HLT-362V Article Analysis 2
HLT-362V Article Analysis 2
HLT-362V Article Analysis 2
| Article Citation
and Permalink (APA format)
|
Zhu, W., Wu, Y., Meng, Y. F., Xing, Q., Tao, J. J., & Lu, J. (2018). Association of obesity and risk of diabetic retinopathy in diabetes patients: a meta-analysis of prospective cohort studies. Medicine, 97(32).
Retrieved from:
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Jung, S., Kim, M. K., Shin, J., Lee, N., Woo, H. W., Choi, B. Y., … & Lee, Y. H. (2020). Positive association of alcohol consumption with incidence of hypertension in adults aged 40 years and over: Use of repeated alcohol consumption measurements. Clinical Nutrition, 39(10), 3125-3131.
Retrieved from: https://www.sciencedirect.com/science/article/abs/pii/S0261561420300431
|
| Point | Description | Description |
| Broad Topic Area/Title | Association of obesity and risk of diabetic retinopathy in diabetes patients. | Positive association of alcohol consumption with incidence of hypertension in adults aged 40 years and over. |
| Define Hypotheses | Null Hypothesis (Ho): There is no association between obesity and risk of diabetic retinopathy in diabetes patients.
Alternative Hypothesis (H1): There is an association between obesity and risk of diabetic retinopathy in diabetes patients. |
Null Hypothesis (Ho):
There is no positive association of alcohol consumption and the incidence of hypertension in adults aged 40 years and over Alternative Hypothesis (H1): There is positive association of alcohol consumption and the incidence of hypertension in adults aged 40 years and over |
| Define Independent and Dependent Variables and Types of Data for Variables | Independent variable: Body weight or BMI (Continuous variable)
Dependent variable: diabetes (blood sugar level) (Continuous variable)
|
Independent variable: quantity of alcohol consumed (continuous, discrete variable)
Dependent variable: Blood pressure (continuous, discrete variable) |
| Population of Interest for the Study | Diabetes and obese patients | The population of interest in the study was non-hypertensive Korean adults aged above 40 years in the rural areas (Singh et al., 2018). |
| Sample | The sample size used in the study was 13. | The study consisted of 4989 participants (Jung et al., 2020) |
| Sampling Method | Stratified sampling method was used in the study process | Simple random sampling technique was used to identify women with different drinking habits. |
| How Were Data Collected? | The data was obtained from the healthcare databases that have been recorded over a period. PubMed and EMBASE databases were mainly considered in the study as sources of data (Zhu et al., 2018). | The data applied in the study were obtained from the healthcare databases in the rural areas. |
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References
Jung, S., Kim, M. K., Shin, J., Lee, N., Woo, H. W., Choi, B. Y., … & Lee, Y. H. (2020). Positive association of alcohol consumption with
HLT-362V Article Analysis 2
incidence of hypertension in adults aged 40 years and over: Use of repeated alcohol consumption measurements. Clinical Nutrition, 39(10), 3125-3131. https://www.sciencedirect.com/science/article/abs/pii/S0261561420300431
Singh, G. M., Danaei, G., Farzadfar, F., Stevens, G. A., Woodward, M., Wormser, D., … & Prospective Studies Collaboration (PSC). (2018). The age-specific quantitative effects of metabolic risk factors on cardiovascular diseases and diabetes: a pooled analysis. PloS one, 8(7), e65174. https://doi.org/10.1371/journal.pone.0065174
Zhu, W., Wu, Y., Meng, Y. F., Xing, Q., Tao, J. J., & Lu, J. (2018). Association of obesity and risk of diabetic retinopathy in diabetes patients: a meta-analysis of prospective cohort studies. Medicine, 97(32). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133614/
When analyzing quantitative articles, it is important to consider the methodologies and statistics that have been used. The methodologies used in a study can influence the results, so it is important to be aware of them. Additionally, the statistics that are used can also be misleading. It is therefore essential to examine both the methodologies and the statistics in order to get a clear understanding of the article’s findings. The purpose of this assignment is to analyze three quantitative articles by identifying the variables, methodologies, and the statistical approaches that have been used.
Article Analysis 1
| Article Citation and Permalink (APA format) | Liao, Y. Y., Chu, C., Wang, Y., Zheng, W. L., Ma, Q., Hu, J. W., … & Mu, J. (2020). Sex differences in impact of long-term burden and trends of body mass index and blood pressure from childhood to adulthood on arterial stiffness in adults: A 30-year cohort study. Atherosclerosis, 313, 118-125.
Permalink: https://doi.org/10.1016/j.atherosclerosis.2020.10.003
|
Kelly, L. A., Gee, P. M., & Butler, R. J. (2021). Impact of nurse burnout on organizational and position turnover. Nursing Outlook, 69(1), 96-102.
