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      Do environmental risk factors for the development of psychosis distribute differently across dimensionally assessed psychotic experiences?

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          Abstract

          Psychotic experiences (PE) are associated with poorer functioning, higher distress and the onset of serious mental illness. Environmental exposures (e.g. childhood abuse) are associated with the development of PE. However, which specific exposures convey risk for each type or dimension of PE has rarely been explored. The Oxford Wellbeing Life and Sleep (OWLS) survey includes 22 environmental risk factors for psychosis and was designed to examine how environmental risks are associated with specific dimensions of PE. Multivariate logistic regression models were fit using these risk factors to predict six dimensions of PE (perceptual abnormalities, persecutory ideation, bizarre ideas, cognitive disorganisation, delusional mood and negative symptoms). Models were built using only 70% of the data, and then fit to the remaining data to assess their generalisability and quality. 1789 (27.2% men; mean age = 27.6; SD = 10.9) survey responses were analysed. The risk factors predictive of the most PE were anxiety, social withdrawal during childhood and trauma. Cannabis and depression predicted three dimensions with both predicting bizarre ideas and persecutory ideation. Psychological abuse and sleep quality each predicted two dimensions (persecutory ideation and delusional mood). Risk factors predicting one PE dimension were age (predicting cognitive disorganisation), physical abuse (bizarre ideas), bullying and gender (persecutory ideation); and circadian phase (delusional mood). These results lend support for a continuum of psychosis, suggesting environmental risks for psychotic disorders also increase the risk of assorted dimensions of PE. Furthermore, it advocates the use of dimensional approaches when examining environmental exposures for PE given that environmental risks distribute differently across dimensions.

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          The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research

          Despite the prevalence of sleep complaints among psychiatric patients, few questionnaires have been specifically designed to measure sleep quality in clinical populations. The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire which assesses sleep quality and disturbances over a 1-month time interval. Nineteen individual items generate seven "component" scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for these seven components yields one global score. Clinical and clinimetric properties of the PSQI were assessed over an 18-month period with "good" sleepers (healthy subjects, n = 52) and "poor" sleepers (depressed patients, n = 54; sleep-disorder patients, n = 62). Acceptable measures of internal homogeneity, consistency (test-retest reliability), and validity were obtained. A global PSQI score greater than 5 yielded a diagnostic sensitivity of 89.6% and specificity of 86.5% (kappa = 0.75, p less than 0.001) in distinguishing good and poor sleepers. The clinimetric and clinical properties of the PSQI suggest its utility both in psychiatric clinical practice and research activities.
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            The short-form version of the Depression Anxiety Stress Scales (DASS-21): construct validity and normative data in a large non-clinical sample.

            To test the construct validity of the short-form version of the Depression anxiety and stress scale (DASS-21), and in particular, to assess whether stress as indexed by this measure is synonymous with negative affectivity (NA) or whether it represents a related, but distinct, construct. To provide normative data for the general adult population. Cross-sectional, correlational and confirmatory factor analysis (CFA). The DASS-21 was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,794). Competing models of the latent structure of the DASS-21 were evaluated using CFA. The model with optimal fit (RCFI = 0.94) had a quadripartite structure, and consisted of a general factor of psychological distress plus orthogonal specific factors of depression, anxiety, and stress. This model was a significantly better fit than a competing model that tested the possibility that the Stress scale simply measures NA. The DASS-21 subscales can validly be used to measure the dimensions of depression, anxiety, and stress. However, each of these subscales also taps a more general dimension of psychological distress or NA. The utility of the measure is enhanced by the provision of normative data based on a large sample.
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              Life between Clocks: Daily Temporal Patterns of Human Chronotypes

              Human behavior shows large interindividual variation in temporal organization. Extreme "larks" wake up when extreme "owls" fall asleep. These chronotypes are attributed to differences in the circadian clock, and in animals, the genetic basis of similar phenotypic differences is well established. To better understand the genetic basis of temporal organization in humans, the authors developed a questionnaire to document individual sleep times, self-reported light exposure, and self-assessed chronotype, considering work and free days separately. This report summarizes the results of 500 questionnaires completed in a pilot study individual sleep times show large differences between work and free days, except for extreme early types. During the workweek, late chronotypes accumulate considerable sleep debt, for which they compensate on free days by lengthening their sleep by several hours. For all chronotypes, the amount of time spent outdoors in broad daylight significantly affects the timing of sleep: Increased self-reported light exposure advances sleep. The timing of self-selected sleep is multifactorial, including genetic disposition, sleep debt accumulated on workdays, and light exposure. Thus, accurate assessment of genetic chronotypes has to incorporate all of these parameters. The dependence of human chronotype on light, that is, on the amplitude of the light:dark signal, follows the known characteristics of circadian systems in all other experimental organisms. Our results predict that the timing of sleep has changed during industrialization and that a majority of humans are sleep deprived during the workweek. The implications are far ranging concerning learning, memory, vigilance, performance, and quality of life.
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                Author and article information

                Contributors
                jan.cosgrave@ndcn.ox.ac.uk
                Journal
                Transl Psychiatry
                Transl Psychiatry
                Translational Psychiatry
                Nature Publishing Group UK (London )
                2158-3188
                19 April 2021
                19 April 2021
                2021
                : 11
                : 226
                Affiliations
                [1 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, , University of Oxford, ; Oxford, UK
                [2 ]GRID grid.83440.3b, ISNI 0000000121901201, Department of Clinical, Educational and Health Psychology, , University College London, ; London, UK
                [3 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, Department of Physiology, Pharmacology and Neuroscience, , University of Bristol, Biomedical Sciences Building, University Walk, ; Bristol, UK
                [4 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Department of Statistics, , University of Oxford, South Parks Road, ; Oxford, UK
                [5 ]GRID grid.5510.1, ISNI 0000 0004 1936 8921, Norwegian Centre for Violence & Traumatic Stress Studies, , University of Oslo, ; Oslo, Norway
                [6 ]GRID grid.5012.6, ISNI 0000 0001 0481 6099, Department of Clinical Psychological Science, , Maastricht University, Maastricht University, ; Maastricht, The Netherlands
                [7 ]GRID grid.416938.1, ISNI 0000 0004 0641 5119, Department of Psychiatry, , University of Oxford, Warneford Hospital, ; Oxford, UK
                [8 ]Oxford Health National Health Service (NHS) Foundation Trust, Oxford, UK
                [9 ]GRID grid.12650.30, ISNI 0000 0001 1034 3451, Departments of Radiation Sciences and Molecular Biology, , Umeå University, ; Umeå, Sweden
                [10 ]GRID grid.12650.30, ISNI 0000 0001 1034 3451, Wallenberg Centre for Molecular Medicine (WCMM), , Umeå University, ; Umeå, Sweden
                Author information
                http://orcid.org/0000-0002-1150-2423
                http://orcid.org/0000-0003-1061-8106
                http://orcid.org/0000-0002-3404-1279
                http://orcid.org/0000-0003-3355-3202
                http://orcid.org/0000-0002-1021-5887
                http://orcid.org/0000-0002-1426-2816
                http://orcid.org/0000-0001-6055-2067
                http://orcid.org/0000-0003-2480-3329
                Article
                1265
                10.1038/s41398-021-01265-2
                8055691
                33875641
                329386d7-7a21-4583-ab58-59b4d944aaab
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 April 2020
                : 9 January 2021
                : 4 February 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000272, DH | National Institute for Health Research (NIHR);
                Award ID: HQR00960
                Award ID: HQR00960
                Award ID: A90305
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100010269, Wellcome Trust (Wellcome);
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Clinical Psychology & Psychiatry
                schizophrenia,bipolar disorder,human behaviour
                Clinical Psychology & Psychiatry
                schizophrenia, bipolar disorder, human behaviour

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