Because of space restrictions, this editorial focuses on the randomised controlled trial (RCT) as an example of quantitative research,and grounded theory as an exampleofqualitativeresearch . While the purpose of stratified random sampling is to improve participant representation, the purpose of cluster sampling is to improve sampling efficiency, thus reducing time and cost.3. Inferential statistical analyses are based on the assumption that the sample from which data were derived has been obtained randomly. Sampling Theory and Generalizability in Nursing Research Sampling theory refers to the study of the relationships that exist between a population and the samples which are drawn from a population. A refusal rate is the number and percentage of subjects who declined to participate in the study. Research ethics, informed consent, and participant recruitment. 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. These studies are referred to as, In some cases, a hypothetical population is defined for a study. and transmitted securely. Representativeness is usually evaluated by comparing the numerical values of the sample (a statistic such as the mean) with the same values from the target population. Please enable it to take advantage of the complete set of features! In large population sets, elements may already have assigned numbers. 444-445). What Is Sampling Theory in Nursing Research? Hainer V, et al. In the example just presented with a sample size of 160, if 40 subjects withdrew from the study, then 120 subjects were retained or completed the study. Sampling theory describes two sampling domains: probability and nonprobability. Potential subjects cannot be excluded just because they are too sick, not sick enough, coping too well, or not coping adequately. Nutrients. 2012 Jan;5(1):7-13. doi: 10.4103/0974-1208.97779. The second situation is in cases in which the individual elements making up the population are unknown, preventing the development of a sampling frame. 85 If the first name is not replaced, the remaining 49 names have a 9 in 49 chance, or a 0.18 probability, of being selected. 18. Cluster sampling provides a means for obtaining a larger sample at a lower cost. Systematic variation or bias is most likely to occur when the sampling process is not random. Perspectives on Emotional Care: A Qualitative Study with Cancer Patients, Carers, and Health Professionals. The accuracy with which the population parameters have been estimated within a study is referred to as precision. There is less opportunity for systematic bias if subjects are selected randomly, although it is possible for a systematic bias to occur by chance. 20 The sample retention was 223 women for a retention rate of 90% (223 249 100% = 89.6% = 90%), and the sample attrition rate was 26 women for an attrition rate of 10% (100% 90% = 10%). AJN The American Journal of Nursing121(3):53-57, March 2021. In some cases, this random selection continues through several stages and is referred to as multistage cluster sampling. 91 TABLE 15-1 This situation could occur, for example, if all the subjects were college students, which has been the case in the development of many measurement methods in psychology. Probability (Random) Sampling Methods Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. 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). There are two main categories of sampling methods: probability and non-probability. Survey sampling issues in primary care research. For instance, the researcher could require that 30% of the sample have an admission diagnosis of chronic obstructive pulmonary disease. It is used to measure a concept of interest. 06 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. Stigmatization and mental health in a diverse sample of transgender women. Sampling theory in medical science is a study of gathering information about a population by investigating only a part of it. Many of these studies use data available in large databases, such as the census data or other government-maintained databases. There are still many purposive methods of nonprobability sampling that researchers employ to approximate the population of interest. official website and that any information you provide is encrypted (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. Application of simple random sampling and the attrition of only three (4%) subjects from the study seem to provide a sample representative of the target population. Conlon C, et al. Freedman D, et al. Twiss et al. 58 The sampling plan provides detail about the application of a sampling method in a specific study. In some cases, this random selection continues through several stages and is referred to as, Click to share on Twitter (Opens in new window), Click to share on Facebook (Opens in new window), Click to share on Google+ (Opens in new window). Reasons for withdrawal included the desire for a different exercise program (. FOIA HHS Vulnerability Disclosure, NLM Support Center Sampling error reduces the power of a study, or the ability of the statistical analyses conducted to detect differences between groups or to describe the relationships among variables (Aberson, 2010; Cohen, 1988). Precision in estimating parameters requires well-developed methods of measurement that are used repeatedly in several studies. Twiss et al. Imagine trying to arrange personal meetings with 100 people, each in a different part of the United States. Keywords: nurses, male, turnover, adaptation, grounded theory, qualitative research Introduction Because of rapidly changing medical policies and changes in awareness about nursing . The eligible RNs were those who had a functioning work e-mail account and who worked fulltime, on inpatient units, providing direct patient care. (Djukic et al., 2010, pp. 2021 Jul 24;13(8):2529. doi: 10.3390/nu13082529. Random variation is the expected difference in values that occurs when one examines different subjects from the same sample. For example, individuals who successfully lose weight would be a hypothetical population. Quantitative, outcomes, and intervention research Sample attrition rate is calculated by dividing the number of subjects withdrawing from a study by the, ment receives usual or standard care and is generally referred to as a. parameters of the population, have a chance to be represented in the sample. As the sample size becomes larger, overall variation in sample values decreases, with more values being close to the sample mean. 39 Sampling error occurs as a result of random variation and systematic variation. For example, if the researcher is selecting 10 subjects from a population of 50, the first name has a 1 in 5 chance (10 draws, 50 names), or a 0.2 probability, of being selected. An official website of the United States government. 