9. The 5th Edition, continues to meet the needs of today's students with an expanded focus on the middle range theories and practice models. Sampling theory in nursing research is the process of grouping a set of individuals, events, behaviors, or other items to investigate. Twiss et al. The sample of 75 women was randomly selected, but the researchers did not indicate the process for the random selection. 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. However, it has some disadvantages. Aschengrau A, Seagre GR III. Probability and Nonprobability Sampling Methods Commonly Applied in Nursing Research. (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. Conlon C, et al. 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). Most of the variation from the mean is in the same direction; it is systematic. The researcher can use a computer to select these numbers randomly to obtain a sample. Simple Random Sampling The sampling frame in this study included the names of the 746 RNs who were asked to participate in the study. There can be some differences in the probability for the selection of each element, depending on whether the name or number of the selected element is replaced before the next name or number is selected. Sampling theory can be considered biased since the researcher is picking the population group they want to study. The use of the term control groupthe group not receiving the treatmentis usually limited to studies using random sampling and random assignment to the treatment and control groups. The results of a study that has assembled its sample appropriately can be more confidently applied to the population from which the sample came. Biases may be introduced that make generalization to the broader target population difficult to defend. These studies are referred to as, In some cases, a hypothetical population is defined for a study. There are two main categories of sampling methods: probability and non-probability. Knowledge of sampling methods is essential to design quality research. In some cases, this random selection continues through several stages and is referred to as multistage cluster sampling. 4. Ulrich et al. This theory was developed so as to establish which of the ways utilized in acquiring . The study by Twiss et al. In this case, mathematically weighting the findings from each stratum can equalize the representation to ensure proportional contributions of each stratum to the total score of the sample. (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). The first situation is when a simple random sample would be prohibitive in terms of travel time and cost. 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. The variable or variables chosen for stratification need to be correlated with the dependent variables being examined in the study. However, random sampling must take place in an accessible population that is representative of the target population. However, in quasi-experimental or experimental studies, the primary purpose of sampling criteria is to limit the effect of extraneous variables on the particular interaction between the independent and dependent variables. 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%. For example, individuals who successfully lose weight would be a hypothetical population. 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]. 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. These sampling criteria probably were narrowly defined by the researchers to promote the selection of a homogeneous sample of postmenopausal BCSs with bone loss. Simple random sampling is the most basic of the probability sampling methods. In: Statistics. The IQs of the subjects have introduced a systematic bias. Sampling error decreases, power increases, data collection time is reduced, and the cost of the study is lower if stratification is used (Fawcett & Garity, 2009; institutions, or organizations with which elements of the identified population would be linked. Figure 15-2 Sampling error. 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. 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). Sampling theory is the study of relationships existing between a population and samples drawn from the population. Hogan TM, et al. 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. 8th ed. The study by Twiss et al. I think this all sounds like a pretty standard way to . In large population sets, elements may already have assigned numbers. The difference is random because the value of each subject is likely to vary in a different direction. Sample attrition is the withdrawal or loss of subjects from a study. PMC Acceptancerate=160(numberaccepting)200(numbermeetingsamplingcriteria)=0.8100%=80% Please try again soon. However, many researchers use nonprobability sampling because in many cases, probability sampling is not practical, feasible, or ethical. Factors that affect self-care behaviour of female high school students with dysmenorrhoea: a cluster sampling study. 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 a sample to be representative, it must be similar to the target population in as many ways as possible. 3 Sampling decisions are made for the explicit purpose of obtaining the richest possible source of information to answer the research . 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. 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. For example, numbers are assigned to medical records, organizational memberships, and professional licenses. Boston: Cengage Learning; 2006. p. 76396. Those G theory analogs are found in a decision (D) study. Nonprobability sampling. For systematic sampling to be considered probability sampling, the initial starting point of the sample (the fourth person in this example) is chosen at random. In cluster sampling, the researcher develops a sampling frame that includes a list of all the states, cities, The NHIS [National Health Interview Survey] methodology employs a multistage probability cluster sampling design [sampling method] that is representative of the NHIS target universe, defined as the civilian noninstitutionalized population (Botman, Moore, Moriarty, & Parsons, 2000, p. 14; National Center for Health Statistics). Twiss et al. In this research column, we provide an introduction to these key sampling techniques and draw on examples from the cardiovascular research. 2021 Oct 1;121(10):59-62. doi: 10.1097/01.NAJ.0000794280.73744.fe. Obese individuals who choose to enter a program to lose weight may differ from obese individuals who do not enter a program. 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. Table 15-2 is useful only if the population number is less than 100. In selecting the study sample, the primary goal is to minimize sampling error(the discrepancy between the study sample and the target population). In these cases, it is often possible to obtain lists of institutions or organizations with which the elements of interest are associated. The sampling theory . However, even in a random sample, systematic variation can occur if potential subjects decline participation. 