Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B model

Charuai Suwanbamrung; Benchawan Srinam; Pakawan Promkool; Warissara Suwannakarn; Sangchom Siripanich; Md Siddikur Rahman; Muhammad Haroon Stanikzai

doi:10.1371/journal.pone.0300509

. 2024 Mar 14;19(3):e0300509. doi: 10.1371/journal.pone.0300509

Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B model

Charuai Suwanbamrung ^1,², Benchawan Srinam ², Pakawan Promkool ², Warissara Suwannakarn ², Sangchom Siripanich ^1,², Md Siddikur Rahman ³, Muhammad Haroon Stanikzai ^4,^*

Editor: Pei Boon Ooi⁵

PMCID: PMC10939195 PMID: 38483878

Abstract

Background

The COVID-19 pandemic has imposed unprecedented suffering on social and individual levels worldwide. Vaccines against COVID-19 have been prioritized as a crucial strategy for ending the pandemic as well as minimizing its consequences.

Objectives

This study aimed to determine the uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the Capability, Opportunity, Motivation, and Behavior (COM-B) model.

Methods

We conducted a web-based cross-sectional study in the Hat Yai district, Songkhla province in Southern Thailand, in September and October 2021. The questionnaire was composed of sections on sociodemographic characteristics, COVID-19 vaccination status, and COM-B constructs. We employed a multivariable logistic regression analysis to determine factors associated with the uptake of the COVID-19 vaccine. We set statistical significance at p < 0.05.

Results

In this study, females constituted 54.7% of the total participants (n = 358), and nearly half of the participants (45.8%) were in the younger age group (18–29). Of all the participants, 59.5% (95%CI: 54.2%-64.6%) received at least one dose of the COVID-19 vaccine. Factors associated with the uptake of COVID-19 vaccine and their adjusted OR (95% CI) were being married: 3.59 (2.06–6.24), having a graduate degree: 2.34 (1.38–3.96), gainfully employed: 3.30 (1.91–5.67), having a high level of opportunity: 2.90 (1.48–5.66), and having a high level of motivation: 2.87 (1.17–17.08).

Conclusion

The uptake of COVID-19 vaccines was moderate in this population. Moreover, the results showed that the COM-B model is useful in predicting COVID-19 vaccine uptake. The findings of this study could be used to aid future public health interventions in any event of outbreaks similar to COVID-19 disease in Thailand and beyond.

Introduction

Over the past three years, the COVID-19 pandemic has resulted in a growing burden of biopsychosocial problems in developing and developed countries [1, 2]. On an individual level, the disaster has resulted in an overwhelming number of bio-psycho-social deficits in the general population that impacted the physical, psychological, and social aspects of their health and well-being [3, 4]. In response to this largest health crisis of our time, the development and deployment of effective vaccines has been prioritized as a crucial strategy to contain the spread of the virus and reduce its impact on public health [5, 6].

Following the catastrophic first wave of the COVID-19 pandemic, multi-national pharmaceutical industries made vaccines available sporadically during the second wave and in large amounts after the second wave [6]. The administration of COVID-19 vaccines has dramatically shifted the nature of the disease, leading to a marked reduction in the number of cases and deaths [7, 8]. Immediately following the successful development of multiple effective and safe COVID-19 vaccines, the World Health Organization (WHO) urged all countries to vaccinate at least 70% of their populations by mid-2022, with priority given to vaccinating health workers and the most vulnerable groups (e.g., individuals over 60 years of age, those with compromised immune system, and those with pre-existing medical conditions) [9].

However, the proportion of people vaccinated against COVID-19 reflects significant global disparities. Moreover, vaccination rates are suboptimal, particularly in the developing countries. Data assert that approximately 70.3% of the world’s population has received at least one dose of the COVID-19 vaccine [10]. In developing countries, however, this proportion is only 32.3% [11]. In Thailand, vaccination escalated rapidly, where about 82.5% of the population has received at least their first dose of the COVID-19 vaccine as of June 2023 [11], with notably lower coverage in remote areas [12].

Although vaccination remains a cornerstone of the COVID-19 pandemic response, broad public support remains elusive. For instance, a recent global systematic review found that the global pooled acceptance rate of the COVID-19 vaccine was 64.9%, with significant variations across WHO regions (range; 60.8%-81.6%) [13]. Other relevant studies have also found that the acceptance rate of the COVID-19 vaccine varies substantially from country to country and even from region to region within a country [14, 15]. In Thailand, the acceptance rates of the COVID-19 vaccine reported ranged from 58% to 95.6% [12, 13, 16]. However, the above studies were mainly among vulnerable populations and emanated from regions other than the South.

Consistent findings of extensive research indicate that the decision to vaccinate against COVID-19 is influenced by diverse factors, including sociodemographic characteristics, sociocultural and religious considerations, political perspectives, trust in healthcare professionals and current vaccines, the availability and accessibility of vaccination services, and fear of COVID-19 [12, 14, 17–19]. Studies from Thailand reported a strong association of sociodemographics and health system influencers with the COVID-19 vaccination decision [12, 15].

There is a growing recognition that theory-based behavioral models can effectively predict COVID-19 preventive behaviors [20, 21]. The capability, opportunity, motivation, and behavior (COM-B) model is recognized as an efficacious framework for preventing COVID-19 disease and acts as a practical framework for designing and promoting preventive behaviors [21, 22]. The results of several studies indicate that the application of this model is successful in COVID-19 prevention [23, 24]. There is little knowledge in the study area of the COM-B model, predicting the uptake of COVID-19 vaccines.

This study conducted in 2021 captured a period when the uptake of COVID-19 vaccines was suboptimal worldwide. However, at the time of writing this paper, the situation for COVID-19 vaccine acceptance has improved significantly. Recognizing the challenges encountered at the initial stages of COVID-19 vaccine acceptance, it becomes even more critical to identify gaps in the adoption of healthy behavior to devise effective interventions and implementation approaches. As an example, the COM-B model in COVID-19 vaccine uptake can provide implicit insights from behavior change models as a potential solution to any event of outbreaks similar to COVID-19 disease in Thailand and beyond.

