu/en/news/ema-recommends-covid-19-vaccine-moderna-authorisation-eu (accessed on 28 April 2022).
- EMA. Recommends COVID-19 Vaccine Janssen for Authorisation in the EU. Available online: https://www.ema.europa.eu/en/news/ema-recommends-covid-19-vaccine-janssen-authorisation-eu (accessed on 28 April 2022).
- Vaccination Report against COVID-19. Available online: https://www.gov.pl/web/szczepimysie/raport-szczepien-przeciwko-covid-19 (accessed on 22 July 2022).
- Anderson, R.M.; Vegvari, C.; Truscott, J.; Collyer, B.S. Challenges in creating herd immunity to SARS-CoV-2 infection by mass vaccination. Lancet 2020, 396, 1614–1616. [Google Scholar] [CrossRef]
- Simione, L.; Vagni, M.; Gnagnarella, C.; Bersani, G.; Pajardi, D. Mistrust and Beliefs in Conspiracy Theories Differently Mediate the Effects of Psychological Factors on Propensity for COVID-19 Vaccine. Front. Psychol. 2021, 12, 683684. [Google Scholar] [CrossRef]
- Murphy, J.; Vallières, F.; Bentall, R.P.; Shevlin, M.; McBride, O.; Hartman, T.K.; McKay, R.; Bennett, K.; Mason, L.; Gibson-Miller, J.; et al. Psychological characteristics associated with COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom. Nat Commun 2021, 12, 29. [Google Scholar] [CrossRef]
- Babicki, M.; Mastalerz-Migas, A. Attitudes toward Vaccination against COVID-19 in Poland. A Longitudinal Study Performed before and Two Months after the Commencement of the Population Vaccination Programme in Poland. Vaccines 2021, 9, 503. [Google Scholar] [CrossRef] [PubMed]
- Raciborski, F.; Jankowski, M.; Gujski, M.; Pinkas, J.; Samel-Kowalik, P. Changes in Attitudes towards the COVID-19 Vaccine and the Willingness to Get Vaccinated among Adults in Poland: Analysis of Serial, Cross-Sectional, Representative Surveys, January-April 2021. Vaccines 2021, 9, 832. [Google Scholar] [CrossRef] [PubMed]
- Sowa, P.; Kiszkiel, Ł.; Laskowski, P.P.; Alimowski, M.; Szczerbinski, Ł.; Paniczko, M.; Moniuszko-Malinowska, A.; Kaminski, K. COVID-19 Vaccine Hesitancy in Poland-Multifactorial Impact Trajectories. Vaccines 2021, 9, 876. [Google Scholar] [CrossRef] [PubMed]
- Oleksy, T.; Wnuk, A.; Maison, D.; Łyś, A. Content matters. Different predictors and social consequences of general and government-related conspiracy theories on COVID-19. Personal. Individ. Differ. 2021, 168, 110289. [Google Scholar] [CrossRef] [PubMed]
- Neumann-Böhme, S.; Varghese, N.E.; Sabat, I.; Barros, P.P.; Brouwer, W.; Van Exel, J.; Schreyögg, J.; Stargardt, T. Once We Have It, Will We Use It? A European Survey on Willingness to Be Vaccinated against COVID-19. Eur. J. Health Econ. 2020, 21, 977–982. [Google Scholar] [CrossRef]
- Callaghan, T.; Moghtaderi, A.; Lueck, J.A.; Hotez, P.; Strych, U.; Dor, A.; Fowler, E.F.; Motta, M. Correlates and disparities of intention to vaccinate against COVID-19. Soc. Sci. Med. 2021, 272, 113638. [Google Scholar] [CrossRef] [PubMed]
- Fridman, A.; Gershon, R.; Gneezy, A. COVID-19 and vaccine hesitancy: A longitudinal study. PLoS ONE 2021, 16, e0250123. [Google Scholar] [CrossRef] [PubMed]
- Edwards, B.; Biddle, N.; Gray, M.; Sollis, K. COVID-19 Vaccine Hesitancy and Resistance: Correlates in a Nationally Representative Longitudinal Survey of the Australian Population. PLoS ONE 2021, 16, e0248892. [Google Scholar] [CrossRef]
