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Nursing Research 63-377 Dr. Wally J. Bartfay

Nursing Research 63-377 Dr. Wally J. Bartfay. “If you want something done, ask someone who’s busy!” (Wally J. Bartfay, 2003). Review Quiz. (1) __________ are scientific investigations that make observations & collect data according to explicit criteria

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Nursing Research 63-377 Dr. Wally J. Bartfay

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  1. Nursing Research 63-377Dr. Wally J. Bartfay “If you want something done, ask someone who’s busy!” (Wally J. Bartfay, 2003)

  2. Review Quiz • (1) __________ are scientific investigations that make observations & collect data according to explicit criteria • (2) True or “classic” experiments have 3 essential criteria (list them): • (i) • (ii) • (iii)

  3. Types of Experimental Designs • (1) True or Classic experiments (pretest-posttest control group design) • (2) Solomon four-group design (similar to true experiment but has 2 additional groups, an experimental after-group and a control after-group) • (3) After-only design (also called post-test only control group design, has 2 groups like true experiment but no pretesting occurs)

  4. True or Classic Experiment

  5. Solomon four-group design

  6. After-only (post-test) experimental design

  7. Non-experimental Research Designs: Relationship/ difference Studies • (1) Correlational studies: examines relationship between 2 or more variables (eg., serum ferritin levels & AMI) • (2) Developmental studies (time perspective) • (a) Cross-sectional: specific relationships examined at one point in present time (effects of age on attitudes towards smoking in public places) • (b) Cohort studies:subject groups are compared based on specific characteristics (e.g., smokers vs. non-smokers) • (c) Longitudinal & prospective studies: data collected on same subjects at different time points in the future (subjects serve as their own controls, e.g., Framingham Heart Study) • (d) Retrospective: attempt to link present events with past events (e.g., incidence of prostate CA in chimney sweepers in London in the 19 Century)

  8. Methodological Research • Is development & evaluation of data-collection instruments, scales, or techniques (e.g., SF-26 for QOL, Caregiver Burden Scale) • Psychometrics deals with theory & development behind these (e.g., constructs/ concepts like anxiety, stress, caring)

  9. Methodological Research: Basic Steps • (1) Clearly define the construct/ concept or behaviour to be measured • (2) Formulate the items for the instrument/ tool to be used • (3) Develop clear instructions for users & respondents (age & educ. level appropriate) • (4) Test the tool’s/ instruments reliability & validity

  10. Meta-Analysis • Not a design per se, but a research method • Takes results of several studies in a specific area & synthesizes their findings to draw conclusions regarding the state of knowledge in a defined area & indications for future research (e.g., all studies examining exposure to asbestos & development of lung CA) • Can be used to synthesize both experimental & non-experimental studies

  11. Secondary Analysis • Not a research design but a form of research in which the researcher takes previously collected data from one study & reanalyzes data for secondary purpose • Original study may be experimental or non-experimental • E.g., original study examined stress & immune response in mothers with LBW infants. • Secondary analysis done on data from healthy mothers to describe whether effects of nutrition & physical activity in postpartum women according to 4 wt. categories (1) underweight; (2) normal weight; (3) overweight, and (4) obese

  12. Research Population • Is a well-defined set that has certain specified properties • It can be composed of people, animals, objects or events • Target populations: is the entire set of cases about which the researcher would like to make generations (e.g., nursing students, 1st time mothers, pt’s with COPD)

  13. Samples & Elements • Sample is a set of elements that make up the population • Element is the most basic unit about which information is collected (e.g., the person, place or object)

  14. Sampling • Is a process of selecting a portion or subset of the designated population to represent the entire population • Its purpose is to increase the efficiency of a research study • When done correctly, the researcher can draw inferences & make generations about the target population

  15. Major Sampling Types • (1) Representative sample: is one whose key characteristics closely approximate those of the population (e.g., 70% of population in a study of child-rearing practices were employed full-time, sample should be same %) • (2) Nonprobabilty: elements are chosen by nonrandom sampling (findings are less generalizable) • (3) Probability: uses some form of random selection when the sample units are chosen

  16. Major Sampling Types • (4) Quoto sampling: a form of nonprobability sampling in which knowledge about the population of interest is used to build some representativeness into the sample (uses strata) • (5) Purposive sampling: researcher selects subjects who are considered to be typical of the population (CA pt’s who have undergone bone marrow transplant due to leukemia)

  17. Sampling Basics

  18. Confounding variables • Occurs when there is an extrinsic factor that is associated with the predictor variable & a cause of the outcome variable • E.g., cigarette smoking is a likely confounder in ETOH-induced CHF • Simplest strategy to deal with it is to include specific criteria for inclusion/ exclusion

  19. Inclusion & exclusion criteria: • Also known as “delimitation” criteria • Lists characteristics of subjects that must be present or not present (e.g., certain age group, gender, specific Dx or Rx etc) • Criteria that specify your target population in the study • E.g., only non-smokers included in study looking at effects of ETOH-induced CHF

  20. Specification • Here the researcher “specifies” what criteria will be included & excluded & helps to control for potential confounding effects • E.g., only non-smokers included in study looking at effects of ETOH-induced CHF

  21. Matching • Used often in case-control studies • Involves selecting for each case a control with the same value of the confounding variable • E.g., In a study of ETOH as a predictor of CHF, the ETOH drinking case (subject with CHF) who smoked 1 pack cig. QD would be compared with a ETOH drinking case (subject with CHF) who DID NOT smoke 1 pack cig. QD

  22. Advantages to matching: • (1) Is an effective way to prevent confounding by constitutional factors like age & gender that are often strong determinants of outcome • (2) Used to control confounders that can’t be measured & controlled in any other way (e.g., twins matched to examine effects of environments vs. genetics) • (3) Increases precision of comparisons between groups and thus the power of the study • (4) May be used for sampling convenience, to narrow down an otherwise impossibly large number of potential controls

  23. Disadvantages of matching: • (1) Often requires additional time & expense to identify a match for each subject • (2) B/C matching is also a sampling strategy, the decision to match is made at beginning of study & is irreversible • (3) Possibility of “over-matching” exists, when the matching variable is not a confounder b/c it isn’t associated with the outcome at all

  24. Coping with confounders in the analysis phase: Stratification • assures that only cases & controls (or exposed & unexposed subjects) with similar levels of a potential confounding variable are compared • Involves segregating the subjects into “strata” (subgroups) according to the level of a potential confounder & then examining the relationship between the predictor & outcome separately in each stratum • Principal disadvantage is that only limited number of variables can be controlled for simultaneously • E.g., Confounders for MI include BP, cholesterol profiles, cig. Smoking, BMI, ETOH intake (to stratify on these 5 variables, & if only 3 strata each, would require 35 strata = 243

  25. Coping with confounders in the analysis phase: Adjustment • Statistical techniques that “model” the nature of the associations among the variables in order to separate out the effect of the confounder • Has advantage of multivariate adjustment techniques which can control for the influence of many confounders simultaneosly using “continuous variables” (e.g., age)

  26. Have a great week… • Sing, laugh and be merry…life as a student is great in comparison to the hostile reality of the work world….

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