ABSTRACT
Objective:
To evaluate factors associated with the adoption of coronavirus disease 2019 (COVID-19) preventive health behaviors among adults in Antigua and Barbuda.
Methods:
A nationally representative cross-sectional survey was conducted from September 22 to November 29, 2021. Data were collected via computer-assisted telephone interviewing to (1) assess the COVID-19 information sources utilized and the preventive behaviors adopted by study participants and (2) assess the impact of COVID-19 on noncommunicable diseases (NCDs) and mental health. The survey asked about demographic factors, the use of information sources regarding COVID-19, COVID-19 prevention behaviors, NCD diagnoses, and mental health. Findings for objective 1 are presented. A descriptive analysis for demographic variables and COVID-19 information sources utilized by study participants was performed. A multivariable logistic regression was conducted to investigate factors associated with the adoption of preventive behaviors.
Results:
Data from 2 001 telephone interviews were used in the analysis. Most participants were female (53.3%), never married (59.2%), and reported being educated beyond secondary school level (75.4%). The main media outlets accessed for COVID-19 prevention information were social networks, television, and radio, respectively. Participants reported that the Ministry of Health, Wellness and the Environment was viewed as the most trusted information source. We found no association with marital status, education level, main source of COVID-19 information, most trusted source that influenced behavior change, and the practicing of social distancing by persons who reported adhering to COVID-19 prevention strategies always or sometimes.
Conclusion:
Our characterization of information sources utilized and COVID-19 preventive behaviors provides baseline information for the development of future public health prevention and promotional efforts.
Keywords: Caribbean region, COVID-19, pandemics, information sources
RESUMEN
Objetivo.
Evaluar los factores relacionados con la adopción de comportamientos de salud preventivos contra la enfermedad por el coronavirus del 2019 (COVID-19) en la población adulta de Antigua y Barbuda.
Métodos.
Del 22 de septiembre al 29 de noviembre del 2021 se llevó a cabo una encuesta transversal representativa a nivel nacional. Los datos se recogieron mediante entrevistas telefónicas asistidas por computadora con el fin de: 1) evaluar las fuentes de información sobre la COVID-19 utilizadas y las medidas de prevención adoptadas por las personas que participaron en el estudio, y 2) evaluar repercusión de la COVID-19 en las enfermedades no transmisibles (ENT) y la salud mental. En la encuesta se hicieron preguntas sobre los factores demográficos, el uso de fuentes de información sobre la COVID-19, los comportamientos de prevención de la COVID-19, los diagnósticos de ENT y la salud mental. A continuación se presentan los resultados correspondientes al primer objetivo. Se realizó un análisis descriptivo de las variables demográficas de las personas participantes y de las fuentes de información sobre la COVID-19 que consultaron. Mediante una regresión logística multivariante se investigaron los factores asociados con la adopción de comportamientos preventivos.
Resultados.
En el análisis se utilizaron los datos de 2001 entrevistas telefónicas. La mayoría de las personas que participaron fueron mujeres (53,3%), solteras (59,2%) y con una escolaridad declarada superior a la enseñanza secundaria (75,4%). Los principales medios de comunicación consultados con el fin de obtener información sobre la prevención de la COVID-19 fueron las redes sociales, la televisión y la radio, en ese orden. Las personas encuestadas indicaron que el Ministerio de Salud, Bienestar y Medioambiente se consideraba como la fuente de información que inspiraba mayor confianza. No se observó ninguna asociación entre el estado civil, la escolaridad, la principal fuente de información sobre la COVID-19, la fuente de mayor confianza que influyó en la modificación del comportamiento y la práctica del distanciamiento social por parte de las personas que refirieron haber seguido, siempre o en ocasiones, las estrategias de prevención de la COVID-19.
Conclusiones.
La presente descripción de las fuentes de información utilizadas y de los comportamientos preventivos adoptados frente a la COVID-19 proporciona datos de referencia para las iniciativas futuras de prevención y promoción en el ámbito de la salud pública.
Palabras clave: Región del Caribe, COVID-19, pandemias, fuentes de información
RESUMO
Objetivo.
Avaliar os fatores associados à adoção de comportamentos de saúde preventivos em relação à doença pelo coronavírus 2019 (COVID-19) entre adultos em Antígua e Barbuda.
Métodos.
Um inquérito transversal representativo de âmbito nacional foi realizado entre 22 de setembro e 29 de novembro de 2021. Os dados foram coletados por meio de entrevistas telefônicas assistidas por computador com o objetivo de (1) avaliar as fontes de informação sobre a COVID-19 usadas e os comportamentos preventivos adotados pelos participantes do estudo, e (2) avaliar o impacto da COVID-19 nas doenças não transmissíveis (DNTs) e na saúde mental. A pesquisa abordou fatores demográficos, o uso de fontes de informação sobre a COVID-19, comportamentos de prevenção da COVID-19, diagnósticos de DNTs e saúde mental. São apresentados os resultados relativos ao objetivo 1. Foi realizada uma análise descritiva das variáveis demográficas e das fontes de informação sobre a COVID-19 usadas pelos participantes do estudo. Uma regressão logística multivariável foi utilizada para investigar os fatores associados à adoção de comportamentos preventivos.
Resultados.
Foram usados na análise os dados de 2001 entrevistas por telefone. A maioria dos participantes era do sexo feminino (53,3%) e nunca casada (59,2%) e declarava ter escolaridade acima do ensino médio (75,4%). Os principais meios de comunicação consultados para obter informações sobre a prevenção da COVID-19 foram as redes sociais, a televisão e o rádio, nessa ordem. Os participantes relataram que o Ministério da Saúde, do Bem-Estar e do Meio Ambiente era considerado a fonte de informações mais confiável. Não foram encontradas associações com o estado civil, o nível de escolaridade, a principal fonte de informações sobre a COVID-19, a fonte mais confiável que influenciou mudanças de comportamento e a prática do distanciamento social por parte das pessoas que relataram aderir às estratégias de prevenção da COVID-19 sempre ou às vezes.
