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1.

Distinguish between qualitative

and quantitative data.

Quantitative=data

collected through numbers, cause & effect, generalization from sample to

population, objectivity, nomothetic approach. (experiments & correlations)

Qualitative=

data collected through interaction, data is usually text & descriptive,

open for interpretation, subjectivity, idiographic approach. (case studies,

interviews & observations)

Idiographic

(qualitative)=1 specific person/group/event e.t.c, explore uniqueness,

experience.

Nomothetic

(quantitative)= want to find general laws about human behaviour, predictionsàsamplingàmethods.

Inductive=

go in & see what you find. Explore/observeàtheory.

Deductive=

theoryàexperiment

to test hypothesis.

Receptivity=

to understand meaning from a specific group of people we need to look

through the eyes of the people involved.

2.

Explain strengths and limitations

of a qualitative approach to research.

-time consuming, a lot of data.

-difficult to analyze, no strategy for analysis

-interpretation of data could be subjective.

-“participant expectation” and “research bias” are problems.

+rich data, in-depth descriptions

+complex & sensitive issues e.g. violent relationships

+explains phenomena

+new ideas/theories

+high ecological validity (in natural environment)

3.

To what extent can findings be generalized

from qualitative studies?

Generalization=

generalize findings from a study means that the results are relevant outside

the context of the study itself

1.

representational= findings can be applied to other populations,

populations which are similar or linked in some way.

2.

inferential/transferability= settings outside the study, if the setting

is well described.

3.

theoretical= theoretical concepts from the study can be used to make new

ones, if other studies support.

4.

Discuss ethical considerations

in qualitative research.

Special ethics in qualitative research because it’s usually, long-term,

close personal contact, objectivity, covert, overt observations…

Informed consent: participants need to sign consent to participate in

research.

Debriefing: at the end all true aims should be revealed. Any deception

should be revealed and justified and participants should leave without stress.

Confidentiality/anonymity: all info should be confidential and the

person involved should not be able to be identified e.g. in case studies.

Withdrawal: in beginning of research participants need to be informed

that they have the right to leave at any time and can have their data removed

at any time.

Protection of participants: participants should leave in the same mental

and physical state as they entered.

5.

Discuss sampling techniques

appropriate to qualitative research, (e.g. purposive, snowball and

convenience/opportunity sampling).

Purposive:

when you want particular characteristics, topic or participants. E.g age,

gender, attitudes, social roles. Or experiences, domestic violence, being

homeless, having cancer…

+participants represent the topic

+easy to select sample

-sampling could be biased

-difficult to generalize from small sample

Snowball:

ask participants in the study if they know others who want to participate.

+cost-efficient & easy to collect participants

+useful in sensitive research where participants can’t easily be found.

-likely to be biased because participants know each other they may have same

attitudes/experiences.

-ethics, confidentiality and anonymity hard since participants know each other.

Convenience/opportunity:

a particular group who happen to be available (e.g. first 10 obese people to

walk by).

+easy & cost-efficient to find participants.

+quick to collect data and do research.

-likely to be biased

-low credibility

6.

Explain effects of participant

expectations and researcher bias in qualitative research.

Participant

expectations: feel they have to behave in a specific way to please the

researcher. Not natural behaviour. Results not valid or true representation.

Researcher bias: not paying attention, researchers own beliefs determining the

process and affecting the results.

Can be avoided by: (reflexivity=researcher reflects on their own beliefs

1. Personal: researchers values,

belief, experiences, interests and political stands.

2. Epistemological: how is knowledge

generated, method- interview is more bias than questionnaire etc, research

question is too limited). (reflect upon method chosen and questions asked and

how data is analyzed)

7.

Explain the importance of credibility

in qualitative research.

Credibility=(internal

validity),trustworthiness of research when the findings of the research reflect

the meaning as described by participants. Triangulation and researcher

reflexivity (=researcher explains how individual bias could affect research

process and how it is prevented) is used to increase trustworthiness.

8.

Explain the effect of triangulation

on the credibility/trustworthiness of qualitative research.

Triangulation=use

of 2 or more different methods, data, researchers and/or theories to increase

trustworthiness.

-

Method:

use 2 or more methods e.g. observation, interview, case study, questionnaire,

survey.

-

Data:

conducting research at different times, locations, groups.

-

Researcher:

several researchers compare conclusions and review data and interpretation.

