ObjectiveTo investigate the effect of positive family behavior support on emotional and behavioral problems in preschool children with epilepsy. Methods A total of 80 preschool epileptic children and their parents who were admitted to the Department of Neurology of our hospital from October 2022 to February 2023 were selected as the research objects, and were divided into experimental group and control group with 40 cases each by random number table method. The control group received neurology routine nursing, and the experimental group received positive family behavior support intervention based on the control group. The scores of family intimacy and adaptability scale, strengths and difficulties questionnaire, medication compliance and quality of life of epilepsy children were compared before and after intervention between the two groups. ResultsAfter intervention, the scores of strength and difficulty questionnaire in experimental group were lower than those in control group (P<0.05), and the scores of family intimacy and adaptability scale, quality of life and medication compliance in experimental group were higher than those in control group (all P<0.05). ConclusionThe application of positive family behavior support program can reduce the occurrence of emotional behavior problems, improve family closeness and adaptability, improve medication compliance, and improve the quality of life of preschool children with epilepsy.
ObjectiveTo explore the influence factors of therapeutic compliance and emotional expression of first-degree relatives in acute schizophrenic patients with psychotic symptoms.
MethodsThe Brief Psychiatric Rating Scale (BPRS) was used to measure the severity of psychotic symptoms in sixty schizophrenic patients from June to September 2014 in West China Hospital and the Toronto Alexithymia Scale (TAS) was used to survey the emotional expression in their family members. The homemade treatment adherence scale was used to survey the treatment adherence in patients for one week.
ResultsThere was a poor therapeutic compliance in nineteen patients with acute schizophrenia (32%) and the other 41(68%) had good therapeutic compliance; the relatives of schizophrenic patients had high TAS scores (male: 67.61±10.03; female: 69.68±11.46) than the normal models did (P ＜ 0.05) . The differences between the patients with different therapeutic compliance in BPRS total score, reactivator, hostile and suspicion factor (P ＜ 0.05) . The therapeutic compliance was related to the severity of the psychotic symptoms (P ＜ 0.05) . Conclusions There is a bad emotional expression in the relatives of acute schizophrenic patients. The psychotic symptoms can influence the therapeutic compliance. The milder the psychotic symptoms, the better the therapeutic dependence.
ObjectiveTo identify the effects of transition to siblinghood (TTS) on the firstborn children’s emotions and behaviors, and to define the time of TTS.MethodsCBM, VIP, CNKI, WanFang Data, PubMed, Web of Science and EBSCO were electronically searched to collect studies on the emotional and behavioral characteristics of firstborn children in TTS from inception to December 31st, 2019. Two reviewers independently screened literature, extracted data and assessed the risk bias of included studies. Then, qualitative methods were used to analyze the studies.ResultsA total of 13 studies involving 980 children were included. 12 behavioral related studies explored self-behavior of the firstborn children during TTS, 3 studies focused on the interaction behavior between the firstborn children and their parents, the firstborn children and the second children. The systematic reviews found that TTS showed both positive and negative effects on the behavioral characteristics of firstborn children, primarily the negative effects. Firstborn children’s anxiety, confrontation and attachment showed 3 different patterns over time, respectively. Two studies showed the increase of negative emotions of firstborn children during TTS. The time range of TTS was mainly concentrated in the third trimester to 12 months after the birth of the second child.ConclusionsThe current evidence shows that TTS primarily increases the negative emotions and behaviors of firstborn children, and the behaviors of firstborn children changes over time. Due to limited quality and quantity of the included studies, more high quality studies are required to verify above conclusions.
ObjectivesTo systematically review the association between pubertal development progression and emotional and behavioral problems.MethodsVIP, CNKI, CBM, WanFang Data, PubMed, Web of Science and EBSCO databases were electronically searched to collect studies on the relationship between pubertal tempo or trajectory and emotional and behavioral problems from inception to December 31st, 2019. Two reviewers independently screened literature, extracted data and assessed risk of bias of included studies. Qualitative methods were then used to analyze the data.ResultsA total of 14 cohort studies were included. The results showed that depression was the most studied emotional problem, and 2 of the 3 studies found a significant association between faster pubertal tempo and more depressive symptoms in juvenile males. However, no association was found in 3 of the 4 studies on juvenile females. The content of behavioral problems of included studies was broad, including internalizing and externalizing problems, substance abuse, attention problem, self-control, first-sexual experience, delinquency, conduct disorder, peer relationship, etc. However, few studies on the same behaviors, and the relationship between behavioral problems was unclear.ConclusionsThe faster pubertal tempo may be associated with depression in juvenile males. The association between pubertal tempo and behavioral problems in males and females remain to be determined by more studies.
Emotion is a crucial physiological attribute in humans, and emotion recognition technology can significantly assist individuals in self-awareness. Addressing the challenge of significant differences in electroencephalogram (EEG) signals among different subjects, we introduce a novel mechanism in the traditional whale optimization algorithm (WOA) to expedite the optimization and convergence of the algorithm. Furthermore, the improved whale optimization algorithm (IWOA) was applied to search for the optimal training solution in the extreme learning machine (ELM) model, encompassing the best feature set, training parameters, and EEG channels. By testing 24 common EEG emotion features, we concluded that optimal EEG emotion features exhibited a certain level of specificity while also demonstrating some commonality among subjects. The proposed method achieved an average recognition accuracy of 92.19% in EEG emotion recognition, significantly reducing the manual tuning workload and offering higher accuracy with shorter training times compared to the control method. It outperformed existing methods, providing a superior performance and introducing a novel perspective for decoding EEG signals, thereby contributing to the field of emotion research from EEG signal.
