Chapter 11 Flashcards
T/F
In Qualitative studies, it is expected that, once a plan has been made, the methods will not be altered
F - in both Ql + Qn it is very possible that research methods will need to be revised as they are implemented
In some Ql methods, methods are expected to change as study progresses
steps in research process
- Define + describe knowledge gap or problem
- Develop detailed plan to gather info
- Implement the study
- Analyze + interpret results
- Disseminate the findings of the study
owledge gap or problem
Goals of step 1 (Define + describe the knowledge gap or problem)
Goal of first step in research is to establish a foundation of knowledge of what is already known
- Using existing theory + research to ID problem
- Requires thoughtful analysis b/c rarely does theory or past research easily blend into obvious research process
IN the first step, authors need to identify assumptions. What does this mean?
Why is this important?
need to ID assumptions that are embedded in the approach to a problem + the purposes being considered – this can be helpful b/c may realize we need to research + confirm the assumptions before we can move forward
Assumptions = dea that are taken for granted or viewed as through without conscious or explicit testing
T/F It is not uncommon to start with a bunch of potential research questions + then refine it to one
T
What is done in step 2 (develop a plan to gather info)…basically planning the study
- Includes decicing on general approach to be taken to the study + specific research design; IDing and developing plans for the study sample or participants; planning the measurement process; & last step is IRB proposal must be written + submitted in prep for implementation of the study
- Decide on sample + approaches to sampling
What must be considered during step 2 (planning)?
- Must consider what is known what has been shown to work, and what is feasible, time, cost, esblished measures or approaches + other resources (space, access to samples)
- Considering rigor, validity + reliability
- Consider how to mitigate Hawthorne effect
What part of the study design do the concepts of rigor, validity + reliability r/t most to when planning the study?
are central to decisions made about methods + measurement
Box 11.1:
Considerations affecting development of the detailed research plan:
1) Methods + samples used in previous research
2) Potential setting(s) for the study
3) Experience + knowledge of the researcher(s)
4) Resources available (time + money)
5) Subject safety + rights
6) Rigor, reliability, validity
What is the last step of the panning process (step 2) in research process?
- IRB approval (last step of this process) will require written proposal describing study background, purpose, literature review, design and measures, and how the rights of the subjects will be assured
- May also need to write funding grant proposals
Beyond providing funding + granting approval, how can the process of writing IRB and funding grants be helpful for the researchers?
• Both funding + IRB proposals provide outside input into the plans of the research study and often significantly improve those plans before the study is implemented
One of biggest responsibilities of the researcher during implementation is to….?
keep meticulous documentation of the sampling + data collection process
What sort of things need to be documented during the implementation phase?
• Need to document who declined or dropped out, any recision to sampling criteria, changes in timing or measurement process, and any anecdotal or incidental data that becomes relevant during the study implementation
Is the research process linear?
NO
• Steps are pretty fluid…may be moving back and forth between planning + implementation or next step (analysis + interpretation)
• May need to tweak sampling or data collection processes if encountering issues
During what kind of study (qn or ql) is it more likely that analysis will be interwoven with the implementation step (and all of the steps really) in the research process?
Ql
Why do you not want to analyze data in a qn study before the implementation phase is over?
What is an exception to this?
• In quantitative, usually don’t do this until full data is collected – want to isolate and control phenomena and not risk “contaminating the data collection process with ideas generated from the analysis”
Exception of this is analysis of sample characteristics (purposive or matched sample requires analysis of subject characteristics during the study implementation to effectively implement the sampling plan
how are records kept duri g the analysis + interpretation phase in ql and qn studies?
in Ql, done through audit trail + notations within software programs
in Qn, often documented in codebook
Codebook =
• record of categorizations, labeling + manipulation of data about variables in Qn study; is like audit trail…gives detailed description of how data were managed
o Includes info about how each of variables in study was measured, how data from the study was reviewed+ transferred into computer files, and all decisions made regarding the management of problems such as incomplete or confusing responses + decisions made around data analysis
how (generally) is analysis + interpretation of Qn + Ql data carried out?
- Qualitative data first transcribed into work processing program..is very time consuming. Can then be analyzed in qualitative analysis program or printed + done in hard copy
- Qn data also has to be transcribed into computer software programs. Once in data file must be carefully examined for accuracy
When is data interpretation done?
What is taken into account here?
• Interpretation is last step of analysis process – need to take into whole process up to this point as well as researcher’s expertise
What’s the last step in the research process?
Dissemination of the info
How is disseminating research results done?
- Spreading the knowledge!
- May occur through agency or organization that funded or hosted the study
- Often reported back to participants
- Lots of other obvious ways of disseminating info
What is aggregated data? And how does this r/t to anonymity of participants?
• Aggregated data = results are reported from entire sample rather than individuals
Must ensure anonymity of participants – requires that data primarily are reported in the aggregate and that there is careful scrutiny of the data
Does using aggregated data only in a research report guarantee anonymity of participants?
No - With small sample, it is possible that even aggregated data and elimination of traditional identifiers will not keep anonymity
