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BPT02 Research and Evidence in Physiotherapy > Quantitative Research > Flashcards

Quantitative Research Flashcards

1
Q

Definition of Quantitative Research

A

Research methods dealing with NUMBERS and anything that is MEASURABLE IN A SYSTEMATIC WAY of investigation of phenomena and their relationships. It is used to answer questions on relationships within measurable variables with an intention to explain, predict and control a phenomenon.

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2
Q

Purpose of Quantitative vs Qualitative Research

A

Quantitative: Measuring outcomes. Generalize results from sample to population - How much?

Qualitative: Deep understanding of phenomenon (often exploratory) - What? Why?

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3
Q

Data Collection of Quantitative vs Qualitative Research

A

Quantitative: Standardized techniques (e.g. tests, scales, questionnaires).

Qualitative: Unstructured or semi-structured techniques (e.g. interviews, open ended questionnaires, focus groups) (i.e. less structure).

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4
Q

Data analysis of Quantitative vs Qualitative Research

A

Quantitative: Numerical comparisons and statistical inferences.

Qualitative: Themes from descriptions.

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5
Q

Research Question of Quantitative vs Qualitative Research

A

Quantitative: Clearly defined (PICO)

Qualitative: Not (always) clearly defined (PICo, SPIDER, SPICE)

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6
Q

Goal of Quantitative vs. Qualitative Research

A

Quantitative: Verify the theory, Test hypothesis.

Qualitative: Development of theory, hypothesis.

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7
Q

Key Characteristics of Quantitative Research

A
  • Process is deductive (To test the idea/s)
  • Data is numeric (To enable statistical analysis).
  • Pre-specified methods are used (to ensure scientific rigour).
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8
Q

4 Steps of Quantitative Research

A

Theory - Hypothesis - Obeservation/test - Confirmation/rejection

You have a theory, from it you make a hypothesis, test the hypothesis, confirm or deny the hypothesis.

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9
Q

Key Objectives of Quantitative Research

A
  • To describe (Impact/burden of the problem)

- To evaluate (Connection between the dependent and independent variable vs causation) (To test a treatment).

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9
Q

Key Objectives of Quantitative Research

A
  • To describe (Impact/burden of the problem).
  • To evaluate (Connection between the dependent and independent variable vs causation) (To test a treatment).
  • To predict (Identify variables that predict outcomes).
  • To compare (Identify differences between groups) (provide a base of evidence for practice).
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10
Q

Research Designs

A

Descriptive (PO)

  • Survey/Case reports
  • Qualitative

Analytical (PICO)

  • Observational analytic
  • Experimental
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11
Q

Descriptive Design

A
  • Without an intervention (retrospective)
  • Not to quantify relationships
  • Reveal important findings - make a new hypothesis
  • N (number of participants) can be small, but # variables can be large.
  • Case reports, Case-series, single case design, qualitative studies and surveys (cross-sectional) studies.
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12
Q

Analytical Design

A
  • Quantify relationship between two factors: Effect of intervention/exposure on outcome.
  • Test hypothesis
  • Measuring intervention/exposure (observational analytic design: case-control, cohort, cross-sectional…)
    Or
  • Researcher manipulates intervention/exposure (experimental design: RCT).
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13
Q

Quasi Experimental

A

Test causality with sub-optimal variable control (when you cannot control every confounding factor).
- Before - after design

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14
Q

True Experimental

A

Test causality with optimal variable control (no confounding factors).
- Randomized Control Trial

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15
Q

Case-Study/Case-Series

A
  • No control group
  • Explore new treatment/topic on which limited knowledge exists
  • Often qualitative (rare in quantitative: used when not enough participants are found (rare diseases))

Participant with condition of interest → Information about clinical outcome.

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16
Q

Case-Control Design

A
  • Retrospective
  • Two groups: one with desired outcome - one without. What might have caused the desired outcome? Compare the differences.
  • Data already existing. Does not modify the data.
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17
Q

Advantages of Case-Control Design

A
  • Quick and cheap
  • Only feasible method for very rare disorders or those with long lag between exposure and outcome.
  • Fewer subjects needed than cross-sectional.
18
Q

Disadvantages of Case-Control Design

A
  • Reliance on recall or records to determine exposure status.
  • Confounders
  • Selection of control groups is difficult
  • Potential bias: recall, selection
  • Have to trust that everything regarding the intervention was done correctly.
19
Q

Cohort Design

A
  • Adaption of RCT, for when you cannot do random sampling.
  • Controlling confounding factors more important than random sampling.
  • The results cannot be verified 100% because of confounding factors.
  • Prospective (can also be retrospective)

Participants → Exposure to intervention → Outcome
→ No exposure to intervention

20
Q

Advantages of Cohort Design

A
  • Ethically safe
  • Subjects can be matched
  • Can establish timing and directionality of events
  • Eligibility criteria and outcome assessments can be standardized.
  • Administratively easier and cheaper than RCT.
21
Q

Disadvantages of Cohort Design

A
  • Controls difficult to identify
  • Exposure may be linked to a hidden confounder
  • Blinding can be difficult
  • No Randomization
  • For rare diseases, large sample size or long follow-up necessary.
22
Q

Cross-Sectional Design

A
  • One time measurement
  • No groups comparison
  • No intervention
  • Used to understand a phenomenon
  • Which factors influence particular outcome
  • Exploratory
  • No causality

Participants → Measurement of outcomes and other factors at the same time

23
Q

Advantages of Cross-Sectional Design

A
  • Cheap and simple

- Ethically safe

24
Q

Disadvantages of Cross-Sectional Design

A
  • Establishes association at most, not causality
  • Susceptible to Recall bias
  • Confounders may be unequally distributed
  • Group size may be unequal
25
Q

Before-After Design

A
  • Prospective
  • Assess and compare outcomes before and after intervention
  • No control group, not comparing groups
  • More than 5 participants
  • Bigger, more complicated outcome

Participants → Assessment → Intervention → Outcome

26
Q

Single Case Design

A
  • Same as Before-After Design, but less participants (max 5).
  • Simple outcome
  • Can have more than one intervention
  • Prospective
  • Participants studied during multiple phases

Individual client → baseline evaluation → intervention → evaluation → intervention

27
Q

Randomized Control Trial

A
  • Experimental study
  • Gold standard of research
  • Random allocation of participants in groups (increased internal validity).
  • 1 Experimental group (exposed to intervention) vs 1 control group (not exposed to intervention)
  • Tests effectiveness of intervention (causality)
  • Highly controlled

Participants → stratification → randomization → experimental group OR control group → outcome

28
Q

Advantages of Randomized Control Trial

A
  • Unbiased distribution of confounders
  • Blinding more likely
  • Randomization facilitates statistical analysis
29
Q

Disadvantages of RCT

A
  • Expensive (time and money)
  • Volunteer bias
  • Ethically problematic at times (Participants that are dying that do a clinical trial might receive a placebo when actual intervention might help.
30
Q

Randomized control trial vs Single Case Design

A

Major differences:
- Means by which the experimental control is achieved
- Number of participants
Both are scientifically credible when properly applied
RCT: Evaluate treatment effects by comparing two groups
SCD: Does this treatment work on this particular patient?

31
Q

Independent Variable

A

Intervention

32
Q

Dependent Variable

A

Variable that is being observed.

- Should only vary in response to the independent variable. (Has to be able to be modified by the independent variable).

33
Q

Extraneous Variable

A

Same as confounding factors.

Need to control → isolate effect of the independent variable on the dependent variable.

34
Q

Essential Elements to Experimental Design

A

(Randomized Control Trial)

  • Random assignment
  • Researcher-controlled manipulation of independent variable (No confounding factors)
  • Researcher control of experimental setting, including control group
  • Control of variance (sampling criteria, variables)
35
Q

Validity of the Trial

A

An actual score that is measured by these points:

  • Comparability of groups at the beginning
  • Large numbers (power calculation essential)
  • Blinding of raters/assessors and statisticians
  • No confounding factors
  • Reliability of the measurements
36
Q

Potential Causes of Bias in Quantitative Research

A
  • Researchers
  • setting
  • sample
  • How groups were formed
  • Measurement tools (Does it have good validity for the age group)
  • Data collection process
  • Data and duration of study
  • Statistical tests and analysis interpretation
37
Q

Why is rigor important?

A
  • Validity of the study depends on it.

- Striving for excellence in research and adherence to detail.

38
Q

How to uphold rigor in research?

A
  • Precise measurement tools, a representative sample, and a tightly controlled study design.
  • Logical reasoning is essential.
  • Precision, accuracy, detail and order required.
39
Q

Internal Validity

A
  • Level to which the independent variable caused the outcome of the study.
  • Are you actually measuring what was intended to measure?
  • Avoiding confounding factors.
40
Q

External Validity

A

Generalize results.

Can the outcome be generalized to the whole population.

41
Q

Reliability

A

The accuracy and repeatability of the measured outcome (same results each time it’s done).

Reliable, not valid: dots in one place, not in the middle.
Valid, not reliable: dots spread around evenly.
Neither valid nor reliable: dots spread around half.
Both reliable and valid: dots in one place, in the middle.

42
Q

Reliability vs Validity

A

Reliability: Consistency of a measure.
Validity: Accuracy of a measure.

BPT02 Research and Evidence in Physiotherapy (10 decks)

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