- Lazarus, J.V.; Wyka, K.; Rauh, L.; Rabin, K.; Ratzan, S.; Gostin, L.O.; Larson, H.J.; El-Mohandes, A. Hesitant or Not? The Association of Age, Gender, and Education with Potential Acceptance of a COVID-19 Vaccine: A Country-Level Analysis. J. Health Commun. 2020, 25, 799–807. [Google Scholar] [CrossRef]
- Oleksy, T.; Wnuk, A.; Gambin, M.; Łyś, A.; Bargiel-Matusiewicz, K.; Pisula, E. Barriers and facilitators of willingness to vaccinate against COVID-19: Role of prosociality, authoritarianism and conspiracy mentality. A four-wave longitudinal study. Personal. Individ. Differ. 2022, 190, 111524. [Google Scholar] [CrossRef]
- Lindholt, M.F.; Jørgensen, F.; Bor, A.; Petersen, M.B. Public Acceptance of COVID-19 Vaccines: Cross-National Evidence on Levels and Individual-Level Predictors Using Observational Data. BMJ Open 2021, 11, e048172. [Google Scholar] [CrossRef]
- Pagliaro, S.; Sacchi, S.; Pacilli, M.G.; Brambilla, M.; Lionetti, F.; Bettache, K.; Bianchi, M.; Biella, M.; Bonnot, V.; Boza, M.; et al. Trust predicts COVID-19 prescribed and discretionary behavioral intentions in 23 countries. PLoS ONE 2021, 16, e0248334. [Google Scholar] [CrossRef] [PubMed]
- Malik, A.A.; McFadden, S.M.; Elharake, J.; Omer, S.B. Determinants of COVID-19 Vaccine Acceptance in the US. EClinicalMedicine 2020, 26, 100495. [Google Scholar] [CrossRef]
- Sallam, M. COVID-19 Vaccine Hesitancy Worldwide: A Concise Systematic Review of Vaccine Acceptance Rates. Vaccines 2021, 9, 160. [Google Scholar] [CrossRef] [PubMed]
- Biswas, M.R.; Alzubaidi, M.S.; Shah, U.; Abd-Alrazaq, A.A.; Shah, Z. A Scoping Review to Find Out Worldwide COVID-19 Vaccine Hesitancy and Its Underlying Determinants. Vaccines 2021, 9, 1243. [Google Scholar] [CrossRef] [PubMed]
- Aw, J.; Seng, J.; Seah, S.; Low, L.L. COVID-19 Vaccine Hesitancy-A Scoping Review of Literature in High-Income Countries. Vaccines 2021, 9, 900. [Google Scholar] [CrossRef] [PubMed]
- Zintel, S.; Flock, C.; Arbogast, A.L.; Forster, A.; von Wagner, C.; Sieverding, M. Gender differences in the intention to get vaccinated against COVID-19: A systematic review and meta-analysis. Z. Gesundh. = J. Public Health 2022, 1–25. [Google Scholar] [CrossRef]
- Domnich, A.; Cambiaggi, M.; Vasco, A.; Maraniello, L.; Ansaldi, F.; Baldo, V.; Bonanni, P.; Calabrò, G.E.; Costantino, C.; de Waure, C.; et al. Attitudes and Beliefs on Influenza Vaccination during the COVID-19 Pandemic: Results from a Representative Italian Survey. Vaccines 2020, 8, 711. [Google Scholar] [CrossRef]
- Soares, P.; Rocha, J.V.; Moniz, M.; Gama, A.; Laires, P.A.; Pedro, A.R.; Dias, S.; Leite, A.; Nunes, C. Factors Associated with COVID-19 Vaccine Hesitancy. Vaccines 2021, 9, 300. [Google Scholar] [CrossRef] [PubMed]
- Patwary, M.M.; Alam, M.A.; Bardhan, M.; Disha, A.S.; Haque, M.Z.; Billah, S.M.; Kabir, M.P.; Browning, M.H.E.M.; Rahman, M.M.; Parsa, A.D.; et al. COVID-19 Vaccine Acceptance among Low- and Lower-Middle-Income Countries: A Rapid Systematic Review and Meta-Analysis. Vaccines 2022, 10, 427. [Google Scholar] [CrossRef] [PubMed]
- Troiano, G.; Nardi, A. Vaccine hesitancy in the era of COVID-19. Public Health 2021, 194, 245–251. [Google Scholar] [CrossRef] [PubMed]
- Independent Vaccination Ads Motivate Higher Levels of Vaccine Action than Federal Government’s Attempts. Available online: https://www.forethought.com.au/our-thinking/independent-vaccination-ads-motivate-higher-levels-of-vaccine-action-than-federal-governments-attempts (accessed on 21 June 2022).
- Goryńska, E. Przymiotnikowa Skala Nastroju UMACL Geralda Matthewsa, A. Grahama Chamberlaina, Dylana M. Jonesa; Pracownia Testów Psychologicznych Polskiego Towarzystwa Psychologicznego: Warszawa, Polska, 2005. [Google Scholar]
- Matthews, G.; Jones, D.M.; Chamberlain, A.G. Refining the Measurement of Mood: The UWIST Mood Adjective Checklist. Br. J. Psychol. 1990, 81, 17–42. [Google Scholar] [CrossRef]
- Brzozowski, P. Skala Uczuć Pozytywnych i Negatywnych SUPIN: Polska Adaptacja Skali PANAS Davida Watsona i Lee Anny Clark; Pracownia Testów Psychologicznych Polskiego Towarzystwa Psychologicznego: Warszawa, Polska, 2010. [Google Scholar]
- Watson, D.; Clark, L.A.; Tellegen, A. Development and Validation of Brief Measures of Positive and Negative Affect: The PANAS Scales. J. Pers. Soc. Psychol. 1988, 54, 1063–1070. [Google Scholar] [CrossRef] [PubMed]
- Juczyński, Z. Narzędzia Pomiaru w Promocji i Psychologii Zdrowia; Pracownia Testów Psychologicznych Polskiego Towarzystwa Psychologicznego: Warszawa, Polska, 2012. [Google Scholar]
- Diener, E.; Emmons, R.A.; Larsen, R.J.; Griffin, S. The Satisfaction with Life Scale. J. Pers. Assess. 1985, 49, 71–75. [Google Scholar] [CrossRef] [PubMed]
- Scheier, M.F.; Carver, C.S.; Bridges, M.W. Distinguishing Optimism from Neuroticism (and Trait Anxiety, Self-mastery, and Self-esteem): A Reevaluation of the Life Orientation Test. J. Pers. Soc. Psychol. 1994, 67, 1063–1078. [Google Scholar] [CrossRef] [PubMed]
- Strelau, J.; Jaworska, A.; Wrześniewski, K.; Szczepaniak, P. Kwestionariusz Radzenia Sobie w Sytuacjach Stresowych; Pracownia Testów Psychologicznych Polskiego Towarzystwa Psychologicznego: Warszawa, Polska, 2005. [Google Scholar]
- Endler, N.; Parker, J.D. Coping Inventory for Stressful Situations; Multi-Health Systems: Toronto, ON, Canada, 1990. [Google Scholar]
- R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing; R Core Team: Vienna, Austria, 2021; Available online: https://www.R-project.org/ (accessed on 1 May 2022).
- Tian, T.; Zhang, J.; Hu, L.; Jiang, Y.; Duan, C.; Li, Z.; Wang, X.; Zhang, H. Risk factors associated with mortality of COVID-19 in 3125 counties of the United States. Infect. Dis. Poverty 2021, 10, 3. [Google Scholar] [CrossRef]
- Raciborski, F.; Samel-Kowalik, P.; Gujski, M.; Pinkas, J.; Arcimowicz, M.; Jankowski, M. Factors Associated with a Lack of Willingness to Vaccinate against COVID-19 in Poland: A 2021 Nationwide Cross-Sectional Survey. Vaccines 2021, 9, 1000. [Google Scholar] [CrossRef]
- Twardowska-Staszek, E.; Biel, K.; Rostek, I. Causes of Stress Among Poles and How They Cope with Stress during the COVID-19 Pandemic. Front. Psychiatry 2022, 13, 829918. [Google Scholar] [CrossRef]
- Khubchandani, J.; Sharma, S.; Price, J.H.; Wiblishauser, M.J.; Sharma, M.; Webb, F.J. COVID-19 Vaccination Hesitancy in the United States: A Rapid National Assessment. J. Community Health 2021, 46, 270–277. [Google Scholar] [CrossRef]
