ESRA 2027 sessions by theme
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Inclusive and accessible survey design in an increasingly self-completion survey world |
| Coordinator 1 | Mr Tim Hanson (European Social Survey HQ (City St George's, University of London)) |
| Coordinator 2 | Ms Alice McGee (Verian) |
| Coordinator 3 | Ms Victoria Elsey (Ipsos) |
Session Details
In recent years, many surveys have shifted from interviewer-administration to self-completion designs. The motivations for this are clear: falling response rates with interviewer surveys, potential cost savings of self-completion, and removal of interviewer effects, to name a few. But while self-completion approaches offer many benefits, the inclusiveness and accessibility of these designs need to be carefully considered.
There are groups who may find participating in a survey without the assistance of an interviewer more challenging. For example, the 2023 Survey of Adult Skills found the average proportion of adults with ‘very poor literacy skills’ was 26% - and that recent declines in literacy were particularly evident among the least educated segments of the population. Alongside falling literacy levels, those with certain disabilities may find self-completion surveys more challenging. For example, in the UK, 1.5 million people have a learning disability and more than 2 million are living with sight loss.
Self-completion surveys require respondents to follow written instructions in the contact materials and typically to complete self-administered questionnaires unassisted. This may therefore reduce the scope to participate among those with low literacy or certain disabilities. Within this context, meeting accessibility standards is a necessary step, but this alone may not be sufficient, because technical compliance does not automatically make a survey inclusive for all participants.
For this session, we invite papers that address the above challenges. We welcome those that have tried different solutions to improve inclusivity, accessibility and representation among these groups in the context of predominantly self-completion surveys. This may include, for example, offering other completion modes, supported completion methods, adapting survey materials (e.g. use of plain/easy language) or technological solutions or AI tools. Papers that provide evidence of the extent that any strategies used have had an