Materials and methods

Study settings and design

A web-based cross-sectional study was conducted in the Hat Yai district, an urban area of Songkhla Province in Southern Thailand, in September and October 2021. The district is divided into sixteen administrative units or sub-districts and is lodging approximately 286,274 people [25]. We selected the Hat Yai district for the present study due to its designation as one of the areas significantly affected by the COVID-19 pandemic. Moreover, this district, characterized by certain demographics, cultural factors, or socioeconomic conditions could provide broader implications for public health policies and interventions in other developing regions of the world.

Study population

We recruited a total of 358 participants who were currently active members of the Facebook group HATY AIZ (a social media platform dedicated to community engagement and connection) to participate in an anonymous survey using the online Google survey forms via Facebook Messenger. Our participants mainly lived in cities, were young, spoke Thai, and were willing to participate in this study.

Sample size and sampling procedures

The estimated sample size was 325, obtained by a sample size calculation from the Facebook group HATY AIZ records, which documented the number of active adult members (800 members; July–August 2021) with a 95% confidence level, a 5% margin of error, a design effect of 1.5, and a 10% nonresponse rate. We increased the calculated sample size from a minimum of 325 participants to 379 participants in the prevision of missing data. The final analyses consist of 358 participants with their complete data sets. We used convenience sampling (voluntary participation) to recruit our participants in this study.

Study measures

Based on relevant literature, we developed a structured questionnaire with sections on sociodemographic information, COM-B constructs, and participants’ intentions to get vaccinated against COVID-19.

In this study, we used six sociodemographic characteristics as independent variables: sex (male/female); age (18–29, 30–44, 45–59, >60); marital status (currently married, currently unmarried); education (undergraduate, graduate or higher); occupation (occupation with uncertain income, occupation with regular income); and income in Baht (≤ 26000, > 26000).

We employed the comprehensive theoretical model grounded in the COM-B model to understand the factors influencing the individuals’ behavior toward receiving the COVID-19 vaccination [20, 21]. The adapted COM-B model has three constructs: (1) capability, (2) opportunity, and (3) motivation with good psychometric properties for facilitating behavioral change.

The capability and opportunity constructs were measured using 12-item scales: capability (two negatives and ten positives) and opportunity (three negatives and nine positives). Each item was scored from 0 (unfavorable response) to 1 (favorable response), which yields a total score from 0 to 12. In each scale, a score of ≥ 10 was used to signify a high level of capability and opportunity for receiving the COVID-19 vaccination, as defined in prior work [20, 26].

We employed a 5-point Likert scale to measure the motivation construct. The motivation construct consists of 12 items, including 6-item positive and 6-item negative subscales. Each item in the positive constructs was scored from 5 (strongly agree) to 0 (strongly disagree) and vice versa in the negative constructs, yielding a total score from 12 to 60. A score of ≥ 48 was used to signify a high level of motivation for receiving the COVID-19 vaccination [26, 27].

The outcome variable of this study was the respondents’ behavior regarding the uptake of the COVID-19 vaccine. The participants in this survey were asked about their COVID-19 vaccination status and the responses were in a dichotomous ‘yes’ or ‘no’ format.

Data collection

The questionnaire, which consisted of sections on socio-demographic information, COVID-19 vaccine-related information, and the COM-B model, was initially drafted in English and later translated into Thai (local language) for the ease of administration. Before the commencement of the study, we pretested the questionnaire in another Facebook group with 65 participants to check and revise (if required) its verbal consistency. Additionally, we checked the structure reliability of the questionnaire in the pretested sample, and the Cronbach’s Alpha value (Thai version) for capability, opportunity, motivation, and total was 0.86, 0.77, 0.82, and 0.83, respectively.

We distributed the Thai version of the questionnaire through the HATY AIZ Facebook group and were available for responses from September 10, 2021, to October 31, 2021. Once a potential client accessed the online survey form, a consent form appeared on the first page indicating the study description, objectives, and participants’ right to withdraw at any time. If the client would like to participate, they could willfully provide their consent and choose their desired language of the form. Only then did the clients complete and submit the anonymous survey questionnaire.

Statistical analysis

We employed descriptive statistics to understand participants’ capability, opportunity, and motivation to adopt the new behavior, i.e., acceptance of the COVID-19 vaccine. We employed multivariable logistic regression analysis to determine factors associated with the uptake of the COVID-19 vaccine. In all analyses, the assumptions for the multivariable logistic regression model were met. We set statistical significance at p < 0.05.

Ethical consideration

The Ethics Committee for Human Research, Walailak University approved this study (ref. no. WUEC-21-214-01; Dated: August 16, 2021). All participants agreed to the terms of an electronic consent form before they could participate in the study. The electronic consent form included information on study description, objectives, and participants’ right to withdraw at any time. Moreover, we followed the ethical principles outlined in the Declaration of Helsinki.

Results

Table 1 indicates the sociodemographic characteristics of our study participants. A total of 358 Facebook users from the HATY AIZ group aged 18–60 years were included in this study. In our sample, 54.7% (196) were female, and nearly half of the participants (45.8%, 164) were young (18–29). Approximately one-third (42.7%, 153) of our participants were married, and more than two-thirds (64.5%, 231) were gainfully employed. The monthly household income was ≤ 26000 Baht (750 USD, July 2023) in more than half of the participants (55%, 197). Data on participants’ educational attainment and travel history are summarized in Table 1.

Table 1. Sociodemographic characteristics of the study participants (n = 358).

Variables	Frequency (%)
Age (In completed years)
18–29	164 (45.8)
30–44	104 (29.1)
45–59	80 (22.3)
≥ 60	10 (2.8)
Sex
Male	162 (45.3)
Female	196 (54.7)
Marital status
Single	192 (53.6)
Married	153 (42.7)
Separated/Divorced	13 (3.6)
Educational status
Secondary school (level 1–3)	9 (2.5)
Secondary school (level 4–6)	41 (11.4)
Vocational Certificate/Diploma	72 (20.1)
Bachelor degree	220 (61.5)
Higher education	16 (4.5)
Employment status
Employed with regular income	231 (64.5)
Employed with uncertain income	127 (35.5)
Monthly household income (in Baht)
≤ 26000	197 (55.0)
> 26000	161 (45.0)
History of travel to/or from another province in the last 14 days
Yes	35 (9.8)
No	323 (90.2)
History of exposure to COVID-19 patients in the last 14 days
Yes	29 (8.1)
No	329 (91.9)

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Capability to receive COVID-19 vaccine

The mean score of the capability construct was 10.80 (± 1.35 SD) with a range of 3–12 points, and nearly two-thirds (249; 69.6%) of participants showed a high level of capability. Table 2 illustrates the detailed reflections of our participants on the capability construct within the COM-B model.

