paper evaluations Flashcards

1
Q

Name 10 principal appraisal questions

A
  1. Credibility of the findings in light of earlier research?
  2. Has understanding been extended? alternative ways of thinking?
  3. Study aims clearly stated? conclusions directed towards aim of study? all questions discussed?
  4. Detailed description of the contexts in which the study was conducted to allow applicability to other settings
  5. What is the review process?
  6. Discussion of limitations of research design and their implications for the study evidence
  7. Sample composition/case inclusion – how well is the eventual coverage described?
  8. How well was the data collection carried out?
  9. How well has the approach to and formulation of the analysis been conveyed (vermittelt)?
  10. How well has detail, depth and complexity (i.e. richness) of the data been conveyed?
  11. How adequately has the research process been documented?
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2
Q

confirmation bias

A

interpretation of findings is rarely completely independent of our previous beliefs or preconceptions.

For example, higher standards of evidence may be required in the case of study findings that contradict an individual’s initial expectations, compared with a study that agrees with these expectations

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3
Q

types of clinical research studies

A

experimental or

observational

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4
Q

Hierarchy of evidence

A
  1. Systematic reviews and meta-analyses
  2. Randomised controlled trial
  3. Cohort studies
  4. Case control studies
  5. Cross sectional studies
  6. Case reports and case series
  7. Editorials and opinions
  8. In vitro research
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5
Q

What is a RCT

A

A study in which a number of similar people are randomly assigned to 2 (or more) groups to test a specific drug, treatment or other intervention. One group (the experimental group) has the intervention being tested, the other (the comparison or control group) has an alternative intervention, a dummy intervention (placebo) or no intervention at all.

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6
Q

Cohort studies

used when?

A

following groups of people over time

follow-up of study participants with varying exposures to observe which animals develop the outcome(s) of interest (e.g. clinical disease or mortality), and to

determine the effect of exposures on the outcome.

identifying the risk factors and causes of disease

potential confounding bias if retrospective!!!!

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7
Q

Case control studies

what are they used for?

risk?

A

observational study

comparison of two existing groups differing in outcome: compare group on the basis of some supposed causal attribute

  • used to identify factors that may contribute to a medical condition - cases are only recruited for the study once they have developed disease - good for rare diseases, fe narcolepsy
  • produces only an odds ratio, (inferior measure of strength of association compared to relative risk)
  • RISK FOR RECALL BIAS
  • difficult to find apporpriate control group
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8
Q

Cross sectional studies

what are they used for

A

SNAP SHOT

collect data from many different individuals at a single point in time.

purely observational

selection of participants based on particular variables of interest

USED TO: to describe characteristics that exist in a community, f.e.prevalence of disease

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9
Q

What is a case report

what is a case series

what are they used for?

A
  • detailed report of the symptoms, signs, diagnosis, treatment, and follow-up of an individual patient
  • used to describe unusual or novel occurence
  • follows a group of patients who have a similar diagnosis or intervention over a certain period of time.
  • describing the effectiveness of interventions on unusual diagnoses, and for describing unusual responses
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10
Q

Bias can be defined as

A

systematic (nonrandom) error in design, conduct or analysis of a study resulting in mistaken estimates

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11
Q

What is selection bias and what are different types 4

A

when the composition of study subjects or participants in a research project systematically differs from the source population.

  • nonresponse bias (e.g. respondents differ compared with those who do not respond in a questionnaire study
  • follow-up bias (loss to follow-up is different between groups being compared)
  • selective entry bias (e.g. use of horses that are currently racing is biased towards a healthy horse population
  • detection bias (controls wrongly classified when they have the disease of interest because, for example, they did not receive the same examination protocol as cases
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12
Q

Name the 3 main groups of bias

A

Selection bias: composition of study subjects or participants in a research project systematically differs from the source population.

Information bias: Occurs when the outcomes, exposures of interest (factors measured) or other data are incorrectly classified or measured. This might be, for example, due to use of poor diagnostic criteria

Confounding bias: mixing of the effects of two or more factors. f.e. testing effect of transport - includes maybe also high head carriage, no water,…

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13
Q

Randomized control study minimize which bias?

A

if blinded: reduces information or measurement bias.

random allocation to treatment groups:

  • reduces confounding bias
  • reduces selection bias
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14
Q

Difference between RTC and controlled clinical trials

A

Papers describing comparative studies in which subjects are allocated to intervention or control groups in a

nonrandom manner

are termed controlled clinical trials

risk of selection bias

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15
Q

What is a sample size calculation

A

For many studies, and in particular RCTs:

sample size clearly defined and justified using appropriate calculations

>>> big enough to have a high chance of detecting, as statistically significant, a worthwhile effect if it exists

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16
Q

Statistical tests are either

A

parametric (i.e. they assume that the data were sampled from a normal distribution)

nonparametric (i.e. they do not assume that the data were sampled from any particular distribution

Inappropriate statistical tests commonly used include use of parametric tests when data are not normally distributed, conducting multiple testing and ignoring clustered data