Explanations of Insomnia

Primary insomnia can be learnt through association after experiencing stress-related insomnia. When insomnia occurs that is a result of stress and anxiety, an association forms between the bed and sleeplessness, so insomnia persists even when stress disappears. Sleep-related anxiety and the expectation of insomnia leads to learned insomnia, in a self-fulfilling prophecy.

This explanation of insomnia has found valuable real-world application in the use of CBT (cognitive behavioural therapy) to treat primary insomnia - breaking the association between the bed and sleeplessness to reduce anxiety over being unable to sleep. The success of this therapy supports the learnt explanation of insomnia - if the disorder can be unlearned through therapy, this suggests that it was a learnt behaviour in the first place.

Research by Storms and Nisbett supports the hypothesis of learned insomnia. In a clinical trial of insomniacs, participants went to sleep faster on placebo pills they believed to be stimulants, attributing their state of wakefulness to the pill rather than insomnia, so they relaxed enough to go to sleep. The group given pills they believed to be anxiolytics took even longer to get to sleep than normal, assuming that their insomnia was unusually severe that night due to their unaltered level of wakefulness. This supports the suggestion of self-generated anxiety over insomnia being a causal factor in the perpetuation of insomnia.


Gender differences in the diagnosis of primary and secondary insomnia suggests that this theory may be beta gender biased in its explanation of insomnia. The incidence rate of insomnia is higher in females, who also tend to have higher levels of anxiety and neuroticism - this supports the concept of stress as a factor which can lead to learned insomnia, but suggests that it is inaccurate to attribute the same cause to both sexes, as they experience the condition differently, with females more prone to stress-induced insomnia. It would be gender biased to assume that insomnia has the same causes in both males and females.

The genetic explanation of insomnia explains the condition as a result of an inherited gene defect in the genes responsible for the healthy function of the brain stem, leading to irregularities with the sleep/wake cycle. This is based on the observation that insomnia starts early on in life in most sufferers, suggesting that an innate biological cause rather than a learned behaviour is responsible.

Research by Watson et al supports the role of genes in the development of insomnia, studying 1800 pairs of twins. The concordance rate in genetically identical, monozygotic twins was 47%, while the concordance rate in non-identical, dizygotic twins was only 15%. This increased concordance rate in monozygotic twins supports the concept of a genetic basis for insomnia, but shows that genetics cannot completely explain the condition - monozygotic twins are completely genetically identical, so if the condition was entirely genetic in origin, they would show a 100% concordance rate. 

Although Watson et al's observed concordance rates would support the role of nature in the development of insomnia, twin studies alone are not enough to separate the influences of nature and nurture when determining a condition's origin. Monozygotic twins tend to be treated more similarly and share more similar environments than dizygotic twins, meaning that the higher concordance rate may be due to monozygotic twins sharing more environmental factors that could lead to the development of insomnia, such as stress, sleep deprivation and obesity. The concordance rates of obesity were markedly high between both types of twin - it is possible that the increased concordance rate of insomnia in monozygotic twins was a result of an increased concordance rate of obesity, a factor known to contribute to insomnia. 

Dauviliers and Tafti found further supporting evidence for the genetic explanation of insomnia, identifying several gene mutations implicated in the disorder. They also pointed to the genetic illness fatal familial insomnia as supporting evidence - an incredibly rare and heritable prion disease presenting in middle age which leads to a gradual death from sleep deprivation. The heritable nature of this disease suggests that some forms of insomnia have a definite genetic basis.

Explanations of Narcolepsy

The main explanations for narcolepsy involve genes and the neurotransmitter orexin. It has been suggested that a defective gene on chromosome 6 is responsible for narcolepsy in humans, based on the identification of a defective gene on chromosome 12 responsible for narcolepsy in dogs. These genes code for proteins in the brain which act as receptors for orexin, which plays a role in the regulation of appetite, sleep and wakefulness. With these receptors functioning abnormally, regular orexin transmission cannot happen in the brain so it cannot properly control sleep behaviour - leading to the symptoms of narcolepsy such as excessive daytime sleepiness, cataplexy and sleep paralysis.

It is also suggested that narcoleptics transition straight into REM sleep from wakefulness rather than going through light sleep and slow wave sleep first, leading to the sudden loss of muscle tone in cataplexy and sleep paralysis; hypnogogic hallucinations represent dreams experienced in a state of semi-wakefulness.

Lin et al provided supporting evidence for the role of genetics in the development of narcolepsy. Using genetic analysis techniques, a gene mutation on the 12th chromosome was identified in dogs as being responsible for narcolepsy - on a gene which regulates orexin receptors. A similar mutation on the 6th chromosome was identified on a gene with the same regulatory purposes - these results would support the hypothesis that genetics and impaired orexin receptors may play a causal role in narcolepsy. 

Thannickal et al carried out research supportive of Lin's suggested role of orexin in narcolepsy. Scanning the brains of narcoleptics and healthy controls, they found a severely reduced quantity of orexin-producing cells in the narcoleptics compared to the control group - supporting the hypothesis of abnormally low orexin levels causing narcolepsy. However, determining the direction of cause and effect is a difficulty with these results - although the reduced density of orexin cells may have caused narcolepsy, the condition itself may have caused the reduction in orexin. Causation cannot be determined, weakening the validity of the supporting evidence.

However, research by Gordon et al supports a different explanation - of narcolepsy as an autoimmune disorder, rather than it being caused by genetics or orexin. Mice were injected with antibodies from the blood of either narcoleptics or non-narcoleptics - the group injected with narcoleptic antibodies developed the symptoms of narcolepsy. This suggests that narcolepsy is caused by our own antibodies malfunctioning and attacking brain tissue, challenging the genetic and orexin hypothesis.

On one level, Gordon's research can be seen as scientifically credible through its use of a control group. The use of one group injected with non-narcoleptic antibodies to compare the experimental group to allows cause and effect to be determined - we can be fairly sure that the injection of the antibodies led to the development of narcoleptic symptoms in the mice. However, the use of non-human animals is an issue here - neurological or immune differences between mice and humans may mean that it would be overly anthropomorphic and invalid to generalise the conclusions of this study to humans - narcolepsy may not work the same way in both species.

The orexin explanation of narcolepsy has valuable real world application in the use of stimulants such as Ritalin and Modafinil to treat the excessive sleepiness associated with the condition. These stimulants act as orexin agonists, and have had much success in treating the sleepiness, cataplexy and lapses into daytime sleep that the condition causes, and the success suggests that narcolepsy does have a cause related to orexin deficiencies. 

