Reliability and validity of the Chinese version of the COVID-19 Phobia Scale.

BACKGROUND: The COVID-19 pandemic has become a source of fear worldwide and has negative mental health effects on the general population. In 2022, the epidemic continues to be characterized by many points, widespread and frequent in China, and the situation is serious and complex. To provide an effective and scientific tool, the study validated the Chinese version of the COVID-19 Phobia Scale (C19P-SC). METHODS: This study selected 1138 Chinese individuals (age ranged 13 to 80). RESULTS: Cronbach's alpha coefficient for the C19P-SC was 0.93 (the coefficients of the four dimensions ranged from 0.75 to 0.85). The results of the confirmatory factor analysis supported the four-factor structure of the C19P-SC. Meanwhile, there was a positive and significant correlation between coronaphobia and state anxiety (r = 0.48, p < 0.001). The metric invariance hypothesis and the scalar invariance hypothesis were valid in the different subgroups. Significant multivariate effects of gender, education level, and identity differences on coronaphobia were found. CONCLUSIONS: The Chinese version of the COVID-19 Phobia Scale has good psychometric properties and is suitable for measuring COVID-19 phobia in Chinese individuals.

A deep feature fusion network for fetal state assessment.

CTG (cardiotocography) has consistently been used to diagnose fetal hypoxia. It is susceptible to identifying the average fetal acid-base balance but lacks specificity in recognizing prenatal acidosis and neurological impairment. CTG plays a vital role in intrapartum fetal state assessment, which can prevent severe organ damage if fetal hypoxia is detected earlier. In this paper, we propose a novel deep feature fusion network (DFFN) for fetal state assessment. First, we extract spatial and temporal information from the fetal heart rate (FHR) signal using a multiscale CNN-BiLSTM network, increasing the features' diversity. Second, the multiscale CNN-BiLSM network and frequently used features are integrated into the deep learning model. The proposed DFFN model combines different features to improve classification accuracy. The multiscale convolutional kernels can identify specific essential information and consider signal's temporal information. The proposed method achieves 61.97%, 73.82%, and 66.93% of sensitivity, specificity, and quality index, respectively, on the public CTU-UHB database. The proposed method achieves the highest QI on the private database, verifying the proposed method's effectiveness and generalization. The proposed DFFN combines the advantages of feature engineering and deep learning models and achieves competitive accuracy in fetal state assessment compared with related works.

Volition in prospective Memory: Evidence against differences between free and fixed target events.

Volition is the extent to which actions are generated as a result of internal states in contrast to responses to external conditions or dictated by external events. Delayed intentions about future action are stored in prospective memory until the intended action has to be formed at a later point in time. It is unknown how voluntary choice affects prospective memory. We compared the difference between freely chosen and fixed targets on the reaction times and task performance in the ongoing task and for the target stimuli in a prospective memory task. The task performance and the reaction time was modelled using a Bayesian hierarchical drift-diffusion model. The analysis showed no differences between self-chosen and fixed prospective memory cues on task responses. The result suggests that volition in choosing the cue to act upon or given a fixed cue does not make a difference for prospective memory task performance.

Device architectures for low voltage and ultrafast graphene integrated phase modulators.

The atomic layer thin geometry and semi-metallic band diagram of graphene can be utilized for significantly improving the performance matrix of integrated photonic devices. Its semiconductor-like behavior of Fermi-level tunability allows graphene to serve as an active layer for electro-optic modulation. As a low loss metal layer, graphene can be placed much closer to active layer for low voltage operation. In this work, we investigate hybrid device architectures utilizing semiconductor and metallic properties of the graphene for ultrafast and energy efficient electro-optic phase modulators on semiconductor and dielectric platforms. (1) Directly contacted graphene-silicon heterojunctions. Without oxide layer, the carrier density of graphene can be modulated by the directly contact to silicon layer, while silicon intrinsic region stays mostly depleted. With doped silicon as electrodes, carrier can be quickly injected and depleted from the active region in graphene. The ultrafast carrier transit time and small RC constant promise ultrafast modulation speed (3dB bandwidth of 67 GHz) with an estimated Vπ·L of 1.19 V·mm. (2) Graphene integrated lithium niobite modulator. As a transparent electrode, graphene can be placed close to integrated lithium niobate waveguide for improving coupling coefficient between optical mode profile and electric field with minimal additional loss (4.6 dB/cm). Numerical simulation indicates 2.5× improvement of electro-optic field overlap coefficient, with estimated V π of 0.2 V.

Metabolite abnormalities in psychosis risk: A meta-analysis of proton magnetic resonance spectroscopy studies.

Accumulating evidence implicates that individuals at high-risk of psychosis have already exhibited pathophysiological changes in brain metabolites including glutamate, gamma-Aminobutyric Acid (GABA), N-Acetylaspartate (NAA), creatine (Cr), myo-inositol (MI) and choline (Cho). These changes may contribute to the development of schizophrenia and associate with psychotic genes. However, specific metabolic changes of brain sub-regions in individuals at risk have still been controversial. Thus, the current study aimed to investigate the brain metabolic changes including glutamate, Glx, GABA, GABA/Glx, NAA, Cr, MI and Cho levels in individuals at risk by conducting a case-control meta-analysis and meta-regression of proton magnetic resonance spectroscopy studies. Primary outcomes revealed that individuals at risk exhibited increased Cr levels at the rostral medial prefrontal cortex (rmPFC), decreased NAA and Cr levels at the thalamus, and increased MI levels at the dorsolateral prefrontal cortex. Sub-group analyses further indicated that individuals with clinical high-risk (CHR) exhibited increased Cr levels at the medial prefrontal cortex (mPFC) and decreased Glx levels at the thalamus, while individuals with genetic risk (siblings of psychiatric patients) exhibited significant increased Glx and MI levels at the mPFC. However, GABA, GABA/Glx and Cho levels showed no significant result. These findings suggest that the dysfunctional metabolites at the mPFC and the thalamus may be an essential neurobiological basis at the early stage of psychosis.

Trajectories of schizotypy and their emotional and social functioning: An 18-month follow-up study.

Schizotypy is a set of personality traits that convey liability to develop schizophrenia. Studying schizotypy in healthy individuals may facilitate the understanding of the psychopathological processes underlying schizophrenia. The present study aimed to examine the developmental trajectories of schizotypy over time using a longitudinal study design. The Chapman Scales for Psychosis Proneness were administered to 1541 college students at baseline, and subsequently at six-monthly intervals up to 18months. Latent class growth analysis was conducted to track the different trajectories. In addition, self-reported scales were used to measure idea of reference, emotional experiences and expression, stress and coping, as well as social functioning. We identified four latent classes with distinct trajectories: "nonschizotypy" group (LC1), "stable high schizotypy" group (LC3), "high reactive schizotypy" group (LC2) and "low reactive schizotypy" group (LC4). These findings suggest that there may be distinct developmental trajectories for schizotypy. Two groups may be of particular interest: the "stable high schizotypy" group that displayed the worst clinical and functioning outcomes on almost all measures and the "high reactive schizotypy" group characterized by a relatively rapid decline in functioning.

The effects of working memory training on enhancing hedonic processing to affective rewards in individuals with high social anhedonia.

Anhedonia is a core feature of the negative symptoms of schizophrenia and is less responsive to antipsychotic medication. Little is known whether anhedonia could be alleviated by cognitive training. The present study aimed to examine whether hedonic deficits observed in individuals with high social anhedonia could be reduced by working memory (WM) training. Thirty-four individuals with high social anhedonia were randomly assigned to either a WM training group or a control group. The WM training group received 20 sessions of dual n-back task training for four weeks. The affective incentive delay task was administered in all participants before the training and one month later. The results showed that individuals who received the WM training showed significant improvement in WM performance (F(19, 304)=55.80, p<0.001) and they also showed significant improvement in approach sensitivity to rewards (p=0.004). These preliminary findings suggest that hedonic processing could be improved through WM training in individuals with high social anhedonia. These results may have important implications for the development of non-pharmacological interventions to alleviate anhedonia in patients with schizophrenia.

The neuroplastic effect of working memory training in healthy volunteers and patients with schizophrenia: Implications for cognitive rehabilitation.

We conducted an activation likelihood estimation (ALE) meta-analysis to quantitatively review the existing working memory (WM) training studies that investigated neural activation changes both in healthy individuals and patients with schizophrenia. ALE analysis of studies in healthy individuals indicates a widespread distribution of activation changes with WM training in the frontal and parietal regions, especially the dorsolateral prefrontal cortex, the medial frontal cortex and the precuneus, as well as subcortical regions such as the insula and the striatum. WM training is also accompanied by activation changes in patients with schizophrenia, mainly in the dorsolateral prefrontal cortex, the precuneus and the fusiform gyrus. Our results demonstrate that WM training is accompanied by changes in neural activation patterns in healthy individuals, which may provide the basis for understanding neuroplastic changes in patients with schizophrenia.