what is sampling theory in nursing research

This study included clearly identified inclusion and exclusion sampling or eligibility criteria that are presented in the following excerpt. Sampling Methods Probability sampling (random sampling) It is a selection process that ensures each participant the same probability of being selected. To achieve simple random sampling, elements are selected at random from the sampling frame. 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. Most of the variation from the mean is in the same direction; it is systematic. 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%). 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. A heterogeneous sample increases your ability to generalize the findings to a larger target population. A statistic is then estimated and applied to the whole population. The .gov means its official. 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. To achieve simple random sampling, elements are selected at random from the sampling frame. If five subjects are to be selected from a population of 100 and the researcher decides to go across the column to the right, the subject numbers chosen are 58, 25, 15, 55, and 38. A sampling plan defines the process of making the sample selections; sample denotes the selected group of people or elements included in a study. Some values are higher and others are lower than the sample mean. Table 15-2 shows a section from a random numbers table. Please enable it to take advantage of the complete set of features! may email you for journal alerts and information, but is committed 13 4th ed. For example, there is no list of all the heart surgery patients who complete rehabilitation programs in the United States. 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. Systematic sampling In addition, a sample must represent the demographic characteristics, such as age, gender, ethnicity, income, and education, which often influence study variables. The term used by researchers depends of the philosophical paradigm that is reflected in the study and the design. 28 Stratification ensures that all levels of the identified variable, in this example age, are adequately represented in the sample. National Library of Medicine Wooldridge JM. Sampling error is usually larger with small samples and decreases as the sample size increases. 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. A large sampling error means that the sample is not providing a precise picture of the population; it is not representative. 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%. 14-15) sampling text. 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. 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]. Attritionrate=40(numberwithdrawing)160(samplesize)=0.25100%=25% However, even in a random sample, systematic variation can occur if potential subjects decline participation. There are many types of sampling methods, but most sampling falls into two main categories: probability sampling, and non-probability sampling. sharing sensitive information, make sure youre on a federal These biases are similar to biases that may be encountered in a nonrandom sample (Thompson, 2002). 72 Figure 15-1 shows the relationships among the population, target population, and accessible populations. Am J Nurs 2021;121(1):647. Please read ahead to understand more about what this program does. 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. Contact author: Alexa Colgrove Curtis, [emailprotected]. Unauthorized use of these marks is strictly prohibited. It is better to provide a rate in addition to the number of subjects withdrawing or completing a study. Again, these units could be people, events, or other subjects of interest. The study was conducted in obstetric intensive care units and services of all the public and university hospitals in the province of Eskisehir, Turkey. During the 4 month study, 281 patients attended for the cesarean operations to the obstetric intensive care units and services of all hospitals concerned [target population and settings]. Sampling theory can be considered biased since the researcher is picking the population group they want to study. 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 . However, such disadvantages can be offset to some extent by the use of a larger sample. Therefore, the sampling design of the NHIS includes oversampling of minorities. (Fouladbakhsh & Stommel, 2010, pp. 43 One of the most important surveys that stimulated improvements in sampling techniques was the U.S. census. Am J Nurs. St. Louis: Elsevier; 2017. p. 32962. The .gov means its official. Inclusion sampling criteria are characteristics that a subject or element must possess to be part of the target population. The study sample might have been stronger with a more equal number of NP and PA subjects. Therefore, the sampling design of the NHIS includes oversampling of minorities. (, Using Statistics to Determine Differences, The Practice of Nursing Research Appraisal Synthesis and Gener, Quantitative, outcomes, and intervention research, Quantitative, qualitative, outcomes, and intervention research, Qualitative and sometimes quantitative research. Data is temporarily unavailable. An extreme example of this problem is the highly restrictive sampling criteria used in some experimental studies that result in a large sampling error and greatly diminished representativeness. your express consent. The final sample was large (1536 subjects) with strong representation for both NPs (833 subjects) and PAs (689 subjects). 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. Then, from the sample size, we can make inferences as to the population. PMC An official website of the United States government. Unauthorized use of these marks is strictly prohibited. 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. In other studies, the entire population of interest in the study is small and well defined. Methods of achieving random sampling are described later in the chapter. "Sampling theory was developed to determine the most effective was of acquiring a sample that accurately reflects the population under study. In nursing, nurses collect data to diagnose people in order to make decisions about their care. The series is designed to give nurses the knowledge and skills they need to participate in research, step by step. For example, if study participants who choose to leave the study tend to be poorer with less education, the nurse researcher will have difficulty generalizing the study findings to these populations. The hope is that it is representative of the population, shares the same characteristics. Exclusion criteria limit true randomness. For example, the researcher might first randomly select states and next randomly select cities within the sampled states. In: 7. 33 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. Figure 15-2 Sampling error. A systematic review of research papers in the Journal of Advanced Nursing. 77 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). 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). 