- Eberhardt, J.; Ling, J. Predicting COVID-19 vaccination intention using protection motivation theory and conspiracy beliefs. Vaccine 2021, 39, 6269–6275. [Google Scholar] [CrossRef]
- Lamy, L.; Guegan, J.; Fischer-Lokou, J.; Guéguen, N. Being vaccinated for love or despite fear of vaccination? The influence of priming on vaccination intention among young French people. Health Psychol. Rep. 2022, 10, 31–36. [Google Scholar] [CrossRef]
- Prati, G. Mental health and its psychosocial predictors during national quarantine in Italy against the coronavirus disease 2019 (COVID-19). Anxiety Stress Coping 2021, 34, 145–156. [Google Scholar] [CrossRef] [PubMed]
- Talarowska, M.; Chodkiewicz, J.; Nawrocka, N.; Miniszewska, J.; Biliński, P. Mental Health and the SARS-CoV-2 Epidemic—Polish Research Study. Int. J. Environ. Res. Public Health 2020, 17, 7015. [Google Scholar] [CrossRef] [PubMed]
DEMOGRAPHIC VARIABLES | n | % | |
---|---|---|---|
AGE | Under 22 | 129 | 30.94 |
23–34 years of age | 96 | 23.02 | |
35–60 years of age | 174 | 41.73 | |
Over 60 years of age | 18 | 4.32 | |
SEX | women | 372 | 89.21 |
men | 45 | 10.79 | |
MARITAL STATUS | single | 238 | 57.07 |
married | 143 | 34.29 | |
divorced or separated | 22 | 5.28 | |
widow/widower | 5 | 1.2 | |
clergy | 9 | 2.1 | |
CHILDREN | no | 246 | 58.99 |
yes | 171 | 41.01 | |
PLACE OF RESIDENCE | big city | 147 | 35.25 |
medium-size city | 69 | 16.55 | |
small town | 60 | 14.39 | |
village | 141 | 33.81 | |
EDUCATION | basic vocational | 7 | 1.68 |
secondary | 44 | 10.55 | |
higher | 200 | 47.96 | |
I am still learning/studying | 166 | 39.81 | |
EMPLOYMENT | I work full-time | 184 | 44.12 |
I work part-time | 14 | 3.36 | |
I do not work | 18 | 4.3 | |
pensioner | 13 | 3.12 | |
pupil/student | 85 | 20.38 | |
I am learning/studying and working | 103 | 24.70 |
PARAMETER | GROUP | p | ||||
---|---|---|---|---|---|---|
GROUP A (N = 104) | GROUP B (N = 92) | GROUP C (N = 221) | TOTAL (N = 417) | |||
AGE [YEARS] | MSD | 37.98 ± 1 5.06 | 32.13 ± 1 3.14 | 33.62 ± 1 3.37 | 34.38 ± 1 3.9 | p = 0.006 * |
median | 3 7.5 | 24 | 29 | 31 | ||
quartiles | 23–50 | 21–4 1.5 | 22–45 | 22–45 | A > C,B | |
SEX | Women | 91 (8 7.50%) | 88 (9 5.65%) | 193 (8 7.33%) | 372 (8 9.21%) | p = 0.078 |
Men | 13 (1 2.50%) | 4 (4.35%) | 28 (1 2.67%) | 45 (10.79%) | ||
MARITAL STATUS | Single | 52 (50.00%) | 55 (59.78%) | 131 (59.28%) | 238 (57.07%) | p = 0.801 |
Married | 42 (40.38%) | 28 (30.43%) | 73 (33.03%) | 143 (34.29%) | ||
Divorced/Separated | 6 (5.77%) | 6 (6.52%) | 10 (4.52%) | 22 (5.28%) | ||
Widow/Widower | 2 (1.92%) | 1 (1.09%) | 2 (0.90%) | 5 (1.20%) | ||
Clergy | 2 (1.92%) | 2 (2.17%) | 5 (2.26%) | 9 (2.16%) | ||
CHILDREN | No | 55 (52.88%) | 56 (60.87%) | 135 (61.09%) | 246 (58.99%) | p = 0.343 |
Yes | 49 (47.12%) | 36 (39.13%) | 86 (38.91%) | 171 (41.01%) | ||
PLACE OF RESIDENCE | Big city | 44 (42.31%) | 28 (30.43%) | 75 (33.94%) | 147 (35.25%) | p = 0.479 |
Medium-sized city | 17 (16.35%) | 14 (15.22%) | 38 (17.19%) | 69 (16.55%) | ||
