Sampling peer response

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Sampling methods and sizes

Whether quantitative or qualitative research is being conducted, the sample size must be a good representation of what is being researched and large enough to yield the results needed (EL-MASRI, 2017). The sample size can be randomly selected (probability sampling) or carefully based on specific criteria. Quantitative research is statistical and allows the researcher to select a larger, more extensive, and diverse population (Gray et al., 2017).

On the other hand, qualitative research tends to have a smaller sample size since it relies more on open-ended questions about the person’s ideas, personal experiences, and descriptions of events using non-numerical data (Gray et al., 2017).

Chosen sampling method and reason

The sampling method that I would use to conduct my study on collaborative care for patients with mental illness and comorbidities would be probability sampling (Gray et al., 2017). Probability sampling (randomized sampling) allows for randomly selecting a group of people from a specific population. This type of sampling is less time-consuming, cost-effective, and minimizes the risk of biased sampling (Gray et al., 2017). Probability sampling can be further categorized as simple random sampling, stratified random sampling, systematic sampling, cluster sampling, and multistage sampling (Bhardwaj, 2019).  

Determining the sample type and size

I would start my study with Stratified Random Sampling. My sample would include Physicians and Mental Health Professionals from primary care practice, hospitals, and community centers. I would specify the classifications, such as age, gender, religion, race, etc., and make sure that the variables match the study’s objectives (Bhardwaj, 2019). I would assign a unique number to each person, separate the Physicians and Therapists into two groups, my strata groups, and randomly draw 50 numbers from each group. Studies show that results are higher when your sample elements are chosen from a specific strata (Bhardwaj, 2019).

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Sampling- peer response

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Comparing Sampling Methods and Sample Sizes for Quantitative versus Qualitative Research

For quantitative research, sampling methods can be categorized as probability or non-probability. Probability sampling ensures that each member of the population has a greater than zero chance of being selected for the sample, while non-probability sampling does not guarantee equal representation of the population (Groves et al., 2017). Common probability sampling methods include simple random sampling, stratified random sampling, cluster sampling, and systematic sampling. Non-probability sampling methods for quantitative research include convenience sampling, quota sampling, purposive sampling, and snowball sampling. The sample size in quantitative research is determined through statistical calculations based on the desired level of precision and confidence in the results.

In qualitative research, sampling methods are generally non-probability, as the goal is often to gain insight and discover the meaning of a particular phenomenon rather than to generalize. Three common sampling methods in qualitative research include purposive sampling, snowball sampling, and theoretical sampling. The sample size in qualitative research is often determined by saturation of data, which occurs when additional sampling no longer provides additional information, only redundancy (Groves et al., 2017).

Sampling Method for Selected Evidence-Based Practice

A randomized controlled trial (RCT) using a probability sampling method would be appropriate to research whether regular aerobic exercise results in reduced symptoms of depression for adults with depression. A simple random sampling method can be used to select participants from a larger pool of adults with depression who meet the study’s criteria, this ensures that the results are representative of the population. This helps to minimize bias and increase the generalizability of the findings. Randomization also helps to control selection threat and increase the internal validity of the study (Groves et al., 2017).

Determining Sample Type and Size for Selected Evidence-Based Practice

The sample type for my selected topic must be representative of the population of interest, and that would be adults diagnosed with depression who are not currently engaged in regular aerobic exercise. The sample should be selected using a probability sampling method, such as simple random sampling, to ensure that every eligible individual in the population has an equal chance of being selected for the study. The sample size should be large enough to achieve sufficient power to detect a significant effect of regular aerobic exercise on symptoms of depression. The sample size calculation should be based on statistical methods that take into account the study design, expected effect size, level of significance, and desired power (Karakaya & Alparslan, 2022). 

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