Background: Although a range of risk factors have been linked with poor mental health across the population, the underlying pathways leading to mental ill health remain unclear. There is a need to investigate the effects and interplay of both protective and risk factors. This population-based study aimed to explore the effects of individual and contextual factors on mental health status. Record-linkage was implemented between health and lifestyle data drawn from HealthWise Wales (HWW), a national population health survey of people > 16 years who live or access their healthcare in Wales, and treatment data from primary healthcare records. Mental health status was assessed using three different measures, including the self-reported MHI-5 and WEMWBS scales and mental health treatment in electronic healthcare records (EHR).
Result: Using cross-sectional data from 27,869 HWW participants aged over 16 years, lifestyle factors, resilience, social cohesion and neighbourhood attraction were associated with mental health across all measures. However, compared to contextual factors, the cluster of individual factors was more closely associated with poor mental health, explaining more of the variance across all measures used (MHI-5: 9.8% versus 5.4%; WEMWBS: 15.9% versus 10.3%; EHR: 5.5% versus 3.0%). Additional analysis on resilience sub-constructs indicated that personal skills were the most closely correlated with poorer mental health.
Conclusion: Mental health status was more closely linked with individual factors across the population than contextual factors. Interventions focusing on improving individual resilience and coping skills could improve mental health outcomes and reduce the negative effect of contextual factors such as negative neighbourhood perceptions.
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http://dx.doi.org/10.1186/s12889-022-13013-2 | DOI Listing |
J Med Internet Res
January 2025
Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, Ulm University, Ulm, Germany.
Background: Unobtrusively collected objective sensor data from everyday devices like smartphones provide a novel paradigm to infer mental health symptoms. This process, called smart sensing, allows a fine-grained assessment of various features (eg, time spent at home based on the GPS sensor). Based on its prevalence and impact, depression is a promising target for smart sensing.
View Article and Find Full Text PDFJ Prim Care Community Health
January 2025
Instituto de Investigación Biomédica de Málaga, Málaga, Spain.
Aim: To investigate the detection and initial management of first psychotic episodes, as well as established schizophrenia, within the primary care of the Andalusian Health System.
Background: Delay in detecting and treating psychosis is associated with slower recovery, higher relapse risk, and poorer long-term outcomes. Often, psychotic episodes go unnoticed for years before a diagnosis is established.
Personal Disord
January 2025
Laboratoire sur les Interactions Cognition, Action, Émotion (LICAE), UFR STAPS, Universite Paris-Nanterre.
This study aimed to assess measurement invariance for the Five-Factor Inventory for (Oltmanns & Widiger, 2020) across nine national samples from four continents ( = 6,342), and to validate a French translation in seven French-speaking national samples. All were convenience samples of adults. Exploratory factor analyses supported a four-factor structure in the French-speaking Western samples (Belgium, Canada, France, and Switzerland) while a three-factor structure was preferred in the French-speaking African samples (Burkina Faso and Togo), and no adequate structure was found in the Indian sample.
View Article and Find Full Text PDFPersonal Disord
January 2025
Department of Psychological Science, Kent State University.
Antagonism is a personality domain located in most major trait models and is central to multiple personality disorders. This construct has been linked to many societally harmful externalizing behaviors (e.g.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!