Existing emotion recognition research is typically limited to static laboratory settings and has not fully handle the changes in emotional states in dynamic scenarios. To address this problem, this paper proposes a method for dynamic continuous emotion recognition based on electroencephalography (EEG) and eye movement signals. Firstly, an experimental paradigm was designed to cover six dynamic emotion transition scenarios including happy to calm, calm to happy, sad to calm, calm to sad, nervous to calm, and calm to nervous. EEG and eye movement data were collected simultaneously from 20 subjects to fill the gap in current multimodal dynamic continuous emotion datasets. In the valence-arousal two-dimensional space, emotion ratings for stimulus videos were performed every five seconds on a scale of 1 to 9, and dynamic continuous emotion labels were normalized. Subsequently, frequency band features were extracted from the preprocessed EEG and eye movement data. A cascade feature fusion approach was used to effectively combine EEG and eye movement features, generating an information-rich multimodal feature vector. This feature vector was input into four regression models including support vector regression with radial basis function kernel, decision tree, random forest, and K-nearest neighbors, to develop the dynamic continuous emotion recognition model. The results showed that the proposed method achieved the lowest mean square error for valence and arousal across the six dynamic continuous emotions. This approach can accurately recognize various emotion transitions in dynamic situations, offering higher accuracy and robustness compared to using either EEG or eye movement signals alone, making it well-suited for practical applications.
ObjectiveTo systematically review the influence of childhood psychosocial stress on pubertal emotional and behavioral problems. MethodsThe PubMed, OVID, EBSCO, Web of Science, CBM, VIP, WanFang Data and CNKI databases were electronically searched to collect studies on the relationships between childhood psychosocial stress and pubertal emotional and behavioral problems from inception to February 29, 2024. Two reviewers independently screened the literature, extracted data and assessed the risk of bias in the included studies. Qualitative methods were then used to analyze the data. ResultsA total of 41 cohort studies were included. The outcomes of 19 studies involved pubertal emotional problems, 26 studies involved behavioral problems, and 7 studies involved overall problems. The results showed that depression (14/19) and anxiety (8/19) were the most commonly reported emotional behaviors. Most studies (17/19) showed that childhood psychological stress had a positive predictive effect on pubertal emotional problems. Behavioral problems involved many outcomes, including smoking, drinking, illegal substance use, self-injurious behavior, suicide, externalizing behavior, criminal behavior, bullying behavior, sexual behavior, mobile phone dependence, etc. However, few studies were on the same behaviors, and the relationship between childhood psychosocial stress and behavioral problems was unclear. ConclusionChildhood psychosocial stress may have a positive predictive effect on depression and anxiety. The associations between childhood psychosocial stress and pubertal behavioral problems and other emotional problems remain to be determined by more studies.
There are two modes to display panoramic movies in virtual reality (VR) environment: non-stereoscopic mode (2D) and stereoscopic mode (3D). It has not been fully studied whether there are differences in the activation effect between these two continuous display modes on emotional arousal and what characteristics of the related neural activity are. In this paper, we designed a cognitive psychology experiment in order to compare the effects of VR-2D and VR-3D on emotional arousal by analyzing synchronously collected scalp electroencephalogram signals. We used support vector machine (SVM) to verify the neurophysiological differences between the two modes in VR environment. The results showed that compared with VR-2D films, VR-3D films evoked significantly higher electroencephalogram (EEG) power (mainly reflected in α and β activities). The significantly improved β wave power in VR-3D mode showed that 3D vision brought more intense cortical activity, which might lead to higher arousal. At the same time, the more intense α activity in the occipital region of the brain also suggested that VR-3D films might cause higher visual fatigue. By the means of neurocinematics, this paper demonstrates that EEG activity can well reflect the effects of different vision modes on the characteristics of the viewers’ neural activities. The current study provides theoretical support not only for the future exploration of the image language under the VR perspective, but for future VR film shooting methods and human emotion research.
ObjectiveTo study whether emotional management can alleviate the occupational burnout of the health care providers.
MethodsFrom May 1st 2015 to February 29th 2016, we sampled the medical workers of a class-3 grade-A hospital randomly, and performed the emotional management through self-emotion management and professionals-conducted emotion-management. The discrepancies before and after intervention were studied using Maslach Burnout Inventory General Survey (MBI-GS).
ResultsIn total, 100 medical workers were enrolled in our study, of which there were 27 males and 73 females. There were 11 doctors and 89 nurses. The average age was (34.5±5.6) years. According to the MBI-GS survey, there were 69 medical workers suffering from occupational burnout. There were significant statistical differences before and after intervention in the MBI-GS scores in four aspects including emotion exhaustion, work status, sense of achievement and the total scores (P＜0.05).
ConclusionThe medical workers can alleviate the occupational burnout under the self-management or professionals-conducted management of emotion.
In audiovisual emotion recognition, representational learning is a research direction receiving considerable attention, and the key lies in constructing effective affective representations with both consistency and variability. However, there are still many challenges to accurately realize affective representations. For this reason, in this paper we proposed a cross-modal audiovisual recognition model based on a multi-head cross-attention mechanism. The model achieved fused feature and modality alignment through a multi-head cross-attention architecture, and adopted a segmented training strategy to cope with the modality missing problem. In addition, a unimodal auxiliary loss task was designed and shared parameters were used in order to preserve the independent information of each modality. Ultimately, the model achieved macro and micro F1 scores of 84.5% and 88.2%, respectively, on the crowdsourced annotated multimodal emotion dataset of actor performances (CREMA-D). The model in this paper can effectively capture intra- and inter-modal feature representations of audio and video modalities, and successfully solves the unity problem of the unimodal and multimodal emotion recognition frameworks, which provides a brand-new solution to the audiovisual emotion recognition.
