UZH-Logo

Maintenance Infos

Predicting perceived need for mental health care in a community sample: an application of the self-regulatory model


Oexle, Nathalie; Ajdacic-Gross, Vladeta; Müller, Mario; Rodgers, Stephanie; Rössler, Wulf; Rüsch, Nicolas (2015). Predicting perceived need for mental health care in a community sample: an application of the self-regulatory model. Social Psychiatry and Psychiatric Epidemiology, 50(10):1593-1600.

Abstract

PURPOSE: Most people with mental health problems do not use mental health services, resulting in poor psychiatric outcomes and greater illness burden. Although perceiving the need for mental health care was identified to be a key factor for service use, factors that explain differences in perceived need for mental health care are incompletely understood. The present paper investigates the role of illness representations in predicting perceived need for mental health care. METHODS: In a community sample of 202 persons currently distressed by symptoms related to mental illness, illness representations were assessed using the Brief Illness Perception Questionnaire and perceived need for mental health care was measured by the Self-Appraisal of Illness Questionnaire. Multiple linear regression models were used to determine the association between a person's illness representations and the level of perceived need for mental health care. RESULTS: Two illness representations were positively associated with perceived need for mental health care: the belief that treatment could improve the current mental health problem and the attribution of experienced symptoms to a mental health problem. Increased perceived need for care was related to current mental health service use. CONCLUSIONS: Interventions that aim to increase mental health service use could focus on people's attitudes toward mental health treatment and enable people to recognize symptoms as a mental illness.

Abstract

PURPOSE: Most people with mental health problems do not use mental health services, resulting in poor psychiatric outcomes and greater illness burden. Although perceiving the need for mental health care was identified to be a key factor for service use, factors that explain differences in perceived need for mental health care are incompletely understood. The present paper investigates the role of illness representations in predicting perceived need for mental health care. METHODS: In a community sample of 202 persons currently distressed by symptoms related to mental illness, illness representations were assessed using the Brief Illness Perception Questionnaire and perceived need for mental health care was measured by the Self-Appraisal of Illness Questionnaire. Multiple linear regression models were used to determine the association between a person's illness representations and the level of perceived need for mental health care. RESULTS: Two illness representations were positively associated with perceived need for mental health care: the belief that treatment could improve the current mental health problem and the attribution of experienced symptoms to a mental health problem. Increased perceived need for care was related to current mental health service use. CONCLUSIONS: Interventions that aim to increase mental health service use could focus on people's attitudes toward mental health treatment and enable people to recognize symptoms as a mental illness.

Citations

2 citations in Web of Science®
2 citations in Scopus®
Google Scholar™

Altmetrics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Psychiatric University Hospital Zurich > Clinic for Psychiatry, Psychotherapy, and Psychosomatics
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2015
Deposited On:15 Dec 2015 11:43
Last Modified:05 Apr 2016 19:41
Publisher:Springer
ISSN:0933-7954
Publisher DOI:https://doi.org/10.1007/s00127-015-1085-3
PubMed ID:26084865

Download

Full text not available from this repository.
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations