what is sampling theory in nursing research

In any case, it is rarely possible to obtain a purely random sample for nursing studies because of informed consent requirements. This study included clearly identified inclusion and exclusion sampling or eligibility criteria that are presented in the following excerpt. 22 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. Using random sampling, the researcher cannot decide that person X would be a better subject for the study than person Y. Figure 15-1 Population, sample, and subject selected for a study. Please try after some time. 20 2021 Jul 24;13(8):2529. doi: 10.3390/nu13082529. A diagram showing the connection betweenpopulation andsample size. This listing of members of the population is referred to as the, Probability sampling methods have been developed to ensure some degree of precision in estimations of the population parameters. network sampling (otherwise known as snowball sampling). The following sections explain these concepts; later in the chapter, these concepts are used to explain various sampling methods. Probability sampling methods have been developed to ensure some degree of precision in estimations of the population parameters. Another technique is to assign a number to each name in the sampling frame. An element can be a person, event, behavior, or any other single unit of study. Data from subjects associated with the same institution are likely to be correlated and not completely independent. 56 Systematic variation is greatest when a high number of subjects withdraw from the study before the data have been collected or when a large number of subjects withdraw from one group but not the other in the study (Kerlinger & Lee, 2000; Thompson, 2002). Table 15-2 is useful only if the population number is less than 100. Bookshelf 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). Random variation is the expected difference in values that occurs when one examines different subjects from the same sample. Recruitment of hard-to-reach population subgroups via adaptations of the snowball sampling strategy. Highlight selected keywords in the article text. Grounded theory (GT) is a research method concerned with the generation of theory,1 which is 'grounded' in data that has been systematically collected and analysed.2 It is used to uncover such things as social relationships and behaviours of groups, known as social processes.3 It was developed in California, USA by Glaser and Strauss during their study'Awareness of Dying'.1 It is a . Sample surveys. Nonprobability sampling. 12. One of the most important surveys that stimulated improvements in sampling techniques was the U.S. census. Instead, they would recruit a sample of lung cancer patients, such as willing participants from a regional oncology center. Sampling theory was developed to determine mathematically the most effective way to acquire a sample that would accurately reflect the population under study. 2021 Jan 1;121(1):64-67. doi: 10.1097/01.NAJ.0000731688.58731.05. This pointthat studying an entire population is, in most cases, unnecessaryis the key to the theory of sampling. Data collection continues until theoretical saturation is achieved.12 For example, as the nurse researcher begins to understand more about the context of early opioid initiation in the study example, the researcher might choose to intentionally sample participants with similar experiences, such as a history of adverse childhood events. Representativeness of the sample refers to how well aligned the study sample is to the target population.2 In an ideal setting, a study sample would perfectly mirror the target population; however, this, as we know, is impossible. To study the prevalence of elder abuse in nursing homes, Schiamberg and colleagues conducted a random digit-dialing telephone survey of noninstitutionalized adults in Michigan who have a relative in long-term care. Many of these studies use data available in large databases, such as the census data or other government-maintained databases. Keywords: nurses, male, turnover, adaptation, grounded theory, qualitative research Introduction Because of rapidly changing medical policies and changes in awareness about nursing . The criteria are developed from the research problem, the purpose, a review of literature, the conceptual and operational definitions of the study variables, and the design. 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). If equal numbers of each group are used, each group would contain at least 25 subjects; however, the white non-Hispanic group would be underrepresented. The advertiser boasts that four of five doctors recommend its product; the newscaster announces that John Jones is predicted to win the senate election by a margin of 3 to 1; the newspaper reports that scientists studies have found that taking a statin drug, such as atorvastatin (Lipitor), significantly reduces the risk of coronary artery disease. Selection without replacement gives each element different levels of probability for selection. The sampling component is an important part of the research process that needs to be carefully thought out and clearly described. A heterogeneous sample increases your ability to generalize the findings to a larger target population. HHS Vulnerability Disclosure, Help While recruitment and retention of research subjects can be one of the most challenging aspects of sampling, strategic messaging, relationship building, and financial incentives may facilitate the process. Selection bias and sampling plan. 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. The sample selection strategy (the sampling plan) is constructed with the intent to minimize selection bias in the selection of participants from within the sampling frame. One of the most important surveys that stimulated improvements in sampling techniques was the U.S. census. sharing sensitive information, make sure youre on a federal A, You might identify broad sampling criteria for a study, such as all adults older than 18 years of age able to read and write English. A sampling plan defines selecting a sample; a sample refers to the chosen group of individuals or items of study. 