32 Each approach offers distinct advantages and disadvantages and must be considered critically. In other studies, the entire population of interest in the study is small and well defined. Editor's note: This is the third article in a series on clinical research by nurses. The sampling methods to be included in this text are identified in Table 15-1 and are linked to the types of research that most commonly incorporate them. Recruitment of hard-to-reach population subgroups via adaptations of the snowball sampling strategy. Sometimes researchers provide an acceptance rate, or the number and percentage of the subjects who agree to participate in a study, rather than a refusal rate. Exclusion criteria limit the generalization of the study findings and should be carefully considered before being used in a study. Usually researchers report either the acceptance rate or the refusal rate but not both. The term subject, and sometimes research participant, is used within the context of the postpositivist paradigm of quantitative research (see Chapter 2). Sampling Methods Probability sampling (random sampling) It is a selection process that ensures each participant the same probability of being selected. Weight gain and blood pressure in toddlers born very preterm. 10 Burlington, MA: Jones and Bartlett Learning; 2020. A study might have inclusion or exclusion sampling criteria (or both). Because of the importance of generalizing, there are risks to defining the accessible population too narrowly. In experimental studies that use a control group, subjects are randomly selected and randomly assigned to either the control group or the experimental group. Sampling error limits generalizability and research accuracy (validity) by introducing bias into the study. 25 Subjects may be limited to individuals who are not participating in any other study. 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). Contact author: Alexa Colgrove Curtis, [emailprotected]. In these cases, it is often possible to obtain lists of institutions or organizations with which the elements of interest are associated. Epidemiologists sometimes use entire populations for their large database studies. 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. You may also needUsing Statistics to Determine DifferencesUsing Statistics to Describe VariablesMeasurement ConceptsUsing Statistics to PredictSelecting a Quantitative Research DesignCollecting and Managing DataFrameworksDisseminating Research Findings Theoretical sampling is a qualitative sampling technique that evolves over the course of a study as the researcher begins to understand more from the emerging data. For example, if 200 potential subjects met the sampling criteria, and 40 refused to participate in the study, the refusal rate would be 20%. 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. For example, if the researcher draws names out of a hat to obtain a sample, each name must be replaced before the next name is drawn to ensure equal opportunity for each subject. This study included clearly identified inclusion and exclusion sampling or eligibility criteria that are presented in the following excerpt. 55 Because the subjects have something in common, their values tend to be similar to the values of others in the sample but different in some way from the values of the population as a whole. This study included clearly identified inclusion and exclusion sampling or eligibility criteria that are presented in the following excerpt. These biases are similar to biases that may be encountered in a nonrandom sample (Thompson, 2002). According to sampling theory, it is impossible to select a sample randomly from a population that cannot be clearly defined. These researchers obtained their sample using a simple random sampling method that is described in the following excerpt from their study. 11. The likelihood is increased that the sample is representative of the target population and the results are an accurate reflection of reality. 69 About 1,300 staff RNs [population] were employed at the hospital at the time of the study. A total of 746 RNs who met eligibility criteria were invited to participate in the study [sampling frame of target population]. With a comparison group, there is an increase in the possibility of preexisting differences between that group and the experimental group receiving the treatment. In studies involving a treatment, subjects in the control group who do not receive the treatment may be more likely to withdraw from the study. Sampling decisions have a major impact on the meaning and generalizability of the findings. To avoid disparities in the representation of any one hospital in a random sample of clinical nurses within the health care system, the researcher can use stratified random sampling to randomly select a designated number of nurses within each hospital. These studies are referred to as population studies (Barhyte, Redman, & Neill, 1990). 