Video assisted thoracoscopic surgery for spinal conditions

Neurology India534489-49

Socioeconomic determinants of multimorbidity: a population-based household survey of Hong Kong Chinese

<b>Introduction</b> Multimorbidity has been well researched in terms of consequences and healthcare implications. Nevertheless, its risk factors and determinants, especially in the Asian context, remain understudied. We tested the hypothesis of a negative relationship between socioeconomic status and multimorbidity, with contextually different patterns from those observed in the West.<p></p> <b>Methods</b> We conducted our study in the general Hong Kong (HK) population. Data on current health conditions, health behaviours, socio-demographic and socioeconomic characteristics was obtained from HK Government’s Thematic Household Survey. 25,780 individuals aged 15 or above were sampled. Binary logistic and negative binomial regression analyses were conducted to identify risk factors for presence of multimorbidity and number of chronic conditions, respectively. Sub-analysis of possible mediation effect through financial burden borne by private housing residents on multimorbidity was also conducted.<p></p> <b>Results</b> Unadjusted and adjusted models showed that being female, being 25 years or above, having an education level of primary schooling or below, having less than HK$15,000 monthly household income, being jobless or retired, and being past daily smoker were significant risk factors for the presence of multimorbidity and increased number of chronic diseases. Living in private housing was significantly associated with higher chance of multimorbidity and increased number of chronic diseases only after adjustments.<p></p> <b>Conclusions</b>Less advantaged people tend to have higher risks of multimorbidity and utilize healthcare from the public sector with poorer primary healthcare experience. Moreover, middle-class people who are not eligible for government subsidized public housing may be of higher risk of multimorbidity due to psychosocial stress from paying for the severely unaffordable private housing

The association of types of training and practice settings with doctors’ empathy and patient enablement among patients with chronic illness in Hong Kong

Background: The increase in non-communicable disease (NCD) is becoming a global health problem and there is an increasing need for primary care doctors to look after these patients although whether family doctors are adequately trained and prepared is unknown. Objective: This study aimed to determine if doctors with family medicine (FM) training are associated with enhanced empathy in consultation and enablement for patients with chronic illness as compared to doctors with internal medicine training or without any postgraduate training in different clinic settings. Methods: This was a cross-sectional questionnaire survey using the validated Chinese version of the Consultation and Relational Empathy (CARE) Measure as well as Patient Enablement Instrument (PEI) for evaluation of quality and outcome of care. 14 doctors from hospital specialist clinics (7 with family medicine training, and 7 with internal medicine training) and 13 doctors from primary care clinics (7 with family medicine training, and 6 without specialist training) were recruited. In total, they consulted 823 patients with chronic illness. The CARE Measure and PEI scores were compared amongst doctors in these clinics with different training background: family medicine training, internal medicine training and those without specialist training. Generalized estimation equation (GEE) was used to account for cluster effects of patients nested with doctors. <b>Results</b> Within similar clinic settings, FM trained doctors had higher CARE score than doctors with no FM training. In hospital clinics, the difference of the mean CARE score for doctors who had family medicine training (39.2, SD = 7.04) and internal medicine training (35.5, SD = 8.92) was statistically significant after adjusting for consultation time and gender of the patient. In the community care clinics, the mean CARE score for doctors with family medicine training and those without specialist training were 32.1 (SD = 7.95) and 29.2 (SD = 7.43) respectively, but the difference was not found to be significant. For PEI, patients receiving care from doctors in the hospital clinics scored significantly higher than those in the community clinics, but there was no significant difference in PEI between patients receiving care from doctors with different training backgrounds within similar clinic setting. Conclusion: Family medicine training was associated with higher patient perceived empathy for chronic illness patients in the hospital clinics. Patient enablement appeared to be associated with clinic settings but not doctors’ training background. Training in family medicine and a clinic environment that enables more patient doctor time might help in enhancing doctors’ empathy and enablement for chronic illness patients

Associations between self-reported and objective face recognition abilities are only evident in above- and below-average recognisers

The 20-Item Prosopagnosia Items (PI-20) was recently introduced as a self-report measure of face recognition abilities and as an instrument to help the diagnosis of prosopagnosia. In general, studies using this questionnaire have shown that observers have moderate to strong insights into their face recognition abilities. However, it remains unknown whether these insights are equivalent for the whole range of face recognition abilities. The present study investigates this issue using the Mandarin version of the PI-20 and the Cambridge Face Memory Test Chinese (CFMT-Chinese). Our results showed a moderate negative association between the PI-20 and the CFMT-Chinese. However, this association was driven by people with low and high face recognition ability, but absent in people within the typical range of face recognition performance. The implications of these results for the study of individual differences and the diagnosis of prosopagnosia are discussed

No influence of threat uncertainty on fear generalization

Fear overgeneralization and perceived uncertainty about future outcomes have been suggested as risk factors for clinical anxiety. However, little is known regarding how they influence each other. In this study, we investigated whether different levels of threat uncertainty influence fear generalization. Three groups of healthy participants underwent a differential fear conditioning protocol followed by a generalization test. All groups learned to associate one female face (conditioned stimulus, CS+) with a female scream (unconditioned stimulus, US), whereas the other face (CS−) was not associated with the scream. In order to manipulate threat uncertainty, one group (low uncertainty, n = 26) received 80%, the second group (moderate uncertainty, n = 32) received 60%, and the third group (high uncertainty, n = 30) 40% CS-US contingency. In the generalization test, all groups saw CS+ and CS− again along with four morphs resembling the CSs in steps of 20%. Subjective (expectancy, valence, and arousal ratings), psychophysiological (skin conductance response, SCR), and visuocortical (steady-state visual evoked potentials, ssVEPs) indices of fear were registered. Participants expected the US according to their reinforcement schedules and the discriminative responses to CS+/CS− increased with more uncertainty in skin conductance. However, acquisition of conditioned fear was not evident in ssVEPs. During the generalization test, we found no effect of threat uncertainty in any of the measured variables, but the strength of generalization for threat expectancy ratings was positively correlated with dispositional intolerance of uncertainty. This study suggests that mere threat uncertainty does not modulate fear generalization.</p

A Systematic Review of the Inter-individual Differences in Avoidance Learning

Avoidance is typically adaptive given it prevents threat. However, avoidance becomes maladaptive when it is executed out of proportion of threat (i.e., excessive or insufficient avoidance), persists in the absence of threat, or excessively generalizes to other innocuous situations. Although there has been an increase in research in these different processes of maladaptive avoidance, the role of inter-individual differences in these avoidance processes receives less research attention, despite its theoretical and clinical importance. In this systematic review, we summarized the role of inter-individual traits that relate to risk or resilient factors for anxiety-related disorders, trauma-and stressor-related disorders, obsessive-compulsive related disorders, pain related disorders, eating-related disorders, and affective disorders. A majority of the inter-individual differences had an apparent mixed or null effect on the different processes of avoidance. We discussed this lack of evidence of inter-individual differences on avoidance due to a lack of methodological and/or analytical consensus in the field, in addition to a lack of integration of recent findings into existing theories. Recommendations for future research are discussed, with a focus on examining the conditions or experimental parameters for certain inter-individual traits to manifest their effects on avoidance, identifying the nuances of methodological and/or inter-individual differences in avoidance, and a call for integrating recent preliminary findings into existing theories.</p

Molecular analysis of CHX10 and MFRP in Chinese subjects with primary angle closure glaucoma and short axial length eyes

Molecular Vision141313-131

The synergistic effect of cation mixing in mesoporous BixFe1 xVO4 heterojunction photoanodes for solar water splitting

Mixed metal vanadates are an interesting class of materials due to their favorable bandgap for visible light absorption and their catalytic activity. Here, we report a novel BixFe1 amp; 8722;xVO4 mixture system fabricated by electrospinning, which upon annealing is composed of triclinic FeVO4 and monoclinic BiVO4 phases. The mixture demonstrates extended optical absorption and a clear bandgap shift as compared with a pure BiVO4. This is also accompanied by an extended wavelength range for its photoactivity as evident from the incident photon to current efficiency. In addition, the mixture with a Bi Bi Fe ratio of 0.5 i.e., x 0.5 shows superior charge transfer and charge separation efficiency. The improved charge transfer efficiency is attributed to the higher catalytic activity of the mixed cation, while the presence of a BiVO4 FeVO4 heterojunction enhances the charge separation. The formation of the heterojunction is verified through detailed microscopic investigations revealing BiVO4 particles intimately surrounded by FeVO4. Our results demonstrate the advantage of establishing a mixture of complex metal oxides in extending optical absorption and boosting the photoelectrochemical performanc

Fraction-score: a generalized support measure for weighted and maximal co-location pattern mining

Co-location patterns, which capture the phenomenon that objects with certain labels are often located in close geographic proximity, are defined based on a support measure which quantifies the prevalence of a pattern candidate in the form of a label set. Existing support measures share the idea of counting the number of instances of a given label set C as its support, where an instance of C is an object set whose objects collectively carry all labels in C and are located close to one another. However, they suffer from various weaknesses, e.g., fail to capture all possible instances, or overlook the cases when multiple instances overlap. In this paper, we propose a new measure called Fraction-Score which counts instances fractionally if they overlap. Fraction-Score captures all possible instances, and handles the cases where instances overlap appropriately (so that the supports defined are more meaningful and anti-monotonic). We develop efficient algorithms to solve the co-location pattern mining problem defined with Fraction-Score. Furthermore, to obtain representative patterns, we develop an efficient algorithm for mining the maximal co-location patterns, which are those patterns without proper superset patterns. We conduct extensive experiments using real and synthetic datasets, which verified the superiority of our proposals