The identification of a possible chromosome mutation responsible for narcolepsy does not necessarily mean that genes are a definite cause, as it is possible that environmental triggers can play a role. It is more likely that the condition can be explained through a diathesis-stress hypothesis, with a genetic basis requiring specific environmental stressors to be present in order to result in the condition, an interaction between the effects of both nature and nurture. Not all people with the 6th chromosomal mutation on the specific gene develop narcolepsy, while not all narcoleptics have this gene mutation - suggesting factors other than genetics are involved. It would be too reductionist to simplify the condition down to the presence of one gene, ruling out environmental triggers such as stress or sleep deprivation or biological factors such as autoimmune malfunction.

Explanations of Sleepwalking

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Sleepwalking tends to run in families, being 10 times more likely if a first-degree relative has a history of sleepwalking, and having higher concordance rates between monozygotic (genetically identical) than dizygotic (non-identical) twins. This has led to the development of a genetic explanation which suggests that sleepwalking has a genetic basis, being coded for by the presence of a certain gene.

Bassetti provided supporting evidence for the genetic explanation of sleepwalking, gene-testing 16 adult sleepwalkers to find that 50% had a gene found in only 25% of the general population - HLA-DQB1*05, partially responsible for producing HLA immune regulation proteins. The fact that HLA-DQB1*05 gene is twice as common in sleepwalkers as in non-sleepwalkers suggests that it in some way leads to the inhibition of motor control which causes sleepwalking, supporting the genetic hypothesis. However, other factors must be involved in sleepwalking, or else the gene would be present in 100% of sleepwalkers.

Lecendreux et al provide further supporting evidence for the genetic explanation of sleepwalking, finding a concordance rate of 50% in monozygotic twins compared to 17% concordance in dizygotic twins. This supports a genetic basis but not a complete explanation - it cannot be entirely genetic, or else a 100% monozygotic concordance rate would have been found.

Although the genetic explanation is well supported by research evidence, it is an overly reductionist explanation of sleepwalking, being unable to explain the condition's incidence in all sufferers. To reduce a complex syndrome down to the presence of a single gene is an oversimplification - other factors must be important, as only 50% of sleepwalkers have the gene suggested as an explanation, and there is not 100% concordance between monozygotic twins. There is research to support the role for personality factors in sleepwalking - such as Type A personalities being more likely to experience the condition - and the genetic explanation ignores these suggested personality and environmental factors and cannot fully explain sleepwalking as a result.

Additionally, the genetic explanation is overly deterministic, stating that if you possess a certain gene or combination of genes, you'll sleepwalk, while this is not necessarily the case, as 24% of people with the HLC-DQB1*05 gene do not sleepwalk. The existence of these counterexamples suggests that having the gene will not necessarily lead to sleepwalking, challenging the explanation's predictive validity. Cases of crimes comitted while sleepwalking have raised the free will versus determinism debate - in the case of Ken Parkes, who killed his family members while sleepwalking and was later acquitted for murder, the law fell on the side of determinism, claiming that he was not in control of his actions and therefore should not be held responsible.

Identical twins tend to share a very similar environment during childhood and adolescence, so the influence of nature can't be separated from the influence of nurture to determine a direct cause and effect for the genetic basis of sleepwalking. Genetically identical twins may also have shared environmental factors during upbringing such as stress, alcohol and other drug usage and sleep deprivation - due to these multiple confounding variables as aspects of nuture, sleepwalking cannot be pinned down as a result of nature through the use of concordance studies.

The psychodynamic approach explains sleepwalking as a result of repressed unconscious desires to sleep where they slept as a child, and a way of working through unconscious anxieties. During REM sleep the person is paralysed and cannot act out their dreams - once they transition to NREM and can move, this instinctive energy and desire to return to where they slept as a child is expressed through sleepwalking.

However, this explanation lacks face validity - most sleepwalkers are children rather than adults, so a desire to return to the place of childhood sleep would only explain the condition in the small proportion of sufferers that are adults. Similarly, it fails to explain the range of activities carried out by sleepwalkers - cooking food, eating - behaviours completely unrelated to returning to the place of childhood sleep. 

The higher incidence rate of sleepwalking in children than in adults is likely to be explained by the fact that children spend more time in slow wave sleep, when sleepwalking takes place - so there is more opportunity for the behaviour to occur. Also, it could be explained by parts of the brain that inhibit movement in sleep not being fully developed in children - as supported by Hublin et al who found that 20% of children experience sleepwalking compared to 2 % of adults, suggesting that a lack of neurological maturation and development is the cause. 

The psychodynamic explanation is also unfalsifiable and untestable, as the unconscious mind cannot be directly accessed reliably and objectively. The explanation does not treat psychology using the scientific methodology and objectivity that it should, and lacks scientific credibility as a result; unlike the genetic approach which uses quantifiable techniques such as genome sequencing and chromosome analysis to gather objective data.

Cultural Influences on Gender Roles

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Across the many global cultures, there are many similarities and differences between gender roles - the attitudes, behaviours and traits adopted by either sex.  Division of labour between genders is a practice found in most cultures - in the majority of societies, food preparation and child raising are primarily done by women, whereas hunting and resource provision are usually done by men. Similarly, socialisation of genders towards certain traits appears to be consistent across cultures - men are usually socialised towards assertiveness and independence; women towards assertiveness and independence. This suggests that biological factors are more important than cultural factors in determining gender roles.

However, significant differences in gender roles exist between cultures as a result of differing cultural influences. Male superiority in spatial perceptual tasks are only found in tight-knit, sedentary, and is absent or inverted in looser, nomadic societies - Berry et al suggested that these sex differences are a result of sociocultural factors rather than human biology, and suggested that conformity differences are similar in origin - a result of social environment rather than nature, being more pronounced in tight-knit, sedentary societies. This suggests that sex differences in both conformity and spatial perception are due to cultural factors rather than human biology.

Perception of "gender" also varies between cultures, with not all cultures having the binary male/female categorisation typical of the western world. The concept of binary gender categorisation not being a global norm is supported by the example of the "berdache" in Native American tribal Crow culture is a biological male who chooses to be the "wife" of a warrior rather than a warrior, but is not scorned or ridiculed for this. 

Similarities in gender roles between cultures would suggest a natural, genetic and biological component to gender roles, differences would suggest that gender roles are mainly due to nurture, environment and different socialisation processes.