Conclusão:
A caracterização das fontes de informação usadas e dos comportamentos preventivos em relação à COVID-19 fornece dados de referência para a elaboração de futuras iniciativas de prevenção e promoção da saúde pública.
Palavras-chave: Região do Caribe, COVID-19, pandemias, fonte de informação
The World Health Organization (WHO) was notified by the Chinese government of an outbreak of viral pneumonia in Wuhan City on 31 December 2019 (1). This viral pneumonia was later classified as a new disease: COVID-19 caused by the viral agent SARS-CoV-2 (2), with cases subsequently being identified in several countries outside of China. Antigua and Barbuda reported its first case of COVID-19 on March 13, 2020, from an individual with a history of international travel (3). Subsequent management of COVID-19 cases by the Antigua and Barbuda health system relied on local and regional medical expertise and international evidence. Early response measures involved establishment of a national COVID-19 task force, launch of a COVID-19 education and awareness campaign, refurbishment of the Margetson Ward at Holberton Hospital to provide care for infected persons, laboratory testing of suspected cases, isolation of infected individuals, and contact tracing to identify potentially infected cases. When the international scientific community learned that SARS-CoV-2 was transmitted via droplets, and in the absence of an effective treatment or vaccine, public health measures shifted to suppressing spread of infection through the promotion of nonpharmaceutical interventions.
As European and North American countries appeared to be struggling to address the unfolding COVID-19 pandemic, regional Heads of Government of the Caribbean Community (CARICOM) acted quickly and held a series of meetings to harmonize their responses and implement national measures to restrict population movement (4). Caribbean countries implemented a range of border closures, lock-down measures, and mask mandates. On March 26, 2020, the government of Antigua and Barbuda closed the V. C. Bird International Airport to all international commercial air traffic (5). On March 27, 2020, two weeks following the first reported COVID-19 case, the cabinet declared a state of emergency (SOE) (6). Under the SOE, a curfew from 8 pm to 6 am daily commenced at 12 am Saturday, March 28, 2020, with the Royal Police Force of Antigua and Barbuda and the Antigua and Barbuda Defense Force patrolling the streets to ensure compliance with the curfew hours (6). During the SOE, (i) only essential workers were permitted to operate; (ii) individuals were required to wear masks in public spaces; (iii) select businesses, such as pharmacies, financial institutions, supermarkets, gasoline stations, bakeries, and airline and cleaning services, were allowed to conduct business during restricted hours; and (iv) public gatherings, such as attendance at funerals and weddings, were confined to the congregation of no more than 25 persons at one time (6).
While restrictions on the movement of people helped slow the spread of the SARS-CoV-2 virus, the effect on the country’s tourism-dependent economy was significant (7). On June 1, 2020, the government reopened its borders to international and regional air traffic on a phased approach (8). Arriving passengers were required to quarantine in designated locations for 14 days, wear masks in public places, and adhere to screening and temperature checks by the Port Health Authority (8). The SOE and curfew that had been implemented to reduce spread of the SARS-CoV-2 virus ended on December 23, 2020, approximately 9 months following its declaration (9). Although these ended, other protocols around the management of the spread of the SARS-CoV-2 virus, such as wearing masks in public, practicing social distancing, etc., remained in place for several months especially in the weeks and months before vaccines became available (9). The first round of COVID-19 vaccines was distributed February 17, 2021, and due to limited supply, utilized a phased vaccination approach (10).
Several communication channels were used to reach the population with COVID-19 preventive messages and keep them well informed on national directives. These included use of social media platforms, government websites, and leveraging local media outlets (television, newspapers, and radio). Public health messaging was focused on providing guidance to the public to improve their knowledge about COVID-19 and its spread, influencing their attitudes to adopt public health preventive behaviors, and improving adherence to public health preventive measures. Previous research has shown that the decision of persons to adopt preventive measures against infectious diseases can be influenced by several factors, including socioeconomic variables (for example, gender, age, marital status, and educational background), perceived risk of contracting the disease, leadership, and trust (11).
While the impact of the COVID-19 pandemic on countries is multifaceted, restrictive measures imposed during the pandemic may have limited the ability of persons with noncommunicable diseases (NCDs) to access medical care and other health services, engage in outdoor activities, and access healthy foods (12). During public health crises, the need for timely data to support decision-making is even more critical. In 2020, the Pan American Health Organization (PAHO) developed and launched the Rapid Mobile Phone Survey (RaMPS) initiative as a complementary surveillance tool for use by CARICOM Member States to assess policies and interventions on NCDs in adults in light of the COVID-19 pandemic (13). From September 22 to November 29, 2021, the Ministry of Health, Wellness and Environment (MOHWE) conducted the RaMPS. The objectives of the study were to (i) assess COVID-19 information sources and preventive behaviors adopted and (ii) gauge the impact of COVID-19 on NCDs and mental health. This report presents the findings from an assessment of the use of and trust in information sources, and their association with the adoption of public health preventive behaviors. Findings on the impact of COVID-19 on NCDs and mental health will be forthcoming in another publication.
MATERIALS AND METHODS
Setting
Antigua and Barbuda, a small island developing state (SIDS) in the Lesser Antilles, is composed of three islands: Antigua measuring 280 km2, Barbuda measuring 160 km2, and the uninhabited Redonda measuring 1.6 km2 (14). According to the 2011 census, the total population of the country was 85 567 people, with 83 933 in Antigua and 1 634 in Barbuda (15). Administratively, the country is divided into six parishes—St. John (the most populous), St. George, St. Peter, St. Phillip, St. Paul, and St. Mary—and two dependencies: Barbuda and Redonda. In 2022, approximately 91% of the population had access to internet services (16).
Study Design and Population
A cross-sectional RaMPS, which utilized computer-assisted telephone interviewing (CATI), was conducted to (i) assess COVID-19 information sources utilized and preventive behaviors adopted by study participants and (ii) assess the impact of COVID-19 on NCDs and mental health. Although CATI can be associated with low response rates, this approach was used as it is a low-cost, efficient method that did not require physical interaction as the population at large was still being advised to practice social distancing. The study was conducted from September 22 to November 29, 2021, and included persons living in Antigua and Barbuda ≥18 years of age with access to a mobile phone. Inactive and business mobile numbers were excluded from the study.
