Types of research - experiments, observations, case studies, correlations etc.

Big Research Methods post coming up. This shall cover the two types of research (experimental and non-experimental), as well as the purpose of pilot studies.

Black: Description
Red: Negative evaluation of a design or technique.
Blue: Positive evaluation of a design or technique.
Purple: My notes/hints/tips.

IV: Independent variable, the variable that changes.
DV: Dependent variable, the variable that is measured.
EV: Extraneous variables, factors that could affect the DV but that aren't being studied.

Experimental Methods

A laboratory experiment takes under controlled conditions, with participants aware that they are being studied. The independent variable is manipulated to look for an effect on the dependent variable, and extraneous variables are controlled.

The high levels of extraneous variable control increase the internal validity of the results, the degree to which the study measures that which it claims to - as we can be more  confident that factors other than the IV aren't influencing our results.

This helps to determine cause and effect and to establish a potential causal relationship between the IV and the DV.

The standardisation of procedure, instructions and apparatus gives this experimental method more replicability, allowing us to test for reliability and consistency by carrying out repeats at other times or on different samples from the target population.

Demand characteristics are more likely to occur in a laboratory experiment - being fully aware that they are in an experiment and an artificially designed setting, participants could alter their behaviour to either help or confound the research. This unnatural behaviour reduces the internal validity of the results.

The use of an artificial, controlled, and often unrealistic setting reduces the ecological validity of the results - the extent to which a study's results can be applied to a real life situation.

A field experiment takes place in a natural environment, with the participant usually unaware that they are taking part. The experimenter still manipulates the IV to look for an effect on the DV, but has less control over EVs than in a laboratory experiment.

Field experiments have more ecological validity than laboratory experiments, the use of a natural setting meaning that measured behaviour is more realistic and representative of people's behaviour in their everyday environment. 

Demand characteristics are less likely to occur in a field experiment, as due to the natural setting and potentially being unaware of the IV manipulation, participants are less likely to modify their behaviour to help or hinder the research, an action which would reduce the validity of the results.

Less control over extraneous variables makes the establishment of cause and effect more difficult and reduce the internal validity of the results - without the control of a lab experiment, it is difficult to know if the observed change in the DV is a result of IV manipulation, or a result extraneous variables. This makes establishing a causal relationship hard.

In a natural experiment, a natural setting is used, extraneous variables are not controlled, and the experimenter takes advantage of a naturally occurring change in the IV, rather than directly manipulating it.

Natural experiments allow for studying the effects of the IV when directly manipulating the IV would be too difficult or unethical.

Natural experiments have the highest external validity, being set in a natural environment without deliberate experimental manipulation of the IV. As a result of this, their results most accurately reflect real-world behaviour and attitudes, having the highest ecological validity of the three types of experiment.

The lack of direct IV manipulation limits the ability of the researchers to establish cause and effect, making it difficult to determine a direct causal relationship between the independent and the dependent variables.

Natural experiments are usually impossible to replicate due to the highly specific conditions, relying on a natural variation in the IV to carry out the research. This limits the ability to test for the reliability and consistency of the results that could otherwise be achieved through replication.

Non-Experimental Methods

Correlational research involves the examining of a relationship between two covariables (variables being investigated - correlations do NOT use an IV and a DV - both variables change and are measured, and neither are directly set by the researcher.)

Rather than being a research method in and of itself, correlational research collects and analyses data from many other research methods - for example, observations, questionnaires, interviews and experiments. 

The relationship between two covariables can be a positive correlation (as one increases, so does the other), a negative correlation (as one increases, the other decreases) or neither - no correlation can potentially exist.

Correlational research allows us to study areas that would be unethical to study by manipulation of variables - e.g, the relationship between police funding and levels of violent crime.

It allows us to study based off already known information, and attempt to draw a correlation between that and newly acquired data.

Correlations do not necessarily indicate direct causation or the direction of the relationship - a correlation between two variables does not mean one causes the other, and even if it does, it does not tell us which one causes the other - the direction of causation is unknown.

We can never rule out a third variable that explains the relationship between the covariables - if causation exists, it is not always direct, but often a result of a third, "intervening" variable.

Observations as a research method involve watching behaviour to look for patterns - often using a predefined set of behavioural categories and seeing how often behaviours from those categories occur. They can be participant or non-participant, covert or overt, and controlled or naturalistic.

Controlled observations determine duration and a list of behaviours to observe, rate and categorise first, whereas naturalistic observations are more "seeing what happens" - with no set behaviour ratings or categories.

Covert observations are carried out without the knowledge or consent of those being studied, in a situation where they would not reasonably expect to be observed. There are ethical issues with the lack of consent here, but "participants" will behave more naturally as they are unaware that they are being studied - meaning results have higher ecological validity.

In an overt observation, the participants have consented to being observed, in a situation where they would not reasonably expect to be. This is more ethically sound than a covert observation, as participants have given informed consent to be studied, but are likely to change their behaviour due to demand characteristics as they are aware of the researchers observing them, and could try to either help or hinder the research or engage in more socially desirable behaviour - reducing the validity of results.

Participant observations are where the researcher takes part in the activity being observed, becoming a member of the group. This allows them to more deeply understand behaviours and dynamics that may be a part of the group's culture and confusing to outsiders, but they may affect their own results by influencing the group that they're observing.

In non-participant observations, the researcher is observing the group without being a part of it. They may misinterpret behaviour or dynamics, being unable to fully understand them from an outsider's perspective, but will not affect their own results by influencing the behaviour of the group they're observing.

Observations are fairly subjective and unscientific - two researchers might interpret the same behaviour in completely different ways. To alleviate this, a method of testing for inter-rater reliability is used - raters observing the behaviour agree on a rating and categorisation system before carrying out their observation, so the same behaviour will be interpreted in the same way consistently between different observers.

Interviews are a verbal method of gathering data, where a participant will be asked a series of questions by a researcher and their responses will be recorded. They can be structured, unstructured or semi-structured.

Structured interviews have a set question list, which the researcher does not deviate from.

The researcher can make sure that they'll address the most important and desirable issues, while avoiding too much irrelevant information.

It is easier to compare responses between participants when using a structured interview, as all participants are asked the same questions.

However, there is no room for participants to elaborate upon and to explore any important points that arise - they are more restricted and can give less in-depth information.