Early research by Mead supports the concept of cultural differences leading to different gender roles. Social groups in the tribes of Papua New Guinea were studied; Mead found that Arapesh men and women were gentle, responsive and cooperative, Mundugamor men and women were violent and aggressive, but Tchambuli showed distinct gender roles - men were emotionally dependent, whereas women were dominant and impersonal. The presence of distinct gender roles in one tribe but not the others suggests that gender differences are a product of society and culture, rather than biology - suggesting that cultural influences are more important than biology in determining gender roles.

Mead's interpretations of her results with respect to gender roles were originally ones of cultural determinism, suggesting that differences between males and females such are a result of social rather biological factors. However, she then changed this view to one of cultural relativism, suggesting that in all three societies, men were more aggressive than women, but these differences were just expressed differently depending on cultural socialisation processes.

Williams and Best provided supporting evidence for cultural similarities in gender stereotyping, suggesting that gender roles are biological and innate rather than a result of socialisation. 2800 participants across 30 different countries categorised adjectives as either "male" or "female" in very similar ways - "dominant" and "aggressive" were almost universally categorised as male, whereas "nurturant" and "deferent" were almost universally categorised as female.


However, several methodological flaws limit the validity of Williams and Best's research. First, the adjectival allocation task was a forced, binary choice - there was no option for "neither" or "both" - the division between male and female stereotypes may have been exaggerated. Secondly, the task related to opinion stereotypes and not behaviour - although gender stereotypes may significantly affect behaviour, this is not demonstrated or measured by the study. Finally, the participants, although from a range of cultures, were all university students - this may be reflected in their values systems, being exposed to similar global influences such as books, films, and higher education. This might explain the apparent high level of cultural similarity of gender stereotyping. 

Whiting and Edwards researched the gender attitudes and behaviours of a variety of global cultures, and found that it was fairly universal for girls to be encouraged into domestic and child-rearing roles, while boys were assigned tasks involving responsibility outside the home such as looking after animals. This suggests that the concept of specific male and female gender roles is highly prevalent cross-culturally, and therefore probably biological in origin, suggesting that biological factors are more important than cultural influence in the development of gender roles.

Much of the evidence for cultural similarities and differences in gender roles comes from studies carried out by western researchers investigating both western and non-western cultures. Research methods such as Williams and Best's adjectival allocation questionnaire to measure cultural gender stereotyping were developed in western cultural contexts and may not be applicable to other cultures' behavioural norms and attitudes - it would be imposing an etic to generalise the results of these questionnaires when used in cultures other than the one they were designed in. Berry et al suggested that most cross-cultural studies carried out by western researchers reflect a western interpretation of human mind and behaviour and view participants from other cultures through this lens - they suggest the use of more indigenous researchers to reduce this bias. 

Evidence that indicates clear cultural differences in gender roles, such as that of Mead and the differences in aggression between men and women in Papuan tribes, supports the nurture side of the nature vs nurture debate, suggesting that gender differences arise due to the influence of culture in the socialisation process. Evidence that indicates cultural similarities in gender roles, such as that of Whiting and Edwards and Williams and best supports nature's influence in gender roles, suggesting that gender roles have evolved to become part of our genetic code due to serving an adaptive evolutionary purpose. Evidence supports both sides of the debate - it is ultimately likely that gender roles are a combination of both genetic factors and socialisation, interactionalist mechanisms between nature and nurture as suggested by the biological approach.

Gender Schema Theory

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Suggested by Martin and Halverson, this is a similar cognitive theory to Kohlberg's theory, emphasising the active role of the child and their thinking in their gender development. However, it differs from Kohlberg's in claiming that basic gender identity is enough for a child to actively seek to observe and imitate gender-appropriate behaviour (Kohlberg had suggested that this only happens at the gender constancy phase, around age 7) , and suggesting that the development of schemas affects later behaviour, especially in terms of memory and selective attention.


GST suggests that gender develops through the formation of schemas - mental clusters of related items which together represent a concept relating to the world. Children learn schemas from information received from their parents, other children, and media such as books and television. This leads to the development of a schema of gender-appropriate behaviour - what toys to play with, what to wear, how to act and so on. Through identifying as a boy or a girl, children join an ingroup, leading them to positively evaluate their own group, and negatively evaluate outgroups (the other sex.) This motivates the child to be like their own group and to avoid the behaviour of the opposite sex, and actively seek information about their ingroup's behaviour, acquiring an ingroup schema.


This leads to the resilience of gender beliefs, where the child holds firm and rigid schemas that are resistant to change, influencing selective attention. They will ignore or misremember information that conflicts with their schemas - for example, if a boy sees a film with a male nurse, the existing schema is not altered - this schematic anomaly is ignored.


Supporting evidence for the early formation of schemas as an aspect of GST comes from a study by Campbell (2000.) A visual preference technique was used to observe babies aged 3, 9 and 18 months, finding in both sexes a preference for observing same-sex babies (more noticeable in boys) - with both genders preferring to watch "male" activities. This supports Martin and Halverson's suggestion that babies develop schemas long before they are able to speak, and that schemas drive selective attention - supporting GST's central tenet of gender ingroup formation leading to selective attention to same-sex ingroup members exhibiting gendered behaviour.


Further supporting evidence for GST comes from Poulin-Dubois et al, who asked 63 Canadian toddlers to choose a doll to carry out a series of tasks typically thought male, female or neutral. Girls aged 24 months chose the "gender-appropriate" doll, which boys did not do until 31 months. This is concordant with Cambell's findings that young children pay selective attention on a sex basis between the age of 24 and 31, far before Kohlberg's suggested age of 7 years.


However, both of these studies found gender differences between boys and girls - in Campbell's study, boys preferred to watch same-sex activities, whereas girls preferred to watch opposite-sex activities; in Poulin-Dubois et al's study, girls and boys developed the ability to identify gendered behaviour at different ages. GST claims that boys and girls develop their gender identity in the same way, so it cannot account for these differences. It would be beta bias to generalise the same developmental mechanisms to both genders, as research evidence suggests that girls and boys develop their schemas in different ways at different times.


Tenenbaum and Leaper criticised GST, claiming that it doesn't explain where schemas originate from, only their role - despite the importance of schemas - and sought to explain this aspect of GST. Carrying out a meta-analysis of 43 studies involving 10'000 participants, they looked for a relationship between the gender schemas of parents, and those of their children. They found an overall correlation of +0.16 - weak, but significant. This indicates that gender schemas are partially learnt through socialisation by parents - this correlation was too significant to be explained by chance.