Random digit dialing through support from the Research Triangle Institute (RTI International) was used to generate the study sample. The sample was stratified by mobile network operator (MNO) with each stratum proportional to the market share of each of the three MNOs operating in Antigua and Barbuda (APUA, Digicel, and Flow). A total of 13 153 mobile numbers were called, with 5 363 users contacted. In total, 2 001 persons were willing to participate in the study and full interviews were conducted, representing a 38.2% completion rate.
Survey Instrument
As no standardized scales had been developed for a Caribbean population, a 36-question instrument was developed and organized into 5 sections. Section 1 contained five questions and focused on the agreement to participate in the study and demographics (age, sex, and place of residence) as stated by the participant. Section 2 consisted of two questions to capture background information on the participant—highest level of education and marital status. In the context of COVID-19, the next three sections included the following: 10 questions focused on individual risk behaviors and protection, 3 questions regarding risk communication, and 16 questions focused on access to services. Question types included single-option, categorical, contingency, Likert, and open-ended.
A team of 38 interviewers were trained via a 3-day course that combined classroom training with real-world practice to verbally administer the questionnaire. Interviewers introduced themselves and explained that the study was part of the MOHWE’s surveillance activities related to NCDs in the context of COVID-19 and that the interview will take approximately 15 minutes.
Statistical Analysis
Data were cleaned and analyzed using SPSS version 28 software. Descriptive analysis was conducted for demographic variables. Frequencies and percentages were calculated for all categorical variables, and measures of central tendency were also calculated for continuous variables. Chi-squared tests were performed to assess the bivariate relationship between sociodemographic characteristics (sex, age, marital status, education) and COVID-19 mitigation behaviors (social distancing, avoiding public spaces/transport, using face coverings, official prevention messages). For outcome variables (e.g., practiced social distancing, used a mask/chin strap that included “don’t know” and “refuse to answer”), response categories with less than 5% of responses were removed (e.g., “never,” “don’t know”). A p-value of <0.05 was considered to be statistically significant. Logistic regression models were used to assess adjusted odds ratios (aORs) and confidence intervals. The main effect model, which included age and sex, was used to assess the strength of the association of the remaining variables by individually adding each variable to the main effect model.
Ethical Considerations
Participants were informed that their participation in the study was voluntary with no direct benefits, guaranteed anonymity, and required verbal informed consent. The study was conducted according to the ethical standards of the MOHWE. Ethical review and approval were obtained from the Pan American Health Organization Ethics Review Committee (reference number PAHOERC.0399.01).
RESULTS
Sociodemographic Characteristics
The sociodemographic profile of the 2 001 respondents is detailed in Table 1. The mean age of respondents was 41.9 years (range 18–84; standard deviation ±14.7). The majority of respondents were female, 1 066 (53.3%), and single, never married 1 184 (59.2%). Approximately half of respondents reported that they lived in St. John, 1 021 (51.0%), and 1 491 (75.4%) reported being educated beyond secondary school level.
TABLE 1. Sociodemographic characteristics of respondents (n = 2 001).
|
Characteristics |
Variables |
Total (%) |
|---|---|---|
|
Sex |
Female |
1 066 (53.3) |
|
Male |
935 (46.7) |
|
|
Age |
18–29 |
518 (25.9) |
|
30–44 |
583 (29.1) |
|
|
45+ |
900 (45.0) |
|
|
Marital status* |
Single, never married |
1 184 (59.2) |
|
Married |
614 (30.7) |
|
|
Divorced |
121 (6.0) |
|
|
Widowed |
47 (2.3) |
|
|
Concubine |
18 (0.9) |
|
|
Location* |
Rural |
1 199 (59.9) |
|
Urban |
747 (37.3) |
|
|
Parish |
St. John |
1 021 (51.0) |
|
St. Mary |
221 (11.0) |
|
|
St. Paul |
225 (11.2) |
|
|
St. Philip |
106 (5.3) |
|
|
St. George |
271 (13.5) |
|
|
St. Peter |
127 (6.3) |
|
|
Barbuda |
30 (1.5) |
|
|
Education |
Without official schooling |
27 (1.3) |
|
Primary |
200 (10.0) |
|
|
Secondary |
898 (44.9) |
|
|
Technical |
259 (12.9) |
|
|
University or higher |
593 (29.6) |
Source: Original table for this publication.
Note: Participants were also given the response option “refuse to answer” and “don’t know.” These values were not included in this table.
Adoption of Preventive Behaviors
Table 2 describes the preventive behaviors taken by respondents to protect themselves or others from COVID-19. Social distancing was “always” practiced by 1 463 (74.9%) of respondents and “sometimes” by 490 (25.1%) of respondents. Public places were avoided “always” by 442 (22.1%) of respondents and “sometimes” by 1 222 (61.2%) of respondents. Public transport was avoided “always” by 1 344 (67.3%) of respondents and “sometimes” by 336 (16.8%) of respondents, and a face mask or chin strap was used “always” by 1 712 (88.4%) of respondents and “sometimes” by 225 (11.6%) of respondents.
