9. Network or snowball sampling Understanding the differences in sampling techniques may aid nurses in effective appraisal of research literature and provide a reference pointfor nurses who engage in cardiovascular research. With a stratified random sample, you could use a smaller sample size to achieve the same degree of representativeness as a large sample acquired through simple random sampling. 444-445) A numerical value of a population is called a parameter. The acceptance rate is calculated by dividing the number of potential subjects who agree to participate in a study by the number of potential subjects who meet sampling criteria and multiplying the result by 100%. Purpose or purposeful sampling The number touched is the starting place. Addressing Bias in Electronic Health Record-Based Surveillance of Cardiovascular Disease Risk: Finding the Signal Through the Noise. It is a selection process that ensures each participant the same probability of being selected. Random sampling is the best method for ensuring that a sample is representative of the larger population. Random sampling can be: It is the selection process in which the probability that any one individual or subject selected is not equal to the probability that another individual or subject may be chosen. The probability of inclusion and the degree to which the sample represents the population are unknown. The major problem with nonprobability sampling is that sampling bias can occur. Nonprobability sampling can be: Suresh KP and Chandrashekara, S. Sample size estimation and power analysis for clinical research studies.Journal of Human Reprouductive Sciences. In general, the larger the sample size, the smaller the sampling error. Women were excluded if they (a) had a recurrence of breast cancer; (b) were currently taking hormone therapy, bisphosphonates, glucocorticosteroids, or other drugs affecting bone; (c) were currently engaging in ST exercises; (d) had a body mass index (BMI) of 35 or greater; (e) had serum calcium, creatinine, or thyroid stimulating hormone (if on thyroid therapy) outside normal limits; or (f) had active gastrointestinal problems or other conditions that prohibited ST exercises, risedronate, calcium, or vitamin D intake [exclusion sampling criteria]. (Twiss et al., 2009, p. 72). In selecting the study sample, the primary goal is to minimize sampling error(the discrepancy between the study sample and the target population). 69 Table 15-2 is useful only if the population number is less than 100. All of these examples use sampling techniques. The sampling frame in this study included the names of the 746 RNs who were asked to participate in the study. In nursing, nurses collect data to diagnose people in order to make decisions about their care. Because it is impossible to know the sampling error exactly, all sampling errors are approximate and are based on a calculation called the standard deviation. Four sampling designs have been developed to achieve probability sampling: simple random sampling, stratified random sampling, cluster sampling, and systematic sampling. In these types of studies, the sampling criteria need to be specific and designed to make the population as homogeneous or similar as possible to control for the extraneous variables. The variable or variables chosen for stratification need to be correlated with the dependent variables being examined in the study. Yang MF, et al. The site is secure. A sampling plan describes the strategies that will be used to obtain a sample for a study. In systematic random sampling (SYS), units are selected from the frame at regular intervals, and a sampling interval and a random start are required. If you know the refusal rate, you can also subtract the refusal rate from 100% to obtain the acceptance rate. A study might have inclusion or exclusion sampling criteria (or both). For the results to be generalizable to both male and female patients, a nurse researcher may specify that the sample will include 50% women and 50% men. doi: 10.7759/cureus.16260. This article reviews probability and non-probability sampling methods, lists and defines specific sampling techniques, and provides pros and cons for consideration. Using random sampling, the researcher cannot decide that person X would be a better subject for the study than person Y. The number of individuals in the population, who they are, how much weight they have lost, how long they have kept the weight off, and how they achieved the weight loss are unknown. Non-probability sampling involves non-random selection based on convenience or other criteria, allowing you to easily collect data. (2009) of the effects of ST exercises on muscle strength, balance, and falls of BCSs with bone loss was introduced earlier in this chapter with the discussion of sampling criteria; the following excerpt presents the acceptance rate and sample attrition for this study. 