Small town | 16 (15.38%) | 13 (14.13%) | 31 (14.03%) | 60 (14.39%) | ||
Village | 27 (25.96%) | 37 (40.22%) | 77 (34.84%) | 141 (33.81%) | ||
EDUCATION | Primary/secondary | 0 (0.00%) | 0 (0.00%) | 0 (0.00%) | 0 (0.00%) | p = 0.082 |
Basic vocational | 1 (0.96%) | 2 (2.17%) | 4 (1.81%) | 7 (1.68%) | ||
Average | 6 (5.77%) | 14 (1 5.22%) | 24 (10.86%) | 44 (10.55%) | ||
Higher | 62 (5 9.62%) | 36 (3 9.13%) | 102 (4 6.15%) | 200 (4 7.96%) | ||
I am still learning/studying | 35 (3 3.65%) | 40 (4 3.48%) | 91 (4 1.18%) | 166 (3 9.81%) | ||
EMPLOYMENT | I work full-time | 52 (50.00%) | 28 (30.43%) | 104 (47.06%) | 184 (44.12%) | p = 0.004 * |
I work on a casual basis | 2 (1.92%) | 8 (8.70%) | 4 (1.81%) | 14 (3.36%) | ||
I am not working | 5 (4.81%) | 6 (6.52%) | 7 (3.17%) | 18 (4.32%) | ||
I am a pensioner | 7 (6.73%) | 3 (3.26%) | 3 (1.36%) | 13 (3.12%) | ||
Pupil/student | 18 (1 7.31%) | 21 (2 2.83%) | 46 (20.81%) | 85 (20.38%) | ||
I am learning/studying and working | 20 (1 9.23%) | 26 (2 8.26%) | 57 (2 5.79%) | 103 (2 4.70%) |
PARAMETER | GROUP | p | ||||
---|---|---|---|---|---|---|
GROUP A (N = 104) | GROUP B (N = 92) | GROUP C (N = 221) | TOTAL (N = 417) | |||
Economic conditions | My standard of living has not changed | 57 (54.81%) | 40 (43.48%) | 104 (47.06%) | 201 (48.20%) | p = 0.53 |
My standard of living has decreased | 31 (29.81%) | 31 (33.70%) | 73 (33.03%) | 135 (32.37%) | ||
My standard of living has risen | 16 (15.38%) | 21 (22.83%) | 44 (19.91%) | 81 (19.42%) | ||
Have you had COVID-19? | Not | 66 (63.46%) | 52 (56.52%) | 134 (60.63%) | 252 (60.43%) | p = 0.609 |
Yes | 38 (36.54%) | 40 (43.48%) | 87 (3 9.37%) | 165 (39.57%) | ||
Has anyone in your family had COVID-19? | Not | 31 (29.81%) | 34 (36.96%) | 95 (4 2.99%) | 160 (38.37%) | p = 0.071 |
Yes | 73 (70.19%) | 58 (63.04%) | 126 (5 7.01%) | 257 (61.63%) | ||
Which of the following situations stress you the most? ** | Lack of social contacts | 34 (32.69%) | 33 (35.87%) | 74 (33.48%) | 141 (33.81%) | p = 0.886 |
Lack of respirators and medical staff in hospitals | 37 (35.58%) | 22 (23.91%) | 56 (25.34%) | 115 (27.58%) | p = 0.105 | |
Unemployment or the prospect of losing one’s job | 18 (17.31%) | 17 (18.48%) | 48 (21.72%) | 83 (19.90%) | p = 0.602 | |
Possibility of contracting COVID-19 | 31 (29.81%) | 12 (13.04%) | 51 (23.08%) | 94 (22.54%) | p = 0.019 * | |
The possibility of my loved ones contracting COVID-19 | 70 (67.31%) | 33 (35.87%) | 105 (47.51%) | 208 (49.88%) | p < 0.001 * | |
Online teaching | 44 (42.31%) | 23 (25.00%) | 62 (28.05%) | 129 (30.94%) | p = 0.013 * | |
Restrictions | 25 (24.04%) | 46 (50.00%) | 65 (29.41%) | 136 (32.61%) | p < 0.001 * | |
My family’s financial problems | 22 (21.15%) | 23 (25.00%) | 50 (2 2.62%) | 95 (22.78%) | p = 0.812 | |
National economic situation | 72 (69.23%) | 53 (5 7.61%) | 111 (50.23%) | 236 (56.59%) | p = 0.005 * | |
Political situation in the country | 84 (80.77%) | 51 (5 5.43%) | 127 (57.47%) | 262 (62.83%) | p < 0.001 * | |
