Displaying publications 61 - 75 of 75 in total

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  1. Ab Aziz WA, Musa KI, Ibrahim MI, Osman Y, Shafei MN
    Cureus, 2023 May;15(5):e38937.
    PMID: 37313064 DOI: 10.7759/cureus.38937
    INTRODUCTION: Job stress is an important occupational health problem globally. Hence, identification of workers at risk of developing job stress is paramount to the decision-makers. This study aims to estimate the proportion of job stress and its relationship with different categories of healthcare workers (HCWs) in the primary care and public health settings in northeastern Malaysia.

    METHODOLOGY: A cross-sectional study involving 520 HCWs across all categories was conducted in Kelantan State, Malaysia. A proforma and validated Malay version of the Job Content Questionnaires were administered to obtain the data. The participants were then classified into four categories of workers according to Karasek's job demands-control model classification which were active, passive, high strain, and low strain.

    RESULTS: We found that a total of 145 (28.5%) HCWs in the study have job stress (high-strain job type). HCWs with a degree or higher qualification had the highest proportion of job stress (41.2%), while the diploma group has the lowest proportion of job stress among the four academic qualification groups (22.9%). Pearson chi-square shows a significant association between Karasek's job types and the level of social support from their supervisors (p < 0.05) but no association between job strain and the level of supervisor's social support (p > 0.05).

    CONCLUSION: Job stress among HCWs is prevalent, and the professional group had the highest percentage of risk job stress as compared to other groups. There is a significant association between the supervisor's social support and Karasek's job strain categories.

  2. Che Nawi CMNH, Mohd Hairon S, Wan Yahya WNN, Wan Zaidi WA, Hassan MR, Musa KI
    Cureus, 2023 Aug;15(8):e44142.
    PMID: 37753006 DOI: 10.7759/cureus.44142
    The quick advancement of digital technology through artificial intelligence has made it possible to deploy machine learning to predict stroke outcomes. Our aim is to examine the trend of machine learning applications in stroke-related research over the past 50 years. We used search terms stroke and machine learning to search for English versions of original and review articles and conference proceedings published over the past 50 years in Scopus and Web of Science databases. The Biblioshiny web application was utilized for the analysis. The trend of publication and prominent authors and journals were analyzed and identified. The collaborative network between countries was mapped, and a thematic map was used to monitor the authors' trending keywords. In total, 10,535 publications authored by 44,990 authors from 2,212 sources were retrieved. Two distinct clusters of collaborative network nodes were observed, with the United States serving as a connecting node. Three terms - deep learning, algorithms, and neural networks - are observed in the early stages of the emerging theme. Overall, international research collaborations, the establishment of global research initiatives, the development of computational science, and the availability of big data have facilitated the pervasive use of machine learning techniques in stroke research.
  3. Hasani WSR, Muhamad NA, Hanis TM, Maamor NH, Chen XW, Omar MA, et al.
    BMC Public Health, 2023 Aug 16;23(1):1561.
    PMID: 37587427 DOI: 10.1186/s12889-023-16466-1
    BACKGROUND: Cardiovascular disease (CVD) is a significant cause of premature mortality worldwide, with a growing burden in recent years. Despite this, there is a lack of comprehensive meta-analyses that quantify the extent of premature CVD mortality. Study addressed this gap by estimating the pooled age-standardized mortality rate (ASMR) of premature CVD mortality.

    METHODS: We conducted a systematic review of published CVD mortality studies that reported ASMR as an indicator for premature mortality measurement. All English articles published as of October 2022 were searched in four electronic databases: PubMed, Scopus, Web of Science (WoS), and the Cochrane Central Register of Controlled Trials (CENTRAL). We computed pooled estimates of ASMR using random-effects meta-analysis. We assessed heterogeneity from the selected studies using the I2 statistic. Subgroup analyses and meta regression analysis was performed based on sex, main CVD types, income country level, study time and age group. The analysis was performed using R software with the "meta" and "metafor" packages.

