Sampling Methods Probability sampling (random sampling) It is a selection process that ensures each participant the same probability of being selected. Critical questions are provided to help researchers choose a sampling method. 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. Copyright 2021 Wolters Kluwer Health, Inc. All rights reserved. The development of a thoughtful sampling plan is essential to support the validity of nursing research. Get new journal Tables of Contents sent right to your email inbox, http://links.lww.com/AJN/A204; [Other] (0 KB), Articles in PubMed by Alexa Colgrove Curtis, PhD, MPH, FNP, PMHNP, Articles in Google Scholar by Alexa Colgrove Curtis, PhD, MPH, FNP, PMHNP, Other articles in this journal by Alexa Colgrove Curtis, PhD, MPH, FNP, PMHNP, Selection and Implementation of Outcome Measurements, Privacy Policy (Updated December 15, 2022). For example, if nursing researchers were interested in exploring issues related to lung cancer, it is not likely they would have access to all lung cancer patients in the United States. (2009) found significant improvement in muscle strength and balance for the treatment group but no significant difference in the number of falls between the treatment and comparison groups. maintain their nursing identity and further their efforts for developing a nursing specialty. 25 A podcast with the authors is available at www.ajnonline.com. 58 Burlington, MA: Jones and Bartlett Learning; 2020. Acceptancerate=160(numberaccepting)200(numbermeetingsamplingcriteria)=0.8100%=80% In: Burns and Grove's the practice of nursing research: appraisal, synthesis, and generation of evidence. 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. Systematic bias increases as the subjects refusal rate increases. 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. J Adv Nurs. For example, one could conduct a study in which the defined population was all living recipients of heart and lung transplants. 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. Population, sample, and subject selected for a study. The sample of 75 women was randomly selected, but the researchers did not indicate the process for the random selection. For each person in the target or accessible population to have an opportunity to be selected for the sample, each person in the population must be identified. MeSH 54 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). 77 Because of the importance of generalizing, there are risks to defining the accessible population too narrowly. Most textbooks on sampling describe this procedure (Levy & Lemsbow, 1980; Thompson, 2002; Yates, 1981). Table 15-2 shows a section from a random numbers table. Selection bias and sampling plan. The sampling method implemented in a study varies with the type of research being conducted. 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%). 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 study by Twiss et al. A heterogeneous sample increases your ability to generalize the findings to a larger target population. 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. Random variation is the expected difference in values that occurs when one examines different subjects from the same sample. In these types of studies, the sampling criteria need to be specific and designed to make the population as. [1]Kelley, K., Clark, B., Brown V., and J. Sitzia. In addition, a sample must represent the demographic characteristics, such as age, gender, ethnicity, income, and education, which often influence study variables. The theoretical and mathematical rationale for sampling-related decisions evolved from survey research. Values of individual subjects vary from the value of the sample mean. 43 We can estimate the population parameter by identifying the values obtained in previous studies examining the same variables. A sampling plan defines the process of making the sample selections; sample denotes the selected group of people or elements included in a study. 34 Twiss et al. Hence, sampling theory also consists of estimation methods. 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. When elements are persons, they are usually referred to as subjects or research participants or informants (see Figure 15-1). The researcher selects subjects from the sampling frame using a sampling plan. These biases are similar to biases that may be encountered in a nonrandom sample (Thompson, 2002). Misrepresenting random sampling? Sampling error is usually larger with small samples and decreases as the sample size increases. Each column will present the concepts that underpin evidence-based practice-from research design to 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. A modified grounded theory study of how psychiatric nurses work with suicidal people. Section from a Random Numbers Table With a comparison group, there is an increase in the possibility of preexisting differences between that group and the experimental group receiving the treatment. Refusalrate=40(numberrefusing)200(numbermeetingsamplingcriteria)=0.2100%=20%. 17. Sampling strategies have been devised to accomplish these three tasks and to optimize sample selection. 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). The method you use to pick individuals out of the group to study. Qualitative research 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. 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. In sampling methods, parameters of the population are estimated from the sample drawn from the population. There are many types of sampling methods, but most sampling falls into two main categories: probability sampling, and non-probability sampling. In this research column, we provide an introduction to these key sampling techniques and draw on examples from the cardiovascular research. 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 The term study or research participant or informant is used in the context of the naturalistic paradigm of qualitative research (Fawcett & Garity, 2009; Munhall, 2012). One of the most important surveys that stimulated improvements in sampling techniques was the U.S. census. As further names are drawn, the probability of being selected decreases. 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. Even if the original sample is random, persons who volunteer or consent to participate in a study may differ in important ways from persons who are unwilling to participate. In stratified random sampling, the subjects are randomly selected on the basis of their classification into the selected strata. Sampling theory describes two sampling domains: probability and nonprobability. Quantitative, outcomes, and intervention research Because this is a quasi-experimental study that examined the impact of the treatment on the dependent or outcome variables, the increased controls imposed by the sampling criteria strengthened the likelihood that the study outcomes were caused by the treatment and not by extraneous variables. The plan is developed to enhance representativeness, reduce systematic bias, and decrease the sampling error. Capili B. Probability sampling. To achieve simple random sampling, elements are selected at random from the sampling frame. It is better to provide a rate in addition to the number of subjects withdrawing or completing a study. Accessibility 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. 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%. Instead, researchers study a sample to make estimates about the total population. Because this is a quasi-experimental study that examined the impact of the treatment on the dependent or outcome variables, the increased controls imposed by the sampling criteria strengthened the likelihood that the study outcomes were caused by the treatment and not by extraneous variables. Each column will present the concepts that underpin evidence-based practice-from research design to data interpretation. 8. Twiss et al. International Journal for Quality in Health Care, 15 (3): 261-266. to maintaining your privacy and will not share your personal information without