The interviewee has very little control over the progression of the interview - this may make it feel more like an interrogation, and make them more reluctant to give answers.

Unstructured interviews have a topic of discussion, but no set questions - letting the conversation take a natural route.

The interviewee has more control over the direction of conversation, potentially being more willing to give information.

There is room for elaboration and for exploration of areas of interest, meaning that a more in-depth reply can be given if a topic of particular interest surfaces.

It is difficult to compare answers between participants, since not everyone will have been asked the same questions due to the natural flow of conversation.

Lots of irrelevant information can be given over the course of an unstructured interview, wasting both the participant and the researcher's time.

The researcher cannot be sure that all topics of interest will be discussed.

A semi-structured interviews has a topic of discussion and a number of key points to address, but lacks the direct questions used in a structured interview and the free flow of conversation used in an unstructured interview. It functions as a balance between the other two styles.

Interviews tend to give us rich, qualitative data that gives us in-depth insight into people's views and beliefs. 

However, this data is difficult to quantify - being difficult to statistically analyse, compare and look for trends.

Generally, interviews suffer from social desirability bias as people feel pressured to give socially acceptable answers that don't reflect their true beliefs and behaviours - this reduces the validity of the research.

Open and closed questions can be used - open questions give rich, detailed and qualitative responses that are difficult to analyse and compare, whereas closed questions give objective, shallow and quantitative data that can be numerically analysed with relative ease. A Likert scale can be used for quantifiability in a questionnaire or interview - presenting a statement, and asking the participant to indicate on a numerical scale how much they agree or disagree.

Questionnaires can use open or closed questions, and involve the participant responding to a range of questions about a particular topic of interest.

Especially through use of the internet, questionnaires can reach a huge range of people very quickly - this makes them easy and quick to analyse results and draw conclusions from a large sample size.

However, questionnaires have a poor response rate, and suffer from self-selection bias - biased towards the specific type of person with a helpful temperament that is more likely to reply to questionnaires. This makes them unrepresentative and lacking in validity, not representing a range of temperaments and personalities. Generally, only people with a strong opinion either way reply - so researchers could lack insight into the views of the middle ground.

Questionnaires measure opinion rather than behaviour - reducing validity by not accurately reflecting the way people behave, but rather the way they consider themselves to feel. They can also suffer from social desirability bias, as participants might be likely to give the answers that present them in the best light, rather than the most truthful answers.

Case studies are in-depth studies of an individual or a small group who are particularly of interest in a certain area of research, often over an extended period of time. They use a range of other research methods to gather data into the participants, including interviews, observation, questionnaires and content analysis of diaries.

They provide in-depth, qualitative and unique insight into the lives of psychologically significant individuals, studying things that otherwise be too obscure to study in the general population, or would be unethical to induce in order to study.

They are often longitudinal, allowing the researcher to study change over a long period of time - such as the progression or degeneration of a specific condition. The longitudinal nature allows a trusting relationship to build up, making the participant more willing to give sensitive information.

However, as a trust relationship builds up between the researcher and case subject, the study loses objectivity as the researcher seeks to present them in a certain light, meaning results start to lack internal validity.

Case studies' longitudinal nature gives them high levels of participant attrition - becoming unrepresentative through self-selection, biased towards the kind of participant who doesn't drop out.


Content analysis involves analysing the results of questionnaires, interviews, experimental results, speech, literature and other methods of data collection to look for meaning and to identify trends. Discourse analysis is a sub-type that involves specific focus on speech patterns and conversations. Content analysis uses quantitative research methods to analyse qualitative data and make inferences into the media, the writers, the audience, the culture and time of the content. Content is broken down into manageable categories on a variety of levels such as words, word sense, phrase, sentence and theme - then quantitatively examined.


This method allows us to quantify data that would otherwise be qualitative, and far less scientific.


Content analysis uses pre-existing information to draw conclusions, meaning that it is very open to measures of inter-rater reliability - the same source can be analysed by multiple researchers.


However, if inter-rater reliability is not used, then this a very subjective research method, as researchers could come to completely different conclusions about the same piece of content.

Pilot Studies

Pilot studies involve carrying out the proposed research on a small group within the target population before carrying it out on the main sample, for a number of reasons.

• Identifying any issues with the instructions and research - such as confusing or ambiguous tasks, and offensive or irrelevant questions.

• Checking all raters are using rating scales or content analysis techniques correctly, agreeing on what constitutes a certain behaviour - to increase inter-rater reliability.

• To check the suitability of the stimuli - tasks are not too difficult or skillful for participants to carry out, nor too boring that they lose concentration and drop out halfway through.

Reliability and Validity

Only description really here - Research Methods doesn't have the clear AO1/AO2 division that the other units have.

Validity

Validity is the extent to which research measures what it claims to measure – a test of emotional intelligence should measure emotional intelligence rather than something else, like memory.

Internal validity refers to how much the effects on the DV observed in a study are due to IV manipulation, rather than something else – whether there is a causal relationship between the IV and the DV.

Internal validity can be improved by:

• Extraneous variable (EV) control
• Standardisation of instructions
• Counterbalancing
• Controlling for individual differences
• Reducing demand characteristics and investigator effects.

Ecological validity refers to the extent to which the results of a study can be generalised to other settings and situations. A study entirely carried out on university students might have very poor ecological validity due to the specific culture or practices of its setting, which would make it difficult to accurately generalise.

Population validity – The extent to which the results of a study can be generalised to people other than the studied sample. Studies are often Eurocentric or Americanocentric, reflecting a westernised worldview and an individualist philosophy, often being inapplicable and invalid when applied to eastern, collectivist cultures.

Validity over time – The extent to which the results of a study can be generalised to other historical or future societies and situations. Results from Solomon Asch's study on conformity in America during a period of the Cold War known as McCarthyism, where individuality was highly discouraged, may not apply to America's more liberal and tolerant society nowadays.

To test for validity we can use:

• Concurrent validity – Assessing how well a study’s results correlate with another study at a similar time that has already  been validated – if they have similar results and conclusions, the study we are assessing is more valid.

• Content validity – The extent to which a measure represents all elements of the system or construct being studied. For example, a measure of intelligence is more valid if it takes into account emotional, verbal, spatial and mathematical intelligence, rather than just a single measure.