    RESULTS: A total of 15 studies met the inclusion criteria. The estimated global ASMR for premature mortality from total CVD was 96.04 per 100,000 people (95% CI: 67.18, 137.31). Subgroup analysis by specific CVD types revealed a higher ASMR for ischemic heart disease (ASMR = 15.57, 95% CI: 11.27, 21.5) compared to stroke (ASMR = 12.36, 95% CI: 8.09, 18.91). Sex-specific differences were also observed, with higher ASMRs for males (37.50, 95% CI: 23.69, 59.37) than females (15.75, 95% CI: 9.61, 25.81). Middle-income countries had a significantly higher ASMR (90.58, 95% CI: 56.40, 145.48) compared to high-income countries (21.42, 95% CI: 15.63, 29.37). Stratifying by age group indicated that the age groups of 20-64 years and 30-74 years had a higher ASMR than the age group of 0-74 years. Our multivariable meta-regression model suggested significant differences in the adjusted ASMR estimates for all covariates except study time.

    CONCLUSIONS: This meta-analysis synthesized a comprehensive estimate of the worldwide burden of premature CVD mortality. Our findings underscore the continued burden of premature CVD mortality, particularly in middle-income countries. Addressing this issue requires targeted interventions to mitigate the high risk of premature CVD mortality in these vulnerable populations.

  4. Che Nawi CMNH, Mohd Hairon S, Wan Yahya WNN, Wan Zaidi WA, Musa KI
    Cureus, 2023 Dec;15(12):e50426.
    PMID: 38222138 DOI: 10.7759/cureus.50426
    Background Stroke is a significant public health concern characterized by increasing mortality and morbidity. Accurate long-term outcome prediction for acute stroke patients, particularly stroke mortality, is vital for clinical decision-making and prognostic management. This study aimed to develop and compare various prognostic models for stroke mortality prediction. Methods In a retrospective cohort study from January 2016 to December 2021, we collected data from patients diagnosed with acute stroke from five selected hospitals. Data contained variables on demographics, comorbidities, and interventions retrieved from medical records. The cohort comprised 950 patients with 20 features. Outcomes (censored vs. death) were determined by linking data with the Malaysian National Mortality Registry. We employed three common survival modeling approaches, the Cox proportional hazard regression (Cox), support vector machine (SVM), and random survival forest (RSF), while enhancing the Cox model with Elastic Net (Cox-EN) for feature selection. Models were compared using the concordance index (C-index), time-dependent area under the curve (AUC), and discrimination index (D-index), with calibration assessed by the Brier score. Results The support vector machine (SVM) model excelled among the four, with three-month, one-year, and three-year time-dependent AUC values of 0.842, 0.846, and 0.791; a D-index of 5.31 (95% CI: 3.86, 7.30); and a C-index of 0.803 (95% CI: 0.758, 0.847). All models exhibited robust calibration, with three-month, one-year, and three-year Brier scores ranging from 0.103 to 0.220, all below 0.25. Conclusion The support vector machine (SVM) model demonstrated superior discriminative performance, suggesting its efficacy in developing prognostic models for stroke mortality. This study enhances stroke mortality prediction and supports clinical decision-making, emphasizing the utility of the support vector machine method.
  5. Adil SO, Uddin F, Musa KI, Khan A, Shakeel A, Shafique K, et al.
    Int J Gen Med, 2023;16:4295-4305.
    PMID: 37753441 DOI: 10.2147/IJGM.S423151
    PURPOSE: The presence of metabolic syndrome (MetS) is linked to an increased risk of cardiovascular disease (CVD) development. In this study, CVD risk was calculated among individuals with newly diagnosed MetS using the Framingham Risk Score (FRS) and Globorisk Score. The FRS and Globorisk score are particularly relevant in predicting CVD risk as these scores include key MetS-related risk factors like blood pressure, cholesterol levels, and age.

    PATIENTS AND METHODS: A community-based cross-sectional study was conducted at various sites in Karachi, Pakistan, from February 2022 to August 2022. Newly diagnosed cases of MetS with no physical disability, known illness, and not taking any regular medication were recruited. MetS was defined based on the definition of International Diabetes Federation. The major outcome was 10-year risk for CVD using the FRS and Globorisk Score.

    RESULTS: Of 304 patients, 59.2% were classified as low risk according to FRS, while 20.4% were classified as moderate and high risk each. Using the Globorisk score, 44.6% of 224 patients were classified as low risk, 34.4% as moderate risk, and 21.0% as high risk. A moderate positive correlation was observed between the two CVD risk scores (r = 0.651, 95% CI 0.58-0.71). Both risk scores have reported age, gender, and current smokers as significant risk factors in predicting CVD in 10-years (P < 0.05).

