Documentation of Qualitative and Quantitative Research Methods

Introduction

Quantitative research design involves objectives, logic and numbers. The research questions are usually clearly defined, and they always require structured research instruments to enable the realization of objective conclusions. On the other hand, qualitative research design involves analysis and collection of data that is non-numerical (Mehrad & Zangeneh, 2019). It majorly offers solutions to the how and whys of the phenomenon being investigated. In most cases, it explores the meanings of the typical human experiences. There is a need to document the two research designs to understand their differences. Therefore, the paper is set to document qualitative and quantitative research methods by focusing on their differences and their use in research studies related to the consumption of marijuana.

Part 1

Differences between Qualitative and Quantitative Research

Sampling and Sample Sizes

The qualitative approach utilizes the non-probability sampling purposeful approaches. The sampling technique allows the selection of the study participants intentionally due to their capacity to offer pertinent information crucial in explaining the research questions (Rahman, 2023). The quantitative research methodology relies on probability-based criteria. Probability sampling is usually vital in the filtration of individuals from a population to create a sample (Rashid et al., 2021). Nevertheless, the sample sizes in the quantitative approach are usually large compared to qualitative research, which generally has relatively low sample sizes.

Data types

Quantitative data types involve the continuous and the discrete data. The constant data involves numerical values that take any possible interval and range (Sileyew, 2019). The continuous data is represented as fractional and decimal values and can be easily divided into smaller units. It involves time, temperature, weight and height measurements. The discreet data concerns numerical values that can only take on distinct and specific values. Conversely, data in qualitative data is described and felt. The main types are ordinal, nominal and binary. The data types allow researchers to understand the meanings and trends of natural actions (Mehrad & Zangeneh, 2019).

Data Collection Approaches

The data collection process often focuses on sample sizes that are relatively low in qualitative design (Renjith et al., 2021). In most cases, the data is always detailed and rich to allow the data users to make objective and informed conclusions from the entire methodology. On the contrary, the quantitative research process focuses on the potential of collecting data from generally large sample sizes. The large sample sizes are usually instrumental in explaining a larger population to allow for generalization (Kinyua, 2023). The probability sampling techniques include cluster, systematic, stratified, and simple random sampling. Non-probability involves quota, consecutive and convenience sampling.

Data Analysis Approaches

Qualitative research involves the systemizing of descriptive data that is collected via observations, surveys and interviews. The data analysis often identifies the themes and patterns informing the textual data (Busetto, Wick & Gumbinger, 2020). The techniques used include discourse analysis, grounded theory, and narrative, thematic and content analysis. Content analysis quantifies and examines the presence of particular images, concepts, subjects and words. Data analysis in quantitative research aims to identify relationships, trends and patterns between variables through statistical and mathematical calculations (Mehrad & Zangeneh, 2019). The analysis is usually more objective due to its reliance on facts and its capacity to realize quick answers for sample sizes that are relatively large.

Part 2

Research Design for a Qualitative Design

In the study by Mercurio et al., 2019 a qualitative research design is involved where the research involved qualitative interviews. The interview involved a semi-structured agenda designed to collect the participant’s information regarding their use, perceptions and reasons for using marijuana. The study participants were recruited by obtaining medical cards for the marijuana users who perceived that utilizing marijuana would alleviate the symptoms being demonstrated by the patients. Besides, the participants were supposed to be 18-70 years old. The interviews were carried out, then de-identified and transcribed after being audio recorded. The data coding was refined in the entire coding process to involve the emergent topics (Mercurio et al., 2019). The codes were summarized and reviewed to establish the key themes necessary in the reporting process. The study’s main themes were comparing other medications to medical marijuana, the impacts of medical marijuana policy and marijuana substitution with other medications.

Research Design for Quantitative Research

The study by Zuckermann et al. (2020) involved a quantitative research design where the analysis was longitudinal. The study involved high school students from Canada among students who are currently in grades 9-12. The study aimed to assess the spontaneous cannabis prevalence, cessation and reduction between the different transitions at the grade levels. The study measures were those associated with truancy, homework completion, English and math academic achievement and frequency of cannabis use. Data collected was from 89 schools from about 45298 students, and the data was linked for two consecutive years. The linkage resulted in a dataset containing 37231 students. The modelling of effects that are long-term makes data for three consecutive years to be linked, leading to the generation of 42861 by 13476 students. The sample size reduction resulted from the students needing more data collection because of absences and scheduled spares from their learning institutions due to personal reasons. The variables utilized in the study were cannabis use, substance use, and academic variables. The analysis of the results was in version 9.4 of SAS. A multinomial logit transition model was vital in accounting for the bivariate dependencies between two continuous time pint observations. Zuckermann et al. (2020) identify that the Markov model modelling approach is well-centred and has been used to analyze the transition in similar contexts over time. The data was analyzed and visualized in tables and graphs, offering more insight into the study findings.

Conclusion

In summary, the documentation of qualitative and quantitative research methods by focusing on their differences and their use in research studies related to the consumption of marijuana is critical in understanding the nature of qualitative and quantitative research. The qualitative approach utilizes the non-probability sampling purposeful approaches, and the quantitative research methodology relies on probability-based criteria. Quantitative data types involve continuous and discrete data, while qualitative data types are ordinal, nominal and binary. The data collection process often focuses on sample sizes that are relatively low in qualitative design and large sample sizes in quantitative design.

References

Busetto, L., Wick, W., & Gumbinger, C. (2020). How to use and assess qualitative research methods.  Neurological Research and Practice, 2, 1-10.

Kinyua, R. F. (2023). Quantitative Research Designs, a Review of Extant Literature.

Mehrad, A., & Zangeneh, M. H. T. (2019). Comparison between qualitative and quantitative research approaches: Social sciences.  International Journal For Research In Educational Studies, Iran, 5(7), 1-7.

Mercurio, A., Aston, E. R., Claborn, K. R., Waye, K., & Rosen, R. K. (2019). Marijuana as a substitute for prescription medications: A qualitative study. Substance use & misuse, 54(11), 1894-1902.

Rahman, M. M. (2023). Sample Size Determination for Survey Research and Non-Probability Sampling Techniques: A Review and Set of Recommendations.  Journal of Entrepreneurship, Business and Economics, 11(1), 42-62.

Rashid, A., Rasheed, R., Amirah, N. A., Yusof, Y., Khan, S., & Agha, A. A. (2021). A Quantitative Perspective of Systematic Research: Easy and Step-by-Step Initial Guidelines. Turkish Online Journal of Qualitative Inquiry, 12(9).

Renjith, V., Yesodharan, R., Noronha, J. A., Ladd, E., & George, A. (2021). Qualitative methods in health care research. International journal of preventive medicine, 12.

Sileyew, K. J. (2019). Research design and methodology. Cyberspace, 1-12.

Zuckermann, A. M., Gohari, M. R., de Groh, M., Jiang, Y., & Leatherdale, S. T. (2020). Original quantitative research-Cannabis cessation among youth: rates, patterns and academic outcomes in a large prospective cohort of Canadian high school students. Health Promotion and Chronic Disease Prevention in Canada: Research, Policy and Practice, 40(4), 95.