Evidence map›Paper›PMID 40906054›Full record

ArticleJournal of autism and developmental disorders2025

Measurement of Anxiety and Depression Among Autistic Adults: Concordance Between Diagnostic and Screening Instruments in a Feasibility Study.

Annabelle M Mournet, Linnea A Lampinen, Lauren A Pepa, Gentiana Kukaj, Brian C Chu, Vanessa H Bal

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Article in Journal of autism and developmental disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Annabelle M MournetRutgers, The State University of New Jersey, Piscataway, USA.
Linnea A LampinenRutgers, The State University of New Jersey, Piscataway, USA.
Lauren A PepaRutgers, The State University of New Jersey, Piscataway, USA.
Gentiana KukajRutgers, The State University of New Jersey, Piscataway, USA.
Brian C ChuRutgers, The State University of New Jersey, Piscataway, USA.
Vanessa H BalRutgers, The State University of New Jersey, Piscataway, USA. Vanessa.bal@rutgers.edu.ORCID http://orcid.org/0000-0003-0750-823X

Funding

GSAPP Collaborative Autism Grant funded by Rutgers New Brunswick Chancellor-Provost Strategic Initiative Funds GSAPP Collaborative Autism Grant funded by Rutgers New Brunswick Chancellor-Provost Strategic Initiative FundsNew Jersey Governor's Council for Medical Research and Treatment of Autism CAUT23APL008
6 · The paper itself

Abstract

The current study aims to report on the concordance between the PHQ-9, GAD-7, Adult Self Report (ASR), Anxiety and Related Disorders Interview Schedule for DSM-5 (ADIS-5), and best estimate clinical diagnosis (BECD) among autistic adults. The current analyses leverage baseline data from a feasibility treatment study of autistic adults receiving group behavioral activation therapy to address anxiety and depressive symptoms. Interclass correlation coefficients, area under the curve, sensitivity, and specificity were computed to compare the tools to one another at various clinical cut-off levels. Post-intervention outcome data were used for internal replication. The ADIS-5 classifications of Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD) had strong concordance in comparison to the BECD in the Baseline comparisons, but more variable in the Outcome data. For the GAD-7, the mild cut-off had the highest concordance with BECD of any anxiety condition. PHQ-9 moderate cut-off performed most consistently with BECD and ADIS-5 MDD diagnosis. The present analyses further highlight the need for ongoing systematic investigation of the validity of anxiety and depression screening and diagnostic tools in autistic adults. Brief screening tools appear to serve their function well; more research on clinical diagnostic interviews (e.g., ADIS-5) will be needed to standardize diagnostic practices and inclusion in clinical trials. For now, BECDs of co-occurring conditions should remain the gold standard in clinical research aimed at understanding and treating co-occurring conditions in autistic adults.

Indexed as

AdultsAnxietyAutismDepressionMeasurement

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.