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• With reference to relevant research studies, eThe first paper I read, titled “The impact of ingroup favoritism on self-esteem: A normative perspective” regards the need for positive self-esteem that people have, and the effect that ingroup favoritism has on one’s self esteem. This research was conducted by Vincenzo Iacoviello, Jacques Berent, Natasha Stine Frederic, and Andrea Pereira. The researchers argue that “ingroup favoritism increases self-esteem to the extent that such behavior is congruent with one’s ingroup norms.
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  The researchers first discuss the Social Identity Theory, a prominent social psychology theory that hypothesizes that “people have a basic motivation to enhance or maintain self-esteem, which can be satisfied by achieving or maintaining a positive social identity”. This theory led to two corollaries, one stating that people with low self-esteem “should display higher levels of ingroup favoritism” than people with high self-esteem. The second corollary states that people that favor the ingroup have heightened self-esteem. The paper dwells on the second corollary, stating that when the ingroup has a set of social norms, conformity and favoritism to the ingroup norms causes members to increase their senses of belonginess. The researchers argue that instead of the classic perspective, which states that being in a good group yields self-esteem, the normative perspective suggests that being a good group member yields self-esteem.

  To study the normative perspective, the researchers made three studies. The first directly manipulated the ingroups norms, specifically whether they were pro- or anti-discriminatory, and hypothesized that the effects if ingroup favoritism were contingent on the normativity of such behavior (Hypothesis 1). The second study dwelt on whether the ingroup norm was descriptive or injunctive, and they hypothesized that an injunctive norm would have more of an effect on self-esteem (Hypothesis 2). The third study looked at interpersonal differences, and hypothesized that as a person conformed more to the norm, the more likely it would influence self-esteem (Hypothesis 3).

  To conduct Study 1, the researcher drew American participants from Amazon’s Mechanical Turk. They were randomly assigned to one of four groups, divided by ingroup or no ingroup favoritism, and academia or sports social context. To create the discrimination norm, the researchers told the participants that “a transnational American-Canadian institution would provide funds” to the US (ingroup) and Canada (outgroup). The study manipulated whether the US received more funds, the same funds, or less funds than Canada, and then gave the participants a bogus response on how the funds would be allocated. Participants then took a self-esteem test. Study 1 found that the academia group displayed increased self-esteem to ingroup favoritism, while the sports group did not. Study 1 gave evidence to Hypothesis 1.

  Study 2 looked to further confirm this, and manipulated whether the participants had or did not have ingroup favoritism, if they had pro- or anti-discriminatory norm, and if they had descriptive or injunctive norm. Study 2 followed a similar process as Study 1, but before getting the bogus response, they were told how the rest of their group responded. They then took the self-esteem test. Study 2’s results showed that self-esteem “depends on them feeling they are good group members and comply to prescriptive norms regarding intergroup discrimination”.

  Study 3 looked at how conformity influenced the normative perspective. They took a group of participants from Geneva and tested how much each valued conformity. They then told them that Geneva (ingroup) and Basel (outgroup) would be receiving funds for traffic flow. They went through a similar process to measure their ingroup favoritism and self-esteem as in Studies 1 and 2. Study 3 found that self-esteem increased with ingroup favoritism if the participant valued conformity. Overall, this entire study largely supports a normative perspective on the impact of ingroup favoritism on self-esteem.

  The second article I read was titled “Being Your Actual or Ideal Self? What It Means to Feel Authentic in a Relationship”. This research was conducted by Muping Gan and Serena Chen. The research intends to explain what exactly makes a relationship feel authentic or genuine. It evaluates the current hypotheses on what results in an authentic relationship; if being your actual self, ideal self, or both, makes a relationship authentic. This research includes five studies.

  The pilot study looked at common beliefs on what made a relationship genuine. It asked participants to rate how they thought relationships were authentic to them – whether being their ideal or real self, or both, made relationships more authentic. They reported if they were closer to their partner when they idealized themselves or acted themselves. 70% of participants reported that they felt closer to their partner when they acted their actual selves. However, the importance relationship-ideal had a high mean overlap, showing that it had some basis.

  The first study looked at “what predicts relational authenticity”. Participants were surveyed and asked to “described their actual, ideal and relational selves and then rated their similarity”. 272 participants were given the survey, and were asked questions like “How similar or different is who you are and/or how you act with your romantic partner from who you would ideally like to be in general?”. Participants also measured how authentic their relationships were on a scale from 1 to 9. All questions were randomized for each participant. Study 1 ultimately showed that relational-ideal overlap contributed to a more authentic relationship than actual-relational authenticity.

  Study 2 manipulated “whether participants perceived high, low, or baseline levels of relational-ideal overlap and measured their state relational authenticity”. Participants were randomly assigned to high, low or control relational-ideal overlap conditions. They were given questions specific to their group, and then they were all given a survey to see their current perception of their relationship. Study 2 found that the low- overlap conditioned group reported less relational-ideal overlap compared to other groups. The high-overlap conditioned group, however, did not yield high relationship-ideal overlap, suggesting a high baseline.

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  Study 3 looked at the different effects relational-ideal or actual-relational overlap had on relationship authenticity. This study crossed the low- versus high-overlap manipulation with the type of overlap, actual or ideal. Participants were placed in one of four groups, and reported their answers to questions regarding how they acted in their relationship, how they normally act, and how authentic their relationship seemed. This study found that the more a person acts like their ideal self, the more authentic the relationship seemed.

  Study 4 looked at whether authenticity in relationships resulted from relational self-matching ideal self or having one’s self-aspect match their ideal-self. This study made four groups, crossing low vs high overlap with type of overlap (actual-ideal vs relational-ideal). Participants were randomly assigned to each group and put under the groups conditions. They were then asked questions regarding how they wanted to act and how they really acted, as well as how they acted and wanted to act in relationships. Then they answered questions on relationship authenticity. Results ultimately showed that high relational-ideal overlap led to higher relationship authenticity, and that acting as your ideal self in general yielded no effect on relationship authenticity.

  This research helps support the hypothesis that matching your relationship-self to your ideal-self helped lead to a more authentic relationship. This research aimed to add more evidence to this claim. The studies ultimately showed people’s perception in the pilot study did not align with what the study showed.

  The third article I read was titled “You are what you eat: An empirical investigation go the relationship between spicy food and aggressive cognition”. This research was conducted by Rishtee K. Batra, Tanuka Ghoshal, and Rajagopal Raghunathan. This research wanted to empirically test the popular phrase “you are what you eat”. The research was organized into three studies. Before the studies, people were asked what food would best prepare them for a meeting with a confrontational colleague. The answers were “hot and spicy”, “neither hot and spicy nor bland and mild”, or “bland and mild”. The result from this survey suggests that the common belief is that spicy food leads more aggressive actions. Participants were then a part of the studies.

  Study 1 was a “preliminary test for the association between spicy food and aggression”. They looked at self-reported consumption of spicy food and self-reported aggression levels. To keep the participants from knowing the study had to do with aggression, they paired the questions with attributes unrelated to aggression. The results to this study showed that those that ate spicier food reported higher levels of aggressive behavior. This result is limited, however, because it relies on measured, not manipulated, data, it isn’t completely indicative that people who eat spicy food are more aggressive.

  Study 2 looked to further research the spicy food – aggression relationship. This experiment manipulated the intake of spicy food and looked at the aggression response. Participants were randomly assigned to a spicy or mild food group. After eating, they were exposed to “a vignette in which the protagonist behaves in an ambiguously aggressive manner”. The participants then indicated how aggressive they perceived the protagonist. It was found that eating spicy food made participants perceive the protagonist as more aggressive, which showed that they themselves were more aggressive. This Study, paired with study 1, showed that spicy food primed people for aggressive thoughts.

  Study 3 explored the aggression relationship to the sense it was exposed to, meaning whether a person became more aggressive when exposed to spicy food visually or verbally. For this study, participants were randomly assigned to one of four groups, which crossed food type (spicy vs non-spicy) and sense (visual vs verbal). They were either shown pictures of food or told about food. Participants then rated how spicy the food probably was. Lastly, they took the same tests in Study 2 see measure their aggression levels. Results from Study 3 showed that aggression can still be triggered without even eating the food. It can result from simply mentioning the food. The study also showed that visual cues had a more prominent aggression response than did verbal cues. This entire study helps corroborate the saying “you are what you eat”. People that enjoy spicy food tend to be more aggressive than those that don’t.

