Applied Statistics T5 DQ2

Describe the rationale for the application of ethical guidelines in data collection. Using an article that you cited in the Article Analysis 1 or Article Analysis 2 assignments (see attachments), evaluate the article from a Christian worldview perspective and identify potential ethical considerations that may have occurred when sampling, collecting data, analyzing data, or publishing results. Provide rationale and support for your evaluation.

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Initial discussion question posts should be a minimum of 200 words and include at least two references cited using APA format.

Article Analysis 1

Article Citation and Permalink
(APA format)

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Article 1

Doust, M. V., Hojjati, H., & Farhangi, H. (

2

020).

Effect of spiritual care based on Ghalbe Salim on anxiety in adolescents with cancer.

Journal of Religion and Health, 59(6), 2857-2865.

https://eds-p-ebscohost-com.lopes.idm.oclc.org/eds/detail/detail?vid=1&sid=1af38ed8-5f3c-4845-bf43-c682b6d18058%40redis&bdata=JnNpdGU9ZWRzLWxpdmUmc2NvcGU9c2l0ZQ%3d%3d#AN=edsjsr.10.2307.45387013&db=edsjsr

Article 2

Miraki, M. R., Nasirzadeh, M., Sayadi, A. R., & AbdolKarimi, M. (2024).

Effect of the Lazarus’ transactional model-based intervention on stress control and coping in patients with type 2 diabetes.

Health Education and Health Promotion, 12(4), 597-603
https://eds-p-ebscohost-com.lopes.idm.oclc.org/eds/detail/detail?vid=1&sid=8ad389eb-7089-49ee-92bb-bc8d55dad3f9%40redis&bdata=JnNpdGU9ZWRzLWxpdmUmc2NvcGU9c2l0ZQ%3d%3d#db=cul&AN=182103762

Criteria

Description

Description

Broad Topic Area/Title

Effect of spiritual care based on Ghalbe Salim on anxiety in adolescents with cancer. Effect of the Lazarus’ transactional model-based intervention on stress control and coping in patients with type 2 diabetes.

Identify Independent and Dependent Variables and Type of Data for the Variables

Independent Variable: Spiritual care intervention (Categorical: intervention vs. control group)

The dependent variable is anxiety levels among adolescents with cancer (Ordinal: measured on the March Anxiety Scale for Children).

Independent Variable – Educational intervention based on Lazarus transactional model (Categorical – intervention and control groups)

Dependent variables: The dependent variables of the study include stress levels and coping habits of the patients with type 2 diabetes (ordinal data: collected using the Cohen Perceived Stress Scale, as well as the Jalowiec Coping Strategies Scale).

Population of Interest for the Study

At the Pediatric Center of Doctor Sheikh Hospital located in Mashhad, Iran, adolescents with cancer.

Type 2 diabetic patients who were being treated at the diabetes clinic of Anar City, Iran.

Sample

40 adolescents with cancer


20 in the intervention (spiritual care) group


20 in the control group

82 patients with type 2 diabetes


40 in the intervention group


42 in the control group

Sampling Method

Randomized sampling method. Randomly, participants were assigned to the intervention and control groups.

Method: The method utilized was randomized sampling method on basis of available patient records at the diabetes clinic.

Descriptive Statistics (Mean, Median, Mode; Standard Deviation)

Identify examples of descriptive statistics in the article.

Before Intervention:

– Intervention Group Anxiety Score: 75.25 ± 15.2

No significant difference (p < 0.01) in Control Group Anxiety Score.

After Intervention:

– Intervention Group Anxiety Score: 44.55 ± 7.62

The effect of the intervention made up 50% of the posttest changes.

Before Intervention:

In Intervention Group, perceived stress score was found to be 25.17 ± 7.25.

The Control Group Perceived Stress score was 26.20 ± 6.11.

After Intervention:

The Intervention Group Perceived Stress Score was 13.47 ± 4.73.

– For Control Group, mean score of Control Group Perceived Stress Score was 29.25 ± 5.57

A significant effect (p < 0.001) via analysis of covariance was confirmed.

© 2023. Grand Canyon University. All Rights Reserved.

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© 2023. Grand Canyon University. All Rights Reserved.

