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Preparing and Conducting Interviews to Collect Data - Essay Example

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This paper "Preparing and Conducting Interviews to Collect Data" has discussed the unstructured interview technique as an important data collection method in qualitative research. The scenario provided implies that qualitative data will be collected, hence the use of the data collection method. …
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Extract of sample "Preparing and Conducting Interviews to Collect Data"

The paper "Preparing and Conducting Interviews to Collect Data" is a worthy example of an essay on nursing. Primary data collection is an important component of contemporary nursing research. Available literature demonstrates that using the right data collection method not only ensures that data are collected in a scientific and standardized manner, but also guarantees high-quality research and credible findings due to the enhancement of the accuracy, validity, and reliability of research findings (Udtha, Nomie, Yu, & Sanner, 2015).

The present study discusses the unstructured interview technique as an important data collection method in qualitative research. The interview technique, according to Sullivan-Bolyai and Bova (2014), is “a method of data collection where a data collector asks subjects to respond to a set of open-ended or closed-ended questions” (p. 279). The interview technique can be used in both qualitative and quantitative research, with available nursing scholarship demonstrating that quantitative interview questions are closed-ended whereas qualitative research questions are open-ended (Doody & Noonan, 2013).

Interviews are optimally utilized when the data collector may need to illuminate the task for the research participant or is interested in gathering more personal information from the respondent, as semi-structured and open-ended questions allow more varied information to be collected (Sullivan-Bolyai & Bova, 2014). There is a range of formats from which to choose, including structured interviews (each respondent is asked the same questions using the same wording and in the same order as all the other participants), unstructured interviews (characterized by a broad open question and subsequent questions that are dependent on the respondent’s responses), and semi-structured interviews (involve the use of predetermined questions, where the data collector is free to request for clarification).

Unstructured interviews can be useful in a scenario that demands the researcher to have an in-depth understanding of persons providing care to family members with long-term illnesses such as Parkinson's disease and Dementia. In such a scenario, the researcher purposes to not only gain deep insight into an underlying issue but also to assist participants to describe what is important to them (Doody & Noonan, 2013). As such, asking questions in an unstructured format and having the opportunity to probe further by asking subsequent questions may assist the participants to express in detail their experiences, behaviors, feelings, or attitudes of being a caregiver to a family member with a long-term illness (Sullivan-Bolyai & Bova, 2014).

This data collection method is best in the described scenario as it enables the researcher to develop rapport with participant, gives the researcher the opportunity to observe as well as listen, enables more complex questions to be asked, and provides the researcher with the opportunity to probe the participant’s responses and seek for further clarification (Sullivan-Bolyai & Bova, 2014; Udtha et al., 2015). The unstructured interview technique is associated with potential pitfalls.

In the described scenario, the data collection method may seem intrusive to the participants given that there is an opportunity to probe issues associated with caring for terminally ill patients. Additionally, the data collection method may be susceptible to bias, particularly in contexts where the participant may desire to please the researcher or in situations where the participant may provide an official point of view rather than a personal opinion of the issues at hand (Sullivan-Bolyai & Bova, 2014).

Caution needs to be exercised to ensure that the pitfalls highlighted do not compromise the quality of data and subsequent findings.

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