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. Exclusion criteria limit the generalization of the study findings and should be carefully considered before being used in a study. 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 most common method of random selection is the computer, which can be programmed to select a sample randomly from the sampling frame with replacement. Acceptancerate=160(numberaccepting)200(numbermeetingsamplingcriteria)=0.8100%=80%, Acceptancerate=100%refusalrateor100%20%=80%. However, the study would have been strengthened by a discussion of the process for random sampling and a clarification of how the subjects were assigned to groups. Critical questions are provided to help researchers choose a sampling method. Twiss et al. The sampling method implemented in a study varies with the type of research being conducted. Knowledge of sampling methods is essential to design quality research. Sampling error is usually larger with small samples and decreases as the sample size increases. For example, if a study had a sample size of 160, and 40 people withdrew from the study, the attrition rate would be 25%. Nursing Research, Step by Step is coordinated by Bernadette Capili, PhD, NP-C: [emailprotected] The authors have disclosed no potential conflicts of interest, financial or otherwise. (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. Sampling refers to the process used to select a portion of the population for study. While more cost-effective and often more convenient, nonprobability sampling increases the risk of sampling bias and therefore limits generalizability and creates threats to research validity. Key concepts of sampling theory are (1) populations, (2) elements, (3) sampling criteria, (4) representativeness, (5) sampling errors, (6) randomization, (7) sampling frames, and (8) sampling plans. 2014 Jun;61(3):105-11. doi: 10.6224/JN.61.3.105. E8-E9) Selection with replacement, the most conservative random sampling approach, provides exactly equal opportunities for each element to be selected (Thompson, 2002). Each approach offers distinct advantages and disadvantages and must be considered critically. People who do not have access to care are usually excluded from health-focused studies. 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. Biases may be introduced that make generalization to the broader target population difficult to defend. National Library of Medicine sharing sensitive information, make sure youre on a federal The series is designed to give nurses the knowledge and skills they need to participate in research, step by step. Four sampling designs have been developed to achieve probability sampling: simple random sampling, stratified random sampling, cluster sampling, and systematic sampling. Researchers need to provide logical reasons for their inclusion and exclusion sampling criteria, and certain groups should not be excluded without justification. Sampling, data collection, and data analysis. For example, there is no list of all the heart surgery patients who complete rehabilitation programs in the United States. Variables commonly used for stratification are age, gender, ethnicity, socioeconomic status, diagnosis, geographical region, type of institution, type of care, care provider, and site of care. To enhance representativeness of the sample, researchers attempt to align the study sample with the target population on as many characteristics as possible. Your sampling decisions heavily influence the validity of the findings. An accessible population is the portion of the target population to which the researchers have reasonable access. There is less opportunity for systematic bias if subjects are selected randomly, although it is possible for a systematic bias to occur by chance. (608) 262-2020 The sampling strategy employed is of utmost importance to ensure that a representative sample of participants is chosen. Some values are higher and others are lower than the sample mean. The use of a computer to select a sample randomly is usually the most efficient and unbiased process. In purposeful sampling, the researcher intentionally recruits participants based on population, exposure, experience, or outcome to obtain information-rich data relating to a phenomenon of interest.2, 11 For example, a nurse researcher may want to purposefully select young adults who began using opioids during adolescence within a rural community for a contextual examination of opioid use initiation. 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]. 85 Sampling Theory. In addition, a sample must represent the demographic characteristics, such as age, gender, ethnicity, income, and education, which often influence study variables. In a third step, clusters of dwelling units form the secondary sampling units selected from each substratum [3rd stage cluster sampling]. The difference is random because the value of each subject is likely to vary in a different direction. National Library of Medicine Cluster sampling is used in two situations. Finally, within each secondary sampling unit, all African American and Hispanic households were selected for interviews, whereas other households were sampled at differing rates within the substrata. Because of the importance of generalizing, there are risks to defining the accessible population too narrowly. The acceptance rate, the sample and group retention rates, and the reasons for subjects attrition indicate limited potential for systematic variation in the study sample. 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. Data is temporarily unavailable. modify the keyword list to augment your search. 13 If 20% of the nursing target population is male, ideally, 20% of the study sample would be male as well. Sample surveys. 