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1,558 results for “Mental Health”
Data from: Why we need more nature at work: effects of natural elements and sunlight on employee mental health and work attitudes
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Data from: Mental health status of Sri Lanka Navy personnel three years after end of combat operations: a follow up study
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Predictors of controlled prescription drug nonmedical and lifetime use among patients accessing public mental health services in Uganda: a cross-sectional study
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Training beyond borders: A WPA pilot project for child and adolescent mental health course in Pakistan
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Supplementary material 2 from: Hyam R (2020) Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study. Research Ideas and Outcomes 6: e53542. https://doi.org/10.3897/rio.6.e53542
Landsat Products Used
Figure 3 from: Hyam R (2020) Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study. Research Ideas and Outcomes 6: e53542. https://doi.org/10.3897/rio.6.e53542
Figure 3 Mental health prescriptions vs winter-greenness at 250 m from home for pure-urban Data Zones beanplot (Kampstra 2008). Horizontal lines are individual values. Curves are density of data points at values. Thicker horizontal line is average for group.
Supplementary material 1 from: Hyam R (2020) Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study. Research Ideas and Outcomes 6: e53542. https://doi.org/10.3897/rio.6.e53542
ESRI Shape file of SIMD DataZones
Figure 2 from: Hyam R (2020) Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study. Research Ideas and Outcomes 6: e53542. https://doi.org/10.3897/rio.6.e53542
Figure 2 Sampling of a single data point, postcode EH8 9AJ (orange dot) within Data Zone S01008671 (black outline). The 100, 250 and 500 metre buffer zones are shown in orange. Blue dots are other sampling points. Green shading represents greenness (NDVI).
Figure 4 from: Hyam R (2020) Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study. Research Ideas and Outcomes 6: e53542. https://doi.org/10.3897/rio.6.e53542
Figure 4 Mental health prescriptions vs seasonal difference at 250 m from home for pure-urban Data Zones beanplot (Kampstra 2008). Horizontal lines are individual values. Curves are density of data points at values. Thicker horizontal line is average for group.
Figure 1 from: Hyam R (2020) Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study. Research Ideas and Outcomes 6: e53542. https://doi.org/10.3897/rio.6.e53542
Figure 1 An area of south central Edinburgh illustrating distribution of sample points within Data Zones. Background is OpenStreetMap. Black outlines are DataZone boundaries. Blue dots are small user postcode locations that are used for sampling. Green shading represents summer-greenness (NDVI).
Supplementary material 4 from: Hyam R (2020) Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study. Research Ideas and Outcomes 6: e53542. https://doi.org/10.3897/rio.6.e53542
Results Data Tables
Supplementary material 3 from: Hyam R (2020) Greenness, mortality and mental health prescription rates in urban Scotland - a population level, observational study. Research Ideas and Outcomes 6: e53542. https://doi.org/10.3897/rio.6.e53542
Small User Postcodes
Outdoor activity participation improves adolescents' mental health and well-being during the COVID-19 pandemic
<p>The COVID-19 pandemic is reshaping human interactions with the natural environment, generating profound consequences for health and well-being. To assess the effects of COVID-19 on the outdoor recreation participation and well-being of adolescents we conducted a nationally representative survey of youth ages 10-18 across the United States (n = 624) using a Qualtrics XM panel between April 30 and June 15, 2020. Survey questions focused on frequency of participation in several types of outdoor activities before and during the pandemic. Activity categories included outdoor play activities (e.g., running, biking), nature-based activities (e.g., camping, fishing), and spending outdoor time with family. We assessed changes in the psychological health of youth using a four-item subjective well-being scale validated by the World Health Organization. Paired t-tests revealed significant decreases in both outdoor recreation participation (64% of youth reported declines) and subjective well-being (52% reported declines) during the pandemic. A regression model examining correlates of changes in subjective well-being (<i>R<sup>2</sup></i>=0.42) revealed strong associations between subjective well-being and changes in outdoor play activities (<i>B</i>=0.44, <i>p</i><0.001) and changes in nature-based activities (<i>B</i>=0.21, <i>p</i>=0.016). Youth who continued to participate in these activities during COVID-19 reported significantly smaller drops in subjective well-being, whereas youth whose outdoor participation waned were more negatively impacted by the pandemic. Furthermore, youth who reported high levels of outdoor play activity participation before the pandemic were also less likely to experience post-COVID-19 declines in subjective well-being. These results contribute to our understanding of adolescent psychological reactions to the COVID-19 pandemic, as well as highlighting the critical role that time outdoors and time in nature can play in bolstering youth resilience to environmental stressors.</p>
Data from: Health assessment of French university students and risk factors associated with mental health disorders
Objective: The first year of university is a particularly stressful period and can impact academic performance and students' health. The aim of this study was to evaluate the health and lifestyle of undergraduates and assess risk factors associated with psychiatric symptoms. Materials and methods: Between September 2012 and June 2013, we included all undergraduate students who underwent compulsory a medical visit at the university medical service in Nice (France) during which they were screened for potential diseases during a diagnostic interview. Data were collected prospectively in the CALCIUM database (Consultations Assistés par Logiciel pour les Centres Inter-Universitaire de Médecine) and included information about the students' lifestyle (living conditions, dietary behavior, physical activity, use of recreational drugs). The prevalence of psychiatric symptoms related to depression, anxiety and panic attacks was assessed and risk factors for these symptoms were analyzed using logistic regression. Results: A total of 4,184 undergraduates were included. Prevalence for depression, anxiety and panic attacks were 12.6%, 7.6% and 1.0%, respectively. During the 30 days preceding the evaluation, 0.6% of the students regularly drank alcohol, 6.3% were frequent-to-heavy tobacco smokers, and 10.0% smoked marijuana. Dealing with financial difficulties and having learning disabilities were associated with psychiatric symptoms. Students who were dissatisfied with their living conditions and those with poor dietary behavior were at risk of depression. Being a woman and living alone were associated with anxiety. Students who screened positively for any psychiatric disorder assessed were at a higher risk of having another psychiatric disorder concomitantly. Conclusion: The prevalence of psychiatric disorders in undergraduate students is low but the rate of students at risk of developing chronic disease is far from being negligible. Understanding predictors for these symptoms may improve students' health by implementing targeted prevention campaigns. Further research in other French universities is necessary to confirm our results.