• Face validity – Whether the test appears, at face value, to measure what it claims to. 
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Reliability

Reliability is the consistency of a research study or measuring test – to what extent the results match the results of similar studies, or how much the study can be replicated and achieve similar results.

Internal reliability is the degree to which a measure is consistent within itself – checking that all parts of a study are testing for the same thing.

To assess internal reliability, we can use the split-half method for any metric or study that uses a numerical system such as a numbered rating or likert scale. Splitting a participant's responses to the questions into two halves and tallying up the totals should yield similar results if the metric has high internal reliability - indicating that questions have similar degrees of relevance and importance. Scores on one half are correlated with the other half - a more positive correlation indicates higher internal reliability of the metric.

External reliability is the extent to which a measure or metric varies from one use to another - whether through time or through who is carrying out the research. This can be assessed through use of the:

Test-retest method – Carrying out multiple tests at different points in time to measure the stability and reliability of the metric over a long period of time. The test is given to the same participant again at a later point in time, and the scores are correlated. A more positive correlation indicates higher external reliability.

Inter-rater reliability – Have multiple raters carry out an assessment using the same metric or test with the same rating scale and check that they have similar results.

Hypotheses, Sampling and Design

First research methods post today! More will follow as I consolidate the rest of the unit.


Black: Description
Red: Negative evaluation of a design or technique.
Blue: Positive evaluation of a design or technique.
Purple: My notes/hints/tips

Experimental Designs

An independent groups design has different groups of participants randomly allocated to each condition of the independent variable. For example, an experiment with two conditions of the IV and a control group would have three different groups of participants - one for each condition. Random allocation is used to prevent researcher bias from favouring one IV condition over another and consciously or unconsciously selecting the group to reflect this favour.

No order effects – the same participant does not participate multiple times, so there are no carried over effects of practice, boredom or fatigue.

Lower chance of demand characteristics – if people are only in one condition of the IV, they are less likely to attempt to guess the aim of the study and change their behaviour to either help or hinder the researcher.

The same apparatus can be used in both conditions – since participants only carry out one IV condition, the experimental stimulus will be unfamiliar to them – they will not have encountered it before.

However, more participants required than for the repeated measures design, so it’s more time consuming.

Also, individual differences between participants in each group may affect results – variations in age, sex, social background and ability that reduce validity.

In a repeated measures design, the same participants take part in each condition of the independent variable. This means that each condition of the experiment includes the same group of participants. 

Fewer participants are needed as the same group part in all conditions – saving time in gathering the sample.

There are no individual differences between groups that could affect the results – the individual differences are only internal, between participants in the same group.

Order effects may reduce the validity of the results, the order of the conditions affecting participants’ behaviour.  Performance in the second trial may be different due to practice, fatigue, and boredom. Counterbalancing can be used to spread order effects equally between all the IV conditions – participants are randomly assigned to complete IV conditions in different orders  - one group does (A) then (B), the other does (B) then (A), helping to offset order effects.

Demand characteristics are also more likely in this design – if people participate in all the conditions of the IV, they are more likely to guess the aim of the study and adjust their behaviour to help or hinder the researcher - both of which damage validity.

The researcher can't use the same apparatus twice – participants will have already encountered the stimulus in the first condition, so it cannot be reused in the second.

In a matched pairs design, participants are paired up with someone with very similar relevant abilities and characteristics, and are then randomly assigned to IV conditions or the control group. Ideally, somebody in one IV condition would be paired to their identical twin in the other condition - but this is rarely practical.

This design avoids order effects, so counterbalancing is not necessary.

Reduces individual differences between the conditions, because the participants are paired up so each has somebody in the other IV condition with similar attributes and characteristics.

The same apparatus can be used in both conditions – since participants only carry out one IV condition, the stimulus will be unfamiliar to them – they will not have encountered it before.

Demand characteristics are less likely, as each participant only participates in one condition of the IV so there is less chance of them trying to guess the aim and changing behaviour.

Sampling Techniques

An opportunity sample consists of simply selecting people as participants who are available and willing at the required time – for example, just going up to people on the street and asking them to participate in your research.

An opportunity sample is quick, convenient, and practical – allowing for the selection of many participants fairly easily just by using those who are available and willing.

Very unrepresentative sample as you only get a specific social demographic – the kind of people likely to be around at the time and place of sample gathering.

Often biased by the researcher, who will likely choose people who present as “helpful” – rather than those representative of a range of personalities and temperaments.

In a random sample, every member of the target population has an equal chance of being selected as a member of the sample population – using methods such as pulling names from a hat.

For very large samples, this provides the best chance of an unbiased and representative sample – theoretically the random nature of selection will not lead to any biases, as everyone has an equal chance of selection.

No researcher bias, as the researchers have no control over whom from the target population is selected as a participant.

 

For large populations, it is time-consuming and difficult to create a list of every individual in the target population, so a less representative but easier sample such as a volunteer or opportunity sample might be more practical.

 

A volunteer sample works through self-selection – individuals who have chosen to be involved in a study form the sample population, for example, people who responded to a newspaper advertisement asking for participants in a study will be chosen to participate.

Relatively convenient and ethical if it leads to informed consent – a large sample of participants can be gathered very quickly for a large-scale study such as a questionnaire or survey.

The researcher can advertise for specific traits and demographics in participants that they desire, if relevant, – e.g. Milgram’s use of a volunteer sample to select those to form a specific sample population of males between age 18 and 60, simulating the gender and age demographics of Nazi soldiers in WWII.

Unrepresentative, as it is biased towards the kind of person who will respond to advertisements and volunteer their time – biased towards a specific helpful kind of personality and temperament that is not representative of the general population.

Hypotheses

Hypotheses are testable, provable and falsifiable statements that predict the outcome of a study.

A directional hypothesis suggests that different IV conditions will affect the DV, and the direction of the effect – which way the DV will influence the IV. For example, "participants who have recently eaten carrots will be able to correctly identify more objects in a dark room than those who have not recently eaten carrots.

A non-directional hypothesis suggests that different IV conditions will affect the DV, but does not suggest a direction. For example, "there will be a difference in the number of objects in a dark room correctly identified, between participants who have recently eaten carrots, and those who have not recently eaten carrots."

