Why we Run: Survey Pilot Complete

I’ve been very quiet on the blog for the last few months as I’ve been finalising and piloting cropped-runometer-logo.gifthe survey that is a major part of my PhD research project into the British running scene, as well as writing the first drafts of two chapters of my thesis.

At last though, the pilot data has been collected and analysed, the survey tool has been tweaked and it’s now ready to be sent out into the big wide world to seek its fortune, hopefully shedding new light on the motivations and practices around running, and describing the hidden factors that impact peoples’ relationships to the sport. Hopefully the responses will start coming in over the next few days.

The pilot went extremely well, with over 50 people responding. That’s 20 more than I needed, but only a fraction of what I’ll require for the full survey. The good thing is that – as expected – fellow runners have been extremely helpful in passing the survey on to friends and running partners, and many are keen to participate.

Over the coming weeks I will be contacting running groups, clubs, race organisers and institutions to see if they would be kind enough to help raise awareness of the survey. I’ll also be taking to social media to see what kind of response that can generate.

I’ll be posting regularly now, with updates and findings as they come through.

The final survey is available now, at www.bigrunningsurvey.co.uk. If you run I would love to hear from you!

What are psychographics?

If you’ve been visiting my site regularly you’ve no doubt come across the word ‘psychographics’ a few times. Not everyone is familiar with this term, so to save myself (and you) from having to explain the word every time I use it I’ve added this reference page.psychographics definition

What are psychographics?

To describe the characteristics of a particular group we’re used to the idea of using demographic data such as age, gender, education level or location. This information helps us to give the group some defining features that allow us to compare it to other groups, to work out if other people or populations are part of the group or to focus marketing activities on the right people.

For example: the group ‘night clubbers’ has the demographic characteristics of being mostly under 25, evenly split between males and females and mostly single.

In this case we’ve identified a particular group based on a known behaviour (going to night clubs) and made some generalisations about the typical demographic characteristics of the group as a whole.

But demographic data can also be used to segment a particular group into subgroups to help us understand variations in behaviour or outcomes within the larger group. This can be done in a number of ways, including simply splitting the group in terms of one variable (for example, into male and female night clubbers) or by using statistical techniques to look for clusters of demographic factors that, when they occur together, tend to correspond to a certain ‘target’ behaviour or other variable of interest to the researcher.

So, let’s say we want to split the night clubbers group into segments that correspond to their scores on a variable about how often they go clubbing. Using a statistical cluster analysis we can find out how the main group can be segmented into subgroups made up of people that tend to frequent nightclubs at a similar regularity. So it might turn out that the subgroup that goes clubbing 2-3 times per week are best defined as predominantly female, low income students, and under the age of 23; the group who go less than once per month might turn out to be predominantly male, high income and over the age of 30.

Demographics can be an excellent way of describing and segmenting populations, but because they only look at relatively objective factors they can miss out on a lot of rich and important detail about what makes people tick. It’s all very well saying people under 40 are more likely to buy an ipod than those over 40, but surely we’d have a much better predictor of purchase if we split a group by factors like whether or not they are big music fans or technophobes (for which age might be an imperfect proxy). This is where psychographics comes in.

Psychographics takes the study of groups into new areas: interests, attitudes, opinions, motivations, values, personality and lifestyle choices. It enables us to describe and segment  populations by the way they think rather than by demographic factors, which is often very useful to market researchers looking to develop a detailed picture of existing or potential customers.

A simple example of a psychographic segmentation is a political opinion poll. Here a population is divided up according to an opinion or intention: who will you vote for?

In combination, psychographics and demographics can provide a powerful way of defining groups and predicting behaviour. In my research I am using both types of data to help create a set of profiles of different types of runner based on their relationship to the sport. Each profile will have a different combination of factors (e.g. values, attitudes, motivations, age, gender, socioeconomic status) that correspond to – and help explain – the ways they practice their sport.