Table 2. Capability to receive COVID-19 vaccine (n = 358).

Items	Reponses, Frequency (%)
Items	Yes	No
Knowledge of the spread of COVID-19 disease	351 (98)	7 (2)
Knowledge of the signs and symptoms associated with COVID-19 disease	347 (96.9)	11 (3.1)
COVID-19 vaccine can boost immunity	329 (91.9)	29 (8.1)
Knowledge of the vaccine doses and schedule	264 (73.7)	94 (26.3)
It is necessary to get enough sleep and refrain from consuming alcohol, tea, and coffee before vaccination	344 (96.1)	14 (3.9)
Individuals can go home without any surveillance and are not required to wait for 30 minutes to observe any symptoms post vaccination^*	75 (20.9)	283 (79.1)
Knowledge of factors that increase the risk for severe COVID-19	344 (96.1)	14 (3.9)
COVID-19 can be transmitted easily within families when a family member has signs and symptoms of COVID-19 disease	346 (96.6)	12 (3.4)
COVID-19 doesn’t affect individuals’ daily activities^*	82 (22.9)	276 (77.1)
COVID-19 results in unemployment and income loss	346 (96.6)	12 (3.4)
Vaccination can be reserved online or through public channels	335 (93.6)	23 (6.4)
Decisions to receive the vaccine can be affected by its adverse effects	302 (84.4)	56 (15.6)
	High	Low
Level of capability (cut-off point 90%)	249 (69.6)	109 (30.4)

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* Negative capability

Opportunity to receive COVID-19 vaccine

The mean score of the opportunity construct was 10.04 (± 1.72 SD) with a range of 2–12 points, and about 41.9% (150) of participants had a high level of opportunity to receive the COVID-19 vaccine. The detailed opportunity construct and participants’ reflections are illustrated in Table 3.

Table 3. Opportunity to receive COVID-19 vaccine (n = 358).

Items	Reponses, Frequency (%)
Items	Yes	No
You are supported by family and friends to receive the vaccine	324 (90.4)	34 (9.5)
You are informed to register for the vaccine	303 (84.6)	55 (15.4)
You live in a high-risk area for the COVID pandemic	313 (87.4)	45 (12.6)
You think that shopping malls and companies are sources of COVID-19 infection	326 (91.1)	32 (8.9)
You need a vaccine due to the disease‘s impact on your employment^*	320 (89.4)	38 (10.6)
You need the government to provide vaccines for all citizens	333 (93.0)	25 (7.0)
You ask for a vaccine that fulfills all your needs^*	228 (63.7)	130 (36.3)
Vaccine is available near your residence	293 (81.8)	65 (18.2)
The risk of infection is not increased if individuals are not vaccinated^*	155 (43.7)	203 (56.7)
Adherence to social distancing measures lowers your risk of the COVID-19 disease	316 (88.3)	42 (11.7)
You can select the type of vaccine	238 (66.5)	120 (33.5)
You can travel to receive vaccine	342 (95.5)	16 (4.5)
	High	Low
Level of opportunity (cut-off point 90%)	150 (41.9)	208 (58.1)

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* Negative opportunity

Motivation to receive COVID-19 vaccine

The mean score of the motivation construct was 41.18 (± 8.81 SD) with a range of 24–60 points, and a small number of the participants (12%, 43) had a high level of motivation to receive the COVID-19 vaccine. The detailed motivation construct and participants’ reflections are illustrated in Table 4.

Table 4. Motivation to receive COVID-19 vaccine (n = 358).

Items	Responses, Frequency (%)
Items	Strongly agree	Agree	Neutral	Disagree	Strongly disagree
You have fears about the spread of COVID-19 infection^*	102 (28.5)	45 (12.6)	58 (16.2)	57 (17.9)	96 (26.8)
You are worried that you might be infected with COVID-19 in the future^*	133 (37.2)	44 (12.3)	75 (20.9)	51 (14.2)	55 (15.4)
COVID-19 vaccines have side effects^*	1 (0.3)	6 (1.7)	48 (13.4)	79 (22.1)	224 (62.6)
You are afraid of the COVID-19 vaccine side effects^*	118 (33.0)	35 (9.8)	77 (21.5)	55 (15.4)	73 (20.4)
COVID-19 vaccines are necessary for the control of the pandemic	281 (78.5)	51 (14.2)	24 (6.7)	0 (0.0)	2 (0.6)
COVID-19 vaccines prevent infection rather than severity^*	78 (21.8)	38 (10.6)	67 (18.7)	52 (14.5)	123 (34.4)
Individuals receive vaccines to avoid the COVID-19 infection	163 (45.5)	44 (12.3)	47 (13.1)	42 (11.7)	62 (17.3)
Most individuals receive vaccines only to maintain their rights^*	106 (29.6)	40 (11.2)	71 (19.8)	48 (13.4)	93 (26.0)
Have trust in COVID-19 vaccines provided by the government	66 (18.4)	62 (17.3)	74 (20.7)	36 (10.1)	120 (33.5)
Have trust in COVID-19 vaccines as they are registered by FDA	100 (27.9)	74 (20.7)	78 (21.8)	30 (8.4)	76 (21.2)
Information about COVID-19 vaccines affects the decision to receive the vaccine	243 (67.9)	66 (18.4)	44 (12.3)	2 (0.6)	3 (0.8)
You trust healthcare professionals‘ advice to receive the COVID-19 vaccine	236 (65.9)	68 (19.0)	36 (10.1)	4 (1.1)	14 (3.9)
				High	Low
Level of motivation (cut-off point 90%)				43 (12.0)	315 (88.0)

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* Negative motivation

At the time of this study, around two-thirds (59.5%, 95%CI: 54.2%-64.6%) of study participants had received at least one dose of the COVID-19 vaccine.

Factors associated with the uptake of COVID-19 vaccine in our sample

A multivariable logistic regression analysis indicated that being married (AOR = 3.59, 95%CI: 2.06–6.24), having a graduate degree (AOR = 2.34, 95%CI: 1.38–3.96), employed with a regular income (AOR = 3.30, 95%CI: 1.91–5.67), having a high level of opportunity (AOR = 2.90, 95%CI: 1.48–5.66), and having a high level of motivation (AOR = 2.87, 95%CI: 1.17–17.08) were associated with uptake of the COVID-19 vaccine (Table 5).

Table 5. Factors associated with the uptake of COVID-19 vaccine; crude and adjusted odds ratio with 95% CI.

Independent Variables	Categories	Vaccination status		Crude Odds Ratio (95% CI)	p-value	Adjusted Odds Ratio (95% CI)	p-value
Independent Variables	Categories	Yes	No	Crude Odds Ratio (95% CI)	p-value	Adjusted Odds Ratio (95% CI)	p-value
Age	18–44	147	121	1	0.01	-	-
Age	≥45	66	24	2.26 (1.33–3.82)	0.01	-	-
Sex	Male	99	63	1.05 (0.87–1.27)	0.20	-	-
Sex	Female	114	82	1	0.20	-	-
Marital status	Currently married	115	38	3.30 (2.09–5.22)	0.03	3.59 (2.06–6.24)	0.02
Marital status	Currently unmarried	98	107	1	0.03	1	0.02
Education status	Undergraduate	61	61	1	0.01	1	0.03
Education status	Graduate	152	84	1.81 (1.16–2.82)		2.34 (1.38–3.96)	0.03
Employment status	Uncertain income	114	117	1	<0.001	1	<0.001
Employment status	Regular income	99	28	3.62 (2.21–5.93)	<0.001	3.30 (1.91–5.67)	<0.001
Level of capability	Low	190	125	1	0.21	-	-
Level of capability	High	23	20	0.75 (0.39–1.43)	0.21	-	-
Level of opportunity	Low	167	125	1	<0.001	1	<0.001
Level of opportunity	High	46	20	1.72 (0.97–3.05)	<0.001	2.90 (1.48–5.66)	<0.001
Level of motivation	Low	177	138	1	<0.001	1	<0.001
Level of motivation	High	36	7	4.01 (1.73–9.28)	<0.001	2.87 (1.17–7.08)	<0.001

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Discussion

This study discovered the association between the COM-B constructs and COVID-19 vaccination behaviors. To the best of our knowledge, few documents have been published about the COVID-19 vaccine uptake via the COM-B model constructs. The study is important, as often time is not taken to understand how theory-based behavioral change models influence people’s behavior toward COVID-19 vaccinations and what are the needs for effective immunization programs from a population perspective. This is informative as the population’s behaviors toward an effective immunization program may differ from region to region, with significant implications for policymaking and restructuring immunization services.

In this study, we found that 59.5% of our study participants had received at least one dose of the COVID-19 vaccine. The results of previous studies demonstrated that the uptake of the COVID-19 vaccine in the Thai population ranged from 58% to 95.6% [12, 13, 16]. Also, national statistics reported that the uptake of the COVID-19 vaccine in the general population of Thailand was 82.5% [11]. Therefore, the COVID-19 vaccination rate in this study is lower than that recorded in most previous studies and national statistics. This difference may be attributed to a small sample size for the population sourced in this study. The possibility of differences in sociodemographics, study design, and geographic locations cannot be excluded. The acceptance and uptake of vaccines are affected by multiple factors including geographic location, time, sociodemographics, politics, culture, and vaccine type [13, 28]. Hence, we recommend further studies involving larger and geographically diverse populations to verify these findings.

Our study showed that the education level of the participants was significantly associated with the uptake of the COVID-19 vaccine. This finding is similar to earlier pertinent literature that pointed out that higher educational attainment is strongly associated with the acceptance and uptake of the COVID-19 vaccine [13, 28, 29]. Surprisingly, a similar study in Iran found an inverse relationship, which is contrary to our findings [30]. The decrease in acceptance of the COVID-19 vaccine among educated Iranians may coincide with the initiation of vaccination in Iran before the findings of large clinical trials were announced. However, studies have shown that higher education levels may have a significant effect on immunization coverage [13, 28]. Given the findings of this study, providing credible information through various mediums coupled with the enhancement of health literacy through educational interventions and community messages could be useful in adopting a new health behavior, particularly for those with lower educational attainment. Moreover, these interventions could also be effective in addressing any remaining COVID-19 vaccine hesitancy in the community.

Consistent with relevant literature, our findings indicate that COVID-19 vaccine uptake was lower in currently unmarried participants than those currently married. Studies have found that vaccine uptake was higher in participants who were married [28, 31]. Given these findings, vaccination policies and strategies specific to populations with single/separated marital status for future pandemics are crucial, particularly considering specific concerns or preferences in such cases.

We noted that employed participants with a regular income had 3.3 times higher odds of getting vaccinated than those with unreliable income. Similar studies have shown an association between employment status and COVID-19 vaccination status [28, 30]. Employment vaccination requirements may have played some role as the data were collected after vaccination mandates by the Thai government. In fact, stable income is a crucial socioeconomic factor influencing people’s health attitudes and behaviors. Therefore, considering socioeconomic factors such as income and employment is crucial when addressing the health needs of the population.

It is well known that theory-based behavioral models are crucial in adopting a new behavior [32–34]. We observed that 69.6%, 41.9%, and 12% of our study participants, respectively, had a high level of capability, opportunity, and motivation to receive the COVID-19 vaccine according to the COM-B model. In addition, we found that participants with high levels of opportunity and motivation were more likely to receive their first dose of the COVID-19 vaccine than participants with low levels of opportunity and motivation. Several studies reported that factors that influence behavioral intentions toward the COVID-19 vaccine are multi-dimensional [28, 29]. A study in Thailand found that the constructs in the COM-B model could successfully generate themes of behaviors that affect COVID-19 prevention behaviors [23]. Other studies have revealed that the adapted COM-B model provides refined details for each construct in the vaccine context [22, 24]. Based on the COM-B constructs, effective interventions could be designed based on the predictors of capability, opportunity, and motivation which can be beneficial in a variety of disaster, geographic and socioeconomic contexts to improve healthy behaviors.

