Study Subject Selection, Sampling, and Measurements Paper

Study Subject Selection, Sampling, and Measurements Paper

Study Subject Selection, Sampling, and Measurements Paper

In communities and health care institutions, health care professionals come across people with varying health needs. As professionally and ethically mandated, health care professionals should explore health problems in-depth and provide evidence-based solutions. Research from systematic reviews, randomized controlled trials, and other sources is the foundation of evidence-based practice. Since research is demanding and time-consuming, researchers should select a convenient sample whose findings can be generalized to represent the health state of a broader population. The purpose of this paper is to describe the target population of the study. Other sections include inclusion and exclusion criteria, the sampling method, and the estimated sample size.

Target Population and Intended Sample

Researchers make decisions based on data from samples. As a result, they should get adequate samples from the target population. For this study, the target population is people suffering from THC intoxication. The hypothesis is that CBD can effectively treat THC intoxication, which is critical in improving public health. According to Nieswiadomy and Bailey (2018), it is impractical to study the entire population hence the need for a sample. Study populations consist of the target and the accessible population. To ensure research completeness and make valid deductions, the sample will comprise patients with THC intoxication presenting seeking medication help.

Inclusion and Exclusion Criteria

Samples contain different elements depending on the research objectives and time available, among other elements. To qualify for inclusion, the subjects must have at least one sign of THC intoxication. They also need to be accessible throughout the study period and willingly participate. Besides, the participants should be of sound mind and without a co-occurring disorder. Underage subjects and those undergoing treatment through other options apart from CBD will be excluded. No subject will be excluded based on gender to create a truly representative sample.

Defining the Population

Health care researchers can explore health problems affecting health outcomes in health care organizations or an issue hampering community health. The primary objective should be developing interventions to promote health in a prioritized or at-risk population. The population for this cannabis research is a clinical population. Different from a community population, a clinical population consists of people possessing some common characteristics related to public health. Such a population usually visits health care facilities for health assistance, and illness manifestation can be clinically determined. Also, the question formulated for research is a clinical question. The aim is to explore the effectiveness of CBD on THC from a clinical dimension.

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Probability vs. Non-probability Sampling

Researchers must do everything possible to provide accurate deductions. According to Nieswiadomy and Bailey (2018), researchers can make valid claims about the population based on data from the sample alone when they choose it properly. As a result, the most effective sampling method for this study is probability sampling. Also called random sampling, probability sampling involves a random selection process to obtain a sample from population members (Nieswiadomy & Bailey, 2018). The primary goal of probability sampling is to obtain representative elements of the population. Similarly, the sampled population will represent the population of people with THC.

Sampling methods affect research outcomes and accuracy depending on their strengths and limitations. Probability sampling is a systematic, scientific process. The researcher specifies the chance of the subject being selected for the sample. Since selections are independent of each other, researchers prevent investigator bias in sample selection (Foulkes et al., 2020). Other advantages include a greater ability to generalize findings and using inferential statistics with greater confidence. Despite the minimal bias, there is no guarantee that variables of interest in the population will be present in the sample. Probability sampling only allows the researcher to estimate the chance of a subject being included in the sample.

Non-probability sampling is an approach where not all members of the study population get an equal chance for selection to participate in the study. Nieswiadomy and Bailey (2018) posited that most researchers choose non-probability sampling due to its convenience and the desire to use the available subjects. Unfortunately, non-probability sampling is more likely to produce a biased sample than random selection. Besides, some population elements may not have any chance to be included in the sample. The high exclusion probability restricts the generalizations that researchers can make about the study findings (Foulkes et al., 2020). Due to these shortcomings, probability sampling is the best for the current study since the effectiveness of the treatment method should be generalized.

The Sample Size

The sample size is a critical research consideration. Since the current study examines the efficacy of a treatment option, small sample size can be used. Some research subjects will be offered CBD, and an equally assigned group will not be offered the treatment. Vasileiou et al. (2018) conjectured that too small samples should be avoided since they prevent extrapolating the findings. As a result, convenient small sample size will be selected. The probability of amplifying the detection of differences increases as the sample size expands. As a result, small sample size will prevent emphasizing non-clinically significant statistical differences.

Conclusion

Researchers select samples from a target population. As described in this paper, a target population comprises the entire group of people in which the researcher wants to generalize the study findings. The sample should contain an accessible population and people willing to participate in the study. Researchers must also use an appropriate sampling method to ensure valid deductions. Probability sampling is the most effective for this study since it gives the subjects an equal chance to be included in the sample. Since the study evaluates the efficacy of CBD on THC intoxication, small sample size can be used.

References

Foulkes, A. S., Balasubramanian, R., Qian, J., & Reilly, M. P. (2020). Non-random sampling leads to biased estimates of transcriptome association. Scientific Reports, 10(1), 1-9. https://doi.org/10.1038/s41598-020-62575-x

Nieswiadomy, R. M., & Bailey, C. (2018). Foundations of nursing research. Pearson.

Vasileiou, K., Barnett, J., Thorpe, S., & Young, T. (2018). Characterising and justifying sample size sufficiency in interview-based studies: Systematic analysis of qualitative health research over a 15-year period. BMC Medical Research Methodology, 18(1), 1-18. https://doi.org/10.1186/s12874-018-0594-7

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Submit your plan and strategy for study subject selection, sampling, and measurements. Use the assigned textbook chapter as a guide and provide examples, references, and citations to support your rationale. Answer and include the following prompts in your submission: (Paragraph/Essay style; 500-1000 words)
What is your target population? What is your intended sample?
What are your inclusion and exclusion criteria? How will your criteria create a truly representative sample?
Is your population a clinical population or a community population?
Will you utilize probability or non-probablity sampling? What are the advantages and disavantages of each type of sampling?
Based on the features of your target population, estimate what sample size is likely to be necesary: (“small” vs “large”) and explain why. No numerical values are necessary.