A nurse-manager describes this process for IV insertions on a surgical unit: "We began requiring RNs to cleanse all peripheral insertion sites with both alcohol and an iodine-based cleanser before starting an IV because several multi-institutional studies found a statistically significant decrease in IV-related septicaemia rates for surgical clients when both alcohol and iodine were used as cleansers as compared with those who had alcohol-only cleansing prior to IV insertions."

Qualitative research is the most likely research design for this study. Qualitative research is a type of research that explores and describes the meanings, experiences, and perspectives of human phenomena. Qualitative research does not aim to test hypotheses or measure variables, but rather to generate rich and in-depth data that can be analyzed using various methods, such as thematic analysis, content analysis, or grounded theory. Qualitative research often uses purposive or convenience sampling, which means that the researcher selects participants who can provide relevant and diverse information about the phenomenon of interest. Qualitative research also often uses an iterative or emergent design, which means that the researcher adjusts the research questions, methods, and sampling strategies as the data collection and analysis progress. Therefore, it is possible that the number of subjects in a qualitative study increased between the time the study was begun and the date the researcher concluded the data collection, as the researcher may have identified new or additional participants who could contribute to the understanding of the phenomenon.

Quasi-experimental research is a type of research that examines the effects of an intervention or treatment on an outcome variable using a non-randomized or pre-existing group design. Quasi- experimental research aims to test hypotheses and measure variables using statistical analysis, such as analysis of variance or regression. Quasi-experimental research usually uses fixed or predetermined sampling and design strategies, which means that the researcher decides the number and characteristics of participants and groups before starting the data collection. Therefore, it is unlikely that the number of subjects in a quasi-experimental study increased between the time the study was begun and the date the researcher concluded the data collection, as this would compromise the validity and reliability of the study.

Experimental research is a type of research that examines the effects of an intervention or treatment on an outcome variable using a randomized controlled trial design. Experimental research aims to test hypotheses and measure variables using statistical analysis, such as analysis of variance or regression. Experimental research usually uses fixed or predetermined sampling and design strategies, which means that the researcher decides the number and characteristics of participants and groups before starting the data collection. Therefore, it is unlikely that the number of subjects in an experimental study increased

between the time the study was begun and the date the researcher concluded the data collection, as this would compromise the validity and reliability of the study.

Quantitative research is a broad term that encompasses both quasi-experimental and experimental research, as well as other types of research that use numerical data and statistical analysis to answer research questions. Quantitative research usually uses fixed or predetermined sampling and design strategies, which means that the researcher decides the number and characteristics of participants and groups before starting the data collection. Therefore, it is unlikely that the number of subjects in a quantitative study increased between the time the study was begun and the date the researcher concluded the data collection, as this would compromise the validity and reliability of the study.

Stratified random sampling is the type of sampling method that the researcher should choose to best answer the study question. Stratified random sampling is a type of probability sampling technique that involves dividing the population into homogeneous subgroups or strata based on a relevant characteristic or variable, and then selecting a random sample from each stratum using simple random sampling or systematic sampling. The proportion of participants from each stratum can be proportional or disproportional to their representation in the population. Stratified random sampling ensures that each subgroup or stratum is adequately represented in the sample, and that the sample is more representative and generalizable to the population. In this study question, the researcher wants to compare the adherence to a daily exercise regimen between clients discharged in warmer months and those discharged in colder months from a postoperative orthopedic unit. Therefore, the researcher can use stratified random sampling to divide the population of clients discharged from the orthopedic unit after joint replacement surgery during the past 12 months into two strata based on the season of discharge (warmer months or colder months), and then select a random sample from each stratum using simple random sampling or systematic sampling.


The other options are not correct because:

Quota sampling is a type of non-probability or convenience sampling technique that involves selecting participants who meet certain criteria or quotas until the desired sample size or proportion is reached. Quota sampling does not ensure that each participant has an equal chance of being selected, and that the sample is representative and generalizable to the population. In this study question, quota sampling would not be appropriate because it would not guarantee that the clients discharged in warmer months and those discharged in colder months are randomly and representatively selected from the population.

True random sampling is a type of probability sampling technique that involves selecting participants from a list or population using a random number generator or table. True random sampling ensures that each participant has an equal chance of being selected, and that the sample is representative and generalizable to the population. However, true random sampling does not ensure that each subgroup or stratum is adequately represented in the sample, and that the sample is more representative and generalizable to the population. In this study question, true random sampling would not be appropriate because it would not guarantee that the clients discharged in warmer months and those discharged in colder months are equally and proportionally represented in the sample.

Convenience sampling is a type of non-probability or convenience sampling technique that involves selecting participants who are easily available and accessible to the researcher. Convenience sampling does not ensure that each participant has an equal chance of being selected, and that the sample is representative and generalizable to the population. In this study question, convenience sampling would not be appropriate because it would not guarantee that the clients discharged in warmer months and those discharged in colder months are randomly and representatively selected from the population.