Background: It is well established that quality of life (QOL) and functioning ability are impaired in psychosis, especially schizophrenia. Little is known about QOL and functioning in subjects vulnerable to psychosis (VTP).
Method: Three samples of nonpsychotic subjects (first-degree relatives of psychotic or severely ill patients, treatment-seeking patients, and a random community sample, in all 133 subjects) were assessed by the Structured Interview for Prodromal Symptoms and their vulnerability to psychosis was defined by severity of lifetime psychotic-like positive symptoms (nonsymptomatic, symptomatic, VTP). Quality of life was assessed by the Heinrichs' Quality of Life Scale and the Global Assessment of Functioning Ability (GAF) was used to measure functioning. Variance of QOL and GAF was explained by vulnerability status and psychiatric symptoms.
Results: Quality of life and functioning ability decreased linearly as positive symptom intensity increased and was lowest in the VTP subjects when background factors were controlled for. In multivariate analysis, negative symptoms predicted low QOL/GAF scores in addition to vulnerability status that was based on positive symptoms.
Conclusion: Vulnerability to psychosis is associated with decreased QOL and impaired functioning ability. Although current diagnostic evaluation of patients at high risk of psychosis relies heavily on the occurrence of positive symptoms, negative symptoms seem to be strongly associated with QOL and functioning ability in VTP subjects. This should be taken into account when assessing putatively vulnerable patients and planning treatment interventions for them.
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http://dx.doi.org/10.1016/j.comppsych.2006.10.008 | DOI Listing |
Cytotherapy
January 2025
Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain. Electronic address:
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January 2025
Clinical Research Development Unit of Tabriz Valiasr Hospital, Tabriz University of Medical Sciences, Tabriz, Iran.
Fluoride (F), as a natural element found in a wide range of sources such as water and certain foods, has been proven to be beneficial in preventing dental caries, but concerns have been raised regarding its potential deleterious effects on overall health. Sodium fluoride (NaF), another form of F, has the ability to accumulate in reproductive organs and interfere with hormonal regulation and oxidative stress pathways, contributing to reproductive toxicity. While the exact mechanisms of F-induced reproductive toxicity are not fully understood, this review aims to elucidate the mechanisms involved in testicular and ovarian injury.
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January 2025
Institute of Grassland Science, School of Life Sciences, Key Laboratory of Vegetation Ecology, Ministry of Education, Northeast Normal University, Changchun, China.
The intricate biogeochemical cycling of multiple elements plays a pivotal role in upholding a myriad of ecosystem functions. However, our understanding of elemental stoichiometry and coupling in response to global changes remains primarily limited to plant carbon: nitrogen: phosphorus (C: N: P). Here, we assessed the responses of 11 elements in plants from different functional groups to global changes.
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January 2025
School of Medicine, Qom University of Medical Sciences, Qom, Iran.
Introduction: Intrinsic Capacity in integrated geriatric care emphasizes the importance of a thorough functional assessment. Monitoring the intrinsic capacity of older individuals provides standardized and reliable information to prevent early disability. This study assessed the relationship between intrinsic capacity and functional ability in older adults.
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January 2025
Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups.
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