  These Research Papers helped me understand how psychological research is conducted. Research requires an advanced understanding of statistics to understand data and whether it is reliable. There is also a standard way the information is laid out. All research papers start with the “Abstract”, indicating general points about the study. It is then followed by general information, like important terms and previous research, that might be necessary for the understanding of the paper. Next, they list out all the studies, and include the method, procedure, participants, results, and discussion. Following all the studies, research then has a general discussion to evaluate all the information collected from the studies. These papers gave me a general understanding of the methods behind psychology research, and the way it is presented.

  valuate the extent to which our understanding of our social world is constrained by our schemas.

Humans utilise mental structures known as schemas, which can constrain thinking and promote fixity, the extent of which will be evaluated in this essay. It will do this by first providing a brief description of schemas, it will then consider how they constrain our understanding of the social world by referring to relevant studies, discuss their benefits and drawbacks and finally draw it all together in its conclusion.

Individuals perceive the world through combining information from the senses, known as bottom up processing, with prior knowledge stored in the memory, known as top down processing. This process helps shape our perceptions and beliefs of how things usually happen in the social world and ultimately influences our behaviour, known as schematic processing (Buchanan et al., 2007). Different schemas are formed for different ‘objects’, such as ‘person schemas’, ‘role schemas’ and ‘event schemas’. One theory is that schemas are needed as our brains do not have the capacity to deal with the massive amounts of information which bombard our senses, with schemas filtering out what information is relevant to aid understanding, this view of schemas as limiting control and choice and determining interpretations and judgements is known as the cognitive miser model (ibid, 2007).

Schemas can be extremely useful as they help us make quick decisions about the social world and reduce the brain’s workload, paradoxically they can also be constraining by categorizing people in terms of their schema type, rather than their individual characteristics. This can be particularly prevalent when meeting someone for the first time and can lead to bias, discrimination and stereotyping. These schemas can also be self confirming and as such promote fixity which can be difficult to change, as if we expect someone to act in a certain way then we may interpret their actions as such. Darley and Gross’ (1983, cited in Buchanan et al., 2007, p.66) study provides evidence of this; in their study they presented US students with an introductory and exam performance video of a fictional person called Hannah. In one condition, Hannah’s introductory video portrayed her as of high socio-economic status and in the other condition she was portrayed as of low socio-economic status. When shown both the introductory and exam videos, participants displayed evidence of stereotyping, categorisation and prejudice, as those who were shown the high status video judged her to have high ability and vice versa.

Another example of schemas as constraining is through the process of attributions, which are explanations we arrive at to account for our own and other people’s behaviour. Heider (1958; Heider and Simmmell, 1944, ibid, p.60) proposed that lay individuals act like naïve psychologists and look for regularity and predictability, building models of causality with regards to behaviour. They also argued that attributions of causality can be understood in terms of internal (dispositional) causes, and external (situational) causes, known as locus of causality. Likewise, in their study, Jones and Davis (1965, ibid, p.72) concluded that individuals have a tendency to explain others behaviour in terms of internal factors as it tells us more about the other person and helps us to predict their future behaviour. Furthermore Harold Kelley’s (1967, ibid, p.72) covariation mode, which studies covariation and correlation between events suggests we use complicated subconscious procedures to examine three particular types of data, consensus, consistency and distinctiveness, assigning weightings to each variable in order to attribute an internal or external locus of causality. Kelley used an experimental study method, utilising vignettes, gaining very precise and testable results to support his theory. Whilst there are a number of studies to support the theory of attributions, there is also criticism that they overstate the rationality of causal reasoning and ignore any environmental and emotive influences.

