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Labor intensive, less formula-oriented and is a challenging task.
-no systematic or universal rules
-enormous amounts of data
-requires inductive skills and creativity to extract the most meaningful patterns, identify themes and weave them together
-goal is to reduce data for reporting purposes |
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| undergoes constant revision; really captures the meaning of the data they are finding |
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| read and look for meaningful segments/patterns and themes |
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| analyze patterns of everyday life to acquire a deeper understanding of the culture. Describe cultural symbols and identify cultural rules. |
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| concerned with the generation of categories, properties and hypotheses, NOT testing them. The product is the theoretical model. Use constant comparisons. |
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1. Transcribe
2. Develop a categorization scheme
3. Code data
4. Organize/use computer programs to manage if possible
5. Actual analysis pp. 469-71 |
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| Steps of Qualitative Analysis |
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| : [used mostly for statistical tests] looking at variability; this summarizes the average amount of the deviation of the values of the mean; how do these scores deviate |
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| to test the difference in proportion in two groups; correlational |
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| may be different depending on the day or the way the person feels; participant's responses to questions posed by the researcher, as in an interview. Most common data collection approach in both qualitative and quantative nursing studies. |
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| Biophysiological measures |
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| ex: vital signs, look at labs; decreases that human bias |
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| these come from our perspective; they may have bias |
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| : these come from existing data; you may gain new knowledge or a new understanding of the records that have already existed |
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| structure for data collection |
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| how structured should our data collection be/ structured (exact questions) vs. unstructured (tell me about…); the same data omfp os gathered from all participants in a comparable, prespecified way. |
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| Quantifiability in data collection |
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| what gender are you? (1- to males, 2- to females) see this type of question in the demographic section of a survey |
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| obtrusiveness in data collection |
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| how obvious you are in terms of your data collection; there are ethical implications to doing this type of data collection |
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| objectivity in data collection |
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| objective (collecting lab values, vital signs ect) vs. subjective (tell me how you feel about this situation) |
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| unstructured/semi-structured data collection |
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| (might have a list of topics or broad questions and you have an ability to ask more questions if you want more information), |
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| highly structured interviews in data collection |
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| (provide greater depth, quality, they tend to be more costly, they have a high return, they are more powerful then mail or paper kinds of surveys) |
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| performed directly within or on the individual or animal (ex: vital signs; vital capacity ect) |
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| we extract some material or substance and use that or send that to the lab for analysis (ex: blood tests; urine tests; bacterial tests; biopsies) Very accurate; very precise; and very objective. |
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| - Social desirability response set bias: |
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| a tendency to misrepresent attitudes or traits by giving answers that are consistent with prevailing social views |
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| Extreme response set bias |
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| a tendency to consistently express extreme attitudes or feelings (ex: strongly agree), leading to distortions because extreme responses may be unrelated to the trait being measured. |
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| Acquiescence response set bias |
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| a tendency to agree with statements regardless of their content by some people (yea-sayers) The opposite tendency for other people (nay-sayers) to disagree with statements independently of the question content is less common. |
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| . Immersion/crystallization |
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| (intuitive and interpretive) |
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| you have carefully collected your data and have kept notes on that. And is available for anyone that wasn’t to look at them. |
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| creativity, thoroughness, congruence, and sensitivity |
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| qualitative researchers value... |
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| rigor, validity, and objectivity. |
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| Qualitative researchers value... |
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| refers to the use of multiple referents to draw conclusions about what constitutes truth it also helps to capture a more complete and contextualized portrait of the phenomenon under study. |
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involves the use of multiple data sources to validate conclusions (three types of data triangulation),
1. time: involves collecting data on the same phenomenon or about the same people at different points in time.
2. Space: involves collecting data on the same phenomenon in multiple sites to test for cross site consistency
3. Person: involves collecting data for different types of levels of people, individuals, groups. |
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| involves using multiple methods of data collection about the same phenomenon |
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| investigator triangulation |
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| (coding and analysis)- refers to the use of two or more researchers to make data collection, coding and analytic decisions. |
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(multiple perspectives being used)- researchers use competing theories or hypotheses in the analysis and interpretation of their data.
c. External checks:
Peer debriefing- involves sessions with peers to review and explore various aspects of the inquiry
Member checks- researchers provide feedback to study participants about emerging interpretations and obtain participants reaction.
