Psychological Distress, Dental Health, and Dental Fear among Finnish University Students: A National Survey

The aim of this study was to study the association between dental fear, psychologicaldistress, and perceived symptoms of teeth controlled for age, gender, educational sector, andtobacco use. The data from the Finnish University Student Health Survey 2016 targeting students (n= 10,000) of academic universities and universities of applied sciences were used.  Psychologicaldistress was measured with the Clinical Outcomes in Routine Evaluation 10 (CORE-10) and the GeneralHealth Questionnaire 12 (GHQ-12) and dental fear with the question ‘Do you feel scared aboutreceiving dental care?’. The study included 3110 students. In logistic regression analyses thosewith psychological distress (measured with CORE-10 and GHQ-12) and those reporting teeth-relatedsymptoms were more likely than their counterparts to have high dental fear.  In gender-specificanalyses men with psychological distress (measured with CORE-10) and women with teeth-relatedsymptoms were more likely to have high levels of dental fear.  Finnish university students withpsychological distress and teeth-related symptoms were more likely to experience higher levels ofdental fear than their counterparts were.  The results of this study support possible commonvulnerability factors that dental fear and other psychological disorders may share.</p

Association between dental fear and eating disorders and Body Mass Index among Finnish university students: a national survey

Background: Little is known about the association between eating disorders (ED) and dental fear. This study inves- tigated the association between dental fear and EDs through body mass index (BMI), and SCOFF (sick, control, one stone, fat, food) questionnaire among Finnish university students. We hypothesised that dental fear is associated with EDs and BMI.Methods:  We used the latest data from the Finnish University Student Health Survey 2016. This survey targeted undergraduate Finnish students (n     10,000) of academic universities and universities of applied sciences. We enquired about e.g. age, gender, height, weight, educational sector and perceived mental well-being. We used the SCOFF questionnaire to assess those at risk for developing EDs. The question ‘Do you feel scared about dental care?’ enquired about dental fear. We used the chi-square test and gender-specific logistic regression to analyse the associations between dental fear, EDs and BMI controlling for age, educational sector and mental well-being.Results:  In total, 3110 students participated in the study. Overall 7.2% of the students reported high dental fear and 9.2% scored SCOFF positive; more women than men reported high dental fear (11.2% vs. 3.8%, pthe association between dental fear and EDs and BMI. Among females, when controlling for educational sector and BMI, those with positive SCOFF score were more likely to have high dental fear than those with negative SCOFF score (OR 1.6; CI 1.0–2.4). After adding perceived mental well-being to the gender-specific regression analyses, overweight and obese males, BMI ≥ 25 (OR 2.4; CI 1.3–4.4) and females with poor to moderate mental well-being (OR 2.1; CI 1.4–2.9) were more likely than their counterparts to have high dental fear.Conclusions:  Among the Finnish university students BMI in males and problems of mental well-being in females were positively associated with high dental fear. The results of this study support possible common vulnerability factors that dental fear and other psychological disorders may share.</p

Shape and gray level descriptors for surface defect image retrieval and classification

Nowadays, the problem of image retrieval and classification plays an important role in the fields of image analysis and pattern recognition. With an increasing amount of real-world image data to be processed and stored, the development of powerful retrieval tools has also become a central problem in various industrial machine vision applications. The goal of finding similar objects from large and often distributed image collections is shared by the developers and users of machine vision systems. The focus of this thesis is on the field of surface defect imaging that has been applied to paper and metal manufacturing. Current surface inspection systems are capable of detecting various defects and producing gray level images of them. The defect images are collected into large image databases. Effective retrieval and classification methods are necessary to analyze the defects stored in the database. The goal of this thesis is to present visual descriptors that characterize the defect shape and gray level distribution. The majority of the methods presented consider the shape using Fourier description of the boundary line of the defect. For this kind of shape description, novel Fourier-based approaches are presented. These approaches add a multiresolution property to conventional Fourier shape descriptors. This is achieved by combining discrete wavelet transform with discrete Fourier transform in shape description. Another approach to multiresolution shape description uses boundary smoothing combined with Fourier shape description. In addition, a method to combine defect boundary with defect s gray level information in Fourier description is presented. The gray level distribution of a defect image is described using binary co-occurrence matrix that outperforms commonly used second order statistical measures in defect image retrieval. The proposed shape descriptors provide a significant improvement over the conventional Fourier shape description of the defects. The experimental results reveal that retrieval accuracy can be easily improved by using the proposed multiscale Fourier descriptors. The descriptors which use a combination of defect shape and gray level provide a novel method that is capable of improving retrieval performance without increasing descriptor dimensionality

Shape and gray level descriptors for surface defect image retrieval and classification