TABLE 2. COVID-19 preventive behaviors by sociodemographic factors.
|
Variables |
Practiced social distancing a (n = 1 953) |
Avoided public places (n = 1 997) |
Avoided public transport (n = 1 996) |
Used a mask/chin strapb (n = 1 937) |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Always |
Sometimes |
Always |
Sometimes |
Never |
Always |
Sometimes |
Never |
Always |
Sometimes |
|||||
|
No. (%) |
No. (%) |
p -value |
No. (%) |
No. (%) |
No. (%) |
p -value |
No. (%) |
No. (%) |
No. (%) |
p -value |
No. (%) |
No. (%) |
p -value |
|
|
Sex |
<0.001 |
0.047 |
0.531 |
<0.001 |
||||||||||
|
Male |
641 (70.9) |
263 (29.1) |
190 (20.3) |
572 (61.2) |
173 (18.5) |
638 (68.3) |
148 (15.8) |
148 (15.8) |
775 (85.1) |
136 (14.9) |
||||
|
Female |
822 (78.4) |
227 (21.6) |
252 (23.7) |
650 (61.2) |
160 (15.1) |
706 (66.5) |
188 (17.7) |
168 (15.8) |
937 (91.3) |
89 (8.7) |
||||
|
Age |
<0.001 |
<0.001 |
<0.001 |
<0.001 |
||||||||||
|
18-29 |
318 (63.1) |
186 (36.9) |
87 (16.8) |
324 (62.5) |
107 (20.7) |
293 (56.9) |
117 (22.7) |
105 (20.4) |
402 (80.9) |
95 (19.1) |
||||
|
30-44 |
421 (74.4 |
145 (25.6) |
124 21.3) |
343 (58.8) |
116 (19.9) |
416 (71.4) |
81 (13.9) |
86 (14.8) |
504 (89.4) |
60 (10.6) |
||||
|
45+ |
724 (88.0) |
159 (18.0) |
231 (25.8) |
555 (61.9) |
110 (12.3) |
635 (70.7) |
138 (15.4) |
125 (13.9) |
806 (92.0) |
70 (8.0) |
||||
|
Marital Status |
<0.001 |
0.758 |
<0.001 |
<0.001 |
||||||||||
|
Not Married |
969 (72.7) |
363 (27.3) |
300 (21.9) |
835 (61.0) |
233 (17.0) |
863 (63.2) |
262 (19.2) |
240 (19.2) |
1 144 (86.4) |
180 (13.6) |
||||
|
Married |
482 (79.8) |
122 (20.2) |
137 (22.4) |
379 (61.9) |
96 (15.7) |
471 (76.7) |
71 (11.6) |
72 (11.7) |
553 (92.8) |
43 (7.2) |
||||
|
Location |
0.174 |
0.104 |
0.061 |
0.658 |
||||||||||
|
Rural |
868 (73.7) |
309 (26.3) |
272 (22.7) |
741 (61.9) |
184 (15.4) |
811 (67.7) |
214 (17.9) |
173 (14.4) |
1 022 (88.0) |
139 (12.0) |
||||
|
Urban |
556 (76.6) |
170 (23.4) |
151 (20.2) |
456 (61.0) |
140 (18.7) |
501 (67.2) |
112 (15.0) |
133 (17.8) |
643 (88.8) |
81 (11.2) |
||||
|
Parish |
0.298 |
0.114 |
0.232 |
0.248 |
||||||||||
|
St. John |
724 (72.8) |
271 (27.2) |
223 (21.9) |
624 (61.3) |
171 (16.8) |
683 (67.0) |
162 (15.9) |
174 (17.1) |
872 (88.3) |
116 (11.7) |
||||
|
St. Mary |
167 (77.3) |
49 (22.7) |
47 (21.3) |
128 (57.9) |
46 (20.8) |
132 (60.0) |
52 (23.6) |
36 (16.4) |
185 (86.0) |
30 (14.0) |
||||
|
St. Paul |
175 (79.9) |
44 (20.1) |
46 (20.5) |
148 (66.1) |
30 (13.4) |
145 (64.4) |
46 (20.4) |
34 (15.1) |
203 (91.4) |
19 (8.6) |
||||
|
St. Philip |
79 (76.0) |
25 (24.0) |
23 (21.7) |
67 (63.2) |
16 (15.1) |
71 (67.0) |
21 (19.8) |
14 (13.2) |
91 (90.1) |
10 (9.9) |
||||
|
St. George |
203 (76.3) |
63 (23.7) |
59 (21.8) |
171 (63.1) |
41 (15.1) |
205 (75.9) |
32 (11.9) |
33 (12.2) |
235 (89.7) |
27 (10.3) |
||||
|
St. Peter |
92 (73.6) |
33 (26.4) |
30 (23.6) |
73 (57.5) |
24 (18.9) |
90 (71.4) |
17 (13.5) |
19 (15.1) |
102 (82.9) |
21 (17.1) |
||||
|
Barbuda |
23 (82.1) |
5 (17.9) |
14 (46.7) |
11 (36.7) |
5 (16.7) |
18 (60.0) |
6 (20.0) |
6 (20.0) |
24 (92.3) |
2 (7.7) |
||||
|
Education |
0.171 |
<0.001 |
<0.001 |
0.224 |
||||||||||
|
Without official schooling |
21 (80.8) |
5 (19.2) |
6 (22.2) |
14 (51.9) |
7 (25.9) |
14 (51.9) |
7 (25.9) |
6 (22.2) |
18 (75.0) |
6 (25.0) |
||||
|
Primary |
156 (79.6) |
40 (20.4) |
61 (30.7) |
119 (59.8) |
19 (9.5) |
119 (60.1) |
49 (24.7) |
30 (15.2) |
173 (90.1) |
19 (9.9) |
||||
|
Secondary |
659 (75.1) |
219 (24.9) |
213 (23.7) |
565 (63.0) |
119 (13.3) |
554 (61.8) |
188 (21.0) |
154 (17.2) |
763 (88.0) |
104 (12.0) |
||||
|
Technical |
172 (69.6) |
75 (30.4) |
48 (18.5) |
160 (61.8) |
51 (19.7) |
176 (68.2) |
39 (15.1) |
43 (16.7) |
219 (88.0) |
30 (12.0) |
||||
|
University or higher |
435 (74.6) |
148 (25.4) |
112 (19.0) |
345 (58.4) |
134 (22.7) |
466 (78.6) |
49 (8.3) |
78 (13.2) |
522 (89.5) |
61 (10.5) |
||||
Source: Original table for this publication.
Note:
“Never” and “don’t know” categories were removed for this analysis
“Don’t know," “did not leave home in the last two weeks,” and “no” categories were removed for this analysis.