A null hypothesis suggests that the IV will not affect the DV, and any difference in results will be due to chance or experimental error. For example, "there will be no difference in the number of objects in a dark room correctly identified, between participants who have recently eaten carrots, and those who have not recently eaten carrots."

Before being used to a form a hypothesis, variables must be operationalized - being made quantifiable and measurable. For example, the operationalised IV in the above is "eaten carrots recently: yes or no", and the operationalised DV is "number of objects correctly identified in a dark room."
An alternative hypothesis is any hypothesis other than the null.

The use of biological interventions in reducing addictive behaviour

Black: AO1 - Description
Blue: AO2 - Evaluation - studies
Red: AO2 - Evaluation - evaluative points/IDAs
Purple: My notes/hints/tips

Varenicline is a prescription medication used to treat nicotine addiction, functioning as a partial agonist for nicotine receptors – stimulating them more weakly than nicotine itself. It both reduces cravings for and decreases the pleasurable effects of nicotine, helping people to quit smoking. Varenicline is usually administered orally, in tablet form.

In a double blind trial, Gonzalez et al (2006) found 44% continuous smoking abstinence during the last 4 weeks of a 12-week treatment in participants taking varenicline, compared to 18% of placebo-treated subjects and 30% of bupropion-treated subjects. After a year, the varenicline group had significantly increased prolonged abstinence compared to other treatments – over double that of a placebo, and slightly more than bupropion. This suggests that varenicline is an effective method of treatment, helping just under half of smokers quit in the short-term, and about a fifth in the long-term.

The fact that they looked at the effects of varenicline over a year, rather than just in the short term, makes this study’s results more valid – showing that varenicline is effective at prolonged rehabilitation from smoking rather than just short-term abstinence.

That 18% of patients managed to quit in the short-term via placebo treatment brings the effectiveness of the drug into question, suggesting that there is more to drug therapy than just biological mechanisms – the belief in having a drug to treat their addiction made them more likely to successfully quit. We cannot definitively say what proportion of those who successfully quit, quit due to the varenicline's effectiveness, or due to the placebo effect.

Aubin et al (2008) compared participants receiving varenicline to those receiving NRT, Nicotine Replacement Therapy. Patients were either on transdermal nicotine patches for 10 weeks, or varenicline for 12 weeks. Prolonged smoking abstinence for the last 4 weeks of treatment was higher for varenicline than nicotine patches – 56% vs. 43%. After a year, rates of prolonged abstinence were still higher for varenicline – 26% vs. 20%. 

Brose et al (2013) compared varenicline and NRT, measuring abstinence using carbon monoxide readings. They found that varenicline was more efficient - 43% compared to 37%.

Unlike many other studies into biological interventions, this study used a scientific, biological and objective measurement of abstinence, rather than self-report surveys and questionnaires, which could give untrue or misleading answers due to a social desirability bias.

Nicotine Replacement Therapy is based around nicotine administration in ways other than smoking tobacco, such as chewing gum, nicotine patches, and e-cigarettes. Rather than acting as a nicotine receptor agonist, they administer nicotine without the multitude of harmful effects associated with smoking, such as lung disease and cancers from chemicals in cigarette smoke.

West (2014) surveyed nearly 6000 smokers in the UK who had tried to quit smoking without the aid of prescription medication or professional support. Participants who used e-cigarettes were 60% more likely to successfully quit than those who used over-the-counter NRT or willpower alone, suggesting that e-cigarettes are the most effective publicly available form of NRT. This effectiveness has been explained by them filling a psychological as well as a biological need – going through a very similar procedure to the action of smoking a cigarette fulfils both, whereas conventional forms of NRT just fulfil a biological need. 

However, it has been suggested that e-cigarettes could increase the risk of future relapse, as they do not break this psychological procedural behaviour pattern of “smoking” like other forms of NRT do.

However, a 2012 study by Harvard University suggested that NRT may not actually be that effective. Surveying nearly 800 adult smokers who had recently quit, they were asked whether or not they had used NRT, joined a quit-smoking program, or received professional help. One-third of quitters surveyed reported to have relapsed, and there was no difference in relapse rate between those who used NRT and those who didn’t, suggesting that NRT might not actually play a role in helping people quit. 

On the other hand, a Cochrane systematic review challenges this, suggesting that NRT may be effective after all – analysing 50000 people over 150 trials of NRT, they found that it increased the chances of stopping smoking from 50% to 70%, but found no difference in effectiveness between different types of nicotine administration method, e.g. e-cigarettes, patches, gum.

The theory of planned behaviour as an intervention into addiction

Black: AO1 - Description
Blue: AO2 - Evaluation - studies
Red: AO2 - Evaluation - evaluative points/IDAs
Purple: My notes/hints/tips

This theory assumes that an individual's personal attitudes, subjective norms and perceived control

over their behaviour influence their intention to perform the behaviour. That intention, in turn, predicts whether the behaviour will occur. The TPB assumes a causal relationship between an individual's attitudes about a behaviour, their intention, and the actual performance of that behaviour.  Applied to intervening in the addictive behaviour of smoking, the theory of planned behaviour would reduce addiction in a three step process.

 Firstly, change subjective norms regarding behaviour such as smoking – change the public’s perception to make them believe smoking is harmful, unacceptable and antisocial – through methods such as public health campaigns. Change the law to make public smoking no longer a norm, or tobacco not to be advertised at the point of 

Secondly, change personal attitudes – show the individual that smoking is bad for them and a socially undesirable behaviour - using campaigns like the Toxic Cycle, or graphic warnings on cigarette 

Finally, change their level of perceived behavioural control – show people that they have the power to control and to quit their addictive behaviour – using methods like the Smokefree Products and NHS Quit Kits.

Critics would argue that the theory of planned behaviour is too rational – being able to explain intention, but not behaviour. The majority of people who try to give up smoking fail – due to psychological and physical dependence. The theory of planned behaviour does not take biological dependency into account – the body adjusts to be able to cope with nicotine, and neuroadaptation occurs, causing withdrawal symptoms when they try to quit. 

Armitage (1999) argued that the TPB was too rational an explanation of addiction as it ignored factors such as emotion, compulsion, and social pressures -  for example, many people smoke or drink when under stress or other negative emotions, or in social situations such as being in a group of friends who they usually smoke with.

