EIP final review

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Texas A&M University *

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1807

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Health Science

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Jun 24, 2024

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docx

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Uploaded by MegaStarLemur35

Final exam review UNIT 9 Qualitative research  To identify, describe, and ultimately understand human/ organizational behaviors, attitudes, and experiences and how they influence health  Uses the subjects’ own words and narrative summaries of observable behavior to express data NOT NUMBERS  Relies on words and images  PROS : Smaller sample size, open-ended process, targeted, specific, more affordable  CONS : Time consuming, subjective data, limited generalizability due to small sample size, data can be missed if the wrong questions are asked No numbers Descriptive Rich detail Thematic analysis Qualitative research five main design Case study Followed 1 person over time- ex: patient w a rare diagnosis and they followed them  Interviews, Documents, Reports, Observations Narrative Time-consuming, translated videos into a narrative Phenomenology Interest that involves more than 1 person, interview and sit down to get information Grounded theory The researcher doesn't have a theory in mind, not well studied or evidence to support a theory Ethnography Cultures, context, how do people differ, or share routine/rituals Interest in the culture within the person  Qualitative sampling methods  Purposive sampling  Subjects aren’t selected randomly but rather a specific purpose by the researcher to best meet the needs of the study “judgment sampling’  Convenience sampling  Obtained by ‘convenience’ from a group of people that are easy to contact  Voluntary response  Easy to contact/ participants volunteer to be in  Snowball  When it’s difficult to recruit, researchers will use participants to recruit others, as they get in contact with more people  How do you collect qualitative data (qualitative data collection methods)?  Nonprobability sampling methods where subjects/individuals are selected using non-random criteria, not every person has a chance of being included UNIT 10

Mixed Methods studies  Using both quantitative and qualitative approaches within 1 study strengthens the validity of the findings Concluding through different routines qualitative and quantitative Convergent Exploratory sequential Explanatory sequential Literature review as a process vs a product  Process identifies topic, searches literature, selects/organizes articles, develops thesis/purpose  Product summarizes articles on a topic Differentiate between the different types  Narrative, systematic review, scoping review UNIT 11 Reliability (repeatability)  Can you reply on the results?  Formula= true score/ observed score  Measures of reliability  What is Internal consistency ? Be prepared to judge whether a scale has excellent, great, good, or poor internal consistency  What is inter-rater reliability and how is it measured? What % agreement between the two raters is considered good?  The same phenomenon is measured by DIFFERENT observers 10-20% of your data and have the 2 nd person independently code it  What is intra-rater reliability and how is it measured? What % agreement between the two raters is considered good?  The same person measures the same phenomenon REPEATEDLY Variability (measures what it's suppose to measure)  Content Do two measures agree on the same result?  The results are supported by another scale  Criterion (concurrent & predictive) Does one outcome predict the result of another?  Construct Does the tool measure a theoretical construct accurately?  Does the results from our muscle strength scale correlate with scores from a ROM scale? QUALITATIVE (CATEGORICAL VARIABLES) Nominal (by name) gender, race, eye color Ordinal (in order) letter grade, agree/disagree QUANTITATIVE (NUMERICAL VARIABLES) Interval (distance is meaningful) temperature, 1-10 rating scales Ratio (absolute zero) time, weight, height

Pg. 266 Range: difference between highest and lowest values in the distribution Variance: considers the dispersion of individual values around the mean Standard deviation: derived from variance and allows variance to be expressed in the same unit of measurement Z-SCORE Null hypothesis: NO SIGNIFICANT DIFFERENCE between specific populations, any observed difference being due to sampling/ experimental error Cohen's d value- effect size Small effect size d= .2 or less Medium effect size= .5 Large effect size= .8 or more Alpha 95% or .05 Type 1 error: difference in statistical conclusion

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