Bornman, Juan, 1968-2025-01-222025-01-222025-042024-10*A2025http://hdl.handle.net/2263/100249DOI: https://doi.org/10.25403/UPresearchdata.27824676.v2Mini Dissertation (MA (Augmentative and Alternative Communication))--University of Pretoria, 2024.Background: Due to its ability to distribute information to a vast consumer audience, the mainstream mass media has globally played an essential role in increasing public awareness of Autism Spectrum Disorder (ASD) and the myriad of interventions that accompany it. This increased media focus often makes it difficult for stakeholders to separate legitimate science-based intervention options with a clear evidence-base from pseudoscience and/or anti-sciences. Subsequently, there has also been an increased awareness as to the importance of so-called ‘red flags’ (i.e., warning signs) to identify such pseudoscientific intervention programmes. However, no clear guidelines could be found in the literature that stakeholders could utilise to guide them in recognising inaccurate or questionable sources of information that represent pseudoscientific ASD intervention programmes. Aims: This study aims to firstly synthesise and describe the warning signs (i.e., red flags) that have been introduced and described in the literature for stakeholders to gauge the research evidence-base of intervention programmes for children with autism by means of a scoping review. Secondly, to socially validate these red flags with experts with the intention of proposing a ‘red flag’ checklist that can be used by all stakeholders to gauge the scientific basis of ASD intervention programmes. Method: This study utilises a six-step scoping review methodology to map out the broad body of relevant literature concerning the outlined research question. Search terms were entered into eight databases and two journals were hand searched following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping reviews (PRISMA-ScR) guidelines. A total of 171 records were identified. Following the removal of duplicates and applying the inclusion and exclusion criteria, seven publications remained from which data were extracted and synthesised. A qualitative content analysis framework was used to categorise data into main themes (i.e., red flags). Step 6 included a custom-designed survey based on the results of steps 1 to 5 of the review. It required experts within the field of autism to comment on the retention, adaption, or removal of the specific red flags. Descriptive statistics were utilised to analyse the survey data. Results: Results from the scoping review indicated that publications regarding the ‘red flags’ or warning signs associated with intervention programmes have increased over the last decade, and were mostly aimed at practitioners. In total, 87 red flags were mentioned in the literature, which were then collated under 13 main themes. During the social validation phase, participants agreed that more than half of the proposed red flags could be retained in their current format and none of the red flags needed to be removed. Adaptations were proposed for five signs, and these were primarily focused on linguistic and conceptual changes. Conclusion: The availability of a freely accessible, easy-to-understand-and-use ‘red flag’ checklist may assist stakeholders to identify and distinguish between ASD intervention programmes with and without a credible evidence-base.en© 2023 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.UCTDSustainable Development Goals (SDGs)AntiscienceAutism spectrum disorder (ASD)Evidence-based practice (E3BP)Intervention programmesNon-evidence-based practicePseudoscienceRed flagsStakeholdersWarning signsDeveloping a ‘red flag’ checklist to identify ASD intervention programmes without a clear evidence base : a scoping review with expert panel social validationMini Dissertationu17134902https://doi.org/10.25403/UPresearchdata.27824676