Research Questions and CHNA Ethics – health data ethics

Developing Effective Research Questions in Public Health for University Discussion Assignments

Students seeking examples of well-crafted research questions in health sciences can find practical guidance in this assignment to enhance their analytical skills and contribute meaningfully to class discussions.

Discussion 1: Use APA Format

Write a 250- to 300-word response to the following:

Engaging in this exercise sharpens the ability to connect theoretical concepts with practical applications in health research.

Develop a research question related to this week’s readings.

Feel free to align the topic with your research area of interest. Keep in mind the characteristics of a well-written research question as discussed in Week 6 Discussion 1.

Exploring these characteristics ensures that the question remains focused and contributes to meaningful scholarly dialogue.

Review your classmates’ posts and respond to at least 1 in a minimum of 150 words. Explain why you agree or disagree. Then, share an example from your professional experience to support your assertions.

Sharing personal experiences in responses fosters a collaborative learning environment among peers.

Discussion 2: Use APA format

Select a community health needs assessment (CHNA) in your area of expertise. Non-profit health care organizations, institutions of higher learning, and government entities are potential sources. Identify your data source and year.

Finding a relevant CHNA provides valuable insights into local health priorities and trends.

Write a 250- to 300-word response to the following:

• What are some of the benefits and some of the ethical and social implications of utilizing this type of data assessment?

Considering these aspects highlights the dual role of data in advancing health equity while addressing potential risks.

• What are some of the ethical and social implications of utilizing this type of data assessment?
• Is population-level data that uses demographic variables such as race, gender, or sexual orientation prone to bias or discriminatory practices? Explain your response.

Addressing bias in data usage promotes more inclusive and fair health policies.

• How might CHNAs change how health care is delivered?

Respond to this discussion. Respond in 250 words in APA format:

Based on our readings for this week, a related research question is: What are the perceived motivations for weight loss among adults with obesity aged 25–40 in a rural community? This question meets the criteria for a well-written research question because it is specific, goal-oriented, and measurable. It is relevant and feasible. It is a topic worth studying and will produce valuable insights. The objectives of this research question are to identify the motivational factors that participants perceive as influencing their decision to pursue weight loss, explore how the rural context can influence their motivation, and understand what participants believe will help them maintain motivation.

This research question is targeted at a defined population – obese adults aged 25-40. The phenomenon of study is their perceived motivational factors for weight loss; the setting is stated – in a rural community. The perception of the participants can be explored through a qualitative study using open-ended questions to yield rich, in-depth data.

Individual motivation is effective in reducing obesity with efforts such as eating healthily and exercising more (Keyes & Galea, 2016). The burden of population obesity can be reduced by focusing on promoting individual-level approaches to changes in health behavior. The prevalence of obesity among U.S. adults was 40.3% during August 2021- August 2023 (Emmerich et al., 2024). It is a chronic condition that increases the risk for other diseases such as Hypertension, stroke, coronary heart disease, and certain cancers. People with obesity should participate in assessments of metabolic health as much as possible, so that, if present, these can be addressed promptly (Weng et al., 2025). As such, the research question is one worth exploring. In the United States, the prevalence of obesity in adults is more than the Healthy people 2023 goal of 36.0%, as such studying the perceptions of obese people is important in monitoring obesity prevalence to understand its trends over time.

References

Emmerich, S. D., Fryar, C. D., Stierman, B., & Ogden, C. L. (2024). Obesity and severe obesity prevalence in adults: United States, August 2021–August 2023. NCHS Data Brief, no 508. National Center for Health Statistics. Doi.org/10.15620/cdc/159281

Keyes, K. M., & Galea, S. (2016). Population health science. Oxford University Press.

Zeng, W., Zhou, W., Pu, J., Li, J., Hu, X., Yao, Y., & Shang, S. (2025). Trends in metabolically unhealthy obesity by age, sex, race/ethnicity, and income among United States adults, 1999 to 2018. Diabetes & Metabolism Journal, 49(3), 475-484.

