Effectiveness of educational strategies to teach evidence-based dentistry to undergraduate dental students: a systematic review.

OBJECTIVES: Evidence-based dentistry (EBD) training has been widely promoted in dental schools around the world and policymakers ask for suitable strategies to teach EBD within undergraduate dental education. The present study aims to evaluate the effectiveness of these strategies on dental students' knowledge, attitude, and skills. METHODS: PubMed, Embase, Scopus, Cochrane Central Register of Controlled Trials, and Eric databases were searched using search terms obtained from Medical Subject Headings (MeSH) terms and free text method without time restrictions, up to November 2022. The identified articles were screened based on titles and abstracts for inclusion criteria. Subsequently, relevant articles underwent data extraction. Finally, the risk of bias was assessed through Joanna Briggs Institute critical appraisal checklists. RESULTS: Twelve of 439 studies were included: nine quasi-experimental studies, two cross-sectional, and one randomized controlled trial study. Regarding the overlap among categories, six studies assessed knowledge, seven assessed attitude, and eight focused on skills or performance in EBD. Due to the heterogeneity of the interventions and results of included studies, a meta-analysis was not performed. EBD was mostly taught in small group collaborations. Interventions included lectures, workshops, seminars, small group sessions, journal clubs, online sessions, or a combination of them in various frequencies and duration. CONCLUSIONS: EBD implementation into dental curricula is improving through strategies including designing continuing and frequent dental education courses, establishing collaborative student research groups, utilizing online tools for EBD education, and dividing EBD courses into shorter modules. The systematic review protocol was registered in PROSPERO (ID: CRD42022350238).

Biallelic loss of LDB3 leads to a lethal pediatric dilated cardiomyopathy.

Autosomal dominant variants in LDB3 (also known as ZASP), encoding the PDZ-LIM domain-binding factor, have been linked to a late onset phenotype of cardiomyopathy and myofibrillar myopathy in humans. However, despite knockout mice displaying a much more severe phenotype with premature death, bi-allelic variants in LDB3 have not yet been reported. Here we identify biallelic loss-of-function variants in five unrelated cardiomyopathy families by next-generation sequencing. In the first family, we identified compound heterozygous LOF variants in LDB3 in a fetus with bilateral talipes and mild left cardiac ventricular enlargement. Ultra-structural examination revealed highly irregular Z-disc formation, and RNA analysis demonstrated little/no expression of LDB3 protein with a functional C-terminal LIM domain in muscle tissue from the affected fetus. In a second family, a homozygous LDB3 nonsense variant was identified in a young girl with severe early-onset dilated cardiomyopathy with left ventricular non-compaction; the same homozygous nonsense variant was identified in a third unrelated female infant with dilated cardiomyopathy. We further identified homozygous LDB3 frameshift variants in two unrelated probands diagnosed with cardiomegaly and severely reduced left ventricular ejection fraction. Our findings demonstrate that recessive LDB3 variants can lead to an early-onset severe human phenotype of cardiomyopathy and myopathy, reminiscent of the knockout mouse phenotype, and supporting a loss of function mechanism.

Prevalence of Early Childhood Caries and the Related Factors among 3-5- Year-Old Children in Babol, Iran.

Statement of the Problem: Regular dental checkups to diagnose early childhood caries (ECC) are critical for maintaining and improving children's oral health and well-being. The prevalence of ECC is important for planning proper oral health programs. Purpose: This study aimed to investigate the prevalence of ECC and its related factors in children aged 3 to 5 years at Babol, Iran. Materials and Method: This cross-sectional study was conducted on 280 children aged 3-5 years in the kindergartens of Babol. Children were examined for dental caries according to World Health Organization criteria. The variables such as age, gender, health, nutritional habits, parents' educational level, parents' job status, and level of dental care were recorded in the questionnaire. Data were analyzed using t-test, chi-square and ANOVA and p< 0.05 was considered significant. Results: Average decayed-missing-filled teeth (dmft) were 4.03±3.6 and 73.2% in children with ECC, while 26.8% were caries-free. A significant association was found between age, snack consumption, father's education, mother's job, nocturnal drinking milk, tooth-brushing, and a history of dental check up before age 2 with ECC. Conclusion: The results of this analysis showed a high prevalence of ECC in Babol. Therefore, educational and interventional programs in prevention and dental health care, especially for mothers, nurses, and teachers of these age groups, should be considered.

Pediatric patients' reasons for visiting dentists in all WHO regions.