Nowadays, the problem of image retrieval and classification plays an important role in the fields of image analysis and pattern recognition. With an increasing amount of real-world image data to be processed and stored, the development of powerful retrieval tools has also become a central problem in various industrial machine vision applications. The goal of finding similar objects from large and often distributed image collections is shared by the developers and users of machine vision systems. The focus of this thesis is on the field of surface defect imaging that has been applied to paper and metal manufacturing. Current surface inspection systems are capable of detecting various defects and producing gray level images of them. The defect images are collected into large image databases. Effective retrieval and classification methods are necessary to analyze the defects stored in the database. The goal of this thesis is to present visual descriptors that characterize the defect shape and gray level distribution. The majority of the methods presented consider the shape using Fourier description of the boundary line of the defect. For this kind of shape description, novel Fourier-based approaches are presented. These approaches add a multiresolution property to conventional Fourier shape descriptors. This is achieved by combining discrete wavelet transform with discrete Fourier transform in shape description. Another approach to multiresolution shape description uses boundary smoothing combined with Fourier shape description. In addition, a method to combine defect boundary with defect s gray level information in Fourier description is presented. The gray level distribution of a defect image is described using binary co-occurrence matrix that outperforms commonly used second order statistical measures in defect image retrieval. The proposed shape descriptors provide a significant improvement over the conventional Fourier shape description of the defects. The experimental results reveal that retrieval accuracy can be easily improved by using the proposed multiscale Fourier descriptors. The descriptors which use a combination of defect shape and gray level provide a novel method that is capable of improving retrieval performance without increasing descriptor dimensionality

Psychological distress, dental health, and dental fear among Finnish university students:a national survey

Abstract The aim of this study was to investigate the association between dental fear, psychological distress, and perceived symptoms of teeth controlled for age, gender, educational sector, and tobacco use. The data from the Finnish University Student Health Survey 2016 targeting students (n = 10,000) of academic universities and universities of applied sciences were used. Psychological distress was measured with the Clinical Outcomes in Routine Evaluation 10 (CORE-10) and the General Health Questionnaire 12 (GHQ-12) and dental fear with the question ‘Do you feel scared about receiving dental care?’. The study included 3110 students. In logistic regression analyses those with psychological distress (measured with CORE-10 and GHQ-12) and those reporting teeth-related symptoms were more likely than their counterparts to have high dental fear. In gender-specific analyses men with psychological distress (measured with CORE-10) and women with teeth-related symptoms were more likely to have high levels of dental fear. Finnish university students with psychological distress and teeth-related symptoms were more likely to experience higher levels of dental fear than their counterparts were. The results of this study support possible common vulnerability factors that dental fear and other psychological disorders may share

Association between dental fear and eating disorders and Body Mass Index among Finnish university students:a national survey

Abstract Background: Little is known about the association between eating disorders (ED) and dental fear. This study investigated the association between dental fear and EDs through body mass index (BMI), and SCOFF (sick, control, one stone, fat, food) questionnaire among Finnish university students. We hypothesised that dental fear is associated with EDs and BMI. Methods: We used the latest data from the Finnish University Student Health Survey 2016. This survey targeted undergraduate Finnish students (n = 10,000) of academic universities and universities of applied sciences. We enquired about e.g. age, gender, height, weight, educational sector and perceived mental well-being. We used the SCOFF questionnaire to assess those at risk for developing EDs. The question ‘Do you feel scared about dental care?’ enquired about dental fear. We used the chi-square test and gender-specific logistic regression to analyse the associations between dental fear, EDs and BMI controlling for age, educational sector and mental well-being. Results: In total, 3110 students participated in the study. Overall 7.2% of the students reported high dental fear and 9.2% scored SCOFF positive; more women than men reported high dental fear (11.2% vs. 3.8%, p &lt; 0.001) and scored positive on SCOFF (14.2% vs. 3.6%, p &lt; 0.001). Gender modified the association between dental fear and EDs and BMI. Among females, when controlling for educational sector and BMI, those with positive SCOFF score were more likely to have high dental fear than those with negative SCOFF score (OR = 1.6; CI = 1.0–2.4). After adding perceived mental well-being to the gender-specific regression analyses, overweight and obese males, BMI ≥ 25 (OR = 2.4; CI 1.3–4.4) and females with poor to moderate mental well-being (OR = 2.1; CI 1.4–2.9) were more likely than their counterparts to have high dental fear. Conclusions: Among the Finnish university students BMI in males and problems of mental well-being in females were positively associated with high dental fear. The results of this study support possible common vulnerability factors that dental fear and other psychological disorders may share

On the formation mechanism of impurity–helium solids: evidence for extensive clustering

Optical emission studies on a discharged nitrogen-helium gas jet injected into superfluid helium near 1.5 K are described. The analysis of atomic (a-group) and molecular Vegard-Kaplan transitions clearly indicates that the emitting species are embedded in the nitrogen clusters. The formation of the clusters is most efficient in the crater formed on the liquid surface. The model calculations based on the classical bubble model and density functional theory suggest that under the experimental conditions only clusters consisting of more than 1000 molecules have a kinetic energy sufficient for the stable cavity formation inside liquid helium. The results obtained suggest that the formation of impurity-helium solids is a consequence of extensive clustering in the gas jet