    CONCLUSION: The outcome of both CVD risk scores predicted moderate-to-high risk of CVD in 10-years in almost half of the newly diagnosed patients with MetS. In particular, the risk of development of CVD in 10-years in newly diagnosed MetS is higher with increasing age, in male gender, and current smokers.

  6. Sidek NN, Tengku Ismail TA, Kamalakannan S, Chen XW, Romli MH, Mat Said MZ, et al.
    Front Neurol, 2023;14:1222260.
    PMID: 37905189 DOI: 10.3389/fneur.2023.1222260
    INTRODUCTION: Recognizing the burden experienced by caregivers of stroke survivors, an intervention using mobile health applications (mHealth apps) has been proposed to support and empower stroke caregivers. This study aimed to assess the acceptability and expectations of healthcare providers, who play a vital role as gatekeepers in the healthcare system, to ensure the effectiveness and sustainability of the intervention.

    METHODS: This was a concurrent mixed-method study design, with healthcare providers involved in stroke care management in the northeast regions of Malaysia as study participants. The qualitative component of the study was conducted using a phenomenological approach that involved in-depth interviews to explore the acceptability and expectations of healthcare providers regarding the adoption of mHealth apps in the context of stroke caregiving. The study was complemented by quantitative data collected through an online survey using an adjusted version of the technology acceptance model tool.

    RESULTS: In total, 239 participants from diverse backgrounds and professions were enrolled in the study, with 12 in the qualitative component and 227 in the quantitative component. The findings from the quantitative survey showed that over 80% of the participants expressed their intention to use mHealth apps. The qualitative component generated two themes related to the acceptability and expectations of mHealth apps, which were integrated with the quantitative findings. Additionally, in-depth interviews revealed a new theme, namely the key features of mHealth, with three sub-themes: availability of services for caregivers, provision of knowledge skills, and supporting caregivers in managing stroke patients.

    CONCLUSION: Healthcare providers demonstrated excellent acceptability of this mHealth intervention as part of caregiving assistance, particularly with the inclusion of essential key features. However, future investigations are necessary to establish the feasibility of integrating the mHealth app into the healthcare system and to ensure its long-term sustainability.

  7. Adil SO, Musa KI, Uddin F, Shafique K, Khan A, Islam MA
    Front Endocrinol (Lausanne), 2023;14:1223424.
    PMID: 37876536 DOI: 10.3389/fendo.2023.1223424
    INTRODUCTION: Anthropometric indices are affordable and non-invasive methods for screening metabolic syndrome (MetS). However, determining the most effective index for screening can be challenging.

    OBJECTIVE: To investigate the accuracy of anthropometric indices as a screening tool for predicting MetS among apparently healthy individuals in Karachi, Pakistan.

    METHODS: A community-based cross-sectional survey was conducted in Karachi, Pakistan, from February 2022 to August 2022. A total of 1,065 apparently healthy individuals aged 25 years and above were included. MetS was diagnosed using International Diabetes Federation guidelines. Anthropometric indices were defined based on body mass index (BMI), neck circumference (NC), mid-upper arm circumference (MUAC), waist circumference (WC), waist to height ratio (WHtR), conicity index, reciprocal ponderal index (RPI), body shape index (BSI), and visceral adiposity index (VAI). The analysis involved the utilization of Pearson's correlation test and independent t-test to examine inferential statistics. The receiver operating characteristic (ROC) analysis was also applied to evaluate the predictive capacities of various anthropometric indices regarding metabolic risk factors. Moreover, the area under the curve (AUC) was computed, and the chosen anthropometric indices' optimal cutoff values were determined.

    RESULTS: All anthropometric indices, except for RPI in males and BSI in females, were significantly higher in MetS than those without MetS. VAI [AUC 0.820 (95% CI 0.78-0.86)], WC [AUC 0.751 (95% CI 0.72-0.79)], WHtR [AUC 0.732 (95% CI 0.69-0.77)], and BMI [AUC 0.708 (95% CI 0.66-0.75)] had significantly higher AUC for predicting MetS in males, whereas VAI [AUC 0.693 (95% CI 0.64-0.75)], WHtR [AUC 0.649 (95% CI 0.59-0.70)], WC [AUC 0.646 (95% CI 0.59-0.61)], BMI [AUC 0.641 (95% CI 0.59-0.69)], and MUAC [AUC 0.626 (95% CI 0.57-0.68)] had significantly higher AUC for predicting MetS in females. The AUC of NC for males was 0.656 (95% CI 0.61-0.70), while that for females was 0.580 (95% CI 0.52-0.64). The optimal cutoff points for all anthropometric indices exhibited a high degree of sensitivity and specificity in predicting the onset of MetS.

