PsycCritiques最新文献

Diverse approaches to the treatment of depressive disorders are necessary to improve evidence-based practice and maximize treatment outcomes. As a result, a range of behaviors and other factors associated with the onset and course of depressive disorders should be examined more comprehensively. Behavioral activation (BA) is a treatment approach to these disorders that can be tailored to address certain health behaviors within the context of depression in an attempt to promote health behaviors whose adoption and maintenance can prove complementary in the treatment of depression. We conducted a scoping review of published studies in which BA-based interventions were used to promote certain health behaviors in individuals with depression. Our search of Medline and the Web of Science identified 336 potential candidate studies. Following screening and with the application of inclusion and exclusion criteria to isolate potentially eligible full-text records, we ultimately identified and evaluated 20 papers that report the nature and efficacy of these modified interventions. Across various domains, including substance use, exercise, medication adherence, and occupational and social success, we found evidence that many-but not all-of the studies we reviewed demonstrated that BA-based interventions were efficacious in promoting the health behavior of interest as well as reducing depressive symptomatology in participants. Implications for more widespread dissemination of such interventions, especially via mobile and web-based platforms due to their accessibility and affordability, are discussed. More research on the feasibility and efficacy of BA-based interventions tailored toward various determinants of health behavior and comorbidities of depressive disorders is warranted.

Various types of colored pigments have been recovered naturally from biological sources including shells, flowers, insects, and so on in the past. At present, such natural colored substances (dyes) are replaced by manmade dyes. On the other hand, due to their continuous usage in various purpose, these artificial dyes or colored substances persist in the environmental surroundings. For example, industrial wastewater contains diverse pollutant substances including dyes. Several of these (artificial dyes) were found to be toxic to living organisms. In recent times, microbial-based removal of dye(s) has gained more attention. These methods were relatively inexpensive for eliminating such contaminants in the environmental system. Hence, various researchers were isolated microbes from environmental samples having the capability of decolorizing synthetic dyes from industrial wastewater. Furthermore, the microorganisms which are genetically engineered found higher degradative/decolorize capacity to target compounds in the natural environs. Very few reviews are available on specific dye treatment either by chemical treatments or by bacteria and/or fungal treatments. Here, we have enlightened literature reports on the removal of different dyes in microbes like bacteria (including anaerobic and aerobic), fungi, GEM, and microbial enzymes and also green-synthesized nanoparticles. This up-to-date literature survey will help environmental managements to co-up such contaminates in nature and will help in the decolorization of dyes.

Purpose: This inquiry aims to develop an appraisal tool to offer greater granularity in weighing evidence in the field of healthcare design research.

Background: In evidence-based design (EBD), the goal is to implement interventions that result in a meaningful and optimal effect based on current best evidence. Although multiple appraisal tools (many adopted from medical disciplines) have been instrumental in evaluating studies in the field of healthcare design research to identify the best evidence, they do not necessarily consider the unique contexts of healthcare design research, and methodologies appropriate to the field.

Methods: Five basic types of studies are ranked based on the level of confidence that they offer regarding the estimate of an effect: (1) meta-analysis studies, (2) causal studies, (3) correlational studies, (4) descriptive studies, and (5) anecdotal evidence. Causal studies are further divided into four levels based on the interaction of two factors: (1) type of intervention and (2) groups' equivalency and extraneous variable control.

Results: An eight-level hierarchy of evidence for healthcare design research is proposed that is expected to improve upon previous hierarchies in three major ways: (a) including research methods that are more relevant to healthcare design research, (b) enhancing evaluation accuracy and reliability by providing a clearer definition of studies based on their key components rather than using study labels alone, and (c) distinguishing different levels of evidence, particularly in causal studies.

Conclusions: The proposed appraisal tool is developed specifically for EBD by reflecting on the unique context of healthcare design research and practice.

Heart diseases cause over 17.9 million total deaths globally, making them the leading source of mortality. The aim of this review is to describe the characteristic mechanical, chemical and cellular properties of human cardiac tissue and how these properties can be mimicked in 3D bioprinted tissues. Furthermore, the authors review how current healthy cardiac models are being 3D bioprinted using extrusion-, laser- and inkjet-based printers. The review then discusses the pathologies of cardiac diseases and how bioprinting could be used to fabricate models to study these diseases and potentially find new drug targets for such diseases. Finally, the challenges and future directions of cardiac disease modeling using 3D bioprinting techniques are explored.

