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Nursing - Bloomberg > ⚖️430: Research Methods QUANTITATIVE FINAL > Flashcards

⚖️430: Research Methods QUANTITATIVE FINAL Flashcards

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1
Q

What are the major classes of quantitative design?

A
  1. Experimental (and Quasi-experimental)

2. Non-experimental

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2
Q

What are the 3 criteria of causality?

A
  1. Preceded the effect in time
  2. Association between the cause and effect
  3. Relationship cannot be due to the influence of a third variable or confounder
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3
Q

What are the 3 aspects of experimental design?

A
  1. Manipulation
  2. Control/comparison
  3. Randomization
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4
Q

What are the different experimental designs?

A
  1. Randomized controlled trial (POSTTEST ONLY)
  2. Randomized controlled trial (PRETEST-POSTTEST)
  3. Cross-Over Design
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5
Q

What is a cross-over experimental design?

A

Sample:

  1. Treatment 1 ➡️ washout ➡️ Treatment 2
  2. Treatment 2 ➡️ washout ➡️ Treatment 1
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6
Q

What is a pretest-posttest randomized controlled trial experimental design?

A

Measures outcomes before and after experimental and control interventions

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7
Q

What are limitations of experimental designs?

A
  1. Not everything can be manipulated
  2. Hawthorne Effect
  3. Blinding not always possible
  4. May be unethical to withhold care
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8
Q

What are quasi-experimental designs?

A

Involves a manipulation but lacks either randomization or control group

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9
Q

What are the 2 categories of quasi-experimental designs?

A
  1. Non-equivalent control group design
    (Intervention group compared to nonrandomized control group)
  2. Within-subjects designs
    (One group studied before and after intervention)
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10
Q

What are strengths of quasi-experimental designs?

A

More feasible as compared to a true experiment

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11
Q

What are limitations of quasi-experimental designs?

A
  1. More difficult to infer causality

2. Rival explanations for results

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12
Q

What are categories of non-experimental designs?

A
  1. Correlational cause-probing research
  2. Descriptive correlational designs
  3. Univariate descriptive studies
  4. Cohort studies
  5. Case-control study
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13
Q

What is a cohort study?

A

Investigator identified exposed and none posed groups (cohorts) and follows them forward in time.

  • Useful when harmful outcomes occur infrequently

***Exposed and unexposed may begin with different risks of target outcomes (CONFOUNDING)

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14
Q

What are strengths of non-experimental designs?

A
  1. Efficient way to collect large amounts of data when intervention/randomization no possible
  2. Does not require artificial provision of exposure
  3. Treatments not withheld
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15
Q

What are limitations of non-experimental designs?

A
  1. Rival explanations for results

2. Limited ability to infer causality

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16
Q

Cross-sectional

A

Data collection at one time point, or more than one in close succession

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17
Q

Longitudinal

A
  1. Data collected at multiple time points over days/months/years
  2. Better at showing patterns of changed and at clarifying whether a chase occurred before an effect
  3. ATTRITION = loss of participants over time
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18
Q 
Which is NOT another term for randomization? 
A. Random sampling
B. Random allocation 
C. Random assignment 
D. None of the above
A

A. Random sampling

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19
Q

What are the 4 main aspects of Validity?

A
  1. Statistical Conclusion Validity
  2. Internal Validity
  3. Construct Validity
  4. External Validity
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20
Q

Validity

A

The degree to which inferences made in a study are accurate and well-founded

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21
Q

What are ways of controlling extraneous/confounding variables?

A
  1. Constancy of conditions
  2. Formal protocol to enhance intervention fidelity
  3. Randomization
  4. Homogeneity (restricting sample)
  5. Matching
  6. Statistical control (ex. Analysis of covariance)
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22
Q

Statistical conclusion validity

A

The ability to detect true relationships statistically

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23
Q

What are threats to statistical conclusion validity?

A
  1. Low statistical power (ex. low sample size)
  2. Weakly defined “cause” - independent variable poorly constructed
  3. Low implementation fidelity
  4. Poor intervention adherence
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24
Q

Internal validity

A

Extent to which it can be inferred that the independent variable caused or influenced the dependent variable

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25
Q

What are threats to internal validity?

A
  1. Temporal ambiguity
  2. Selection threat - bias arising from preexisting differences between groups
  3. History - other events co-ocurring with the causal factor
  4. Maturation - processes that result from passage of time
  5. Mortality/attrition - differential loss from groups
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26
Q

Construct validity

A

Key constructs are adequately captured in the study and thus the evidence in a study supports inferences about the constructs that are intended to represent.

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27
Q

What are threats to construct validity?

A
  1. Poor construct validity of measurement tools
  2. Reactivity to the study situation (Hawthorne Effect)
  3. Researcher expectancies
  4. Novelty effect
  5. Compensatory effects
  6. Treatment diffusion or contamination
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28
Q

External validity

A

The extent to which it can be inferred that the relationships observed in a study hold true in other samples or settings (ie. generalizability)

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29
Q

What are threats to external validity?

