The Effect of Educational Intervention Based on the Health Belief Model on Medication Adherence among Patients with Diabetes Referred to a Diabetes Center in Zarand, Kerman

Background: Medication adherence in patients with diabetes is one of the main factors in diabetic patients care. The aim of this study was to investigate the effect of educational intervention based on the Health Belief Model (HBM) on medication adherence in patients with diabetes referred to a diabetes center in Zarand, Iran, in 2014. Methods: This quasi-experimental study was performed on 100 patients with diabetes. The patients were divided into two groups (intervention and control). Data were collected using a researcher-made questionnaire including demographic variables, constructs of HBM, and the Morisky self-report questionnaire. The intervention group were divided into 5 groups including 8-12 patients, and according to the HBM, education was performed in four 60-90 minute sessions during one month. One month after the intervention, data were collected again and analyzed using descriptive statistics, linear regression, and Mann–Whitney U test. Results: There was a significant difference in mean score of knowledge, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, perceived efficacy, and cues to action between intervention and control groups after the intervention. Medication adherence was significantly related to the level of education (P=0.006). Among constructs of HBM, perceived self-efficiency was the strongest predicting factor (P=0.03). After the intervention, the mean scores of perceived sensitivity (P<0.001), perceived severity (P<0.001), perceived benefits (P<0.001), perceived barriers (P<0.001), perceived self-efficiency (P<0.0001), cue to action (P<0.0001), and medication adherence (P<0.0001) increased significantly. Conclusion: Education based on the HBM was effective in increasing adherence to medical instructions in patients with type 2 diabetes

Effective Factors on Oral Health-Promoting Behaviors among Elementary School Students Based on BASNEF Model

Effective Factors on Oral Health-Promoting Behaviors among Elementary School Students Based on BASNEF Model Naseri Pour Takallo Zohreh1, Ahmadi Tabatabaei Seyed Vahid2, Zolala Farzaneh3, Mohseni Mohabbat4* 1. Msc Student, Department of Health Education and Health Promotion, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran. 2. Assistant Professor, Research Center for Social Determinants of Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran. 3. Associate Professor , Research Center for Modeling in Health, Institute of Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran 4. Assistant Professor, Social Determinants of Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran *Correspondence: Department of Health Education and Health Promotion, Health School, Kerman University of Medical Sciences, Haft-Bagh Road , Kerman, Iran. Email: [email protected] Tel: 03431325098 Fax: 03431325094 Abstract: Introduction: Oral diseases are the most common diseases in the world, and among them, tooth decay is the most common problem. The aim of this study was to determine the effective factors on oral health-promoting behaviors among elementary school students of Baft based on BASNEF Model in 2015. Methods: This cross-sectional descriptive-analytical study was conducted on 200 elementary school students who were selected using multistage random sampling method. Data were collected using a researcher-made questionnaire including 62 questions consisted of two parts: demographic information and constructs of BASNEF model (attitude, subjective norms, behavioral intention, enabling factors, and behaviors). Data were analyzed using SPSS 16. Results: Score of oral health-promoting behaviors in 74% of the students was moderate and in 20% of the students was good. Statistically significant relationship was observed between oral health-promoting behaviors of the students and class grades (P=0.004), mother's education (P=0.004), father's education (P=0.034), and father's occupation (P=0.007). Among the constructs of BASNEF model, enabling factors (β=0.511) and then behavioral intentions (β=0.426) were the strongest predicting factors of oral health behavior. Conclusion: According to the obtained results, enabling factors were the most effective constructs of oral health-promoting behaviors; therefore, oral health promoters are recommended to focus on this issue. Key¬words: Health Promotion, Oral Health, Students, BASNEF Model Citation: Naseri Pour Takallo Z, Ahmadi Tabatabaei SV, Zolala F, Mohseni M. Effective Factors on Oral Health-Promoting Behaviors among Elementary School Students Based on BASNEF Model. Journal of Health Based Research 2016; 2(3): 259-273

Breast Self – examination Predictors based on Precede Model: a study on female active health volunteers in Zarand City

Background & Objectives: Breast cancer is still the most common malignancy leading to women mortality worldwide and late diagnosis of breast cancer is still one of the main causes of death in affected women. One of the ways of early detection of breast cancer is breast self – examination. The aim of this study was to determine predicting factors of breast self - examination in female active health volunteers of Zarand/ Iran based on Precede model. Methods: In this descriptive- analytical study, all participants of active heath volunteer program in health centers of zarand (110 women) were recruited. Data were collected using a researcher – made questionnaire consisted of two sections of demographic information and constructs of Precede model. Data were analyzed through SPSS22 and by using descriptive statistics (distribution and central tendency, frequency and percent) and analytic statistics (logistic regression). Results: Mean age of participants was 37.76 ± 9.75 years and 81.8 % of them were married. Among Precede constructs, predisposing factors (self-efficacy: OR=1.46 and knowledge: OR=1.30) had the highest predicting role. Performing breast self - examination showed significant relationship with level of education (OR=0.01), family history of breast cancer (OR=0.02) and marital status (OR=0.04). Conclusion: Since predisposing factors were the most important predicting factors for breast - self-examination, in planning health education programs, more attention should be paid to improving women's self - efficacy and increasing their awareness about breast self – examination. Key¬words: Breast Self - Examination, Precede Model, Predicting, Health Volunteers Citation: Khaleghi Mahani H, Fadakar MM, Ahmadi Tabatabaei SV, Mirzai M, Poursharifei A. Breast Self – examination Predictors based on Precede Model: a study on female active health volunteers in Zarand City. Journal of Health Based Research 2017; 3(1): 71-85

Short-term effect of two education methods on oral health among hearing impairment children

BACKGROUND AND AIM: Poor oral health among children with impaired hearing has been reported frequently due to lack of communication skills and effective health educations. In this study, we assessed the effect of two training methods on short-term oral health outcomes among children with impaired hearing. METHODS: In this experimental study, 80 hearing impairment (HI) student aged 7-19 years old were randomized into two groups, one group watched a guided training video and the other group was educated by a dental model. The training sessions were weekly and continued for 1 month. A trained dentist examined all participants using O’Leary plaque index (PI) at baseline, 1-month, and 3-month visits. RESULTS: At baseline, the difference between the mean O’Leary PI in the video training and dental model training groups was not significant (34.3% vs. 35.6%). In the video training group, sharp decrease was seen at the 1-month visit (reinforcement periods), i.e., 18.7% (P = 0.001), followed by a slight increase at the 3-month visit (non-reinforcement periods), i.e., 19.1% (P = 0.100), respectively. On the other hand, in the dental model, a decreasing trend was seen 24.7% at 1-month (reinforcement periods) and 19.9% (P = 0.001) at 3-month visits (non-reinforcement periods). Overall, there were no significant differences between the two methods of training (P = 0.300). CONCLUSION: Both video and dental model effectively improve the oral health of children with HI in short term. Continuous school-based oral health education programs, particularly for HI children, need to be considered. KEYWORDS: Hearing Impairment; Plaque Index; Oral Health; Educatio

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Predicting of Factors influencing physical activity in women for the prevention of osteoporosis according the Precede Model