A hypothetical population assumes the presence of a population that cannot be defined according to sampling theory rules, which require a list of all members of the population. Methods of achieving random sampling are described later in the chapter. A profile of acute care in an aging America: snowball sample identification and characterization of United States geriatric emergency departments in 2013. It is an effective method to get information that can be used to develop hypotheses and propose associations. (2009) identified that 249 participants or subjects met the sampling criteria and 249 were enrolled in the study indicating that the acceptance rate for the study was 100%. Subjects within each stratum are expected to be more similar (homogeneous) in relation to the study variables than they are to be similar to subjects in other strata or the total sample. It's a way of measuring how much a person's personality is similar to yours. 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). 13 An accessible population is the portion of the target population to which the researchers have reasonable access. To use a table of random numbers, the researcher places a pencil or a finger on the table with the eyes closed. 63 In some cases, a hypothetical population is defined for a study. The term subject, and sometimes research participant, is used within the context of the postpositivist paradigm of quantitative research (see Chapter 2). Sample surveys. The likelihood is increased that the sample is representative of the target population and the results are an accurate reflection of reality. The accessible population must be representative of the target population. Precision in estimating parameters requires well-developed methods of measurement that are used repeatedly in several studies. Instead, they would recruit a sample of lung cancer patients, such as willing participants from a regional oncology center. Refusalrateformula=number potential subjectsrefusing to participatenumber potentialsubjects meeting sample criteria100%. Careers. Disclaimer. Common methods of nonprobability sampling include the following2: In convenience sampling, a researcher's selection of participants is chiefly driven by the availability of potential research participants.2, 4 For example, a convenience sample might comprise all patients admitted to a specific clinical unit during the study period. This chapter examines sampling theory and concepts; sampling plans; probability and nonprobability sampling methods for quantitative, qualitative, outcomes, and intervention research; sample size; and settings for conducting studies. Editor's note: This is the third article in a series on clinical research by nurses. These researchers obtained their sample using a simple random sampling method that is described in the following excerpt from their 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. Subjects may be limited to individuals who are not participating in any other study. The sample is most like the target population if the attrition rate is low (<10% to 20%) and the subjects withdrawing from the study are similar to the subjects completing the study. Careers, The group of people you want to study and understand. If potential subjects have diminished autonomy or are unable to give informed consent, consent must be obtained from their legal representatives. Epidemiologists sometimes use entire populations for their large database studies. For each person in the target or accessible population to have an opportunity to be selected for the sample, each person in the population must be identified. Sampleattritionrateformula=numbersubjectswithdrawingsamplesize100% AJN The American Journal of Nursing121(3):53-57, March 2021. 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). To use a table of random numbers, the researcher places a pencil or a finger on the table with the eyes closed. Good arguments exist for both approaches. The researcher selects subjects from the sampling frame using a sampling plan. Sampling error limits generalizability and research accuracy (validity) by introducing bias into the study. There are also the difficulties of sampling student performance over time and of controlling test conditions (p. 1). Systematic variation can also occur in studies with high sample attrition. The number touched is the starting place. Sample selection is a very important but sometimes underestimated part of a research study. Some values are higher and others are lower than the sample mean. Sampling theory was developed to determine mathematically the most effective way to acquire a sample that would accurately reflect the population under study. Probability samples reduce sampling error. In stratified random sampling, a population is first categorized into specific, nonoverlapping groups (or strata); random samples are then taken from within each group (see Figure 1).5 Stratified sampling facilitates the representation of important participant characteristics in the study sample and improves data collection from underrepresented subgroups. Bethesda, MD 20894, Web Policies 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. In statistical theory based on probability, this means that the sample is more likely to resemble the larger population, and thus more accurate inferences can be made about the larger population. In nursing, nurses collect data to diagnose people in order to make decisions about their care. An element can be a person, event, behavior, or any other single unit of study. To enhance representation, this number could be proportionally weighted based on the size of each hospital's clinical nursing employee pool. The researcher, who has a vested interest in the study, could (consciously or unconsciously) select subjects whose conditions or behaviors are consistent with the study hypothesis. These samples are more likely to represent the population than samples obtained with nonprobability sampling methods. National Library of Medicine The second situation is in cases in which the individual elements making up the population are unknown, preventing the development of a sampling frame. Systematic variation, or systematic bias, is a consequence of selecting subjects whose measurement values are different, or vary, in some specific way from the population. Related Studies conducted in private hospitals usually exclude poor patients, and other settings could exclude elderly or undereducated patients. 4. 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. 38 Sampling methodology influences how well the study represents the target population, and thereby affects the generalizability of the study. 10 Data is temporarily unavailable. (2006) used a stratified random sampling method to obtain their sample of nurse practitioners (NPs) and physician assistants (PAs) for the purpose of studying the ethical conflict of these healthcare providers associated with managed care. 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. 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. 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 subjects 80 years or older.
