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FE > Research Consolidation slides > Flashcards

Research Consolidation slides Flashcards

1
Q

Aim

A

Broad, general, long-term

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2
Q

Objectives

A

Specific, focused, short-term, measurable

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3
Q

Research questions

A

Rephrase objectives to focus on variables

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4
Q

Qualitative

A

Descriptive

Phenomenological

Ethnographical

Grounded theory

Participatory action research
(PAR)

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5
Q

Quantitative

A

Experimental (hypothesis testing)
* Randomised controlled trials
* Quasi-experimental trials

Non-experimental (descriptive,
correlational)
* Cross-sectional
* Cohort
* Case-control

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6
Q

Qualitative vs Quantitative

Focus

A

Qualitative: Quality (features)

Quantitative: Quantity (numbers)

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7
Q

Qualitative vs Quantitative

Reasoning

A

Qualitative: Usually inductive

Quantitative: Usually deductive

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8
Q

Qualitative vs Quantitative

Goal

A

Qualitative: Understand

Quantitative: Predict, test hypotheses

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9
Q

Qualitative vs Quantitative

Sample size

A

Qualitative: Small, purposive

Quantitative: Large, general

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10
Q

Qualitative vs Quantitative

Data collection

A

Qualitative: Interviews, observations

Quantitative: Questionnaires, experiments

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11
Q

Qualitative vs Quantitative

Data analysis

A

Qualitative: Researchers’ interpretation

Quantitative: Statistical methods

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12
Q

Qualitative vs Quantitative

Results/findings

A

Qualitative: Usually verbatim quotes

Quantitative: Usually precise numbers

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13
Q

Quantitative research question

A

PICO

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14
Q

Literature review vs Systematic review

Purpose

A

LR: Provide context/background
information, not meant to answer
research question.

SR: Identifies, selects, synthesises, and appraises studies that meet prespecified inclusion criteria to answer a research question.

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15
Q

Literature review vs Systematic review

Protocol

A

LR: No protocol

SR: A-priori protocol is developed and published
(PROSPERO)

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16
Q

Literature review vs Systematic review

Search

A

LR: Nil, normally includes well-known
articles

SR: Well-defined, comprehensive search strategy

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17
Q

Literature review vs Systematic review

Methodological appraisal

A

LR: NIL

SR: Internal validity is judged by various tools eg
ROB

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18
Q

Literature review vs Systematic review

Synthesis

A

LR: Usually narrative

SR: Narrative, meta-analysis, meta-synthesis

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19
Q

Literature review vs Systematic review

Findings

A

LR: Not reproducible

SR: Reproducible

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20
Q

Observational studies

A

Cohort studies
Cross-sectional studies
Case-control studies
Case reports

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21
Q

Experimental studies (causal r/s)

A

Randomized
controlled trials

Quasi-experimental
studies

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22
Q

Synthesized evidence

A

Umbrella
review

Meta-
analyses

Systematic
reviews

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23
Q

Steps to perform a systematic review

A

Find a good topic

Formulate clear and well-defined research question

Develop systematic review protocol

Conduct systematic search strategy

TiAb and full-text screening using eligibility criteria

Methodological appraisal

Data extraction & organisation

Data analysis

Evidence quality appraisal

Write: integrate, synthesise, summarise

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24
Q

Qualitative research study
design definition

A

A type of research method that collects non- numerical data for in-depth understanding of phenomenon in their natural setting.

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25
Q

Qualitative research study
design Purpose

A

Explore a phenomenon (e.g. perception, meaning, experience) that is vague

  • Groundwork for quantitative study when there is insufficient insights
  • E.g. why people behaviour a certain way?
  • Explain a quantitative result
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26
Q

Formulating research question: Types of inquiry

A

Ontological (understand
participants’ realities)

Epistemological (understand
knowledge of phenomenon)

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27
Q

Qualitative design: Descriptive

A

Describe and interpret perceptions/meanings.

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28
Q

Qualitative design: Grounded theory

A

Collect rich data on a topic to inductively develop
theories.

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29
Q

Qualitative design: Phenomenological

A

Understand a phenomenon by describing and interpreting participants’ lived experiences.

30
Q

Qualitative design: Ethnography

A

Researchers immerse themselves in target groups to understand culture.

31
Q

Qualitative design: Participatory action

A

Both researchers and participants conduct research together to drive social change.

32
Q

Data collection methods

A

In-depth interviews
*Individual vs focus group
- Semi-structured vs Unstructured

  • Observations + field notes
  • Use of 5 senses
  • Surveys with open-ended questions
  • Secondary data
  • Existing texts, images, audio-recordings, video-recordings
33
Q

Aim of In-depth interview techniques

A

Aim: Evoke thick and rich responses to obtain in-depth
information

34
Q

In-depth interview techniques

A

Build rapport + participant information
* Anonymity & confidentiality
* Permission to audio-tape record
* Develop an interview guide with open-ended questions
* More Why? How?