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Article Analysis 2

Article Citation

and Permalink
(APA format)

Article 1

Chen, X., Jiang, H., Zhang, Y., Wang, X., Liu, P., & Zhou, Q. (2024).
The incidence rate of allergic reactions induced by oxaliplatin is higher in patients with rectal cancer compared with colon cancer.

Drug & Chemical Toxicology. Jul2024, Vol. 47 Issue 4, p

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65-371. 7p.

https://eds-p-ebscohost-com.lopes.idm.oclc.org/eds/detail/detail?vid=1&sid=b03eae11-a677-4d5e-8cc1-a18531811086%40redis&bdata=JnNpdGU9ZWRzLWxpdmUmc2NvcGU9c2l0ZQ%3d%3d#db=a9h&AN=178176294

Article 2

Kosami, K., Kuwabara, M., Okayama, A., & Ae, R. (2025).

Body Mass Index and Weight Change as Predictors of Hypertension Development: A Sex-Specific Analysis.

Nutrients (NUTRIENTS), Jan2025; 17(1): 119. (16p)

https://eds-p-ebscohost-com.lopes.idm.oclc.org/eds/detail/detail?vid=4&sid=b03eae11-a677-4d5e-8cc1-a18531811086%40redis&bdata=JnNpdGU9ZWRzLWxpdmUmc2NvcGU9c2l0ZQ%3d%3d#db=cul&AN=182442479

Criteria

Description

Description

Broad Topic Area/Title

The study shows incidence rate of allergic reactions to the oxaliplatin in patients with cancer.

The risk of developing hypertension is influenced by BMI and weight change, particularly with regard to sex differences.

Define the Null and Alternative Hypotheses

Null Hypothesis (H₀): There is no significant increase of allergic reactions due to oxaliplatin in cancer patients.

Alternative Hypothesis (H₁): Oxaliplatin significantly increases the incidence of allergic reactions compared to cancer patients.

H₀: There is no significant association between BMI, weight change, and the development of hypertension.

H₁: The BMI and weight changes contributes significantly to the development of hypertension.

Define Independent and Dependent Variables and Types of Data for Variables

Independent Variable: Oxaliplatin exposure (categorical: exposed/not exposed)

Dependent Variable: Allergic reaction occurrence (categorical: yes/no)

Independent Variables: BMI and weight change (continuous)

Dependent Variable: Hypertension development (categorical: yes/no)

Population of Interest for the Study

Cancer patients undergoing oxaliplatin treatment.

The Japanese adults aged 40–75 who were participating in the national health screening program.

Sample

Provide page citation for sample information.

A study with 5243 cancer patients under oxaliplatin treatment was documented (p. 249).

397,181 participants from the Japanese Specific Health Checkup program (p. 3).

Sampling Method

Hospital records are used in a retrospective cohort study.

Retrospective two-point cohort study.

How Were the Data Collected?

Provide page citation.

Electronical medical records and patient reported allergy symptoms were used to obtain data (p. 250).

Outputs from the Japanese Specific Health Checkup database, including BMI, weight changes, and diagnoses of hypertension, are collected (p. 4).

Inferential Statistics

Clearly identify which hypothesis tests were used and the results.

The incidence rates of allergic reactions were analyzed by the chi-square tests.

The odds of oxaliplatin induced allergic reaction was then determined using logistic regression where the odds ratio was 2.45 (95% CI: 1.98 – 3.02, p < 0.05).

The relationship between BMI, weight changes and hypertension was assessed using multivariable logistic regression.

In the study significant associations between increased BMI and hypertension (OR = 1.11, 95% CI: 1.11–1.12) and between weight gain and hypertension (OR = 1.09, 95% CI: 1.09–1.10, p < 0.05) (p. 8) were found.

Assess the Appropriateness of Statistical Methods Used in This Study

Provide rationale to support your response.

Logistic regression is appropriate for study of categorical outcomes (allergic reaction: yes/no).

Chi-square tests will accept incidence rates>0, and are used to compare incidence rates between groups.

The study included proper control of confounders like age and prior history of allergy.

The relationship between the BMI/weight change to hypertension is assessed by multivariable logistic regression, which is an appropriate method to examine such a predictive relationship.

Analyses were stratified by sex improving robustness in findings.

The increased sample size increases the statistical power and generalizability.

© 2023. Grand Canyon University. All Rights Reserved.

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