Limitations

Our findings have several limitations. The smaller sample size allows less precision in the findings. Considering the use of an online survey approach, elder participants and participants with low education may be under-represented in our sample. We employed the Thai version of the COM-B model in the context of the COVID-19 vaccine for the first time, while their psychometric properties require assertion. We have not assessed the bio-psycho-social health of our subjects, and their socio-cultural affiliations that may have confounded their uttered responses. Finally, the findings of this study are limited to a particular period of the pandemic, and since then there have been substantial improvements in the acceptance of the COVID-19 vaccine.

Conclusion

We found that 59.5% of our study participants had received at least one dose of a COVID-19 vaccine. The uptake of the COVID-19 vaccine was influenced by the sociodemographics of our participants (i.e., educational attainment, marital status, and employment status). We also found that opportunity and motivation constructs of the COM-B model effectively predicted the uptake of the COVID-19 vaccines. The findings of this study could be used to inform evidence-based interventions in a variety of disaster, geographic and socioeconomic contexts to improve healthy behaviors.

Supporting information

S1 Dataset. Microsoft excel file with minimal dataset.

(XLSX)

pone.0300509.s001.xlsx^{(63.3KB, xlsx)}

Acknowledgments

The authors sincerely thank all the people in the high-risk district who were involved in the study for their assistance and support.

Data Availability

The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information Files.

Funding Statement

This study was financially supported by the Excellent Center for Dengue and Community Public Health [WU-COE-66-16], School of Public Health, Walailak University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. 2024 Mar 14;19(3):e0300509. doi: 10.1371/journal.pone.0300509.r001

Author response to previous submission

12 Aug 2023

Attachment

Submitted filename: Rebuttal Letter.docx

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PLoS One. doi: 10.1371/journal.pone.0300509.r002

Decision Letter 0

Kittisak Jermsittiparsert

2 Nov 2023

PONE-D-23-22650Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B ModelPLOS ONE

Dear Dr. Stanikzai,

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Additional Editor Comments:

Overall, this manuscript was written quite well and received very positive feedback from reviewers. If this manuscript is submitted for consideration at the end of 2021 or early 2022, it will need to be accepted and published quickly as it is a study to face the urgent situation at that time. However, now that the COVID-19 situation has passed and interest in vaccination has decreased a lot because it is not something that people still don't know even a little bit about it that might be helpful. Looking at the details of this manuscript, I found that these are issues that many studies have already addressed. This is especially true when considering the population of this study that is not unique or may provide new, deeper or more interesting answers. To make this manuscript interesting and useful for publication at this time, the authors need to improve this manuscript in at least two parts.

1) Point out how important and interesting the southern region of Thailand is within a context of a developing country. However, there should also be strong empirical data to support it.

2) If it is not possible to change the independent variables used in the study, the authors should not only point out what variables are present but also explain the interesting points from the discovery of the relationship between those variables. This is not only to answer questions about COVID-19, but also to deal with future outbreaks in this type of area.

This means that the authors need to be more explicit about the issues being studied and how they are more important or interesting than in many previous studies. Moreover, it is a discussion and expansion to show how the results of this research can be further developed to obtain answers that are more useful than existing research.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I have no concerns about the issue of republishing. This research is a new research study in the context of the southern region of Thailand. and have research ethics standards certified by the host university In addition, this research also writes useful research results that will lead to future public health guidelines in Thailand and countries with similar contexts.

Reviewer #2: The study is ethically sound, receiving approval from Walailak University's Ethics Committee and obtaining informed consent from participants. The research demonstrates exceptional originality, as confirmed by a favorable plagiarism assessment. It appropriately references current literature, covering a wide range of topics related to COVID-19 and vaccination. The study design, a web-based cross-sectional approach in a high-risk urban area, aligns with its objectives and uses academically sound measures. Statistical analysis and interpretation are generally appropriate, though presenting confidence intervals for percentages and means and providing more detailed interpretation of logistic regression results could enhance clarity. Overall, the conclusions are well-supported by data and analyses, highlighting a 59.5% vaccine uptake rate and identifying demographic factors and the influence of the COM-B model on vaccine acceptance. The study suggests further research and provides valuable insights for evidence-based interventions. For the full details of my reviews, please refer to the attached MS WORD file, named "SRIRATH-SENT1112023.docx."

**********

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Reviewer #1: Yes: Naksit Sakdapat

Reviewer #2: Yes: Srirath Gohwong, Ph.D.

**********

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Attachment

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PLoS One. 2024 Mar 14;19(3):e0300509. doi: 10.1371/journal.pone.0300509.r003

Author response to Decision Letter 0

21 Dec 2023

Dear Editor,

We would like to thank the editor and the reviewers for their thoughtful evaluation of our manuscript entitled “Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B Model”. Please find our revised manuscript along with tracked changes file (yellow highlighted), which we believe is substantially strengthened now that we have incorporated reviewers’ recommendations.

Journal requirements:

We made amendments according to the journal requirements.

Additional Editor Comments:

Response: Thank you so much for your positive comments. We would like to add the findings of this study could be of significant importance in adopting a new behavior through application of the COM-B model in any given disaster. We have provided more details for the practical implications of our key findings (yellow highlighted in the manuscript).

To make this manuscript interesting and useful for publication at this time, the authors need to improve this manuscript in at least two parts.

1. Point out how important and interesting the southern region of Thailand is within a context of a developing country. However, there should also be strong empirical data to support it.

Response: Thank you so much. We agree with your comment and added details in the introductions section and methodology, and pointed out this point through out the discussion of our revised manuscript (Please see lines 95-102, lines 106-112, please see full discussion).

2. If it is not possible to change the independent variables used in the study, the authors should not only point out what variables are present but also explain the interesting points from the discovery of the relationship between those variables. This is not only to answer questions about COVID-19, but also to deal with future outbreaks in this type of area. This means that the authors need to be more explicit about the issues being studied and how they are more important or interesting than in many previous studies. Moreover, it is a discussion and expansion to show how the results of this research can be further developed to obtain answers that are more useful than existing research.