Magnetic resonance imaging - is high precision method for diagnosing cardiovascular diseases. Simultaneously with the anatomy and function of the right ventricle, magnetic resonance imaging allows to assess the pulmonary circulation, which leads to the widespread use of this method in the diagnosis and dynamic monitoring of patients with pulmonary arterial hypertension. The article is devoted to the assessment of cardiac remodeling and risk stratification of this group of patients. Special attention is given to new prognostic parameters included in the scale for risk stratification of patients with pulmonary hypertension of the European Society of Cardiology/European Respiratory Society 2022.

Background: Healthcare-associated infections (HAIs) are a significant healthcare burden in Canada. National surveillance of HAIs at sentinel acute care hospitals is conducted by the Canadian Nosocomial Infection Surveillance Program. This article describes device and surgical procedure-related HAI epidemiology in Canada from 2017 to 2021.

Methods: Data were collected from over 60 Canadian sentinel acute care hospitals between January 1, 2017, and December 31, 2021, for central line-associated bloodstream infections (CLABSIs), hip and knee surgical site infections (SSIs), cerebrospinal fluid shunt SSIs and paediatric cardiac SSIs. Case counts, rates, patient and hospital characteristics, pathogen distributions and antimicrobial resistance data are presented.

Results: Between 2017 and 2021, 2,898 device and surgical procedure-related infections were reported, with CLABSIs in intensive care units representing 69% (n=2,002) of all reported infections under surveillance. Significant rate increases were observed in adult mixed intensive care unit CLABSIs (1.08-2.11 infections per 1,000 line days, p=0.014) while decreases were observed in SSIs following knee arthroplasty (0.34-0.27 infections per 100 surgeries, p=0.05). No changes in trends were observed in the other reported HAIs. Of the 3,089 pathogens identified, the majority were gram-positive (66%), followed by gram negative (23%) and fungi (11%). Coagulase-negative staphylococci (22%) and Staphylococcus aureus (17%) were the most frequently isolated pathogens.

Conclusion: Epidemiological and microbiological trends among select device and surgical procedure-related HAIs are essential for benchmarking infection rates nationally and internationally, identifying any changes in infection rates or antimicrobial resistance patterns and helping inform hospital infection prevention and control and antimicrobial stewardship policies and programs.

Background: The purpose of this research was to investigate the characteristics, clinical manifestations, incidence, and risk factors in ethambutol-induced optic neuropathy (EON) in the Thai population.

Methods: Patients treated with ethambutol for tuberculosis (TB) were retrospectively identified in the medical record of a tertiary hospital in Thailand from January 2012 to August 2019. Development of EON was determined through review of ophthalmology records. Comparison was made between patients with EON and those without EON to identify possible risk factors. Ophthalmic outcomes were characterized.

Results: Among 4,141 patients who received ethambutol for TB treatment, 1,062 had an ophthalmology encounter, and 20 (0.5% overall, 1.88% with ophthalmology encounters) developed EON. In unadjusted analysis, compared to patients without EON, those with EON had a similar daily dose, but longer duration of ethambutol treatment (P=0.02). They were older (mean 43.74 vs. 58.60 years, P=0.001), more likely to have hypertension (P=0.02) and smoke (p=0.01). There were no differences in gender, body mass index, diabetes, dyslipidemia, HIV infection or glomerular filtration rate. The peripapillary retinal nerve fiber layer, ganglion cell analysis, and vascular density as measured using retinal optical coherence tomography were impacted by EON. In adjusted logistic regression analysis, age greater than 60 (OR = 8.71, p = 0.01) and smoking (OR = 7.06, p = 0.01) were independent risk factors for EON.

Conclusion: In patients treated with ethambutol, the incidence proportion of EON was 0.5% among those with ethambutol administered and 1.88% among those with ethambutol and an eye visit. Potential EON risk factors were age, hypertension, smoking, and duration of ethambutol medication. Smoking has not been associated with EON in prior studies.

Background  The endoscopic endonasal approach (EEA) is a commonly used technique for resection of sellar, suprasellar, and anterior fossa masses. One of the most troublesome complications of this technique is cerebrospinal fluid (CSF) leak. In this study, we evaluate the risk factors and consequences of CSF leak on surgical outcomes. Methods  The current study is a retrospective single-institution cohort study evaluating patients who underwent EEA for sellar and/or suprasellar masses from July 2017 to March of 2020. Risk factors for intraoperative and postoperative CSF leak were evaluated, including sellar defect size, tumor volume and pathology, age, body mass index, prior endoscopic endonasal surgery, lumbar drain placement, nasoseptal and mucosal graft use, year of surgery, and cavernous sinus invasion. Postoperative infection, perioperative antibiotic use, and length of stay were also evaluated. Results  Our study included 175 patients. Sellar defect size ( p  = 0.015) and intraoperative CSF leak ( p  < 0.001) were significantly associated with an increased risk of postoperative CSF leak. Patients with nasoseptal flaps were more likely to have a postoperative CSF leak than those with free mucosal grafts ( p  = 0.025). Intraoperative CSF leak, Cushing's disease, and lumbar drain placement were associated with an increased length of stay. Conclusion  Sellar defect size, intraoperative CSF leak, and nasoseptal flap use were associated with an increased risk of postoperative CSF leak. Intraoperative CSF leak, Cushing's disease, and lumbar drain placement are all associated with an increased length of stay.

Background: Illness perception is assigned an increasing role in the control of chronic disease. This study examines illness perception and perceived benefits related to illness in persons with type 1 diabetes mellitus. We used quantitative and qualitative methods for a more in-depth analysis.

Participants and procedure: The participants (N = 110; mean age: 31.52 years; 80.9% women) completed online questionnaires: the Brief Illness Perception Questionnaire (B-IPQ), the perceived benefits subscale of the Illness Cognition Questionnaire (ICQ) and the Hospital Anxiety and Depression Scale (HADS). Interpretative phenomenological analysis (IPA) was used to analyze patients' responses to an open-ended question regarding perceived benefits.

Results: Perceived benefits score was positively correlated with personal (ρ = .20) and treatment control: life-style (ρ = .25) and coherence (ρ = .22). Negative correlations were noted between B-IPQ total score (ρ = -.30), concern (ρ = -.30), depression (ρ = -.35), anxiety (ρ = -.32) and irritability (ρ = -.19). 52.7% of participants reported at least one benefit of having type 1 diabetes. Patients who reported at least one benefit had statistically significantly higher scores in the perceived benefits subscale (p < .001), personal control (p = .005) and treatment control (p = .030) and lower scores in consequences (p = .023), identity (p = .045), concern (p < .001), emotional response (p < .001), and illness perception total score (p < .001) than those who did not report any benefit. IPA revealed four main themes: personal benefits, health-related benefits, social contacts and economic benefits.

Conclusions: The study revealed that in patients with type 1 diabetes perceived disease benefits are closely related to more positive illness perception and lower levels of depression, anxiety and irritability. The findings suggest that addressing potential benefits related to illness may influence the emotional state.

Drawings have been widely used as a window to the mind; as such, they can reveal some aspects of the cognitive and emotional worlds of other animals that can produce them. The study of non-human drawings, however, is limited by human perception, which can bias the methodology and interpretation of the results. Artificial intelligence can circumvent this issue by allowing automated, objective selection of features used to analyze drawings. In this study, we use artificial intelligence to investigate seasonal variations in drawings made by Molly, a female orangutan who produced more than 1299 drawings between 2006 and 2011 at the Tama Zoological Park in Japan. We train the VGG19 model to first classify the drawings according to the season in which they are produced. The results show that deep learning is able to identify subtle but significant seasonal variations in Molly's drawings, with a classification accuracy of 41.6%. We use VGG19 to investigate the features that influence this seasonal variation. We analyze separate features, both simple and complex, related to color and patterning, and to drawing content and style. Content and style classification show maximum performance for moderately complex, highly complex, and holistic features, respectively. We also show that both color and patterning drive seasonal variation, with the latter being more important than the former. This study demonstrates how deep learning can be used to objectively analyze non-figurative drawings and calls for applications to non-primate species and scribbles made by human toddlers.