Functional Interviewing Was Associated With Improved Agreement Among Expert Psychiatrists in Estimating Claimant Work Capacity: A Secondary Data Analysis of Real-Life Work Disability Evaluations.

International Classification of Functioning, Disability and Health disability evaluation evaluation studies evidence-based medicine independent medical evaluation mental disorders work capacity evaluation work participation

Journal

Frontiers in psychiatry
ISSN: 1664-0640
Titre abrégé: Front Psychiatry
Pays: Switzerland
ID NLM: 101545006

Informations de publication

Date de publication:
2020
Historique:
received: 05 02 2020
accepted: 15 06 2020
entrez: 29 7 2020
pubmed: 29 7 2020
medline: 29 7 2020
Statut: epublish

Résumé

Functional evaluations establish functional and work (in-)capacities in the context of disability assessments and are increasingly recommended as a modern technique for work disability assessments. The RELY (Reliable disability EvaLuation in psychiatrY)-studies introduced semi-structured functional interviews in real-life assessments of claimants with mental disorders for evaluating their self-perceived health-related limitations and for investigating the reproducibility of work capacity (WC) estimates. Functional interviews elicit claimants' self-perceptions about their work-related limitations and capacities in the labour market. This secondary data analysis explored the coverage of work-related key topics in these interviews and investigated whether interviews with high coverage (versus low coverage) of work-related topics resulted in better reproducibility of WC estimates among experts. Thirty video-taped RELY-assessments underwent a content analysis along a predefined framework for functional interviewing, including the claimant's self-perceived work limitations and work-related health complaints as centrepieces of functional interviewing. Following transcription, interviews were segmented into coding units. Coding units were allocated to the five steps with 19 key topics of the framework. Enquiry into key topics was ascertained by summing the functional coding units per key topic. Median split grouped the interviews into high and low coverage of functional topics and compared them for inter-rater reliability (intraclass correlation coefficient, ICC) and inter-rater agreement (standard error of measurement, SEM). Interviews were broken down in 40,010 coding units, 31% of which addressed functional topics. Enquiries in self-perceived work limitations and work-related health complaints were sparse (coding units median Content analysis showed little enquiry by experts on claimants' self-perceived activity limitations and work-related capacity. The association between interviews with higher functional coverage and better expert agreement on the claimants' remaining WC requires confirmation in prospective studies.

Identifiants

pubmed: 32719624
doi: 10.3389/fpsyt.2020.00621
pmc: PMC7350701
doi:

Types de publication

Journal Article

Langues

eng

Pagination

621

Informations de copyright

Copyright © 2020 von Allmen, Kedzia, Dettwiler, Vogel, Kunz and de Boer.

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Auteurs

David Y von Allmen (DY)

Evidence-based Insurance Medicine, Department of Clinical Research, University of Basel and University Hospital of Basel, Basel, Switzerland.

Sarah Kedzia (S)

Evidence-based Insurance Medicine, Department of Clinical Research, University of Basel and University Hospital of Basel, Basel, Switzerland.

Raphael Dettwiler (R)

Evidence-based Insurance Medicine, Department of Clinical Research, University of Basel and University Hospital of Basel, Basel, Switzerland.

Nicole Vogel (N)

Evidence-based Insurance Medicine, Department of Clinical Research, University of Basel and University Hospital of Basel, Basel, Switzerland.

Regina Kunz (R)

Evidence-based Insurance Medicine, Department of Clinical Research, University of Basel and University Hospital of Basel, Basel, Switzerland.

Wout E L de Boer (WEL)

Evidence-based Insurance Medicine, Department of Clinical Research, University of Basel and University Hospital of Basel, Basel, Switzerland.

Classifications MeSH