Introduction: Osteoporosis is the most common metabolic bone disease which is nowadays known as a public health problem. Physical activity to maintain healthy bones is an important factor in preventing osteoporosis. The aim of this study was to determine a model for predicting factors influencing physical activity among women for the prevention of osteoporosis according to the Precede Model in Kerman, Iran. Method: This cross-sectional analytical descriptive study was performed on 120 women referred to health centers of Kerman city during 2014. They were selected randomly through multi- stages sampling method. Data were collected using the International Physical Activity Questionnaire (IPAQ) and a self-administrated questionnaire according to constructs of the PRECEDE Model (Predisposing Reinforcing, and Enabling Factors) andanalyzed by descriptive statistics (measures of central tendency, dispersion, frequency and percent) and analysis statistics (logistic regression, Pearson correlation) using SPSS software version 18. Results: The results showed thatthe mean age of the participants were 32.44 ± 6.97 years. 29.2% of women had intense, 5.35% moderate, and 7.66% mild physical activity. The results also indicated that enabling factors was the most predictive factors of physical activity both in raw (P=0.023, OR=1/122) and adjusted models (P=0.041, OR=1/137). Conclusion: As enabling factors were the most important predictive factor for physical activity, it is recommended that health promotion interventions be planned according to these factors to improve physical activity and prevent osteoporosis mong women. Key­words: Predicting, Physical Activity, Osteoporosis, Women, Precede Model Citation: Tabasinejad N, Ahmadi Tabatabaei S­V, Khanjani N, Mohseni M. Predicting Factors Influencing Physical Activity in Women for thePrevention of Osteoporosis According to the Precede Model. Journal of Health Based Research 2015 1(2): 155-166

Breast Self – examination Predictors based on Precede Model: a study on female active health volunteers in Zarand City

Background & Objectives: Breast cancer is still the most common malignancy leading to women mortality worldwide and late diagnosis of breast cancer is still one of the main causes of death in affected women. One of the ways of early detection of breast cancer is breast self – examination. The aim of this study was to determine predicting factors of breast self - examination in female active health volunteers of Zarand/ Iran based on Precede model. Methods: In this descriptive- analytical study, all participants of active heath volunteer program in health centers of zarand (110 women) were recruited. Data were collected using a researcher – made questionnaire consisted of two sections of demographic information and constructs of Precede model. Data were analyzed through SPSS22 and by using descriptive statistics (distribution and central tendency, frequency and percent) and analytic statistics (logistic regression). Results: Mean age of participants was 37.76 ± 9.75 years and 81.8 % of them were married. Among Precede constructs, predisposing factors (self-efficacy: OR=1.46 and knowledge: OR=1.30) had the highest predicting role. Performing breast self - examination showed significant relationship with level of education (OR=0.01), family history of breast cancer (OR=0.02) and marital status (OR=0.04). Conclusion: Since predisposing factors were the most important predicting factors for breast - self-examination, in planning health education programs, more attention should be paid to improving women's self - efficacy and increasing their awareness about breast self – examination. Keywords: Breast Self - Examination, Precede Model, Predicting, Health Volunteers Citation: Khaleghi Mahani H, Fadakar MM, Ahmadi Tabatabaei SV, Mirzai M, Poursharifei A. Breast Self – examination Predictors based on Precede Model: a study on female active health volunteers in Zarand City. Journal of Health Based Research 2017; 3(1): 71-85

Short-term effect of two education methods on oral health among hearing impairment children

BACKGROUND AND AIM: Poor oral health among children with impaired hearing has been reported frequently due to lack of communication skills and effective health educations. In this study, we assessed the effect of two training methods on short-term oral health outcomes among children with impaired hearing. METHODS: In this experimental study, 80 hearing impairment (HI) student aged 7-19 years old were randomized into two groups, one group watched a guided training video and the other group was educated by a dental model. The training sessions were weekly and continued for 1 month. A trained dentist examined all participants using O’Leary plaque index (PI) at baseline, 1-month, and 3-month visits. RESULTS: At baseline, the difference between the mean O’Leary PI in the video training and dental model training groups was not significant (34.3% vs. 35.6%). In the video training group, sharp decrease was seen at the 1-month visit (reinforcement periods), i.e., 18.7% (P = 0.001), followed by a slight increase at the 3-month visit (non-reinforcement periods), i.e., 19.1% (P = 0.100), respectively. On the other hand, in the dental model, a decreasing trend was seen 24.7% at 1-month (reinforcement periods) and 19.9% (P = 0.001) at 3-month visits (non-reinforcement periods). Overall, there were no significant differences between the two methods of training (P = 0.300). CONCLUSION: Both video and dental model effectively improve the oral health of children with HI in short term. Continuous school-based oral health education programs, particularly for HI children, need to be considered