THE IMPORTANCE OF POSITIVE AND NEGATIVE RELIGIOUS COPING STYLES IN MENTAL HEALTH AMONG BULLIED AND NON-BULLIED STUDENTS IN INDONESIA
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Figure 1 from: Liebal K, Denzer V, Eisenhauer N, Fritsche I, Kunzmann U, Oña L, Quaas MF, Staude I, Wirth C (2024) Biodiversity, mental health and well-being: psychological mechanisms and moderators of a complex relationship (BIOWELL). Research Ideas and Outcomes 10: e116333. https://doi.org/10.3897/rio.10.e116333
Figure 1 BIOWELL objectives and related work packages. We will use a mixed-method approach collecting data in controlled experimental field settings, uncontrolled field settings (marked with tree: forests, green spaces, gardens) and in the laboratory (marked with conical flask: e.g., eye-tracking experiments). WP5 will integrate the results of the single work packages and build a synthesised model at the end of the project term.
EFFECT OF THE COMMUNITY IN PROVIDING MENTAL HEALTH
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Mental Health Outcomes and Their Correlates in the Post-COVID-19 Era Among University Students and Staff in Indonesia
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COVID 19 Mental Health Survey May 2020-May 2021
<p>This data set assesses the mental health of four separate cohorts across mainly the UK and Germany each one at a different time point using an online survey. The COVID-19 exposure and COVID-19 related mental health survey was designed as an online survey using EvaSys (https://www.evasys.de, Electric Paper Evaluationssysteme GmbH, Luneburg, Germany), see Knolle et al. (2021, BMC psychology) or Daimer et al. (2021, Frontiers psychology) for a detailed description. The questionnaires were available in German and English. For participant recruitment we used a snowball sampling strategy to reach the general public in Germany and the UK. The “Spring 2020 survey” was collected from 27/04/2020 - 31/05/2020, approximately five weeks after the introduction of the nationwide lockdowns in the UK and Germany. Completion of this first survey took approximately 35 min. The three follow-up surveys took only about 15 minutes, as they did not include question on subjective change of psychological distress (“Autumn 2020 survey”: 10/09/2020 – 18/10/2020; “Winter 2021 survey”: 10/01/2021 – 07/02/2021; “Spring 2021 survey”: 01/05/2021 – 31/05/2021).</p>
A scoping review exploring vocational rehabilitation interventions for mental health service users with chronic mental illness in low-income to upper-middle-income countries
<p class="MsoNormal"><strong><span>Objective</span></strong></p> <p class="MsoNormal"><span>To synthesize research published on vocational rehabilitation (VR) interventions offered in institutions, by occupational therapists, to mental health service users (MHSUs) with chronic mental illness, in low-income to upper middle-income countries (L-UMIC).</span></p> <p class="MsoNormal"><strong><span>Design</span></strong></p> <p class="MsoNormal"><span>This scoping review used Arksey and O'Malley's methodological framework, the Preferred Reporting Items for Systematic Reviews extension for Scoping Reviews (PRISMA-ScR) and Joanna Briggs scoping review guidelines. </span></p> <p class="MsoNormal"><strong><span>Data Sources</span></strong></p> <p class="MsoNormal"><span>We searched PsycInfo, EBSCOhost, HINARI, Google scholar, Medline, CINAHL, PubMed, Cochrane Library, Scopus, Science Direct and Wiley online library between 15 July and 31 August 2021. </span></p> <p class="MsoNormal"><strong><span>Eligibility Criteria</span></strong></p> <p class="MsoNormal"><span>Sources, published in English between 2011 and 2021, on institution-based VR in occupational therapy for MHSUs who had chronic mental illness in L-UMIC were included. We included primary studies of any design.</span></p> <p class="MsoNormal"><strong><span>Data extraction and synthesis</span></strong></p> <p class="MsoNormal"><span>Three reviewers used Mendeley to manage identified references, Rayyan for abstract and full text screening, and Microsoft Excel for data extraction. Data was sifted and sorted by key categories and themes.</span></p> <p class="MsoNormal"><strong><span>Results</span></strong></p> <p class="MsoNormal"><span>895 sources were identified, and their title and abstracts reviewed. 207 sources were included for full text screening. 12 articles from 4 countries (South Africa, India, Brazil & Kenya) were finally included. Types of VR intervention included supported employment, case management and prevocational </span><span>skills training. Client centeredness, support and empowerment were the key VR principles identified. Teaching of illness self-management, job analysis and matching, job coaching, trial placement, and vocational guidance and counseling, were the main intervention strategies reported.</span></p> <p class="MsoNormal"><strong><span>Conclusions </span></strong></p> <p class="MsoNormal"><span>VR intervention in institutions for MHSUs in L-UMIC revealed the multidimensional uniqueness of individual MHSU's vocational ability, needs and contexts. The interventions allowed client-centered approaches that offer support, and empowerment beyond the boundaries of the institutions. Occupational therapists offering VR need to expand their interventions beyond their institutions to contexts where MHSUs are working or intending to work.</span></p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.