NR 449 Week 4 Discussion: Sampling

NR 449 Week 4 Discussion: Sampling

NR 449 Week 4 Discussion: Sampling

Name

Chamberlain University

NR-449 Evidence-Based Practice

Prof. Name

Date

Sampling

Implications of Using Convenience Sampling in Research

Convenience sampling is a frequently applied non-probability technique in which participants are selected based on their easy accessibility. Researchers often choose this method due to its cost-effectiveness, efficiency, and practical application in various contexts. However, its limitations significantly affect research reliability and validity.

The most critical issue with convenience sampling is bias. Because participants are not randomly selected, the sample often fails to represent the broader target population. This lack of representativeness severely limits the generalizability of study findings (Houser, 2018). For example, in healthcare research, relying on participants from one hospital may yield results that are not transferable to other healthcare settings.

Another drawback is selection bias, where researchers may—intentionally or unintentionally—choose participants aligning with their expectations. This type of bias directly threatens internal validity (Emerson, 2015).

Practical Example and Limitations

A study on nurses’ perceptions of family violence (FV) screening demonstrates these limitations. Conducted within a rural healthcare system, the study relied on nurses who were accessible and had completed online training. While results showed nurses valued FV screening tools, the findings lacked generalizability due to the limited sample scope (Durham-Pressley, 2018).

Table 1

Study ComponentDescription
Research FocusFamily violence screening by nurses
Sampling MethodConvenience sampling
Sample CharacteristicsNurses from a rural healthcare system
LimitationLimited generalizability beyond the study context

This example highlights the necessity of acknowledging convenience sampling’s boundaries and exercising caution in interpretation.

Considerations for Ethical and Methodological Soundness

Although convenience sampling presents challenges, it remains useful in pilot and exploratory studies where time and resources are limited. Bias may be reduced through random assignment after participant recruitment. For instance, in a pilot trial of a virtual nursing intervention, convenience sampling was employed due to resource constraints, but the researchers acknowledged the restricted generalizability and advised further studies with more representative samples (Cote et al., 2018).

Ethical considerations remain critical. Paavilainen et al. (2014) emphasize that informed consent, participant privacy, and minimization of harm are essential in any study, including those using convenience samples.

Table 2 – Summary of Key Points

FactorAdvantageDisadvantage
AccessibilityQuick and easy recruitmentHigher bias risk; limited generalizability
CostMinimal financial resources neededPossible underrepresentation of groups
Use in Pilot StudiesEffective for early-stage researchFindings not broadly applicable
Ethical ConsiderationsCan still follow ethical standardsMust ensure voluntary participation and informed consent

Understanding Convenience Sampling in Healthcare Research

Also known as availability sampling, convenience sampling is popular in healthcare due to its efficiency. However, it is often criticized for introducing bias and reducing external validity.

Practical Example in Sickle Cell Research

In hydroxyurea treatment studies for sickle cell disease, including only diagnosed patients is essential. If participants without the disease were included, positive outcomes could be wrongly attributed to the drug. Additionally, excluding racial or ethnic groups beyond sub-Saharan Africa could introduce cultural and biological biases, limiting applicability (Houser, 2018).

Sampling Bias in Pharmacy Settings

A pharmacy study asking patients about a 90-day medication supply may yield biased results because insurance coverage and co-payment structures influence preferences. Similarly, during events like Hurricane Harvey, displaced patients using certain pharmacies distorted the representativeness of data (Houser, 2018).

Bias and Limitations of Convenience Sampling

Table 3 – Limitations of Convenience Sampling

LimitationExplanation
Non-representative sampleParticipants often share similar demographic traits, reducing diversity.
Sampling biasOver- or underrepresentation of certain groups.
Limited generalizabilityFindings may not apply to other populations.
Replication issuesResults may vary significantly in repeated studies.

Comparison to Other Sampling Methods

Compared with purposive or random sampling, convenience sampling lacks intentional selection. For example, in studying flipped classrooms in nursing education, purposive sampling could involve selecting students from multiple institutions, while convenience sampling might only capture those available after class, leading to less representative findings (Palinkas et al., 2015).

Snowball Sampling as a Complement

Snowball sampling can complement convenience sampling. Here, initial participants suggest additional participants, which is useful for accessing hard-to-reach populations, such as patients with rare diseases or healthcare professionals reporting medication errors (Emerson, 2015; Sheu et al., 2009).

