Beyond interviews: professional assessment narratives as ecologically grounded qualitative data for understanding autistic masking

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Wheeler, M. (2026). Beyond interviews: professional assessment narratives as ecologically grounded qualitative data for understanding autistic masking. Advances in Autism, 1-16. https://doi.org/10.1108/aia-03-2026-0028

Publication date: 1 Sep 2026 Added to AutiHub: 26 Oct 2026 Type: Article Article language: English
Publisher source (DOI) OpenAlex source

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Authors

Publication authors
1
Publication authors identified as autistic
1 / 1 (100.0%)
  1. Marc Wheeler *

Abstract

Purpose This study aims to explore how autistic masking may be identifiable within routinely generated professional assessment narratives. While research on camouflaging has relied largely on interviews and retrospective self-report, educational and clinical assessments generate extensive narrative documentation describing pupils’ functioning across contexts. The paper advances the argument that practitioner-generated assessment narratives constitute an under-recognised form of naturally occurring qualitative data capable of illuminating masking-related processes in real-world developmental contexts. Design/methodology/approach This study adopts a conceptual and practice-informed methodological perspective drawing on three sources: existing research on autistic masking, qualitative traditions concerned with naturally occurring documentary data and practitioner-informed insights from applied educational assessment contexts. Three adapted and anonymised excerpts from routine assessment documentation are presented solely to illustrate how the proposed framework may operate in practice. The examples were reviewed with a second practitioner to consider plausible alternative interpretations. Findings Masking-related processes may be reflected in assessment narratives through patterns of contextual discrepancy, effortful participation, competence–support mismatch and descriptions of fatigue or emotional cost. These patterns typically emerge through narrative comparison across contexts rather than isolated behavioural indicators. Professional documentation may therefore contain meaningful qualitative evidence of masked need that remains under-recognised when interpretation focuses primarily on observable behaviour or standardised measures. Originality/value The paper highlights practitioner-generated assessment narratives as an underused qualitative data source for autism research. By conceptualising these materials as ecologically grounded qualitative evidence, it extends methodological approaches to studying camouflaging and strengthens connections between autism research and applied professional practice.

Bibliography cited by this reference

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Cited bibliography overview

These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 27 Oct 2026 10:35.

Cited references
28
With a DOI
25
Without a DOI, from raw bibliography text
3
3 / 28 (10.7%) cited references include at least one author identified as autistic.
References with data to complete
0 / 28 (0.0%)
References with detected author names
28 / 28 (100.0%)
Without detected author names
0
Without a structured title
0
Without a stable identifier
3
References with raw author names still to review
0
References with external metadata lookup issues
0
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
107
From DOI or external metadata
107
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
0
67 / 107 (62.6%) names are linked to an author already present in AutiHub. 40 / 107 (37.4%) names are not yet linked.
Names linked to a person identified as autistic
7 / 107 (6.5%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 7 / 67 (10.4%). Distinct people identified as autistic: 7 / 94 (7.4%).
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