Response: Thank you so much. We are indeed very thankful for this feedback. We have revised most sections of our manuscript and addressed this important issue of how our findings can be important in future events like COVID-19 disease. Moreover, we have expanded our discussion of how our findings can be useful (Please see lines 338-340, lines 343-345, lines 364-369, lines 372-375, lines 380-383, lines 394-397, and lines 411-415). We have also highlighted key findings for policy consideration. Thank you once again and we really hope that our manuscript would be acceptable to you.

Response to Reviewers’ comments

Response to Reviewer 1 comments

I have no concerns about the issue of republishing. This research is a new research study in the context of the southern region of Thailand, and as research ethics standards certified by the host university. In addition, this research also writes useful research results that will lead to future public health guidelines in Thailand and countries with similar contexts.

Response: Thank you so much for recommending the publication of our manuscript.

Response to Reviewer 2 comments

1. The study is ethically sound, receiving approval from Walailak University's Ethics Committee and obtaining informed consent from participants. The research demonstrates exceptional originality, as confirmed by a favorable plagiarism assessment. It appropriately references current literature, covering a wide range of topics related to COVID-19 and vaccination. The study design, a web-based cross-sectional approach in a high-risk urban area, aligns with its objectives and uses academically sound measures.

Response: Thank you so much for constructive and positive feedback.

2. Statistical analysis and interpretation are generally appropriate, though presenting confidence intervals for percentages and means and providing more detailed interpretation of logistic regression results could enhance clarity.

Response: Thank you so much for this feedback. We have added 95% CI for COVID-19 vaccines percentages, added means for COM-B constructs, and added p-value to the logistic regression results (Please see the results).

3. Overall, the conclusions are well supported by data and analyses, highlighting a 59.5% vaccine uptake rate and identifying demographic factors and the influence of the COM-B model on vaccine acceptance. The study suggests further research and provides valuable insights for evidence-based interventions.

Response: Thank you so much.

Responses to reviewer 2 detailed feedback.

1. The research complies with ethical standards for experimentation and research integrity, as it was granted approval by Walailak University's Ethics Committee (reference number WUEC-21-214-01, dated August 16, 2021). Informed consent was diligently secured from all participants through an official online consent form, as provided by the committee. This form transparently communicated the study's goals, objectives, and the participants' entitlement to withdraw at any point. Furthermore, the study steadfastly adhered to the ethical principles outlined in the Declaration of Helsinki, which stands as one of its outstanding strengths.

Response: Thank you so much.

2. The title of this study, "Enhancing COVID-19 Vaccine Uptake in High-Risk Urban Populations in Southern Thailand through the Application of the COM-B Model," boldly showcases its unique and innovative approach. The assessment for potential plagiarism conducted by Chulalongkorn University resulted in a favorable outcome, revealing a similarity index of 0.00% (Source: [http://plag.grad.chula.ac.th], [http://www.chula.ac.th/en/]). This academic research demonstrates exceptional originality and quality, and the plagiarism assessment findings reinforce my confidence in its academic integrity.

Response: Thank you so much for positive feedback.

3. Is the work clearly and accurately presented and does it cite the current literature?

The work does cite a range of current literature relevant to the research topic. The references included in the provided text encompass a variety of sources, including academic journals, international organizations like the World Health Organization (WHO), and primary research studies. The references cover a wide range of topics related to the COVID-19 pandemic, vaccination, and factors influencing vaccine acceptance.

Response: Thank you so much.

4. Is the study design appropriate and does the work have academic merit? Are Experiments, statistics, and other analyses performed to a high technical standard and are described in sufficient detail?

a. The study design is well-suited to the research objectives, involving a web-based cross-sectional study conducted in Hat Yai district, an urban area in southern Thailand significantly affected by the COVID-19 pandemic. The study's focus on COVID-19 vaccine uptake among high-risk urban populations is justified. The measures, including socio-demographic characteristics and the adapted Capability, Opportunity, Motivation, and Behavior (COM-B) model, are academically sound. The data collection process is well documented, with pretesting and reliability checks. The statistical analysis using SPSS, descriptive statistics, and multivariable logistic regression aligns with the study's objectives. The use of a significance level (P < .05) is appropriately stated.

Response: Thank you so much.

b. However, providing more detail on specific statistical tests, control variables, and effect sizes would enhance the analysis, especially multivariable logistic regression. Logistic multiple regression is a statistical approach employed when analyzing a binary outcome variable, such as yes/no or 1/0, in relation to multiple independent variables (predictors or covariates). The author should reveal the specific conditions and assumptions of Logistic multiple regression: the outcome must be binary, observations should be independent, a linear relationship between predictors and log-odds is assumed, multicollinearity should be avoided, a sufficient sample size is needed, outliers need attention, perfect separation can pose challenges, model fit must be evaluated, odds ratios should be appropriately interpreted, and causal relationships should be established through experimental designs or advanced statistical methods. Adhering to these considerations is vital for ensuring the robustness and reliability of results. Collaboration with a statistician or data analyst is recommended for addressing complex modeling issues and assessing potential assumption violations.

Response: Thank you so much. We agree with your comments and have added the suggested details. In our methods, we have declared that all assumptions for multivariable logistic regression analysis were met (Please see line 177-178).

c. The limitations of the study are well-acknowledged, including the smaller sample size, potential under-representation of certain demographic groups, and the fact that the study focused on a particular period of the pandemic. The study's recognition of these limitations demonstrates a thorough understanding of the research's scope and potential constraints.

Response: Thank you so much for the positive feedback.

5. If applicable, are the statistical analysis and its interpretation appropriate?

a. The statistical analysis and interpretation of the data are generally appropriate. The study presents a comprehensive analysis of the socio-demographic characteristics of the participants, their capability, opportunity, motivation, and the factors associated with COVID-19 vaccine uptake. The use of descriptive statistics, such as percentages and means, is suitable for presenting the data. The logistic regression analysis effectively identifies factors associated with the vaccine uptake.

Response: Thank you so much.

b. However, there is room for minor improvements. While the results are well presented, it would be beneficial to include the confidence intervals for the percentages and means to indicate the precision of the estimates. Moreover, the interpretation of the logistic regression results could be more detailed, explaining the adjusted odds ratios and their implications more explicitly. In conclusion, the study's analysis and interpretation are sound, but enhancing clarity and precision in presenting results and their implications would further strengthen the paper.

