Lecture 6 Data Collection PDF

Summary

This lecture covers data types and collection methods, including phases of data collection (permission, collection, and handling). It discusses various tools, such as surveys, interviews, and secondary data analysis. The document also outlines how to ensure data quality and the advantages and disadvantages of secondary data analysis.

Full Transcript

Data Types and Collection Methods Dr. K. Karunamoorthi M.Sc., M.Phil., DPHM., Ph.D., FRES (London)., Faculty of Public Health & Tropical Medicne Jazan University Kingdom of Saudi Arabia Email: [email protected] Phases in the Data Collection Process Three main stages can be distinguished:  P...

Data Types and Collection Methods Dr. K. Karunamoorthi M.Sc., M.Phil., DPHM., Ph.D., FRES (London)., Faculty of Public Health & Tropical Medicne Jazan University Kingdom of Saudi Arabia Email: [email protected] Phases in the Data Collection Process Three main stages can be distinguished:  Phase 1: Permission to proceed  Phase 2: Data collection  Phase 3: Data handling Phase 1: Permission to Proceed  Consent must be obtained from the;  Authorities:  Individuals  Community  Organizing meetings at national or provincial level, at district and ‫ في‬،‫قاطعات‬/‫ستوى الوطني أو ا‬/‫تنظيم اجتماعات على ا‬ .‫نطقة وعلى مستوى القرية‬/‫ا‬ at village level.  Clinical studies: Written informed consent. Phase 2: Data Collection When collecting our data, we have to consider: • Logistics: who will collect what, when and with what resources • Quality control WHEN should the Data be Collected? Consideration should be given to: • Availability of research team members, • The appropriate season(s) to conduct the field work, • Accessibility and availability of the sampled population, and • Public holidays and Vacation periods. Ensuring Quality It is extremely important for the reliable and valid, Otherwise it may lead to false or misleading conclusions. • Prepare a field work manual for the research team • Selection of appropriate research assistants - from the same educational level; • Train research assistants - Interview techniques • Pre-test research instruments and research procedures • Strict supervision – Larger survey • Interviewers to check whether the questionnaire is filled in completely Phase 3: Data Handling  Collected Data should be; – Checked for completeness and accuracy, – Clear procedure should be developed for handling and storing them.  Questionnaires are to be numbered; – identify the person who will be responsible for storing the data; – and how they are going to be stored. Basic Survey Types Surveys can be administered in a number of ways:  Face to face  Telephone  Self-administered 8 9 Data Collection Tools  Participatory Methods  Records and Secondary Data  Observation  Surveys and Interviews  Focus Groups  Diaries, Journals, Self-reported Checklists  Expert Judgment  Delphi Technique (It is an excellent way to gather feedback and reach a consensus among many experts. it can predict future risks and opportunities). IPDET © 2009 Different Approaches for Data Collection/Data Analysis  Experiment  Participant Observation  Survey  Ethnography (systematic study of people and cultures.).  Quasi-Experiment  Secondary Data Analysis  Content Analysis  Historical Comparative Methods (Archival Analysis )  Individual Qualitative Interview  Textual Analysis  Focus Group Discussion Data Analysis Secondary Data Analysis  A type of research in which data collected by others are reanalyzed. Primary Data Analysis  Original analysis of the data collected in a study. Meta-Analysis  ‘Analysis of analysis’  Quantitative procedure for summarizing or integrating the findings obtained from a literature.  Uses the results of individual research projects on the same topic as data points for a statistical study of the topic. Secondary Data Analysis ADVANTAGE  Saves cost for data collection.  Saves time required for data collection.  May obtain data otherwise impossible. Secondary Data Analysis.., DISADVANTAGE  Data collected may not be suitable for the researcher’s purposes. (Validity)  All necessary data may not be available in existing data.  Requires time to search for the data set.  Original data set may not be accurate.  Existing data sets may contain more variables than what the researchers need. Need time to sort out the data.

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