Evidence map›Paper›PMID 36590603›Full record

ArticleFrontiers in psychiatry2022

Exploring the predictive properties of the Hayes Ability Screening Index subtest background information in identifying individuals with MBID among in-patients with SUD.

Kirsten J Braatveit, Jörg Assmus, Oddbjørn Hove

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 49% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Kirsten J BraatveitDepartment of Research and Innovation, Helse Fonna HF, Haugesund, Norway.
Jörg AssmusHelse Bergen HF, Haukeland University Hospital, Bergen, Norway.
Oddbjørn HoveDepartment of Research and Innovation, Helse Fonna HF, Haugesund, Norway.
Fonna Hospital TrustHaukeland University Hospital · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: For individuals with substance use disorder (SUD), mild to borderline intellectual disability (MBID) goes undetected in treatment clinics. The Hayes Ability Screening Index (HASI) has been found to be a valid, time-saving screening instrument for MBID in SUD treatment. MBID can have significant implications for treatment planning and outcomes. Therefore, it is important to have methods for the early recognition of these comorbid conditions. Because of less sensitivity to recent or ongoing substance use, the HASI subtest background information may be particularly valuable as an early screening of MBID. The main aim was to investigate the convergent, predictive, and discriminant validity of the HASI subtest background information in identifying in-patients with SUD as MBID or non-MBID. Methods: Eighty-four in-patients with SUD aged 19-64 participated in this multicentre study. MBID was diagnosed according to the ICD-10 using WAIS-IV, Vineland II, and self-reported childhood learning difficulties. Results: The main finding was that, among the HASI subtests, background information was the strongest predictor. A HASI background information cut between 6 and 7 showed a sensitivity of 78% and a specificity of 72%. Conclusion: The HASI subtest background information has acceptable convergent, predictive, and discriminant validity as a screening for MBID among in-patients in SUD treatment.

Indexed as

borderline intellectual disabilityinpatientintellectual disabilitylearning difficultiesscreeningsubstance use disorder

Identifiers

PMID36590603
PMCPMC9797666
OpenAlexW4312224167

What OpenQuestion holds

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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.