Griffiths

Griffiths (1994) 

The role of cognitive bias and skill in fruit machine gambling

Background
cognitive bias: observer effects in the human mind, some of which can lead to perceptual distortion, inaccurate judgement or illogical interpretation. It's a phenomenon studied in cognitive science and social psychology.

why gamblers gamble (reasons given by gamblers):
. To provide excitement
. To be more social, shyness
. To numb up unpleasant feelings, not think about problems
. To relax after a stressful day
. To solve money problems

Lesson 2 

Today we looked at the sample/participants, examples of cognitive bias in gamblers, how qualitative data was measured, content analysis, how the quantitative DV's were measured, procedure, controls, results of behaviour, significant behavioural findings, significance in research, skills of fruit machine gambling reported by gamblers, significant findings of differences, usefulness, improvements that could be made, how this would be operationalised and the implicatons of this; weaknesses, observations and strengths of the study. 

content analysis: carried out in a similar way to an observation by putting the number of times a certain behaviour (utterance) occurs into categories and then adding them up.

OCR Core studies

Psychology of individual differences: Griffiths (1994)

The role of cognitive bias and skill in fruit machine gambling

INFORMATION: Aim: To examine cognitive biases in gambling behaviour. It has been proposed that gamblers show biases in their thought processes. The study examines the behaviour of regular (R) and non-regular (non-R) gamblers when playing on fruit machines. It tests: (i) if their skill at gambling is real or perceived (by comparing their success); (ii) what the cognitive activities are of R and non-R gamblers (using the ‘thinking aloud method’); and (iii) the R and non-R gamblers’ subjective views of skill (using semi-structured interviews). Hypotheses: (a) there will be no difference in objective measures of skill between R and non-R gamblers; (b) R gamblers will produce more irrational verbalisations than non-R gamblers; and (c) R and non-R gamblers will view the skill of fruit-machine playing differently.

METHOD: Method: Observation, interviews. Setting: Amusement arcade. Participants (ps): 60 ps (mean age 23.4 years). All had played on fruit machines at least once. There were 30 R gamblers (29 males) who played at least once a week and 30 non-R gamblers (15 males) who gambled once a month or less. Procedure: All ps were given £3 to gamble which gave them 30 free gambles. All were asked to gamble for a minimum of 60 gambles. If they did, they could keep the winnings or continue playing. R and non-R ps were randomly allocated into a ‘thinking aloud’ group or ‘non-thinking aloud’ group. The ‘thinking aloud’ group were asked to verbalise every thought they had while playing. The verbalisations were recorded and transcribed within 24 hours. For all ps, the author recorded objective behavioural measures (e.g., the total time played and the amount of winnings). All ps were also interviewed about their views of the skill involved in fruit-machine playing.

RESULTS: Objective measures: There was no difference between R and non-R gamblers (R gamblers did have a higher playing rate of gambles than non-R gamblers but there was no difference in winnings). Verbalisations: Content analysis showed that R gamblers produced significantly more irrational verbalisations (14%) than non-R gamblers (2.5%), such as personifying the machine (e.g., “It stitches me up every time”). Subjective measures: Semi-structured interviews showed that R gamblers viewed themselves as above average in skill, whereas non-R gamblers viewed themselves as below average.

CONCLUSION: The findings support the hypotheses. The difference between R and non-R gamblers is most likely cognitive rather than down to skill. R gamblers process information differently and believe that there is more skill involved than there actually is.

Experimental method &design	Observation and semi-structured interview (plus content analysis of qualitative data).
Experimental sampling	Participants were recruited via adverts in local universities and colleges. Regular gamblers recruited through a regular gambler known to the researcher. Male-biased sample (44 males, 16 females) but see ‘Generalisations’ below.
Controls	Good (e.g., all participants had played on fruit machines at least once).
Qualitative/quantitative measures	Quantitative data consisted of record of length of time gambling of fruit machine, number of wins, etc. Qualitative data consisted of verbalisations in ‘think aloud’ groups. The qualitative data was transformed into quantitative data using content analysis. A coding scheme was used to put utterances into categories, these were then tallied and analysed (e.g., calculated as a percentage of total utterances, and analysed using t-tests). Content analysis of data has high ecological validity but the categorisation of verbalisations is subjective.
Ecological validity	The research has good ecological validity (e.g., it was conducted in a local amusement arcade rather than in a laboratory; it used qualitative data collected in this setting).
Confounding variables	The verbalisations were transcribed and categorised by the researcher who was not blind to the hypotheses.
Usefulness of research	The knowledge of irrational thought processes may be a help in rehabilitating gamblers through cognitive behaviour modification (e.g., by trying to modify their thought patterns).
Validity/reliability	The reliability and validity of the categorisation of the participants’ utterances is unknown as the utterances were specific to the gambling context, which was only observed by the researcher.
Generalisations	As the study uses a large proportion of male participants, it is not clear how much the findings can generalise to females. However, fruit machine gambling is very male-dominated so it is not surprising that only one female regular gambler was recruited.
Observation studies	The observational method has high ecological validity but it is difficult to replicate.
Self-report measures	It used self-report methods which may not really reflect the participants’ real views/thoughts. It used semi-structured interviews which are flexible but open-ended questions are harder to analyse than in structured interviews.