Institute of Psychology, Chinese Academy of Sciences
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Effects of mother-infant skin-to-skin contact on mother-infant relationship and maternal psychology feelings: A qualitative study
No full textAimsTo explore the effects of mother-infant skin-to-skin contact on mother-infant relationship and maternal psychology feelings.DesignAn exploratory qualitative research design using semi-structured interviews.MethodsA total of 64 mother-infant pairs who met the inclusion criteria were selected as the experimental subjects to receive early and continuous intervention of mother-infant skin-to-skin contact (SSC). On this basis, the qualitative research method of procedural grounded theory was used to conduct semi-structured interviews with 18 puerperas before discharge from the hospital; the three-level coding method of procedural grounded theory and Graneheim & Lundman qualitative content analysis method were combined to conductinterview content analysis in Nvivo 12 software, so as to extractcore categories and condense the theme.Results(1) The data were coded to extract five core categories, namely, birth experience, role transition, contact perception, mother-infant connection and parental efficacy; (2) there were statistically significant differences in the number of coding reference points in five nodes before and after SSC, that is, mothers' positive feelings, newborns' physical characteristics noticed by their mothers, mother-infant connection, role transition and birth experience. The number of coding reference points after SSC was statistically significant greater than before SSC; (3) The coding interview results showed that SSC could promote the sense of happiness in nurturing
Interaction of childhood trauma with <i>BDNF</i> and <i>FKBP5</i> gene polymorphisms in predicting burnout in general occupational groups
No full textBoth the BDNF gene rs6265 and the FKBP5 gene rs1360780 polymorphisms are independently associated with adult psychotic-like experiences, when exposed to high childhood abuse; however, it remains unclear whether the relationship between childhood abuse and burnout is moderated by these two single nucleotide polymorphisms (SNPs). Furthermore, there is an interaction between glucocorticoid receptor transcriptional activity and BDNF signaling. Therefore, we investigated the interaction of these two SNPs with childhood trauma in predicting burnout. We recruited 990 participants (mean age 33.06 years, S.D. = 6.31) from general occupational groups and genotyped them for rs6265 and rs1360780. Burnout, childhood trauma, resilience, and job stress were measured through a series of rating scales. Gene-by-environment and gene-by-gene-by-environment interactions were examined using linear hierarchical regression and PROCESS macro in SPSS. Covariates included demographics and resilience. We found that rs6265 moderated the association between job stress and emotional exhaustion. Both rs6265 and rs1360780 moderated the association between childhood abuse and cynicism. There was significant interaction of childhood abuse x rs6265 x rs1360780 on emotional exhaustion and reduced personal accomplishment, so that rs6265 CC genotype and rs1360780 TT genotype together predicted higher levels of emotional exhaustion under high childhood abuse, while rs6265 TT genotype and rs1360780 CC genotype together exerted a resilient effect on reduced personal accomplishment in the face of childhood abuse. Our findings suggest that the rs6265 CC genotype and rs1360780 TT genotype may jointly contribute to increased risk of burnout under childhood trauma
Sex differences and risk factors of self-reported suicide attempts in middle-aged Chinese Han patients with first-episode drug-na?ve anxious depression: a large-scale cross-sectional study
No full textThis study aims to investigate sex differences and risk factors for self-reported suicide attempts among Chinese Han middle-aged patients with first-episode drug-na & iuml;ve (FEDN) anxious depression (AD). A total of 1796 patients with FEDN major depressive disorder were enrolled in this study, including 341 middle-aged patients with AD. We compared the prevalence, demographics, and clinical characteristics of suicide attempts between male and female patients with FEDN middle-aged AD. We also explored the risk factors for self-reported suicide attempts in this population using binary logistic regression analysis. The male/female ratio was 91/250 and the age of onset was 51.50 +/- 4.13. Our results showed that there were no significant sex differences in the prevalence of self-reported suicide attempts in middle-aged patients with FEDN AD. However, we did find significant differences in several demographic and clinical characteristics between self-reported suicide attempters and non-suicide attempters. Moreover, severe anxiety, measured by the Hamilton Anxiety Rating Scale score, was identified as a risk factor for self-reported suicide attempts in female middle-aged AD patients. Additionally, elevated thyroid peroxidase antibody (TPOAb) levels were linked to self-reported suicide attempts in male AD patients. Our findings suggest that there are no significant sex differences in the prevalence of self-reported suicide attempts in this population, but there may be sex-specific risk factors for self-reported suicide attempts in middle-aged AD. Clinical psychiatrists need to pay attention to thyroid hormone levels in middle-aged anxious depression.