Another example of schemas as constraining is through the various biases’ which can influence judgements and decision making skills and can be self serving. One such bias is known as the fundamental attribution error (FAE), which occurs when we have a tendency to explain the behaviour of others as down to internal factors. However, whilst evidence of FAE has been found in the United States, Miller (1984, ibid, p.77) found that the less individualistic culture of India showed no evidence of FAE, suggesting FAE may be a product of culture. Likewise, actor/observer effect (AOE) occurs when we explain our own behaviour as a result of external attributions. Storms (1973, ibid, p.76) study provides evidence to FAE and AOE as well as suggesting that perceptual salience plays a part in our judgements, which is when one part of the perceptual field has significance to the perceiver and therefore attracts attention. Kahneman and Tversky (1973, ibid, p.83) also found evidence of perceptual salience, utilising vignettes which gave short descriptions of individuals who could be either engineers or lawyers. They found that participants declared a 50 per cent chance of the individual being of a Lawyer, missing the fact they were informed that the room contained 70 per cent lawyers, supporting the theory of perceptual salience as the ‘actor’ is the most salient part of the vignette. This also supplied evidence of an over reliance on ‘representativeness heuristics’ which is the tendency to make categorisations based on whether an item represents the group to which it belongs, leading to judgemental errors. Similarly, some events can be easier to remember, particularly if recent and can lead to errors in judgements, known as ‘availability heuristics’. In addition, Lau and Russell (1980, ibid, p.77) found evidence of self serving biases’, with individuals displaying a tendency to attribute successes to internal factors and failures to external causes. They also utilised vignettes, increasing ecological validity by analysing actual sports interviews, coding explanations in terms of locus of causality. One possible explanation for a self serving bias is that it is a cognitive bias, in other words we succeed because we expect to as we have put effort in to increase our chances of success, likewise if we do not succeed we attribute this to external factors. Another potential explanation is a motivational bias, driven by a need to enhance self esteem, portray a positive self image and feel in control.

Schemas can also be constraining as they can influence our perception of risk, individuals becoming more optimistic about risks than statistics warrant, known as optimistic bias. There have been numerous studies on the subject, including Weinstein (1987, Ibid, p.88) who used questionnaires to gauge participants attitudes to health and safety risks as opposed to someone with equal exposure to that risk and found that most unfoundedly rated their risk as below average, supporting evidence of an optimistic bias. This could also be explained in terms of a lack of availability heuristics and experience of the risks. It could be argued that the optimistic bias is a self serving bias, leading to a less stressful and more productive life, reducing feelings of anxiety and promoting happiness.

In contrast to the cognitive miser model, Fiske and Taylor’s (1991, ibid, p.70) Motivated Tactician model argues that when motivated, humans can be less machine like and can be fully engaged thinkers, utilising strategies based on goals, motives and needs. They also suggest three levels of automaticity of schematic processing, including preconscious automaticity where stereotypes are activated by physical attributes and so on and which are outside of the perceivers awareness, and a goal dependent level, which can be likened to Ruscher et al.’s (2000, ibid, p.68) workplace relations experimental study, in which participants will seek information that is not congruent with the relevant schema. They found that individuals act like motivated tacticians when the achievement of goals is reliant on another individual, seeking out extra information about individuals rather than relying on stereotypical characteristics. Whilst these studies provide evidence for the capability in humans to think consciously and analyse situations based on motivation, it can be argued that this model ignores the importance of quick decision making, and the emotive and environmental influences on judgements.

Finally, one criticism that can be attributed to the theories from within the experimental social psychology perspective discussed thus far is the lack of ecological validity. However, a number of schema related constraints can be evidenced in Joffe’s (1999, ibid, p.93) ecologically valid, cross cultural study of the risk perception associated with HIV/AIDS. Joffe was concerned with the social representations of risk, which are based on the shared perceptions and beliefs of groups. She conducted semi-structured interviews with 60 Individuals, comprising of an equal share of British and South Africans, blacks and whites, heterosexual and homosexuals in their early 20’s. Joffe found evidence of the optimistic bias, with individuals rating their chances of contracting the diseases as below average. She also found evidence of attribution theory with participants acting like naïve scientists seeking causality and displaying the FAE when apportioning blame and attributing that to dispositional factors, forming a kind of ingroup bias and outgroup prejudice and discrimination, possibly as a form of psychological defence of the ingroup, which mirrors Tajfel’s (1971, cited in Phoenix, 2007, p.62) Social Identity Theory. Joffe’s study provides ecologically valid evidence of how schema can lead to attributions, stereotyping, bias, poor judgemental skills and prejudice towards others and a possibly hazardous perception of risk to self.

This essay has evaluated the extent to which our understanding of our social world is constrained by our schemas by first giving a brief description of schema theory. It then evaluated a number of concepts related to schema theory such as categorisation, attributions, judgemental influences, biases’ and perception to risk and although the majority of studies lacked ecological validity due to laboratory settings, it concluded with an ecologically valid study which evidenced all these concepts. Ultimately it has found that although schemas can be constraining and promote fixity, it can be argued that they offer an evolutionary survival advantage by avoiding anxiety associated with the need to constantly make time consuming reasoned judgements and as such increase happiness.

Word Count: 1650

References:

Buchanan, K., Anand, P., Joffe, H., and Thomas, K. (2007) ‘Perception and understanding the social world’ in D. Miell., Phoenix, A. and Thomas, K. (eds), DSE212 Mapping Psychology (Book 2), Milton Keynes, The Open University.

Phoenix, A. (2007) ‘Identities and diversities’ in D. Miell., Phoenix, A. and Thomas, K. (eds), DSE212 Mapping Psychology (Book 1), Milton Keynes, The Open University.

The relationship between associates and same category distractor words in the picture-word interference paradigm

Abstract:

In order to compare the effects of shared category membership and associates a picture-word interference task was you. Participants were presented with a task whereby they had to name a given stimulus but ignore the superimposed distractor word. The distractor word was either related or unrelated to the stimulus and was from one of three conditions; same category members that are associates, same category members that are not associates and different category members that are associates. Results found that same category members that are not associates impaired performance, contrarily, associates that are not same category members appeared to improve their performance. These results questions the orthodox view that lexical selection only involves a competition element and put forward the idea that some distractor words may result in facilitation.

Introduction:

The production of language is a complex process which is imperative in human communication. The ability for a human to produce language is fast and efficient; it is thought that an individual can produce approximately two to three words per second, this is remarkable as there are about fifty to one-hundred thousand words in the average humans mental lexicon. Producing language consists of many different processes, in particular this study is interested in lexical selection for spoken naming. There are many theories as to the way in which lexicalization works, this is the process from which a semantic representation develops into a word. It has been thought that when seeing a stimulus a semantic representation of that stimulus activates a range of lexical representations from which one is selected. As naming the stimulus is restricted to the production of a single word there is competition in which only one out of the many activated words will be selected.

A picture-word interference task (MacLeod, 1991) has been commonly used to study the effect of which a distractor word has on the time it take individuals to name a stimulus. This task is comparable to that of the Stroop interference task (Stoop, 1935). Stroop presented individuals with words (names of colours) which were either written in black of a incongruent colour. He found that when the word was incongruent it interfered with participant’s performance. Although similar to the Stoop interference task, the picture-word interference task instruct participants to name a image and ignore the superimposed word. As this task uses images, a variety of target words and distractors can be used from a range of categories, which do not necessarily have to be from the same ‘response set’. This task has consistently found that when the superimposed word produced greater interference on participant’s performance when it was semantically related compared to when it was semantically unrelated.

The picture-word interference task ask participants to name an object but ignore the superimposed word. Although this is similar to the Stroop interference task, it differs in that by using pictures a wide variety of target words and distractors from many different categories can be used which don’t necessarily have to be from the same ‘response set’. The picture-word interference task has found that presenting participants with a distractor word that is semantically related to an object interfered with participant’s naming time more then when the word was semantically unrelated. This is thought to reflect competition in the process of lexical selection.

Costa, Alario and Caramazza (2005) conducted a study which consisted two experiments both of which instructed the participants to name the image and ignore the distractor word. In the first experiment participants were presented with four different types of distractors; semantically related word relating to part of the image that could not be seen, semantically unrelated words, categorically related word and categorically unrelated words. In order to control for any difference that may have occurred due to the difference properties of the distractor word the second experiment presented the image four times each with a different type of distractor. These distractors included a word which corresponded with part of the image, an unrelated word and two unrelated filler distractors. Costa et al (2005) found that words that were categorically related produced semantic interference, however, words that related to parts of the image that were not visually present led to semantic facilitation.

Further studies have also found that distractor words do not also result in an interference effect and certain distractors can improve participant’s performance. For example, Sailor, Brooks, Bruening, Seiger-Gardner and Guterman (2009) found that same category distractors (‘co-ordinates’) interfered with participant’s naming times. However, when the distractor was associated to the stimulus a facilitation effect occurred. A study conducted by de Zubicarary, Hansen, and McMahon, (2013) also found a facilitation effect from associates. The findings from these studies challenge the idea that all related distractor words compete for lexical selection.

