Exploring the factor structure of the mini-ICF-APP in an inpatient clinical sample, according to the psychiatric diagnosis

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.

Exploring the factor structure of the mini-ICF-APP in an inpatient clinical sample, according to the psychiatric diagnosis

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.

[Mental health and environmental health. A prospective view. SESPAS Report 2020]

Since the dawn of psychiatry, the environment has been an essential factor in the study and understanding of mental illness. Traditionally, the interrelationship between genome and environment has been a central theme in research on the etiopathogenesis of mental health problems and in the very conception of mental health. In its application to psychopathology and mental health, psychiatric enviromics was defined as «the study of environmental conditions and processes that promote mental health or increase the risk of developing mental disorders». However, environmental health -at least in Spain and in connection with its powers within the Spanish General Health System- has paid attention to aspects pertaining to risks associated with the physical, chemical and biological pollution of the air, the water and the ground, as well as to its correlation with food pollution. Although environmental risks such as air quality, extreme temperatures, noise, climate change and various environmental toxicants can play a particularly important role, they can hardly be identified as single etiopathogenic elements. This work reviews the recent literature on environmental research and problems of psychiatric morbidity and mortality. Although the results are inconclusive, future lines of research should consider a more agile interdisciplinary collaboration, allowing, on the one hand, a better understanding of mental illness and, on the other hand, to be able to shift from "traditional" environmental health to an environmental health that takes social environmental factors into account and seriously addresses the still little studied concept of "social pollution".