Inter-rater reliability 0-1 (0,7=high)

-

Theory:

using different theories/perspectives to come to a conclusion

+bias is

reduced

+credibility increases

+counteract researcher bias

+more complete interpretation of results

+new ideas of looking at data

-could be confusing with many different methods, theories, researchers or data.

9.

Explain reflexivity in

qualitative research.

reflexivity=researcher

reflects on their own beliefs

1. Personal: researchers values,

belief, experiences, interests and political stands.

2. Epistemological: how is knowledge

generated, method- interview is more bias than questionnaire etc, research

question is too limited). (reflect upon method chosen and questions asked and

how data is analyzed)

10.

Evaluate semi-structured,

focus group and narrative interviews.

Interview:

self-report method, participant is asked questions. Provides in-depth info

about an issue or question.

-

Structured:

fixed questions, preset order, do not deviate from script. Closed ended

questions.

+easy, objective and more generalizable

-validity

-

Unstructured:

free-flow, conversation, own opinions/ideas, list of general topics not

questions. Open-ended questions.

+pursue interesting points

-replication and time cost

-

Semi-structured:

structure + unstructured. Both open and closed-ended questions. Themes and

questions.

+flexibility of both un/structured

-time consuming analysis

Effects:

Gender: positive to opposite sex e.g. men said fewer sexual partners ti females

than male interviewers.

Ethnicity: different ethnic groups=more formal. Same ethnic group=positive,

relaxed.

Formal roles: not equal=try to impress, change answers according to.

Personality: chemistry affect outcome of interviews.

Evaluative cues from interviewer: critical or approval reactions.

Focus

groups: 6-10 people, discussion of a common characteristic. Often purposive

sampling. Homogenous: participants share features. Heterogeneous: participants

are different.

+quick/convenient data

+natural setting, high ecological validity

+answers: what, how and why

-not appropriate for sensitive topics

-conformity

Narrative

interviews: are individual interpretations of the world. Is a mix of facts and

interpretations of experiences. Often constructed like a real story with intro,

middle and end. Interviewer asks stimulating questions. Interviewer doesn’t

interrupt.

+in-depth understanding of meaning in peoples lives

+can be used with all people

+useful in exploring socially sensitive topics: gives insight in how people

thing and why they experience what they do.

-time consuming to analyze

-could go in all directions, data not useful

-ethics

11.

Discuss considerations involved before,

during and after an interview, (e.g. sampling method, data recording,

traditional versus postmodern transcription, debriefing).

Data recording:

1. Visual: moving pictures, +accuracy, -participant reaction and behaviour due

to researcher.

2. Audio: +accuracy, -does not record important gestures/body language.

3. Written: ratings made on the spot, +less intimidating, -data could be

missed.

Sampling

method for data:

1. Event: specific behaviors recorded every time they occur, +limits a lot of

other behaviour so its easier to spot and not miss, -difficult to observe that

behaviour in big areas (easily missed).

2. Time: recorded behaviour from e.g. 5-6 pm or every 5th minute.

+reduces time, -behaviors easily missed.

3. Point: record behaviour of one individual and observer that person all the

time. +accuracy of behaviour recorded, -easily to miss others behaviour which

influences that person.

Before:

pilot study.

Data collection-choice of interview based on aim, time and resources.

interviewer-choosing the right one, gender, ethnicity, age, language, clothing/appearance.

sampling-purposive, snowball, convenience.

data recording-audio, video, notes

transcriptions of data- word by word text of interview. Some include pauses,

laughter and interruptions.

ethics- research socially sensitive, emotional stress, informed consent and

briefing.

reflexivity- research reflects on own bias.

setting and well prepared material.

During:

establish rapport-trust and open relationship, makes participants talk freely.

data recording-make sure equipment works and is on.

active and neutral listening-ask q. clearly, don’t interrupt, be neutral.

body language.

After:

debriefing-participants should be informed about results and possibility to

withdraw.

confidentiality and anonymity – participants cannot be identified, no names.

credibility check – ask for others to review interpretations, triangulation.

12.

Explain how researchers use inductive

content analysis (thematic analysis) on interview transcripts.

Inductive

content analysis = method for analyzing people/ organizations.

1. Read and reread transcripts: notes

with rich data (=detailed and thick descriptions of, phenomena, context,

intentions, process and setting).

2. Identify emerging themes (coding and

connecting themes).

3. Structure themes: higher and lower

order + examples/quotations. (graphical representations).

4. Summary of themes (=produce an

account) + quotations. Data saturation: no new data can be found. (nominal

data, categories, chi-square, inferential statistics).