BACKGROUND: Oral Function, Orofacial Pain, Orofacial Appearance, and Psychosocial Impact are the four oral health-related quality of life (OHRQoL) dimensions (4D) or areas in which oral disorders impact pediatric patients. Using their dentists' assessment, the study aimed to evaluate whether pediatric dental patients' oral health concerns fit into the 4D of the Oral Health-Related Quality of Life (OHRQoL) construct. METHODS: Dentists who treat children from 32 countries and all WHO regions were selected from a web-based survey of 1580 international dentists. Dentists were asked if their pediatric patients with current or future oral health concerns fit into the 4D of the Oral Health-Related Quality of Life (OHRQoL) construct. Proportions of all pediatric patients' oral health problems and prevention needs were computed. FINDINGS: Data from 101 dentists treating children only and 523 dentists treating children and adults were included. For 90% of pediatric patients, their current oral health problems fit well in the four OHRQoL dimensions. For 91% of oral health problems they intended to prevent in the future were related to these dimensions as well. Both numbers increased to at least 96% when experts analyzed dentists´ explanations of why some oral health problems would not fit these four categories. CONCLUSIONS: The study revealed the four fundamental components of dental patients, i.e., the four OHRQoL dimensions (Oral Function, Orofacial Pain, Orofacial Appearance, and Psychosocial Impact) are also applicable for pediatric patients, regardless of whether they have current or future oral health concerns, and should be considered when measuring OHRQoL in the pediatric dental patient population.

Why Patients Visit Dentists - A Study in all World Health Organization Regions.

OBJECTIVE: The dimensions of oral health-related quality of life (OHRQoL) Oral Function, Orofacial Pain, Orofacial Appearance, and Psychosocial Impact are the major areas where patients are impacted by oral diseases and dental interventions. The aim of this study was to evaluate whether dental patients' reasons to visit the dentist fit the 4 OHRQoL dimensions. METHODS: Dentists (N = 1580) from 32 countries participated in a web-based survey. For their patients with current oral health problems, dentists were asked whether these problems were related to teeth, mouth, and jaws' function, pain, appearance, or psychosocial impact or whether they do not fit the aforementioned 4 categories. Dentists were also asked about their patients who intended to prevent future oral health problems. For both patient groups, the proportions of oral health problems falling into the 4 OHRQoL dimensions were calculated. RESULTS: For every 100 dental patients with current oral health problems, 96 had problems related to teeth, mouth, and jaws' function, pain, appearance, or psychosocial impact. For every 100 dental patients who wanted to prevent future oral health problems, 92 wanted to prevent problems related to these 4 OHRQoL dimensions. Both numbers increased to at least 98 of 100 patients when experts analyzed dentists' explanations of why some oral health problems would not fit the four dimension. For the remaining 2 of 100 patients, none of the dentist-provided explanations suggested evidence against the OHRQoL dimensions as the concepts that capture dental patients' suffering. CONCLUSION: Oral Function, Orofacial Pain, Orofacial Appearance, and Psychosocial Impact capture dental patients' oral health problems worldwide. These 4 OHRQoL dimensions offer a psychometrically sound and practical framework for patient care and research, identifying what is important to dental patients.

Sensor fault detection in a class of nonlinear systems using modal Kalman filter.

Kalman filter and its different variants are commonly used as optimal methods for fault detection in various types of system components. In this paper, a newly introduced type of aforementioned filters, called modal Kalman filter, is extended and utilized in order to estimate the states of nonlinear systems, for sensor fault detection purposes, in a class of nonlinear certain systems. This method, in contrast to the extended Kalman filter, which employs only the linear term of Taylor expansion, retains higher-order terms; as a result, the estimation error will reduce accordingly. Practicality and effectivity of this method, and its superiority over Kalman filter, in terms of accuracy and promptness of sensor fault detection, are also verified with simulation results.

Validation and evaluation of the Mandarin version of the oral health literacy adult questionnaire in Taiwan.

OBJECTIVES: This study aimed to translate the Oral Health Literacy Adult Questionnaire into a Mandarin version (MOHL-AQ) and to examine its psychometric properties. METHODS: A methodological research using psychometric testing and evaluation of a translated instrument. A convenience sample of 402 participants from northern Taiwan were recruited for the validation of the MOHL-AQ. Internal consistency reliability, split-half reliability, inter-rater reliability, face validity, content validity, and construct validity were evaluated. RESULTS: The value of internal consistency and split-half reliability of the MOHL-AQ were 0.77 and 0.78, respectively. Content validity reported a high content validity index (CVI = 95%). Exploratory factor analysis (EFA) and parallel analysis (PA) were used to determine a unidimensional model and confirmatory factor analysis (CFA) was employed to confirm the model. The indices of good fit model were achieved at GFI = 0.93, AGFI = 0.92, RMSEA = 0.04, CFI = 0.90, PGFI = 0.73, χ2 /df = 1.86 (p < .001). Most of the item-total correlations indicated adequate and acceptable convergent validity (r > .30). CONCLUSION: MOHL-AQ demonstrates adequate psychometric properties for measuring the oral health literacy in Mandarin-speaking population. Public health nurses can use MOHL-AQ to assess oral health literacy in the community settings and further screen potential population with inadequate oral health literacy.

