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  1. Akram A, Fuadfuad MD, Malik AM, Nasir Alzurfi BM, Changmai MC, Madlena M
    J Adv Med Educ Prof, 2017 Apr;5(2):67-72.
    PMID: 28367462
    INTRODUCTION: MICAP is a new notation in which the teeth are indicated by letters (I-incisor, C-canine, P-premolar, M-molar) and numbers [1,2,3] which are written superscript and subscript on the relevant letters. FDI tooth notation is a two digit system where one digit shows quadrant and the second one shows the tooth of the quadrant. This study aimed to compare the short term retention of knowledge of two notation systems (FDI two digit system and MICAP notation) by lecture method.

    METHODS: Undergraduate students [N=80] of three schools participated in a cross-over study. Two theory-driven classroom based lectures on MICAP notation and FDI notation were delivered separately. Data were collected using eight randomly selected permanent teeth to be written in MICAP format and FDI format at pretest (before the lecture), post-test I (immediately after lecture) and post-test II (one week after the lecture). Analysis was done by SPSS version 20.0 using repeated measures ANCOVA and independent t-test.

    RESULTS: The results of pre-test and post-test I were similar for FDI education. Similar results were found between post-test I and post-test II for MICAP and FDI notations.

    CONCLUSION: The study findings indicated that the two notations (FDI and MICAP) were equally mind cognitive. However, the sample size used in this study may not reflect the global scenario. Therefore, we suggest more studies to be performed for prospective adaptation of MICAP in dental curriculum.

  2. Marzo RR, Chen HWJ, Abid K, Chauhan S, Kaggwa MM, Essar MY, et al.
    Front Public Health, 2022;10:998272.
    PMID: 36187682 DOI: 10.3389/fpubh.2022.998272
    BACKGROUND: Misinformation has had a negative impact upon the global COVID-19 vaccination program. High-income and middle-income earners typically have better access to technology and health facilities than those in lower-income groups. This creates a rich-poor divide in Digital Health Literacy (DHL), where low-income earners have low DHL resulting in higher COVID-19 vaccine hesitancy. Therefore, this cross-sectional study was undertaken to assess the impact of health information seeking behavior on digital health literacy related to COVID-19 among low-income earners in Selangor, Malaysia.

    METHODS: A quantitative cross-sectional study was conducted conveniently among 381 individuals from the low-income group in Selangor, Malaysia. The remote data collection (RDC) method was used to gather data. Validated interviewer-rated questionnaires were used to collect data via phone call. Respondents included in the study were 18 years and older. A normality of numerical variables were assessed using Shapiro-Wilk test. Univariate analysis of all variables was performed, and results were presented as means, mean ranks, frequencies, and percentages. Mann-Whitney U test or Kruskal Wallis H test was applied for the comparison of DHL and health information seeking behavior with characteristics of the participants. Multivariate linear regression models were applied using DHL as dependent variable and health information seeking behavior as independent factors, adjusting for age, gender, marital status, educational status, employment status, and household income.

    RESULTS: The mean age of the study participants was 38.16 ± 14.40 years ranging from 18 to 84 years. The vast majority (94.6%) of participants stated that information seeking regarding COVID-19 was easy or very easy. Around 7 percent of the respondents cited reading information about COVID-19 on the internet as very difficult. The higher mean rank of DHL search, content, reliability, relevance, and privacy was found among participants who were widowed, had primary education, or unemployed. An inverse relationship was found between overall DHL and confidence in the accuracy of the information on the internet regarding COVID-19 (β = -2.01, 95% CI = -2.22 to -1.79).

    CONCLUSION: It is important to provide support to lower-income demographics to assist access to high-quality health information, including less educated, unemployed, and widowed populations. This can improve overall DHL.

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