In the second of this occasional series, I will be exploring a recent study I carried out with Professor Raymond MacDonald (The University of Edinburgh). The article, titled 'Predictive factors of music piracy: An exploration of personality using the HEXACO PI-R', was published in the journal Musicae Scientiae earlier this year and can be found here.
In short, the drive behind the article was to see if personality in any contributed towards an individuals propensity to favour music piracy. The results showed that this was indeed the case, with analysis suggesting people who do favour music piracy are more likely to be open, less likely to be conscientious and less likely to be honest. With regards to the latter trait, further analysis revealed that individuals favouring piracy were less fair (or more unfair, if you like).
But how does one achieve all of this? Let's briefly consider the research process of designing a survey methods research study.
Firstly, an appropriate piece of apparatus was chosen to measure personality, the HEXACO PI-R (Lee and Ashton, 2004). This instrument was chosen over rivals due to the inclusion of the 'H' scale which explores honesty (of interest, given the research topic). Then, to avoid the limitations of self-report methodology which plagues much research on digital piracy ("How many songs have you illegally downloaded over the last 12 months" etc.), a scale was constructed to measure attitudes towards music piracy without actually using the loaded word of 'piracy' at all - attitudes have been shown as predictors of music piracy engagement in other research.
The new instrument to measure attitudes towards music piracy (AMP-12) was pre-tested (successfully) on a small sample of participants to check it's reliability in statistical terms; such analysis effectively confirms that the questionnaire items actually ask what they aim to ask (and helped weed out the ones which did not).
This leaves us with the right tools for the job (in a manner of speaking). Next, we need some willing participants to get some data.
Using a variety of recruitment sources, all largely under the umbrella of 'opportunity sampling', a large enough sample to meet the needs of the research was sought out and completed an online version of the questionnaire (there are practical advantages to online surveys over pen-and-paper including a greater likelihood of more honest responses). Once the desired sample size was gained, the dataset was collated (further to excluding some individuals who did not finish the survey or process the materials carefully - this is routine practice).
Boom.
Hypothesis-testing was carried out using a Hierarchical regression and analyses produced the results outlined in the article, including finding preference for digital music and being 24 or younger as predictors of pro-piracy attitudes. Data analysis involves asking sophisticated statistical software some big questions; in this instance, SPSS was used. Ultimately, the tests chosen informed us that the chances of our findings occuring by chance were so small that we can readily assume they had not, and reflected our observations on personality. In other words, the analysis strongly suggests, to levels of what is known as statistical significance (a shorthand for being at least 95% confident), that the results were genuine, and that personality does guide the attitudes towards music piracy amongst the sample.
The process above is not far away from that of most studies using survey methodology, with broad questions like 'How can I measure this?' guiding the process. Given we are not blessed with physical scales like time, weight, etc. (like physical sciences), Social Scientists must develop appropriate instruments for measuring whatever it is they are measuring on any given study. No one study 'proves' anything, but if, over time, the same results keep coming up using different methods and different samples, then it can be readily assumed that we're onto something. To re-iterate, no one study proves anything - what it does do, is confirm or reject various hypotheses.
In this study, the decision to choose the HEXACO PI-R (Lee and Ashton, 2004) was supported, given the novel findings on honesty which would not have been generated if a different instrument was chosen. In other words, the hypothesis that personality was a predictor of attitudes towards music piracy was upheld. The assumption behind this was that personality guides much music-related behaviour such as preference for various genres, so why not how people listen to music?
The findings (see the article for the conclusions drawn) not only further the psychological underpinnings of music piracy engagement, but have policy implications. This is, or ought to be, the desired outcomes of any empirical research: 1) To make contributions to the scientific literature on a given topic to date and 2) Generate findings to the benefit of various stakeholders in the real world.
As Shermer (2011) explains, there is a need to teach how science works, rather than simply reporting merely on what is known from science. I agree.
While it's all very well for me to go into some detail on this research article, the thinking behind it is hard to articulate given there's a lack of understanding on the experimental method, hypothesis-testing etc. in the general public. I have made some effort to explain the research process as straightforwardly as possible, and will continue to to so in future blog entries on my other research articles to date which employ a broad range of methodology.
Feedback on the success or failure of my efforts above to describe the research process would be welcome, ahead of future entries in this series.
