A nursing researcher wants to estimate the prevalence of gestational diabetes among pregnant women in rural India. Which of the following sampling techniques is best suited for this purpose?

1. A

   Purposive sampling

2. B

   Quota sampling

3. C

   Simple random sampling

4. D

   Snowball sampling

Appeared in: GMCH Nursing Officer-2025

Explanation

• The research goal is to 'estimate prevalence', which requires a sample that accurately represents the entire population to allow for generalization.
• Simple random sampling is a probability sampling method, which ensures that every individual in the population has an equal and independent chance of being selected.
• This method minimizes selection bias, making it the gold standard for quantitative studies aiming to estimate population-wide statistics like disease prevalence.
• Using this method allows the researcher to apply statistical tests and calculate a margin of error for the prevalence estimate, ensuring scientific rigor.

Why Other Options Were Wrong

• Option A: This is a non-probability method where the researcher uses their judgment to select participants they believe are most appropriate for the study. It is highly subjective and prone to bias, making it unsuitable for estimating population prevalence.
• Option B: This is a non-probability method where the sample is created to reflect the proportions of certain characteristics (e.g., age, socioeconomic status) in the population. However, the actual selection of individuals within each quota is non-random and often based on convenience, which introduces bias.
• Option D: This non-probability method involves participants referring other potential participants. It is used for populations that are hidden, hard-to-reach, or socially stigmatized. Pregnant women in rural India do not fit this description.

Related Visual

• Visual 1: Flowchart - A diagram distinguishing between Probability Sampling (Simple Random, Stratified, Cluster) and Non-Probability Sampling (Convenience, Quota, Purposive, Snowball), highlighting that only probability methods allow for generalization to a wider population.

Clinical Relevance

• Nursing practice connection: Knowing Sampling techniques in nursing research helps nurses interpret findings accurately and avoid errors in routine assessment, medication administration, and patient teaching.
• Understanding sampling methods is fundamental for evidence-based practice, as it allows nurses to critically evaluate the quality and generalizability of research findings before applying them to patient care.
• Nurses often participate in clinical research and quality improvement projects; knowledge of correct sampling techniques ensures that the data collected is valid and the conclusions are reliable.
• What if? If the research question was to understand the cultural beliefs and practices related to diet during pregnancy among women with gestational diabetes in a specific village, then Purposive Sampling would be a more appropriate choice to select information-rich participants.

How to Approach the Question

• First, identify the core objective of the research study from the question stem: 'to estimate the prevalence'.
• Recognize that 'prevalence' is a statistical measure intended to describe an entire population. This means the findings must be generalizable.
• Recall the two main categories of sampling: probability (random) and non-probability (non-random). Only probability sampling allows for valid generalization.
• Evaluate each option to determine its category. Simple random sampling is a probability method. Purposive, quota, and snowball sampling are all non-probability methods.
• Conclude that the only probability sampling method listed is the best choice for a study aiming to estimate population prevalence.

Concept Tested & Keywords

• Concept Tested: Sampling techniques in nursing research
• Stem keywords: estimate prevalence, gestational diabetes, pregnant women, rural India, sampling techniques
• Lead-in keywords: best suited
• Clinical cues: Age/sex group narrows the expected diagnosis, intervention, or normal reference range.
• Negative lead-in flag: false

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