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. The final sample was large (1536 subjects) with strong representation for both NPs (833 subjects) and PAs (689 subjects). In: 7. Perspectives on Emotional Care: A Qualitative Study with Cancer Patients, Carers, and Health Professionals. Cluster Sampling Continuing with the opioid example above, the nurse researcher may ask study participants who started opioid use during adolescence to recruit other participants with a similar substance use history. There are two main categories of sampling methods: probability and non-probability. What is Sampling Theory in Nursing Research? Retentionrate=120(numberretained)160(samplesize)=0.75100%=75% One question that arises in relation to stratification is whether each stratum should have equivalent numbers of subjects in the sample (termed disproportionate sampling) or whether the numbers of subjects should be selected in proportion to their occurrence in the population (termed proportionate sampling). Research ethics, informed consent, and participant recruitment. Simple Random Sampling 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). 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]. Most textbooks on sampling describe this procedure (Levy & Lemsbow, 1980; Thompson, 2002; Yates, 1981). 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. Network sampling helps recruit study participants who might otherwise be difficult to reach. Steinke EE. The method of achieving this opportunity is referred to as random sampling. Subjects may be limited to individuals who are not participating in any other study. Before In some studies, the entire population is the target of the study. Exclusion criteria limit the generalization of the study findings and should be carefully considered before being used in a study. 93 2012 Jan;5(1):7-13. doi: 10.4103/0974-1208.97779. Djukic, Kovner, Budin, and Norman (2010) studied the effect of nurses perceived physical work environment on their job satisfaction and described their sampling frame in the following excerpt. Editor's note: This is the third article in a series on clinical research by nurses. Confused about theoretical sampling? Federal government websites often end in .gov or .mil. In the past, some groups, such as women, ethnic minorities, elderly adults, and poor people, were unnecessarily excluded from studies (Larson, 1994). Probability sampling methods are most commonly applied in quantitative, outcomes, and intervention research. Most of the variation from the mean is in the same direction; it is systematic. It is especially important that the sample be representative in relation to the variables you are studying and to other factors that may influence the study variables. Sampleretentionrateformula=numbersubjectscompletingstudysamplesize100%, Retentionrate=120(numberretained)160(samplesize)=0.75100%=75%. Probability sampling methods have been developed to ensure some degree of precision in estimations of the population parameters. 43 Careers, The group of people you want to study and understand. With this knowledge, you can make intelligent judgments about sampling when you are critically appraising studies or developing a sampling plan for your own study. 10 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. If the accessible population is limited to a particular setting or type of setting, the individuals seeking care at that setting may be different from the individuals who would seek care for the same problem in other settings or from individuals who self-manage their problems. Quantitative, outcomes, and intervention research apply a variety of probability and nonprobability sampling methods. 66 34 The likelihood is increased that the sample is representative of the target population and the results are an accurate reflection of reality. The series is designed to give nurses the knowledge and skills they need to participate in research, step by step. The study sampling frames for the NPs and PAs are representative of all 50 states and the District of Columbia, and the lists for the sampling frames were from quality sources. The list for PAs was derived from the American Academy of Physicians Assistants (AAPA), and a comprehensive list of NPs was derived from the medical and nursing boards of the 50 states and the District of Columbia [sampling frames for NPs and PAs]. After undeliverable (1.9%) and other disqualified respondents (13.2%, i.e., no longer practicing, non-primary-care practitioner) were removed, the overall adjusted response rate was 50.6%. (Ulrich et al., 2006, p. 393). 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%. Stratified random sampling is used when the researcher knows some of the variables in the population that are critical to achieving representativeness. There is less opportunity for systematic bias if subjects are selected randomly, although it is possible for a systematic bias to occur by chance. Exclusion criteria tend to increase the systematic bias in the sample and increase the sampling error. Usually researchers report either the acceptance rate or the refusal rate but not both. National Library of Medicine PMC The treatment group retention was 110 women with a retention rate of 89% (110 124 100% = 88.7% = 89%). As the sample size increases, the sample mean is also more likely to have a value similar to that of the population mean. 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. The sample of 75 women was randomly selected, but the researchers did not indicate the process for the random selection. There are two primary types of sampling methods that you can use in your research: Probability sampling involves random selection, allowing you to make strong statistical inferences about the whole group. TABLE 15-1 The accessible population must be representative of the target population. This correlation can cause a decrease in precision and an increase in sampling error. Systematic random sampling is the selection of participants in a preordained, orderly sequence. The difference between a sample statistic and a population parameter is called the sampling error (Figure 15-2). Non-probability sampling methods are those in which elements are chosen through non-random methods for inclusion into the research study and include convenience sampling, purposive sampling, and snowball sampling. The retention rates for both groups were very strong and comparable (treatment group 89% and comparison group 90%). 