Running and the Sociological Ghetto

sociology of runningWhenever I get asked about the subject of my PhD I have to suppress the urge to launch into a sort of paranoid defence of the sociological relevance and intellectual seriousness of my research topic. Running – and sport as a whole – lacks the gravitas of heavyweight sociological topics like racism, power or poverty. It sounds suspiciously like an area belonging to one of those low-currency, smirk-afflicted new disciplines like leisure studies. I hear myself excusing the subject matter as an ‘interesting prism’ through which to examine wider, deeper social issues (aging, identity, community), or else gloss over the subject matter altogether in favour of explaining more esoteric aspects of the research design or data analysis. No doubt this has a lot to do with my own insecurities, but my reticence needs to be understood in the context of lingering academic prejudices surrounding the study of sport in sociology.

Early in our discipline’s history, classical sociologists worked hard to demarcate a distinct zone of expertise in contrast to more established sciences. Part of this process was to prise apart ‘social’ and ‘natural’ spheres, leaving the study of nature – including the human body – to biologists and establishing sociology’s authority over a social world hacked off at its biological roots. This division, underpinned by Descartes’ ontological dichotomy of mind and body, shaped the development of sociology for many decades, with the result that sport, the bodily activity par excellence, was largely neglected. And even today, following the ‘somatic turn’ in sociology, sport retains a whiff of disrepute. According to Carrington (2010)  ‘sport both hyper-accentuates and finds itself on the wrong side of a supposedly insurmountable (and deeply ‘classed’) dualism between useless physicality and purposeful intellectualism’. As a result, according to Bourdieu (1987) ‘there are, on the one hand, those who know sport very well on a physical level but do not know how to talk about it and, on the other hand, those who know sport very poorly on a practical level and who could talk about it, but disdain doing so, or do so without rhyme or reason’. Sport’s awkward marginality within sociology is neatly embodied in the person of Loic Wacquant, who, despite having authored a highly respected study of boxing in Chicago (Wacquant, 2004), remained at pains to deny that his subject was the sport itself, but rather ‘the twofold incorporation of social structures: the collective creation of proficient bodies and the ingenuous unfolding of the socially constituted powers they harbor’ (Wacquant, 2005 in Carrington, 2010). Elsewhere he said that following the success of his boxing study, his association with Pierre Bourdieu had saved him from ‘disappearing into the oblivion of the sociology of sport’ (see Miller, 1997). I can empathise with Wacquant’s resistance to attempts to ghettoise his work, and sympathise with his argument that sport can be studied as a manifestation of universal social processes rather than simply in and of itself. However, I would also argue that sport, and running in particular, are important social phenomena that deserve study in their own right. For sociology to neglect or downgrade sport, a category of social action as ubiquitous to and specifically shaped by our times as any other, seems to me a failure of sociological objectivity and a kind of wilful myopia. If as sociologists we aim to discern the deep bone structure beneath the fleshy face of society it is vital that we subject all of its undulations, all of its features, to serious sociological scrutiny, not just those we a priori deem worthy of attention. After all, would a study of the culture of ancient Rome be complete without reference to the amphitheatre? Or of classical Greece without mention of the gymnasium or Olympic Games?

Top 8 reasons to stop running

What – if anything – would stop you from running?reasons to stop running

A survey of frequent runners identified these 8 reasons as the things most likely to cause them to have to stop.

Interestingly, apart from items 3 and 4 which are both about motivation, the sequence is exactly the same for both frequent and occasional runners, although occasional runners rate all of the reasons as more likely to force them to stop than their keener counterparts. The percentages give the frequent runners’ response rate in red, occasional runners’ in blue).

Top 8 reasons why runners would give up their sport

  1. Injury or physical disability (73% / 83% of respondents agreed)

  2. Less free time available for running (31% / 58%)

  3. Loss of motivation (29% / 48%)

  4. Wanting to spend time doing other sports instead (21% / 52%)

  5. Running partner stops (8% / 16%)

  6. Financial cost of running too great (8% / 16% )

  7. Break-up of running group (8% / 12%)

  8. Departure of coach (4% / 6%)

On average we can see that frequent runner rate themselves as 40% less likely to quit in the face of setbacks or difficulties than occasional runners.

