Data Collection And Management Techniques
Data Collection And Management Techniques
Observation, interview, and review of documents are the most common sources of data collection. In a qualitative research study on alternative and complementary medicine for schizophrenics, both interviews and observation are appropriate data collection methods (Creswell, 2013). The research will primarily use interviews, including person-to-person and group interviews, as well as focus groups. A highly structured interview framework will be employed with predetermined questions, while remaining flexible to include open-ended questions to gather additional insights from participants. These open-ended questions will allow for variations in wording and order to elicit comprehensive responses.
Ethical considerations will be prioritized, ensuring informed consent and building rapport with participants to foster trust. Such rapport will encourage respondents to openly share thoughts and feelings about antipsychotic drugs and the potential need for alternative treatments. Sample questions may include inquiries about side effects experienced from antipsychotics and opinions on alternative therapy options. The goal is to create an environment where participants feel comfortable expressing their genuine perspectives.
Prior to data collection, the researcher will identify specific data requirements based on the research questions. Individual interviews will be recorded via audio or video, with participants’ consent and assurances of confidentiality. Data management will involve securing access rights by consulting relevant authorities and following protocols for data confidentiality and security. Backup procedures, access controls, and storage protocols will be established, including the selection of appropriate software and storage media. Metadata documenting data collection methods and content will be computerized and stored securely.
The entire data lifecycle will be considered, including how data will be handled after the research concludes. Nikon’s Nivo M total station software, renowned for its clarity and efficiency, will facilitate data organization and measurement accuracy. It supports quick configuration and reduces time spent switching modes, which optimizes data processing. This software is suitable for managing raw data, making coding more efficient, and ensuring high-quality data in demanding field conditions.
In conclusion, effective data collection and management are vital to the success of qualitative research (Patton, 2002). The techniques chosen must align with the research objectives, questions, and context. For this study on schizophrenia treatment options, the combination of structured and open-ended interviews, ethical considerations, and reliable data management tools will ensure comprehensive and credible results.
References
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