QUIZ 3: Chapter 27 Systematic Reviews of Research Evidence Flashcards

1
Q

What type of review does this describe:

“a review that methodically integrates research evidence about a specific research question using carefully developed sampling & data collection procedures that are spelled out in advanced in a protocol”

A

Systematic review (p. 653

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2
Q

True or False:

systematic reviews, unlike other types of reviews, are a process of developing, testing, & adhering to a protocol with explicit rules for gathering data - the research evidence - from studies that address a particular problem

A

True

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3
Q

Is a systematic review of evidence from qualitative studies also known as a meta-analysis?

A

No, a meta analysis is a systematic review of evidence from QUANTITATIVE studies

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4
Q

Yes or No:

Is the essence of a meta-analysis that information from various studies be used to develop a common metric, the effect size?

A

Yes

and the effect size averages are averaged across studies, which yields information about the EXISTENCE of a relationship between variables as well as the MAGNITUDE of this relationship

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5
Q

Name 3 advantages to meta-analyses?

(may be helpful to think of the chorus to that song back in the day…“Are you down with O.P.P?” as an acronym for remembering these advantages)…on another note, i had NO idea what that actually stood for until i just looked it up, whoa!

A

Objectivity
Power
Precision

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6
Q

Which advantage does this describe (objectivity, power, or precision):

  • draws conclusions about how big an effect an intervention has
  • estimate effect size across multiple studies yields smaller confidence intervals than individual studies
A

Precision (p. 654-655)

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7
Q

Which advantage does this describe (objectivity, power, or precision):

  • makes decisions more explicit
  • integration is statistical
A

Objectivity (p. 654)

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8
Q

Which advantage does this describe (objectivity, power, or precision):

  • probability of detecting a true relationship between the IV and DV
  • combining results across multiple studies increases this
A

Power (p. 654)

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9
Q

Which step is out of order within the “Steps in a Meta Analysis”:

  1. Formulating a problem
  2. Designing the meta-analysis study
  3. Searching literature for data
  4. Analyzing data
  5. Extracting/encoding data for analysis
  6. Calculating effects
  7. Evaluating study quality
  8. Writing report
A

4 and #7 should be switched

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10
Q

Which step of the steps in a meta analysis does this describe (formulating a problem, designing the meta-analysis study, searching literature for data, evaluating the study quality, extracting/encoding data for analysis, calculating effects, analyzing data, writing report):

  • essential for collecting & integrating meaningful data
  • start with broad question
  • narrow down to specific question (key constructs conceptually defined; indicate boundaries of inquiry)
  • develop a problem statement
A

Formulating a problem

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11
Q

Which step of the steps in a meta analysis does this describe (formulating a problem, designing the meta-analysis study, searching literature for data, evaluating the study quality, extracting/encoding data for analysis, calculating effects, analyzing data, writing report):

  • using standardized search strategies
  • deciding on published vs. grey literature
  • addressing publication bias
A

Searching the literature

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12
Q

Which step of the steps in a meta analysis does this describe (formulating a problem, designing the meta-analysis study, searching literature for data, evaluating the study quality, extracting/encoding data for analysis, calculating effects, analyzing data, writing report):

  • develop or select quality assessment scales
  • decide on coding for quality elements
A

Evaluating the study quality

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13
Q

Which step of the steps in a meta analysis does this describe (formulating a problem, designing the meta-analysis study, searching literature for data, evaluating the study quality, extracting/encoding data for analysis, calculating effects, analyzing data, writing report):

  • project organization
  • planned sampling procedures
  • quality of primary study
  • statistical heterogeneity
A

Designing the meta-analysis study

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14
Q

Which step of the steps in a meta analysis does this describe (formulating a problem, designing the meta-analysis study, searching literature for data, evaluating the study quality, extracting/encoding data for analysis, calculating effects, analyzing data, writing report):

  • calculate effect size for each study
  • if outcomes across studies are on identical scales (subtract the mean of outcome from treatment and control groups)
  • if outcomes are on different scales (use neutral index - Cohen d)
  • if outcomes across studies are dichotomous (calculate relative risk, odds ratio, & absolute risk reduction)
A

Calculating effects

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15
Q

Which step of the steps in a meta analysis does this describe (formulating a problem, designing the meta-analysis study, searching literature for data, evaluating the study quality, extracting/encoding data for analysis, calculating effects, analyzing data, writing report):

  • extract relevant info about variables of interest
  • develop data extraction form
  • develop codes & coding manual
A

Extracting/encoding data

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16
Q

Which step of the steps in a meta analysis does this describe (formulating a problem, designing the meta-analysis study, searching literature for data, evaluating the study quality, extracting/encoding data for analysis, calculating effects, analyzing data, writing report):

  • disseminating findings
  • Cochrane & PRISMA
A

writing report

17
Q

Which step of the steps in a meta analysis does this describe (formulating a problem, designing the meta-analysis study, searching literature for data, evaluating the study quality, extracting/encoding data for analysis, calculating effects, analyzing data, writing report):

  • calculate summary statistic that captures effect for each study
  • pooled effect estimate is computed as weighted average for all studies
  • identify heterogeneity (visual inspection with forest plots, statistical inspection with chi-square)
  • decide on fixed effects vs. random effects
  • examine factors affecting heterogeneity
  • handle study quality
  • address publication bias
A

analyzing data

18
Q

What do these 2 factors affect (within analyzing the data)?:

  1. subgroup analyses (involves splitting the effect size info from studies into distinct categorical groups, such as gender)
  2. meta-regression (involves predicting the effect size based on possible explanatory factors)
A

heterogeneity (pgs. 663-664)

19
Q

Can you name 4 strategies that deal with the issue of study quality in a meta-analysis?

A
  1. review inclusion/exclusion criteria
  2. determine if sensitive analysis is needed
  3. consider quality as basis for exploring heterogeneity
  4. weight studies according to quality criteria (p. 664)
20
Q

I didn’t create a flashcard for this, but it may be helpful to look at the funnel plot figures in chapter 27 that examine the possibility of a publication bias

A

Page 665