The National Autistic Society (NAS) ran a survey about terminology between December 2013 and February 2014, which informed its campaigning and led to the publication of the article Which terms should be used to describe autism? in Autism Journal in 2015.
As part of an otherwise frustrating dialogue with the NAS, Carol Povey, Director of its Centre for Autism, shared some of the processed anonymised data from this data as used internally by the NAS. A partial set of the cleaned data as processed for the article was later obtained from Liz Pellicano and Lorcan Kenny. The data for the article had been cleaned by the paper's authors in their initial submission and following review comments. Unfortunately, these data sets were shared in confidence and neither have been published.
In trying to better understand these datasets, I noticed some discrepancies between them. A concern is that the process of cleaning the data before analysis may affect survey-based articles on autism in a specific way. When both autistics and non-autistics are surveyed, the cleaning process appears to disproportionately affect the autistic cohort. Here's the text of the letter to the editor of the Autism Journal in which I detail this concern:
Does data cleaning disproportionately affect autistics?
In Kenny et al.’s paper (2016), titled ‘Which terms should be used to describe autism? Perspectives from the UK autism community’, the authors analysed data from the UK’s National Autistic Society’s (NAS) survey on terminology. In the paper, they detail how they removed a significant number of participants prior to data analysis. They state,
In all, 4622 people responded to the survey. Participants who (a) did not specify any connection with autism (n=19), (b) did not complete all four key questions on describing autism (n=453), (c) were under 18 years or preferred not to state their age (n = 284) and (d) were not resident in the United Kingdom or preferred not to state their place of residence (n=396) were excluded from the data set prior to analysis. Subsequent analysis was therefore based on complete responses from 3470 participants.
I believe that comparing results from the raw data and that of the data with these participants removed shows that this removal has disproportionately affected the processing for autistics compared to that for the other categories of respondents such as families and professionals.
For example, in Table 2, the modes for four rows for the ‘autistic’ column are different for the processed data compared to the raw results. Only one row is different for the ‘Parent’ and ‘Family/friend’ columns and none for the ‘Professional’ column.
I would suggest there is a reason for this. Anecdotally, autistics who have issues with the wording of survey questions or the possible set of answers often either object to continue filling in the survey or skip the offending questions (and often attempt to get in touch with the researchers for corrections and clarifications). There are 453 incomplete such entries in the NAS survey by autistics – which have been removed from analysis and, ultimately, were not taken into account for the processing in the final article.
This very limited comparison raises the hypotheses, supported by anecdotes, that cleaning of data in surveys targeted at both an autistic and non-autistic cohort may introduce a bias disproportionately affecting the responses from autistics. Further work on whole sets of data before and after the cleaning for several surveys is required to reach any conclusion.
Reference
Autistic responses
Looking solely at responses by autistics in the cleaned data, i.e., the autistic perspective, there are a few interesting outcomes (see tables below).
The preference for identity-first terminology (e.g., I am autistic) by autistics is clear:
Also ‘autistic person’ is always rated lower, by autistics, than ‘autistic' or 'is autistic’. This seem to imply that adding 'person' is redundant, though it may of course be context dependent.
Lastly, the second table below shows at least 53% of the autistic respondents were aspie, so the autistic respondents may not represent the full diversity of autistics.
What next?
Hopefully some researchers will investigate further whether the cleaning of data in surveys targeted at both an autistic and non-autistic cohort does introduce a bias disproportionately affecting the responses from autistics.
Several questions in the survey had very similar, but different, sets of answers and I wonder how many respondents analysed the subtlety of the different questions when answering them. (It also means that one cannot directly compare the different questions as the sets of answers are not identical.)
This important research paper raises many issues about accessibility at all stages of research, when surveys questions could be confusing and the way the data was analysed may have created bias disproportionately affecting autistic respondents, who may have felt unable to answer one or more of the questions. The solution to improve autism research is to involve autistics from the design to the analysis of research projects.
| Which words/phrases do you prefer to use when communicating about autism? (Select all that apply) | Autistic |
|---|---|
| Autism | 64% |
| Autistic | 61% |
| On the autism spectrum | 56% |
| Aspie | 47% |
| Autism spectrum disorder (ASD) | 39% |
| Autistic person | 36% |
| Has autism | 35% |
| High functioning autism (HFA) | 32% |
| Person with autism | 28% |
| Autism spectrum condition (ASC) | 28% |
| Low functioning autism (LFA) | 8% |
| Autist | 7% |
| Classic autism | 6% |
| Pervasive developmental disorder (PDD) | 5% |
| Kanner’s autism | 2% |
| Kanner’s syndrome | 1% |
| Other (please specify) | 20% |
| How do you describe yourself, your child, or those you work with? (Select all that apply) | Autistic |
|---|---|
| Has Asperger's | 53% |
| Aspergers syndrome | 51% |
| On the autism spectrum | 45% |
| Autistic | 43% |
| Aspie | 38% |
| Is autistic | 35% |
| Autism spectrum disorder (ASD) | 28% |
| Has autism | 28% |
| High functioning autism (HFA) | 23% |
| Autistic person | 22% |
| Autism spectrum condition (ASC) | 18% |
| Person with autism | 18% |
| Is Aspergic | 6% |
| Autist | 4% |
| Pervasive Developmental Disorder (PDD) | 3% |
| Classic autism | 2% |
| Low functioning autism (LFA) | 1% |
| Kanner’s autism | 1% |
| Kanner's syndrome | 0% |
| Other (please specify) | 11% |
| Please rate the following words or phrases (mode) | Autistic |
|---|---|
| Asperger syndrome | 5 |
| Aspie | 5 |
| On the autism spectrum | 4 |
| Autistic | 4 |
| Person with autism or person with Asperger’s | 4 |
| Has Asperger’s or autism | 4 |
| Autistic person | 3 |
| High functioning autism | 3 |
| Autism spectrum disorder (ASD) | 3 |
| Autism spectrum condition (ASC) | 3 |
This post was simultaneously published on the Speak up blog, which accepts comments.
[Update 2017-01-31] Cas published on Spacious Perspicacious the result of their autistic survey also showing a clear preference for identity-first terminology:
The top 5 ways for us to describe ourselves were:
- I’m autistic - 66.3%
- I’m on the [autism] spectrum - 40.8%
- I’m Autistic - 30.9%
- I have Asperger’s Syndrome - 29.9%
- I have an ASD (autism spectrum disorder or autistic spectrum disorder) - 23.1%
[Update 2019-01-15] The responses in the 2008 survey of Autistic not weird, answered by 11,521 respondents, are also consistent with the earlier surveys:
[...] professionals (including me, once upon a time) are taught to use person-first language, but those on the spectrum themselves are more willing to claim the word “autistic” as their identity.
51.62% of autistic respondents use ‘autistic person’ only, versus 22.73% for non-autistic respondents with an autistic relative and 12.97% for non-autistic respondents who do not have an autistic relative. (The same groups of respondents use ‘person with autism’ only resp. 11.80%, 36.17% and 49.22%).
Bootnote Related post: