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Sequence organization of autistic children's play with caregivers: Rethinking follow-in directives.

Kristen Bottema-BeutelShannon CrowleySo Yoon Kim
Published in: Autism : the international journal of research and practice (2021)
In this article we use a qualitative method, conversation analysis, to examine videos of caregivers interacting with their young autistic children who are in the early phases of language learning. Conversation analysis involves preparation of detailed transcripts of video data, which are then analyzed together to understand how interactional moves (e.g. talk, gestures, and physical conduct) are linked with prior and subsequent interactional moves. We analyzed data from 15 participants, and focused on instances when caregivers made a proposal about something the child was playing with. In previous research, similar instances have been referred to as "follow-in directives." We found that these proposals were embedded in sequences that had a similar structure, and were prefaced with a 'pre-proposal'; where the caregiver established the child's interest in a joint activity and signaled the upcoming proposal. The caregiver's talk was also provided in such a way that there was a clear "slot" for the child's turn, which made it easy for the child's actions to become part of an interactional sequence. In addition, proposal sequences were very negotiable-the caregivers do not usually insist that the child follow through on the proposal, only that they produce an action that could be taken as a response. Finally, there were some instances where the child's turn was very precisely timed to occur right at the end of a caregiver's proposal; this precise timing could signal the child's understanding of how interactional turn-taking works. We suggest that this method of examining caregiver-child interactions provides new insights into how interactions proceed, which could be useful for future intervention research.
Keyphrases
  • mental health
  • palliative care
  • randomized controlled trial
  • young adults
  • physical activity
  • autism spectrum disorder
  • machine learning
  • mass spectrometry
  • sensitive detection
  • high resolution
  • tandem mass spectrometry