Tenenbaum and Leaper's research can be considered culturally biased, taking place in predominantly Western and industrialised countries such as North America and Europe, with only 1 of 43 taking place in Asia. Bearing in mind how much parenting practices differ between cultures, it's imposing an etic to suggest that inheriting schemas from parents through socialisation is a global developmental norm - other cultures may place less emphasis as European cultures do on children growing up to be a reflection of their parents' beliefs and values.


GST helps us understand why children's beliefs and attitudes about gender roles and behaviours are so inflexible - children only pay selective attention to information that is consistent with or confirms their schemas.  Therefore, if children see someone engaging in a schema-inconsistent behaviour they'll ignore or forget it.


Compared to the biological approach, this theory heavily supports the role of nurture, suggesting gender is learnt through ingroup schemas and observation/imitation of the same sex; the biological approach supports natural factors such as the influence of hormones, chromosomes and neuroanatomy as being the most important factors in gender development. Both theories have research to support them - with evidence such as the David Reimer case study supporting the role of genetics, and Campbell et al's visual preference technique supporting the role of selective attention. There is evidence for both sides of the debate, leading to the increasing popularity of the interactionalist biosocial approach, suggesting that gender is a result of both biology and environment.


This approach is based around social learning from members of same-sex ingroups, suggesting that we learn gender appropriate behaviour through the socialisation process. Kohlberg's cognitive developmental approach suggests a similar method - we pass through developmental phases of how we understand gender, but only at the stage of gender constancy experienced after the age of 7, do we pay selective attention to gendered behaviour. Although the approaches are similar, they differ strongly in this key factor, with Martin and Halverson suggesting that we have the cognitive ability to observe and imitate gendered behaviour from between two and three years old.

Social Influences on Gender

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Gender roles are learned through observation and imitation of live and symbolic models - for example, parents, teachers, peers and the media, who convey social messages about the importance of gender role-appropriate behaviour. We observe their examples of gender-appropriate behaviour and then seek to imitate them in the social learning process. Based on learning theory principles of operant conditioning, children are seen as being positively reinforced for behaving in gender-appropriate ways.

Socialising agents model examples of appropriate and inappropriate behaviour, and also the consequences of conforming or not conforming to gender norms.

Through observational learning, children acquire knowledge regarding gender roles without actually ‘doing’ anything; children observe gender role models being reinforced or punished for gender-appropriate and gender-inappropriate behaviour (vicarious reinforcement) and will imitate behaviours that they saw being reinforced and not imitate those they saw being punished. SLT therefore explains the acquisition of gender role stereotypes in this manner.

Gender appropriate behaviour is reinforced by parents giving praise and toys. Fathers have been shown to reinforce gender-appropriate behaviour more than mothers (especially in sons)

Supporting evidence comes from Lytton & Romney (1991), who found that parents reinforced with praise and attention stereotypical gender behaviours in both boys and girls – for example, what activities they participated in – suggesting that social environmental factors are important in determining gender behaviour. However, children were also raised similarly in many ways, suggesting that reinforcement alone cannot account for the development of gender behaviours.

Further supporting evidence comes from Fagot & Leinbach (1995), who compared children raised in ‘traditional’ families, where dad went to work and mum cared for children, with children raised in ‘alternative’ families, where mum and dad shared child care. At age 4, children were given gender-labelling tasks as a means of testing gender schemas. The ‘traditional’ family children displayed more gender role stereotyping and use gender labels earlier, suggesting that parents do act as gender role models for their children.

TV, cinemas, magazines, music play a role in the acquisition, shaping and maintenance of gender roles. Males tend to be more represented on TV and tend to be in higher-status roles. Males and females portrayed in gender stereotypical ways. Media is invasive and persistent.

Supporting evidence for the role of the media comes from Pierce (1993) who conducted a content analysis of teenage girls’ magazines. Girls tended to be portrayed as weak and reliant on others, with a focus on being in a relationship rather than having independent aspirations, demonstrating the influence of the media in establishing gender attitudes and behaviours, and supporting social learning theory’s explanation.

Peers have a strong influence, especially when children are slightly older. Children show preferences for same-gender playmates and segregate into same-sex groups. Peers are intolerant of gender-inappropriate behaviour, regulating one another! Young children’s gender role stereotypes are very rigid, but become less so as children mature.

Supporting the influence of peers in gender development, Archer & Lloyd reported that 3-year-old children who played the opposite sex’s games were ridiculed by their peers and ostracised, supporting the idea that peers police gender roles. This supports the idea that children develop an idea of what constitutes gender-appropriate behaviour from how their peers react to behaviour, supporting the role of peers in the social learning process.

Challenging the idea that gendered behaviour is directly learnt from peers, Lamb & Roopnarine observed preschool children at play and found that when male-type behaviour was reinforced in girls the behaviour continued for a shorter time than when male-type behaviour was reinforced in boys. This suggests that peer reinforcement mainly acts as a reminder, rather than as a way of learning gender appropriate behaviour – the children had already learnt the behaviours from their parents.

Compared to other explanations such as the evolutionary and the biological approaches, theories of social influences on gender fall firmly on the nurture side of the nature-nurture debate, explaining gendered behaviour as a direct result of learning processes – mainly through social learning from parents, peers and the media. This sharply opposes the biological approach, for example, which claims that gender development results from the influences of hormones, genetics and neuroanatomy – strongly backing the role of nature in the debate. Both explanations have significant research evidence to support them – for example, the case study of David Reimer for the biological approach, the research of Lytton and Romney for the influence of society. This has led to the increasing popularity of the interactionalist biosocial approach, which explains gender development as an interaction between environmental and biological processes.

Theories of social influence are primarily based around the learning approach, ignoring other factors such as cognitions (as suggested by Kohlberg’s cognitive developmental approach), neuroanatomy and behaviour-influencing hormones such as testosterone (as suggested by the biological approach) and genetics over the course of our evolutionary history (as suggested by the evolutionary approach.) With a significant level of research support, social influence theory can be considered strong in its own right, but fails to account for many other factors shown to affect gender, being reductionist in its attempt to simplify such a complex area such as gender development into the result of simple behavioural learning processes.