Permalink: https://www.sciencedirect.com/science/article/pii/S0029655420300877
|
Lee, E., & Kim, Y. (2019). Effect of university students’ sedentary behavior on stress, anxiety, and depression. Perspectives In Psychiatric Care, 55(2), 164.
Permalink: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7818186/
|
| Point | Description | Description | Description |
| Broad Topic Area/Title |
Sex differences in impact of long-term burden and trends of body mass index and blood pressure from childhood to adulthood on arterial stiffness in adults |
Impact of nurse burnout on organizational and position turnover |
Effect of university students’ sedentary behavior on stress, anxiety, and depression |
| Identify Independent and Dependent Variables and Type of Data for the Variables | Independent variable: long-term burden of body mass index (BMI)
(Type: continuous, numeric variable) Dependent variable: Arterial Stiffness (AS) (Type: continuous, numeric variable) |
Independent Variable: Rates of nurse burnout (Type: continuous, numeric variable)
Dependent variable: Organizational and position turnover (Type: continuous, numeric variable) |
Independent variable: stress, anxiety, and depression (continuous, numeric variable)
Dependent variable: sedentary behavior (categorical variable)
|
| Population of Interest for the Study | School students aged 6–15 years with no chronic diseases in their medical history. | Direct care nurses in different hospitals |
University students |
| Sample |
The sample size used was 1553. In other words 1553 individuals aged 6–15 years were considered in the study (Kelly et al., 2021). |
The sample size used was 3,135. In other words, a 3,135 direct care nurses were considered in the research process (Lee & Kim, 2019). |
The sample size was 244. In other words, 244 students were considered in the study
|
| Sampling Method | Simple random sampling method was used to identify the study participants from the population under the study. | From the study, simple random sampling technique was used to identify the study participants. Survey of direct care nurses was mainly used. |
Simple random sampling |
| Descriptive Statistics (Mean, Median, Mode; Standard Deviation)
Identify examples of descriptive statistics in the article. |
ü Media and interquartile range were applied.
Median for age in childhood was 12 Quartile 1 was 9, and quartile 3 was 14. ü Percentages Male constituted 869 (56.0%) Female constituted 684 (44.0%) ü Mean ü Standard deviation
|
ü Mean Age 39.9 ü Standard deviation of Age 10.63 ü Percentages |
Some of the descriptive statistics considered in the study include:
ü Mean of Sedentary behavior =7.96 ü S.D =3.35 ü Minimum= 0.49 ü Median = 7.57 ü Maximum = 18
|
| Inferential Statistics
Identify examples of inferential statistics in the article. |
Some of the inferential statistics used in the article include:
ü Regression analysis
The standardized regression coefficient, β = 6.45, p < 0.001), ü Correlation P< 0.05 ü logistic regression
|
Some of the inferential statistics used in the quantitative article include:
ü logistic regression with p-value at 0.05 ü linear regressions were used to predict nurse burnout (partially determined by resiliency
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Some of the inferential statistics that have been used include:
ü Independent samples t‐test (at p-value of 0.05) ü One‐way analysis of variance (ANOVA) (at p-value of 0.05) (Liao et al., 2020) ü Simple logistic regression |
Conclusion
When it comes to quantitative article analysis, it’s important to consider the methodologies and statistics that have been used. This is because these factors can impact the results of the analysis and how you interpret them. For example, if a study uses a method that is not as reliable as another method, then you would want to be cautious about relying too heavily on its results. Likewise, if a study has a small sample size or uses a selective group of participants, then you would want to take its findings with a grain of salt. In addition to considering the methodology and statistics used in a study, it’s also important to look at the author’s qualifications. Quantitative methodologies are essential when it comes to obtaining valid results from experiments, surveys and other research. The three articles which this analysis considers each made use of quantitative methods in order to achieve their outcomes. These methodologies are key to the effective application of statistics and data in order to form safe and accurate conclusions. Furthermore, quantitative methodologies serve as crucial tools in evaluating hypotheses, allowing researchers to draw reliable scientific inferences that hold up under scrutiny. Without quantitative methods, any outcomes that result from research would be impossible to verify or refute confidently.
References
Kelly, L. A., Gee, P. M., & Butler, R. J. (2021). Impact of nurse burnout on organizational and position turnover. Nursing Outlook, 69(1), 96-102. https://www.sciencedirect.com/science/article/pii/S0029655420300877
Lee, E., & Kim, Y. (2019). Effect of university students’ sedentary behavior on stress, anxiety, and depression. Perspectives In Psychiatric Care, 55(2), 164. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7818186/
Liao, Y. Y., Chu, C., Wang, Y., Zheng, W. L., Ma, Q., Hu, J. W., … & Mu, J. (2020). Sex differences in impact of long-term burden and trends of body mass index and blood pressure from childhood to adulthood on arterial stiffness in adults: a 30-year cohort study. Atherosclerosis, 313, 118-125. https://doi.org/10.1016/j.atherosclerosis.2020.10.003