Inductive

reasoning(qualitative): observationàgeneralizationàtheory.

Deductive reasoning(could be quantitative): theoryàpredictionsàexperiment.

13.

Evaluate participant,

non-participant, naturalistic, overt and covert observations.

Observation:

observing natural behaviour. No cause and effect.

Observer

participation

Participant:

observer participates in the study.

-difficult to gather data

-replication not possible

-researcher could affect participants

-ethics

+insight in special groups

+high ecological validity-natural behaviour and setting.

Non-participant:

undercover researcher, observe from a distance.

-ethics

-deception

-if you know you are being observedàno natural behaviour

+/-research bias

Setting

Naturalistic: parks,

stores, playgrounds.

+high ecological validity

+public places (ethics)

+natural behaviour

-confounding variables

-no cause and effect

Controlled: lab.

+might avoid confounding variables

+replication possible

-no natural behaviour

Disclosure

Covert: undercover.

+high ecological validity

+unique data

-ethics

-dangerous cults/gangs

Overt: participants

are aware they are being watched.

+ethics

-change behaviour

Structure

Structured:

deductive.

+easy to gather data

-easy to miss data

Unstructured: inductive.

-a lot of data

14.

Discuss considerations involved

in setting up and carrying out an observation (e.g. audience effect,

Hawthorne effect, disclosure).

Method

considerations: decide overt/covert, participant/non-participant.

Ethics: informed consent, debriefing, anonymity.

Sampling: purposive, snowball, convenience & point, event, time.

Data recording: video, audio, written.

Observer characteristic: gender, age, ethnicity e.t.c should be similar to

those being observed.

Objectivity of researcher: be several or just one, better with many because if

one observer is observing for a long time there is higher chance they will be

subjective. Credibility and reflexivity.

Analysis of data: conductive content analysis and thematic analysis.

15.

Discuss how researchers analyze

data obtained in observational research.

Inductive

content analysis = method for analyzing people/ organizations.

1. Read and reread transcripts: notes

with rich data (=detailed and thick descriptions of, phenomena, context,

intentions, process and setting).

2. Identify emerging themes (coding and

connecting themes).

3. Structure themes: higher and lower

order + examples/quotations. (graphical representations).

4. Summary of themes (=produce an

account) + quotations. Data saturation: no new data can be found. (nominal

data, categories, chi-square, inferential statistics).

16.

Evaluate the use of case

studies in research.

Case study:

in-depth investigation of human experience in the participants’ natural

environment=high ecological validity. Participant can be a person, group,

location, organization or event. Aim is to describe, understand and explain a

phenomenon. Case studies are useful when investigating sensitive topics.

Characteristics

of case studies: process oriented=occurs over time opposite to experiment

“snapshot”.

Nomothetic: general

laws, many participants, quantitative.

vs

Idiographic:

specific,1 participant, qualitative.

Intrinsic:

interesting in their own way, only represent themselves.

vs

Extrinsic: represent

a general phenomena.

Descriptive: purpose

it to generate a detailed description of phenomena. Description will generate

new knowledge, no earlier theory. Inductive.

vs

Explanatory: and is

to describe and find explanation. Includes analysis based on existing theory and

generating new one. Deductive or inductive if no existing theory is used.

Strengths:

+new research.

+contradicts established theories.

+gives insight into phenomena.

+investigation

possible for rare situations that cannot be engineered e.g it is not ethical

to take out parts of the brain just to see what happens.

vs

Limitations:

-replication not possible.

-researcher bias (since its process oriented researchers could get subjective

in recording and analyzing.

-relies on memory.

-social desirability: participants change behaviour to appear more socially

acceptable.

Ethics:

Confidentiality: could be hard to keep the participant unidentifiable.

Informed consent: can a person who is e.g deprived/sick give informed consent?

Is it ok for others to decide for them?

Invasion of privacy: since they will be followed for a long period of time they

might feel invaded in their privacy.

17.

Explain how a case study could be

used to investigate a problem in an organization or group (e.g. football team,

a school, family).

18.

Discuss the extent to which

findings can be generalized from a single case study.

Some

believe this is impossible but it is possible if there is:

Generalization=

generalize findings from a study means that the results are relevant outside the

context of the study itself

1.

representational= findings can be applied to other populations,

populations which are similar or linked in some way.

2.

inferential/transferability= settings outside the study, if the setting

is well described.

3. theoretical=

theoretical concepts from the study can be used to make new ones, if

other studies support.

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