    CONCLUSION: BMI, WC, WHtR, and VAI were the most important anthropometric predictors for MetS in apparently healthy individuals of Pakistan, while BSI was found to be the weakest indicator.

  8. Rodzlan Hasani WS, Muhamad NA, Hanis TM, Maamor NH, Wee CX, Omar MA, et al.
    PLoS One, 2023;18(4):e0283879.
    PMID: 37083866 DOI: 10.1371/journal.pone.0283879
    INTRODUCTION: Premature mortality refers to deaths that occur before the expected age of death in a given population. Years of life lost (YLL) is a standard parameter that is frequently used to quantify some component of an "avoidable" mortality burden.

    OBJECTIVE: To identify the studies on premature cardiovascular disease (CVD) mortality and synthesise their findings on YLL based on the regional area, main CVD types, sex, and study time.

    METHOD: We conducted a systematic review of published CVD mortality studies that reported YLL as an indicator for premature mortality measurement. A literature search for eligible studies was conducted in five electronic databases: PubMed, Scopus, Web of Science (WoS), and the Cochrane Central Register of Controlled Trials (CENTRAL). The Newcastle-Ottawa Scale was used to assess the quality of the included studies. The synthesis of YLL was grouped into years of potential life lost (YPLL) and standard expected years of life lost (SEYLL) using descriptive analysis. These subgroups were further divided into WHO (World Health Organization) regions, study time, CVD type, and sex to reduce the effect of heterogeneity between studies.

    RESULTS: Forty studies met the inclusion criteria for this review. Of these, 17 studies reported premature CVD mortality using YPLL, and the remaining 23 studies calculated SEYLL. The selected studies represent all WHO regions except for the Eastern Mediterranean. The overall median YPLL and SEYLL rates per 100,000 population were 594.2 and 1357.0, respectively. The YPLL rate and SEYLL rate demonstrated low levels in high-income countries, including Switzerland, Belgium, Spain, Slovenia, the USA, and South Korea, and a high rate in middle-income countries (including Brazil, India, South Africa, and Serbia). Over the past three decades (1990-2022), there has been a slight increase in the YPLL rate and the SEYLL rate for overall CVD and ischemic heart disease but a slight decrease in the SEYLL rate for cerebrovascular disease. The SEYLL rate for overall CVD demonstrated a notable increase in the Western Pacific region, while the European region has experienced a decline and the American region has nearly reached a plateau. In regard to sex, the male showed a higher median YPLL rate and median SEYLL rate than the female, where the rate in males substantially increased after three decades.

    CONCLUSION: Estimates from both the YPLL and SEYLL indicators indicate that premature CVD mortality continues to be a major burden for middle-income countries. The pattern of the YLL rate does not appear to have lessened over the past three decades, particularly for men. It is vitally necessary to develop and execute strategies and activities to lessen this mortality gap.

    SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021288415.

  9. Vaithilingam S, Hwang LA, Nair M, Ng JWJ, Ahmed P, Musa KI
    PLoS One, 2023;18(3):e0282520.
    PMID: 36920970 DOI: 10.1371/journal.pone.0282520
    BACKGROUND: Sporadic outbreaks of COVID-19 remain a threat to public healthcare, especially if vaccination levels do not improve. As Malaysia begins its transition into the endemic phase, it is essential to identify the key determinants of COVID-19 vaccination intention amongst the pockets of the population who are still hesitant. Therefore, focusing on a sample of individuals who did not register for the COVID-19 vaccination, the current study integrated two widely used frameworks in the public health domain-the health belief model (HBM) and the theory of reasoned action (TRA)-to examine the inter-relationships of the predictors of vaccination intention amongst these individuals.

    METHODOLOGY: Primary data from 117 respondents who did not register for the COVID-19 vaccination were collected using self-administered questionnaires to capture predictors of vaccination intention amongst individuals in a Malaysian context. The partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the data.