A
  1. Sample that is mom-representative of population
  2. Intervention that is difficult to replicate
  3. Artificiality of research environment
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30
Q

Open-ended questions

A
  1. Allows for more in-depth data

2. Analysis can be difficult and time-consuming

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31
Q

Closed-ended questions

A
  1. Greater privacy

2. Less likely to go unanswered

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32
Q

Composite psychosocial scales

A

Used to make fine quantitative discriminations among people

With different attitudes, perceptions, or needs

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33
Q

Likert Scales

A
  1. Consist of several declarative statements (items) expressing viewpoints
  2. Responses are on ah agree/disagree continuum (usually 5 to 7)
  3. Responses to items are summed to compute a total scale score (SUMMATED RATING SCALE)
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34
Q

Observation in quantitative studies

A
  1. Structured observations of pre-specifies units (ex. Behaviours, actions, events)
  2. Structures in what to observe, how long, and how to record

Methods:

  1. Category systems
  2. Checklists
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35
Q

Bromage Score

A

Observational rating on a descriptive continuum to test degree of motor block after epidural

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36
Q

What are disadvantages of observations?

A
  1. REACTIVITY = Behaviours May be altered by awareness of being observed
  2. Observer bias
  3. Resources required to gain entry into setting
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37
Q

In vivo measurements

A

Performed directly within or on living organisms (ex. Blood pressure)

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38
Q

In vitro measurements

A

Performed outside the organism’s body (ex. Urinalysis)

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39
Q

What are advantages of biophysical measures?

A
  1. Precision
  2. Objective
  3. Validity
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40
Q

What are disadvantages of biophysical measures?

A
  1. Resources required
  2. Many factors may affect variability
  3. Ethical responsibilities
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41
Q

What are the 2 types of biophysical measures?

A
  1. In vivo

2. In vitro

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42
Q

Errors of Measurement

A

Obtained score = True score +/- Error

= Signal +/- Noise

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43
Q

Reliability

A

The extent to which scores are free from measurement errors.

Reliability is consistency of measure, validity is accuracy of measure.

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44
Q

Reliability coefficients

A

0.00 to 1.00

Unsatisfactory < 0.70
Desirable >= 0.80

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45
Q

What are the 3 methods of assessing reliability?

A
  1. Test-Retest Reliability
  2. Internal Consistency
  3. Interrater Reliability
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46
Q

Test-Retest Reliability

A

Administration of the same measure to the same people on two occasions. Check correlation of test scores with retest scores.

47
Q

Internal Consistency

A

(Cronbach’s a)
Consistency across items in a composite scale. Instrument is administered on one occasion and the relationship between items tested.

48
Q

Interrater Reliability

A

Similarity between measurements of multiple observers/raters using the same instrument.

49
Q

Instrument Validity

A

The degree to which an instrument measures what it is supposed to measure

50
Q

What are the 4 aspects of instrument validity?

A
  1. Face validity
  2. Content validity
  3. Criterion-related validity
  4. Construct validity
51
Q

Face validity

A

Refers to whether the instrument looks as though it is measuring the appropriate construct. Based on judgment, no objective criteria for assessment.

52
Q

Content Validity

A

The degree to which an instrument has an appropriate sample of items for the construct being measured.

53
Q

Content Validity Index (CVI)

A
  • Expert evaluation
  • Quantitative measure
  • Proportion of items that are highly relevant on a numerical scale

Desired >= 0.8

54
Q

Criterion-Related Validity

A

The degree to which scores on an instrument are a good reflection of a “gold standard” criterion for the same construct.

55
Q

How is Criterion-related Validity evaluated?

A
  1. Concurrent Validity = correlated with external criterion, measured at the same time
  2. Predictive Validity = correlates with external criterion, measured at a future point in time
56
Q

Construct validity

A

Degree evidence captures the construct of interest. Especially useful for when there is no “gold standard” comparison.

57
Q

How is construct validity evaluated?

A

Known-groups (Discrimination) Validity

  1. Convergent Validity = test correlates with other measures of same construct
  2. Divergent Validity = test DOES NOT correlate with measures of other/different constructs
58
Q

How are measurements have both Reliability and Validity?

A

Reliability is necessary but not sufficient for validity.

Together the Obtained Score = True Score

59
Q

Statistical Significance

A

The results from the sample data are unlikely to have been caused by chance.

60
Q

Clinical Significance

A

The results have practical importance

61
Q

Confidence Intervals (CI)

A

Range of values within which a population parameter is expected to lie.

The narrower the CI, the more precise the estimate of effect.