Armitage & Conner (2001) did a meta-analysis and found that the TPB was good at predicting intention but not actual behaviour - although the theory of planned behaviour may help explain an attitude change which leads to somebody trying to quit their addictive behaviour, this intention change does not directly translate into managing to give up their addictive behaviour.

Albarracin (2005) criticised the use of self-report questionnaires to measure the TPB, believing them to be unreliable as they are better at assessing attitude and intention rather than actual behaviour. People also tend to give socially desirable answers - for example, addicts tend to play down or under-estimate the extent of their addiction. Alternatively, they may simply be unaware of the extent of their addiction. 

The Cochrane systematic review (2011) found that exposure to tobacco advertising and promotion, including POS displays, increases the likelihood that adolescents will develop a smoking addiction. This supports the assumption of the TPB that social attitudes play a major role in addictive behaviour - subjective norms considering a behaviour acceptable makes it more likely that people will carry out that behaviour.

Klag argued that self-determination theory is a better predictor of quitting, suggesting that people quit an addictive behaviour due to circumstances unique to them – life events such as having a child, or having a relative die due to their addiction - powerful individualistic triggers rather than generic social pressures.

Risk factors affecting vulnerability to addiction

Another application-heavy section here - you'll often be presented with a scenario and asked to identify and explain risk factors that are present, and then evaluate the risk factors using supporting evidence. Remember to specifically signpost any research you take from this as supporting evidence - making sure it counts for AO2 rather than AO1

Black: AO1 - Description
Blue: AO2 - Evaluation - studies
Red: AO2 - Evaluation - evaluative points/IDAs
Purple: My notes/hints/tips

Stress: Increased stress levels are positively correlated with an increased vulnerability to developing dependencies, often initiating them as a maladaptive way of coping with stress. The self-medication cognitive model of addiction explains addictive behaviours as initiating in order to alleviate the effects of existing life stressors such as anxiety or a lack of self-confidence, suggesting that people initiate the specific addictive behaviour that they feel will help them best cope with a specific source of stress.

Childs + DeWitt (2010) investigated the effects of stress on cigarette smoking, looking specifically at its effects on cigarette craving, the subjective effects of smoking, and smoking behaviour in daily smokers. A sample of smokers was given a stressful task to complete, and then given a chance to smoke or earn money over a 2-hour period. Both before and after the task, stress was measured both objectively (through heart rate and cortisol levels) and subjectively (through self-reported anxiety and desire to smoke.) These measurements were also taken after they smoked a cigarette when given the chance to. Participants were more inclined to smoke for stress relief than to earn money. Stress did seem to increase cravings to smoke and pleasure obtained from smoking, but did not seem to increase the amount of cigarettes that were smoked.


Cleck + Blendy (2008) reported that people with stress-related psychiatric disorders such as depression and anxiety (that are often related to addictive drug usage and exposure to chronic stressful life conditions such as abuse) have an increased rate of nicotine, alcohol and cocaine usage, suggesting stress is an important factor in determining vulnerability levels to addiction.

These results can also be used to support self-medication cognitive model of addiction – the concept of nicotine taken to alleviate stress and anxiety supports the central concept of self-medication.


Peer group: Peer pressure is a very powerful factor that can influence the behaviour of an individual, especially during childhood and adolescence. Peer pressure can work as a form of operant conditioning – if peer groupings encourage and socially reward addictive behaviours, thrill seeking and experimentation, individuals within the peer group will have an increased vulnerability to both initiation and maintenance of addictive behaviours. Peers also act as a form of social learning, modelling addictive behaviours so others will observe and imitate them, and being rewarded by peer approval as a form of vicarious reinforcement.

Bricker et al (2006) investigated the extent to which childhood friends influenced smoking behaviour. A sample of 4744 children was studied and it was found that close friends influenced them:

• To try smoking 38% of the time
• To move on to monthly smoking 10% of the time
• To move on from monthly to daily smoking 11% of the time.

This study also found that close friends were 12% more influential in the initiation of smoking in the sample children than parents’ smoking was. However, close friends smoking were 16% less influential than parents smoking in the move to daily smoking. This suggests that peers play a role in initiation more than they do maintenance, when the family and parents become more important. This supports the role of social learning theory as an explanation of addictive behaviour initiation – 38% of children initiated an addictive behaviour due to observation and imitation.

Wagner and Anthony (2002) found that cannabis smokers were more likely to progress to cocaine usage due to being in peer groupings where there are opportunities for new drug experiences, suggesting that peers can act as a social context “gateway” to other addictive behaviours. This supports the role of peer groups in the initiation and maintenance of addictive behaviour.

However, cause and effect cannot be established with complete certainty when studying the role of peer groups in addiction – it is possible that instead of peer groups influencing dependency behaviours, individuals who are already dependent will seek out peer groups that accept and encourage their dependent behaviour – social selection rather than social influence.

Gender: it has been suggested that males and females take different factors into consideration when making the decision to initiate smoking. Men tend to be more likely than women to take part in most addictive behaviours and to have a larger repertoire of gambling activity than women.

Amos and Bostock (2007) carried out a qualitative study of 15-16 year old Scottish smokers, and found that smoking played a different role for the two genders, differences revolving around diverse social relationships, interests and activities. For example, boys were more likely to consider the impact that smoking would have on fitness and the ability to play sport, while girls focused more on the aesthetic effects of smoking, such as their clothes and bodies smelling of smoke. This supports the idea that different genders consider different factors when initiating addictive behaviour.

They suggested a real world application from the result of this study: stop-smoking campaigns aimed at girls and boys should be designed differently and with a different message to target the ill effects of smoking that each gender specifically focuses on in order to better target their message to their audience demographic.

Personality: Originally, it was suggested that addiction leads to personality defects, but research has indicated that certain personality traits can predispose an individual to the development of addiction. Traits associated with extroversion, introversion, neuroticism and psychoticism can increase vulnerability to addiction. . Extroversion involves sociability, liveliness, and thrill-seeking, and according to Eysenck’s theories, the thrill-seeking tendencies of extroverts make them more likely to develop an addiction. On the other hand, some introvert traits such as shyness and lack of confidence can make addiction more likely.  

