Background: Researchers have examined the relationship between mental health and weather/pollution with mixed results. The current study aimed to examine a range of weather and atmospheric phenomena and their association with time-bound mental health data.
Methods: Nineteen different weather/pollution variables were examined in connection with an archive of self-reported mental health data for university students participating in mental health treatment (n=16,452) using the Outcome Questionnaire 45.2 (OQ-45). Statistical approach involved randomly selecting 500 subjects from the sample 1000 different times and testing each variable of interest using mixed models analyses.
Results: Seasonal changes in sun time were found to best account for relationships between weather variables and variability in mental health distress. Increased mental health distress was found during periods of reduced sun time hours. A separate analysis examining subjects' endorsement of a suicidality item, though not statistically significant, demonstrated a similar pattern. Initial results showed a relationship between pollution and changes in mental health distress; however, this was mediated by sun time.
Limitations: This study examined a relatively homogenous, predominantly European American, and religious sample of college counseling clients from an area that is subject to inversions and is at a high altitude and a latitude where sun time vacillates significantly more than locations closer to the equator.
Conclusions: Seasonal increases in sun time were associated with decreased mental health distress. This suggests the need for institutions and public health entities to plan for intervention and prevention resources and strategies during periods of reduced sun time.
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http://dx.doi.org/10.1016/j.jad.2016.07.021 | DOI Listing |
J Neural Transm (Vienna)
January 2025
Laboratory of Biological Psychiatry, Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, 13 Liulin Road, Tianjin, 300222, China.
Bipolar disorder (BD) frequently coexists with anxiety disorders, creating complex challenges in clinical therapy and management. This study investigates the prevalence, prognostic implications, and treatment strategies for comorbid BD and anxiety disorders. High comorbidity rates, particularly with generalized anxiety disorder, underscore the necessity of thorough clinical assessments to guide effective management.
View Article and Find Full Text PDFJ Immigr Minor Health
January 2025
Watson Institute for International and Public Affairs and the School of Public Health, Brown University, Providence, USA.
Eur J Hum Genet
January 2025
Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India.
Mitochondrial membrane protein-associated neurodegeneration (MPAN) is a rare neurodegenerative disorder characterized by spastic paraplegia, parkinsonism and psychiatric and/or behavioral symptoms caused by variants in gene encoding chromosome-19 open reading frame-12 (C19orf12). We present here seven patients from six unrelated families with detailed clinical, radiological, and genetic investigations. Childhood-onset patients predominantly had a spastic ataxic phenotype with optic atrophy, while adult-onset patients were presented with cognitive, behavioral, and parkinsonian symptoms.
View Article and Find Full Text PDFJ Occup Rehabil
January 2025
Faculty of Health Sciences, Curtin School of Allied Health, Curtin University, Perth, WA, Australia.
Purpose: Workers' compensation claims can negatively affect the wellbeing of injured workers. For some, these negative effects continue beyond finalisation of the workers' compensation claim. It is unclear what factors influence wellbeing following finalisation of a workers' compensation claim.
View Article and Find Full Text PDFCommun Psychol
January 2025
Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
How do people model the world's dynamics to guide mental simulation and evaluate choices? One prominent approach, the Successor Representation (SR), takes advantage of temporal abstraction of future states: by aggregating trajectory predictions over multiple timesteps, the brain can avoid the costs of iterative, multi-step mental simulation. Human behavior broadly shows signatures of such temporal abstraction, but finer-grained characterization of individuals' strategies and their dynamic adjustment remains an open question. We developed a task to measure SR usage during dynamic, trial-by-trial learning.
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