Methods in AS Psychology

Questionnaires:

• Pos: cheaper, easier, gain qualitative data, large amounts collected
  
• Neg: qualitative hard to analyse, potentially v subjective, researcher effects

Unstructured interviews: seen as guided conversation

• Pos: flexible, generate qualitative data using open questions, more validity
• Neg: time-consuming, expensive for skilled interviewers to be collected

Semi-structured interviews: set questions that divert based on what the PP says

• Pos: flexible, generates qualitative and quantitative data
• Neg: not replicable, interviewer effects

Structured interviews: questions already set beforehand

• Pos: easily replicated, quick to conduct, large sample used
• Neg: not flexible therefore lack detail as only closed questions asked

Random: random number generated to find PPs with no bias

• Pros: no bias, representative
• Cons: a lot of time, effort and money spent

Stratified: sample based on proportions of target populations

• Pros: highly representative of target population
• Cons: difficult to do and very time consuming

Opportunity: PPs taken from convenience

• Pros: quick and easy way of choosing PPs
• Cons: likely biased and not representative

Volunteer: use an incentive to get people to come

• Pros: very quick, have willing PPs
• Cons: very biased, not representative could be costly depending on incentive
  

Quantitative data: numerical data

• Pros: easy to analyse, relationship between IV and DV easy to see, objective, easily repeated
• Cons: context ignored, usually larger sample needed, ignores opinions

Qualitative data: written data

• Pros: detailed, rich data, takes into account context and opinions
  
• Cons: often subjective and biased to interpretation, time-consuming, hard to analyse

Converts qualitative data into quantitative data.

Once data is transcribed (where necessary) data is reviewed repeatedly so that the researcher can identify trends in the meaning conveyed by language.

The themes identified are re-analysed so that they become more refined and relevant and given short hand codes.  The researcher can then annotate the transcript with the codes that have been identified.

The themes identified can be used to support or challenge existing theories, with specific examples of data or quotes being used as supporting evidence.

Pros: analyse a variety of forms of data, e.g. qualitative

Cons: subjective, not repeatable, very biased

Respect:

• Informed consent: aims of experiment digressed.
• Confidentiality: names of PP kept from public.

Responsibility:

• Right to withdraw: PP can leave the experiment at any time.
• Protection from harm: no physical or psychological harm to PP.

Competence:

• Maximising benefit/minisimg harm: do the benefits outweigh the costs?
• Practise within limits of ability: having the correct credentials to carry out the test.

Integrity:

• Avoid deception: give as much of the truth as possible about the experiment.
• Debrief: does after care need to be provided after the completion of the test?

Lab Experiments:

Pros: easy to replicate using standardised procedures, allow for precise control of extraneous and independent variables, allow for cause and effect relationships to be established, high internal validity.

Cons: artificial setting may produce unnatural behaviour, low ecological validity, little mundane realism, hard to generalise findings to real life, demand characteristics and experimenter effects may bias results and become confounding variables.

Field Experiments:

Pros: behaviour more likely to reflect real life, high ecological validity, less likely for demand characteristics affecting results as PP may not know they're being studied (covert), high mundane realism.

Cons: less control over extraneous variables that might bias results, not replicable, no internal validity.

The IV: the varibale that is changed for the effect to be tested.

The DV: the variable that is measured.

Experimental hypothesis: states the IV will have an effect on the DV.

Null hypothesis: states the IV will have no effect on the DV.

Experimentor effects: bias arising from charactersitcs of the experimentor (halo effect).

Demand characteristics: where PPs form an interpretation of the experiments purpose and change behaviour accordingly to fit what they think the aim is.

Counterbalancing: way to cancel out fallouts of order and practise effects in repeated measures.

Randomisation: using a random number generator to choose PPs.

Order effects: results from when PPs do the same condition again so results may be skewed as they know what to expect (during repeated measures).

Experimental and research designs:

Repeated measures: same PP in every condition.

• Pros: can make direct comparisons, cheaper with fewer PPs needed.
• Cons: practise effects, order effects, needs counterbalancing to cancel these out.

Independent groups: seperate groups doing different conditions.

• Pros: avoids order and fatigue effects as well as demand characteristics.
• Cons: individual differences potentially becoming confoudning variables.

Matched pairs: matched groups for different conditions.

• Pros: gets rid of participant variables.
• Cons: demand characteristics.

Operalisation of variables:

• Extraneous variables: variables the experimentor has no control over that have the capacity to become confoudning variables.
• Confounding variables: a variable that affects the DV over and above the IV, therefore completly skewing the aim of the experiment.

Objectivity: results taken without the experimentors bias.

Reliability: can the experiment be repeated again?

Validity: did the experiment complete and gain the results it said it would?

Internal validity: was it controlled (lab experiments)?

External (ecological) validity: was it natural and representatve of real life (field experiments)?

Predictive validity: were the results collected predictable e.g. SZ has high predictive validity as you can predict what will happen to someone diagnosed with schizpphrenia (SZ).

Positive: can lead to further research, identifies a relationship between variables, allows the researcher to investigate naturally occuring variables.

Negative: only identifies a correlation, no cause and effect, does not allow for the ability to go beyond the data given.

Cause and effect issues: as mentioned in the cons, correlational research does not allow for a cause and effect relationship to be established. E.g. it may find a strong relationship between ice cream sales and shark attacks, but does not mean shark attacks cause high ice cream sales  (it most likely to do with the season being summer).

Co-variables: instead of describing the experiment via IV and DV, because both variables are changed and measured in correlaional research, the variables changed and measured are called co-variables.

Participant: watchiong the events or situation or activities from inside by taking part in the group to be observed.

• Pros: oberservation of natural behaviour, studying real character so gives better understanding.
• Cons: lacks objectivity, biased, limited range of experiences, no control, time-consuming.

Non-paticipant: watching participants from a far, passively.

• Pros: objective and neutral, easy to record data.
• Cons: demand characteristics, change behaviour as they know they're being studied, time consuming.

Naturalistc: where the researcher observes behaviour that occurs naturally. 

• Pros: high ecological validity, allows study of wide range of behaviour.
• Cons: demand characterisitcs, no control over variables, not reliable.

• Legal requirements: research must not break the law regarding endangered and protected species.
• Replacement: where possible, live animals should be replaced with research alternative, like simulations. Animals should only be used as a last resort.
• Choice of species: species bred in captivity are ethically preferable to taken from the wild, and should not be highly sentient (feeling) animals.
• Reduction: number of animals used should be minimised as much as possible.
• Animal care: when not being studied, animals must be housed, fed and watered in a suitable way as well as being given space and companionship appropriate to the species.
• Disposal: when research is over, animals should be disposed of humanely, idealy kept alive for breeding or as pets.
• Procedures: animals must be treated humanely during research which involved three areas:
• 1. Caging: social species need companionship and cages large enough for the animal.
• 2. Deprivation: some food deprivation is allowable (may be normal for animals) but distress should be minimised.
• 2. Pain: anaesthtics should be used, animals given medical treatment after research. Humane killing is suffering cannot be reduced.

Controls: variables that need to be kept constant in order to obtain valid results (e.g. sex, age of PPs).

Hypothesis: proposed explanation made on the basis of limited evidence as a starting point for further investigation.

Independent/dependent variables: IV changed to see an effect in the DV.

Measurability: is the experiment measurable? Can it be meaured and comapred?

Paradigm: is the experiment significant enough to create a change in the scientific thinking of the topic?

Falsifiability: good science means the ability to prove something wrong, such as with Carlsson who proved himself and the dopamine hypothesis wrong.

Objectivity: is the study unbiased and without opinions influencing it?

Repeatability: repeatablility proves reliability and leads to good science.

Empricalism: was empircal evidence collected? Described as being based on, concerned with, or verifiable by observation or experience rather than theory or pure logic.

Reductionism: is the study reductionist? Reductionism is described as analysing and describing a complex phenomenon in terms of its simple or fundamental constituents.

Validity: is the study valid? Is it logically or factually sound? Has it researched what it set out to follow and gained results accordingly? Internal vs ecological validity.

Open questions:

• Pros: unlimited range of answers, reveals thoughts and emotions, responses can be expanded upon and clarified.
• Cons: more time, answers may be hard to compare and analyse, limited control over the length of response, analysis difficulty, costly and time-consuming.

Closed questions:

• Pros: easy and quick to answer, consistent response, likert scale can give emotions, less costly, easier to analyse.
• Cons: may not have exact answer respondent wanted to give, can lead to misleading questions.

Alternate hypothesis: opposite to the null, expects a result and effect from the investigation.

Researcher effects: the appearance or behaviour of the interviewer may influence the answers of the respondent, which is a problem as it can bias the results of the study and make them invalid.

Structured:

Overt: the observed group is aware of the presence of the researcher and that their behaviour is being.

• Pros: informed consent obtained, pracitcal, valid.
• Cons: demand characteristics, biased, lacks objectivity.

Covert: means the participants are unare of the presence of the researcher.

• Pros: little demand characteristics, allows study of behaviours that may not be normally studied.
• Cons: difficult to record data, no consent, often dangerous to researchers.

The construction of theory through methodic gathering and analysis of data.

A study using grounded theory is likely to begin with a question, or even just with the collection of qualitative data.

As researchers review the data collected, repeated ideas, concepts or elements become apparent, and are tagged with codes, which have been extracted from the data.

As more data is collected, and re-reviewed, codes can be grouped into concepts, and then into categories. These categories may become the basis for new theory.

Pros: avoids making assumptions, hollistic

Cons: time consuming, can lead to bias