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. Random sampling increases the extent to which the sample is representative of the target population. When a systematic bias occurs in an experimental study, it can lead the researcher to believe that a treatment has made a difference when, in actuality, the values would be different even without the treatment. Cutcliffe JR, et al. Cluster sampling is the process of randomly selecting complete groups (clusters) of population units from the survey frame. When the study is complete, the findings are generalized from the sample to the accessible population and then to the target population if the study has a representative sample (see the next section). For a sample to be representative, it must be similar to the target population in as many ways as possible. For example, if stratification is being achieved by ethnicity and the population is 45% white non-Hispanic, 25% Hispanic nonwhite, 25% African American, and 5% Asian, your research team would have to decide whether to select equal numbers of each ethnic group or to calculate a proportion of the sample. There are many types of sampling methods, but most sampling falls into two main categories: probability sampling, and non-probability sampling. 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. An official website of the United States government. Exclusion criteria limit the generalization of the study findings and should be carefully considered before being used in a study. 17. Thus, a study that uses random sampling techniques may have such restrictive sampling criteria that the sample is not truly random. That said, the researcher must be alert to a number of methodological and ethical pitfalls associated with recruitment and retention.18 Recruitment techniques such as monetary incentives for participation may bias the study outcome; and the extent that subjects systematically discontinue participation in the study may disrupt the balance of the study sample, creating threats to generalizability and study validity. The sampling theory . The method of achieving this opportunity is referred to as random sampling. Cluster Sampling Methods of achieving random sampling are described later in the chapter. The study would have been strengthened if the researchers would have included not only the numbers but also the sample and group retention rates. The opposite of the attrition rate is the, 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). Am J Nurs. For example, the researcher places a pencil on 58 in Table 15-2, which is in the fourth column from the left and fourth row down. 3 This type of research often involves a small number of participants to explore in-depth feelings, experiences and held beliefs. Misrepresenting random sampling? The aim of sampling is to approximate a larger population on characteristics relevant to the research question, to be representative so that researchers can make inferences about the larger population. There are two main categories of sampling methods: probability and non-probability. Common methods of probability sampling include the following6: In simple random sampling, study participants are randomly selected from the sampling frame using a randomization mechanism, as previously discussed. It is important that assessment techniques possess both validity and reliability. Most of the variation from the mean is in the same direction; it is systematic. The results of a study that has assembled its sample appropriately can be more confidently applied to the population from which the sample came. The study was conducted at a large urban hospital in the U.S. northeast region that is a nongovernment, not-for-profit, general medical and surgical major teaching hospital. Instead, researchers study a sample to make estimates about the total population. The only nursing research and theory book with primary works by the original theorists. High refusal rates to participate in a study have been linked to individuals with serious physical and emotional illnesses, low socioeconomic status, and weak social networks (Neumark, Stommel, Given, & Given, 2001). The series is designed to give nurses the knowledge and skills they need to participate in research, step by step. 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 833 NPs and 689 PAs add to 1522 subjects and it is unclear why the sample size is identified as 1536 unless there are missing data from subjects. Stratified Random Sampling to maintaining your privacy and will not share your personal information without
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. Thus, a study that uses random sampling techniques may have such restrictive sampling criteria that the sample is not truly random. A sampling method is the process of selecting a group of people, events, behaviors, or other elements that represent the population being studied. . Random sampling leaves the selection to chance and decreases sampling error and increases the validity of the study (Thompson, 2002). Persons who are able to participate fully in the procedure for obtaining informed consent are often selected as subjects. These criteria ensure a large target population of heterogeneous or diverse potential subjects. J Adv Nurs. Sampling Plan The researcher selects subjects from the sampling frame using a sampling plan. These inclusion and exclusion sampling criteria were appropriate for the study to reduce the effect of possible extraneous variables that might have an impact on the treatment (ST exercises) and the measurement of the dependent variables (muscle strength, balance, and falls). Chang SF, Chuang MH. sharing sensitive information, make sure youre on a federal Sampling. Minimizing sampling error. Researchers also should be aware of sampling error. From the population we take a sampling to create the sample size. Not having the time or budget to administer a survey to all 200 nurses, the researcher chooses instead to randomly select a sample of 50 nurses using a computerized randomization tool. The researcher can use a computer to select these numbers randomly to obtain a sample. In addition, a sample must represent the demographic characteristics, such as age, gender, ethnicity, income, and education, which often influence study variables. Systematic bias increases as the subjects refusal rate increases. The final sample was large (1536 subjects) with strong representation for both NPs (833 subjects) and PAs (689 subjects).
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