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For people living with mental illness, support from social network members, including family, romantic partners, and friends, is critical but often inadequate. However, robust theoretical explanations for why it might it be difficult to support people living with mental illness are lacking. We assessed an appraisal-based model of uncertainty, hypothesizing that fear and anxiety and supportive communication efficacy mediate the association between mental illness uncertainty and support provision (i.e., quantity and quality). We also predicted that perceptions of others' communication about their mental illness (i.e., ambiguity and volume) would exacerbate feelings of fear and anxiety in relation to uncertainty. Analyses of data gathered from 300 individuals across the United States (age = 34.07, = 9.49; 50% female) supported our central prediction; uncertainty had a negative direct or indirect effect on all support types and overall support quality, partly through decreases in supportive communication efficacy. Counter to predictions, fear and anxiety positively predicted support quantity for all types. Findings of this study point to a difficult situation for social network members: although uncertainty seems to motivate support provision by activating fear and anxiety, this effect could be undermined for forms of support that require complex communication skills (e.g., emotional, esteem, overall quality) through corresponding decreases in supportive communication efficacy. We discuss the theoretical and practical implications of this research for social support and relationships within the context of mental illness.
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http://dx.doi.org/10.1080/10410236.2020.1831166 | DOI Listing |
Alzheimers Dement
September 2025
Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
Introduction: We compared and measured alignment between the Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard used by electronic health records (EHRs), the Clinical Data Interchange Standards Consortium (CDISC) standards used by industry, and the Uniform Data Set (UDS) used by the Alzheimer's Disease Research Centers (ADRCs).
Methods: The ADRC UDS, consisting of 5959 data elements across eleven packets, was mapped to FHIR and CDISC standards by two independent mappers, with discrepancies adjudicated by experts.
Results: Forty-five percent of the 5959 UDS data elements mapped to the FHIR standard, indicating possible electronic obtainment from EHRs.
Hum Brain Mapp
September 2025
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA.
Investigating neuroimaging data to identify brain-based markers of mental illnesses has gained significant attention. Nevertheless, these endeavors encounter challenges arising from a reliance on symptoms and self-report assessments in making an initial diagnosis. The absence of biological data to delineate nosological categories hinders the provision of additional neurobiological insights into these disorders.
View Article and Find Full Text PDFInt J Dermatol
September 2025
Department of Dermatology, Emory University School of Medicine, Atlanta, Georgia, USA.
J Appl Res Intellect Disabil
September 2025
Department of Pedagogy, Faculty of Education and Social Work, University of Valladolid, Valladolid, Spain.
Background: Mental health (MH) problems are more common in people with intellectual disabilities (ID), yet under-diagnosis persists, which may be partly due to a lack of appropriate assessment tools. This study presents a systematic review of instruments used to assess MH problems in Spanish-speaking adults with ID.
Method: Following PRISMA guidelines, a search was conducted in Web of Science, PsycINFO, and Scopus using terms related to ID, MH and assessment.