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). Sampleattritionrateformula=numbersubjectswithdrawingsamplesize100% Refusalrate=40(numberrefusing)200(numbermeetingsamplingcriteria)=0.2100%=20%. Probability samples reduce sampling error. Women were excluded if they (a) had a recurrence of breast cancer; (b) were currently taking hormone therapy, bisphosphonates, glucocorticosteroids, or other drugs affecting bone; (c) were currently engaging in ST exercises; (d) had a body mass index (BMI) of 35 or greater; (e) had serum calcium, creatinine, or thyroid stimulating hormone (if on thyroid therapy) outside normal limits; or (f) had active gastrointestinal problems or other conditions that prohibited ST exercises, risedronate, calcium, or vitamin D intake [exclusion sampling criteria]. (Twiss et al., 2009, p. 72) Sampling theory in medical science is a study of gathering information about a population by investigating only a part of it. Qualitative and sometimes quantitative research 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. However, even in a random sample, systematic variation can occur if potential subjects decline participation. Potential subjects cannot be excluded just because they are too sick, not sick enough, coping too well, or not coping adequately. For instance, perhaps a nurse researcher is interested in examining work satisfaction among clinical nurses within a large health care system. In a second step, primary sampling units were partitioned into substrata (up to 21) based on concentrations of African American and Hispanic populations [2nd stage cluster sampling]. The next column will discuss measurement in quantitative research, including the concepts of reliability and validity. 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 term, There is less opportunity for systematic bias if subjects are selected randomly, although it is possible for a systematic bias to occur by chance. In sampling methods, parameters of the population are estimated from the sample drawn from the population. 13. Sampling theory was developed to determine the most effective way to acquire a sample that accurately reflects the population under study. For a study examining the relationship between patient satisfaction and triage nursing care in the ED, researchers randomly sampled every fifth person who presented to the ED. Twiss et al. PMC To do that, you need to collect samples from a group of individuals who all share a common trait. All rights reserved. Sampling Theory. 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]. Chang SF, Chuang MH. The plan is developed to enhance representativeness, reduce systematic bias, and decrease the sampling error. 66 A refusal rate is the number and percentage of subjects who declined to participate in the study. Sampling Method 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. The site is secure. However, even in a random sample, systematic variation can occur if potential subjects decline participation. sharing sensitive information, make sure youre on a federal Am J Nurs. 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. In experimental studies that use a control group, subjects are randomly selected and randomly assigned to either the control group or the experimental group. 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. 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 study by Twiss et al. 54 Generalizing means that the findings can be applied to more than just the sample under study because the sample is representative of the target population. Clipboard, Search History, and several other advanced features are temporarily unavailable. The accessible population must be representative of the target population. Explore the historical and contemporary theories that are the foundation of nursing practice today. 750 Highland Ave, Madison, WI 53705-2221 Qualitative research Sampling decisions have a major impact on the meaning and generalizability of the findings. Nonprobability Sampling Methods 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. When elements are persons, they are usually referred to as subjects or research participants or informants (see Figure 15-1). Sampling error occurs as a result of random variation and systematic variation. The sample is obtained from the accessible population by a particular sampling method, such as simple random sampling. Thus, a study that uses random sampling techniques may have such restrictive sampling criteria that the sample is not truly random. 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 sample of 75 women was randomly selected, but the researchers did not indicate the process for the random selection. Nurs Health Sci. Selecting the sample for a research study. To use a table of random numbers, the researcher places a pencil or a finger on the table with the eyes closed. For example, suppose a researcher is conducting a study of stress among medicalsurgical nurses. For a sample to be representative, it must be similar to the target population in as many ways as possible. 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. 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). In some cases, a hypothetical population is defined for a study. 70 However, sampling criteria should not become so restrictive that the researcher cannot find an adequate number of study participants. The IQs of the subjects have introduced a systematic bias. government site. In the example mentioned earlier, 200 potential subjects met the sampling criteria; 160 agreed to participate in the study, and 40 refused. 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. Some error has occurred while processing your request. Capili B. In addition, a sample must represent the demographic characteristics, such as age, gender, ethnicity, income, and education, which often influence study variables. Stratification ensures that all levels of the identified variable, in this example age, are adequately represented in the sample. For instance, while researchers might want to explore topics related to cigarette smoking among U.S. adult smokers, they would never be able to identify a study sample that perfectly matches all the characteristics, both observable (such as gender) and unobservable (the many social and environmental factors shaping smoking behaviors), of the general population of smokers. The IQs of the subjects have introduced a systematic bias. 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 Biases may be introduced that make generalization to the broader target population difficult to defend. 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. Each of these sampling strategies has trade-offs. 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. E8-E9) Many of these studies use data available in large databases, such as the census data or other government-maintained databases. In addition, a researcher cannot exclude a subset of people from selection as subjects because he or she does not agree with them, does not like them, or finds them hard to deal with. While probability sampling minimizes selection bias and enhances generalizability of a study, it is often associated with sizable time and financial costs, particularly if the study sample is large.

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