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HLT-362V Article Analysis 1 Guide
The HLT-362V Article Analysis 1 assignment requires you to find two quantitative research articles on a health topic and complete an analysis template that breaks down each study’s purpose, design, sample, variables, instruments, statistical tests, findings, and limitations. It is a critical-reading exercise, not a calculation task — you are showing that you can dissect quantitative research the way a nurse evaluating evidence would. Both articles must be peer-reviewed and quantitative, and your citations must follow APA 7. This guide walks through every field of the template, shows a fully worked example analyzing two real nurse-burnout studies, and explains how to spot the statistical tests so you can complete the assignment with confidence.
What Is the HLT-362V Article Analysis 1 Assignment?
Article Analysis 1 is a Topic 2 assignment in HLT-362V Applied Statistics for Health Care that asks you to locate two quantitative studies and analyze them inside a provided template. The purpose is to build your ability to read, interpret, and evaluate quantitative nursing research.
The assignment is structured as a table or worksheet with one column per article. For each study you identify the citation, purpose, design, sample, variables, data-collection instruments, statistical tests, results, and limitations.
Both articles must be quantitative — meaning they collect numerical data and analyze it statistically — and peer-reviewed. Qualitative studies, literature reviews, and opinion pieces do not qualify. This connects directly to the conceptual groundwork in Application of Statistics in Health Care, the Topic 1 paper.
How Do You Complete the Article Analysis Template?
You complete the template by answering each criterion separately for both articles, using specific details pulled directly from each study. Vague, generic answers lose points; graders want evidence that you actually read the methods section.
Work through these fields for each article:
- APA citation and permalink — a correct APA 7 reference plus a working DOI or link.
- Purpose / research question — why the study was done.
- Research design — the type of quantitative study (e.g., cross-sectional, cohort, experimental).
- Population and sample — who was studied and how many.
- Variables — the independent and dependent variables.
- Instruments — the scales or tools used to collect data.
- Statistical tests — the analyses used (e.g., t-test, correlation, regression).
- Findings and significance — the results and whether they were statistically significant.
- Limitations — what weakens the study.
- Application to practice — how the findings could inform nursing.
How Do You Find Acceptable Quantitative Research Articles?
You find acceptable articles by searching library databases for recent, peer-reviewed studies that report numerical data and statistical analysis. The GCU Library, CINAHL, PubMed, and Google Scholar are the standard starting points.
Use these criteria to confirm an article qualifies:
- Peer-reviewed journal source, ideally published within the last five years.
- A methods section describing a sample size and data collection.
- A results section reporting statistics such as means, correlations, p-values, or regression coefficients.
- A clear quantitative design — cross-sectional, cohort, case-control, or experimental.
If an article only describes themes, interviews, or lived experiences without numbers, it is qualitative and will not meet the requirement.
How Do You Identify the Statistical Tests in a Study?
You identify the statistical tests by reading the data-analysis subsection of the methods, which names the specific procedures used. Authors almost always state them explicitly, often alongside the software used.
Common tests you will encounter include:
- Descriptive statistics — means, standard deviations, and frequencies that summarize the sample. Our Summary and Descriptive Statistics guide explains these in depth.
- Correlation (e.g., Pearson’s r) — measures the strength of a relationship between two variables.
- t-tests and ANOVA — compare means between groups.
- Regression — predicts an outcome from one or more variables.
- Probability and sampling concepts — underpin how results generalize, as covered in our Population and Sampling Distribution guide.
HLT-362V Article Analysis 1 Example
For Reference Use Only: This worked sample is provided as a study reference and example only. Need a custom Article Analysis completed with your own articles and rubric? Message us on WhatsApp: +1 564-544-6924
Article Analysis 1
[Student Name]
College of Nursing and Health Care Professions, Grand Canyon University
HLT-362V: Applied Statistics for Health Care
[Instructor Name]
[Due Date]
Article Analysis 1
This analysis examines two recent peer-reviewed quantitative studies on nurse burnout, a topic with direct implications for patient safety and workforce retention. The first study investigates resilience and burnout among British nurses during the COVID-19 pandemic, and the second examines sex differences in burnout and work-family conflict among Chinese emergency nurses. The table below summarizes each study’s purpose, design, sample, variables, instruments, statistical methods, findings, limitations, and relevance to practice.