Relationship between Independent Variables and Preventive Behaviors
The authors observed that there was a statistically significant relationship with sex and those who practiced social distancing (p < 0.001), avoided public places (p = 0.047), and used a mask or chin strap (p < 0.001). Age was found to be statistically significant for the four preventive behaviors analyzed in this study (p < 0.001). There was a statistically significant association with marital status and respondents who practiced social distancing (p < 0.001), avoided public transportation (p < 0.001), and used a mask or chin strap. Education was statistically significant for respondents who avoided public places (p < 0.001) and public transport (p < 0.001). There was no statistically significant association with locality (rural versus urban) and parish with any of the preventive behaviors, as shown in Table 2.
Use of and Trust in COVID-19 Information Sources
As shown in Table 3, the most frequently consulted sources of information were social networks 687 (34.6%), television 532 (26.8%), and radio 357 (18.0%). The most commonly trusted sources were the MOHWE 598 (30.1%), WHO 484 (24.3%), and friends and family 212 (10.7%).
TABLE 3. Trust and perception of COVID-19 information sources and impact on behavior change (n = 1 988).
|
Think official prevention messages have influenced behavior changes |
|||||
|---|---|---|---|---|---|
|
Yes |
No |
||||
|
Characteristics |
Variables |
Total number (%) |
Number (%) |
Number (%) |
p -value |
|
Sex |
0.015 |
||||
|
Male |
931 (46.8) |
689 (74.0) |
242 (26.0) |
||
|
Female |
1 057 (53.2) |
832 (78.7) |
225 (21.3) |
||
|
Age |
0.014 |
||||
|
18–29 |
516 (26.0) |
371 (71.9) |
145 (28.1) |
||
|
30–44 |
580 (29.2) |
449 (77.4) |
131 (22.6) |
||
|
45+ |
892 (44.9) |
701 (78.6) |
191 (21.4) |
||
|
Marital Status |
0.009 |
||||
|
Not married |
1 362 (69.1) |
1 020 (74.9) |
342 (25.1) |
||
|
Married |
609 (30.9) |
489 (80.3) |
120 (19.7) |
||
|
Parish |
0.870 |
||||
|
St. John |
1 014 (51.0) |
774 (76.3) |
240 (23.7) |
||
|
St. Mary |
218 (11.0) |
172 (78.9) |
46 (21.1) |
||
|
St. Paul |
225 (11.3) |
170 (75.6) |
55 (24.4) |
||
|
St. Philip |
105 (5.3) |
85 (81.0) |
20 (19.0) |
||
|
St. George |
269 (13.5) |
202 (75.1) |
67 (24.9) |
||
|
St. Peter |
127 (6.4) |
95 (74.8) |
32 (25.2) |
||
|
Barbuda |
30 (1.5) |
23 (76.7) |
7(23.3) |
||
|
Location |
0.321 |
||||
|
Rural |
1 189 (61.5) |
919 (77.3) |
270 (22.7) |
||
|
Urban |
744 (38.5) |
560 (75.3) |
184 (24.7) |
||
|
Education |
<0.001 |
||||
|
Without official schooling |
27 (1.4) |
17 (63.0) |
10 (37.0) |
||
|
Primary |
199 (10.0) |
125 (62.8) |
74 (37.2) |
||
|
Secondary |
891 (44.8) |
693 (77.8) |
198 (22.2) |
||
|
Technical |
257 (12.9) |
198 (77.0) |
59 (23.0) |
||
|
University or higher |
592 (29.8) |
474 (80.1) |
118 (19.9) |
||
|
Most trusted source that influenced behavior changes |
<0.010 |
||||
|
Community leader |
23 (1.2) |
17 (73.9) |
6 (26.1) |
||
|
Friends and family |
212 (10.7) |
143 (67.5) |
69 (32.5) |
||
|
Independent medical societies |
135 (6.8) |
97 (71.9) |
38 (28.1) |
||
|
Ministry of Health |
598 (30.1) |
515 (86.1) |
83 (13.9) |
||
|
Pan American Health Organization |
132 (6.6) |
111 (84.1) |
21 (4.5) |
||
|
World Health Organization |
484 (24.3) |
394 (81.4) |
90 (18.6) |
||
|
Religious community |
55 (2.8) |
46 (83.6) |
9 (16.4) |
||
|
Another source |
43 (2.2) |
32 (74.4) |
11 (25.6) |
||
|
None |
285 (14.3) |
148 (51.9) |
137 (48.1) |
||
|
Main media outlet used for information on how to prevent COVID |
<0.001 |
||||
|
Radio |
357 (18.0) |
280 (78.4) |
77 (21.6) |
||
|
Social networks |
687 (34.6) |
540 (78.6) |
147 (21.4) |
||
|
Television |
532 (26.8) |
443 (83.3) |
89 (16.7) |
||
|
Websites |
210 (10.6) |
151 (71.9) |
59 (28.1) |
||
|
|
87 (4.4) |
60 (69.0) |
27 (31.0) |
||
|
Other |
20 (1.0) |
11 (55.0) |
9 (45.0) |
||
|
None |
92 (4.6) |
34 (37.0) |
58 (63.0) |
||
Source: Original table for this publication.
Perceived Influence of COVID-19 Official Messaging on Behavior
Overall, the majority of respondents [1 521 (76.5%)] reported their belief that official COVID-19 preventive messages influenced their change in behavior. Of the 1 521 respondents, 832 (54.7%) were female and 689 (45.3%) were male. We observed that there was a statistically significant association of the perceived influence of COVID-19 messaging on behavior with sex (p = 0.015), with age (p = 0.014), with marital status (p = 0.009), with education (p < 0.01), with information source (p < 0.001), and most trusted source (p < 0.010). No statistically significant association was found to occur with parish and urban or rural areas (Table 3).
Predictors of Preventive Behaviors
In the regression analysis presented in Table 4, there was no statistically significant association with marital status, rural or urban locality, education level, main source of COVID-19 information, the most trusted source that influenced behavior changes, and the practicing of social distancing (always versus sometimes) when controlling for age and sex.
