Dataset Information

The Heterogeneity of Mental Health Assessment.

ABSTRACT: Across the landscape of mental health research and diagnosis, there is a diverse range of questionnaires and interviews available for use by clinicians and researchers to determine patient treatment plans or investigate internal and external etiologies. Although individually, these tools have each been assessed for their validity and reliability, there is little research examining the consistency between them in terms of what symptoms they assess, and how they assess those symptoms. Here, we provide an analysis of 126 different questionnaires and interviews commonly used to diagnose and screen for 10 different disorder types including depression, anxiety, obsessive compulsive disorder (OCD), post-traumatic stress disorder (PTSD), attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), addiction, bipolar disorder, eating disorder, and schizophrenia, as well as comparator questionnaires and interviews that offer an all-in-one cross-disorder assessment of mental health. We demonstrate substantial inconsistency in the inclusion and emphasis of symptoms assessed within disorders as well as considerable symptom overlap across disorder-specific tools. Within the same disorder, similarity scores across assessment tools ranged from 29% for assessment of bipolar disorder to a maximum of 58% for OCD. Furthermore, when looking across disorders, 60% of symptoms were assessed in at least half of all disorders illustrating the extensive overlap in symptom profiles between disorder-specific assessment tools. Biases in assessment toward emotional, cognitive, physical or behavioral symptoms were also observed, further adding to the heterogeneity across assessments. Analysis of other characteristics such as the time period over which symptoms were assessed, as well as whether there was a focus toward frequency, severity or duration of symptoms also varied substantially across assessment tools. The consequence of this inconsistent and heterogeneous assessment landscape is that it hinders clinical diagnosis and treatment and frustrates understanding of the social, environmental, and biological factors that contribute to mental health symptoms and disorders. Altogether, it underscores the need for standardized assessment tools that are more disorder agnostic and span the full spectrum of mental health symptoms to aid the understanding of underlying etiologies and the discovery of new treatments for psychiatric dysfunction.

SUBMITTER: Newson JJ

PROVIDER: S-EPMC7057249 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The Heterogeneity of Mental Health Assessment.

Newson Jennifer J JJ Hunter Daniel D Thiagarajan Tara C TC

Frontiers in psychiatry 20200227

Across the landscape of mental health research and diagnosis, there is a diverse range of questionnaires and interviews available for use by clinicians and researchers to determine patient treatment plans or investigate internal and external etiologies. Although individually, these tools have each been assessed for their validity and reliability, there is little research examining the consistency between them in terms of what symptoms they assess, and how they assess those symptoms. Here, we pro ...[more]

PMID: 32174852

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Project description:IntroductionThe initial year of medical school is linked to a decline in mental health. To assess mental health comprehensively, the dual-factor model posits the consideration of both psychopathology (e.g., depression) and positive mental health (e.g., well-being). Previous mental health research among medical students has primarily examined these two factors independently. This study uses the dual-factor approach for a deeper understanding of mental health changes during the first year of medical school.MethodsStudents from eight German medical schools (N = 450) were surveyed three times (T0 = entering medical school, T1 = end of the first semester, T2 = end of the second semester) regarding depression (PHQ-9), well-being (subscale of FAHW-12), and general life satisfaction (German Single-Item Scale L1). Latent profile analysis was used to identify distinct mental health groups based on their combinations of psychopathology and positive mental health. We then analysed trajectories descriptively by examining the longitudinal stability and dynamics of mental health group membership during the first year of medical school.ResultsWe identified five mental health groups: (1) complete mental health, (2) moderately mentally healthy, (3) symptomatic but content, (4) vulnerable, and (5) troubled. The examination of change trajectories unveiled diverse paths pointing towards both recovery and deterioration. In comparison to the other groups, students belonging to the complete mental health group exhibited greater stability and a higher potential to recover after initial deteriorations in the first semester.ConclusionsOur study uncovers distinct mental health trajectories in the first year of medical school, emphasizing the crucial role of initial mental health status. Our findings stress the diverse nature of mental health changes in medical students, underscoring the need for tailored prevention strategies. The implications for research and practice are discussed.