Talk less, listen more → use prompts, silence

DO NOT use leading questions

35
Q

Sampling methods

A
  1. Convenience
  2. Purposive
  3. snowball
  4. Theoretical
36
Q

Convenience sampling

A

Volunteers through advertisements

37
Q

Purposive sampling

A

Non-probability sampling based on criteria set
beforehand

38
Q

Snowball sampling

A

Recruited participants to recommend others

39
Q

Theoretical
(grounded-theory) sampling

A

Decide on next target participant as collection continues

40
Q

Sample size normally based on

A

data saturation: when no more
new information emerges

41
Q

Descriptive (most basic) sample size

A

> 12 (Clark & Braun, 2013)

42
Q

Grounded theory

A

20-30

43
Q

Phenomenological

A

~10

44
Q

Ethnography

A

25-50

45
Q

Focus group

A

≥3 groups, each 7-10 participants

46
Q

Basic data analysis method slide

A
47
Q

General data analysis steps

A
  1. Prepare: Materials for data analysis

Transcript (include context of data collection) e.g. situation (time and date), environment (private room or in the open space), facial expression (e.g. facial grimace when talking about sensitive issues)

  1. Immerse/familiarise: Iterative reading
  2. Code: Label patterns/meaning units
  3. Allow themes & subthemes to emerge
48
Q

6-steps thematic analysis

A
  1. Familiarize with data
  2. Generating initial
    codes
  3. Searching for themes
  4. Reviewing themes
  5. Defining and naming
    themes
  6. Producing the report
49
Q
  1. Familiarize with data
A

Transcribing data, reading and rereading the data, noting down initial ideas

50
Q
  1. Generating initial
    codes
A

Coding interesting features of the data in a systematic fashion across the entire data set, collating
data relevant to each code

51
Q
  1. Searching for themes
A

Collating codes into potential themes, gathering all data relevant to each potential theme

52
Q
  1. Reviewing themes
A

Checking if the themes work in relation to the coded extracts (Level 1) and the entire data set
(Level 2), generating a thematic ‘map’ of the analysis

53
Q
  1. Defining and naming
    themes
A

Ongoing analysis to refine the specifics of each theme, and the overall story the analysis tells,
generating clear definitions and names for each theme

54
Q
  1. Producing the report
A

Selection of vivid, compelling extract examples, final analysis of selected extracts, relating back of
the analysis to the research question and literature, producing a scholarly report of the analysis

55
Q

Computer-assisted data analysis

A

E.g. Nvivo, Atlas.ti,
MaxQDA

56
Q

Trustworthiness

A

A set of strategies used to establish trust or confidence (Lincoln, 1989; Morse, 2015)

57
Q
A
58
Q

Trustworthiness table

A
58
Q

Rigor in Qualitative study

A
59
Q

Quantitative research study
design, Key dimensions to consider:

A

Experimental vs non-experimental

  • (RCT, quasi-experimental to identify causal r/s) vs (e.g. descriptive,
    correlational, comparative)

-Cross-sectional vs longitudinal
Snapshot vs change over time

  • Retrospective vs prospective
60
Q

True Experimental (RCT)

A

PreTest-posttest control group

Posttest-only control group

61
Q

Quasi-Exp

A

Non-equivalent Control group pretest-posttest

One group pretest-posttest

Time series design

62
Q

Non-Exp

A

Descriptive

Descriptive Correlation

Comparative design

63
Q

True experimental research (RCT)

A

Gold standard for testing causal relationships

  • Also called pretest-posttest design with randomization
  • Non-equivalent pretest-posttest is called quasi-experimental
    trial

Characteristics:
* Intervention: manipulation of IV
* Control group
* Random assignment (group assignment by equal chance to eliminate confounding factors, allowing us to ascertain that DV is indeed caused by IV)

64
Q

Randomization

A

Minimise selection bias through allocation concealment

Trials with unclear randomization shown to overestimate
interventional effects by 40%(Schulz & Grimes, 2002)

Best to have different people performing different steps of
randomization to prevent bias during

  • Participant recruitment
  • Participant allocation
  • Intervention administration
  • Outcome assessment
65
Q

Quasi Experimental research Strength

A

Practical

it is difficult or impossible to deliver an innovative treatment randomly to some people but not to others

People are not always willing to be randomised in clinical trials

66
Q

Quasi Experimental research Weakness

A

Weaken the cause and effect relationship

Absence of randomisation
-> implied change in DV= effect of IV + initial group difference in internal factor

Absence of control group
-> implied change in DV = effect of IV + effect of unknown external factor

67
Q

One group pretest-posttest design

A
68
Q

Non-experimental research

A

Descriptive
* E.g. Examine the quality of life among patients with CHD

Correlational
* Examine relationship between variables
* E.g. Examine the relationship between medication adherence and
quality of life in patients with CHD

Comparative
* To compare variables between samples
* E.g. A comparative study on health-related quality of life between
patients with MI and DM

69
Q

Cross sectional vs longitudinal

A
70
Q

Retrospective vs prospective

A

FE (7 decks)

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