TABLE 4. Factors associated with COVID–19 preventive behaviors practiced always ver-sus sometimes.
|
Social distancing (always vs sometimes) |
Used a mask (always vs sometimes) |
Think official prevention messages have influenced behavior changes (yes vs no) |
|||||
|---|---|---|---|---|---|---|---|
|
Characteristics |
Variables |
Adjusted odds ratio |
Confidence interval |
Adjusted odds ratio |
Confidence interval |
Adjusted odds ratio |
Confidence interval |
|
Marital status |
|||||||
|
Married |
1.122 |
0.872–1.444 |
1.573 |
1.083–2.286 |
1.268 |
0.987–1.629 |
|
|
Not married |
Reference |
||||||
|
Location |
|||||||
|
Rural |
0.824 |
0.661–1.027 |
0.897 |
0.667–1.205 |
1.104 |
0.890–1.370 |
|
|
Urban |
Reference |
||||||
|
Education |
|||||||
|
Without official schooling |
1.371 |
0.502–3.747 |
0.344 |
0.129–0.916 |
0.408 |
0.181–0.919 |
|
|
Primary |
1.099 |
0.730–1.654 |
0.894 |
0.510–1.570 |
0.379 |
0.263–0.545 |
|
|
Secondary |
1.082 |
0.845–1.385 |
0.923 |
0.656–1.299 |
0.897 |
0.693–1.162 |
|
|
Technical |
0.890 |
0.635–1.248 |
1.037 |
0.645–1.669 |
0.906 |
0.634–1.296 |
|
|
University or higher |
Reference |
||||||
|
Most trusted source that influenced behavior changes |
|||||||
|
Community leader |
0.741 |
0.292–1.883 |
1.115 |
0.248–5.008 |
0.484 |
0.185–1.267 |
|
|
Friends and family |
0.744 |
0.521–1.063 |
0.744 |
0.521–1.063 |
0.353 |
0.244–0.513 |
|
|
Independent medical societies |
0.989 |
0.631–1.552 |
0.512 |
0.317–0.826 |
0.419 |
0.269–0.653 |
|
|
Pan American Health Organization |
0.771 |
0.497–1.197 |
0.602 |
0.327–1.110 |
0.846 |
0.502–1.426 |
|
|
World Health Organization |
0.946 |
0.709–1.263 |
0.919 |
0.595–1.419 |
0.729 |
0.526–1.012 |
|
|
Religious community |
1.217 |
0.605–2.450 |
0.642 |
0.271–1.520 |
0.841 |
0.396–1.784 |
|
|
Another source |
1.144 |
0.511–2.561 |
1.662 |
0.386–7.159 |
0.455 |
0.220–0.940 |
|
|
None |
0.844 |
0.602–1.182 |
0.411 |
0.267–0.634 |
0.180 |
0.129–0.250 |
|
|
Ministry of Health |
Reference |
||||||
|
Main media outlet used for information on how to prevent COVID |
|||||||
|
Radio |
1.294 |
0.932–1.796 |
1.152 |
0.740–1.796 |
0.900 |
0.647–1.251 |
|
|
Television |
1.238 |
0.932–1.645 |
1.727 |
1.126–2.648 |
1.226 |
0.903–1.665 |
|
|
Websites |
1.042 |
0.730–1.488 |
0.810 |
0.519–1.264 |
0.672 |
0.472–0.959 |
|
|
|
0.840 |
0.514–1.373 |
0.982 |
0.508–1.899 |
0.601 |
0.367–0.983 |
|
|
Other |
2.523 |
0.569–11.193 |
2.274 |
0.297–17.424 |
0.287 |
0.115–0.713 |
|
|
None |
0.976 |
0.581–1.641 |
0.520 |
0.291–0.928 |
0.151 |
0.095–0.241 |
|
|
Social networks |
Reference |
||||||
Source: Original table for this publication.
Note: Each model was adjusted for age and sex only.
With respect to the use of a mask (always versus sometimes) to prevent COVID-19 infection, married individuals had increased odds of always using a mask [aOR 1.573; 95% confidence interval (CI) 1.083–2.286] compared to unmarried persons. Respondents who used television as their primary source for information to prevent COVID-19 infection were more likely to always wear a mask (aOR 1.727; 95% CI 1.126–2.648). Individuals who reported no main primary source of information to prevent COVID-19 infection (aOR 0.520; 95% CI 0.291–0.928) and independent medical societies as their most trusted source of COVID-19 information (aOR 0.512; 95% CI 0.317–0.826) were less likely to wear a mask.
In terms of thinking that official prevention messages did not influence behavior changes, individuals without official schooling (aOR 0.408; 95% CI 0.181–0.919); with only primary schooling (aOR 0.379; 95% CI 0.263–0.545); and respondents who used websites as their information sources (aOR 0.672; 95% CI 0.472–0.959), WhatsApp (aOR 0.601; 95% CI 0.367–0.983), other information sources (aOR 0.287; 95% CI 0.115–0.713), no information sources (aOR 0.151; 95% CI 0.095–0.244), trusted information from friends and family (aOR 0.353; 95% CI 0.244–0.513), trusted independent medical societies (aOR 0.419; 95% CI 0.269–0.653), and trusted other sources (aOR 0.455; 95% CI 0.220–0.940) were all less likely to think that official prevention messages influenced behavior changes.
With respect to preventive behaviors practiced always versus never and sometimes versus never as presented in Table 5, persons who avoided public spaces always versus never were more likely to have secondary school education (aOR 1.773; 95% CI 1.121–2.803). Persons who avoided public spaces sometimes versus never were more likely to have secondary school education (aOR 1.466; 95% CI 1.008–2.133), and viewed friends and family (aOR 1.776; 95% CI 1.087–2.904) and the WHO (aOR 4.469; 95% CI 1.005–2.149) as their most trusted information source.
