Confirmatory Factor Analysis of Knowledge, Attitude, and Behaviour Questionnaire towards Oral Health among Indian Adults

Selvaraj, Siddharthan; Naing, Nyi Nyi; Wan-Arfah, Nadiah; Prasadh, Somasundaram

doi:10.3390/jpm11040320

Cited by 13 publications

(18 citation statements)

References 27 publications

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“…Furthermore, confirmatory factor analysis of our questionnaire had ideal goodness of fit values and had good convergent and discriminant validity. The results of our confirmatory factor analysis had statistically significant values [1]. The questionnaire took nearly 5 to 10 min to complete.…”

Section: Ethics Approvals and Data Collection Proceduresmentioning

confidence: 66%

“…Oral diseases are considered to have a wide presence around the globe, which is associated with remarkable morbidity. The Indian population in particular have a considerable imbalance towards their oral health care [1]. Considering oral conditions among Indian adults, about 25% of adults experience mild to moderate periodontitis, on the other hand severe periodontitis is seen among 19% adults [2].…”

Section: Introductionmentioning

confidence: 99%

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Demographic and Habitual Factors of Periodontal Disease among South Indian Adults

Selvaraj

Naing

Wan-Arfah

et al. 2021

IJERPH

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The aim of this study was to evaluate the performance of a set of sociodemographic and habits measures on estimating periodontal disease among south Indian adults. This cross-sectional study was carried out among 288 individuals above 18 years old in Tamil Nadu, India. The outcome of the study was periodontal disease, measured by WHO criteria. The covariates were age, ethnicity, smoking and alcohol habit. The assessment of factors predicting periodontal disease was carried out by multiple logistic regression analysis using R version 3.6.1. The demographic factors like age group (AOR = 3.56; 95% CI 1.69–7.85), ethnicity (AOR = 6.07; 95% CI 2.27–18.37), non-alcoholic (AOR = 0.31; 95% CI 0.13–0.64) and non-smoking (AOR = 0.33; 95% CI 0.15–0.67) were found to be associated with the outcome. The maximum log likelihood estimate value was −30.5 and AIC was 385 for the final model, respectively. Receiver operating characteristic (ROC) curve for the periodontal disease was 0.737. We can conclude that sociodemographic factors and habits were useful for predicting periodontal diseases.

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Section: Ethics Approvals and Data Collection Proceduresmentioning

confidence: 66%

Section: Introductionmentioning

confidence: 99%

Demographic and Habitual Factors of Periodontal Disease among South Indian Adults

Selvaraj

Naing

Wan-Arfah

et al. 2021

IJERPH

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“…Furthermore, confirmatory factor analysis of our oral health KAB questionnaire had ideal goodness-of-fit values and had good convergent and discriminant validity. The results of our confirmatory factor analysis had statistically significant values [14].…”

Section: Content Of the Questionnairementioning

confidence: 60%

“…The interval of samples was obtained by dividing the total size of the population by the desired sample size needed for the study. Based on a recommendation by Selvaraj et al, sample size was estimated in our study [14]. The participants resided in a residential community in Chennai, and those who fulfilled the inclusion criteria were considered.…”

Section: Methodsmentioning

confidence: 99%

“…Data collection was done by utilizing proper protective equipment like a face mask, face shield, and SOP guidelines given by the health department of Tamil Nadu government was followed in a rightful manner. Then, the individuals were asked to answer the validated questionnaire [14]. It took nearly 10 minutes to complete the questionnaire.…”

Section: Data Collection Proceduresmentioning

confidence: 99%

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Assessment on Oral Health Knowledge, Attitude, and Behaviour and its Association with Sociodemographic and Habitual Factors of South Indian Population

Selvaraj¹,

Naing²,

Wan-Arfah³

et al. 2021

Pesqui. Bras. Odontopediatria Clín. Integr.

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Objective: To assess the oral health knowledge, attitude, behaviour, and its association with sociodemographic and habitual factors among South Indian Population. Material and Methods: A total of 288 adults living in a residential community situated in Chennai were selected by systematic random sampling method participated in this cross-sectional study. Data collection was carried out using a validated questionnaire. Results: About 97.9% of the participants in our study had good knowledge, 33.3% had a positive attitude and 48.2% had adequate oral health behaviour. Sociodemographic and habitual factors like diet (p=0.006), education (p=0.009), and employment (p=0.003) were significantly associated with knowledge. On the other hand, diet (p=0.012) was the only factor significantly associated with attitude. Ownership of house (p= 0.030) was significantly associated with behaviour and no factor was associated with all three KAB profiles. Absence of correlation were identified between Knowledge-Attitude (r=0.11, p=0.23), Knowledge-Behaviour (r= -0.037, p= 0.68) and Attitude-Behaviour (r =0.01, p=0.94). Conclusion: It has been found a massive number of participants possessed a high knowledge level towards oral health. On the other hand, less than half of the participants had a positive attitude and adequate behaviour towards oral health. No positive linear correlation was seen among knowledge, attitude, and behaviour towards oral health.

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Oprea¹,

Bârã²,

Jin³

et al. 2023

Education, Research and Business Technologies

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Confirmatory Factor Analysis of Knowledge, Attitude, and Behaviour Questionnaire towards Oral Health among Indian Adults

Cited by 13 publications

References 27 publications

Demographic and Habitual Factors of Periodontal Disease among South Indian Adults

Demographic and Habitual Factors of Periodontal Disease among South Indian Adults

Assessment on Oral Health Knowledge, Attitude, and Behaviour and its Association with Sociodemographic and Habitual Factors of South Indian Population

Sustainable Communities with Smart Meters. A Statistical Measurement Model to Cope with Electricity Consumers’ Behavior

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