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. Researchers need to provide logical reasons for their inclusion and exclusion sampling criteria, and certain groups should not be excluded without justification. The higher the refusal rate, the less the sample is representative of the target population. Palinkas LA, et al. 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%. 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. The sampling plan provides detail about the application of a sampling method in a specific study. In network or snowball sampling, study participants recruit other potential participants with similar characteristics or experiences relating to the study objectives. To use a table of random numbers, the researcher places a pencil or a finger on the table with the eyes closed. 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. When one . 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]. Stratification ensures that all levels of the identified variable, in this example age, are adequately represented in the sample. 93 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. You can define parameters by conducting a series of descriptive and correlational studies, each of which examines a different segment of the target population; then perform a meta-analysis to estimate the population parameter (Thompson, 2002). 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. 11. 30 20 There is less opportunity for systematic bias if subjects are selected randomly, although it is possible for a systematic bias to occur by chance. Sample attrition rate is calculated by dividing the number of subjects withdrawing from a study by the sample size and multiplying the results by 100%. 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). If 20% of the nursing target population is male, ideally, 20% of the study sample would be male as well. A study might have inclusion or exclusion sampling criteria (or both). The plan is developed to enhance representativeness, reduce systematic bias, and decrease the sampling error. Bethesda, MD 20894, Web Policies 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. Moving the pencil or finger up, down, right, or left, the researcher uses the numbers in order until the desired sample size is obtained. 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. 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 term used by researchers depends of the philosophical paradigm that is reflected in the study and the design. The comparison group retention was 113 women with a retention rate of 90% (113 125 = 90.4% = 90%). However, even in a random sample, systematic variation can occur if potential subjects decline participation. Patient satisfaction with triage nursing care in Hong Kong. The accessible population might be elements 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. 3 This type of research often involves a small number of participants to explore in-depth feelings, experiences and held beliefs. 33 Systematic variation or bias is most likely to occur when the sampling process is not random. Sampleattritionrateformula=numbersubjectswithdrawingsamplesize100%. In large population sets, elements may already have assigned numbers. A large sampling error means that the sample is not providing a precise picture of the population; it is not representative. Inferential statistical analyses are based on the assumption that the sample from which data were derived has been obtained randomly. Subjects and the care they receive in research centers are different from patients and the care they receive in community clinics, public hospitals, veterans hospitals, and rural health clinics. 3rd ed. Wolters Kluwer Health 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. (608) 262-2020 Using random sampling, the researcher cannot decide that person. [1]Kelley, K., Clark, B., Brown V., and J. Sitzia. The NHIS [National Health Interview Survey] methodology employs a multistage probability cluster sampling design [sampling method] that is representative of the NHIS target universe, defined as the civilian noninstitutionalized population (Botman, Moore, Moriarty, & Parsons, 2000, p. 14; National Center for Health Statistics). The retention rates for both groups were very strong and comparable (treatment group 89% and comparison group 90%). Engaging theoretical sampling in diverse grounded theory studies. There are two main categories of sampling methods: probability and non-probability. However, the sample was a great strength of this study and appeared to represent the target population of NPs and PAs currently practicing in primary care in the United States. Researchers need to provide logical reasons for their inclusion and exclusion sampling criteria, and certain groups should not be excluded without justification. 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. The number touched is the starting place. In a third step, clusters of dwelling units form the secondary sampling units selected from each substratum [3rd stage cluster sampling]. Refusal and Acceptance Rates in Studies Sampling means simply studying a proportion of the population rather than the whole. Using random sampling, the researcher cannot decide that person X would be a better subject for the study than person Y. Random variation is the expected difference in values that occurs when one examines different subjects from the same sample. Unlike quantitative analysis, data collection and data analysis in qualitative research often occur concurrently. 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. 2021 Jul 24;13(8):2529. doi: 10.3390/nu13082529. Potential subjects cannot be excluded just because they are too sick, not sick enough, coping too well, or not coping adequately. Four sampling designs have been developed to achieve probability sampling: simple random sampling, stratified random sampling, cluster sampling, and systematic sampling. 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. 12. 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. 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. Obese individuals who choose to enter a program to lose weight may differ from obese individuals who do not enter a program. 22 70 For instance, the researcher could require that 30% of the sample have an admission diagnosis of chronic obstructive pulmonary disease. A profile of acute care in an aging America: snowball sample identification and characterization of United States geriatric emergency departments in 2013. Before Am J Nurs. The subjects were evenly divided with 25 in each group, but the researchers do not indicate if the assignment to groups was random or based on the convenience of the subjects or researchers. 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]. 