1. Exploring the factor structure of the mini-ICF-APP in an inpatient clinical sample, according to the psychiatric diagnosis
- Author
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Julio Bobes, Godehard Weniger, Erich Seifritz, Stephan T. Egger, Stefan Vetter, University of Zurich, and Egger, Stephan T
- Subjects
610 Medicine & health ,03 medical and health sciences ,2738 Psychiatry and Mental Health ,0302 clinical medicine ,Cronbach's alpha ,medicine ,Humans ,030212 general & internal medicine ,Bipolar disorder ,Depressive Disorder, Major ,Inpatients ,Mental Disorders ,General Medicine ,medicine.disease ,Personality disorders ,030227 psychiatry ,Psychiatry and Mental health ,Alcoholism ,Schizophrenia ,10054 Clinic for Psychiatry, Psychotherapy, and Psychosomatics ,Quality of Life ,Major depressive disorder ,Anxiety ,medicine.symptom ,Psychology ,Psychosocial ,Neurocognitive ,Clinical psychology - Abstract
Introduction Psychosocial functioning is a key factor determining prognosis, severity, impairment and quality of life in people who have a mental disorder. The mini-ICF-APP was developed to provide a standardised classification of functioning and disability. However, despite its gaining popularity little is known about its structure and performance. This paper examines the structure of the mini-ICF-APP using factor analysis techniques. Materials and methods In a clinical sample of 3178 patients, with psychiatric diagnoses from several ICD-10 categories, we analysed internal consistency, item inter-correlations and the factorial structure of the data, with reference to ICD-10 diagnostic categories; Neurocognitive Disorders; Alcohol Use Disorders; Substance Use Disorders; Schizophrenia and Psychotic Disorders; Bipolar Disorder; Major Depressive Disorder; Anxiety Disorders; Personality Disorders; and Neurodevelopmental Disorders. Results We found good internal consistency and item inter-correlations (Cronbach alpha = 0.92) for the mini-ICF-APP. We were able to identify pivotal domains (flexibility, assertiveness and intimate relationships), which demonstrate sub-threshold influences on other domains. The factor analysis yielded a one-factor model as ideal for the whole sample and for all diagnostic categories. For some diagnostic categories the data suggested a two or three-factor model, however, with poorer fit indices. Conclusions The factor structure of the mini-ICF-APP appears to modify according to the main diagnosis. However, a one-factor model demonstrates better fit regardless of diagnostic category. Consequently, we consider the mini-ICF-APP to be a trans-diagnostic measurement instrument for the assessment and grading of psychosocial functioning. The use of the mini-ICF-APP sum score seems to best reflect the degree of impairment in an individual, even taking into account that affected domains may lead to sub-threshold effects on other domains.
- Published
- 2021