Final Considerations in Healthcare Research

Although convenience sampling is often necessary in healthcare research due to practical limitations, researchers must remain transparent about its weaknesses. Strategies such as using strict inclusion/exclusion criteria, applying random assignment within convenience groups, and triangulating data from multiple sources can improve rigor.

Understanding Convenience Sampling and Its Implications on Research Validity

Overview of Sampling Methods and Their Impact

Sampling methods directly influence a study’s reliability and validity. While convenience sampling is practical, it undermines external validity by failing to capture diversity (Houser, 2018; Chamberlain College of Nursing, 2019).

Advantages and Disadvantages

AdvantagesDisadvantages
Quick and inexpensiveHigh risk of bias
Suitable for pilot studiesLimited generalizability
Requires minimal logistical planningNon-representative samples

Real-World Application and Bias Concerns

For example, a hospital chain piloting a policy only in its Houston branch produced favorable results due to supportive staff. However, such outcomes may not apply across branches with differing staff attitudes (Balingit, 2019).

Usefulness in Pilot Studies and Small-Scale Research

Convenience sampling is valuable in early research phases to refine methods before larger trials. Its role here is to evaluate processes, not generalize to wider populations (Iglesias, 2019; Hobbs, 2019).

Expert Insight and Criticism

Bornstein et al. (2017) caution against overreliance on convenience samples due to their homogeneity and poor reproducibility. Similarly, Ogunbanwo (2019) emphasizes that findings from one institution cannot represent broader populations.

Contextual Appropriateness and Ethical Considerations

Etikan (2016) explains that while convenience sampling offers speed, it lacks purposive sampling’s intentional selection, potentially compromising data richness. Transparency and ethical rigor are vital when applying this method.

Summary Table: Perspectives on Convenience Sampling

ContributorKey Insight
Chona BalingitInitially critical but later acknowledged utility in pilot studies.
Melissa CastroHighlighted potential bias and poor representation.
Professor HobbsSupported its cost-effective use in pilot research.
Olukayode OgunbanwoEmphasized weak external validity.
Joanne Mae YabutWarned against skewed results from homogeneity.
Etikan (2016)Compared with purposive sampling, highlighting ethical concerns.

References

Bornstein, M. H., Jager, J., & Putnick, D. L. (2017). Sampling in developmental science: Situations, shortcomings, solutions, and standards. Developmental Review, 33(4), 357–370.

Chamberlain College of Nursing. (2019). Week 4: Lesson – Considerations for Human Subject Samples. Retrieved from https://chamberlain.instructure.com

Cote, J., Fortin, M., Auger, P., Rouleau, G., Dubois, S., Boudreau, N., Vaillant, I., & Gelinas-Lemay, E. (2018). Web-based tailored intervention to support optimal medication adherence among kidney transplant recipients: Pilot parallel-group randomized controlled trial. JMIR Formative Research. https://doi.org/10.2196/formative.9707

NR 449 Week 4 Discussion: Sampling

Durham-Pressley, C. (2018). Nurse perceptions of the family violence screening process and education program in a rural healthcare system. Nursing, 48(1), 56. https://doi.org/10.1097/01.NURSE.0000527617.52655.2f

Emerson, R. W. (2015). Convenience sampling, random sampling, and snowball sampling: How does sampling affect the validity of research? Journal of Visual Impairment & Blindness, 109(2), 164–168. https://doi.org/10.1177/0145482X1510900215

Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11

Gilliland, J., Clark, A. F., Kobrzynski, M., & Filler, G. (2015). Convenience sampling of children presenting to hospital-based outpatient clinics. American Journal of Public Health, 105(7), 1332-1335.

Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Burlington, MA: Jones & Bartlett Learning.

Paavilainen, E., Lepistö, S., & Flinck, A. (2014). Ethical issues in family violence research in healthcare settings. Nursing Ethics, 21(1), 43–52. https://doi.org/10.1177/0969733013486794

NR 449 Week 4 Discussion: Sampling

Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533-544.

Sheu, S., Wei, I., Chen, C., Yu, S., & Tang, F. (2009). Using snowball sampling method with nurses to understand medication administration errors. Journal of Clinical Nursing, 18(4), 559-569. https://doi.org/10.1111/j.1365-2702.2007.02048.x