2014 Jun;61(3):105-11. doi: 10.6224/JN.61.3.105. However, even in a random sample, systematic variation can occur if potential subjects decline participation. However, many researchers use nonprobability sampling because in many cases, probability sampling is not practical, feasible, or ethical. The remaining 26 women (exercise = 14; comparison = 12) withdrew from the study before 24 months. In its popular format, descriptive research is used to describe characteristics and/or behaviour of sample population. Quantitative, outcomes, and intervention research E8-E9), within a country, state, city, hospital, nursing unit, or clinic, such as the adults with diabetes in a primary care clinic in Fort Worth, Texas. The first situation is when a simple random sample would be prohibitive in terms of travel time and cost. These researchers obtained their sample using a simple random sampling method that is described in the following excerpt from their study. The population is a particular group of people, such as people who have had a myocardial infarction, or type of element, such as nasogastric tubes, that is the focus of the research. 3 This type of research often involves a small number of participants to explore in-depth feelings, experiences and held beliefs. Attritionrate=40(numberwithdrawing)160(samplesize)=0.25100%=25% sharing sensitive information, make sure youre on a federal These studies are referred to as population studies (Barhyte, Redman, & Neill, 1990). In the first stage, 339 primary sampling units were selected from about 1,900 area sampling units representing counties, groups of adjacent counties, or metropolitan areas covering the 50 states and the District of Columbia [1st stage cluster sampling]. In this research column, we provide an introduction to these key sampling techniques and draw on examples from the cardiovascular research. The refusal rate is calculated by dividing the number of potential subjects refusing to participate by the number of potential subjects meeting sampling criteria and multiplying the results by 100%. Figure 15-2 Sampling error. For example, suppose a researcher is conducting a study of stress among medicalsurgical nurses. These samples are more likely to represent the population than samples obtained with nonprobability sampling methods. To do that, you need to collect samples from a group of individuals who all share a common trait. "Sampling theory was developed to determine the most effective was of acquiring a sample that accurately reflects the population under study. Sampleattritionrateformula=numbersubjectswithdrawingsamplesize100% Women were included if they were 35-77 years of age, had a history of stage 0 (in situ), I, or II breast cancer, a BMD [bone mineral density] T-score of 1.0 or less at any of three sites (hip, spine, forearm), were at least 6 months post breast-cancer treatment and 12 months postmenopausal, resided within 100 miles of one of four research sites (Omaha, Lincoln, Kearney, and Scottsbluff, NE), and had their physicians permission to participate [inclusion sampling criteria]. The only nursing research and theory book with primary works by the original theorists. 17. The study was conducted in obstetric intensive care units and services of all the public and university hospitals in the province of Eskisehir, Turkey. During the 4 month study, 281 patients attended for the cesarean operations to the obstetric intensive care units and services of all hospitals concerned [target population and settings]. Usually researchers report either the acceptance rate or the refusal rate but not both. 01 Attritionrate=40(numberwithdrawing)160(samplesize)=0.25100%=25%. Exclusion criteria limit the generalization of the study findings and should be carefully considered before being used in a study. The study was conducted in obstetric intensive care units and services of all the public and university hospitals in the province of Eskisehir, Turkey. During the 4 month study, 281 patients attended for the cesarean operations to the obstetric intensive care units and services of all hospitals concerned [target population and settings]. The theoretical, mathematical rationale for decisions related to sampling emerged from survey research, although the techniques were first applied to experimental research by agricultural scientists. Reasons for withdrawal included the desire for a different exercise program (n = 7); insufficient time (n = 6); intolerance to meds (n = 5); cancer recurrence (n = 5); health problems (n = 2); and relocation (n = 1). (Twiss et al., 2009, p. 22) This correlation can cause a decrease in precision and an increase in sampling error. The theoretical and mathematical rationale for sampling-related decisions evolved from survey research. (2010) clearly identified their target population as women needing cesarean operations, and the 281 women with presenting orders provided the sampling frame for the study. 3rd ed. Twiss et al. In cluster sampling, the researcher develops a sampling frame that includes a list of all the states, cities, institutions, or organizations with which elements of the identified population would be linked. 