scholarly journals The Relationship of Smartphone Addiction and Alexithymia

2021 ◽  
Author(s):  
İbrahim Gündoğmuş ◽  
Mehmet Sinan Aydın ◽  
Ayhan Algül
Keyword(s):  
Smartphone Addiction ◽  
Relationship Of ◽  
The Relationship

scholarly journals The relationship of smartphone addiction with psychological distress and neuroticism among university medical students

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Leonard Yik-Chuan Lei ◽  
Muhd Al-Aarifin Ismail ◽  
Jamilah Al-Muhammady Mohammad ◽  
Muhamad Saiful Bahri Yusoff
Keyword(s):  
Psychological Distress ◽  
Medical Students ◽  
Linear Regression ◽  
Personality Trait ◽  
Psychological Health ◽  
Smartphone Addiction ◽  
P Value ◽  
Simple Linear Regression ◽  
Relationship Of ◽  
The Relationship

Abstract Background Smartphone plays a vital role in higher education as it serves as a device with multiple functions. Smartphone addiction was reported on the rise among college and university students. The addiction may result in unwanted consequences on their academic performance and psychological health. One factor that consistently relates to psychological distress and smartphone addiction is the neurotic personality trait. This study explored the relationship of smartphone addiction with psychological health and neuroticism among USM medical students. Methods A cross-sectional study was carried out on medical students in a public medical school. DASS-21, the neuroticism-subscale of USMaP-i and SAS-SV were administered to measure psychological distress, neuroticism, and smartphone addiction of the medical students. Spearman correlation was performed to examine the correlation between smartphone addiction with psychological distress and neuroticism. Simple linear regression was performed to investigate relationship factors of smartphone addiction. Results A total of 574 medical students participated in this study. The prevalence of smartphone addiction was 40.6%. It was higher among male (49.2%) compared to female (36.6%) medical students. The result showed a fair positive correlation between smartphone addiction and psychological health (rdepression = 0.277, p-value < 0.001; ranxiety = 0.312, p-value < 0.001; rstress = 0.329, p-value < 0.001). However, there was a poor positive correlation between smartphone addiction and neuroticism (r = 0.173, p-value < 0.001). The simple linear regression showed a significant increase in the levels of depression, anxiety, stress and neuroticism upon one unit increase in smartphone addiction (bdepression = 0.101, p-value < 0.001; banxiety = 0.120, p-value < 0.001; bstress = 0.132, p-value < 0.001; bneuroticism = 0.404, p-value < 0.05). These results indicated significant relationships between smartphone addiction, psychological health and neuroticism. Conclusion This study suggested a high prevalence of smartphone addiction among medical students, particularly in male medical students. The smartphone addiction might lead to psychological problems and the most vulnerable group is the medical student with the neurotic personality trait.

scholarly journals The Relationship of Cigarette Addiction, Smartphone Addiction and Self-Control of Men's Dormitory Students

2020 ◽  
Vol 7 (2) ◽  
pp. 147-154
Author(s):  
Andreas Wisnu Adi Purnomo ◽  
J.T. Lobby Loekmono
Keyword(s):  
Significant Relationship ◽  
Sampling Technique ◽  
Self Control ◽  
Smartphone Addiction ◽  
Multiple Correlation ◽  
Christian University ◽  
Analysis Technique ◽  
R Value ◽  
Relationship Of ◽  
The Relationship

This study aims to determine whether there is a significant relationship between cigarette addiction, simultaneous smartphone addiction and self-control. The subjects who became respondents were students who live in the male dormitory of Satya Wacana Christian University, totalling 109 students as the population. The sampling technique chosen was purposive sampling with the criteria of students who were active smokers and were involved in using smartphones. The research method used is correlational quantitative. The sample consisted of 33 students. The analysis technique used is the multiple correlation formula. Based on the results of various correlation analyzes, the R-value is -0.350 in the opposite direction. For comparison, the Fcount value is found to be 2.128 and the F table with a significant 5% of 4,130. In other words, Fcount Ftable, which means there is no significant relationship. The results of this study found that there was no significant relationship between cigarette addiction, simultaneous smartphone addiction and self-control.

The relationship of the scleractinian corals to the rugose corals

Paleobiology ◽  
1980 ◽  
Vol 6 (02) ◽  
pp. 146-160 ◽  
Author(s):  
William A. Oliver
Keyword(s):  
Critical Points ◽  
Scleractinian Corals ◽  
Convincing Evidence ◽  
Early Triassic ◽  
Rugose Corals ◽  
History Of ◽  
The Subject ◽  
Relationship Of ◽  
The Relationship ◽  
Biologic Factors

The Mesozoic-Cenozoic coral Order Scleractinia has been suggested to have originated or evolved (1) by direct descent from the Paleozoic Order Rugosa or (2) by the development of a skeleton in members of one of the anemone groups that probably have existed throughout Phanerozoic time. In spite of much work on the subject, advocates of the direct descent hypothesis have failed to find convincing evidence of this relationship. Critical points are:(1) Rugosan septal insertion is serial; Scleractinian insertion is cyclic; no intermediate stages have been demonstrated. Apparent intermediates are Scleractinia having bilateral cyclic insertion or teratological Rugosa.(2) There is convincing evidence that the skeletons of many Rugosa were calcitic and none are known to be or to have been aragonitic. In contrast, the skeletons of all living Scleractinia are aragonitic and there is evidence that fossil Scleractinia were aragonitic also. The mineralogic difference is almost certainly due to intrinsic biologic factors.(3) No early Triassic corals of either group are known. This fact is not compelling (by itself) but is important in connection with points 1 and 2, because, given direct descent, both changes took place during this only stage in the history of the two groups in which there are no known corals.

Skeletal elements of crinoid echinoderms: High-resolution structural and microanalytical results

1983 ◽  
Vol 41 ◽  
pp. 194-195
Author(s):  
D. F. Blake ◽  
L. F. Allard ◽  
D. R. Peacor
Keyword(s):  
High Resolution ◽  
Marine Invertebrates ◽  
Sea Urchins ◽  
Structural Features ◽  
Sea Stars ◽  
High Resolution Tem ◽  
Relationship Of ◽  
The Relationship ◽  
Insight Into

Echinodermata is a phylum of marine invertebrates which has been extant since Cambrian time (c.a. 500 m.y. before the present). Modern examples of echinoderms include sea urchins, sea stars, and sea lilies (crinoids). The endoskeletons of echinoderms are composed of plates or ossicles (Fig. 1) which are with few exceptions, porous, single crystals of high-magnesian calcite. Despite their single crystal nature, fracture surfaces do not exhibit the near-perfect {10.4} cleavage characteristic of inorganic calcite. This paradoxical mix of biogenic and inorganic features has prompted much recent work on echinoderm skeletal crystallography. Furthermore, fossil echinoderm hard parts comprise a volumetrically significant portion of some marine limestones sequences. The ultrastructural and microchemical characterization of modern skeletal material should lend insight into: 1). The nature of the biogenic processes involved, for example, the relationship of Mg heterogeneity to morphological and structural features in modern echinoderm material, and 2). The nature of the diagenetic changes undergone by their ancient, fossilized counterparts. In this study, high resolution TEM (HRTEM), high voltage TEM (HVTEM), and STEM microanalysis are used to characterize tha ultrastructural and microchemical composition of skeletal elements of the modern crinoid Neocrinus blakei.

Studies on Leukemogenic and Sarcomagenic Viruses

1970 ◽  
Vol 28 ◽  
pp. 156-157
Author(s):  
Leon Dmochowski
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
Morphological Properties ◽  
Mode Of Development ◽  
Relationship Of ◽  
The Relationship

Electron microscopy has proved to be an invaluable discipline in studies on the relationship of viruses to the origin of leukemia, sarcoma, and other types of tumors in animals and man. The successful cell-free transmission of leukemia and sarcoma in mice, rats, hamsters, and cats, interpreted as due to a virus or viruses, was proved to be due to a virus on the basis of electron microscope studies. These studies demonstrated that all the types of neoplasia in animals of the species examined are produced by a virus of certain characteristic morphological properties similar, if not identical, in the mode of development in all types of neoplasia in animals, as shown in Fig. 1.

The relationship of IGE receptor topography to signaling activity in RBL-2H3 mast cells

1991 ◽  
Vol 49 ◽  
pp. 236-237
Author(s):  
J.R. Pfeiffer ◽  
J.C. Seagrave ◽  
C. Wofsy ◽  
J.M. Oliver
Keyword(s):  
Mast Cells ◽  
Protein A ◽  
Scattered Electron ◽  
Ige Receptor ◽  
Receptor Complexes ◽  
Ige Binding ◽  
Electron Imaging ◽  
Small Clusters ◽  
Relationship Of ◽  
The Relationship

In RBL-2H3 rat leukemic mast cells, crosslinking IgE-receptor complexes with anti-IgE antibody leads to degranulation. Receptor crosslinking also stimulates the redistribution of receptors on the cell surface, a process that can be observed by labeling the anti-IgE with 15 nm protein A-gold particles as described in Stump et al. (1989), followed by back-scattered electron imaging (BEI) in the scanning electron microscope. We report that anti-IgE binding stimulates the redistribution of IgE-receptor complexes at 37“C from a dispersed topography (singlets and doublets; S/D) to distributions dominated sequentially by short chains, small clusters and large aggregates of crosslinked receptors. These patterns can be observed (Figure 1), quantified (Figure 2) and analyzed statistically. Cells incubated with 1 μg/ml anti-IgE, a concentration that stimulates maximum net secretion, redistribute receptors as far as chains and small clusters during a 15 min incubation period. At 3 and 10 μg/ml anti-IgE, net secretion is reduced and the majority of receptors redistribute rapidly into clusters and large aggregates.

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