To advance what is already known about lexical selection for spoken naming, this current study aims to replicate the methodology of the picture-word interference task to investigate what types of relationships produce facilitation and interference. To do this the experiment will make a comparison between three different condition; same category members that are also associates, same category members that are not associates and different category members that associates. This something previous research has not yet studied, doing this should provide a further insight in the role of associates and same category membership.

Using what is already known about language production, there is an expectation that distractor words that are associated to the stimulus but are from a different semantic category will facilitate participants performance. However, distractor words that are associated to the stimulus but are from a different semantic category will result in an interference effect. Due to the lack of research in this particular area it is difficult to predict the effect of distractor words that are associates from the same category.

Method:

Participants:

Seventy-seven participants, all of which were fluent in reading and speaking English language were recruited from the University of Essex community via opportunity sampling.

Apparatus:

Participants completed the study using SuperLab 5 on Macintosh computers. Participant’s performance was timed using the computers build in microphone.

Materials:

The experiment included twenty different line drawings (which SuperLab 5 presented as stimuli) , each drawing had a single distractor word superimposed upon it. The superimposed words were in Geneva 36-point font and presented in lower-case.

Design:

This experiment used a two by three within-subjects design. The dependent variable in this study was the time taken for participants to state the target word of the image. One of the independent variables were the relatedness of the distractor word (either related or unrelated). The second independent variable was the type of distractor word which consisted of three levels; associates that were from a different category from the target word, associates that were from the same category as the target word and distractors that were not associated with the target word but were from the same category. Moss & Older (1996) classification of mean associative strength was used. For the associate different and the associate same conditions related distractor word were equated, there was zero association in the non-associate same condition. Each participant completed six different conditions, the order of these conditions were randomised.

Procedure:

Before starting the experiment participants engaged in a familiarisation stage for approximately a minute and a half. At this stage, twenty target pictures were provided with their ‘target name’, the purpose of this was to familiarise participants with the word of which they were expected to produce in the experiment.

After the familiarisation stage participants engaged in a practice trial, (consisting of ten trials) they were instructed to name the stimulus on the screen and ignore the superimposed word. Participants then began the primary experiment whereby the completed one-hundred and twenty trials. Participant’s had to vocally state the name of the stimulus that they were presented with, the computer started the timer as soon as the image appeared and stopped as soon as sound as heard. Once the participant had stated their answer the experiment had to determined whether the response was appropriate . The experiment pressed the ‘Z’ key is response was deemed appropriate and the ‘X’ key if not.

Results:

Each of the seventy-seven participants generated two scores for each trial; a response time score for each trial and a experimenter decision time score. The experimenters decision time score was completely excluded from the analysis. Several exclusion were then made, these were naming times that were quicker than 250m/s, naming times that were longer than 2500m/s and responses of which the experimenter classified as inappropriate.

Any participant which had more than twenty excluded responses were not included in any further analysis. As well as this, a further eight participants were excluded from the data analysis due to technical errors. This resulted in a total of sixty-three participant’s being included in the data analysis. Their remaining response times were then averaged to produce a total of six means (one for each condition), these means are shown in figure 1.

A three by two related analysis of variance was then conducted between type and relatedness. There was a significant main effect for ‘type’, F (2,124) = 9.170, p < .001, (Mean (M) for associate different categories = 864, M for associate same category = 878, M for non-associate same category = 888) this suggests that participants were significantly faster at naming the stimulus when the distractor was from the associate different category condition then when it in either of the same category conditions.

In contrast, there was no significant main effect of relatedness, F (1,62) = .125, p = .725, (M for related = 877, M for unrelated = 876) proposing the idea that participants naming response time did not differ significantly regardless of whether the word was related or unrelated to the distractor.

A significant interaction was found between type and relatedness F (2,124) =6.444, p = .002, this imply that the type of the distracter had a different effect on naming response in the related and unrelated condition. This suggest that the effect of relatedness is different for the different levels of type.

To explore the interaction further, a Tukey post hoc test was conducted to further investigate the effect of relatedness. The Tukey test found that in the associate different category condition naming times were significantly faster when the distractor was related rather than when it was unrelated (refer to means in figure 1). In contrast, in the non-associate same category naming times were significantly faster when the distractor was unrelated compared to when it was related (refer to means in figure 1). There was no significant different found between relatedness in the associate same category condition.