    RESULTS: Subjective norms and attitude play key mediating roles between the HBM factors and vaccination intention amongst the unregistered respondents. In particular, subjective norms mediate the relationship between cues to action and vaccination intention, highlighting the significance of important others to influence unregistered individuals who are already exposed to information from mass media and interpersonal discussions regarding vaccines. Trust, perceived susceptibility, and perceived benefits indirectly influence vaccination intention through attitude, indicating that one's attitude is vital in promoting behavioral change.

    CONCLUSION: This study showed that the behavioral factors could help understand the reasons for vaccine refusal or acceptance, and shape and improve health interventions, particularly among the vaccine-hesitant group in a developing country. Therefore, policymakers and key stakeholders can develop effective strategies or interventions to encourage vaccination amongst the unvaccinated for future health pandemics by targeting subjective norms and attitude.

  10. Adil SO, Musa KI, Uddin F, Khan A, Khan I, Shakeel A, et al.
    Arch Public Health, 2024 Feb 20;82(1):22.
    PMID: 38378657 DOI: 10.1186/s13690-024-01250-3
    OBJECTIVE: To determine the prevalence and associated risk factors of undiagnosed metabolic syndrome (MetS) using three different definitions among apparently healthy adults of Karachi, Pakistan.

    METHODS: This community-based cross-sectional survey was conducted in Karachi, Pakistan, from January 2022 to August 2022. A total of 1065 healthy individuals aged 25-80 years of any gender were consecutively included. MetS was assessed using the National Cholesterol Education Program for Adult Treatment Panel (NCEP-ATP) III guidelines, International Diabetes Federation (IDF), and modified NCEP-ATP III.

    RESULTS: The prevalence of MetS was highest with the modified NCEP-ATP III definition at 33.9% (95% CI: 31-36), followed by the IDF definition at 32.2% (95% CI: 29-35). In contrast, the prevalence was lower at 22.4% (95% CI: 19-25) when using the NCEP ATP III definition. The risk of MetS significantly increases with higher BMI, as defined by the IDF criteria (adjusted OR [ORadj] 1.13, 95% CI 1.09-2.43), NCEP-ATP III criteria (ORadj 1.15, 95% CI 1.11-1.19), and modified NCEP-ATP III criteria (ORadj 1.16, 95% CI 1.12-1.20). Current smokers had significantly higher odds of MetS according to the IDF (ORadj 2.72, 95% CI 1.84-4.03), NCEP-ATP III (ORadj 3.93, 95% CI 2.55-6.06), and modified NCEP-ATP III (ORadj 0.62, 95% CI 0.43-0.88). Areca nut use was associated with higher odds of MetS according to both IDF (ORadj 1.71, 95% CI 1.19-2.47) and modified NCEP-ATP III criteria (ORadj 1.58, 95% CI 1.10-2.72). Furthermore, low physical activity had significantly higher odds of MetS according to the NCEP-ATP III (ORadj 1.36, 95% CI 1.01-1.84) and modified NCEP-ATP III criteria (ORadj 1.56, 95% CI 1.08-2.26).

    CONCLUSION: One-third of the healthy individuals were diagnosed with MetS based on IDF, NCEP-ATP III, and modified NCEP-ATP III criteria. A higher BMI, current smoking, areca nut use, and low physical activity were significant factors.

  11. Azman N, Leong Bin Abdullah MFI, Musa KI, Hassan N, Mohd Shariff N
    J Psychosoc Oncol, 2024 Mar 06.
    PMID: 38449103 DOI: 10.1080/07347332.2024.2325498
    PURPOSE: While the unmet healthcare needs are still being improved upon, the wellbeing of cancer patients has increasingly become a prime concern in Malaysia. The objective of this study is to ascertain the trend of unmet supportive care needs, post-traumatic growth (P T G), coping strategies, and social supports among patients with breast cancer over the three time points of treatment: T1 at early diagnosis, T2 for three months after diagnosis, and T3 for six months after diagnosis.

    METHODS: A total of 240 cancer patients participated in this prospective cohort study, with follow-up visits from October 2019 until July 2021. Data were collected using several instruments: Brief COP E, the Source of Social Support Scale (SSSS), the Post-Traumatic Growth Inventory - Short Form (P T GI-SF), and a Malay version of the 34-Item Shortform Supportive Care Need Survey (SCNS-SF34).

