Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire
Purpose Predictions are complex, multisensory, and dynamic processes involving real-time adjustments based on environmental inputs. Disruptions to prediction abilities have been proposed to underlie characteristics associated with autism. While there is substantial empirical literatur...
| Main Authors: | , , , , , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer Science and Business Media LLC
2024
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| Online Access: | https://hdl.handle.net/1721.1/154927 |
| _version_ | 1824457855659409408 |
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| author | O’Brien, Amanda M. May, Toni A. Koskey, Kristin L. K. Bungert, Lindsay Cardinaux, Annie Cannon, Jonathan Treves, Isaac N. D’Mello, Anila M. Joseph, Robert M. Li, Cindy Diamond, Sidney Gabrieli, John D. E. Sinha, Pawan |
| author2 | McGovern Institute for Brain Research at MIT |
| author_facet | McGovern Institute for Brain Research at MIT O’Brien, Amanda M. May, Toni A. Koskey, Kristin L. K. Bungert, Lindsay Cardinaux, Annie Cannon, Jonathan Treves, Isaac N. D’Mello, Anila M. Joseph, Robert M. Li, Cindy Diamond, Sidney Gabrieli, John D. E. Sinha, Pawan |
| author_sort | O’Brien, Amanda M. |
| collection | MIT |
| description | Purpose
Predictions are complex, multisensory, and dynamic processes involving real-time adjustments based on environmental inputs. Disruptions to prediction abilities have been proposed to underlie characteristics associated with autism. While there is substantial empirical literature related to prediction, the field lacks a self-assessment measure of prediction skills related to daily tasks. Such a measure would be useful to better understand the nature of day-to-day prediction-related activities and characterize these abilities in individuals who struggle with prediction.
Methods
An interdisciplinary mixed-methods approach was utilized to develop and validate a self-report questionnaire of prediction skills for adults, the Prediction-Related Experiences Questionnaire (PRE-Q). Two rounds of online field testing were completed in samples of autistic and neurotypical (NT) adults. Qualitative feedback from a subset of these participants regarding question content and quality was integrated and Rasch modeling of the item responses was applied.
Results
The final PRE-Q includes 19 items across 3 domains (Sensory, Motor, Social), with evidence supporting the validity of the measure’s 4-point response categories, internal structure, and relationship to other outcome measures associated with prediction. Consistent with models of prediction challenges in autism, autistic participants indicated more prediction-related difficulties than the NT group.
Conclusions
This study provides evidence for the validity of a novel self-report questionnaire designed to measure the day-to-day prediction skills of autistic and non-autistic adults. Future research should focus on characterizing the relationship between the PRE-Q and lab-based measures of prediction, and understanding how the PRE-Q may be used to identify potential areas for clinical supports for individuals with prediction-related challenges. |
| first_indexed | 2024-09-23T07:55:38Z |
| format | Article |
| id | mit-1721.1/154927 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2025-02-19T04:16:38Z |
| publishDate | 2024 |
| publisher | Springer Science and Business Media LLC |
| record_format | dspace |
| spelling | mit-1721.1/1549272024-12-23T06:41:51Z Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire O’Brien, Amanda M. May, Toni A. Koskey, Kristin L. K. Bungert, Lindsay Cardinaux, Annie Cannon, Jonathan Treves, Isaac N. D’Mello, Anila M. Joseph, Robert M. Li, Cindy Diamond, Sidney Gabrieli, John D. E. Sinha, Pawan McGovern Institute for Brain Research at MIT Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Purpose Predictions are complex, multisensory, and dynamic processes involving real-time adjustments based on environmental inputs. Disruptions to prediction abilities have been proposed to underlie characteristics associated with autism. While there is substantial empirical literature related to prediction, the field lacks a self-assessment measure of prediction skills related to daily tasks. Such a measure would be useful to better understand the nature of day-to-day prediction-related activities and characterize these abilities in individuals who struggle with prediction. Methods An interdisciplinary mixed-methods approach was utilized to develop and validate a self-report questionnaire of prediction skills for adults, the Prediction-Related Experiences Questionnaire (PRE-Q). Two rounds of online field testing were completed in samples of autistic and neurotypical (NT) adults. Qualitative feedback from a subset of these participants regarding question content and quality was integrated and Rasch modeling of the item responses was applied. Results The final PRE-Q includes 19 items across 3 domains (Sensory, Motor, Social), with evidence supporting the validity of the measure’s 4-point response categories, internal structure, and relationship to other outcome measures associated with prediction. Consistent with models of prediction challenges in autism, autistic participants indicated more prediction-related difficulties than the NT group. Conclusions This study provides evidence for the validity of a novel self-report questionnaire designed to measure the day-to-day prediction skills of autistic and non-autistic adults. Future research should focus on characterizing the relationship between the PRE-Q and lab-based measures of prediction, and understanding how the PRE-Q may be used to identify potential areas for clinical supports for individuals with prediction-related challenges. 2024-05-13T16:11:00Z 2024-05-13T16:11:00Z 2024-05-07 2024-05-12T03:11:46Z Article http://purl.org/eprint/type/JournalArticle 0162-3257 1573-3432 https://hdl.handle.net/1721.1/154927 O’Brien, A.M., May, T.A., Koskey, K.L.K. et al. Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire. J Autism Dev Disord (2024). PUBLISHER_CC en 10.1007/s10803-024-06379-2 Journal of Autism and Developmental Disorders Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer Science and Business Media LLC Springer US |
| spellingShingle | O’Brien, Amanda M. May, Toni A. Koskey, Kristin L. K. Bungert, Lindsay Cardinaux, Annie Cannon, Jonathan Treves, Isaac N. D’Mello, Anila M. Joseph, Robert M. Li, Cindy Diamond, Sidney Gabrieli, John D. E. Sinha, Pawan Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire |
| title | Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire |
| title_full | Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire |
| title_fullStr | Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire |
| title_full_unstemmed | Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire |
| title_short | Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire |
| title_sort | development of a self report measure of prediction in daily life the prediction related experiences questionnaire |
| url | https://hdl.handle.net/1721.1/154927 |
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