Research into the effects of social influence on gender has important real-world application in challenging certain regressive or outdated gender stereotypes in society – changing social norms and expectations through the portrayal of non-traditional gender stereotypes in the media. For example, Pingree (1978) found that stereotyping was reduced when children were shown advertisements with women in non-traditional gender roles, leading to pressure on programme makers to use this information to challenge attitudes. However, not all research supports the effectiveness of this technique – Pingree found that pre-adolescent boys experienced stronger stereotypes after being presented with examples of non-traditional gender roles, perhaps a backlash which occurs due to boys of this age wanting to take a view counter to that of views held by adults. Similarly, this conflicts with gender schema theory’s suggestion that information inconsistent with our rigid gender schemas is misremembered or ignored.

Biosocial Theories of Gender Development

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The biosocial approach takes a social constructionist approach to gender development. arguing that concepts of gender are artificial and a result of social norms rather than being an innate biological concept.


Money and Ehrhardt's biosocial theory suggests that gender development is the result of interactions between biological and sociocultural factors. Biological factors include chromosomes (XX for a female, XY for a male), and the neurodevelopmental and physical effects of prenatal hormones such as testosterone. Sociocultural factors include early socialisation based on cultural responses to biological stereotyping - this stereotyping can include the labelling of a child as a boy or a girl by parents and peers. The biological factors that lead to parental labelling as "girl" or "boy" then lead to different environments and reactions from others, which lead to gender development as boys and girls are socialised in different ways - leading to gender role identity and sexual orientation.


Eagly and Wood's social role theory suggests that psychological gender differences are a result of roles which men and women are assigned, which were a result of physical differences in our evolutionary history. For example, in our history, men were assigned the role of hunter due to their larger size - this lead to psychological, gendered characteristics such as aggression and impulsivity. Females were assigned the role of homemakers, which lead to psychological, gendered characteristics such as being empathetic and nurturing. While evolutionary theory states that selection pressures lead to physical and psychological differences which determine gender roles, social role theory suggests that physical differences lead to differently assigned gender roles, which lead to psychological differences as an aspect of gender.


Supporting evidence for the biosocial theory of gender development comes from Smith and Lloyd's 1978 study. Babies were dressed in non-gender specific clothes, then labelled with a male or female name. It was found that people would play with them in different ways according to their gender label, with boys being treated in a more physical manner. This supports biosocial theory's suggestion that initial parental gender labels (which participants believed was based on biology) affect how the child is treated and the socialisation process, providing evidence for the hypothesis that biological labels lead to different environments and social interactions, influencing gender development.


Schaffer (2004) provides further supporting evidence for the biosocial theory. A sample of 200 adults was showed a video of a 9-month-old baby, named "David" or "Dana", playing with toys and responding to stimuli. The adult labelled the baby's behaviour and emotions in gender typical ways according to whether they believed it male or female. Again, this shows that the gender identity label affects how others in society react to and stereotype the child, causing different gender development. This supports the biosocial hypothesis that biological labels as "male" or "female" lead to differential treatment from society, leading to different socialisation processes and gender development.


However, conflicting evidence for the biosocial approach comes from a study by Luxen (2007), finding sex differences in toy preferences in very young children even before socialisation can take place. This suggests that innate gender differences exist before the socialisation process - implying that gender differences are a result of pure biology rather than a reaction between biology and social environment. This challenges the approach's claim that gender role and identity is a result of socialisation based on biological sex, suggesting that nature is far more important than nurture.


The case study of David Reimer provides further conflicting evidence for the biosocial approach to gender development. Regardless of the way his parents attempted to socialise him to be psychologically female, adopting feminine traits and gender roles, upon learning his true genetic sex he rejected these attempts at socialisation and began to identify as male despite opposite parental labelling. The fact that a biological male who was socialised through toys, clothes, name and social environment as female still ultimately identified as male suggests that biology is a much more powerful force than society is in gender development, challenging the biosocial approach's claim of biological and social interactions being responsible.


The biosocial approach theoretically combines both biological and environmental factors to explain gender development, and could therefore be considered more holistic than approaches such as the evolutionary or cognitive-developmental approaches, which explain development in terms of either biology or thought processes, not both. This approach does not reduce gender development to a single, exclusive account of human behaviour. However, the majority of research points to either biological or social aspects as being the determining factor in gender development - not both! For example, Luxen's research and the case study of David Reimer firmly suggests that biology is more important than environment - no studies show an equal importance of biology and society, suggesting that a holistic explanation of gender is inaccurate.


However, in contrast to other theories such as the biological and evolutionary approaches and Kohlberg's cognitive developmental model, the biosocial theory does not explicitly favour either side of the nature-nurture debate. Instead, it assigns a role to elements of nature, through its biological sex component, and elements of nurture, through the importance of socialisation in the development of gendered behaviour. It is an interactionalist approach, unlike other approaches which could potentially oversimplify gender by explaining it as purely a result of neuroanatomy and genetics, or of cognitive processes, or of social learning.


Social Role Theory has an important real world application in lending scientific credibility towards egalitarian philosophies such as feminism, working to bring about a state of greater gender equality. Whilst approaches such as the evolutionary theory have been regarded as a force against gender equality, stating that sex differences are innate and cannot be changed by altering social contexts, the social role approach emphasises the flexibility of gender roles and behaviour. This gives it high ethical appeal because sex roles are perceived as a result of social and biological factors rather than purely biological, therefore more flexible, offering people opportunities to create and develop aspects of the self which may otherwise be constrained by typical ideas of masculinity and femininity.

Kohlberg's Cognitive Developmental Theory of Gender

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Blue: AO2 - Research
Red: AO3 - Evaluative points/IDAs

Influenced by earlier theories of cognitive development that saw children as actively progressing through developmental stages, Kohlberg’s theory of gender development works on three principles: maturation (children can only progress to the next stage with adequate cognitive ability and maturity), universality (all children go through the same stages, albeit at different times) and socialisation (children are more likely to observe and imitate same-sex role models.) Kohlberg suggests that children understand gender differently at different ages, actively developing an understanding of gender from the environment, with three different stages.

 

Gender identity – around age 2 to 3 ½, children understand the concept of their own sex, using the labels “boy” and “girl” in reference to themselves or others, but do not understand that gender is stable for life, and have very little understanding of what it means.

 

Gender stability – around age 3 ½, the child realises that their sex will not change, knowing that they will grow up to be a “mummy” or a “daddy”. However, they are still easily misled by superficial appearances – believing that a woman cutting her hair will turn her into a man.

 

Gender constancy – between the ages 4 ½ to 7, the child realises that gender is constant – people stay the same despite superficial appearance changes. This final stage is based on Piaget’s principle of “conservation” – the ability to know that things remain the same even after changes in appearance.