Response: Thank you so much for the constructive feedback. We have added the suggested points to the results (please see the results section). Moreover, we have detailed the implications of our findings in the discussion section (Please see lines 338-340, lines 343-345, lines 364-369, lines 372-375, lines 380-383, lines 394-397, and lines 411-415).

6. Are the conclusions drawn adequately supported by the results? [Conclusions are presented in an appropriate fashion and are supported by the data.]

The study's conclusions find robust support in the data and analyses. It reports a COVID-19 vaccine uptake rate of 59.5% among participants, backed by the data's clear portrayal of vaccination status and construct scores for capability, opportunity, and motivation. Furthermore, the study uncovers various demographic factors linked to vaccine acceptance, such as marital status, education, and employment, as indicated by the odds ratios derived from multivariable logistic regression analysis. Notably, the study underscores the effectiveness of the COM-B model's opportunity and motivation constructs in driving vaccine uptake, leveraging comprehensive data from Tables 2, 3, and 4. It wisely calls for future research encompassing larger and more diverse populations to validate these findings and offers guidance on evidence-based interventions for enhancing COVID-19 vaccine uptake based on the identified factors and COM-B constructs.

Response: Thank you so much for clarifying these important findings and providing positive feedback to our manuscript.

At last, we would like to thank respected editor and respected reviewers for the overall positive feedback on our manuscript and hope that it will be acceptable to them.

Sincerely,

Attachment

Submitted filename: Response to Reviewers.docx

pone.0300509.s004.docx^{(36.1KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0300509.r004

Decision Letter 1

Pei Boon Ooi

22 Feb 2024

PONE-D-23-22650R1Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B ModelPLOS ONE

Dear Dr. Stanikzai,

==============================

Dear author:

Thank you for the revision and taking the efforts to address all comments. To further improve the manuscript's readability, we would like to invite you to address the below.

1. Abstract" Add in the total number of sample size after the word the word Participant= Results: In this study, females constituted 54.7% of the total participants (n=XX)...

2. Given these findings, vaccination polices and strategies specific to populations with single/separated marital status for future pandemics are crucial, particularly considering the likelihood of lower social support in such cases. This is not clear in term of what do you meant by likelihood of lower social support and how is it related to the single/separated marital status?

3. Please format the tables according to PLOS ONE requirement.

4. Please attached a letter of proofread of the entire revised manuscript.

5. Please help to provide at short 1 line on "HATY AIZ"- what is HATY AIZ?

6. In the procedure section, please state the right to withdraw as well as token of appreciation- if applicable.

7. Please change all p-value in upper case e.g., in here "statistical significance at P < 0.05" (line 178, abstract) to lower case and italic "p <0.05"

8. Seeking your elaboration on Capability, Opportunity, Motivation, and Behavior. In line 145, you mentioned that "In each scale, a score of >10 was used to signify a high level of capability' but in line 204 and 205, it was also stated that "The mean score of the capability construct was 9.53 (± 1.55 SD) with a range of 3-12 points, and 205 nearly two-thirds (249; 69.6%) of them showed a high level of capability". 9.53 certainly is not >10. Hence, I am not sure how did you arrive at the conclusion that "205 nearly two-thirds (249; 69.6%) of them showed a high level of capability". Same concern on "Opportunity to receive COVID-19 vaccine". Can you please clarify this for better readability?

9. Please include this article in your in text citation - line 78 to support the claim on "trust in healthcare professionals" - https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-022-12632-z (citation requests are optional)

==============================

Please submit your revised manuscript by Apr 07 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
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We look forward to receiving your revised manuscript.

Kind regards,

Pei Boon Ooi, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

Dear author:

Thank you for the revision and taking the efforts to address all comments. To further improve the manuscript's readability, we would like to invite you to address the below.

1. Abstract" Add in the total number of sample size after the word the word Participant= Results: In this study, females constituted 54.7% of the total participants (n=XX)...

3. Please format the tables according to PLOS ONE requirement.

4. Please attached a letter of proofread of the entire revised manuscript.

5. Please help to provide at short 1 line on "HATY AIZ"- what is HATY AIZ?

6. In the procedure section, please state the right to withdraw as well as token of appreciation- if applicable.

7. Please change all p-value in upper case e.g., in here "statistical significance at P < 0.05" (line 178, abstract) to lower case and italic "p"

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: It is a particularly interesting study that studies the use of COVID-19 vaccines. In groups High-risk urban populations in southern Thailand. The model is integrated opportunity, motivation, and behavior (COM-B Model). The findings are detailed comprehensive and beneficial to Thailand's public health in the future. It can be used to plan policy measures on intervention measures in the event of an outbreak similar to COVID-19.

Reviewer #2: The study, titled "Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B Model," provided a clear and accurate presentation, utilizing a web-based cross-sectional approach in the Hat Yai district, Southern Thailand. It strengthened its findings by drawing on a diverse array of contemporary literature, encompassing socio-economic implications, global vaccine acceptance rates, and factors influencing vaccine acceptance. Through an extensive citation of current literature, the research established a robust contextual foundation, weaving insights from reviews on socio-economic impacts, paradigms of vaccine development, and studies on vaccine acceptance rates into its analytical framework. The comprehensive and up-to-date engagement with relevant sources enhanced the study's credibility, providing a well-supported backdrop for its research findings. "I am honored to have the opportunity to read this paper."

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Srirath G., Ph.D.

**********

Attachment

Submitted filename: GOIINC18022024.docx

pone.0300509.s005.docx^{(15.1KB, docx)}

PLoS One. 2024 Mar 14;19(3):e0300509. doi: 10.1371/journal.pone.0300509.r005

Author response to Decision Letter 1

24 Feb 2024

Dear Editor,

We would like to thank the editor and the reviewers for their positive evaluation of our manuscript entitled “Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B Model”. Please find our revised manuscript along with tracked changes file (yellow highlighted), which we believe is substantially strengthened now that we have incorporated editorial recommendations.

Journal requirements:

We made amendments according to the journal requirements.

Additional Editor Comments:

Thank you for the revision and taking the efforts to address all comments. To further improve the manuscript's readability, we would like to invite you to address the below.

