Chapter 3 Study Designs, Area, Populations, Data Processing PDF

Summary

This document details research methodology, specifically focusing on study designs, areas, populations, and data processing. It covers various study designs like descriptive, analytical, and experimental, and discusses sampling techniques like probability and non-probability sampling.

Full Transcript

Chapter 3 Research methodology  Contents 1. Study design. 2. Study area and setting. 3. Study populations. 4. Sample size and sampling technique. 5. Data collection tools and technique. 6. Variables under study. 7. Data analysis. 8. Ethical considerations. 1. Study design  The study de...

Chapter 3 Research methodology  Contents 1. Study design. 2. Study area and setting. 3. Study populations. 4. Sample size and sampling technique. 5. Data collection tools and technique. 6. Variables under study. 7. Data analysis. 8. Ethical considerations. 1. Study design  The study designs can be classified based on the overall aim of the study as follows: 1. Descriptive study designs: aim to search for facts. 2. Analytical study designs: aim to search for causes. 3. Experimental study designs: aim to put solution into actions. 2. Study area and setting Description of study area by geographical boundaries, departments and detailed description about specific department. 3. Study population Including the targeted populations of the study by their characteristics.  Inclusion and exclusion criteria: 1. Inclusion criteria including the characteristics of study group and willing to participate during study period. 2. Exclusion criteria: characteristics of study group excluded from study. 4. Sample size and sampling technique  Sampling methods There are two major sampling methods used by investigators to draw samples 1. Probability samples. 2. Non-probability samples.  The probability samples include: 1. Simple random sample. 2. Systematic sample. 3. Stratified sample. 4. Cluster sample. 5. Multi-stage sample. Simple random sample Thus if a population is 5000 and a sample of 200 is to be drawn, then every one of the 5000 has the same chance of being selected in the 200 sample subjects.  example: A simple random sample of 50 pupils is to be obtained from a total population of a primary school of 500 pupils: One way is to put all the names from your population into a box and then select a subset (e.g., pull out 50 names from the box). Researchers typically use a computer program that randomly selects their samples. systematic random sample This is defined as the process in which the selection is done systematically according to a list of the targeted population. First, determine the sampling interval, which is symbolized by “k,” (it is the population size divided by the desired sample size). Second, randomly select a number between 1 and k, and include that person in your sample. Third, also include each k element in your sample. for example if k is 10 and your randomly selected number between 1 and 10 was 5, then you will select persons 5, 15, 25, 35, 45, etc.  Example: A researcher conducted a research in khartoum teaching hospital about knowledge, attitude and practice of medical doctors towards informed consent. The estimated sample size was 250 and the total number of the medical doctors on that date of the study mounted to 1000. The researcher used systematic sample to draw the participants. The researcher first obtained a list of all the doctors in khartoum teaching hospital. Then calculated the sample interval through dividing 1000 by 250 which was equal to 4. Then selected a random number between 1 and 4 using a random number generator. If the number was 3, then selected the individual enlisted number 3 in the list, then followed by 7, 11, 15,19 etc.  Sample size The number of participants should included in a study.  It can be estimated by 1. Total coverage if total number of participants is less than 200. 2. Use published tables. 3. Use sample size of similar study. 4. Use statistical formulas. 5. Data collection tools and technique  Data collection The process by which the investigator collects information required to answer the research questions. For each method there are specific instruments which are used for collecting data. State clearly: Which information to be collected? How to collect data? Who will collect the data? When to collect the data?  The common data collection methods include: interviewing can be held through instruments including questionnaire, interview guidance. 1. Individual interviewing methods: Interviewing is defined as the technique in which the interviewer meets the study subjects. 2. group interviewing method The groups of study subjects meet discuss, exchange ideas around a certain topic relevant to the research. Group discussion is the commonest instrument for this purpose. 3. observation method The data collected by observation. checklist is the commonest instrument used for this purpose. 4. Review of records, registers and reports The secondary data obtained by carrying review of collected data (secondary) in documents, records and reports. Instruments such as summary sheets and checklists are commonly used.  Note Well-constructed instruments are needed to collect quality data. Classically a questionnaire is formed up of questions covering all the study variables. But sections like clinical examination; laboratory investigations may be included as separate chapters in the questionnaire  The questionnaire A list of questions by which the researcher generates data from the study subjects. clinical & laboratory findings are included as they are elicited: presence/absence of enlarged spleen, Hb%, blood glucose level  Questionnaire design questionnaire design is a skill. 6.The study variables Variables are characteristics which take on different values in a study and which are measured. Variables may be: qualitative or quantitative. Only variables that are directly related to the objectives of the study are to be selected.  Dependent variables: These are outcome or effect variables. they are the variables in which the changes are the results of the level or amount of independent variables.  Independent variables: These are input or cause variables. they are the variables that are manipulated or treated in a study in order to see what effect differences in them will have on those variables proposed as being dependent on them.  Example: A certain study aims to determine the effect of such risk factors as age, nutritional status, presence of smokers in the family on the incidence of acute respiratory tract infections in children under 5 years of age. The dependent variable: incidence of ARI. The independent variables: age, nutritional status, presence of smokers in the family. 7. Data analysis plan 1. Computerized analysis by using computer through statistical package of social program (SPSS). (frequency, percentage, mean, standard deviation and chi-square test). 2. Manual analysis.  Study results may presented in form of tables and figures. 8. Ethical considerations: The research should respect the rights of participants, treat data with confidentiality (by using coded questionnaire). The participants should informed that, the information will be used for research only, he/ she has a right to participate in the study or not and he can discontinue at any time during study period and questionnaire will be filled by nurses in their rest time without any interpretation to their work. Approval was taken from university to ministry of health and hospitals. Approval from administrative authorities hospital should be taken. Consent should obtained from all participants after explanation. Participants has a right to benefit from the researcher knowledge. Any question? Thank you

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