62
Q

Relative Risk vs Absolute Risk

A

Absolute = likelihood event will occur under specific conditions

Relative = likelihood event with occur in a group compared to another group with different behaviours, environments, etc

Clinical significance of a given Relative Risk cannot be made unless you know the Absolute Risk.

63
Q

Number Needed to Treat (NNT)

A

Number of people that would need to receive the intervention to prevent one additional bad outcome.

Lower baseline absolute risk ➡️ higher NNT
Higher baseline absolute risk ➡️ lower NNT

64
Q

What are the 5 types of reviews?

A
  1. Systematic Review
  2. Meta-Analysis
  3. Meta-Synthesis
  4. Scoping Review
  5. Narrative Review
65
Q

What are the 6 steps in conducting a Review?

A
  1. Research Question
  2. Sampling of Primary Studies
  3. Quality Appraisal of Primary Studies
  4. Data extraction
  5. Data analysis
  6. Evidence Synthesis
66
Q

Systematic Review

A

Rigorous synthesis of research findings in a particular research question, using systematic sampling and data collection procedures and a formal protocol.

Goals:

  1. Reduction of bias and random error
  2. Transparency
  3. Reproducibility and Verifiability
67
Q

Literature search in a systematic review

A
  1. Detailed and Exhaustive
  2. Search strategy shoul reflect focused clinical question
  3. High yield expected
68
Q

Data extraction in a systematic review

A
  1. Collect relevant study information

2. Preferably performed in duplicate

69
Q

Analysis in a systematic review

A
  1. Qualitative synthesis (Narrative description) = provides overview of the available studies, common results, discrepancies, etc
  2. Quantitative synthesis (Meta-analysis) = only possible if studies are similar enough to be combined statistically
70
Q

Meta-Analysis

A
  1. Statistical process for combining results of multiple studies
  2. Attempts to overcome the problem of reduced statistical power in small sample sizes by combining results
  3. Results often depicted in a Forest Plot (or Blobbogram)
71
Q

Metasynthesis

A

Integration and/or comparison of findings from multiple qualitative studies.

Purpose = generate new knowledge

72
Q

Scoping Review

A

Determines the general state of knowledge related to a specific question and locate gaps in the literature.

Broader scope that a systematic review, but follows an established methodology

73
Q

Narrative Review

A
  1. Depends on authors’ bias
  2. Author picks criteria
  3. Search any databases, less structures and comprehensive
  4. Methods not usually specified
  5. Only narrative summary
  6. Can’t replicate review
74
Q

Systematic Review

A
  1. Scientific approach to a review article
  2. Criteria determines at outset (a priori)
  3. Comprehensive systematic search for relevant articles; use of systematic strategy
  4. Explicit methods of appraisal and synthesis
  5. Meta-analysis
  6. Reproducible
75
Q

Clinical practice guidelines development process

A
  1. Establish guideline development group
  2. Develop practice recommendations
  3. External review
  4. Monitoring and Updating
76
Q

What are the 6 Levels of Evidence?

A

Ia. Meta-analysis or Systematic reviews of randomized controlled trials
Ib. At least one randomized controlled trial
IIa. At least one well-designed controlled study without randomization
IIb. At least one other type of well-designed quasi-experimental study without randomization
III. Well-designed non-experimental descriptive studies, such as comparative or correlation
IV. Expert committee reports or opinions

77
Q

What are types of clinical practice guideline developers?

A
  1. Government agencies (ie. Ontario)
  2. Professional Associations (ie. RNAO)
  3. Disease or Population-Specific Organizations (ie. Heart&Stroke)
  4. International Organizations (ie. WHO)
  5. Other Organizations (ie. CAMH)
78
Q

What are challenges with Knowledge Transmission (KT)?

A
  1. Using plethora of terms to describe KT
  2. KT engages researchers and knowledge users with different perspectives
  3. KT involves a complex set of interactions
  4. Successful KT involves practice chance to change outcomes
79
Q

Ethical imperative for Knowledge Transmission (KT)

A
  1. (1/3) of patients DO NOT get treatments of proven effectiveness
  2. (3/4) of patients do not have info they need for decision making
  3. (1/4) of patients get care that is NOT NEEDED or Potentially harmful
  4. (1/2) of physicians DO NOT have evidence they need for decision making
80
Q

Diffusion of innovations (Rogers,1962,2003)

A

Influential theory that generally assumed to represent or form theoretical foundation of research utilization or KT. Explains the process and spread of an innovation within a social system.

81
Q

What are the 4 main factors that influence diffusion?

A
  1. Innovation
  2. Communication (method to inform others)
  3. Time (from first knowledge to acceptance/rejection)
  4. Social system
82
Q

What are the 5 steps in the process of innovation adoption?