In short, the drive behind the article was to see if personality in any contributed towards an individuals propensity to favour music piracy. The results showed that this was indeed the case, with analysis suggesting people who do favour music piracy are more likely to be open, less likely to be conscientious and less likely to be honest. With regards to the latter trait, further analysis revealed that individuals favouring piracy were less fair (or more unfair, if you like).
But how does one achieve all of this? Let's briefly consider the research process of designing a survey methods research study.
Firstly, an appropriate piece of apparatus was chosen to measure personality, the HEXACO PI-R (Lee and Ashton, 2004). This instrument was chosen over rivals due to the inclusion of the 'H' scale which explores honesty (of interest, given the research topic). Then, to avoid the limitations of self-report methodology which plagues much research on digital piracy ("How many songs have you illegally downloaded over the last 12 months" etc.), a scale was constructed to measure attitudes towards music piracy without actually using the loaded word of 'piracy' at all - attitudes have been shown as predictors of music piracy engagement in other research.
The new instrument to measure attitudes towards music piracy (AMP-12) was pre-tested (successfully) on a small sample of participants to check it's reliability in statistical terms; such analysis effectively confirms that the questionnaire items actually ask what they aim to ask (and helped weed out the ones which did not).
This leaves us with the right tools for the job (in a manner of speaking). Next, we need some willing participants to get some data.
Using a variety of recruitment sources, all largely under the umbrella of 'opportunity sampling', a large enough sample to meet the needs of the research was sought out and completed an online version of the questionnaire (there are practical advantages to online surveys over pen-and-paper including a greater likelihood of more honest responses). Once the desired sample size was gained, the dataset was collated (further to excluding some individuals who did not finish the survey or process the materials carefully - this is routine practice).
Boom.
Hypothesis-testing was carried out using a Hierarchical regression and analyses produced the results outlined in the article, including finding preference for digital music and being 24 or younger as predictors of pro-piracy attitudes. Data analysis involves asking sophisticated statistical software some big questions; in this instance, SPSS was used. Ultimately, the tests chosen informed us that the chances of our findings occuring by chance were so small that we can readily assume they had not, and reflected our observations on personality. In other words, the analysis strongly suggests, to levels of what is known as statistical significance (a shorthand for being at least 95% confident), that the results were genuine, and that personality does guide the attitudes towards music piracy amongst the sample.
The process above is not far away from that of most studies using survey methodology, with broad questions like 'How can I measure this?' guiding the process. Given we are not blessed with physical scales like time, weight, etc. (like physical sciences), Social Scientists must develop appropriate instruments for measuring whatever it is they are measuring on any given study. No one study 'proves' anything, but if, over time, the same results keep coming up using different methods and different samples, then it can be readily assumed that we're onto something. To re-iterate, no one study proves anything - what it does do, is confirm or reject various hypotheses.
In this study, the decision to choose the HEXACO PI-R (Lee and Ashton, 2004) was supported, given the novel findings on honesty which would not have been generated if a different instrument was chosen. In other words, the hypothesis that personality was a predictor of attitudes towards music piracy was upheld. The assumption behind this was that personality guides much music-related behaviour such as preference for various genres, so why not how people listen to music?
The findings (see the article for the conclusions drawn) not only further the psychological underpinnings of music piracy engagement, but have policy implications. This is, or ought to be, the desired outcomes of any empirical research: 1) To make contributions to the scientific literature on a given topic to date and 2) Generate findings to the benefit of various stakeholders in the real world.
As Shermer (2011) explains, there is a need to teach how science works, rather than simply reporting merely on what is known from science. I agree.
While it's all very well for me to go into some detail on this research article, the thinking behind it is hard to articulate given there's a lack of understanding on the experimental method, hypothesis-testing etc. in the general public. I have made some effort to explain the research process as straightforwardly as possible, and will continue to to so in future blog entries on my other research articles to date which employ a broad range of methodology.
Feedback on the success or failure of my efforts above to describe the research process would be welcome, ahead of future entries in this series.
Tweets @musicpiracyblog
References
Brown, S.C. and MacDonald. R.A.R. (2014). Predictive factors of music piracy: An exploration of personality using the HEXACO PI-R. Musicae Scientae, 18(1), 53-64.
Shermer, M. (2011). The Believing Brain. New York: Times Books.
Brown, S.C. and MacDonald. R.A.R. (2014). Predictive factors of music piracy: An exploration of personality using the HEXACO PI-R. Musicae Scientae, 18(1), 53-64.
Shermer, M. (2011). The Believing Brain. New York: Times Books.
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