 

Thompson (1975) found that by 2 year, children given pictures of boys and girls could select same-sex pictures, demonstrating that children could self-label and identify the gender of others. By 3 years, 90% showed gender identity, compared to only 76% of 2 year olds, showing the developmental nature of the concept. Supports the age ranges  that Kohlberg suggested for each stage – Kohlberg suggested that children develop gender identity aged 2 ½, and this is supported by the vast majority of children having reached this stage by 3 years old – far more than had reached this stage at 2 years.

 

McConaghy (1979) found that if a doll was dressed in transparent clothing so its genitals were visible, children of 3 to 5 years judged its gender by its clothes, not its genitals, supporting the idea of children of this age using superficial physical indicators to determine gender. This supports Kohlberg’s suggestion that until age 4 ½ to 7, most children are in a stage of gender stability – they realise that gender does not change, but are still misled by superficial appearances such as clothing.

 

Rabban (1950) found that children’s thinking changes as they age. 3 year olds demonstrated gender identity but don’t know what gender they will grow into. By age 5, 97% demonstrated gender stability. This supports the ages Kohlberg suggested at which a child progresses to the stage of gender stability – around 3 ½ to 4 ½, as well as the concept of gender development as being due to increasingly sophisticated cognitive processes with age.

Kohlberg’s theory is more holistic than certain explanations for gender development such as the evolutionary approach (explaining the social prevalence of gendered behaviour as purely a result of our evolutionary history), as Kohlberg’s theory takes into account both cognitive factors (developmental stages requiring the cognitive ability to progress past them) and social factors (observing and imitating same-sex models as a form of social learning. However, it can be considered reductionist through ignoring certain aspects of human biology that have shown to be responsible for gender development – in the case study of David Reimer, genetic biological sex was the deciding factor in his final gender identity despite overwhelming social factors aiming to change this.

 

This theory may be gender biased, as some critics claim that females are being judged using a male standard. This is largely because Kohlberg's original research, which he used as a basis for this model, was done only on males. However, gender development happens differently in males than it does in females, for example – the greater willingness of girls to participate in masculine activities than boys to participate in feminine activities.  Slaby and Frey’s research evidence supports the suggestion that Kohlberg’s theory is gender biased – the gender constant girls observed the opposite sex model more than the same sex model, while the gender constant boys did not, suggesting that it is beta bias to assume equivalency of development between sexes.

 

While Kohlberg’s theory of gender development suggests that gender development is primarily a cognitive process, albeit with social learning from same-sex models, other theories challenge this, suggesting other primary factors that influence gender development. For example, the biological approach suggests that hormones and genes are the two most important factors in gender development – two factors of which Kohlberg’s theory makes no mention, suggesting that gender behaviour and identity are determined by thought processes. Additionally, the social approach to gender explains it as a result of social reinforcement processes – seeing the child as a passive product of the society around it rather than the active figure that Kohlberg suggests – these theories are not completely mutually compatible, and vary hugely in their approach to how we develop gender.

 

Ethics in Psychological Research

You will often be asked to identify ethical issues in a given study and asked how they can be addressed - remember to refer to the source to look at possible issues in the methodology such as deception and failure to protect participants from harm.


Black: AO1 - Description of an ethical issue.
Red: AO2/3 - Way of dealing with an ethical issue.


Informed consent – participants should agree to be in an experiment after being made aware of the aim of the experiment and their role in it. Before giving their consent, they must be made aware how data are collected, what exactly they’re doing in the experiment, and, in an independent groups design, they must be made aware what those in the other condition are doing. The research must fully explain the experiment's duration and methodology, as well as the expected benefits to society of the research and any potential risks and discomforts to the participant.

Deception - participants should not be deceived as to their role in the experiment. This includes active deception through lying to them,  and passive deception through just withholding information and not being outright with everything they’re entitled to be told.

However, in some areas of research it is not always possible to get informed consent, and necessary to deceive participants - in certain studies into social influence, the participant must be unaware that they are in a study, so that demand characteristics don't invalidate the results. In this scenario, there are other ways in which consent can be obtained:

• Prior general consent - asking for consent beforehand when explaining the general area of research, asking if they feel comfortable and consent to taking part to research in that area and possibly being deceived - without mentioning a specific form of deception.

• Presumptive consent - take another sample from the target population and ask them if they'd consent to the study - if they all would, presume that your experimental sample would too.

• Colleague consent - ask other professionals if they thought participants would give informed consent to the study - if they think so, carry out the research presuming consent from this.

• Ethics committees - talk a committee of psychologists and non-psychologists through your methodology, outlining any issues that may arise, the purpose and procedure of the research, and seek approval from them before seeking general consent.

Debriefing - after the study has concluded, address any questions and concerns participants may have towards the purpose and procedure of the research, reassure participants that their results will be kept confidential, remind them of their right to withdraw and remind them of everything covered under informed consent regulations.

Confidentiality – the data should not allow readers to identify individual participants – all names, addresses, dates of birth and other identifying information should be removed so that the remaining data is completely anonymous.

Right to withdraw – participants should be told at the start of the experiment that they can withdraw whenever they want to, their results will not be published, and they can take any money that they are entitled to. They must be reminded of this right throughout, at the end of the experiment, and during the debriefing. Participants should not be pressured to continue if the study is causing them distress, as was the case in Milgram's famous study of obedience.


Protection: The participant should not experience any more harm or distress over the course of the study than they might reasonably expect carrying out day-to-day activities. The researchers should ensure that the participants do not leave the experiment in a worse psychological or physical state than when they started.

Explanations of Gender Dysphoria

Black: AO1 - Description
Blue: AO2 - Research
Red: AO3 - Evaluative points/IDAs

A psychosocial explanation, mental illness theory suggests that gender dysphoria is related to mental illness, which is in turn a result of childhood trauma or maladaptive upbringing. Coates et al (1991) carried out a case study of a boy who developed gender dysphoria, claiming that this was his response to his mother’s post-abortion depression. The trauma occurred when the boy was three – a time when children are particularly sensitive to gender issues – and Coates et al suggested that the trauma led to a cross-gender fantasy as a means of resolving anxiety.

Cole et al (1997) studied 435 individuals experiencing gender dysphoria and reported that the range of psychiatric conditions displayed was no greater than found in a non-dysphoric control group; challenging mental illness theory’s suggestion that gender dysphoria is related to trauma or psychological pathology.