Response: We also would like to thank the respected editor and reviewers for their approval of our responses and revision. Each point was very helpful for making our paper better and suitable for publication in your prestigious journal. As such, we have tried to amend the manuscript in light of all your and reviewers’ comments and the journal guideline. Please find our responses to the editorial requests.

1. Abstract" Add in the total number of sample size after the word the word Participant= Results: In this study, females constituted 54.7% of the total participants (n=XX)...

Response: Thank you so much for you’re your constructive feedback. We have added the sample size (please see page: 2, line: 29).

Response: Thank you. We agree with you that this section was not clear and revised as suggested (please see lines 295 and 296).

3. Please format the tables according to PLOS ONE requirement.

Response: Thank you. We formatted our tables according to PLOS ONE requirement.

4. Please attached a letter of proofread of the entire revised manuscript.

Response: Thank you so much for this suggestion. All authors re-edited the manuscript to remove the grammatical errors and improve the manuscript. Besides, we have sent the manuscript to English language expert in US (our colleague) and she has proofread it. Please let us know if any error remains.

5. Please help to provide at short 1 line on "HATY AIZ"- what is HATY AIZ?

Response: Thank you so much. We agree with your suggestion and have added a line on HATY AIZ group (please see line 113).

6. In the procedure section, please state the right to withdraw as well as token of appreciation- if applicable.

Response: Thank you. In our research, participants had the right to withdraw at any stage and we have added these details into the procedure section (please see lines 163 and 185).

7. Please change all p-value in upper case e.g., in here "statistical significance at P < 0.05" (line 178, abstract) to lower case and italic "p <0.05"

Response: Thank you so much. We made changes as suggested (please see line 26, line 175, and Table 5 heading).

Response: Thank you so much for your meticulous observation. We checked our descriptive statistics again and found that there was some error in typing and the mean scores have been corrected now. We have also checked our other analyses and the findings were correctly typed in other cases, except this section which was highlighted by the editor. Additionally the cut-off score should have been written ≥ 10 (typo mistake). We have made these corrections too. Please see the changes on lines 143, 208, 217, and 231.

Response: Thank you so much for this suggestion. We have added this relevant citation into our manuscript.

Response to Reviewers’ comments

Response to Reviewer 1 comments

Comment: It is a particularly interesting study that studies the use of COVID-19 vaccines. In groups High-risk urban populations in southern Thailand. The model is integrated opportunity, motivation, and behavior (COM-B Model). The findings are detailed comprehensive and beneficial to Thailand's public health in the future. It can be used to plan policy measures on intervention measures in the event of an outbreak similar to COVID-19.

Response: Thank you so much for your constructive feedback and recommendation on the publication of our manuscript.

Response to Reviewer 2 comments

Comment: The study, titled "Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B Model," provided a clear and accurate presentation, utilizing a web-based cross-sectional approach in the Hat Yai district, Southern Thailand. It strengthened its findings by drawing on a diverse array of contemporary literature, encompassing socio-economic implications, global vaccine acceptance rates, and factors influencing vaccine acceptance. Through an extensive citation of current literature, the research established a robust contextual foundation, weaving insights from reviews on socio-economic impacts, paradigms of vaccine development, and studies on vaccine acceptance rates into its analytical framework. The comprehensive and up-to-date engagement with relevant sources enhanced the study's credibility, providing a well-supported backdrop for its research findings. "I am honored to have the opportunity to read this paper."

Response: Thank you so much for your suggestions and comments. Your suggestion and comments have significantly improved our manuscript.

At last, we would like to thank respected editor and respected reviewers for the overall positive feedback and help on the improvement of our manuscript and hope that it will be acceptable to them.

Sincerely,

Attachment

Submitted filename: Response to Reviewers.docx

pone.0300509.s006.docx^{(30KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0300509.r006

Decision Letter 2

Pei Boon Ooi

29 Feb 2024

Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B Model

PONE-D-23-22650R2

Dear Dr. Stanikzai,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Pei Boon Ooi, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0300509.r007

Acceptance letter

Pei Boon Ooi

5 Mar 2024

PONE-D-23-22650R2

PLOS ONE

Dear Dr. Stanikzai,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

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on behalf of

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Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Dataset. Microsoft excel file with minimal dataset.

(XLSX)

pone.0300509.s001.xlsx^{(63.3KB, xlsx)}

Attachment

Submitted filename: Rebuttal Letter.docx

pone.0300509.s002.docx^{(24.4KB, docx)}

Attachment

Submitted filename: SRIRATH-SENT1112023.docx

pone.0300509.s003.docx^{(19KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0300509.s004.docx^{(36.1KB, docx)}

Attachment

Submitted filename: GOIINC18022024.docx

pone.0300509.s005.docx^{(15.1KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0300509.s006.docx^{(30KB, docx)}

Data Availability Statement

The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information Files.

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PERMALINK

Uptake of COVID-19 vaccine among high-risk urban populations in Southern Thailand using the COM-B model

Charuai Suwanbamrung

Benchawan Srinam

Pakawan Promkool

Warissara Suwannakarn

Sangchom Siripanich

Md Siddikur Rahman

Muhammad Haroon Stanikzai

Roles

Abstract

Background

Objectives

Methods

Results

Conclusion

Introduction

Materials and methods

Study settings and design

Study population

Sample size and sampling procedures

Study measures

Data collection

Statistical analysis

Ethical consideration

Results

Table 1. Sociodemographic characteristics of the study participants (n = 358).

Capability to receive COVID-19 vaccine

Table 2. Capability to receive COVID-19 vaccine (n = 358).

Opportunity to receive COVID-19 vaccine

Table 3. Opportunity to receive COVID-19 vaccine (n = 358).

Motivation to receive COVID-19 vaccine

Table 4. Motivation to receive COVID-19 vaccine (n = 358).

Factors associated with the uptake of COVID-19 vaccine in our sample

Table 5. Factors associated with the uptake of COVID-19 vaccine; crude and adjusted odds ratio with 95% CI.

Discussion

Limitations

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Author response to previous submission

Decision Letter 0

Kittisak Jermsittiparsert

Roles

Author response to Decision Letter 0

Decision Letter 1

Pei Boon Ooi

Roles

Author response to Decision Letter 1

Decision Letter 2

Pei Boon Ooi

Roles

Acceptance letter

Pei Boon Ooi

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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