This study explores sex differences in self-reported suicide attempts among Chinese Han middle-aged patients with first-episode drug-na & iuml;ve (FEDN) major depressive disorder (MDD) and anxious depression (AD).1. No significant sex differences in the prevalence of self-reported suicide attempts were observed; however, important demographic and clinical differences between suicide attempters and non-suicide attempters were identified.2. Middle-aged depression is associated with increased self-reported suicide attempts risk during ages 45-60 due to mood swings and hormonal changes.3. Psychotic symptoms in MDD patients are linked to higher suicide risk, and severe anxiety, measured by the HAMA score, is a risk factor for self-reported suicide attempts in female middle-aged AD patients.4. Elevated TPOAb levels are associated with self-reported suicide attempts in male AD patients.These findings emphasize the need for further research on sex-specific risk factors in middle-aged anxious depression to enhance suicide prevention strategies
KETCH: A Knowledge-Enhanced Transformer-Based Approach to Suicidal Ideation Detection from Social Media Content
No full textSuicidal ideation (SI), as a psychiatric emergency, requires immediate assistance and intervention. Most people with SI do not actively seek help from mental health professionals, which may result in irreversible consequences. Research has shown that individuals experiencing SI increasingly express their thoughts and emotions on social media platforms, making the latter a viable venue for suicidal ideation detection (SID). This paper proposes, develops, and evaluates a knowledge-enhanced transformer-based approach (KETCH) to SID from social media content. KETCH comprises several key novel design artifacts, including a social media-oriented SI lexicon, a model-level method for integrating domain knowledge (i.e., lexicon) into a state-of-theart transformer, and aligned dynamic embedding and lexicon-based enhancement that integrate domain relevance and contextual importance of terms to effective SID. We evaluate KETCH's performance with social media data in two different languages collected from distinct platforms, and further examine its generalizability to user-level models for suicide risk prediction and depression detection. The results demonstrate the superior effectiveness, robustness, and generalizability of KETCH via a series of empirical evaluation and a field study. Our research makes multifold research contributions and opens up practical opportunities for timely detection and proactive intervention of SI, which can have far-reaching impacts on public health, the economy, and society
Modulation of Social Information Processing on Pupil Size and Its Mechanisms
No full textPupil size, as a window into the minds of others, plays a crucial role in social interaction. While previous studies have focused on the influence of non-social factors, such as the physical properties of stimuli, on pupil diameter, recent research has emphasized the significant connection between social information processing and pupil size. In this comprehensive review, we aim to explore how the processing of social stimuli (e.g., face, biological motion) and their emotional characteristics affect pupil size. In essence, pupil size is believed to reflect an individual's perception of social stimuli. It goes beyond simple physical properties and encompasses the processing of complex social information, including social contexts and interactions. The modulation of pupil size in response to social stimuli is believed to be driven by two key mechanisms: emotional arousal and social attention. When individuals encounter emotionally charged social cues, their pupils tend to dilate, indicating heightened emotional engagement. Similarly, the dilation of pupils when individuals focus on specific social cues suggests an increased allocation of cognitive resources to process relevant social information. Furthermore, the connection between pupil size and social information processing has provided intriguing findings in individuals with autism spectrum disorder (ASD). Known for their significant social deficits, individuals with ASD exhibited abnormal pupillary responses when presented with social stimuli. These findings raise the possibility of utilizing pupillary responses as a potential index for identifying individuals with ASD at a relatively younger age. Moreover, the incorporation of pupillary response measurements in the diagnosis holds great promise in transcending the limitations of the minimum diagnostic age. This can have important implications both in terms of theoretical understanding and practical applications related to the diagnosis and intervention of ASD