And only physical injury or disability rate as sufficient reason to stop running for most serious runners. No surprise there.

Data from Scheerder et al (2009) quoted in Borger et al (2015), in Scheerder et al (2015).

Sport and Social Class – The Rankings

This is a follow-up to an article I published earlier this week that looked at how people’s socioeconomic background (crudely, their ‘class’) was a great predictor of the kinds of sports they got involved in.Sports by socioeconomic group

Based on a large scale survey of sports participants, running came in just below sports like sailing, yoga and windsurfing, but above cycling, basketball and football in terms of the socioeconomic status of its enthusiasts.

But the data I used for that study was from Belgium, and I only included a handful of sports. So this post is designed to provide an English perspective, as well as much wider coverage in terms of the sports included in the comparison.

I’ve taken data from Sport England’s massive ‘Active People Survey‘, an annual sports participation survey of over 160,000 people, and done a bit of number crunching to compile a list of popular sports ranked by their relative popularity to high and low status groups.

More precisely, I generated a ratio of the rate of participation in each sport by high socioeconomic group people to the rate of participation for the low socioeconomic group. Sorry if that sounds confusing, but what it means is:

If a sport gets a score of 2 on the ranking that would mean it is twice as popular with the high status group as it is with the low status group. Or, if a sport gets 0.5 then the likelihood of a high status person participating in the sport is half that of a low status person.

So this is about comparing the appeal of each sport to the two groups, not comparing the total numbers in each group participating.

The two socioeconomic status categories are defined using the N-SEC classification system used in the UK census. Here’s a list of those included in each group:

Higher Status

  1. Higher managerial and professional occupations
  2. Lower managerial and professional occupations
  3. Intermediate occupations (clerical, sales, service)
  4. Small employers and own account workers

Lower Status

5. Lower supervisory and technical occupations
6. Semi-routine occupations
7. Routine occupations
8. Never worked and long-term unemployed

‘Participation’ is defined as taking part in a sport at least once per week.

The UK’s ‘Poshest’ Sport Rankings

Rank

Sport

Participation Rate Ratio

1 Tennis 3.89
2 Squash 3.00
3 Keep-fit Classes 2.43
4 Golf 2.42
5 Mountaineering 2.40
6 Running 2.28
7 Road Cycling 2.25
8 Swimming – Outdoor 2.09
9 Athletics – Track & Field 2.08
10 Aerobics 2.05
11 Badminton – Indoor 1.87
12 Hockey 1.67
13 Swimming – Indoor 1.60
14 Netball 1.53
15 Fitness & Conditioning 1.50
16 Gym 1.49
17 Table Tennis 1.29
18 Boxing 1.20
19 Karate 1.06
20 Equestrian 1.05
21 Bowls 1.03
22 Shooting 1.00
23 Cricket 0.97
24 Football 0.94
25 Rugby Union – 15-a-side 0.73
26 Tenpin Bowling 0.71
27 Basketball 0.63
28 Snooker 0.60
29 Pool 0.56
30 Angling 0.54
31 Darts 0.40

Note: A high rank doesn’t mean better! The sports that are doing the best to encourage as wide a range of participants as possible are those towards the middle of the table with scores around 1. These are equally attractive to both ends of the social spectrum.

You can see that most sports are more popular with the higher status group than the lower status group (i.e. they have a participation ratio above 1). This reflects the fact that participation in sport as a whole is more common amongst the middle class than the working class.

Looking at the detail, there are a quite few surprising results. As with the Belgian results, running is pretty high up the list – only just behind golf and mountaineering, but I wouldn’t have guessed rugby or cricket would be in the lower half of the table,or that equestrian sports and shooting have such similar levels of appeal across the classes. But the data is from a very reliable source and from a huge sample, so we have to take it seriously.

I’d love to hear your interpretations for any of these figures.