2021
DOI: 10.3390/ijerph18073755
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An Empirical Study on Diabetes Depression over Distress Evaluation Using Diagnosis Statistical Manual and Chi-Square Method

Abstract: Diabetes distress is an alternative disorder that is often associated with depression syndromes. Psychosocial distress is an alternative disorder that acts as a resistance to diabetes self-care management and compromises diabetes control. Yet, in Nigeria, the focus of healthcare centers is largely inclined toward the medical aspect of diabetes that neglects psychosocial care. In this retrospective study, specific distress was measured by the Diabetes Distress Screening (DDS) scale, and depression was analyzed … Show more

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Cited by 5 publications
(3 citation statements)
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“…Oktaviani et al selected the physique monitoring data in 2015, based on the national physique monitoring bulletin in 2014, and used statistical methods to group and compare the male faculty members of Zhejiang Normal University [10]. Noman et al used the national survey data of students' physique and health from 1985 to 2014 to analyze the change trend of excellent rate of students' physique and health in different years and the difference of excellent rate of students with different characteristics and used the log-binomial regression model to analyze the relevant factors of students' physique and health [11]. Although the academic research results on the evaluation methods of the impact of physical training on physical indicators are relatively rich, the evaluation methods of the impact of physical training on physical indicators based on in-depth learning are relatively few.…”
Section: Introductionmentioning
confidence: 99%
“…Oktaviani et al selected the physique monitoring data in 2015, based on the national physique monitoring bulletin in 2014, and used statistical methods to group and compare the male faculty members of Zhejiang Normal University [10]. Noman et al used the national survey data of students' physique and health from 1985 to 2014 to analyze the change trend of excellent rate of students' physique and health in different years and the difference of excellent rate of students with different characteristics and used the log-binomial regression model to analyze the relevant factors of students' physique and health [11]. Although the academic research results on the evaluation methods of the impact of physical training on physical indicators are relatively rich, the evaluation methods of the impact of physical training on physical indicators based on in-depth learning are relatively few.…”
Section: Introductionmentioning
confidence: 99%
“…Training accuracy and training loss with respect to epochs are illustrated in Figures 5 and 6. Performance metrics such as accuracy, recall, precision, and F1-score were measured to evaluate the model, and these are given as follows [34]: Performance metrics such as accuracy, recall, precision, and F1-score were measured to evaluate the model, and these are given as follows [34]: Performance metrics such as accuracy, recall, precision, and F1-score were measured to evaluate the model, and these are given as follows [34]…”
Section: Resnet Modelmentioning
confidence: 99%
“…Considering the above, the fundamental objective of this study was to develop an accurate phenotype prediction model against antimicrobials. For this purpose, machine learning approaches called bio-Weka [29], and random forest (RF), and logistic regression (LR) [30][31][32] were used on the data mining platform called Weka (v3.9.2) (an open source java-based software) [33][34][35] for acquiring classifcation accuracy assumptions to accurately predict the phenotypes against a panel of twelve antimicrobial agents, including ampicillin, amoxicillin, meropenem, cefepime, fosfomycin, ceftazidime, chloramphenicol, erythromycin, tetracycline, gentamycin, butirosin, and ciprofoxacin from whole genome sequence data of P. aeruginosa. Signifcantly, this study can further enhance the antimicrobial predictions of various bacterial agents in clinical trials.…”
Section: Introductionmentioning
confidence: 99%