| Criterion | Article 1 | Article 2 |
| APA citation | Abdulmohdi, N. (2024). The relationships between nurses’ resilience, burnout, perceived organisational support and social support during the second wave of the COVID-19 pandemic: A quantitative cross-sectional survey. Nursing Open, 11(1), e2036. | Diao, D., Chen, X., Zhong, L., Zhang, H., & Zhang, J. (2024). Sex differences in burnout and work-family conflict among Chinese emergency nurses: A cross-sectional study. Frontiers in Public Health, 12, 1492662. |
| Permalink / DOI | https://doi.org/10.1002/nop2.2036 | https://doi.org/10.3389/fpubh.2024.1492662 |
| Purpose / research question | To examine the level of resilience and burnout among British nurses during the second wave of the COVID-19 pandemic, and how personal, social, and organisational factors influenced them. | To use sex-specific analyses to examine the associations between dimensions of burnout and work-family role behavior conflict among Chinese emergency department nurses. |
| Research design | Quantitative, descriptive cross-sectional self-report survey. | Quantitative cross-sectional survey. |
| Population / sample | 111 staff nurses working in the UK NHS and private sector, recruited by convenience sampling between January and April 2021. | 1,540 emergency department nurses from 30 tertiary hospitals across mainland China, surveyed December 2023 to January 2024. |
| Variables | Independent: perceived organisational support, social support, and personal/demographic factors. Dependent: nurses’ resilience and burnout. | Independent: work-family role behavior conflict and sex/demographic variables. Dependent: burnout dimensions (emotional exhaustion, depersonalization, reduced personal accomplishment). |
| Instruments | A self-administered questionnaire combining validated resilience, burnout, perceived organisational support, and social support scales. | A structured questionnaire capturing demographics, a work-family role behavior conflict scale, and a burnout scale. |
| Statistical tests | Descriptive statistics, Pearson’s correlation coefficient, and multiple linear regression (SPSS v28; Shapiro-Wilk test confirmed normality for parametric tests). | Descriptive statistics, group comparisons by sex, Pearson correlation analyses, and multiple linear regression. |
| Key findings / significance | Resilience and burnout were significantly correlated with organisational and social support; regression identified support-related factors as significant predictors of nurses’ resilience and burnout during the pandemic. | Burnout and work-family conflict were positively associated in both sexes. Regression showed emotional exhaustion, depersonalization, and reduced accomplishment were each significantly associated with conflict. Male nurses reported slightly higher mean burnout (11.63) and conflict (43.4) than female nurses (11.14 and 42.23). |
| Limitations | Small convenience sample (n = 111) drawn from nurses attending one university course, limiting generalizability; the cross-sectional design cannot establish causation. | Cross-sectional design prevents causal inference; a single-country convenience sample and self-report measures may introduce bias. |
| Application to practice | Supports organisational investment in social and managerial support to protect nurse resilience and reduce burnout. | Highlights the need for sex-sensitive, family-friendly scheduling and support to reduce burnout among emergency nurses. |
References
Abdulmohdi, N. (2024). The relationships between nurses’ resilience, burnout, perceived organisational support and social support during the second wave of the COVID-19 pandemic: A quantitative cross-sectional survey. Nursing Open, 11(1), e2036. https://doi.org/10.1002/nop2.2036
Diao, D., Chen, X., Zhong, L., Zhang, H., & Zhang, J. (2024). Sex differences in burnout and work-family conflict among Chinese emergency nurses: A cross-sectional study. Frontiers in Public Health, 12, 1492662. https://doi.org/10.3389/fpubh.2024.1492662
How Is Article Analysis 1 Graded?
Article Analysis 1 is graded on the accuracy and completeness of your analysis, the quality of your chosen articles, and APA formatting. Each template field carries weight, so a blank or vague cell costs you.
The rubric generally rewards:
- Correct identification of design, variables, and statistical tests.
- Appropriate, peer-reviewed quantitative article selection.
- Accurate APA 7 citations and working permalinks.
- Clear, specific descriptions rather than copied abstract text.
Common Mistakes to Avoid
Most lost points come from a handful of recurring errors. Watch for these:
- Choosing a qualitative study or a literature review instead of a quantitative one.
- Copying the abstract verbatim instead of analyzing in your own words.
- Naming the wrong statistical test, or leaving the statistics field vague.
- Incorrect APA citations or broken permalinks.
- Mismatched articles that don’t share a coherent topic.
HLT-362V Article Analysis 1 FAQ
What kind of articles do I need for Article Analysis 1?
You need two peer-reviewed quantitative research articles that report numerical data and statistical analysis. Qualitative studies, systematic reviews, and opinion articles do not meet the requirement.
How do I know if a study is quantitative?
A study is quantitative if it collects numerical data and analyzes it with statistics such as means, correlations, t-tests, or regression. The methods section will describe a sample size and a data-analysis plan using statistical tests.
Do the two articles have to be on the same topic?
The two articles should address a related health topic so your analysis is coherent, though they do not have to be identical in focus. Choosing a shared theme, such as nurse burnout, makes comparison easier and stronger.
What statistical tests should I look for?
Look for descriptive statistics, correlation, t-tests, ANOVA, and regression, which are the most common in nursing research. The data-analysis subsection of the methods names the exact tests used.
Does Article Analysis 1 require APA format?
Yes, the citations and permalinks must follow APA 7 formatting. The body of the analysis is completed inside the provided template rather than as a formal essay.
About the Author
This guide was prepared by the Gradevia academic team, specialists in nursing and health-sciences coursework support for students at GCU, WGU, Walden, and Liberty University. Our writers hold graduate degrees in nursing, public health, and applied statistics, and have produced hundreds of rubric-aligned HLT-362V resources covering applied statistics, descriptive statistics, sampling distributions, article analysis, and evidence-based practice. We focus on helping busy working nurses understand the method, not just the answer.
Article Update Log
June 18, 2026 — Initial publication. Comprehensive guide to HLT-362V Article Analysis 1: how to complete the analysis template, how to find peer-reviewed quantitative articles, how to identify statistical tests, a fully worked example analyzing two real 2024 nurse-burnout studies (Abdulmohdi, 2024; Diao et al., 2024), grading notes, Summary and Descriptive Statistics, and Population and Sampling Distribution guides, and FAQ.
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