TABLE 5. Factors associated with COVID–19 preventive behaviors practiced always ver-sus never and sometimes versus never.
|
Avoided public spaces |
Avoided public transport |
||||
|---|---|---|---|---|---|
|
Always vs Never |
Sometimes vs Never |
Always vs Never |
Sometimes vs Never |
||
|
Characteristics |
Variables |
Adjusted odds ratio (confidence interval) |
Adjusted odds ratio (confidence interval) |
Adjusted odds ratio (confidence interval) |
Adjusted odds ratio (confidence interval) |
|
Marital status |
|||||
|
Not married |
1.202 (0.859–1.681) |
1.063 (0.796–1.418) |
0.628 (0.463–0.851) |
1.129 (0.761–1.674) |
|
|
Married |
Reference |
||||
|
Location |
|||||
|
Urban |
0.749 (0.556–1.011) |
0.820 (0.639–1.053) |
0.820 (0.636–1.056) |
0.681 (0.494–0.940) |
|
|
Rural |
Reference |
||||
|
Education |
|||||
|
University+ |
0.790 (0.492–1.270) |
0.778 (0.533–1.135) |
1.360 (0.898–2.062) |
0.701 (0.398–1.234) |
|
|
Without official schooling |
0.772 (0.239–2.497) |
0.582 (0.220–1.535) |
0.463 (0.167–1.287) |
1.391 (0.427–4.538) |
|
|
Primary |
2.548 (1.310–4.955) |
1.668 (0.924–3.012) |
0.767 (0.448–1.313) |
1.913 (0.999–3.665) |
|
|
Secondary |
1.773 (1.121–2.803) |
1.466 (1.008–2.133) |
0.814 (0.556–1.194) |
1.378 (0.848–2.241) |
|
|
Technical |
Reference |
||||
|
Most trusted source that influenced behavior changes |
|||||
|
Community leader |
1.164 (0.247–5.482) |
2.131 (0.596–7.612) |
1.733 (0.377–7.972) |
4.791 (0.964–23.819) |
|
|
Friends and family |
1.720 (0.981–3.016) |
1.776 (1.087–2.904) |
0.883 (0.546–1.425) |
1.570 (0.871–2.829) |
|
|
Independent medical societies |
0.875 (0.456–1.678) |
1.362 (0.801–2.315) |
1.329 (0.749–2.356) |
0.736 (0.323–1.679) |
|
|
Ministry of Health |
1.408 (0.906–2.190) |
1.837 (1.255–2.689) |
1.110 (0.753–1.637) |
1.501 (0.914–2.466) |
|
|
Pan American Health Organization |
0.949 (0.491–1.834) |
1.398 (0.806–2.425) |
1.727 (0.922–3.235) |
1.204 (0.527–2.749) |
|
|
World Health Organization |
0.950 (0.603–1.497) |
1.469 (1.005–2.149) |
1.169 (0.785–1.741) |
1.124 (0.668–1.891) |
|
|
Religious community |
1.340 (0.486–3.696) |
2.244 (0.950–5.298) |
0.774 (0.353–1.693) |
2.051 (0.849–4.957) |
|
|
Another source |
0.916 (0.360–2.330) |
0.857 (0.379–1.936) |
0.695 (0.306–1.578) |
0.968 (0.331–2.834) |
|
|
None |
Reference |
||||
|
Main media outlet used for information on how to prevent COVID |
|||||
|
Radio |
0.575 (0.114–2.901) |
0.776 (0.167–3.595) |
2.119 (0.767–5.582) |
3.535 (0.683–18.283) |
|
|
Social networks |
0.460 (0.092–2.288) |
0.689 (0.151–3.147) |
2.107 (0.775–5.732) |
3.112 (0.610–15.877) |
|
|
Television |
0.537 (0.107–2.679) |
0.862 (0.188–3.956) |
2.358 (0.865–6.424) |
3.602 (0.705–18.394) |
|
|
Websites |
0.310 (0.060–1.599) |
0.537 (0.115–2.511) |
3.137 (1.088–9.045) |
2.481 (0.452–13.613) |
|
|
|
0.385 (0.068–2.175) |
0.702 (0.141–3.494) |
1.697 (0.544–5.294) |
5.449 (0.969–30.630) |
|
|
None |
0.427 (0.080–2.280) |
0.330 (0.067–1.610) |
1.581 (0.527–4.741) |
1.837 (0.317–10.647) |
|
|
Other |
Reference |
||||
Source: Original table for this publication.
Note: Each model was adjusted for age and sex only.
DISCUSSION
To the authors’ knowledge, this study is the first national cross-sectional survey to assess information sources and preventive behaviors of adults during the COVID-19 pandemic in Antigua and Barbuda. Our findings showed that there was a high number of self-reported COVID-19 preventive behaviors among study participants. Multiple sociodemographic factors, such as sex, age, marital status, and education level, increased the likelihood of engaging in COVID-19 preventive behaviors. Consistent with other findings, women were more likely to comply with preventive behaviors (17, 18). This could be likely due to women engaging in caregiving tasks and thus feeling more responsible for themselves and their families. Additionally, as women tend to be more prone to anxiety, they may be more likely to adhere to preventive behaviors to prevent illness and death.
Uptake of preventive actions by study participants was associated with increased age (19). This may be explained by the weakening of overall health as individuals age, reducing the likelihood of naturally defending oneself against infection and disease. Additionally, as comorbid conditions increase with age, older individuals may have been more likely to adopt preventive behaviors as comorbidities were associated with more severe disease outcomes (20). Married persons were more likely to observe preventive behaviors given their nature to be protective of those around them (21). Persons with higher educational attainment were more likely to live in healthy neighborhoods, maintain healthy behaviors such as practice social distancing, and access more affordable health care (22).
Main media sources for information about COVID-19 utilized by study participants included social media, television, radio, and websites. While knowledge about the specific social media platforms utilized by participants could have provided important information about its role in promoting preventive behavior, this was not assessed within this study. However, further investigation in this area could prove useful in guiding the MOHWE in its development and dissemination of preventive and promotional health messaging in future.