Irregularities in mother-son relationship are another factor suggested to contribute to the development of gender dysphoria. Stoller (1975) proposed that GID results from distorted parental attitudes – in clinical interviews with individuals diagnosed with GID, they displayed overly and atypically close mother-son relationships; he suggested that this led to greater female identification and a confused gender identity.

Zucker et al (1996) studied boys with concerns about gender identity and their mothers. Of the boys who were eventually diagnosed with GID, 64% were also diagnosed with separation anxiety disorder, compared to 38% in the boys with subclinical GID symptoms. This supports Stoller’s suggestion of abnormal maternal attachment as a factor in gender dysphoria, but can only explain MtF (Male to Female) transsexuality – it does not suggest an explanation for FtM.

A biological theory of gender dysphoria, the brain-sex theory suggests that male and female brains are structurally different, and the brains of transsexuals do not match their genetic sex. A region of the brain called the BSTc, located in the thalamus, is twice as large in heterosexual men as in heterosexual women, and contains twice the number of neurons – and in transsexuals, BSTc size correlates with psychological gender, rather than biological sex, suggesting a mismatch between the brains and biological sexes of transsexuals.

Two research studies support this theory: Zhou et al (1995) and Krujiver et al (2000) found that the number of neurons in the BSTc of MtF transsexuals was similar to those of biological females, while the number of neurons in the BSTc of FtM transsexuals was similar to those of biological males. This supports the theory’s explanation of gender dysphoria as having a mismatch between chromosomal sex and psychological gender.

However, Chung et al (2002) provided powerful conflicting evidence for this theory – finding that the differences in BSTc volume between males and females do not emerge until adulthood – whereas most transsexuals experience their feelings of gender dysphoria to begin in early childhood. This suggests that the differences in the BSTc reported by Zhou and Krujiver could not be the cause for gender dysphoria, but rather a possible effect.

Additionally, Hulshoff Pol et al (2006) found that transgender hormone therapy does affect the size of the BSTc, and the individuals in Zhou and Krujiver’s studies had been receiving hormone therapy. Therefore, it may be that the hormones caused the finding in transsexuals that their brain sex was closer to their gender identity than their biological sex, challenging the validity of the supporting evidence.

There is other evidence to support the theory of gender dysphoria as a result of neuroanatomical abnormalities – Rametti et al (2011) studied the brains of FtM transsexuals before they started transgender hormone therapy, and found amounts of white matter more closely resembling individuals of their gender identity than of their biological sex.

Environmental effects have also been suggested as a biological factor that can contribute to the development of gender dysphoria – environmental pollutants such as DDT contain oestrogens which may mean that males are exposed to abnormally high levels of female hormones during gestation, causing a mismatch between genetic sex and hormone-influenced gender identity.

A study by Vreugdenhil et al (2002) supports this explanation of gender dysphoria, finding that boys born to mothers exposed to dioxins, a chemical class promoting oestrogen production, displayed more feminised play than a control group, suggesting that environmental chemical factors can lead to a mismatch between gender identity and genetic sex.

Blanchard proposed two distinct subcategories of transsexuality: “homosexual transsexuals”, who wish to change biological sex because they are attracted to their current biological sex (e.g. a homosexual male who wishes to transition to female) and “non-homosexual transsexuals” who wish to change sex because they are “autogynephilic” – attracted to the idea of themselves as the other sex. These groups are so different that it is impossible to presume that the dysphoria has the same root cause – suggesting that there are different explanations for different types of gender dysphoria.

There are ethical issues with research into dysphoria, namely that it is an extremely socially sensitive area of research, with potentially huge social consequences for individuals represented by the research. For example, if a biological cause is identified this might help others to become more accepting of transsexuals, understanding that it is not their fault, or it may cause individuals born with the biological cause present to be harmed or neglected, because it might be incorrectly assumed that future transsexualism is inevitable. Evidence from research suggests that a simple deterministic cause and effect relationship is unlikely – either way, the outcome has important social consequences for sufferers of gender dysphoria.

There is important real-world application of these explanations of gender dysphoria. Colapinto (2000) reports that 1 in 2000 people are born with anomalous genitals that do not match their genetic sex, and research into gender dysphoria is very important in determining the effect of such anomalies and determining the best solutions. Societies such as the “Organisation Intersex International” argue that our society must place less emphasis on biological sex and recognise gender characteristics as a social construction to allow intersex individuals to determine their own gender identity – psychological research is important to supply research evidence to support or challenge such arguments.

Cole (1997) found that MtF transsexuals scored much differently in the masculinity-femininity scale of the MMPI to FtM transsexuals or a control group without GID. Additionally, the incidence of MtF gender dysphoria has been found to be much higher than FtM gender dysphoria. These differences in the way the sexes experience gender dysphoria suggests that it is beta gender bias and an oversimplification to assume equivalence of origin in both genders – current theories don’t explain why biological males experience GID differently and more often than biological females; a more accurate theory should explain these differences.

Psychological Reports and Peer Review

Black - AO1 - Description
Red - AO2/3 - Evaluation


When psychological journal articles are published, they have an abstract - a brief summary of the research, outlining the aim, hypothesis, method, results and conclusion. This helps the reader decide whether the research is relevant to what they're trying to find out, and whether they should read on.


Psychological research has practical applications and practical implications. Practical implications are what we can infer and interpret from the results of the research - what it adds to our understanding of a field of psychology. Practical applications are how the findings and conclusions can be used in a real-life scenario - ways in which the research can beneficially change how people behave.

Peer Review

The peer review process involves other knowledgeable psychologists studying similar topics reviewing the researcher, assessing the credibility, the legitimacy and the accuracy of the research. This serves several purposes.

• To verify the academic integrity of the researcher - that they aren't plagiarising other academics, and are giving appropriate credit to the authors of their sources.
• To check that appropriate statistical tests have been used for the level of the data and experimental design chosen.
• To check that legitimate, valid conclusions and interpretations have been drawn from the results - ascertaining that results have not been misinterpreted.
• To make sure that findings are novel and contribute to a broader body of knowledge in its field - rather than a simple replication of research already carried out in the same social and historical context.
• To make sure that the researcher is not making unjustified claims about the importance and social significance of their research.
• To make sure that any ethical issues that arose over the course of the research were handled appropriately, and that the BPS ethical guidelines were adequately followed.
• To ensure that all research is reviewed by fellow experts, maintaining academic standards of research - so poor quality research is not published in reputable journals.

However, there are several problems and issues with the process of peer review.