54 Many of us have preconceived notions about samples and sampling, which we acquired from television commercials, polls of public opinion, market researchers, and newspaper reports of research findings. For example, if your study examines attitudes toward acquired immunodeficiency syndrome (AIDS), the sample should represent the distribution of attitudes toward AIDS that exists in the specified population. A sample of 249 participants met the screening criteria and they were enrolled in the study. Of the 249 women, 223 completed the 24-month testing and were included in the analysis (exercise [treatment group] = 110; comparison = 113). Probability sampling methods have been developed to ensure some degree of precision in estimations of the population parameters. (2009) identified specific inclusion and exclusion sampling criteria to designate the subjects in the target population precisely. Cluster sampling is a probability sampling method applied when the population is heterogeneous; it is similar to stratified random sampling but takes advantage of the natural clusters or groups of population units that have similar characteristics (Fawcett & Garity, 2009). While less expensive, nonprobability sampling techniques are prone to selection bias and often do not produce a sample that fully represents the target population. This type is a more common method used in nursing research because of the limitations of the availability of show more content In determining whether the generalization of the study findings is appropriate based on the study sampling criteria, it is important to examine the sample inclusion and exclusion criteria (Grove, et al., 2015). Acceptancerateformula=numberpotentialsubjectsagreeingtoparticipatenumberpotentialsubjectsmeetingsamplecriteria100% A study might have inclusion or exclusion sampling criteria (or both). 77 Degirmen, Ozerdogan, Sayiner, Kosgeroglu, and Ayranci (2010, p. 153) conducted a pretest-posttest randomized controlled experimental study to determine the effect of hand and foot massage and foot massage only interventions on the postoperative pain of women who had a cesarean operation. Random sampling leaves the selection to chance and decreases sampling error and increases the validity of the study (Thompson, 2002). It's a way of measuring how much a person's personality is similar to yours. The method of achieving this opportunity is referred to as random sampling. Figure 15-1 shows the relationships among the population, target population, and accessible populations. The comparison group retention was 113 women with a retention rate of 90% (113 125 = 90.4% = 90%). In: 5. Steinke EE. Cluster sampling Researchers also need to provide a rationale for subjects withdrawing from the study and to determine if they are different from the subjects who complete the study. All samples with human subjects must be volunteer samples, which includes individuals willing to participate in the study, to protect the rights of the individuals (Fawcett & Garity, 2009). Generalizing means that the findings can be applied to more than just the sample under study because the sample is representative of the target population. However, this study may systematically underrepresent employed adults who were unable to answer the phone during work hours, therefore limiting the generalizability of the study. In addition, a researcher cannot exclude a subset of people from selection as subjects because he or she does not agree with them, does not like them, or finds them hard to deal with. In descriptive or correlational studies, the sampling criteria may be defined to ensure a heterogeneous population with a broad range of values for the variables being studied. Systematic bias increases as the subjects refusal rate increases. 72 An accessible population is the portion of the target population to which the researchers have reasonable access. Alexa Colgrove Curtis is assistant dean of graduate nursing and director of the MPHDNP dual degree program and Courtney Keeler is an associate professor, both at the University of San Francisco School of Nursing and Health Professions. One of the most important surveys that stimulated improvements in sampling techniques was the U.S. census. Sampling Design in Nursing Research Editor's note: This is the third article in a series on clinical research by nurses. Sampling criteria may include characteristics such as the ability to read, to write responses on the data collection instruments or forms, and to comprehend and communicate using the English language. 2023 Feb 4;11(4):452. doi: 10.3390/healthcare11040452. The accuracy with which the population parameters have been estimated within a study is referred to as precision. For example, a narrow definition of the accessible population reduces the ability to generalize from the study sample to the target population and diminishes the meaningfulness of the findings. For example, a narrow definition of the accessible population reduces the ability to generalize from the study sample to the target population and diminishes the meaningfulness of the findings. Purposeful sampling, also known as selective sampling, is used in both quantitative and qualitative research. 2021 Jan 1;121(1):64-67. doi: 10.1097/01.NAJ.0000731688.58731.05. Accessible potential research participants who meet the research subject selection criteria create the sampling frame from which the study sample is drawn. A sample of 249 participants met the screening criteria and they were enrolled in the study. Of the 249 women, 223 completed the 24-month testing and were included in the analysis (exercise [treatment group] = 110; comparison = 113). The difference is random because the value of each subject is likely to vary in a different direction.
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