A
  1. Knowledge
  2. Persuasion
  3. Decision
  4. Implementation
  5. Confirmation
83
Q

PEST Analysis

A

Societal Characteristics

  1. Political
  2. Economic
  3. Socio Cultural
  4. Technological
84
Q

KT (implementation) Strategies

A
  1. Reminders
  2. Educational (written) Materials
  3. Educational Outreach
  4. Audit & Feedback
85
Q

What is a Tailored Intervention?

A

Interventions planned after investigating factors that explain current practice and reasons for resistance to change.

  • Barriers identified through observation, focus groups, interview, surveys
86
Q

A theoretical integration of qualitative findings is known as a:

A

Meta-synthesis

87
Q

Can purposive sampling be used in quantitative research?

A

Yes

88
Q

What is a Type I statistical error?

A

The rejection of a null hypothesis when it should not be rejected

(False positive)

Risk is controlled by the level of significance (alpha) that is < 0.5 or 0.1

89
Q

Type II Statistical Error

A

Failure to reject the null hypothesis when it should be rejected.

False negative.

Controlled by ensuring adequate power.

90
Q

Can a low response rate threaten the external validity of quantitative research study?

A

Yes

91
Q

What are the 4 levels of Measurement?

A
  1. Nominal = data classified into categories (ie. gender, diagnosis)
  2. Ordinal = ranked categories (ie. disease stage)
  3. Interval = meaningful difference between values (ie. temperature, shoe size)
  4. Ratio = Meaningful difference between values within absolute zero (ie. height, fatigue score)
92
Q

Descriptive Statistics

A

Used to present, organize, and summarize the data from the sample.

  1. Univariate statistics
  2. Bivariate statistics
93
Q

Inferential Statistics

A

Used to make inferences about the population from the sample

94
Q

Univariate Descriptive Statistics

A

Measures of Central Tendency:

  1. Mean
  2. Median
  3. Mode

Measures of Dispersion:

  1. Range
  2. Standard Deviation (SD)
  3. Variance
95
Q

Positively skewed distribution

A

/\__

96
Q

Negatively skewed distribution

A

___/\

97
Q

Contingency Table - Bivariate descriptive statistics

A

A two-dimensional frequency distribution; frequencies of two variables are cross-tabulated.

Cells at intersections of rows and columns display counts and percentages.

Variables Nominal or Ordinal

98
Q

Correlation = Bivariate descriptive statistics

A

Indicates direction and magnitude of relationship between two variables.

Interval-ratio measures.

Correlation coefficient = Pearson’s r

99
Q

Null Hypothesis

A

Statistical tests to either reject or fail to reject the null hypothesis.

H0: There is no difference/relationship between the IV and DV.

H1: There is a difference.

100
Q

P<0.05

A

There is less than 5% chance that the difference is observed given the null hypothesis.

REJECT the null hypothesis

101
Q

P>0.05

A

There is a greater than 5% chance that the difference is observed given the null hypothesis.

FAIL TO REJECT the null hypothesis.

102
Q

Statistical Power

A

A measure of the probability that the statistical test will detect significant difference/effect IF ONE EXISTS.

103
Q

How is statistical power determined?

A
  1. Effect size (size of treatment/relationship effect)
  2. Alpha level
  3. Sample size

Smaller effect size = lower power
Smaller alpha = lower power

Power analysis should be done in advance to determine sample size.

104
Q

Parametric Statistics

A

For interval-ratio data that are normally distributed.

Ex:

  1. T-tests
  2. ANOVA
  3. Correlation
  4. Regression
105
Q

Non-Parametric Statistics

A

For nominal-ordinal data or non-normally distributed interval-ratio data.

Examples:

  1. Chi-squared (x2) Test
  2. Mann Whitney U test
106
Q

What is a 95% Confidence Interval?

A

Confident that the true point estimate lies within this range 95 times out of 100.

107
Q

How do you determine differences in continuous outcomes?

A

A confidence interval that includes 0 (ie. -0.5 - 4.8) signifies that it is plausible that there is no difference.

108
Q

How do you determine differences in odds ratios and relative risk?

A

A confidence interval that includes 1 (ie. 0.1-3.2) signifies that it is plausible that there is no difference.

109
Q

Cronbach’s alpha

A

The mean of all possible split-half correlations. Measures internal consistency.

110
Q

Convergent validity

A

A form of criterion validity where the criteria includes other measures of the same construct

111
Q

Relative Risk

A

Ratio of probabilities comparing risk of event among those exposed and not exposed.

Example:

(Risk of event in Treatment Group)/(Risk of event in control group)

112
Q

Odds ratio

A

Compares the presence to absence of an exposure given already known outcome.

Example:

(Odds of event in Treatment group)/(Odds of event in control group)

113
Q

Triangulation in Quantitative Research

A

Using multiple measures of an outcome variable to see if predicted effects are consistent.

Ex: Sleep diary + Actigraphy + Polysomnography

Nursing - Bloomberg (52 decks)

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