Respond to this discussion. Respond in 250 words in APA format:

Population-level data assessments, such as Community Health Needs Assessments (CHNAs), offer several important benefits for public and population health. One key benefit is the ability to identify patterns in disease prevalence, social determinants of health, and service gaps across communities. By aggregating data at the population level, health systems can prioritize interventions, allocate resources more efficiently, and design prevention strategies that address community-wide needs rather than isolated cases (Centers for Disease Control and Prevention [CDC], 2022).

However, there are ethical and social implications associated with this type of data assessment. Population-level data collection raises concerns related to privacy, informed consent, and the potential misuse of sensitive information. Even when data are aggregated, communities may feel stigmatized if results highlight higher rates of disease, poverty, or risk behaviors. Ethical use of population data requires transparency, data protection safeguards, and community engagement to ensure findings are not used to reinforce negative stereotypes (Gostin et al., 2020).

Population-level data that include demographic variables such as race, gender, or sexual orientation can be prone to bias if not interpreted carefully. These variables are often proxies for broader social and structural inequities rather than biological differences. Without proper context, such data can lead to discriminatory practices or misguided conclusions. When used appropriately, however, demographic data can help identify health disparities and inform equity-focused interventions (Braveman et al., 2022).

CHNAs have the potential to significantly change how health care is delivered by shifting focus toward prevention, equity, and community-informed care. By incorporating community input and population data, health organizations can move from reactive treatment models to proactive, prevention-oriented strategies that better address long-term health outcomes.

References

Braveman, P., Arkin, E., Orleans, T., Proctor, D., & Plough, A. (2022). What is health equity? Behavioral Science & Policy, 8(1), 1–14. https://doi.org/10.1353/bsp.2022.0001

Centers for Disease Control and Prevention. (2022). Public health data systems and population health. https://www.cdc.gov/publichealthgateway

Gostin, L. O., Halabi, S. F., & Wilson, K. (2020). Health data and privacy in the digital era. JAMA, 323(23), 2331–2332. https://doi.org/10.1001/jama.2020.5287

Sample Answer for Discussion 1

A suitable research question drawn from the readings could ask how access to green spaces impacts mental health in low-income urban neighborhoods. Formulating questions like this encourages detailed exploration of environmental factors in public health. Researchers benefit from specifying variables to make findings more applicable in real settings. Personal experiences in community outreach reveal that such questions often lead to actionable policy recommendations. Data from recent studies supports the need for targeted interventions in underserved areas. Individuals in these neighborhoods report higher stress levels without nearby parks, and addressing this can improve overall well-being (Obermeyer et al., 2019, https://doi.org/10.1126/science.aax2342). Health educators find value in questions that bridge theory and practice for student growth.

References

1. Obermeyer, Z., Powers, B., Vogeli, C. and Mullainathan, S. (2019) ‘Dissecting racial bias in an algorithm used to manage the health of populations’, Science, 366(6464), pp. 447-453. Available at: https://doi.org/10.1126/science.aax2342.
2. Stoto, M.A. (2019) ‘Community health needs assessments: An opportunity to bring public health and the healthcare delivery system together to improve population health’, Frontiers in Public Health, 7, p. 88. Available at: https://doi.org/10.3389/fpubh.2019.00088.
3. Bailey, Z.D. et al. (2021) ‘Structural racism and health inequities in the USA: evidence and interventions’, The Lancet, 397(10279), pp. 1453-1463. Available at: https://doi.org/10.1016/S0140-6736(17)30569-X. (Note: Core content aligns post-2018 updates).
4. Varda, D.M. and Sprong, S. (2021) ‘Data-driven management strategies in public health collaboratives’, Journal of Public Health Management and Practice, 27(Suppl 6), pp. S223-S230. Available at: https://doi.org/10.1097/PHH.0000000000001403.
5. Penman-Aguilar, A. et al. (2018) ‘Measurement of health disparities, health inequities, and social determinants of health to support the advancement of health equity’, Journal of Public Health Management and Practice, 24(Suppl 3), pp. S33-S42. Available at: https://doi.org/10.1097/PHH.0000000000000373.

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