Interoceptive awareness mediated the effects of a 15-minute diaphragmatic breathing on empathy for pain: A randomized controlled trial
No full textAlthough empathy for pain plays an important role in positive interpersonal relationships and encourages engagement in prosocial behavior, it remains largely unknown whether empathy for pain could be effectively altered by psychophysiological techniques. This study aimed to investigate the impact of a single session of diaphragmatic breathing practice on empathy for pain and examine the potential mechanism involving interoceptive awareness. A total of 66 healthy participants were randomly assigned to the intervention group or the control group. The intervention group received a 15-minute diaphragmatic breathing (DB) practice with real-time biofeedback, while the control group was to gaze at a black screen at rest and not engaged in any other activities. Before and after the invention, all participants were instructed to evaluate the intensity and unpleasantness of empathy for pain while watching different pictures with pain or non-pain conditions. The Multidimensional Assessment of Interoceptive Awareness (MAIA) was then administered to measure interoceptive awareness. The results indicated a significant interaction between group and time with regard to empathy for pain and MAIA. The DB group showed a statistically significant decrease in both pain intensity and unpleasantness during the pain picture condition, as well as a noteworthy increase in MAIA scores. The control group did not demonstrate any substantial changes. More importantly, the regulation of attention, a dimension of MAIA, had a significant mediating effect on the impact of diaphragmatic breathing on reported unpleasantness. Diaphragmatic breathing could serve as a simple, convenient, and practical strategy to optimize human empathy for pain that warrants further investigation, which has important implications not only for individuals with impaired empathy for pain but also for the improvement of interoceptive awareness
Sex differences in prevalence and clinical correlates of internet addiction among Chinese adolescents with schizophrenia
No full textBackground Patients with schizophrenia (SCZ) exhibit sex differences in various aspects, and patients with SCZ have a high prevalence of internet addiction (IA). However, sex differences in IA among patients with SCZ mostly remain unstudied, particularly in Chinese adolescent patients with SCZ. This study investigated sex differences in prevalence, risk factors, and clinical correlates of IA among Chinese adolescent patients with SCZ.Methods A total of 706 adolescent patients with SCZ were enrolled in this study using a cross-sectional design and a convenience sampling method. Demographics and clinical data of the patients were collected using a standardized clinical assessment form. The Positive and Negative Syndrome Scale (PANSS) and the Young's Internet Addiction Test were used to evaluate psychopathological symptoms and IA respectively.Results Overall, the prevalence of IA among Chinese adolescent patients with SCZ was 26.30% (95% CI: 23.09-29.60%). In Chinese adolescents with SCZ, there was a sex difference in the comorbidity of IA (males: 33.33% vs. females: 21.69%). Binary logistic regression analysis showed that IA was significantly predicted by good socioeconomic status in male and female patients with SCZ. City of living and PANSS total score were associated with IA in male patients with SCZ. In contrast, hospitalization rate and depression score were associated with IA in female patients with SCZ.Conclusion Our study suggests sex differences in clinical correlates of IA in Chinese adolescent patients with SCZ. An additional longitudinal study is required to confirm the findings of the present study
Crossmodal Transfer and Its Cognitive Neural Mechanisms
No full textCrossmodal transfer is the ability to apply the knowledge acquired in one sensory modality to another. Researches on crossmodal transfer investigate how the brain represents information from different sensory modalities, and provide new insights to improve cognitive processing efficiency and reduce repeated learning. To clarify the characteristics and mechanism of crossmodal transfer, this article first introduced the crossmodal transfer effect in different field of research, such as object recognition, category learning, and time perception. After that, the theoretical researches on the representation type of crossmodal transfer were reviewed, mainly including multisensory theory and multisensory mental imagery theory as well as the supportive and opposite