d. Searching for disconfirming evidence
e. Researcher credibility- want to make sure that the researchers are credible of the topic and the process. |
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| strategies include triangulation, data saturation; constant comparison, establish this data is credible. Refers to confidence in the truth of the data and interpretation of them. Qualitative researchers must strive to establish confidence in the truth of the findings for the participants. |
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| strategies include audit trail, multiple interviews, coding checks that show agreement. Refers to the stability of data over time and over conditions. |
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| strategies include audit trail, self reflection of the researcher evidenced by journals, accurate recording keeping. Refers to objectivity, that is the potential for congruence between tow or more independent people about the data’s accuracy, relevance and meaning. |
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| strategies include deliberately trying to find negative case examples, congruent findings with other research, replication of the study, clear explanation of the boundaries/limitations of the study, transfer what we found to a broader range of people. Refers to the extent to which qualitative findings can be transferred to other settings or groups. |
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includes randomized clinical trials for evidence based practice. Most reviews in Cochrane collaboration use meta-analysis. Problems include publication bias.
Definition: address the same research question and the same variables and look at the studies related to that. analysis within an analysis. Information from various studies is used to develop a common metric, an effect size. Offers a simple yet powerful advantage as a method of integration: objectivity. Advantage is that it concerns power. |
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integration of qualitative findings, don’t summarize, taking each study and result and look at the grand picture of it all, compare the findings and use some type of statistic to make meaning out of it. The goal is to look for a new explanation.
It is the bringing together and breaking down of findings examining them, discovering the essential features and in some ways combining phenomena into a transformed whole. |
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| direct observation of people's behaviors, characteristics and circumstances is an alternative to self-reports for certain research questions. (commonly used with grounded theory/ethnography.) |
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| scale (like a scale for measuring weight) |
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| is a device that assigns a numeric score to people along a continuum. (most common: likert: which consisters of several declarative statements (items) that express a viewpoint on a topic- how much do you agree or disagree with a statement) |
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| scale (like a scale for measuring weight) |
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| is a device that assigns a numeric score to people along a continuum. (most common: likert: which consisters of several declarative statements (items) that express a viewpoint on a topic- how much do you agree or disagree with a statement) |
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| brief descriptions of events or situations to which respondents are asked to react. |
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| lowest level, involves using numbers simplyh to categorize attributes. (examples: blood type or gender) |
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| ranks objects based on their relative standing on an attribute. (ex: researcher orders people from heaviest to lightest)Doesn't tell us how much greater one level is than another. |
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| occurs when researchers can specify the ranking of objects on an attribute and the distance between those objects. (ex: IQ test) |
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| highest level; have a rational, meaningful zero and therefore provide information about the absolute magnitude of the attribute. (ex: person's weight) |
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| consistency with which an instrument measures the attribute. |
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| the extent to which similar results are obtained on two separate occasions. |
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| a numeric index that quantifies an instruments reliability; .00-1.00; the higher the number the more reliable. The more homogenous the sample lowe the reliability coefficient will be. |
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| measure of degree; it is not proven but rather supported by evidence. The degree to which an instrument measures what is suppose to measure. |
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| the ability of a measure to identify a “case” correctly, that is, to screen in or diagnose a condition correctly. A measures sensitivity is its rate of yielding “true positives”. |
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| is the measure’s ability to identify noncases correctly, that is, to screen out those without the condition. Specificity is an instrument’s rate of yielding “true negatives”. |
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| provide a way of drawing conclusion about a population based on the data obtained from a sample; help the researcher decide whether the null (research) hypothesis should be accepted as true or rejected as false |
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| occurs when the null is rejected when it is actually true (there is no difference) how do we decrease our type 1 error= by increasing our probability |
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| occurs when the null is accepted when actually the null is false (there really is a difference) One can reduce the risk of a type 2 error by increasing the sample size. |
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| procedure used to test the statistical significance of a difference between the means of two groups is the parametric test called... |
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| Analysis of variance (ANOVA) |
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| used to test mean group differences of three or more groups. Decomposes the variability of a dependent variable into two components: variability attrubutable to the independent variable (ex: group status) and variability due to all other sources. (ex: individual differences, measurement error) |
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| Multiple comparison procedures |
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| their function is to isolate the differences between group means that are responsible for rejecting the overall ANOVA null hypothesis. |
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| used to hypotheses about the proportion of cases in different categories, as in a contingency table. |
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| CONSORT (consolidated standards of reporting trials) guidelines |
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| been adopted by major medical and nursing journals to help readers track study participants. |
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