Name
Chamberlain University
NR-449 Evidence-Based Practice
Prof. Name
Date
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).
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 Component | Description |
---|---|
Research Focus | Family violence screening by nurses |
Sampling Method | Convenience sampling |
Sample Characteristics | Nurses from a rural healthcare system |
Limitation | Limited generalizability beyond the study context |
This example highlights the necessity of acknowledging convenience sampling’s boundaries and exercising caution in interpretation.
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
Factor | Advantage | Disadvantage |
---|---|---|
Accessibility | Quick and easy recruitment | Higher bias risk; limited generalizability |
Cost | Minimal financial resources needed | Possible underrepresentation of groups |
Use in Pilot Studies | Effective for early-stage research | Findings not broadly applicable |
Ethical Considerations | Can still follow ethical standards | Must ensure voluntary participation and informed consent |
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.
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).
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).
Table 3 – Limitations of Convenience Sampling
Limitation | Explanation |
---|---|
Non-representative sample | Participants often share similar demographic traits, reducing diversity. |
Sampling bias | Over- or underrepresentation of certain groups. |
Limited generalizability | Findings may not apply to other populations. |
Replication issues | Results may vary significantly in repeated studies. |
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 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).
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.
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 | Disadvantages |
---|---|
Quick and inexpensive | High risk of bias |
Suitable for pilot studies | Limited generalizability |
Requires minimal logistical planning | Non-representative samples |
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).
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).
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.
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
Contributor | Key Insight |
---|---|
Chona Balingit | Initially critical but later acknowledged utility in pilot studies. |
Melissa Castro | Highlighted potential bias and poor representation. |
Professor Hobbs | Supported its cost-effective use in pilot research. |
Olukayode Ogunbanwo | Emphasized weak external validity. |
Joanne Mae Yabut | Warned against skewed results from homogeneity. |
Etikan (2016) | Compared with purposive sampling, highlighting ethical concerns. |
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
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
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