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1.
Medicine (Baltimore) ; 99(38): e22190, 2020 Sep 18.
Article in English | MEDLINE | ID: mdl-32957346

ABSTRACT

Researchers seek to identify optimal journals for submission based on their studies but tend to rely on journal impact factors or scientific journal rankings. We investigated research trends by selecting high-frequency words from author keywords (AKs), analyzing subject areas, and performing quantitative data analysis of Korean dental journals. Consequently, we suggest a method for choosing journals that fit a specific subject area.We used a corpus of 9 Korean dentistry journals regarded in Korea as quality internationally approved journals. AKs occurring more than 10 times were assigned to Medical Subject Headings (MeSH) terms and subcategories, which were then categorized using the MeSH tree structure. KnowledgeMatrix Plus and VOSviewer were used to analyze network relationships, density, and clustering.The AKs were of 7527 types, 15,960 terms, and formed 54 clusters. The AKs with 10+ occurrence were 199 types, 4289 terms, and formed 9 clusters. Assigning the AKs with 10+ occurrence to MeSH terms led to expanding 732 types of AK terms into 249 types with 9 clusters and 4268 links. Core study areas over the past 10 years were facial asymmetry, a topic under oral surgery and medicine, and orthognathic surgery focused on mandibular fractures, followed by shear bond strength of zirconia. Analyzing 16 MeSH subject categories, we found that the "analytical, diagnostic and therapeutic techniques and equipment" category had the largest distribution of AKs (40.7%). This was followed by "diseases" (21.2%) and "anatomy" (14.90%). The orthognathic surgery cluster was the largest, followed by the shear bond strength cluster. Dental implants is a core area with strong links to high-occurrence words, such as cone-beam computed tomography and mandible, which were distributed in the order of The Journal of Advanced Prosthodontics (37.8%) and Journal of Periodontal & Implant Science (30.6%). Five clusters were closely packed in the center, 2 clusters were formed above the center, 1 cluster was formed below the center, and a cluster on the right was widespread.Cluster analysis using AKs and MeSH may be a good analytic method for researchers to determine expanding research areas and select optimal journals for paper submission.


Subject(s)
Bibliometrics , Dentistry , Medical Subject Headings , Periodicals as Topic , Republic of Korea
2.
Community Ment Health J ; 56(5): 915-924, 2020 07.
Article in English | MEDLINE | ID: mdl-32020386

ABSTRACT

This cross-sectional and descriptive study aimed to investigate factors that affected the happiness of rural residents. The study used a convenience sample consisting of 1029 Korean rural residents from the Gyeong-gi Province collected between November and December 2014. The results found that people aged 60 and over were happier than those between 15 and 19 years old. Happiness was correlated with age, income, violence, social support, subjective health, depression, and suicidal ideation. Factors affecting the happiness of rural residents were depression, social support, suicidal ideation, and age, and these factors explained 48.0% of the variance in happiness. The results demonstrate that the happiness of rural residents was affected by various psychological factors and supportive intervention should be developed to enhance the happiness of people living in rural areas.


Subject(s)
Happiness , Suicidal Ideation , Aged , Cross-Sectional Studies , Depression/epidemiology , Humans , Middle Aged , Risk Factors , Rural Population , Social Support
3.
Medicine (Baltimore) ; 98(26): e16060, 2019 Jun.
Article in English | MEDLINE | ID: mdl-31261513

ABSTRACT

The purpose of this study was to investigate the association between objectively-measured lifestyle factors and health factors in patients with knee osteoarthritis (OA).In this cross-sectional study, 52 patients with knee OA were examined. Lifestyle factors were measured using a wearable smartwatch (step counts, walking distance, calorie consumption, sleep hours) and by self-report (eating speed). Body mass index (BMI), waist circumference, blood pressure, muscle strength of knee extensor and hip abductor, knee pain, symptoms, daily living function, sports recreation function, quality of life by knee injury and OA outcome score (KOOS) were measured to obtain data on health factors. Correlations and regression analysis were used to analyze the relationship between lifestyle factors and health factors.KOOS subscales (pain, symptom, daily living function) and hip abductor strength were positively correlated with daily step count, which was the only independently contributing lifestyle factor. Additionally, knee pain duration and diastolic blood pressure were negatively correlated with daily step count. BMI and waist circumference showed no correlation with physical activity data, but were negatively correlated with sleep duration and eating speed.The findings of this study contribute to expanding the knowledge on how lifestyle habits of older patients with knee OA contribute to their health status. Daily step counts were associated with knee OA-related pain, symptom, function in daily living, duration of knee pain, blood pressure, and strength of hip abductor. BMI and waist circumference were associated with sleep duration and eating speed.


Subject(s)
Health Status , Life Style , Osteoarthritis, Knee/epidemiology , Accelerometry , Aged , Arthralgia/epidemiology , Arthralgia/etiology , Arthralgia/physiopathology , Blood Pressure , Body Mass Index , Case-Control Studies , Cross-Sectional Studies , Exercise , Feeding Behavior , Female , Humans , Male , Middle Aged , Muscle Strength , Osteoarthritis, Knee/complications , Osteoarthritis, Knee/physiopathology , Sleep , Waist Circumference
4.
Clin Nutr Res ; 7(4): 291-296, 2018 Oct.
Article in English | MEDLINE | ID: mdl-30406058

ABSTRACT

I determined whether water consumption reduces energy intake and affects satiety in non-obese young adults. The final subjects consisted of 15 individuals (8 women and 7 men) with average ages of 26.4 and 23.5 years for women and men, respectively. When subjects drank water before eating a test meal, they ate a lower amount of the test meal compared to eating test meals under waterless and postload water conditions (preload water: 123.3 g vs. waterless: 161.7 g or postload water: 163.3 g, p < 0.05). Water consumption after eating a test meal did not affect energy intake. When the subjects drank water before eating a test meal, despite consuming a lower amount, the subjects did not feel significantly less satiety than eating meals under waterless or postload water conditions. The finding that pre-meal water consumption led to a significant reduction in meal energy intake in young adults suggests that pre-meal water consumption may be an effective weight control strategy, although the mechanism of action is unknown.

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