HLT 362 Article Analysis 1

Sample Answer

Article Analysis 1

• Article Citation and Permalink (APA format) Han, L., Ma, Y., Wei, S., Tian, J., Yang, X., Shen, X., … & Shi, Y. (2017). Are home visits an effective method for diabetes management? A quantitative systematic review and meta‐analysis. Journal of diabetes investigation, 8(5), 701-708.
  Retrieved from https //doi.org/10.1161/CIRCRESAHA.118.314487
• Berard, L., Bonnemaire, M., Mical, M., & Edelman, S. (2018). Insights into optimal basal insulin titration in type 2 diabetes R esults of a quantitative survey. Diabetes, Obesity and Metabolism, 20(2), 301-308. Retrieved from
• https //dom-pubs.onlinelibrary.wiley.com/doi/full/10.1111/dom.13064 Webster, E. K., Logan, S. W., Gray, W. N., & Robinson, L. E. (2018). A cross-sectional study on the relationship between the risk of hypertension and obesity status among pre-adolescent girls from rural areas of Southeastern region of the United States. Preventive medicine reports, 12, 135-139. Retrieved from https //www.sciencedirect.com/science/article/pii/S221133551830189X

Point Description Description Description

Broad Topic Area/Title

The main topic of the study is the effectiveness of home visits in diabetes management. The main topic of the study is insights into optimal basal insulin titration in type 2 diabetes.

The main topic of the study is the relationship between obesity status and the risk of hypertension among pre-adolescent girls from rural areas in, USA.
Identify Independent and Dependent Variables and Type of Data for the Variables Independent variable Home visit interventions, categorical variable
Dependent variable Treatment outcomes (glycated hemoglobin concentrations), continuous variable, ordinal. Independent variable Basal insulin initiation and titration, categorical variable, ordinal

Dependent variable

healthcare professional (HCP) and patient attitudes, categorical, ordinal Independent variable Bodyweight, continuous variable, numeric
Dependent variable Blood pressure; continuous variable with the numeric value.

The population of Interest for the Study

Diabetic patients under home-based care

HCPs and patients with T2DM in the USA, France, and Germany. Patients were aged 18 years and above and have been on BI was about six to thirty-six months.
Female children and pre-adolescents from the rural areas of the United States.

Sample

686 participants with diabetes

• Respondents comprised 386 HCPs and
  
• 318 people with T2DM The sample size included 139 female children and pre-adolescents

Sampling Method Simple random sampling was used to select respondents A simple random sampling method was used to identify respondents Simple random sampling was applied in the selection of the respondents.
Descriptive Statistics (Mean, Median, Mode; Standard Deviation)
Identify examples of descriptive statistics in the article.

Mean difference of glycated hemoglobin concentrations mean difference −0.79% [−9 mmol/mol], 95% confidence interval [CI] −0.93 to −0.25% [11 to −3 mmol/mol] Some the descriptive statistics applied in data analysis include

• Duration of T2DM, years,
• Mean= 11.4
• (SD) = 10.4 The descriptive statistics applied in the process of data analysis include
• Mean age of the respondents = 8.85
  
• SD  1.67 

Inferential Statistics

Identify examples of inferential statistics in the article. The inferential statistics used in the article include:

• χ2‐test (α = 0.1) Regression coefficient with a p-value of 0.05,
  
• Begg’s test and Egger’s test; (P > 0.1, I 2 < 50%) The inferential statistics applied in data analysis include
  
• Correlation between the dependent and independent variable,
  
• France vs Germany, P ≤ .01.
  
• USA vs Germany, P < .05.
  
• Chi-square analysis X2(1, N = 138) = 7.09, p < .01
  
• Pearson correlation is significant at the p < .01 level.
  
• Logistic regression analysis