19 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. 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 theoretical, mathematical rationale for decisions related to sampling emerged from survey research, although the techniques were first applied to experimental research by agricultural scientists. 2003. The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). The treatment group retention was 110 women with a retention rate of 89% (110 124 100% = 88.7% = 89%). There can be some differences in the probability for the selection of each element, depending on whether the name or number of the selected element is replaced before the next name or number is selected. However, random sampling must take place in an accessible population that is representative of the target population. 8600 Rockville Pike Qualitative and sometimes quantitative research Selection without replacement gives each element different levels of probability for selection. Misrepresenting random sampling? Four sampling designs have been developed to achieve probability sampling: simple random sampling, stratified random sampling, cluster sampling, and systematic sampling. For example, the researcher might first randomly select states and next randomly select cities within the sampled states. 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. Sampling methodology influences how well the study represents the target population, and thereby affects the generalizability of the study. evolve.elsevier.com/Grove/practice/ Age limitations are often specified, such as adults 18 years and older. Sample size estimation and power analysis for clinical research studies. Curr Epidemiol Rep. 2017 Dec;4(4):346-352. doi: 10.1007/s40471-017-0130-z. Bethesda, MD 20894, Web Policies 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. If the accessible population is defined as individuals in a white, upper-middle-class setting, one cannot generalize to nonwhite or lower income populations. The sampling theory was established to help find the most suitable method of acquiring a sample that exactly represents the study population using mathematical formulae. To achieve these goals, researchers need to understand the techniques of sampling and the reasoning behind them. However, in quasi-experimental or experimental studies, the primary purpose of sampling criteria is to limit the effect of extraneous variables on the particular interaction between the independent and dependent variables. All subsets of the population, which may differ from one another but contribute to the parameters of the population, have a chance to be represented in the sample. 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. The sampling plan provides detail about the application of a sampling method in a specific study. This article reviews probability and non-probability sampling methods, lists and defines specific sampling techniques, and provides pros and cons for c 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. Twiss et al. Wolters Kluwer Health, Inc. and/or its subsidiaries. 07 The researcher selects subjects from the sampling frame using a sampling plan. However, tables are available for larger populations, such as the random numbers table provided in the online resources for this textbook or the Thompson (2002, pp. 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. Thus, a study that uses random sampling techniques may have such restrictive sampling criteria that the sample is not truly random. Disclaimer. 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. 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. 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. The opposite of the attrition rate is the retention rate, or the number and percentage of subjects completing the study. Selecting the sample for a research study. 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. 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. 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. Your message has been successfully sent to your colleague. Systematic variation can also occur in studies with high sample attrition. Usually researchers report either the acceptance rate or the refusal rate but not both. Data is temporarily unavailable. 34 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). The study has a strong response rate of 50.6% for a mailed questionnaire, and the researchers identified why certain respondents were disqualified. Therefore, the sampling design of the NHIS includes oversampling of minorities. (Fouladbakhsh & Stommel, 2010, pp. 63 Random Variation In the aforementioned situation, if proportions are used and the sample size is 100, the study would include only five Asians, hardly enough to be representative. 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. The study sample might have been stronger with a more equal number of NP and PA subjects. Exclusion criteria limit the generalization of the study findings and should be carefully considered before being used in a study. Am J Nurs. Also known as random sampling, probability sampling constructs the study sample by randomly selecting participants from the sampling frame such that each member of the sampling frame has an equal chance of inclusion in the study.5 Probability sampling is considered the gold standard in quantitative research design because it enhances generalizability and reduces threats to validity by minimizing selection bias. In nursing, nurses collect data to diagnose people in order to make decisions about their care. If the method of selecting subjects produces a sample with a systematic bias, increasing the sample size would not decrease the sampling error. Cardiovascular nursing research covers a wide array of topics from health services to psychosocial patient experiences. Similarly, the study sample should mirror the target population on other characteristics, such as age, education, and nursing experience. Because of the importance of generalizing, there are risks to defining the accessible population too narrowly. Sample attrition should be reported in the published study to determine if the final sample represents the target population. The following sections describe the different types of probability and nonprobability sampling methods most commonly used in quantitative, qualitative, outcomes, and intervention research in nursing. It is important that assessment techniques possess both validity and reliability. However, random sampling must take place in an accessible population that is representative of the target population. Sampling Error All subsets of the population, which may differ from one another but contribute to the parameters of the population, have a chance to be represented in the sample. 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. Random sampling leaves the selection to chance and decreases sampling error and increases the validity of the study (Thompson, 2002).
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