Figure 1: Means and standard deviations for each independent variable

Discussion:

The results of this study found a facilitation effect when presenting participants distractor words that were associated to the stimulus but from a different semantic category. Contrarily, distractor word that were not associates but from the same category produced an interference effect. However, performance was not affected by distractors that were associates and from the same category of the stimulus.

The interference effect found in these results can be explained by the selection by competition hypothesis. This hypothesis suggest that when attempting to name a stimulus semantically related words will also be activated. This activation of multiple words lead to competition, the word that receives the most activation will eventually be produced but the initial competition causes a delay in the selection process. Although this hypothesis successfully explains why interference occur it does not explain why distractors that are associated to the stimulus facilitate participant’s performance.

Reolofs (1992) developed two assumptions to explain why interference and facilitation effects occur. His first assume that when the target and distracter words are semantically related there are higher activation levels in these words which interfere with participant’s performance. The second assumption proposes the idea that selection competition is restricted to items that are from the same response set. This theory would assume that those words that were associates but not related to the stimuli would not enter in to the lexical competition but may still activate the target words, resulting in facilitation.

The response exclusion hypothesis (Mahon, Costa, Peterson, Vargas & Caramazza, 2007) also provides a further explanation as to why these different effects occur. Mahon et al (2007), proposed the idea that there is a single channel speech output buffer where only one word can be produced at a time. They suggested that there is a response relevant criteria which attempts to exclude all non-target words from entering the buffer. Those words which are not from the same semantic category will be faster to exclude than those is same semantic category. As these non-related words do not enter the buffer it makes it easier for participants to produce the target word.

It is difficult to conclude why distractor words that are both semantically related and associated to the stimulus has no effect on participants performance. It can be assumed that as the word is associated to the stimulus it is attempting to facilitate performance but as it also is semantically related it is competing for lexical competition, thus, working in opposite direction leads them to balance out one another.

The findings from this study are consistent with previous studies such as Costa, Alario, and Caramazza (2005). This results of this primary study replicate what has previously been found in that words from the same semantic category produce interference whereas associates can lead to facilitation. The findings from prior studies and this one, challenge the existing ideas about language production and support the idea that lexical production for spoken naming is not solely result of lexical completion.

Future studies could looked deeper into the effect of distractor words that are associates and semantically related to a stimulus, as what is known about these types of distractor words are vague. When doing this, the study could control for ‘word frequency’, it is thought that words which are more frequently used are recognised faster than those that are not. These high frequency words are said to have a lower threshold of activation, this may have influenced the results of previous studies. For example in this primary study, it likely that an image of a car would be classified as a high frequency word whereas squirrel may be a low frequency word, resulting car being quicker to name.

Further research could also be conducted on those who are bilingual. Focusing on this specific population will examine whether having more words in your mental lexicon causes greater interference effect and facilitation effect. If a greater interference effect and facilitation effect was found within these individuals it provided greater support and knowledge for what is already known about lexical selection.

Language production is a complex phenomena which is deficient in its research. Understanding language production can widen our understanding about one of the only aspects that makes humans unique. Knowing more about language production can help advance what is already known about patients with spoken language impairments such as aphasia sufferers. It could also give insight in to the development of language production.

References:

Costa, A. A.-X. (2005). On the categorical nature of the semantic interference effect in the picture–word interference paradigm. Psychonomic Bulletin & Review, 125-131.

de Zubicaray, G. I. (2013). Differential processing of thematic and categorical conceptual relations in spoken word production. Journal of Experimental Psychology: General, 131-142.

MacLeod, C. M. (1991). Half a century of research on the Stroop effect: an integrative review. Psychological Bullentin, 163-203.

Mahon, B. Z. (2007). Lexical selection is not by competition: a reinterpretation of semantic interference and facilitation effects in the picture-word interference paradigm. Journal of Experimental Psychology: Learning, Memory, and Cognition, 503-535.

Moss, H. &. (1996). Birkbeck word association norms. Psychology Press.

Roelofs, A. (1992). A spreading-activation theory of lemma retrieval in speaking. Cognition, 107-142.

Sailor, K. B.-G. (2009). Exploring the time course of semantic interference and associative priming in the picture–word interference task. The Quarterly Journal of Experimental Psychology , 789-801.

Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of experimental psychology, 643-663.