Eysenck and Grosson (1991) used the EPQ (Eysenck Personality Questionnaire) to compare 221 addicts to 310 non-addicts, finding that addicts had many more personality items on the neuroticism scale linked to anxiety and depression. However, cause and effect is an issue here – being addicted to a substance could cause anxiety and depression, rather than anxiety and depression leading to self-medication through addictive substances.

Eysenck linked excess dopamine levels in people with a psychotic personality to addiction, but the rise in dopamine levels caused by many addictive drugs could lead to a rise in personality traits associated with psychoticism such as aggression and impulsivity – can’t determine cause and effect.

Francis (1996) found a link between alcohol, heroin and benzodiazepine and nicotine addictions, and higher than normal neuroticism and psychoticism levels – suggesting that personality factors can affect the likelihood of addictive behaviour developing. 

There is very little empirical evidence to suggest a causal link between the thrill-seeking dimension of extroversion and the initiation of addictive behaviours.

The concept of an addictive personality is supported by the fact that certain individuals can become dependent on many things, either simultaneously or over time. For example, a heroin addict overcoming their heroin dependency and becoming an alcoholic. This idea is also supported by the fact that many recovered addicts develop equally strong compulsions towards other activities not typically seen as addictive behaviours, such as long-distance running, or religious fervour.  

Age: Younger age groups are more likely to engage in online gambling 

The British Gambling Prevalence Survey found high prevalence of online gambling in younger age groups – 15% for those aged 25-34, 1% for those aged 75 or over, across both genders. Across both genders, problem gambling rates did not vary by age, but in men, problem gambling prevalence higher in younger age groups than older – 2.1% in 16-24 age group, 0.4% for 75+ age group. This suggests that belonging to a younger age group can put one at a higher risk for the development of addictive behaviour.

Media: Social Learning Theory suggests that addiction is learnt through observation and imitation, and that figures in the media such as celebrities or fictional characters can act as models for addictive behaviours. If the addictive behaviour is presented in a positive light or the model is rewarded for their behaviour, the viewers are more likely to imitate them and initiate the addictive behaviour themselves, an example of vicarious reinforcement.

Gunsekera et al (2005) carried out a content analysis of 87 popular films released over a period of 20 years. They found that: 8% featured cannabis, 68% featured tobacco, and 32% featured drunken behaviour, and  most that featured them tended to portray these drug-taking behaviours positively.

Dalton et al (2003) surveyed 3547 children aged 10-14, all of whom were non-smokers. 1-2 years later, a follow-up study found that those who had been exposed to the most smoking in films were significantly more likely to have started smoking. Dalton concluded that greater exposure to addictive behaviour in the media leads to an increase risk of developing that addictive behaviour themselves. However, determining cause and effect may be an issue here: it may have been that the type of children likely to start smoking were also more likely to seek out that kind of film. 

Distefan et al (2004) surveyed adolescent smokers and asked them to nominate a favourite film star. One third of participants named a star who smoked on screen – this was seen to play a large part in predicting these adolescents’ own smoking behaviour – particularly among girls. However, this was a correlational study, so we cannot rule out a third variable such as a thrill-seeking personality that could lead children both to start smoking, and to be more drawn to film stars that both smoke and star in more action-based films.

The British Gambling Prevalence Survey of 2011 reported that 73% of the adult population had participated in some form of gambling over the past year, a prevalence increase of 5% from the rate observed in 2007. This correlates with a 600% increase in exposure to gambling adverts on television since the 2005 Gambling Act. Although this is only correlational, it could suggest that the increased media exposure and gambling adverts led to the increase of gambling behaviour in the general public. 

A quick note on the role of the media in addictive behaviour

Questions on the influence of the media on addictive behaviour will either ask about positive, negative, or both effects on addiction. If they ask for the negative effects, use the research studies I outlined in my post on risk factors for addiction (Gunsekera, Dalton and Distefan), and if they ask for the positive effects, use your knowledge of the Toxic Cycle and Gamble Aware campaigns outlined in my post on public health interventions.

Cognitive explanations of addiction

Black: AO1 - Description
Blue: AO2 - Evaluation - studies
Red: AO2 - Evaluation - evaluative points/IDAs
Purple: My notes/hints/tips

Cognitions are thoughts, perceptions, reasonings and beliefs. The cognitive approach suggests that addictive behaviours develop due to faulty and irrational thought processes, and suggests several mechanisms for how these thought processes lead to addiction.

Gelkopf developed the self-medication model of addiction, which states that individuals carefully select addictive substances or behaviours based on perceived problems in their life, believing that the substance or behaviour will provide an effective solution to these problems. For example, someone may start smoking to alleviate stress, start drinking alcohol in social situations due to a lack of confidence, or gamble due to financial difficulties.

This model can explain initiation - people start an addictive behaviour due to a pre-existing stressor, maintenance - the behaviour can appear to help in the short term due to associations formed between the addiction and alleviation of the stressor (e.g. nicotine with calmness, alcohol with confidence), and relapse - once someone stops carrying out the addictive behaviour, they will relapse as soon as the initial stressor reoccurs, believing that the stressor has reocurred due to stopping the addictive behaviour.

People often carry out addictive behaviours without any underlying social or psychological hardships to resolve - confident people drink alcohol, non-anxious people smoke, and rich people gamble, so the self-medication model fails to explain initation of addictive behaviours in the absence of a triggering stressor.

Cause and effect is an issue with this model - it is often unclear whether the addictive behaviour develops to medicate for a pre-existing issue, or whether the issue is caused by the addiction. Many pathological gamblers also suffer from depression, and though the model would suggest that people with depression turn to gambling as a form of self-medication escapism, other psychologists have suggested that the causation is the other way round - that depression can develop as a result of poverty brought on by a gambling addiction. Becona (1996) found evidence of major depressive disorders in the majority of problem gamblers, but it is not clear whether the gambling caused the depression or vice versa. A similar cause and effect issue exists with smoking - it could be a self-medication coping response to stress, or stress could be brought on by illnesses caused by smoking.

The self-medication model can explain the disparity between genders in rates of depression and alcoholism reported by the NHS. In the UK, 1 in 4 women will undergo treatment for depression at some time, compared to 1 in 10 men, while men are twice as likely to show signs of alcohol dependency as women. The self-medication model explains this as a result of increased social acceptability of alcoholic self-medication for men - men are more likely to turn to substance abuse to treat their mental health issues than women, who are more likely to seek professional help.