Impeded access to treatment for other diseases | 66 (63.46%) | 60 (6 5.22%) | 131 (59.28%) | 257 (61.63%) | p = 0.558 | |
Other | 4 (3.85%) | 8 (8.70%) | 11 (4.98%) | 23 (5.52%) | p = 0.292 |
PARAMETER | GROUP | |||||
---|---|---|---|---|---|---|
GROUP A (N = 104) | GROUP B (N = 92) | GROUP C (N = 221) | p | |||
UMACL | HT | M/SD | 25.16 ± 2.01 | 24.89 ± 1.82 | 25.21 ± 2.03 | p = 0.387 |
median | 25 | 25 | 25 | |||
quartiles | 24–26 | 24–26 | 24–26 | |||
TA | M/SD | 22.62 ± 3.86 | 22.12 ± 3.68 | 21.94 ± 3.67 | p = 0.262 | |
median | 23 | 22 | 21 | |||
quartiles | 20–26 | 20–25 | 19–25 | |||
EA | M/SD | 23.3 ± 3.91 | 23.98 ± 4.05 | 23.91 ± 3.7 | p = 0.17 | |
median | 23 | 2 3.5 | 24 | |||
quartiles | 20–26 | 21–27 | 22–26 | |||
PANAS | PA | M/SD | 28.05 ± 8.38 | 25.45 ± 9.34 | 26.3 ± 7.97 | p = 0.071 |
median | 29 | 25 | 27 | |||
quartiles | 23.75–33 | 17–32 | 20–31 | |||
NA | M/SD | 22.89 ± 9.27 | 21.55 ± 9.12 | 20.37 ± 8.43 | p = 0.072 | |
median | 2 1.5 | 20 | 18 | |||
quartiles | 1 4.75–30 | 14–2 8.25 | 14–25 | |||
SWLS | M/SD | 20.28 ± 6.83 | 19.33 ± 7.01 | 19.55 ± 5.91 | p = 0.373 | |
median | 21 | 18 | 20 | |||
quartiles | 15–26 | 14–25 | 15–24 | |||
LOT-R | M/SD | 14.55 ± 4.8 | 14.23 ± 5.48 | 14.18 ± 4.5 | p = 0.836 | |
median | 15 | 15 | 15 | |||
quartiles | 11–18 | 11–18 | 11–17 | |||
CISS | TOC | M/SD | 58.07 ± 8.92 | 55.67 ± 9 | 56.55 ± 8.57 | p = 0.151 |
median | 58 | 55 | 56 | |||
quartiles | 51–65 | 50–63 | 51–62 | |||
EOC | M/SD | 47.66 ± 12.02 | 49.66 ± 13.13 | 47.64 ± 10.59 | p = 0.241 | |
median | 47 | 51 | 47 | |||
quartiles | 39–5 6.25 | 3 8.75–61 | 40–55 | |||
AOC | M/SD | 46.65 ± 8.12 | 47.65 ± 9.57 | 47.27 ± 8.5 | p = 0.8 | |
median | 48 | 47 | 48 | |||
quartiles | 40–52 | 41.75–54 | 41–54 | |||
D | M/SD | 20.56 ± 5.04 | 2 1.82 ± 6.08 | 21.53 ± 5.43 | p = 0.224 | |
median | 21 | 2 1.5 | 22 | |||
quartiles | 17–24 | 18–25 | 17–26 | |||
SD | M/SD | 17.76 ± 3.76 | 17.16 ± 4.03 | 17.35 ± 3.88 | p = 0.474 | |
median | 18 | 17 | 17 | |||
quartiles | 15–20 | 14–20 | 15–20 |
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
Twardowska-Staszek, E.; Rostek, I.; Biel, K. Sociodemographic and Psychological Variables and Concerns Related to COVID-19 Vaccination among Polish Citizens. Int. J. Environ. Res. Public Health 2022, 19, 9507. https://doi.org/10.3390/ijerph19159507
Twardowska-Staszek E, Rostek I, Biel K. Sociodemographic and Psychological Variables and Concerns Related to COVID-19 Vaccination among Polish Citizens. International Journal of Environmental Research and Public Health. 2022; 19(15):9507. https://doi.org/10.3390/ijerph19159507
Chicago/Turabian StyleTwardowska-Staszek, Estera, Irmina Rostek, and Krzysztof Biel. 2022. "Sociodemographic and Psychological Variables and Concerns Related to COVID-19 Vaccination among Polish Citizens" International Journal of Environmental Research and Public Health 19, no. 15: 9507. https://doi.org/10.3390/ijerph19159507