Project description:BackgroundThe worldwide rise in common mental disorders (CMDs) is posing challenges in the provision of and access to care, particularly for immigrant, refugee and racialized groups from low-income backgrounds. eHealth tools, such as the Interactive Computer-Assisted Client Assessment Survey (iCCAS) may reduce some barriers to access. iCCAS is a tablet-based, touch-screen self-assessment completed by clients while waiting to see their family physician (FP) or nurse practitioner (NP). In an academic-community initiative, iCCAS was made available in English and Spanish at a Community Health Centre in Toronto through a mixed-method trial.MethodsThis paper reports the perspectives of clients in the iCCAS group (n = 74) collected through an exit survey, and the perspectives of 9 providers (four FP and five NP) gathered through qualitative interviews. Client acceptance of the tool was assessed for cognitive and technical dimensions of their experience. They rated twelve items for perceived Benefits and Barriers and four questions for the technical quality.ResultsMost clients reported that the iCCAS completion time was acceptable (94.5 %), the touch-screen was easy to use (97.3 %), and the instructions (93.2 %) and questions (94.6 %) were clear. Clients endorsed the tool's Benefits, but were unsure about Barriers to information privacy and provider interaction (mean 4.1, 2.6 and 2.8, respectively on a five-point scale). Qualitative analysis of the provider interviews identified five themes: challenges in Assessing Mental Health Services, such as case complexity, time, language and stigma; the Tool's Benefits, including non-intrusive prompting of clients to discuss mental health, and facilitation of providers' assessment and care plans; the Tool's Integration into everyday practice; Challenges for Use (e.g. time); and Promoting Integration Effectively, centered on the timing of screening, setting readiness, language diversity, and technological advances.ConclusionsParticipant clients and providers perceived iCCAS as an easy and useful tool for mental health assessments at the Community Health Centre and similar settings. The findings are anticipated to inform further work in this area.Trial registrationClinicalTrials.gov; NCT02023957 ; Registered retrospectively 12 Dec. 2013.

Project description:BACKGROUND AND HYPOTHESIS: Heterogeneity in clinical manifestations and disease progression in Chronic Obstructive Pulmonary Disease (COPD) lead to consequences for patient health risk assessment, stratification and management. Implicit with the classical "spill over" hypothesis is that COPD heterogeneity is driven by the pulmonary events of the disease. Alternatively, we hypothesized that COPD heterogeneities result from the interplay of mechanisms governing three conceptually different phenomena: 1) pulmonary disease, 2) systemic effects of COPD and 3) co-morbidity clustering, each of them with their own dynamics. OBJECTIVE AND METHOD: To explore the potential of a systems analysis of COPD heterogeneity focused on skeletal muscle dysfunction and on co-morbidity clustering aiming at generating predictive modeling with impact on patient management. To this end, strategies combining deterministic modeling and network medicine analyses of the Biobridge dataset were used to investigate the mechanisms of skeletal muscle dysfunction. An independent data driven analysis of co-morbidity clustering examining associated genes and pathways was performed using a large dataset (ICD9-CM data from Medicare, 13 million people). Finally, a targeted network analysis using the outcomes of the two approaches (skeletal muscle dysfunction and co-morbidity clustering) explored shared pathways between these phenomena. RESULTS: (1) Evidence of abnormal regulation of skeletal muscle bioenergetics and skeletal muscle remodeling showing a significant association with nitroso-redox disequilibrium was observed in COPD; (2) COPD patients presented higher risk for co-morbidity clustering than non-COPD patients increasing with ageing; and, (3) the on-going targeted network analyses suggests shared pathways between skeletal muscle dysfunction and co-morbidity clustering. CONCLUSIONS: The results indicate the high potential of a systems approach to address COPD heterogeneity. Significant knowledge gaps were identified that are relevant to shape strategies aiming at fostering 4P Medicine for patients with COPD.

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The Heterogeneity of Mental Health Assessment.

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The Heterogeneity of Mental Health Assessment.

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