Comparison of the Effect of Toothbrushing Education Via Video, Lecture and Pamphlet on the Dental Plaque Index of 12-Year-Old Children.

The aim of this study was to compare the effect of different modes of toothbrushing education (lecture, video and pamphlet) on the dental plaque index (PI) of adolescents. The cluster randomized intervention was performed on 128 participants aged 12 years, who were allocated into four groups based on the type of intervention. Group 1: no intervention; and groups 2, 3, 4: education via lecture, video, and pamphlet, respectively (n = 32). Their plaque index was measured at the baseline, 24 h and two months later. Data were analyzed by repeated measures analysis of variance (ANOVA), one-way ANOVA, independent and paired t-test. The plaque indices of groups 2, 3, 4 at 24 h (p values < 0.001) and two months (p values < 0.001) showed a significant reduction when compared to the baseline. The lowest PI score was observed in the pamphlet, video and lecture groups at 24 h, respectively. After 2 months, the lowest score of PI was measured in lecture, video and pamphlet groups, respectively; however, these differences were non-significant. Therefore, toothbrushing education via lecture, video and pamphlet reduced the dental plaque index with the same effectiveness.

Emotional stress recognition using a new fusion link between electroencephalogram and peripheral signals.

BACKGROUND: This paper proposes a new emotional stress assessment system using multi-modal bio-signals. Electroencephalogram (EEG) is the reflection of brain activity and is widely used in clinical diagnosis and biomedical research. METHODS: We design an efficient acquisition protocol to acquire the EEG signals in five channels (FP1, FP2, T3, T4 and Pz) and peripheral signals such as blood volume pulse, skin conductance (SC) and respiration, under images induction (calm-neutral and negatively excited) for the participants. The visual stimuli images are selected from the subset International Affective Picture System database. The qualitative and quantitative evaluation of peripheral signals are used to select suitable segments of EEG signals for improving the accuracy of signal labeling according to emotional stress states. After pre-processing, wavelet coefficients, fractal dimension, and Lempel-Ziv complexity are used to extract the features of the EEG signals. The vast number of features leads to the problem of dimensionality, which is solved using the genetic algorithm as a feature selection method. RESULTS: The results show that the average classification accuracy is 89.6% for two categories of emotional stress states using the support vector machine (SVM). CONCLUSION: This is a great improvement in results compared to other similar researches. We achieve a noticeable improvement of 11.3% in accuracy using SVM classifier, in compared to previous studies. Therefore, a new fusion between EEG and peripheral signals are more robust in comparison to the separate signals.

Optimal Tracking Control of Unknown Discrete-Time Linear Systems Using Input-Output Measured Data.

In this paper, an output-feedback solution to the infinite-horizon linear quadratic tracking (LQT) problem for unknown discrete-time systems is proposed. An augmented system composed of the system dynamics and the reference trajectory dynamics is constructed. The state of the augmented system is constructed from a limited number of measurements of the past input, output, and reference trajectory in the history of the augmented system. A novel Bellman equation is developed that evaluates the value function related to a fixed policy by using only the input, output, and reference trajectory data from the augmented system. By using approximate dynamic programming, a class of reinforcement learning methods, the LQT problem is solved online without requiring knowledge of the augmented system dynamics only by measuring the input, output, and reference trajectory from the augmented system. We develop both policy iteration (PI) and value iteration (VI) algorithms that converge to an optimal controller that require only measuring the input, output, and reference trajectory data. The convergence of the proposed PI and VI algorithms is shown. A simulation example is used to verify the effectiveness of the proposed control scheme.

New oral health literacy instrument for public health: development and pilot testing.

AIM: The aim of the present study was to develop a functional oral health literacy (OHL) instrument for adults, including new measures of literacy skills (OHL Adults Questionnaire: OHL-AQ). METHODS: An item pool was provided, and an expert panel evaluated the items by assessing the content validity index and content validity ratio. The reliability analysis, including internal consistency and reproducibility, were examined using Cronbach's alpha coefficient and intraclass correlation coefficient (ICC). In addition a known-groups comparison was performed to assess how well the questionnaire discriminates between individuals who differ in education and brushing behavior. RESULTS: A total of 97 participants were studied. The mean age of the participants was 36.3 (standard deviation [SD] = 12.8) years; 34% had more than 12 years' formal education. Overall, 39.2% of interviewees had inadequate, 16.5% had marginal, and 44.3% had adequate OHL. The internal consistency, as measured by Cronbach's alpha, was found to be 0.72, and the ICC was 0.84. Participants who brushed more frequently had significantly higher OHL scores (P = 0.03). The association between OHL scores and years of education was also significant (P < 0.001). CONCLUSION: The OHL-AQ is a valid and reliable measure of functional OHL, with additional sections for evaluating listening and decision-making skills.

A policy iteration approach to online optimal control of continuous-time constrained-input systems.

This paper is an effort towards developing an online learning algorithm to find the optimal control solution for continuous-time (CT) systems subject to input constraints. The proposed method is based on the policy iteration (PI) technique which has recently evolved as a major technique for solving optimal control problems. Although a number of online PI algorithms have been developed for CT systems, none of them take into account the input constraints caused by actuator saturation. In practice, however, ignoring these constraints leads to performance degradation or even system instability. In this paper, to deal with the input constraints, a suitable nonquadratic functional is employed to encode the constraints into the optimization formulation. Then, the proposed PI algorithm is implemented on an actor-critic structure to solve the Hamilton-Jacobi-Bellman (HJB) equation associated with this nonquadratic cost functional in an online fashion. That is, two coupled neural network (NN) approximators, namely an actor and a critic are tuned online and simultaneously for approximating the associated HJB solution and computing the optimal control policy. The critic is used to evaluate the cost associated with the current policy, while the actor is used to find an improved policy based on information provided by the critic. Convergence to a close approximation of the HJB solution as well as stability of the proposed feedback control law are shown. Simulation results of the proposed method on a nonlinear CT system illustrate the effectiveness of the proposed approach.

Determinants of oral health: does oral health literacy matter?

Objective. To evaluate oral health literacy, independent of other oral health determinants, as a risk indicator for self-reported oral health. Methods. A cross-sectional population-based survey conducted in Tehran, Iran. Multiple logistic regression analysis served to estimate the predictive effect of oral health literacy on self-reported oral health status (good versus poor) controlling for socioeconomic and demographic factors and tooth-brushing behavior. Results. In all, among 1031 participants (mean age 36.3 (SD 12.9); 51% female), women reported brushing their teeth more frequently (P < 0.001) and scored higher for oral health literacy (mean 10.9 versus 10.2, P < 0.001). In the adjusted model, high age (OR = 1.01, 95% CI 1.003-1.034), low education (OR = 1.88, 95% CI 1.23-2.87), small living area in square meters per person (OR = 1.85, 95% CI 1.003-3.423), poor tooth brushing behavior (OR = 3.35, 95% CI 2.02-5.57), and low oral health literacy scores (OR = 1.58, 95% CI 1.02-2.45) were significant risk indicators for poor self-reported oral health. Conclusions. Low oral health literacy level, independent of education and other socioeconomic determinants, was a predictor for poor self-reported oral health and should be considered a vital determinant of oral health in countries with developing health care systems.

Artificial Neural Networks Analysis Used to Evaluate the Molecular Interactions between Selected Drugs and Human Cyclooxygenase2 Receptor.

OBJECTIVE(S): A fast and reliable evaluation of the binding energy from a single conformation of a molecular complex is an important practical task. Artificial neural networks (ANNs) are strong tools for predicting nonlinear functions which are used in this paper to predict binding energy. We proposed a structure that obtains binding energy using physicochemical molecular descriptions of the selected drugs. MATERIAL AND METHODS: The set of 33 drugs with their binding energy to cyclooxygenase enzyme (COX2) in hand, from different structure groups, were considered. 27 physicochemical property descriptors were calculated by standard molecular modeling. Binding energy was calculated for each compound through docking and also ANN. A multi-layer perceptron neural network was used. RESULTS: The proposed ANN model based on selected molecular descriptors showed a high degree of correlation between binding energy observed and calculated. The final model possessed a 27-4-1 architecture and correlation coefficients for learning, validating and testing sets equaled 0.973, 0.956 and 0.950, respectively. CONCLUSION: RESULTS show that docking results and ANN data have a high correlation. It was shown that ANN is a strong tool for prediction of the binding energy and thus inhibition constants for different drugs in very short periods of time.

Adaptive optimal control of unknown constrained-input systems using policy iteration and neural networks.

This paper presents an online policy iteration (PI) algorithm to learn the continuous-time optimal control solution for unknown constrained-input systems. The proposed PI algorithm is implemented on an actor-critic structure where two neural networks (NNs) are tuned online and simultaneously to generate the optimal bounded control policy. The requirement of complete knowledge of the system dynamics is obviated by employing a novel NN identifier in conjunction with the actor and critic NNs. It is shown how the identifier weights estimation error affects the convergence of the critic NN. A novel learning rule is developed to guarantee that the identifier weights converge to small neighborhoods of their ideal values exponentially fast. To provide an easy-to-check persistence of excitation condition, the experience replay technique is used. That is, recorded past experiences are used simultaneously with current data for the adaptation of the identifier weights. Stability of the whole system consisting of the actor, critic, system state, and system identifier is guaranteed while all three networks undergo adaptation. Convergence to a near-optimal control law is also shown. The effectiveness of the proposed method is illustrated with a simulation example.