Our study found that participants were the most trusting of messages from the MOHWE, followed by messages from WHO and friends and family, respectively. The annual threat of being impacted by hurricanes has influenced life in much of the Caribbean. Caribbean governments have regularly implemented stay-at-home orders, states of emergency, and curfews (mainly during hours of darkness), in preparation for tropical storms making landfall and during their on-shore impact. This norm, of a country’s government serving as the authority during crisis events, and restricting movement of the public, has likely contributed to the willingness of persons to accept and comply with the stringent mobility restrictions implemented by the Antigua and Barbuda government in response to the COVID-19 pandemic (23). The vulnerability of SIDS to extreme shocks necessitates timely decision-making and evidence-based political leadership to minimize impact in response to public health crises. It is likely that repeated experiences with infectious disease outbreaks (e.g., dengue), in addition to natural disasters, has created an environment in which the governmental authority takes swift action to protect the country’s fragile health system, and a general public that adheres to the government’s directive.
In this study, the majority of persons reported that they always and sometimes practiced social distancing, avoided public spaces and public transport, and wore a face mask or chin strap. Of note, our study was conducted from September to November 2021, 20 months after the first reported COVID-19 case, and approximately 7 months following the availability of vaccines compared to other countries, with similar studies. Therefore, persons may have been more likely to comply with COVID-19 protocols around the management of the spread of the virus as government directives had been in existence for several months and the public may have become accustomed to practicing social distancing, wearing masks in public, and engaging in other preventive behaviors.
Previous research has highlighted that trust in information sources is a predictor of preventive behavior (24). We also found a statistically significant association between trust in COVID-19 information and its perceived influence on preventive behavior. We found no association with marital status, rural or urban locality, education level, main source of COVID-19 information, the most trusted source that influenced behavior changes, and the practice of social distancing (always versus sometimes). The chief medical officer was the lead spokesperson for the provision of information about COVID-19 and its spread and prevention to the general public. Hearing directly from the country’s top public health professional may have likely also contributed to adherence to prevention behaviors. This high level of trust in the MOHWE is indicative of the Antigua and Barbuda government’s recognition of their public health leaders as experts when faced with public health crises. By taking guidance from the top health lead in the MOHWE, the government likely established the tone for the wider society through its display of leadership and respect to its local public health professionals.
Our study is not without limitations. First, the representativeness of the study may have been affected by sampling bias as only persons who had access to a mobile phone were eligible to participate in the study. Second, as our study relied on self-reported behavior, the results may be vulnerable to social desirability bias. To counter this, multiple interviewers were trained to capture data via telephone interviews so as to create a relaxed atmosphere for participants to speak freely. Third, our study was conducted from September 22 to November 29, 2021, when there was much more abundant scientific information about COVID-19 and its prevention compared to earlier periods at the start of the COVID-19 pandemic. Fourth, as this was a cross-sectional study, it restricts the making of causal inferences. The results of this survey, however, are valuable as it was conducted in the midst of a pandemic and under a state of emergency when preventive action was critical for slowing the spread of the SARS-CoV-2 virus given the limited availability of vaccines.
CONCLUSION
From our study, multiple sociodemographic factors, such as sex, age, marital status, and education level, increased the likelihood of persons engaging in COVID-19 preventive actions in Antigua and Barbuda. The majority of study participants reported that they always and sometimes practiced social distancing, avoided public spaces and public transport, and wore a face mask or chin strap in keeping with government protocols to manage spread of the SARS-CoV-2 virus. We observed that although social media was the main source for information about COVID-19 utilized by study participants, participants were the most trusting of messages from the MOHWE. We found no association with marital status, rural or urban locality, education level, main source of COVID-19 information, the most trusted source that influenced behavior changes, and the practice of social distancing (always versus sometimes). In summary, these findings provide evidence that the public regards the MOHWE as a trusted source for information on public health crises and that there is an opportunity to utilize tailored messaging for general preventive and health promotion efforts.
Acknowledgments.
Special thanks to Roberta Caixeta, Advisor, Noncommunicable Diseases, Surveillance, Prevention and Control; Dolores Ondarsuhu, Technical Officer, Population-based Surveys for Noncommunicable Diseases, Surveillance and Prevention and Control, of the Pan American Health Organization (PAHO); and Christa Roberts, former Epidemiology Manager, Ministry of Health, Wellness and the Environment, Antigua and Barbuda, for their leadership with the Rapid Mobile Phone Survey (RaMPS) project. We are grateful to Patrice Lawrence-Williams, Advisor, Noncommunicable Diseases and Mental Health, Jamaica, Cayman Islands, and Bermuda for technical guidance, and for the random digit dialing support provided by the Research Triangle Institute (RTI International). RaMPS was supported through the PAHO-CDC Cooperative Agreement on Non-Communicable Diseases and Health Promotion signed between PAHO and the United States Centers for Disease Control and Prevention (CDC).
Funding Statement
This study was supported by funding from the Public Health Agency of Canada (PHAC): Assessing and Strengthening Non-Communicable Disease Risk Factors Surveillance in Eastern Caribbean Countries (435011). The funders reviewed and approved the survey instrument utilized in the study.
Footnotes
Financial support.
This study was supported by funding from the Public Health Agency of Canada (PHAC): Assessing and Strengthening Non-Communicable Disease Risk Factors Surveillance in Eastern Caribbean Countries (435011). The funders reviewed and approved the survey instrument utilized in the study.
Data availability.
The data supporting the findings of this study are available from the Ministry of Health, Wellness and the Environment at contact@health.gov.ag upon reasonable request.
Declaration of artificial intelligence (AI) use.
No artificial intelligence (AI) tools were used in the creation, writing, or editing of the manuscript.
Disclaimer.
Authors hold sole responsibility for the views expressed in the manuscript, which may not necessarily reflect the opinion or policy of the RPSP/PAJPH and/or PAHO.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data supporting the findings of this study are available from the Ministry of Health, Wellness and the Environment at contact@health.gov.ag upon reasonable request.