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      Metacognitive beliefs and their relationship with anxiety and depression in physical illnesses: A systematic review

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          Abstract

          Anxiety and depression are common among patients with chronic physical illnesses and have a significant impact on morbidity, quality of life, and health service utilisation. Psychological treatment of anxiety and depression has small to moderate efficacy in this group and is not commonly based on a model of causal mechanisms. A novel approach to understanding and improving mental health outcomes in physical illnesses is needed. One approach may be to explore the role of metacognitive beliefs which are reliably associated with anxiety and depression in individuals with mental health difficulties. The current systematic review aimed to evaluate the contribution of metacognitive beliefs to anxiety and depression across physical illnesses. Systematic searches were conducted on Web of Science, PsychINFO, MEDLINE, Embase, and CINAHL of studies published between 1997 and January 2019. 13 eligible studies were identified that in sum comprised 2851 participants. Metacognitive beliefs were found to have reliable, moderate, positive and significant associations with anxiety and depression symptoms across a range of physical illnesses. There appeared to be commonality and some specificity in the relationships. Negative metacognitive beliefs concerned with uncontrollability and danger of worry were associated with both anxiety and depression across all physical illnesses assessed, whilst more specific associations emerged for individual medical conditions where positive beliefs about worry, cognitive confidence and cognitive self-consciousness were unique correlates. Negative metacognitive beliefs of uncontrollability and danger significantly and positively predicted symptoms of anxiety and depression after controlling for factors including age, gender, disease factors and cognition (illness perceptions and intolerance of uncertainty). The results suggest that the metacognitive model of psychological disorder is applicable to psychological symptoms of anxiety and depression across a range of chronic medical conditions, implying that metacognitive therapy might be helpful in improving outcomes in multiple morbidities that involve poor mental and medical health.

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          Most cited references58

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          Modelling cognition in emotional disorder: The S-REF model

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            The association between chronic illness, multimorbidity and depressive symptoms in an Australian primary care cohort.

            To assess the link between multimorbidity, type of chronic physical health problems and depressive symptoms The study was a cross-sectional postal survey conducted in 30 General Practices in Victoria, Australia as part of the diamond longitudinal study. Participants included 7,620 primary care attendees; 66% were females; age range from 18 to 76 years (mean = 51 years SD = 14); 81% were born in Australia; 64% were married and 67% lived in an urban area. The main outcome measures include the Centre for Epidemiologic Studies Depression Scale (CES-D) and a study-specific self-report check list of 12 common chronic physical health problems. The prevalence of probable depression increased with increasing number of chronic physical conditions (1 condition: 23%; 2 conditions: 27%; 3 conditions: 30%; 4 conditions: 31%; 5 or more conditions: 41%). Only 16% of those with no listed physical conditions recorded CES-D scores of 16 or above. Across the listed physical conditions the prevalence of 'probable depression' ranged from 24% for hypertension; 35% for emphysema; 35% for dermatitis to 36% for stroke. The dose-response relationship is reduced when functional limitations and self-rated health are taken into account, suggesting that these factors mediate the relationship. A clear dose-response relationship exists between the number of chronic physical problems and depressive symptoms. The relationship between multimorbidity and depression appears to be mediated via self-perceived health related quality of life. Primary care practitioners will identify more cases of depression if they focus on those with more than one chronic health problem, no matter what the problems may be, being especially aware in the group who rate their health as poor/fair.
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              Rating depressive patients.

              Various methods can be used for assessing symptoms of depression. These include check lists, scales for patient self-rating and rating scales completed by trained professional observers. Each technique has its special place in psychiatric research and each technique has its own strengths and weaknesses. A common concern on the part of psychiatrists is the fear that numerical assessment is dehumanizing. This is not the case as this method is intended only to make statistical analysis convenient and in no way reduces the concern for the subject's individuality. A commonly used depression rating scale, the Hamilton, has been extensively used in clinical trials of antidepressant drugs and for other purposes in clinical research. The various items of that scale are discussed and the system of rating explored from a clinician's point of view.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Investigation
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                10 September 2020
                2020
                : 15
                : 9
                : e0238457
                Affiliations
                [1 ] Research and Innovation, Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom
                [2 ] Division of Nursing, Midwifery & Social Work, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
                [3 ] Faculty of Biology, Medicine and Health, School of Psychological Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
                University of Vienna, AUSTRIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-6877-8650
                http://orcid.org/0000-0001-7713-1592
                Article
                PONE-D-20-00665
                10.1371/journal.pone.0238457
                7500039
                32911486
                15285f94-7ca3-4be4-84d7-ee308394aafa
                © 2020 Capobianco et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 10 January 2020
                : 17 August 2020
                Page count
                Figures: 1, Tables: 3, Pages: 19
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100007602, Programme Grants for Applied Research;
                Award ID: RP-PG-1211-20011
                Award Recipient :
                This study represents independent research funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research (PGfAR) Programme (Grant Reference Number RP-PG-1211-20011). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health.
                Categories
                Research Article
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognition
                Metacognition
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Depression
                Biology and Life Sciences
                Psychology
                Emotions
                Anxiety
                Social Sciences
                Psychology
                Emotions
                Anxiety
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Neuropsychiatric Disorders
                Anxiety Disorders
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Neuroses
                Anxiety Disorders
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Medicine and Health Sciences
                Neurology
                Epilepsy
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Clinical Psychology
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Clinical Psychology
                Social Sciences
                Psychology
                Cognitive Psychology
                Clinical Psychology
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Medical Conditions
                Metabolic Disorders
                Diabetes Mellitus
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files.

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