findings. The research progresses on the neural mechanism of crossmodal transfer using ERP and fMRI techniques were introduced, mainly including metamodal theory, and multisensory reverse hierarchy theory as well as the supportive and opposite findings. The objective and subjective factors which influenced crossmodal transfer effect were sorted out, in which we suggested that the modality dominance phenomenon supports the metamodal theory, while other factors such as sensory experience, age, setting of learning tasks and stimulus features support theories such as the multisensory hypothesis. Finally, we described the potential applications of the current research findings on crossmodal transfer and pointed out future research questions in this field
Electrophysiological Mechanisms of Sleep Homeostasis
No full textThe brain's neural circuits consist of a large number of highly unstable networks. Despite the existence of many internal and external factors that continuously disturb the balance, our brains employ an array of homeostatic mechanisms that allow neurons or neural circuits to sense how active they are, and when they deviate from a target value, whereby a force must be generated to move neuronal activity back toward this target. Sleep is one of the well-known physiological states in the regulation of homeostasis. Sleep pressure increases during wakefulness and decreases during sleep. When sleep is lost (e. g., sleep deprivation), this loss is compensated by extending or strengthening subsequent sleep. These phenomena are known as sleep homeostasis. The dysregulation of sleep homeostasis accompanies brain -related diseases such as schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder. More importantly, it can significantly undermine the basis of traditional sleep hygiene practices for these diseases. Therefore, clarifying the mechanisms of sleep homeostasis is important for therapy, but it remains an unsolved mystery. In addition to pharmacological treatment, non-invasive brain stimulation has become one of the most promising tools for clinical treatment in recent years due to its low cost, portability and low incidence of side effects. In order to promote relevant technologies, this review will focus on the electrophysiological mechanisms of sleep homeostasis. We first discuss the electrophysiological marker of sleep homeostasis, slow -wave activity, then move to the neuronal firing rates, finally discuss more aspects of sleep homeostasis, including differences in brain area, sleep stages, learning and individual differences
Machine learning in small sample neuroimaging studies: Novel measures for schizophrenia analysis
No full textNovel features derived from imaging and artificial intelligence systems are commonly coupled to construct computer-aided diagnosis (CAD) systems that are intended as clinical support tools or for investigation of complex biological patterns. This study used sulcal patterns from structural images of the brain as the basis for classifying patients with schizophrenia from unaffected controls. Statistical, machine learning and deep learning techniques were sequentially applied as a demonstration of how a CAD system might be comprehensively evaluated in the absence of prior empirical work or extant literature to guide development, and the availability of only small sample datasets. Sulcal features of the entire cerebral cortex were derived from 58 schizophrenia patients and 56 healthy controls. No similar CAD systems has been reported that uses sulcal features from the entire cortex. We considered all the stages in a CAD system workflow: preprocessing, feature selection and extraction, and classification. The explainable AI techniques Local Interpretable Model-agnostic Explanations and SHapley Additive exPlanations were applied to detect the relevance of features to classification. At each stage, alternatives were compared in terms of their performance in the context of a small sample. Differentiating sulcal patterns were located in temporal and precentral areas, as well as the collateral fissure. We also verified the benefits of applying dimensionality reduction techniques and validation methods, such as resubstitution with upper bound correction, to optimize performance.
A CAD system using sucal features derived from brain structural is implemented though statistical, machine learning and deep learning techniques. Explainable AI techniques were applied to enhance the interpretability. Sulcal patterns in specific brain areas associated with schizophrenia, such as temporal and precentral areas, and the collateral fissure were identified. imag
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