Kassel (2007) found that adolescent smokers most commonly reported smoking when they were experiencing negative moods, supporting the theory of addictive behaviours developing as a coping mechanism to deal with stressors and negativities in daily life.

Parrott (1988) explained maintenance and relapse in terms of self-medication to avoid withdrawal symptoms. Abstaining from nicotine, even for a brief period, causes increased stress and anxiety in the form of cravings - smoking immediately relieves this anxiety and stress. This supports the self-medication explanation of smoking - that of nicotine as a coping mechanism for anxiety.

Heuristics are mental shortcuts that allow us to quickly solve problems and come to judgements based on prior experience. Heuristics theory suggests that gamblers maintain their behaviour through the use of a number of irrational heuristics in their information processing, overestimating their ability, overplaying their winnings, and downplaying their losses to support the perceived rationality of their behaviour.

Representative bias (Gambler’s fallacy) suggests that we apply a law of averages to a very small sequence of numbers, assuming that if something happens frequently during a short period of time, it will happen less frequently in the future.

Availability bias suggests that we put too much weighting on information from recent events, claiming that if something can be recalled, it must be important, or at least more important than information from events which are not recalled.

Illusory correlations are where the brain irrationally draws a correlation between two variables where there is none – often as the result of an associative accident. A perception of a relationship between two variables is formed where no relationship exists.


Henslin (1987) found that American players of the dice game Craps would roll the dice slowly when hoping to get a low number, and roll them quickly and hard when attempting to get a high number, even though there is no logical reason to believe that this would affect the outcome. This supports the concept of illusory correlations playing a role in gambling addictions, helping gamblers justify their behaviour to themselves by perceiving themselves to be more in control of outcomes than they actually are.

Griffiths (1994) found that regular gamblers over-estimated their skills, made more irrational verbalisations suggesting cognitive biases and were more likely to engage in machine personification, talking to the machine - supporting the concept of cognitive biases being used by gamblers to justify their own behaviours to themselves.


(Not much AO2 - supporting evidence to go with the final mechanism - cognitive dissonance - so seeing as we aren't asked more than 12 markers on a single aspect of addiction, learning the above in great detail is likely to be more useful than this final approach. It is easier to apply to smoking than Heuristics Theory is, though, so it could be very useful if an application question comes up in that area.)

Cognitive dissonance is another mechanism that cognitive psychology uses to explain addictive behaviour, and it results from a conflict between reasoning and behaviour. When an imbalance in our perception of the risks and benefits of an addictive behaviour occurs, this causes discomfort in the form of cognitive dissonance, so we alter our thought processes to minimise perceived costs and to maximise perceived benefits.

On a rational level, addicts understand smoking to be a negative behaviour, leading to social stigma, health problems and long-term illness. However, they are addicted to the behaviour of smoking, so adapt their belief systems to reconcile their behaviour with their rational understanding. They would make changes to their beliefs such as mentally minimising the risk or maximising the perceived benefits of smoking to help accommodate their addiction – “alleviating their cognitive dissonance” by changing from rational to irrational thinking.

Cognitive dissonance theory can explain maintenance of addiction – why people carry on an addictive behaviour despite being fully aware of the risks involved. They distort their own cognitive processes to to minimise perceived cost and maximise perceived benefit, leading themselves to believe their addictive behaviour is self harmful than it actually is.

It can explain initiation - people with negative views towards a substance or behaviour that feel pressured into starting it could mentally minimise risks and maximise rewards in order to justify their own initiation of the behaviour. 

It can explain relapse - maximising benefits and minimising risks of starting again and alleviating negative conseqences when withdrawal symptoms kick in, making reinitiation of the addictive behaviour seem more desirable than it otherwise would without cognitive dissonance. 

Evolutionary explanations of the development of gender roles

Think I'll write up a bit of Gender tonight, as it's the most recent and fresh in my mind (and I really enjoyed this topic) - addiction and R.M will follow over the next week!

Black: AO1 - Description
Blue: AO2 - Evaluation - studies
Red: AO2 - Evaluation - evaluative points/IDAs
Purple: My notes/hints/tips

While gender is defined as the social and psychological characteristics of males and females, gender roles are the differences in attitude, interests and behaviour that members of each gender adopt. For example, in most cultures, women usually look after babies, whereas men are usually the resource providers. Evolutionary theory suggests that gender roles appeared as an adaptive behaviour thousands of years ago, and then evolved to be ingrained in the DNA of modern humans due to the advantages they provided to survival and reproduction.

Parental Investment Theory (PIT) explains different gender roles as a result of different levels of parental investment between the mother and the father - for males, each offspring requires relatively little parental investment, whereas, reproduction for females involves a considerable investment. PIT can explain different reproductive strategies between genders as an aspect of gender roles. With many limiting factors reducing the amount of offspring they can have - a narrower fertility window, 9 month pregnancies, a limited supply of eggs, and carrying out the majority of childcare, a reproductive strategy of choosiness is more adaptive for women - choosing the men who display genetic fitness and status, having few offspring, and investing heavily to ensure their survival. With their only limiting factor being access to willing females, a reproductive strategy of promiscuity is adaptive for men - having many offspring with many women, and investing little into each child.

Supporting evidence for a difference in reproductive strategies as an aspect of gender roles comes from Clark and Hatfield's 1989 study into gender attitudes towards casual sex in a sample of university students. When approached with an offer of sex, all the female participants declined, while 75% of male participants accepted. This supports the concept of different adaptive sexual strategies between genders - with a much more limited reproductive capacity than men, choosiness is more likely to be an adaptive sexual strategy for women, whereas men's reproductive capacities are less limited by biological constraints, so promiscuity is a much more adaptive strategy. This link between adaptive sexual strategies and different gender roles is evidenced by the gender differences in willingness to have casual sex.

Cultural bias is an issue here when trying to apply results globally - the reported disparity in sexual strategies could be more a product of cultural norms than evolutionary differences in gender roles, and therefore would not apply cross-culturally. Casual sex and promiscuity is much more acceptable in some cultures than others - it is imposing an etic to generalise Clark and Hatfield's results from an American study to less tolerant countries like Saudi Arabia, so conclusions cannot necessarily be generalised. Additionally, there is more of a social stigma to promiscuity in women than in men, so female participants in Clark and Hatfield's study could have been less likely to accept the offer of casual sex than men because of the social taboo, rather than because of evolutionary differences in gender roles.