15 Similar to stratified random sampling, cluster random sampling uses natural geographic and organizational clusters of potential research participants to create a sampling frame.2 For example, in exploring work satisfaction among clinical nurses using a cluster sampling methodology, the researcher would randomly select cities from which to draw the sample, then randomly select hospitals from within each city, and finally randomly assign nurses from within each hospital to participate in the study. Probability and Nonprobability Sampling Methods Commonly Applied in Nursing Research However, some of the outcomes are more valid than others, partly because of the sampling techniques used. 72 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). This study has an excellent acceptance rate (100%) and a very strong sample retention rate of 90% for a 24-month-long study. Potential subjects cannot be excluded just because they are too sick, not sick enough, coping too well, or not coping adequately. Importantly, these types of studies do not focus on reasons for the occurrence of the phenomenon. Values of individual subjects vary from the value of the sample mean. Sampling Plan The next column will discuss measurement in quantitative research, including the concepts of reliability and validity. Probability samples reduce sampling error. Bethesda, MD 20894, Web Policies Four sampling designs have been developed to achieve probability sampling: simple random sampling, stratified random sampling, cluster sampling, and systematic sampling. Sample size estimation and power analysis for clinical research studies. For example, the researcher might first randomly select states and next randomly select cities within the sampled states. Clipboard, Search History, and several other advanced features are temporarily unavailable. 54 The sampling component is an important part of the research process that needs to be carefully thought out and clearly described. (2009) conducted a quasi-experimental study to examine the effects of strength and weight training (ST) exercises on muscle strength, balance, and falls of breast cancer survivors (BCSs) with bone loss (population). Sampling error limits generalizability and research accuracy (validity) by introducing bias into the study. In some studies, the entire population is the target of the study. For example, identifying all women in active labor in the United States, all people grieving the loss of a loved one, or all people coming into an emergency department would be impossible. The term probability sampling method refers to the fact that every member (element) of the population has a probability higher than zero of being selected for the sample. 444-445). 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. Random sampling can be: simple random sampling stratified random sampling, and Probability sampling involves random selection, each person in the group or community has an equal chance of being chosen. Capili B. The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). 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. The extent of the difference is the sampling error (see Figure 15-2). In stratified random sampling, the subjects are randomly selected on the basis of their classification into the selected strata. The plan is developed to enhance representativeness, reduce systematic bias, and decrease the sampling error. Share this: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) Hospitals within the randomly selected cities might then be randomly selected. 17. Using theoretical sampling, the qualitative researcher intentionally samples additional participants to gain further insight into information obtained from previous study participants to inform ongoing theory development. (2009) also provided a rationale for the subjects attrition, and the reasons were varied and seemed appropriate and typical for a study lasting 24 months. to maintaining your privacy and will not share your personal information without The selection included all of the most populous primary sampling units in the United States and stratified probability samples (by state, area poverty level, and population size) of the less populous ones. Because of the importance of generalizing, there are risks to defining the accessible population too narrowly. Fouladbakhsh and Stommel (2010, p. E8) used multistage cluster sampling in their study of the complex relationships among gender, physical and psychological symptoms, and use of specific CAM [complementary and alternative medicine] health practices among individuals living in the United States who have been diagnosed with cancer. These researchers described their sampling method in the following excerpt from their study. 44 Probability sampling is the random selection of elements from the population, where each element of the population has an equal and independent chance of being included in the sample. The sampling method implemented in a study varies with the type of research being conducted. As further names are drawn, the probability of being selected decreases. Probability samples contain some type of randomization and consist of simple, stratified, systematic, cluster, and sequential ty Selecting the sample for a research study Sampleretentionrateformula=numbersubjectscompletingstudysamplesize100% Twiss et al. The number touched is the starting place. A sample is collected from a sampling frame, or the set of information about the accessible units in a sample. For example, if in conducting your research you selected a stratified random sample of 100 adult subjects using age as the variable for stratification, the sample might include 25 subjects in the age range 18 to 39 years, 25 subjects in the age range 40 to 59 years, 25 subjects in the age range 60 to 79 years, and 25, One question that arises in relation to stratification is whether each stratum should have equivalent numbers of subjects in the sample (termed, A self-administered questionnaire was mailed to an initial stratified random sample [sampling method] of 3,900 NPs and PAs practicing in the United States. 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. Please read ahead to understand more about what this program does. International Journal for Quality in Health Care, 15 (3): 261-266. Quantitative, outcomes, and intervention research

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