Nursing

 

Discussion 6 Responses

 

Topic 1 : Using examples, compare and contrast the sampling strategies of qualitative versus quantitative research designs. Describe some advantages and disadvantages of each.

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Response 1: (Jared)

Sampling strategies us in both qualitative and quantitative research design differ and share certain qualities.  At its core sampling strategies involve elements in which possible elements in a study are taken into account. Sampling methods in application in qualitative and quantitative research design boast different strengths and weaknesses depending on their respective research design. Quota sampling and convenience sampling is typically used in qualitative studies while purposive and theoretical sampling is used in qualitative studies.

With convenience sampling researchers provide elements for inclusion in the sample based on accessibility. This form of sampling generalizes groups to review a large array of subjects. Although this form will allow more subjects, many may not contribute to the study. For instance, in a setting to determine a percentage of movie go-ers that watch action movies, this from of design will take into account everyone who goes to the movie theater. Quota sampling on the other hand selects certain elements in groups for study rather than being randomly selected. In samples such as these groups can be selected to reflect the subject population. In the same scenario previously stated, targetting those who chose to go to the movie theater, with quota sampling population by age to determine which age group better suits the population studied.

Comparative to quantitative research design, qualitative design uses different forms to achieve sampling. Purposive sampling is used by selecting distinct groups of individuals who either have lived the experience or have expertise in the event or experience being studied (Brown, 2017). In this research design, studies could hand pick movie goers that have watched action movies to sample how the group feels about said experience. In addition with Theoretical sampling, is used to collect data from initial groups to analyses and identify other groups that can be added. With this sampling style, studies can take a group that has watched an action movie for the first time, determine what age groups enjoyed the movie, and determine which age group to market advertisement of the movie to. Each form of sampling can be used in many ways and is imperative to chose correct sample sizes to maximize efficacy in research.

 

Response 2: (karen)

The type of sampling used in quantitative research are probability sampling and selected nonprobability sampling. Probability sampling methods include:

Simple random sampling: This type of sample includes subjects that are randomized so that there is an equal chance of being selected. This type of sampling is time consuming when there is a large sample.

Stratified random sampling: This type of sampling includes subjects or elements that are divided into groups or strata based on characteristics which the study has defined such as age groups. This can also be time consuming when it is a large group. An advantage is that the sampling size is more generalizable.

Cluster sampling: This type of sampling includes clustering from a large group to a smaller group to choose subjects. The disadvantage of this type of sampling is that it is more likely not a representative of the general population. The advantage is that it is less time consuming compared to other types of sampling.

Systemic random sampling: This type of sampling involves choosing subjects or elements by selecting a random start from a list. What ever the number is chosen then that will be the starting point of which the researcher will begin from the kth number. This type of sampling is easier and faster to conduct. A disadvantage is that it the generalization of the population is most likely not represented.

 

In qualitative research, nonprobability sampling is used. The different types of nonprobability sampling methods include:

Convenience sampling: This type of sampling strategy is not randomized. It uses the most available things or people to include in the study. The disadvantage of this type of study is that the representation of the sample study is not an accurate representation of the population or group being examined or researched. The advantage of this study is that it is its convenience.

Quota sampling: This type of sampling involves participants or subjects that are chosen from each stratum. The disadvantage of this type is that it may not represent the generalized population but is convenient type of sampling method.

Purposive sampling: This type of sampling is used when the desired or type of population being studied is difficult to attain or locate. Its purpose is to understand or gain insight of the event or experience being studied. The focus is not on the subjects but of the event or experience.

Theoretical sampling: This type of sampling method is used in grounded theory. The data collected is from a group of participants who were chosen after conducting preliminary questions/analysis. The disadvantage of this type of study is that is can not be used for generalization of the population.

 

Topic 2: How is data used to evaluate health outcomes within your work environment and at the national level? Provide an example for both.

 

Response 1: (chislon)

 

Data is utilized at both the immediate and national levels for health care evaluation and care plan changes. At the micro-level in individual health care settings, data from individual patients are taken into account at every step of their health management process. For example, if a patient is recovering from serious surgery, their vitals may be monitored extremely closely to ensure that healing is going according to plan. After a follow-up occurs over a long period, the outcome for that specific procedure provides a single data point that helps to inform the physicians and nurses about the efficacy of the procedure and how it may go for future patients in that setting. For patients who are on prescribed medication, blood work may be taken regularly to monitor any side effects and adjust either dosage or what pharmacotherapy is used. When the patient is responding well to the specific dosage, the care team can view it as a successful health outcome.

At the national level, data is obtained from large populations of individuals with a specific health history or condition to monitor their outcomes when given a specific treatment plan. Widespread training of health care professionals and applications of health care treatments can be adjusted when data is obtained that may go against existing methods. For instance, the structure of health care plans that work to achieve better outcomes for elderly populations with their specific goals and needs has been adjusted recently as a result of the Covid-19 pandemic (Fulmer et al., 2021). Long-term studies, especially randomized controlled trials, are especially useful for nursing practices that involve pharmaceutical interventions and their safety, side effects, and both positive and negative potential health outcomes.

 

Response 2 (Erika)

I would have to say that data is used many times in forms of statistics within the work environment and on a national level.