PIT can also explain differences in aggression between the genders - higher levels of aggression are considered to be a trait of male gender roles much more than a trait of female gender roles. In our evolutionary history, female choosiness meant that males had to compete with each other - intraspecific competition - to be reproductively successful. Physical and behavioural characteristics which are helpful in a fight (such as size, strength, and aggression) are passed into the gene pool - these then constitute aspects of masculine gender roles in the modern world. (Probably the AO1 segment least crucial and the one to drop if you're really pressed for time in the exam - not much supporting evidence or criticism of this that I could find, so it can appear a bit tacked-on, it might be better to invest more time in the other two AO1 chunks.)

Finally, Wilson suggests that our ancestors started living in monogamous male/female pair bonds because it conveyed an evolutionary advantage - females gained protection and guaranteed resources, while males could guard their mates from other males, avoiding cuckoldry and increasing parental certainty. This formation of pair bonds led to the division of labour between the couple, which turned into gender roles - the stronger males hunted and foraged, while the more nurturing females performed tasks that could be done simultaneously to childcare, such as farming and preparing food. This led to an evolutionary advantage in societies that adopted these gender roles, leading to the creation of bigger social groups.

The almost ubiquitous nature of these gender roles across many different cultures in the modern world supports the evolutionary approach's explanation of gender role development. The status of division of labour as an almost global etic suggests that the tendency to develop specific gender roles is a fundamental part of human genetic code, rather than a product of social norms, meaning that humans have evolved this way due to the adaptive advantage provided by gender roles.

However, a study by Daly and Wilson (1988) challenges the evolutionary approach's explanation of gender roles. Between the years of 1933 and 1961, in Denmark, all cases of female-female murder were of infanticide - Hardy (1999) argued that this shows women are not always warm and nurturing, in contrast with the suggested gender roles of evolutionary theory. However, some proponents of evolutionary theory challenge Hardy's interpretation, saying that mothers must respond to environmental conditions in ways that increase the chances of their own survival, not just that of their offspring - so sometimes, due to poverty, female gender roles involve favouring one child over another, or their own wellbeing over the wellbeing of their children. (Happy Valentines' Day, everyone, here's a study on parental infanticide to lighten the mood)

It has been suggested that researcher bias is an issue with this study - the unusual and arbitrary choice of years and country could suggest that the researchers picked a specific sample with which to challenge evolutionary explanations, and this evidence is not a representation reflection of female behaviour, but was just specifically selected in order to criticise the evolutionary approach to gender roles.

Buss (1989) provides supporting evidence for the evolutionary explanation for the development of gender roles. Gathering information about mate preferences from 37 cultural groups, Buss found a strong tendency in females to seek males with resources and ambition - males who fulfilled the traditional gender role of resource provision. Males had a tendency to seek physical attractiveness and youthfulness in females - females who fulfilled the traditional evolutionary gender role of bearing and raising children. However, not all of the results supported evolutionary predictions - the idea that men would place more importance than women on chastity in a partner was only supported to a small extent. Otherwise, Buss' results support the concept of evolutionarily rooted gender roles in modern society that are reflected in the traits we find attractive.

It can be argued that despite its advantage of being representative of many different cultural groups, Buss' study did not treat psychology in a scientific manner, using an unscientific and highly subjective methodology. His use of questionnaires yielded unfalsifiable and potentially inaccurate data - questionnaires are prone to social desirability bias, as participants may have given untrue answers which presented them in a certain, socially acceptable way. This makes Buss' results potentially invalid.

Holloway et al (2002) provides supporting evidence for evolutionary explanations of gender roles in a study of male and female chimpanzees. Human males tend to be 1.1 times bigger than human females, but in chimpanzees, where selection pressures for male physical competition are more intense, males tend to be 1.3 times bigger than females. This supports the concept of gender roles being selected through evolution - male size and strength are selected for more in a more physically competitive species than in a less competitive species.

Biological determinism is a large problem with the evolutionary approach to gender role development - an abundance of obvious counterexamples to the predictions of evolutionary theory suggests that free will plays a significant role in modern gender roles, rather than just genetic predermination. The existence of successful, stable couples where traditional gender roles are inverted, e.g,  a highly paid, powerful woman in a position such as a doctor or CEO, and a house-husband who does the majority of the childraising, mean that it is overly deterministic to suggest that evolutionary psychology has caused the gender roles that exist in society today.

The evolutionary approach to gender roles is also overly reductionist, focusing entirely on the genetic "hard-wiring" of behaviour to explain the difference in contemporary gender roles. It ignores other potentially important factors such as the role of socialisation - an influence whose effect can be demonstrated by rapidly changing gender roles in modern society. The departure from traditional cultural expectations of men and women has led to changing gender roles - with a higher proportion of females in higher education and historically masculine professions. Accounting gender difference purely to evolution ignores these cultural expectations which play a powerful part in assigning gender roles.

Investigations into this area of psychology are potentially unethical, as much research here deals with socially sensitive issues of gender roles and expectations. Evolutionary theory sees men and women as being unable to escape from biologically determined roles - this creates social and political issues. The determinism of the approach means that results and conclusions should be treated sensitively in order to avoid reinforcing historically unfair and oppressive gender roles and expectations. Although gender equality is gradually progressing, it is only recently, for example, that the UK government changed the law regarding maternity and paternity leave to allow either gender leave from work to carry out the parenting role.

The theory seems to have overall face validity, providing a plausible explanation for physical differences and different mating behaviours between the genders. It can also provide an explanation for the extinction of the Neanderthals and the survival of Homo Sapiens - our psychological ability to form pair bonds and divide labour between the genders gave us greater food production efficiency, which helped our species survive and reproduce - an ability which the Neanderthals lacked.

Sorry I haven't been very active recently!

Sorry for the lack of posts recently, I've been very busy with my other subjects and haven't had as much time to dedicate to this as usual! Over half term (so, by the 22nd Feb) I will write all the posts for Addiction, and hopefully make a start on Research Methods, so don't think that I've stopped for any reason! Thanks for the encouraging comments you've been giving me, and I'm glad that lots of people are finding this helpful!