    RESULTS: The results indicated a significant change from T1 to T3 for all domains of the unmet needs (p-value < 0.001), except for the sexual domain. A lower SCNS-SF34 score resulted from more unfavorable social support. The P T GI-SF results indicated a trend toward meeting the unmet needs, and a higher SCNS-SF-34 score predicted a considerably higher P T GI-SF score.

    CONCLUSIONS: Our study findings suggest that majority of the factors evaluated in terms of unmet needs among cancer patients have undergone considerable changes.

  12. Damanhuri NH, Hairi NN, Ismail M, Jeganathan R, Karalasingam SD, Nasir MJM, et al.
    Cureus, 2024 Apr;16(4):e59152.
    PMID: 38680821 DOI: 10.7759/cureus.59152
    Background Spontaneous preterm birth (SPB) is a global public health concern with devastating health effects on SPB survivors. This study aimed to determine modifiable antenatal risk factors associated with SPB among women attending government healthcare facilities in Malaysia. Methodology A retrospective record review of 49,416 national obstetrics registry data from 2015 was conducted and analyzed using binary logistic regression based on six antenatal factor divisions. Results Mothers with pre-existing diabetes had higher odds (adjusted odds ratio (aOR) = 3.09) of delivering prematurely than mothers without diabetes. Mothers with chronic hypertension with superimposed pre-eclampsia (aOR = 2.51) and gestational hypertension (aOR = 1.44) had higher odds of experiencing preterm birth than mothers with no hypertension. Underweight mothers had higher odds (aOR = 1.27) of delivering prematurely than mothers with an ideal body mass index (18.5 to <25.0 kg/m2). Mothers with moderate anemia (hemoglobin level: 7 to <9 g/dL) had higher odds (aOR = 1.18) of preterm birth than mothers with normal hemoglobin levels (≥11 g/dL). Conclusions Maternal biomarkers, such as glucose level, blood pressure, BMI, and hemoglobin level, play an important role in reducing the rate of SPB in Malaysia. This study recommends strengthening pre-pregnancy, antenatal, and postpartum care through multidisciplinary and multi-agency team collaboration, addressing both modifiable and non-modifiable risk factors and adopting a dual approach that combines preventive and curative care.
  13. Hwang LA, Vaithilingam S, Ng JWJ, Nair M, Ahmed P, Musa KI
    PLoS One, 2024;19(4):e0301383.
    PMID: 38687718 DOI: 10.1371/journal.pone.0301383
    BACKGROUND: Vaccination has been one of the most effective preventive strategies to contain the COVID-19 pandemic. However, as the COVID-19 vaccines' effect wanes off after some time and given their reduced level of protection against mutation strains of the virus, the calls for boosters and second boosters signal the need for continuous vaccination for the foreseeable future. As Malaysia transitions into the endemic phase, the nation's ability to co-exist with the virus in the endemic phase will hinge on people's continuance intention to be vaccinated against the virus. Adapting the expectations confirmation model (ECM) to the public health context and in a developing country, this study integrates the ECM with the health belief model (HBM) and the theory of reasoned action (TRA) to examine the inter-relationships of the predictors of people's continuance intention to vaccinate against COVID-19.

    METHODOLOGY: Data were collected using self-administered questionnaires from 1,914 respondents aged 18 and above by a marketing consulting firm via its online panel. The partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the data.

    RESULTS: Out of the 1,914 respondents, 55.9% reported having a continuance intention to vaccinate against COVID-19, similar to other developing countries. The multivariate analysis revealed that perceived usefulness and satisfaction significantly influenced individuals' continuance intention to vaccinate against COVID-19. Additionally, attitude was found to play a key role in influencing behavioral change among individuals towards their perceptions of continuously getting vaccinated against COVID-19.

    CONCLUSIONS: By integrating three theoretical frameworks (i.e., HBM, TRA and ECM), this study showed that behavioral characteristics could provide insights towards continuance vaccination intention. Hence, policymakers and key stakeholders can develop effective public health strategies or interventions to encourage vaccine booster uptake by targeting behavioral factors such as perceived usefulness, attitude, satisfaction, and subjective norms.

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