Statics is defined as, “The branch of mathematics that collects, analyzes, interprets, and presents numerical data in terms of samples and populations; The numerical outcomes and probabilities derived from calculations on raw data.”  (Schmidt & Brown, 2019, p 331)

For example, with COVID-19, you would hear the news what was being reported that an estimated 99% of the population was recovering from COVID-19 without any major complications. Mild cases: The majority (81%) of these coronavirus disease cases were mild cases. Mild cases include all patients without pneumonia or cases of mild pneumonia. (Roser, et al 2020, p 26). This was information being collected from the population, hospitals, clinics, etc… reporting this information as the virus spread and the effects of it was being monitored and studied. Both on a local and national level. One of the factors being note, reported and studied was that of specific treatment for symptomatic patients and results of those treatments. This was extremely helpful on a personal level and national level as more people were affected by the virus.  Providers were given protocol at hospitals on how to treat patients with specific symptoms, time frame of virus onset, and co-morbidity issues. I base some of this on personal experience because of having had family in the hospital and receiving information on how the providers communicated why they could either provide specific medication or not.

In my work environment as cases came through for case management and as data was being collected from patients with open cases for COVID-19 the number of patients who were hospitalized was being recorded in their charts and case, as where those who were almost symptom free, with limited to no treatment. The information that was being collected and studied for successful treatment of COVID-19 was extremely helpful in dealing with the cases that we saw and handled in case management. It helped in being able to determine appropriateness of treatment for approval and so forth when providers requested treatment. Considering the newness of the virus and how it was affecting the population and the newly explored forms of combating it and treating it was extremely challenging, and therefore data collection has been crucial with COVID-19 to aid providers in treatment of the virus.

 

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Solution

Discussion 6 Responses

Reply 1: (Jared)

I agree with you that the ideal sampling techniques in qualitative research is convenience and purposeful sampling. However, convenience and purposeful sampling are preferred in qualitative research because they align best with nearly all types of qualitative research designs. Researchers prefer to use purposeful sampling when they want detailed information related to given phenomena under investigation. Purposeful sampling is a very subjective approach to the recruitment of participants in particular research. An example of purposive sampling includes a student who would want to interview nurses on their perceptions of different leadership styles in a healthcare facility. On the other hand, when conducting qualitative research, researchers utilize convenience sampling as a way of recruiting participants that might be easily and conveniently accessible (Gill, 2020).

References

Gill, S. L. (2020). Qualitative Sampling Methods. Journal of Human Lactation, 36(4), 579–581.

https://doi.org/10.1177/0890334420949218

Reply 2: (Karen)

I agree with you that probability sampling approaches are important in quantitative research. Probability sampling methods allow a researcher to choose samples from a large population using methods that are based on probability theories. Probability sampling methods involve taking random selection so as to make strong statistical inferences related to a certain target population. Probability sampling methods include simple random sampling, cluster sampling, stratified and systematic sampling, therefore, have numerous benefits, which include the absence of sampling bias and systematic errors, having a higher level of reliability for research findings, having an increased accuracy-related to an estimation of sampling errors, and providing a possibility that can make inferences related to a population (Elfil & Negida, 2017).  On the other hand, the shortcomings of probability sampling include that the methods are more time-consuming, more expensive than non-probability sampling, and more complex compared to non-probability sampling (Elfil & Negida, 2017).

References

Elfil, M., & Negida, A. (2017). Sampling methods in Clinical Research; an Educational

Review. Emergency (Tehran, Iran)5(1), e52.

 

Reply 1: (Chilson)

I agree with you that data is utilized in evaluating health outcomes both at the micro and macro level. The micro-level therefore represents healthcare settings where patients seek health care services. The delivery of healthcare services to patients begins with the collection of data that can help in their diagnosis and subsequent treatment. After patients visit a Healthcare facility, the first that healthcare providers will take is to examine the patient and take their vitals while also obtaining qualitative data by interviewing such patients. Through the subjective and objective data obtained from patients through interviews and various tests, healthcare practitioners can therefore be able to make an accurate diagnosis and recommend the best treatments for their patients. On the other hand, on a macro level, the national level data is used to determine the prevalence and incidence of certain conditions and also to evaluate the effectiveness of various public health interventions (Pastorino et al., 2019).

References

Pastorino, R., de Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European Journal of Public Health, 29(Supplement_3), 23–27. https://doi.org/10.1093/eurpub/ckz168

 

Reply 2 (Erika)

I agree with you that data plays a significant role in understanding the prevalence of certain conditions, the threat they pose to public health, and also evaluating the effectiveness of various interventions that may be taken to deal with certain public health threats (Adane et al., 2019). For instance, during the Covid 19, pandemic data was utilized to evaluate the prevalence and incidence of Covid 19 and also the rate of mortality and morbidity caused by the condition. However, data was also used to evaluate the effectiveness of various public health interventions to deal with the Covid-19 in a pandemic, such as social distancing measures and the use of face masks. Currently, data is being used to evaluate the effectiveness of Covid 19 vaccines.

 

 

References

Adane, K., Gizachew, M., & Kendie, S. (2019). The role of medical data inefficient patient care delivery: a review.Risk Management and Healthcare Policy, Volume 12, 67–73. https://doi.org/10.2147/rmhp.s179259