Minimizing sampling error. Sampling strategies have been devised to accomplish these three tasks and to optimize sample selection. 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. 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. Systematic sampling The opposite of the attrition rate is the retention rate, or the number and percentage of subjects completing the study. Community-Based Survey Exploring Use of the Dietary Supplement Creatine by Adult Non-Athletes. Acceptancerate=100%refusalrateor100%20%=80% Qualitative research usually includes nonprobability sampling methods. 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. 52 Hogan and colleagues used a snowball sample to identify geriatric EDs for their study of the number, distribution, and characteristics of geriatric EDs in the United States. 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. 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. sharing sensitive information, make sure youre on a federal Professional Development, Leadership and Scholarship, Professional Partners Supporting Diverse Family Caregivers Across Settings, Supporting Family Caregivers: No Longer Home Alone, Nurse Faculty Scholars / AJN Mentored Writing Award. Keyword Highlighting
The outcomes of the study were that foot and hand massage interventions significantly reduced postoperative pain experienced by the women and that foot and hand massage was significantly more effective than foot massage only. If the mean is used to describe the sample, the values of individuals in that sample will not all be exactly the same as the sample mean. 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. Selection without replacement gives each element different levels of probability for selection. your express consent. What is Sampling Theory in Nursing Research? Qualitative research generates evidence and helps nurses determine . The site is secure. The subgroup that you are going to study, intended to be representative of the population at large for the characteristics of interest. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. A refusal rate is the number and percentage of subjects who declined to participate in the study. All of these factors limit representativeness and limit our understanding of the phenomena important in practice. 1. In quantitative, intervention, and outcomes research, the findings from a study are generalized first to the accessible population and then, if appropriate, more abstractly to the target population. As the sample size becomes larger, overall variation in sample values decreases, with more values being close to the sample mean. Careers. Sampling Method Purpose or purposeful sampling 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. A large sampling error means that the sample is not providing a precise picture of the population; it is not representative. The sample is obtained from the accessible population by a particular sampling method, such as simple random sampling. Systematic variation, or systematic bias, is a consequence of selecting subjects whose measurement values are different, or vary, in some specific way from the population. 2023 Feb 4;11(4):452. doi: 10.3390/healthcare11040452. Table 15-2 is useful only if the population number is less than 100. Log In or Register to continue This article reviews probability and non-probability sampling methods, lists and defines specific sampling techniques, and provides pros and cons for c Moving the pencil or finger up, down, right, or left, the researcher uses the numbers in order until the desired sample size is obtained. Highlight selected keywords in the article text. Clipboard, Search History, and several other advanced features are temporarily unavailable. Stratification is not as useful if one stratum contains only a small number of subjects. 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. The sampling plan provides detail about the application of a sampling method in a specific study. 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). 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. Selection of the study participants. To accomplish this goal, the researcher must acquire a list of every member of the population through the use of the sampling criteria to define membership. Degirmen et al. 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). The comparison group retention was 113 women with a retention rate of 90% (113 125 = 90.4% = 90%). 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. The next column will discuss measurement in quantitative research, including the concepts of reliability and validity. While "population" is about the generality of the universe or groups of people, "sample" refers to a fraction of persons from the population. Sampling error is the approximate difference between the results from a sample of people from a larger group, and the likely results of studying every single person in that group. The sample was selected from the national lists provided by Medical Marketing Services, an independently owned organization that manages medical industry lists (www.mmslists.com/main.asp). The IQs of the subjects have introduced a systematic bias. In: Introductory econometrics: a modern approach. 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. Because of systematic variance, the sample mean is different from the population mean. Am J Nurs. Unable to load your collection due to an error, Unable to load your delegates due to an error. Acceptancerateformula=numberpotentialsubjectsagreeingtoparticipatenumberpotentialsubjectsmeetingsamplecriteria100% 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. A refusal rate is the number and percentage of subjects who declined to participate in the study. You may be trying to access this site from a secured browser on the server. 15 It is tempting to exclude uncooperative or assertive individuals.
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