• Peer review is time consuming and expensive - it can take months or years for research to be reviewed and published, delaying the publication of important findings.
• Reviewers usually work in the same field as the author of the research - there could be an incentive to delay the publication of their rivals' important findings, especially when financial research grants are at stake.
• There is a bias towards more well-respected and prestigious institutions and researchers - papers from these are more likely to be approved simply due to the renown of the institution or individual, even if they are of no higher standard of academic integrity than research from a less prestigious one.
• There is a tendency to favour the scientific status quo - research which supports the commonly accepted scientific theories and approaches at the time of its review is more likely to be considered valid and to be approved than research which challenges the established scientific consensus. Peer review may slow down the revolution from one scientific paradigm to another.
• Review may be biased through the reviewer's personal, subjective views differing from those expressed in the submitted report - e.g, if the reviewer is convinced that intelligence is highly genetic, they may look unfavourably upon research that suggests a role for environmental factors in intelligence, and reject research papers that suggest this.
• The "file drawer phenomenon" - peer review tends to favour positive results that support the hypothesis rather than those which challenge the hypothesis or support a null. Many negative or null findings are simply not published - left in the researcher's file drawer. This biases our understanding of a topic towards supporting theories that might not consistently be supported by research, but only the supporting evidence is published.

Inferential and Descriptive Statistics, Data Levels, Significance and p-Values

If unsure on the types of hypothesis and what they predict, I'd suggest reading this post: http://samsa2psych.blogspot.co.uk/2016/02/hypotheses-sampling-and-design.html before trying to get your head around inferential statistics!

Descriptive Statistics

Descriptive statistics help us draw conclusions from the results of a set of data, giving a typical score. They are divided into measures of central tendency and measures of dispersion.


Measures of central tendency such as the mean (add all the values up, divide by number of values), median (arrange the values in numerical order, take the one in the middle) and mode (most common value.)


Measures of dispersion give a spread of results, suggesting the consistency of the values that make up our results. These include range (difference between highest and lowest value), interquartile range, and standard deviation.

Inferential Statistics

Inferential statistics tell us the probability of differences in our results being due to direct IV manipulation (an alternative hypothesis = a causal link between the IV and the DV) rather than through chance or extraneous variables. The inferential test used depends on the experimental design and the level of data collected - data can be classified as one of three types.


Nominal level data - the most basic form, named categories. We know little other than what category a result fits into. For example, measuring height using nominal level data could be done through two categories: "above 6ft" and "below 6ft"


Ordinal level data (rank measurement)- data is ordered from highest to lowest value. We don't know the gaps and boundaries between rankings (parameters) but we know what order results come in. For example, measuring height using ordinal level data would be done by arranging results in order of highest to lowest value.


Likert scales are an example of ordinal data - a participant is given a statement and asked how much they agree or disagree with it - a response of "4" means that they agree more than a response of "2" - but we do not know how much more - it lacks parameters.


In Milgram's study of conformity, he measured the maximum voltage electric shock the participants would give to a confederate - but this data is only "at least ordinal" - administering 200V did not necessarily make participants twice as conforming as administering 100V, or half as conforming as administering 400V.


Interval level data - we know that gaps and boundaries between data, and the parameters are scientifically equivalent. For example, measuring height in metres and centimetres. Ratio level data is a type of interval data starting at 0 - for example, height.


Metrics such as words remembered from a list are also not necessarily interval level data - it is unclear how much each word remembered represents a better memory - someone who can remember 10 words does not necessarily have only twice as good a memory as someone who can remember 5.


In cases such as the above, we say the data is at least ordinal level, and treat it accordingly - when it is ambiguous as to whether the data is ordinal or interval.-

Types of Inferential Statistical Test

Once we have established the level of the data collected, we select an appropriate test to calculate the statistical significance of the results.


                Repeated Measures/Matched Pairs     Independent Groups     Correlational




Nominal    Binomial Sign Test                           Chi-Squared              Chi-Squared




Ordinal    Wilcoxon Signed Ranks            Mann-Whitney U          Spearman's RHO        



Interval     Related t-Test                                Unrelated t-Test               Pearson's










These tests give us a p-value, a measure of the probability that our results are due to chance/EVs rather than IV manipulation (validating the alternative hypothesis). Our calculated p-values are compared to a number ranging from 0 to 1.0 to judge its significance. (The "critical value")


p ≤ 0.10 means that the probability that results are due to chance (p) is less than or equal to 0.1 (10%) - meaning that the probability of the results being due to IV manipulation is greater than or equal to 90% - if our p-value is less than 0.10, we can be 90% certain that the alternative hypothesis is valid.


Generally, in psychology, we measure significance by p ≤ 0.05 - p is less than 5%, meaning that for results to be statistically significant, we must be 95% sure that they are due to IV manipulation, not chance. The value that p must be less than is our "critical value" - required for significance. This is a fairly stringent measurement of significance - although sometimes p ≤ 0.01 is used - 99%.


A type 1 error occurs when we are led to incorrectly thinking that there is a significant difference, and accepting our alternative hypothesis, when in fact there is not a significant difference, and our hypothesis is incorrect. We incorrectly reject a null hypothesis. This is done by setting the required significance value too high (e.g. p ≤ 0.2 means 20% chance that results are due to chance is still counted as statistically significant) - and having a p-value lower than this significance level. The more stringent our level of significance, the less chance of making a type 1 error. At p ≤ 0.01, the chance of a type 1 error is 1% or less.


A type 2 error occurs when we are led to incorrectly believing that there is no significant difference where one does actually exist, and rejecting our alternative hypothesis despite it being valid and correct. We incorrectly accept a null hypothesis. This is done by setting the required significance value too low (e.g. p ≤ 0.01 means only 1%  or less chance that results are due are chance are counted as significant - 98.9 % chance of alternative hypothesis being correct is rejected as insignificant - 99% is required for significance) and having a p-value higher than the significance level. The more stringent our level of significance, the greater chance of making a type 2 error.


Answering questions on this, refer to three points in your answer - the calculated p value, the value required to indicate significance (critical value), and the degree of significance - if, to be significant, the critical value is 0.05, then we have a fairly high degree of significance when p ≤ 0.05 - the probability that our results are due to IV manipulation rather than chance or EVs is greater than or equal to 95%. This would be phrased by writing "this result is significant at the p≤0.05 level"


Some inferential statistical tests have significance values work in the opposite way, with the calculated value needing to be greater than the critical value for significance. This will be told to you in the question if this happens.

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.