Introduction: In qualitative research the SAMPLING process is usually determined by the methodology employed. However, this is not always evident in published qualitative research papers as many qualitative studies appear not to have a clearly defined methodological approach. Indeed, pragmatic researches focus on the need to adopt a flexible rather than rigid approach to application of qualitative methodologies. Therefore, this study was performed to review previous research to clarify qualitative SAMPLING. Valid articles and books were used in this review study.Method: The keywords qualitative research and SAMPLING were searched in Cumulative Index to Nursing and Allied Health Literature (CINAHL), ProQuest, PsycINFO, ScienceDirect, Scopus, and Medline databases.Results: Although SAMPLING methods in qualitative research are known as purposive SAMPLING, there is an extensive spectrum of SAMPLING methods such as quota, snowball, theoretical, critical cases, homogeneity, sequential, criterion, and combination SAMPLING.Conclusion: The purpose of SAMPLING in qualitative research is not to establish a random or representative sample draw from a population, but rather to identify specific groups of people, who either possess characteristics or live experiences relevant to the social phenomenon being studied. Informants are identified because they will enable the exploration of a particular aspect of behavior relevant to the research. The benefits of the qualitative approach to health care research are becoming increasingly recognized by both academics and clinicians. However, misunderstandings about the philosophical basis and the methodological approach remain. The process of SAMPLING is one of the principal areas of confusion. SAMPLING is a very complex issue in qualitative research. This is due to the many variations of qualitative SAMPLING described in the literature, and much confusion and overlapping of types of SAMPLING.

Background: A detailed study of hidden and hard to reach populations in order to identify their characteristics is essential because they endanger the health of the society by their dangerous behaviors. However, SAMPLING in these populations through conventional SAMPLING methods is impossible due to reasons such as being hidden and lacking a precise frame.Methods: In this article, applicable concepts and key points in the implementation of respondent driven SAMPLING were defined by focusing on designs that aimed to study dangerous and hidden behaviors such as dangerous sexual behavior, injecting drug abuse, and HIV infection.Findings: The merits of the respondent driven SAMPLING are the production of unbiased and effective estimations of necessary parameters in populations at risk of rare and hidden diseases in comparison to other chain referral and conventional SAMPLING methods, and the innovations of this SAMPLING method during its implementation.Conclusion: The application of the respondent driven SAMPLING method in order to achieve unbiased and precise estimates of the prevalence rate of rare and hidden diseases is recommended in health programs of the society.

Evaluating SAMPLING accuracy is of great importance prior to SAMPLING practice. Since it is expected to be a relationship between soil properties and ancillary environmental variables, proper SAMPLING points are those that better simulate the probability distributions of these variables. The possibility of SAMPLING from low probability tails is very low for random and regular network methods, while the Latin Hypercube SAMPLING (LHS) method divides the input probability distribution into equal intervals and one sample is taken from each interval. The satellite images band and digital elevation model (DEM) were used as inputs to determine the SAMPLING points in LHS. Three methods including random, regular network and LHS SAMPLING strategies were employed in three SAMPLING densities of 100, 50 and 25 points in the study area of 52,000 ha to simulate the probability distribution of Landsat ETM+ bands and DEM. The simulated probability distributions were then compared with the population distribution and soil salinity data. Results indicated that there is no significant difference between the SAMPLING strategies in 100 and 50 SAMPLING densities to simulate the mean of population, as the SAMPLING density decreased, the Residual Mean Square Error (RMSE) increased. In 25 point SAMPLING density, the RMSE for LHS, regular network, and random SAMPLING methods were 4, 7.83, and 17.5 percents, respectively. Results further indicated that LHS can efficiently simulate the input probability distribution even in low SAMPLING densities. The RMSE values for estimating soil salinity in the original population were 4.22 and 8.66 dS/m in 100 and 25 SAMPLING densities, respectively. Although the calculated RMSE was larger than that of input parameters of image bands and DEM, it could simulate the population probability distribution of soil salinity with enough accuracy. In conclusion, the best SAMPLING method in this research was Latin hypercube method with a density of 25 SAMPLING points.

SAMPLING hidden populations is challenging due to the lack of convenience statistical frames. Since most populations exposed to special diseases are hidden and hard to reach, SAMPLING methods that produce representative and efficient samples from the populations have become a study subject for researches all over the world. Because of the unknown probability of selecting samples in conventional SAMPLING methods and also invalidity of generalizing the results of non-probability SAMPLING methods to the statistical population, the necessity of introducing probability chain-referral SAMPLING methods, such as the respondent driven SAMPLING method becomes imperative. In this article, besides introducing the respondent driven SAMPLING method, some of the advantages of this method as relative decrease of the bias of estimates, declining the non-response rate by paying incentives and allocating weights proportional to reciprocal of the social network size of respondents to produce unbiased estimates are described. Moreover, some disadvantages of this method such as lack of producing differential samples by selecting similar seeds, lack of reaching more efficient method than snowball SAMPLING by implementing this method improperly and lack of achieving to equilibrium by existing weak social networks among members of interested population are stated. Another aim of this article is to compare SAMPLING methods of hidden population with the respondent driven SAMPLING method which are the results of implementing this method in different surveys and existing simulations.

Considering the importance of the mass campaign for measles- rubella vaccination in the elimination of measles and Congenital Rubella Syndrome, and also the necessity of the accurate quantitative and qualitative assessment of the process of this program and the estimation of the information coverage regarding the passive launch of the program, this assessment has been carried out within the population covered by Tehran University of Medical Sciences using a standard method. This study is descriptive- analytical. The necessary sample size was defined as 390 people for the estimation of the immunization coverage, 190 people in each step of the information coverage (and a total of 570 people for the overall three steps), and finally 24 executive teams for the assessment of the quality of the service. Lot Quality Assurance SAMPLING and subsequent analysis were used for the assessment of service quality, with the upper threshold set at 80% and the lower threshold at 30%. Each lot was defined acceptable or unacceptable based on the quality of the vaccination, the cold chain, the competence of the human resource, and the availability of the necessary materials and equipment. Data analysis was done using the Chi-Square and Fisher's exact tests. 96.4% (95% CI: between 94.6% and 98.2%) of the people between 5 and 25 years old had received the MR vaccine. 7 people (1.8%) of the vaccinated people were not in the target group of vaccination. From the total 190 people who were studied on the basis of information coverage, 152 people (80.9%), 184 people (96.8%) and 190 people (100%) were informed about the mass campaign for MR vaccination in the first, second, and the third steps respectively. More than 80% of the people were informed about the program through TV. The quality of the vaccination was acceptable in 19 executive teams (79.1%) and unacceptable in the other 5 executive teams (20.9%). In this study, the quality of the cold chain was acceptable in 23 executive teams (95.8%) and unacceptable in one team (4.2%). The competence of the human resource, the necessary materials and equipment for MR vaccination was acceptable in all 24 executive teams under study (100%). The enforcement of the mass campaign in such short period of time compared to similar programs in other countries demonstrated the success of the collaborators in the execution of this program. Overall it seems that regarding the quality of vaccination, information coverage, and the provision of materials and equipment in health centers of the districts, the program has achieved its goals.